Search results for: “User acceptance of computer technology:A comparison of two theoretical models ”

Authors: Azeez O. Idris, Benjamin O. Orimolade, Potlako J. Mafa, Alex T. Kuvarega, Usisipho Feleni, Bhekie B. Mamba

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We report a simple and cheaper method for the electrochemical detection of Se(IV) using carbon nanodots (CNDTs) prepared from oat. The carbon nanodots were synthesised by green and facile approach and characterised using scanning electron microscopy, high-resolution transmission electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, and Raman spectroscopy. The CNDT was used to fabricate an electrochemical sensor for the quantification of Se(IV) in water. The modification of glassy carbon electrode (GCE) with carbon nanodots led to an increase in the electroactive surface area of the electrode, which enhances the redox current peak of [Fe(CN)₆]₃₋/₄‒ in comparison to the bare GCE. Using the square wave voltammetry, the detection limit and quantification limit of 0.05 and 0.167 ppb were obtained under the optimised parameters using deposition potential of -200 mV, 0.1 M HNO₃ electrolyte, electrodeposition time of 60 s, and pH 1. The results further revealed that the GCE-CNDT was not susceptible to many interfering cations except Cu(II) and Pb(II), and Fe(II). The sensor fabrication involves a one-step electrode modification and was used to detect Se(IV) in a real water sample, and the result obtained is in agreement with the inductively coupled plasma technique. Overall, the electrode offers a cheap, fast, and sensitive way of detecting selenium in environmental matrices.

Keywords: carbon nanodots, square wave voltammetry, nanomaterials, selenium, sensor

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: Patience Muchini, Electdom Matandiroya, Emmanuel Mashonjowa

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A ground-end manifestation of space weather phenomena is known as geomagnetically induced currents (GICs). GICs flow along the electric power transmission cables connecting the transformers and between the grounding points of power transformers during significant geomagnetic storms. Geomagnetically induced currents have been studied in other regions and have been noted to affect the power grid network. In Zimbabwe, grid failures have been experienced, but it is yet to be proven if these failures have been due to GICs. The purpose of this paper is to characterize geomagnetically induced currents with a power grid network. This paper analyses data collected, which is geomagnetic data, which includes the Kp index, DST index, and the G-Scale from geomagnetic storms and also analyses power grid data, which includes reactive power, relay tripping, and alarms from high voltage substations and then correlates the data. This research analysis was first theoretically analyzed by studying geomagnetic parameters and then experimented upon. To correlate, MATLAB was used as the basic software to analyze the data. Latitudes of the substations were also brought into scrutiny to note if they were an impact due to the location as low latitudes areas like most parts of Zimbabwe, there are less severe geomagnetic variations. Based on theoretical and graphical analysis, it has been proven that there is a slight relationship between power system failures and GICs. Further analyses can be done by implementing measuring instruments to measure any currents in the grounding of high-voltage transformers when geomagnetic storms occur. Mitigation measures can then be developed to minimize the susceptibility of the power network to GICs.

Keywords: adverse space weather, DST index, geomagnetically induced currents, KP index, reactive power

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Authors: Baleeqs, O. Adegoke, Adeola, O. Aburime

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Juvenile delinquency is fast becoming one of the largest problems facing many societies due to many different factors ranging from parental factors to bullying at schools all which had led to different theoretical notions by different scholars. Delinquency is an illegal or immoral behaviour, especially by the young person who behaves in a way that is illegal or that society does not approve of. The purpose of the study was to investigate causes and effects of delinquent behaviours among adolescent in juvenile home in Osun State. A descriptive survey research type was employed. The random sampling technique was used to select 100 adolescents in Juvenile home in Osun State. Questionnaires were developed and given to them. The data collected from this study were analyzed using frequency counts and percentage for the demographic data in section A, while the two research hypotheses postulated for this study were tested using t-test statistics at the significance level of 0.05. Findings revealed that the greatest school effects of delinquent behaviours among adolescent in juvenile home in Osun by respondents were their aggressive behaviours. Findings revealed that there was a significant difference in the causes and effects of delinquent behaviours among adolescent in juvenile home in Osun State. It was also revealed that there was no significant difference in the causes and effects of delinquent behaviours among secondary school students in Osun based on gender. These recommendations were made in order to address the findings of this study: More number of teachers should be appointed in the observation home so that it will be possible to provide teaching to the different age group of delinquents. Developing the infrastructure facilities of short stay homes and observation home is a top priority. Proper counseling session’s interval is highly essential for these juveniles.

Keywords: behaviour, delinquency, juvenile, random sampling, statistical techniques, survey

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Authors: Carolina Cuéllar, Paz González

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Research has shown that school leadership has a significant indirect effect on students’ achievements. In Chile, evidence has also revealed that this impact is stronger in vulnerable schools. With the aim of strengthening school leadership, public policy has taken up the challenge of enhancing capabilities of novice principals through the implementation of induction programs, which include a mentoring component, entrusting the task of delivering these programs to universities. The importance of using mentoring or coaching models in the preparation of novice school leaders has been emphasized in the international literature. Thus, it can be affirmed that building leadership capacity through partnership is crucial to facilitate cognitive and affective support required in the initial phase of the principal career, gain role clarification and socialization in context, stimulate reflective leadership practice, among others. In Chile, mentoring is a recent phenomenon in the field of school leadership and it is even more new in the preparation of new principals who work in public schools. This study, funded by the Chilean Ministry of Education, sought to explore the challenges and lessons arising from the design and implementation of mentoring processes which are part of the induction programs, according to the perception of the different actors involved: ministerial agents, university coordinators, mentors and novice principals. The investigation used a qualitative design, based on a study of three cases (three induction programs). The sources of information were 46 semi-structured interviews, applied in two moments (at the beginning and end of mentoring). Content analysis technique was employed. Data focused on the uniqueness of each case and the commonalities within the cases. Five main challenges and lessons emerged in the design and implementation of mentoring within the induction programs for new principals from Chilean public schools. They comprised the need of (i) developing a shared conceptual framework on mentoring among the institutions and actors involved, which helps align the expectations for the mentoring component within the induction programs, along with assisting in establishing a theory of action of mentoring that is relevant to the public school context; (ii) recognizing trough actions and decisions at different levels that the role of a mentor differs from the role of a principal, which challenge the idea that an effective principal will always be an effective mentor; iii) improving mentors’ selection and preparation processes trough the definition of common guiding criteria to ensure that a mentor takes responsibility for developing critical judgment of novice principals, which implies not limiting the mentor’s actions to assist in the compliance of prescriptive practices and standards; (iv) generating common evaluative models with goals, instruments and indicators consistent with the characteristics of mentoring processes, which helps to assess expected results and impact; and (v) including the design of a mentoring structure as an outcome of the induction programs, which helps sustain mentoring within schools as a collective professional development practice. Results showcased interwoven elements that entail continuous negotiations at different levels. Taking action will contribute to policy efforts aimed at professionalizing the leadership role in public schools.

Keywords: induction programs, mentoring, novice principals, school leadership preparation

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Authors: Sanchali Das, Swapan Debbarma

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Music mood classification is developing in both the areas of music information retrieval (MIR) and natural language processing (NLP). Some of the Indian languages like Hindi English etc. have considerable exposure in MIR. But research in mood classification in regional language is very less. In this paper, powerful audio based feature for Kokborok Christian song is identified and mood classification task has been performed. Kokborok is an Indo-Burman language especially spoken in the northeastern part of India and also some other countries like Bangladesh, Myanmar etc. For performing audio-based classification task, useful audio features are taken out by jMIR software. There are some standard audio parameters are there for the audio-based task but as known to all that every language has its unique characteristics. So here, the most significant features which are the best fit for the database of Kokborok song is analysed. The regression-based model is used to find out the independent parameters that act as a predictor and predicts the dependencies of parameters and shows how it will impact on overall classification result. For classification WEKA 3.5 is used, and selected parameters create a classification model. And another model is developed by using all the standard audio features that are used by most of the researcher. In this experiment, the essential parameters that are responsible for effective audio based mood classification and parameters that do not significantly change for each of the Christian Kokborok songs are analysed, and a comparison is also shown between the two above model.

Keywords: Christian Kokborok song, mood classification, music information retrieval, regression

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Authors: R. Lekaviciene, D. Antiniene

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Attempts to split the construct of emotional intelligence (EI) into separate components – ability to understand own and others’ emotions and ability to control own and others’ emotions may be meaningful more theoretically than practically. In real life, a personality encounters various emotional situations that require exhibition of complex EI to solve them. Emotional situation solution tests enable measurement of such undivided EI. The object of the present study is to determine sociodemographic and other factors that are important for emotional situation solutions. The study involved 1,430 participants from various regions of Lithuania. The age of participants varied from 17 years to 27 years. Emotional social and interpersonal situation scale EI-DARL-V2 was used. Each situation had two mandatory answering formats: The first format contained assignments associated with hypothetical theoretical knowledge of how the situation should be solved, while the second format included the question of how the participant would personally resolve the given situation in reality. A questionnaire that contained various sociodemographic data of subjects was also presented. Factors, statistically significant for emotional situation solution, have been determined: gender, family structure, the subject’s relation with his or her mother, mother’s occupation, subjectively assessed financial situation of the family, level of education of the subjects and his or her parents, academic achievement, etc. The best solvers of emotional situations are women with high academic achievements. According to their chosen study profile/acquired profession, they are related to the fields in social sciences and humanities. The worst solvers of emotional situations are men raised in foster homes. They are/were bad students and mostly choose blue-collar professions.

Keywords: emotional intelligence, emotional situations, solution of situation, young people

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Authors: Srivilai Worametrachanon, Arunee Apichartsrangkoon, Jiranat Techarang, Boonrak Phanchaisri

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A human-digestive simulator consisted of four colon compartments, i.e., stomach, small intestine, proximal colon and distal colon used to harbor L. casei 01 plus either pasteurized ordinary-purple-rice drinks or germinated-purple-rice drinks. Accordingly, three treatment compositions had been set up and the effects of treatments on colon bacterial communities including their by-products were thoroughly examined. L. casei 01 plus purple-rice drinks gave rise to significantly high formation (P ≤ 0.05) of short-chain-fatty acids (SCFA) of which highest acetic acid was found followed by propionic and butyric acids, while the germinated-rice drink showed the greatest impact. Moreover, the effect was more pronounced upon prolonged fermentation. In addition, the influence of treatments on colon microbes was also demonstrated. Accordingly, desirable bacteria including colon Lactobacilli and Bifidobacteria were significantly increased (P ≤ 0.05) in both colons in comparison with the control and the effect was more prominent after adding purple-rice drink. On the other hand, undesirable Clostridia and coliforms were apparently diminished by the influence of treatment conditions, in which both compartments exhibited similar results.

Keywords: human-digestive simulator, Lactobacillus casei 01, Pasteurized-purple-rice drinks

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Authors: C. Fernandez-Plaza, I. Abad, E. Diaz, I. Diaz

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Births occurring before the 37th week of gestation are considered preterm births. A threat of preterm is defined as the beginning of regular uterine contractions, dilation and cervical effacement between 23 and 36 gestation weeks. To author's best knowledge, the factors that determine the beginning of the birth are not completely defined yet. In particular, the incidence of sleep habits on preterm births is weekly studied. The aim of this study is to develop a model to predict the factors affecting premature delivery on pregnancy, based on the above potential risk factors, including those derived from sleep habits and light exposure at night (introduced as 12 variables obtained by a telephone survey using two questionnaires previously used by other authors). Thus, three groups of variables were included in the study (maternal, fetal and sleep habits). The study was approved by Research Ethics Committee of the Principado of Asturias (Spain). An observational, retrospective and descriptive study was performed with 481 births between January 1, 2015 and May 10, 2016 in the University Central Hospital of Asturias (Spain). A statistical analysis using SPSS was carried out to compare qualitative and quantitative variables between preterm and term delivery. Chi-square test qualitative variable and t-test for quantitative variables were applied. Statistically significant differences (p < 0.05) between preterm vs. term births were found for primiparity, multi-parity, kind of conception, place of residence or premature rupture of membranes and interruption during nights. In addition to the statistical analysis, machine learning methods to look for a prediction model were tested. In particular, tree based models were applied as the trade-off between performance and interpretability is especially suitable for this study. C5.0, recursive partitioning, random forest and tree bag models were analysed using caret R-package. Cross validation with 10-folds and parameter tuning to optimize the methods were applied. In addition, different noise reduction methods were applied to the initial data using NoiseFiltersR package. The best performance was obtained by C5.0 method with Accuracy 0.91, Sensitivity 0.93, Specificity 0.89 and Precision 0.91. Some well known preterm birth factors were identified: Cervix Dilation, maternal BMI, Premature rupture of membranes or nuchal translucency analysis in the first trimester. The model also identifies other new factors related to sleep habits such as light through window, bedtime on working days, usage of electronic devices before sleeping from Mondays to Fridays or change of sleeping habits reflected in the number of hours, in the depth of sleep or in the lighting of the room. IF dilation < = 2.95 AND usage of electronic devices before sleeping from Mondays to Friday = YES and change of sleeping habits = YES, then preterm is one of the predicting rules obtained by C5.0. In this work a model for predicting preterm births is developed. It is based on machine learning together with noise reduction techniques. The method maximizing the performance is the one selected. This model shows the influence of variables related to sleep habits in preterm prediction.

Keywords: machine learning, noise reduction, preterm birth, sleep habit

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Authors: Bathmajaa Muralisankar

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As much as railway station infrastructure designs and ticket-booking norms have been changed to facilitate use by differently abled persons, the railway train compartments themselves have not been made user-friendly for differently abled persons. Owing to safety concerns, dependency on others for their travel, and fear of isolation, differently abled people do not prefer travelling by train. Rather than including a dedicated compartment open only to the differently abled, including the latter with others in the normal compartment (with the proposed modifications discussed here) will make them feel secure and make for an enhanced travel experience for them. This approach also represents the most practical way to include a particular category of people in the mainstream society. Lowering the height of the compartment doors and providing a wider entrance with a ramp will provide easy entry for those using wheelchairs. As well, removing the first two alternate rows and the first two side seats will not only widen the passage and increase seating space but also improve wheelchair turning radius. This will help them travel without having to depend on others. Seating arrangements may be done to accommodate their family members near them instead of isolating the differently abled in a separate compartment. According to present ticket-booking regulations of the Indian Railways, three to four disabled persons may travel without their family or one to two along with their family, and the numbers may be added or reduced. To help visually challenged and hearing-impaired persons, in addition to the provision of special instruments, railings, and textured footpaths and flooring, the seat numbers above the seats may be set in metal or plastic as an outward projection so the visually impaired can touch and feel the numbers. Braille boards may be included at the entrance to the compartment along with seat numbers in the aforementioned projected manner. These seat numbers may be designed as buttons, which when pressed results in an announcement of the seat number in the applicable local language as well as English. Emergency buttons, rather than emergency chains, within the easy reach of disabled passengers will also help them.

Keywords: dependency, differently abled, inclusion, mainstream society

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Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Afshin Karimzadeh Fard

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Experimental & numeral study of temperature distribution during milling process, is important in milling quality and tools life aspects. In the present study the milling cross-section temperature is determined by using Artificial Neural Networks (ANN) according to the temperature of certain points of the work piece and the points specifications and the milling rotational speed of the blade. In the present work, at first three-dimensional model of the work piece is provided and then by using the Computational Heat Transfer (CHT) simulations, temperature in different nods of the work piece are specified in steady-state conditions. Results obtained from CHT are used for training and testing the ANN approach. Using reverse engineering and setting the desired x, y, z and the milling rotational speed of the blade as input data to the network, the milling surface temperature determined by neural network is presented as output data. The desired points temperature for different milling blade rotational speed are obtained experimentally and by extrapolation method for the milling surface temperature is obtained and a comparison is performed among the soft programming ANN, CHT results and experimental data and it is observed that ANN soft programming code can be used more efficiently to determine the temperature in a milling process.

Keywords: artificial neural networks, milling process, rotational speed, temperature

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: Piyush Swami, Bijaya Ketan Panigrahi, Sneh Anand, Manvir Bhatia, Tapan Gandhi

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Visual inspection of electroencephalogram (EEG) signals to detect epileptic signals is very challenging and time-consuming task even for any expert neurophysiologist. This problem is most challenging in under-developed and developing countries due to shortage of skilled neurophysiologists. In the past, notable research efforts have gone in trying to automate the seizure detection process. However, due to high false alarm detections and complexity of the models developed so far, have vastly delimited their practical implementation. In this paper, we present a novel scheme for epileptic seizure detection using empirical mode decomposition technique. The intrinsic mode functions obtained were then used to calculate the standard deviations. This was followed by probability density based classifier to discriminate between non-ictal and ictal patterns in EEG signals. The model presented here demonstrated very high classification rates ( > 97%) without compromising the statistical performance. The computation timings for each testing phase were also very low ( < 0.029 s) which makes this model ideal for practical applications.

Keywords: electroencephalogram (EEG), epilepsy, ictal patterns, empirical mode decomposition

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Authors: Clif P. Lewis, Ise-Lu Möller

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The COVID-19 pandemic has had a profound impact on employment. The ‘future of work’ is now the ‘present of work’. Changes in the social context within which organisations are embedded necessitated drastic changes in how we work. Through the leveraging of technology and changes in mindset, we have seen exciting innovations in the world of work. This global shift in the context of employment offers a unique opportunity to examine a key unresolved issue in the study of Burnout, namely contextual antecedents. This study answers the call for deeper empirical insight into the contexts within which Burnout occur. We explore the emergence of Burnout within a remote work context by using survey data that incorporates the latest global work trends into the Areas of Worklife framework.

Keywords: burnout, remote work, pandemic, wellness

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Authors: N. Balamurugan, N. V. Mahalakshmi

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Compression ignition (CI) engines are known for their high thermal efficiency in comparison with spark-ignited (SI) engines. This makes CI engines a potential candidate for the future prime source of power for transportation sector to reduce greenhouse gas emissions and to shrink carbon footprint. However, CI engines produce high levels of NOx and soot emissions. Conventional methods to reduce NOx and soot emissions often result in the infamous NOx-soot trade-off. The injection parameters are one of the most important factors in the working of CI engines. The engine performance, power output, economy etc., is greatly dependent on the effectiveness of the injection parameters. The injection parameter has their direct impact on combustion process and pollutant formation. The injection parameter’s values are required to be optimised according to the application of the engine. Control of fuel injection mode is one method for reduction of NOx and soot emissions that is achievable. This study aims to assess, compare and analyse the influence of the effect of injection characteristics that is SOI timing studied on combustion and emissions in in-cylinder combustion processes with that of conventional DI Diesel Engine system using the commercial Computational Fluid Dynamic (CFD) package STAR- CD ES-ICE.

Keywords: variation of injection timing, compression ignition engine, spark-ignited, Computational Fluid Dynamic

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Authors: Nasser Almonawer

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Timely reaction to an evolving global business environment and volatile market conditions necessitates system and process flexibility, which in turn demands agile and adaptable architecture and a steady infusion of affordable new technologies. On the contrary, a large number of organizations utilize systems characterized by inflexible and obsolete legacy architectures. To effectively respond to the dynamic contemporary business environments, such architectures must be migrated to robust and modular open architectures. To this end, this paper proposes an integrated decision support system for a seamless migration to open systems. The proposed decision support system (DSS) integrates three well-established quantitative and qualitative decision-making models—namely, the Delphi method, Analytic Hierarchy Process (AHP) and Goal Programming (GP) to (1) assess risks and establish evaluation criteria; (2) formulate migration strategy and rank candidate systems; and (3) allocate resources among the selected systems.

Keywords: decision support systems, open systems architecture, analytic hierarchy process (AHP), goal programming (GP), delphi method

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Authors: Manasse Elusma, Thung-Hong Lin, Chun-yin Lee

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The relationship between hunger and war or conflict remains to be discussed. Do wars or conflicts cause hunger and food scarcity, or is the reverse relationship is true? As the world becomes more peaceful and wealthier, some countries are still suffered from hunger and food shortage. So, eradicating hunger calls for a more comprehensive understanding of the relationship between conflict and hunger. Several studies are carried out to detect the importance of conflict or war on food security. Most of these studies, however, perform only descriptive analysis and largely use food security indicators instead of the global hunger index. Few studies have employed cross-country panel data to explicitly analyze the association between conflict and chronic hunger, including hidden hunger. Herein, this study addresses this issue and the knowledge gap. We combine global datasets to build a new panel dataset including 143 countries from 1989 to 2020. This study examines the effect of conflict on hunger with fixed effect models, and the results show that the increase of conflict frequency deteriorates hunger. Peacebuilding efforts and war prevention initiative are required to eradicate global hunger.

Keywords: armed conflict, food scarcity, hidden hunger, hunger, malnutrition

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Authors: A. Shafaghat, H. Khabbaz, S. Moravej, Ah. Shafaghat

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The bearing capacity of closely spaced shallow footings alters with their spacing and the shape of footing. In this study, the bearing capacity and settlement of two adjacent footings constructed on a sand layer are investigated. The effect of different footing shapes including square, circular, ring and strip on sandy soil is captured in the calculations. The investigations are carried out numerically using PLAXIS-3D software and analytically employing conventional settlement equations. For this purpose, foundations are modelled in the program with practical dimensions and various spacing ratios ranging from 1 to 5. The spacing ratio is defined as the centre-to-centre distance to the width of foundations (S/B). Overall, 24 models are analyzed; and the results are compared and discussed in detail. It can be concluded that the presence of adjacent foundation leads to the reduction in bearing capacity for round shape footings while it can increase the bearing capacity of rectangular footings in some specific distances.

Keywords: bearing capacity, finite element analysis, loose sand, settlement equations, shallow foundation

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Authors: Bismark Agbemble

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This paper talks about how project-based learning (PBL) is being infused or implemented in the educational sphere of Africa. The paper navigates through the liminal aspects of PBL as a pedagogical approach to bridge the divide between theoretical knowledge and its application within school curriculums. Given that contextualized learning can be embodied, the abstract vehemently discusses that PBL creates an opportunity for students to work on projects that are of academic relevance in their local settings. It presents PBL’s growth of critical thinking, problem-solving, cooperation, and communications, which is vital in getting young citizens to prepare for the 21st-century revolution. In addition, the abstract stresses the possibility that PBL could become a stimulus to creativity and innovation wherein learning becomes motivated from within by intrinsic motivations. The paper advocates for a holistic approach that is based on teacher’s professional development with the provision of adequate infrastructural facilities and resource allocation, thus ensuring the success and sustainability of PBLs in African education systems. In the end, the paper positions this as a transformative educational methodology that has great potential in helping to shape an African generation that is prepared for a great future.

Keywords: student centered pedagogy, constructivist learning theory, self-directed learning, active exploration, real world challenges, STEM, 21st century skills, curriculum design, classroom management, project base learning curriculum, global intelligence, social and communication skills, transferable skills, critical thinking, investigatable learning, life skills

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Authors: Nathi Ram, Saurabh K. Yadav

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In turbomachinery, the turbulent flow occurs due to the use of high velocity of low kinematic viscosity lubricants and used in many industrial applications. In the present work, the performance of symmetric slot-entry hybrid worn journal bearing under laminar and turbulent lubrication has been investigated. For turbulent lubrication, the Reynolds equation has been modified using Constantinescu turbulent model. This modified equation has been solved using the finite element method. The effect of turbulent lubrication on bearing’s performance has been presented for symmetric hybrid journal bearing. The slot-entry hybrid worn journal bearing under turbulent/laminar regimes have been investigated. It has been observed that the stiffness and damping coefficients are more for the bearing having slot width ratio (SWR) of 0.25 than the bearing with SWR of 0.5 and 0.75 under the turbulent regime. Further, it is also observed that for constant wear depth parameter, stability threshold speed gets increased for bearing operates at slot width ratio 0.25 under turbulent lubrication.

Keywords: hydrostatic bearings, journal bearings, restrictors, turbulent flow models, finite element technique

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Authors: B. S. Chaudhary

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The severity and frequencies of different disasters on the globe is increasing in recent years. India is also facing the disasters in the form of drought, cyclone, earthquake, landslides, and floods. One of the major causes of disasters in northern India is flood. There are great losses and extensive damage to the agricultural crops, property, human, and animal life. This is causing environmental imbalances at places. The annual global figures for losses due to floods run into over 2 billion dollar. India is a vast country with wide variations in climate and topography. Due to widespread and heavy rainfall during the monsoon months, floods of varying magnitude occur all over the country during June to September. The magnitude depends upon the intensity of rainfall, its duration and also the ground conditions at the time of rainfall. Haryana, one of the agriculturally dominated northern states is also suffering from a number of disasters such as floods, desertification, soil erosion, land degradation etc. Earthquakes are also frequently occurring but of small magnitude so are not causing much concern and damage. Most of the damage in Haryana is due to floods. Floods in Haryana have occurred in 1978, 1988, 1993, 1995, 1998, and 2010 to mention a few. The present paper deals with the Remote Sensing and GIS applications in preparing flood risk maps in parts of Haryana State India. The satellite data of various years have been used for mapping of flood affected areas. The Flooded areas have been interpreted both visually and digitally and two classes-flooded and receded water/ wet areas have been identified for each year. These have been analyzed in GIS environment to prepare the risk maps. This shows the areas of high, moderate and low risk depending on the frequency of flood witness. The floods leave a trail of suffering in the form of unhygienic conditions due to improper sanitation, water logging, filth littered in the area, degradation of materials and unsafe drinking water making the people prone to many type diseases in short and long run. Attempts have also been made to enumerate the causes of floods. The suggestions are given for mitigating the fury of floods and proper management issues related to evacuation and safe places nearby.

Keywords: flood mapping, GIS, Haryana, India, remote sensing, space technology

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Authors: K. Jagannath, Akhilesh Kotian, S. S. Sharma, Achutha Kini U., P. R. Prabhu

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Boiling process is characterized by the rapid formation of vapour bubbles at the solid–liquid interface (nucleate boiling) with pre-existing vapour or gas pockets. Computational fluid dynamics (CFD) is an important tool to study bubble dynamics. In the present study, CFD simulation has been carried out to determine the bubble detachment diameter and its terminal velocity. Volume of fluid method is used to model the bubble and the surrounding by solving single set of momentum equations and tracking the volume fraction of each of the fluids throughout the domain. In the simulation, bubble is generated by allowing water-vapour to enter a cylinder filled with liquid water through an inlet at the bottom. After the bubble is fully formed, the bubble detaches from the surface and rises up during which the bubble accelerates due to the net balance between buoyancy force and viscous drag. Finally when these forces exactly balance each other, it attains a constant terminal velocity. The bubble detachment diameter and the terminal velocity of the bubble are captured by the monitor function provided in FLUENT. The detachment diameter and the terminal velocity obtained is compared with the established results based on the shape of the bubble. A good agreement is obtained between the results obtained from simulation and the equations in comparison with the established results.

Keywords: bubble growth, computational fluid dynamics, detachment diameter, terminal velocity

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Authors: Shams Ul Hussain Zaheer, Bibi Alia, Shehla Shams

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With the creation of human beings, almost all of them are blessed with the award of the power of expression, and this series starts from the life of Adam (A.S) in Paradise when he was blesses with language and knowledge and given priority upon the Angels. Later on, when the population spread and many other languages came into being, the method of the different people of different regions remained various. And when the Arabic was formed as a language after Ismail (A.S) and his sons spread in the gulf area, the words adopted from other gulf languages also became a part of this new language with it immense. Beside this, the tone of expression in other areas of the word was different, but the incidents, norms of bad and good, parameters for like and dislike, thinking styles, and rules of good and bad governance with social values remained round about the same. People practiced their lives according to the set norms everywhere in the world. Especially the two built, i.e., Hijaz and Khurasan, wherein Arabs and Pashtun accordingly were dwelling; it seems that their social values were much closed to each other. These norms reflect in various kinds of literature of both of the nations, but this article deals in with their proverbs specifically. This article discusses the intellectual telepathic between them in a research way. And put the defined similarities and dissimilarities between both in the proverb. And it also draws a sketch in front of readers that how the thinking and expression styles remains same in humans. As it belongs to a comparative analysis of the proverbs so, the same methodology has been adopted in the articles.

Keywords: intellectual telepathy, hijaz, arab, khurasan, pashtun, proverbs, comparison

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Authors: Nasir Iqbal, Khurram Siraj, Rizwan Raza

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Solid oxide fuel cell (SOFC) is the promising technology now days. SOFC can be operated with different types of fuels available. In this work catalytic anode is prepared with metal oxides i.e. Li, Ni, Zn and Sn and tested for catalytic activity with natural gas as a fuel. The operating temperature range is 170-750°C as observed with the help of TGA. Electrical conductivity and fuel cell performance has been observed for four different samples with varying composition of Sn and Zn. It is concluded that the sample having greater concentration of Zn shows better conductivity and power density results. All the results are promising and verified with different characterizations.

Keywords: catalytic activity, solid oxide fuel cell, energy material, natural gas

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Authors: Masoud Safdari, Jacob Fish

Abstract:

Despite vast amount of existing theoretical knowledge, the implementation of a universal multiscale modeling, analysis, and simulation software framework remains challenging. Existing multiscale software and solutions are often domain-specific, closed-source and mandate a high-level of experience and skills in both multiscale analysis and programming. Furthermore, tools currently existing for Atomistic-to-Continuum (AtC) multiscaling are developed with the assumptions such as accessibility of high-performance computing facilities to the users. These issues mentioned plus many other challenges have reduced the adoption of multiscale in academia and especially industry. In the current work, we introduce Multiscale Hub (MsHub), an effort towards making AtC more accessible through cloud services. As a joint effort between academia and industry, MsHub provides a universal web-enabled framework for practical multiscaling. Developed on top of universally acclaimed scientific programming language Python, the package currently provides an open-source, comprehensive, easy-to-use framework for AtC coupling. MsHub offers an easy to use interface to prominent molecular dynamics and multiphysics continuum mechanics packages such as LAMMPS and MFEM (a free, lightweight, scalable C++ library for finite element methods). In this work, we first report on the design philosophy of MsHub, challenges identified and issues faced regarding its implementation. MsHub takes the advantage of a comprehensive set of tools and algorithms developed for AtC that can be used for a variety of governing physics. We then briefly report key AtC algorithms implemented in MsHub. Finally, we conclude with a few examples illustrating the capabilities of the package and its future directions.

Keywords: atomistic, continuum, coupling, multiscale

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Authors: Ali panahi-Kosar Khosravi

Abstract:

Earthquake resilience is one of the most important theoretical and practical concepts in crisis management. Over the past few decades, the rapid growth of urban areas and developing lower urban areas (especially in developing countries) have made them more vulnerable to human and natural crises. Therefore, the resilience of urban communities, especially low-income and unhealthy neighborhoods, is of particular importance. The present study seeks to assess and evaluate the resilience of neighborhoods in the center of district 6 of Tabriz in terms of awareness, knowledge and personal skills, social and psychological capital, managerial-institutional, and the ability to return to appropriate and sustainable conditions. The research method in this research is descriptive-analytical. The authors used library and survey methods to collect information and a questionnaire to assess resilience. The statistical population of this study is the total households living in the four neighborhoods of Shanb Ghazan, Khatib, Gharamalek, and Abuzar alley. Three hundred eighty-four families from four neighborhoods were selected based on the Cochran formula using a simple random sampling method. A one-sample t-test, simple linear regression, and structural equations were used to test the research hypotheses. Findings showed that only two social and psychological awareness and capital indicators in district 6 of Tabriz had a favorable and approved status. Therefore, considering the multidimensional concept of resilience, district 6 of Tabriz is in an unfavorable resilience situation. Also, the findings based on the analysis of variance indicated no significant difference between the neighborhoods of district 6 in terms of resilience, and most neighborhoods are in an unfavorable situation.

Keywords: resilience, statistical analysis, earthquake, district 6 of tabriz

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Authors: Maria V. Morozova, Zoya A. Mikhaylovskaya, Elena S. Buyanova, Sofia A. Petrova, Ksenia V. Arishina, Robert G. Zaharov

Abstract:

The present work is devoted to the investigation of two series of doped bismuth molybdates: Bi₂₆-₂ₓMn₂ₓMo₁₀O₆₉-d and Bi₂₆Mo₁₀-₂yMn₂yO₆₉-d. Complex oxides were synthesized by conventional solid state technology and by co-precipitation method. The products were identified by powder diffraction. The powders and ceramic samples were examined by means of densitometry, laser diffraction, and electron microscopic methods. Porosity of the ceramic materials was estimated using the hydrostatic method. The electrical conductivity measurements were carried out using impedance spectroscopy method.

Keywords: bismuth molybdate, columnar structures, impedance spectroscopy, oxygen ionic conductors

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Authors: Massimiliano Frezza, Sergio Bianchi, Augusto Pianese

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Introduced by Shannon in 1948 in the field of information theory as the average rate at which information is produced by a stochastic set of data, the concept of entropy has gained much attention as a measure of uncertainty and unpredictability associated with a dynamical system, eventually depicted by a stochastic process. In particular, the Shannon entropy measures the degree of order/disorder of a given signal and provides useful information about the underlying dynamical process. It has found widespread application in a variety of fields, such as, for example, cryptography, statistical physics and finance. In this regard, many contributions have employed different measures of entropy in an attempt to characterize the financial time series in terms of market efficiency, market crashes and/or financial crises. The Shannon entropy has also been considered as a measure of the risk of a portfolio or as a tool in asset pricing. This work investigates the theoretical link between the Shannon entropy and the multifractional Brownian motion (mBm), stochastic process which recently is the focus of a renewed interest in finance as a driving model of stochastic volatility. In particular, after exploring the current state of research in this area and highlighting some of the key results and open questions that remain, we show a well-defined relationship between the Shannon (log)entropy and the memory function H(t) of the mBm. In details, we allow both the length of time series and time scale to change over analysis to study how the relation modify itself. On the one hand, applications are developed after generating surrogates of mBm trajectories based on different memory functions; on the other hand, an empirical analysis of several international stock indexes, which confirms the previous results, concludes the work.

Keywords: Shannon entropy, multifractional Brownian motion, Hurst–Holder exponent, stock indexes

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Authors: Raza Abdulla Saeed

Abstract:

In this study, the three-dimensional cavitating turbulent flow in a complete Francis turbine is simulated using mixture model for cavity/liquid two-phase flows. Numerical analysis is carried out using ANSYS CFX software release 12, and standard k-ε turbulence model is adopted for this analysis. The computational fluid domain consist of spiral casing, stay vanes, guide vanes, runner and draft tube. The computational domain is discretized with a three-dimensional mesh system of unstructured tetrahedron mesh. The finite volume method (FVM) is used to solve the governing equations of the mixture model. Results of cavitation on the runner’s blades under three different boundary conditions are presented and discussed. From the numerical results it has been found that the numerical method was successfully applied to simulate the cavitating two-phase turbulent flow through a Francis turbine, and also cavitation is clearly predicted in the form of water vapor formation inside the turbine. By comparison the numerical prediction results with a real runner; it’s shown that the region of higher volume fraction obtained by simulation is consistent with the region of runner cavitation damage.

Keywords: computational fluid dynamics, hydraulic francis turbine, numerical simulation, two-phase mixture cavitation model

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Authors: Nooshin Salari, Viliam Makis

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In this paper, we propose a condition-based maintenance policy for multi-unit systems considering the existence of economic dependency among units. We consider a system composed of N identical units, where each unit deteriorates independently. Deterioration process of each unit is modeled as a three-state continuous time homogeneous Markov chain with two working states and a failure state. The average production rate of units varies in different working states and demand rate of the system is constant. Units are inspected at equidistant time epochs, and decision regarding performing maintenance is determined by the number of units in the failure state. If the total number of units in the failure state exceeds a critical level, maintenance is initiated, where units in failed state are replaced correctively and deteriorated state units are maintained preventively. Our objective is to determine the optimal number of failed units to initiate maintenance minimizing the long run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. A numerical example is developed to demonstrate the proposed policy and the comparison with the corrective maintenance policy is presented.

Keywords: reliability, maintenance optimization, semi-Markov decision process, production

Procedia PDF Downloads 144