Search results for: knowledge management model

Authors: Ali Javaid, Rizwan Latif, Syed Adnan Qasim, Imran Shafi

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To control combustion inside a direct injection diesel engine, fuel atomization is the best tool. Controlling combustion helps in reducing emissions and improves efficiency. Cavitation is one of the most important factors that significantly affect the nature of spray before it injects into combustion chamber. Typical fuel injector nozzles are small and operate at a very high pressure, which limits the study of internal nozzle behavior especially in case of diesel engine. Simulating cavitation in a fuel injector will help in understanding the phenomenon and will assist in further development. There is a parametric variation between high speed and high torque low speed diesel engines. The objective of this study is to simulate internal spray characteristics for a low speed high torque diesel engine. In-nozzle cavitation has strong effects on the parameters e.g. mass flow rate, fuel velocity, and momentum flux of fuel that is to be injected into the combustion chamber. The external spray dynamics and subsequently the air – fuel mixing depends on a lot of the parameters of fuel injecting the nozzle. The approach used to model turbulence induced in – nozzle cavitation for high-torque low-speed diesel engine, is homogeneous equilibrium model. The governing equations were modeled using Matlab. Complete Model in question was extensively evaluated by performing 3-D time-dependent simulations on Open FOAM, which is an open source flow solver and implemented in CFD (Computational Fluid Dynamics). Results thus obtained will be analyzed for better evaporation in the near-nozzle region. The proposed analyses will further help in better engine efficiency, low emission, and improved fuel economy.

Keywords: cavitation, HEM model, nozzle flow, open foam, turbulence

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Authors: Mosses E. Lufuke, Lorna M. Kamau

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This paper attempted to assess whether the size of the regional economic bloc has an impact to the flow of trade to a particular country. Two different sized blocs (COMESA and EAC) and one country (Tanzania) have been used as the point of references. Using the results from of the analyses, the paper also was anticipated to establish whether it was rational for Tanzania to withdraw its membership from COMESA (the larger bloc) to join EAC (the small one). Gravity model has been used to estimate the relationship between the variables, from which the bilateral trade flows between Tanzania and the eighteen member countries of the two blocs (COMESA and EAC) was employed for the time between 2000 and 2013. In the model, the dummy variable for regional bloc (bloc) at which the Tanzania trade partner countries belong are also added to the model to understand which trade bloc exhibit higher trade flow with Tanzania. From the findings, it was noted that over the period of study (2000-2013) Tanzania acknowledged more than 257% of trade volume in EAC than in COMESA. Conclusive, it was noted that the flow of trade is explained by many other variables apart from the size of regional bloc; and that the size by itself offer insufficient evidence in causality relationship. The paper therefore remain neutral on such staggered switching decision since more analyses are required to establish the country’s trade flow, especially when if it had been in multiple membership of COMESA and EAC.

Keywords: economic bloc, flow of trade, size of bloc, switching

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Authors: D. B. Gohil

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Closed die forging is a very complex process, and measurement of actual forces for real material is difficult and time consuming. Hence, the modelling technique has taken the advantage of carrying out the experimentation with the proper model material which needs lesser forces and relatively low temperature. The results of experiments on the model material then may be correlated with the actual material by using the theory of similarity. There are several methods available to resolve the complexity involved in the closed die forging process. Finite Element Method (FEM) and Finite Difference Method (FDM) are relatively difficult as compared to the slab method. The slab method is very popular and very widely used by the people working on shop floor because it is relatively easy to apply and reasonably accurate for most of the common forging load requirement computations.

Keywords: experimentation, forging, process modeling, strain distribution

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Authors: Nileshkumar Vishnav, Aditya Tatu

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A recent approach of representing graph signals and graph filters as polynomials is useful for graph signal processing. In this approach, the adjacency matrix plays pivotal role; instead of the more common approach involving graph-Laplacian. In this work, we follow the adjacency matrix based approach and corresponding algebraic signal model. We further expand the theory and introduce the concept of similarity of two graphs. The similarity of graphs is useful in that key properties (such as filter-response, algebra related to graph) get transferred from one graph to another. We demonstrate potential applications of the relation between two similar graphs, such as nonuniform filter design, DTMF detection and signal reconstruction.

Keywords: graph signal processing, algebraic signal processing, graph similarity, isospectral graphs, nonuniform signal processing

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Authors: Felermino D. M. A. Ali, S. C. Ng

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E-learning is an evolutionary form of distance learning and has become better over time as new technologies emerged. Today, efforts are still being made to embrace E-learning systems with emerging technologies in order to make them better. Among these advancements, Educational Data Mining (EDM) is one that is gaining a huge and increasing popularity due to its wide application for improving the teaching-learning process in online practices. However, even though EDM promises to bring many benefits to educational industry in general and E-learning environments in particular, its principal drawback is the lack of easy to use tools. The current EDM tools usually require users to have some additional technical expertise to effectively perform EDM tasks. Thus, in response to these limitations, this study intends to design and implement an EDM application framework which aims at automating and simplify the development of EDM in E-learning environment. The application framework introduces a Service-Oriented Architecture (SOA) that hides the complexity of technical details and enables users to perform EDM in an automated fashion. The framework was designed based on abstraction, extensibility, and interoperability principles. The framework implementation was made up of three major modules. The first module provides an abstraction for data gathering, which was done by extending Moodle LMS (Learning Management System) source code. The second module provides data mining methods and techniques as services; it was done by converting Weka API into a set of Web services. The third module acts as an intermediary between the first two modules, it contains a user-friendly interface that allows dynamically locating data provider services, and running knowledge discovery tasks on data mining services. An experiment was conducted to evaluate the overhead of the proposed framework through a combination of simulation and implementation. The experiments have shown that the overhead introduced by the SOA mechanism is relatively small, therefore, it has been concluded that a service-oriented architecture can be effectively used to facilitate educational data mining in E-learning environments.

Keywords: educational data mining, e-learning, distributed data mining, moodle, service-oriented architecture, Weka

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Authors: Zhiyan Meng, Dan Liu, Jintao Meng

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Dependable encrypted traffic classification is crucial for improving cybersecurity and handling the growing amount of data. Large language models have shown that learning from large datasets can be effective, making pre-trained methods for encrypted traffic classification popular. However, attention-based pre-trained methods face two main issues: their large neural parameters are not suitable for low-computation environments like mobile devices and real-time applications, and they often overfit by getting stuck in local minima. To address these issues, we developed a lightweight transformer model, which reduces the computational parameters through lightweight vocabulary construction and Squeeze-and-Excitation Block. We use sharpness-aware optimization to avoid local minima during pre-training and capture temporal features with relative positional embeddings. Our approach keeps the model's classification accuracy high for downstream tasks. We conducted experiments on four datasets -USTC-TFC2016, VPN 2016, Tor 2016, and CICIOT 2022. Even with fewer than 18 million parameters, our method achieves classification results similar to methods with ten times as many parameters.

Keywords: sharpness-aware optimization, encrypted traffic classification, squeeze-and-excitation block, pretrained model

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Authors: Nurdiana Gaus, Mahmud Tang

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This paper analyses changes being experienced by academics in Indonesian state university systems as a result of government-driven policy and the impacts of these changes on academics work and organisations. This analysis is located in the main concept of neoliberal agenda with its associated discourse of New Public Management. The purpose of this analysis is to show how public administrative reforms adopting neoliberal agenda have been disseminated in Indonesian higher education reform via policies and programmes of the government. This essay is expected to clarify the concept of neoliberalism in the administrative reforms within higher education institutions by examining and understanding its implementation in Indonesian context and how this impacted on the structural changes in universities and academics work.

Keywords: neoliberalism, higher education, Indonesia, new public management

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Authors: Mattia Testuzza

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Public health is a social endeavour, which involves many different actors: from extremely stratified, structured health systems to unofficial networks of people and knowledge. Health and diseases are an intertwined individual and social experiences. Both patients and health workers navigate this public space through relations of trust. Trust in healthcare goes from the personal trust between a patient and her/his doctor to the trust of both the patient and the health worker in the medical knowledge and the healthcare system. Trust it is not a given, but it is continuously negotiated, given and gained. The key to understand these essential relations of trust in health is to recognise them as a social practice, which therefore implies agency and power. In these terms, health is constantly public and made public, as trust emerges as a meaningfully political phenomenon. Trust as a power relation can be observed at play in the implementation of public health policies such as the WHO’s Directly-Observed Theraphy Short-course (DOTS), and with the increasing concern for drug-resistance that tuberculosis pose, looking at the role of trust in the healthcare delivery system and implementation of public health policies becomes significantly relevant. The ethnographic fieldwork was carried out in four months through observation of the daily practices at the National Tuberculosis Center of Nepal, and semi-structured interviews with MultiDrug-Resistant Tuberculosis (MDR-TB) patients at different stages of the treatment, their relatives, MDR-TB specialised nurses, and doctors. Throughout the research, the role which trust plays in tuberculosis treatment emerged as one fundamental ax that cuts through all the different factors intertwined with drug-resistance development, unfolding a tension between the DOTS policy, which undermines trust, and the day-to-day healthcare relations and practices which cannot function without trust. Trust also stands out as a key component of the solutions to unforeseen issues which develop from the overall uncertainty of the context - for example, political instability and extreme poverty - in which tuberculosis treatment is carried out in Nepal.

Keywords: trust, tuberculosis, drug-resistance, politics of health

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Authors: Argaw T. Gurmu, Muhammad N. Mahmood

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The objective of this research is to identify the architecture and construction management students’ learning challenges of the building measurement. This research used the survey data obtained collected from the students who completed the building measurement unit. NVivo qualitative data analysis software was used to identify relevant themes. The analysis of the qualitative data revealed the major learning difficulties such as inadequacy of practice questions for the examination, inability to work as a team, lack of detailed understanding of the prerequisite units, insufficiency of the time allocated for tutorials and incompatibility of lecture and tutorial schedules. The output of this research can be used as a basis for improving the teaching and learning activities in construction measurement units.

Keywords: building measurement, construction management, learning challenges, evaluate survey

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Authors: Nabil Mezhoud

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The economic operation of electric energy generating systems is one of the predominant problems in energy systems. Due to the need for better reliability, high energy quality, lower losses, lower cost and a clean environment, the application of renewable and sustainable energy sources, such as wind energy, solar energy, etc., in recent years has become more widespread. In this work, one of a bio-inspired meta-heuristic algorithm inspired by the flashing behavior of fireflies at night called the Firefly Algorithm (FFA) is applied to solve the Optimal Energy Management (OEM) and the environmental index (EI) problems of a micro-grid (MG) operating by Renewable and Sustainable Generation Systems (RSGS). Our main goal is to minimize the nonlinear objective function of an electrical microgrid, taking into account equality and inequality constraints. The FFA approach was examined and tested on a standard MG system composed of different types of RSGS, such as wind turbines (WT), photovoltaic systems (PV), and non-renewable energy, such as fuel cells (FC), micro turbine (MT), diesel generator (DEG) and loads with energy storage systems (ESS). The results are promising and show the effectiveness and robustness of the proposed approach to solve the OEM and the EI problems. The results of the proposed method have been compared and validated with those known references published recently.

Keywords: renewable energy sources, energy management, distributed generator, micro-grids, firefly algorithm

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Authors: M. Medrano, M. D. M. S., L. Younes, M. D.

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Introduction: Incidence of tibial hemimelia is 1:1,000,000. Due to pre-existing case studies and literature, there is now a better understanding of the genetics, etiology and pathoanatomy of tibial hemimelia, but an underlying cause is generally unknown. This presentation aims to discuss a rare, congenital lower limb deficiency observed in a patient in order to identify potential prenatal risk factors and future considerations for the patient’s well-being. Observation: A newborn female child, born full term via spontaneous vaginal delivery after induction of labor to unaffected and non-consanguineous parents. The prenatal course was notable for limited and disjointed prenatal care as well as maternal tobacco and marijuana use, anemia of pregnancy, and inadequate weight gain. Prenatal imaging showed lower extremity deformity with the inability to visualize tibia and bilateral clubfeet in the setting of Intrauterine Growth Restriction (IUGR). The patient presented with right equino varus deformity of the foot and right knee joint deformity. Radiological imaging showed the absence of the right tibia and varus angulation of the right foot with dislocation of the tibiotalar joint. Normal femur with lateral and mild anterior displacement of a wide fibula (Weber Type VIIa). Due to the absence of the patient’s tibia and knee extensor mechanism, the patient was not a candidate for reconstructive surgery and ultimately underwent successful right knee disarticulation. Discussion and Conclusion: By utilizing a retrospective chart review of this case, possible risk factors in prenatal care may be identified and add to existing knowledge on etiology. Hopefully, a cause can be clearly identified in the future and, thus, addressed in the prenatal period. In addition, we can investigate the patient’s well-being and adjustment post-operatively to support outpatient management of an uncommon anomaly.

Keywords: Tibial hemimelia, prenatal care, pediatric orthopedics, congenital deformity

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Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

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Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

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Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

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Authors: Yun-Tao Zhang, Jong-Yeop Bae, Whoi-Yul Kim

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Background modeling and subtraction in video analysis has been widely proved to be an effective method for moving objects detection in many computer vision applications. Over the past years, a large number of approaches have been developed to tackle different types of challenges in this field. However, the dynamic background and illumination variations are two of the most frequently occurring issues in the practical situation. This paper presents a new two-layer model based on codebook algorithm incorporated with local binary pattern (LBP) texture measure, targeted for handling dynamic background and illumination variation problems. More specifically, the first layer is designed by block-based codebook combining with LBP histogram and mean values of RGB color channels. Because of the invariance of the LBP features with respect to monotonic gray-scale changes, this layer can produce block-wise detection results with considerable tolerance of illumination variations. The pixel-based codebook is employed to reinforce the precision from the outputs of the first layer which is to eliminate false positives further. As a result, the proposed approach can greatly promote the accuracy under the circumstances of dynamic background and illumination changes. Experimental results on several popular background subtraction datasets demonstrate a very competitive performance compared to previous models.

Keywords: background subtraction, codebook model, local binary pattern, dynamic background, illumination change

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Authors: Rahat Zaman

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The present study was conducted to investigate psychological well-being and positive and negative affect among adults. The sample comprised 221 adults; the sample was collected from all over Pakistan. Psychological well-being was measured with the help of the psychological well-being scale developed by Ryff and Keyes (1995). Lifestyle was measured with the help of the Health Promoting Lifestyle Profile Scale developed by Walker et al. (1995). Positive and negative effects were measured by PANAS, developed by Watson, Clark, and Tellegen (1998). To check the properties of scale, the alpha reliability coefficient was calculated. To test the hypotheses of the research, correlation, independent sample t-rest, and ANOVA were computed. It was hypothesized that there would be a positive relationship between psychological well-being and lifestyles and positive affect. The results show that psychological well-being, lifestyle, and positive affect are positively related. This also supports our hypothesis. The research also searched for relationships in the study variables according to the demographics of the sample. The respondents varied according to their dominant affect levels with respect to their psychological well-being and lifestyles. The research found significant differences for the genders in life appreciation, nutrition, and negative affect. Single and married individuals differed significantly on autonomy, environmental mastery, life appreciation, nutrition, and stress management. Individuals showed significant differences with respect to their living situation, joint and nuclear family members showed significant differences in personal growth, autonomy, health responsibilities, social support, physical activities, and stress management. The sample showed significant differences in environmental mastery, personal growth, purpose in life, life appreciation, health responsibilities, physical activities, stress management, and negative affect when divided in socioeconomic status. Age-wise analysis showed significant differences in autonomy, personal growth, purpose in life, life appreciation, nutrition, and stress management. Provincially significant differences were found in life appreciation, nutrition, social support, physical activities, and stress management, and both positive and negative effects were experienced. Implications of the results are discussed.

Keywords: wellbeing, healthy lifestyle, self acceptance, positive

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Authors: Jafar Khodagholizadeh

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In this talk, we study the tensor mode equation of perturbation in the presence of nonzero $-\Lambda$ as dark energy, whose dynamic nature depends on the Hubble parameter $ H$ and/or its time derivative. Dark energy, according to the total vacuum contribution, has little effect during the radiation-dominated era, but it reduces the squared amplitude of gravitational waves (GWs) up to $60\%$ for the wavelengths that enter the horizon during the matter-dominated era. Moreover, the observations bound on dark energy models, such as running vacuum model (RVM), generalized running vacuum model (GRVM), and generalized running vacuum subcase (GRVS), are effective in reducing the GWs’ amplitude. Although this effect is less for the wavelengths that enter the horizon at later times, this reduction is stable and permanent.

Keywords: gravitational waves, dark energy, GW's amplitude, all stage universe

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Authors: Femy M. Makkar, S. Chandrakaran, N. Sankar

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The concept of reinforced earth has been used in the field of geotechnical engineering since 1960s, for many applications such as, construction of road and rail embankments, pavements, retaining walls, shallow foundations, soft ground improvement and so on. Conventionally, planar geosynthetic materials such as geotextiles and geogrids were used as the reinforcing elements. Recently, the use of three dimensional reinforcements becomes one of the emerging trends in this field. So, in the present investigation, three dimensional geogrid is proposed as a reinforcing material. Laboratory scaled plate load tests are conducted on a model square footing resting on 3D geogrid reinforced sand bed. The performance of 3D geogrids in triangular and square pattern was compared with conventional geogrids and the improvement in bearing capacity and reduction in settlement and heave are evaluated. When single layer of reinforcement was placed at an optimum depth of 0.25B from the bottom of the footing, the bearing capacity of conventional geogrid reinforced soil improved by 1.85 times compared to unreinforced soil, where as 3D geogrid reinforced soil with triangular pattern and square pattern shows 2.69 and 3.05 times improvement respectively compared to unreinforced soil. Also, 3D geogrids performs better than conventional geogrids in reducing the settlement and heave of sand bed around the model footing.

Keywords: 3D reinforcing elements, bearing capacity, heavy, settlement

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Authors: A. El-S. Makled, M. K. Al-Tamimi

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A mathematical model to predict the performance parameters (thrusts, chamber pressures, fuel mass flow rates, mixture ratios, and regression rates during firing time) of hybrid rocket motor (HRM) is evaluated. The internal ballistic (IB) hybrid combustion model assumes that the solid fuel surface regression rate is controlled only by heat transfer (convective and radiative) from flame zone to solid fuel burning surface. A laboratory HRM is designed, manufactured, and tested for low thrust profile space missions (10-15 N) and for validating the mathematical model (computer program). The polymer material and gaseous oxidizer which are selected for this experimental work are polymethyle-methacrylate (PMMA) and polyethylene (PE) as solid fuel grain and gaseous oxygen (GO₂) as oxidizer. The variation of various operational parameters with time is determined systematically and experimentally in firing of up to 20 seconds, and an average combustion efficiency of 95% of theory is achieved, which was the goal of these experiments. The comparison between recording fire data and predicting analytical parameters shows good agreement with the error that does not exceed 4.5% during all firing time. The current mathematical (computer) code can be used as a powerful tool for HRM analytical design parameters.

Keywords: hybrid combustion, internal ballistics, hybrid rocket motor, performance parameters

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Authors: Lani Fraizer

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Increasingly, individuals from diverse professional and academic backgrounds are making a conscious choice to pursue careers related to social change; a sophisticated understanding of social entrepreneur education is becoming ever more important. Social entrepreneurs are impassioned change makers who characteristically combine leadership and entrepreneurial spirits to problem solve social ills affecting our planet. Generating partnership opportunities and nurturing them is an important part of their change-making work. Faced with the complexities of these partnerships, social entrepreneurs and people who work with them need to be well prepared to tackle new and unforeseen challenges faced. As partnerships become even more critical to advance initiatives at scale, for example, understanding the partnership brokering role is even more important for educators who prepare these leaders to establish and sustain multi-stakeholder partnerships. This paper aims to provide practitioners in social entrepreneurship with enhanced knowledge of partnership brokering and identify directions for future research. A literature review search from January 1977 to May 2015 was conducted using the combined keywords ‘partnership brokering’ and ‘social entrepreneurship’ via WorldCat, one of the largest database catalogs in the world with collections of more than 10,000 worldwide. This query focused on literature written in the English language and analyzed solely the role of partnership brokering in social entrepreneurship. The synthesis of the literature review found three main themes emerging: the need for more professional awareness of partnership brokering and its value add in systems change-making work, the need for more knowledge on developing partnership brokering competencies, and the need for more applied research in the area of partnership brokering and how it is practiced by practitioners in social entrepreneurship. The results of the review serve to emphasize and reiterate the importance of partnership brokers in social entrepreneurship work, and act as a reminder of the need for further scholarly research in this area to bridge the gap between practice and research.

Keywords: partnership brokering, leadership, social entrepreneurship, systems changemaking

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Authors: Nancy N. Sharmila, Aparna Mishra

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Hemiparesis affects almost 80% of stroke patients each year. It is marked by paralysis or weakness on one half of the body. Our model provides both assistance and physical therapy for hemiparesis patients for swift recovery. In order to accomplish our goal a force is provided that pulls the forearm up (as in flexing the arm), and pushes the forearm down (as in extending the arm), which will also assist the user during ADL (Activities of Daily Living). The model consists of a mechanical component which is placed around the patient’s bicep and an EMG control circuit to assist patients in daily activities, which makes it affordable and easy to use. In order to enhance the neuromuscular system’s effectiveness in synchronize the movement, proprioceptive neuromuscular facilitation (PNF) concept is used. The EMG signals are acquired from the unaffected arm as an input to drive the orthosis. This way the patient is invigorated to use the orthosis for regular exercise.

Keywords: EMG, hemiparesis, orthosis, rehabilitation

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Authors: Leorisyl D. Siarot

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It is conventional to see and hear Filipinos, in general, speak two or more languages. This phenomenon brings us to a closer look on how our minds process the input and produce an output with a specific chosen language. This study aimed to generate a theoretical model which explained the interaction of the first and the second languages in the human mind. After a careful analysis of the gathered data, a theoretical prototype called Language Activation Model was generated. For every string, there are three specialized banks: lexico-semantics, morphono-syntax, and pragmatics. These banks are interrelated to other banks of other language strings. As the bilingual learns more languages, a new string is replicated and is filled up with the information of the new language learned. The principles of the first and second languages' interaction are drawn; these are expressed in laws, namely: law of dominance, law of availability, law of usuality and law of preference. Furthermore, difficulties encountered in the learning of second languages were also determined.

Keywords: bilingualism, psycholinguistics, second language learning, languages

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Authors: Nasir Khalid, S. Thirumalaichelvam

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In most buildings, according to US Department of Energy Data Book, the electrical consumption attributable to centralized heating and ventilation of air- condition (HVAC) component can be as high as 40-60% of the total electricity consumption for an entire building. To provide efficient energy management for the market today, researchers are finding new ways to develop a system that can save electrical consumption of buildings even more. In this concept paper, a system known as Intelligent Chiller Energy Efficiency (iCEE) System is being developed that is capable of saving up to 25% from the chiller’s existing electrical energy consumption. In variable frequency drives (VFDs), research has found significant savings up to 30% of electrical energy consumption. Together with the VFDs at specific Air Handling Unit (AHU) of HVAC component, this system will save even more electrical energy consumption. The iCEE System is compatible with any make, model or age of centrifugal, rotary or reciprocating chiller air-conditioning systems which are electrically driven. The iCEE system uses engineering principles of efficiency analysis, enthalpy analysis, heat transfer, mathematical prediction, modified genetic algorithm, psychometrics analysis, and optimization formulation to achieve true and tangible energy savings for consumers.

Keywords: variable frequency drives, adjustable speed drives, ac drives, chiller energy system

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Authors: Kazuki Kamada, Haruka Yamashita

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In Japan, taxi is one of the popular transportations and taxi industry is one of the big businesses. However, in recent years, there has been a difficult problem of reducing the number of taxi drivers. In the taxi business, mainly three passenger catching methods are applied. One style is "cruising" that drivers catches passengers while driving on a road. Second is "waiting" that waits passengers near by the places with many requirements for taxies such as entrances of hospitals, train stations. The third one is "dispatching" that is allocated based on the contact from the taxi company. Above all, the cruising taxi drivers need the experience and intuition for finding passengers, and it is difficult to decide "the destination for cruising". The strong recommendation system for the cruising taxies supports the new drivers to find passengers, and it can be the solution for the decreasing the number of drivers in the taxi industry. In this research, we propose a method of recommending a destination for cruising taxi drivers. On the other hand, as a machine learning technique, the embedding models that embed the high dimensional data to a low dimensional space is widely used for the data analysis, in order to represent the relationship of the meaning between the data clearly. Taxi drivers have their favorite courses based on their experiences, and the courses are different for each driver. We assume that the course of cruising taxies has meaning such as the course for finding business man passengers (go around the business area of the city of go to main stations) and course for finding traveler passengers (go around the sightseeing places or big hotels), and extract the meaning of their destinations. We analyze the cruising history data of taxis based on the embedding model and propose the recommendation system for passengers. Finally, we demonstrate the recommendation of destinations for cruising taxi drivers based on the real-world data analysis using proposing method.

Keywords: taxi industry, decision making, recommendation system, embedding model

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Authors: M.Rüştü Karaman, İsmail İşeri, Kadir Saltalı, A.Reşit Brohi, Ayhan Horuz, Mümin Dizman

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Considerable relations has recently been given to the environmental hazardous caused by agricultural chemicals such as excess fertilizers. In this study, a neural network approach was investigated in the prediction of potential nitrate pollution across different land-use patterns by using a feedforward multilayered computer model of artificial neural network (ANN) with proper training. Periodical concentrations of some anions, especially nitrate (NO3-), and cations were also detected in drainage waters collected from the drain pipes placed in irrigated tomato field, unirrigated wheat field, fallow and pasture lands. The soil samples were collected from the irrigated tomato field and unirrigated wheat field on a grid system with 20 m x 20 m intervals. Site specific nitrate concentrations in the soil samples were measured for ANN based simulation of nitrate leaching potential from the land profiles. In the application of ANN model, a multi layered feedforward was evaluated, and data sets regarding with training, validation and testing containing the measured soil nitrate values were estimated based on spatial variability. As a result of the testing values, while the optimal structures of 2-15-1 was obtained (R2= 0.96, P < 0.01) for unirrigated field, the optimal structures of 2-10-1 was obtained (R2= 0.96, P < 0.01) for irrigated field. The results showed that the ANN model could be successfully used in prediction of the potential leaching levels of nitrate, based on different land use patterns. However, for the most suitable results, the model should be calibrated by training according to different NN structures depending on site specific soil parameters and varied agricultural managements.

Keywords: artificial intelligence, ANN, drainage water, nitrate pollution

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Authors: Anila Xhahysa, Migena Ceyhan, Neki Kuka, Klajdi Qoshi, Damiano Koxhaj

Abstract:

The seismic event catalog has been updated in the framework of a bilateral project supported by the Central European Investment Fund and with the extensive support of Global Earthquake Model Foundation to update Albania's national seismic hazard model. The earthquake catalogue prepared within this project covers the Western Balkan area limited by 38.0° - 48°N, 12.5° - 24.5°E and includes 41,806 earthquakes that occurred in the region between 510 BC and 2022. Since the moment magnitude characterizes the earthquake size accurately and the selected ground motion prediction equations for the seismic hazard assessment employ this scale, it was chosen as the uniform magnitude scale for the catalogue. Therefore, proxy values of moment magnitude had to be obtained by using new magnitude conversion equations between the local and other magnitude types to this unified scale. The Global Centroid Moment Tensor Catalogue was considered the most authoritative for moderate to large earthquakes for moment magnitude reports; hence it was used as a reference for calibrating other sources. The best fit was observed when compared to some regional agencies, whereas, with reports of moment magnitudes from Italy, Greece and Turkey, differences were observed in all magnitude ranges. For teleseismic magnitudes, to account for the non-linearity of the relationships, we used the exponential model for the derivation of the regression equations. The obtained regressions for the surface wave magnitude and short-period body-wave magnitude show considerable differences with Global Earthquake Model regression curves, especially for low magnitude ranges. Moreover, a conversion relation was obtained between the local magnitude of Albania and the corresponding moment magnitude as reported by the global and regional agencies. As errors were present in both variables, the Deming regression was used.

Keywords: regression, seismic catalogue, local magnitude, tele-seismic magnitude, moment magnitude

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Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

Abstract:

Large eddy simulation (LES) has been extensively used in the investigation of turbulence. LES calculates the grid-resolved large-scale motions and leaves small scales modeled by sublfilterscale (SFS) models. Among the existing SFS models, the deconvolution model has been used successfully in the LES of the engineering flows and geophysical flows. Despite the wide application of deconvolution models, the effects of subfilter scale dynamics and filter anisotropy on the accuracy of SFS modeling have not been investigated in depth. The results of LES are highly sensitive to the selection of filters and the anisotropy of the grid, which has been overlooked in previous research. In the current study, two critical aspects of LES are investigated. Firstly, we analyze the influence of sub-filter scale (SFS) dynamics on the accuracy of direct deconvolution models (DDM) at varying filter-to-grid ratios (FGR) in isotropic turbulence. An array of invertible filters are employed, encompassing Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The significance of FGR becomes evident, as it acts as a pivotal factor in error control for precise SFS stress prediction. When FGR is set to 1, the DDM models cannot accurately reconstruct the SFS stress due to the insufficient resolution of SFS dynamics. Notably, prediction capabilities are enhanced at an FGR of 2, resulting in accurate SFS stress reconstruction, except for cases involving Helmholtz I and II filters. A remarkable precision close to 100% is achieved at an FGR of 4 for all DDM models. Additionally, the further exploration extends to the filter anisotropy to address its impact on the SFS dynamics and LES accuracy. By employing dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with the anisotropic filter, aspect ratios (AR) ranging from 1 to 16 in LES filters are evaluated. The findings highlight the DDM's proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. High correlation coefficients exceeding 90% are observed in the a priori study for the DDM's reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as lter anisotropy increases. In the a posteriori studies, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, encompassing velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strain-rate tensors, and SFS stress. It is observed that as filter anisotropy intensify, the results of DSM and DMM become worse, while the DDM continues to deliver satisfactory results across all filter-anisotropy scenarios. The findings emphasize the DDM framework's potential as a valuable tool for advancing the development of sophisticated SFS models for LES of turbulence.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Nino Chomakhashvili, Nino Chikhladze, Nato Pitskhelauri, Maia Bitskhinashvili

Abstract:

The dental practice is associated with occupational health challenges. Ergonomic risks in the workplace can significantly impair a dentist's work capacity and may even result in the premature end of their career. Implementing ergonomic principles in dental practice aims to prevent work-related musculoskeletal disorders. Many studies have been conducted in various countries such as Sweden, Denmark, Germany, Poland, and Australia to examine the prevalence of musculoskeletal disorders among dentists. However, to the best of authors knowledge there have been no studies on the application of ergonomic principles in dental practice in Georgia. This study focused on evaluating the ergonomic conditions of dental practice in Georgia and determining how common musculoskeletal disorders are among them. The survey was conducted using a random sampling method in selected dental clinics. A tailored questionnaire consisting of 40 questions, created using insights from international practices, was utilized for the study. Two hundred ninety-one filled questionnaires were used for the analysis. Most respondents reported that their workplaces adhered to ergonomic standards. However, 53.6% experienced frequent back pain, with 50.9% suffering from neck pain, 47.9% from shoulder pain, and 47.1% from lower back pain. Many noted that pain had caused them to reduce their working hours. Nearly all respondents expressed a desire to enhance their knowledge about ergonomics and the prevention of occupational diseases. They indicated a preference for participating in continuous professional development programs (61.5%), receiving information through leaflets (12.0%), and attending online webinars (26.6%). Integrating ergonomic principles into the dental practice is crucial for preventing work-related musculoskeletal disorders. It is essential to offer continuous professional development programs and provide information to dentists, via leaflets, thematic online or hybrid webinars.

Keywords: dental practice, ergonomic risks, musculoskeletal disorders, occupational health

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Authors: Jennifer Wheeldon, Nick de Viggiani, Nikki Cotterill

Abstract:

Background: Urinary and fecal incontinence affect a significant proportion of older adults aged 65 and over who permanently reside in residential and nursing home facilities. Incontinence symptoms have been linked to comorbidities, an increased risk of infection and reduced quality of life and mental wellbeing of residents. However, continence care provision can often be poor, further compromising the health and wellbeing of this vulnerable population. Objectives: To identify experiences and perceptions of continence care provision in older adult residential care settings and to identify factors that help or hinder good continence care provision. Settings included both residential care homes and nursing homes for older adults. Methods: A qualitative evidence synthesis using systematic review methodology established the current evidence-base. Data from 20 qualitative and mixed-method studies was appraised and synthesized. Following the review process, 10* qualitative interviews with staff working in older adult residential care settings were conducted across six* sites, which included registered managers, registered nurses and nursing/care assistants/aides. Purposive sampling recruited individuals from across England. Both evidence synthesis and interview data was analyzed thematically, both manually and with NVivo software. Results: The evidence synthesis revealed complex barriers and facilitators for continence care provision at three influencing levels: macro (structural and societal external influences), meso (organizational and institutional influences) and micro (day-to-day actions of individuals impacting service delivery). Macro-level barriers included negative stigmas relating to incontinence, aging and working in the older adult social care sector, restriction of continence care resources such as containment products (i.e. pads), short staffing in care facilities, shortfalls in the professional education and training of care home staff and the complex health and social care needs of older adult residents. Meso-level barriers included task-centered organizational cultures, ageist institutional perspectives regarding old age and incontinence symptoms, inadequate care home management and poor communication and teamwork among care staff. Micro-level barriers included poor knowledge and negative attitudes of care home staff and residents regarding incontinence symptoms and symptom management and treatment. Facilitators at the micro-level included proactive and inclusive leadership skills of individuals in management roles. Conclusions: The findings of the evidence synthesis study help to outline the complexities of continence care provision in older adult care homes facilities. Macro, meso and micro level influences demonstrate problematic and interrelated barriers across international contexts, indicating that improving continence care in this setting is extremely challenging due to the multiple levels at which care provision and services are impacted. Both international and national older adult social care policy-makers, researchers and service providers must recognize this complexity, and any intervention seeking to improve continence care in older adult care home settings must be planned accordingly and appreciatively of the complex and interrelated influences. It is anticipated that the findings of the qualitative interviews will shed further light on the national context of continence care provision specific to England; data collection is ongoing*. * Sample size is envisaged to be between 20-30 participants from multiple sites by Spring 2023.

Keywords: continence care, residential and nursing homes, evidence synthesis, qualitative

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Authors: Expedito Pinto De Paula Junior

Abstract:

Current systems such as artificial satellites, airplanes, automobiles, turbines, power systems and air traffic controls are becoming increasingly more complex and/or highly integrated as defined in SAE-ARP-4754A (Society Automotive Engineering - Certification considerations for highly-integrated or complex aircraft systems standard). Among other processes, the development of such systems requires careful Change and Configuration Management (CCM) to establish and maintain product integrity. Understand the maturity of CCM process based in historical approach is crucial for better implementation in hardware and software lifecycle. The sense of work organization, in all fields of development is directly related to the order and interrelation of the parties, changes in time, and record of these changes. Generally, is observed that engineers, administrators and managers invest more time in technical activities than in organization of work. More these professionals are focused in solving complex problems with a purely technical bias. CCM process is fundamental for development, production and operation of new products specially in the safety critical systems. The objective of this paper is open a discussion about the historical revision based in standards focus of CCM around the world in order to understand and reflect the importance across the years, the contribution of this process for technology evolution, to understand the mature of organizations in the system lifecycle project and the benefits of CCM to avoid errors and mistakes during the Lifecycle Product.

Keywords: changes, configuration management, historical, revision

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Authors: Rohit Kothari, Muneer Mohamed, Vivekanandh K., Sunmeet Sandhu, Preema Sinha, Anuj Bhatnagar

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Introduction: Hyper-IgE syndrome is a rare primary immunodeficiency syndrome characterised by triad of severe atopic dermatitis, recurrent pulmonary infections, and recurrent staphylococcal skin infections. The diagnosis requires a high degree of suspicion, typical clinical features, and not mere rise in serum-IgE levels, which may be seen in multiple conditions. Genetic studies are not always possible in a resource poor setting. This study highlights various presentations of Hyper-IgE syndrome in skin of color children. Case-series: Our study had six children of Hyper-IgE syndrome aged twomonths to tenyears. All had onset in first ten months of life except one with a late-onset at two years. All had recurrent eczematoid rash, which responded poorly to conventional treatment, secondary infection, multiple episodes of hospitalisation for pulmonary infection, and raised serum IgE levels. One case had occasional vesicles, bullae, and crusted plaques over both the extremities. Genetic study was possible in only one of them who was found to have pathogenic homozygous deletions of exon-15 to 18 in DOCK8 gene following which he underwent bone marrow transplant (BMT), however, succumbed to lower respiratory tract infection two months after BMT and rest of them received multiple courses of antibiotics, oral/ topical steroids, and cyclosporine intermittently with variable response. Discussion: Our study highlights various characteristics, presentation, and management of this rare syndrome in children. Knowledge of these manifestations in skin of color will facilitate early identification and contribute to optimal care of the patients as representative data on the same is limited in literature.

Keywords: absolute eosinophil count, atopic dermatitis, eczematous rash, hyper-immunoglobulin E syndrome, pulmonary infection, serum IgE, skin of color

Procedia PDF Downloads 132