Search results for: Kalyani Kulkarni
69 Enhancement of Capacity in a MC-CDMA based Cognitive Radio Network Using Non-Cooperative Game Model
Authors: Kalyani Kulkarni, Bharat Chaudhari
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This paper addresses the issue of resource allocation in the emerging cognitive technology. Focusing the quality of service (QoS) of primary users (PU), a novel method is proposed for the resource allocation of secondary users (SU). In this paper, we propose the unique utility function in the game theoretic model of Cognitive Radio which can be maximized to increase the capacity of the cognitive radio network (CRN) and to minimize the interference scenario. The utility function is formulated to cater the need of PUs by observing Signal to Noise ratio. The existence of Nash equilibrium is for the postulated game is established.Keywords: cognitive networks, game theory, Nash equilibrium, resource allocation
Procedia PDF Downloads 43968 Electronically Controlled Motorized Steering System (E-Mo Steer)
Authors: M. Prasanth, V. Nithin, R. Keerthana, S.Kalyani
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In the current scenario, the steering system in automobiles is such that the motion from the steering wheel is transferred to driving wheel by mechanical linkages. In this paper, we propose a method to design a steering mechanism using servomotors to turn the wheels instead of linkages. In this method, a steering angle sensor senses the turn angle of the steering wheel and its output is processed by an electronical control module. Then the ECM compares the angle value to that of a standard value from a look-up database. Then it gives the appropriate input power and the turning duration to the motors. Correspondingly, the motors turn the wheels by means of bevel gears welded to both the motor output shafts and the wheel hubs. Thus, the wheels are turned without the complicated framework of linkages, reducing the driver’s effort and fatigue considerably.Keywords: electronic control unit, linkage-less steering, servomotors, E-Mo Steer
Procedia PDF Downloads 23667 A System to Detect Inappropriate Messages in Online Social Networks
Authors: Shivani Singh, Shantanu Nakhare, Kalyani Nair, Rohan Shetty
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As social networking is growing at a rapid pace today it is vital that we work on improving its management. Research has shown that the content present in online social networks may have significant influence on impressionable minds. If such platforms are misused, it will lead to negative consequences. Detecting insults or inappropriate messages continues to be one of the most challenging aspects of Online Social Networks (OSNs) today. We address this problem through a Machine Learning Based Soft Text Classifier approach using Support Vector Machine algorithm. The proposed system acts as a screening mechanism the alerts the user about such messages. The messages are classified according to their subject matter and each comment is labeled for the presence of profanity and insults.Keywords: machine learning, online social networks, soft text classifier, support vector machine
Procedia PDF Downloads 47266 Experiential Learning: A Case Study for Teaching Operating System Using C and Unix
Authors: Shamshuddin K., Nagaraj Vannal, Diwakar Kulkarni, Raghavendra Nakod
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In most of the universities and colleges Operating System (OS) course is treated as theoretical and usually taught in a classroom using conventional teaching methods. In this paper we are presenting a new approach of teaching OS through experiential learning, the course is designed to suit the requirement of undergraduate engineering program of Instrumentation Technology. This new approach has benefited us to improve our student’s programming skills, presentation skills and understanding of the operating system concepts.Keywords: pedagogy, interactive learning, experiential learning, OS, C, UNIX
Procedia PDF Downloads 56565 Computation of Natural Logarithm Using Abstract Chemical Reaction Networks
Authors: Iuliia Zarubiieva, Joyun Tseng, Vishwesh Kulkarni
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Recent researches has focused on nucleic acids as a substrate for designing biomolecular circuits for in situ monitoring and control. A common approach is to express them by a set of idealised abstract chemical reaction networks (ACRNs). Here, we present new results on how abstract chemical reactions, viz., catalysis, annihilation and degradation, can be used to implement circuit that accurately computes logarithm function using the method of Arithmetic-Geometric Mean (AGM), which has not been previously used in conjunction with ACRNs.Keywords: chemical reaction networks, ratio computation, stability, robustness
Procedia PDF Downloads 12964 Analysis of the Inverse Kinematics for 5 DOF Robot Arm Using D-H Parameters
Authors: Apurva Patil, Maithilee Kulkarni, Ashay Aswale
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This paper proposes an algorithm to develop the kinematic model of a 5 DOF robot arm. The formulation of the problem is based on finding the D-H parameters of the arm. Brute Force iterative method is employed to solve the system of non linear equations. The focus of the paper is to obtain the accurate solutions by reducing the root mean square error. The result obtained will be implemented to grip the objects. The trajectories followed by the end effector for the required workspace coordinates are plotted. The methodology used here can be used in solving the problem for any other kinematic chain of up to six DOF.Keywords: 5 DOF robot arm, D-H parameters, inverse kinematics, iterative method, trajectories
Procedia PDF Downloads 16663 Foil Bearing Stiffness Estimation with Pseudospectral Scheme
Authors: Balaji Sankar, Sadanand Kulkarni
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Compliant foil gas lubricated bearings are used for the support of light loads in the order of few kilograms at high speeds, in the order of 50,000 RPM. The stiffness of the foil bearings depends both on the stiffness of the compliant foil and on the lubricating gas film. The stiffness of the bearings plays a crucial role in the stable operation of the supported rotor over a range of speeds. This paper describes a numerical approach to estimate the stiffness of the bearings using pseudo spectral scheme. Methodology to obtain the stiffness of the foil bearing as a function of weight of the shaft is given and the results are presented.Keywords: foil bearing, simulation, numerical, stiffness estimation
Procedia PDF Downloads 31062 Review on Effective Texture Classification Techniques
Authors: Sujata S. Kulkarni
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Effective and efficient texture feature extraction and classification is an important problem in image understanding and recognition. This paper gives a review on effective texture classification method. The objective of the problem of texture representation is to reduce the amount of raw data presented by the image, while preserving the information needed for the task. Texture analysis is important in many applications of computer image analysis for classification include industrial and biomedical surface inspection, for example for defects and disease, ground classification of satellite or aerial imagery and content-based access to image databases.Keywords: compressed sensing, feature extraction, image classification, texture analysis
Procedia PDF Downloads 39761 Reliability Analysis of Heat Exchanger Cycle Using Non-Parametric Method
Authors: Apurv Kulkarni, Shreyas Badave, B. Rajiv
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Non-parametric reliability technique is useful for assessment of reliability of systems for which failure rates are not available. This is useful when detection of malfunctioning of any component is the key purpose during ongoing operation of the system. The main purpose of the Heat Exchanger Cycle discussed in this paper is to provide hot water at a constant temperature for longer periods of time. In such a cycle, certain components play a crucial role and this paper presents an effective way to predict the malfunctioning of the components by determination of system reliability. The method discussed in the paper is feasible and this is clarified with the help of various test cases.Keywords: heat exchanger cycle, k-statistics, PID controller, system reliability
Procedia PDF Downloads 35360 Video Stabilization Using Feature Point Matching
Authors: Shamsundar Kulkarni
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Video capturing by non-professionals will lead to unanticipated effects. Such as image distortion, image blurring etc. Hence, many researchers study such drawbacks to enhance the quality of videos. In this paper, an algorithm is proposed to stabilize jittery videos .A stable output video will be attained without the effect of jitter which is caused due to shaking of handheld camera during video recording. Firstly, salient points from each frame from the input video are identified and processed followed by optimizing and stabilize the video. Optimization includes the quality of the video stabilization. This method has shown good result in terms of stabilization and it discarded distortion from the output videos recorded in different circumstances.Keywords: video stabilization, point feature matching, salient points, image quality measurement
Procedia PDF Downloads 27359 Synthesis and Performance Study of Co3O4 as a Bi-Functional Next Generation Material
Authors: Shrikaant Kulkarni, Akshata Naik Nimbalkar
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In this worki a method protocol has been developed for the synthesis of innovative Co3O4 material by using a method of chemical synthesis followed by calcination. The effect of calcination temperature on the morphology, structure and catalytic performance on material in question is investigated by using characterization tools like scanning electron microscopy (SEM), X-ray diffraction (XRD) spectroscopy and electrochemical techniques. The SEM images reveal that the morphology of the Co3O4 material undergoes a change from the rod to a beadlike shape on calcination at temperature of 700 °C. The XRD image shows that although the morphology of synthesized Co3O4 material exhibits a cubic phase but it differs in crystallinity depending upon morphology. Similarly spherical beadlike Co3O4 material has exhibited better activity than its rodlike counterpart which is reflected from electrochemical findings. Further, its performance in terms of bifunctional nature and hlods a lot much of promise as a excellent electrode material in the next generation batteries and fuel cells.Keywords: bifunctional, next generation material, Co3O4, XRD
Procedia PDF Downloads 33758 Interactive Learning Practices for Class Room Teaching
Authors: Shamshuddin K., Nagaraj Vannal, Diwakar Kulkarni
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This paper presents details of teaching and learning pedagogical techniques attempted for the undergraduate engineering program to improve the concentration span of students in a classroom. The details of activities such as valid statement, quiz competition, classroom paper, group work and product marketing to make the students remain active for the entire class duration and to improve presentation skills are presented. These activities shown tremendous improvement in student’s performance in academics, also in asking questions, concept understanding and interaction with the course instructor. With these pedagogical activities we are able to achieve Program outcome elements and ABET Program outcomes such as d, i, g and h which are difficult to achieve through the conventional teaching methods.Keywords: activities, pedagogy, interactive learning, valid statement, quiz competition, classroom papers, group work, product marketing
Procedia PDF Downloads 61657 A Review on Modeling and Optimization of Integration of Renewable Energy Resources (RER) for Minimum Energy Cost, Minimum CO₂ Emissions and Sustainable Development, in Recent Years
Authors: M. M. Wagh, V. V. Kulkarni
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The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques
Procedia PDF Downloads 30156 Critical Analysis of Heat Exchanger Cycle for its Maintainability Using Failure Modes and Effect Analysis and Pareto Analysis
Authors: Sayali Vyas, Atharva Desai, Shreyas Badave, Apurv Kulkarni, B. Rajiv
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The Failure Modes and Effect Analysis (FMEA) is an efficient evaluation technique to identify potential failures in products, processes, and services. FMEA is designed to identify and prioritize failure modes. It proves to be a useful method for identifying and correcting possible failures at its earliest possible level so that one can avoid consequences of poor performance. In this paper, FMEA tool is used in detection of failures of various components of heat exchanger cycle and to identify critical failures of the components which may hamper the system’s performance. Further, a detailed Pareto analysis is done to find out the most critical components of the cycle, the causes of its failures, and possible recommended actions. This paper can be used as a checklist which will help in maintainability of the system.Keywords: FMEA, heat exchanger cycle, Ishikawa diagram, pareto analysis, RPN (Risk Priority Number)
Procedia PDF Downloads 36955 Performance Evaluation of Various Segmentation Techniques on MRI of Brain Tissue
Authors: U.V. Suryawanshi, S.S. Chowhan, U.V Kulkarni
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Accuracy of segmentation methods is of great importance in brain image analysis. Tissue classification in Magnetic Resonance brain images (MRI) is an important issue in the analysis of several brain dementias. This paper portraits performance of segmentation techniques that are used on Brain MRI. A large variety of algorithms for segmentation of Brain MRI has been developed. The objective of this paper is to perform a segmentation process on MR images of the human brain, using Fuzzy c-means (FCM), Kernel based Fuzzy c-means clustering (KFCM), Spatial Fuzzy c-means (SFCM) and Improved Fuzzy c-means (IFCM). The review covers imaging modalities, MRI and methods for noise reduction and segmentation approaches. All methods are applied on MRI brain images which are degraded by salt-pepper noise demonstrate that the IFCM algorithm performs more robust to noise than the standard FCM algorithm. We conclude with a discussion on the trend of future research in brain segmentation and changing norms in IFCM for better results.Keywords: image segmentation, preprocessing, MRI, FCM, KFCM, SFCM, IFCM
Procedia PDF Downloads 29454 Integrated Management of Diseases of Vegetables and Flower Crops Grown in Protected Condition under Organic Production System
Authors: Shripad Kulkarni
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Plant disease is an impairment of the normal state of a plant that interrupts or modifies its vital functions. Disease occurs on different parts of plants and cause heavy losses. Diagnosis of Problem is very important before planning any management practice and this can be done based on appearance of the crop, examination of the root and examination of the soil. There are various types of diseases such as biotic (transmissible) which accounts for ~30% whereas , abiotic (not transmissible) diseases are the major one with ~70% incidence. Plant diseases caused by different groups of organism’s belonging fungi, bacteria, viruses, nematodes and few others have remained important in causing significant losses in different crops indicating the urgent need of their integrated management. Various factors favor disease development and different steps and methods are involved in management of diseases under protected condition. Management of diseases through botanicals and bioagents by modifying root and aerial environment, vector management along with care to be taken while managing the disease are analysed.Keywords: organic production system, diseases, bioagents and polyhouse, agriculture
Procedia PDF Downloads 37353 Potential Role of IL-1β in Synovial Fluid in Modulating Multiple Joint Tissue Pathologies Leading to Inflammation and Accelerating Cartilage Degeneration
Authors: Priya Kulkarni, Soumya Koppikar, Datta Shinde, Shantanu Deshpande, Narendrakumar Wagh, Abhay Harsulkar
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Osteoarthritis (OA) is associated with multiple and overlapping aetiologies. IL-1β is produced by stressed tissue and known to aggravate disease pathologies. We selected 10 patients with elevated IL-1β in their synovial fluids (SF). We hypothesized IL-1β as nodal-point connecting different pathologies. IL-1β was higher in all meniscal tear (MT) patients perhaps as the earliest response to injury. Since MT above age of 30 leads to OA in less than 5 years, it is attributed that IL-1β modulates OA pathology. Among all bilateral OA patients, an interesting case operated for Total-Knee-Replacement revealed differential cartilage degeneration demonstrating strong association with higher IL-1β. Symptoms like acute-pain, effusion and redness were correlated with higher IL-1β and NO (Nitric-oxide). However, higher IL-1β was also found without typical-inflammation characterized by infiltration of neutrophils and macrophages. Cultured synoviocytes responded to IL-1β by releasing NO. In conclusion, IL-1β in SF acquires central position influencing different OA pathologies and aetiologies.Keywords: IL-1β, meniscal tear, osteoarthritis, synovial fluid
Procedia PDF Downloads 55452 Comparison of Different Machine Learning Models for Time-Series Based Load Forecasting of Electric Vehicle Charging Stations
Authors: H. J. Joshi, Satyajeet Patil, Parth Dandavate, Mihir Kulkarni, Harshita Agrawal
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As the world looks towards a sustainable future, electric vehicles have become increasingly popular. Millions worldwide are looking to switch to Electric cars over the previously favored combustion engine-powered cars. This demand has seen an increase in Electric Vehicle Charging Stations. The big challenge is that the randomness of electrical energy makes it tough for these charging stations to provide an adequate amount of energy over a specific amount of time. Thus, it has become increasingly crucial to model these patterns and forecast the energy needs of power stations. This paper aims to analyze how different machine learning models perform on Electric Vehicle charging time-series data. The data set consists of authentic Electric Vehicle Data from the Netherlands. It has an overview of ten thousand transactions from public stations operated by EVnetNL.Keywords: forecasting, smart grid, electric vehicle load forecasting, machine learning, time series forecasting
Procedia PDF Downloads 7251 Organic Contaminant Degradation Using H₂O₂ Activated Biochar with Enhanced Persistent Free Radicals
Authors: Kalyani Mer
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Hydrogen peroxide (H₂O₂) is one of the most efficient and commonly used oxidants in in-situ chemical oxidation (ISCO) of organic contaminants. In the present study, we investigated the activation of H₂O₂ by heavy metal (nickel and lead metal ions) loaded biochar for phenol degradation in an aqueous solution (concentration = 100 mg/L). It was found that H₂O₂ can be effectively activated by biochar, which produces hydroxyl (•OH) radicals owing to an increase in the formation of persistent free radicals (PFRs) on biochar surface. Ultrasound treated (30s duration) biochar, chemically activated by 30% phosphoric acid and functionalized by diethanolamine (DEA) was used for the adsorption of heavy metal ions from aqueous solutions. It was found that modified biochar could remove almost 60% of nickel in eight hours; however, for lead, the removal efficiency reached up to 95% for the same time duration. The heavy metal loaded biochar was further used for the degradation of phenol in the absence and presence of H₂O₂ (20 mM), within 4 hours of reaction time. The removal efficiency values for phenol in the presence of H₂O₂ were 80.3% and 61.9%, respectively, by modified biochar loaded with nickel and lead metal ions. These results suggested that the biochar loaded with nickel exhibits a better removal capacity towards phenol than the lead loaded biochar when used in H₂O₂ based oxidation systems. Meanwhile, control experiments were set in the absence of any activating biochar, and the removal efficiency was found to be 19.1% when only H₂O₂ was added in the reaction solution. Overall, the proposed approach serves a dual purpose of using biochar for heavy metal ion removal and treatment of organic contaminants by further using the metal loaded biochar for H₂O₂ activation in ISCO processes.Keywords: biochar, ultrasound, heavy metals, in-situ chemical oxidation, chemical activation
Procedia PDF Downloads 10350 Efficient Motion Estimation by Fast Three Step Search Algorithm
Authors: S. M. Kulkarni, D. S. Bormane, S. L. Nalbalwar
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The rapid development in the technology have dramatic impact on the medical health care field. Medical data base obtained with latest machines like CT Machine, MRI scanner requires large amount of memory storage and also it requires large bandwidth for transmission of data in telemedicine applications. Thus, there is need for video compression. As the database of medical images contain number of frames (slices), hence while coding of these images there is need of motion estimation. Motion estimation finds out movement of objects in an image sequence and gets motion vectors which represents estimated motion of object in the frame. In order to reduce temporal redundancy between successive frames of video sequence, motion compensation is preformed. In this paper three step search (TSS) block matching algorithm is implemented on different types of video sequences. It is shown that three step search algorithm produces better quality performance and less computational time compared with exhaustive full search algorithm.Keywords: block matching, exhaustive search motion estimation, three step search, video compression
Procedia PDF Downloads 45249 Modelling and Simulation of Single Mode Optical Fiber Directional Coupler for Medical Application
Authors: Shilpa Kulkarni, Sujata Patrikar
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A single-mode fiber directional coupler is modeled and simulated for its application in medical field. Various fiber devices based on evanescent field absorption, interferometry, couplers, resonators, tip coated fibers, etc, have been developed so far, suitable for medical application. This work focuses on the possibility of sensing by single mode fiber directional coupler. In the preset work, a fiber directional coupler is modeled to detect the changes taking place in the surrounding medium optoelectronically. In this work, waveguiding characteristics of the fiber are studied in depth. The sensor is modeled and simulated by finding photocurrent, sensitivity and detection limit by varying various parameters of the directional coupler. The device is optimized for the best possible output. It is found that the directional coupler shows measurable photocurrents and good sensitivity with coupling length in micrometers. It is thus a miniature device, hence, suitable for medical applications.Keywords: single mode fiber directional coupler, modeling and simulation of fiber directional coupler sensor, biomolecular sensing, medical sensor device
Procedia PDF Downloads 23348 Improved Predictive Models for the IRMA Network Using Nonlinear Optimisation
Authors: Vishwesh Kulkarni, Nikhil Bellarykar
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Cellular complexity stems from the interactions among thousands of different molecular species. Thanks to the emerging fields of systems and synthetic biology, scientists are beginning to unravel these regulatory, signaling, and metabolic interactions and to understand their coordinated action. Reverse engineering of biological networks has has several benefits but a poor quality of data combined with the difficulty in reproducing it limits the applicability of these methods. A few years back, many of the commonly used predictive algorithms were tested on a network constructed in the yeast Saccharomyces cerevisiae (S. cerevisiae) to resolve this issue. The network was a synthetic network of five genes regulating each other for the so-called in vivo reverse-engineering and modeling assessment (IRMA). The network was constructed in S. cereviase since it is a simple and well characterized organism. The synthetic network included a variety of regulatory interactions, thus capturing the behaviour of larger eukaryotic gene networks on a smaller scale. We derive a new set of algorithms by solving a nonlinear optimization problem and show how these algorithms outperform other algorithms on these datasets.Keywords: synthetic gene network, network identification, optimization, nonlinear modeling
Procedia PDF Downloads 12147 Numerical Study of Base Drag Reduction Using Locked Vortex Flow Management Technique for Lower Subsonic Regime
Authors: Kailas S. Jagtap, Karthik Sundarraj, Nirmal Kumar, S. Rajnarasimha, Prakash S. Kulkarni
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The issue of turbulence base streams and the drag related to it have been of important attention for rockets, missiles, and aircraft. Different techniques are used for base drag reduction. This paper presents the numerical study of numerous drag reduction technique. The base drag or afterbody drag of bluff bodies can be reduced easily using locked vortex drag reduction technique. For bluff bodies having a cylindrical shape, the base drag is much larger compared to streamlined bodies. For such bodies using splitter plates, the vortex can be trapped between the base and the plate, which results in smooth flow. Splitter plate with round and curved corner shapes has influence in drag reduction. In this paper, the comparison is done between single splitter plate as different positions and with the bluff body. Base drag for the speed of 30m/s can be reduced about 20% to 30% by using single splitter plate as compared to the bluff body.Keywords: base drag, bluff body, splitter plate, vortex flow, ANSYS, fluent
Procedia PDF Downloads 14846 Modeling User Context Using CEAR Diagram
Authors: Ravindra Dastikop, G. S. Thyagaraju, U. P. Kulkarni
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Even though the number of context aware applications is increasing day by day along with the users, till today there is no generic programming paradigm for context aware applications. This situation could be remedied by design and developing the appropriate context modeling and programming paradigm for context aware applications. In this paper, we are proposing the static context model and metrics for validating the expressiveness and understandability of the model. The proposed context modeling is a way of describing a situation of user using context entities , attributes and relationships .The model which is an extended and hybrid version of ER model, ontology model and Graphical model is specifically meant for expressing and understanding the user situation in context aware environment. The model is useful for understanding context aware problems, preparing documentation and designing programs and databases. The model makes use of context entity attributes relationship (CEAR) diagram for representation of association between the context entities and attributes. We have identified a new set of graphical notations for improving the expressiveness and understandability of context from the end user perspective .Keywords: user context, context entity, context entity attributes, situation, sensors, devices, relationships, actors, expressiveness, understandability
Procedia PDF Downloads 31245 Evaluating Key Attributes of Effective Digital Games in Tertiary Education
Authors: Roopali Kulkarni, Yuliya Khrypko
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A major problem in educational digital game design is that game developers are often focused on maintaining the fun and playability of an educational game, whereas educators are more concerned with the learning aspect of the game rather than its entertaining characteristics. There is a clear need to understand what key aspects of digital learning games make them an effective learning medium in tertiary education. Through a systematic literature review and content analysis, this paper identifies, evaluates, and summarizes twenty-three key attributes of digital games used in tertiary education and presents a summary digital game-based learning (DGBL) model for designing and evaluating an educational digital game of any genre that promotes effective learning in tertiary education. The proposed solution overcomes limitations of previously designed models for digital game evaluation, such as a small number of game attributes considered or applicability to a specific genre of digital games. The proposed DGBL model can be used to assist game designers and educators with creating effective and engaging educational digital games for the tertiary education curriculum.Keywords: DGBL model, digital games, educational games, game-based learning, tertiary education
Procedia PDF Downloads 23444 Alumni Experiences of How Their Undergraduate Medical Education Instilled and Fostered a Commitment to Community-Based Work in Later Life: A Sequential Exploratory Mixed-Methods Study
Authors: Harini Aiyer, Kalyani Premkumar
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Health professionals are the key players who can help achieve the goals of population health equity. Social accountability (SA) of health professionals emphasizes their role in addressing issues of equity in the population they serve. Therefore, health professional education must focus on instilling SA in health professionals. There is limited literature offering a longitudinal perspective of how students sustain the practice of SA in later life. This project aims to identify the drivers of social accountability among physicians. This study employed an exploratory mixed methods design (QUAL-> Quant) to explore alumni perceptions and experiences. The qualitative data, collected via 20 in-depth, semi-structured interviews, provided an understanding of the perceptions of the alumni regarding the influence of their undergraduate learning environment on their SA. This was followed by a quantitative portion -a questionnaire designed from the themes identified from the qualitative data. Emerging themes from the study highlighted community-centered education and a focus on social and preventative medicine in both curricular and non-curricular facilitators of SA among physicians. Curricular components included opportunities to engage with the community, such as roadside clinics, community-orientation programs, and postings at a secondary hospital. Other facilitators that emerged were the faculty leading by example, a subsidized fee structure, and a system that prepared students for practice in rural and remote areas. The study offers a fresh perspective and dimension on how SA is addressed by medical schools. The findings may be adapted by medical schools to understand how their own SA initiatives have been sustained among physicians over the long run.Keywords: community-based work, global health, health education, medical education, providing health in remote areas, social accountability
Procedia PDF Downloads 5343 Investigations on Utilization of Chrome Sludge, Chemical Industry Waste, in Cement Manufacturing and Its Effect on Clinker Mineralogy
Authors: Suresh Vanguri, Suresh Palla, Prasad G., Ramaswamy V., Kalyani K. V., Chaturvedi S. K., Mohapatra B. N., Sunder Rao TBVN
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The utilization of industrial waste materials and by-products in the cement industry helps in the conservation of natural resources besides avoiding the problems arising due to waste dumping. The use of non-carbonated materials as raw mix components in clinker manufacturing is identified as one of the key areas to reduce Green House Gas (GHG) emissions. Chrome sludge is a waste material generated from the manufacturing process of sodium dichromate. This paper aims to present studies on the use of chrome sludge in clinker manufacturing, its impact on the development of clinker mineral phases and on the cement properties. Chrome sludge was found to contain substantial amounts of CaO, Fe2O3 and Al2O3 and therefore was used to replace some conventional sources of alumina and iron in the raw mix. Different mixes were prepared by varying the chrome sludge content from 0 to 5 % and the mixes were evaluated for burnability. Laboratory prepared clinker samples were evaluated for qualitative and quantitative mineralogy using X-ray Diffraction Studies (XRD). Optical microscopy was employed to study the distribution of clinker phases, their granulometry and mineralogy. Since chrome sludge also contains considerable amounts of chromium, studies were conducted on the leachability of heavy elements in the chrome sludge as well as in the resultant cement samples. Estimation of heavy elements, including chromium was carried out using ICP-OES. Further, the state of chromium valence, Cr (III) & Cr (VI), was studied using conventional chemical analysis methods coupled with UV-VIS spectroscopy. Assimilation of chromium in the clinker phases was investigated using SEM-EDXA studies. Bulk cement was prepared from the clinker to study the effect of chromium sludge on the cement properties such as setting time, soundness, strength development against the control cement. Studies indicated that chrome sludge can be successfully utilized and its content needs to be optimized based on raw material characteristics.Keywords: chrome sludge, leaching, mineralogy, non-carbonate materials
Procedia PDF Downloads 17942 Investigations on Enhancement of Fly Ash in Cement Manufacturing through Optimization of Clinker Quality and Fly Ash Fineness
Authors: Suresh Vanguri, Suresh Palla, K. V. Kalyani, S. K. Chaturvedi, B. N. Mohapatra
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Enhancing the fly ash utilization in the manufacture of cement is identified as one of the key areas to mitigate the Green House Gas emissions from the cement industry. Though increasing the fly ash content in cement has economic and environmental benefits, it results in a decrease in the compressive strength values, particularly at early ages. Quality of clinker and fly ash were identified as predominant factors that govern the extent of absorption of fly ash in the manufacturing of cement. This paper presents systematic investigations on the effect of clinker and fly ash quality on the properties of resultant cement. Since mechanical activation alters the physicochemical properties such as particle size distribution, surface area, phase morphology, understanding the variation of these properties with activation is required for its applications. The effect of mechanical activation on fly ash surface area, specific gravity, flow properties, lime reactivity, comparative compressive strength (CCS), reactive silica and mineralogical properties were also studied. The fineness of fly ash was determined by Blaine’s method, specific gravity, lime reactivity, CCS were determined as per the method IS 1727-1967. The phase composition of fly ash was studied using the X-ray Diffraction technique. The changes in the microstructure and morphology with activation were examined using the scanning electron microscope. The studies presented in this paper also include evaluation of Portland Pozzolana Cement (PPC), prepared using high volume fly ash. Studies are being carried out using clinker from cement plants located in different regions/clusters in India. Blends of PPC containing higher contents of activated fly ash have been prepared and investigated for their chemical and physical properties, as per Indian Standard procedures. Changes in the microstructure of fly ash with activation and mechanical properties of resultant cement containing high volumes of fly ash indicated the significance of optimization of the quality of clinker and fly ash fineness for better techno-economical benefits.Keywords: flow properties, fly ash enhancement, lime reactivity, microstructure, mineralogy
Procedia PDF Downloads 42441 Ultrasound Markers in Evaluation of Hernias
Authors: Aniruddha Kulkarni
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In very few cases of external hernias we require imaging modalities as on most occasions clinical examination tests are good enough. Ultrasound will help in chronic abdominal or groin pain, equivocal clinical results & complicated hernias. Ultrasound is useful in assessment of cause of raised intrabdominal pressure. In certain cases will comment about etiology, complications and chronicicty of lesion. Screening of rest of abdominal organs too is important advantage being real time modality. Cost effectiveness, no radiation allows modality be used repeatedly in indicated cases. Sonography is better accepted by patients too as it is cost effective. Best advanced tissue harmonic equipment and increasing expertise making it popular. Ultrasound can define surgical anatomy, rent size, contents, etiological /recurrence factors in great detail and with authority hence accidental findings in a planned surgical procedure can be easily avoided. Clinical dynamic valselva and reducibility test can better documented by real time ultrasound study. In case of recurrence, Sonography will help in assessing the hernia details better as being dynamic real time investigation. Ultrasound signs in case of internal hernias are well comparable with CT findings.Keywords: laparoscopic repair, Hernia, CT findings, chronic pain
Procedia PDF Downloads 46640 Emotion Classification Using Recurrent Neural Network and Scalable Pattern Mining
Authors: Jaishree Ranganathan, MuthuPriya Shanmugakani Velsamy, Shamika Kulkarni, Angelina Tzacheva
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Emotions play an important role in everyday life. An-alyzing these emotions or feelings from social media platforms like Twitter, Facebook, blogs, and forums based on user comments and reviews plays an important role in various factors. Some of them include brand monitoring, marketing strategies, reputation, and competitor analysis. The opinions or sentiments mined from such data helps understand the current state of the user. It does not directly provide intuitive insights on what actions to be taken to benefit the end user or business. Actionable Pattern Mining method provides suggestions or actionable recommendations on what changes or actions need to be taken in order to benefit the end user. In this paper, we propose automatic classification of emotions in Twitter data using Recurrent Neural Network - Gated Recurrent Unit. We achieve training accuracy of 87.58% and validation accuracy of 86.16%. Also, we extract action rules with respect to the user emotion that helps to provide actionable suggestion.Keywords: emotion mining, twitter, recurrent neural network, gated recurrent unit, actionable pattern mining
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