Search results for: real time kernel preemption

Authors: Dominic Wentworth-Linton, Shian Gao

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This project was aimed at investigating the effect of velocity stacks on the intakes of internal combustion engines for motorsport applications. The intake systems in motorsport are predominantly fuel injection with a plate mounted for the stacks. Using Computational Fluid Dynamics software, the relationship between the stack length and power and torque delivery across the engine’s rev range was investigated and the results were used to choose the best option for its intended motorsport discipline. The test results are expected to vary with engine geometry and its natural manufacturer characteristics. The test was also relevant in bridging between computational data and real simulation as the results show flow, pressure and velocity readings but the behaviour of the engine is inferred from the nature of each test. The results of the data analysis were tested in a real-life simulation on a dynamometer to prove the theory of stack length on power and torque delivery, which helps determine the most suitable stack for the Vauxhall engine for rallying in the Caribbean.

Keywords: CFD simulation, Internal combustion engine, Intake system, Dynamometer test

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Authors: Irene Capecchi, Tommaso Borghini, Iacopo Bernetti

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One of the most common pieces of equipment still used today for pruning, felling, and processing trees is the chainsaw in forestry. However, chainsaw use highlights dangers and one of the highest rates of accidents in both professional and non-professional work. Felling is proportionally the most dangerous phase, both in severity and frequency, because of the risk of being hit by the plant the operator wants to cut down. To avoid this, a correct sequence of chainsaw cuts must be taught concerning the different conditions of the tree. Virtual reality (VR) makes it possible to virtually simulate chainsaw use without danger of injury. The limitations of the existing applications are as follow. The existing platforms are not symmetrical collaborative because the trainee is only in virtual reality, and the trainer can only see the virtual environment on a laptop or PC, and this results in an inefficient teacher-learner relationship. Therefore, most applications only involve the use of a virtual chainsaw, and the trainee thus cannot feel the real weight and inertia of a real chainsaw. Finally, existing applications simulate only a few cases of tree felling. The objectives of this research were to implement and test a symmetrical collaborative training application based on VR and mixed reality (MR) with the overlap between real and virtual chainsaws in MR. The research and training platform was developed for the Meta quest 2 head-mounted display. The research and training platform application is based on the Unity 3D engine, and Present Platform Interaction SDK (PPI-SDK) developed by Meta. PPI-SDK avoids the use of controllers and enables hand tracking and MR. With the combination of these two technologies, it was possible to overlay a virtual chainsaw with a real chainsaw in MR and synchronize their movements in VR. This ensures that the user feels the weight of the actual chainsaw, tightens the muscles, and performs the appropriate movements during the test allowing the user to learn the correct body posture. The chainsaw works only if the right sequence of cuts is made to felling the tree. Contact detection is done by Unity's physics system, which allows the interaction of objects that simulate real-world behavior. Each cut of the chainsaw is defined by a so-called collider, and the felling of the tree can only occur if the colliders are activated in the right order simulating a safe technique felling. In this way, the user can learn how to use the chainsaw safely. The system is also multiplayer, so the student and the instructor can experience VR together in a symmetrical and collaborative way. The platform simulates the following tree-felling situations with safe techniques: cutting the tree tilted forward, cutting the medium-sized tree tilted backward, cutting the large tree tilted backward, sectioning the trunk on the ground, and cutting branches. The application is being evaluated on a sample of university students through a special questionnaire. The results are expected to test both the increase in learning compared to a theoretical lecture and the immersive and telepresence of the platform.

Keywords: chainsaw, collaborative symmetric virtual reality, mixed reality, operator training

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Authors: Md. Ahsan Ayub, Kazi A. Kalpoma, Humaira Tasnim Proma, Syed Mehrab Kabir, Rakib Ibna Hamid Chowdhury

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Constraint Satisfaction Problem (CSP) is observed in various applications, i.e., scheduling problems, timetabling problems, assignment problems, etc. Researchers adopt a CSP technique to tackle a certain problem; however, each technique follows different approaches and ways to solve a problem network. In our exhaustive study, it has been possible to visualize the processes of essential CSP algorithms from a very concrete constraint satisfaction example, NQueens Problem, in order to possess a deep understanding about how a particular constraint satisfaction problem will be dealt with by our studied and implemented techniques. Besides, benchmark results - time vs. value of N in N-Queens - have been generated from our implemented approaches, which help understand at what factor each algorithm produces solutions; especially, in N-Queens puzzle. Thus, extended decisions can be made to instantiate a real life problem within CSP’s framework.

Keywords: arc consistency (AC), backjumping algorithm (BJ), backtracking algorithm (BT), constraint satisfaction problem (CSP), forward checking (FC), least constrained values (LCV), maintaining arc consistency (MAC), minimum remaining values (MRV), N-Queens problem

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Authors: Verónica Díaz Quezada

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The importance given to the development of the problem solving skill and the requirement to solve problems framed in mathematical or real life contexts, in practice, they are not evidence in relation to the teaching of proportional variations. This qualitative and descriptive study aims to (1) to improve problem solving ability of high school students in Chile, (ii) to elaborate and describe a didactic intervention strategy based on learning situations in proportional variations, focused on solving types of routine problems of various contexts and non-routine problems. For this purpose, participant observation was conducted, test of mathematics problems and an opinion questionnaire to thirty-six high school students. Through the results, the highest academic performance is evidenced in the routine problems of purely mathematical context, realistic, fantasy context, and non-routine problems, except in the routine problems of real context and compound proportionality problems. The results highlight the need to consider in the curriculum different types of problems in the teaching of mathematics that relate the discipline to everyday life situations

Keywords: algebra, high school, proportion variations, nonroutine problem solving, routine problem solving

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Authors: Misagh Faezipour

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This paper explores the effects of screen time on children from a systems engineering perspective. We reviewed literature from several related works on the effects of screen time on children to explore all factors and interrelationships that would impact children that are subjected to using long screen times. Factors such as kids' age, parent attitudes, parent screen time influence, amount of time kids spend with technology, psychosocial and physical health outcomes, reduced mental imagery, problem-solving and adaptive thinking skills, obesity, unhealthy diet, depressive symptoms, health problems, disruption in sleep behavior, decrease in physical activities, problematic relationship with mothers, language, social, emotional delays, are examples of some factors that could be either a cause or effect of screen time. A systems engineering perspective is used to explore all the factors and factor relationships that were discovered through literature. A causal model is used to illustrate a graphical representation of these factors and their relationships. Through the causal model, the factors with the highest impacts can be realized. Future work would be to develop a system dynamics model to view the dynamic behavior of the relationships and observe the impact of changes in different factors in the model. The different changes on the input of the model, such as a healthier diet or obesity rate, would depict the effect of the screen time in the model and portray the effect on the children’s health and other factors that are important, which also works as a decision support tool.

Keywords: children, causal model, screen time, systems engineering, system dynamics

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Authors: Pavan K. Rallabandi, Kailash C. Patidar

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In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

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Authors: Lauren G. Coggins

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Catheter-associated urinary tract infections (CAUTI) and central line-associated bloodstream infections (CLABSI) are among the most common healthcare-associated infections (HAI), contributing to prolonged lengths of stay, greater costs of patient care, and increased patient mortality. Evidence-based preventative care bundles exist to establish consistent, safe patient-care practices throughout an entire organization, helping to ensure the collective application of care strategies that aim to improve patient outcomes and minimize complications. The cardiac intensive care unit at a nationally ranked teaching and research hospital in the United States exceeded its annual CAUTI and CLABSI targets in the fiscal year 2019, prompting examination into the unit’s infection prevention efforts that included preventative care bundles for both HAIs. Adherence to the CAUTI and CLABSI preventative care bundles was evaluated through frequent audits conducted over three months, using standards and resources from The Joint Commission, a globally recognized leader in quality improvement in healthcare and patient care safety. The bundle elements with the lowest scores were identified as the most commonly missed elements. Three elements from both bundles, six elements in total, served as key content areas for the educational interventions targeted to bedside nurses. The CAUTI elements included appropriate urinary catheter order, appropriate continuation criteria, and urinary catheter care. The CLABSI elements included primary tubing compliance, needleless connector compliance, and dressing change compliance. An integrated, multi-platform education campaign featured content on each CAUTI and CLABSI preventative care bundle in its entirety, with additional reinforcement focused on the lowest scoring elements. One-on-one educational materials included an informational pamphlet, badge buddy, a presentation to reinforce nursing care standards, and real-time application through case studies and electronic health record demonstrations. A digital hub was developed on the hospital’s Intranet for quick access to unit resources, and a bulletin board helped track the number of days since the last CAUTI and CLABSI incident. Audits continued to be conducted throughout the education campaign, and staff were given real-time feedback to address any gaps in adherence. Nearly every nurse in the cardiac intensive care unit received all educational materials, and adherence to all six key bundle elements increased after the implementation of educational interventions. Recommendations from this implementation include providing consistent, comprehensive education across multiple teaching tools and regular audits to track adherence. The multi-platform education campaign brought focus to the evidence-based CAUTI and CLABSI bundles, which in turn will help to reduce CAUTI and CLABSI rates in clinical practice.

Keywords: education, healthcare-associated infections, infection, nursing, prevention

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Authors: Norm Josephy, Lucy Kimball, Victoria Steblovskaya

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Hedging of a portfolio of European options under proportional transaction costs is considered. Our discrete time financial market model extends the binomial market model with transaction costs to the case where the underlying stock price ratios are distributed over a bounded interval rather than over a two-point set. An optimal hedging strategy is chosen from a set of admissible non-self-financing hedging strategies. Our approach to optimal hedging of a portfolio of options is based on theoretical foundation that includes determination of a no-arbitrage option price interval as well as on properties of the non-self-financing strategies and their residuals. A computational algorithm for optimizing an investor relevant criterion over the set of admissible non-self-financing hedging strategies is developed. Applicability of our approach is demonstrated using both simulated data and real market data.

Keywords: extended binomial model, non-self-financing hedging, optimization, proportional transaction costs

Procedia PDF Downloads 240

Authors: Shoeb A. Adeel, Shashant Anand, Vivek Paul, Dinesh, Suraj, Roshan

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The paper presents a study of micro air vehicles (MAVs) with wingspans of 20 Cm with two different airfoil configurations. MAVs have vast potential applications in both military and civilian areas. These MAVs are fully autonomous and supply real-time data. The paper focuses on two different designs of the MAVs one being N22 airfoil and the other a flat plate with similar dimension. As designed, the MAV would fly in a low Reynolds-number regime at airspeeds of 15 & 20 m/sec. Propulsion would be provided by an electric motor with an advanced lithium. Because of the close coupling between vehicle elements, system integration would be a significant challenge, requiring tight packaging and multifunction components to meet mass limitations and Centre of Gravity (C.G) balancing. These MAVs are feasible and within a couple of years of technology development in key areas including sensors, propulsion, Aerodynamics, and packaging these would be easily available to the users at affordable prices. The paper finally compares the flight performance of the two configurations.

Keywords: airfoil, CFD, MAV, flight performance, endurance, climb, lift, drag

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Authors: Dejenie Birile Gemeda, Wilhelm Stork

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The power system is one of the most important systems in modern society. The existing power system is approaching the critical operating limits as views of several power system operators. With the increase of load demand, high capacity and long transmission networks are widely used to meet the requirement. With the integration of renewable energies such as wind and solar, the uncertainty, intermittence bring bigger challenges to the operation of power systems. These dynamic uncertainties in the power system lead to power disturbances. The disturbances in a heavily stressed power system cause distance relays to mal-operation or false alarms during post fault power oscillations. This unintended operation of these relays may propagate and trigger cascaded trappings leading to total power system blackout. This is due to relays inability to take an appropriate tripping decision based on ensuing power swing. According to the N-1 criterion, electric power systems are generally designed to withstand a single failure without causing the violation of any operating limit. As a result, some overloaded components such as overhead transmission lines can still work for several hours under overload conditions. However, when a large power swing happens in the power system, the settings of the distance relay of zone 3 may trip the transmission line with a short time delay, and they will be acting so quickly that the system operator has no time to respond and stop the cascading. Misfiring of relays in absence of fault due to power swing may have a significant loss in economic performance, thus a loss in revenue for power companies. This research paper proposes a method to distinguish stable power swing from unstable using dynamic line rating (DLR) in response to power swing or disturbances. As opposed to static line rating (SLR), dynamic line rating support effective mitigation actions against propagating cascading outages in a power grid. Effective utilization of existing transmission lines capacity using machine learning DLR predictions will improve the operating point of distance relay protection, thus reducing unintended power outages due to power swing.

Keywords: blackout, cascading outages, dynamic line rating, power swing, overhead transmission lines

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Authors: Preeti Aghalayam, Jay Shah

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Underground coal gasification (UCG) is the in-situ gasification of unmineable coals to produce syngas. In UCG, gasifying agents are injected into the coal seam, and a reactive cavity is formed due to coal consumption. The cavity formed is typically hemispherical, and this report consists of the MATLAB model of the UCG cavity to predict the composition of the output gases. There are seven radial and two time-variant ODEs. A MATLAB solver (ode15s) is used to solve the radial ODEs from the above equations. Two for-loops are implemented in the model, i.e., one for time variations and another for radial variation. In the time loop, the radial odes are solved using the MATLAB solver. The radial loop is nested inside the time loop, and the density odes are numerically solved using the Euler method. The model is validated by comparing it with the literature results of laboratory-scale experiments. The model predicts the radial and time variation of the product gases inside the cavity.

Keywords: gasification agent, MATLAB model, syngas, underground coal gasification (UCG)

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Authors: Tyler Gill, Sophia Daniels

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The paper examines how accessing the spatial-temporal constrains of data will help inform policymakers and law enforcement officials. The authors utilize Chicago crime data from 2006-2016 to demonstrate how the Emerging Hot Spot Tool is an ideal hot spot clustering approach to analyze crime data. Traditional approaches include density maps or creating a spatial weights matrix to include the spatial-temporal constrains. This new approach utilizes a space-time implementation of the Getis-Ord Gi* statistic to visualize the data more quickly to make better decisions. The research will help complement socio-cultural research to find key patterns to help frame future policies and evaluate the implementation of prior strategies. Through this analysis, homicide trends and patterns are found more effectively and recommendations for use by non-traditional users of GIS are offered for real life implementation.

Keywords: crime mapping, emerging hot spot analysis, Getis-Ord Gi*, spatial-temporal analysis

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Authors: Zainab Almukhtar, Adel Merabet

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In this paper, a method for maximum power point tracking of a photovoltaic energy conversion system is presented. This method is based on using the difference between the power from the solar panel and an estimated power value to control the DC-DC converter of the photovoltaic system. The difference is continuously compared with a preset error permitted value. If the power difference is more than the error, the estimated power is multiplied by a factor and the operation is repeated until the difference is less or equal to the threshold error. The difference in power will be used to trigger a DC-DC boost converter in order to raise the voltage to where the maximum power point is achieved. The proposed method was experimentally verified through a PV energy conversion system driven by the OPAL-RT real time controller. The method was tested on varying radiation conditions and load requirements, and the Photovoltaic Panel was operated at its maximum power in different conditions of irradiation.

Keywords: control system, error, solar panel, MPPT tracking

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Authors: Virgilio Angelo Gelera Gener

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This study investigates the role of short-term accommodations on the place brand and real estate development of urban areas. It aims to know the perceptions of the general public, real estate developers, as well as city and barangay-level local government units (LGUs) on how these lodgings affect the place brand and land value of a community. It likewise attempts to identify the personal and institutional variables having a great influence on said perceptions in order to provide a better understanding of these establishments and their relevance within urban localities. Using certain sources, Malate, Manila was identified to be the ideal study area of the thesis. This prompted the employment of mixed methods research as the study’s fundamental data gathering and analytical tool. Here, a survey with 350 locals was done, asking them questions that would answer the aforementioned queries. Thereafter, a Pearson Chi-square Test and Multinomial Logistic Regression (MLR) were utilized to determine the variables affecting their perceptions. There were also Focus Group Discussions (FGDs) with the three (3) most populated Malate barangays, as well as Key Informant Interviews (KIIs) with selected city officials and fifteen (15) real estate company representatives. With that, survey results showed that although a 1992 Department of Tourism (DOT) Circular regards short-term accommodations as lodgings mainly for travelers, most people actually use it for their private/intimate moments. Because of this, the survey further revealed that short-term accommodations exhibit a negative place brand among the respondents though they also believe that it’s still one of society’s most important economic players. Statistics from the Pearson Chi-square Test, on the other hand, indicate that there are fourteen (14) out of seventeen (17) variables exhibiting great influence on respondents’ perceptions. Whereas MLR findings show that being born in Malate and being part of a family household was the most significant regardless of socio-economic level and monthly household income. For the city officials, it was revealed that said lodgings are actually the second-highest earners in the City’s lodging industry. It was further stated that their zoning ordinance treats short-term accommodations just like any other lodging enterprise. So it’s perfectly legal for these establishments to situate themselves near residential areas and/or institutional structures. A sit down with barangays, on the other hand, recognized the economic benefits of short-term accommodations but likewise admitted that it contributes a negative place brand to the community. Lastly, real estate developers are amenable to having their projects built near short-term accommodations, for they do not have any bad views against it. They explained that their projects sites have always been motivated by suitability, liability, and marketability factors only. Overall, these findings merit a recalibration of the zoning ordinance and DOT Circular, as well as the imposition of regulations on their sexually suggestive roadside advertisements. Then, once relevant measures are refined for proper implementation, it can also pave the way for spatial interventions (like visual buffer corridors) to better address the needs of the locals, private groups, and government.

Keywords: estate planning, place brand, real estate development, short-term accommodations

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Authors: Hassam Muazzam

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This paper devises an autonomous self-driven vehicle that is capable of taking a disabled person to his/her desired location using three different power sources (gasoline, solar, electric) without any control from the user, avoiding the obstacles in the way. The GPS co-ordinates of the desired location are sent to the main processing board via a GSM module. After the GPS co-ordinates are sent, the path to be followed by the vehicle is devised by Pythagoras theorem. The distance and angle between the present location and the desired location is calculated and then the vehicle starts moving in the desired direction. Meanwhile real-time data from ultrasonic sensors is fed to the board for obstacle avoidance mechanism. Ultrasonic sensors are used to quantify the distance of the vehicle from the object. The distance and position of the object is then used to make decisions regarding the direction of vehicle in order to avoid the obstacles using artificial neural network which is implemented using ATmega1280. Also the vehicle provides the feedback location at remote location.

Keywords: autonomous self-driven vehicle, obstacle avoidance, desired location, pythagoras theorem, neural network, remote location

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Authors: Ana Sofia Saldanha

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The globalization is changing the translation world day after day, year after year. The need to know more about new technologies, clients, companies and social networks is becoming more and more demanding and competitive. The recently graduated translators usually do not know where to go, what to do or even who to contact to start their careers in translation. It is well known that there are innumerous webinars, books, blogs, webpages and even Facebook pages indicating what to do, what not to do, rates, how your CV should look like, etc. but are these pieces of advice of real translators? Translators, who work daily with clients, who understand their demands, requests, questions? As far as today`s trends, the answer is NO. Most of these pieces of advice are just theoretical and far away from the real translation world. Therefore, mentoring is becoming a very important tool to help and guide new translators starting their career. An effective and well-oriented mentoring is a powerful way to orient these translators on how to create their CVs, where to send CVs, how to approach clients, how to answer emails and how to negotiate rates in an efficient way. Mentoring is crucial when properly delivered by professional and experienced translators, to help developing careers. The advice and orientation sessions are almost a 'weapon' to destroy the barriers created by opinions, by influences or even by universities. This new trend is the future path of new translators and is the future of the translation industry and professionals, however minds and spirits need to be opened and engaged in this new way of developing skills.

Keywords: mentoring, translation, translators, orientation, professional path

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Authors: Cinzia Carrodano, Dimitri Konstantas

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Risk is part of our lives. In today’s society risk is connected to our safety and safety has become a major priority in our life. Each person lives his/her life based on the evaluation of the risk he/she is ready to accept and sustain, and the level of safety he/she wishes to reach, based on highly personal criteria. The assessment of risk a person takes in a complex environment and the impact of actions of other people’actions and events on our perception of risk are alements to be considered. The concept of Holistic Risk Assessment (HRA) aims in developing a methodology and a model that will allow us to take into account elements outside the direct influence of the individual, and provide a personalized risk assessment. The concept is based on the fact that in the near future, we will be able to gather and process extremely large amounts of data about an individual and his/her environment in real time. The interaction and correlation of these data is the key element of the holistic risk assessment. In this paper, we present the HRA concept and describe the most important elements and considerations.

Keywords: continuous data, dynamic risk, holistic risk assessment, risk concept

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Authors: Abdur Raheem, Ado Yakub

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Urban violence in the form of ethnic and religious conflicts have been on the increase in many African cities in the recent years of which most of them are the result of intense and bitter competition for political power, the control of limited economic, social and environmental resources. In Nigeria, the emergence of the Boko Haram insurgency in most parts of the north eastern parts have ignited violence, bloodshed, refuge exodus and internal migration. Not only do the persistent attacks of the sect create widespread insecurity and fear, it has also stifled normal processes of trade and investments most especially real property investment which is acclaimed to accelerate the economic cycle, thus the need to evolve strategies for an improved property market in such areas. This paper, therefore, examines the impact of these social crisis on effective and efficient utilization of real properties as a resource towards the development of the economy, using a descriptive analysis approach where particular emphasis was based on trends in residential housing values; volume of estimated property transactions and real estate investment decisions by affected individuals. Findings indicate that social crisis in the affected areas have been a clog on the wheels of property development and investment as properties worth hundreds of millions have been destroyed thereby having great impact on property values. Based on these findings, recommendations were made to include the need to strategically continue investing in property during such times, the need for Nigerian government to establish an active conflict monitoring and management unit for prompt response, encourage community and neighbourhood policing to ameliorate security challenges in Nigeria.

Keywords: social crisis, property market, economy, resources, north-eastern Nigeria

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Authors: Praveen Adusumilli, Meher Lakshmi Konatam, Sadashivudu Gundeti, Stalin Bala

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The invention of trastuzumab has changed the treatment of breast cancer and lives of many patients all over the world. Despite many patients getting benefitted from the drug, it is out of reach for most of the patients. There is very limited real world data regarding the epidemiology and clinical outcome of Her2neu positive breast cancer patients. Materials and Methods: This is a retrospective analysis of breast cancer patients presenting to a tertiary care cancer centre in Southern India from 2007 to2013. All early and locally advanced breast cancer patients, who were Her2neu 3+ on IHC are included in the study and evaluated in terms of epidemiology, 3-year disease free survival (DFS)and 5-year overall survival(OS). Chemotherapy regimens used were-FAC 6 cycles or AC 4 cycles followed by 12 cycles of weekly paclitaxel . Trastuzumab was given after 6 cycles of FAC or weekly with paclitaxel followed by 3weekly maintenance until 1 year. Results: Over the period of this study there were 885 newly diagnosed cases of carcinoma breast, of which 242 (27%) were Her2neu positive, 360(40%) were hormone receptor positive, and 212(24%) were triple negative. A total of 71(8%) were Her2neu equivocal of which only 10 patients got FISH test done. Of the 212 newly diagnosed patients, only 74 (29%) opted to have standard of care therapy with trastuzumab at our centre, out of which 52(24%), 8(3%), received under insurance, paying basis respectively. 14(9%) patients received the care as part of clinical trial program (ALTTO trial). 7 (9.72%) patients developed decrease of ejection fraction by greater than 10%, requiring stoppage of trastuzumab out of which 5 were restarted in 2 months. Patients receiving trastuzumab along with chemotherapy had longer 3year DFS 92% vs. 60% (p value<0.0001) when compared to chemotherapy alone. 5 year OS was 87% vs 44% (p-value <0.0001) compared to chemotherapy alone. Conclusion: Trastuzumab with chemotherapy improves the DFS and OS in Her2neu positive patients. The biggest constraint is the cost of the treatment and absence of universal health security net to treat all patients with this diagnosis.

Keywords: breast cancer, Her 2 neu positive, real world data, Trastuzumab

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: F. Fatoye, C. E. Mbada, T. Gebrye, A. O. Ogunsola, C. Fatoye, O. Oyewole

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Musculoskeletal disorders (MSDs) are a major cause of pain and disability. It is likely to become a greater economic and public health burden that is unnecessary. Thus, reliable prevalence figures are important for both clinicians and policy-makers to plan health care needs for those affected with the disease. This study estimated hospital based real-world prevalence of MSDs in Nigeria. A review of medical charts for adult patients attending Physiotherapy Outpatient Clinic at the Obafemi Awolowo University Teaching Hospitals Complex, Osun State, Nigeria between 2009 and 2018 was carried out to identify common MSDs including low back pain (LBP), cervical spondylosis (CSD), post immobilization stiffness (PIS), sprain, osteoarthritis (OA), and other conditions. Occupational class of the patients was determined using the International Labour Classification (ILO). Data were analysed using descriptive statistics of frequency and percentages. Overall, medical charts of 3,340 patients were reviewed within the span of ten years (2009 to 2018). Majority of the patients (62.8%) were in the middle class, and the remaining were in low class (25.1%) and high class (10.5%) category. An overall prevalence of 47.35% of MSD was found within the span of ten years. Of this, the prevalence of LBP, CSD, PIS, sprain, OA, and other conditions was 21.6%, 10%, 18.9%, 2%, 6.3%, and 41.3%, respectively. The highest (14.2%) and lowest (10.5%) prevalence of MSDs was recorded in the year of 2012 and 2018, respectively. The prevalence of MSDs is considerably high among Nigerian patients attending outpatient a physiotherapy clinic. The high prevalence of MSDs underscores the need for clinicians and decision makers to put in place appropriate strategies to reduce the prevalence of these conditions. In addition, they should plan and evaluate healthcare services to improve the health outcomes of patients with MSDs. Further studies are required to determine the economic burden of the condition and examine the clinical and cost-effectiveness of physiotherapy interventions for patients with MSDs.

Keywords: musculoskeletal disorders, Nigeria, prevalence, real world

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Authors: Nguyen Huy Hoang, Do Thanh Quan, Tran Vu Kien

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The use of the active radar to measure the coordinates of ultra-light drones is frequently difficult due to long-distance, absolutely small radar cross-section (RCS) and obstacles. Since ultra-light drones are usually controlled by the Time Difference of Arrival (RF), the paper proposed a method to measure the coordinates of ultra-light drones in the space based on the arrival time of the signal at receiving antennas and the time difference of arrival (TDOA). The experimental results demonstrate that the proposed method is really potential and highly accurate.

Keywords: ultra-light drone, TDOA, radar cross-section (RCS), RF

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Authors: Ashiff Khan, A. Seetharaman, Abhijit Dasgupta

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The new era of big data (BD) is influencing chemical industries tremendously, providing several opportunities to reshape the way they operate and help them shift towards intelligent manufacturing. Given the availability of free software and the large amount of real-time data generated and stored in process plants, chemical industries are still in the early stages of big data adoption. The industry is just starting to realize the importance of the large amount of data it owns to make the right decisions and support its strategies. This article explores the importance of professional competencies and data science that influence BD in chemical industries to help it move towards intelligent manufacturing fast and reliable. This article utilizes a literature review and identifies potential applications in the chemical industry to move from conventional methods to a data-driven approach. The scope of this document is limited to the adoption of BD in chemical industries and the variables identified in this article. To achieve this objective, government, academia, and industry must work together to overcome all present and future challenges.

Keywords: chemical engineering, big data analytics, industrial revolution, professional competence, data science

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Authors: M. Berrehail, F. Benamira

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We study the quantum motion of a particle in the presence of a time- dependent linear potential using an operator invariant that is quadratic in p and linear in q within the framework of the Lewis-Riesenfeld invariant, The special invariant operator proposed in this work is demonstrated to be an Hermitian operator which has an Airy wave packet as its Eigenfunction

Keywords: airy wave packet, ivariant, time-dependent linear potential, unitary transformation

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Authors: Kyoung-Jae Kim

Abstract:

Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

Procedia PDF Downloads 275

Authors: Revaz Chigladze

Abstract:

The purpose of the research is to investigate the surfaces of Jupiter's Galilean moons, namely which moon has the most uniform surface among them, what is the difference between the front (in the direction of motion) and the back sides of each moon's surface, as well as the temporal variations of the moons. Since 1981, the E. Kharadze National Astrophysical Observatory of Georgia has been conducting polarimetric (P) and photometric (M) observations of Jupiter's Galilean moons with telescopes of different diameters (40 cm and 125 cm) and the polarimeter ASEP-78 in combination with them and the latest generation photometer with a polarimeter and modern light receiver SBIG. As it turns out from the analysis of the observed material, the parameters P and M depend on α-the phase angle of the moon (satellite), L- the orbital latitude of the moon (satellite), λ- the wavelength, and t - the period of observation, i.e., P = P (α, L, λ , t), and similarly M = M (α, L, λ. , t). Based on the analysis of the observed material, the following was studied: Jupiter's Galilean moons: dependence of the magnitude and phase angle of the degree of linear polarization for different wavelengths; Dependence of the degree of polarization and the orbital longitude; dependence between the magnitude of the degree of polarization and the wavelength; time dependence of the degree of polarization and the dependence between photometric and polarimetric characteristics (including establishing correlation). From the analysis of the obtained results, we get: The magnitude of the degree of polarization of Jupiter's Galilean moons near the opposition significantly differs from zero. Europa appears to have the most uniform surface, and Callisto the least uniform. Time variations are most characteristic of Io, which confirms the presence of volcanic activity on its surface. Based on the observed material, it can be seen that the intensity of light reflected from the front hemisphere of the first three moons: Io, Europa, and Ganymede, is less than the intensity of light reflected from the rear hemisphere, and in the case of the Callisto it is the opposite. The paper provides a convincing (natural, real) explanation of this fact.

Keywords: Galilean moons, polarization, degree of polarization, photometry, front and rear hemispheres

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Authors: Junkyeong Kim, Seunghee Park, Ju-Won Kim, Myung-Sug Cho

Abstract:

Recently, demands for the construction of Nuclear Power Plants (NPP) using high strength concrete (HSC) has been increased. However, HSC might be susceptible to brittle fracture if the curing process is inadequate. To prevent unexpected collapse during and after the construction of HSC structures, it is essential to confirm the strength development of HSC during the curing process. However, several traditional strength-measuring methods are not effective and practical. In this study, a novel method to estimate the strength development of HSC based on electromechanical impedance (EMI) measurements using an embedded piezoelectric sensor is proposed. The EMI of NPP concrete specimen was tracked to monitor the strength development. In addition, cross-correlation coefficient was applied in sequence to examine the trend of the impedance variations more quantitatively. The results confirmed that the proposed technique can be applied successfully monitoring of the strength development during the curing process of HSC structures.

Keywords: concrete curing, embedded piezoelectric sensor, high strength concrete, nuclear power plant, self-sensing impedance

Procedia PDF Downloads 497

Authors: Zahra Afshordi

Abstract:

Instagram, as an everyday life social network, hosts from the ultrasound image of an unborn fetus to the pictures of newly placed gravestones and funerals. It is a platform that allows its users to create a second identity independently from and at the same time in relation to the real space identity. The motives behind this identification are what this article is about. This article studies the motivations of Instagram users mourning for celebrities with a focus on the death of MohammadReza Shajarian. The Shajarian’s death had a wide reflection on Instagram Persian-speaking users. The purpose of this qualitative survey is to comprehend and study the user’s motivations in posting mourning and memorializing content. The methodology of the essay is a hybrid methodology consisting of content analysis and open-ended interviews. The results highlight that users' motives are more than just simple sympathy and include political protest, gaining cultural capital, reaching social status, and escaping from solitude.

Keywords: case study, celebrity, identity, Instagram, mourning, qualitative survey

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Authors: Pedro Esteban

Abstract:

Planning a hybrid power system (HPS) that integrates renewable generation sources, non-renewable generation sources and energy storage, involves determining the capacity and size of various components to be used in the system to be able to supply reliable electricity to the connected load as required. Nowadays it is very common to integrate solar photovoltaic (PV) power plants for renewable generation as part of HPS. The solar PV system is usually balanced via a second form of generation (renewable such as wind power or using fossil fuels such as a diesel generator) or an energy storage system (such as a battery bank). Hybrid power systems can also provide other forms of power such as heat for some applications. Modern hybrid power systems combine power generation and energy storage technologies together with real-time energy management and innovative power quality and energy efficiency improvement functionalities. These systems help customers achieve targets for clean energy generation, they add flexibility to the electrical grid, and they optimize the installation by improving its power quality and energy efficiency.

Keywords: microgrids, hybrid power systems, energy storage, grid code compliance

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Authors: Simangele Dlamini

Abstract:

Smart city development is seen as a way of facing the challenges brought about by the growing urban population the world over. Research indicates that cities have a role to play in combating urban challenges like crime, waste disposal, greenhouse gas emissions, and resource efficiency. These solutions should be such that they do not make city management less sustainable but should be solutions-driven, cost and resource-efficient, and smart. This study explores opportunities on how the City of Johannesburg, South Africa, can use Geographic Information Systems, Big Data and the Internet of Things (IoT) in identifying opportune areas to initiate smart city initiatives such as smart safety, smart utilities, smart mobility, and smart infrastructure in an integrated manner. The study will combine Big Data, using real-time data sources to identify hotspot areas that will benefit from ICT interventions. The GIS intervention will assist the city in avoiding a silo approach in its smart city development initiatives, an approach that has led to the failure of smart city development in other countries.

Keywords: smart cities, internet of things, geographic information systems, johannesburg

Procedia PDF Downloads 126