Search results for: real time pest tracking
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21491

Search results for: real time pest tracking

16571 A Semantic and Concise Structure to Represent Human Actions

Authors: Tobias Strübing, Fatemeh Ziaeetabar

Abstract:

Humans usually manipulate objects with their hands. To represent these actions in a simple and understandable way, we need to use a semantic framework. For this purpose, the Semantic Event Chain (SEC) method has already been presented which is done by consideration of touching and non-touching relations between manipulated objects in a scene. This method was improved by a computational model, the so-called enriched Semantic Event Chain (eSEC), which incorporates the information of static (e.g. top, bottom) and dynamic spatial relations (e.g. moving apart, getting closer) between objects in an action scene. This leads to a better action prediction as well as the ability to distinguish between more actions. Each eSEC manipulation descriptor is a huge matrix with thirty rows and a massive set of the spatial relations between each pair of manipulated objects. The current eSEC framework has so far only been used in the category of manipulation actions, which eventually involve two hands. Here, we would like to extend this approach to a whole body action descriptor and make a conjoint activity representation structure. For this purpose, we need to do a statistical analysis to modify the current eSEC by summarizing while preserving its features, and introduce a new version called Enhanced eSEC or (e2SEC). This summarization can be done from two points of the view: 1) reducing the number of rows in an eSEC matrix, 2) shrinking the set of possible semantic spatial relations. To achieve these, we computed the importance of each matrix row in an statistical way, to see if it is possible to remove a particular one while all manipulations are still distinguishable from each other. On the other hand, we examined which semantic spatial relations can be merged without compromising the unity of the predefined manipulation actions. Therefore by performing the above analyses, we made the new e2SEC framework which has 20% fewer rows, 16.7% less static spatial and 11.1% less dynamic spatial relations. This simplification, while preserving the salient features of a semantic structure in representing actions, has a tremendous impact on the recognition and prediction of complex actions, as well as the interactions between humans and robots. It also creates a comprehensive platform to integrate with the body limbs descriptors and dramatically increases system performance, especially in complex real time applications such as human-robot interaction prediction.

Keywords: enriched semantic event chain, semantic action representation, spatial relations, statistical analysis

Procedia PDF Downloads 126
16570 Inviscid Steady Flow Simulation Around a Wing Configuration Using MB_CNS

Authors: Muhammad Umar Kiani, Muhammad Shahbaz, Hassan Akbar

Abstract:

Simulation of a high speed inviscid steady ideal air flow around a 2D/axial-symmetry body was carried out by the use of mb_cns code. mb_cns is a program for the time-integration of the Navier-Stokes equations for two-dimensional compressible flows on a multiple-block structured mesh. The flow geometry may be either planar or axisymmetric and multiply-connected domains can be modeled by patching together several blocks. The main simulation code is accompanied by a set of pre and post-processing programs. The pre-processing programs scriptit and mb_prep start with a short script describing the geometry, initial flow state and boundary conditions and produce a discretized version of the initial flow state. The main flow simulation program (or solver as it is sometimes called) is mb_cns. It takes the files prepared by scriptit and mb_prep, integrates the discrete form of the gas flow equations in time and writes the evolved flow data to a set of output files. This output data may consist of the flow state (over the whole domain) at a number of instants in time. After integration in time, the post-processing programs mb_post and mb_cont can be used to reformat the flow state data and produce GIF or postscript plots of flow quantities such as pressure, temperature and Mach number. The current problem is an example of supersonic inviscid flow. The flow domain for the current problem (strake configuration wing) is discretized by a structured grid and a finite-volume approach is used to discretize the conservation equations. The flow field is recorded as cell-average values at cell centers and explicit time stepping is used to update conserved quantities. MUSCL-type interpolation and one of three flux calculation methods (Riemann solver, AUSMDV flux splitting and the Equilibrium Flux Method, EFM) are used to calculate inviscid fluxes across cell faces.

Keywords: steady flow simulation, processing programs, simulation code, inviscid flux

Procedia PDF Downloads 429
16569 Do European Hedge Fund Managers Time Market Liquidity?

Authors: Soumaya Ben Kheilifa, Dorra Mezzez Hmaied

Abstract:

We propose two approaches to examine whether European hedge fund managers can time market liquidity. Using a sample of 1616 European hedge funds, we find evidence of liquidity timing. More importantly, this ability adds economic value to investors. Thus, it represents valuable managerial skill and a major source of European hedge funds’ performance. Also we show that the majority of these funds demonstrate liquidity timing ability especially during liquidity crisis. Finally, it emerged that our main evidence of liquidity timing remains significant after controlling for market timing and volatility timing.

Keywords: european hedge funds, liquidity timing ability, market liquidity, crisis

Procedia PDF Downloads 392
16568 The European Union: Considering Its Alleged Endangerment

Authors: Jesús Ulloa

Abstract:

The creation, rise, and consolidation of far right-wing, ultranationalist, and eurosceptic parties in Europe after the Second World War pose a real threat towards the disintegration of the European Union. Starting more than thirty years ago with Jean-Marie Le Pen's FN and Margaret Thatcher's policies, to Marine Le Pen's current FN and anti-immigration proposals along with Nigel Farage's UKIP and their intentions to leave the European Union, the progress of right-wing parties should be noted, taking into account that they may have very important differences within their postures but that they also reach common ground in certain areas. The actual disintegration of the EU would represent an enormous failure of the new liberal world order. Through this essay, the roots of this political parties will be analyzed and the conclusion of whether the disintegration may become a reality or if the principles of cooperation and unity will prevail will be answered.

Keywords: eurosceptic, ultarnationalist, right-wing, European Union

Procedia PDF Downloads 583
16567 Deep Learning-Based Liver 3D Slicer for Image-Guided Therapy: Segmentation and Needle Aspiration

Authors: Ahmedou Moulaye Idriss, Tfeil Yahya, Tamas Ungi, Gabor Fichtinger

Abstract:

Image-guided therapy (IGT) plays a crucial role in minimally invasive procedures for liver interventions. Accurate segmentation of the liver and precise needle placement is essential for successful interventions such as needle aspiration. In this study, we propose a deep learning-based liver 3D slicer designed to enhance segmentation accuracy and facilitate needle aspiration procedures. The developed 3D slicer leverages state-of-the-art convolutional neural networks (CNNs) for automatic liver segmentation in medical images. The CNN model is trained on a diverse dataset of liver images obtained from various imaging modalities, including computed tomography (CT) and magnetic resonance imaging (MRI). The trained model demonstrates robust performance in accurately delineating liver boundaries, even in cases with anatomical variations and pathological conditions. Furthermore, the 3D slicer integrates advanced image registration techniques to ensure accurate alignment of preoperative images with real-time interventional imaging. This alignment enhances the precision of needle placement during aspiration procedures, minimizing the risk of complications and improving overall intervention outcomes. To validate the efficacy of the proposed deep learning-based 3D slicer, a comprehensive evaluation is conducted using a dataset of clinical cases. Quantitative metrics, including the Dice similarity coefficient and Hausdorff distance, are employed to assess the accuracy of liver segmentation. Additionally, the performance of the 3D slicer in guiding needle aspiration procedures is evaluated through simulated and clinical interventions. Preliminary results demonstrate the effectiveness of the developed 3D slicer in achieving accurate liver segmentation and guiding needle aspiration procedures with high precision. The integration of deep learning techniques into the IGT workflow shows great promise for enhancing the efficiency and safety of liver interventions, ultimately contributing to improved patient outcomes.

Keywords: deep learning, liver segmentation, 3D slicer, image guided therapy, needle aspiration

Procedia PDF Downloads 48
16566 Sociocultural and Critical Approach for Summer Study Abroad Program in Higher Education

Authors: Magda Silva

Abstract:

This paper presents the empirical and the theoretical principles associated with the Duke in Brazil Summer Program. Using a sociocultural model and critical theory, this study abroad maximizes students’ ability to enrich language competence, intercultural skills, and critical thinking. The fourteen-year implementation of this project demonstrates the global importance of foreign language teaching as the program unfolds into real life scenarios within the cultures of distinct regions of Brazil; Cosmopolitan Rio, in the southeast, and rural Belém, northern Amazon region.

Keywords: study abroad, critical thinking, sociocultural theory, foreign language, empirical, theoretical

Procedia PDF Downloads 409
16565 Top-K Shortest Distance as a Similarity Measure

Authors: Andrey Lebedev, Ilya Dmitrenok, JooYoung Lee, Leonard Johard

Abstract:

Top-k shortest path routing problem is an extension of finding the shortest path in a given network. Shortest path is one of the most essential measures as it reveals the relations between two nodes in a network. However, in many real world networks, whose diameters are small, top-k shortest path is more interesting as it contains more information about the network topology. Many variations to compute top-k shortest paths have been studied. In this paper, we apply an efficient top-k shortest distance routing algorithm to the link prediction problem and test its efficacy. We compare the results with other base line and state-of-the-art methods as well as with the shortest path. Then, we also propose a top-k distance based graph matching algorithm.

Keywords: graph matching, link prediction, shortest path, similarity

Procedia PDF Downloads 358
16564 Optimization of Structures Subjected to Earthquake

Authors: Alireza Lavaei, Alireza Lohrasbi, Mohammadali M. Shahlaei

Abstract:

To reduce the overall time of structural optimization for earthquake loads two strategies are adopted. In the first strategy, a neural system consisting self-organizing map and radial basis function neural networks, is utilized to predict the time history responses. In this case, the input space is classified by employing a self-organizing map neural network. Then a distinct RBF neural network is trained in each class. In the second strategy, an improved genetic algorithm is employed to find the optimum design. A 72-bar space truss is designed for optimal weight using exact and approximate analysis for the El Centro (S-E 1940) earthquake loading. The numerical results demonstrate the computational advantages and effectiveness of the proposed method.

Keywords: optimization, genetic algorithm, neural networks, self-organizing map

Procedia PDF Downloads 311
16563 Enhanced Test Scheme based on Programmable Write Time for Future Computer Memories

Authors: Nor Zaidi Haron, Fauziyah Salehuddin, Norsuhaidah Arshad, Sani Irwan Salim

Abstract:

Resistive random access memories (RRAMs) are one of the main candidates for future computer memories. However, due to their tiny size and immature device technology, the quality of the outgoing RRAM chips is seen as a serious issue. Defective RRAM cells might behave differently than existing semiconductor memories (Dynamic RAM, Static RAM, and Flash), meaning that they are difficult to be detected using existing test schemes. This paper presents an enhanced test scheme, referred to as Programmable Short Write Time (PSWT) that is able to improve the detection of faulty RRAM cells. It is developed by applying multiple weak write operations, each with different time durations. The test circuit embedded in the RRAM chip is made programmable in order to supply different weak write times during testing. The RRAM electrical model is described using Verilog-AMS language and is simulated using HSPICE simulation tools. Simulation results show that the proposed test scheme offers better open-resistive fault detection compared to existing test schemes.

Keywords: memory fault, memory test, design-for-testability, resistive random access memory

Procedia PDF Downloads 387
16562 Regenerating Habitats. A Housing Based on Modular Wooden Systems

Authors: Rui Pedro de Sousa Guimarães Ferreira, Carlos Alberto Maia Domínguez

Abstract:

Despite the ambitions to achieve climate neutrality by 2050, to fulfill the Paris Agreement's goals, the building and construction sector remains one of the most resource-intensive and greenhouse gas-emitting industries in the world, accounting for 40% of worldwide CO ₂ emissions. Over the past few decades, globalization and population growth have led to an exponential rise in demand in the housing market and, by extension, in the building industry. Considering this housing crisis, it is obvious that we will not stop building in the near future. However, the transition, which has already started, is challenging and complex because it calls for the worldwide participation of numerous organizations in altering how building systems, which have been a part of our everyday existence for over a century, are used. Wood is one of the alternatives that is most frequently used nowadays (under responsible forestry conditions) because of its physical qualities and, most importantly, because it produces fewer carbon emissions during manufacturing than steel or concrete. Furthermore, as wood retains its capacity to store CO ₂ after application and throughout the life of the building, working as a natural carbon filter, it helps to reduce greenhouse gas emissions. After a century-long focus on other materials, in the last few decades, technological advancements have made it possible to innovate systems centered around the use of wood. However, there are still some questions that require further exploration. It is necessary to standardize production and manufacturing processes based on prefabrication and modularization principles to achieve greater precision and optimization of the solutions, decreasing building time, prices, and waste from raw materials. In addition, this approach will make it possible to develop new architectural solutions to solve the rigidity and irreversibility of buildings, two of the most important issues facing housing today. Most current models are still created as inflexible, fixed, monofunctional structures that discourage any kind of regeneration, based on matrices that sustain the conventional family's traditional model and are founded on rigid, impenetrable compartmentalization. Adaptability and flexibility in housing are, and always have been, necessities and key components of architecture. People today need to constantly adapt to their surroundings and themselves because of the fast-paced, disposable, and quickly obsolescent nature of modern items. Migrations on a global scale, different kinds of co-housing, or even personal changes are some of the new questions that buildings have to answer. Designing with the reversibility of construction systems and materials in mind not only allows for the concept of "looping" in construction, with environmental advantages that enable the development of a circular economy in the sector but also unleashes multiple social benefits. In this sense, it is imperative to develop prefabricated and modular construction systems able to address the formalization of a reversible proposition that adjusts to the scale of time and its multiple reformulations, many of which are unpredictable. We must allow buildings to change, grow, or shrink over their lifetime, respecting their nature and, finally, the nature of the people living in them. It´s the ability to anticipate the unexpected, adapt to social factors, and take account of demographic shifts in society to stabilize communities, the foundation of real innovative sustainability.

Keywords: modular, timber, flexibility, housing

Procedia PDF Downloads 79
16561 An Improved GA to Address Integrated Formulation of Project Scheduling and Material Ordering with Discount Options

Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

Abstract:

Concurrent planning of the resource constraint project scheduling and material ordering problems have received significant attention within the last decades. Hence, the issue has been investigated here with the aim to minimize total project costs. Furthermore, the presented model considers different discount options in order to approach the real world conditions. The incorporated alternatives consist of all-unit and incremental discount strategies. On the other hand, a modified version of the genetic algorithm is applied in order to solve the model for larger sizes, in particular. Finally, the applicability and efficiency of the given model is tested by different numerical instances.

Keywords: genetic algorithm, material ordering, project management, project scheduling

Procedia PDF Downloads 302
16560 Comparison of Sedentary Behavior and Physical Activity between Children with Autism Spectrum Disorder and the Controls

Authors: Abdulrahman M. Alhowikan, Nadra E. Elamin, Sarah S. Aldayel, Sara A. AlSiddiqi, Fai S. Alrowais, Laila Y. Al-Ayadhi

Abstract:

Background: A growing body of research has suggested that physical activities (PA) have important implications for improving the performance of ASD children. They revealed that the physiological, cognitive, psychological, and behavioral functioning had improved after performing some physical activities. Methods: We compared the sedentary behavior and physical activities between children with autism spectrum disorder (n=21) and age-matched control group (n=30), using the ActiGraph GT3X+ for the assessments. Results: Our results revealed that the total time spent in sedentary activity and the total sedentary activity counts were highly significant in the control group compared to the ASD group (p < 0.001, p=0.001, respectively). ASD spent a significantly longer time than the controls engaging on vigorous physical activity (VPA) (p=0.017). The results also indicated that there were no significant differences between both groups for the total counts and time spent in light physical activity (LPA) and moderate physical activity (MPA). Conclusion: The finding highlights the importance of physical activity intervention for ASD children, using accurate and precise measurement tools to record all activities.

Keywords: Autism spectrum disorders, motor skills, physical activity, ActiGraph GT3X+, moderate-to vigorous-intensity physical activity

Procedia PDF Downloads 137
16559 Outlier Detection in Stock Market Data using Tukey Method and Wavelet Transform

Authors: Sadam Alwadi

Abstract:

Outlier values become a problem that frequently occurs in the data observation or recording process. Thus, the need for data imputation has become an essential matter. In this work, it will make use of the methods described in the prior work to detect the outlier values based on a collection of stock market data. In order to implement the detection and find some solutions that maybe helpful for investors, real closed price data were obtained from the Amman Stock Exchange (ASE). Tukey and Maximum Overlapping Discrete Wavelet Transform (MODWT) methods will be used to impute the detect the outlier values.

Keywords: outlier values, imputation, stock market data, detecting, estimation

Procedia PDF Downloads 81
16558 Pathway Linking Early Use of Electronic Device and Psychosocial Wellbeing in Early Childhood

Authors: Rosa S. Wong, Keith T.S. Tung, Winnie W. Y. Tso, King-Wa Fu, Nirmala Rao, Patrick Ip

Abstract:

Electronic devices have become an essential part of our lives. Various reports have highlighted the alarming usage of electronic devices at early ages and its long-term developmental consequences. More sedentary screen time was associated with increased adiposity, worse cognitive and motor development, and psychosocial health. Apart from the problems caused by children’s own screen time, parents today are often paying less attention to their children due to hand-held device. Some anecdotes suggest that distracted parenting has negative impact on parent-child relationship. This study examined whether distracted parenting detrimentally affected parent-child activities which may, in turn, impair children’s psychosocial health. In 2018/19, we recruited a cohort of preschoolers from 32 local kindergartens in Tin Shui Wai and Sham Shui Po for a 5-year programme aiming to build stronger foundations for children from disadvantaged backgrounds through an integrated support model involving medical, education and social service sectors. A comprehensive set of questionnaires were used to survey parents on their frequency of being distracted while parenting and their frequency of learning and recreational activities with children. Furthermore, they were asked to report children’s screen time amount and their psychosocial problems. Mediation analyses were performed to test the direct and indirect effects of electronic device-distracted parenting on children’s psychosocial problems. This study recruited 873 children (448 females and 425 males, average age: 3.42±0.35). Longer screen time was associated with more psychosocial difficulties (Adjusted B=0.37, 95%CI: 0.12 to 0.62, p=0.004). Children’s screen time positively correlated with electronic device-distracted parenting (r=0.369, p < 01). We also found that electronic device-distracted parenting was associated with more hyperactive/inattentive problems (Adjusted B=0.66, p < 0.01), fewer prosocial behavior (Adjusted B=-0.74, p < 0.01), and more emotional symptoms (Adjusted B=0.61, p < 0.001) in children. Further analyses showed that electronic device-distracted parenting exerted influences both directly and indirectly through parent-child interactions but to different extent depending upon the outcome under investigation (38.8% for hyperactivity/inattention, 31.3% for prosocial behavior, and 15.6% for emotional symptoms). We found that parents’ use of devices and children’s own screen time both have negative effects on children’s psychosocial health. It is important for parents to set “device-free times” each day so as to ensure enough relaxed downtime for connecting with children and responding to their needs.

Keywords: early childhood, electronic device, psychosocial wellbeing, parenting

Procedia PDF Downloads 164
16557 Load Flow Analysis of 5-IEEE Bus Test System Using Matlab

Authors: H. Abaal, R. Skouri

Abstract:

A power flow analysis is a steady-state study of power grid. The goal of power flow analysis is to determine the voltages, currents, and real and reactive power flows in a system under a given load conditions. In this paper, the load flow analysis program by Newton Raphson polar coordinates Method is developed. The effectiveness of the developed program is evaluated through a simple 5-IEEE test system bus by simulations using MATLAB.

Keywords: power flow analysis, Newton Raphson polar coordinates method

Procedia PDF Downloads 603
16556 Algorithms Inspired from Human Behavior Applied to Optimization of a Complex Process

Authors: S. Curteanu, F. Leon, M. Gavrilescu, S. A. Floria

Abstract:

Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models.

Keywords: artificial neural networks, human behaviors of learning and cooperation, human competitive behavior, optimization algorithms

Procedia PDF Downloads 108
16555 Recognition of Early Enterococcus Faecalis through Image Treatment by Using Octave

Authors: Laura Victoria Vigoya Morales, David Rolando Suarez Mora

Abstract:

The problem of detecting enterococcus faecalis is receiving considerable attention with the new cases of beachgoers infected with the bacteria, which can be found in fecal matter. The process detection of this kind of bacteria would be taking a long time, which waste time and money as a result of closing recreation place, like beach or pools. Hence, new methods for automating the process of detecting and recognition of this bacteria has become in a challenge. This article describes a novel approach to detect the enterococcus faecalis bacteria in water by using an octave algorithm, which embody a network neural. This document shows result of performance, quality and integrity of the algorithm.

Keywords: Enterococcus faecalis, image treatment, octave and network neuronal

Procedia PDF Downloads 230
16554 Quadrotor in Horizontal Motion Control and Maneuverability

Authors: Ali Oveysi Sarabi

Abstract:

In this paper, controller design for the attitude and altitude dynamics of an outdoor quadrotor, which is constructed with low cost actuators and drivers, is aimed. Before designing the controller, the quadrotor is modeled mathematically in Matlab-Simulink environment. To control attitude dynamics, linear quadratic regulator (LQR) based controllers are designed, simulated and applied to the system. Two different proportional-integral-derivative action (PID) controllers are designed to control yaw and altitude dynamics. During the implementation of the designed controllers, different test setups are used. Designed controllers are implemented and tuned on the real system using xPC Target. Tests show that these basic control structures are successful to control the attitude and altitude dynamics.

Keywords: helicopter balance, flight dynamics, autonomous landing, control robotics

Procedia PDF Downloads 509
16553 Impact Location From Instrumented Mouthguard Kinematic Data In Rugby

Authors: Jazim Sohail, Filipe Teixeira-Dias

Abstract:

Mild traumatic brain injury (mTBI) within non-helmeted contact sports is a growing concern due to the serious risk of potential injury. Extensive research is being conducted looking into head kinematics in non-helmeted contact sports utilizing instrumented mouthguards that allow researchers to record accelerations and velocities of the head during and after an impact. This does not, however, allow the location of the impact on the head, and its magnitude and orientation, to be determined. This research proposes and validates two methods to quantify impact locations from instrumented mouthguard kinematic data, one using rigid body dynamics, the other utilizing machine learning. The rigid body dynamics technique focuses on establishing and matching moments from Euler’s and torque equations in order to find the impact location on the head. The methodology is validated with impact data collected from a lab test with the dummy head fitted with an instrumented mouthguard. Additionally, a Hybrid III Dummy head finite element model was utilized to create synthetic kinematic data sets for impacts from varying locations to validate the impact location algorithm. The algorithm calculates accurate impact locations; however, it will require preprocessing of live data, which is currently being done by cross-referencing data timestamps to video footage. The machine learning technique focuses on eliminating the preprocessing aspect by establishing trends within time-series signals from instrumented mouthguards to determine the impact location on the head. An unsupervised learning technique is used to cluster together impacts within similar regions from an entire time-series signal. The kinematic signals established from mouthguards are converted to the frequency domain before using a clustering algorithm to cluster together similar signals within a time series that may span the length of a game. Impacts are clustered within predetermined location bins. The same Hybrid III Dummy finite element model is used to create impacts that closely replicate on-field impacts in order to create synthetic time-series datasets consisting of impacts in varying locations. These time-series data sets are used to validate the machine learning technique. The rigid body dynamics technique provides a good method to establish accurate impact location of impact signals that have already been labeled as true impacts and filtered out of the entire time series. However, the machine learning technique provides a method that can be implemented with long time series signal data but will provide impact location within predetermined regions on the head. Additionally, the machine learning technique can be used to eliminate false impacts captured by sensors saving additional time for data scientists using instrumented mouthguard kinematic data as validating true impacts with video footage would not be required.

Keywords: head impacts, impact location, instrumented mouthguard, machine learning, mTBI

Procedia PDF Downloads 217
16552 Electromagnetically-Vibrated Solid-Phase Microextraction for Organic Compounds

Authors: Soo Hyung Park, Seong Beom Kim, Wontae Lee, Jin Chul Joo, Jungmin Lee, Jongsoo Choi

Abstract:

A newly-developed electromagnetically vibrated solid-phase microextraction (SPME) device for extracting nonpolar organic compounds from aqueous matrices was evaluated in terms of sorption equilibrium time, precision, and detection level relative to three other more conventional extraction techniques involving SPME, viz., static, magnetic stirring, and fiber insertion/retraction. Electromagnetic vibration at 300~420 cycles/s was found to be the most efficient extraction technique in terms of reducing sorption equilibrium time and enhancing both precision and linearity. The increased efficiency for electromagnetic vibration was attributed to a greater reduction in the thickness of the stagnant-water layer that facilitated more rapid mass transport from the aqueous matrix to the SPME fiber. Electromagnetic vibration less than 500 cycles/s also did not detrimentally impact the sustainability of the extracting performance of the SPME fiber. Therefore, electromagnetically vibrated SPME may be a more powerful tool for rapid sampling and solvent-free sample preparation relative to other more conventional extraction techniques used with SPME.

Keywords: electromagnetic vibration, organic compounds, precision, solid-phase microextraction (SPME), sorption equilibrium time

Procedia PDF Downloads 254
16551 Fostering Organizational Learning across the Canadian Sport System through Leadership and Mentorship Development of Sport Science Leaders

Authors: Jennifer Walinga, Samantha Heron

Abstract:

The goal of the study was to inform the design of effective leadership and mentorship development programming for sport science leaders within the network of Canadian sport institutes and centers. The LEAD (Learn, Engage, Accelerate, Develop) program was implemented to equip sport science leaders with the leadership knowledge, skills, and practice to foster a high - performance culture, enhance the daily training environment, and contribute to optimal performance in sport. After two years of delivery, this analysis of LEAD’s effect on individual and organizational health and performance factors informs the quality of future deliveries and identifies best practice for leadership development across the Canadian sport system and beyond. A larger goal for this project was to inform the public sector more broadly and position sport as a source of best practice for human and social health, development, and performance. The objectives of this study were to review and refine the LEAD program in collaboration with Canadian Sport Institute and Centre leaders, 40-50 participants from three cohorts, and the LEAD program advisory committee, and to trace the effects of the LEAD leadership development program on key leadership mentorship and organizational health indicators across the Canadian sport institutes and centers so as to capture best practice. The study followed a participatory action research framework (PAR) using semi structured interviews with sport scientist participants, program and institute leaders inquiring into impact on specific individual and organizational health and performance factors. Findings included a strong increase in self-reported leadership knowledge, skill, language and confidence, enhancement of human and organizational health factors, and the opportunity to explore more deeply issues of diversity and inclusion, psychological safety, team dynamics, and performance management. The study was significant in building sport leadership and mentorship development strategies for managing change efforts, addressing inequalities, and building personal and operational resilience amidst challenges of uncertainty, pressure, and constraint in real time.

Keywords: sport leadership, sport science leader, leadership development, professional development, sport education, mentorship

Procedia PDF Downloads 23
16550 A New Method Presentation for Locating Fault in Power Distribution Feeders Considering DG

Authors: Rahman Dashti, Ehsan Gord

Abstract:

In this paper, an improved impedance based fault location method is proposed. In this method, online fault locating is performed using voltage and current information at the beginning of the feeder. Determining precise fault location in a short time increases reliability and efficiency of the system. The proposed method utilizes information about main component of voltage and current at the beginning of the feeder and distributed generation unit (DGU) in order to precisely locate different faults in acceptable time. To evaluate precision and accuracy of the proposed method, a 13-node is simulated and tested using MATLAB.

Keywords: distribution network, fault section determination, distributed generation units, distribution protection equipment

Procedia PDF Downloads 401
16549 Technical and Economic Potential of Partial Electrification of Railway Lines

Authors: Rafael Martins Manzano Silva, Jean-Francois Tremong

Abstract:

Electrification of railway lines allows to increase speed, power, capacity and energetic efficiency of rolling stocks. However, this process of electrification is complex and costly. An electrification project is not just about design of catenary. It also includes installation of structures around electrification, as substation installation, electrical isolation, signalling, telecommunication and civil engineering structures. France has more than 30,000 km of railways, whose only 53% are electrified. The others 47% of railways use diesel locomotive and represent only 10% of the circulation (tons.km). For this reason, a new type of electrification, less expensive than the usual, is requested to enable the modernization of these railways. One solution could be the use of hybrids trains. This technology opens up new opportunities for less expensive infrastructure development such as the partial electrification of railway lines. In a partially electrified railway, the power supply of theses hybrid trains could be made either by the catenary or by the on-board energy storage system (ESS). Thus, the on-board ESS would feed the energetic needs of the train along the non-electrified zones while in electrified zones, the catenary would feed the train and recharge the on-board ESS. This paper’s objective deals with the technical and economic potential identification of partial electrification of railway lines. This study provides different scenarios of electrification by replacing the most expensive places to electrify using on-board ESS. The target is to reduce the cost of new electrification projects, i.e. reduce the cost of electrification infrastructures while not increasing the cost of rolling stocks. In this study, scenarios are constructed in function of the electrification’s cost of each structure. The electrification’s cost varies considerably because of the installation of catenary support in tunnels, bridges and viaducts is much more expensive than in others zones of the railway. These scenarios will be used to describe the power supply system and to choose between the catenary and the on-board energy storage depending on the position of the train on the railway. To identify the influence of each partial electrification scenario in the sizing of the on-board ESS, a model of the railway line and of the rolling stock is developed for a real case. This real case concerns a railway line located in the south of France. The energy consumption and the power demanded at each point of the line for each power supply (catenary or on-board ESS) are provided at the end of the simulation. Finally, the cost of a partial electrification is obtained by adding the civil engineering costs of the zones to be electrified plus the cost of the on-board ESS. The study of the technical and economic potential ends with the identification of the most economically interesting scenario of electrification.

Keywords: electrification, hybrid, railway, storage

Procedia PDF Downloads 431
16548 Mammotome Vacuum-Assisted Breast Biopsy versus Conventional Open Surgery: A Meta-Analysis

Authors: Dylan Shiting Lu, Samson Okello, Anita Chunyan Wei, Daniel Xiao Li

Abstract:

Mammotome vacuum-assisted breast biopsy (MVB) introduced in 1995 can be used for the removal of benign breast lesions. Whether or not MVB is a better option compared to conventional open surgery is inconclusive. We aim to compare the clinical and patient-related outcomes between MVB and open surgery to remove benign breast tumors less than 5 cm in women. We searched English and Chinese electronic databases with the keywords of Mammotome, clinical trial (CT), vacuum-assisted breast biopsy for studies comparing MVB and open surgery until May 2021. We performed a systematic review and random-effects meta-analysis to compare incision size, operation time, intraoperative blood loss, healing time, scar length, patient satisfaction, postoperative hematoma rate, wound infection rate, postoperative ecchymosis, and postoperative sunken skin among those who have Mammotome and those who have surgery. Our analysis included nine randomized CTs with 1155 total patients (575 Mammotome, 580 surgery) and mean age 40.32 years (standard deviation 3.69). We found statistically significant favorable outcomes for Mammotome including blood loss (ml) [standardized mean difference SMD -5.03, 95%CI (-7.30, -2.76)], incision size (cm) [SMD -12.22, 95%CI (-17.40, -7.04)], operation time (min) [SMD -6.66, 95%CI (-9.01, -4.31)], scar length (cm) [SMD -7.06, 95%CI (-10.76, -3.36)], healing time (days) [SMD -6.57, 95%CI (-10.18, -2.95)], and patient satisfaction [relative risk RR 0.38, 95%CI (0.13, 1.08)]. In conclusion, Mammotome vacuum-assisted breast biopsy compared to open surgery shows better clinical and patient-related outcomes. Further studies should be done on whether or not MVB is a better option for benign breast tumors excision.

Keywords: clinical and patient outcomes, open surgery, Mammotome vacuum-assisted breast biopsy, meta-analysis

Procedia PDF Downloads 217
16547 A Machine Learning Approach for the Leakage Classification in the Hydraulic Final Test

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

Procedia PDF Downloads 213
16546 Kinetic Study of Municipal Plastic Waste

Authors: Laura Salvia Diaz Silvarrey, Anh Phan

Abstract:

Municipal Plastic Waste (MPW) comprises a mixture of thermoplastics such as high and low density polyethylene (HDPE and LDPE), polypropylene (PP), polystyrene (PS) and polyethylene terephthalate (PET). Recycling rate of these plastics is low, e.g. only 27% in 2013. The remains were incinerated or disposed in landfills. As MPW generation increases approximately 5% per annum, MPW management technologies have to be developed to comply with legislation . Pyrolysis, thermochemical decomposition, provides an excellent alternative to convert MPW into valuable resources like fuels and chemicals. Most studies on waste plastic kinetics only focused on HDPE and LDPE with a simple assumption of first order decomposition, which is not the real reaction mechanism. The aim of this study was to develop a kinetic study for each of the polymers in the MPW mixture using thermogravimetric analysis (TGA) over a range of heating rates (5, 10, 20 and 40°C/min) in N2 atmosphere and sample size of 1 – 4mm. A model-free kinetic method was applied to quantify the activation energy at each level of conversion. Kissinger–Akahira–Sunose (KAS) and Flynn–Wall–Ozawa (FWO) equations jointly with Master Plots confirmed that the activation energy was not constant along all the reaction for all the five plastic studied, showing that MPW decomposed through a complex mechanism and not by first-order kinetics. Master plots confirmed that MPW decomposed following a random scission mechanism at conversions above 40%. According to the random scission mechanism, different radicals are formed along the backbone producing the cleavage of bonds by chain scission into molecules of different lengths. The cleavage of bonds during random scission follows first-order kinetics and it is related with the conversion. When a bond is broken one part of the initial molecule becomes an unsaturated one and the other a terminal free radical. The latter can react with hydrogen from and adjacent carbon releasing another free radical and a saturated molecule or reacting with another free radical and forming an alkane. Not every time a bonds is broken a molecule is evaporated. At early stages of the reaction (conversion and temperature below 40% and 300°C), most products are not short enough to evaporate. Only at higher degrees of conversion most of cleavage of bonds releases molecules small enough to evaporate.

Keywords: kinetic, municipal plastic waste, pyrolysis, random scission

Procedia PDF Downloads 354
16545 Anagliptin: A Japanese Made Dipeptidyl Peptidase-4 Inhibitor That Naturally Lowers LDL-Cholesterol in Type 2 Diabetes

Authors: C. Iitake, K. Iitake

Abstract:

Background and Aims: The number of diabetic patients based on obesity is increasing drastically in Asia. Since most patients have multiple complications, if one medicine can treat those at the same time, it would contribute to financial savings and patients’ compliance. A Japanese-made DPP-4 inhibitor, Anagliptin is only sold in Japan and South Korea. It is said to have its unique aspect of lowering LDL-cholesterol (LDL-C) levels together with lowering blood glucose. We have assessed 63 patients in our faculty to investigate this fact clinically and statistically. Method: Patients with type 2 diabetes who has been treated with Anagliptin for the first time was investigated changes in HbA1c, fasting and random blood glucose and LDL-C levels from the baseline at 1 month, 6 months and 1 year. Results: 29 patients (46.1%) were given DPP-4 inhibitors for the first time (original group), and 34 patients (53.9%) were using other DPP-4 inhibitors before Anagliptin (exchanged group). The change in HbA1c and fasting glucose from the baseline were -2.0% (P < 0.001) and -38.3mg/dl (P < 0.01) respectively with original group, -0.5% (P < 0.01) and -29.4mg/dl (P < 0.01) respectively with exchanged group. 23 patients (36.5%) were using statins or fibrates and 28 patients (44.4%) were using none, and its LDL-C change were -8.1mg/dl (P = 0.2582) and -10.1mg/dl(P < 0.05) respectively. 16 patients(25%) with LDL-C level ≥ 140mg/dl, change were -21.7mg/dl(P < 0.05). LDL-C change did not have a correlation coefficient (=-0.03238) with change in HbA1c and was not affected by other diabetic drugs. Conclusion: These findings indicate that Anagliptin is a potential treatment option for type 2 diabetes complicated by hyperlipidemia.

Keywords: DPP-4 inhibitors, anagliptin, LDL-cholesterol, type 2 diabetes

Procedia PDF Downloads 154
16544 Identification of the Most Effective Dosage of Clove Oil Solution as an Alternative for Synthetic Anaesthetics on Zebrafish (Danio rerio)

Authors: D. P. N. De Silva, N. P. P. Liyanage

Abstract:

Zebrafish (Danio rerio) in the family Cyprinidae, is a tropical freshwater fish widely used as a model organism in scientific research. Use of effective and economical anaesthetic is very important when handling fish. Clove oil (active ingredient: eugenol) was identified as a natural product which is safer and economical compared to synthetic chemicals like methanesulfonate (MS-222). Therefore, the aim of this study was to identify the most effective dosage of clove oil solution as an anaesthetic on mature Zebrafish. Clove oil solution was prepared by mixing pure clove oil with 94% ethanol at a ratio of 1:9 respectively. From that solution, different volumes were selected as (0.4 ml, 0.6 ml and 0.8 ml) and dissolved in one liter of conditioned water (dosages : 0.4 ml/L, 0.6 ml/L and 0.8 ml/L). Water quality parameters (pH, temperature and conductivity) were measured before and after adding clove oil solution. Mature Zebrafish with similar standard length (2.76 ± 0.1 cm) and weight (0.524 ± 0.1 g) were selected for this experiment. Time taken for loss of equilibrium (initiation phase) and complete loss of movements including opercular movement (anaesthetic phase) were measured. To detect the efficacy on anaesthetic recovery, time taken to begin opercular movements (initiation of recovery phase) until swimming (post anaesthetic phase) were observed. The results obtained were analyzed according to the analysis of variance (ANOVA) and Tukeys’ method using SPSS version 17.0 at 95% confidence interval (p<0.5). According to the results, there was no significant difference at the initiation phase of anaesthesia in all three doses though the time taken was varied from 0.14 to 0.41 minutes. Mean value of the time taken to complete the anaesthetic phase at 0.4 ml/L dosage was significantly different with 0.6 ml/L and 0.8 ml/L dosages independently (p=0.01). There was no significant difference among recovery times at all dosages but 0.8 ml/L dosage took longer time compared to 0.6 ml/L dosage. The water quality parameters (pH and temperature) were stable throughout the experiment except conductivity, which increased with the higher dosage. In conclusion, the best dosage need to anaesthetize Zebrafish using clove oil solution was 0.6 ml/L due to its fast initiation of anaesthesia and quick recovery compared to the other two dosages. Therefore clove oil can be used as a good substitute for synthetic anaesthetics because of its efficacy at a lower dosage with higher safety at a low cost.

Keywords: anaesthetics, clove oil, zebrafish, Cyprinidae

Procedia PDF Downloads 716
16543 Error Amount in Viscoelasticity Analysis Depending on Time Step Size and Method used in ANSYS

Authors: A. Fettahoglu

Abstract:

Theory of viscoelasticity is used by many researchers to represent behavior of many materials such as pavements on roads or bridges. Several researches used analytical methods and rheology to predict the material behaviors of simple models. Today, more complex engineering structures are analyzed using Finite Element Method, in which material behavior is embedded by means of three dimensional viscoelastic material laws. As a result, structures of unordinary geometry and domain like pavements of bridges can be analyzed by means of Finite Element Method and three dimensional viscoelastic equations. In the scope of this study, rheological models embedded in ANSYS, namely, generalized Maxwell elements and Prony series, which are two methods used by ANSYS to represent viscoelastic material behavior, are presented explicitly. Subsequently, a practical problem, which has an analytical solution given in literature, is used to verify the applicability of viscoelasticity tool embedded in ANSYS. Finally, amount of error in the results of ANSYS is compared with the analytical results to indicate the influence of used method and time step size.

Keywords: generalized Maxwell model, finite element method, prony series, time step size, viscoelasticity

Procedia PDF Downloads 369
16542 Robust H∞ State Feedback Control for Discrete Time T-S Fuzzy Systems Based on Fuzzy Lyapunov Function Approach

Authors: Walied Hanora

Abstract:

This paper presents the problem of robust state feedback H∞ for discrete time nonlinear system represented by Takagi-Sugeno fuzzy systems. Based on fuzzy lyapunov function, the condition ,which is represented in the form of Liner Matrix Inequalities (LMI), guarantees the H∞ performance of the T-S fuzzy system with uncertainties. By comparison with recent literature, this approach will be more relaxed condition. Finally, an example is given to illustrate the proposed result.

Keywords: fuzzy lyapunov function, H∞ control , linear matrix inequalities, state feedback, T-S fuzzy systems

Procedia PDF Downloads 288