Search results for: real time PCR (qPCR)

Authors: Gyo Woo Lee, Man Young Kim

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A mathematical heat transfer model for the prediction of transient heating of the slab in a direct-fired walking beam type reheating furnace has been developed by considering the nongray thermal radiation with given furnace environments. The furnace is modeled as radiating nongray medium with carbon dioxide and water with five-zoned gas temperature and the furnace wall is considered as a constant temperature lower than furnace gas one. The slabs are moving with constant velocity depending on the residence time through the non-firing, charging, preheating, heating, and final soaking zones. Radiative heat flux obtained by considering the radiative heat exchange inside the furnace as well as convective one from the surrounding hot gases are introduced as boundary condition of the transient heat conduction within the slab. After validating thermal radiation model adopted in this work, thermal fields in both model and real reheating furnace are investigated in terms of radiative heat flux in the furnace and temperature inside the slab. The results show that the slab in the furnace can be more heated with higher slab emissivity and residence time.

Keywords: reheating furnace, steel slab, radiative heat transfer, WSGGM, emissivity, residence time

Procedia PDF Downloads 278

Authors: Wesley H. Brewer, John C. Sanford

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SciPaaS is a prototype development of an execution platform/middleware designed to make it easy for scientists to rapidly deploy their scientific applications (apps) to the cloud. It provides all the necessary infrastructure for running typical IXP (Input-eXecute-Plot) style apps, including: a web interface, post-processing and plotting capabilities, job scheduling, real-time monitoring of running jobs, and even a file/case manager. In this paper, first the system architecture is described and then is demonstrated for a two scientific applications: (1) a simple finite-difference solver of the inviscid Burger’s equation, and (2) Mendel’s Accountant—a forward-time population genetics simulation model. The implications of the prototype are discussed in terms of ease-of-use and deployment options, especially in cloud environments.

Keywords: web-based simulation, cloud computing, Platform-as-a-Service (PaaS), rapid application development (RAD), population genetics

Procedia PDF Downloads 583

Authors: E. Dahlen

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Inflation can be calculated from either the prices of consumer products or from salaries. This paper presents a logical exercise that shows it is easier to calculate inflation from salaries than from consumer products. While the prices of consumer products may change due to technological advancement, such as automation, which must be corrected for, salaries do not. If technological advancements are not accounted for within calculations based on consumer product prices, inflation can be confused with real wage changes, since both inflation and real wage changes affect the prices of consumer products. The method employed in this paper is a logical exercise. Logical arguments are presented that suggest the existence of many different feasible ways by which inflation can be determined. Then a short mathematical exercise will be presented which shows that one of these methods –using salaries – contains the fewest number of unknown parameters, and hence, is the preferred method, since the risk of mistakes is lower. From the results, it can be concluded that salaries, rather than consumer products, should be used to calculate inflation.

Keywords: inflation, logic, math, real wages

Procedia PDF Downloads 319

Authors: Hamed Yousefi, Farnaz Mohammadi, Niloufar Mirian, Navid Amini

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Investigating possible capacities of visual functions where adapted mechanisms can enhance the capability of sports trainees is a promising area of research, not only from the cognitive viewpoint but also in terms of unlimited applications in sports training. In this paper, the visual evoked potential (VEP) and event-related potential (ERP) signals of amateur and trained volleyball players in a pilot study were processed. Two groups of amateur and trained subjects are asked to imagine themselves in the state of receiving a ball while they are shown a simulated volleyball field. The proposed method is based on a set of time-frequency features using algorithms such as Gabor filter, continuous wavelet transform, and a multi-stage wavelet decomposition that are extracted from VEP signals that can be indicative of being amateur or trained. The linear discriminant classifier achieves the accuracy, sensitivity, and specificity of 100% when the average of the repetitions of the signal corresponding to the task is used. The main purpose of this study is to investigate the feasibility of a fast, robust, and reliable feature/model determination as a neurofeedback parameter to be utilized for improving the volleyball players’ performance. The proposed measure has potential applications in brain-computer interface technology where a real-time biomarker is needed.

Keywords: visual evoked potential, time-frequency feature extraction, short-time Fourier transform, event-related spectrum potential classification, linear discriminant analysis

Procedia PDF Downloads 131

Authors: Junkyeong Kim, Jooyoung Park, Aoqi Zhang, Seunghee Park

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The tensile force of Pre-Stressed Concrete (PSC) girder is the most important factor for evaluating the performance of PSC girder bridges. To measure the tensile force of PSC girder, several NDT methods were studied. However, conventional NDT method cannot be applied to the real-size PSC girder because the PS tendons could not be approached. To measure the tensile force of real-size PSC girder, this study proposed embedded EM sensor based tensile force estimation method. The embedded EM sensor could be installed inside of PSC girder as a sheath joint before the concrete casting. After curing process, the PS tendons were installed, and the tensile force was induced step by step using hydraulic jacking machine. The B-H loop was measured using embedded EM sensor at each tensile force steps and to compare with actual tensile force, the load cell was installed at each end of girder. The magnetization energy loss, that is the closed area of B-H loop, was decreased according to the increase of tensile force with regular pattern. Thus, the tensile force could be estimated by the tracking the change of magnetization energy loss of PS tendons. Through the experimental result, the proposed method can be used to estimate the tensile force of the in-situ real-size PSC girder bridge.

Keywords: tensile force estimation, embedded EM sensor, magnetization energy loss, PSC girder

Procedia PDF Downloads 331

Authors: Tomoko Usui

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In the field of linguistics, it has been said that concepts associated with space and motion systematically contribute structure to the temporal concept. This is the conceptual metaphor theory. conceptual metaphors typically employ a more abstract concept (time) as their target and a more concrete or physical concept as their source (space). This paper will examine two major temporal conceptual metaphors: Ego-centered Moving Time Metaphor and Time-RP Metaphor. Moving time generally receives a front-back orientation, however, Japanese shows a different orientation given to time. By means of Ego perspective, this paper will illustrate the paradox of a metaphorical orientation in time.

Keywords: Ego-centered Moving Time Metaphor, Japanese saki, temporal metaphors, Time RP Metaphor

Procedia PDF Downloads 493

Authors: Prasad Kalagura, B. Veeresh kumar

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We constructed an interface system that would allow a similarly paralyzed user to interact with a computer with almost full functional capability. A real-time tracking algorithm is implemented based on adaptive skin detection and motion analysis. The clicking of the mouse is activated by the user's eye blinking through a sensor. The keyboard function is implemented by voice recognition kit.

Keywords: embedded ARM7 processor, mouse pointer control, voice recognition

Procedia PDF Downloads 572

Authors: Pierre Kancir, Jean-Philippe Diguet, Marc Sevaux

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One of the main difficulties in developing multi-robot systems (MRS) is related to the simulation and testing tools available. Indeed, if the differences between simulations and real robots are too significant, the transition from the simulation to the robot won’t be possible without another long development phase and won’t permit to validate the simulation. Moreover, the testing of different algorithmic solutions or modifications of robots requires a strong knowledge of current tools and a significant development time. Therefore, the availability of tools for MRS, mainly with flying drones, is crucial to enable the industrial emergence of these systems. This research aims to present the most commonly used tools for MRS simulations and their main shortcomings and presents complementary tools to improve the productivity of designers in the development of multi-vehicle solutions focused on a fast learning curve and rapid transition from simulations to real usage. The proposed contributions are based on existing open source tools as Gazebo simulator combined with ROS (Robot Operating System) and the open-source multi-platform autopilot ArduPilot to bring them to a broad audience.

Keywords: ROS, ArduPilot, MRS, simulation, drones, Gazebo

Procedia PDF Downloads 202

Authors: M. Wigwe, M. Y Soloman, E. Pirayesh, R. Eghorieta, N. Stegent

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The moving reference point (MRP) technique has been used in the analyses of the first three stages of two fracturing jobs. The results obtained verify the proposition that a hydraulic fracture in shale grows in spurts rather than in a continuous pattern as originally interpreted by Nolte-Smith technique. Rather than a continuous Mode I fracture that is followed by Mode II, III or IV fractures, these fracture modes could alternate throughout the pumping period. It is also shown that the Nolte-Smith time parameter plot can be very helpful in identifying the presence of natural fractures that have been intersected by the hydraulic fracture. In addition, with the aid of a fracture length-time plot generated from any fracture simulation that matches the data, the distance from the wellbore to the natural fractures, which also translates to the actual fracture length for the stage, can be determined. An algorithm for this technique is developed. This procedure was used for the first 9 minutes of the simulated frac job data. It was observed that after 7mins, the actual fracture length is about 150ft, instead of 250ft predicted by the simulator output. This difference gets larger as the analysis proceeds.

Keywords: shale, fracturing, reservoir, simulation, frac-length, moving-reference-point

Procedia PDF Downloads 745

Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Rock mechanical investigation is one of the most crucial activities in underground operations, especially in surveys related to hydrocarbon exploration and production, geothermal reservoirs, energy storage, mining, and geotechnics. There is a wide range of traditional methods for driving, collecting, and analyzing rock mechanics data. However, these approaches may not be suitable or work perfectly in some situations, such as fractured zones. Cutting-edge technologies have been provided to solve and optimize the mentioned issues. Internet of Things (IoT), Edge, and Cloud Computing technologies (ECt & CCt, respectively) are among the most widely used and new artificial intelligence methods employed for geomechanical studies. IoT devices act as sensors and cameras for real-time monitoring and mechanical-geological data collection of rocks, such as temperature, movement, pressure, or stress levels. Structural integrity, especially for cap rocks within hydrocarbon systems, and rock mass behavior assessment, to further activities such as enhanced oil recovery (EOR) and underground gas storage (UGS), or to improve safety risk management (SRM) and potential hazards identification (P.H.I), are other benefits from IoT technologies. EC techniques can process, aggregate, and analyze data immediately collected by IoT on a real-time scale, providing detailed insights into the behavior of rocks in various situations (e.g., stress, temperature, and pressure), establishing patterns quickly, and detecting trends. Therefore, this state-of-the-art and useful technology can adopt autonomous systems in rock mechanical surveys, such as drilling and production (in hydrocarbon wells) or excavation (in mining and geotechnics industries). Besides, ECt allows all rock-related operations to be controlled remotely and enables operators to apply changes or make adjustments. It must be mentioned that this feature is very important in environmental goals. More often than not, rock mechanical studies consist of different data, such as laboratory tests, field operations, and indirect information like seismic or well-logging data. CCt provides a useful platform for storing and managing a great deal of volume and different information, which can be very useful in fractured zones. Additionally, CCt supplies powerful tools for predicting, modeling, and simulating rock mechanical information, especially in fractured zones within vast areas. Also, it is a suitable source for sharing extensive information on rock mechanics, such as the direction and size of fractures in a large oil field or mine. The comprehensive review findings demonstrate that digital transformation through integrated IoT, Edge, and Cloud solutions is revolutionizing traditional rock mechanical investigation. These advanced technologies have empowered real-time monitoring, predictive analysis, and data-driven decision-making, culminating in noteworthy enhancements in safety, efficiency, and sustainability. Therefore, by employing IoT, CCt, and ECt, underground operations have experienced a significant boost, allowing for timely and informed actions using real-time data insights. The successful implementation of IoT, CCt, and ECt has led to optimized and safer operations, optimized processes, and environmentally conscious approaches in underground geological endeavors.

Keywords: rock mechanical studies, internet of things, edge computing, cloud computing, underground surveys, geological operations

Procedia PDF Downloads 51

Authors: Wedad Albalawi

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The mathematical inequalities have been the core of mathematical study and used in almost all branches of mathematics as well in various areas of science and engineering. The inequalities by Hardy, Littlewood and Polya were the first significant composition of several science. This work presents fundamental ideas, results and techniques and it has had much influence on research in various branches of analysis. Since 1934, various inequalities have been produced and studied in the literature. Furthermore, some inequalities have been formulated by some operators; in 1989, weighted Hardy inequalities have been obtained for integration operators. Then, they obtained weighted estimates for Steklov operators that were used in the solution of the Cauchy problem for the wave equation. They were improved upon in 2011 to include the boundedness of integral operators from the weighted Sobolev space to the weighted Lebesgue space. Some inequalities have been demonstrated and improved using the Hardy–Steklov operator. Recently, a lot of integral inequalities have been improved by differential operators. Hardy inequality has been one of the tools that is used to consider integrity solutions of differential equations. Then dynamic inequalities of Hardy and Coposon have been extended and improved by various integral operators. These inequalities would be interesting to apply in different fields of mathematics (functional spaces, partial differential equations, mathematical modeling). Some inequalities have been appeared involving Copson and Hardy inequalities on time scales to obtain new special version of them. A time scale is defined as a closed subset contains real numbers. Then the inequalities of time scales version have received a lot of attention and has had a major field in both pure and applied mathematics. There are many applications of dynamic equations on time scales to quantum mechanics, electrical engineering, neural networks, heat transfer, combinatorics, and population dynamics. This study focuses on double integrals to obtain new time-scale inequalities of Copson driven by Steklov operator. They will be applied in the solution of the Cauchy problem for the wave equation. The proof can be done by introducing restriction on the operator in several cases. In addition, the obtained inequalities done by using some concepts in time scale version such as time scales calculus, theorem of Fubini and the inequality of H¨older.

Keywords: time scales, inequality of Hardy, inequality of Coposon, Steklov operator

Procedia PDF Downloads 71

Authors: Andi Intan Purnamasari, Supriyadi, Sulbadana, Aminuddin Kasim

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Law functions as social control. Providing arrangements not only for legal certainty, but also in the scope of justice and expediency. The three values ​​achieved by law essentially function to bring comfort to each individual in carrying out daily activities. However, it is undeniable that global conditions have changed the orientation of people's lifestyles. Some people want to ensure their existence in the digital world which is popularly known as the metaverse. Some countries even project their city to be a metaverse city. The order of life is no longer limited to the real space, but also to the cyber world. Not infrequently, legal events that occur in the cyber world also force the law to position its position and even prevent crime in cyberspace. Through this research, conceptually it provides a view of the legal position in crime prevention in the Metaverse world. when the law acts to regulate the situation in the virtual world, of course some people will feel disturbed, this is due to the thought that the virtual world is a world in which an avatar can do things that cannot be done in the real world, or can be called a world without boundaries. Therefore, when the law is present to provide boundaries, of course the concept of the virtual world itself becomes no longer a cyber world that is not limited by space and time, it becomes a new order of life. approach, approach, approach, approach, and approach will certainly be the method used in this research.

Keywords: crime, cyber, metaverse, law

Procedia PDF Downloads 145

Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

Procedia PDF Downloads 138

Authors: Yuxiang Pan, Yong Qiu, Chenlei Gu, Ping Wang

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In the past decade, three-dimensional (3D) tumor cell models have attracted increasing interest in the field of drug screening due to their great advantages in simulating more accurately the heterogeneous tumor behavior in vivo. Drug sensitivity testing based on 3D tumor cell models can provide more reliable in vivo efficacy prediction. The gold standard fluorescence staining is hard to achieve the real-time and label-free monitoring of the viability of 3D tumor cell models. In this study, micro-groove impedance sensor (MGIS) was specially developed for dynamic and non-invasive monitoring of 3D cell viability. 3D tumor cells were trapped in the micro-grooves with opposite gold electrodes for the in-situ impedance measurement. The change of live cell number would cause inversely proportional change to the impedance magnitude of the entire cell/matrigel to construct and reflect the proliferation and apoptosis of 3D cells. It was confirmed that 3D cell viability detected by the MGIS platform is highly consistent with the standard live/dead staining. Furthermore, the accuracy of MGIS platform was demonstrated quantitatively using 3D lung cancer model and sophisticated drug sensitivity testing. In addition, the parameters of micro-groove impedance chip processing and measurement experiments were optimized in details. The results demonstrated that the MGIS and 3D cell-based biosensor and would be a promising platform to improve the efficiency and accuracy of cell-based anti-cancer drug screening in vitro.

Keywords: micro-groove impedance sensor, 3D cell-based biosensors, 3D cell viability, micro-electromechanical systems

Procedia PDF Downloads 125

Authors: Kamonwat Suksumek, Seeronk Prichanont

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Access block refers to the situation where Emergency Department (ED) patients requiring hospital admission spend an unreasonable holding time in an ED because their access to a ward is blocked by the full utilization of the ward’s beds. Not only it delays the proper treatments required by the patients, but access block is also the cause of ED’s overcrowding. Clearly, access block is an inter-departmental problem that needs to be brought to management’s attention. This paper focuses on the analysis of strategies to address the access block problem, both in the operational and intermediate levels. These strategies were analyzed through a simulation model with a real data set from a university hospital in Thailand. The paper suggests suitable variable levels for each strategy so that the management will make the final decisions.

Keywords: access block, emergency department, health system analysis, simulation

Procedia PDF Downloads 403

Authors: Chin-Yuan Hsieh, Wei-Chun Lu, Yu-Hong Zeng

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The situation of a group of fish die is frequently found due to the fish disease caused by the deterioration of aquaculture water quality. The toxic ammonia is produced by animals as a byproduct of protein. The system is designed by the smart sensor technology and developed by the mathematical model to monitor the water parameters 24 hours a day and predict the relationship among twelve water quality parameters for monitoring the water quality in aquaculture. All data measured are stored in cloud server. In productive ponds, the daytime pH may be high enough to be lethal to the fish. The sudden change of the aquaculture conditions often results in the increase of PH value of water, lack of oxygen dissolving content, water quality deterioration and yield reduction. From the real measurement, the system can send the message to user’s smartphone successfully on the bad conditions of water quality. From the data comparisons between measurement and model simulation in fish aquaculture site, the difference of parameters is less than 2% and the correlation coefficient is at least 98.34%. The solubility rate of oxygen decreases exponentially with the elevation of water temperature. The correlation coefficient is 98.98%.

Keywords: aquaculture, sensor, ammonia, dissolved oxygen

Procedia PDF Downloads 274

Authors: Imen Boudali, Marwa Ragmoun

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The Vehicle Routing Problem with Hard Time Windows (VRPHTW) is a basic distribution management problem that models many real-world problems. The objective of the problem is to deliver a set of customers with known demands on minimum-cost vehicle routes while satisfying vehicle capacity and hard time windows for customers. In this paper, we propose to deal with our optimization problem by using a new hybrid stochastic algorithm based on two metaheuristics: Chemical Reaction Optimization (CRO) and Greedy Randomized Adaptive Search Procedure (GRASP). The first method is inspired by the natural process of chemical reactions enabling the transformation of unstable substances with excessive energy to stable ones. During this process, the molecules interact with each other through a series of elementary reactions to reach minimum energy for their existence. This property is embedded in CRO to solve the VRPHTW. In order to enhance the population diversity throughout the search process, we integrated the GRASP in our method. Simulation results on the base of Solomon’s benchmark instances show the very satisfactory performances of the proposed approach.

Keywords: Benchmark Problems, Combinatorial Optimization, Vehicle Routing Problem with Hard Time Windows, Meta-heuristics, Hybridization, GRASP, CRO

Procedia PDF Downloads 408

Authors: Javier Romera, Alberto Justo, Ignacio Fidalgo, Joshue Perez, Javier Araluce

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Nowadays, individuals with mobility needs face a significant challenge when docking vehicles. In many cases, after parking, they encounter insufficient space to exit, leading to two undesired outcomes: either avoiding parking in that spot or settling for improperly placed vehicles. To address this issue, the following paper presents a parking control system employing gestural teleoperation. The system comprises three main phases: capturing body markers, interpreting gestures, and transmitting orders to the vehicle. The initial phase is centered around the MediaPipe framework, a versatile tool optimized for real-time gesture recognition. MediaPipe excels at detecting and tracing body markers, with a special emphasis on hand gestures. Hands detection is done by generating 21 reference points for each hand. Subsequently, after data capture, the project employs the MultiPerceptron Layer (MPL) for indepth gesture classification. This tandem of MediaPipe's extraction prowess and MPL's analytical capability ensures that human gestures are translated into actionable commands with high precision. Furthermore, the system has been trained and validated within a built-in dataset. To prove the domain adaptation, a framework based on the Robot Operating System (ROS), as a communication backbone, alongside CARLA Simulator, is used. Following successful simulations, the system is transitioned to a real-world platform, marking a significant milestone in the project. This real vehicle implementation verifies the practicality and efficiency of the system beyond theoretical constructs.

Keywords: gesture detection, mediapipe, multiperceptron layer, robot operating system

Procedia PDF Downloads 91

Authors: Saeed Eskandari, Seyed Rasoul Mehdikhani

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Radiation sources have been used in many industries, such as gamma sources in medical imaging. These waves have destructive effects on humans and the environment. It is very important to detect and find the source of these waves because these sources cannot be seen by the eye. A portable robot has been designed and built with the purpose of revealing radiation sources that are able to scan the place from 5 to 20 meters away and shows the location of the sources according to the intensity of the waves on a two-dimensional digital image. The operation of the robot is done by measuring the pixels separately. By increasing the image measurement resolution, we will have a more accurate scan of the environment, and more points will be detected. But this causes a lot of time to be spent on scanning. In this paper, to overcome this challenge, we designed a method that can optimize this time. In this method, a small number of important points of the environment are measured. Hence the remaining pixels are predicted and estimated by regression algorithms in machine learning. The research method is based on comparing the actual values of all pixels. These steps have been repeated with several other radiation sources. The obtained results of the study show that the values estimated by the regression method are very close to the real values.

Keywords: regression, machine learning, scan radiation, robot

Procedia PDF Downloads 72

Authors: Zhe Li, Aihua Cai

Abstract:

Aiming at the problem of high-density clutter and interference affecting radar detection target track initiation in ECM and complex radar mission, the traditional radar target track initiation method has been difficult to adapt. To this end, we propose a multi-algorithm fusion learning track initiation algorithm, which transforms the track initiation problem into a true-false track discrimination problem, and designs an algorithm based on 1DCNN(One-Dimensional CNN)combined with Bi-LSTM (Bi-Directional Long Short-Term Memory )for fusion classification. The experimental dataset consists of real trajectories obtained from a certain type of three-coordinate radar measurements, and the experiments are compared with traditional trajectory initiation methods such as rule-based method, logical-based method and Hough-transform-based method. The simulation results show that the overall performance of the multi-algorithm fusion learning track initiation algorithm is significantly better than that of the traditional method, and the real track initiation rate can be effectively improved under high clutter density with the average initiation time similar to the logical method.

Keywords: track initiation, multi-algorithm fusion, 1DCNN, Bi-LSTM

Procedia PDF Downloads 73

Authors: Derkaoui Orkia, Lehireche Ahmed

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The topic of this article is to exploring the potentialities of a powerful optimization technique, namely Semidefinite Programming, for solving NP-hard problems. This approach provides tight relaxations of combinatorial and quadratic problems. In this work, we solve the maximum clique problem using this relaxation. The clique problem is the computational problem of finding cliques in a graph. It is widely acknowledged for its many applications in real-world problems. The numerical results show that it is possible to find a maximum clique in polynomial time, using an algorithm based on semidefinite programming. We implement a primal-dual interior points algorithm to solve this problem based on semidefinite programming. The semidefinite relaxation of this problem can be solved in polynomial time.

Keywords: semidefinite programming, maximum clique problem, primal-dual interior point method, relaxation

Procedia PDF Downloads 216

Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

Procedia PDF Downloads 67

Authors: Emad Alenany, M. Adel El-Baz

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In this paper, the flow of different classes of patients into a hospital is modelled and analyzed by using the queueing network analyzer (QNA) algorithm and discrete event simulation. Input data for QNA are the rate and variability parameters of the arrival and service times in addition to the number of servers in each facility. Patient flows mostly match real flow for a hospital in Egypt. Based on the analysis of the waiting times, two approaches are suggested for improving performance: Separating patients into service groups, and adopting different service policies for sequencing patients through hospital units. The separation of a specific group of patients, with higher performance target, to be served separately from the rest of patients requiring lower performance target, requires the same capacity while improves performance for the selected group of patients with higher target. Besides, it is shown that adopting the shortest processing time and shortest remaining processing time service policies among other tested policies would results in, respectively, 11.47% and 13.75% reduction in average waiting time relative to first come first served policy.

Keywords: queueing network, discrete-event simulation, health applications, SPT

Procedia PDF Downloads 182

Authors: Xiaoxian Zhang

Abstract:

Guidelines of ecological risk assessment (ERA) and food safety assessment (FSA) used nowadays, based on an S-shaped threshold dose-response curve (SDR), fail to consider hormesis, a reproducible biphasic dose-response model represented as a J-shaped or an inverted U-shaped curve, that occurs in the real-life environment across multitudinous compounds on cells, organisms, populations, and even the ecosystem. Specifically, in SDR-based ERA and FSA practice, predicted no effect concentration (PNEC) is calculated separately for individual substances from no observed effect concentration (NOEC, usually equivalent to 10% effect concentration (EC10) of a contaminant or food condiment) over an assessment coefficient that is bigger than 1. Experienced researchers doubted that hormesis in the real-life environment might lead to a waste of limited human and material resources in ERA and FSA practice, but related data are scarce. In this study, hormetic effects on bioluminescence of Aliivibrio fischeri (A. f) induced by sulfachloropyridazine (SCP) under 40 conditions to simulate the real-life scenario were investigated, and hormetic effects on growth of human MCF-7 cells caused by brown sugar and mascavado sugar were found likewise. After comparison of related parameters, it has for the first time been proved that there is a 50% probability for safe concentration (SC) of contaminants and food condiments to fall within the hormetic-stimulatory range (HSR) or left to HSR, revealing the unreliability of traditional parameters in standardized (eco)toxicological studies, and supporting qualitatively and quantitatively the over-strictness of ERA and FSA resulted from misuse of SDR. This study provides a novel perspective for ERA and FSA practitioners that hormesis should dominate and conditions where SDR works should only be singled out on a specific basis.

Keywords: dose-response relationship, food safety, ecological risk assessment, hormesis

Procedia PDF Downloads 137

Authors: Hongquan Zhang

Abstract:

Inspired by endogenous protein motors, researchers have constructed various synthetic DNA motors based on the specificity and predictability of Watson-Crick base pairing. However, the application of DNA motors to signal amplification and biosensing is limited because of low mobility and difficulty in real-time monitoring of the walking process. The objective of our work was to construct a new type of DNA motor termed target-triggered DNA motors that can walk for hundreds of steps in response to a single target binding event. To improve the mobility and processivity of DNA motors, we used gold nanoparticles (AuNPs) as scaffolds to build high-density, three-dimensional tracks. Hundreds of track strands are conjugated to a single AuNP. To enable DNA motors to respond to specific protein and nucleic acid targets, we adapted the binding-induced DNA assembly into the design of the target-triggered DNA motors. In response to the binding of specific target molecules, DNA motors are activated to autonomously walk along AuNP, which is powered by a nicking endonuclease or DNAzyme-catalyzed cleavage of track strands. Each moving step restores the fluorescence of a dye molecule, enabling monitoring of the operation of DNA motors in real time. The motors can translate a single binding event into the generation of hundreds of oligonucleotides from a single nanoparticle. The motors have been applied to amplify the detection of proteins and nucleic acids in test tubes and live cells. The motors were able to detect low pM concentrations of specific protein and nucleic acid targets in homogeneous solutions without the need for separation. Target-triggered DNA motors are significant for broadening applications of DNA motors to molecular sensing, cell imagining, molecular interaction monitoring, and controlled delivery and release of therapeutics.

Keywords: biosensing, DNA motors, gold nanoparticles, signal amplification

Procedia PDF Downloads 79

Authors: Seyedamir Makinejadsanij

Abstract:

One of the most important factors in the production of quality steel is to know the exact weight of steel in the steelmaking area. In this study, a calculation method is presented to estimate the exact weight of the melt as well as the objects transported by the overhead crane. Iran Alloy Steel Company's steelmaking area has three 90-ton cranes, which are responsible for transferring the ladles and ladle caps between 34 areas in the melt shop. Each crane is equipped with a Disomat Tersus weighing system that calculates and displays real-time weight. The moving object has a variable weight due to swinging, and the weighing system has an error of about +-5%. This means that when the object is moving by a crane, which weighs about 80 tons, the device (Disomat Tersus system) calculates about 4 tons more or 4 tons less, and this is the biggest problem in calculating a real weight. The k-means algorithm is an unsupervised clustering method that was used here. The best result was obtained by considering 3 centers. Compared to the normal average(one) or two, four, five, and six centers, the best answer is with 3 centers, which is logically due to the elimination of noise above and below the real weight. Every day, the standard weight is moved with working cranes to test and calibrate cranes. The results are shown that the accuracy is about 40 kilos per 60 tons (standard weight). As a result, with this method, the accuracy of moving weight is calculated as 99.95%. K-means is used to calculate the exact mean of objects. The stopping criterion of the algorithm is also the number of 1000 repetitions or not moving the points between the clusters. As a result of the implementation of this system, the crane operator does not stop while moving objects and continues his activity regardless of weight calculations. Also, production speed increased, and human error decreased.

Keywords: k-means, overhead crane, melt weight, weight estimation, swing problem

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Authors: Kohei Shimasaki, Tomoaki Okamura, Idaku Ishii

Abstract:

We propose a vibration imaging method for high frame rate (HFR)-video-based localization of vibrating objects with large translations. When the ratio of the translation speed of a target to its vibration frequency is large, obtaining its frequency response in image intensities becomes difficult because one or no waves are observable at the same pixel. Our method can precisely localize moving objects with vibration by virtually translating multiple image sequences for pixel-level short-time Fourier transform to observe multiple waves at the same pixel. The effectiveness of the proposed method is demonstrated by analyzing several HFR videos of flying insects in real scenarios.

Keywords: HFR video analysis, pixel-level vibration source localization, short-time Fourier transform, virtual translation

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Authors: Caroline Mendes, Mary McNamara, Orla Howe

Abstract:

Drug delivery systems are proposed for use in cancer treatment to specifically target cancer cells and deliver a therapeutic dose without affecting normal cells. For that purpose, the use of folate receptors (FR) can be considered a key strategy, since they are commonly over-expressed in cancer cells. In this study, cyclodextrins (CD) have being used as vehicles to target FR and deliver the chemotherapeutic drug, methotrexate (MTX). CDs have the ability to form inclusion complexes, in which molecules of suitable dimensions are included within their cavities. Here, β-CD has been modified using folic acid so as to specifically target the FR. Thus, this drug delivery system consists of β-CD, folic acid and MTX (CDEnFA:MTX). Cellular uptake of folic acid is mediated with high affinity by folate receptors while the cellular uptake of antifolates, such as MTX, is mediated with high affinity by the reduced folate carriers (RFCs). This study addresses the gene (mRNA) and protein expression levels of FRs and RFCs in the cancer cell lines CaCo-2, SKOV-3, HeLa, MCF-7, A549 and the normal cell line BEAS-2B, quantified by real-time polymerase chain reaction (real-time PCR) and flow cytometry, respectively. From that, four cell lines with different levels of FRs, were chosen for cytotoxicity assays of MTX and CDEnFA:MTX using the MTT assay. Real-time PCR and flow cytometry data demonstrated that all cell lines ubiquitously express moderate levels of RFC. These experiments have also shown that levels of FR protein in CaCo-2 cells are high, while levels in SKOV-3, HeLa and MCF-7 cells are moderate. A549 and BEAS-2B cells express low levels of FR protein. FRs are highly expressed in all the cancer cell lines analysed when compared to the normal cell line BEAS-2B. The cell lines CaCo-2, MCF-7, A549 and BEAS-2B were used in the cell viability assays. 48 hours treatment with the free drug and the complex resulted in IC50 values of 93.9 µM ± 15.2 and 56.0 µM ± 4.0 for CaCo-2 for free MTX and CDEnFA:MTX respectively, 118.2 µM ± 16.8 and 97.8 µM ± 12.3 for MCF-7, 36.4 µM ± 6.9 and 75.0 µM ± 10.5 for A549 and 132.6 µM ± 16.1 and 288.1 µM ± 26.3 for BEAS-2B. These results demonstrate that free MTX is more toxic towards cell lines expressing low levels of FR, such as the BEAS-2B. More importantly, these results demonstrate that the inclusion complex CDEnFA:MTX showed greater cytotoxicity than the free drug towards the high FR expressing CaCo-2 cells, indicating that it has potential to target this receptor, enhancing the specificity and the efficiency of the drug. The use of cell imaging by confocal microscopy has allowed visualisation of FR targeting in cancer cells, as well as the identification of the interlisation pathway of the drug. Hence, the cellular uptake and internalisation process of this drug delivery system is being addressed.

Keywords: cancer treatment, cyclodextrins, drug delivery, folate receptors, reduced folate carriers

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Authors: Jalil Boudjadar

Abstract:

Dynamic Voltage and Frequency Scaling (DVFS) multicore platforms are promising execution platforms that enable high computational performance, less energy consumption and flexibility in scheduling the system processes. However, the resulting interleaving and memory interference together with per-core frequency tuning make real-time guarantees hard to be delivered. Besides, energy consumption represents a strong constraint for the deployment of such systems on energy-limited settings. Identifying the system configurations that would achieve a high performance and consume less energy while guaranteeing the system schedulability is a complex task in the design of modern embedded systems. This work studies the trade-off between energy consumption, cores utilization and memory bottleneck and their impact on the schedulability of DVFS multicore time-critical systems with a hierarchy of shared memories. We build a model-based framework using Parametrized Timed Automata of UPPAAL to analyze the mutual impact of performance, energy consumption and schedulability of DVFS multicore systems, and demonstrate the trade-off on an actual case study.

Keywords: time-critical systems, multicore systems, schedulability analysis, energy consumption, performance analysis

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Authors: Sonam Behl, Raju, Ginu Rajan, Paul Farrar, B. Gangadhara Prusty

Abstract:

Reinforcing dental composites with micro-sized fibres can significantly improve the physio-mechanical properties of dental composites. The short fibres can be oriented randomly within dental composites, thus providing quasi-isotropic reinforcing efficiency unlike unidirectional/bidirectional fibre reinforced composites enhancing anisotropic properties. Thus, short fibres reinforced dental composites are getting popular among practitioners. However, despite their popularity, resin-based dental composites are prone to failure on account of shrinkage during photo polymerisation. The shrinkage in the structure may lead to marginal gap formation, causing secondary caries, thus ultimately inducing failure of the restoration. The traditional methods to evaluate polymerisation shrinkage using strain gauges, density-based measurements, dilatometer, or bonded-disk focuses on average value of volumetric shrinkage. Moreover, the results obtained from traditional methods are sensitive to the specimen geometry. The present research aims to evaluate the real-time shrinkage strain at selected locations in the material with the help of optical fibre Bragg grating (FBG) sensors. Due to the miniature size (diameter 250 µm) of FBG sensors, they can be easily embedded into small samples of dental composites. Furthermore, an FBG array into the system can map the real-time shrinkage strain at different regions of the composite. The evaluation of real-time monitoring of shrinkage values may help to optimise the physio-mechanical properties of composites. Previously, FBG sensors have been able to rightfully measure polymerisation strains of anisotropic (unidirectional or bidirectional) reinforced dental composites. However, very limited study exists to establish the validity of FBG based sensors to evaluate volumetric shrinkage for randomly oriented fibres reinforced composites. The present study aims to fill this research gap and is focussed on establishing the usage of FBG based sensors for evaluating the shrinkage of dental composites reinforced with randomly oriented fibres. Three groups of specimens were prepared by mixing the resin (80% UDMA/20% TEGDMA) with 55% of silane treated BaAlSiO₂ particulate fillers or by adding 5% of micro-sized fibres of diameter 5 µm, and length 250/350 µm along with 50% of silane treated BaAlSiO₂ particulate fillers into the resin. For measurement of polymerisation shrinkage strain, an array of three fibre Bragg grating sensors was embedded at a depth of 1 mm into a circular Teflon mould of diameter 15 mm and depth 2 mm. The results obtained are compared with the traditional method for evaluation of the volumetric shrinkage using density-based measurements. Degree of conversion was measured using FTIR spectroscopy (Spotlight 400 FT-IR from PerkinElmer). It is expected that the average polymerisation shrinkage strain values for dental composites reinforced with micro-sized fibres can directly correlate with the measured degree of conversion values, implying that more C=C double bond conversion to C-C single bond values also leads to higher shrinkage strain within the composite. Moreover, it could be established the photonics approach could help assess the shrinkage at any point of interest in the material, suggesting that fibre-Bragg grating sensors are a suitable means for measuring real-time polymerisation shrinkage strain for randomly fibre reinforced dental composites as well.

Keywords: dental composite, glass fibre, polymerisation shrinkage strain, fibre-Bragg grating sensors

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