Search results for: graphics processing units

Authors: Amirhossein Khazali, Mohsen Kalantar

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Energy storage units can play an important role to provide an economic and secure operation of future energy systems. In this paper, a stochastic energy and reserve market clearing scheme is presented considering storage energy units. The approach is proposed to deal with stochastic and non-dispatchable renewable sources with a high level of penetration in the energy system. A two stage stochastic programming scheme is formulated where in the first stage the energy market is cleared according to the forecasted amount of wind generation and demands and in the second stage the real time market is solved according to the assumed scenarios.

Keywords: energy and reserve market, energy storage device, stochastic programming, wind generation

Procedia PDF Downloads 574

Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

Procedia PDF Downloads 57

Authors: Yasser F. Hassan

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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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Authors: Muhammet Dursun Kaya, Hasan Asil

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In recent years, different methods have been proposed to optimize question processing in database. Although different methods have been proposed to optimize the query, but the problem which exists here is that most of these methods destroy the query execution plan after executing the query. This research attempts to solve the above problem by using a combination of methods of communicating with the database (the present questions in the programming code and using store procedures) and making query processing adaptive in database, and proposing a new approach for optimization of query processing by introducing the idea of dynamic store procedures. This research creates dynamic store procedures in the database according to the proposed algorithm. This method has been tested on applied software and results shows a significant improvement in reducing the query processing time and also reducing the workload of DBMS. Other advantages of this algorithm include: making the programming environment a single environment, eliminating the parametric limitations of the stored procedures in the database, making the stored procedures in the database dynamic, etc.

Keywords: relational database, agent, query processing, adaptable, communication with the database

Procedia PDF Downloads 371

Authors: Reza Rezaeipour Honarmandzad

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Wavelet analysis is an exciting method for solving difficult problems in mathematics, physics, and engineering, with modern applications as diverse as wave propagation, data compression, signal processing, image processing, pattern recognition, etc. Wavelets allow complex information such as signals, images and patterns to be decomposed into elementary forms at different positions and scales and subsequently reconstructed with high precision. In this paper a wavelet-based signal processing algorithm for airplane cable fault location is proposed. An orthogonal discrete wavelet decomposition and reconstruction algorithm is used to eliminate the noise in the aircraft cable fault signal. The experiment result has shown that the character of emission pulse and reflect pulse used to test the aircraft cable fault point are reserved and the high-frequency noise are eliminated by means of the proposed algorithm in this paper.

Keywords: wavelet analysis, signal processing, orthogonal discrete wavelet, noise, aircraft cable fault signal

Procedia PDF Downloads 524

Authors: P. Tanuska, A. Elias, P. Vazan, B. Zahradnikova

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This article describes the information system for measuring and evaluating the dose rate in the environment of nuclear power plants Mochovce and Bohunice in Slovakia. The article presents the results achieved in the implementation of the EU project–Research of monitoring and evaluation of non-standard conditions in the area of nuclear power plants. The objectives included improving the system of acquisition, measuring and evaluating data with mobile and autonomous units applying new knowledge from research. The article provides basic and specific features of the system and compared to the previous version of the system, also new functions.

Keywords: information system, dose rate, mobile devices, nuclear power plant

Procedia PDF Downloads 376

Authors: Robson da C. Santos, Carlos Henrique de A. S. P. Coutinho, Lucas Moreira Dias, Gerson Gomes Cunha

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The article refers to the development of an augmented reality 3D display, through the control of servo motors and projection of image with aid of video projector on the model. Augmented Reality is a branch that explores multiple approaches to increase real-world view by viewing additional information along with the real scene. The article presents the broad use of electrical, electronic, mechanical and industrial automation for geospatial visualizations, applications in mathematical models with the visualization of functions and 3D surface graphics and volumetric rendering that are currently seen in 2D layers. Application as a 3D display for representation and visualization of Digital Terrain Model (DTM) and Digital Surface Models (DSM), where it can be applied in the identification of canyons in the marine area of the Campos Basin, Rio de Janeiro, Brazil. The same can execute visualization of regions subject to landslides, as in Serra do Mar - Agra dos Reis and Serranas cities both in the State of Rio de Janeiro. From the foregoing, loss of human life and leakage of oil from pipelines buried in these regions may be anticipated in advance. The physical design consists of a table consisting of a 9 x 16 matrix of servo motors, totalizing 144 servos, a mesh is used on the servo motors for visualization of the models projected by a retro projector. Each model for by an image pre-processing, is sent to a server to be converted and viewed from a software developed in C # Programming Language.

Keywords: visualization, 3D models, servo motors, C# programming language

Procedia PDF Downloads 342

Authors: Gülcan Taşkıran, Ayla Bayık Temel

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Background: Florence Nightingale, the modern founder of the nursing, is most famous for her role as a nurse. But not so much known about her contributions as a mathematician and statistician. Aim: In this conceptual article it is aimed to examine Florence Nightingale's statistics education, how she used her passion for statistics and applied statistical data in nursing care and her scientific contributions to statistical science. Design: Literature review method was used in the study. The databases of Istanbul University Library Search Engine, Turkish Medical Directory, Thesis Scanning Center of Higher Education Council, PubMed, Google Scholar, EBSCO Host, Web of Science were scanned to reach the studies. The keywords 'statistics' and 'Florence Nightingale' have been used in Turkish and English while being screened. As a result of the screening, totally 41 studies were examined from the national and international literature. Results: Florence Nightingale has interested in mathematics and statistics at her early ages and has received various training in these subjects. Lessons learned by Nightingale in a cultured family environment, her talent in mathematics and numbers, and her religious beliefs played a crucial role in the direction of the statistics. She was influenced by Quetelet's ideas in the formation of the statistical philosophy and received support from William Farr in her statistical studies. During the Crimean War, she applied statistical knowledge to nursing care, developed many statistical methods and graphics, so that she made revolutionary reforms in the health field. Conclusions: Nightingale's interest in statistics, her broad vision, the statistical ideas fused with religious beliefs, the innovative graphics she has developed and the extraordinary statistical projects that she carried out has been influential on the basis of her professional achievements. Florence Nightingale has also become a model for women in statistics. Today, using and teaching of statistics and research in nursing care practices and education programs continues with the light she gave.

Keywords: Crimean war, Florence Nightingale, nursing, statistics

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Authors: Dipankar Deka

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Exploration and production of Oil & Gas is a very challenging business on which a nation’s energy security depends on. The exploration and Production of hydrocarbon is a very precise and time-bound process. The striking rate of hydrocarbon in a drilled well is so uncertain that the success rate is only 31% in 2021 as per Rigzone. Huge cost is involved in drilling as well as the production of hydrocarbon from a well. Due to this very reason, no one can effort to lose a well because of faulty machines, which increases the non-productive time (NPT). Numerous activities that include manpower and machines synchronized together works in a precise way to complete the full cycle of exploration, rig movement, drilling and production of crude oil. There are several machines, both fixed and mobile, are used in the complete cycle. Most of these machines have a tight schedule of work operating in various drilling sites that are simultaneously being drilled, providing a very narrow window for maintenance. The shutdown of any of these machines for even a small period of time delays the whole project and increases the cost of production of hydrocarbon by manifolds. Moreover, these machines are custom designed exclusively for oil field operations to be only used in Mining Exploration Licensed area (MEL) earmarked by the government and are imported and very costly in nature. The cost of some of these mobile units like Well Logging Units, Coil Tubing units, Nitrogen pumping units etc. that are used for Well stimulation and activation process exceeds more than 1 million USD per unit. So the increase of self-life of these units also generates huge revenues during the extended duration of their services. In this paper we are considering the very critical mobile oil field equipment like Well Logging Unit, Coil Tubing unit, well-killing unit, Nitrogen pumping unit, MOL Oil Field Truck, Hot Oil Circulation Unit etc., and their extensive preventive maintenance in our auto workshop. This paper is the outcome of 10 years of structured automobile maintenance and minute documentation of each associated event that allowed us to perform the comparative study between the new practices of preventive maintenance over the age-old practice of system-based corrective maintenance and its impact on the self-life of the equipment.

Keywords: automobile maintenance, preventive maintenance, symptom based maintenance, workshop technologies

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Authors: Eiko Takaoka, Yoshiyuki Fukushima, Koichiro Hirose, Tadashi Hasegawa

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Although all high school students in Japan are required to learn informatics, many of them do not learn this topic sufficiently. In response to this situation, we propose a support package for high school informatics classes. To examine what students learned and if they sufficiently understood the context of the lessons, a questionnaire survey was distributed to 186 students. We analyzed the results of the questionnaire and determined the weakest units, which were “basic computer configuration” and “memory and secondary storage”. We then developed a package for teaching these units. We propose that our package be applied in high school classrooms.

Keywords: computer science unplugged, computer science outreach, high school curriculum, experimental evaluation

Procedia PDF Downloads 387

Authors: M. Kustyawati, F. Pratama, D. Saputra, A. Wijaya

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Tempe composes of not only molds but also bacteria and yeasts. The structure of microorganisms needs to be in balance number in order the tempe to be an acceptable quality for an extended time. Sub supercritical carbon dioxide can be a promising preservation method for tempe as it induces microbial inactivation avoiding alterations of its quality attributes. Fresh tempe were processed using supercritical and sub supercritical CO2 for a defined holding times, then the growth ability of molds and bacteria were analyzed. The results showed that the supercritical CO2 processing for 5 minutes reduced the number of bacteria and molds to 0.30 log cycle and 1.17 log cycles, respectively. In addition, sub supercritical CO2 processing for 20 minutes had fungicidal effect against mold tempe; whereas, the sub supercritical CO2 for 10 minutes had reducing effect against bacteria tempe, and had fungistatic affect against mold tempe. It suggested that sub-supercritical CO2 processing for 10 min could be useful alternative technique for preservation of tempe.

Keywords: tempe, sub supercritical CO2, fungistatic effect, preservation

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Authors: Robel Habtemariam

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Globally, wind energy and photovoltaics (PV) solar energy are among the leading renewable energy sources (RES) in terms of installed capacity. In order to increase the contribution of RES to the power supply system, large scale energy integration is required, mainly due to wind energy and PV. In this paper, an investigation has been made on the electrical power supply systems of Taiwan and Greece in order to integrate high level of wind and photovoltaic (PV) to increase the penetration of renewable energy resources. Currently, both countries heavily depend on fossil fuels to meet the demand and to generate adequate electricity. Therefore, this study is carried out to look into the two cases power supply system by developing a methodology that includes major power units. To address the analysis, an approach for simulation of power systems is formulated and applied. The simulation is based on the non-dynamic analysis of the electrical system. This simulation results in calculating the energy contribution of different types of power units; namely the wind, PV, non-flexible and flexible power units. The calculation is done for three different scenarios (2020, 2030, & 2050), where the first two scenarios are based on national targets and scenario 2050 is a reflection of ambitious global targets. By 2030 in Taiwan, the input of the power units is evaluated as 4.3% (wind), 3.7% (PV), 65.2 (non-flexible), 25.3% (flexible), and 1.5% belongs to hydropower plants. In Greece, much higher renewable energy contribution is observed for the same scenario with 21.7% (wind), 14.3% (PV), 38.7% (non-flexible), 14.9% (flexible), and 10.3% (hydro). Moreover, it examines the ability of the power systems to deal with the variable nature of the wind and PV generation. For this reason, an investigation has also been done on the use of the combined wind power with pumped storage systems (WPS) to enable the system to exploit the curtailed wind energy & surplus PV and thus increase the wind and PV installed capacity and replace the peak supply by conventional power units. Results show that the feasibility of pumped storage can be justified in the high scenario (that is the scenario of 2050) of RES integration especially in the case of Greece.

Keywords: large scale energy integration, photovoltaics solar energy, pumped storage systems, renewable energy sources

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Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

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Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

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Authors: Iqbal Felani

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A Coal-Fired Power Plant has some integrated facilities to handle coal from three separated coal yards to eight units power plant’s bunker. But nowadays the facilities are not reliable enough for supporting the system. Management planned to invest some facilities to increase the reliability. They also had a plan to make single spesification of coal used all of the units, called Single Quality Coal (SQC). This simulation would compare before and after improvement with two scenarios i.e First In First Out (FIFO) and Last In First Out (LIFO). Some parameters like stay time, reorder point and safety stock is determined by the simulation. Discrete event simulation based software, Flexsim 5.0, is used to help the simulation. Based on the simulation, Single Quality Coal with FIFO scenario has the shortest staytime with 8.38 days.

Keywords: Coal Yard Management, Discrete event simulation First In First Out, Last In First Out.

Procedia PDF Downloads 671

Authors: Kasidis Chomrat, Nopasit Chakpitak, Anukul Tamprasirt, Annop Thananchana

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Internet of Things devices or IoT and Edge Computing has become one of the biggest things happening in innovations and one of the most discussed of the potential to improve and disrupt traditional business and industry alike. With rises of new hang cliff challenges like COVID-19 pandemic that posed a danger to workforce and business process of the system. Along with drastically changing landscape in business that left ruined aftermath of global COVID-19 pandemic, looming with the threat of global energy crisis, global warming, more heating global politic that posed a threat to become new Cold War. How emerging technology like edge computing and usage of specialized design visual processing units will be great opportunities for business. The literature reviewed on how the internet of things and disruptive wave will affect business, which explains is how all these new events is an effect on the current business and how would the business need to be adapting to change in the market and world, and example test benchmarking for consumer marketed of newer devices like the internet of things devices equipped with new edge computing devices will be increase efficiency and reducing posing a risk from a current and looming crisis. Throughout the whole paper, we will explain the technologies that lead the present technologies and the current situation why these technologies will be innovations that change the traditional practice through brief introductions to the technologies such as cloud computing, edge computing, Internet of Things and how it will be leading into future.

Keywords: internet of things, edge computing, machine learning, pattern recognition, image classification

Procedia PDF Downloads 155

Authors: Y. Zhang, J. Perez, S. Marnier

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To date, no study on goaltending butterfly motion has been completed in real conditions, during an ice hockey game or training practice, to the author's best knowledge. This motion, performed to save score, is unnatural, intense, and repeated. The target of this research activity is to identify representative biomechanical criteria for this goaltender-specific movement pattern. Determining specific physical parameters may allow to will identify the risk of hip and groin injuries sustained by goaltenders. Four professional or academic goalies were instrumented during ice hockey training practices with five inertial measurement units. These devices were inserted in dedicated pockets located on each thigh and shank, and the fifth on the lumbar spine. A camera was also installed close to the ice to observe and record the goaltenders' activities, especially the butterfly motions, in order to synchronize the captured data and the behavior of the goaltender. Each data recorded began with a calibration of the inertial units and a calibration of the fully equipped goaltender on the ice. Three butterfly motions were recorded out of the training practice to define referential individual butterfly motions. Then, a data processing algorithm based on the Madgwick filter computed hip and knee joints joint range of motion as well as angular specific angular velocities. The developed algorithm software automatically identified and analyzed all the butterfly motions executed by the four different goaltenders. To date, it is still too early to show that the analyzed criteria are representative of the trauma generated by the butterfly motion as the research is only at its beginning. However, this descriptive research activity is promising in its ecological assessment, and once the criteria are found, the tools and protocols defined will allow the prevention of as many injuries as possible. It will thus be possible to build a specific training program for each goalie.

Keywords: biomechanics, butterfly motion, human motion analysis, ice hockey, inertial measurement unit

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Authors: Mehmet Savsar

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Several factors affect productivity of Food Processing Assembly Lines (FPAL). Engineers and line managers usually do not recognize some of these factors and underutilize their production/assembly lines. In this paper, a special food processing assembly line is studied in detail, and procedures are presented to illustrate how productivity and efficiency of such lines can be increased. The assembly line considered produces ten different types of freshly prepared salads on the same line, which is called mixed model assembly line. Problems causing delays and inefficiencies on the line are identified. Line balancing and related tools are used to increase line efficiency and minimize balance delays. The procedure and the approach utilized in this paper can be useful for the operation managers and industrial engineers dealing with similar assembly lines in food processing industry.

Keywords: assembly lines, line balancing, production efficiency, bottleneck

Procedia PDF Downloads 388

Authors: Ayman Mutahar Alrassas, Shaoran Ren, Renyuan Ren, Hung Vo Thanh, Mohammed Hail Hakimi, Zhenliang Guan

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The significant effect of CO₂ on global climate and the environment has gained more concern worldwide. Enhance oil recovery (EOR) associated with sequestration of CO₂ particularly into the depleted oil reservoir is considered the viable approach under financial limitations since it improves the oil recovery from the existing oil reservoir and boosts the relation between global-scale of CO₂ capture and geological sequestration. Consequently, practical measurements are required to attain large-scale CO₂ emission reduction. This paper presents an integrated modeling workflow to construct an accurate 3D reservoir geological model to estimate the storage capacity of CO₂ under geological uncertainty in an unconventional oil reservoir of the Paleogene Shahejie Formation (Es1) in the block Nv32, Shenvsi oilfield, China. In this regard, geophysical data, including well logs of twenty-two well locations and seismic data, were combined with geological and engineering data and used to construct a 3D reservoir geological modeling. The geological modeling focused on four tight reservoir units of the Shahejie Formation (Es1-x1, Es1-x2, Es1-x3, and Es1-x4). The validated 3D reservoir models were subsequently used to calculate the theoretical CO₂ storage capacity in the block Nv32, Shenvsi oilfield. Well logs were utilized to predict petrophysical properties such as porosity and permeability, and lithofacies and indicate that the Es1 reservoir units are mainly sandstone, shale, and limestone with a proportion of 38.09%, 32.42%, and 29.49, respectively. Well log-based petrophysical results also show that the Es1 reservoir units generally exhibit 2–36% porosity, 0.017 mD to 974.8 mD permeability, and moderate to good net to gross ratios. These estimated values of porosity, permeability, lithofacies, and net to gross were up-scaled and distributed laterally using Sequential Gaussian Simulation (SGS) and Simulation Sequential Indicator (SIS) methods to generate 3D reservoir geological models. The reservoir geological models show there are lateral heterogeneities of the reservoir properties and lithofacies, and the best reservoir rocks exist in the Es1-x4, Es1-x3, and Es1-x2 units, respectively. In addition, the reservoir volumetric of the Es1 units in block Nv32 was also estimated based on the petrophysical property models and fund to be between 0.554368

Keywords: CO₂ storage capacity, 3D geological model, geological uncertainty, unconventional oil reservoir, block Nv32

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Authors: Jianghao Hu, Hongyu Wang

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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

Procedia PDF Downloads 154

Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

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Real-time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Therefore, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Canny edge detection is one of the common blocks in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: high level synthesis, canny edge detection, hardware accelerators, computer vision

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Authors: Antonyous Fawzy Boshra Girgis

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Nutrition labels are diet-related health policies. They help individuals improve food-choice decisions and reduce intake of calories and unhealthy food elements, like cholesterol. However, many individuals do not pay attention to nutrition labels or fail to appropriately understand them. According to the literature, thinking and cognitive styles can have significant effects on attention to nutrition labels. According to the author's knowledge, the effect of global/local processing on attention to nutrition labels has not been previously studied. Global/local processing encourages individuals to attend to the whole/specific parts of an object and can have a significant impact on people's visual attention. In this study, this effect was examined with an experimental design using the eye-tracking technique. The research hypothesis was that individuals with local processing would pay more attention to nutrition labels, including nutrition tables and traffic lights. An experiment was designed with two conditions: global and local information processing. Forty participants were randomly assigned to either global or local conditions, and their processing style was manipulated accordingly. Results supported the hypothesis for nutrition tables but not for traffic lights.

Keywords: nutrition, public health, SA Harvest, foodeye-tracking, nutrition labelling, global/local information processing, individual differencesmobile computing, cloud computing, nutrition label use, nutrition management, barcode scanning

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Authors: Khaled M. Alhawiti

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This paper investigates the future of medicine and the use of Natural language processing. The importance of having correct clinical information available online is remarkable; improving patient care at affordable costs could be achieved using automated applications to use the online clinical information. The major challenge towards the retrieval of such vital information is to have it appropriately coded. Majority of the online patient reports are not found to be coded and not accessible as its recorded in natural language text. The use of Natural Language processing provides a feasible solution by retrieving and organizing clinical information, available in text and transforming clinical data that is available for use. Systems used in NLP are rather complex to construct, as they entail considerable knowledge, however significant development has been made. Newly formed NLP systems have been tested and have established performance that is promising and considered as practical clinical applications.

Keywords: clinical information, information retrieval, natural language processing, automated applications

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Authors: O. Maklouf, Ahmed Abdulla

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A general decline in the cost, size, and power requirements of electronics is accelerating the adoption of integrated GPS/INS technologies in consumer applications such Land Vehicle Navigation. Researchers are looking for ways to eliminate additional components from product designs. One possibility is to drop one or more of the relatively expensive gyroscopes from microelectromechanical system (MEMS) versions of inertial measurement units (IMUs). For land vehicular use, the most important gyroscope is the vertical gyro that senses the heading of the vehicle and two horizontal accelerometers for determining the velocity of the vehicle. This paper presents a simplified integration algorithm for strap down (ParIMU)\GPS combination, with data post processing for the determination of 2-D components of position (trajectory), velocity and heading. In the present approach we have neglected earth rotation and gravity variations, because of the poor gyroscope sensitivities of the low-cost IMU and because of the relatively small area of the trajectory.

Keywords: GPS, ParIMU, INS, Kalman filter

Procedia PDF Downloads 516

Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh

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Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.

Keywords: Malmquist Index, Grey's Theory, CCR Model, network data envelopment analysis, Iran electricity power chain

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Authors: Ram Mohan, Richard Haney, Ajit Kelkar

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Current developments in computing have shown the advantage of using one or more Graphic Processing Units (GPU) to boost the performance of many computationally intensive applications but there are still limits to these GPU-enhanced systems. The major factors that contribute to the limitations of GPU(s) for High Performance Computing (HPC) can be categorized as hardware and software oriented in nature. Understanding how these factors affect performance is essential to develop efficient and robust applications codes that employ one or more GPU devices as powerful co-processors for HPC computational modeling. This research and technical presentation will focus on the analysis and understanding of the intrinsic interrelationship of both hardware and software categories on computational performance for single and multiple GPU-enhanced systems using a computationally intensive application that is representative of a large portion of challenges confronting modern HPC. The representative application uses unstructured finite element computations for transient composite resin infusion process flow modeling as the computational core, characteristics and results of which reflect many other HPC applications via the sparse matrix system used for the solution of linear system of equations. This work describes these various software and hardware factors and how they interact to affect performance of computationally intensive applications enabling more efficient development and porting of High Performance Computing applications that includes current, legacy, and future large scale computational modeling applications in various engineering and scientific disciplines.

Keywords: graphical processing unit, software development and engineering, performance analysis, system architecture and software performance

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Authors: Fatima El Kandoussi, Lamiae El Hdiddioui, Mustapha Bouragba

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The woodwork of thuja in Essaouira is one of the main crafts in Morocco. Certainly, marquetry reflects both cultural and artistic identity of the city, considering the talent and ancestral knowledge of craftsman working in marquetry. Yet, the production units encounter a considerable number of difficulties among which insufficiencies within marketing practices. Consequently, it is obvious that major improvements are needed, and supportive solutions must be provided in order to improve the Essaouira’s marquetry, as a symbol of the entire province. Thus, the establishment of Thuja Label is a necessary measure that would be the key to ensuring sustainability of this vital craft. The main purpose of this paper is to study marketing practices’ current state of the production units in the marquetry of Essaouira, therefore to recommend remedial actions likely to raise them up to the required functional level.

Keywords: craft, marketing practices, marquetry, thuja label

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Authors: Sanjay Singh, Sushil Kumar, Rashmi Jain

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Quantum registering is another pattern in computational hypothesis and a quantum mechanical framework has a few helpful properties like Entanglement. We plan to store data concerning the structure and substance of a basic picture in a quantum framework. Consider a variety of n qubits which we propose to use as our memory stockpiling. In recent years classical processing is switched to quantum image processing. Quantum image processing is an elegant approach to overcome the problems of its classical counter parts. Image storage, retrieval and its processing on quantum machines is an emerging area. Although quantum machines do not exist in physical reality but theoretical algorithms developed based on quantum entangled states gives new insights to process the classical images in quantum domain. Here in the present work, we give the brief overview, such that how entangled states can be useful for quantum image storage and retrieval. We discuss the properties of tripartite Greenberger-Horne-Zeilinger and W states and their usefulness to store the shapes which may consist three vertices. We also propose the techniques to store shapes having more than three vertices.

Keywords: Greenberger-Horne-Zeilinger, image storage and retrieval, quantum entanglement, W states

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Authors: Dong Liu

Abstract:

By sending a high-frequency probe wave and a low-frequency pump wave to a specimen, the vibroacoustic method evaluates the defect’s severity according to the modulation index of the received signal. Many studies experimentally proved the significant sensitivity of the modulation index to the tiny contact type defect. However, it has also been found that the modulation index was highly affected by the frequency of probe or pump waves. Therefore, the chirp signal has been introduced to the VAM method since it can assess multiple frequencies in a relatively short time duration, so the robustness of the VAM method could be enhanced. Consequently, the signal processing method needs to be modified accordingly. Various studies utilized different algorithms or combinations of algorithms for processing the VAM signal method by chirp excitation. These signal process methods were compared and used for processing a VAM signal acquired from the steel samples.

Keywords: vibroacoustic modulation, nonlinear acoustic modulation, nonlinear acoustic NDT&E, signal processing, structural health monitoring

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Authors: Michael Gidey Gebru

Abstract:

Most DEA models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp DEA into DEA with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the DEA model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units’ efficiency. Finally, the developed DEA model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, DEA, fuzzy, decision making units, higher education institutions

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Authors: Adriana Haulica

Abstract:

Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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