Search results for: target efficiency

Authors: Houxiang Zhu, Chun Liang

Abstract:

The CRISPR-Cpf1 system has been successfully applied in genome editing. However, target efficiency of the CRISPR-Cpf1 system varies among different gRNA sequences. The published CRISPR-Cpf1 gRNA data was reanalyzed. Many sequences and structural features of gRNAs (e.g., the position-specific nucleotide composition, position-nonspecific nucleotide composition, GC content, minimum free energy, and melting temperature) correlated with target efficiency were found. Using machine learning technology, a support vector machine (SVM) model was created to predict target efficiency for any given gRNAs. The first web service application, CRISPR-DT (CRISPR DNA Targeting), has been developed to help users design optimal gRNAs for the CRISPR-Cpf1 system by considering both target efficiency and specificity. CRISPR-DT will empower researchers in genome editing.

Keywords: CRISPR-Cpf1, genome editing, target efficiency, target specificity

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Authors: Emanuele Peggi

Abstract:

The regulation of competitive takeover bids is one of the most problematic issues of any legislation on takeovers since it concerns a particular type of market, that of corporate control, whose peculiar characteristic is that companies represent "assets" unique of their kind, for each of which there will be a relevant market characterized by the presence of different subjects interested in acquiring control. Firstly, this work aims to analyze, from a comparative point of view, the regulation of takeover bids in competitive scenarios, characterized by the presence of multiple takeover bids for the same target company, and contribute to the debate on the impact that various solutions adopted in some legal systems examined (Italy, UK, and USA) have had on the efficiency of the market for corporate control. Secondly, the different auction models identified by the economic literature and their possible applications to corporate acquisitions in competitive scenarios will be examined, as well as the consequences that the application of each of them causes on the efficiency of the market for corporate control and the interests of the target shareholders. The scope is to study the possibility of attributing to the management of the target company the power to design the auction in order to better protect the interests of shareholders through the adoption of ad hoc models according to the specific context. and in particular on the ground of their assessment of the buyer's risk profile.

Keywords: takeovers, auction theory, shareholders, target company

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Authors: Abdullah Erden, Filiz Erden

Abstract:

In the present information society era, a change is seen in every field together with changing technology. Along with this change, importance given to information and human who is the producer of information increased. Work life and working conditions included in these changes have also been affected. The most important factors that disturb employees in offices are lighting, ventilation, noise and office furniture. Upon arrangement of these according to ergonomic principles, performance and efficiency of employees will increase. Fatigue and stress resulting from office environment are harmful for employees. Attention and efficiency of employee who feels bad will decrease. It should be noted that office employees are human and affected from environment. It should be allowed them to work in comfortable, healthy and peaceful environment. As a result, efficiency will increase and target will be reached. In this study, it has been focused on basic concepts such as office management and efficiency, effects of ergonomics on office efficiency has been examined. Also, a place is given to the factors affecting operational efficiency and effects of physical environment on employees.

Keywords: ergonomics, efficiency, office design, office

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

Abstract:

During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving the army, moving convoys etc. The radar operator selects one of the promising targets into single target tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper, we present a technique using mathematical and statistical methods like fast fourier transformation (FFT) and principal component analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, FFT, principal component analysis, eigenvector, octave-notes, DSP

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Authors: Khanh D.Do, Loi V.Nguyen, Thanh N.Nguyen, Thang M.Nguyen, Vu T.Tran

Abstract:

Along with the development of Secondary surveillance radar (SSR) in air traffic surveillance systems, the Multipath phenomena has always been a noticeable problem. This following article discusses the geometrical aspect and power aspect of the Multipath interference caused by reflection in SSR and proposes a method to deal with these unwanted multipath targets (ghosts) by false-target position predicting and adaptive target suppressing. A field-experiment example is mentioned at the end of the article to demonstrate the efficiency of this measure.

Keywords: multipath, secondary surveillance radar, digital signal processing, reflection

Procedia PDF Downloads 117

Authors: G. C. Tikkiwal, Mukesh Upadhyay

Abstract:

During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving army, moving convoys etc. The Radar operator selects one of the promising targets into Single Target Tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper we present a technique using mathematical and statistical methods like Fast Fourier Transformation (FFT) and Principal Component Analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, fft, principal component analysis, eigenvector, octave-notes, dsp

Procedia PDF Downloads 319

Authors: Khomkrit Mongkhuntod, Chatchawal Chaichana, Atipoang Nuntaphan

Abstract:

Feed Water Heater is the important equipment for thermal power plant. The heating temperature from feed heating process is an impact to power plant efficiency or heat rate. Normally, the degradation of feed water heater that operated for a long time is effect to decrease plant efficiency or increase plant heat rate. For Mae Moh power plant, each unit operated more than 20 years. The degradation of the main equipment is effect of planting efficiency or heat rate. From the efficiency and heat rate analysis, Mae Moh power plant operated in high heat rate more than the commissioning period. Some of the equipment were replaced for improving plant efficiency and plant heat rates such as HP turbine and LP turbine that the result is increased plant efficiency by 5% and decrease plant heat rate by 1%. For the target of power generation plan that Mae Moh power plant must be operated more than 10 years. These work is focus on thermal efficiency analysis of feed water heater to compare with the commissioning data for find the way to improve the feed water heater efficiency that may effect to increase plant efficiency or decrease plant heat rate by use heat balance model simulation and economic value add (EVA) method to study the investment for replacing the new feed water heater and analyze how this project can stay above the break-even point to make the project decision.

Keywords: feed water heater, power plant efficiency, plant heat rate, thermal efficiency analysis

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Authors: Mahbube Eghtesad

Abstract:

For a number of years, the problem of simultaneous detection and tracking of a target has been one of the most relevant and challenging issues in a wide variety of military and civilian systems. We develop methods for detecting and tracking a target using an orthogonal frequency division multiplexing (OFDM) based radar. As a preliminary step we introduce the target trajectory and Gaussian noise model in discrete time form. Then resorting to match filter and Kalman filter we derive a detector and target tracker. After that we propose an OFDM radar in order to achieve further improvement in tracking performance. The motivation for employing multiple frequencies is that the different scattering centers of a target resonate differently at each frequency. Numerical examples illustrate our analytical results, demonstrating the achieved performance improvement due to the OFDM signaling method.

Keywords: matched filter, target trashing, OFDM radar, Kalman filter

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Authors: Yawen Wang, Hongchang Chen, Shaomei Li, Chao Gao, Jiangpeng Zhang

Abstract:

As the main challenge for target tracking is accounting for target scale change and real-time, we combine Mean-Shift and PCA-SIFT algorithm together to solve the problem. We introduce similarity comparison method to determine how the target scale changes, and taking different strategies according to different situation. For target scale getting larger will cause location error, we employ backward tracking to reduce the error. Mean-Shift algorithm has poor performance when tracking scale-changing target due to the fixed bandwidth of its kernel function. In order to overcome this problem, we introduce PCA-SIFT matching. Through key point matching between target and template, that adjusting the scale of tracking window adaptively can be achieved. Because this algorithm is sensitive to wrong match, we introduce RANSAC to reduce mismatch as far as possible. Furthermore target relocating will trigger when number of match is too small. In addition we take comprehensive consideration about target deformation and error accumulation to put forward a new template update method. Experiments on five image sequences and comparison with 6 kinds of other algorithm demonstrate favorable performance of the proposed tracking algorithm.

Keywords: target tracking, PCA-SIFT, mean-shift, scale-adaptive

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Authors: Mahboobeh Eghtesad, Reza Mohseni

Abstract:

We develop methods for detecting a target for orthogonal frequency division multiplexing (OFDM) based radars. As a preliminary step we introduce the target and Gaussian noise models in discrete–time form. Then, resorting to match filter (MF) we derive a detector for two different scenarios: a non-fluctuating target and a Rayleigh fluctuating target. It will be shown that a MF is not suitable for Rayleigh fluctuating targets. In this paper we propose a reduced-complexity method based on fast Fourier transfrom (FFT) for such a situation. The proposed method has better detection performance.

Keywords: constant false alarm rate (CFAR), match filter (MF), fast Fourier transform (FFT), OFDM radars, Rayleigh fluctuating target

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Authors: S. Kreitlein, N. Eder, J. Franke

Abstract:

The importance of energy efficiency within the production process increases steadily. Unfortunately, so far no tools for a comprehensive assessment of energy efficiency within the production process exist. Therefore the Institute for Factory Automation and Production Systems of the Friedrich-Alexander-University Erlangen-Nuremberg has developed two methods with the goal of achieving transparency and a quantitative assessment of energy efficiency: EEV (Energy Efficiency Value) and EPE (Energetic Process Efficiency). This paper describes the basics and state of the art as well as the developed approaches.

Keywords: energy efficiency, energy efficiency value, energetic process efficiency, production

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Authors: Davood Rajabi, Mojgan Yazdani

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Non-linear Muskingum model is an efficient method for flood routing, however, the efficiency of this method is influenced by three applied parameters. Therefore, efficiency assessment of Imperialist Competition Algorithm (ICA) to evaluate optimum parameters of non-linear Muskingum model was addressed through this study. In addition to ICA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were also used aiming at an available criterion to verdict ICA. In this regard, ICA was applied for Wilson flood routing; then, routing of two flood events of DoAab Samsami River was investigated. In case of Wilson flood that the target function was considered as the sum of squared deviation (SSQ) of observed and calculated discharges. Routing two other floods, in addition to SSQ, another target function was also considered as the sum of absolute deviations of observed and calculated discharge. For the first floodwater based on SSQ, GA indicated the best performance, however, ICA was on first place, based on SAD. For the second floodwater, based on both target functions, ICA indicated a better operation. According to the obtained results, it can be said that ICA could be used as an appropriate method to evaluate the parameters of Muskingum non-linear model.

Keywords: Doab Samsami river, genetic algorithm, imperialist competition algorithm, meta-exploratory algorithms, particle swarm optimization, Wilson flood

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Authors: Tian Xia, Yuan Yan Tang

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In order to obtain higher small target detection accuracy, this paper presents an effective algorithm inspired by the local contrast mechanism. The proposed method can enhance target signal and suppress background clutter simultaneously. In the first stage, a enhanced image is obtained using the proposed Weighted Laplacian of Gaussian. In the second stage, an adaptive threshold is adopted to segment the target. Experimental results on two changeling image sequences show that the proposed method can detect the bright and dark targets simultaneously, and is not sensitive to sea-sky line of the infrared image. So it is fit for IR small infrared target detection.

Keywords: small target detection, local contrast, human vision system, Laplacian of Gaussian

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Authors: AmirHossein Mohajerzadeh, Mohammad Alishahi, Saeed Aslishahi, Mohsen Zabihi

Abstract:

In this paper, we consider sensor nodes with the capability of measuring the bearings (relative angle to the target). We use geometric methods to select a set of observer nodes which are responsible for collecting data from the target. Considering the characteristics of target tracking applications, it is clear that significant numbers of sensor nodes are usually inactive. Therefore, in order to minimize the total network energy consumption, a set of sensor nodes, called sentinel, is periodically selected for monitoring, controlling the environment and transmitting data through the network. The other nodes are inactive. Furthermore, the proposed algorithm provides a joint scheduling and routing algorithm to transmit data between network nodes and the fusion center (FC) in which not only provides an efficient way to estimate the target position but also provides an efficient target tracking. Performance evaluation confirms the superiority of the proposed algorithm.

Keywords: coverage, routing, scheduling, target tracking, wireless sensor networks

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Authors: Ruomeng Xiao, Zhulin Zong, Longfa Yang

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Aiming at the problem that the target signal is difficult to detect under the strong ground clutter environment, this paper proposes a clutter suppression algorithm based on the combination of singular value decomposition and the Mallat fast wavelet algorithm. The method first carries out singular value decomposition on the radar echo data matrix, realizes the initial separation of target and clutter through the threshold processing of singular value, and then carries out wavelet decomposition on the echo data to find out the target location, and adopts the discard method to select the appropriate decomposition layer to reconstruct the target signal, which ensures the minimum loss of target information while suppressing the clutter. After the verification of the measured data, the method has a significant effect on the target extraction under low SCR, and the target reconstruction can be realized without the prior position information of the target and the method also has a certain enhancement on the output SCR compared with the traditional single wavelet processing method.

Keywords: clutter suppression, singular value decomposition, wavelet transform, Mallat algorithm, low SCR

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Authors: Koirala Abarodh, Maghaiya Ujjwal, Guragain Phani Raj

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This analysis is focused on defining the spectrum evaluation model for telecom operators in terms of the total cost of ownership (TCO). A quantitative approach for specific case analysis research methodology has been used for identifying the results. Specific input parameters like target user experience, year-on-year traffic growth, capacity site limit per year, target new spectrum type, bandwidth, spectrum efficiency, UE penetration have been used for the spectrum evaluation process and desired outputs in terms of a number of sites, capex in USD and required spectrum bandwidth have been calculated. Furthermore, this study gives a comparison of capex investment for target growth with and without addition spectrum. As a result, the combination of new spectrums 700 and 2600 band have a better evaluation in terms of TCO and performance and it is recommended to use this band in terms of 5G rather than current expansion in current 1800 and 2100 band.

Keywords: spectrum, capex planning, 5G, case study methodology

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Authors: Yufeng Li, Yinan Ma, Jing Wu, Chengnian Long

Abstract:

Infrared object detection aims at separating small and dim targets from cluttered backgrounds, and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications, such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in the F1 score over the existing state-of-the-art model.

Keywords: infrared small target detection, high noise, robustness, soft-threshold coordinate attention, feature fusion

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Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

Abstract:

Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

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Authors: Yanshuang Zhang, Byungho Jeong

Abstract:

There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO model

Keywords: DEA, Super-efficiency, Time Lag, research activities

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Authors: Mahmoud Huleihil

Abstract:

In this study, the performance of a thermodynamic gas cycle of magnetohydrodynamic (MHD) power generation is considered and presented in terms of power efficiency curves. The dissipation mechanisms considered include: fluid friction modeled by means of the isentropic efficiency of the compressor, heat transfer leakage directly from the hot reservoir to the cold heat reservoir, and constant velocity of the MHD generator. The study demonstrates that power and efficiency vanish at the extremes of both slow and fast operating conditions. These points are demonstrated on power efficiency curves and the locus of efficiency at maximum power and the locus of maximum efficiency. Qualitatively, the considered loss mechanisms have a similar effect on the efficiency at maximum power operation and on maximum efficiency operation, thus these efficiencies are reduced, even for small values of the loss mechanisms.

Keywords: magnetohydrodynamic generator, electrical efficiency, maximum power, maximum efficiency, heat engine

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Authors: Richard G. Carranza, Juan Ospina

Abstract:

The fin efficiency for a helical fin with a fixed fin tip (or arbitrary) temperature boundary condition is presented. Firstly, the temperature profile throughout the fin is determined via an energy balance around the fin itself. Secondly, the fin efficiency is formulated by integrating across the entire surface of the helical fin. An analytical expression for the fin efficiency is presented and compared with the literature for accuracy.

Keywords: efficiency, fin, heat, helical, transfer

Procedia PDF Downloads 652

Authors: Tianyang Xu

Abstract:

Small underwater targets generally have a non-centrosymmetric geometry, and the acoustic scattering field of the target has spatial inhomogeneity under active sonar detection conditions. In view of the above problems, this paper takes the hemispherical cylindrical shell as the research object, and considers the angle continuity implied in the echo characteristics, and proposes a cluster-driven research method for the non-uniform characteristics of target echo angle. First, the target echo features are extracted, and feature vectors are constructed. Secondly, the t-SNE algorithm is used to improve the internal connection of the feature vector in the low-dimensional feature space and to construct the visual feature space. Finally, the implicit angular relationship between echo features is extracted under unsupervised condition by cluster analysis. The reconstruction results of the local geometric structure of the target corresponding to different categories show that the method can effectively divide the angle interval of the local structure of the target according to the natural acoustic scattering characteristics of the target.

Keywords: underwater target;, non-uniform characteristics;, cluster-driven method;, acoustic scattering characteristics

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Authors: V. Ramu Reddy, Parijat Deshpande, Ranjan Dasgupta

Abstract:

This paper presents different methodology for an acoustic source sensing and localization in an unknown environment. The developed methodology includes an acoustic based sensing and localization system, a converging target localization based on the recursive direction of arrival (DOA) error minimization, and a regressive obstacle avoidance function. Our method is able to augment the existing proven localization techniques and improve results incrementally by utilizing robot locomotion and is capable of converging to a position estimate with greater accuracy using fewer measurements. The results also evinced the DOA error minimization at each iteration, improvement in time for reaching the destination and the efficiency of this target localization method as gradually converging to the real target position. Initially, the system is tested using Kinect mounted on turntable with DOA markings which serve as a ground truth and then our approach is validated using a FireBird VI (FBVI) mobile robot on which Kinect is used to obtain bearing information.

Keywords: acoustic source localization, acoustic sensing, recursive direction of arrival, robot locomotion

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Authors: Michael Ayomoh, Adriaan Roux, Oyindamola Omotuyi

Abstract:

This paper presents an efficient robot navigation model in a multi-target domain amidst static and dynamic workspace obstacles. The problem is that of developing an optimal algorithm to minimize the total travel time of a robot as it visits all target points within its task domain amidst unknown workspace obstacles and finally return to its initial position. In solving this problem, a classical algorithm was first developed to compute the optimal number of paths to be travelled by the robot amidst the network of paths. The principle of shortest distance between robot and targets was used to compute the target point visitation order amidst workspace obstacles. Algorithm premised on the standard polar coordinate system was developed to determine the length of obstacles encountered by the robot hence giving room for a geometrical estimation of the total surface area occupied by the obstacle especially when classified as a relevant obstacle i.e. obstacle that lies in between a robot and its potential visitation point. A stochastic model was developed and used to estimate the likelihood of a dynamic obstacle bumping into the robot’s navigation path and finally, the navigation/obstacle avoidance algorithm was hinged on the hybrid virtual force field (HVFF) method. Significant modelling constraints herein include the choice of navigation path to selected target points, the possible presence of static obstacles along a desired navigation path and the likelihood of encountering a dynamic obstacle along the robot’s path and the chances of it remaining at this position as a static obstacle hence resulting in a case of re-routing after routing. The proposed algorithm demonstrated a high potential for optimal solution in terms of efficiency and effectiveness.

Keywords: multi-target, mobile robot, optimal path, static obstacles, dynamic obstacles

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Authors: Terence Soule, Tami Al Ghamdi

Abstract:

To study how to transfer knowledge from multiple source problems to the target problem, we modeled the Transfer Learning (TL) process using Genetic Algorithms as the model solver. TL is the process that aims to transfer learned data from one problem to another problem. The TL process aims to help Machine Learning (ML) algorithms find a solution to the problems. The Genetic Algorithms (GA) give researchers access to information that we have about how the old problem is solved. In this paper, we have five different source problems, and we transfer the knowledge to the target problem. We studied different scenarios of the target problem. The results showed combined knowledge from multiple source problems improves the GA performance. Also, the process of combining knowledge from several problems results in promoting diversity of the transferred population.

Keywords: transfer learning, genetic algorithm, evolutionary computation, source and target

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Authors: Jaime A. Palma-Mendoza

Abstract:

A supply chain consists of different processes and when conducting supply chain re-design is necessary to identify the relevant processes and select a target for re-design. A solution was developed which consists to identify first the relevant processes using the Supply Chain Operations Reference (SCOR) model, then to use Analytical Hierarchy Process (AHP) for target process selection. An application was conducted in an Airline MRO supply chain re-design project which shows this combination can clearly aid the identification of relevant supply chain processes and the selection of a target process for re-design.

Keywords: decision support systems, multiple criteria analysis, supply chain management

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Authors: Mohammad Izadkhah, Mojtaba Hoseini, Alireza Khalili Tehrani

Abstract:

In this paper we presented a new method for tracking flying targets in color video sequences based on contour and kernel. The aim of this work is to overcome the problem of losing target in changing light, large displacement, changing speed, and occlusion. The proposed method is made in three steps, estimate the target location by particle filter, segmentation target region using neural network and find the exact contours by greedy snake algorithm. In the proposed method we have used both region and contour information to create target candidate model and this model is dynamically updated during tracking. To avoid the accumulation of errors when updating, target region given to a perceptron neural network to separate the target from background. Then its output used for exact calculation of size and center of the target. Also it is used as the initial contour for the greedy snake algorithm to find the exact target's edge. The proposed algorithm has been tested on a database which contains a lot of challenges such as high speed and agility of aircrafts, background clutter, occlusions, camera movement, and so on. The experimental results show that the use of neural network increases the accuracy of tracking and segmentation.

Keywords: video tracking, particle filter, greedy snake, neural network

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Authors: Christine M. Corrales, Gloria G. Delan, Rachel Luz V. Rica, Alfonso S. Piquero

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Marine protected areas (MPAs) in the study sites were established 8-13 years ago and are presently operational. This study was conducted to gather baseline information on the diversity, density and biomass of coral reef fishes inside and outside the four marine protected areas (MPAs) of Cawayan, Dalaguete; Daan-Lungsod Guiwang, Alcoy; North Granada, Boljoon and Sta. Cruz, Ronda. Coral reef fishes in the MPAs were identified using Fish Visual Census Method. Results of the t-test showed that the mean diversity (fish species/250m2) of target and non-target reef fish species found inside and outside the MPAs were significantly different. Density (ind./1,000m2) of target species inside and outside the MPAs showed no significant difference. Similarly, density of non-target species inside and outside the MPAs also showed no significant difference. This is an indication that fish density inside and outside the MPAs were more or less of the same condition. The mean biomass (kg/1,000m2) of target species inside and outside the MPAs showed a significant difference in contrast with non-target species inside and outside the MPAs which showed a no significant difference. Higher biomass of target fish species belonging to family Caesonidae (fusiliers) and Scaridae (parrotfishes) were commonly observed inside the MPAs. Results showed that fish species were more diverse with higher density and biomass inside the MPAs than the outside area. However, fish diversity and density were mostly contributed by non-target species. Hence, long term protection and management of MPAs is needed to effectively increase fish diversity, density and biomass specifically on target fish species.

Keywords: biomass, density, diversity, marine protected area, target fish species

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Authors: Bahram Fathi, Mahdi Khodaparast Mashhadi, Masuod Homayounifar

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Global awareness on energy security and climate change has created much interest in assessing energy efficiency performance. A number of previous studies have contributed to evaluate energy efficiency performance using different analytical techniques among which data envelopment analysis (DEA) has recently received increasing attention. Most of DEA-related energy efficiency studies do not consider undesirable outputs such as CO2 emissions in their modeling framework, which may lead to biased energy efficiency values. Within a joint production frame work of desirable and undesirable outputs, in this paper we construct energy efficiency performance index for measuring energy efficiency performance by using environmental DEA model with CO2 emissions. We finally apply the index proposed to assess the energy efficiency performance in OPEC over time.

Keywords: energy efficiency, environmental, OPEC, data envelopment analysis

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Authors: Chen Bo, Wen Zengping

Abstract:

Based on the results of previous studies, we focus on the research of real ground motion selection and scaling method for structural performance-based seismic evaluation using nonlinear dynamic analysis. The input of earthquake ground motion should be determined appropriately to make them compatible with the site-specific hazard level considered. Thus, an optimized selection and scaling method are established including the use of not only Monte Carlo simulation method to create the stochastic simulation spectrum considering the multivariate lognormal distribution of target spectrum, but also a spectral shape parameter. Its applications in structural fragility analysis are demonstrated through case studies. Compared to the previous scheme with no consideration of the uncertainty of target spectrum, the method shown here can make sure that the selected records are in good agreement with the median value, standard deviation and spectral correction of the target spectrum, and greatly reveal the uncertainty feature of site-specific hazard level. Meanwhile, it can help improve computational efficiency and matching accuracy. Given the important infection of target spectrum’s uncertainty on structural seismic fragility analysis, this work can provide the reasonable and reliable basis for structural seismic evaluation under scenario earthquake environment.

Keywords: ground motion selection, scaling method, seismic fragility analysis, spectral shape

Procedia PDF Downloads 263