• Title/Summary/Keyword: Maximization methods

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Partial AUC maximization for essential gene prediction using genetic algorithms

  • Hwang, Kyu-Baek;Ha, Beom-Yong;Ju, Sanghun;Kim, Sangsoo
    • BMB Reports
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    • v.46 no.1
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    • pp.41-46
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    • 2013
  • Identifying genes indispensable for an organism's life and their characteristics is one of the central questions in current biological research, and hence it would be helpful to develop computational approaches towards the prediction of essential genes. The performance of a predictor is usually measured by the area under the receiver operating characteristic curve (AUC). We propose a novel method by implementing genetic algorithms to maximize the partial AUC that is restricted to a specific interval of lower false positive rate (FPR), the region relevant to follow-up experimental validation. Our predictor uses various features based on sequence information, protein-protein interaction network topology, and gene expression profiles. A feature selection wrapper was developed to alleviate the over-fitting problem and to weigh each feature's relevance to prediction. We evaluated our method using the proteome of budding yeast. Our implementation of genetic algorithms maximizing the partial AUC below 0.05 or 0.10 of FPR outperformed other popular classification methods.

Experimental Evaluation of Distance-based and Probability-based Clustering

  • Kwon, Na Yeon;Kim, Jang Il;Dollein, Richard;Seo, Weon Joon;Jung, Yong Gyu
    • International journal of advanced smart convergence
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    • v.2 no.1
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    • pp.36-41
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    • 2013
  • Decision-making is to extract information that can be executed in the future, it refers to the process of discovering a new data model that is induced in the data. In other words, it is to find out the information to peel off to find the vein to catch the relationship between the hidden patterns in data. The information found here, is a process of finding the relationship between the useful patterns by applying modeling techniques and sophisticated statistical analysis of the data. It is called data mining which is a key technology for marketing database. Therefore, research for cluster analysis of the current is performed actively, which is capable of extracting information on the basis of the large data set without a clear criterion. The EM and K-means methods are used a lot in particular, how the result values of evaluating are come out in experiments, which are depending on the size of the data by the type of distance-based and probability-based data analysis.

The Construction of large and Long Tunnel Using Bulk Explosives (벌크폭약을 이용한 대단면 장대터널 시공 사례)

  • 노상림;문상호;조영천;이상필;유지영
    • Explosives and Blasting
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    • v.22 no.3
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    • pp.65-70
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    • 2004
  • Lately, the length of tunnel, the number of long-large tunnel over 3 lanes are steeply increased because of the request for high-speed and straight road. Therefore, the maximization of excavation efficiency is needed in tunnel construction. The sapaesan tunnel (4 lanes with the length of 4km) construction was delayed with environmental conflict far 2 years. For making-up delayed construction period, various new methods were adopted to improve excavation length, look-out and blasting efficiency. This study introduced bulk explosive which is new method in tunnel blasting and verified the efficiency of bulk explosive far long-large tunnel.

Reducing Decoding Complexity by Improving Motion Field Using Bicubic and Lanczos Interpolation Techniques in Wyner-Ziv Video Coding

  • Widyantara, I Made O.;Wirawan, Wirawan;Hendrantoro, Gamantyo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.9
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    • pp.2351-2369
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    • 2012
  • This paper describes interpolation method of motion field in the Wyner-Ziv video coding (WZVC) based on Expectation-Maximization (EM) algorithm. In the EM algorithm, the estimated motion field distribution is calculated on a block-by-block basis. Each pixel in the block shares similar probability distribution, producing an undesired blocking artefact on the pixel-based motion field. The proposed interpolation techniques are Bicubic and Lanczos which successively use 16 and 32 neighborhood probability distributions of block-based motion field for one pixel in k-by-k block on pixel-based motion field. EM-based WZVC codec updates the estimated probability distribution on block-based motion field, and interpolates it to pixel resolution. This is required to generate higher-quality soft side information (SI) such that the decoding algorithm is able to make syndrome estimation more quickly. Our experiments showed that the proposed interpolation methods have the capability to reduce EM-based WZVC decoding complexity with small increment of bit rate.

Power System Enhanced Monitoring through Strategic PMU Placement Considering Degree of Criticality of Buses

  • Singh, Ajeet Kumar;Fozdar, Manoj
    • Journal of Electrical Engineering and Technology
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    • v.13 no.5
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    • pp.1769-1777
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    • 2018
  • This paper proposes a method for optimal placement of Phasor Measurement Units (PMUs) considering system configuration and its attributes during the planning phase of PMU deployment. Each bus of the system is assessed on four diverse attributes; namely, redundancy of measurements, rotor angle and frequency monitoring of generator buses, reactive power deficiency, and maximum loading limit under transmission line outage contingency, and a consolidated 'degree of criticality' is determined using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The major contribution of the proposed work is the development of modified objective function which incorporates values of the degree of criticality of buses. The problem is formulated as maximization of the aggregate degree of criticality of the system. The resultant PMU configuration extends complete observability of the system and majority of the PMUs are located on critical buses. As budgetary restrictions on utilities may not allow installation PMUs even at optimal locations in a single phase, multi-horizon deployment of PMUs is also addressed. The proposed approach is tested on IEEE 14-bus, IEEE 30-bus, New England (NE) 39-bus, IEEE 57-bus and IEEE 118-bus systems and compared with some existing methods.

A Study on Dry Bulkers' Optimal Deadweight and Speed under Certain Available Cargo Lot Sizes (선적화물량에 따른 살적화물선의 최적적화중량준 및 속력의 결정에 관한 연구)

  • 이명진
    • Journal of the Korean Institute of Navigation
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    • v.8 no.1
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    • pp.17-48
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    • 1984
  • The economy of ship's size and speed is affected by the freight rates, sailing distances, cargo handling rates, fuel oil prices and even interest rates of the borrowed funds. It can be a step more powerful measures if the economic evaluation model takes in a cargo lot size which prevails in the shipping markets. This paper has dealt with hypothetical cargo lots which happen to the market with uniform distribution in probability. The evaluation models are either profit maximization method or cost minimization method. The former compares among different voyages in profitability to the invested funds, the later defines the transportation efficiency in ton-mile unit and be used in comparing two or more transportation means. This paper adopted both of above methods to derive out ships economical evaluation contours for the various ship's speed and deadweight for certain cargo lot sizes, which can be used as important managerial decision data in purchasing ships or selecting a most profitable one among the proposed voyages. This evaluation contours will also be efficiently used in appraising so called "handy size ships" in connection with port water depth and conditions of voyage tracks.ge tracks.

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Collective Interaction Filtering Approach for Detection of Group in Diverse Crowded Scenes

  • Wong, Pei Voon;Mustapha, Norwati;Affendey, Lilly Suriani;Khalid, Fatimah
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.2
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    • pp.912-928
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    • 2019
  • Crowd behavior analysis research has revealed a central role in helping people to find safety hazards or crime optimistic forecast. Thus, it is significant in the future video surveillance systems. Recently, the growing demand for safety monitoring has changed the awareness of video surveillance studies from analysis of individuals behavior to group behavior. Group detection is the process before crowd behavior analysis, which separates scene of individuals in a crowd into respective groups by understanding their complex relations. Most existing studies on group detection are scene-specific. Crowds with various densities, structures, and occlusion of each other are the challenges for group detection in diverse crowded scenes. Therefore, we propose a group detection approach called Collective Interaction Filtering to discover people motion interaction from trajectories. This approach is able to deduce people interaction with the Expectation-Maximization algorithm. The Collective Interaction Filtering approach accurately identifies groups by clustering trajectories in crowds with various densities, structures and occlusion of each other. It also tackles grouping consistency between frames. Experiments on the CUHK Crowd Dataset demonstrate that approach used in this study achieves better than previous methods which leads to latest results.

Impact of aperture-thickness on the real-time imaging characteristics of coded-aperture gamma cameras

  • Park, Seoryeong;Boo, Jiwhan;Hammig, Mark;Jeong, Manhee
    • Nuclear Engineering and Technology
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    • v.53 no.4
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    • pp.1266-1276
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    • 2021
  • The mask parameters of a coded aperture are critical design features when optimizing the performance of a gamma-ray camera. In this paper, experiments and Monte Carlo simulations were performed to derive the minimum detectable activity (MDA) when one seeks a real-time imaging capability. First, the impact of the thickness of the modified uniformly redundant array (MURA) mask on the image quality is quantified, and the imaging of point, line, and surface radiation sources is demonstrated using both cross-correlation (CC) and maximum likelihood expectation maximization (MLEM) methods. Second, the minimum detectable activity is also derived for real-time imaging by altering the factors used in the image quality assessment, consisting of the peak-to-noise ratio (PSNR), the normalized mean square error (NMSE), the spatial resolution (full width at half maximum; FWHM), and the structural similarity (SSIM), all evaluated as a function of energy and mask thickness. Sufficiently sharp images were reconstructed when the mask thickness was approximately 2 cm for a source energy between 30 keV and 1.5 MeV and the minimum detectable activity for real-time imaging was 23.7 MBq at 1 m distance for a 1 s collection time.

Estimation of Hovering Flight Time of Battery-Powered Multicopters

  • Cho, Mun jin;Han, Cheolheui
    • Journal of Aerospace System Engineering
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    • v.15 no.4
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    • pp.11-20
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    • 2021
  • The estimation of hovering flight time of multicopters using the battery power propulsion system is important for the development and design of the aircraft and its operation. For a given operational weight, the maximum possible battery weight can be decided using both a conventional energy density method and a new Peukert law. In the present study, the hovering flight time is predicted using both methods. The specific data of multicopters in the published literatures were employed for the computation of the hovering flight time. The results were validated with the measured data. The effect of figure of merit of propeller, battery discharging process on the hovering flight time was evaluated, Finally, the effect of the battery cell and package connection types on the hovering time was investigated. It was found that the combination of serial battery cell connections and parallel package connection is the bast in the endurance maximization aspect. As the cell number increases in a package, the hovering flight time is increased. There exists the max. battery ratio for the given takeoff gross weight.

Explicit Dynamic Coordination Reinforcement Learning Based on Utility

  • Si, Huaiwei;Tan, Guozhen;Yuan, Yifu;peng, Yanfei;Li, Jianping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.3
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    • pp.792-812
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    • 2022
  • Multi-agent systems often need to achieve the goal of learning more effectively for a task through coordination. Although the introduction of deep learning has addressed the state space problems, multi-agent learning remains infeasible because of the joint action spaces. Large-scale joint action spaces can be sparse according to implicit or explicit coordination structure, which can ensure reasonable coordination action through the coordination structure. In general, the multi-agent system is dynamic, which makes the relations among agents and the coordination structure are dynamic. Therefore, the explicit coordination structure can better represent the coordinative relationship among agents and achieve better coordination between agents. Inspired by the maximization of social group utility, we dynamically construct a factor graph as an explicit coordination structure to express the coordinative relationship according to the utility among agents and estimate the joint action values based on the local utility transfer among factor graphs. We present the application of such techniques in the scenario of multiple intelligent vehicle systems, where state space and action space are a problem and have too many interactions among agents. The results on the multiple intelligent vehicle systems demonstrate the efficiency and effectiveness of our proposed methods.