• Title/Summary/Keyword: multi-metric

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Optimizing Mobile Advertising Using Ad Refresh Interval

  • Truong, Vinh
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.2
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    • pp.117-122
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    • 2016
  • Optimizing the number of ad clicks is a large-scale learning problem that is central to the multi-billion dollar mobile advertising industry. There are currently several optimization methods used, including ad mediation and ad positioning. This paper proposes a new method to optimize mobile advertising by using the ad refresh interval. A new metric, which can measure and compare mobile advertising performance, takes into account time limitations. The results achieved from this optimization study could maximize revenue for mobile advertisers and publishers. This research has high applicability. It also lays out a solid background for future research in this promising area.

Geometry-based quality metric for multi-view autostereoscopic 3D display

  • Saveljev, Vladimir;Son, Jung-Young;Kwack, Kae-Dal
    • 한국정보디스플레이학회:학술대회논문집
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    • 2009.10a
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    • pp.1014-1017
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    • 2009
  • The analytical expression for quality function is found including the dependence on disparity. The problem is considered in the projective coordinates for which the forward and backward transformation matrices are found. The formation of side observer regions is considered. The probability of the pseudo stereo effect is also estimated. Testing patterns are improved in order to provide higher accuracy of measurements. This is confirmed in experiments.

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Target candidate fish species selection method based on ecological survey for hazardous chemical substance analysis (유해화학물질 분석을 위한 생태조사 기반의 타깃 후보어종 선정법)

  • Ji Yoon Kim;Sang-Hyeon Jin;Min Jae Cho;Hyeji Choi;Kwang-Guk An
    • Korean Journal of Environmental Biology
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    • v.41 no.2
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    • pp.109-125
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    • 2023
  • This study was conducted to select target fish species as baseline research for accumulation analysis of major hazardous chemicals entering the aquatic ecosystem in Korea and to analyze the impact on fish community. The test bed was selected from a sewage treatment plant, which could directly confirm the impact of the inflow of harmful chemicals, and the Geum River estuary where harmful chemicals introduced into the water system were concentrated. A multivariable metric model was developed to select target candidate fish species for hazardous chemical analysis. Details consisted of seven metrics: (1) commercially useful metric, (2) top-carnivorous species metric, (3) pollution fish indicator metric, (4) tolerance fish metric, (5) common abundant metric, (6) sampling availability (collectability) metric, and (7) widely distributed fish metric. Based on seven metric models for candidate fish species, eight species were selected as target candidates. The co-occurring dominant fish with target candidates was tolerant (50%), indicating that the highest abundance of tolerant species could be used as a water pollution indicator. A multi-metric fish-based model analysis for aquatic ecosystem health evaluation showed that the ecosystem health was diagnosed as "bad conditions". Physicochemical water quality variables also influenced fish feeding and tolerance guild in the testbed. Eight water quality parameters appeared high at the T1 site, indicating a large impact of discharging water from the sewage treatment plant. T2 site showed massive algal bloom, with chlorophyll concentration about 15 times higher compared to the reference site.

Multi-Objective Modular Design Method Using Similarity Concept (유사도 개념을 이용한 다목적 모듈화 설계법)

  • Nahm, Yoon-Eui;Ishikawa, Haruo
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.35 no.4
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    • pp.16-23
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    • 2012
  • At present, the significance of a new manufacturing system that can shift from 'mass production' and consider life cycles of a product is pointed out and extremely expected. In such a situation, it is recognized that the modular design, often called 'unit design,' is the important design methodology which realizes the new production system enabling 'cost reduction,' 'flexible production of a multi-functional artifact,' 'settlement of an environmental issue,' and so on. A module (unit) of a product is generally defined as 'the parts group made into the sub-system from a certain specific viewpoint.' So far, there have been many researches related to the modular design. However, they are often limited to a certain viewpoint (objective). This paper proposes a simple but effective method for multi-objective modular design. In the proposed method, a new design metric, called similarity index, is proposed to evaluate the modular design candidates from the multiple viewpoints.

Optimization-based Image Watermarking Algorithm Using a Maximum-Likelihood Decoding Scheme in the Complex Wavelet Domain

  • Liu, Jinhua;Rao, Yunbo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.1
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    • pp.452-472
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    • 2019
  • Most existing wavelet-based multiplicative watermarking methods are affected by geometric attacks to a certain extent. A serious limitation of wavelet-based multiplicative watermarking is its sensitivity to rotation, scaling, and translation. In this study, we propose an image watermarking method by using dual-tree complex wavelet transform with a multi-objective optimization approach. We embed the watermark information into an image region with a high entropy value via a multiplicative strategy. The major contribution of this work is that the trade-off between imperceptibility and robustness is simply solved by using the multi-objective optimization approach, which applies the watermark error probability and an image quality metric to establish a multi-objective optimization function. In this manner, the optimal embedding factor obtained by solving the multi-objective function effectively controls watermark strength. For watermark decoding, we adopt a maximum likelihood decision criterion. Finally, we evaluate the performance of the proposed method by conducting simulations on benchmark test images. Experiment results demonstrate the imperceptibility of the proposed method and its robustness against various attacks, including additive white Gaussian noise, JPEG compression, scaling, rotation, and combined attacks.

The Applications of a Multi-metric LEHA Model for an Environmental Impact Assessments of Lake Ecosystems and the Ecological Health Assessments (호수생태계 환경영향평가를 위한 LEHA 다변수 모델 적용 및 생태건강성 평가)

  • Han, Jeong-Ho;An, Kwang-Guk
    • Journal of Environmental Impact Assessment
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    • v.21 no.3
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    • pp.483-501
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    • 2012
  • The purpose of this study was to apply a multi-metric model of Lentic Ecosystem Health Assessments(LEHA) for environmental impact assessments of Cheongpyung Reservoir during 2005 - 2006 and assessed the ecological model values. The ecosystem model of LEHA was composed of eleven metrics such as biological parameters($B_p$), physical parameters($P_p$), and chemical parameters($C_p$), and determined the rank of ecological health by the criteria. The variables of $B_p$ were metrics of % sensitive species($M_2$, NMS) and insectivore species($M_5$, % $I_n$), which decrease as the water quality degradates, and these metric values were low as 1.5% and 32.4%, respectively. In contrast, the proportions of tolerant species and omnivore species as the other $B_p$ parameters were 43% and 62%, respectively, which indicate a degradation and disturbance of the ecosystem. Riparian vegetation coverage($M_9$, % $V_c$) as a variable of $P_p$, were higher in the 2nd than 1st survey, and decreased toward the dam site from the headwaters. This was due to a habitat simplification(modifications) by frequent bottom dredging of sand and rocks. The variables of $C_p$ were two metrics of specific conductivity($M_{10}$, $C_I$) as an indicator of ionic contents(cations and anions) and the Trophic State Index(TSI) based on chlorophyll-a($M_{11}$, $TSI_{CHL}$) as an indicator of trophic state. These metric values of $C_p$ had high temporal variations, but low spatial variations on the main axis of the reservoir along with the ecological health of a good condition. The environmental impact assessments using the LEHA multi-metric model indicated that the model values of LEHA averaged 30.7 in 1st survey(fair - poor condition) vs. 28 in 2nd survey(poor condition), indicating a temporal variation of the ecological health. The model values of LEHA showed a minimum(28) in the lacustrine zone(S5) and ranged from 29 to 30 in the other locations sampled, indicating a low longitudinal variation. Overall, environmental impact assessments, based on LEHA model, suggest that chemical water quality conditions were in good, but biological conditions were disturbed due to habitat modifications by frequent dredgings in the system.

Joint Transmitter and Receiver Design Based on SPPLNR for Multi-user MIMO Channel with Channel Estimation Error (채널 추정 오차가 있는 다중사용자 다중안테나 채널에서 신호 대 포스트-프로세싱 리키지 및 잡음비 기반 송신기와 수신기 결합 설계)

  • Seo, Dong-Joon;Lee, Pan-Hyung;Lee, Jae-Hong
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.46 no.2
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    • pp.53-59
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    • 2009
  • In multi-user MIMO systems, a base station transmits multiple data to multi-user simultaneously in order to improve performance and bandwidth efficiency. When the base station transmits multiple data to multi-user simultaneously, multi-user interference occurs severely. In this paper, we define a post-processing leakage as the total power leaked from desired user to all other users after combining at the output of each user. Using concept of the post-processing leakage, we also define a performance metric, the so called signal-to-post-processing-leakage-plus-noise ratio (SPPLNR). Assuming that the receiver is the minimum mean square error (MMSE) receiver, we propose an iterative SPPLNR-based beamforming that determines beamforming vectors and combining vectors by using an iterative method. The proposed scheme does not impose a condition on the relation between the number of transmit antennas for the base station and the number of receive antennas for users. Simulation results show that the proposed scheme outperforms a beamforming scheme perfectly eliminating the multi-user interference when channel estimation error exists.

Optimization of Sheet Metal Forming Process Using Mahalanobis Taguchi System (마하라노비스 다구찌(Mahalanobis Taguchi) 시스템을 이용한 박판 성형 공정의 최적화)

  • Kim, Kyung-Mo
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.15 no.1
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    • pp.95-102
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    • 2016
  • Wrinkle, spring-back, and fracture are major defects frequently found in the sheet metal forming process, and the reduction of such defects is difficult as they are affected by uncontrollable factors, such as variations in properties of the incoming material and process parameters. Without any countermeasures against these issues, attempts to reduce defects through optimal design methods often lead to failure. In this research, a new multi-attribute robust design methodology, based on the Mahalanobis Taguchi System (MTS), is presented for reducing the possibilities of wrinkle, spring-back, and fracture. MTS performs experimentation, based on the orthogonal array under various noise conditions, uses the SN ratio of the Mahalanobis distance as a performance metric. The proposed method is illustrated through a robust design of the sheet metal forming process of a cross member of automotive body.

Optimal Design of Inverse Electromagnetic Problems with Uncertain Design Parameters Assisted by Reliability and Design Sensitivity Analysis

  • Ren, Ziyan;Um, Doojong;Koh, Chang-Seop
    • Journal of Magnetics
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    • v.19 no.3
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    • pp.266-272
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    • 2014
  • In this paper, we suggest reliability as a metric to evaluate the robustness of a design for the optimal design of electromagnetic devices, with respect to constraints under the uncertainties in design variables. For fast numerical efficiency, we applied the sensitivity-assisted Monte Carlo simulation (S-MCS) method to perform reliability calculation. Furthermore, we incorporated the S-MCS with single-objective and multi-objective particle swarm optimization algorithms to achieve reliability-based optimal designs, undertaking probabilistic constraint and multi-objective optimization approaches, respectively. We validated the performance of the developed optimization algorithms through application to the optimal design of a superconducting magnetic energy storage system.