• Title/Summary/Keyword: Large-scale optimization

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Formulation of a novel bacterial consortium for the effective biodegradation of phenol

  • Dhanya, V.
    • Advances in environmental research
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    • v.9 no.2
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    • pp.109-121
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    • 2020
  • Phenol is frequently present as the hazardous pollutant in petrochemical and pesticide industry wastewater. Because of its high toxicity and carcinogenic potential, a proper treatment is needed to reduce the hazards of phenol carrying effluent before being discharged into the environment. Phenol biodegradation with microbial consortium offers a very promising approach now a day's. This study focused on the formulation of phenol degrading bacterial consortium with three bacterial isolates. The bacterial strains Bacillus cereus strain VCRC B540, Bacillus cereus strain BRL02-43 and Oxalobacteraceae strain CC11D were isolated from detergent contaminated soil by soil enrichment technique and was identified by 16s rDNA sequence analysis. Individual cultures were degrade 100 μl phenol in 72 hrs. The formulated bacterial consortium was very effective in degrading 250 μl of phenol at a pH 7 with in 48 hrs. The study further focused on the analysis of the products of biodegradation with Fourier Transform Infrared Spectroscopy (FT/IR) and Gas Chromatography-Mass Spectroscopy (GC-MS). The analysis showed the complete degradation of phenol and the production of Benzene di-carboxylic acid mono (2-ethylhexyl) ester and Ethane 1,2- Diethoxy- as metabolic intermediates. Biodegradation with the aid of microorganisms is a potential approach in terms of cost-effectiveness and elimination of secondary pollutions. The present study established the efficiency of bacterial consortium to degrade phenol. Optimization of biodegradation conditions and construction of a bioreactor can be further exploited for large scale industrial applications.

Pilot Sequence Assignment for Spatially Correlated Massive MIMO Circumstances

  • Li, Pengxiang;Gao, Yuehong;Li, Zhidu;Yang, Dacheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.1
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    • pp.237-253
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    • 2019
  • For massive multiple-input multiple-output (MIMO) circumstances with time division duplex (TDD) protocol, pilot contamination becomes one of main system performance bottlenecks. This paper proposes an uplink pilot sequence assignment to alleviate this problem for spatially correlated massive MIMO circumstances. Firstly, a single-cell TDD massive MIMO model with multiple terminals in the cell is established. Then a spatial correlation between two channel response vectors is established by the large-scale fading variables and the angle of arrival (AOA) span with an infinite number of base station (BS) antennas. With this spatially correlated channel model, the expression for the achievable system capacity is derived. To optimize the achievable system capacity, a problem regarding uplink pilot assignment is proposed. In view of the exponential complexity of the exhaustive search approach, a pilot assignment algorithm corresponding to the distinct channel AOA intervals is proposed to approach the optimization solution. In addition, simulation results prove that the main pilot assignment algorithm in this paper can obtain a noticeable performance gain with limited BS antennas.

Optimizing the composition of the medium for the viable cells of Bifidobacterium animalis subsp. lactis JNU306 using response surface methodology

  • Dang, Thi Duyen;Yong, Cheng Chung;Rheem, Sungsue;Oh, Sejong
    • Journal of Animal Science and Technology
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    • v.63 no.3
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    • pp.603-613
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    • 2021
  • This research improved the growth potential of Bifidobacterium animalis subsp lactis strain JNU306, a commercial medium that is appropriate for large-scale production, in yeast extract, soy peptone, glucose, L-cysteine, and ferrous sulfate. Response surface methodology (RSM) was used to optimize the components of this medium, using a central composite design and subsequent analyses. A second-order polynomial regression model, which was fitted to the data at first, significantly lacked fitness. Thus, through further analyses, the model with linear and quadratic terms plus two-way, three-way, and four-way interactions was selected as the final model. Through this model, the optimized medium composition was found as 2.8791% yeast extract, 2.8030% peptone soy, 0.6196% glucose, 0.2823% L-cysteine, and 0.0055% ferrous sulfate, w/v. This optimized medium ensured that the maximum biomass was no lower than the biomass from the commonly used blood-liver (BL) medium. The application of RSM improved the biomass production of this strain in a more cost-effective way by creating an optimum medium. This result shows that B. animalis subsp lactis JNU306 may be used as a commercial starter culture in manufacturing probiotics, including dairy products.

A Novel Broadband Channel Estimation Technique Based on Dual-Module QGAN

  • Li Ting;Zhang Jinbiao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.5
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    • pp.1369-1389
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    • 2024
  • In the era of 6G, the rapid increase in communication data volume poses higher demands on traditional channel estimation techniques and those based on deep learning, especially when processing large-scale data as their computational load and real-time performance often fail to meet practical requirements. To overcome this bottleneck, this paper introduces quantum computing techniques, exploring for the first time the application of Quantum Generative Adversarial Networks (QGAN) to broadband channel estimation challenges. Although generative adversarial technology has been applied to channel estimation, obtaining instantaneous channel information remains a significant challenge. To address the issue of instantaneous channel estimation, this paper proposes an innovative QGAN with a dual-module design in the generator. The adversarial loss function and the Mean Squared Error (MSE) loss function are separately applied for the parameter updates of these two modules, facilitating the learning of statistical channel information and the generation of instantaneous channel details. Experimental results demonstrate the efficiency and accuracy of the proposed dual-module QGAN technique in channel estimation on the Pennylane quantum computing simulation platform. This research opens a new direction for physical layer techniques in wireless communication and offers expanded possibilities for the future development of wireless communication technologies.

Power Generation Loss Characteristics Analysis for O&M Management of Floating Offshore Wind Farms (부유식 해상풍력 유지보수 관리 적용을 위한 발전손실량 특성 분석)

  • Seong-Bin Mun;Song-Kang An;Won-gyeong Seong;Young-Jin Oh
    • Journal of Wind Energy
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    • v.13 no.1
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    • pp.5-14
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    • 2022
  • Currently, the Korean government is driving the construction of large-scale floating offshore wind farms to increase domestic renewable energy generation and decrease carbon emissions. In offshore wind farms, maintenance approaches can be limited more often than onshore wind farms by marine weather conditions (wave height, etc.). Therefore, maintenance planning optimization is more important to minimize maintenance costs and power generation loss by downtime. Additionally, the power generation of a wind farm is affected by wind speed as well as wind direction because of the wake effect, so it is possible that power generation loss by downtime is also dependent on combinations of weather conditions (wind speed and direction) and the location of wind turbines for maintenance. In this study, the effects of the wind conditions and the locations of tripped wind turbines on power generation loss were explored for a hypothetical floating offshore wind farm. In order to calculate the power generation of a wind farm, a wake effect calculator was developed based on Jensen's formula. Then, a simple methodology of determining maintenance priorities that minimize power generation loss was proposed.

Performance Comparison between Neural Network Model and Statistical Model for Prediction of Damage Cost from Storm and Flood (신경망 모델과 확률 모델의 풍수해 예측성능 비교)

  • Choi, Seon-Hwa
    • The KIPS Transactions:PartB
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    • v.18B no.5
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    • pp.271-278
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    • 2011
  • Storm and flood such as torrential rains and major typhoons has often caused damages on a large scale in Korea and damages from storm and flood have been increasing by climate change and warming. Therefore, it is an essential work to maneuver preemptively against risks and damages from storm and flood by predicting the possibility and scale of the disaster. Generally the research on numerical model based on statistical methods, the KDF model of TCDIS developed by NIDP, for analyzing and predicting disaster risks and damages has been mainstreamed. In this paper, we introduced the model for prediction of damage cost from storm and flood by the neural network algorithm which outstandingly implements the pattern recognition. Also, we compared the performance of the neural network model with that of KDF model of TCDIS. We come to the conclusion that the robustness and accuracy of prediction of damage cost on TCDIS will increase by adapting the neural network model rather than the KDF model.

Cost Distribution Strategies in the Film Industry: the Simplex Method (영화의 유통전략에 대한 연구: 심플렉스 해법을 중심으로)

  • Hwang, Hee-Joong
    • Journal of Distribution Science
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    • v.14 no.10
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    • pp.147-152
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    • 2016
  • Purpose - High quality films are affected by both the production stage and various variables such as the size of the movie investment and marketing that changes consumers' perceptions. Consumer preferences should be recognized first to ensure that the movie is successful. If a film is produced without pre-investigation and analysis of consumer demand and taste, the probability of success will be low. This study investigates the balance of production costs, marketing costs, and profits using game theory, suggesting an optimization strategy using the simplex method of linear programming. Research design, data, and methodology - Before the release of the movie, initial demand is assumed to be driven largely by marketing costs. In the next phase, demand is assumed to be driven purely by a movie's production cost and quality, which might also further determine consumer demand. Thus, it is essential to determine how to distribute pure production costs and other costs (marketing) in a limited movie production budget. Moreover, it should be taken into account how to optimally distribute under the assumption that the audience and production company's input resources are limited. This research simplifies the assumptions for large-scale and relatively small-scale movie investments and examines how movie distribution participant profits differ when each cost is invested differently. Results - When first movers or market leaders have to choose both quality and marketing, it has been proven that pursuing a strategy choosing only one is more likely than choosing both. In this situation, market leaders should maximize marketing costs under the premise that market leaders will not lag their quality behind the quality of second movers. Additionally, focusing on movie marketing that produces a quick effect while ceding creative activity to increase movie quality is a natural outcome in the movie distribution environment since a cooperative strategy between market competitors is not feasible. Conclusions - Government film development policy should ignore quality competition between movie production companies and focus on preventing marketing competition. If movie production companies focus on movie production quality improvement then a creative competition would ensue.

3D Printing in Modular Construction: Opportunities and Challenges

  • Li, Mingkai;Li, Dezhi;Zhang, Jiansong;Cheng, Jack C.P.;Gan, Vincent J.L.
    • International conference on construction engineering and project management
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    • 2020.12a
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    • pp.75-84
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    • 2020
  • Modular construction is a construction method whereby prefabricated volumetric units are produced in a factory and are installed on site to form a building block. The construction productivity can be substantially improved by the manufacturing and assembly of standardized modular units. 3D printing is a computer-controlled fabrication method first adopted in the manufacturing industry and was utilized for the automated construction of small-scale houses in recent years. Implementing 3D printing in the fabrication of modular units brings huge benefits to modular construction, including increased customization, lower material waste, and reduced labor work. Such implementation also benefits the large-scale and wider adoption of 3D printing in engineering practice. However, a critical issue for 3D printed modules is the loading capacity, particularly in response to horizontal forces like wind load, which requires a deeper understanding of the building structure behavior and the design of load-bearing modules. Therefore, this paper presents the state-of-the-art literature concerning recent achievement in 3D printing for buildings, followed by discussion on the opportunities and challenges for examining 3D printing in modular construction. Promising 3D printing techniques are critically reviewed and discussed with regard to their advantages and limitations in construction. The appropriate structural form needs to be determined at the design stage, taking into consideration the overall building structural behavior, site environmental conditions (e.g., wind), and load-carrying capacity of the 3D printed modules. Detailed finite element modelling of the entire modular buildings needs to be conducted to verify the structural performance, considering the code-stipulated lateral drift, strength criteria, and other design requirements. Moreover, integration of building information modelling (BIM) method is beneficial for generating the material and geometric details of the 3D printed modules, which can then be utilized for the fabrication.

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Overproduction of Xanthophyll Pigment in Flavobacterium sp. JSWR-1 under Optimized Culture Conditions

  • Jegadeesh Raman;Young-Joon Ko;Jeong-Seon Kim;Da-Hye Kim;Soo-Jin Kim
    • Journal of Microbiology and Biotechnology
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    • v.34 no.3
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    • pp.710-724
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    • 2024
  • Flavobacterium can synthesize xanthophyll, particularly the pigment zeaxanthin, which has significant economic value in nutrition and pharmaceuticals. Recently, the use of carotenoid biosynthesis by bacteria and yeast fermentation technology has shown to be very efficient and offers significant advantages in large-scale production, cost-effectiveness, and safety. In the present study, JSWR-1 strain capable of producing xanthophyll pigment was isolated from a freshwater reservoir in Wanju-gun, Republic of Korea. Based on the morphological, physiological, and molecular characteristics, JSWR-1 classified as belonging to the Flavobacterium species. The bacterium is strictly aerobic, Gram-negative, rod-shaped, and psychrophilic. The completed genome sequence of the strain Flavobacterium sp. JSWR-1 is predicted to be a single circular 3,425,829-bp chromosome with a G+C content of 35.2% and 2,941 protein-coding genes. The optimization of carotenoid production was achieved by small-scale cultivation, resulting in zeaxanthin being identified as the predominant carotenoid pigment. The enhancement of zeaxanthin biosynthesis by applying different light-irradiation, variations in pH and temperature, and adding carbon and nitrogen supplies to the growth medium. A significant increase in intracellular zeaxanthin concentrations was also recorded during fed-batch fermentation achieving a maximum of 16.69 ± 0.71 mg/l, corresponding to a product yield of 4.05 ± 0.15 mg zeaxanthin per gram cell dry weight. Batch and fed-batch culture extracts exhibit significant antioxidant activity. The results demonstrated that the JSWR-1 strain can potentially serve as a source for zeaxanthin biosynthesis.

Assessing the Vulnerability of Network Topologies under Large-Scale Regional Failures

  • Peng, Wei;Li, Zimu;Liu, Yujing;Su, Jinshu
    • Journal of Communications and Networks
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    • v.14 no.4
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    • pp.451-460
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    • 2012
  • Natural disasters often lead to regional failures that can cause network nodes and links co-located in a large geographical area to fail. Novel approaches are required to assess the network vulnerability under such regional failures. In this paper, we investigate the vulnerability of networks by considering the geometric properties of regional failures and network nodes. To evaluate the criticality of node locations and determine the critical areas in a network, we propose the concept of ${\alpha}$-critical-distance with a given failure impact ratio ${\alpha}$, and we formulate two optimization problems based on the concept. By analyzing the geometric properties of the problems, we show that although finding critical nodes or links in a pure graph is a NP-complete problem, the problem of finding critical areas has polynomial time complexity. We propose two algorithms to deal with these problems and analyze their time complexities. Using real city-level Internet topology data, we conducted experiments to compute the ${\alpha}$-critical-distances for different networks. The computational results demonstrate the differences in vulnerability of different networks. The results also indicate that the critical area of a network can be estimated by limiting failure centers on the locations of network nodes. Additionally, we find that with the same impact ratio ${\alpha}$, the topologies examined have larger ${\alpha}$-critical-distances when the network performance is measured using the giant component size instead of the other two metrics. Similar results are obtained when the network performance is measured using the average two terminal reliability and the network efficiency, although computation of the former entails less time complexity than that of the latter.