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Relevant bibliographies by topics / Bid Optimizer

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Academic literature on the topic 'Bid Optimizer'

Author: Grafiati

Published: 6 September 2023

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Journal articles on the topic "Bid Optimizer"

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Ferraz, José Euclides De Melo, and Christian Johannes Zimmer. "Inclusão de Custos de Transação Não-Lineares na Otimização Média-Variância." Brazilian Review of Finance 3, no. 2 (January 1, 2005): 195. http://dx.doi.org/10.12660/rbfin.v3n2.2005.1150.

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In this article we propose a new way to include transaction costs into a mean-variance portfolio optimization. We consider brokerage fees, bid/ask spread and the market impact of the trade. A pragmatic algorithm is proposed, which approximates the optimal portfolio, and we can show that is converges in the absence of restrictions. Using Brazilian financial market data we compare our approximation algorithm with the results of a non-linear optimizer.

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Patil, Ganesh Sampatrao, Anwar Mulla, Subhojit Dawn, and Taha Selim Ustun. "Profit Maximization with Imbalance Cost Improvement by Solar PV-Battery Hybrid System in Deregulated Power Market." Energies 15, no. 14 (July 21, 2022): 5290. http://dx.doi.org/10.3390/en15145290.

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The changeable nature of renewable sources creates difficulties in system security and stability. Therefore, it is necessary to study system risk in several power system scenarios. In a wind-integrated deregulated power network, the wind farm needs to submit the bid for its power-generating quantities a minimum of one day ahead of the operation. The wind farm submits the data based on the expected wind speed (EWS). If any mismatch occurs between real wind speed (RWS) and expected wind speed, ISO enforces the penalty/rewards to the wind farm. In a single word, this is called the power market imbalance cost, which directly distresses the system profit. Here, solar PV and battery energy storage systems are used along by the wind farm to exploit system profit by grasping the negative outcome of imbalance cost. Along with system profit, the focus has also been on system risk. The system risk has been calculated using the risk assessment factors, i.e., Value-at-Risk (VaR) and Cumulative Value-at-risk (CVaR). The work is performed on a modified IEEE 14 and modified IEEE 30 bus test system. The solar PV-battery storage system can supply the demand locally first, and then the remaining power is given to the electrical grid. By using this concept, the system risk can be minimized by the incorporation of solar PV and battery storage systems, which have been studied in this work. A comparative study has been performed using three dissimilar optimization methods, i.e., Artificial Gorilla Troops Optimizer Algorithm (AGTO), Artificial Bee Colony Algorithm (ABC), and Sequential Quadratic Programming (SQP) to examine the consequence of the presented technique. The AGTO has been used for the first time in the risk assessment and alleviation problem, which is the distinctiveness of this work.

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Jinba, Takahiro, Hiroto Kitagawa, Eriko Azuma, Keiji Sato, Hiroyuki Sato, Kiyohiko Hattori, and Keiki Takadama. "Multi-objective Optimization for Common and Special Components: First Step Toward Network Optimization of Regular and Non-Regular Flights." New Mathematics and Natural Computation 11, no. 02 (May 20, 2015): 183–99. http://dx.doi.org/10.1142/s1793005715400050.

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To optimize the problem composed of (i) the common components which should be optimized from the viewpoint of all objective functions and (ii) the special components which should be optimized from the viewpoint of one of the objective functions, this paper proposes a new multi-objective optimization method which optimizes not only the common components for all objective functions but also the special ones for each objective function. To investigate the effectiveness of the proposed method, this paper tested our method on the test-bed problem which is an extended version of the 0/1 knapsack problem. The intensive experiments have revealed the following implications: (i) Our method finds better solutions which have higher fitness than the conventional method (NSGA-II); (ii) our method can find the solutions that had a large norm (which corresponds to a high profit of an airline company in the flight scheduling problem) with the high rate of the common components; and (iii) since the crowding distance employed in our method contributes to keeping the diversity during the solution search, our method has high exploration capability of solutions.

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S. B, Rashmi, Praveen B, and Tilak B G. "Design of Optimized Reversible BCD Adder/Subtractor." International Journal of Engineering and Technology 3, no. 3 (2011): 230–34. http://dx.doi.org/10.7763/ijet.2011.v3.229.

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Ren, Yu Yan, Jie Bao, Ming Sun, and Hong Rui Wang. "Application of SVM Based on Improved Quantum Particle Swarm Optimization in Bio-Mimetic Robotic Horse." Advanced Materials Research 204-210 (February 2011): 306–9. http://dx.doi.org/10.4028/www.scientific.net/amr.204-210.306.

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Quantum principles is introduced in particle swarm optimization to optimize SVM, aiming that common optimization algorithms of SVM are easy to relapse into local extreme values and optimization result bad. Quantum particle swarm optimization can improve traverse property of particle, thus can overcome the limitation of local extreme values and optimize SVM well. Use the optimized SVM to control the motion of bio-mimetic robotic horse. And simulation results show that this algorithm can achieve the best control effect quickly and accurately.

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Yang, Dalian, Jingjing Miao, Fanyu Zhang, Jie Tao, Guangbin Wang, and Yiping Shen. "Bearing Fault Diagnosis Using a Support Vector Machine Optimized by an Improved Ant Lion Optimizer." Shock and Vibration 2019 (June 27, 2019): 1–20. http://dx.doi.org/10.1155/2019/9303676.

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Bearing is an important mechanical component that easily fails in a bad working environment. Support vector machines can be used to diagnose bearing faults; however, the recognition ability of the model is greatly affected by the kernel function and its parameters. Unfortunately, optimal parameters are difficult to select. To address these limitations, an escape mechanism and adaptive convergence conditions were introduced to the ALO algorithm. As a result, the EALO method was proposed and has been applied to the more accurate selection of SVM model parameters. To assess the model, the vibration acceleration signals of normal, inner ring fault, outer ring fault, and ball fault bearings were collected at different rotation speeds (1500 r/min, 1800 r/min, 2100 r/min, and 2400 r/min). The vibration signals were decomposed using the variational mode decomposition (VMD) method. The features were extracted through the kernel function to fuse the energy value of each VMD component. In these experiments, the two most important parameters for the support vector machine—the Gaussian kernel parameter σ and the penalty factor C—were optimized using the EALO algorithm, ALO algorithm, genetic algorithm (GA), and particle swarm optimization (PSO) algorithm. The performance of these four methods to optimize the two parameters was then compared and analyzed, with the EALO method having the best performance. The recognition rates for bearing faults under different tested rotation speeds were improved when the SVM model parameters optimized by the EALO were used.

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Shivakumar, R., R. Lakshmipathi, and Y. Suresh. "Implementation of Bio Inspired Genetic Optimizer in enhancing Power System Stability." International Journal of Engineering and Technology 2, no. 3 (2010): 263–68. http://dx.doi.org/10.7763/ijet.2010.v2.131.

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Schäpper, Daniel, Rita Lencastre Fernandes, Anna Eliasson Lantz, Fridolin Okkels, Henrik Bruus, and Krist V. Gernaey. "Topology optimized microbioreactors." Biotechnology and Bioengineering 108, no. 4 (December 1, 2010): 786–96. http://dx.doi.org/10.1002/bit.23001.

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Regalado-Méndez, Alejandro, Martín Ruiz, José A. Hernández-Servín, Reyna Natividad, Rubi Romero, Mario E. Cordero, Carlos Estrada-Vázquez, and Ever Peralta-Reyes. "Electrochemical Mineralization of Ibuprofen on BDD Electrodes in an Electrochemical Flow Reactor: Numerical Optimization Approach." Processes 8, no. 12 (December 17, 2020): 1666. http://dx.doi.org/10.3390/pr8121666.

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Statistical analysis was applied to optimize the electrochemical mineralization of ibuprofen with two boron-doped diamond (BDD) electrodes in a continuous electrochemical flow reactor under recirculation batch mode. A central composite rotatable (CCR) experimental design was used to analyze the effect of initial pH (2.95–13.04), current intensity (2.66–4.34 A), and volumetric flow rate (0.16–1.84 L/min) and further optimized by response surface methodology (RSM) to obtain the maximum mineralization efficiency and the minimum specific energy consumption. A 91.6% mineralization efficiency (EM) of ibuprofen with a specific energy consumption (EC) of 4.36 KW h/g TOC within 7 h of treatment was achieved using the optimized operating parameters (pH0 = 12.29, I = 3.26 A, and Q of 1 L/min). Experimental results of RSM were fitted via a third-degree polynomial regression equation having the performance index determination coefficients (R2) of 0.8658 and 0.8468 for the EM and EC, respectively. The reduced root-mean-square error (RMSE) was 0.1038 and 0.1918 for EM and EC, respectively. This indicates an efficient predictive performance to optimize the operating parameters of the electrochemical flow reactor with desirability of 0.9999993. Besides, it was concluded that the optimized conditions allow to achieve a high percentage of ibuprofen mineralization (91.6%) and a cost of 0.002 USD $/L. Therefore, the assessed process is efficient for wastewater remediation.”

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Huiqing, Zhang, Ye Chunsong, Zhang Xian, Yang Fan, Yang Jun, and Zhou Wei. "Optimization of photo-Fenton process of RO concentrated coking wastewater using response surface methodology." Water Science and Technology 66, no. 4 (August 1, 2012): 816–23. http://dx.doi.org/10.2166/wst.2012.254.

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The objective of this study was aimed at investigating the removal of chemical oxygen demand (COD) from reverse osmosis (RO) concentrated coking wastewater by the photo-Fenton process. The optimum extraction conditions for the photo-Fenton process by Box–Behnken design (BBD) and response surface methodology (RSM) to establish a predictive polynomial quadratic model were discussed based on a single factor test. Optimized parameters validated by the analysis of variances (ANOVA) were found to be H2O2 concentration of 345.2 mg/L, pH value of 4.1 and reaction time of 103.5 minutes under ultraviolet irradiation. The experimental results of the COD removal under the optimized conditions presented better agreement with the predicted values with deviation error of 3.2%. The results confirmed that RSM based on BBD was a suitable method to optimize the operating conditions of RO concentrated coking wastewater.

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Dissertations / Theses on the topic "Bid Optimizer"

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Bhandare, Ashray Sadashiv. "Bio-inspired Algorithms for Evolving the Architecture of Convolutional Neural Networks." University of Toledo / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1513273210921513.

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Correll, David. "Optimized landscape plans for bio-oil production." [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1464191.

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Schamberger, Stefan. "Shape optimized graph partitioning." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=983282455.

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Mazzotti, Matilde <1986&gt. "Physiological studies to optimize algal biomass production in phytoremediation processes." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/6934/1/tesi_Matilde_Mazzotti.pdf.

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Nowadays microalgae are studied, and a number of species already mass-cultivated, for their application in many fields: food and feed, chemicals, pharmaceutical, phytoremediation and renewable energy. Phytoremediation, in particular, can become a valid integrated process in many algae biomass production systems. This thesis is focused on the physiological and biochemical effects of different environmental factors, mainly macronutrients, lights and temperature on microalgae. Microalgal species have been selected on the basis of their potential in biotechnologies, and nitrogen occurs in all chapters due to its importance in physiological and applicative fields. There are 5 chapters, ready or in preparation to be submitted, with different specific matters: (i) to measure the kinetic parameters and the nutrient removal efficiencies for a selected and local strain of microalgae; (ii) to study the biochemical pathways of the microalga D. communis in presence of nitrate and ammonium; (iii) to improve the growth and the removal efficiency of a specific green microalga in mixotrophic conditions; (iv) to optimize the productivity of some microalgae with low growth-rate conditions through phytohormones and other biostimulants; and (v) to apply the phyto-removal of ammonium in an effluent from anaerobic digestion. From the results it is possible to understand how a physiological point of view is necessary to provide and optimize already existing biotechnologies and applications with microalgae.

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Mazzotti, Matilde <1986&gt. "Physiological studies to optimize algal biomass production in phytoremediation processes." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/6934/.

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Nowadays microalgae are studied, and a number of species already mass-cultivated, for their application in many fields: food and feed, chemicals, pharmaceutical, phytoremediation and renewable energy. Phytoremediation, in particular, can become a valid integrated process in many algae biomass production systems. This thesis is focused on the physiological and biochemical effects of different environmental factors, mainly macronutrients, lights and temperature on microalgae. Microalgal species have been selected on the basis of their potential in biotechnologies, and nitrogen occurs in all chapters due to its importance in physiological and applicative fields. There are 5 chapters, ready or in preparation to be submitted, with different specific matters: (i) to measure the kinetic parameters and the nutrient removal efficiencies for a selected and local strain of microalgae; (ii) to study the biochemical pathways of the microalga D. communis in presence of nitrate and ammonium; (iii) to improve the growth and the removal efficiency of a specific green microalga in mixotrophic conditions; (iv) to optimize the productivity of some microalgae with low growth-rate conditions through phytohormones and other biostimulants; and (v) to apply the phyto-removal of ammonium in an effluent from anaerobic digestion. From the results it is possible to understand how a physiological point of view is necessary to provide and optimize already existing biotechnologies and applications with microalgae.

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Vanden, Berg Andrew M. "Optimization-simulation framework to optimize hospital bed allocation in academic medical centers." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120223.

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Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 99-100).
Congestion, overcrowding, and increasing patient wait times are major challenges that many large, academic centers currently face. To address these challenges, hospitals must effectively utilize available beds through proper strategic bed allocation and robust operational day-to-day bed assignment policies. Since patient daily demand for beds is highly variable, it is frequent that the physical capacity allocated to a given clinical service is not sufficient to accommodate all of the patients who belong to that service. This situation could lead to extensive wait time of patients in various locations in the hospital (e.g., the emergency department), as well as clinically and operationally undesirable misplacements of patients in hospital floors/beds that are managed by other clinical services than the ones to which the patients belong. In this thesis, we develop an optimization-simulation framework to optimize the bed allocation at Mass General Hospital. Detailed, data-driven simulation suggests that the newly proposed bed allocation would lead to significant reduction in patient intra-day wait time in the emergency department and other hospital locations, as well as a major reduction in the misplacements of patients in the Medicine service, which is the largest service in the hospital. We employ a two-pronged approach. First, we developed a detailed simulation setting of the entire hospital that could be used to assess the effectiveness of day-to-day operational bed assignment policies given a specific bed allocation. However, the simulation does not allow tractable optimization that seeks to find the best bed allocation among all possible allocations. This motivates the development of a network-flow/network design inspired mixed integer program that approximates the operational performance of bed allocations and allows us to effectively search for approximately the best allocation. The mixed integer program can be solved via a scenario sampling approach to provide candidate bed allocations. These are then tested and evaluated via the simulation setting. These tools facilitate expert discussions on how to modify the existing bed allocation at MGH to improve the day-to-day performance of the bed assignment process.
by Andrew M. Vanden Berg.
S.M.

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Thelen, Andrea. "Optimized surface extraction from holographic data." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=980418798.

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Bär, Werner. "Optimized delivery of intensity modulated radiotherapy." [S.l.] : [s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=965610934.

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Abbruzzese, Vito. "Using bio-manipulation to optimise nutrient management within intensive farm systems." Thesis, Lancaster University, 2017. http://eprints.lancs.ac.uk/86607/.

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Optimising the use of organic amendments, such as livestock slurry, on commercial farms represents one route through which the reliance of agricultural production on inorganic fertiliser use might be reduced. For economic, environmental and geopolitical reasons, decoupling future agricultural production from inorganic fertiliser use is desirable, particularly if increases in future demand for food at global scale are to be met sustainably. However, there remains substantial uncertainty surrounding the impacts of organic amendments on many of the key physico-chemical and microbial properties of agricultural soils. This uncertainty reduces the likelihood that land owners and land managers will adjust farming practices in order to deliver more widespread use of organic amendments to support production. In this context, the research reported in this thesis sought to understand how the management of livestock slurry within intensive grassland systems can be optimised to support production. The thesis had a particular focus on understanding how the soil microbial community mediates the input of livestock slurry, in terms of the influence of this community on the cycling and crop-availability of macronutrients within soil. The thesis first examined the impact of a biological slurry additive, SlurryBugs, on the nutrient content of livestock slurry during storage, finding positive effects of the additive particularly with respect to the total phosphorus (P), where an increase by 27% was observed compared to the control slurry treatment, and the total solids contents of slurry during storage. It was hypothesised that the SB additive may have altered the emission of phosphine (PH3) from slurry during storage. Subsequently, the impacts of slurry application, both with and without the biological additive, on soil organic matter (SOM), as well as on the nitrogen (N) and P content of grassland soils were examined, in comparison to inorganic fertiliser and control treatments. Positive effects following slurry application were observed, spanning SOM, Olsen P, mineral N and soil pH conditions. Finally, the impacts of applying slurry alongside a range of carbon (C) substrates of different quality (glucose, glucose-6-phosphate (G6P), and cellulose) to a grassland soil were examined, in terms of the partitioning of C within soil as mediated by the microbial community and in terms of changes in the structure and biomass of the soil microbial community. The results revealed an increase in the soil microbial biomass, as well as a decrease in the cumulative respiration, following the application of both slurry types, alongside a carbohydrate, compared to the treatment with the carbohydrate alone, likely due to a microbial metabolic mechanism known as preferential substrate utilisation. In addition, a bacterial predominance within the soil microbial community was observed in all treatments, with increasing dominance of fungi toward the end of the 49-day incubations. This thesis also revealed that the quality of C substrates represented a major factor affecting both the extent of mineralisation and of incorporation of externally-derived C into microbial biomass. The application of 14C-glucose or 14C-G6P to soil resulted in a significantly greater incorporation of 14C into microbial biomass by 68 or 57%, respectively, compared to 41% following the 14C-cellulose application. Further, the addition of US slurry alongside 14C-glucose generated a significantly greater extent of mineralisation by 30%, compared to the treatments with AS slurry or with only 14C-glucose added with 19 and 21%, respectively. Taken together, the data reported within this thesis have potentially important implications for the way in which livestock slurry is managed as a nutrient resource on commercial farms, as well as for broader environmental concerns including the acidification of agricultural soils and the impact of agricultural soils on the global C cycle.

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陳從輝 and Chung-fai Chan. "MOS parameter extraction globally optimized with genetic algorithm." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31212785.

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Books on the topic "Bid Optimizer"

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Enterprise analytics: Optimize performance, process, and decisions through big data. Upper Saddle River, N.J: FT Press, 2013.

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Boer, Brian. Optimized core design and fuel management of a pebble-bed type nuclear reactor. Amsterdam: IOS Press, 2008.

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Thompson, David C. (Attorney), author, ed. The reputation economy: How to optimize your digital footprint in a world where your reputation is your most valuable asset. London: Piatkus, 2015.

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Wessely, Christian, and Theresia Heimerl, eds. Weltentwürfe im Comic/film. Schüren Verlag, 2018. http://dx.doi.org/10.5771/9783741001260.

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Comics, bis in die späten 1990er-Jahre oft als kulturelles Randprodukt gering geschätzt, geraten in Zeiten der multimedialen Kommunikation zunehmend in den Aufmerksamkeitsfokus. Im Comic erscheint das Bild auf das Allerwesentlichste hin destilliert und durch das Medium Text erweitert. In einem bis wenigen Bildern lassen sich so, optimiert für die Aufmerksamkeitsspanne der Web 2.0-Generation, weltanschauliche, religiöse und soziale Probleme formulieren und zugleich scheinbare oder tatsächliche Lösungsvorschläge transportieren. Ihr Potential für ein Millionenpublikum entfalten sie in den letzten Dekaden aber durch zahlreiche Verfilmungen, ob als Anime, Arthouse oder Blockbuster. Die Erforschung dieses Potentials ist noch weitgehend unentdecktes Gebiet. In diesem Band werden erste Akzente gesetzt.

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Big data en recursos humanos : analytics y metricas para optimizar el rendimiento - 1. edicion. Ecoe Ediciones, 2019.

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Pease, Gene. Optimize your greatest asset--your people: How to apply analytics to big data to improve your human capital investments. 2015.

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Phillips, Katharine A. Pharmacotherapy and Other Somatic Treatments for Body Dysmorphic Disorder. Edited by Katharine A. Phillips. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190254131.003.0025.

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This chapter discusses pharmacotherapy for body dysmorphic disorder (BDD), including barriers to treatment, essential groundwork for prescribing, first-line treatment with serotonin-reuptake inhibitors (SRIs), and optimal dosing and trial duration (higher SRI doses and longer trials are more often needed for BDD than for most other disorders). SRIs are the first-line medication treatment for both delusional BDD and nondelusional BDD. Medication may be used for BDD of mild to moderate severity, and it is essential for more severely ill and suicidal patients and for those with severe depressive symptoms. Pharmacotherapy that is optimized for BDD usually alleviates symptoms and not uncommonly leads to remission. The chapter also discusses steps to take when an SRI is not effective, such as raising the SRI dose even further as well as SRI augmentation and switching strategies. SRI continuation and discontinuation, and the potential usefulness of non-SRI medications and other somatic treatments are also discussed. Challenges that clinicians often encounter when treating BDD and that can be addressed with pharmacotherapy—severe depression, suicidality, and problematic substance use—are also discussed.

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Parikh, Dilip. How to Optimize Fluid Bed Processing Technology: Part of the Expertise in Pharmaceutical Process Technology Series. Elsevier Science & Technology Books, 2017.

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Holdaway, Keith R. Harness Oil and Gas Big Data with Analytics: Optimize Exploration and Production with Data-Driven Models. Wiley & Sons, Incorporated, John, 2014.

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Holdaway, Keith. Harness Oil and Gas Big Data with Analytics: Optimize Exploration and Production with Data Driven Models. Wiley & Sons, Incorporated, John, 2014.

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Book chapters on the topic "Bid Optimizer"

1

Chen, Xuxi, Tianlong Chen, Yu Cheng, Weizhu Chen, Ahmed Awadallah, and Zhangyang Wang. "Scalable Learning to Optimize: A Learned Optimizer Can Train Big Models." In Lecture Notes in Computer Science, 389–405. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20050-2_23.

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Ambrosino, Daniela, and Anna Sciomachen. "Using a Bin Packing Approach for Stowing Hazardous Containers into Containerships." In Optimized Packings with Applications, 1–18. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18899-7_1.

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Weber, Matthias, Patrick Goodwill, and Steven Conolly. "Mouse Bed Optimized for MPI." In Springer Proceedings in Physics, 331–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24133-8_53.

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Leke, Collins Achepsah, and Tshilidzi Marwala. "Missing Data Estimation Using Ant-Lion Optimizer Algorithm." In Studies in Big Data, 103–14. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01180-2_7.

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Jolly, Jessica. "Optimize Model Performance." In Microsoft Power BI Data Analyst Certification Companion, 187–91. Berkeley, CA: Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9013-2_8.

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Shao, Yanling, and Wenyong Dong. "Considering User Distribution and Cost Awareness to Optimize Server Deployment." In Big Data, 135–47. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1899-7_10.

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Liu, Lianye, Jinping Liu, Juanjuan Wu, Jiaming Zhou, and Meiling Cai. "Novelty Detection-Based Automated Anomaly Identification via Optimized Deep Generative Model." In Big Data, 117–34. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9709-8_9.

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Muzi, Francesco, Riccardo Marzo, and Francesco Nardi. "Digital Information Management in the Built Environment: Data-Driven Approaches for Building Process Optimization." In The Urban Book Series, 123–32. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-29515-7_12.

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AbstractIn Italy, the traditional management of construction works, throughout life cycle, still dominates the market compared to a digital approach. This research aims at bringing out the potential and benefits of a digital management by developing strategies and methodologies able to optimize processes related to three different use cases. The proposed use cases have been developed by applying digital methodologies to different building contexts, aiming at both site management and management of the built environment. The first case deals with an important public building of 35,000 m2 located in a residential context in the center of Rome. The use of digital methodology made it possible to optimize and prevent problems related to large-scale works and construction sites located in central residential areas. The second case concerns a residential complex of 16 buildings located in Rome, where the BIM model supplies a constant flow of information for predictive maintenance system. The last one refers to port infrastructures located on the coast of Lazio region in Italy. The digital information model was developed to set up a risk management system capable of safely managing the port’s main assets. In conclusion, the results achieved through the implementation of a digital approach generated by a structured information flow integrated with the BIM model, allowed an optimized management of time and economic resources in the three case studies mentioned, although the diversity of objectives and types of construction works. This improvement is made possible by a shared and connected digital model, characterized by a high level of geometric and informative detail and cloud computing strategies to enhance process efficiency, supporting decision-making and information management.

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Su, Man-Na, Zhi-Jian Fang, Shao-Zhen Ye, Ying-Jie Wu, and Yang-Geng Fu. "An Optimized Artificial Bee Colony Based Parameter Training Method for Belief Rule-Base." In Big Data, 77–93. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2922-7_5.

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Roy, Chandrima, Kashyap Barua, Sandeep Agarwal, Manjusha Pandey, and Siddharth Swarup Rautaray. "Horizontal Scaling Enhancement for Optimized Big Data Processing." In Advances in Intelligent Systems and Computing, 639–49. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1951-8_58.

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Conference papers on the topic "Bid Optimizer"

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Sriram, Somanchi, Nittala Chaitanya, and Yadati Narahari. "A Novel Bid Optimizer for Sponsored Search Auctions Using Cooperative Game Theory." In 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology. IEEE, 2009. http://dx.doi.org/10.1109/wi-iat.2009.191.

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Sahoo, Manoranjan, Nibha Rani, and Tanmoy Malakar. "A Solution of Bid-based dynamic economic load dispatch using Competitive Swarm Optimizer approach." In 2020 IEEE Students Conference on Engineering & Systems (SCES). IEEE, 2020. http://dx.doi.org/10.1109/sces50439.2020.9236697.

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O’Rourke, Julia M., and Carolyn C. Seepersad. "Examining Efficiency in Bioinspired Design." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-13147.

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In what ways and to what extent are bioinspired designs (BIDs) and the biological systems that inspire them ‘efficient’? The answer to this question provides insight into the potential role BID could have in the generation of energy- and materials-efficient designs. By qualifying and clarifying efficiency-related claims in the context of biological evidence, this paper contributes to the theoretical foundation for BID for efficiency and provides guidance to those developing design tools and methodologies aimed at using BID to enhance the efficiency of engineered products and systems. This paper is organized into three main sections. First, a study is presented examining the reasons authors in the BID community cite when motivating their work. Of the 127 sources analyzed, 40 referenced ‘efficiency’, establishing empirically that efficiency of BIDs and the biological organisms that inspire them is a central motivation for work in BID. Second, efficiency-related claims most commonly made by authors in BID are explained and analyzed using authoritative biological and BID literature. Ultimately, some of the claims prove problematic. However, when qualified appropriately, these claims provide significant insight into how the oft-cited examples of efficiency in biology and BID have arisen. Finally, a study uncovering trends in sustainable BIDs is presented, and the efficiency-related trends are discussed. This study provides examples of some efficiency-related characteristics of biological systems that are successfully being transferred to engineered products and systems through BID. Specifically, the sustainable BIDs analyzed are shown to frequently meet four efficiency-related green design guidelines (GDGs) better than functionally-equivalent non-bioinspired alternatives. Additionally, passive mechanisms, multifunctional designs, and optimized geometries are discussed and shown to be prevalent in the sample of sustainable BIDs studied.

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Singh, Sachchidanand. "Optimize cloud computations using edge computing." In 2017 International Conference on Big Data, IoT and Data Science (BID). IEEE, 2017. http://dx.doi.org/10.1109/bid.2017.8336572.

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Sui, Jianbo, and Naohiko Sugita. "Optimization of Drill Bits for Bone Drilling Procedure." In ASME 2018 13th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/msec2018-6340.

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The paper presents a methodology to optimize drill bits to realize safe drilling of bone materials for many surgeries like orthopedics and neurosurgery. First, a mechanistic model is introduced to relate drilling forces to main drill bit geometry parameters. Then a genetic algorithm is developed to optimize drill bit geometry parameters by minimization of drilling forces based on the mechanistic model. Finally prototypes of drill bits with optimized geometry parameters are produced and drilling experiments are conducted to verify the advantages of these new drill bits. The results show that by comparison with normal drill bit, the average drilling forces are reduced to more than 50% by drill bits with optimized geometry parameters under a wide range of drilling conditions.

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Giftson Joy, John Abish, and Robello Samuel. "Fast Drilling Optimizer for Drilling Automation." In SPE Western Regional Meeting. SPE, 2021. http://dx.doi.org/10.2118/200881-ms.

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Abstract The rate of penetration (ROP) was optimized using a particle swarm optimization algorithm for real-time field data to reduce drilling time and increase efficiency. ROP is directly related to drilling costs and is a major factor in determining mechanical specific energy, which is often used to quantify drilling efficiency. Optimization of ROP can therefore help cut down costs associated with drilling. ROP values were chosen from real-time field data, accounting for weight on bit, bit rotation, flow rate variation along with bit wear. A random forest regressor was used to find correlations between the dependent parameters. The parameters were then optimized for the given constraints to find the optimal solution space. The boundary constraints for the ROP function were determined from the real-time data. The function parameters were optimized using a particle swarm optimization algorithm. This is a meta-heuristic model used to optimize an objective function for its maximum or minimum within given constraints. The optimization method makes use of a population of solution particles which act as the particle swarm. These particles move collectively in the given solution space controlled by a mathematical model based on their position and velocity. This model makes use of the best-known solution for each particle and the global best position of the system to guide the swarm towards the optimal solution. The function was optimized for each well, providing optimal ROP values during real-time drilling. A fast drilling optimizer is crucial to automate and streamline the drilling process. This simultaneous optimization of ROP based on real-time data can be implemented during the process thereby increasing the efficiency of drilling as well as reducing the required drilling time.

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Biju, Sofia, and N. M. Shekokar. "Optimize the energy efficiency of RPL based 6L0WPAN by FL clustering." In 2017 International Conference on Big Data, IoT and Data Science (BID). IEEE, 2017. http://dx.doi.org/10.1109/bid.2017.8336591.

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Bing, Zheng, Li Zhong-kai, and Feng Yi-xiong. "An exploratory study of sorting particle swarm optimizer for multiobjective optimization." In 2009 Fourth International Conference on Bio-Inspired Computing (BIC-TA). IEEE, 2009. http://dx.doi.org/10.1109/bicta.2009.5338139.

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Nunez, Ygnacio Jesus, Fernando Ruiz, Mouza Al Nuaimi, Alexander Amorocho, Nicola Connelly, Hany El-Hafez, and Juan Carlos Fierro. "Analysis of Fracturing Cutter Development and In-Bit Sensing Parameter Optimization when Drilling a Challenging Heterogeneous Section Containing Massive Cherts with a PDC Containing Both Shearing and Fracturing Elements." In Gas & Oil Technology Showcase and Conference. SPE, 2023. http://dx.doi.org/10.2118/214236-ms.

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Abstract A PDC design containing updated fracturing elements and utilizing in-bit sensing to optimize parameters can deliver improved ROP and drill a challenging heterogeneous section containing massive chert in one run compared to previously used PDC. The demonstration is supported by a real field case from an unconventional gas exploratory field project in Abu Dhabi. In this unconventional field, seven wells have been drilled using three bits on average to complete the 12 ¼″ section (tricone and PDC) where the presence of chert has resulted in additional trips due to bit life. The content of cherts are large, at approximately 2,000 ft thick, which is the reason why it was decided to think of a new customized PDC bit design and use it in well number seven. The plan is to prove that is possible to achieve one run to TD by fracturing cutter development and optimized drillers roadmap using in-bit sensing. The new unique PDC shaped cutter, with increased point surface area and thicker diamond table, makes the overall design more impact resistant and reduces vibrations while drilling. In bit sensing data is utilized to increase the efficiency in rock interaction through optimized parameters. It will be used in the ongoing exploratory project to demonstrate its advantage in terms of cost saving and rig time reduction. The study will compare the data with previously used bit and create a basement for the exploratory field in 12 ¼″ section. A strong hypothesis is that this bit will complete the well in this particular area and optimize drilling costs in development studies. Where such non-homogenous formations containing massive cherts can be crossed and have detrimental impact on the bit life, the novelty is to bring to the stage an enhanced combined PDC and parameter solution, which will be able to offer a different alternative by reducing torque, having healthier wells, and optimizing drilling cost in this unconventional field where drilling CAPEX reduction are paramount.

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Mao, Feng, Edgar Blanco, Mingang Fu, Rohit Jain, Anurag Gupta, Sebastien Mancel, Rong Yuan, Stephen Guo, Sai Kumar, and Yayang Tian. "Small Boxes Big Data: A Deep Learning Approach to Optimize Variable Sized Bin Packing." In 2017 IEEE Third International Conference on Big Data Computing Service and Applications (BigDataService). IEEE, 2017. http://dx.doi.org/10.1109/bigdataservice.2017.18.

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Reports on the topic "Bid Optimizer"

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Saydah, Ben, and Craig Behnke. Optimized Co-Processing of Algae Bio-Crude through a Petroleum Refinery. Office of Scientific and Technical Information (OSTI), March 2014. http://dx.doi.org/10.2172/1364623.

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Styles, Richard, Scott Glenn, and Mitchell Brown. An optimized combined wave and current bottom boundary layer model for arbitrary bed roughness. Coastal and Hydraulics Laboratory (U.S.), July 2017. http://dx.doi.org/10.21079/11681/22734.

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Abuhamad, Grace, Cory Salveson, Lilia Stubrin, and Carlos Braga. Abierta configuration options Inteligencia artificial en el sector de maquinaria agrícola de Argentina: diagnóstico de madurez y recomendaciones de política para acelerar la adopción. Inter-American Development Bank, February 2022. http://dx.doi.org/10.18235/0004000.

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Durante la última década, el ritmo de mejora de la inteligencia artificial (IA) sorprendió incluso a los más expertos, creando nuevos mercados y oportunidades de progreso en numerosas áreas. En el 2020, el BID decidió explorar opciones de política pública para promover la adopción de la IA y para ello, seleccionó el sector de la maquinaria agrícola de Argentina. Con cerca de 1,200 empresas, se trata de una industria intensiva en ciencia, tecnología e innovación, susceptible de introducir mejoras en autonomía y automatización en las máquinas existentes, desarrollar nuevos dispositivos y servicios, y optimizar procesos de negocio. Para el desarrollo de este proyecto, el BID contrató a Element AI, una de las compañías líderes en el desarrollo de IA a nivel mundial, para (1) evaluar la madurez del sector en la adopción de IA, a partir de un modelo de madurez que distingue cinco dimensiones (estrategia, datos, tecnología, recursos humanos y gobernanza), a lo largo de cinco etapas de madurez a través de las que evolucionan las empresas (exploración, experimentación, formalización, optimización y transformación), y (2) proponer recomendaciones para la acción, según tres perfiles de beneficiarios: firma, clúster y sector público. Este informe presenta los resultados de la evaluación de la madurez y una serie de conclusiones y propuestas, que pueden ser útiles para las futuras políticas públicas que estimulen el desarrollo y la adopción de aplicaciones de IA en el sector de la maquinaria agrícola argentina, y también en otros sectores industriales de la región.

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García Ferro, Luz Ángela, David Zepeda, and Dan Esteban Larrota Rojas. Guía para intercambios de conocimiento. Banco Interamericano de Desarrollo, July 2023. http://dx.doi.org/10.18235/0005025.

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En la era de la información y la rápida evolución tecnológica, el intercambio de conocimiento se ha convertido en un elemento crucial para el éxito y la innovación en las organizaciones. Diversas metodologías han surgido con el objetivo de facilitar y potenciar este intercambio, permitiendo a los individuos y grupos compartir y acceder a conocimientos de manera efectiva. Este documento revisa, analiza y explica algunas metodologías de intercambio de conocimiento desarrollada por la División de conocimiento y aprendizaje del BID, y que son utilizadas en distintos contextos, ya sea en países, sectores, ejes temáticos transversales, entre otros, donde los participantes trabajan juntos en la resolución de problemas complejos, adquiriendo conocimientos prácticos y fomentando el trabajo en equipo, así como el intercambio y generación de ideas creativas, planes de acción, entre otros. Estas metodologías promueven la colaboración y el aprendizaje colectivo, fomentando la transferencia y la generación de nuevo conocimiento y pueden usarse en un contexto virtual, presencial o híbrido. Al utilizar estas herramientas de manera efectiva, las organizaciones y comunidades pueden optimizar la transferencia de conocimiento, impulsando la generación de nuevas ideas y soluciones para afrontar los retos del mundo actual.

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Kumar, Kaushal, and Yupeng Wei. Attention-Based Data Analytic Models for Traffic Flow Predictions. Mineta Transportation Institute, March 2023. http://dx.doi.org/10.31979/mti.2023.2211.

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Traffic congestion causes Americans to lose millions of hours and dollars each year. In fact, 1.9 billion gallons of fuel are wasted each year due to traffic congestion, and each hour stuck in traffic costs about $21 in wasted time and fuel. The traffic congestion can be caused by various factors, such as bottlenecks, traffic incidents, bad weather, work zones, poor traffic signal timing, and special events. One key step to addressing traffic congestion and identifying its root cause is an accurate prediction of traffic flow. Accurate traffic flow prediction is also important for the successful deployment of smart transportation systems. It can help road users make better travel decisions to avoid traffic congestion areas so that passenger and freight movements can be optimized to improve the mobility of people and goods. Moreover, it can also help reduce carbon emissions and the risks of traffic incidents. Although numerous methods have been developed for traffic flow predictions, current methods have limitations in utilizing the most relevant part of traffic flow data and considering the correlation among the collected high-dimensional features. To address this issue, this project developed attention-based methodologies for traffic flow predictions. We propose the use of an attention-based deep learning model that incorporates the attention mechanism with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks. This attention mechanism can calculate the importance level of traffic flow data and enable the model to consider the most relevant part of the data while making predictions, thus improving accuracy and reducing prediction duration.

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Shamblin, Robert, Kevin Whelan, Mario Londono, and Judd Patterson. South Florida/Caribbean Network early detection protocol for exotic plants: Corridors of invasiveness. National Park Service, July 2022. http://dx.doi.org/10.36967/nrr-2293364.

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Exotic plant populations can be potentially catastrophic to the natural communities of South Florida. Aggressive exotics such as Brazillian Pepper (Schinus terebinthifolius) and Melaleuca (Melaleuca quinquinervia) have displaced native habitats and formed monocultures of exotic stands (Dalrymple et al. 2003). Nearby plant nurseries, especially the ones outside the boundaries of Biscayne National Park (BISC) and Everglades National Park (EVER), are a continuous source of new exotic species that may become established within South Florida’s national parks. Early detection and rapid response to these new species of exotic plants is important to maintaining the integrity of the parks’ natural habitats and is a cost-effective approach to management. The South Florida/Caribbean Network (SFCN) developed the South Florida/Caribbean Network Early Detection Protocol for Exotic Plants to target early detection of these potential invaders. Three national parks of South Florida are monitored for invasive, exotic plants using this protocol: Big Cypress National Preserve (BICY), Biscayne National Park (BISC), and Everglades National Park (EVER). These national parks include some 2,411,000 acres (3,767.2 square miles [mi2]) that encompass a variety of habitat types. To monitor the entire area for new species would not be feasible; therefore the basic approach of this protocol is to scan major “corridors of invasiveness,” e.g., paved and unpaved roads, trails, trail heads, off road vehicle (ORV) trails, boat ramps, canals, and campgrounds, for exotic plant species new to the national parks of South Florida. Sampling is optimized using a two- to three-person crew: a trained botanist, a certified herbicide applicator, and optionally a SFCN (or IPMT [Invasive Plant Management Team]) staff member or park staff to take photographs and help with data collection. If infestations are small, they are treated immediately by the herbicide applicator. If large, they are reported to park staff and the Invasive Plant Management Team. The sampling domain is partitioned into five regions, with one region sampled per year. Regions include the terrestrial habitats of Biscayne National Park, the eastern region of Everglades National Park, the western region of Everglades National Park, the northern region of Big Cypress National Preserve, and the southern region of Big Cypress National Preserve. Monitoring of roads, trails, and canals occurs while traveling into and through the parks (i.e., travel at 2–10 mph) using motorized vehicles, airboats, and/or hiking. Campgrounds, boat launches, trailheads, and similar areas, involve complete searches. When an exotic plant is observed, a GPS location is obtained, and coordinates are taken of the plant. Photographs are not taken for every exotic plant encountered, but photographs will be taken for new and unusual species (for example a coastal exotic found in inland habitats). Information recorded at each location includes the species name, size of infestation, abundance, cover class, any treatment/control action taken, and relevant notes. During the surveys, a GPS “track” is also recorded to document the areas surveyed and a field of view is estimated. Field notes, pictures, and GPS data are compiled, entered, and analyzed in a Microsoft Access database. Resource briefs (and optional data summary reports) and associated shapefiles and data are then produced and sent to contacts within the corresponding national parks.

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Willson. L51709 Development-Test Electronic Gas Admission for Large Bore Engines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), August 1994. http://dx.doi.org/10.55274/r0010114.

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The pipeline industry uses over 8,000 large bore engines in gas transmission/compression service". These engines are typically gas fueled and spark ignited. Some early versions of the engines are piston scavenged, but most are turbocharged. Some models, especially those equipped for lean burn operation, utilize pre-combustion chambers for enhanced ignition. Typically, the gaseous fuel is admitted directly into the top of the engine combustion chamber by a cam-operated, mechanical gas admission valve (MGAV). The MGAV is operated by an engine driven cam, cam follower, push rod, and rocker assembly. Such mechanisms offer little in the way of adjustability of the gas admission event: the ability to change the start of gas admission (SOA) and end of gas admission (EOA). The gas admission system is generally optimized for a particular mode of engine operation, typically rated speed and full load, and is fixed in that state. Desired changes in the gas admission cycle are not easily accomplished. At the same time, however, undesired changes commonly occur due to wear, failure, and mis-adjustment of the MGAV drive train. This report documents the development of a natural gas-fueled large-bore engine test bed (LBET) at Colorado State University and the subsequent test of an electronic gas admissions valve (EGAV) with in-cylinder pressure feedback. The LBET is now a state-of-the-art natural gas-fueled test facility. It will be open for use in late 1994 or early 1995 to all parties interested in testing equipment that might lead to safer, more economical and cleaner burning gas fueled engines. The EGAV tests were successful. The valve allows for precise control of fuel admission and end of admission timing. This results in the engine running in a real-time balance condition. Laboratory tests showed a 30% reduction of hydrocarbons and nitrous oxides reductions with a 2% reduction in fuel consumption. Field testing will continue in 1995 prior to commercialization.

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She, Ruifeng, and Yanfeng Ouyang. Generalized Link-Cost Function and Network Design for Dedicated Truck-Platoon Lanes to Improve Energy, Pavement Sustainability, and Traffic Efficiency. Illinois Center for Transportation, November 2021. http://dx.doi.org/10.36501/0197-9191/21-037.

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Recent development of autonomous and connected trucks (ACT) has provided the freight industry with the option of using truck platooning to improve fuel efficiency, traffic throughput, and safety. However, closely spaced and longitudinally aligned trucks impose frequent and concentrated loading on pavements, which often accelerates pavement deterioration and increases the life cycle costs for the highway agency. Also, effectiveness of truck platooning can be maximized only in dedicated lanes; and its benefits and costs need to be properly balanced between stakeholders. This paper proposes a network-design model to optimize (i) placement of dedicated truck-platoon lanes and toll price in a highway network, (ii) pooling and routing of ACT traffic from multiple origins and destinations to utilize these lanes, and (iii) configuration of truck platoons within these lanes (e.g., lateral displacements and vehicle separations). The problem is formulated as an integrated bi-level optimization model. The upper level makes decisions on converting existing highway lanes into dedicated platoon lanes, as well as setting user fees. The lower-level decisions are made by independent shippers regarding the choice of routes and use of platoon lanes vs. regular lanes; and they collectively determine truck traffic in all lanes. Link-cost functions for platoon lanes are obtained by simultaneously optimizing, through dynamic programming, pavement-rehabilitation activities and platoon configuration in the pavement's life cycle. A numerical case study is used to demonstrate the applicability and performance of the proposed model framework over the Illinois freeway system. It is shown that the freight traffic is effectively channelized on a few corridors of platoon lanes and, by setting proper user fees to cover pavement-rehabilitation costs, systemwide improvements for both freight shippers and highway agencies can be achieved.

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Abbott, Albert G., Doron Holland, Douglas Bielenberg, and Gregory Reighard. Structural and Functional Genomic Approaches for Marking and Identifying Genes that Control Chilling Requirement in Apricot and Peach Trees. United States Department of Agriculture, September 2009. http://dx.doi.org/10.32747/2009.7591742.bard.

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Structural and functional genomic approaches for marking and identifying genes that control chilling requirement in apricot and peach trees. Specific aims: 1) Identify and characterize the genetic nature of chilling requirement for flowering and dormancy break of vegetative shoots in Prunusgermplasm through the utilization of existing apricot (NeweYa'ar Research Center, ARO) and peach (Clemson University) genetic mapping populations; 2) Use molecular genetic mapping techniques to identify markers flanking genomic regions controlling chilling; 3) Comparatively map the regions controlling chilling requirement in apricot and peach and locate important genomic regions influencing chilling requirement on the Prunus functional genomic database as an initial step for identification of candidate genes; 4) Develop from the functional genomics database a set of markers facilitating the development of cultivars with optimized chilling requirements for improved and sustained fruit production in warm-winter environments. Dormant apricot (prunus armeniaca L.) and peach [Prunus persica (L.) Batsch] trees require sustained exposure to low, near freezing, temperatures before vigorous floral and vegetative bud break is possible after the resumption of warm temperatures in the spring. The duration of chilling required (the chilling requirement, CR) is determined by the climatic adaptation of the particular cultivar, thus limiting its geographic distribution. This limitation is particularly evident when attempting to introduce superior cultivars to regions with very warm winter temperatures, such as Israel and the coastal southern United States. The physiological mechanism of CR is not understood and although breeding programs deliberately manipulate CR in apricot and peach crosses, robust closely associated markers to the trait are currently not available. We used segregating populations of apricot (100 Fl individuals, NeweYa'ar Research Center, ARO) and peach (378 F2 individuals, Clemson University) to discover several discreet genomic loci that regulate CR and blooming date. We used the extensive genomic/genetic resources available for Prunus to successfully combine our apricot and peach genetic data and identify five QTL with strong effects that are conserved between species as well as several QTL that are unique to each species. We have identified markers in the key major QTL regions for testing in breeding programs which we are carrying out currently; we have identified an initial set of candidate genes using the peach physical/transcriptome map and whole peach genome sequences and we are testing these currently to identify key target genes for manipulation in breeding programs. Our collaborative work to date has demonstrated the following: 1) CR in peach and apricot is predominantly controlled by a limited number ofQTL loci, seven detected in a peach F2 derived map comprising 65% of the character and 12 in an apricot Fl map comprising 71.6% and 55.6% of the trait in the Perfection and A. 1740 parental maps, respectively and that peach and apricot appear in our initial maps to share five genomic intervals containing potentially common QTL. 2) Application of common anchor markers of the Prunus/peach, physical/genetic map resources has allowed us not only to identify the shared intervals but also to have immediately available some putative candidate gene information from these intervals, the EVG region on LG1 in peach the TALY 1 region in apricot on LG2 in peach; and several others involved in vernalization pathways (LGI and LG7). 3) Mapped BACcontigs are easily defined from the complete physical map resources in peach through the common SSR markers that anchor our CR maps in the two species, 4) Sequences of BACs in these regions can be easily mined for additional polymorphic markers to use in MAS applications.

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Delwiche, Michael, Boaz Zion, Robert BonDurant, Judith Rishpon, Ephraim Maltz, and Miriam Rosenberg. Biosensors for On-Line Measurement of Reproductive Hormones and Milk Proteins to Improve Dairy Herd Management. United States Department of Agriculture, February 2001. http://dx.doi.org/10.32747/2001.7573998.bard.

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The original objectives of this research project were to: (1) develop immunoassays, photometric sensors, and electrochemical sensors for real-time measurement of progesterone and estradiol in milk, (2) develop biosensors for measurement of caseins in milk, and (3) integrate and adapt these sensor technologies to create an automated electronic sensing system for operation in dairy parlors during milking. The overall direction of research was not changed, although the work was expanded to include other milk components such as urea and lactose. A second generation biosensor for on-line measurement of bovine progesterone was designed and tested. Anti-progesterone antibody was coated on small disks of nitrocellulose membrane, which were inserted in the reaction chamber prior to testing, and a real-time assay was developed. The biosensor was designed using micropumps and valves under computer control, and assayed fluid volumes on the order of 1 ml. An automated sampler was designed to draw a test volume of milk from the long milk tube using a 4-way pinch valve. The system could execute a measurement cycle in about 10 min. Progesterone could be measured at concentrations low enough to distinguish luteal-phase from follicular-phase cows. The potential of the sensor to detect actual ovulatory events was compared with standard methods of estrus detection, including human observation and an activity monitor. The biosensor correctly identified all ovulatory events during its testperiod, but the variability at low progesterone concentrations triggered some false positives. Direct on-line measurement and intelligent interpretation of reproductive hormone profiles offers the potential for substantial improvement in reproductive management. A simple potentiometric method for measurement of milk protein was developed and tested. The method was based on the fact that proteins bind iodine. When proteins are added to a solution of the redox couple iodine/iodide (I-I2), the concentration of free iodine is changed and, as a consequence, the potential between two electrodes immersed in the solution is changed. The method worked well with analytical casein solutions and accurately measured concentrations of analytical caseins added to fresh milk. When tested with actual milk samples, the correlation between the sensor readings and the reference lab results (of both total proteins and casein content) was inferior to that of analytical casein. A number of different technologies were explored for the analysis of milk urea, and a manometric technique was selected for the final design. In the new sensor, urea in the sample was hydrolyzed to ammonium and carbonate by the enzyme urease, and subsequent shaking of the sample with citric acid in a sealed cell allowed urea to be estimated as a change in partial pressure of carbon dioxide. The pressure change in the cell was measured with a miniature piezoresistive pressure sensor, and effects of background dissolved gases and vapor pressures were corrected for by repeating the measurement of pressure developed in the sample without the addition of urease. Results were accurate in the physiological range of milk, the assay was faster than the typical milking period, and no toxic reagents were required. A sampling device was designed and built to passively draw milk from the long milk tube in the parlor. An electrochemical sensor for lactose was developed starting with a three-cascaded-enzyme sensor, evolving into two enzymes and CO2[Fe (CN)6] as a mediator, and then into a microflow injection system using poly-osmium modified screen-printed electrodes. The sensor was designed to serve multiple milking positions, using a manifold valve, a sampling valve, and two pumps. Disposable screen-printed electrodes with enzymatic membranes were used. The sensor was optimized for electrode coating components, flow rate, pH, and sample size, and the results correlated well (r2= 0.967) with known lactose concentrations.

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