Parametric approaches to fractional programs: Analytical and empirical study

Fractional programming is used to model problems where the objective function is a ratio of functions. A parametric modeling approach provides effective technique for obtaining optimal solutions of these fractional programming problems. Although many heuristic algorithms have been proposed and assessed relative to each other, there are limited theoretical studies on the number of steps to obtain the solution. In this dissertation, I focus on the linear fractional combinatorial optimization problem, a special case of fractional programming where all functions in the objective function and constraints are linear and all variables are binary that model certain combinatorial structures. Two parametric algorithms are considered and the efficiency of the algorithms is investigated both theoretically and computationally. I develop the complexity bounds for these algorithms, and show that they can solve the linear fractional combinatorial optimization problem in polynomial time. In the computational study, the algorithms are used to solve fractional knapsack problem, fractional facility location problem, and fractional transportation problem by comparison to other algorithms (e.g., Newton\u27s method). The relative practical performance measured by the number of function calls demonstrates that the proposed algorithms are fast and robust for solving the linear fractional programs with discrete variables

Supply constrained location-distribution in not-for-profit settings

Inspired by the World Food Programme's activity in the post-civil war food crisis in Angola, this study proposes a systematic approach to address the location distribution problem in not-for-profit settings, where a limited volume of supply has to be allocated to different demand regions. The use of utility functions is key in our framework because it allows the decision-maker to establish priorities by representing the heterogeneous effects of distributing supply to different demand locations (location effect) and to different individuals in the same demand location (diminishing returns effect). We propose the use of two fractional objectives with the utility functions embedded into them: an efficiency measure and a new inequity measure related to the Gini coefficient. The suggested problem has the form of a bi-objective integer linear fractional program and our resolution optimization technique is designed to solve for multiple fractional objective measures. Novel analytical results for the worst-case performance of the proposed resolution technique are provided. Our numerical experiments assess computational efficiency and provide concrete managerial prescriptions. Finally, an illustrative application of our approach in the context of the food crisis in Angola is presented based on an efficiency-inequity trade-off analysis.This research was partially supported by Sejong University[Grant 20180391] (Park) and Purdue University [Doug andMaria DeVos] (Berenguer)

Photoelectrochemical reduction of aqueous protons with a CuO|CuBi2O4 heterojunction under visible light irradiation.

A p-type heterojunction photoelectrode consisting of platinized CuBi2O4 layered on a CuO film was prepared. The CuO|CuBi2O4|Pt electrode photo-generates H2 in pH neutral aqueous solution during visible light irradiation and exhibits a substantially enhanced photocurrent compared to CuO|Pt and CuBi2O4|Pt electrodes. Reduced electron-hole recombination by the band offsets in the heterostructure is responsible for the improved photoelectrochemical performance of CuO|CuBi2O4 with a small band-gap of approximately 1.5 eV.The work at Cambridge was supported by the Christian Doppler Research Association (Austrian Federal Ministry of Economy, Family and Youth and National Foundation for Research, Technology and Development), the OMV Group the EPSRC (EP/H00338X/2) and BBSRC (BB/K010220/1).This is the accepted manuscript version. The final published version is available from the RSC at http://pubs.rsc.org/en/Content/ArticleLanding/2014/CP/C4CP03883E#!divAbstract

Decision Support for Optimal Adaptation of Product and Supply Chain Systems based on Real Options Theory

In order to remain profitable in the highly competitive global market, a manufacturing enterprise is expected to proactively adapt itself in anticipation of unplanned, but foreseeable high impact events. This paper presents a decision model for optimal adaptation of product and supply chain systems subject to sudden, severe changes in the operating environment. Extending our previous work, decision-tree based framework is developed for optimally choosing design-supplier alternatives in multi-product, multi-echelon product and supply chain systems based on the real options theory. A case study on a two-component, two-echelon supply chain is presented which highlights unique characteristics of product quality as compared to cost and time.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87256/4/Saitou57.pd

Adenofibroma of Skene's Duct: A Case Report

Skene's glands, also known as paraurethral glands, are homologues of the male prostate, in which painless cystic masses and inflammation due to obstruction have been rarely found and reported. In addition, there have been rare reported cases of adenocarcinoma of Skene's glands. Recently, the authors experienced the first case of adenofibroma arising in Skene's glands of a 62-year-old woman with coital pain. Hereby, we present the case with pathologic and immunohistochemical findings and a short review of literature

Study of the Ubiquitous Hog Farm System Using Wireless Sensor Networks for Environmental Monitoring and Facilities Control

Many hog farmers are now suffering from high pig mortality rates due to various wasting diseases and increased breeding costs, etc. It is therefore necessary for hog farms to implement systematic and scientific pig production technology to increase productivity and produce high quality pork in order to solve these problems. In this study, we describe such a technology by suggesting a ubiquitous hog farm system which applies WSN (Wireless Sensor Network) technology to the pig industry. We suggest that a WSN and CCTV (Closed-circuit television) should be installed on hog farms to collect environmental and image information which shall then help producers not only in monitoring the hog farm via the Web from outside the farm, but also facilitate the control of hog farm facilities in remote locations. In addition, facilities can be automatically controlled based on breeding environment parameters which are already set up and a SMS notice service to notify of deviations shall provide users with convenience. Hog farmers may increase production and improve pork quality through this ubiquitous hog farm system and prepare a database with information collected from environmental factors and the hog farm control devices, which is expected to provide information needed to design and implement suitable control strategies for hog farm operation

Damage to the cuff of EMG tube at endotracheal intubation by using a lightwand -A case report-

Electromyogpraphic endotracheal tube (EMG tube) is a new device used to monitor recurrent laryngeal nerve integrity during thyroid surgery. The EMG tube has 2 pairs of electrodes on the surface of silicon-based tube reached to inner space of tube cuff. We experienced an unusual endotracheal tube-related problem from the distinct structural feature of the EMG tube. In this case, we intubated a patient who had difficult airway with the EMG tube using a lightwand. After successful endotracheal intubation, we could not expand the pilot balloon and ventilate the patient effectively. We removed the EMG tube and found that one of electrodes of the EMG tube is bended and made a right angle with the long axis of the tube, and perforated the tube cuff. So we report this case to make anesthesia providers aware that much more attention is needed to use EMG tube during endotracheal intubation

Clinical implementation of whole-genome array CGH as a first-tier test in 5080 pre and postnatal cases

<p>Abstract</p> <p>Background</p> <p>Array comparative genomic hybridization (CGH) is currently the most powerful method for detecting chromosomal alterations in pre and postnatal clinical cases. In this study, we developed a BAC based array CGH analysis platform for detecting whole genome DNA copy number changes including specific micro deletion and duplication chromosomal disorders. Additionally, we report our experience with the clinical implementation of our array CGH analysis platform. Array CGH was performed on 5080 pre and postnatal clinical samples from patients referred with a variety of clinical phenotypes.</p> <p>Results</p> <p>A total of 4073 prenatal cases (4033 amniotic fluid and 40 chorionic villi specimens) and 1007 postnatal cases (407 peripheral blood and 600 cord blood) were studied with complete concordance between array CGH, karyotype and fluorescence <it>in situ </it>hybridization results. Among 75 positive prenatal cases with DNA copy number variations, 60 had an aneuploidy, seven had a deletion, and eight had a duplication. Among 39 positive postnatal cases samples, five had an aneuploidy, 23 had a deletion, and 11 had a duplication.</p> <p>Conclusions</p> <p>This study demonstrates the utility of using our newly developed whole-genome array CGH as first-tier test in 5080 pre and postnatal cases. Array CGH has increased the ability to detect segmental deletion and duplication in patients with variable clinical features and is becoming a more powerful tool in pre and postnatal diagnostics.</p