An enhanced concave program relaxation for choice network revenue management

The network choice revenue management problem models customers as choosing from an offer-set, andthe firm decides the best subset to offer at any given moment to maximize expected revenue. The resultingdynamic program for the firm is intractable and approximated by a deterministic linear programcalled the CDLP which has an exponential number of columns. However, under the choice-set paradigmwhen the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has beenproposed but finding an entering column has been shown to be NP-hard. In this paper, starting with aconcave program formulation based on segment-level consideration sets called SDCP, we add a class ofconstraints called product constraints, that project onto subsets of intersections. In addition we proposea natural direct tightening of the SDCP called ?SDCP, and compare the performance of both methodson the benchmark data sets in the literature. Both the product constraints and the ?SDCP method arevery simple and easy to implement and are applicable to the case of overlapping segment considerationsets. In our computational testing on the benchmark data sets in the literature, SDCP with productconstraints achieves the CDLP value at a fraction of the CPU time taken by column generation and webelieve is a very promising approach for quickly approximating CDLP when segment consideration setsoverlap and the consideration sets themselves are relatively small.

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

Adenoid Cystic Carcinoma of the Breast: A Rare Cancer Network Study

Purpose/Objective(s): Mammary adenoid cystic carcinoma (ACC) is a rare breast cancer variant. It accounts for less than 0.1% of all invasive breast malignancies. Typically, it presents as a small breast lump with a low propensity to metastasize to regional lymph nodes or distant sites. The aim of this retrospective multicenter Rare Cancer Network study is to assess prognostic factors and patterns of failure in ACC, as well as the role of radiation therapy (RT) in this rare disease. Materials/Methods: Between January 1980 and December 2007, 61 women with breast ACC were included in this study. Median age was 59 years (range, 28-94 years). The majority of the patients had good performance status (49 patients with WHO 0, 12 patients with WHO 1), and 70% of the patients (n = 42) were premenopausal. Surgery consisted of tumorectomy in 35 patients, mastectomy in 20, or quadrantectomy in 6. Median tumor size was 20 mm (range, 6-170 mm). Surgical margins were clear in 50 (82%) patients. Axillary dissection (n = 41) or sentinel node assessment (n = 10) was realized in the majority of the patients. There were 53 (87%) pN0 and 8 pNx (13%) patients. Estrogen (ER) and progesterone receptor (PR) was negative in 43 (71%) and 42 (69%) patients, respectively. In 16 patients (26%), the receptor status was unknown. Adjuvant chemotherapy or hormonotherapy was administered in 8 (13%) and 7 (12%) patients, respectively. Postoperative RT with a median total dose of 50 Gy (1.8-2.0 Gy/fraction; range, 44-70 Gy) was given in 40 patients. Results: With a median follow-up of 79 months (range, 6-285 months), 5-year overall and disease-free survival (DFS) rates were 94% (95% confidence interval [CI]: 88-100%) and 82% (95% CI: 71-93%), respectively. Five-year locoregional control rate was 95% (95% CI: 89-100%). There were only 4 patients with local relapse who were all salvaged successfully, and 4 other patients developed distant metastases. According to the Common Terminology Criteria for Adverse Events v3.0, late toxicity consisted of grade 2-3 cutaneous fibrosis in 4 (10%) patients, grade 1-2 edema in 2 (5%), and grade 3 lung fibrosis in 2 (5%). In univariate analyses, the outcome was influenced neither by the type of surgery nor the use of postoperative RT. However, positive receptor status had a negative influence on the outcome. Multivariate analysis (Cox model) revealed that negative ER (p = 0.006) or PR (p = 0.04) status was associated with improved DFS. Conclusions: ACC of the breast is a relatively indolent disease with excellent local control and survival. The prognosis of patients with ACC is much better than that for patients with other breast cancers, especially those who are ER and PR negative. The role of postoperative RT is not clear. More aggressive treatments may be warranted for patients with positive receptor status.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Hierarchical neural network with high storage capacity

A recent method used to optimize biased neural networks with low levels of activity is applied to a hierarchical model. As a consequence, the performance of the system is strongly enhanced. The steps to achieve optimization are analyzed in detail.

Development and evaluation of neural network models to estimate daily solar radiation at Córdoba, Argentina

The objective of this work was to develop neural network models of backpropagation type to estimate solar radiation based on extraterrestrial radiation data, daily temperature range, precipitation, cloudiness and relative sunshine duration. Data from Córdoba, Argentina, were used for development and validation. The behaviour and adjustment between values observed and estimates obtained by neural networks for different combinations of input were assessed. These estimations showed root mean square error between 3.15 and 3.88 MJ m-2 d-1 . The latter corresponds to the model that calculates radiation using only precipitation and daily temperature range. In all models, results show good adjustment to seasonal solar radiation. These results allow inferring the adequate performance and pertinence of this methodology to estimate complex phenomena, such as solar radiation.

Performance Characteristics of an Axial-Flux Solid-Rotor-Core Induction Motor

The integration of electric motors and industrial appliances such as pumps, fans, and compressors is rapidly increasing. For instance, the integration of an electric motor and a centrifugal pump provides cost savings and improved performance characteristics. Material cost savings are achieved when an electric motor is integrated into the shaft of a centrifugal pump, and the motor utilizes the bearings of the pump. This arrangement leads to a smaller configuration that occupies less floor space. The performance characteristics of a pump drive can be improved by using the variable-speed technology. This enables the full speed control of the drive and the absence of a mechanical gearbox and couplers. When using rotational speeds higher than those that can be directly achieved by the network frequency the structure of the rotor has to be mechanically durable. In this thesis the performance characteristics of an axial-flux solid-rotor-core induction motor are determined. The motor studied is a one-rotor-one-stator axial-flux induction motor, and thus, there is only one air-gap between the rotor and the stator. The motor was designed for higher rotational speeds, and therefore a good mechanical strength of the solid-rotor-core rotor is required to withstand the mechanical stresses. The construction of the rotor and the high rotational speeds together produce a feature, which is not typical of traditional induction motors: the dominating loss component of the motor is the rotor eddy current loss. In the case of a typical industrial induction motor instead the dominating loss component is the stator copper loss. In this thesis, several methods to decrease the rotor eddy current losses in the case of axial-flux induction motors are presented. A prototype motor with 45 kW output power at 6000 min-1 was designed and constructed for ascertaining the results obtained from the numerical FEM calculations. In general, this thesis concentrates on the methods for improving the electromagnetic properties of an axial-flux solid-rotor-core induction motor and examines the methods for decreasing the harmonic eddy currents of the rotor. The target is to improve the efficiency of the motor and to reach the efficiency standard of the present-day industrial induction motors equipped with laminated rotors.

Transparent and secure remote network storage system using an untrusted server

Työssä kehitettin läpinäkyvä Internet Small Computer Systems Interface-verkkolevyä (iSCSI) käyttävä varmistusjärjestelmä. Verkkolevyn sisältö suojattiin asiakaspään salauskerroksella (dm-crypt). Järjestely mahdollisti sen, että verkkolevylle tallennetut varmuuskopiot pysyivät luottamuksellisina, vaikka levypalvelinta tarjoava taho oli joko epäluotettava tai suorastaan vihamielinen. Järjestelmän hyötykäyttöä varten kehitettiin helppokäyttöinen prototyyppisovellus. Järjestelmän riskit ja haavoittuvuudet käytiin läpi ja analysoitiin. Järjestelmälle tehtiin myös karkea kryptoanalyysi sen teknistenominaisuuksien pohjalta. Suorituskykymittaukset tehtiin sekä salatulle että salaamattomalle iSCSI-liikenteelle. Näistä todettiin, että salauksen vaikutus suorituskykyyn oli häviävän pieni jopa 100 megabittiä sekunnissa siirtävillä verkkonopeuksilla. Lisäksi pohdittiin teknologian muita sovelluskohteita ja tulevia tutkimusalueita.

A comparative performance study of four-pole induction motors and synchronous reluctance motors in variable speed drives

Design aspects of the Transversally Laminated Anisotropic (TLA) Synchronous Reluctance Motor (SynRM) are studied and the machine performance analysis compared to the Induction Motor (IM) is done. The SynRM rotor structure is designed and manufactured for a30 kW, four-pole, three-phase squirrel cage induction motor stator. Both the IMand SynRM were supplied by a sensorless Direct Torque Controlled (DTC) variablespeed drive. Attention is also paid to the estimation of the power range where the SynRM may compete successfully with a same size induction motor. A technicalloss reduction comparison between the IM and SynRM in variable speed drives is done. The Finite Element Method (FEM) is used to analyse the number, location and width of flux barriers used in a multiple segment rotor. It is sought for a high saliency ratio and a high torque of the motor. It is given a comparison between different FEM calculations to analyse SynRM performance. The possibility to take into account the effect of iron losses with FEM is studied. Comparison between the calculated and measured values shows that the design methods are reliable. A new application of the IEEE 112 measurement method is developed and used especially for determination of stray load losses in laboratory measurements. The study shows that, with some special measures, the efficiency of the TLA SynRM is equivalent to that of a high efficiency IM. The power factor of the SynRM at rated load is smaller than that of the IM. However, at lower partial load this difference decreases and this, probably, brings that the SynRM gets a better power factor in comparison with the IM. The big rotor inductance ratio of the SynRM allows a good estimating of the rotor position. This appears to be very advantageous for the designing of the rotor position sensor-less motor drive. In using the FEM designed multi-layer transversally laminated rotor with damper windings it is possible to design a directly network driven motor without degrading the motorefficiency or power factor compared to the performance of the IM.

Task-induced deactivation from rest extends beyond the default mode brain network

Activity decreases, or deactivations, of midline and parietal cortical brain regions are routinely observed in human functional neuroimaging studies that compare periods of task-based cognitive performance with passive states, such as rest. It is now widely held that such task-induced deactivations index a highly organized"default-mode network" (DMN): a large-scale brain system whose discovery has had broad implications in the study of human brain function and behavior. In this work, we show that common task-induced deactivations from rest also occur outside of the DMN as a function of increased task demand. Fifty healthy adult subjects performed two distinct functional magnetic resonance imaging tasks that were designed to reliably map deactivations from a resting baseline. As primary findings, increases in task demand consistently modulated the regional anatomy of DMN deactivation. At high levels of task demand, robust deactivation was observed in non-DMN regions, most notably, the posterior insular cortex. Deactivation of this region was directly implicated in a performance-based analysis of experienced task difficulty. Together, these findings suggest that task-induced deactivations from rest are not limited to the DMN and extend to brain regions typically associated with integrative sensory and interoceptive processes.

APOE status modulates the changes in network connectivity induced by brain stimulation in non-demented elders.

Behavioral consequences of a brain insult represent an interaction between the injury and the capacity of the rest of the brain to adapt to it. We provide experimental support for the notion that genetic factors play a critical role in such adaptation. We induced a controlled brain disruption using repetitive transcranial magnetic stimulation (rTMS) and show that APOE status determines its impact on distributed brain networks as assessed by functional MRI (fMRI).Twenty non-demented elders exhibiting mild memory dysfunction underwent two fMRI studies during face-name encoding tasks (before and after rTMS). Baseline task performance was associated with activation of a network of brain regions in prefrontal, parietal, medial temporal and visual associative areas. APOE ε4 bearers exhibited this pattern in two separate independent components, whereas ε4-non carriers presented a single partially overlapping network. Following rTMS all subjects showed slight ameliorations in memory performance, regardless of APOE status. However, after rTMS APOE ε4-carriers showed significant changes in brain network activation, expressing strikingly similar spatial configuration as the one observed in the non-carrier group prior to stimulation. Similarly, activity in areas of the default-mode network (DMN) was found in a single component among the ε4-non bearers, whereas among carriers it appeared disaggregated in three distinct spatiotemporal components that changed to an integrated single component after rTMS. Our findings demonstrate that genetic background play a fundamental role in the brain responses to focal insults, conditioning expression of distinct brain networks to sustain similar cognitive performance.

The Design and Implementation of Loudspeaker Control Network Protocols

The networking and digitalization of audio equipment has created a need for control protocols. These protocols offer new services to customers and ensure that the equipment operates correctly. The control protocols used in the computer networks are not directly applicable since embedded systems have resource and cost limitations. In this master's thesis the design and implementation of new loudspeaker control network protocols are presented. The protocol stack was required to be reliable, have short response times, configure the network automatically and support the dynamic addition and removal of loudspeakers. The implemented protocol stack was also required to be as efficient and lightweight as possible because the network nodes are fairly simple and lack processing power. The protocol stack was thoroughly tested, validated and verified. The protocols were formally described using LOTOS (Language of Temporal Ordering Specifications) and verified using reachability analysis. A prototype of the loudspeaker network was built and used for testing the operation and the performance of the control protocols. The implemented control protocol stack met the design specifications and proved to be highly reliable and efficient.

Load and Performance Testing of Web Applications on Service Based Environments

Suorituskyky- ja kuormitustestien tekeminen sovelluksille on erittäin tärkeä osa tuotantoprosessia nykypäivänä. Myös Web-sovelluksia testataan yhä enemmän. Tarve suorituskyky- ja kuormitustestien tekemiselle on selvä. Testattavan ympäristön tämänhetkinen, mutta myös tulevaisuuden toimivuus taataan oikein tehdyillä testeillä ja niitä seuraavilla korjaustoimenpiteillä. Suurten käyttäjämäärien testaaminen manuaalisesti on kuitenkin hyvin vaikeaa. Sirpaleisen ympäristön, kuten palveluihin perustuvien Web-sovellusympäristöjen testaaminen on haaste. Tämän työn aiheena on arvioida työkaluja ja menetelmiä, joilla raskaita teollisia Web-sovelluksia voidaan testata. Tavoitteena on löytää testausmenetelmiä, joilla voidaan luotettavasti simuloida suuria käyttäjämääriä. Tavoitteena on myös arvioida erilaisten yhteyksien ja protokollien vaikutusta Web-sovelluksen suorituskykyyn.

Small Cell Carcinoma of the Urinary Bladder: A Retrospective, Multicenter Rare Cancer Network Study of 107 Patients.

PURPOSE: Small cell carcinomas of the bladder (SCCB) account for fewer than 1% of all urinary bladder tumors. There is no consensus regarding the optimal treatment for SCCB. METHODS AND MATERIALS: Fifteen academic Rare Cancer Network medical centers contributed SCCB cases. The eligibility criteria were as follows: pure or mixed SCC; local, locoregional, and metastatic stages; and age ≥18 years. The overall survival (OS) and disease-free survival (DFS) were calculated from the date of diagnosis according to the Kaplan-Meier method. The log-rank and Wilcoxon tests were used to analyze survival as functions of clinical and therapeutic factors. RESULTS: The study included 107 patients (mean [±standard deviation, SD] age, 69.6 [±10.6] years; mean follow-up time, 4.4 years) with primary bladder SCC, with 66% of these patients having pure SCC. Seventy-two percent and 12% of the patients presented with T2-4N0M0 and T2-4N1-3M0 stages, respectively, and 16% presented with synchronous metastases. The most frequent curative treatments were radical surgery and chemotherapy, sequential chemotherapy and radiation therapy, and radical surgery alone. The median (interquartile range, IQR) OS and DFS times were 12.9 months (IQR, 7-32 months) and 9 months (IQR, 5-23 months), respectively. The metastatic, T2-4N0M0, and T2-4N1-3M0 groups differed significantly (P=.001) in terms of median OS and DFS. In a multivariate analysis, impaired creatinine clearance (OS and DFS), clinical stage (OS and DFS), a Karnofsky performance status <80 (OS), and pure SCC histology (OS) were independent and significant adverse prognostic factors. In the patients with nonmetastatic disease, the type of treatment (ie radical surgery with or without adjuvant chemotherapy vs conservative treatment) did not significantly influence OS or DFS (P=.7). CONCLUSIONS: The prognosis for SCCB remains poor. The finding that radical cystectomy did not influence DFS or OS in the patients with nonmetastatic disease suggests that conservative treatment is appropriate in this situation.