The train driver recovery problem—A set partitioning based model and solution method

The need to recover a train driver schedule occurs during major disruptions in the daily railway operations. Based on data from the Danish passenger railway operator DSB S-tog A/S, a solution method to the train driver recovery problem (TDRP) is developed. The TDRP is formulated as a set partitioning problem. We define a disruption neighbourhood by identifying a small set of drivers and train tasks directly affected by the disruption. Based on the disruption neighbourhood, the TDRP model is formed and solved. If the TDRP solution provides a feasible recovery for the drivers within the disruption neighbourhood, we consider that the problem is solved. However, if a feasible solution is not found, the disruption neighbourhood is expanded by adding further drivers or increasing the recovery time period. Fractional solutions to the LP relaxation of the TDRP are resolved with a constraint branching strategy using the depth-first search of the Branch & Bound tree. The LP relaxation of the TDRP possesses strong integer properties. We present test scenarios generated from the historical real-life operations data of DSB S-tog A/S. The numerical results show that all but one tested instances produce integer solutions to the LP relaxation of the TDRP and solutions are found within a few seconds.     

Parallel batch scheduling of equal-length jobs with release and due dates

In this paper we study parallel batch scheduling problems with bounded batch capacity and equal-length jobs in a single and parallel machine environment. It is shown that the feasibility problem 1|p-batch,b<n,r _j ,p _j =p,C _j ≤d _j |− can be solved in O(n ²) time and that the problem of minimizing the maximum lateness can be solved in O(n ²log n) time. For the parallel machine problem P|p-batch,b<n,r _j ,p _j =p,C _j ≤d _j |− an O(n ³log n)-time algorithm is provided, which can also be used to solve the problem of minimizing the maximum lateness in O(n ³log ² n) time.     

An industry experiment on the effects of test-driven development on external quality and productivity

Existing empirical studies on test-driven development (TDD) report different conclusions about its effects on quality and productivity. Very few of those studies are experiments conducted with software professionals in industry. We aim to analyse the effects of TDD on the external quality of the work done and the productivity of developers in an industrial setting. We conducted an experiment with 24 professionals from three different sites of a software organization. We chose a repeated-measures design, and asked subjects to implement TDD and incremental test last development (ITLD) in two simple tasks and a realistic application close to real-life complexity. To analyse our findings, we applied a repeated-measures general linear model procedure and a linear mixed effects procedure. We did not observe a statistical difference between the quality of the work done by subjects in both treatments. We observed that the subjects are more productive when they implement TDD on a simple task compared to ITLD, but the productivity drops significantly when applying TDD to a complex brownfield task. So, the task complexity significantly obscured the effect of TDD. Further evidence is necessary to conclude whether TDD is better or worse than ITLD in terms of external quality and productivity in an industrial setting. We found that experimental factors such as selection of tasks could dominate the findings in TDD studies.     

Urinary proteomic analysis of chronic allograft nephropathy

The pathogenesis of progressive renal allograft injury, which is termed chronic allograft nephropathy (CAN), remains obscure and is currently defined by histology. Prospective protocol-biopsy trials have demonstrated that clinical and standard laboratory tests are insufficiently sensitive indicators of the development and progression of CAN. The study aim was to determine if CAN could be characterized by urinary proteomic data and identify the proteins associated with disease. The urinary proteome of 75 renal transplant recipients and 20 healthy volunteers was analyzed using surface enhanced laser desorption and ionization MS. Patients could be classified into subgroups with normal histology and Banff CAN grades 2-3 with a sensitivity of 86% and a specificity of 92% by applying the classification algorithm Adaboost to urinary proteomic data. Several urinary proteins associated with advanced CAN were identified including α1-microglobulin, β2-microglobulin, prealbumin, and endorepellin, the antiangiogenic C-terminal fragment of perlecan. Increased urinary endorepellin was confirmed by ELISA and increased tissue expression of the endorepellin/perlecan ratio by immunofluoresence analysis of renal biopsies. In conclusion, analysis of urinary proteomic data has further characterized the more severe CAN grades and identified urinary endorepellin, as a potential biomarker of advanced CAN.     

On techniques for angle compensation in nonideal iris recognition.

The popularity of the iris biometric has grown considerably over the past two to three years. Most research has been focused on the development of new iris processing and recognition algorithms for frontal view iris images. However, a few challenging directions in iris research have been identified, including processing of a nonideal iris and iris at a distance. In this paper, we describe two nonideal iris recognition systems and analyze their performance. The word "nonideal" is used in the sense of compensating for off-angle occluded iris images. The system is designed to process nonideal iris images in two steps: 1) compensation for off-angle gaze direction and 2) processing and encoding of the rotated iris image. Two approaches are presented to account for angular variations in the iris images. In the first approach, we use Daugman's integrodifferential operator as an objective function to estimate the gaze direction. After the angle is estimated, the off-angle iris image undergoes geometric transformations involving the estimated angle and is further processed as if it were a frontal view image. The encoding technique developed for a frontal image is based on the application of the global independent component analysis. The second approach uses an angular deformation calibration model. The angular deformations are modeled, and calibration parameters are calculated. The proposed method consists of a closed-form solution, followed by an iterative optimization procedure. The images are projected on the plane closest to the base calibrated plane. Biorthogonal wavelets are used for encoding to perform iris recognition. We use a special dataset of the off-angle iris images to quantify the performance of the designed systems. A series of receiver operating characteristics demonstrate various effects on the performance of the nonideal-iris-based recognition system.     

Automated system of research in the field of experimental mechanics of materials

The article describes an automated system for scientific research Mekhanika devised at the Institute of the Strength of Materials, Academy of Sciences of the Ukraine; the system is suitable for almost complete automation of routine operations in data processing of mechanical experiments connected with the calculation of the state of stress and strain of the test specimen, presenting the results of the calculation in the form of tables and graphs, and with the calculation of the required mechanical characteristics of the material. In addition the system offers the user great possibilities in generalizing the results of experiments, constructing various analytical approximations of the obtained data. The results of experiments and calculations can be stored in a specialized data bank.Translated from Problemy Prochnosti, No. 3, pp. 71–79, March, 1993.     

Solving large multiple-depot multiple-vehicle-type bus scheduling problems in practice

We consider the multiple-depot multiple-vehicle-type scheduling problem (MDVSP) which arises in public transport bus companies and aims to assign buses to cover a given set of timetabled trips with consideration of practical requirements, such as multiple depots and vehicle types as well as depot capacities. An optimal schedule is characterized by minimal fleet size and minimal operational costs including costs for empty movements and waiting time. It is well-known that the MDVSP is NP-hard.Although progress has recently been made in solving large practical MDVSP to optimality with time-space network models, current optimization technology sets limits to the model size that can be solved. In order to approach very large practical instances we propose a two-phase method which produces close to optimal solutions. This modeling approach enables us to solve real-world problem instances with thousands of scheduled trips by direct application of standard optimization software. Furthermore, we introduce the concept of depot groups for the case that a bus may return in the evening into another depot than where it started in the morning.     

Grain boundary effect on electron-beam-induced current in La3Ga5.5Ta0.5O14 crystal

La₃Ga_5.5Ta_0.5O₁₄ crystal recently attracted more attention due to its superior electromechanical properties and high Q × f product. We report that the first electron-beam-induced current experiment on La₃Ga_5.5Ta_0.5O₁₄ single crystal. This method is employed to study the effect of the crystal's grain boundary on the incident electron beam. The experimental results clearly show that when the electron beam scans over the grain boundary of the crystal, a fraction of the carriers recombine at the grain boundary and is unavailable for the current generation. This recombination rate will be enhanced when the electron beam was close to the boundary and cause a dip in the collected current. Although the crystal is an insulator, this effect still can be observed if the coating metal is proper to be chosen. It is also pointed out that the different diffusion lengths of the crystal might be due to the tilted grain boundary.     

Exploratory spatio-temporal visualization: an analytical review

Current software tools for visualization of spatio-temporal data, on the one hand, utilize the opportunities provided by modern computer technologies, on the other hand, incorporate the legacy from the conventional cartography. We have considered existing visualization-based techniques for exploratory analysis of spatio-temporal data from two perspectives: (1) what types of spatio-temporal data they are applicable to; (2) what exploratory tasks they can potentially support.The technique investigation has been based on an operational typology of spatio-temporal data and analytical tasks we specially devised for this purpose. The result of the study is a structured inventory of existing exploratory techniques related to the types of data and tasks they are appropriate for. This result is potentially helpful for data analysts—users of geovisualization tools: it provides guidelines for selection of proper exploratory techniques depending on the characteristics of data to analyze and the goals of analysis. At the same time the inventory as well as the suggested typology of tasks could be useful for tool designers and developers of various domain-specific geovisualization applications. The designers can, on the one hand, see what task types are insufficiently supported by the existing tools and direct their creative activities towards filling the gaps, on the other hand, use the techniques described as basic elements for building new, more sophisticated ones. The application developers can, on the one hand, use the task and data typology in the analysis of potential user needs, on the other hand, appropriately select and combine existing tools in order to satisfy these needs.     

Assessment of oxygen levels in convenience‐style muscle‐based sous vide products through optical means and impact on shelf‐life stability

An optical oxygen analyser was used in two small‐scale industrial trials to non‐destructively assess the quality of packaged convenience foods and packaging process. Beef lasagne packed under 70% vacuum and cooked under standard sous vide conditions was monitored for residual oxygen, using disposable sensors incorporated in each pack and a benchtop optical oxygen analyser. High levels of residual oxygen close to ambient were determined in the majority of packs after packaging, as opposed to anticipated levels of 4–5%. Residual oxygen was monitored over product shelf‐life (4 weeks at +4–10°C) along with measurement of microbial growth and lipid oxidation in food by conventional destructive methods. Oxygen levels in packs went down to almost zero between weeks 2 and 3 indicating deterioration of packaged product. Correlation between oxygen profiles and the rate of microbial growth and lipid oxidation was established. The optical oxygen sensor system was shown to provide valuable information about performance of the packaging process, product storage conditions and food quality in a convenient and cost‐efficient fashion and non‐destructively. Copyright © 2004 John Wiley & Sons, Ltd.