Defect identification in 3-D elastostatics using a genetic algorithm

An inverse problem in engineering mechanics is considered where the position and the geometry of three-dimensional, ellipsoidal defects are identified by using measurements of the mechanical response under static loading on the external surface of the structure. The problem is solved by appropriate combination of genetic optimization (GO) and boundary element method (BEM) and following previously published two-dimensional problems. The three-dimensional case presents some additional difficulties. Furthermore, the function of several genetic operators and the effect of the parameters of genetic optimization on the efficiency of the solution has been numerically examined.     

Hypertension and left ventricular mass index (L.VMI) in patients on regular hemodialysis (RDT)

Background:  Because of high incidence of acquired renal cyst and renal malignancy, it is suggested that spontaneous renal rupture more frequently occurs in patients receiving long‐term hemodialysis than in the general population. This study was performed to evaluate the clinical characteristics of spontaneous renal rupture in hemodialysis patients. Methods:  This retrospective study enrolled 12 hemodialysis patients who developed spontaneous renal rupture. We investigated primary renal disease, duration of dialysis, clinical symptoms and signs, radiologic findings, treatment modalities, and histologic findings. Result:  The mean age of the patients was 54 ± 10 years old and the number of male was 9. Primary renal disease consisted of autosomal dominant polycystic kidney disease (PCKD)(n = 5), chronic glomerulonephritis (n = 2), diabetic nephropathy (n = 1), hypertensive nephropathy (n = 1), unknown cause (n = 3). Presenting symptoms and signs were sudden onset of flank pain in 9 patients and gross hematuria with mild flank pain in 3 patients. Mean duration from initiation of hemodialysis to development of spontaneous renal rupture was 53 ± 36 months. Abdominal computed tomography showed subcapsular or perinephric hematoma in all patients. Of the 7 non‐PCKD patients, 6 patients had multiple acquired renal cysts. Surgical exploration was undertaken in 9 patients. Pathologic examination demonstrated small sized renal cell carcinoma in 2 of 9 patients. Three patients were only treated with conservative management including blood transfusion. All 12 patients recovered without recurrence. Conclusion:  This study demonstrated that genetic or acquired renal cyst was an important cause of spontaneous renal rupture in hemodialysis patients and presenting manifestations were sudden onset of flank pain and gross hematuria.     

A heuristic algorithm for the just-in-time single machine scheduling problem with setups: a comparison with simulated annealing

This paper addresses the single machine early/tardy problem with unrestricted common due date and sequence-dependent setup times. Two algorithms are introduced to reach near-optimum solutions: the SAPT, a heuristic tailored for the problem, and a simulated annealing (SA) algorithm. It will be shown that SA provides solutions with slightly better quality; however, SAPT requires much less computational time. SAPT-SA is a hybrid heuristic that combines both approaches to obtain high quality solutions with low computational cost. Solutions provided by the three algorithms were compared to optimal solutions for problems with up to 25 jobs and to each other for larger problems.     

Exposure data and risk indicators for safety performance assessment in Europe

The objective of this paper is the analysis of the state-of-the-art in risk indicators and exposure data for safety performance assessment in Europe, in terms of data availability, collection methodologies and use. More specifically, the concepts of exposure and risk are explored, as well as the theoretical properties of various exposure measures used in road safety research (e.g. vehicle- and person-kilometres of travel, vehicle fleet, road length, driver population, time spent in traffic, etc.). Moreover, the existing methods for collecting disaggregate exposure data for risk estimates at national level are presented and assessed, including survey methods (e.g. travel surveys, traffic counts) and databases (e.g. national registers). A detailed analysis of the availability and quality of existing risk exposure data is also carried out. More specifically, the results of a questionnaire survey in the European countries are presented, with detailed information on exposure measures available, their possible disaggregations (i.e. variables and values), their conformity to standard definitions and the characteristics of their national collection methods. Finally, the potential of international risk comparisons is investigated, mainly through the International Data Files with exposure data (e.g. Eurostat, IRTAD, ECMT, UNECE, IRF, etc.). The results of this review confirm that comparing risk rates at international level may be a complex task, as the availability and quality of exposure estimates in European countries varies significantly. The lack of a common framework for the collection and exploitation of exposure data limits significantly the comparability of the national data. On the other hand, the International Data Files containing exposure data provide useful statistics and estimates in a systematic way and are currently the only sources allowing international comparisons of road safety performance under certain conditions.     

手动式电磁定位及图像导航的短径癌症放射治疗系统

提出一个用于高剂量短径癌症放射治疗的手动式电磁定们及图像导航系统，该系统主要由4个模块组成：预处理、术前规划、术内导航和术后计划，它们分别对应高剂量短径癌症放射治疗的4个流程：在术前规划阶段，用户可交互地设计探针放置位置以及三维重建病灶轮廓；在手术进行过程中，六自由度的电磁式定位技术实时而精确地跟踪探针位置，高质量的可视化技术指引医生完成手术探针放置任务；手术探针全部放置完毕后，术后计划模板计算剂量分布并利用后装机设备进行放射治疗。初步实验表明，计算机辅助的探针定位比手工定位精度提高2-3倍，手术时间减少5倍以上，同时也减轻了病人所承受的放射剂量。     

The Gestational Effects of Maternal Bone Marker Molecules on Fetal Growth,Metabolism and Long-Term Metabolic Health: A Systematic Review

Fetal exposure in adverse environmental factors during intrauterine life can lead to various biological adjustments, affecting not only in utero development of the conceptus, but also its later metabolic and endocrine wellbeing. During human gestation, maternal bone turnover increases, as reflected by molecules involved in bone metabolism, such as vitamin D, osteocalcin, sclerostin, sRANKL, and osteoprotegerin; however, recent studies support their emerging role in endocrine functions and glucose homeostasis regulation. Herein, we sought to systematically review current knowledge on the effects of aforementioned maternal bone biomarkers during pregnancy on fetal intrauterine growth and metabolism, neonatal anthropometric measures at birth, as well as on future endocrine and metabolic wellbeing of the offspring. A growing body of literature converges on the view that maternal bone turnover is likely implicated in fetal growth, and at least to some extent, in neonatal and childhood body composition and metabolic wellbeing. Maternal sclerostin and sRANKL are positively linked with fetal abdominal circumference and subcutaneous fat deposition, contributing to greater birthweights. Vitamin D deficiency correlates with lower birthweights, while research is still needed on intrauterine fetal metabolism, as well as on vitamin D dosing supplementation during pregnancy, to diminish the risks of low birthweight or SGA neonates in high-risk populations.     

Active learning of user’s preferences estimation towards a personalized 3D navigation of geo-referenced scenes

The current technological evolutions enter 3D geo-informatics into their digital age, enabling new potential applications in the field of virtual tourism, pleasure, entertainment and cultural heritage. It is argued that 3D information provides the natural way of navigation. However, personalization is a key aspect in a navigation system, since a route that incorporates user preferences is ultimately more suitable than the route with the shortest distance or travel time. Usually, user’s preferences are expressed as a set of weights that regulate the degree of importance of the scene metadata on the route selection process. These weights, however, are defined by the users, setting the complexity to the user’s side, which makes personalization an arduous task. In this paper, we propose an alternative approach in which metadata weights are estimated implicitly and transparently to the users, transferring the complexity to the system side. This is achieved by introducing a relevance feedback on-line learning strategy which automatically adjusts metadata weights by exploiting information fed back to the system about the relevance of user’s preferences judgments given in a form of pair-wise comparisons. Practically implementing a relevance feedback algorithm presents the limitation that several pair-wise comparisons (samples) are required to converge to a set of reliable metadata weights. For this reason, we propose in this paper a weight rectification strategy that improves weight estimation by exploiting metadata interrelations defined through an ontology. In the sequel, a genetic optimization algorithm is incorporated to select the most user preferred routes based on a multi-criteria minimization approach. To increase the degree of personalization in 3D navigation, we have also introduced an efficient algorithm for estimating 3D trajectories around objects of interest by merging best selected 2D projected views that contain faces which are mostly preferred by the users. We have conducted simulations and comparisons with other approaches either in the field of on-line learning or route selection using objective metrics in terms of precision and recall values. The results indicate that our system yields on average a 13.76 % improvement of precision as regards the learning strategy and an improvement of 8.75 % regarding route selection. In addition, we conclude that the ontology driven weight rectification strategy can reduce the number of samples (pair-wise comparisons) required of 76 % to achieve the same precision. Qualitative comparisons have been also performed using a use case route scenario in the city of Athens.     

A <Emphasis Type="Italic">k</Emphasis>-norm pruning algorithm for decision tree classifiers based on error rate estimation

Decision trees are well-known and established models for classification and regression. In this paper, we focus on the estimation and the minimization of the misclassification rate of decision tree classifiers. We apply Lidstone’s Law of Succession for the estimation of the class probabilities and error rates. In our work, we take into account not only the expected values of the error rate, which has been the norm in existing research, but also the corresponding reliability (measured by standard deviations) of the error rate. Based on this estimation, we propose an efficient pruning algorithm, called k-norm pruning, that has a clear theoretical interpretation, is easily implemented, and does not require a validation set. Our experiments show that our proposed pruning algorithm produces accurate trees quickly, and compares very favorably with two other well-known pruning algorithms, CCP of CART and EBP of C4.5. Editor: Hendrik Blockeel.     

Named-Entity Recognition from Greek and English Texts

Named-entity recognition (NER) involves the identification and classification of named entities in text. This is an important subtask in most language engineering applications, in particular information extraction, where different types of named entity are associated with specific roles in events. In this paper, we present a prototype NER system for Greek texts that we developed based on a NER system for English. Both systems are evaluated on corpora of the same domain and of similar size. The time-consuming process for the construction and update of domain-specific resources in both systems led us to examine a machine learning method for the automatic construction of such resources for a particular application in a specific language.     

Clock gating methodologies and tools: a survey

Clock gating (CG) is a widely used design method for reducing the dynamic power consumption in digital circuits. Although it is a mature technique, theoretical work and tools for its application are still evolving and considered a matter of ongoing research, due to its significant effect in the overall power of the designs under study. This paper introduces a detailed review of the spectrum of CG approaches, theoretical and practical, from an architectural and register transfer level to synthesis, place and route, and testing issues. Furthermore, tools availability, limitations, and requirements concerning CG are examined for each design flow step. Conclusively, an evaluation of the presented techniques and literature is provided, estimating their usefulness and identifying areas for future research, exploration, and automation. Copyright © 2015 John Wiley & Sons, Ltd.