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.     

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。     

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.     

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.     

Study of emulsions and foams stabilized with Phaseolus vulgaris or Phaseolus coccineus with the addition of xanthan gum or NaCl

The properties of oil/water emulsions stabilized with 1% w/v common bean (Phaseolus vulgaris L.) or scarlet runner bean (P. coccineus L.) proteins, extracted by isoelectric precipitation or ultrafiltration, at pH 7.0 and 5.5 were studied. The stability of emulsions, evaluated on the basis of droplet size, creaming, viscosity and protein adsorption measurements, is increased by the addition of xanthan (0.1 and 0.25% w/v). This is probably due to the increase in the continuous phase viscosity and the creation of a network, which prevents the oil droplets from coalescing. Also, the ability and stability of 1 or 2% w/v foams was studied. Xanthan (0.25% w/v) does not enhance foam formation, but promotes foam stability, possibly owing to the increased viscosity of the aqueous phase, making it more difficult for air to enter the system and create a satisfactory foam volume. The addition of NaCl destabilizes emulsions by lowering the energy barrier and therefore increasing the tendency of the oil droplets to aggregate. However, NaCl at a certain concentration seems to promote the emulsion stability and foaming ability and foam stability. This could be attributed to the alteration of the protein molecule configuration leading to the building of a rigid and viscoelastic protein film around the droplet. Copyright © 2006 Society of Chemical Industry     

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.     

Backward difference formulae for Kuramoto–Sivashinsky type equations

We analyze the discretization of the periodic initial value problem for Kuramoto–Sivashinsky type equations with Burgers nonlinearity by implicit–explicit backward difference formula (BDF) methods, establish stability and derive optimal order error estimates. We also study discretization in space by spectral methods.     

Revisiting the cutting of the firing squad synchronization

Various synchronization algorithms have been introduced in literature during the last decades to deal with the firing squad synchronization problem on cellular automata (CA). Among others defective CA algorithms, where the CA cell is able to transmit information without previous processing, have been also presented. In our case, originating from the classical Mazoyer’s paper, where a minimum-time solution is presented with 6 states, a one-dimensional CA where one cell may permanently fail is presented. In the proposed algorithm, the defective cell can neither process nor transmit information any longer, while it is considered that such dynamic defects may become apparent in any time step of computation. A thorough analysis of the synchronization, in terms of location and time at which cell fails, for the cells found in both sides of defective cell is delivered to decipher the corresponding maximal possible number of synchronized cells in each part of the cut, due to defect, CA array. The proposed algorithm is properly extended to consider more than one defective cells that may occur in the under study one-dimensional CA. Based on the aforementioned analysis, we provide the generalization of synchronization with multiple totally defective cells, while application examples of the generalized CA algorithm in case of two defective cells are also presented. Finally, another intriguing aspect refers to handling of states that could be tentatively characterized as unknown, in a confrontation similar to the previous defective state but also different, since now this(these) cell(s) are not stated as faulty but unknown. As a result, a new one-dimensional CA with less states, compared to the previous CA defective algorithms, able to synchronize the maximal possible number of cells in each part occurs.