A study of train group operation multi-agent model oriented RITS

In this paper, aiming at describing interrelationships and communication mechanisms among agents based on a multi-agent framework of Railway Intelligent Transportation System (RITS), we construct the model about stations and trains in the system, which is called Agent-Oriented G-Net Train Group Operation Model (AGNTOM). The framework degrades the complexity of computation and makes the distribution of simulation system easy in design. The simulated experiments prove that the model provides an effective approach for dealing with communication problems in the system.

Clustering based multi-label classification for image annotation and retrieval

This paper presents a novel multi-label classification framework for domains with large numbers of labels. Automatic image annotation is such a domain, as the available semantic concepts are typically hundreds. The proposed framework comprises an initial clustering phase that breaks the original training set into several disjoint clusters of data. It then trains a multi-label classifier from the data of each cluster. Given a new test instance, the framework first finds the nearest cluster and then applies the corresponding model. Empirical results using two clustering algorithms, four multi-label classification algorithms and three image annotation data sets suggest that the proposed approach can improve the performance and reduce the training time of standard multi-label classification algorithms, particularly in the case of large number of labels.

EPODE approach for childhood obesity prevention : methods, progress and international development

Childhood obesity is a complex issue and needs multistakeholder involvement at all levels to foster healthier lifestyles in a sustainable way. ‘Ensemble Prévenons l'ObésitéDes Enfants’ (EPODE, Together Let's Prevent Childhood Obesity) is a large-scale, coordinated, capacity-building approach for communities to implement effective and sustainable strategies to prevent childhood obesity. This paper describes EPODE methodology and its objective of preventing childhood obesity.

At a central level, a coordination team, using social marketing and organizational techniques, trains and coaches a local project manager nominated in each EPODE community by the local authorities. The local project manager is also provided with tools to mobilize local stakeholders through a local steering committee and local networks. The added value of the methodology is to mobilize stakeholders at all levels across the public and the private sectors. Its critical components include political commitment, sustainable resources, support services and a strong scientific input – drawing on the evidence-base – together with evaluation of the programme.

Since 2004, EPODE methodology has been implemented in more than 500 communities in six countries. Community-based interventions are integral to childhood obesity prevention. EPODE provides a valuable model to address this challenge.

Expansion of congested railway capacity using triple-track line operation based on hourly passenger demand

This paper proposes a method of improving level of service in congested urban railways by means of a triple-track line operation for a highly dense urban area with special travel demand characteristics. Where the future travel demand forecasts show sluggish growth or no growth at all, there is little to no incentives for heavy railway investments like quadruple-track extension and construction of new railway routes to alleviate current railway congestion problems. In such a situation, triple-track line operation can be the best alternative due to its moderate investment cost and ease in land acquisition for just an additional single track along the existing tracks. Our simulation investigation in one of the congested railway lines in Tokyo showed that triple track line operation increases railway capacity by 26% and shortens travel time by 38% in peak direction during morning peak hours. These results are encouraging and are useful for removing current railways problems in Tokyo and in similar urban situations elsewhere.

Railway stations : public realm gateways to sustainable futures of our cities

Train stations are places of connection in our cities and are the gateways of urban space. They represent one of the most exciting places to experience. Some stations make great destinations offering shops, restaurants, museums and exhibition spaces to commuters. While new architecture at railway stations acknowledges heritage, the urban spaces around them provide excellent public areas and rationalise functional needs. Grand spaces with monumental structures, including constant movement of people and trains makes for an exhilarating experience. Modern or historic, great train stations add another level of excitement in the regeneration of our cities. Adding into the mix of the sustainability paradigm, place making of railway stations transforms into sustainable urban centres and signature architecture, but how does it support an environmentally sustainable future? This paper reflects the journey of exploring the challenging situations of balancing the requirements between historic, operational, functional, economic and innovative sustainable design solutions during the Flinders Street Station Design Competition in Melbourne. The author highlights how the unique spatial, social and cultural circumstance of this world-renowned city railway station possesses specific resilient and sustainable design answers to a public realm and city space that challenges established thinking.

Semi-supervised classification based on subspace sparse representation

Graph plays an important role in graph-based semi-supervised classification. However, due to noisy and redundant features in high-dimensional data, it is not a trivial job to construct a well-structured graph on high-dimensional samples. In this paper, we take advantage of sparse representation in random subspaces for graph construction and propose a method called Semi-Supervised Classification based on Subspace Sparse Representation, SSC-SSR in short. SSC-SSR first generates several random subspaces from the original space and then seeks sparse representation coefficients in these subspaces. Next, it trains semi-supervised linear classifiers on graphs that are constructed by these coefficients. Finally, it combines these classifiers into an ensemble classifier by minimizing a linear regression problem. Unlike traditional graph-based semi-supervised classification methods, the graphs of SSC-SSR are data-driven instead of man-made in advance. Empirical study on face images classification tasks demonstrates that SSC-SSR not only has superior recognition performance with respect to competitive methods, but also has wide ranges of effective input parameters.

Poor tolerance of motor cortex rTMS in chronic migraine

Background:
Two small studies had evaluated the efficacy of rTMS in migraine. One tested high frequency rTMS over the dorsolateral prefrontal cortex while the other evaluated 1 Hz rTMS over the vertex.
Aim:
To test the feasibility of 10 Hz rTMS of motor cortex as an adjunctive therapy in patients with chronic migraine.
Materials and Methods:
We randomized (2:1 ratio) chronic migraine patients on medical preventive treatment to receive either rTMS or sham therapy for 10 sessions. rTMS (80% resting motor threshold, 10Hz, 20 trains, 5 secs/train, inter-train interval 1 min, total 1000 stimuli/session) was applied over the right motor cortex.
Result:
Nine patients were randomized. Six received rTMS
and three had sham therapy. Three patients in the rTMS arm withdrew from the study due to increased headache frequency and discomfort from the treatment. The remaining six cases (3 rTMS, 3 sham) completed the study. The study was prematurely stopped due to the significant worsening of headache from rTMS. No significant differences in outcome measures were found between real and sham rTMS.
Conclusion:
Although the study was terminated prematurely, the high dropout rate (50%) due to worsening headaches suggested that rTMS over the motor cortex is poorly tolerated in chronic migraine.

We are in danger

Genre films are constructed out of narrative patterns and plot points that involve or are predicted on crisis, on danger. This is the logic of much if not all mainstream genre cinema: drama has to take place for there to be a story to be told, and for pleasure and identification to be arrested and enthused. Forms of threatening disequilibrium can be personal, domestic, familial, local, external, supernatural and murderous; a way of life can be threatened as well as life itself. There are ideological dimensions at play; the crisis threatens to destabilize patriarchy, heterosexuality, social norms and expectations. Feelings and modes of affect are set in dangerous motion as the crisis unfolds. Trouble may emerge from a wayward or transgressive family member, or it may arrive in town on horses, stagecoaches, trains, cars, spaceships, and on the wind and in the water. The main (and minor) characters in the film are at the center of this storm, and that places viewers at the epicenter of the danger, also. The genre film places us all in danger. The genre film, then, has phenomenal, phenomenological and bio-political potential as a site of cognitive, ideological and carnal endangerment.