Effect of updating training on fluid intelligence in children

Recent studies have indicated that working memory (WM) training can improve fluid intelligence.However,these earlier studies confused the impact of WM storage and central executive function on the effects of training.The current study used the running memory task to train the updating ability of 9-11 year-old children using a double-blind controlled design.The results revealed that children’s fluid intelligence was significantly improved by memory-updating training.Overall,our findings suggest that the increase in fluid intelligence achieved with WM training is related to improving central executive function.     

A rough sets based pruning method for bagging ensemble

Ensemble techniques train a set of component classifiers and then combine their predictions to classify new patterns. Bagging is one of the most popular ensemble techniques for improving weak classifiers. However, it is hard to deploy in many real applications because of the large memory requirement and high computation cost to store and vote the predictions of component classifiers. Rough set theory is a formal mathematical tool to deal with incomplete or imprecise information, which has attracted a lot of attention from theory and application fields. In this paper, a novel rough sets based method is proposed to prune the classifiers obtained from bagging ensemble and select a subset of the component classifiers for aggregation. Experiment results show that the proposed method not only decreases the number of component classifiers but also obtains acceptable performance.     

Satellite Image Adaptive Restoration Using Periodic Plus Smooth Image Decomposition and Complex Wavelet Packet Transforms

A satellite image adaptive restoration method was developed that avoids ringing artifacts at the image boundary and retains oriented features. The method combines periodic plus smooth image decomposition with complex wavelet packet transforms. The framework first decomposes a degraded satellite image into the sum of a "periodic component" and a "smooth component". The Bayesian method is then used to estimate the modulation transfer function degradation parameters and the noise. The periodic component is deconvoluted using complex wavelet packet transforms with the deconvolution result of the periodic component then combined with the smooth component to get the final recovered result. Tests show that this strategy effectively avoids ringing artifacts while preserving local image details (especially directional textures) without amplifying the noise. Quantitative comparisons illustrate that the results are comparable with previous methods. Another benefit is that this approach can process large satellite images with parallel processing, which is important for practical use.     

Task graph reduction algorithm for hardware/software partitioning

Hardware/software(HW/SW) partitioning is one of the key processes in an embedded system.It is used to determine which system components are assigned to hardware and which are processed by software.In contrast with previous research that focuses on developing efficient heuristic,we focus on the pre-process of the task graph before the HW/SW partitioning in this paper,that is,enumerating all the sub-graphs that meet the requirements.Experimental results showed that the original graph can be reduced to 67% in the worst-case scenario and 58% in the best-case scenario.In conclusion,the reduced task graph saved hardware area while improving partitioning speed and accuracy.     

An Energy-Saving Task Scheduling Strategy Based on Vacation Queuing Theory in Cloud Computing

High energy consumption is one of the key issues of cloud computing systems. Incoming jobs in cloud computing environments have the nature of randomness, and compute nodes have to be powered on all the time to await incoming tasks. This results in a great waste of energy. An energy-saving task scheduling algorithm based on the vacation queuing model for cloud computing systems is proposed in this paper. First, we use the vacation queuing model with exhaustive service to model the task schedule of a heterogeneous cloud computing system.Next, based on the busy period and busy cycle under steady state, we analyze the expectations of task sojourn time and energy consumption of compute nodes in the heterogeneous cloud computing system. Subsequently, we propose a task scheduling algorithm based on similar tasks to reduce the energy consumption. Simulation results show that the proposed algorithm can reduce the energy consumption of the cloud computing system effectively while meeting the task performance.     

Parallel Simulation of 3-D Turbulent Flow Through Hydraulic Machinery

Parallel calculational methods were used to analyze incompressible turbulent flow through hydraulic machinery. Two parallel methods were used to simulate the complex flow field. The space decomposition method divides the computational domain into several sub-ranges. Parallel discrete event simulation divides the whole task into several parts according to their functions. The simulation results were compared with the serial simulation results and particle image velocimetry (PIV) experimental results. The results give the distribution and configuration of the complex vortices and illustrate the effectiveness of the parallel algorithms for numerical simulation of turbulent flows.     

Anthropometric Study of the Physique of Hong Kong-Chinese Fire Services Recruits to Streamline the Sizing System

This research applies the principles of anthropometrics to improve existing size charts together with somatotyping techniques to define the physique of the Hong Kong-Chinese Fire Services recruits. The research results proved that age does not correspond with either body measurements or somatotype components. The results of the study demonstrates that the somatotype component (i. e., endomorphy, mesomorphy and ectomorphy) has low to moderate correlation with body girth and body length measurements.     

Analysis of Factors Affecting Execution Performance of OpenMP Programs

OpenMP is able to develop multithreaded programs with lower cost as a promising way to quickly parallelize a great number of serial programs. However, there are many difficulties when developing OpenMP multithreaded programs. Most importantly, the performance of OpenMP programs cannot be guaranteed, which has greatly affected the application of OpenMP. This paper examines several factors that affect the execution performance of OpenMP programs, including loop transformation, scheduling strategy, the number of threads, and nested parallelism. The results show that one of the key reasons for performance degradation is load imbalance, which can be corrected by reasonable use of these key factors to improve the execution performance of OpenMP programs.     

Evaluation of mental fatigue based on multipsychophysiological parameters and kernel learning algorithms

Mental fatigue is an extremely sophisticated phenomenon, which is influenced by the environment, the state of health, vitality and the capability of recovery. A single parameter cannot fully describe it. In this paper, the effects of long time sustained low-workload visual display terminal （VDT） task on psychology are investigated by subjective self-reporting measures. Then power spectral indices of HRV, the P300 components based on visual oddball and wavelet packet parameters of EEG are combined to analyze the impacts of prolonged visual display terminal （VDT） activity on autonomic nervous system and central nervous system. Finally, wavelet packet parameters of EEG are extracted as the features of brain activity in different mental fatigue states. Kernel principal component analysis （KPCA） and support vector machine （SVM） are jointly applied to differentiate two states. The statistic results show that the level of both subjective sleepiness and fatigue increase significantly from pre-task to post-task, which indicate that the long time VDT task induces the mental fatigue to the subjects. The predominant activity of autonomic nervous system of subjects turns to the sympathetic activity from parasympathetic activity after the task. The P300 components and wavelet packet parameters of EEG are strongly related with mental fatigue. Moreover, the joint KPCA-SVM method is able to effectively reduce the dimensionality of the feature vectors, speed up the convergence in the training of SVM and achieve a high recognition accuracy （87%） of mental fatigue state. Multipsychophysiological measures and KPCA-SVM method could be a promising tool for the evaluation of mental fatigue.     

Design and experimental study of thermal control system for AMS cryocoolers

The Alpha Magnetic Spectrometer(AMS) is an instrument for the international scientific experiment,composed of six detectors and 650 micro-electronics.The objective of AMS experiment is to search for dark matter and anti-matter in space.In this paper,the thermal control system for AMS cryocoolers is designed,analyzed and experimentally studied.Using loop heat pipes(LHPs) as the main heat dissipation component,the thermal control system has sufficient heat dissipation capability to prevent the cryocoolers from over temperature(+40℃) in hot environment,meanwhile to ensure temperatures of the cryocoolers higher than their lower limit(-20℃) in cold environment.Experiment results show that the thermal control system for AMS cryocoolers functions stably satisfying design specification.     

Feature Extraction of Fabric Defects Based on Complex Contourlet Transform and Principal Component Analysis

To extract features of fabric defects effectively and reduce dimension of feature space,a feature extraction method of fabric defects based on complex contourlet transform （CCT） and principal component analysis （PCA） is proposed.Firstly,training samples of fabric defect images are decomposed by CCT.Secondly,PCA is applied in the obtained low-frequency component and part of highfrequency components to get a lower dimensional feature space.Finally,components of testing samples obtained by CCT are projected onto the feature space where different types of fabric defects are distinguished by the minimum Euclidean distance method.A large number of experimental results show that,compared with PCA,the method combining wavdet low-frequency component with PCA （WLPCA）,the method combining contourlet transform with PCA （CPCA）,and the method combining wavelet low-frequency and highfrequency components with PCA （WPCA）,the proposed method can extract features of common fabric defect types effectively.The recognition rate is greatly improved while the dimension is reduced.     

Optimal Component Types for the Design of Construction Processes

Within the project preparation phase, experienced professionals manually map design information onto process information with the aim to develop realistic and practical schedules. Unfortunately, the mapping itself is neither part of any underlying data model nor is it supported by current scheduling tools. As a consequence the process of setting up the data model for a schedule is still not supported formally. Huhnt and Enge described a modelling technique that addresses the missing linkage between design and process information[1]. The approach makes use of so called component types. These are template sub-processes that describe the fabrication procedure of typical building components. Decomposing the building into com-ponents and assigning a component type to each component allows for formal support while scheduling. Depending on the decomposition of the building into components and the complexity of the involved component types the specification effort differs. The question about optimal component types arises: Which layout of building components and component types results in minimal specification effort? This paper presents a branch and bound algorithm to determine optimal component types. For a given schedule, which has been modelled based on component types, all possible decompositions into sub-processes are determined. During the decomposition process the encountered configurations are compared. Those with minimal specifica-tion effort are registered. Theoretical and practical examples are examined and discussed.     

Defeating constraint based program analysis with temporal correlation function

Constraint based program analysis is widely used in program validation, program vulnerability analysis, etc. This paper proposes a temporal correlation function to protect programs from analysis. The temporal correlation function can be applied to resist against both static and dynamic function summary and eoncolie testing. What＇ s more, the temporal correlation function can produce different outputs even with same input. This feature can be used to damage the premise of function summary as well as prevent concolie testing process to run the new branch with new input. Experiment results show that this method can reduce efficiency and path coverage of concolic testing, while greatly in- creasing the difficulty of constraint based program analysis.     

Multi-layer synthesis of highly-structured texture

In this paper, a novel concept of multilayer synthesis and a general framework for texture synthesis method are presented. Within this framework, we first decompose the texture into the supposed pattern layer and material layer in the frequency domain by an E-texton extracting algorithm, then manipulate and extend them respectively according to their own personalities, and finally merge the newly synthesized pattern layer and material layer again to generate the final output. Experiment results show that our method not only greatly improves the synthesis quality for those cases that single-layer synthesis cannot handle well but also provides an ability of achieving various special synthesis effects.     

Interactions between working memory and selective attention

Event-related potential (ERP) was used to examine the interactions between working memory and se- lective attention. We combined two unrelated tasks, one requiring working memory and the other se- lective attention, which were performed by some undergraduates. The ERP results revealed that both congruent and incongruent stimuli in the selective attention task evoked an N400 component, reaching the peak point at around 500 ms. The N400 evoked by incongruent stimuli was more negative than that of congruent, which indicated the difference of semantic N400. Furthermore, working memory load had a significant influence on the N400 evoked by selective attention task in parietal region. And working memory load showed difference in the ERPs of working memory retrieval in central and parietal regions. The ERPs of probe under high working memory load were more positive from 350 to 550 ms post-stimulus; however, stimulus type of selective attention had no influence on working memory re- trieval. The present study shows that working memory does not play a major role in the selective at- tention, especially in ignoring distracter, but it influences the performance of the selective attention as the background. The congruency of target and distracter in the selective attention task does not influ- ence the working memory retrieval.     

Inconspicuous anchoring effects generated by false information

The impact of false information on numerical judgments was examined on young normal subjects by an event-related potential （ERP） experiment. To imitate the judgments in real world, we ensured the subjects acknowledged of the target task. The behavioral results found that both uncertain information and false information assimilated the final estimates： higher after higher anchors and lower after lower anchors; and false information caused a weaker anchoring bias than uncertain information. ERP results provided further electro- physiological evidence for the mechanism of anchoring. In the early phrase, it was an accessibility-dominated process in which two kinds of anchors elicited an N300 component related to the accessibility of anchors propositions. The knowledge relevant to targets joined the process in the late phrase, which caused a larger amplitude of late positive component （LPC） for implausible lower anchors than that for plausible higher anchors. Source analysis showed that medial frontal gyrus, whose activity was suggested to signal the need of adjust- ment, was more reliable to explain the LPC elicited by implausible lower anchors. Therefore, we suggest that accessibility is facilitated when the external anchor is consistent with the world knowledge, and adjustment is initiated when the external anchor is inconsistent.     

DDoS Defense Algorithm Based on Multi-Segment Timeout Technology

Through the analysis to the DDoS（distributed denial of service） attack, it will conclude that at different time segments, the arrive rate of normal SYN （Synchronization） package are similar, while the abnormal packages are different with the normal ones. Toward this situation a DDoS defense algorithm based on multi-segment timeout technology is presented, more than one timeout segment are set to control the net flow. Experiment results show that in the case of little flow, multi-segment timeout has the ability dynamic defense, so the system performance is improved and the system has high response rate.     

Involvement of the crebellum in sequential finger movement learning： Evidence from functional magnetic resonance imaging

Whether the cerebellum is involved in voluntary motor learning or motor performance is the subject of a new debate. Using functional magnetic resonance imaging （fMRI）, we examined cerebellar activation in eight voluntecrs before and after an extended period of training. Activation volume on both sides of cerebellum after learning was significantly reduced compared to that before learning even under the same motor frequency. Remarkably, while motor frequency for the training sequence was significantly higher than the control sequence after 41 d of learning, activation in the cerebellum for both sequences, with respect to activation loci and volumes, was very similar. These results suggest that the cerebellum was involved in motor learning but not motor performance. Changes of cerebellar activation from training thus appear to be associated with learning but not with improvement on task performance.     

An Intelligent Agent Approach to Adaptive Project Management

This paper presents the initial steps to integrating a distributed discrete event simulation system with a framework for intelligent software agents. The resulting system has a simulation component that is based on the high-level architecture (HLA) and an agent component that implements the belief-desire-intention (BDI) approach to agent modelling. The architecture is connected to a real-time information source. The framework was successfully applied to a real-life monitoring system for a tunnel-boring machine excavation project that helped with forecasting and managing the project timelines in response to the changes in the uncertain excavation environment. This project is presented as a test case and demonstrates encouraging results for integrative modelling of large-scale problems with elements of uncertainty.     

Material differences of auditory source retrieval: Evidence from event-related potential studies

Two event-related potential experiments were conducted to investigate the temporal and the spatial distributions of the old/new effects for the item recognition task and the auditory source retrieval task using picture and Chinese character as stimuli respectively. Stimuli were presented on the center of the screen with their names read out either by female or by male voice simultaneously during the study phase and then two testa were performed separately. One test task was to differentiate the old items from the new ones, and the other task was to judge the items read out by a certain voice during the study phase as targets and other ones as non-targets. The results showed that the old/new effect of the auditory source retrieval task was more sustained over time than that of the item recognition task in both experiments, and the spatial distribution of the former effect was wider than that of the latter one. Both experiments recorded reliable old/new effect over the prefrontal cortex during the source retrieval task. However, there existed some differences of the old/new effect for the auditory source retrieval task between picture and Chinese character, and LORETA source analysis indicated that the differences might be rooted in the temporal lobe. These findings demonstrate that the relevancy of the old/new effects between the item recognition task and the auditory source retrieval task supports the dual-process model; the spatial and the temporal distributions of the old/new effect elicited by the auditory source retrieval task are regulated by both the feature of the experimental material and the perceptual attribute of the voice.