A robust method for axis identification

The present paper proposes a new method for axis identification in discrete axially symmetrical geometric models. This method is based on-a-never-used-before property of the axially symmetrical surfaces for which the symmetry line of any section curve of the surface (or of a portion of it in the case of an incomplete axially symmetrical surface) always intersects the axis of symmetry of the surface. Thus the working principle of the method makes it very robust to local defectiveness, measurement noise and outliers.In order to compare it with the most cited methods presented in literature, several types of tests have been designed and performed. The robustness of those methods, on the one hand, has been evaluated by defining the Statistical Confidence Boundary at 1σ confidence level. The trueness of the method, on the other hand, has been evaluated on geometric models obtained by measuring real objects. The high robustness, which characterizes the proposed method, makes it particularly suitable for product geometric inspection where high accuracy is required.     

Parallel chaos optimization algorithm with migration and merging operation

Chaos optimization algorithm (COA) utilizes the chaotic maps to generate the pseudo-random sequences mapped as the decision variables for global optimization applications. A kind of parallel chaos optimization algorithm (PCOA) has been proposed in our former studies to improve COA. The salient feature of PCOA lies in its pseudo-parallel mechanism. However, all individuals in the PCOA search independently without utilizing the fitness and diversity information of the population. In view of the limitation of PCOA, a novel PCOA with migration and merging operation (denoted as MMO-PCOA) is proposed in this paper. Specifically, parallel individuals are randomly selected to be conducted migration and merging operation with the so far parallel solutions. Both migration and merging operation exchange information within population and produce new candidate individuals, which are different from those generated by stochastic chaotic sequences. Consequently, a good balance between exploration and exploitation can be achieved in the MMO-PCOA. The impacts of different one-dimensional maps and parallel numbers on the MMO-PCOA are also discussed. Benchmark functions and parameter identification problems are used to test the performance of the MMO-PCOA. Simulation results, compared with other optimization algorithms, show the superiority of the proposed MMO-PCOA algorithm.     

Semantically enriched Massive Open Online Courses (MOOCs) platform

Massive Open Online Courses (MOOCs) are becoming an essential source of information for both students and teachers. Noticeably, MOOCs have to adapt to the fast development of new technologies; they also have to satisfy the current generation of online students. The current MOOCs’ Management Systems, such as Coursera, Udacity, edX, etc., use content management platforms where content are organized in a hierarchical structure. We envision a new generation of MOOCs that support interpretability with formal semantics by using the SemanticWeb and the online social networks. Semantic technologies support more flexible information management than that offered by the current MOOCs’ platforms. Annotated information about courses, video lectures, assignments, students, teachers, etc., can be composed from heterogeneous sources, including contributions from the communities in the forum space. These annotations, combined with legacy data, build foundations for more efficient information discovery in MOOCs’ platforms. In this article we review various Collaborative Semantic Filtering technologies for building Semantic MOOCs’ management system, then, we present a prototype of a semantic middle-sized platform implemented at Western Kentucky University that answers these aforementioned requirements.     

Negotiation based adaptive learning sequences: Combining adaptivity and adaptability

This study proposes a negotiation-based approach to combine the notion of adaptivity (system-controlled adaptation) and adaptability (user-controlled adaptation) for an adaptive learning system. The system suggests adaptations and the student also submits his/her adaptation preference. When the student preference opposes the system suggestion, the student then negotiates with the system to reach an agreement of adaptation. A negotiation-based adaptive learning system (NALS) is implemented to support the generation of personalized adaptive learning sequences by system negotiations with students regarding assessments of learning performance (i.e. negotiated open student model) of the current content and choices of the next learning content (i.e. negotiation of adaptation). Students require two metacognitions in deciding adaptive learning sequences: self-assessment for evaluating their understanding of the current content and regulation for choosing appropriate learning content. Negotiated open student model are used for assist student self-assessment and negotiation of adaptation are used for assist student regulation of content choices. An experiment was conducted to compare a system-controlled adaptive learning system (SALS, adaptivity), a user-controlled adaptive learning system (UALS, adaptability), and a NALS. The results revealed that NALS promoted better metacognitions in student calibration (i.e. self-assessment) accuracy and learning content choices (i.e. regulation). Preliminary evidences also showed that NALS promoted better student performance in a delay test. The results further suggested that students with poor calibration accuracy and inappropriate content choices were not suitable to use UALS and were suitable to use SALS. The NALS can also be used for training students to make appropriate adaptation for learning.     

基于Labview的RGL棒位通道再鉴定试验台设计

反应堆控制棒棒控系统(RGL)是核电站主要的控制系统之一。控制棒组件(RCCA)是核反应堆压力容器内的主要控制部件,因此,用以检查RCCA在低速状态下插入和提升过程中,命令棒位与测量棒位是否一致的试验"RGL棒位通道再鉴定"非常重要。为提高大亚湾核电站在大修期间RGL棒位通道再鉴定试验的效率,设计一种新的RGL棒位通道再鉴定试验台。该试验台解决了试验数据分析困难等问题,且简便易用,对该试验具有重要意     

Modeling Smart Grid neighborhoods with the ENERsip ontology

The electricity consumption in the buildings sector has been steadily increasing during the last decade, up to the point that energy efficiency in this sector has become a major problem for governments, utilities, customers, and the environment. The foreseen high penetration of distributed micro-generation facilities based on renewables can help to reduce the environmental footprint of buildings and households, although the complexity of managing effectively the electric grid increases dramatically under these conditions. The IEEE 2030 standard for interoperability in the Smart Grid remarks upon the importance of well-defined data models in such complex scenarios and puts emphasis on the benefits of ontologies and OWL (Web Ontology Language) for this purpose. This paper presents an OWL-based ontology that formally defines the vocabulary and taxonomy and captures the engineering and business semantics of this domain of knowledge (i.e., energy efficiency in the so-called nZEN – nearly Zero-Energy Neighborhoods). This ontology has been defined under the scope of the EU (European Union) research project ENERsip. The paper also highlights the main benefits the ontology brought to all the phases of the project life cycle, as well as how future work can make the most out of it.     

Bayesian system identification of dynamical systems using large sets of training data: A MCMC solution

In the last 20 years the applicability of Bayesian inference to the system identification of structurally dynamical systems has been helped considerably by the emergence of Markov chain Monte Carlo (MCMC) algorithms – stochastic simulation methods which alleviate the need to evaluate the intractable integrals which often arise during Bayesian analysis. In this paper specific attention is given to the situation where, with the aim of performing Bayesian system identification, one is presented with very large sets of training data. Building on previous work by the author, an MCMC algorithm is presented which, through combing Data Annealing with the concept of ‘highly informative training data’, can be used to analyse large sets of data in a computationally cheap manner. The new algorithm is called Smooth Data Annealing.     

Crosstalk-aware multi-bit flip-flop generation for power optimization

Applying multi-bit flip-flops (MBFFs) for clock power reduction in modern nanometer ICs has been becoming a promising lower-power design technique. Many previous works tried to utilize as more MBFFs with larger number of bits as possible to gain more clock power saving. However, an MBFF with larger number of bits may lead to serious crosstalk due to the close interconnecting wires belonging to different signal nets which are connected to the same MBFF. This paper analyzes, evaluates, and compares the relationship between power consumption and crosstalk when applying MBFFs with different numbers of bits. To solve the addressed problem, a novel crosstalk-aware power optimization approach is further proposed to optimize power consumption while satisfying the crosstalk constraint. Experimental results show that the proposed approach is very effective in crosstalk avoidance when applying MBFFs for power optimization.     

Sexual self-presentation on social network sites: Who does it and how is it perceived?

The aims of this study were to investigate (a) the role of peer factors in adolescents’ sexual self-presentation on social network sites, and (b) how adolescents who present themselves sexually online are evaluated by others. 238 high school students (aged 12–18) evaluated either a sexual or non-sexual online presentation of same-sex and opposite-sex peers. Moreover, they filled in a questionnaire about their own self-presentation behavior. Findings showed that peer norms played a crucial role in whether adolescents posted sexual pictures of themselves online. Moreover, need for popularity was a strong predictor for posting such pictures. Girls who presented themselves in sexual ways were evaluated more negatively by other girls but more positively by boys. Similarly, boys who presented themselves in sexual ways were evaluated more positively by girls but not by boys.     

A new catalyst based on a nickel(II) complex of diiminodiphosphine for hydrogen evolution and oxidation

Based on that hydrogen energy is widely used in fuel cells, we focus our interests on the design and research of new complexes that catalyze the reaction in both directions, such as hydrogen evolution reactions (HERs) and hydrogen oxidation reactions (HORs). A highly efficient catalyst for both hydrogen evolution and oxidation, based on a nickel(II) complex, [Ni-en-P₂](ClO₄)₂, has been designed and provided by the reaction of Ni(ClO₄)₂ with N,N′-bis[o-(diphenylphosphino)benzylidene]ethylenediamine (en-P₂) in our group. Its structure has been determined by X-ray diffraction. [Ni-en-P₂](ClO₄)₂ can electro-catalyze hydrogen evolution both from acetic acid and a neutral buffer (pH 7.0) with a turnover frequency (TOF) of 204 and 1327 mol of hydrogen per mole of catalyst per hour (H₂/mol catalyst/h) under an overpotential (OP) of 914.6 mV and 836.6 mV, respectively. [Ni-en-P₂](ClO₄)₂ also can electro-catalyze hydrogen oxidation with a TOF of 111.7 s⁻¹ under an OP of 330 mV. The results can be attributed to that [Ni^II-en-P₂](ClO₄)₂ has three good reversible redox waves at 1.01 (Ni^III/II), −0.79 (Ni^II/I) and −1.38 V (Ni^I/0) versus Fc^+/0, respectively. We hope these findings can afford a new method for the design of electrocatalysts for both H₂ evolution and H₂ oxidation.