Difference between mechanical alloying and mechanical disordering in the amorphization reaction of Al50Ta50 in a rod mill

Amorphous Al₅₀Ta₆₀ alloy powders have been synthesized by mechanical alloying (MA) from elemental powders of aluminium and tantalum, and mechanical disordering (MD) from crystalline intermetallic compound powders of AlTa respectively using the rod milling technique. The mechanically alloyed and the mechanically disordered alloy powders were characterized by X-ray diffraction, scanning electron microscopy, electron probe microanalysis, transmission electron microscopy, differential thermal analysis, differential scanning calorimetry and chemical analysis. The results have shown that the crystal-to amorphous transformation in the MD process occurs through one stage, while the crystallineto-amorphous formation in the MA process occurs through three stages. At the early and intermediate stages of the MA time, heating the alloy powders to 700 K leads to the formation of an amorphous phase by a solid-state amorphizing reaction. At the final stage of the MA time, the amorphous phase is crystallized through a single sharp exothermic peak. Contrary to this, amorphous alloy powders produced by MD are crystallized through two broad exothermic peaks.     

激光退火对Inconel 718微观组织和硬度的影响

研究激光退火对Inconel718时效合金的显微组织和硬度的影响.一台2.5kW的CO2激光机被用来照射试样的表面.在激光能作用下,试样表面层被加热后空冷.通过控制激光工艺参数,在表面不发生熔化的前提下,能够使一定厚度表面层内的硬度降低到标准退火合金的水平,而不影响试样内部母材的硬度.显微组织观察显示表面层的基体强化相(γ″和γ‘)在激光照射过程中被固溶,而其它二次相没有变化.γ″和γ‘的固溶被确定是表面层硬度下降的原因.在其它试验条件不变时,确立了退火层生成时由激光散焦距离和扫描速度描述的工艺参数范围.     

Predicting viewer-perceived activity/dominance in soccer games with stick-breaking HMM using data from a fixed set of cameras

We attempted to predict activity/dominance for soccer games, where activity is defined as the degree of activity of the game as perceived by the viewer, whereas dominance is the degree at which the viewer perceives a particular team to dominate over the other team. Such activity/dominance information would help a layman viewer understand the game. It would also enable construction of an automatic digest creation system that extracts scenes having high activity/dominance. There are two facets of this study: 1. The main part of the underlying prediction model consists of a Stick-Breaking Hidden Markov Model, where the data automatically estimates the number of states of the Markov process behind the data. 2. The data used in this paper is vector time-series data consisting of player, referee, and ball positions, together with team information, acquired by a set of fixed cameras. The problem was approached with a Bayesian framework where learning and prediction were implemented by three different methods: Markov Chain Monte Carlo, Expectation Maximization, and Variational Bayes. The proposed method was tested using a dataset consisting of 10 professional soccer games and was compared against standard regression methods.     

Generalized measuring-worm algorithm: high-accuracy mapping and movement via cooperating swarm robots

Recently, many extensive studies have been conducted on robot control via self-positioning estimation techniques. In the simultaneous localization and mapping (SLAM) method, which is one approach to self-positioning estimation, robots generally use both autonomous position information from internal sensors and observed information on external landmarks. SLAM can yield higher accuracy positioning estimations depending on the number of landmarks; however, this technique involves a degree of uncertainty and has a high computational cost, because it utilizes image processing to detect and recognize landmarks. To overcome this problem, we propose a state-of-the-art method called a generalized measuring-worm (GMW) algorithm for map creation and position estimation, which uses multiple cooperating robots that serve as moving landmarks for each other. This approach allows problems of uncertainty and computational cost to be overcome, because a robot must find only a simple two-dimensional marker rather than feature-point landmarks. In the GMW method, the robots are given a two-dimensional marker of known shape and size and use a front-positioned camera to determine the marker distance and direction. The robots use this information to estimate each other’s positions and to calibrate their movement. To evaluate the proposed method experimentally, we fabricated two real robots and observed their behavior in an indoor environment. The experimental results revealed that the distance measurement and control error could be reduced to less than 3 %.     

Variable space diversity, crossover and mutation in MOEA solving many-objective knapsack problems

In this work, we analyze variable space diversity of Pareto optimal solutions (POS) and study the effectiveness of crossover and mutation operators in evolutionary many-objective optimization. First we examine the diversity of variables in the true POS on many-objective 0/1 knapsack problems with up to 20 items (bits), showing that variables in POS become noticeably diverse as we increase the number of objectives. We also verify the effectiveness of conventional two-point and uniform crossovers, Local Recombination that selects mating parents based on proximity in objective space, and two-point and uniform crossover operators which Controls the maximum number of Crossed Genes (CCG). We use NSGA-II, SPEA2, IBEA _??+? and MSOPS, which adopt different selection methods, and many-objective 0/1 knapsack problems with $n=\{100,250,500,750,\mbox{1,000}\}$ items (bits) and m?=?{2,4,6,8,10} objectives to verify the search performance of each crossover operator. Simulation results reveal that Local Recombination and CCG operators significantly improve search performance especially for NSGA-II and MSOPS, which have high diversity of genes in the population. Also, results show that CCG operators achieve higher search performance than Local Recombination for m?≥?4 objectives and that their effectiveness becomes larger as the number of objectives m increases. In addition, the contribution of CCG and mutation operators for the solutions search is analyzed and discussed.     

A content search system considering the activity and context of a mobile user

People routinely carry mobile devices in their daily lives and obtain a variety of information from the Internet in many different situations. In searching for information (content) with a mobile device, a user’s activity (e.g., moving or stationary) and context (e.g., commuting in the morning or going downtown in the evening) often change, and such changes can affect the user’s degree of concentration on his or her mobile device’s display and information needs. Therefore, a search system should provide the user with an amount of information suitable for the current activity and a type of information suitable for the current context. In this study, we present the design and implementation of a content search system that considers a mobile user’s activity and context, with the goal of reducing the user’s operation load for content search. The proposed system switches between two kinds of content search systems according to the user’s activity: the location-based content search system is activated when the user is stationary (e.g., standing and sitting), while a menu-based content search system is activated when the user is moving (e.g., walking). Both systems present information according to user context. The location-based system presents detailed information via menus and a map according to location-based categories. The menu-based system presents only a few options to enable users to get content easily. Through user experiments, we confirmed that participants could get desired information more easily with this system than with a commercial search system.     

FENECIA: failure endurable nested-transaction based execution of composite Web services with incorporated state analysis

Interest in the Web services (WS) composition (WSC) paradigm is increasing tremendously. A real shift in distributed computing history is expected to occur when the dream of implementing Service-Oriented Architecture (SOA) is realized. However, there is a long way to go to achieve such an ambitious goal. In this paper, we support the idea that, when challenging the WSC issue, the earlier that the inevitability of failures is recognized and proper failure-handling mechanisms are defined, from the very early stage of the composite WS (CWS) specification, the greater are the chances of achieving a significant gain in dependability. To formalize this vision, we present the FENECIA (Failure Endurable Nested-transaction based Execution of Composite Web services with Incorporated state Analysis) framework. Our framework approaches the WSC issue from different points of view to guarantee a high level of dependability. In particular, it aims at being simultaneously a failure-handling-devoted CWS specification, execution, and quality of service (QoS) assessment approach. In the first section of our framework, we focus on answering the need for a specification model tailored for the WS architecture. To this end, we introduce WS-SAGAS, a new transaction model. WS-SAGAS introduces key concepts that are not part of the WS architecture pillars, namely, arbitrary nesting, state, vitality degree, and compensation, to specify failure-endurable CWS as a hierarchy of recursively nested transactions. In addition, to define the CWS execution semantics, without suffering from the hindrance of an XML-based notation, we describe a textual notation that describes a WSC in terms of definition rules, composability rules, and ordering rules, and we introduce graphical and formal notations. These rules provide the solid foundation needed to formulate the execution semantics of a CWS in terms of execution correctness verification dependencies. To ensure dependable execution of the CWS, we present in the second section of FENECIA our architecture THROWS, in which the execution control of the resulting CWS is distributed among engines, discovered dynamically, that communicate in a peer-to-peer fashion. A dependable execution is guaranteed in THROWS by keeping track of the execution progress of a CWS and by enforcing forward and backward recovery. We concentrate in the third section of our approach on showing how the failure consideration is trivial in acquiring more accurate CWS QoS estimations. We propose a model that assesses several QoS properties of CWS, which are specified as WS-SAGAS transactions and executed in THROWS. We validate our proposal and show its feasibility and broad applicability by describing an implemented prototype and a case study.     

Analysis of Speaker Adaptation Algorithms for HMM-Based Speech Synthesis and a Constrained SMAPLR Adaptation Algorithm

In this paper, we analyze the effects of several factors and configuration choices encountered during training and model construction when we want to obtain better and more stable adaptation in HMM-based speech synthesis. We then propose a new adaptation algorithm called constrained structural maximum a posteriori linear regression (CSMAPLR) whose derivation is based on the knowledge obtained in this analysis and on the results of comparing several conventional adaptation algorithms. Here, we investigate six major aspects of the speaker adaptation: initial models; the amount of the training data for the initial models; the transform functions, estimation criteria, and sensitivity of several linear regression adaptation algorithms; and combination algorithms. Analyzing the effect of the initial model, we compare speaker-dependent models, gender-independent models, and the simultaneous use of the gender-dependent models to single use of the gender-dependent models. Analyzing the effect of the transform functions, we compare the transform function for only mean vectors with that for mean vectors and covariance matrices. Analyzing the effect of the estimation criteria, we compare the ML criterion with a robust estimation criterion called structural MAP. We evaluate the sensitivity of several thresholds for the piecewise linear regression algorithms and take up methods combining MAP adaptation with the linear regression algorithms. We incorporate these adaptation algorithms into our speech synthesis system and present several subjective and objective evaluation results showing the utility and effectiveness of these algorithms in speaker adaptation for HMM-based speech synthesis.