Search results

The purpose of this study is to simulate the temperature distribution during an electron beam freeform fabrication (EBF³) process based on a fully threaded tree (FTT) technique in various scales and to analyze the temperature variation with time in different regions of the part.

This study presented a revised model for the temperature simulation in the EBF³ process. The FTT technique was then adopted as an adaptive grid strategy in the simulation. Based on the simulation results, an analysis regarding the temperature distribution of a circular deposit and substrate was performed.

The FTT technique was successfully adopted in the simulation of the temperature field during the EBF³ process. The temperature bands and oscillating temperature curves appeared in the deposit and substrate.

The FTT technique was introduced into the numerical simulation of an additive manufacturing process. The efficiency of the process was improved, and the FTT technique was convenient for the 3D simulations and multi-pass deposits.

Efficient operation of supply chain management (SCM) software is highly dependent on performance of its data structures that are used for data storage and retrieval. Each module in the software should use data structures that are appropriate for the types of operations performed in that module. The purpose of this paper is to develop and introduce an efficient data structure for storage and retrieval of data related to capacity of resources.

A major aim of supply management systems is timely production and delivery of products. This paper reviews data structures and designs an efficient data structure for storage and retrieval of data that is used in the scheduling module of SCM software.

This paper introduces a new data structure and search and update algorithms. This data structure can be used in SCM software to record the availability of non‐storable resources.

This is the first paper that discusses the role of data structures in SCM software and develops a data structure that can be used in the scheduling routine of SCM systems. Scheduling is one of the complex modules of SCM software. Some of the special characteristics related to capacity of resources to develop a data structure that can be efficiently searched and updated as part of scheduling routines were used in the new data structure. This data structure is a modified version of threaded height‐balanced binary search tree. Each node in the proposed tree has one more key than a node in the ordinary threaded height‐balanced binary search tree. The available algorithms in the literature on search and update operations on height‐balanced binary search trees are modified to suit the proposed tree.

Items of information that have been stored in a computer normally need to be accessed via their contents. In principle this is always possible by doing an exhaustive scan of the entire file of information, but to achieve the access efficiently we use some sort of organizing principle, a file organization or file structure, to reduce the amount anning. Typically the items retrieved are a response to a request which fully or partially specifies their contents. Often the file organization requires pre‐processing of the body of information so that a secondary body of information (an index or directory) may be created which in some sense reveals the contents of the file. So, ultimately file structures are time saving devices, where we pay for the time saved by extra storage. They enable us quickly to find items of information by completely or partially specifying their contents.

To utilize the idle computational resources in a network to collectively solve middle to large problems, this paper aims to propose an integrated distributed computing platform, Java distributed code generating and computing (JDGC).

The proposed JDGC is fully decentralized in that every participating host is identical in function. It allows standard, single machine‐oriented Java programs to be transparently executed in a distributed system. The code generator reduces the communication overhead between runtime objects based on a detailed analysis of the communication affinities between them.

The experimental results show that JDGC can efficiently reduce the execution time of applications by utilizing the networked computational resources.

JDGC releases the developers from any special programming considerations for distributed environment, and solves the portability problem of using system‐specific programming methods.

The problem of motif discovery has become a significant challenge in the era of big data where there are hundreds of genomes requiring annotations. The importance of motifs has led many researchers to develop different tools and algorithms for finding them. The purpose of this paper is to propose a new algorithm to increase the speed and accuracy of the motif discovering process, which is the main drawback of motif discovery algorithms.

All motifs are sorted in a tree-based indexing structure where each motif is created from a combination of nucleotides: ‘A’, ‘C’, ‘T’ and ‘G’. The full motif can be discovered by extending the search around 4-mer nucleotides in both directions, left and right. Resultant motifs would be identical or degenerated with various lengths.

The developed implementation discovers conserved string motifs in DNA without having prior information about the motifs. Even for a large data set that contains millions of nucleotides and thousands of very long sequences, the entire process is completed in a few seconds.

Experimental results demonstrate the efficiency of the proposed implementation; as for a real-sequence of 1,270,000 nucleotides spread into 2,000 samples, it takes 5.9 s to complete the overall discovering process when the code ran on an Intel Core i7-6700 @ 3.4 GHz machine and 26.7 s when running on an Intel Xeon x5670 @ 2.93 GHz machine. In addition, the authors have improved computational performance by parallelizing the implementation to run on multi-core machines using the OpenMP framework. The speedup achieved by parallelizing the implementation is scalable and proportional to the number of processors with a high efficiency that is close to 100%.

October 10^th, 2010

Offers a broad overview on Japanese prototype service robot R&D trends and examples.

Displays two examples of service robotics: the forestry robot WOODY‐1, and the android presenter and entertainer/informer/guide Repliee Q1.

More and more frequently robotics usage has expanded into more diverse areas that involve work outside the confines of the factory floor. The paper highlights interesting Japanese service robot prototypes, as well as identifies some new R&D trends and requirements.

The potential for new service robotics applications is enormous, ranging from childcare and nursing, to forestry.

The practical implications of the increased diversity of service robotics will reduce human workload and environmental strain.

Reveals examples of innovation in service robot design and application.

China is the world’s largest user market for digital technologies and experiencing unprecedented rates of rural-urban migration set to create the world’s first “urban billion”. This is an important context for studying nuanced adoption behaviours that define a digital divide. Large-scale studies are required to determine what behaviours exist in such populations, but can offer limited ability to draw inferences about why. The purpose of this paper is to report a large-scale study inside China that probes a nuanced “digital divide” behaviour: consumer demographics indicating ability to pay by electronic means but behaviour suggesting lack of willingness to do so, and extends current demographics to help explain this.

The authors report trans-national access to commercial “Big Data” inside China capturing the demographics and consumption of millions of consumers across a wide range of physical and digital market channels. Focusing on one urban location we combine traditional demographics with a new measure that reflecting migration: “Distance from Home”, and use data-mining techniques to develop a model that predicts use behaviour.

Use behaviour is predictable. Most use is explained by value of the transaction. “Distance from Home” is more predictive of technology use than traditional demographics.

Results suggest traditional demographics are insufficient to explain “why” use/non-use occurs and hence an insufficient basis to formulate and target government policy.

The authors understand this to be the first large-scale trans-national study of use/non-use of digital channels within China, and the first study of the impact of distance on ICT adoption.

High resolution simulations of body-internal electric field strengths induced by magneto-quasistatic fields from wireless power transfer systems are computationally expensive. The exposure simulation can be split into two separate simulation steps allowing the calculation of the magnetic flux density distribution, which serves as input into the second simulation step to calculate the body-internal electric fields. In this work, the magnetic flux density is interpolated from in situ measurements in combination with the scalar-potential finite difference scheme to calculate the resulting body-internal field. These calculations are supposed to take less than 5 s to achieve a near real-time visualization of these fields on mobile devices. The purpose of this work is to present an implementation of the simulation on graphics processing units (GPUs), allowing for the calculation of the body-internal field strength in about 3 s.

This work uses the co-simulation scalar-potential finite difference scheme to determine the body-internal electric field strength of human models with a voxel resolution of 2 × 2 × 2 mm³. The scheme is implemented on GPUs. This simulation scheme requires the magnetic flux density distribution as input, determined from radial basis functions.

Using NVIDIA A100 GPUs, the body-internal electric field strength with high-resolution models and 8.9 million degrees of freedom can be determined in about 2.3 s.

This paper describes in detail the used scheme and its implementation to make use of the computational performance of modern GPUs.

The purpose of this paper is to propose efficient algorithms for structural grouping over Extensible Markup Language (XML) data, called TOPOLOGICAL ROLLUP (T‐ROLLUP), which are to compute aggregation functions based on XML data with multiple hierarchical levels. They play important roles in the online analytical processing of XML data, called XML‐OLAP, with which complex analysis over XML can be performed to discover valuable information from XML.

Several variations of algorithms are proposed for efficient T‐ROLLUP computation. First, two basic algorithms, top‐down algorithm (TDA) and bottom‐up algorithm (BUA), are presented in which the well‐known structural‐join algorithms are used. The paper then proposes more efficient algorithms, called single‐scan by preorder number and single‐scan by postorder number (SSC‐Pre/Post), which are also based on structural joins, but have been modified from the basic algorithms so that multiple levels of grouping are computed with a single scan over node lists. In addition, the paper attempts to adopt the algorithm for parallel execution in multi‐core environments.

Several experiments are conducted with XMark and synthetic XML data to show the effectiveness of the proposed algorithms. The experiments show that proposed algorithms perform much better than the naïve implementation. In particular, the proposed SSC‐Pre and SSC‐Post perform better than TDA and BUA for all cases. Beyond that, the experiment using the parallel single scan algorithm also shows better performance than the ordinary basic algorithm.

This paper focuses on the T‐ROLLUP operation for XML data analysis. For this reason, other operations related to XML‐OLAP, such as CUBE, WINDOWING, and RANKING should also be investigated.

The paper presents an extended version of one of the award winning papers at iiWAS2008.