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1.Does organizational mindfulness facilitate enterprise system adaptation and organizational agility?

Author:Lee, Neil Chueh-An ; Liu, Gloria H.W. ; Wang, Cheng-Hui

Source:Proceedings of the 24th Pacific Asia Conference on Information Systems Information Systems (IS) for the Future, PACIS 2020,2020,Vol.

Abstract:Nowadays firms rely on enterprise systems (ES) to enable organizational agility. However, uncertain environments require firms continuously adapt their ES to meet changing business needs. What factor will drive ES adaptation remains an understudied issue. This study holds that firms need to foster organizational mindfulness to facilitate ES adaptation and organizational agility. Substantial literature has examined the effects of various IT-related capabilities on organizational agility. Organizational attributes, such as organizational mindfulness, are rarely studied. We build and test a model based on the perspectives of organizational mindfulness and boundary object. Based on 138 responses of Taiwanese manufacturing firms, our findings demonstrate the importance of organizational mindfulness in achieving higher ES adaptation and thereby organizational agility. Implications of the results for practices and academics are provided. © Proceedings of the 24th Pacific Asia Conference on Information Systems Information Systems (IS) for the Future, PACIS 2020. All rights reserved.

2.Prediction of exchange rates with machine learning

Author:Goncu, Ahmet

Source:ACM International Conference Proceeding Series,2019,Vol.

Abstract:In this study a macroeconomic model is considered to predict the next month’s monthly average exchange rates via machine learning based regression methods including the Ridge, decision tree regression, support vector regression and linear regression. The model incorporates the domestic money supply, real interest rates, Federal Funds rate of the USA, and the last month’s monthly average exchange rate to predict the next month’s exchange rate. Monthly data with 148 observations from the US Dollar and Turkish Lira exchange rates are considered for the empirical testing of the model. Empirical results show that the Ridge regression offers accurate estimation for investors or policy makers with relative errors less than 60 basis points. Policy makers can obtain point estimates and confidence intervals for analyzing the effects of interest rate cuts on the exchange rates. © 2019 Association for Computing Machinery.

3.Recent development of multi-purpose utility tunnels in China

Author:Luo, Y. ; Zhang, C. ; Hammad, A.

Source:Proceedings, Annual Conference - Canadian Society for Civil Engineering,2019,Vol.2019-June

Abstract:Repeated excavations of buried utilities cause road congestion and maintenance conflicts. Besides, the interference of buried utilities in limited underground spaces does not meet the requirement of sustainable urban underground development. Multi-purpose utility tunnels (MUTs) integrate all utilities together in one tunnel and can be accessed by humans. MUTs reduce the excavation needs and costs and avoid the traffic congestion caused by excavations. MUTs also provide easy access for inspection and maintenance of all types of utilities inside the tunnel. There are many MUTs in use in Europe and Japan, but the development of new tunnels in recent years is limited and lacks long-term planning. On the contrary, China is making a big progress in MUT planning and construction in recent years because the Chinese government is taking MUT construction as an important urban infrastructure development. The experience of MUT planning, construction and management in China can be very useful for other countries to examine the potential of MUTs as a sustainable option for future municipal asset rehabilitation projects. This paper first reviews the new development of MUTs including MUT history in China and the total planned and constructed lengths. Furthermore, several projects in major Chinese cities are reviewed including basic data on the length, cross-section, utilities housed, and cost analysis. It is concluded that although the initial cost of MUTs is high, they are sustainable and cost-effective infrastructures for underground utilities in the long term. It is hoped that this paper will encourage further research about the usage of MUTs. � 2019 Canadian Society for Civil Engineering. All rights reserved.

4.Compliance Current Effect on Switching Behavior of Hafnium Oxide based RRAM

Author:Qi, YF;Zhao, C;Fang, YX;Lu, QF;Liu, CG;Yang, L;Zhao, CZ


Abstract:In this study, we compared the basic switching behaviors of HfO2, Al2O3 and HfAlOx (Hf:Al=9:1) based RRAM with Ti top electrode by setting various compliance currents (1mA, 5mA, 10mA, 15mA). The resistance ratio of HfO2 based RRAM (20 -> 320) increases with compliance current whereas it drops not obviously for Al2O3 based RRAM (85 -> 54). HfAlOx (Hf:Al=9:1)) based one has the best resistance ratio (300-440) and resistance stability. All low resistance state (LRS) resistance values of three samples are around 100 Omega with large compliance current while there is a difference in HRS resistance which causes the ratio difference accordingly. The dominant mechanism of resistive switching is the formation and rupture of the conductive filament composed of oxygen vacancies. The appropriate compliance current selection and doping technology to high-k materials should be considered in further study.

5.Advances in Swarm and Computational Intelligence: 6th International Conference, ICSI 2015 held in conjunction with the Second BRICS Congress, CCI 2015 Beijing, China, June 25-28, 2015 Proceedings, Part II


Source:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),2015,Vol.9141

Abstract:[No abstract available]

6.Evolving linear discriminant in a continuously growing dimensional space for incremental attribute learning

Author:Wang,Ting;Guan,Sheng Uei;Ting,T. O.;Man,Ka Lok;Liu,Fei

Source:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),2012,Vol.7513 LNCS

Abstract:Feature Ordering is a unique preprocessing step in Incremental Attribute Learning (IAL), where features are gradually trained one after another. In previous studies, feature ordering derived based upon each individual feature's contribution is time-consuming. This study attempts to develop an efficient feature ordering algorithm by some evolutionary approaches. The feature ordering algorithm presented in this paper is based on a criterion of maximum mean of feature discriminability. Experimental results derived by ITID, a neural IAL algorithm, show that such a feature ordering algorithm has a higher probability to obtain the lowest classification error rate with datasets from UCI Machine Learning Repository. © IFIP International Federation for Information Processing 2012.

7.A Citation-Based Recommender System for Scholarly Paper Recommendation

Author:Haruna, K;Ismail, MA;Bichi, AB;Chang, V;Wibawa, S;Herawan, T


Abstract:Several approaches have been proposed to help researchers in acquiring relevant and useful scholarly papers from the enormous amount of information (information overload) that is available over the internet. The significant challenge for those approaches is their assumption of the availability of the whole contents of each of the candidate recommending papers to be freely accessible, which is not always the case considering the copyright restrictions. Also, they immensely depend on priori user profiles, which required a significant number of registered users for the systems to work effectively, and a stumbling block for the creation of a new recommendation system. This paper proposes a citation-based recommender system based on the latent relations connecting research papers for the scholarly paper recommendation. The novelty of the proposed approach is that unlike the existing works, the latent associations that exist between a scholarly paper and its various citations are utilised. The proposed approach aimed to personalise scholarly recommendations regardless of the user expertise and research fields based on paper-citation relations. Experimental results have shown significant improvement over other baseline methods.

8.Promotion-based input partitioning of neural network

Author:Guo, Shujuan ; Guan, Sheng-Uei ; Li, Weifan ; Zhao, Linfan ; Song, Jinghao ; Cao, Mengying

Source:Lecture Notes in Electrical Engineering,2014,Vol.272 LNEE

Abstract:To improve the learning performance and precision of neural network, this paper introduces an input-attribute partitioning algorithm with an aim to increase the promotion among them. If a better performance could be obtained by training some attributes together, it is considered that there is positive effect among these attributes. It is assumed that by putting attributes, among which there are positive effect, a lower error can be obtained. After partitioning, multiple learners were employed to tackle each group. The final result is obtained by integrating the result of each learner. It turns out that, this algorithm actually can reduce the classification error in supervised learning of neural network. © Springer-Verlag Berlin Heidelberg 2014.


Author:Krilavicius, T;Man, KL


Abstract:The goal of the radiation therapy is to give as much dose as possible to the target volume and avoid giving any dose at all to a normal tissue. Despite the advances of the computer-based control current technology does not allow to compensate respiratory movement. It considerably restricts effectiveness of such treatment the case of lung cancer. In this paper we present a work in progress, a timed model of radiation treatment system developed to analyze a potential set up for a system that compensates respiratory motion. We model the system with Uppaal, a tool for modeling, validation and verification of real-time systems modeled as networks of timed automata, extended with data types (bounded integers, arrays, etc.). The model is used to validate understanding of the model and selected scenarios.

10.Enhanced LSTM with Batch Normalization

Author:Wang, LN;Zhong, GQ;Yan, SJ;Dong, JY;Huang, KZ


Abstract:Recurrent neural networks (RNNs) are powerful models for sequence learning. However, the training of RNNs is complicated because the internal covariate shift problem, where the input distribution at each iteration changes during the training as the parameters have been updated. Although some work has applied batch normalization (BN) to alleviate this problem in long short-term memory (LSTM), unfortunately, BN has not been applied to the update of the LSTM cell. In this paper, to tackle the internal covariate shift problem of LSTM, we introduce a method to successfully integrate BN into the update of the LSTM cell. Experimental results on two benchmark data sets, i.e. MNIST and Fashion-MNIST, show that the proposed method, enhanced LSTM with BN (eLSTM-BN), has achieved a faster convergence than LSTM and its variants, while obtained higher classification accuracy on sequence learning tasks.

11.Planetary systems in star clusters

Author:Kouwenhoven, M.B.N. ; Shu, Qi ; Cai, Maxwell Xu ; Spurzem, Rainer

Source:Memorie della Societa Astronomica Italiana - Journal of the Italian Astronomical Society,2016,Vol.87

Abstract:Thousands of confirmed and candidate exoplanets have been identified in recent years. Consequently, theoretical research on the formation and dynamical evolution of planetary systems has seen a boost, and the processes of planet-planet scattering, secular evolution, and interaction between planets and gas/debris disks have been well-studied. Almost all of this work has focused on the formation and evolution of isolated planetary systems, and neglect the effect of external influences, such as the gravitational interaction with neighbouring stars. Most stars, however, form in clustered environments that either quickly disperse, or evolve into open clusters. Under these conditions, young planetary systems experience frequent close encounters with other stars, at least during the first 106-107years, which affects planets orbiting at any period range, as well as their debris structures. © 2016 SAIt.

12.Study Frequency Characteristics of Ground By Using Four Electrode Method

Author:Nayel, M


Abstract:This paper studies the effect of frequencies and penetration depth on ground impedance, resisitivity and permittivity. The effect of injected a step like current in the four electrode method for ground resistivity and permittivity measurements are investigated. The ground impedance is obtained from measured voltage and current wave forms. A balance transformer is used to inject a step current in outer electrode and sink the same current from the other outer electrode. Calculation models had been proposed to explain physically the effects of frequency and penetration depth on four electrodes method measurements.

13.RF characteristics of wireless capsule endoscopy in human body

Author:Zhang,Meng;Lim,Eng Gee;Wang,Zhao;Tillo,Tammam;Man,Ka Lok;Wang,Jing Chen

Source:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),2013,Vol.7861 LNCS

Abstract:Wireless capsule endoscopy (WCE) is an ingestible electronic diagnostic device capable of working wirelessly, without all the limitations of traditional wired diagnosing tools, such as cable discomfort and the inability to examine highly convoluted sections of the small intestine. However, this technique is still encountering a lot of practical challenges and requires further improvements. This paper is to propose the methodology of investigating the performance of a WCE system by studying its electromagnetic (EM) wave propagation through the human body. Based on this investigation, the capsule's positioning information can be obtained. The WCE transmission channel model is constructed to evaluate signal attenuations and to determine capsule position. The detail of this proposed research methodology is presented in this paper. © 2013 Springer-Verlag.

14.Big visual data analysis for built environment information modeling

Author:Zhang, C. ; Guo, F. ; Fan, L. ; Ali, Y.

Source:Proceedings, Annual Conference - Canadian Society for Civil Engineering,2019,Vol.2019-June

Abstract:Due to the availability of large amount visual data collected, big data analysis can be used to solve engineering problems. Meanwhile, information technology is also playing an essential role in enhancing multidisciplinary solutions for more complicated problems. This paper proposes a framework of applying big visual data (BVD) into Built Environment Information Modeling (BEIM). Four tiers have been defined to provide a guideline for data collection, modelling, application and optimization. Some preliminary research work carried out by the research team is presented in the paper as well, to show the feasibility and applicability of the proposed method. � 2019 Canadian Society for Civil Engineering. All rights reserved.


Author:Dounas, T;Spaeth, AB


Abstract:The paper presents the geometrical investigation of a three-dimensional dovetail joint that can lead (timber) frame construction to more than two-dimensional frames; the creation of timber construction with timber members meeting at irregular angles can be shown to be feasible, simplifying overall construction. Traditional joints in timber construction usually work only in two dimensions, in other words in planar surfaces, resulting thus in complicated assemblies in three-dimensions. Stemming from traditional timber dovetail joints, the universal joint under investigation is produced under revolution of the geometry of a dovetail fastener through its middle axis. The resulting concave disk can connect timber elements under irregular angles, without the need for the structural members to lie in the same plane. The joint works due to friction between members rather than using any other element of bonding, allowing for the assembly of joints and structural members with no specialized tools. The paper explores the geometric constraints and degrees of freedom that such a disk creates in timber construction, and consequently in similar linear construction systems.


Author:Tate, D;Hu, XY;Li, MY;Wang, RT


Abstract:This paper presents the results of teaching robust design techniques to industrial design students in the Chinese context. Year 3 students in a Bachelor of Engineering programme at Xi'an Jiaotong-Liverpool University in Suzhou, China studied robust design techniques over a one-semester course. As part of the course, the students worked in two groups to apply robust design techniques to traditional Chinese musical instruments: the jinghu and the erhu. The two groups took divergent approaches to the project. One group sought to follow traditional manufacturing processes (craftinaking) for the instruments, and the other applied typical simple prototyping techniques used within industrial design. Through selection of control factors, creation of orthogonal arrays, prototyping, and experimentation, the students were able to characterize the main effects of four control factors on the sound quality of the instruments, loudness or harmonics, and to explore the feasibility of robust design for instrument design.

17.Cyber Physical Computing

Author:Hahanov, V;Hussein, MAA;Hahanova, A;Man, KL


Abstract:Cyber culture of virtual-macro-micro-computing, which formulates, explains and predicts the current processes and phenomena monitoring and control technology in the physical and virtual space is proposed. The verbal and structural definitions of the main types of computing, based on current trends evolution of planet cyber ecosystem are represented. The universal model of MAT-computing: , which leverages three components to create a computational structure in technologically acceptable matter environment is proposed. The info-quantum direction of human expansion into space and the possibility of a similar penetration unearthly biotech objects in the ecosystem of our planet is shown. Computing model, which defines the structure of quasi-optimal digital monitoring and cloud control of scalable technical, biological, social and virtual processes is proposed.

18.Analytics on fireworks algorithm solving problems with shifts in the decision space and objective space

Author:Cheng, Shi ; Chen, Junfeng ; Qin, Quande ; Shi, Yuhui ; Zhang, Qingyu

Source:Nature-Inspired Computing Concepts, Methodologies, Tools, and Applications,2016,Vol.2-3

Abstract:Fireworks algorithms for solving problems with the optima shift in decision space and/or objective space are analyzed in this paper. The standard benchmark problems have several weaknesses in the research of swarm intelligence algorithms for solving single objective problems. The optimum is in the center of search range, and is the same at each dimension of the search space. The optimum shift in decision space and/or objective space could increase the difficulty of problem solving. A mapping strategy, modular arithmetic mapping, is utilized in the original fireworks algorithm to handle solutions out of search range. The solutions are implicitly guided to the center of search range for problems with symmetrical search range via this strategy. The optimization performance of fireworks algorithm on shift functions may be affected by this strategy. Four kinds of mapping strategies, which include mapping by modular arithmetic, mapping to the boundary, mapping to stochastic region, and mapping to limited stochastic region, are compared on problems with different dimensions and different optimum shift range. From experimental results, the fireworks algorithms with mapping to the boundary, or mapping to limited stochastic region obtain good performance on problems with the optimum shift. This is probably because the search tendency is kept in these two strategies. The definition of population diversity measurement is also proposed in this paper, from observation on population diversity changes, the useful information of fireworks algorithm solving different kinds of problems could be obtained. © 2017 by IGI Global. All rights reserved.

19.Flexural test of Tee steel PEC beam

Author:Zhao, BC;Chen, XD;Liu, S;Xia, J


Abstract:To investigate vertical load-bearing capacity of Tee steel PEC beams, test results of two simply supported Tee steel PEC beams under vertical loads are presented. The procedure and method of test was introduced. The carrying capacity and failure mechanism, deformation capacity, mid-span sectional strain distributions were analyzed. The result indicates that the Tee steel PEC beam has good carrying capacity and deformation ability under vertical loads. Tee steel PEC beam specimens with full shear connection exhibit cross sectional strains that meets the flat section assumption. To avoid brittle failure of Tee steel PEC beams, the composite beam should have a larger steel ratio. It is rational that the plastic neutral axis is located in the flange of the concrete plate. Specimens with higher steel ratios have a higher bending strength and stiffness.

20.Edge Orientation Driven Depth Super-Resolution for View Synthesis

Author:Yao, C;Xiao, JM;Jin, J;Ban, XJ

Source:IMAGE AND GRAPHICS, ICIG 2019, PT III,2019,Vol.11903

Abstract:The limited resolution of depth images is a constraint for most of practical computer vision applications. To solve this problem, in this paper, we present a novel depth super-resolution method based on machine learning. The proposed super-resolution method incorporates an edge-orientation based depth patch clustering method, which classifies the patches into several categories based on gradient strength and directions. A linear mapping between the low resolution (LR) and high resolution (HR) patch pairs is learned for each patch category by minimizing the synthesis view distortion. Since depth maps are not viewed directly, they are used to generate the virtual views, our method takes synthesis view distortion as the optimization strategy. Experimental results show that our proposed depth super-resolution approach performs well on depth super-resolution performance and the view synthesis compared to other depth super-resolution approaches.
Total 52 results found
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