An improved LDA approach

Linear discrimination analysis (LDA) technique is an important and well-developed area of image recognition and to date many linear discrimination methods have been put forward. Despite these efforts, there persist in LDA at least three areas of weakness. The first weakness is that not all the discrimination vectors that are obtained are useful in pattern classification. Second, it remains computationally expensive to make the discrimination vectors completely satisfy statistical uncorrelation. The third weakness is that it is necessary to select the appropriate principal components. In this paper, we propose to improve discrimination technique in these three areas and to that end present an improved LDA (ILDA) approach which synthesizes these improvements. Experimental results on different image databases demonstrate that our improvements on LDA are efficient, and that ILDA outperforms other state-of-the-art linear discrimination methods.     

An improved multilevel optimization approach

An improved multilevel optimization approach is proposed. It is also used in the multilevel optimization of frames with beams including buckling constraints. Two types of the improved multilevel approach are treated at the component level. Hybrid approximation technique is adapted at two levels, however the method of moving asymptotes is used at the component level. A new relationship between system variables (A_i) and component variables (t_j) is derived. Four numerical examples show that the improved multilevel approach has generalized applicability and availability.     

An improved visualization-based approach for project portfolio selection

We propose a 2-step interactive approach for solving a project portfolio selection problem as a single-criterium optimization problem. Our approach innovates by using two coordinated charts: an interactive project timeline with drag-and-drop functionalities for project reallocation in time; and an interactive cost and risk chart that combines line charts and bar charts in order to present multidimensional time-based datasets. We also use bar charts related to the allocation of man-hour resources. These functionalities enable users to refine the model that is fed into optimization software in order to achieve results that better correspond to their expectations. We discuss results of a heuristic-based usability evaluation of our prototype, its use in real scenarios, and present preliminary positive feedback from users.     

An improved sample projection approach for image watermarking

Very recently, a novel watermarking scheme named sample projection approach (SPA) has been proposed by Akhaee et al. [1] to improve the watermarking performance against gain attacks. The SPA embeds one message symbol into four signal samples by projecting the line segment formed by the four samples on a certain specific codeline. Based on the SPA, this paper presents an improved sample projection approach (ISPA) by introducing a set of modified codelines to decrease embedding distortion and constructing the long line segments to increase robustness. According to our theoretical analysis of document-to-watermark ratio (DWR), the modified codelines result in a lower embedding distortion than the SPAʼs codelines in the same conditions with regard to payload and robustness. We also derive a theoretical expression for the symbol error rate (SER) of the ISPA against additive white Gaussian noise (AWGN) attack. The numerous experiments conducted on both artificial Gaussian signals and the natural images show that the proposed ISPA outperforms the SPA in terms of robustness against attacks.     

An improved data hiding approach for polygon meshes

We present an improved technique for data hiding in polygonal meshes, which is based on the work of Bogomjakov et al. (Comput. Graph. Forum 27(2):637–642, 2008). Like their method, we use an arrangement on primitives relative to a reference ordering to embed a message. But instead of directly interpreting the index of a primitive in the reference ordering as the encoded/decoded bits, our method slightly modifies the mapping so that our modification doubles the chance of encoding an additional bit compared to Bogomjakov et al.’s (Comput. Graph. Forum 27(2):637–642, 2008). We illustrate the inefficiency in the original mapping of Bogomjakov et al. (Comput. Graph. Forum 27(2):637–642, 2008) with an intuitive representation using a binary tree.     

An improved bias-compensation approach for errors-in-variables model identification

Parametric estimation of the dynamic errors-in-variables models is considered in this paper. In particular, a bias compensation approach is examined in a generalized framework. Sufficient conditions for uniqueness of the identified model are presented. Subsequently, a statistical accuracy analysis of the estimation algorithm is carried out. The asymptotic covariance matrix of the system parameter estimates depends on a user chosen filter and a certain weighting matrix. It is shown how these can be tuned to boost the estimation performance. The numerical simulation results suggest that the covariance matrix of the estimated parameter vector is very close to the Cramér-Rao lower bound for the estimation problem.     

多文档文本摘要的一种改进HITS算法

提出了一种对HITS算法进行改进的新方法，本方法将文档内容与一些启发信息如“短语”，“句子长度”和“首句优先”等结合，用于发现多文档子主题，并且将文档子主题特征转换成图节点进行排序。通过对DUC2004数据的实验，结果显示本方法是一种有效的多文本摘要方法。     

An approach for enhancing fingerprint images using adaptive Gabor filter parameters

This work proposes a technique to enhance fingerprint images through the Gabor filter with adaptive parameters. Firstly, the average ridge and valley of each region as well as their direction are evaluated by a specific directional field algorithm. Secondly, since the filter orientation and the frequency parameters vary according to the fingerprint area, the fingerprint topological structure is enhanced by the Gabor filter with adaptive parameters. Finally, experimental tests show accurate final results for the matching step of an on-line recognition process. The text was submitted by the authors in English. Sanderson L. Gonzaga de Oliveira graduated from the Pontificia Universidade Catolica do Parana in 1996 and received his M.Sc. degree in 2004. Currently, he is a doctoral candidate in the Universidade Federal Fluminense, Brazil. His research interests include Image Processing and Computer Modeling. Author of 15 papers. A. Conci is a Dr.Sc. professor in the Department of Computer Science in Universidade Federal Fluminense. Her research interests include Biomechanics, Applications of Computer Vision, and Image Processing. F. M. Viola received his B.Sc. in Computer Science in 1999 and his M.Sc. at Universidade Federal Fluminense in 2006. His research interests include Biometrics and Image Processing.     

An improved parameter identification approach for piecewise affine model

This study proposes a high-efficient approach to identify the piecewise affine (PWA) model. The proposed approach constitutes two major steps, initial estimation and refinement process. In the initial estimation, Hough Transform (HT) is adopted to generate a group of submodel candidates; then a variable-threshold technique is applied to pick up the real submodel. In the refinement process, not only the distance constraint between data points and submodel's hyperplanes but also the clustering constraint between data points in regression regions are considered. An efficient algorithm is presented to alternately refine the submodel's parameters and the subregression sets. In the case study, the proposed approach is used to identify the fault model of the track circuit in high-speed railway. Analysis shows that the proposed approach has linear time complexity and exhibits superior data availability in small-sample case.     

An improved grey group decision-making approach

In complex group decision-making, decision makers and decision attributes are the core of the relevant activities. Targeting the problem of scheme ranking and behavioural characteristics that exist in group decision-making, from the perspective of group negotiation and decision-making system coordination, by exploiting the grey target and grey relation analysis, this paper establishes a novel grey group decision-making approach. We define a group measure matrix of scheme, consensus ideal scheme, and decision-making resource coefficient. Then, by borrowing Nash’s bargaining idea, and maximizing group negotiation satisfaction and minimizing system coordination deviation, we construct a two-step optimization model to solve for the group consensus ideal scheme and its measure value matrix. In addition, we take decision-making schemes as research objects; and from the two dimensions of decision maker and attribute, we characterize and measure the closeness degree of decision maker information and attribute information by using the distance between the group measure matrices of scheme and consensus ideal scheme, so that we are able to construct a novel grey scheme matrix similar incidence analysis model. Lastly, we take the group decision-making problem of selecting the location of a garbage disposal station as a case analysis, and explore the economic significance and theoretical value of the model.     

An improved distributed concolic testing approach

Distributed concolic testing (DCT) for complex programs takes a remarkable computational time. Also, the achieved modified condition/decision coverage (MC/DC) for such programs is often inadequate. We propose an improved DCT approach that reduces the computational time and simultaneously enhanced the MC/DC. We have named our approach SMCDCT (scalable MC/DC percentage calculator using DCT). Our experimental study on forty‐five C programs indicates 6.62% of average increase in MC/DC coverage. Copyright © 2016 John Wiley & Sons, Ltd.     

An improved approach for constrained robust model predictive control

In this paper, we present a new technique to address constrained robust model predictive control. The main advantage of this new approach with respect to other well-known techniques is the reduced conservativeness. Specifically, the technique described in this paper can be applied to polytopic uncertain systems and is based on the use of several Lyapunov functions each one corresponding to a different vertex of the uncertainty's polytope.     

Emotion-regulatory chatbots for enhancing consumer servicing: An interpersonal emotion management approach

To reduce service staff's burden in customer servicing and improve the performance of automatic service recovery, we propose an emotion-regulatory chatbot for service recovery applications drawing on interpersonal emotion management (IEM) theory. In addition, we develop a model to examine the underlying mechanisms through which perceived IEM strategies influence consumers’ emotions and behavioral intentions. Our experimental results verify the effectiveness of IEM strategies. We find that appraisals and consumers’ post-recovery emotions sequentially mediate the relationship between perceived emotion regulatory strategies and positive word-of-mouth (PWOM).     

An approach to feature‐based software construction for enhancing maintainability

While the way we build software affects significantly its maintenance in terms of the effort and cost, the experience level of the maintainer in a software acquirers' organization is also one of concern. In this context, often the maintainer is the user of the system. Unfortunately, it is quite possible to lose the trustworthiness of the software due to the inexperience of the maintainer, especially when the maintainer is without the help of the original developers. One remedy for providing security against the effects of the maintainer's software modifications is to restrict the access to software parts (modules) relative to the experience level of the maintainers. For such a remedy to be successful, the software should be constructed in such a way that its parts under maintenance affect others as little as possible. We propose an approach to software construction aligning the dependencies among software parts in one direction so that they are allocated to maintainers based on their experience level. Our approach decomposes the software into parts based on functionality and orders the parts by essentiality, which indicates how difficult it is to change each part. Then, we align the dependencies in such a way that the less essential functionality is dependent on the more essential functionality. Consequently, any modification on less essential functionality does not affect the essential functionalities. To demonstrate the feasibility of our proposed approach, we applied it to a military application and found that the constructed software enables us to confine maintainers' activity within a limited working area, and thus the software is safer against maintainers' modification. Copyright © 2006 John Wiley & Sons, Ltd.     

An impulse-time perturbation approach for enhancing the robustness of extra-insensitive input shapers

In this paper, perturbation-based extra-insensitive input shapers (PEI-ISs) are proposed to enhance the robustness of the input shaping technique. The extra-insensitive input shaper (EI-IS) has been known to be more robust than the so-called derivative input shapers such as ZVD, ZVDD, and ZVDDD shapers. However, the robustness of the known EI-IS is restricted by the symmetric property in the sensitivity curve. To address this, the PEI-IS is devised by multiplying a series of input shapers in the Laplace domain, of which the impulse times are slightly perturbed from those of the zero vibration (ZV) shaper. For a single-hump case, a closed-form solution to the PEI-IS is provided. For two- and three-hump cases, the approximate solutions are presented. The robustness is evaluated by simulations and assessed by means of the insensitivity. It will be shown that the proposed PEI-IS does improve the robustness and that it can be easily designed.     

一种增强复杂网络抵御相继故障能力的路由算法研究

在现实生活中,许多大型的通信网络或电力网络都可以应用复杂网络进行刻画。然而网络中某些关键节点一旦遭到攻击极易引发相继故障。这种现象的存在极大降低了网络的可靠性。为了提高网络对相继故障的抵御能力,针对现有基于最短路径的路由算法加以改进,降低关键节点在网络中所起的作用,提高了网络负载在各节点间分布的均衡性。通过在典型的复杂网络上进行的仿真实验,证明了改进的路由算法能够大大增强网络对相继故障的抵御能力。     

An improved MIP-based approach for a multi-skill workforce scheduling problem

This paper deals with scheduling complex tasks with an inhomogeneous set of resources. The problem is to assign technicians to tasks with multi-level skill requirements. Here, the requirements are merely the presence of a set of technicians that possess the necessary capabilities. An additional complication is that a set of combined technicians stays together for the duration of a work day. This typically applies to scheduling of maintenance and installation operations. We build schedules by repeated application of a flexible matching model that selects tasks to be processed and forms groups of technicians assigned to combinations of tasks. The underlying mixed integer programming (MIP) model is capable of revising technician-task allocations and performs very well, especially in the case of rare skills.     

An architectural approach to improved program maintainability

A programming standard is described, with the emphasis on the visual aspects of the final product rather than on how the programs are engineered.     

一种改进的基于鲁棒估计的动态数据校正方法

针对目前动态数据校正方法存在的缺陷,本文基于鲁棒估计的原理,提出一种新型的鲁棒估计函数,该函数物理概念清晰,参数调节灵活。基于此函数构造的动态数据校正方法(IRDR),在校正随机误差的同时,可以同步对异常点过失误差进行侦破和识别。CSTR仿真实例表明,该方法可以准确识别出系统所含的多个过失误差,校正结果偏差小,曲线平滑,具有较强优越性。