An improved cuckoo search algorithm and its application in vibration fault diagnosis for a hydroelectric generating unit

This article presents an improved cuckoo search (ICS) algorithm based on the parametric adaptation mechanism and non-uniform mutation. In the ICS algorithm, the biased random walk operator is modified to take advantage of the neighbourhood information of the current solution, and then the control parameters of step size, discovery probability and scaling factor are directly integrated into the optimized problems. Meanwhile, the non-uniform mutation operation is used to adaptively tune the search step of the current optimal solution. To evaluate the feasibility and efficiency of the presented algorithm, three groups of benchmark test functions are employed to perform the validation analysis. Subsequently, to diagnose the vibration fault of a hydroelectric generating unit, a combinational model is built, which combines ICS with a back-propagation neural network (ICSBP). The experimental results indicate that ICS is competitive on the optimization problems, and the ICSBP approach can effectively improve the accuracy of vibration fault diagnosis for a hydroelectric generating unit.     

Temporal information based GoP adaptation for linear video delivery schemes

An original wireless video transmission scheme called SoftCast has been recently proposed to deal with the issues encountered in conventional wireless video broadcasting systems (e.g. cliff effect). In this paper, we evaluate and optimize the performance of the SoftCast scheme according to the transmitted video content. Precisely, an adaptive coding mechanism based on GoP-size adaptation, which takes into account the temporal information fluctuations of the video, is proposed. This extension denoted Adaptive GoP-size mechanism based on Content and Cut detection for SoftCast (AGCC-SoftCast) significantly improves the performance of the SoftCast scheme. It consists in modifying the GoP-size according to the shot changes and the spatio-temporal characteristics of the transmitted video. When hardware capacities, such as buffer or processor performance are limited, an alternative method based only on the shot changes detection (AGCut-SoftCast) is also proposed. Improvements up to 16 dB for the PSNR and up to 0.55 for the SSIM are observed with the proposed solutions at the cut boundaries. In addition, temporal visual quality fluctuations are reduced under 1dB in average, showing the effectiveness of the proposed methods.     

Defect Engineering in Ambipolar Layered Materials for Mode-Regulable Nociceptor

Defect engineering represents a significant approach for atomically thick 2D semiconductor material development to explore the unique material properties and functions. Doping-induced conversion of conductive polarity is particularly beneficial for optimizing the integration of layered electronics. Here, controllable doping behavior in palladium diselenide (PdSe₂) transistor is demonstrated by manipulating its adatom-vacancy groups. The underlying mechanisms, which originate from reversible adsorption/desorption of oxygen clusters near selenide vacancy defects, are investigated systematically via their dynamic charge transfer characteristics and scanning tunneling microscope analysis. The modulated doping effect allows the PdSe₂ transistor to emulate the essential characteristics of photo nociceptor on a device level, including firing signal threshold and sensitization. Interestingly, electrostatic gating, acting as a neuromodulator, can regulate the adaptive modes in nociceptor to improve its adaptability and perceptibility to handle different danger levels. An integrated artificial nociceptor array is also designed to execute unique image processing functions, which suggests a new perspective for extension of the promise of defect engineered 2D electronics in simplified sensory systems toward use in advanced humanoid robots and artificial visual sensors.     

跨领域文本情感分类研究进展

作为社会媒体文本情感分析的重要研究课题之一，跨领域文本情感分类旨在利用源领域资源或模型迁移地服务于目标领域的文本情感分类任务，其可以有效缓解目标领域中带标签数据不足问题.本文从三个角度对跨领域文本情感分类方法行了归纳总结：（1）按照目标领域中是否有带标签数据，可分为直推式和归纳式情感迁移方法；（2）按照不同情感适应性策略，可分为实例迁移方法、特征迁移方法、模型迁移方法、基于词典的方法、联合情感主题方法以及图模型方法等；（3）按照可用源领域个数，可分为单源和多源跨领域文本情感分类方法.此外，论文还介绍了深度迁移学习方法及其在跨领域文本情感分类的最新应用成果.最后，论文围绕跨领域文本情感分类面临的关键技术问题，对可能的突破方向进行了展望.     

Some concerns regarding the CAT16 chromatic adaptation transform

In recent literature, a new chromatic adaptation transform, CAT16, has been published to improve upon the widely used CAT02 model. The CAT16 model is based on the form of the CAT02 transform adopted in CIECAM02, but uses a slightly different sensor space to fix some gamut problems plaguing CIECAM02 and adopts a two-step CAT to ensure symmetry and transitivity. CAT16 is included in CAM16 but is also being promoted as a stand-alone CAT, one that can be used outside of the CAM16 model. However, the use of CAT16 as a stand-alone model can cause inconsistencies in the calculated corresponding colors due to the presence of the relative luminance of the adapting white (Y_w) in the von Kries-Ives gain control factors. Such inconsistencies are not present for the stand-alone version of the CAT02 model, which, unlike the version adopted in CIECAM02, does not include the Y_w factors. CAT16 should therefore be modified by omitting the Y_w factors. In this article, we will briefly discuss these issues in more detail and provide a consistent two-step CAT adopting the CAT16 sensor space.     

Semantics for consistent activation in context-oriented systems

ContextContext-oriented programming languages provide dedicated programming abstractions to define behavioral adaptations and means to combine those adaptations dynamically according to sensed context changes. Some of these languages feature programming abstractions to explicitly define interaction dependencies among contexts. However, the semantics of context activation and the meaning of dependency relations have been described only informally, which in some cases has led to incorrect specifications, faulty implementations and inconsistent system behavior.ObjectiveWith the aim of avoiding faulty implementations and inconsistencies during system execution, this paper proposes both a formal and run-time model of contexts, context activation and context interaction.MethodAs a formal and computational basis, we introduce context Petri nets, a model based on Petri nets, which we found to match closely the structure of contexts in context-oriented systems. The operational semantics of Petri nets permits the modeling of run-time context activations. Existing Petri net analyses allow us to reason about system properties. As validation, we carried out small and medium-sized case studies.ResultsIn the cases explored, context Petri nets served effectively as underlying run-time model to ensure that declared context interaction constraints remain consistent during context manipulation. Moreover, context Petri nets enabled us to analyze certain properties regarding the activation state of particular contexts.ConclusionContext Petri nets thus proved to be appropriate to encode and manage the semantics of context activation, both formally and computationally, so as to preserve the consistency of context-oriented systems.     

Toward the adaptation of component‐based architectures by model transformation: behind smart user interfaces

Graphical user interfaces are not always developed for remaining static. There are GUIs with the need of implementing some variability mechanisms. Component‐based GUIs are an ideal target for incorporating this kind of operations, because they can adapt their functionality at run‐time when their structure is updated by adding or removing components or by modifying the relationships between them. Mashup user interfaces are a good example of this type of GUI, and they allow to combine services through the assembly of graphical components. We intend to adapt component‐based user interfaces for obtaining smart user interfaces. With this goal, our proposal attempts to adapt abstract component‐based architectures by using model transformation. Our aim is to generate at run‐time a dynamic model transformation, because the rules describing their behavior are not pre‐set but are selected from a repository depending on the context. The proposal describes an adaptation schema based on model transformation providing a solution to this dynamic transformation. Context information is processed to select at run‐time a rule subset from a repository. Selected rules are used to generate, through a higher‐order transformation, the dynamic model transformation. This approach has been tested through a case study which applies different repositories to the same architecture and context. Moreover, a web tool has been developed for validation and demonstration of its applicability. The novelty of our proposal arises from the adaptation schema that creates a non pre‐set transformation, which enables the dynamic adaptation of component‐based architectures. Copyright © 2014 Copyright © 2014 John Wiley & Sons, Ltd.