On tasks synchronization with the MMS protocol

The MMS protocol is a powerful tool for communication as well as for synchronization between manufacturing equipment such as robots, programmable logic controllers, etc. This paper shows how the MMS services can be used to handle tasks synchronization in a distributed environment. The MMS weaknesses regarding temporal aspects and possible directions to alleviate these weaknesses are also presented.     

Img2Logo: Generating Golden Ratio Logos from Images

Logos are one of the most important graphic design forms that use an abstracted shape to clearly represent the spirit of a community. Among various styles of abstraction, a particular golden-ratio design is frequently employed by designers to create a concise and regular logo. In this context, designers utilize a set of circular arcs with golden ratios (i.e., all arcs are taken from circles whose radii form a geometric series based on the golden ratio) as the design elements to manually approximate a target shape. This error-prone process requires a large amount of time and effort, posing a significant challenge for design space exploration. In this work, we present a novel computational framework that can automatically generate golden ratio logo abstractions from an input image. Our framework is based on a set of carefully identified design principles and a constrained optimization formulation respecting these principles. We also propose a progressive approach that can efficiently solve the optimization problem, resulting in a sequence of abstractions that approximate the input at decreasing levels of detail. We evaluate our work by testing on images with different formats including real photos, clip arts, and line drawings. We also extensively validate the key components and compare our results with manual results by designers to demonstrate the effectiveness of our framework. Moreover, our framework can largely benefit design space exploration via easy specification of design parameters such as abstraction levels, golden circle sizes, etc.     

Inducing imperfections in germanium nanowires

Nanowires with inhomogeneous heterostructures such as polytypes and periodic twin boundaries are interesting due to their potential use as components for optical,electrical,and thermophysical applications.Additionally,the incorporation of metal impurities in semiconductor nanowires could substantially alter their electronic and optical properties.In this highlight article,we review our recent progress and understanding in the deliberate induction of imperfections,in terms of both twin boundaries and additional impurities in germanium nanowires for new/enhanced functionalities.The role of catalysts and catalyst-nanowire interfaces for the growth of engineered nanowires via a three-phase paradigm is explored.Three-phase bottom-up growth is a feasible way to incorporate and engineer imperfections such as crystal defects and impurities in semiconductor nanowires via catalyst and/or interfacial manipulation."Epitaxial defect transfer"process and catalyst-nanowire interfacial engineering are employed to induce twin defects parallel and perpendicular to the nanowire growth axis.By inducing and manipulating twin boundaries in the metal catalysts,twin formation and density are controlled in Ge nanowires.The formation of Ge polytypes is also observed in nanowires for the growth of highly dense lateral twin boundaries.Additionally,metal impurity in the form of Sn is injected and engineered via third-party metal catalysts resulting in above-equilibrium incorporation of Sn adatoms in Ge nanowires.Sn impurities are precipitated into Ge bi-layers during Ge nanowire growth,where the impurity Sn atoms become trapped with the deposition of successive layers,thus giving an extraordinary Sn content (＞6 at.％) in Ge nanowires.A larger amount of Sn impingement (＞9 at.％) is further encouraged by utilizing the eutectic solubility of Sn in Ge along with impurity trapping.     

Managing sequential ambidexterity in the electronics industry: roles of temporal switching capability and contingent factors

Researchers on organisational ambidexterity have proposed several solutions to address the potential conflicts between exploration activities and exploitation activities. Unlike simultaneous ambidexterity, sequential ambidexterity – defined as temporal switching between exploration and exploitation – has not been examined fully, and the conditions under which this temporal switching can be successful are unclear. This paper proposes the concept of temporal switching capability to better understand the process by which sequential ambidexterity is executed. In addition, we hypothesise that performance effects are contingent upon firm-specific factors: a firm’s business strategy and absorptive capacity. Utilising three sources of data – a secondary database, annual reports and a survey administered to 145 firms in the electronics industry with 10-year observations – we find support for our hypotheses. The results show that the temporal switching capability positively relates to new product performance and that business strategy type and absorptive capacity have moderating effects. The results are meaningful in both theory and practice.     

A multi-streaming SIMD multimedia computing engine

Current multimedia extensions provide a mechanism for general-purpose processors to meet the growing performance demand of multimedia applications. However, the computing performance of these extensions is often limited for the design conceptions of the single data stream. This paper presents an architecture called “multi-streaming SIMD” that enables current multimedia extensions to simultaneously manipulate multiple data streams. To efficiently and flexibly realize the proposed architecture, an operation cell is designed by fusing the logic gates and the storage cells together. Multiple operation cells then are connected to compose a register file with the ability of performing SIMD operations called “Multimedia Operation Storage Unit (MOSU)”. Further, many MOSUs are used to compose a multi-streaming SIMD computing engine that can simultaneously manipulate multiple data streams and exploit the subword parallelisms of the elements in each data stream. This paper also designs three instruction modes (global, coupling, and isolated modes) for programmers to dynamically configure the multi-streaming SIMD computing engine at the instruction level to manipulate different amounts of data streams. Simulation results show that when the multi-streaming SIMD architecture has four 4-register MOSUs, it provides a factor of 3.3×–5.5× performance enhancement for traditional MMX extensions on 12 multimedia kernels.     

Robust planning in optimization for production system subject to random machine breakdown and failure in rework

This study is concerned with robust planning in optimization, specifically in determining the optimal run time for production system that is subject to random breakdowns under abort/resume (AR) control policy and failure in rework. In most real-life production processes, generation of defective items and breakdowns of manufacturing equipment are inevitable. In this study, random defective rate is assumed and all manufactured items are screened. The perfect quality, reworkable and scrap items are identified and separated; failure-in-rework is assumed. The system is also subject to random machine breakdown; and when it occurs, the AR policy is adopted. Under such policy, the production of the interrupted lot will be immediately resumed when the machine is restored. Mathematical modeling and derivation of the production-inventory cost functions for both systems with/without breakdowns are presented. The renewal reward theorem is used to cope with the variable cycle length when integrating cost functions. The long-run average cost per unit time is obtained. Theorems on convexity and on bounds of production run time are proposed and proved. A recursive searching algorithm is developed for locating the optimal run time that minimizes the expected production-inventory costs. A numerical example with sensitivity analysis is provided to give insight into the optimal operational control of such an unreliable system.     

On oligopoly spectrum allocation game in cognitive radio networks with capacity constraints

Dynamic spectrum sharing is a promising technology to improve spectrum utilization in future wireless networks. The flexible spectrum management provides new opportunities for licensed primary user and unlicensed secondary users to reallocate the spectrum resource efficiently. In this paper, we present an oligopoly pricing framework for dynamic spectrum allocation in which the primary users sell excessive spectrum to the secondary users for monetary return. We present two approaches, the strict constraints (type-I) and the QoS penalty (type-II), to model the realistic situation that the primary users have limited capacities. In the oligopoly model with strict constraints, we propose a low-complexity searching method to obtain the Nash Equilibrium and prove its uniqueness. When reduced to a duopoly game, we analytically show the interesting gaps in the leader–follower pricing strategy. In the QoS penalty based oligopoly model, a novel variable transformation method is developed to derive the unique Nash Equilibrium. When the market information is limited, we provide three myopically optimal algorithms “StrictBEST”, “StrictBR” and “QoSBEST” that enable price adjustment for duopoly primary users based on the Best Response Function (BRF) and the bounded rationality (BR) principles. Numerical results validate the effectiveness of our analysis and demonstrate the convergence of “StrictBEST” as well as “QoSBEST” to the Nash Equilibrium. For the “StrictBR” algorithm, we reveal the chaotic behaviors of dynamic price adaptation in response to the learning rates.     

Design of a performance-oriented workplace e-learning system using ontology

E-learning is emerging as a popular learning approach utilized by many organizations. Despite the ever increasing practices of e-learning in the workplace, most e-learning applications fail to meet learners’ needs or serve organization’s quests for success. Significant gaps exist between organizational interests and individual needs when they come to e-learning, which make e-learning applications less goal-effective. To solve this problem, a performance-oriented approach is presented in this study. Key performance indicators (KPIs) are set up to clarify organizational training needs, and help learners establish rational learning objectives. In addition, ontology is used for constructing formal and machine-understandable conceptualization of the performance-oriented learning environment. Using this approach, a KPI-oriented learning ontology and prototype system have been developed and evaluated to demonstrate the effectiveness of the approach.     

Plasmonic enhanced fluorescence spectroscopy using side-polished microstructured optical fiber

We report excitation of surface plasmon in a gold-coated side-polished D-shape microstructure optical fiber (MOF). As the leaky evanescent field from the fiber core becomes highly localized by the plasmon wave, its intensity also gets amplified significantly. Here we demonstrate an efficient use of this intensified field as excitation in fluorescence spectroscopy. The so-called plasmonic enhanced fluorescence emission from Rhodamine B has been investigated experimentally. First, plasmonic effect alone was found to provide an immediate fluorescence enhancement factor of two. Second, experimental results show a good agreement with theoretical modeling. Strong evanescent field generation and surface enhancement with simple metallic coating makes this fiber based device a good candidate for compact fluorescence spectroscopy.