ADAPTIVE RANKS CLONE AND k‐NEAREST NEIGHBOR LIST–BASED IMMUNE MULTI‐OBJECTIVE OPTIMIZATION

Artificial immune systems (AIS) are computational systems inspired by the principles and processes of the vertebrate immune system. The AIS‐based algorithms typically exploit the immune system's characteristics of learning and adaptability to solve some complicated problems. Although, several AIS‐based algorithms have proposed to solve multi‐objective optimization problems (MOPs), little focus have been placed on the issues that adaptively use the online discovered solutions. Here, we proposed an adaptive selection scheme and an adaptive ranks clone scheme by the online discovered solutions in different ranks. Accordingly, the dynamic information of the online antibody population is efficiently exploited, which is beneficial to the search process. Furthermore, it has been widely approved that one‐off deletion could not obtain excellent diversity in the final population; therefore, a k‐nearest neighbor list (where k is the number of objectives) is established and maintained to eliminate the solutions in the archive population. The k‐nearest neighbors of each antibody are founded and stored in a list memory. Once an antibody with minimal product of k‐nearest neighbors is deleted, the neighborhood relations of the remaining antibodies in the list memory are updated. Finally, the proposed algorithm is tested on 10 well‐known and frequently used multi‐objective problems and two many‐objective problems with 4, 6, and 8 objectives. Compared with five other state‐of‐the‐art multi‐objective algorithms, namely NSGA‐II, SPEA2, IBEA, HYPE, and NNIA, our method achieves comparable results in terms of convergence, diversity metrics, and computational time.     

Development of flexible displays using back‐channel‐etched In–Sn–Zn–O thin‐film transistors and air‐stable inverted organic light‐emitting diodes

We developed flexible displays using back‐channel‐etched In–Sn–Zn–O (ITZO) thin‐film transistors (TFTs) and air‐stable inverted organic light‐emitting diodes (iOLEDs). The TFTs fabricated on a polyimide film exhibited high mobility (32.9 cm²/Vs) and stability by utilization of a solution‐processed organic passivation layer. ITZO was also used as an electron injection layer (EIL) in the iOLEDs instead of conventional air‐sensitive materials. The iOLED with ITZO as an EIL exhibited higher efficiency and a lower driving voltage than that of conventional iOLEDs. Our approach of the simultaneous formation of ITZO film as both of a channel layer in TFTs and of an EIL in iOLEDs offers simple fabrication process.     

Back‐channel‐etched thin‐film transistor using c‐axis‐aligned crystal In–Ga–Zn oxide

Our crystalline In–Ga–Zn oxide (IGZO) thin film has a c‐axis‐aligned crystal (CAAC) structure and maintains crystallinity even on an amorphous base layer. Although the crystal has c‐axis alignment, its a‐axis and b‐axis have random arrangement; moreover, a clear grain boundary is not observed. We fabricated a back‐channel‐etched thin‐film transistor (TFT) using the CAAC‐IGZO film. Using the CAAC‐IGZO film, more stable TFT characteristics, even with a short channel length, can be obtained, and the instability of the back channel, which is one of the biggest problems of IGZO TFTs, is solved. As a result, we improved the process of manufacturing back‐channel‐etched TFTs.     

Post BWT stages of the Burrows–Wheeler compression algorithm

The lossless Burrows–Wheeler compression algorithm has received considerable attention over recent years for both its simplicity and effectiveness. It is based on a permutation of the input sequence—the Burrows–Wheeler transformation (BWT)—which groups symbols with a similar context close together. In the original version, this permutation was followed by a Move‐To‐Front transformation and a final entropy coding stage. Later versions used different algorithms, placed after the BWT, since the following stages have a significant influence on the compression rate. This paper describes different algorithms and improvements for these post BWT stages including a new context‐based approach. The results for compression rates are presented together with compression and decompression times on the Calgary corpus, the Canterbury corpus, the large Canterbury corpus and the Lukas 2D 16‐bit medical image corpus. Copyright © 2010 John Wiley & Sons, Ltd.     

Dynamic output‐feedback fuzzy MPC for Takagi‐Sugeno fuzzy systems under event‐triggering–based try‐once‐discard protocol

The fuzzy model predictive control (FMPC) problem is studied for a class of discrete‐time Takagi‐Sugeno (T‐S) fuzzy systems with hard constraints. In order to improve the network utilization as well as reduce the transmission burden and avoid data collisions, a novel event‐triggering–based try‐once‐discard (TOD) protocol is developed for networks between sensors and the controller. Moreover, due to practical difficulties in obtaining measurements, the dynamic output‐feedback method is introduced to replace the traditional state feedback method for addressing the FMPC problem. Our aim is to design a series of controllers in the framework of dynamic output‐feedback FMPC for T‐S fuzzy systems so as to find a good balance between the system performance and the time efficiency. Considering nonlinearities in the context of the T‐S fuzzy model, a “min‐max” strategy is put forward to formulate an online optimization problem over the infinite‐time horizon. Then, in light of the Lyapunov‐like function approach that fully involves the properties of the T‐S fuzzy model and the proposed protocol, sufficient conditions are derived to guarantee the input‐to‐state stability of the underlying system. In order to handle the side effects of the proposed event‐triggering–based TOD protocol, its impacts are fully taken into consideration by virtue of the S‐procedure technique and the quadratic boundedness methodology. Furthermore, a certain upper bound of the objective is provided to construct an auxiliary online problem for the solvability, and the corresponding algorithm is given to find the desired controllers. Finally, two numerical examples are used to demonstrate the validity of proposed methods.     

Energy‐efficient scheduling algorithms for batch‐of‐tasks (BoT) applications on heterogeneous computing systems

One of the major design constraints of a heterogeneous computing system is optimal scheduling, that is, mapping of tasks on the processing nodes in order to optimize the QoS parameters. Because of the huge energy consumption by computing resources, negative environmental effects and reduced system reliability, energy has unavoidably been added as a new parameter to the list of QoS parameters. Energy optimization in scheduling strategies along with makespan makes it an even more challenging combinatorial optimization problem. This work proposes two energy‐aware scheduling algorithms G1 and G2 to schedule a batch‐of‐tasks, made of a collection of independent tasks, on heterogeneous processors in order to minimize the makespan and the energy consumption. The proposed algorithms schedule tasks based on weighted aggregation cost function to the appropriate processors followed by task migration phase designed to further minimize the makespan and the energy consumption. The study evaluates the performance of the proposed algorithms with some of the peers, that is, MinMin, MINSuff on account of makespan, energy consumption, flowtime, and utilization. An experimental study reveals that the proposed algorithm (G2) consistently performs better under various test conditions. Copyright © 2015 John Wiley & Sons, Ltd.     

On the Role of Homogeneity When Controlling Single‐Leader Networks

This paper presents an approach to controlling agent positions in single‐leader networks to target points while explicitly taking agent homogeneity into account. When the capabilities of agents to accomplish tasks at each of the targets are identical, then the label of the target points may be permuted while still expressing the same intention. In single‐leader networks which are not completely controllable, such a permutation of the target points may at times move a target closer to the system's reachable subspace, thereby allowing the network to surpass the limitations on controllability when homogeneity is not considered explicitly. To fully exploit this property in homogeneous networks, it is then necessary to find the permutation of a target point which brings it closest to the reachable subspace. However, finding this optimal permutation is shown to be in general a non‐deterministic polynomial‐time (NP)‐hard problem. Specific network topologies are identified for when finding such an optimal permutation of a target point can be advantageous when controlling single‐leader networks. Moreover, an alternate view of the problem of finding optimal permutations is presented in which clustering‐based algorithms can be applied to find suboptimal solutions.     

Implementation and optimization of GPU‐based parallel one‐step leapfrog ADI‐FDTD for far‐field scattering problems

The one‐step leapfrog alternative‐direction‐implicit finite‐difference time‐domain (ADI‐FDTD), free from the Courant‐Friedrichs‐Lewy (CFL) stability condition and sub‐step computations, is efficient when dealing with fine grid problems. However, solution of the numerous tridiagonal systems still imposes a great computational burden and makes the method hard to execute in parallel. In this paper, we proposed an efficient graphic processing unit (GPU)‐based parallel implementation of the one‐step leapfrog ADI‐FDTD for the far‐field EM scattering simulation of objects, in which we present and analyze the manners of calculation area division and thread allocation and a data layout transformation of z components is proposed to achieve better memory access mode, which is a key factor affecting GPU execution efficiency. The simulation experiment is carried out to verify the accuracy and efficiency of the GPU‐based implementation. The simulation results show that there is a good agreement between the proposed one‐step leapfrog ADI‐FDTD method and Yee's FDTD in solving the far‐field scattering problem and huge benefits in performance were encountered when the method was accelerated using GPU technology.     

Generating effective test cases based on satisfiability modulo theory solvers for service‐oriented workflow applications

Web Service Business Process Execution Language (WS‐BPEL) is one of the most popular service‐oriented workflow applications. The unique features (e.g. dead path elimination semantics and correlation mechanism) of WS‐BPEL applications have raised enormous problems to its test case generation, especially in unit testing. Existing studies mainly assume that each path in the control flow graphs that correspond to WS‐BPEL applications is feasible, which always yields imprecise test cases or complicates testing results. The current study tackles this problem based on satisfiability modulo theory solvers. First, a new coverage criterion is proposed to measure the quality of test sets for testing WS‐BPEL applications. Second, decomposition algorithms are presented to obtain test paths that meet the proposed coverage criterion. Finally, this paper symbolically encodes each test path with several constraints by capturing the unique features of WS‐BPEL. These constraints are solved and the test cases (test paths and test data) are obtained with the help of satisfiability modulo theory solvers to test WS‐BPEL applications effectively. Experiments are conducted using our approach and other typical approaches (e.g. message‐sequence generation‐based approach and concurrent path analysis approach) with 10 WS‐BPEL applications. Experimental results demonstrate that the test cases generated by our approach can avoid instantiating idle instance and expose more faults. Copyright © 2015 John Wiley & Sons, Ltd.     

Mesh‐Free Discrete Laplace–Beltrami Operator

In this work we propose a new discretization method for the Laplace–Beltrami operator defined on point‐based surfaces. In contrast to the existing point‐based discretization techniques, our approach does not rely on any triangle mesh structure, turning out truly mesh‐free. Based on a combination of Smoothed Particle Hydrodynamics and an optimization procedure to estimate area elements, our discretization method results in accurate solutions while still being robust when facing abrupt changes in the density of points. Moreover, the proposed scheme results in numerically stable discrete operators. The effectiveness of the proposed technique is brought to bear in many practical applications. In particular, we use the eigenstructure of the discrete operator for filtering and shape segmentation. Point‐based surface deformation is another application that can be easily carried out from the proposed discretization method.     

Evaluating Bar Coding‐Aided Medication Administration through Identification of Nursing Work Deficiencies

Health care information technology (IT) systems manage administrative and clinical processes more accurately and efficiently. However, their effects on clinical work flow are still not fully understood. In this article, we investigate the bar‐coded medication administration (BCMA) system for its effect on nurses working in inpatient departments. Evaluation is applied by examining work deficiencies before and after the IT system implementation based on a proposed nursing work model. A list of nurse‐perceived risks of work deficiencies related to the current BCMA system has been identified. Results show five main deficiencies that are mainly related to aspects of the IT environment and work schedule/process, including increased workload, IT systems downtime, unclear orders/task schedules, reduced time for patient‐care tasks, and redundant documentation. This study emphasizes the importance of understanding the reciprocal relationship between IT implementation and health care work system. © 2012 Wiley Periodicals, Inc.     

Controlling Chaos and Neimark–Sacker Bifurcation in a Host–Parasitoid Model

In this paper, a new density‐dependent host–parasitoid model is proposed. The modification is based on density‐dependent factor by introducing Hassell growth function in host population. Moreover, the permanence of solutions, existence and uniqueness of positive equilibrium, local asymptotic stability and global behavior of the positive equilibrium point are also investigated. It is demonstrated that system endures Neimark–Sacker bifurcation for wide range of bifurcation parameter. In order to control chaos due to emergence of Neimark–Sacker bifurcation, two feedback control strategies, that is, OGY and hybrid control methods are implemented. Finally, all mathematical analysis, particularly, Neimark–Sacker bifurcation, chaos control strategies, and global asymptotic stability of unique positive point are verified with the help of numerical simulations.     

Distributed output regulation of leader–follower multi‐agent systems

In this paper, distributed leader–follower control algorithms are presented for linear multi‐agent systems based on output regulation theory and internal model principle. By treating a leader to be followed as an exosystem, the proposed framework can be used to generalize existing multi‐agent coordination solutions to allow the identical agents to track an active leader with different dynamics and unmeasurable variables. Moreover, the obtained results for multi‐agent coordination control are an extension of previous work on centralized and decentralized output regulation to a distributed control context. Necessary and sufficient conditions for the distributed output regulation problem are given. Finally, distributed output regulation of some classes of multi‐agent systems with switching interconnection topologies are discussed via both static and dynamic feedback. Copyright © 2011 John Wiley & Sons, Ltd.     

A TWO‐STAGE WIN–WIN MULTIATTRIBUTE NEGOTIATION MODEL: OPTIMIZATION AND THEN CONCESSION

Many automated negotiation models have been developed to solve the conflict in many distributed computational systems. However, the problem of finding win–win outcome in multiattribute negotiation has not been tackled well. To address this issue, based on an evolutionary method of multiobjective optimization, this paper presents a negotiation model that can find win–win solutions of multiple attributes, but needs not to reveal negotiating agents’ private utility functions to their opponents or a third‐party mediator. Moreover, we also equip our agents with a general type of utility functions of interdependent multiattributes, which captures human intuitions well. In addition, we also develop a novel time‐dependent concession strategy model, which can help both sides find a final agreement among a set of win–win ones. Finally, lots of experiments confirm that our negotiation model outperforms the existing models developed recently. And the experiments also show our model is stable and efficient in finding fair win–win outcomes, which is seldom solved in the existing models.     

High‐performance N‐thread software solutions for mutual exclusion

Software solutions for mutual exclusion developed over a 30‐year period, starting with complex ad hoc algorithms and progressing to simpler formal ones. While it is easy to dismiss software solutions for mutual exclusion, as this family of algorithms is antiquated and most platforms support atomic hardware instructions, there is still a need for these algorithms in threaded, embedded systems running on low‐cost processors lacking atomic instructions. While N‐thread solutions are usually short (10–25 lines of code), each is ingenious with exceptionally subtle aspects, often making it difficult to prove correctness or construct an implementation. This work examines correctness and performance of the implementations. An extensive survey of existing algorithms is presented, with explanations of the intuition behind the algorithms and how they work. Several errors were found and corrections made, as well as a few small improvements, in the existing algorithms; two new high‐performance algorithms were developed. Finally, a worst‐case high‐contention performance experiment is performed to compare the algorithms and contrast them with three common locks based on hardware atomic instructions. The results show our two new algorithms are highly competitive with an equivalent hardware lock (Mellor‐Crummey and Scott) over a range of 1–32 processors. Hence, threading is a viable alternative to event‐driven programming for complex embedded systems without atomic instructions. Copyright © 2014 John Wiley & Sons, Ltd.     

Context‐Centric Speech‐Based Human–Computer Interaction

This paper describes research that addresses the problem of dialog management from a strong, context‐centric approach. We further present a quantitative method of measuring the importance of contextual cues when dealing with speech‐based human–computer interactions. It is generally accepted that using context in conjunction with a human input, such as spoken speech, enhances a machine's understanding of the user's intent as a means to pinpoint an adequate reaction. For this work, however, we present a context‐centric approach in which the use of context is the primary basis for understanding and not merely an auxiliary process. We employ an embodied conversation agent that facilitates the seamless engagement of a speech‐based information‐deployment entity by its human end user. This dialog manager emphasizes the use of context to drive its mixed‐initiative discourse model. A typical, modern automatic speech recognizer (ASR) was incorporated to handle the speech‐to‐text translations. As is the nature of these ASR systems, the recognition rate is consistently less than perfect, thus emphasizing the need for contextual assistance. The dialog system was encapsulated into a speech‐based embodied conversation agent platform for prototyping and testing purposes. Experiments were performed to evaluate the robustness of its performance, namely through measures of naturalness and usefulness, with respect to the emphasized use of context. The contribution of this work is to provide empirical evidence of the importance of conversational context in speech‐based human–computer interaction using a field‐tested context‐centric dialog manager.     

Adaptive Ray‐bundle Tracing with Memory Usage Prediction: Efficient Global Illumination in Large Scenes

This paper proposes an adaptive rendering technique for ray‐bundle tracing. Ray‐bundle tracing can be done by per‐pixel linked‐list construction on a GPU rasterization pipeline. This rasterization based approach offers significant benefits for the efficient generation of light maps (e.g., hardware acceleration, tessellation, and recycling of shaders used in real‐time graphics). However, it is inapplicable to large and complex scenes due to the limited capacity of the GPU memory because it requires a high‐resolution frame buffer and high‐capacity node buffer for the linked‐lists. In addition, memory overflow can potentially occur on the per‐pixel linked‐list since the memory usage of the lists is usually unknown before the rendering process. We introduce an adaptive tiling technique with memory usage prediction. Our method uses an appropriately tiled frame buffer, thus eliminating almost all of the overflow risks thanks to our adaptive tile subdivision scheme. Using this technique, we are able to render high‐quality light maps of large and complex scenes which cannot be computed using previous ray‐bundle based methods.