Synthesis and characterization of novel blue azo‐dye derivatives containing acrylate group for dye‐based color filters

Abstract— Even though dyes have a fine resolution and good chromaticities, they are not widely used as coloring materials for color filters (CFs) due to their low thermal stability and chemical resistance. A series of azo‐dye derivatives, which consist of two cross‐linkable acrylate or methacrylate groups to improve thermal and chemical properties, have been synthesized and used to fabricate color filters. The spectral properties and chemical/thermal stabilities of the fabricated CFs were investigated by comparing dye‐based CFs, without a complicated dispersion process, but with pigment‐based CFs using dispersed pigment. Also, more properties including the development test and surface morphologies lithographic properties were studied. The synthesized azo dyes were characterized by elemental analysis, UV‐visible spectra, IR, mass, and ¹H‐NMR spectra.     

Design of a sliding mode controller for an automatic guided vehicle and its implementation

In this paper, a control scheme that combines a kinematic controller and a sliding mode dynamic controller with external disturbances is proposed for an automatic guided vehicle to track a desired trajectory with a specified constant velocity. It provides a method of taking into account specific mobile robot dynamics to convert desired velocity control inputs into torques for the actual mobile robot. First, velocity control inputs are designed for the kinematic controller to make the tracking error vector asymptotically stable. Then, a sliding mode dynamic controller is designed such that the mobile robot’s velocities converge to the velocity control inputs. The control law is obtained based on the backstepping technique. System stability is proved using the Lyapunov stability theory. In addition, a scheme for measuring the errors using a USB camera is described. The simulation and experimental results are presented to illustrate the effectiveness of the proposed controller.     

Pattern recognition using feature feedback: Application to face recognition

In this paper, we propose a new pattern recognition method using feature feedback and present its application to face recognition. Conventional pattern recognition methods extract the features employed for classification using PCA, LDA and so on. On the other hand, in the proposed method, the extracted features are analyzed in the original space using feature feedback. Using reverse mapping from the extracted features to the original space, we can identify the important part of the original data that affects the classification. In this way, we can modify the data to obtain a higher classification rate, make it more compact or abbreviate the required sensors. To verify the applicability of the proposed method, we apply it to face recognition using the Yale Face Database. Each face image is divided into two parts, the important part and unimportant part, using feature feedback, and the classification performed using the feature mask obtained from feature feedback. Also, we combine face recognition with image compression. The experimental results show that the proposed method works well.     

Bi-objective scheduling for reentrant hybrid flow shop using Pareto genetic algorithm

This paper deals with a scheduling problem for reentrant hybrid flowshop with serial stages where each stage consists of identical parallel machines. In a reentrant flowshop, a job may revisit any stage several times. Local-search based Pareto genetic algorithms with Minkowski distance-based crossover operator is proposed to approximate the Pareto optimal solutions for the minimization of makespan and total tardiness in a reentrant hybrid flowshop. The Pareto genetic algorithms are compared with existing multi-objective genetic algorithm, NSGA-II in terms of the convergence to optimal solution, the diversity of solution and the dominance of solution. Experimental results show that the proposed crossover operator and local search are effective and the proposed algorithm outperforms NSGA-II by statistical analysis.     

A data-driven generic simulation model for logistics-embedded assembly manufacturing lines

Simulation has been used to evaluate various aspects of manufacturing systems. However, building a simulation model of a manufacturing system is time-consuming and error-prone because of the complexity of the systems. This paper introduces a generic simulation modeling framework to reduce the simulation model build time. The framework consists of layout modeling software and a data-driven generic simulation model. The generic simulation model was developed considering the processing as well as the logistics aspects of assembly manufacturing systems. The framework can be used to quickly develop an integrated simulation model of the production schedule, operation processes and logistics of a system. The framework was validated by developing simulation models of cellular and conveyor manufacturing systems.     

Efficient RNTS system for privacy of banking off-line customer

With the development in IT technology and with growing demands of users, a ubiquitous environment is being made. Because individual identification is important in ubiquitous environment, RFID technology would be used frequently. RFID is a radio frequency identification technology to replace bar code. The reader transmits query (request of user information) and tag-provides user information. RFID has various advantages, such as high speed identification rates, mass memory storages. However, eavesdropping is possible as well as a problem that user information is exposed (Juels et al. in Conference on Computer and Communications Security—ACM CCS, pp. 103–111, 2003; Ohkubo et al. in RFID Privacy Workshop 2003; Weis et al. in International Conference on Security in Pervasive Computing, pp. 201–212, 2003; Weis et al. in Cryptographic Hardware and Embedded Systems—CHES, pp. 454–469, 2002). Therefore, when off-line customer had visited bank for banking service, RNTS (RFID number ticket service) system provides both anonymity in customer identification and efficiency of banking service. In addition, RNTS system protects privacy of an off-line user visiting the bank and it is an efficient method offering service in order of arriving in the bank.     

Consistent Sets of Secondary Structures in Proteins

Ab initio predictions of secondary structures in proteins have to combine local predictions, based on short fragments of the protein sequence, with consistency restrictions, as not all locally plausible predictions may be simultaneously true. We use the fact that secondary structures are patterns of hydrogen bonds and that a single residue can participate in hydrogen bonds of at most one secondary structure. Consistency of fixed-sized pieces of secondary structures is the easiest to approximate and we formalize it as 1-2 matching problem. Consistency of entire secondary structures is a version of set packing. We also investigate how to form a simple problem if we add the requirement that the secondary structure and the loops that connect them fit together in a metric space. Every problem that we investigated is MAX-SNP hard and it has a constant factor approximation. Computational experience suggests that in biological instances, we can find nearly optimal solutions using heuristics.     

Finding the longest common nonsuperstring in linear time

String inclusion and non-inclusion problems have been vigorously studied in such diverse fields as molecular biology, data compression, and computer security. Among the well-known string inclusion or non-inclusion notions, we are interested in the longest common nonsuperstring. Given a set of strings, the longest common nonsuperstring problem is finding the longest string that is not a superstring of any string in the given set. It is known that the longest common nonsuperstring problem is solvable in polynomial time.In this paper, we propose an efficient algorithm for the longest common nonsuperstring problem. The running time of our algorithm is linear with respect to the sum of the lengths of the strings in the given set, using generalized suffix trees.     

Designing of a type-2 fuzzy logic filter for improving edge-preserving restoration of interlaced-to-progressive conversion

This paper focuses on recently advanced fuzzy models and the application of type-2 fuzzy sets in video deinterlacing. The final goal of the proposed deinterlacing algorithm is to exactly determine an unknown pixel value while preserving the edges and details of the image. To begin, we will discuss some artefacts of spatial, temporal, and spatio-temporal domain deinterlacing methods. In order to address the aforementioned issues, we adopted type-2 fuzzy sets concepts to design a weight evaluating approach. In the proposed method, the upper and lower fuzzy membership functions of the type-2 fuzzy logic filters are derived from the type-1 (or primary) fuzzy membership function. The weights from upper and lower membership functions are considered to be multiplied with the candidate deinterlaced pixels. Experimental results proved that the performance of the proposed method was superior, both objectively and subjectively to other different conventional deinterlacing methods. Moreover, the proposed method preserved the smoothness of the original image edges and produced a high-quality progressive image.     

Efficient single-pass frequent pattern mining using a prefix-tree

The FP-growth algorithm using the FP-tree has been widely studied for frequent pattern mining because it can dramatically improve performance compared to the candidate generation-and-test paradigm of Apriori. However, it still requires two database scans, which are not consistent with efficient data stream processing. In this paper, we present a novel tree structure, called CP-tree (compact pattern tree), that captures database information with one scan (insertion phase) and provides the same mining performance as the FP-growth method (restructuring phase). The CP-tree introduces the concept of dynamic tree restructuring to produce a highly compact frequency-descending tree structure at runtime. An efficient tree restructuring method, called the branch sorting method, that restructures a prefix-tree branch-by-branch, is also proposed in this paper. Moreover, the CP-tree provides full functionality for interactive and incremental mining. Extensive experimental results show that the CP-tree is efficient for frequent pattern mining, interactive, and incremental mining with a single database scan.