In long-haul optical communication system consisting of standard single-mode fiber spans and fiber amplifiers, such as the erbium-doped fiber amplifier, performance is deteriorated by signal distortion due to chromatic dispersion and nonlinearity of the fiber. A combination of dispersion management and optical phase conjugation is an effective technique to compensate for the distortion. In an optical link configured by this combination, a dispersion map mainly affects the compensation of the distorted optical signals. This paper proposes new dispersion maps configured by the decaying or expanding distribution of residual dispersion per span (RDPS) in a dispersion-managed link combined with a midway optical phase conjugator. The effect of the proposed dispersion maps on the compensation for distorted 24 channel × 40 Gbps wavelength-division multiplexed signals was assessed through numerical simulation. It was confirmed that all the proposed dispersion maps are most appropriate for the compensation and, furthermore, for the flexibility of link configuration than conventional links.

Existing web applications and services have historically been implemented using JavaScript. However, new technologies such as artificial intelligence, the Internet of Things, and Big Data are being developed as part of the Fourth Industrial Revolution. With the definition of the HTML5 web standard, services (such as the technologies mentioned above) that were previously not available through the Web become available. These services, however, need to have the same performance as native applications, and implementing these services will require new technologies. Therefore, additional tools that can work on the Web with native performance are needed. In this paper, a system for branching processing was established using JavaScript and WebAssembly, a language that can operate on the Web. This system performs user requests in advance, and requests are branched in a language that produces faster results. Therefore, a service capable of quick response times can be implemented.

Recently, effort to obtain various information from the vast amount of social network services (SNS) big data generated in daily life has expanded. SNS big data comprise sentences classified as unstructured data, which complicates data processing. As the amount of processing increases, a rapid processing technique is required to extract valuable information from SNS big data. We herein propose a system that can extract human sentiment information from vast amounts of SNS unstructured big data using the naïve Bayes algorithm and natural language processing (NLP). Furthermore, we analyze the effectiveness of the proposed method through various experiments. Based on sentiment accuracy analysis, experimental results showed that the machine learning method using the naïve Bayes algorithm afforded a 63.5% accuracy, which was lower than that yielded by the NLP method. However, based on data processing speed analysis, the machine learning method by the naïve Bayes algorithm demonstrated a processing performance that was approximately 5.4 times higher than that by the NLP method.

This paper proposes a solution to the problem of finding a subgraph for a given instance of many terminals on a Euclidean plane. The subgraph is a tree, whose nodes represent the chosen terminals from the problem instance, and whose edges are line segments that connect two corresponding terminals. The tree is required to have the maximum number of nodes while the length is limited and is not sufficient to interconnect all the given terminals. The problem is shown to be NP-hard, and therefore a genetic algorithm is designed as an efficient practical approach. The method is suitable to various probable applications in layout optimization in areas such as communication network construction, industrial construction, and a variety of machine and electronics design problems. The proposed heuristic can be used as a general-purpose practical solver to reduce industrial costs by determining feasible interconnections among many types of components over different types of physical planes.

A pendubot is a representative example of an underactuated system that has fewer actuators than the degree of freedom of the system. In this study, the characteristics of the pendubot are first reviewed; each part is then designed using Solidworks by dividing the pendubot into three parts: the base frame, first link frame, and second link frame. These three parts are then imported into the Simulink environment via a STEP file format, which is the standard protocol used in data exchange between CAD applications. A 3D model of the pendubot is then constructed using Simscape, and the usefulness of the 3D model is validated by a comparison with a dynamic equation derived using the Lagrangian formulation. A linearized model around an upright equilibrium position is finally obtained, and a sliding mode controller is designed based on the linear quadratic regulator. Simulation results showed that the designed controller effectively maintained upright balance of the pendubot in the presence of disturbance.

Differential evolution (DE) is an uncomplicated and serviceable developmental algorithm. Nevertheless, its execution depends on strategies and regulating structures. The combination of several strategies between subpopulations helps to stabilize the probing on DE. In this paper, we propose a unique k-mean soft island model DE(KSDE) algorithm which maintains population diversity through soft island model (SIM). A combination of various approaches, called KSDE, intended for migrating the subpopulation information through SIM is developed in this study. First, the population is divided into k subpopulations using the k-means clustering algorithm. Second, the mutation pattern is singled randomly from a strategy pool. Third, the subpopulation information is migrated using SIM. The performance of KSDE was analyzed using 13 benchmark indices and compared with those of high-technology DE variants. The results demonstrate the efficiency and suitability of the KSDE system, and confirm that KSDE is a cost-effective algorithm compared with four other DE algorithms.

South Korea has allowed parallel importation since 1995. Parallel importation causes competition among importers in the logistics process allowing, consumers to purchase foreign brand products at low prices. Most parallel importers base product pricing on subjective judgements. Fashion products in particular, have different sales rates depending on trends and seasons, so sales performance varies greatly depending on selling price timing and policy. The merchandiser (MD) set the price on parallel importation products by aggregating information on imported products and pricing goods. However, this customized process is very time consuming for the MD. This is because the logistics process of parallel importation's customs clearance procedures and repair works is complicated and takes a significant amount of time. In this paper, we propose an improved parallel importation logistics process based on big data, which automatically sets the price of parallel importation products.

It is important that students are provided opportunities to practice their skills in acquiring radiographic images. However, these opportunities are currently limited because of the risk of radiation exposure. To overcome this limitation, a new augmented reality-based radiography simulator was developed that enables students to practice radiographic techniques as part of self-directed learning without time and space constraints. Subsequently, cross-sectional images of a manikin phantom head obtained via computed tomography were reconstructed into a three-dimensional object. An image marker that could be recognized by a mobile device and could allow users to practice dental radiography techniques was devised. The three-dimensional object was augmented to the mobile device; consequently, among 106 stored dental radiographs on the device, a radiograph corresponding to specific imaging conditions was opened when users performed radiographic procedures. This technology could improve dental students' understanding of dental anatomy and contribute to improving their competency in acquiring dental radiographs.

This paper presents processing-node status-based message scattering and gathering algorithms for multi-processor systems on chip to reduce the communication time between processors. In the message-scattering part of the message-passing interface (MPI) scatter function, data transmissions are ordered according to the proposed linear algorithm, based on the processor status. The MPI hardware unit in the root processing node checks whether each processing node's status is 'free' or 'busy' when an MPI scatter message is received. Then, it first transfers the data to a 'free' processing node, thereby reducing the scattering completion time. In the message-gathering part of the MPI gather function, the data transmissions are ordered according to the proposed linear algorithm, and the gathering is performed. The root node receives data from the processing node that wants to transfer first, and reduces the completion time during the gathering. The experimental results show that the performance of the proposed algorithm increases at a greater rate as the number of processing nodes increases.

A 1.9-GHz linear CMOS power amplifier is presented. An adaptive bias circuit (ABC) that utilizes an AC ground to detect the power level of the input signal is proposed to enhance the linearity and efficiency of the power amplifier. The ABC utilizes the second harmonic component as the input to mitigate the distortion of the fundamental signal. The input power level of the ABC was detected at the AC ground located at the V_DD node of the power amplifier. The output of the ABC was fed into the inputs of the power stage. The input signal distortion was mitigated by detecting the input power level at the AC ground. The power amplifier was designed using a 180 nm RFCMOS process to evaluate the feasibility of the application of the proposed ABC in the power amplifier. The measured output power and power-added efficiency were improved by 1.7 dB and 2.9%, respectively.