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When we load boxes into a container, weight balancing is often considered. It is also important when we stowage containers in a ship. We have found that it is easier to balance the weight in certain types of 2D mesh configuration. In this paper, we have mathematically defined the weight balance in m × n mesh configuration (m and n are all odd numbers), and proved that the weight balance can be found at any number of items. Our theorem can be used to devise an algorithm for balancing the weight of the container vessels or loading the cargo on the train.

Voice conversion is the transform technique of the individuality between source and target speakers. In the previous studies, we proposed the voice conversion using synthesized speeches based on formant or line spectral information. The suggested method used the piecewise linear transform function of formant or LSP(line spectral pairs) features on formant intervals. In this paper, we propose the conversion of the individuality between speakers using a deep neural network. Along with improvements in deep neural network research, end-to-end speech conversion methods have been proposed and the results are suitable for generating more natural utterances compared to the past. Among them, we explore the representative speech generation methods and propose the voice conversion system to use formant features as additional information for local and global conditioned deep neural networks.

For environmental monitoring and risk identification of industrial plants, several monitoring systems using Wireless Sensor Networks (WSNs) have been developed. In this paper, we propose a dynamic duty cycle adjustment mechanism for reduced latency in industrial plants. The proposed method adjusts the duty cycle among predefined risk groups depending on the urgency of sensed data values. To demonstrate its efficacy, we analyze the expected transmission latency model and then discuss the characteristics in detail. We show that the proposed dynamic duty cycle mechanism is a more effective than a periodic mechanism by analyzing the expected latency of them in industrial plants where there are various types of sensory data with different levels of reliability.

Graphical user interface (GUI) is very important to interact with software users. In many studies, therefore, they are trying to convert GUI elements (or widgets) to code or to describe formally its structure by help of domain knowledge or machine learning based algorithms. In this paper, we adopted object detection based on deep neural networks that finds GUI elements by integration of localization and classification. After the successfully detection of GUI components, we will describe the objects as the hierarchical structure and transform those to appropriate codes by synthetic or machine learning algorithms.

The advent of IoT(Internet of Things) has triggered various kinds of USN(Ubiquitous Sensor Network) services in diverse fields. Keeping pace with the advance of USN service, many researchers have conducted studies to figure out low energy consumption of sensors. It is required to develop effective communication way with moving objects by using mobile sensors, not by using fixed sensors. This paper proposes the way to communicate effectively with moving objects and to achieve low energy consumption of sensors by controlling dynamic duty cycle based on mobility. In addition, this paper suggests the real life application for location management system of wild life animals.

Recently it is required to improve digital signage system which supports multilingual service because of the fast-growing number of foreign tourists. The existing digital signage systems obviously support various kinds of multilingual service via the internet connection. However, unfortunately, most foreign tourists are compelled to face limitations to access the real time service of multilingual contents mainly due to their limited internet conditions. This paper has designed digital signage system which supports multilingual service without the internet connection. The basic structure suggested in this paper is that smart device connects to the digital signage system without the internet connection based on Wireless Personal Area Network.

Performance of smart phones has increased to conduct simple PC functions that has become essential to modern people. With the development of smart phones, not only limited inner sensors but various sensors can be connected through USB. However, there is problem that app needs to downloaded when using each sensor. In this paper, a smart phone unified app structure for USB sensor Plug&Play is presented. The structure was designed to download web pages to use various sensors in one app. Unified app communicated with the platform through ADK accessory protocol and implements structure of delivering sensor ID to the web server and downloading device driver, web page. By measurement test, it was confirmed that download time of web page in unified app was 10 times faster than original download time of original app. By managing various sensors by one app, the app is searched every time the sensor changes in which there is no need for downloading several apps.

This research aims to propose a ubiquitous integration monitoring system for the feeding and environment management of livestock production. The integration monitoring system proposed in this research is based on an integrated platform, and consists of livestock shed environment monitoring system, livestock monitoring system, livestock remote medical treatment, and feeding and management system. This research conducts the followings. First, we review the previous researches on livestock related ubiquitous monitoring system to examine the factors to be considered in the proposed system. Then, we design the system and implement the prototype to demonstrate the possibility of the application of this system to real stockbreeding environment.

As smartphones become more and more popular, O2O (Offline-to-Online) applications have been spotlighted. They provide users offline data using NFC, QR, and Beacon technologies. But, there are some problems such as the high cost of server maintenance and the private data spills since they are implemented on WWW technologies. This paper suggests PWW (Person Wide Web) platform that provides server-less service on smartphones. In PWW, a smartphone has a PWW browser which is composed of an anchor scanner, a web view, an API linkage library, and internal/cloud storages. When the PWW browser scans an anchor includes a URL, it opens a web document stored in the internal storage of the smartphone or its corresponding cloud. The web document contains the API linkage library to utilize the several devices like a camera, GPS, and so on in the smartphone. In order to show the usefulness of PWW platform, we described the example of handling private data such as business cards. The PWW platform could be applied to various area in real world by developing web-based mobile applications.

In this paper, we proposed an architecture for supporting sensor transparency in sensor node operating systems, design the standard APIs (Application Programming Interfaces) and sensor device abstraction to provide the sensor transparency and implemented the sensor transparency in the TinyOS, the most well known sensor node operating system. With the proposed sensor node operating system which can support the sensor transparency, application developers can develop the target applications independent to each sensor device by using the standard APIs provided by the sensor node operating system and the sensor device manufacturers also can develop sensor device drivers by using the standard hardware interfaces and HAL (Hardware Adaptation Layer) interfaces independent to the specific hardware platform of sensor nodes.

Software inspection, due to its repeated success on industrial applications, has now become an industry standard practice. Recently, researchers began analyzing inspection data to obtain insights on how software processes can be improved. For example, project managers need to identify potentially error-prone software components so that limited project resource may be optimally allocated. This paper proposes an automated and fuzzy logic-based approach to satisfy such a need. Fuzzy logic offers significant advantages over other approaches due to its ability to naturally represent qualitative aspect of inspection data and apply flexible inference rules. In order to empirically evaluate the effectiveness of our approach, we have analyzed published inspection data and the ones collected from two separate inspection experiments which we had conducted. χ2 analysis is applied to statistically demonstrate validity of the proposed quality prediction model.

Although numerous empirical studies have been conducted to measure the fault detection capability of software analysis methods, few studies have been conducted using programs of similar size and characteristics. Therefore, it is difficult to derive meaningful conclusions on the relative detection ability and cost-effectiveness of various fault detection methods. In order to compare fault detection capability objectively, experiments must be conducted using the same set of programs to evaluate all methods and must involve participants who possess comparable levels of technical expertise. One such experiment was ‘Conflict1’, which compared voting, a testing method, self-checks, code reading by stepwise refinement and data-flow analysis methods on eight versions of a battle simulation program. Since an inspection method was not included in the comparison, the authors conducted a follow-up experiment ‘Conflict2’, in which five of the eight versions from Conflict1 were subjected to Fagan inspection. Conflict2 examined not only the number and types of faults detected by each method, but also the cost-effectiveness of each method, by comparing the average amount of effort expended in detecting faults. The primary findings of the Conflict2 experiment are the following. First, voting detected the largest number of faults, followed by the testing method, Fagan inspection, self-checks, code reading and data-flow analysis. Second, the voting, testing and inspection methods were largely complementary to each other in the types of faults detected. Third, inspection was far more cost-effective than the testing method studied. Copyright © 2002 John Wiley & Sons, Ltd.

A rule-based expert system for the optimal operation of plantwide steam distribution systems is proposed to minimize the net cost of providing energy to the plant. The system is based on the steady-state modeling and simulation of steam generation processes and steam distribution networks. Modeling of steam generation processes and steam distribution networks was performed based on actual plant operation data. Heuristic operational knowledge obtained from experienced plant engineers is incorporated in the form of IF−THEN rules. The proposed system could provide operational information when there were changes in the grade and amount of steam demand. The letdown amount from the very high pressure steam (VS) header and the amount of VS produced at the boiler showed good agreement with those of actual operational data. The prediction of an increase of boiler load caused by self-consumed steam made it possible to prevent an unexpected sudden increase of electricity demand.