Effects of OH radicals on formation of Cu oxide and polishing performance in Cu Chemical Mechanical Polishing

The amount of OH radicals generated varied according to the complexing agent or Cu ion, and the accelerating effect of OH radicals on the rate of Cu oxide formation was found in acidic pH. When Cu I ions and oxalic acid were added to H2O2-based slurry, the decreases in etch and removal rates of Cu were observed because more generation of OH radicals resulted in the formation of thicker Cu oxide compared to additive-free slurry. Therefore, proper control of the formation and dissolution of Cu oxide led to an increase in etch and removal rates.This work was supported by the KOSEF through the Research Center for Energy Conversion and Storage (RCECS), Hanhwa Chemical, Ltd., and by the Institute of Chemical Processes (ICP) in Seoul National University

COORDINATIVE PATTERNS BETWEEN CARVING TURN AND SKIDDING TURN DURING ALPINE SKIING

The purpose of this study was to investigate the coordinative patterns between segments and ski using the continuous relative phase (CRP) on anteroposterior and vertical axis during carving and skidding turn. Fourteen alpine ski instructors were participated in this study. Eight inertial measurement units were used to collect segment kinematic data. Each skier was asked to perform ten carving turns and ten skidding turns on the groomed 15° slope, respectively. CRP angles between all segments and ski were significantly increased during carving turn on the vertical axis. On the other hand, CRP angles between all segments and ski were significantly increased during skidding turn on anteroposterior axis. Therefore, skiers should perform the anti-phase movements of the lower spine-ski, pelvis-ski, thigh-ski and shank-ski on the vertical axis during the carving turn and the in-phase movements of the lower spine-ski, pelvis-ski, thigh-ski and shank-ski on the anteroposterior axis during skidding turn

Development of Sensor Registry System-Based Predictive Information Service Using a Grid

A sensor registry system (SRS) registers sensor metadata and provides them for a seamless semantic process. Recently, network coverage information-based SRS (NC-SRS) was developed to provide sensor information filtering by combining path prediction and network coverage checks. However, the NC-SRS has problems caused by issues such as termination of OpenSignal service and pre-building road segments. Therefore, this paper proposes a sensor registry system-based predictive information service (SRS-PIS) using a grid. SRS-PIS predicts a path based on the grid, checks the network coverage, and filters the sensor. This paper presents a grid-based real-time path prediction algorithm and an algorithm for grouping network service-disabled areas. To obtain network coverage information, we constructed and implemented a grid-based coverage map through experiment to measure the signal strength. As an evaluation, we compared features among SRS-based systems and SRS-PIS, and compared advantages and disadvantages between segment-based and grid-based methods

Canonical Sensor Ontology Builder Based on ISO/IEC 11179 for Sensor Network Environments: A Standardized Approach

The advancement of sensor technology has led to an explosive increase in sensors. It causes semantic heterogeneity problems, and much research has focused on sensor ontology building to solve the problems. However, there are still remaining several issues, and one of the most critical issues is about a method for progressive and dynamic concepts management and reuse of sensor ontology. This paper proposes an ontology generation system based on ISO/IEC 11179–MDR (metadata registry). The proposed system is referred to as the Canonical Sensor Ontology Builder (CaSOB) and can create ontologies by reusing the common concepts registered in a canonical sensor ontology concept registry, an MDR. This paper defines a mapping model and processes to create ontology with the concepts registered in an MDR. Our proposal provides many advantages such as high standardization, consistent concept usage, and easy semantic exchange. Therefore, CaSOB facilitates the high quality sensor ontology creation and reduces the costs of sensor ontology integration and system development

LSTM-Based Path Prediction for Effective Sensor Filtering in Sensor Registry System

The Internet of Things (IoT) is expected to provide intelligent services by receiving heterogeneous data from ambient sensors. A mobile device employs a sensor registry system (SRS) to present metadata from ambient sensors, then connects directly for meaningful data. The SRS should provide metadata for sensors that may be successfully connected. This process is location-based and is also known as sensor filtering. In reality, GPS sometimes shows the wrong position and thus leads to a failed connection. We propose a dual collaboration strategy that simultaneously collects GPS readings and predictions from historical trajectories to improve the probability of successful requests between mobile devices and ambient sensors. We also update the evaluation approach of sensor filtering in SRS by introducing a Monte Carlo-based simulation flow to measure the service provision rate. The empirical study shows that the LSTM-based path prediction can compensate for the loss of location abnormalities and is an effective sensor filtering model

A Network Coverage Information-Based Sensor Registry System for IoT Environments

The Internet of Things (IoT) is expected to provide better services through the interaction of physical objects via the Internet. However, its limitations cause an interoperability problem when the sensed data are exchanged between the sensor nodes in wireless sensor networks (WSNs), which constitute the core infrastructure of the IoT. To address this problem, a Sensor Registry System (SRS) is used. By using a SRS, the information of the heterogeneous sensed data remains pure. If users move along a road, their mobile devices predict their next positions and obtain the sensed data for that position from the SRS. If the WSNs in the location in which the users move are unstable, the sensed data will be lost. Consider a situation where the user passes through dangerous areas. If the user’s mobile device cannot receive information, they cannot be warned about the dangerous situation. To avoid this, two novel SRSs that use network coverage information have been proposed: one uses OpenSignal and the other uses the probabilistic distribution of the users accessing SRS. The empirical study showed that the proposed method can seamlessly provide services related to sensing data under any abnormal circumstance

A Feasibility Study on the Application of Basic Oxygen Furnace (BOF) Steel Slag for Railway Ballast Material

Railway ballast, for which natural crushed stone aggregates have been generally used, is an essential track component for the distribution of train loads along the rails and sleepers to the roadbed. However, the use of natural crushed stone aggregate causes environmental destruction as well as dust production in train service. This paper evaluates the feasibility of using the basic oxygen furnace (BOF) steel slag as railway ballast material. A series of physical and chemical quality tests are performed to investigate the characteristics of the materials associated with the effect of aging period due to the remaining free CaO and MgO in the BOF steel slag. Three different aging periods (i.e., 0, 3, and 6 months) are used to compare with various standards and the properties of the crushed stone aggregates. It is demonstrated that the physical and chemical properties of the BOF steel slag with different aging periods satisfy all requirements of standards sufficiently. Especially, the BOF steel slag without aging (i.e., 0 month) provides the similar physical and chemical properties, when compared to the BOF steel slag with aging (i.e., 3 and 6 months). Thus, it is possible to apply the BOF steel slag regardless of aging periods to the railway ballast materials instead of natural crushed stone aggregates