김상희 교수

This paper describes a six-stage methodology for developing ontologies for engineering design, together with the research methods and evaluation of each stage. The methodology focuses upon understanding a user’s domain models through empirical research. A case study of an ontology for searching, indexing, and retrieving engineering knowledge is described. The root concepts of the ontology were elicited from engineering designers. Relationships between concepts are extracted as the ontology is po

This study combines electroencephalogram (EEG) with virtual reality (VR) technologies to measure the EEG responses of users experiencing changes to architectural elements. We analyze the ratio of alpha to beta waves (RAB) indicators to determine the pre- and poststimulation changes. In our methodology, thirty-three females experience using private rooms in a postpartum care center participated in the experiment. Their brain waves are measured while they are experiencing the VR space of a private

In this article, a reactively sputtered aluminum nitride (AlN) piezoelectric film and its application for a film bulk acoustic resonator (FBAR) device are presented. The FBAR is composed of an AlN film sandwiched between top aluminum (Al) and bottom gold (Au) electrodes and an acoustic reflector block of SiO2/W stacked multilayers. Both the top and bottom electrodes are connected by a transmission line. The insertion loss (S21) and return loss (S11) were 6.1 and 37.19 dB, respectively. Using the

This paper presents an approach of exploiting contexts that are available within design environments in order to improve the understanding of the information needs of a designer. The idea is that such contexts allow reuse tools to acquire information relevant to a designer’s current task and this will increase the relevance of retrieved information. A focus is given on the dynamic features of a design process that often mean that a reuse attempt is opportunistic and task-dependent. Current reuse

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This experimental study was conducted to evaluate the impact behavior of relatively rigid projectiles with conical and hemispherical nose shapes on normal to high-strength and ultrahigh performance concrete (UHPC). For this impact experiment, target specimens with dimensions of 200 200 100 mm and concrete compressive strengths of 35, 80, 100, 120, and 150 MPa were used. The test results showed that as the concrete strength increased, the penetrability of concrete normalized by the kinetic energy

This experimental research aims to evaluate the impact resistance of the crimped wire mesh‐ and steel fiber‐reinforced concrete panels that receive the impact load of the high‐velocity projectile. The concrete panel's impact resistance was evaluated by using variables such as the steel fiber volume fraction, presence of crimped wire‐mesh reinforcement, thickness of panel, impact velocity, and the size of aggregates. The impact resistance was evaluated by using the nondimensional impact factor wh

Bragg reflector thin film resonators (TFR's) using AlN reactively sputtered at room temperature were investigated. The Bragg reflector TFR is composed of a piezoelectric aluminium nitride thin film, electrodes of Al (1500 /spl Aring/) on both sides and reflector layers of an Al-AlN pair. The resonator has a fundamental resonance at 2.81 GHz with a return loss of 3.07 dB.

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A modified procedure of a previous synthetic route for baicalein was developed in order to obtain more than ten grams of baicalein for in vivo test. There were several difficulties in applying the published experimental procedures for a large scale of synthesis. The modified synthetic work was successfully accomplished by reducing amount of strong Lewis acid in Fries rearrangement and using tetrabutylammonium iodide as an additive to speed up the demethylation reaction in refluxing HBr into comp

This study aims to predict the compressive strength of concrete using a machine-learning algorithm with linear regression analysis and to evaluate its accuracy. The open-source software library TensorFlow was used to develop the machine-learning algorithm. In the machine-earning algorithm, a total of seven variables were set: water, cement, fly ash, blast furnace slag, sand, coarse aggregate, and coarse aggregate size. A total of 4297 concrete mixtures with measured compressive strengths were em