• Journal of the Korean Home Economics Association
• /
• v.38 no.12
• /
• pp.29-45
• /
• 2000

The purposes of this study were to determine what factors influence risk perceptions of females and males for milk produced using food-related biotechnology, to test whether risk perceptions or other factors influence self-protection actions and to estimate milk demand response in light of self-protection actions and other economic and demographic factors. The expected utility model was applied to explain the way consumers would take self-protection actions regarding risk perceptions and to drive milk demand. Telephone interviews were conducted and the data were collected from households(females=1,029, males=437) nationwide in the U.S. And the data were analyzed by Heckman two-step method using the software package LIMDEP. Risk perceptions were found to be influenced not by demographic factors but by outrage factors as well as attitudinal factors in both females and males, although some factors were different. In addition, risk perceptions and labeling availability were found to significantly influence self-protection actions in both groups. Furthermore, as an important concern in this study, self-protection action was found to significantly influence milk demand in only male group, implying a consistent behavior of males. Also milk price and household size were found to significantly influence milk demand in both groups. In fact, the results did demonstrate that labeling availability significantly influenced self-protection actions. That is, in markets where labeled laternatives were present, concerned consumers were more likely to self protect by substituting to these products. A policy implication of this result is that labeling food products produced using biotechnology enhances consumer choice. Hence, consumer could express a more accurate demand response and reduce the perceived food safety risk. Furthermore, education for females might be necessary to have a consistent behavior because self-protection action did not significantly influence female's milk demand, though they have greater risk perceptions than males have.

• IEIE Transactions on Smart Processing and Computing
• /
• v.1 no.3
• /
• pp.192-200
• /
• 2012

In order for humans and robots to interact in daily life, robots need to understand human speech and link it to their actions. This paper proposes a hierarchical behavior model for robot action control using natural language commands. The model, which consists of episodes, primitive actions and atomic functions, uses a sentential cognitive system that includes multiple modules for perception, action, reasoning and memory. Human speech commands are translated to sentences with a natural language processor that are syntactically parsed. A semantic parsing procedure was applied to human speech by analyzing the verbs and phrases of the sentences and linking them to the cognitive information. The cognitive system performed according to the hierarchical behavior model, which consists of episodes, primitive actions and atomic functions, which are implemented in the system. In the experiments, a possible episode, "Water the pot," was tested and its feasibility was evaluated.

• Steel and Composite Structures
• /
• v.3 no.2
• /
• pp.111-122
• /
• 2003

The paper presents a model for analysing the shear-lag effect on the slab of twin-girder composite decks subjected to static actions, support settlements and concrete shrinkage, which are the main actions of interest in composite bridge design. The proposed model includes concrete creep behaviour and shear connection flexibility. The shear-lag in the slab is accounted for by means of a new warping function. The considered actions are then applied to a realistic bridge deck and their effects are discussed. The proposed method is utilised to determine the slab effective widths for three different width-length ratios of the deck. Finally, a comparison between the results obtained with the Eurocode EC4-2 and those obtained with the proposed model is performed.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.30 no.11 s.254
• /
• pp.1348-1357
• /
• 2006

In a hybrid three-layer control architecture(deliberative, sequencing, and reflexive), the lowest reflexive layer consists of resources, actions, an action coordinator, and motion controllers. Because the execution of individual components in the reflexive layer should be done in real-time, each component has to be simple and, due to this reason, the Linux-RTAI(Real-Time Application Interface for Linux) has been used as an operating system. In this paper, a navigation control architecture, which combines the components in the reflexive layer and the navigation-related modules in the sequencing layer, is proposed. And then, as basic components, four actions(Goto, Avoid, Move, and EmergencyStop) are designed. Experimental results confirm the effectiveness of the proposed architecture and the performance of individual associated actions.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.10
• /
• pp.1731-1737
• /
• 2016

In this paper, a method is proposed to recognize human actions as nonverbal expression; the proposed method is composed of two steps which are action representation and action recognition. First, MHI(Motion History Image) is used in the action representation step. This method includes segmentation based on depth information and generates spatio-temporal templates to describe actions. Second, CNN(Convolution Neural Network) which includes feature extraction and classification is employed in the action recognition step. It extracts convolution feature vectors and then uses a classifier to recognize actions. The recognition performance of the proposed method is demonstrated by comparing other action recognition methods in experimental results.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2007.12a
• /
• pp.79-80
• /
• 2007

An expert system of collision avoidance developed by CLIPS and Visual C++ is continuously introduced in this paper. Further, a simulation function of collision avoidance is added to the expert system, the function can simulate the avoidance actions of own ship and a specific target of a period of future time. This function can help navigators to estimate collision risk and make proper collision avoidance actions in dangerous situations for navigational safety of ships. Furthermore, navigational rules can also be evaluated during the process of simulation.

• Wind and Structures
• /
• v.12 no.5
• /
• pp.425-439
• /
• 2009

The expediency of revising universal rules for the combination of gravity and lateral actions of wind force-resisting steel structures recommended by the Standards EN 1990 and ASCE/SEI 7-05 is discussed. Extreme wind forces, gravity actions and their combinations for the limit state design of structures are considered. The effect of statistical uncertainties of extreme wind pressure and steel yield strength on the structural safety of beam-column joints of wind force-resisting multistory steel frames designed by the partial factor design (PFD) and the load and resistance factor design (LRFD) methods is demonstrated. The limit state criterion and the performance process of steel frame joints are presented and considered. Their long-term survival probability analysis is based on the unsophisticated method of transformed conditional probabilities. A numerical example illustrates some discrepancies in international design standards and the necessity to revise the rule of universal combinations of loads in wind and structural engineering.

• Journal of Pharmaceutical Investigation
• /
• v.15 no.1
• /
• pp.22-31
• /
• 1985

The influence of some sympathetic blocking agents on pressor actions of norepinephrine and angiotensin was investigated in rabbits. 1. Phentolamine, sympathetic ${\alpha}-blocking$ agent, blocked the pressor action of norepinephrine, but did not affect the pressor action of angiotensin 2. Chlorisondamine, autonomic ganglionic blocking agent, potentiated the both actions of norepinephrine and angiotensin. 3. Guanethidine, bethanidine and debrisoquine, sympathetic neuronal blocking agents, potentiated the action of norepinephrine, while diminished that of angiotensin. 4. Reserpine, norepinephrine depleting agent, increased the pressor response of norepinephrine, but did not influence the pressor action of angiotensin.

• Bulletin of the Korean Mathematical Society
• /
• v.42 no.4
• /
• pp.807-815
• /
• 2005

Let R be a ring with identity, X the set of all nonzero, nonunits of Rand G the group of all units of R. We will consider two group actions on X by G, the regular action and the conjugate action. In this paper, by investigating two group actions we can have some results as follows: First, if G is a finitely generated abelian group, then the orbit O(x) under the regular action on X by G is finite for all nilpotents x $\in$ X. Secondly, if F is a field in which 2 is a unit and F $\backslash\;\{0\}$ is a finitley generated abelian group, then F is finite. Finally, if G in a unit-regular ring R is a torsion group and 2 is a unit in R, then the conjugate action on X by G is trivial if and only if G is abelian if and only if R is commutative.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.4
• /
• pp.2093-2108
• /
• 2017

In this paper, we describe a novel method for recognizing human actions from different views via view knowledge transfer. Our approach is characterized by two aspects: 1) We propose a unsupervised topic transfer model (TTM) to model two view-dependent vocabularies, where the original bag of visual words (BoVW) representation can be transferred into a bag of topics (BoT) representation. The higher-level BoT features, which can be shared across views, can connect action models for different views. 2) Our features make it possible to obtain a discriminative model of action under one view and categorize actions in another view. We tested our approach on the IXMAS data set, and the results are promising, given such a simple approach. In addition, we also demonstrate a supervised topic transfer model (STTM), which can combine transfer feature learning and discriminative classifier learning into one framework.