• Korean Journal of Poultry Science
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• v.50 no.1
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• pp.1-13
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• 2023

The study was carried out to investigate the effects of dietary combined supplementation of antioxidants as catechin and vitamin C on growth performance, meat quality, blood profiles and stress responses of broilers exposed to high temperature. For this experiment, a total of 360 21-day-old male Ross 308 broilers were used. Treatments were assigned with 6 replicates per treatment and 10 birds per replicate in a 2 × 3 factorial design with vitamin C (0, 250 mg/kg) and catechin (0, 600, 1,200 mg/kg). The heat stress environment was maintained at temperature 32±1℃ and relative humidity 60±5% for 24 hours until the end of the experiment. The supplemented antioxidants had no significant difference in weight gain, feed intake and feed conversion ratio (P>0.05). The content of total cholesterol in blood had no interaction, but decrease (P<0.01) in the supplemented catechin group. Also, the supplementation with catechin showed increase in the SOD activity of blood, and lower corticosterone and IgM levels of broilers. The contents of HSP70 and MDA in liver decrease (P<0.05) with the supplementation of antioxidants, and HSP70 showed an interaction between groups. DPPH radical scavenging ability in breast meat increased (P<0.01) in catechin, but meat quality did not show difference according to treatments. Respiratory rate decreased (P<0.05) in catechin, but no interaction with vitamin C. In conclusion, the combination of vitamin C and catechin can alleviate stress under high temperature, such as HSP70 and MDA, but further study on the optimal supplemental level is needed.

• (The) Research of the performance art and culture
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• no.19
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• pp.161-190
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• 2009

This study presents matters of how to analyse the dance of artistic form on the course of transforming folk art to be separated from leisure to become the art form. In particular, the traditional art of dance in Korea has been of collective act like dureh, rather than of individual art, that it had to choose the repeated style of same form and rhythm. In this respect, before it can be said that the dance in its own form became more sophisticated and adopted the artistic segment in the time of modernisation, it is viewed that in the very heart of folk dance there was sufficient ability of artistic material to seek its own right. In this regard, the artistic transformation of seoljanggo nori into seoljanggo dance is an art form which is found in Korea, and expressing rhythm and playfulness is evident and sought attention. Therefore this study puts its importance in analysing how, in the aspect of the course of life of traditional arts, dance is formed in its own right and developed a form of art from fun entertainment. I have chosen, among them, seoljanggo, which used to be a form of fun entertainment and later transformed into a form of art on stage, in particular LeeGyeongh wa seoljanggo dance which maintains the style of Honam Udo farmers' music, and tried to read the text from it. It has resulted in that, Lee Gyeonghwa seoljanggo dance did a new try on tradition, in its development of expressing art through dance and onto more technical sophistication, found in the style of tune and choreography fused into its distinctive form. The art of traditional dance concerns here that seoljanggo has changed from agrarian entertainment to modern stage art, which shows how tradition can be adopted to the contemporary cultural life or to be reinvented to the needs of the aesthetic style that the current society consumes. Thus, it is necessary to think about its role in education and to represent cultural creativity from local developments.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1041-1043
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• 1993

Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)＋dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• (The) Research of the performance art and culture
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• no.38
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• pp.349-383
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• 2019

This discussion is focused on Donghaeanbyulsingut's 'gutchum-pan to pray'. 'Gutchum-pan to pray' is repeated in almost all of the geori in Byulsingut, so it is a crucial chum-pan that can never be disregarded in understanding Byulsingutchum. Meanwhile, it supposes that Donghaeanbyulsingut is grounded on the activity of producing 'praying (words) and dance (motions)' within its relationship with the structure of capitalistic society along with the context of traditional rituals. The motion that is newly generated as a response to the concrete expression of 'praying' conducted by a mudang (a shaman), that is, the expression coming from the inside associated with the praying is seen as gutchum. This dance is bound to be in competition and interest among shaman groups, and they tend to influence one another. If praying leads to dance, a mudang can gain profits from capital as well as the value of labor. When the mudang succeeds in forming a bigger bond of sympathy with her praying, the object of praying gets more eager to select byulbi and dances a heoteunchum (impromptu dance) more vigorously. This means that a mudang's ability to perform a ritual is associated with the object of praying's consumption. With his impromptu motions, the object of praying comes to go into 'the field of consumption' within the structure of capitalistic competition before he is aware of it. Behind the communication that praying leads to dance, a lot of things are associated with one another organically. 'Gutchum-pan to pray' is generated by the continuous movement of diversity and unity that the time has within the ritual of the mudang and the object of praying. It continues to create the future 'self' that is different from the present 'self', and it means that he expects variability from the present 'self' through 'gutchum-pan to pray'. The mudang also prays for him arranging the variability of the other (the object of praying) inside her labor. In a big picture, of course, the mudang expects the variability of herself, too, which is connected to the value of her labor. The variability that they expect forms a crucial axis that determines where the flow of time and space that the 'gutchum-pan to pray' has is directed to. The contents of praying are directly related with the villagers' lives, and what leads to dance is mostly related with their jobs. This implies that what the mudang experiences in her everyday consuming activity is directly associated with the villagers' activity for earning money. In other words, the contents of that praying change constantly according to the flow of capitalistic economy. Also, those striving to respond to it before anyone else also expect better life for them by substituting their self to the 'gutchum-pan to pray' eagerly. If so, who are the ones that generate 'gutchum-pan to pray'? This can be understood through relationship among mudangs, relationship between the mudang and villagers, and also relationship among villagers. Their relationships can never be free from the concepts like labor in capitalistic society, consumption and expenditure, or time; therefore, they come to compete with the other, the present self, or the better self within the diverse relationships. This gets to be expressed in any ways, words or motions. And the range that covers the creation of either group or individual 'gutchum-pan to pray' in the village is the village community. Outside the range, it is upsized to the competition of the village unit, so individual praying may become diminished more easily. Although mudangs pray in each geori, it does not mean all praying leads to dance. Within various relationships between mudangs and villagers, 'gutchum-pan to pray' comes to be generated, repeated, and extinct. As it is mitigated to more positive competition, it does not lead to gutchum any longer. In other words, repeating 'gutchum-pan to pray' previously created has turned the object of praying into the state different from the former. Also, the two groups both have experienced the last step of Byulsingut, and at that point, praying does no longer lead to dance. In other words, from the position of the shaman group, it is the finish of their labor time and ritual performance, and from the perspective of the villagers, it means the finish of consuming activity and participation in a ritual. The characteristics of 'gutchum-pan to pray' can be summarized as follows. First, it goes through the following process: competition in the village group → competition in the group → competition among individuals. Second, repeated praying does not lead to 'gutchum'. Third, in the cases of praying for each of the occupation groups, the mudang can induce a bond of sympathy from the objects of praying directly, and this lead to dance. Fourth, the group that fails in being included in the category of praying gets to be alienated from 'gutchum-pan to pray' repeatedly.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.47-67
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• 2017

Steel plate faults is one of important factors to affect the quality and price of the steel plates. So far many steelmakers generally have used visual inspection method that could be based on an inspector's intuition or experience. Specifically, the inspector checks the steel plate faults by looking the surface of the steel plates. However, the accuracy of this method is critically low that it can cause errors above 30% in judgment. Therefore, accurate steel plate faults diagnosis system has been continuously required in the industry. In order to meet the needs, this study proposed a new steel plate faults diagnosis system using Simultaneous MTS (S-MTS), which is an advanced Mahalanobis Taguchi System (MTS) algorithm, to classify various surface defects of the steel plates. MTS has generally been used to solve binary classification problems in various fields, but MTS was not used for multiclass classification due to its low accuracy. The reason is that only one mahalanobis space is established in the MTS. In contrast, S-MTS is suitable for multi-class classification. That is, S-MTS establishes individual mahalanobis space for each class. 'Simultaneous' implies comparing mahalanobis distances at the same time. The proposed steel plate faults diagnosis system was developed in four main stages. In the first stage, after various reference groups and related variables are defined, data of the steel plate faults is collected and used to establish the individual mahalanobis space per the reference groups and construct the full measurement scale. In the second stage, the mahalanobis distances of test groups is calculated based on the established mahalanobis spaces of the reference groups. Then, appropriateness of the spaces is verified by examining the separability of the mahalanobis diatances. In the third stage, orthogonal arrays and Signal-to-Noise (SN) ratio of dynamic type are applied for variable optimization. Also, Overall SN ratio gain is derived from the SN ratio and SN ratio gain. If the derived overall SN ratio gain is negative, it means that the variable should be removed. However, the variable with the positive gain may be considered as worth keeping. Finally, in the fourth stage, the measurement scale that is composed of selected useful variables is reconstructed. Next, an experimental test should be implemented to verify the ability of multi-class classification and thus the accuracy of the classification is acquired. If the accuracy is acceptable, this diagnosis system can be used for future applications. Also, this study compared the accuracy of the proposed steel plate faults diagnosis system with that of other popular classification algorithms including Decision Tree, Multi Perception Neural Network (MLPNN), Logistic Regression (LR), Support Vector Machine (SVM), Tree Bagger Random Forest, Grid Search (GS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The steel plates faults dataset used in the study is taken from the University of California at Irvine (UCI) machine learning repository. As a result, the proposed steel plate faults diagnosis system based on S-MTS shows 90.79% of classification accuracy. The accuracy of the proposed diagnosis system is 6-27% higher than MLPNN, LR, GS, GA and PSO. Based on the fact that the accuracy of commercial systems is only about 75-80%, it means that the proposed system has enough classification performance to be applied in the industry. In addition, the proposed system can reduce the number of measurement sensors that are installed in the fields because of variable optimization process. These results show that the proposed system not only can have a good ability on the steel plate faults diagnosis but also reduce operation and maintenance cost. For our future work, it will be applied in the fields to validate actual effectiveness of the proposed system and plan to improve the accuracy based on the results.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Clinical and Experimental Pediatrics
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• v.52 no.11
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• pp.1267-1272
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• 2009

Purpose:We examined the ability of preschool aged children to meet the American Thoracic Society (ATS) and European Resiratory Society (ERS) goals for spirometry quality and tried to find out the major factor for improving the rate of success of spiromety test in this age group. Methods:Spirometry was performed in 2-6 aged 155 children with chronic cough or suspicious asthma with the recording of maneuver quality measures of forced expiratory time, end-of-test volume, back-extrapolated volume (Vbe), and forced vital capacity (FVC), as well as flow-volume curve. The subjects were tested several times and the two best results in each subject were selected. All criteria for quality control were suggested by ATS/ERS guidelines. The criteria for starting of the test was Vbe <80 mL and Vbe/FVC <12.5%. The criteria for repeatability of the test was that second highest FVC and FEV1 are within 100 ml or 10% of the highest value, whichever is greater. For the criteria for termination of the test for preschool aged children, we evaluated the flow-volume curve Results:As getting older, the success rate of spirometry increased and rapidly increased after 3 years old. Total success rate of the test was 59.4% (2 years old - 14.3%, 3 years old - 53.7%, 4 years old - 65.1%, 5 years old - 69.7%, 6 years old- 70.8%). The percentage of failure to meet the criteria for starting the test was 6.5%, repeatability of the test was 12.3% and end of the test was 31%. There was a significant difference only in age between success group and failure group. Evaluating the quality control criteria of previous studies, the success rate increased with age. Conclusion:About 60% of preschool aged children met ATS/ERS goals for spirometry test performance and the success rate was highly correlated with age. It is clearly needed that developing more feasible and suitable criteria for quality control of spirometry test in preschool aged children.

• The Korean Journal of Pesticide Science
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• v.2 no.3
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• pp.107-116
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• 1998

Based on the differential growth response to exogenous gibberellic acid ($GA_{3}$) between semi-dwarf wheat(Triticum aestivum) and wild oat(Avena fatua), we examined the possibility of improving the selective performance of several herbicides by $GA_{3}$ application and the physiological background of $GA_{3}$-induced increase in herbicidal activity. Growth of wild oat was 4 to 5 times higher than that of wheat by $GA_{3}$ treatment. Pretreatment of wild oat seed with 300 ppm $GA_{3}$ increased the herbicidal activities of trifluralin and isoproturon by soil-surface application, but not of alachor and metsulfuron-methyl. $GA_{3}$ applied simultaneously with post-emergence herbicides resulted in a significant or moderate improvement of the efficacy of such herbicides as tralkoxydim, fenoxaprop-ethyl, metsulfuron-methyl, metribuzine and isoproturon, but not in the mixtures of oxyfluorfen or paraquat with $GA_{3}$. In the sequencial treatment of tralkoxydim and $GA_{3}$ at interval of one-day, $GA_{3}$ applied prior to tralkoxydim significantly increased a chlorosis and desiccation of leaf without affecting the growth inhibition by tralkoxydim. Tralkoxydim followed by $GA_{3}$ application had lower herbicidal activity than that of $GA_{3}$ followed by tralkoxydim treatment. Electrolyte leakage response of $GA_{3}$-pretreated or $GA_{3}$-untreated wild oat leaf against several compounds inducing membrane. peroxidation was compared. Differencial responses were observed in oxyfluorfen and isoproturon treatments with an increased electrolyte leakage in $GA_{3}$-pretreated tissue, but not in paraquat and rose bengal treatments. These results suggest that $GA_{3}$-induced increase in herbicidal activity is likely to be dependent on a herbicide type and may be due to activation of a metabolic ability related with herbicidal reponse as well as an increase in the herbicide absorbtion and translocation, rather than due to membrane and cell wall extention induced by $GA_{3}$, which in turn makes the herbicides easily enter.