The author is the first man who tried to use an anesthetic on insect specially for silkworm in orde to evaluate the silkworm health and silk yielding ability and the obtained results are as followings. 1. The necessary ether vapor induction for narcosis on silkworms is varied by the glowth of the silkworm which the larger worm is, the longer induction is required. For instance, it was 2∼3 minutes for the worms of third day fifth instar silkworm in case use of ether anesthetic. 2. The longer anesthetic induction for silkworms, the longer recovery needs from anesthesia. In case five minutes ether vapor induction, silkworms recovered narcosis during in 5∼130 minutes which had varied very much by the health variation. 3. The ether induction caused silkworm to vomit digestive juice from a few per cent of the worms, but the chloroform induction showed majority of the worms to vomit the digestive juice out of mouth. So, the ether was found as better anesthetic for silkworms. 4. When ether induction last more than 20∼30 minutes, the recovered silkworms can eat mulberry, but when it gets more than three hours they can not eat mulberry. And when it last more than ten minutes, the silkworm may eat mulberry leaf, but they can not spinn cocoon properly. 5. In case five minutes ether induction for silkworms on third day fifth instar, the stronger variety is, the rallier recovered from narcosis. 6. The recovering duration from narcosis varies regarding with each worm health which shows Poisson′s distribution even in a same variety silkworm. 7. The female worms recover from narcosis earlier than male worms which means the female worm is stronger than male one. 8. The later recovered silkworm from narcosis spinned more rich cocoon silk and ended with smaller pupae weight. Such a tendency showed until at some recovery duration, then the silk yield droped down on the worms recovered in more longer duration. The author (Choe) had named such a relation curve as "Silk Yield Curve against Silkworm Health." 9. The silk yield or cocoon layer ratio had varied from 13 to 27% even in a same worm varity cocoon which showed serious variation and call attention carefulness for the duplication work of a variety silkworm eggs. 10. Not always the rich silk yielding worm is the best worm during the silkworm selection and it should be considered with the silkworm health evaluation. 11. At present situation, only specific breeding expert is allowed to join in the selection service because of need many years experience by use of visual observation, but the ether anesthesia method may help such an evaluation with more accuracy and easy way even for the people in fresh on the field. 12. The effect of the narcosis on the silkworm for the next generation or hybrid worm will be reported in next publication.
The weak foundation of the computing environment caused information leakage and hacking to be uncontrollable, Therefore, dynamic control of security threats and real-time reaction to identical or similar types of accidents after intrusion are considered to be important, h one of the solutions to solve the problem, studies on intrusion detection systems are actively being conducted. To improve the anomaly IDS using system calls, this study focuses on neural networks learning using the soundex algorithm which is designed to change feature selection and variable length data into a fixed length learning pattern, That Is, by changing variable length sequential system call data into a fixed iength behavior pattern using the soundex algorithm, this study conducted neural networks learning by using a backpropagation algorithm. The backpropagation neural networks technique is applied for anomaly detection of system calls using Sendmail Data of UNM to demonstrate its performance.
Journal of Korean Society of Industrial and Systems Engineering
/
v.12
no.20
/
pp.123-138
/
1989
The primary objective of the agency research in the game theory lives in the maintenance of Pareto is optimal condition for the optimal incentive contract. The basic concepts which are related to this objective are reviewed in connection with the general assumptions to model it, the moral hazard and adverse selection which arised from the information asymmetry, and finally the problem of risk distribution. The demand for auditing and the role of auditor have been addressed by ASOBAC. Issues which an auditor is explicitly introduced in a principal-agent framework have been addressed in this paper. These issues must be confronted to appropriately with the auditor, and to achieve an adequate understanding of optimal confronting arrangement with the auditor. The first step in introducing an auditor into this analysis is to examine the game-theoretic foundation of such a expended agency model. The Mathematical program formulated may not yield solution that are resonable. This arises because the program may call for the auditor and manager to play dominated Nash equilibra in some subgame. The nontrivial natures of the subgame implies that randomized strategies by the auditor and manager nay be of crucial importance. The possibilities for overcoming the randomized strategy problem were suggested; change the rule of the game and or impose covexity condition. The former seems unjustifiable in on auditing context, and the latter promising but difficult to achieve. The discussion ended with an extension of the revelation principle to the owner manager-auditor game, assuming strategies. An examination of the restriction and improvement direction of the basic concept of agency theory was addressed in the later part of this paper. Many important aspects of auditor incentives are inherently multiple-agent, multiple-period, multiple-objectine, phenomena and require further analyses and researches.
Journal of the Institute of Electronics Engineers of Korea SP
/
v.45
no.4
/
pp.107-114
/
2008
In this paper, we constructed a speech emotion recognition system that classifies four emotions - neutral, happy, sad, and anger from speech based on male/female gender discrimination. At first, the proposed system distinguish between male and female from a queried speech, then the system performance can be improved by using separate optimized feature vectors for each gender for the emotion classification. As a emotion feature vector, this paper adopts ZCPA(Zero Crossings with Peak Amplitudes) which is well known for its noise-robustic characteristic from the speech recognition area and the features are optimized using SFS method. For a pattern classification of emotion, k-NN and SVM classifiers are compared experimentally. From the computer simulation results, the proposed system was proven to be highly efficient for speech emotion classification about 85.3% regarding four emotion states. This might promise the use the proposed system in various applications such as call-center, humanoid robots, ubiquitous, and etc.
Kim, Seung-Yeon;Kim, Se-Jin;Lee, Hyong-Woo;Ryu, Seung-Wan;Cho, Choong-Ho
The Journal of Korean Institute of Communications and Information Sciences
/
v.35
no.4A
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pp.394-400
/
2010
Mobile Multi-hop Relaying (MMR) system can provide increased system capacity of wireless access network by coverage extension and enhanced transmission rate within the Base Station (BS) coverage area. The previous researches for the MMR system with a non-transparent mode Relay Station (RS) do not consider channel selection procedure of Mobile Station (MS), co-channel interference and Multi-hop Relay Base Station (MR-BS) coverage and RS coverage ratio in MMR system. In this paper, we investigate the performance of MMR uplink system in multicell environments with various topologies. The performance is presented in terms of call blocking probability, channel utilization, outage probability and system throughput by varying offered load. It is found that, for certain system parameters, the MMR uplink system achieve the maximum system throughput when MR-BS coverage to RS coverage ratio is 7.
Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.
One faces four major developmental tasks to achieve in young adulthood, ages between 20 and 40 : intimacy, vocation, marriage and child-rearing. Intimacy is the capacity to commit oneself to concrete affiliations and partnerships and to develop the ethical strength to abide by such commitments, even though they call for significant sacrifices and compromises. Through vocation and marriage young adults become united to networks of persons, find tasks that demand involvement, and gain roles into which they fit and are fitted and which help define their identities. An occupation represents much more than a set of skills and functions : it means a way of life. The extent of vocational choice increases with educational level, and the unconscious factors are frequency the decisive element. The vocational choice stare with fantasy choices in childhood, passes through tentative choices in adolescence, realistic choices in college days, and crystallized choices in post-college days, and finally ends up to the choice of specification. Along with the hazards and the need for realignment of personality functioning, the marriage brings with it new opportunities for self-fulfillment and completion. Motives other than a romantic love gain more importance in the decision to marry and in the choice of a partner. The impulsions to marry are sexual gratification, the desire to propagate, narcissistic gratification, and a need of interdependence. Many factors such as oedipal wishes, sexuality and sexual attractions, socio-economic classes, and geography involve in selection of marriage partner. There are also various motivations to marry a romantic love, the desire for a home of one's own, sexual attractions, the wish for security and a shelter, and the wish for children. The hostile marriage, the marriage on the rebound, the marriage rooted in rescue fantasies, and sado-masochistic marriage are the examples of pathological marriages. A successful marriage will usually both Lead to and require a marked reorganization of the personality structure of each partner that will influence the lurker personality development of each. Many marital problems are largely dependent upon the personality characteristics of one partner which might well create difficulties no manor who was the spouse.
Journal of the Institute of Electronics Engineers of Korea SC
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v.43
no.6
s.312
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pp.1-8
/
2006
Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done recently. Informations from various sensors can be used to find obstacles and plan feasible path. In spite of many solutions of finding optimal path, each can be applied in only a constrained condition. This means that it is difficult to find university good algorithm. An optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose an algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers and cumulative numbers. It has an advantage of fast planning time and completeness of path if one exists. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in dynamic environments. Using the information of the start and destination position, the RAS can be performed for collision-free navigation by reforming feasible paths repeatedly in dynamic environments.
Journal of the Korea Institute of Information Security & Cryptology
/
v.30
no.6
/
pp.1013-1021
/
2020
Malware Authorship Attribution is a research field for identifying malware by comparing the author characteristics of unknown malware with the characteristics of known malware authors. The authorship attribution method using binaries has the advantage that it is easy to collect and analyze targeted malicious codes, but the scope of using features is limited compared to the method using source code. This limitation has the disadvantage that accuracy decreases for a large number of authors. This study proposes a method of 'Defining semantic features from binaries' and 'Defining allowable ranges for redundant features using the concept of survival network' to complement the limitations in the identification of binary authors. The proposed method defines Opcode-based graph features from binary information, and defines the allowable range for selecting unique features for each author using the concept of a survival network. Through this, it was possible to define the feature definition and feature selection method for each author as a single technology, and through the experiment, it was confirmed that it was possible to derive the same level of accuracy as the source code-based analysis with an improvement of 5.0% accuracy compared to the previous study.
To advance the effectiveness of the current Hanwoo improvement system, we developed a general simulation that compared a series of breeding schemes under realistic user circumstances. We call this system the Integrated General Model (IGM) and it allows users to control the breeding schemes and selection methods by manipulating the input parameters. The Current Hanwoo Performance and Progeny Test (CHPPT) scheme was simulated with a Modified Hanwoo Performance and Progeny Test (MHPPT) scheme using a Hanwoo Breeding Farm cow population of the Livestock Improvement Main Center (LOMC) of the National Agricultural Cooperatives Federation (NACF). To compare the two schemes, a new method, the Simple Hanwoo Performance Test (SHPT), which uses ultrasound technology for measuring the carcass traits of live animals, was developed. These three models, including the CHPPT, incorporated three types of selection criteria: phenotype (PH), true breeding value (TBV), and estimated breeding value (EBV). The simulation was scheduled to mimic an actual Hanwoo breeding program; thus, the simulation was run to include the years 1983-2020 for each breeding method and was replicated 10 times. The parameters for simulation were derived from the literature. Approximately 642,000 animals were simulated per replication for the CHPPT scheme; 129,000 animals were simulated for the MHPPT scheme and 112,000 animals for the SHPT scheme. Throughout the 38-year simulation, all estimated parameters of each simulated population, regardless of population size, showed results similar to the input parameters. The deviations between input and output values for the parameters in the large populations were statistically acceptable. In this study, we integrated three simulated models, including the CHPPT, in an attempt to achieve the greatest genetic gains within major economic traits including body weight at 12 months of age (BW12), body weight at 24 months of age (BW24), average daily gain from 6 to 12 months (ADG), carcass weight (CWT), carcass longissimus muscle area (CLMA), carcass marbling score (CMS), ultrasound scanned longissimus muscle area (ULMA), and ultrasound scanned marbling score (UMS).
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