• The Korean Journal of Physiology
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• v.20 no.1
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• pp.53-63
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• 1986

Carbon monoxide(CO) poisoning has been one of the major environmental problems because of the tissue hypoxia, especially brain tissue hypoxia, due to the great affinity of CO with hemoglobin. Inhalation of the pure oxygen$(0_2)$ under the high atmospheric pressure has been considered as the best treatment of CO poisoning by the supply of $0_2$ to hypoxic tissues with dissolved from in plasma and also by the rapid elimination of CO from the carboxyhemoglobin(HbCO). Hydrogen peroxide $(H_2O_2)$ was rapidly decomposed to water and $0_2$ under the presence of catalase in the blood, but the intravenous administration of $H_2O_2$ is hazardous because of the formation of methemoglobin and air embolism. However, it was reported that the enema of $H_2O_2$ solution below 0.75% could be continuously supplied $0_2$ to hypoxic tissues without the hazards mentioned above. This study was performed to evaluate the effect of $H_2O_2$ enema on the elimination of CO from the HbCO in the recovery of the acute CO poisoning. Rabbits weighting about 2.0 kg were exposed to If CO gas mixture with room air for 30 minutes. After the acute CO poisoning, 30 rabbits were divided into three groups relating to the recovery period. The first group T·as exposed to the room air and the second group w·as inhalated with 100% $0_2$ under 1 atmospheric pressure. The third group was administered 10 ml of 0.5H $H_2O_2$ solution per kg weight by enema immediately after CO poisoning and exposed to the room air during the recovery period. The arterial blood was sampled before and after CO poisoning ana in 15, 30, 60 and 90 minutes of the recovery period. The blood pH, $Pco_2\;and\;Po_2$ were measured anaerobically with a Blood Gas Analyzer and the saturation percentage of HbCO was measured by the Spectrophotometric method. The effect of $H_2O_2$ enema on the recovery from the acute CO poisoning was observed and compared with the room air group and the 100% $0_2$ inhalation group. The results obtained from the experiment are as follows: The pH of arterial blood was significantly decreased after CO poisoning and until the first 15 minutes of the recovery period in all groups. Thereafter, it was slowly increased to the level of the before CO poisoning, but the recovery of pH of the $H_2O_2$ enema group was more delayed than that of the other groups during the recovery period. $Paco_2$ was significantly decreased after CO poisoning in all groups. Boring the recovery Period, $Paco_2$ of the room air group was completely recovered to the level of the before CO Poisoning, but that of the 100% $O_2$ inhalation group and the $H_2O_2$ enema group was not recovered until the 90 minutes of the recovery period. $Paco_2$ was slightly decreased after CO poisoning. During the recovery Period, it was markedly increased in the first 15 minutes and maintained the level above that before CO Poisoning in all groups. Furthermore $Paco_2$ of the $H_2O_2$ enema group was 102 to 107 mmHg and it was about 10 mmHg higher than that of the room air group during the recovery period. The saturation percentage of HbCO was increased up to the range of 54 to 72 percents after CO poisoning and in general it was generally diminished during the recovery period. However in the $H_2O_2$ enema group the diminution of the saturation percentage of HbCO was generally faster than that of the 100% $O_2$ inhalation group and the room air group, and its diminution in the 100% $O_2$ inhalation group was also slightly faster than that of the room air group at the relatively later time of the recovery period. In conclusion, the enema of 0.5% $H_2O_2$ solution is seems to facilitate the elimination of CO from the HbCO in the blood and increase $Paco_2$ simultaneously during the recovery period of the acute CO poisoning.

• Applied Microscopy
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• v.23 no.2
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• pp.27-40
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• 1993

This study was taken to examine the light microscopic and ultrastructural changes of gill and kidney of female tilapia{Oreochromis niloticus) adapted in 0%o, 10%o, 20%o, and 30%o salt concentrations, respectively, by light, scanning and transmission electron microscope. The results obtained in these experiments were summarized as follows: Gill chloride cell hyperplasia, gill lamellar epithelial separation, kidney glomerular shrinkage, blood congestion in kidneys and deposition of hyalin droplets in kidney glomeruli, tubules were the histological alterations in Oreochromis niloticus. Incidence and severity of gill chloride cell hyperplasia rapidly increased together with increase of salinity, and the number of chloride cells in gill lamellae rapidly increased in response to high external NaCl concentrations. The ultrastructure by scanning electron microscope(SEM) indicated that the gill secondary lamella of tilapia(Oreochromis niloticus) exposed to seawater, were characterized by rough convoluted surfaces during the adaptation. Transmission electron microscopy(TEM) indicated that mitochondria in chloride cells exposed to seawater, were both large and elongate and contained well-developed cristae. TEM also showed the increased chloride cells exposed to seawater. The presence of two mitochondria-rich cell types is discussed with regard to their possible role in the hypoosmoregulatory changes which occur during seawater-adaptation. Most Oreochromis niloticus adapted in seawater had an occasional glomerulus completely filling Bowman's capsule in kidney, and glomerular shrinkage was occurred higher in kidney tissues of individuals living in 10%o, 20%o, 30%o of seawater than in those living in 0%o of freshwater, and blood congestion was occurred severer in kidney tissues of individuals living 20%o, 30%o of seawater than in those living in 10%o of seawater. There were decreases in the glomerular area and the nuclear area in the main segments of the nephron, and that the nuclear areas of the nephron cells in seawater-adapted tilapia were of smaller size than those from freshwater-adapted fish. Our findings demonstrated that Oreochromis niloticus tolerated moderately saline environment and the increased body weight living in 30%o was relatively higher than that living in 10%o in spite of histopathological changes.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Journal of Chest Surgery
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• v.38 no.2 s.247
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• pp.157-163
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• 2005

Background: Clinical outcomes of esophageal cancer have not been satisfactory in spite of the development of surgical skills and protocols of adjuvant therapy. We analyzed the results of corrective surgical patients for esophageal cancer from January 1992 to July 2002. Material and Method: Among 129 patients with esophageal cancer, this study was performed in 68 patients who received corrective surgery. The ratio of sex was 59 : 9 (male : female) and mean age was $61.07\pm7.36$ years old. Chief complaints of this patients were dysphagia, epigastric pain and weight loss, etc. The locations of esophageal cancer were 4 in upper esophagus, 36 in middle, 20 in lower, 8 in esophagogastric junction. 60 patients had squamous cell cancer and 7 had adenocarcinoma, and 1 had malignant melanoma. Five patients had neoadjuvant chemotherapy. Result: The postoperative stage I, IIA, IIB, III, IV patients were 7, 25, 12, 17 and 7, respectively. The conduit for replacement of esophagus were stomach (62 patients) and colon (6 patients). The neck anastomosis was performed in 28 patients and intrathoracic anastomosis in 40 patients. The technique of anastomosis were hand sewing method (44 patients) and stapling method (24 patients). One of the early complications was anastomosis leakage (3 patients) which had only radiologic leakage that recovered spontaneously. The anastomosis technique had no correlation with postoperative leakage, which stapling method (2 patients) and hand sewing method (1 patient). There were 3 respiratory failures, 6 pneumonia, 1 fulminant hepatitis, 1 bleeding and 1 sepsis. The 2 early postoperative deaths were fulminant hepatitis and sepsis. Among 68 patients, 23 patients had postoperative adjuvant therapy and 55 paitents were followed up. The follow up period was $23.73\pm22.18$ months ($1\~76$ month). There were 5 patients in stage I, 21 in stage 2A, 9 in stage IIB, 15 in stage III and 5 in stage IV. The 1, 3, 5 year survival rates of the patients who could be followed up completely was $58.43\pm6.5\%,\;35.48\pm7.5\%\;and\;18.81\pm7.7\%$, respectively. Statistical analysis showed that long-term survival difference was associated with a stage, T stage, and N stage (p<0.05) but not associated with histology, sex, anastomosis location, tumor location, and pre and postoperative adjuvant therapy. Conclusion: The early diagnosis, aggressive operative resection, and adequate postoperative treatment may have contributed to the observed increase in survival for esophageal cancer patients.

• Korean Journal of Soil Science and Fertilizer
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• v.21 no.3
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• pp.316-338
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• 1988

To identify the physiological phenomena on the sudden wilting of japonica/indica crossed varieties, Pot experiment was carried out under the heavy N application with various levels of potassium in Japan. The results obtained are as follows. 1. Sudden wilting was occurred in both varieties used, Yushin and Milyang 23. The former showed a higher degree than the latter. 2. Sudden wilting was occurred into two types, one at early ripening stage and the other at late ripening stage. The former type was found in the field with low potassium supply and the latter was seemed to be related to varietal wilting tolerence. 3. By the investigation of concerning the effective tillering rate and the change of dry weight of each organ at the heading stage, it was inferred that the growth status from young panicle formation stage to heading stage were related to sudden wilting tolerence. 4. Manganese content at heading stage, ratio of Fe/Mn and Fe. Fe/Mn in stern at late ripening stage and $K_2$ O/N ratio of stem at harvesting stage were recognized as the specific factors in connection with sudden wilting. Mn content in the sudden wilting rice plant was already in creased remarkably at heading stage. In relation to root age and absoption characteristics of Mn, the senility of root before heading stage was inferred as the cause of increase the value of Fe/Mn or Fe. Fe/Mn. 5. The $K_2$ O/N ratio of culm at harvesting stage was lower in upper node than lower node in relation to sudden wilting. And it was well accordance with the fact that the symptoms of sudden wilting proceeded from upper leaf to lower leaf. These phenomenon was different from the usual one that the effect of potassium deficiency was more remarkable in lower node than upper node. 6. All varieties which have a condition of potassium deficiency have a high degree of nitrogen content of leaves at heading stage and the $K_2$ O/N ratio of each organ was low, Especialy, $K_2$ O/N ratio is much lower in sheath and culm than leaves.

• Journal of the Korean Arthroscopy Society
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• v.8 no.2
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• pp.82-88
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• 2004

Purpose: In this study, we intended to ascertain the benefit of KT-2000 Knee arthrometer(KT-2000) in the diagnosis of ACL(Anterior cruciate ligament) injury by comparing the anterior displacement of normal knee with that of ACL deficient knee. Materials and Methods: We designated two examiners to measure the anterior displacement of the knee joint of 30 healthy individuals, using KT-2000, at 30$^{\circ}$ flexion setting of muscle full relaxation, contraction, 25$^{\circ}$ internal rotation and 25$^{\circ}$ external rotation and analyzed these results according to the variables and measured the preoperative anterior displacement of the ACL injured knee in the 30 patients who have gone through an arthroscopic ACL reconstruction later. Results: The results of examiner 1 are 6.5${\pm}$1.5 mm, 2.5${\pm}$0.9 mm, 4.8${\pm}$1.2 mm, 6.4${\pm}$1.3 mm in right knee and 5.6${\pm}$1.3 mm, 2.1${\pm}$0.8 mm, 4.5${\pm}$1.2 mm, 5.2${\pm}$1.3 mm in left knee, in order of muscle full relaxation, contraction, 25$^{\circ}$ internal rotation and 25$^{\circ}$ external rotation. The results of examiner 2 are 6.9${\pm}$1.2mm, 2.9${\pm}$1.1mm, 5.6${\pm}$1.6mm, 6.9${\pm}$1.5mm in right, 5.5${\pm}$1.7 mm,1.9${\pm}$0.9 mm, 5.1${\pm}$1.9 mm, 5.7${\pm}$1.6 mm in left knee, The side to side difference of examiner 1 in the setting of muscle relaxation is 0.9${\pm}$1.0 mm. The anterior displaement of ACL injured knee is average 11${\pm}$2.93 mm and difference of average 6.5${\pm}$2.31 mm form that of normal. In comparison between the right and left knees of healthy individuals, the both results of two examiners showed the statistical difference in the setting of muscle full relaxation but, the results showed the side to side difference below 2 mm in 25case(83%), 21case(70%) respectively and above 3 mm in just 1 case. In the comparison between the normal and ACL injured knees, the results show the statistical difference of the side to side difference in the setting of muscle relaxation(p<0.05). Conclusion: The KT-2000 result is affected by relaxation of muscles around knee, flexion angle of knee joint, rotation of tibia, the strength of displacing force, time of the test and physical factors as height and weight. However, the Accuracy of diagnosis of ACL injury by KT-2000 will increase if the examiner is skillful and the tests are made on the exact position of knee joint.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.139-156
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• 2021

The biggest reason for using a deep learning model in image classification is that it is possible to consider the relationship between each region by extracting each region's features from the overall information of the image. However, the CNN model may not be suitable for emotional image data without the image's regional features. To solve the difficulty of classifying emotion images, many researchers each year propose a CNN-based architecture suitable for emotion images. Studies on the relationship between color and human emotion were also conducted, and results were derived that different emotions are induced according to color. In studies using deep learning, there have been studies that apply color information to image subtraction classification. The case where the image's color information is additionally used than the case where the classification model is trained with only the image improves the accuracy of classifying image emotions. This study proposes two ways to increase the accuracy by incorporating the result value after the model classifies an image's emotion. Both methods improve accuracy by modifying the result value based on statistics using the color of the picture. When performing the test by finding the two-color combinations most distributed for all training data, the two-color combinations most distributed for each test data image were found. The result values were corrected according to the color combination distribution. This method weights the result value obtained after the model classifies an image's emotion by creating an expression based on the log function and the exponential function. Emotion6, classified into six emotions, and Artphoto classified into eight categories were used for the image data. Densenet169, Mnasnet, Resnet101, Resnet152, and Vgg19 architectures were used for the CNN model, and the performance evaluation was compared before and after applying the two-stage learning to the CNN model. Inspired by color psychology, which deals with the relationship between colors and emotions, when creating a model that classifies an image's sentiment, we studied how to improve accuracy by modifying the result values based on color. Sixteen colors were used: red, orange, yellow, green, blue, indigo, purple, turquoise, pink, magenta, brown, gray, silver, gold, white, and black. It has meaning. Using Scikit-learn's Clustering, the seven colors that are primarily distributed in the image are checked. Then, the RGB coordinate values of the colors from the image are compared with the RGB coordinate values of the 16 colors presented in the above data. That is, it was converted to the closest color. Suppose three or more color combinations are selected. In that case, too many color combinations occur, resulting in a problem in which the distribution is scattered, so a situation fewer influences the result value. Therefore, to solve this problem, two-color combinations were found and weighted to the model. Before training, the most distributed color combinations were found for all training data images. The distribution of color combinations for each class was stored in a Python dictionary format to be used during testing. During the test, the two-color combinations that are most distributed for each test data image are found. After that, we checked how the color combinations were distributed in the training data and corrected the result. We devised several equations to weight the result value from the model based on the extracted color as described above. The data set was randomly divided by 80:20, and the model was verified using 20% of the data as a test set. After splitting the remaining 80% of the data into five divisions to perform 5-fold cross-validation, the model was trained five times using different verification datasets. Finally, the performance was checked using the test dataset that was previously separated. Adam was used as the activation function, and the learning rate was set to 0.01. The training was performed as much as 20 epochs, and if the validation loss value did not decrease during five epochs of learning, the experiment was stopped. Early tapping was set to load the model with the best validation loss value. The classification accuracy was better when the extracted information using color properties was used together than the case using only the CNN architecture.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.95-112
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• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

• Journal of Aquaculture
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• v.2 no.2
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• pp.53-90
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• 1989

Feeding proper level of ration matchable with the appetite of fish will enhance production and also prevent waste of food and its consequence, side effects such as pollution of culture medium. To pursue this goal, elaborate studies on dissolved oxygen concentrations- as the major force in inducing appetite and the growth outcome are necessary. The growth of common carp of 67, 200, 400, 600, and 800 gram size groups was studied at oxygen concentrations ranging from 2.0 to 6 mg/$\iota$ in relation to rations from 1 to as many percent of the initial body weight as could be consumed under constant temperature of $25^{\circ}C$. The results from the experiments are summarized as followings; 1. Appetite: The smaller fish exhibited higher degree of appetite than the bigger ones at the same oxygen concentrations. The bigger the fish the less tolerant it was to the lower oxygen thersholds, and the degree of tolerence decreased as ration level increased. 2. Growth : Growth rate (percent per day) increased - unless consumption was suppressed by low oxygen levels- as the ration was increased to maximum. In case of 67 g fish, it reached the highest point of $5.05\%$ / day at $7\%$ ration under 5.0 mg/$\iota$ of oxygen. In case of 200 g fish, the maximum growth rate of $3.75\%$/day appeared at the maximum ration of $6\%$ under 5.5 mg/$\iota$ of oxygen. In 400 g fish, the highest growth of $3.37\%$/day occurred at the maximum ration of $5\%$ and 6.0 mg/$\iota$ of oxygen. In 600 g fish, the highest growth rate of $2.82\%$ /day was at the maximum ration of $4\%$ under 5.5 mg/$\iota$ oxygen. In case of 800g fish, the highest growth rate of $1.95\%$/day was at maximum tested ration of $3\%$ under 5.0 mg/$\iota$ oxygen. 3. Food Conversion Efficiency: Food conversion efficiency ($\%$ dry feed converted into the fish tissue) first increased as the ration was increased, reached maximum at certain food level, then started decreasing with further increase in the ration. The maximum conversion efficiency stood at higher feeding rate for the smaller fish than the larger ones. In case of 67 g fish, the maximum food conversion efficiency was at $4\%$ ration within 3.0-4.0 mg/$\iota$ oxygen. In 200g fish, the maximum efficiency was at $3\%$ ration within 4.0-4.5 mg/$\iota$ oxygen. In 400g fish, the maximum efficiency was at $2\%$ ration within 4.0 - 4.5 mg/$\iota$ oxygen. In 600 and 800g fish, the maximum conversion efficiency shifted to the lowest ration ($1\%$) and lower oxygen ranges. 4. Behaviour: The fish within uncomfortably low oxygen levels exhibited suppressed appetite and movements and were observed to pass feces quicker and in larger quantity than the ones in normal condition; in untolerably low oxygen the fish were lethargic, vomited, and had their normal skin color changed into pale yellow or grey patches. All these processes contributed to reducing food conversion efficiency. On the other hand, the fish within relatively higher oxygen concentrations exhibited higher degree of movement and their food conversion tended to be depressed when compared with sister groups under corresponding size and ration within relatively low oxyen level. 5. Suitability of Oxygen Ranges to Rations: The oxygen level of 2.0- 2.5 mg/$\iota$ was adequate to sustain appetite at $1\%$ ration in all size groups. As the ration was increased higher oxygen was required to sustain the fish appetite and metabolic activity, particularly in larger fish. In 67g fish, the $2\%$ ration was well supported by 2.0-2.5 mg/$\iota$ range; as the ration increased to $5\%$, higher range of 3.0-4.0 mg/$\iota$ brought better appetite and growth; from 5 till $7\%$ (the last tested ration for 67 g fish) oxygen levels over 4.0 mg/$\iota$ could sustain appetite. In 200 g fish, the 2 and $3\%$ rations brought the best growth and conversion rates at 3.5-4.5 mg/$\iota$ oxygen level; from 3 till $6\%$ (the last tested ration at 200 g fish) oxyge groups over 4.5 mg/$\iota$ were matchable with animal's appetite. In 400, 600, and 800 g fish, all the rations above $2\%$ had to be generally supported with oxygen levels above 4.5 mg/$\iota$.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.17-23
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• 2008

Purpose : Because there is a difference depending on the environment as for an inspection equipment the important part of bone density scan and the precision/accuracy of a tester, the management of quality must be made systematically. The equipment failure caused by overload effect due to the aged equipment and the increase of a patient was made frequently. Thus, the replacement of equipment and additional purchases of new bonedensity equipment caused a compatibility problem in tracking patients. This study wants to know whether the clinical changes of patient's bonedensity can be accurately and precisely reflected when used it compatiblly like the existing equipment after equipment replacement and expansion. Materials and methods : Two equipments of GE Lunar Prodigy Advance(P1 and P2) and the Phantom HOLOGIC Spine Road(HSP) were used to measure equipment precision. Each device scans 20 times so that precision data was acquired from the phantom(Group 1). The precision of a tester was measured by shooting twice the same patient, every 15 members from each of the target equipment in 120 women(average age 48.78, 20-60 years old)(Group 2). In addition, the measurement of the precision of a tester and the cross-calibration data were made by scanning 20 times in each of the equipment using HSP, based on the data obtained from the management of quality using phantom(ASP) every morning (Group 3). The same patient was shot only once in one equipment alternately to make the measurement of the precision of a tester and the cross-calibration data in 120 women(average age 48.78, 20-60 years old)(Group 4). Results : It is steady equipment according to daily Q.C Data with $0.996\;g/cm^2$, change value(%CV) 0.08. The mean${\pm}$SD and a %CV price are ALP in Group 1(P1 : $1.064{\pm}0.002\;g/cm^2$, $%CV=0.190\;g/cm^2$, P2 : $1.061{\pm}0.003\;g/cm^2$, %CV=0.192). The mean${\pm}$SD and a %CV price are P1 : $1.187{\pm}0.002\;g/cm^2$, $%CV=0.164\;g/cm^2$, P2 : $1.198{\pm}0.002\;g/cm^2$, %CV=0.163 in Group 2. The average error${\pm}$2SD and %CV are P1 - (spine: $0.001{\pm}0.03\;g/cm^2$, %CV=0.94, Femur: $0.001{\pm}0.019\;g/cm^2$, %CV=0.96), P2 - (spine: $0.002{\pm}0.018\;g/cm^2$, %CV=0.55, Femur: $0.001{\pm}0.013\;g/cm^2$, %CV=0.48) in Group 3. The average error${\pm}2SD$, %CV, and r value was spine : $0.006{\pm}0.024\;g/cm^2$, %CV=0.86, r=0.995, Femur: $0{\pm}0.014\;g/cm^2$, %CV=0.54, r=0.998 in Group 4. Conclusion: Both LUNAR ASP CV% and HOLOGIC Spine Phantom are included in the normal range of error of ${\pm}2%$ defined in ISCD. BMD measurement keeps a relatively constant value, so showing excellent repeatability. The Phantom has homogeneous characteristics, but it has limitations to reflect the clinical part including variations in patient's body weight or body fat. As a result, it is believed that quality control using Phantom will be useful to check mis-calibration of the equipment used. A value measured a patient two times with one equipment, and that of double-crossed two equipment are all included within 2SD Value in the Bland - Altman Graph compared results of Group 3 with Group 4. The r value of 0.99 or higher in Linear regression analysis(Regression Analysis) indicated high precision and correlation. Therefore, it revealed that two compatible equipment did not affect in tracking the patients. Regular testing equipment and capabilities of a tester, then appropriate calibration will have to be achieved in order to calculate confidential BMD.