• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• Korean Journal of Poultry Science
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• v.51 no.2
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• pp.83-95
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• 2024

This study aimed to assess the performance of laying hens across twelve crossbreed strains (i.e., CFCK, CFYC, CFYD, CKCF, CKYC, CKYD, YCYD, YCCF, YCCK, YDCF, YDCK, and YDYC) of Korean native chicken (KNC) and compare them with Hy-Line Brown layers. A total of 287 18-week-old laying hens were placed in battery cages by strains (2-5 birds per pen). Results indicated that the YCYD and YDYC strains exhibited numerically heavier body weights than Hy-Line Brown at week 18-64. CKYC and YDYC strains demonstrated more than 94% viability by week 64. The CFYC strain had an age of first egg laying of 127 days, and the YDCF strain reached an age of 50% egg production at 140 days, both earlier than their parent stock. The YDCF strain showed over 70% egg production for up to 60 weeks. Regarding egg quality, the CKCF and YCCF strains had numerically higher egg weights among the KNC groups at week 24-64, with the YDYC strain showing a darker (P<0.05) eggshell color compared to CKCF at week 40. Moreover, KNC crossbreeds showed a higher (P<0.05) egg yolk ratio than Hy-Line Brown. In conclusion, the YDCF and YCCF crossbreeds exhibited the most desirable new synthetic Korean native commercial layer based on egg production and quality parameters. Therefore, these strains could be a viable substitute for Hy-Line Brown layers.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.6 no.1
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• pp.77-87
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• 1996

In order to compare the difference of the measurement of delta aminolevulinic acid(${\delta}$-ALA) in urine between HPLC method(HALA) and colorimetric method(CALA), and also to provide useful information for the new diagnostic criteria of ${\delta}$-ALA in urine in lead poisoning, if at all possible in the future, authors studied 234 male lead workers who were selected from 7 storage battery factories, 3 secondary smelting industries, and 2 litharge making industries. Study subjects were selected on the basis of blood Zinc protoporphyrin(ZPP) level from low to high concentration to cover wide range of lead exposure. Study variables for this study were ${\delta}$-ALA measured by two different methods, blood lead(PbB), and blood ZPP. The results were as follows: 1. There was very high correlation between ${\delta}$-ALA measured by two method(r = 0.989 : HALA = -0.8194 + 0.8110 ${\times}$ CALA), but the value of CALA was measured about 2mg/L greater than HALA. 2. While the correlations of ${\delta}$-ALA by two method with blood lead and blood ZPP were 0.46 and 0.37 respectively, they were increased to 0.63 and 0.57 if ${\delta}$-ALA values were log-transformed. 3. Simple linear regression of ${\delta}$-ALA measured by two method on ZPP were as follows: CALA = 2.0421 + 0.0341 ${\times}$ ZPP ($R^2=0.1385$ p = 0.0001) HALA = 0.8006 + 0.0280 ${\times}$ ZPP ($R^2=0.1389$ p = 0.0001) 4. Simple linear regression of ${\delta}$-ALA measured by two method on PbB were as follows: CALA = - 0.4134 + 0.1545 ${\times}$ PbB ($R^2=0.2085$ p = 0.0001) HALA = -1.2893 + 0.1287 PbB ($R^2=0.2154$ p = 0.0001), 5. Simple linear regression of log-transformed ${\delta}$-ALA by two method on ZPP and PbB were as follows: logHALA = 0.3078 + 0.0060 ZPP ($R^2=0.3329$ p = 0.0001) logCALA = 1.0189 + 0.0044 ZPP ($R^2=0.3290$ p = 0.0001) logHALA = -0.0221 + 0.0246 PbB ($R^2=0.4046$ p = 0.0001) logCALA = 0.7662 + 0.0184 PbB ($R^2=0.4108$ p = 0.0001) 6. The cumulative percent of colorimetric method to detect lead workers whose value of PbS and ZPP were over screening level such as $40{\mu}/dl$ and $100{\mu}/dl$ respectively was higher than HPLC method if cut-off level of ${\delta}$-ALA for screening of lead poisoning was 5 mg/L. But if cut-off level of ${\delta}$-ALA measured by HPLC was reduced to 3 mg/L which is compatible to 5 mg/L of ${\delta}$-ALA measured by colorimetric method, there were good agreement between two methods and showed dose-response relationship with other lead exposure indices such as PbB and ZPP.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.89-97
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• 2010

This study researches the effects of common features on a no-choice option with respect to regulatory focus theory. The primary interest is in three factors and their interrelationship: common features, no-choice option, and regulatory focus. Prior studies have compiled vast body of research in these areas. First, the "common features effect" has been observed bymany noted marketing researchers. Tversky (1972) proposed the seminal theory, the EBA model: elimination by aspect. According to this theory, consumers are prone to focus only on unique features during comparison processing, thereby dismissing any common features as redundant information. Recently, however, more provocative ideas have attacked the EBA model by asserting that common features really do affect consumer judgment. Chernev (1997) first reported that adding common features mitigates the choice gap because of the increasing perception of similarity among alternatives. Later, however, Chernev (2001) published a critically developed study against his prior perspective with the proposition that common features may be a cognitive load to consumers, and thus consumers are possible that they are prone to prefer the heuristic processing to the systematic processing. This tends to bring one question to the forefront: Do "common features" affect consumer choice? If so, what are the concrete effects? This study tries to answer the question with respect to the "no-choice" option and regulatory focus. Second, some researchers hold that the no-choice option is another best alternative of consumers, who are likely to avoid having to choose in the context of knotty trade-off settings or mental conflicts. Hope for the future also may increase the no-choice option in the context of optimism or the expectancy of a more satisfactory alternative appearing later. Other issues reported in this domain are time pressure, consumer confidence, and alternative numbers (Dhar and Nowlis 1999; Lin and Wu 2005; Zakay and Tsal 1993). This study casts the no-choice option in yet another perspective: the interactive effects between common features and regulatory focus. Third, "regulatory focus theory" is a very popular theme in recent marketing research. It suggests that consumers have two focal goals facing each other: promotion vs. prevention. A promotion focus deals with the concepts of hope, inspiration, achievement, or gain, whereas prevention focus involves duty, responsibility, safety, or loss-aversion. Thus, while consumers with a promotion focus tend to take risks for gain, the same does not hold true for a prevention focus. Regulatory focus theory predicts consumers' emotions, creativity, attitudes, memory, performance, and judgment, as documented in a vast field of marketing and psychology articles. The perspective of the current study in exploring consumer choice and common features is a somewhat creative viewpoint in the area of regulatory focus. These reviews inspire this study of the interaction possibility between regulatory focus and common features with a no-choice option. Specifically, adding common features rather than omitting them may increase the no-choice option ratio in the choice setting only to prevention-focused consumers, but vice versa to promotion-focused consumers. The reasoning is that when prevention-focused consumers come in contact with common features, they may perceive higher similarity among the alternatives. This conflict among similar options would increase the no-choice ratio. Promotion-focused consumers, however, are possible that they perceive common features as a cue of confirmation bias. And thus their confirmation processing would make their prior preference more robust, then the no-choice ratio may shrink. This logic is verified in two experiments. The first is a $2{\times}2$ between-subject design (whether common features or not X regulatory focus) using a digital cameras as the relevant stimulus-a product very familiar to young subjects. Specifically, the regulatory focus variable is median split through a measure of eleven items. Common features included zoom, weight, memory, and battery, whereas the other two attributes (pixel and price) were unique features. Results supported our hypothesis that adding common features enhanced the no-choice ratio only to prevention-focus consumers, not to those with a promotion focus. These results confirm our hypothesis - the interactive effects between a regulatory focus and the common features. Prior research had suggested that including common features had a effect on consumer choice, but this study shows that common features affect choice by consumer segmentation. The second experiment was used to replicate the results of the first experiment. This experimental study is equal to the prior except only two - priming manipulation and another stimulus. For the promotion focus condition, subjects had to write an essay using words such as profit, inspiration, pleasure, achievement, development, hedonic, change, pursuit, etc. For prevention, however, they had to use the words persistence, safety, protection, aversion, loss, responsibility, stability etc. The room for rent had common features (sunshine, facility, ventilation) and unique features (distance time and building state). These attributes implied various levels and valence for replication of the prior experiment. Our hypothesis was supported repeatedly in the results, and the interaction effects were significant between regulatory focus and common features. Thus, these studies showed the dual effects of common features on consumer choice for a no-choice option. Adding common features may enhance or mitigate no-choice, contradictory as it may sound. Under a prevention focus, adding common features is likely to enhance the no-choice ratio because of increasing mental conflict; under the promotion focus, it is prone to shrink the ratio perhaps because of a "confirmation bias." The research has practical and theoretical implications for marketers, who may need to consider common features carefully in a practical display context according to consumer segmentation (i.e., promotion vs. prevention focus.) Theoretically, the results suggest some meaningful moderator variable between common features and no-choice in that the effect on no-choice option is partly dependent on a regulatory focus. This variable corresponds not only to a chronic perspective but also a situational perspective in our hypothesis domain. Finally, in light of some shortcomings in the research, such as overlooked attribute importance, low ratio of no-choice, or the external validity issue, we hope it influences future studies to explore the little-known world of the "no-choice option."

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.123-132
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• 2013

As the smartphones are equipped with various sensors such as the accelerometer, GPS, gravity sensor, gyros, ambient light sensor, proximity sensor, and so on, there have been many research works on making use of these sensors to create valuable applications. Human activity recognition is one such application that is motivated by various welfare applications such as the support for the elderly, measurement of calorie consumption, analysis of lifestyles, analysis of exercise patterns, and so on. One of the challenges faced when using the smartphone sensors for activity recognition is that the number of sensors used should be minimized to save the battery power. When the number of sensors used are restricted, it is difficult to realize a highly accurate activity recognizer or a classifier because it is hard to distinguish between subtly different activities relying on only limited information. The difficulty gets especially severe when the number of different activity classes to be distinguished is very large. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we take to dealing with this ten-class problem is to use the ensemble of nested dichotomy (END) method that transforms a multi-class problem into multiple two-class problems. END builds a committee of binary classifiers in a nested fashion using a binary tree. At the root of the binary tree, the set of all the classes are split into two subsets of classes by using a binary classifier. At a child node of the tree, a subset of classes is again split into two smaller subsets by using another binary classifier. Continuing in this way, we can obtain a binary tree where each leaf node contains a single class. This binary tree can be viewed as a nested dichotomy that can make multi-class predictions. Depending on how a set of classes are split into two subsets at each node, the final tree that we obtain can be different. Since there can be some classes that are correlated, a particular tree may perform better than the others. However, we can hardly identify the best tree without deep domain knowledge. The END method copes with this problem by building multiple dichotomy trees randomly during learning, and then combining the predictions made by each tree during classification. The END method is generally known to perform well even when the base learner is unable to model complex decision boundaries As the base classifier at each node of the dichotomy, we have used another ensemble classifier called the random forest. A random forest is built by repeatedly generating a decision tree each time with a different random subset of features using a bootstrap sample. By combining bagging with random feature subset selection, a random forest enjoys the advantage of having more diverse ensemble members than a simple bagging. As an overall result, our ensemble of nested dichotomy can actually be seen as a committee of committees of decision trees that can deal with a multi-class problem with high accuracy. The ten classes of activities that we distinguish in this paper are 'Sitting', 'Standing', 'Walking', 'Running', 'Walking Uphill', 'Walking Downhill', 'Running Uphill', 'Running Downhill', 'Falling', and 'Hobbling'. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window of the last 2 seconds, etc. For experiments to compare the performance of END with those of other methods, the accelerometer data has been collected at every 0.1 second for 2 minutes for each activity from 5 volunteers. Among these 5,900 ($=5{\times}(60{\times}2-2)/0.1$) data collected for each activity (the data for the first 2 seconds are trashed because they do not have time window data), 4,700 have been used for training and the rest for testing. Although 'Walking Uphill' is often confused with some other similar activities, END has been found to classify all of the ten activities with a fairly high accuracy of 98.4%. On the other hand, the accuracies achieved by a decision tree, a k-nearest neighbor, and a one-versus-rest support vector machine have been observed as 97.6%, 96.5%, and 97.6%, respectively.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.5 no.1
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• pp.8-15
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• 1995

The reliable measurement of metal in biological media in human body is one of critical indicators for the proper evaluation of its toxic effect on human health. Recently in Korea the necessity of quality assurance of measurement in occupational health and occupational hygiene fields brought out regulatory quality control program. Lead is often used as a standard metal for the program in both fields of occupational health and hygiene. During last 20 years lead poisoning was prevalent in Korea and still is one of main heavy metal poisoning and the capability of the measurement of blood lead is one of prerequisites for institute of specialized occupational health in Korea. Furthermore blood lead is most important indicator to evaluate lead burden of human exposure to lead and the reliable and accurate analysis is most needed whenever possible. To evaluate the extent of the interlaboratory differences of blood lead measurement in several well-known institute specialized in occupational health in Korea, authors prepared 68 blood samples from two storage battery industries and all samples were divided into samples with 2 ml. One set of 68 samples were analyzed by authors's laboratory(Soonchunhyang University Institute of Industrial Medicine: SIIM) and 40 samples of other set were analyzed by C University Institute of Industrial Medicine(CIIM) and the rest 28 samples of other set were analyzed by Japanese institute(K Occupational Health Center:KOHC). Authors also prepared test bovine samples which were obtained from Japanese Federation of Occupational Health Organization (JFOHO) for quality control. Authors selected 2 other well-known occupational health laboratories and one laboratory specialized for instrumental analysis. A total of 6 laboratories joined the interlaboratory comparison of blood lead measurement and the results obtained were as follows: 1. There was no significant difference in average blood lead between SIIM and CIIM in different group of blood lead concentration, and the relative standard deviation of two laboratories was less than 3.0%. On the other hand, there was also no significant difference of average blood lead between SIIM and KOHC with relative standard deviation of 6.84% as maximum. 2. Taking less than 15% difference of mean or less than 6 ug/dl difference in below 40 ug/dl in whole blood as a criteria of agreement of measurement between two laboratories, agreement rates were 87.5%(35/40) and 78.6%(22/28) between SIIM and CIIM, SIIM and KOHC respectively. 3. The correlation of blood lead between SIIM and CIIM was 0.975 (p=0.0001) and the regression equation was SIIM = 2.19 + 0.9243 ClIM, whereas the correlation between SUM and KOHC was O.965(p=0.0001) with the equation of SIIM = 1.91 + 0.9794 KOHC. 4. Taking the reference value as a dependent variable and each of 6 laboratories's measurement value as a independent variable, the determination coefficient($R^2$) of simple regression equations of blood lead measurement for bovine test samples were very high($R^2>0.99$), and the regression coefficient(${\beta}$) was between 0.972 and 1.15 which indicated fairly good agreement of measurement results.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.68-79
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• 2009

The interplay between hedonic and utilitarian attributes has assumed special significance in recent years; it has been proposed that consumption offerings should be viewed as experiences that stimulate both cognitions and feelings rather than as mere products or services. This research builds on previous work on hedonic versus utilitarian benefits, regulatory focus theory, customer satisfaction to address two question: (1) Is the shopping goal at the point of purchase different from the shopping value? and (2) Is the customer loyalty after the use different from the shopping value and shopping goal? We surveyed 345 peoples those who have bought the electronic-goods within 6 months. This research dealt with the shopping value which is consisted of 2 types, hedonic and utilitarian. Those who pursue the hedonic shopping value may prefer the pleasure of purchasing experience to the product itself. They tend to prefer atmosphere, arousal of the shopping experience. Consistent with previous research, we use the term "hedonic" to refer to their aesthetic, experiential and enjoyment-related value. On the contrary, Those who pursue the utilitarian shopping value may prefer the reasonable buying. It may be more functional. Consistent with previous research, we use the term "utilitarian" to refer to the functional, instrumental, and practical value of consumption offerings. Holbrook(1999) notes that consumer value is an experience that results from the consumption of such benefits. In the context of cell phones for example, the phone's battery life and sound volume are utilitarian benefits, whereas aesthetic appeal from its shape and color are hedonic benefits. Likewise, in the case of a car, fuel economics and safety are utilitarian benefits whereas the sunroof and the luxurious interior are hedonic benefits. The shopping goals are consisted of the promotion focus goal and the prevention focus goal, based on the self-regulatory focus theory. The promotion focus is characterized into focusing ideal self because they are oriented to wishes and vision. The promotion focused individuals are tend to be more risk taking. They are more sensitive to hope and achievement. On the contrary, the prevention focused individuals are characterized into focusing the responsibilities because they are oriented to safety. The prevention focused individuals are tend to be more risk avoiding. We wanted to test the relation among the shopping value, shopping goal and customer loyalty. Customers show the positive or negative feelings comparing with the expectation level which customers have at the point of the purchase. If the result were bigger than the expectation, customers may feel positive feeling such as delight or satisfaction and they would want to share their feelings with other people. And they want to buy those products again in the future time. There is converging evidence that the types of goals consumers expect to be fulfilled by the utilitarian dimension of a product are different from those they seek from the hedonic dimension (Chernev 2004). Specifically, whereas consumers expect the fulfillment of product prevention goals on the utilitarian dimension, they expect the fulfillment of promotion goals on the hedonic dimension (Chernev 2004; Chitturi, Raghunathan, and Majahan 2007; Higgins 1997, 2001) According to the regulatory focus theory, prevention goals are those that ought to be met. Fulfillment of prevention goals in the context of product consumption eliminates or significantly reduces the probability of a painful experience, thus making consumers experience emotions that result from fulfillment of prevention goals such as confidence and securities. On the contrary, fulfillment of promotion goals are those that a person aspires to meet, such as "looking cool" or "being sophisticated." Fulfillment of promotion goals in the context of product consumption significantly increases the probability of a pleasurable experience, thus enabling consumers to experience emotions that result from the fulfillment of promotion goals. The proposed conceptual framework captures that the relationships among hedonic versus utilitarian shopping values and promotion versus prevention shopping goals respectively. An analysis of the consequence of the fulfillment and frustration of utilitarian and hedonic value is theoretically worthwhile. It is also substantively relevant because it helps predict post-consumption behavior such as the promotion versus prevention shopping goals orientation. Because our primary goal is to understand how the post consumption feelings influence the variable customer loyalty: word of mouth (Jacoby and Chestnut 1978). This research result is that the utilitarian shopping value gives the positive influence to both of the promotion and prevention goal. However the influence to the prevention goal is stronger. On the contrary, hedonic shopping value gives influence to the promotion focus goal only. Additionally, both of the promotion and prevention goal show the positive relation with customer loyalty. However, the positive relation with promotion goal and customer loyalty is much stronger. The promotion focus goal gives the influence to the customer loyalty. On the contrary, the prevention focus goal relates at the low level of relation with customer loyalty than that of the promotion goal. It could be explained that it is apt to get framed the compliment of people into 'gain-non gain' situation. As the result, for those who have the promotion focus are motivated to deliver their own feeling to other people eagerly. Conversely the prevention focused individual are more sensitive to the 'loss-non loss' situation. The research result is consistent with pre-existent researches. There is a conceptual parallel between necessities-needs-utilitarian benefits and luxuries-wants-hedonic benefits (Chernev 2004; Chitturi, Raghunathan and Majaha 2007; Higginns 1997; Kivetz and Simonson 2002b). In addition, Maslow's hierarchy of needs and the precedence principle contends luxuries-wants-hedonic benefits higher than necessities-needs-utilitarian benefits. Chitturi, Raghunathan and Majaha (2007) show that consumers are focused more on the utilitarian benefits than on the hedonic benefits of a product until their minimum expectation of fulfilling prevention goals are met. Furthermore, a utilitarian benefit is a promise of a certain level of functionality by the manufacturer or the retailer. When the promise is not fulfilled, customers blame the retailer and/or the manufacturer. When negative feelings are attributable to an entity, customers feel angry. However in the case of hedonic benefit, the customer, not the manufacturer, determines at the time of purchase whether the product is stylish and attractive. Under such circumstances, customers are more likely to blame themselves than the manufacturer if their friends do not find the product stylish and attractive. Therefore, not meeting minimum utilitarian expectations of functionality generates a much more intense negative feelings, such as anger than a less intense feeling such as disappointment or dissatisfactions. The additional multi group analysis of this research shows the same result. Those who are unsatisfactory customers who have the prevention focused goal shows higher relation with WOM, comparing with satisfactory customers. The research findings in this article could have significant implication for the personal selling fields to increase the effectiveness and the efficiency of the sales such that they can develop the sales presentation strategy for the customers. For those who are the hedonic customers may be apt to show more interest to the promotion goal. Therefore it may work to strengthen the design, style or new technology of the products to the hedonic customers. On the contrary for the utilitarian customers, it may work to strengthen the price competitiveness. On the basis of the result from our studies, we demonstrated a correspondence among hedonic versus utilitarian and promotion versus prevention goal, WOM. Similarly, we also found evidence of the moderator effects of satisfaction after use, between the prevention goal and WOM. Even though the prevention goal has the low level of relation to WOM, those who are not satisfied show higher relation to WOM. The relation between the prevention goal and WOM is significantly different according to the satisfaction versus unsatisfaction. In addition, improving the promotion emotions of cheerfulness and excitement and the prevention emotion of confidence and security will further improve customer loyalty. A related potential further research could be to examine whether hedonic versus utilitarian, promotion versus prevention goals improve customer loyalty for services as well. Under the budget and time constraints, designers and managers are often compelling to choose among various attributes. If there is no budget or time constraints, perhaps the best solution is to maximize both hedonic and utilitarian dimension of benefits. However, they have to make trad-off process between various attributes. For the designers and managers have to keep in mind that without hedonic benefit satisfaction of the product it may hard to lead the customers to the customer loyalty.