• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• The Korean Nurse
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• v.34 no.5
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• pp.52-67
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• 1996

As home care in developing and becoming part of the health care delivery system in Korea, it is necessary to examine the use of nursing diagnoses and related nursing interventions with a view to increasing the standardization of nursing recording. This study was done to examine the nursing diagnosis and related nursing interventions used in home care. Data were collected using a chart review of the nursing notes written for the home care given to 38 patients who had pulmonary diseases or traumatic brain or spinal cord injuries and who had received home care as part of a demonstration home care project in a college of Nursing in Seoul. Early on in the project discussions as to format and use to nursing diagnosis was done and a tool was developed based on Gordon's eleven functional catergories with the addition of categories to cover family and environment. This tool was used in the data collection. Data included nursing diagnosis, etiologies and interventions. Real numbers and percentages were used in the analysis. The results show that the most frequently used diagnoses were in the category of physical function (75.6%), followed by the category of emotional and social function (21.8%). The least frequently used category was the one for family and environment (2.6%). The order of the frequency of recorded nursing interventions was the same, 82.3% for physical function, 16.2% of emotional and social function and 1.5% for family and environment. Under the category of physical functioning the most frequently used nursing diagnoses were related to mobility (62.2%), nutrition (23.6%) and elimination (11.9%). The frequencies of nursing interventions for these three diagnostic categories were 69.8%, 16.0% and 10.8% respectively. For emotional and social functioning, the most frequently used diagnoses were for cognition-perception (37.1%), self-perception (30.6%) and perception of health (23.7%). The ordering of the frequency of nursing interventions varied slightly. The most frequently used interventions were for the category of self-perception (31.7%) followed by cognition-perception (24.1%) and perception of health (22.9%). Looking at individual diagnoses, it was found that within the categroy of physical functioning, the most frequently used diagnosis was "impaired physical mobility" (29.5%) and this diagnosis involved 43.9% of the interventions. This was followed by "ineffective breathing pattern" (19.4%) with 17.7% of interventions, and "alteration in nutrition, less than body requirements" (11.2%) with 8.1% of the interventions. For the emotional social category, noncompliance was the most frequently used nursing diagnosis (18.2%) with 19.2% of the interventions. This was followed by "anxiety" (13.4%) with 13.6% of the interventions and by "knowledge deficit" (13.4%) but with only 5.5% of the interventions. The other diagnoses and interventions did not follow this pattern of frequency. Although there were a large number of diagnostic and intervention events, the number of actual diagnoses and interventions used were relatively small ranging from six interventions for "knowledge deficit" to 40 interventions for "imparied physical mobility". From this it can be concluded that the results of this study could be used as basic data for the development of standardized charts with respect to nursing diagnosis and interventions for clients with pulmonary disease and clients with traumatic brain or spinal cord injuries. Interventions that were direct care activities (1178) were much more frequent that education (430), and assessment and observation (148). There were also few diagnoses or interventions related to the family and the environment. This suggests two areas that need to be developed in home care and that need to be considered in the development of standardized records for use in home care.

• Journal of the Korean earth science society
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• v.44 no.1
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• pp.13-35
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• 2023

Ocean currents play the most important role in causing and controlling global climate change. The water depth of the Yellow Sea is very shallow compared to the East Sea, and the circulation and currents of seawater are quite complicated owing to the influence of various wind fields, ocean currents, and river discharge with low-salinity seawater. The Yellow Sea Warm Current (YSWC) is one of the most representative currents of the Yellow Sea in winter and is closely related to the weather of the southwest coast of the Korean Peninsula, so it needs to be treated as important in secondary-school textbooks. Based on the 2015 revised national educational curriculum, secondary-school science and earth science textbooks were analyzed for content related to the YSWC. In addition, a questionnaire survey of secondary-school science teachers was conducted to investigate their perceptions of the temporal variability of ocean currents. Most teachers appeared to have the incorrect knowledge that the YSWC moves north all year round to the west coast of the Korean Peninsula and is strong in the summer like a general warm current. The YSWC does not have strong seasonal variability in current strength, unlike the North Korean Cold Current (NKCC), but does not exist all year round and appears only in winter. These errors in teachers' subject knowledge had a background similar to why they had a misconception that the NKCC was strong in winter. Therefore, errors in textbook contents on the YSWC were analyzed and presented. In addition, to develop students' and teachers' data literacy, class materials on the YSWC that can be used in inquiry activities were developed. A graphical user interface (GUI) program that can visualize the sea surface temperature of the Yellow Sea was introduced, and a program displaying the spatial distribution of water temperature and salinity was developed using World Ocean Atlas (WOA) 2018 oceanic in-situ measurements of water temperature and salinity data and ocean numerical model reanalysis field data. This data visualization materials using oceanic data is expected to improve teachers' misunderstandings and serve as an opportunity to cultivate both students and teachers' ocean and data literacy.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.11
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• pp.1774-1784
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• 2014

The purpose of this study was to determine obstructive factors and performance level of the HACCP system among elementary schools in Gyeongbuk province. E-mail survey targeted 320 dieticians, and recovery rate was 74.1%. Consequently, 227 responses were analyzed. The questionnaire was composed of 58 items under four sections (general characteristics, dieticians' perceived HACCP performance level, dieticians' perceived CCP performance level, and obstructive factors of HACCP system implementation). The item with the highest rate of HACCP performance level was 'HACCP training for foodservice employees in schools ($4.02{\pm}0.70$)' while the lowest counterpart was 'implementation of HACCP team meeting, reporting, and maintenance ($2.74{\pm}0.99$)'. The performance level of the item 'HACCP training for foodservice employees in schools' was perceived as highest when the number of students eating school meals was greater than 1,101 (P<0.05). Moreover, CCP 4 ($4.44{\pm}0.53$) and CP 5 ($4.44{\pm}0.51$) showed the best performance, whereas CCP 1 showed the lowest performance level ($3.90{\pm}0.60$). Therefore, reinforcement of hygiene instruction in menu planning is perceived as necessary. CCP 1, CCP 6 (P<0.05), and CCP 3 (P<0.001) showed significant differences in performance based on the number of students eating school meals. Further, according to results regarding obstructive factors of HACCP system execution, 'general factor' was the most severe obstructive factor in the application of HACCP ($3.46{\pm}0.62$). Among the 'factors pertaining to dieticians', the item 'hardship of proper monitoring and micro-management due to overwhelming workload' was most influential ($3.46{\pm}0.96$). Furthermore, the item 'low budget allocation by educational offices ($3.90{\pm}0.88$)' was influential among the 'factors pertaining to school administrations'. In conclusion, the results of this research can help solve obstructive factors of elementary school food services and provide knowledge that is essential for the proper implementation of HACCP.

• Journal of Bio-Environment Control
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• v.13 no.4
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• pp.217-225
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• 2004

This study was performed to provide the basic knowledge about the mushroom cultivation facilities. Classified current status of cultivation facilities in Gyeongnam province was investigated by questionnaire. The structure of Pleurotus eryngii cultivation facilities can be classified into the simple and permanent frame type. The simple frame structures were mostly single-span type, on the other hand, the permanent frame structures were more multi-span than simple structures. And the scale of cultivation facilities was very different regardless of structural type. But as a whole, the length, width and ridge height were prevailing approximately 20.0 m, $6.6\~7.0m$ and $4.6\~5.0m$ range, respectively. The floor area was about $132\~160\;m^2$, and floor was built with concrete to protect mushrooms from various harmful infection. The roof slope of the simple and permanent type showed about $41.5^{\circ}\;and\;18.6\~28.6^{\circ}$, respectively. The width and layer number of growing bed for mushroom cultivation were around $1.2\~1.6m$, 4 layers in common, respectively. Most of year round cultivation facilities were equipped with cooler, heater, humidifier, and ventilating fan. Hot water boiler was the most commonly used heating system, the next was electric heater and then steam boiler. The industrial air conditioner has been widely used for cooling. And humidity was controlled mostly by ultra-wave or centrifuging humidifier. But some farmers has been using nozzle system for auxiliary purpose. More then $90\%$ of the mushroom house had the independent environment control system. The inside temperature was usually controlled by sensor, but humidity and $CO_2$ concentration was controlled by timer for each growing stage. The capacity of medium bottle was generally 850 cc and 1100cc, some farms used 800 cc, 950 co and 1,250 cc. Most of mushroom producted has been usually shipped to both circulating company and joint market.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.97-116
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• 2012

Conceptual modeling is an important step for successful system development. It helps system designers and business practitioners share the same view on domain knowledge. If the work is successful, a result of conceptual modeling can be beneficial in increasing productivity and reducing failures. However, the value of conceptual modeling is unlikely to be evaluated uniformly because we are lack of agreement on how to elicit concepts and how to represent those with conceptual modeling constructs. Especially, designing relationships between components, also known as part-whole relationships, have been regarded as complicated work. The recent study, "Representing Part-Whole Relations in Conceptual Modeling : An Empirical Evaluation" (Shanks et al., 2008), published in MIS Quarterly, can be regarded as one of positive efforts. Not only the study is one of few attempts of trying to clarify how to select modeling alternatives in part-whole design, but also it shows results based on an empirical experiment. Shanks et al. argue that there are two modeling alternatives to represent part-whole relationships : an implicit representation and an explicit one. By conducting an experiment, they insist that the explicit representation increases the value of a conceptual model. Moreover, Shanks et al. justify their findings by citing the BWW ontology. Recently, the study from Shanks et al. faces criticism. Allen and March (2012) argue that Shanks et al.'s experiment is lack of validity and reliability since the experimental setting suffers from error-prone and self-defensive design. They point out that the experiment is intentionally fabricated to support the idea, as such that using concrete UML concepts results in positive results in understanding models. Additionally, Allen and March add that the experiment failed to consider boundary conditions; thus reducing credibility. Shanks and Weber (2012) contradict flatly the argument suggested by Allen and March (2012). To defend, they posit the BWW ontology is righteously applied in supporting the research. Moreover, the experiment, they insist, can be fairly acceptable. Therefore, Shanks and Weber argue that Allen and March distort the true value of Shanks et al. by pointing out minor limitations. In this study, we try to investigate the dispute around Shanks et al. in order to answer to the following question : "What is the proper value of the study conducted by Shanks et al.?" More profoundly, we question whether or not using the BWW ontology can be the only viable option of exploring better conceptual modeling methods and procedures. To understand key issues around the dispute, first we reviewed previous studies relating to the BWW ontology. We critically reviewed both of Shanks and Weber and Allen and March. With those findings, we further discuss theories on part-whole (or part-of) relationships that are rarely treated in the dispute. As a result, we found three additional evidences that are not sufficiently covered by the dispute. The main focus of the dispute is on the errors of experimental methods: Shanks et al. did not use Bunge's Ontology properly; the refutation of a paradigm shift is lack of concrete, logical rationale; the conceptualization on part-whole relations should be reformed. Conclusively, Allen and March indicate properly issues that weaken the value of Shanks et al. In general, their criticism is reasonable; however, they do not provide sufficient answers how to anchor future studies on part-whole relationships. We argue that the use of the BWW ontology should be rigorously evaluated by its original philosophical rationales surrounding part-whole existence. Moreover, conceptual modeling on the part-whole phenomena should be investigated with more plentiful lens of alternative theories. The criticism on Shanks et al. should not be regarded as a contradiction on evaluating modeling methods of alternative part-whole representations. To the contrary, it should be viewed as a call for research on usable and useful approaches to increase value of conceptual modeling.

• Journal of Korean Academy of Nursing
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• v.20 no.3
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• pp.430-458
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• 1990

Care is a central concept of nursing. Nursing would not exist without caring. Care and quality of life are closely related. Human behavior is a manifestation of culture. We can say that caring and nursing care are expression of culture. The nurse must understand the relationship of culture with care for ensure quality nursing care. But knowledge of cultural factors in nursing is not well developed. Time and in - depth study are needed to find meaningful relationships between culture and care. Nurses recognized the importance of culturally appropriate nursing There are two care systems in culturally based nursing. The folk care system and the professional nursing care system. The folk care system existed long before the professional nursing care system was introduced into this culture. If the discrepancy between these two care systems is great, the client may receive inappropriate nursing care. Culture and subcaltures are diverse and dynamic in nature. Nurses need to know the caring behaviors, patterns, and their meaning in their own culture. In Korea we have taken some first step to study cultural nursing phenomena. It is not our intent necessarily to return to the past and develop a nationalistic of nursing, but to identify the core of traditional caring and relate that to professional nursing care. Our Assumptions are as follows : 1) Care is essential for human growth, well being and survial. 2) 7here are diverse and universal forma, expressions, patterns, and processes of human care that exist transcul - turally. 3) The behaviors and functions of caring differ according to the social structure of each culture. 4) Cultures have folk and professional care values, beliefs, and practices. To promote the quality of nursing care we must understand the folk care value, beliefs, and practices. We undertook this study to understand caring in our traditional culture. The Goals of this study were as follows : 1) To identify patterns in caring behavior, 2) To identify the structural components of caring, and 3) To understand the meaning and some principles of caring. We faised several questions in this study. Who is the care-giver? Who is the care-receipient? Was the woman the major care -giver at any time? What are the patterns in caring behavior? What art the priciples underlying the caring process? We used an interdisciplinary team approach, composed of representatives from nursing and anthropology, to contribute in -depth understanding of caring through a socicaltural perspeetive. A Field study was conducted in Ro-Bong, a small agricultural kinship village. The subjects were nine women and one man aged be or more years of age. Data were collected from january 15 to 21, 1990 through opem-ended in-depth interviews and observations. The interview focused on caring behaviors sorrounding birth, aging, death and child rearing. We analysed these data for meaning, pattern and priciples of caring. In this report we describe caring behaviors surrounding childbirth. The care-givers were primarily mothers- in -low, other women in the family older than the mother - to- be, older neighbor woman, husbands, and mothers of the mother-to- be. The care receivers were the mother-to-be the baby, and the immediate family as a component of kinship. Emerging caring behavior included praying, helping proscribing, giving moral advice(Deug - Dam), showing concern, instructing, protecting, making preparations, showing consideration, touching, trusting, encouraging, giving emotional comfort, being with, worrying about, being patient, preventing problems, showing by an example, looking after bringing up, taking care of postnatal health, streng thening the health condition, entering into another's feelings(empathizing), and sharing food, joy and sorrow The emerging caring component were affection, touching, nurtuing, teaching, praying, comforting, encouraging, sharing. empathizing, self - discipline, protecting, preparing, helping and compassion. Emerging principles of. caring were solidarity, heir- archzeal relationships, sex - role distinction. Caring during birth expresses the valve of life and reflects the valued traditional beliefs that human birth is given by god and a unique unifying family event reaching back to include the ancestors and foreward to later generations. In addition, We found positive and rational foundations for traditionl caring behaviors surrounding birth, these should not be stigmatized as inational or superstitious. The nurse appropriately adopts the rational and positive nature of traditional caring behaviors to promote the quality of nursing care.

• Journal of Korean Home Economics Education Association
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• v.20 no.2
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• pp.75-94
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• 2008

The purposes of this paper are to describe the newly established reference values of nutrient intakes: to apply the changed dietary reference intakes to the new text book based on the revised curriculum: and to contrive substantial contents in the domain of dietary life(foods & nutrition) of new text book. Dietary Reference Intakes for Koreans(KDRIs) is newly established reference values of nutrient intakes that are considered necessary to maintain the health of Koreans at the optimal state and to prevent chronic diseases and overnutrition. Unlike previously used Recommended Dietary Allowances for Koreas(KRDA), which presented a single reference value for intake of each nutrient, multiple values are set at levels for nutrients to reduce risk of chronic diseases and toxicity as well as prevention of nutrient deficiency. The new KDRIs include the Estimated Average Requirement(EAR), Recommended Intake(RI), Adequate Intake(AI), and Tolerable Upper Intake Level(UL). The EAR is the daily nutrient intake estimated to meet the requirement of the half of the apparently healthy individuals in a target group and thus is set at the median of the distribution of requirements. The RI is set at two standard deviations above the EAR. The AI is established for nutrients for which existing body of knowledge are inadequate to establish the EAR and RI. The UL is the highest level of daily nutrient intake which is not likely to cause adverse effects for the human health. Age and gender subgroups are established in consideration of physiological characteristics and developmental stages: infancy, toddler, childhood, adolescence, adulthood and old age. Pregnancy and lactation periods were considered separately and gender is divided after early childhood. Reference heights and weights are from the Korean Agency for Technology and Standards, Ministry of Commerce, Industry and Energy. The practical application of DRIs to the new books based on the revision in the 7th curriculum is to assess the dietary and nutrient intake as well as to plan a meal. It can be utilized to set an appropriate nutrient goal for the diet as usually eaten and to develop a plan that the individual will consume using a nutrient based food guidance system in the new books based on the revision in the 7th curriculum.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.55-75
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• 2010

Sequential pattern mining aims to discover interesting sequential patterns in a sequence database, and it is one of the essential data mining tasks widely used in various application fields such as Web access pattern analysis, customer purchase pattern analysis, and DNA sequence analysis. In general sequential pattern mining, only the generation order of data element in a sequence is considered, so that it can easily find simple sequential patterns, but has a limit to find more interesting sequential patterns being widely used in real world applications. One of the essential research topics to compensate the limit is a topic of weighted sequential pattern mining. In weighted sequential pattern mining, not only the generation order of data element but also its weight is considered to get more interesting sequential patterns. In recent, data has been increasingly taking the form of continuous data streams rather than finite stored data sets in various application fields, the database research community has begun focusing its attention on processing over data streams. The data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. In data stream processing, each data element should be examined at most once to analyze the data stream, and the memory usage for data stream analysis should be restricted finitely although new data elements are continuously generated in a data stream. Moreover, newly generated data elements should be processed as fast as possible to produce the up-to-date analysis result of a data stream, so that it can be instantly utilized upon request. To satisfy these requirements, data stream processing sacrifices the correctness of its analysis result by allowing some error. Considering the changes in the form of data generated in real world application fields, many researches have been actively performed to find various kinds of knowledge embedded in data streams. They mainly focus on efficient mining of frequent itemsets and sequential patterns over data streams, which have been proven to be useful in conventional data mining for a finite data set. In addition, mining algorithms have also been proposed to efficiently reflect the changes of data streams over time into their mining results. However, they have been targeting on finding naively interesting patterns such as frequent patterns and simple sequential patterns, which are found intuitively, taking no interest in mining novel interesting patterns that express the characteristics of target data streams better. Therefore, it can be a valuable research topic in the field of mining data streams to define novel interesting patterns and develop a mining method finding the novel patterns, which will be effectively used to analyze recent data streams. This paper proposes a gap-based weighting approach for a sequential pattern and amining method of weighted sequential patterns over sequence data streams via the weighting approach. A gap-based weight of a sequential pattern can be computed from the gaps of data elements in the sequential pattern without any pre-defined weight information. That is, in the approach, the gaps of data elements in each sequential pattern as well as their generation orders are used to get the weight of the sequential pattern, therefore it can help to get more interesting and useful sequential patterns. Recently most of computer application fields generate data as a form of data streams rather than a finite data set. Considering the change of data, the proposed method is mainly focus on sequence data streams.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.