• Sleep Medicine and Psychophysiology
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• v.19 no.2
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• pp.68-76
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• 2012

Objectives: Sleep disorders cause changes of autonomic nervous system (ANS) which affect cardiovascular system. Primary insomnia (PI) makes acceleration of sympathetic nervous system (SNS) tone by sleep deficiency and arousal. Obstructive sleep apnea syndrome (OSAS) sets off SNS by frequent arousals and hypoxemias during sleep. We aimed to compare the changes of heart rate variability (HRV) indices induced by insomnia or sleep apnea to analyze for ANS how much to be affected by PI or OSAS. Methods: Total 315 subjects carried out nocturnal polysomnography (NPSG) were categorized into 4 groups - PI, mild, moderate and severe OSAS. Severity of OSAS was determined by apnea-hypopnea index (AHI). Then we selected 110 subjects considering age, sex and valance of each group's size [Group 1 : PI (mean age=$41.50{\pm}13.16$ yrs, AHI <5, n=20), Group 2 : mild OSAS (mean age=$43.67{\pm}12.11$ yrs, AHI 5-15, n=30), Group 3 : moderate OSAS (mean age $44.93{\pm}12.38$ yrs, AHI 16-30, n=30), Group 4 : severe OSAS (mean age=$45.87{\pm}12.44$ yrs, AHI >30, n=30)]. Comparison of HRV indices among the four groups was performed with ANCOVA (adjusted for age and body mass index) and Sidak post-hoc test. Results: We found statistically significant differences in HRV indices between severe OSAS group and the other groups (PI, mild OSAS and moderate OSAS). And there were no significant differences in HRV indices among PI, mild and moderate OSAS group. In HRV indices of PI and severe OSAS group showing the most prominent difference in the group comparisons, average RR interval were $991.1{\pm}27.1$ and $875.8{\pm}22.0$ ms (p=0.016), standard deviation of NN interval (SDNN) was $85.4{\pm}6.6$ and $112.8{\pm}5.4$ ms (p=0.022), SDNN index was $57.5{\pm}5.2$ and $87.6{\pm}4.2$ (p<0.001), total power was $11,893.5{\pm}1,359.9$ and $18,097.0{\pm}1,107.2ms^2$(p=0.008), very low frequency (VLF) was $7,534.8{\pm}1,120.1$ and $11,883.8{\pm}912.0ms^2$ (p=0.035), low frequency (LF) was $2,724.2{\pm}327.8$ and $4,351.6{\pm}266.9ms^2$(p=0.003). Conclusions: VLF and LF which were correlated with SNS tone showed more increased differences between severe OSAS group and PI group than other group comparisons. We could suggest that severe OSAS group was more influential to increased SNS activity than PI group.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.45-69
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• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.91-121
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• 2008

Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.

• Restorative Dentistry and Endodontics
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• v.27 no.4
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• pp.370-381
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• 2002

This study was performed to evaluate the temperature rise on various position of the Buchanan plugger, the peak temperature of plugger's type and the temperature change by its touching time of heat control spling. The heat carrier system 'System B' (Model 1005, Analytic Technologies, USA) and the Buchanan's plug-gers of F, FM, M and ML sizes are used for this study. The temperature was set to 20$0^{\circ}C$ which Dr. Buchanan's "continuous wave of condensation" technique recommended on digital display and the power level on it was set to 10. In order to apply heat on the Buchanan's pluggers, the heat control spring was touched for 1, 2, 3, 4 and 5 seconds respectively. The temperature rise on the surface of the pluggers were measured at 0.5 mm intervals from tip to 20 mm length of shank using the infrared thermography (Radiation Thermometer-IR Temper, NEC San-ei Instruments, Ltd, Japan) and TH31-702 Data capture software program (NEC San-ei Instruments, Ltd, Japan). Data were analyzed using a one way ANOVA followed by Duncan's multiple range test and linear regression test. The results as follows. 1. The position at which temperature peaked was approximately at 0.5 mm to 1.5 mm far from the tip of Buchanan's pluggers (p<0.001). The temperature was constantly decreased toward the shank from the tip of it (p<0.001). 2. When the pluggerss were heated over 5 seconds, the peak temperature by time of measurement revealed from 253.3$\pm$10.5$^{\circ}C$ to 192.1$\pm$3.3$^{\circ}C$ in a touch for 1 sec, from 218.6$\pm$5.$0^{\circ}C$ to 179.5$\pm$4.2$^{\circ}C$ in a touch for 2 sec, from 197.5$\pm$3.$0^{\circ}C$ to 167.5$\pm$3.7$^{\circ}C$ in a touch for 3 sec, from 183.7$\pm$2.5$^{\circ}C$ to 159.8$\pm$3.6$^{\circ}C$ in a touch for 4 sec and from 164.9$\pm$2.$0^{\circ}C$ to 158.4$\pm$1.8$^{\circ}C$ in a touch for 5 sec. A touch for 1 sec showed the highest peak temperature, followed by, in descending order, 2 sec, 3 sec, 4 sec. A touch for 5 sec showed the lowest peak temperature (p<0.001). 3. A each type of pluggers showed different peak temperatures. The peak temperature was the highest in F type and followed by, in descending order, M type, ML type. FM type revealed the lowest peak temperature (p<0.001). The results of this study indicated that pluggers are designed to concentrate heat at around its tip, its actual temperature does not correlate well with the temperature which Buchanan's "continuous wave of condensation" technique recommend, and finally a quick touch of heat control spring for 1sec reveals the highest temperature rise.

• Journal of Radiation Protection and Research
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• v.41 no.1
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• pp.31-39
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• 2016

Background: It is necessary to consider the overall countermeasure for analysis of nuclear activities according to the increase of the nuclear facilities like nuclear power and reprocessing plants in the neighboring countries including China, Taiwan, North Korea, Japan and South Korea. South Korea and comprehensive nuclear-test-ban treaty organization (CTBTO) are now operating the monitoring instruments to detect radionuclides released into the air. It is important to estimate the origin of radionuclides measured using the detection technology as well as the monitoring analysis in aspects of investigation and security of the nuclear activities in neighboring countries. Materials and methods: A three-dimensional forward/backward trajectory model has been developed to estimate the origin of radionuclides for a covert nuclear activity. The developed trajectory model was composed of forward and backward modules to track the particle positions using finite difference method. Results and discussion: A three-dimensional trajectory model was validated using the measured data at Chernobyl accident. The calculated results showed a good agreement by using the high concentration measurements and the locations where was near a release point. The three-dimensional trajectory model had some uncertainty according to the release time, release height and time interval of the trajectory at each release points. An atmospheric dispersion model called long-range accident dose assessment system (LADAS), based on the fields of regards (FOR) technique, was applied to reduce the uncertainties of the trajectory model and to improve the detective technology for estimating the radioisotopes emission area. Conclusion: The detective technology developed in this study can evaluate in release area and origin for covert nuclear activities based on measured radioisotopes at monitoring stations, and it might play critical tool to improve the ability of the nuclear safety field.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.151-171
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• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• The Korean Journal of Franchise Management
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• v.2 no.1
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• pp.173-199
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• 2011

A franchisee has to depend on the overall system, such as knowhow and management support, from a franchisor in the franchise system and the two parties do not start with the same position in economic or information power because the franchisor controls or supports through selling or management styles. For this, unfair trades the franchisor's over controlling and limiting the franchisee might occur and other side effects by the people who give the franchisee scam trades has negatively influenced on the development of franchise industry and national economy. So, the purpose of this study is preventing unfair trade for the franchisee from understanding the causes and problems of dispute between the franchisor and the franchisee focused on the dispute cases submitted the Korea Fair Trade Mediation Agency and seeking ways to secure the transparency of recruitment process and justice of franchise management process. The results of the case analysis are followed; first, affiliation contracts should run on the franchisor's exact public information statement and the surely understanding of the franchisee. Secondly, the franchisor needs to use their past experiences and investigated data for recruiting franchisees. Thirdly, in the case of making a contract with the franchisee, the franchisor has to make sure the business area by checking it with franchisee in person. Fourthly, the contracts are important in affiliation contracts, so enacting the possibility of disputes makes the disputes decreased. Fifthly, lots of investigation and interests are needed for protecting rights and interests between the franchisor and franchisee and preventing the disputes by catching the cause and more practical solutions of the disputes from the government.

• Journal of Environmental Impact Assessment
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• v.4 no.3
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• pp.9-13
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• 1995

In July 1993 a new prescription of the EC was finished, concerning the voluntary participation of enterprises in a common auditing system. By this in the EC-member countries there must be founded centers of environmental auditing where experienced experts of environmental auditing should be accredited. These accredited experts are controllers for evaluating and certification of carried out environmental-auditings. An environmental-auditing practically represents an environmental assessment for an already existing enterprise with establishing corresponding programmes and strategies for the internal management to improve the environmental relations. Much experiences, which could be collected in the field of EIA during the last years may be transfered to this new task immediately. Only an essential difference there should not be overseen because of national legislation EIA in the defined cases must be carried out. By the EC-prescription carrying out an environmental-auditing for an enterprise is optional, it is recommended only. It was not introduced as a must. In spite of this fact because of the hard competition on the market there will be developed a pressure for the enterprises, to carry out such environmental-auditings. At present already a number of first projects in this direction can be seen, in the first line above all enterprises with the necessary economic power want to use this possibility, to gain better positions on the market. We have already gathered the first experiences in this field. We arranged corresponding contacts to several enterprises within the surroundings of Dresden. Within an opening discussion, where the project is explained and discussed with the management of the enterprise very detailed, the understanding, the readiness and the cooperation for the project are generated necessary prerequesits for the success of the whole work. By means of careful detail-work in collaboration with all departments and on all levels of the enterprise the total mass and energy-balances of the factory established and analysed. There are included also such ranges like material delivery, personal policy, public relations and sale as well as waste management. It is important that all people working in the factory have the feeling to be our partners, and not to have the impression to be checked or controled by an outside organization. This one of the most important factors of environmental auditing, in order to wake up and to develop a common interest on all sides. At the end of the environmental auditing there will be according to the prescription of the EC a catalogue of measures to do immediately, short time, mean time and long time for improvement of the environmental situation of the enterprise. All proposals are made in connection with a corresponding economic evaluation. These measures and programmes are declared as the environmental manual and are the basis for the work of the environmental management of the enterprise for the next three years. According to the EC-prescription, the enterprise with this environmental manual can get a corresponding certificate, which may be used for public relation purposes.