• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.34 no.5
• /
• pp.973-980
• /
• 2024

Fuzzing is an automated testing technique that generates a lot of testcases and monitors for exceptions to test a program. Recently, fuzzing research using machine learning has been actively proposed to solve various problems in the fuzzing process, but a comprehensive evaluation of fuzzing research using machine learning is lacking. In this paper, we analyze recent research that applies machine learning to scheduling techniques for fuzzing, categorizing them into reinforcement learning-based and supervised learning-based fuzzers. We evaluated the coverage performance of the analyzed machine learning-based fuzzers against real-world programs with four different file formats and bug detection performance against the LAVA-M dataset. The results showed that AFL-HIER, which applied seed clustering and seed scheduling with reinforcement learning outperformed in coverage and bug detection. In the case of supervised learning, it showed high coverage on tcpdumps with high code complexity, and its superior bug detection performance when applied to hybrid fuzzing. This research shows that performance of machine learning-based fuzzer is better when both machine learning and additional fuzzing techniques are used to optimize the fuzzing process. Future research is needed on practical and robust machine learning-based fuzzing techniques that can be effectively applied to programs that handle various input formats.

• Journal of Intelligence and Information Systems
• /
• v.22 no.1
• /
• pp.83-105
• /
• 2016

Measuring an individual's subjective wellbeing in an accurate, unobtrusive, and cost-effective manner is a core success factor of the wellbeing support system, which is a type of medical IT service. However, measurements with a self-report questionnaire and wearable sensors are cost-intensive and obtrusive when the wellbeing support system should be running in real-time, despite being very accurate. Recently, reasoning the state of subjective wellbeing with conventional sentiment analysis and unstructured data has been proposed as an alternative to resolve the drawbacks of the self-report questionnaire and wearable sensors. However, this approach does not consider contextual polarity, which results in lower measurement accuracy. Moreover, there is no sentimental word net or ontology for the subjective wellbeing area. Hence, this paper proposes a method to extract keywords and their contextual polarity representing the subjective wellbeing state from the unstructured text in online websites in order to improve the reasoning accuracy of the sentiment analysis. The proposed method is as follows. First, a set of general sentimental words is proposed. SentiWordNet was adopted; this is the most widely used dictionary and contains about 100,000 words such as nouns, verbs, adjectives, and adverbs with polarities from -1.0 (extremely negative) to 1.0 (extremely positive). Second, corpora on subjective wellbeing (SWB corpora) were obtained by crawling online text. A survey was conducted to prepare a learning dataset that includes an individual's opinion and the level of self-report wellness, such as stress and depression. The participants were asked to respond with their feelings about online news on two topics. Next, three data sources were extracted from the SWB corpora: demographic information, psychographic information, and the structural characteristics of the text (e.g., the number of words used in the text, simple statistics on the special characters used). These were considered to adjust the level of a specific SWB. Finally, a set of reasoning rules was generated for each wellbeing factor to estimate the SWB of an individual based on the text written by the individual. The experimental results suggested that using contextual polarity for each SWB factor (e.g., stress, depression) significantly improved the estimation accuracy compared to conventional sentiment analysis methods incorporating SentiWordNet. Even though literature is available on Korean sentiment analysis, such studies only used only a limited set of sentimental words. Due to the small number of words, many sentences are overlooked and ignored when estimating the level of sentiment. However, the proposed method can identify multiple sentiment-neutral words as sentiment words in the context of a specific SWB factor. The results also suggest that a specific type of senti-word dictionary containing contextual polarity needs to be constructed along with a dictionary based on common sense such as SenticNet. These efforts will enrich and enlarge the application area of sentic computing. The study is helpful to practitioners and managers of wellness services in that a couple of characteristics of unstructured text have been identified for improving SWB. Consistent with the literature, the results showed that the gender and age affect the SWB state when the individual is exposed to an identical queue from the online text. In addition, the length of the textual response and usage pattern of special characters were found to indicate the individual's SWB. These imply that better SWB measurement should involve collecting the textual structure and the individual's demographic conditions. In the future, the proposed method should be improved by automated identification of the contextual polarity in order to enlarge the vocabulary in a cost-effective manner.

• Archives of design research
• /
• v.19 no.1 s.63
• /
• pp.201-214
• /
• 2006

Modern society is an age of vagueness and confusion. In addition, vagueness, complexity and variety are seen throughout art including modern philosophy, literature, and environmental design. A phenomenon like this shows that modern society has integrated different components as an organic relationship frequently crossing the boundary of fields. This feature can be regarded as hybrid related with accepting contradictory components and binding them into one under relationship between part and whole. As new design concept, presented are attitude to accept the two instead of attitude to select one of the alternatives, abundance instead of dearness, and ambiguity instead of simplicity. This principle has a crucial influence on creative design providing opposing contradiction and several alternative plans as non-deterministic form not completed one and, above all, useful information in mutual dependence and mutual relationship. When it comes to hybrid, therefore, a strategy is needed to consider layer of several fields getting out of standardizing space into a single space. As an event of this situation and concept, space experience means behaving freely based on experience of users' body. It can be known that this experience brings about users' more dynamic experience in comparison with the experience of seeing environmental design from a viewpoint of visual ism on the existing simplicity. Such a practical experience is subjective, synesthetic, and non-observational one. Therefore, hybrid has brought active users to the stage, which is distinguished from synesthesia felt through body's experience, not through observational attitude and visual space which achieve former balance and harmony with non-determination. That's because hybrid creatures are turning to a product resulted from creative imagination instead of from reappearance which makes text visualized. Such experience performed by user's active participation collapses the boundary between special elite-centered art and daily life and it is the present progressive form showing creation process of future events and new esthetic experience.

• Archives of design research
• /
• v.19 no.1 s.63
• /
• pp.253-262
• /
• 2006

Research of color has been developed and also has raised consumer desire through changing from a tool to pursue curiosity or beauty to a tool creating effects in the 20th century. People have been interested in colors as a dynamic expression of results since the color TV appeared. The meaning of colors has been recently diversified as the roles of colors became important to the emotional aspects of design. While auto colors have developed along with such changes of the times, black led the color trend during the first half of the 20th century from 1900 to 1950, a transitional period of economic growth and world war. Since then, automobile production has increased apace with the rapid economic growth throughout the world and automobiles became the most expensive item out of the goods that people use. Accordingly, increasing production induced facility investment in mass production and a technology leveling was achieved. Auto manufacturing processes are very complicated, auto makers gradually recognized that software changes such as to colors or materials was an easier way for the improvement of brand identity as opposed to hardware changes such as the mechanical or design components of the body. Color planning and development systems were segmented in various aspects. In the segmentation issue, pigment technology and painting methods are important elements that have an influence on body colors and have a higher technical correlation with colors than in other industries. In other words, the advanced mixture of pigments is creating new body colors that have not existed previously. This diversifies the painting structure and methods and so maximizes the transparency and depth of body colors. Thus, body colors that are closely related to technical factors will increase in the future and research on color preferences by region have been systemized to cope with global competition due to the expansion and change of auto export regions.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.16 no.1
• /
• pp.86-90
• /
• 2012

Purpose: Quantification of myocardial blood flow (MBF) using dynamic PET imaging has the potential to assess coronary artery disease. Rb-82 plays a key role in the clinical assessment of myocardial perfusion using PET. However, MBF could be overestimated due to the underestimation of left ventricular input function in the beginning of the acquisition when the scanner has non-linearity between count rate and activity concentration due to the scanner dead-time. Therefore, in this study, we evaluated the count rate linearity as a function of the activity concentration in PET data acquired in list mode. Materials & methods: A cylindrical phantom (diameter, 12 cm length, 10.5 cm) filled with 296 MBq F-18 solution and 800 mL of water was used to estimate the linearity of the Biograph 40 True Point PET/CT scanner. PET data was acquired with 10 min per frame of 1 bed duration in list mode for different activity concentration levels in 7 half-lives. The images were reconstructed by OSEM and FBP algorithms. Prompt, net true and random counts of PET data according to the activity concentration were measured. Total and background counts were measured by drawing ROI on the phantom images and linearity was measured using background correction. Results: The prompt count rates in list mode were linearly increased proportionally to the activity concentration. At a low activity concentration (<30 kBq/mL), the prompt net true and random count rates were increased with the activity concentration. At a high activity concentration (>30 kBq/mL), the increasing rate of the prompt net true rates was slightly decreased while the increasing rate of random counts was increased. There was no difference in the image intensity linearity between OSEM and FBP algorithms. Conclusion: The Biograph 40 True Point PET/CT scanner showed good linearity of count rate even at a high activity concentration (~370 kBq/mL).The result indicates that the scanner is useful for the quantitative analysis of data in heart dynamic studies using Rb-82, N-13, O-15 and F-18.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.22 no.2
• /
• pp.228-232
• /
• 2016

As the quantity of HNS sea trasport and the number of HNS accidents at sea are increasing recently, the importance of HNS management is emphasized so that we try to develop marine accident case standard code for making HNS accidents at sea databased systemically in this study. First and foremost, we draw the related requisites of essential accident reports along with internal and external decrees and established statistics of classified items for conducting study, and we referred to analogous standard codes obtained from developed countries in order to research code design. Code design is set like 'Accident occurrence ${\rightarrow}$ The initial accident information ${\rightarrow}$ Accident response ${\rightarrow}$ Accident investigation' in accordance with the general flow of marine HNS accidents of in which the accident information is input and queried. We classified initial accident information into the items of five categories and constructed "Preliminary Information Code(P.I.C.)". In addition we constructed accident response in two categories and accident investigation in three categories that get possible after the accident occurrence as called "Full Information(F.I.C.)", including the P.I.C. It is represented in 3 kinds of steps on each topic by departmentalizing the classified majority as classified middle class and classified minority. As a result of coding marine HNS accident and of the code to a typical example of marine HNS accident, HNS accident was ascertained to be represented sufficiently well. We expect that it is feasible to predict possible trouble or accident henceforward by applying code, and also consider that it is valuable to the preparedness, response and restoration in relation to HNS accidents at sea by managing systemically the data of marine HNS accidents which will occur in the future.

• The Korean Journal of Pesticide Science
• /
• v.17 no.2
• /
• pp.117-125
• /
• 2013

A probabilistic exposure assessment was performed on the monitoring data of pesticides were assessed in agricultural products in Gyeonggi-do from 2006 to 2010. Chlorothalonil, chlorpyrifos, dicofol, endosulfan, EPN, ethoprophos, fenitrothion, methidathion, phenthoate and tebupirimfos were assessed. For this assessment, we used Monte Carlo simulation software and the distribution of concentration and intake were assumed to lognormal distribution by inputting mean and standard deviation. The hazard index (HI, %ADI) of average value and the $95^{th}$ percentile based on a probabilistic method were usually lower than those by a deterministic one. For the whole population, when non-detects data were assigned 0 mg/kg, HI of the average value and the $95^{th}$ percentile showed 0.05~0.70% and 0.11~1.94%, respectively. When nondetects data were assigned 0.005 mg/kg, HI of the average value and the $95^{th}$ percentile were 0.41~4.42% and 0.98~13.81%. For only consumers, when non-detects data were assigned 0 mg/kg, HI of the average value and the $95^{th}$ percentile were 1.24~10.16% and 3.72~33.81%, respectively. When non-detects data were assigned 0.005 mg/kg, HI of the average value and the $95^{th}$ percentile were 3.43~18.26% and 9.45~54.99%, respectively. Methidathion had highest values when both of 0 and 0.005 were assigned to non-detecs data for consumers only. This study showed that agricultural products in Gyeonggi-do were safe because they had less than 100 of HI (%ADI) based on probabilistic exposure assessment.

• Journal of Intelligence and Information Systems
• /
• v.18 no.4
• /
• pp.1-17
• /
• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.

• The KIPS Transactions:PartD
• /
• v.12D no.3 s.99
• /
• pp.417-428
• /
• 2005

Today, IT organizations perform projects with vision related to marketing and financial profit. The objective of realizing the vision is to improve the project performing ability in terms of QCD. Organizations have made a lot of efforts to achieve this objective through process improvement. Large companies such as IBM, Ford, and GE have made over $80\%$ of success through business process re-engineering using information technology instead of business improvement effect by computers. It is important to collect, analyze and manage the data on performed projects to achieve the objective, but quantitative measurement is difficult as software is invisible and the effect and efficiency caused by process change are not visibly identified. Therefore, it is not easy to extract the strategy of improvement. This paper measures and analyzes the project performance, focusing on organizations' external effectiveness and internal efficiency (Qualify, Delivery, Cycle time, and Waste). Based on the measured project performance scores, an OT (Opportunity Tree) model was designed for optimizing the project performance. The process of design is as follows. First, meta data are derived from projects and analyzed by quantitative GQM(Goal-Question-Metric) questionnaire. Then, the project performance model is designed with the data obtained from the quantitative GQM questionnaire and organization's performance score for each area is calculated. The value is revised by integrating the measured scores by area vision weights from all stakeholders (CEO, middle-class managers, developer, investor, and custom). Through this, routes for improvement are presented and an optimized improvement method is suggested. Existing methods to improve software process have been highly effective in division of processes' but somewhat unsatisfactory in structural function to develop and systemically manage strategies by applying the processes to Projects. The proposed OT model provides a solution to this problem. The OT model is useful to provide an optimal improvement method in line with organization's goals and can reduce risks which may occur in the course of improving process if it is applied with proposed methods. In addition, satisfaction about the improvement strategy can be improved by obtaining input about vision weight from all stakeholders through the qualitative questionnaire and by reflecting it to the calculation. The OT is also useful to optimize the expansion of market and financial performance by controlling the ability of Quality, Delivery, Cycle time, and Waste.

• Nuclear Medicine and Molecular Imaging
• /
• v.41 no.4
• /
• pp.317-325
• /
• 2007

Purpose: Biological parameters can be quantified using dynamic PET data with compartment modeling and Nonlinear Least Square (NLS) estimation. However, the generation of parametric images using the NLS is not appropriate because of the initial value problem and excessive computation time. In irreversible model, Patlak graphical analysis (PGA) has been commonly used as an alternative to the NLS method. In PGA, however, the start time ($t^*$, time where linear phase starts) has to be determined. In this study, we suggest a new Multiple Linear Analysis for irreversible radiotracer (MLAIR) to estimate fluoride bone influx rate (Ki). Methods: $[^{18}F]Fluoride$ dynamic PET scans was acquired for 60 min in three normal mini-pigs. The plasma input curve was derived using blood sampling from the femoral artery. Tissue time-activity curves were measured by drawing region of interests (ROls) on the femur head, vertebra, and muscle. Parametric images of Ki were generated using MLAIR and PGA methods. Result: In ROI analysis, estimated Ki values using MLAIR and PGA method was slightly higher than those of NLS, but the results of MLAIR and PGA were equivalent. Patlak slopes (Ki) were changed with different $t^*$ in low uptake region. Compared with PGA, the quality of parametric image was considerably improved using new method. Conclusion: The results showed that the MLAIR was efficient and robust method for the generation of Ki parametric image from $[^{18}F]Fluoride$ PET. It will be also a good alternative to PGA for the radiotracers with irreversible three compartment model.