• Journal of Convergence for Information Technology
• /
• v.11 no.5
• /
• pp.30-37
• /
• 2021

Various devices are connected to the Internet, and attacks using the Internet are occurring. Among such attacks, there are attacks that use malicious URLs to make users access to wrong phishing sites or distribute malicious viruses. Therefore, how to detect such malicious URL attacks is one of the important security issues. Among recent deep learning technologies, neural networks are showing good performance in image recognition, speech recognition, and pattern recognition. This neural network can be applied to research that analyzes and detects patterns of malicious URL characteristics. In this paper, performance analysis according to various parameters was performed on a method of detecting malicious URLs using neural networks. In this paper, malicious URL detection performance was analyzed while changing the activation function, learning rate, and neural network structure. The experimental data was crawled by Alexa top 1 million and Whois to build the data, and the machine learning library used TensorFlow. As a result of the experiment, when the number of layers is 4, the learning rate is 0.005, and the number of nodes in each layer is 100, the accuracy of 97.8% and the f1 score of 92.94% are obtained.

• Journal of Conservation Science
• /
• v.37 no.3
• /
• pp.289-301
• /
• 2021

When investigating old, printed documents, determining whether a work is printed on a woodblock or using a movable metal type is crucial. It is because the history of printing in Korea and across the world relies on determining the relevant printing invention used and the time of use of the movable metal type. Deciphering details from woodblock and metal prints requires various kinds of information regarding the imprint and the work's printing background, such as information on the characters in the printed document, the outline of the pages, the type of ink used, the production period of the ink, and the production period of the Korean paper. Analyzing such information can generally reveal the production period and the methods used on the old document. However, as such information is not documented systematically, relying on the researcher's judgment based on their experience and perception becomes inevitable. This study conducted an experimental investigation of the printing characteristics of woodblock prints using a replicated woodblock of the Wanpanbon edition of the Shimcheongjeon. Subsequently, the various phenomena and characteristics appearing on the woodblock prints were documented for future reference to determine the printing method of old documents. Finally, woodblock novels without an imprint may be used as a reference to estimate the printing dates by determining the degree of wear on the woodblock.

• Journal of the Korean Society of Floral Art and Design
• /
• no.44
• /
• pp.75-100
• /
• 2021

The purpose of this study is to explore ways in which the flower design industry can utilize podcasts that are rapidly growing in recent years. I selected foreign flower podcasts that are ranked on the global podcast chart, and examined the genre, content, components, show hosts and etc. By analyzing the characteristics of the podcast, the type of communication between the host and the audience, the audience interaction, the industry connection, and the media expansion strategy, I tried to derive the possibility of the flower podcast in Korea. As a result of analyzing foreign flower podcasts, podcasters built listener communities based on their rich experience and knowledge through podcasts and used them for education and marketing. They acted as leaders in the industry or led public opinion such as the sustainable flower industry. Podcast shows were repurposed as various content and used to spread flower design culture. In Korea, flower podcasts can be the basis for the formation of a community related to the flower design industry. Flower design experts can use podcasts as a source asset for various content. Listeners within the industry can get hands-on knowledge about the business from flower podcasts. The popular flower podcast will contribute to the vitalization of flower design culture and industry. Flower podcasts can be a starting point to actively cope with the era of personal media.

• International Journal of Computer Science & Network Security
• /
• v.22 no.8
• /
• pp.197-207
• /
• 2022

Given the prevalence of violence in Ukrainian families, measures to prevent parental abusive treatment against children are urgent. It is important to study today's youth awareness about violence within families in order to enhance a culture of engagement with spouses and children in future. The aim of the study is to examine students' reflective experiences and their attitudes towards forms, frequency, causes and effects of parental abusive treatment. During the research the following methods were used step-by-step: theoretical analyses of scientific resources, anonymous questionnaire, quantitative and correlation analyses. According to result of survey 98 students who were interviewed, none of them fell victim of sexual abuse in their families. However, more than a half (51%) of the students surveyed experienced some forms of parental physical punishment. All the interviewed students encountered psychological cases of parental violence. The mostprevalent forms of parental abuse among the interviewees are criticism, negative comparison, emotional detachment, arrogance, intimidation, blackmail and humiliation. The most prevalent consequences of parental abuse among students are anxiety, low self-esteem, insecurity, impatience, suspiciousness, constraint in communication. Students agree that budget limitations, forced labor, criticism, spanking, emotional detachment, ignoring type of communication, reproach, blackmail are acceptable methods of punishment to use when raising their own children. These results clearly demonstrate the problem of the impact of parental abuse on children and its consequences in the future. A virtual dimension of the actualized problem is considered, namely: - virtualization of aggression and cruelty in the postmodern world. - the level of determining the factor of cruelty from the space of virtual culture. - the mirror image of everyday cruelty in the virtual environment; - the phenomenon of video games as a source and context of representation of the factor of cruelty in behavioral realities; - cybercrime as a virtualized result of cruelty in family and everyday realities. - futurological perspectives of virtualization of cruelty in communicative culture in general and in family relations in particular. The postmodern world is fundamentally different from the traditions and culture of the past, primarily due to the development of computer technologies and the virtualization of life in general. So, for example, virtual communities have become, in a certain way, another world, a second reality of life in general. And certain behavioral factors, in particular cruelty in the private environment, became a projection of such a phenomenon as cybercrime. Video games are a unique modern phenomenon, which multipolarly absorb all facets of human potential, communicative tendencies, behavioral and characterological factors, from the warmth of interpersonal relationships to the extreme degree of cruelty.

• Journal of Intelligence and Information Systems
• /
• v.28 no.2
• /
• pp.57-74
• /
• 2022

Recently, artificial intelligence parking control systems have increased the recognition rate of vehicle license plates using deep learning, but there is a problem that they cannot determine vehicles with fake license plates. Despite these security problems, several institutions have been using the existing system so far. For example, in an experiment using a counterfeit license plate, there are cases of successful entry into major government agencies. This paper proposes an improved system over the existing artificial intelligence parking control system to prevent vehicles with such fake license plates from entering. The proposed method is to use the degree of matching of the front feature points of the vehicle as a passing criterion using the ORB algorithm that extracts information on feature points characterized by an image, just as the existing system uses the matching of vehicle license plates as a passing criterion. In addition, a procedure for checking whether a vehicle exists inside was included in the proposed system to prevent the entry of the same type of vehicle with a fake license plate. As a result of the experiment, it showed the improved performance in identifying vehicles with fake license plates compared to the existing system. These results confirmed that the methods proposed in this paper could be applied to the existing parking control system while taking the flow of the original artificial intelligence parking control system to prevent vehicles with fake license plates from entering.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.9
• /
• pp.363-370
• /
• 2022

Grasping a target object among clutter objects without collision requires machine intelligence. Machine intelligence includes environment recognition, target & obstacle recognition, collision-free path planning, and object grasping intelligence of robot hands. In this work, we implement such system in simulation and hardware to grasp a target object without collision. We use a RGB-D image sensor to recognize the environment and objects. Various path-finding algorithms been implemented and tested to find collision-free paths. Finally for an anthropomorphic robot hand, object grasping intelligence is learned through deep reinforcement learning. In our simulation environment, grasping a target out of five clutter objects, showed an average success rate of 78.8%and a collision rate of 34% without path planning. Whereas our system combined with path planning showed an average success rate of 94% and an average collision rate of 20%. In our hardware environment grasping a target out of three clutter objects showed an average success rate of 30% and a collision rate of 97% without path planning whereas our system combined with path planning showed an average success rate of 90% and an average collision rate of 23%. Our results show that grasping a target object in clutter is feasible with vision intelligence, path planning, and deep RL.

• Journal of Advanced Technology Convergence
• /
• v.1 no.1
• /
• pp.15-24
• /
• 2022

This paper tried to investigate the moderating effect of chemyon sensitivity and usage situation in the relationship between self-presentation and brand preference. Data were collected from students of universities located in Chungnam. The analysis results can be summarized as follows. First of all, the effect of self-presentation on symbolic brand preference was not significant in both public and private use situations. On the other hand, the effect of self-presentation on functional brand preference was found to be significant in both situations. Second, the main effect of chemyon sensitivity was significant only when it had a negative effect on functional brand preference in public situations, but was not significant in other cases. Third, looking at the interaction effect of self-presentation and chemyon sensitivity, the brand preference did not show significant changes in those with relatively low chemyon sensitivity, regardless of the level of self-presentation, whether in public or private situations. This study is meaningful in that it reveals that chemyon sensitivity affects brand preference through interaction with self-presentation, whether the consumption situation is public or private.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.15 no.4
• /
• pp.257-270
• /
• 2022

In this paper, we design a smart factory risk improvement system and risk improvement method using AI edge devices. The smart factory risk improvement system collects, analyzes, prevents, and promptly responds to the worker's work performance process in the smart factory using AI edge devices, and can reduce the risk that may occur during work with improving the defect rate when workers perfom jobs. In particular, based on worker image information, worker biometric information, equipment operation information, and quality information of manufactured products, it is possible to set an abnormal risk condition, and it is possible to improve the risk so that the work is efficient and for the accurate performance. In addition, all data collected from cameras and IoT sensors inside the smart factory are processed by the AI edge device instead of all data being sent to the cloud, and only necessary data can be transmitted to the cloud, so the processing speed is fast and it has the advantage that security problems are low. Additionally, the use of AI edge devices has the advantage of reducing of data communication costs and the costs of data transmission bandwidth acquisition due to decrease of the amount of data transmission to the cloud.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.67 no.4
• /
• pp.274-284
• /
• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.6
• /
• pp.275-284
• /
• 2023

Virtual reality simulations are used for education and training in various fields, and are especially widely used in the medical field recently. The education/training simulator consists of tactile/force feedback generation and image/sound output hardware that provides a sense similar to a doctor's treatment of a real patient using real surgical tools, and software that produces realistic images and tactile feedback. Existing simulators are complicated and expensive because they have to use various types of hardware to simulate various surgical instruments used during surgery. In this paper, we propose a dental surgical simulation system using a force feedback device and a morphable haptic controller. Haptic hardware determines whether the surgical tool collides with the surgical site and provides a sense of resistance and vibration. In particular, haptic controllers that can be deformed, such as length changes and bending, can express various senses felt depending on the shape of various surgical tools. When the user manipulates the haptic feedback device, events such as movement of the haptic feedback device or button clicks are delivered to the simulation system, resulting in interaction between dental surgical tools and oral internal models, and thus haptic feedback is delivered to the haptic feedback device. Using these basic techniques, we provide a realistic training experience of impacted wisdom tooth extraction surgery, a representative dental surgery technique, in a virtual environment represented by sophisticated three-dimensional models.