• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.4
• /
• pp.169-176
• /
• 2021

Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation. We first generate gridded trajectory images by mapping the raw vessel trajectories into two dimensional matrix. Based on the gridded image input, we test the proposed model along with the other deep autoencoder-based models for the abnormal trajectory data generated through rotation and speed variation from normal trajectories. We show that the proposed model improves detection accuracy for the generated abnormal trajectories compared to the other models.

• Current Optics and Photonics
• /
• v.5 no.6
• /
• pp.699-710
• /
• 2021

In this study, we propose a biomimetic optical structure design methodology for investigating micro-optical mechanisms associated with the compound eyes of insects. With these compound eyes, insects can respond fast while maintaining a wide field of view. Also, considerable research attention has been focused on the insect compound eyes to utilize these benefits. However, their nano micro-structures are complex and challenging to demonstrate in real applications. An effectively integrated design methodology is required considering the manufacturing difficulty. We show that photorealistic ray-traced visualization is an effective method for designing the biomimetic of a micro-compound eye of an insect. We analyze the image formation mechanism and create a three-dimensional computer-aided design model. Then, a ray-trace visualization is applied to observe the optical image formation. Finally, the segmented images are stitched together to generate an image with a wide-angle; the image is assessed for quality. The high structural similarity index (SSIM) value (approximately 0.84 to 0.89) of the stitched image proves that the proposed MATLAB-based image stitching algorithm performs effectively and comparably to the commercial software. The results may be employed for the understanding, researching, and design of advanced optical systems based on biological eyes and for other industrial applications.

• Composite Materials and Engineering
• /
• v.3 no.3
• /
• pp.221-239
• /
• 2021

This paper presents a multiscale modeling method for sheet molding compound (SMC) composites through a novel bundle packing reconstruction algorithm based on a micro-CT (Computed Tomography) image processing. Due to the complex flow pattern during the compression molding process, the SMC composites show a spatially varying orientation and overlapping of fiber bundles. Therefore, significant inhomogeneity and anisotropy are commonly observed and pose a tremendous challenge to predicting SMC composites' properties. For high-fidelity modeling of the SMC composites, the statistical distributions for the fiber orientation and local volume fraction are characterized from micro-CT images of real SMC composites. After that, a novel bundle packing reconstruction algorithm for a high-fidelity SMC model is proposed by considering the statistical distributions. A method for evaluating specimen level's strength and stiffness is also proposed from a set of high-fidelity SMC models. Finally, the proposed multiscale modeling methodology is experimentally validated through a tensile test.

• International Journal of Computer Science & Network Security
• /
• v.22 no.6
• /
• pp.145-156
• /
• 2022

Children are the foundation and future of this society and understanding their impressions and behaviors is very important and the child's behavioral problems are a burden on the family and society as well as have a bad impact on the development of the child, and the early diagnosis of these problems helps to solve or mitigate them, and in this research project we aim to understand and know the behaviors of children, through artificial intelligence algorithms that helped solve many complex problems in an automated system, By using this technique to read and analyze the behaviors and feelings of the child by reading the features of the child's face, the movement of the child's body, the method of the child's session and nervous emotions, and by analyzing these factors we can predict the feelings and behaviors of children from grief, tension, happiness and anger as well as determine whether this child has the autism spectrum or not. The scarcity of studies and the privacy of data and its scarcity on these behaviors and feelings limited researchers in the process of analysis and training to the model presented in a set of images, videos and audio recordings that can be connected, this model results in understanding the feelings of children and their behaviors and helps doctors and specialists to understand and know these behaviors and feelings.

• The Journal of Information Technology and Database
• /
• v.1 no.1
• /
• pp.31-62
• /
• 1994

Information systems for application areas like office automation, customer service or computer aided manufacturing are usually highly interactive and deal with complex document structures composed of multiple media formats. For the realization of these systems, nonstandard database systems, which we call document databases, need to handle different types of coarse-and fine-grained document objects(like full-text documents, graphics and images), hierarchical and non-hierarchical relationships between objects(like composition-links and cross-references using hypertext structures) and document attributes of different types such as formatting/presentation information and access control. In this paper, we present the underlying data model for document databases based on descriptive markup languages that provide mechanisms for specifying the logical structure(or schema) of individual documents stored in the database. We then describe extensions to the data model for supporting notion of composite structures("join" operators for documents) --composition and hyperlinking mechanisms for representing compound documents and inter-linked documents as unique entites separate from their components. Furthermore, due to the interactive nature of the application domains, the database system in conjunction with clients(or browsers) has to support visual navigation and graphical query mechanisms. We describe the functionality of a new user interface paradigm called HyBrow for meeting the above mentioned requirements. The underlying implementation strategy is also discussed.discussed.

• Journal of Radiopharmaceuticals and Molecular Probes
• /
• v.8 no.2
• /
• pp.139-150
• /
• 2022

Theranostics, a composite word of therapy and diagnosis, is known as personalized medicine and the concept of diagnosis and treatment at the same time. In nuclear medicine, it means performing both therapeutic and diagnostic radioisotope therapy using the same target molecule. The increased production and utilization of ⁶⁴Cu opens a new era of theranostics. The studies introduced here have shown that ⁶⁴CuCl₂ and various compounds or biomolecules labeled with ⁶⁴Cu are unique radiopharmaceuticals with physiological properties suitable for use as diagnostic and therapeutic agents. So far, these two abilities have been described only for radioactive iodine. Although ⁶⁴Cu has complex chemical properties compared to other PET radioisotopes such as ⁶⁸Ga, it has an appropriate half-life and enables high-quality PET images similar to ¹⁸F, which is an advantage in terms of diagnosis. In addition, since it also has therapeutic properties through the release of β^- particles and Auger electrons by electron capture, radiopharmaceuticals using ⁶⁴Cu stand for innovative radiopharmaceuticals for theranostic purposes. Therefore, based on the initial results obtained using ⁶⁴Cu as a therapeutic agent, it is expected that additional research on the application of ⁶⁴Cu will lead to a new era in the theranostics field.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.133-135
• /
• 2022

With the development of IoT and AI technologies and media, various digital devices are being used, and unmanned and automation is progressing rapidly. In particular, high-level image processing technology is required in fields such as smart factories, autonomous driving technology, and intelligent CCTV. However, noise present in the image affects processes such as edge detection and object recognition, and causes deterioration of system accuracy and reliability. In this paper, we propose a filtering algorithm using fuzzy weights to reconstruct images damaged by complex noise. The proposed algorithm obtains a reference value using noise judgment and calculates the final output by applying a fuzzy weight. Simulation was conducted to verify the performance of the proposed algorithm, and the result image was compared with the existing filter algorithm and evaluated.

• The Research Journal of the Costume Culture
• /
• v.30 no.6
• /
• pp.898-918
• /
• 2022

Contemporary fashion research has paid increasing attention to the sublimity in the context of postmodernism. Sublimity is considered essential in contemporary fashion design as it arouses complex emotions which verbal expression cannot describe. Therefore, contemporary fashion designs need to be interpreted in terms of the sublimity. Through a detailed review of literature, the present study discusses Kantian and Lyotardian sublimity as main theories representing conventional and cotemporary concepts of sublimity. This paper selected five Korean fashion designers who won the prize of Samsung Design Fund from 2006 to 2019 and actively introduce their works every year. Images were collected to analyze their designs introduced from 2018 S/S to 2019F/W at their website. In addition, formative and color characteristics were analyzed to identify the changing features of s sublimity. Major findings of analyses are as follows. First, all designers' collections reflected both male and female sublimity with the respect to its formative characteristics. Color characteristics of sublimity indicated that Jeong, Wook Jun's collections represented features of male sublimity and other designers works showed elements of female sublimity. Essentially, the typical contemporary concept of the sublimity was found in the designs of Seo, Hye In. Consequently, female sublimity is more inclusive than male sublimity, while being opened to otherness.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.5
• /
• pp.1466-1488
• /
• 2022

Recently, the importance and necessity of artificial intelligence (AI), especially machine learning, has been emphasized. In fact, studies are actively underway to solve complex and challenging problems through the use of AI systems, such as intelligent CCTVs, intelligent AI security systems, and AI surgical robots. Information security that involves analysis and response to security vulnerabilities of software is no exception to this and is recognized as one of the fields wherein significant results are expected when AI is applied. This is because the frequency of malware incidents is gradually increasing, and the available security technologies are limited with regard to the use of software security experts or source code analysis tools. We conducted a study on MalDC, a technique that converts malware into images using machine learning, MalDC showed good performance and was able to analyze and classify different types of malware. MalDC applies a preprocessing step to minimize the noise generated in the image conversion process and employs an image augmentation technique to reinforce the insufficient dataset, thus improving the accuracy of the malware classification. To verify the feasibility of our method, we tested the malware classification technique used by MalDC on a dataset provided by Microsoft and malware data collected by the Korea Internet & Security Agency (KISA). Consequently, an accuracy of 97% was achieved.

• ETRI Journal
• /
• v.44 no.1
• /
• pp.51-61
• /
• 2022

In this paper, we introduced a novel voxel-wise UV parameterization and view-dependent texture synthesis for the immersive rendering of a truncated signed distance field (TSDF) scene model. The proposed UV parameterization delegates a precomputed UV map to each voxel using the UV map lookup table and consequently, enabling efficient and high-quality texture mapping without a complex process. By leveraging the convenient UV parameterization, our view-dependent texture synthesis method extracts a set of local texture maps for each voxel from the multiview color images and separates them into a single view-independent diffuse map and a set of weight coefficients for an orthogonal specular map basis. Furthermore, the view-dependent specular maps for an arbitrary view are estimated by combining the specular weights of each source view using the location of the arbitrary and source viewpoints to generate the view-dependent textures for arbitrary views. The experimental results demonstrate that the proposed method effectively synthesizes texture for an arbitrary view, thereby enabling the visualization of view-dependent effects, such as specularity and mirror reflection.