• The Journal of Advanced Prosthodontics
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• v.16 no.2
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• pp.91-104
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• 2024

PURPOSE. The objectives of the current study were to estimate the influence of self-reinforced hollow structures with a graded density on the dimensional accuracy, weight, and mechanical properties of Co-Cr objects printed with the direct metal laser sintering (DMLS) technique. MATERIALS AND METHODS. Sixty-five dog-bone samples were manufactured to evaluate the dimensional accuracy of printing, weight, and tensile properties of DMLS printed Co-Cr. They were divided into Group 1 (control) (n = 5), Group 2, 3, and 4 with incorporated hollow structures based on (spherical, elliptical, and diamond) shapes; they were subdivided into subgroups (n = 5) according to the volumetric reduction (10%, 15%, 20% and 25%). Radiographic imaging and microscopic analysis of the fractographs were conducted to validate the created geometries; the dimensional accuracy, weight, yield tensile strength, and modulus of elasticity were calculated. The data were estimated by one-way ANOVA and Duncan's tests at P < .05. RESULTS. The accuracy test showed an insignificant difference in the x, y, z directions in all printed groups. The weight was significantly reduced proportionally to the reduced volume fraction. The yield strength and elastic modulus of the control group and Group 2 at 10% volume reduction were comparable and significantly higher than the other subgroups. CONCLUSION. The printing accuracy was not affected by the presence or type of the hollow geometry. The weight of Group 2 at 10% reduction was significantly lower than that of the control group. The yield strength and elastic modulus of the Group 2 at a 10% reduction showed means equivalent to the compact objects and were significantly higher than other subgroups.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.157-166
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• 2024

Probability of decryption failure of a public key cryptography based on LWE(learning with errors) is determined by its architecture and parameter settings. Since large decryption failure probability leads to attacks[1] on scheme as well as degradation of performance, TiGER[2], a Ring-LWE(R)-based KEM proposed for the first round of KpqC, tried to reduce the decryption failure probability by using error correction code Xef and D2 encoding method. However, D'Anvers et al. has shown that the commonly assumed independence of each bit error is not established since in the case of an encryption scheme based on Ring-LWE(R) using an error correction code, there is error dependency which is not negligible[3]. In this paper, since TiGER does not consider the error dependency, we calcualte the decryption failure probability of TiGER by considering the error dependency. In addition, we found that the bit error probability is incorrectly calculated in TiGER, so we present the correct calculation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.167-177
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• 2024

This paper proposes optimization techniques for SeaSign, an isogeny-based digital signature algorithm. SeaSign combines class group actions of CSIDH with the Fiat-Shamir with abort. While CSIDH-based algorithms have regained attention due to polynomial time attacks for SIDH-based algorithms, SeaSiogn has not undergone significat optimization because of its inefficiency. In this paper, an efficient signing method for SeaSign is proposed. The proposed signing method is simple yet powerful, achived by repositioning the rejection sampling within the algorithm. Additionally, this paper presnts parameters that can provide optimal performance for the proposed algorithm. As a result, by using the original parameters of SeaSign, the proposed method is three times faster than the original SeaSign. Additonally, combining the newly suggested parameters with the signing method proposed in this paper yields a performance that is 290 times faster than the original SeaSign and 7.47 times faster than the method proposed by Decru et al.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.119-130
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• 2024

Universities are open systems that aim to prepare students to meet academic and industrial programs' expectations. It is important for universities to recognize these expectations and to make sure that they are achievable. To do so, graduates' progression tracking system is an essential tool for universities' development to ensure graduate students meet the market requirements. The purpose of this paper is to create automatic tracing system that captures information about students after graduation and creates annual report that represents the status of university students in term of employment or completing their study. It mainly assists graduates to find appropriate jobs that meet their desires or enabling them to complete their higher education by providing all these opportunities in one platform. The system main objective is to improve communication between graduate students, the university and companies. It also aims to identify the difficulties associated with graduate employability and changes are required to serve current students in term of creating new programs or activities. This helps universities to identify and address the existing curriculums and program's strengths and weaknesses and their adequacy, quality and competencies of a graduate in the labor market, which enhances the quality of higher education. we analyzed and implemented the tracing system using PHP language, which speeds up custom web application development and MySQL database, which guarantee data security, high performance, and other features. Graduate students found the proposed system usable and valuable.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.200-206
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• 2024

Laser induced breakdown spectroscopy (LIBS) technique has been used for the elemental composition of the soils. In this technique, a high energy laser pulse is focused on a sample to produce plasma. From the spectroscopic analysis of such plasma plume, we have determined the different elements present in the soil. This technique is effective and rapid for the qualitative and quantitative analysis of all type of samples. In this work a Q-switched Nd: YAG laser operating with its fundamental mode (1064 nm laser wavelength), 5 nanosecond pulse width, and 10 Hz repetition rate was focused on soil samples using 10 cm quartz lens. The emission spectra of soil consist of Iron (Fe), Calcium (Ca), Titanium (Ti), Silicon (Si), Aluminum (Al), Magnesium (Mg), Manganese (Mn), Potassium (K), Nickel (Ni), Chromium (Cr), Copper (Cu), Mercury (Hg), Barium (Ba), Vanadium (V), Lead (Pb), Nitrogen (N), Scandium (Sc), Hydrogen (H), Strontium (Sr), and Lithium (Li) with different finger-prints of the transition lines. The maximum intensity of the transition lines was observed close to the surface of the sample and it was decreased along the axial direction of the plasma expansion due to the thermalization and the recombination process. We have also determined the plasma parameters such as electron temperature and the electron number density of the plasma using Boltzmann's plot method as well as the Stark broadening of the transition lines respectively. The electron temperature is estimated at 14611 °K, whereas the electron number density i.e. 4.1 × 10¹⁶ cm^-3 lies close to the surface.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.601-607
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• 2024

The discharge of oily wastewater into water bodies and soil poses a serious hazard to the environment and public health. Various conventional techniques have been employed to treat oil-water mixtures and emulsions; Unfortunately, these approaches are frequently expensive, time-consuming, and unsatisfactory outcomes. Porous materials and adsorbents are commonly used for purification, but their use is limited by low separation efficiencies and the risk of secondary contamination. Recent advancements in nanotechnology have driven the development of innovative materials and technologies for oil-contaminated wastewater treatment. Nanomaterials can offer enhanced oil-water separation properties due to their high surface area and tunable surface chemistry. The fabrication of nanofiber membranes with precise pore sizes and surface properties can further improve separation efficiency. Notably, novel technologies have emerged utilizing nanomaterials with special surface wetting properties, such as superhydrophobicity, to selectively separate oil from oil-water mixtures or emulsions. These special wetting surfaces are promising for high-efficiency oil separation in emulsions and allow the use of materials with relatively large pores, enhancing throughput and separation efficiency. In this study, we introduce a facile and scalable method for fabrication of superhydrophobic-superoleophilic felt fabrics for oil/water mixture and emulsion separation. AlN nanopowders are hydrolyzed to create the desired microstructures, which firmly adhere to the fabric surface without the need for a binder resin, enabling specialized wetting properties. This approach is applicable regardless of the material's size and shape, enabling efficient separation of oil and water from oil-water mixtures and emulsions. The oil-water separation materials proposed in this study exhibit low cost, high scalability, and efficiency, demonstrating their potential for broad industrial applications.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.178-188
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• 2024

In the near future, it is expected that there will be billions of connected devices using fifth generation (5G) network services. The recently available base stations (BSs) need to mitigate their loads without changing and at the least monetary cost. The available spectrum resources are limited and need to be exploited in an efficient way to meet the ever-increasing demand for services. Device to Device communication (D2D) technology will likely help satisfy the rapidly increasing capacity and also effectively offload traffic from the BS by distributing the transmission between D2D users from one side and the cellular users and the BS from the other side. In this paper, we propose to apply D2D overlay communication with cognitive radio capability in 5G networks to exploit unused spectrum resources taking into account the dynamic spectrum access. The performance metrics; throughput and delay are formulated and analyzed for CSMA-based medium access control (MAC) protocol that utilizes a common control channel for device users to negotiate the data channel and address the contention between those users. Device users can exploit the cognitive radio to access the data channels concurrently in the common interference area. Estimating the achievable throughput and delay in D2D communication in 5G networks is not exploited in previous studies using cognitive radio with CSMA-based MAC protocol to address the contention. From performance analysis, applying cognitive radio capability in D2D communication and allocating a common control channel for device users effectively improve the total aggregated network throughput by more than 60% compared to the individual D2D throughput without adding harmful interference to cellular network users. This approach can also reduce the delay.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.51-60
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• 2024

Aiming at the problem of low contrast and difficult to recognize video images in low-light environment, we propose an adaptive contrast compensation enhancement algorithm based on human visual perception. First of all, the video image characteristic factors in low-light environment are extracted: AL (average luminance), ABWF (average bandwidth factor), and the mathematical model of human visual CRC(contrast resolution compensation) is established according to the difference of the original image's grayscale/chromaticity level, and the proportion of the three primary colors of the true color is compensated by the integral, respectively. Then, when the degree of compensation is lower than the bright vision precisely distinguishable difference, the compensation threshold is set to linearly compensate the bright vision to the full bandwidth. Finally, the automatic optimization model of the compensation ratio coefficient is established by combining the subjective image quality evaluation and the image characteristic factor. The experimental test results show that the video image adaptive enhancement algorithm has good enhancement effect, good real-time performance, can effectively mine the dark vision information, and can be widely used in different scenes.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.59-70
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• 2024

Background: The COVID-19 pandemic (the form of coronaviruses) developed at the end of 2019 and spread rapidly to almost every corner of the world. It has infected around 25,334,339 of the world population by the end of September 1, 2020 [1] . It has been spreading ever since, and the peak specific to every country has been rising and falling and does not seem to be over yet. Currently, the conventional RT-PCR testing is required to detect COVID-19, but the alternative method for data archiving purposes is certainly another choice for public departments to make. Researchers are trying to use medical images such as X-ray and Computed Tomography (CT) to easily diagnose the virus with the aid of Artificial Intelligence (AI)-based software. Method: This review paper provides an investigation of a newly emerging machine-learning method used to detect COVID-19 from X-ray images instead of using other methods of tests performed by medical experts. The facilities of computer vision enable us to develop an automated model that has clinical abilities of early detection of the disease. We have explored the researchers' focus on the modalities, images of datasets for use by the machine learning methods, and output metrics used to test the research in this field. Finally, the paper concludes by referring to the key problems posed by identifying COVID-19 using machine learning and future work studies. Result: This review's findings can be useful for public and private sectors to utilize the X-ray images and deployment of resources before the pandemic can reach its peaks, enabling the healthcare system with cushion time to bear the impact of the unfavorable circumstances of the pandemic is sure to cause

• Journal of Environmental Science International
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• v.33 no.5
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• pp.283-296
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• 2024

This study examined the distribution of airborne metals concentrations and conducted a risk assessment in PM-10 in Gwangju from 2014 to 2022. There were a total of six points, and the concentration of heavy metals at each point was highest in the order of Pyeong-dong(1.5472 ㎍/m³ ) > Nongseong-dong(1.2093 ㎍/m³ ) > Geonguk-dong(1.0100 ㎍/m³ ) > Duam-dong(0.9684 ㎍/m³ ) > Seo-dong(0.9515 ㎍/m³ ) > Nodae-dong(0.8321 ㎍/m³ ). In recent years, the concentration of heavy metals in the atmosphere has generally risen, accompanied by an increase in heavy metals in the soil. The average seasonal concentrations were in the following order: spring(1.4448 ㎍/m³ ) > winter(1.2939 ㎍/m³ ) > fall(0.8303 ㎍/m³ ) > summer (0.5928 ㎍/m³ ). The atmospheric heavy metals most correlated with PM-10 were Ca(0.69), Fe(0.62), Al(0.62) and Mg(0.60). Within the acceptable risk level (1.0E-06) set in this study, heavy metals in the atmosphere were found to have the most excess cancer risk, and the integrated non-cancer risk was as low as 1 or less.