• Tribology and Lubricants
• /
• v.37 no.6
• /
• pp.240-245
• /
• 2021

Ceramic coatings with high hardness and excellent chemical stability have been successfully applied to various machine elements, tools, and implants. However, in the case of monolayer coating on soft substrates, a high-stress concentration at the interface between the coating and the substrate causes delamination of the coating layer. Recently, to overcome this problem, multilayer coatings with a metal layer with a low modulus of elasticity added between the ceramic and the substrate have been widely applied. This study presents the third part of a recent study and focuses on the effect of the number of coating layers on the Brinell hardness of multilayered coating with TiN/Ti, following the two previous studies on a new Brinell hardness test method for a coated surface and on the influence of substrate and coating thickness. Indentation analyses are performed using finite element analysis software, von Mises stress and equivalent plastic strain distributions, load-displacement curves, and residual indentation shapes are presented. The number of TiN/Ti layers considerably affect the stress distributions and indentation shapes. Moreover, the greater the number of TiN/Ti layers, the higher is the Brinell hardness. The stress and plastic strain distributions confirm that the multilayer coatings improve the wear resistance. The results are expected to be used to design and evaluate various coating systems, and additional study is required.

• Tribology and Lubricants
• /
• v.39 no.1
• /
• pp.21-27
• /
• 2023

Surface texturing is widely applied to friction surfaces of various machine elements. Most of the theoretical studies have focused on isothermal (ISO) analyses which consider constant lubricant viscosity. However, there have been limited studies on the effect of oil temperature increase owing to viscous shear. Following the first part of the present study that investigated the effects of film-temperature boundary condition (FTBC) and groove number on the thermohydrodynamic (THD) lubrication characteristics of a surface-textured parallel thrust bearing with multiple rectangular grooves, this study focuses on the effect of groove depths. Current study numerically analyzes the continuity, Navier-Stokes, and energy equations with temperature-viscosity-density relations using a commercial computational fluid dynamics (CFD) software, FLUENT. The results of variation in temperature, velocity, and pressure distributions as well as load-carrying capacity (LCC) and friction force indicate that groove depth and FTBC significantly influence the temperature distribution and pressure generation. The LCC is maximum near the groove depth at which the vortex starts, smaller than the ISO result. For intense grooves, the LCC of THD may be larger than that from ISO. The frictional force decreases as the groove becomes deeper, and decreases more significantly in the case of THD. The study shows that groove depth significantly influences the THD lubrication characteristics of surface-textured parallel thrust bearings.

• International Journal of Computer Science & Network Security
• /
• v.24 no.2
• /
• pp.43-52
• /
• 2024

Medical imaginings assume a important part in the analysis of tumors and cerebrospinal fluid (CSF) leak. Magnetic resonance imaging (MRI) is an image segmentation technology, which shows an angular sectional perspective of the body which provides convenience to medical specialists to examine the patients. The images generated by MRI are detailed, which enable medical specialists to identify affected areas to help them diagnose disease. MRI imaging is usually a basic part of diagnostic and treatment. In this research, we propose new techniques using the 4D-MRI image segmentation process to detect the brain tumor in the skull. We identify the issues related to the quality of cerebrum disease images or CSF leakage (discover fluid inside the brain). The aim of this research is to construct a framework that can identify cancer-damaged areas to be isolated from non-tumor. We use 4D image light field segmentation, which is followed by MATLAB modeling techniques, and measure the size of brain-damaged cells deep inside CSF. Data is usually collected from the support vector machine (SVM) tool using MATLAB's included K-Nearest Neighbor (KNN) algorithm. We propose a 4D light field tool (LFT) modulation method that can be used for the light editing field application. Depending on the input of the user, an objective evaluation of each ray is evaluated using the KNN to maintain the 4D frequency (redundancy). These light fields' approaches can help increase the efficiency of device segmentation and light field composite pipeline editing, as they minimize boundary artefacts.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.19 no.1
• /
• pp.95-107
• /
• 2017

In this study, a preliminary study was undertaken for development of a tunnel incident automatic detection system based on a machine learning algorithm which is to detect a number of incidents taking place in tunnel in real time and also to be able to identify the type of incident. Two road sites where CCTVs are operating have been selected and a part of CCTV images are treated to produce sets of training data. The data sets are composed of position and time information of moving objects on CCTV screen which are extracted by initially detecting and tracking of incoming objects into CCTV screen by using a conventional image processing technique available in this study. And the data sets are matched with 6 categories of events such as lane change, stoping, etc which are also involved in the training data sets. The training data are learnt by a resilience neural network where two hidden layers are applied and 9 architectural models are set up for parametric studies, from which the architectural model, 300(first hidden layer)-150(second hidden layer) is found to be optimum in highest accuracy with respect to training data as well as testing data not used for training. From this study, it was shown that the highly variable and complex traffic and incident features could be well identified without any definition of feature regulation by using a concept of machine learning. In addition, detection capability and accuracy of the machine learning based system will be automatically enhanced as much as big data of CCTV images in tunnel becomes rich.

• Journal of Practical Engineering Education
• /
• v.15 no.1
• /
• pp.119-126
• /
• 2023

Today, in order to improve fuel efficiency and dynamic behavior of automobiles, an era of light weight and simplification of automobile parts is being formed. In order to simplify and design and manufacture the shape of the product, various components are integrated. For example, in order to commercialize three products into one product, product processing is occurring to a very narrow area. In the case of existing parts, precision die casting or casting production is used for processing convenience, and the multi-piece method requires a lot of processes and reduces the precision and strength of the parts. It is very advantageous to manufacture integrally to simplify the processing air and secure the strength of the parts, but if a deep and narrow pocket part needs to be processed, it cannot be processed with the equipment's own spindle. To solve a problem, research on cutting processing is being actively conducted, and multi-axis composite processing technology not only solves this problem. It has many advantages, such as being able to cut into composite shapes that have been difficult to flexibly cut through various processes with one machine tool so far. However, the reality is that expensive equipment increases manufacturing costs and lacks engineers who can operate the machine. In the five-axis cutting processing machine, when producing products with deep and narrow sections, the cycle time increases in product production due to the indirectness of tools, and many problems occur in processing. Therefore, dedicated machine tools and multi-axis composite machines should be used. Alternatively, an angle spindle may be used as a special tool capable of multi-axis composite machining of five or more axes in a three-axis machining center. Various and continuous studies are needed in areas such as processing vibration absorption, low heat generation and operational stability, excellent dimensional stability, and strength securing by using the angle spindle.

• The Transactions of the Korea Information Processing Society
• /
• v.2 no.6
• /
• pp.847-856
• /
• 1995

When a human recognizes nouns in a sentence, s/he associates them with the hyper concepts of onus. For computer to simulate the human's word recognition, it should build the knowledge base (WordNet)for the hyper concepts of words. Until now, works for the WordNet haven't been performed in Korea, because they need lots of human efforts and time. But, as the power of computer is radically improved and common MRD becomes available, it is more feasible to automatically construct the WordNet. This paper proposes the method that automatically builds the WordNet of Korean nouns by using the descripti on of onus in Korean MRD, and it proposes the rules for extracting the hyper concepts (hypernyms)by analyzing structrual characteristics of Korean. The rules effect such characteristics as a headword lies on the rear part of sentences and the descriptive sentences of nouns have special structure. In addition, the WordNet prototype of Korean Nouns is developed, which is made by combining the hypernyms produced by the rules mentioned above. It extracts the hypernyms of about 2,500 sample words, and the result shows that about 92per cents of hypernyms are correct.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.43 no.6 s.312
• /
• pp.43-51
• /
• 2006

This paper proposes a metrics for example matching under the example-based machine translation for English-Korean machine translation. Our metrics served as similarity measure is based on edit-distance algorithm, and it is employed to retrieve the most similar example sentences to a given query. Basically it makes use of simple information such as lemma and part-of-speech information of typographically mismatched words. Edit-distance algorithm cannot fully reflect the context of matched word units. In other words, only if matched word units are ordered, it is considered that the contribution of full matching context to similarity is identical to that of partial matching context for the sequence of words in which mismatching word units are intervened. To overcome this drawback, we propose the context-weighting scheme that uses the contiguity information of matched word units to catch the full context. To change the edit-distance metrics representing dissimilarity to similarity metrics, to apply this context-weighted metrics to the example matching problem and also to rank by similarity, we normalize it. In addition, we generalize previous methods using some linguistic information to one representative system. In order to verify the correctness of the proposed context-weighted metrics, we carry out the experiment to compare it with generalized previous methods.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.47 no.3
• /
• pp.183-193
• /
• 2011

This study made a comparative analysis of behavioral reaction of squid to red (624nm), green (524nm), blue (460nm) & white LED light, its arrival time for the shadow section by making the shadow section in the central section of a water tank just like the bottom part of a squid jigging vessel, and on-site catching efficiency of LED fishing lamp with control fishing vessel. The color LED light showing the highest squidgathering rate as against the shadow section was found to be blue LED light with 39.3% rate under the dark (0.05lx) condition. Under the brighter condition than 0.05lx, white LED light was found to have the highest gathering rate of 41.5%. In addition, it was found that squid gathering rate was high at the shadow section which showed 6.3-fold brightness difference between the shadow section and bright section. As for the arrival time for the shadow section, blue LED light was found to be the fastest in attracting squids in 192.7 seconds under the dark condition while the red LED light was the fastest in luring squids in 164.6 seconds under the bright condition. The ratio of the squid-jigging operation and sailing in fuel consumption of the fishing vessel loaded with LED fishing lamp is about 7 to 1, showing most of the fuel is consumed more in sailing than in squid-jigging operation. As for a catch of squid, the control vessel loaded with MH (Metal Halide) fishing lamp had more catch of 600-7,080 squids than the vessel loaded with LED fishing lamp having a catch of 260-1,700 squids. In addition, even in the comparison of a catch per automatic jigging machine, the catch of the vessel loaded with MH fishing lamp excelled that of the vessel loaded with LED fishing lamp in 6 operations of squid jigging out of 9 operations. The ratio of hand-jigging and automatic jigging machine (one line) in the LED fishing lamp vessel was 1:1.1 excepting the case of having a catch only using an automatic jigging machine, showing almost the same with each other in catches, while in case of a MH fishing lamp vessel, its ratio against hand-jigging was 1 to 5.8, showing hand-jigging excelled in catches.

• The KIPS Transactions:PartC
• /
• v.15C no.5
• /
• pp.351-358
• /
• 2008

Recently, as network flooding attacks such as DoS/DDoS and Internet Worm have posed devastating threats to network services, rapid detection and proper response mechanisms are the major concern for secure and reliable network services. However, most of the current Intrusion Detection Systems(IDSs) focus on detail analysis of packet data, which results in late detection and a high system burden to cope with high-speed network environment. In this paper we propose a lightweight and fast detection mechanism for traffic flooding attacks. Firstly, we use SNMP MIB statistical data gathered from SNMP agents, instead of raw packet data from network links. Secondly, we use a machine learning approach based on a Support Vector Machine(SVM) for attack classification. Using MIB and SVM, we achieved fast detection with high accuracy, the minimization of the system burden, and extendibility for system deployment. The proposed mechanism is constructed in a hierarchical structure, which first distinguishes attack traffic from normal traffic and then determines the type of attacks in detail. Using MIB data sets collected from real experiments involving a DDoS attack, we validate the possibility of our approaches. It is shown that network attacks are detected with high efficiency, and classified with low false alarms.

• The KIPS Transactions:PartA
• /
• v.17A no.3
• /
• pp.127-136
• /
• 2010

A wireless sensor network(WSN) which roles as a mediator between living environment and computers in ubiquitous computing is very essential research area. Due to the constraint that sensor nodes should work in very resource-restricted circumstances, an operating system that can manage resources effectively is demanded. Also, a sensor network should be able to deal with many events quickly and simultaneously in order to respond to various physical changes in outer environment. The Sensor Network Operating System such as TinyOS, MANTIS and NanoQplus is much designed so that it can satisfy such requirement. But, for programmers who develop application program for sensor networks, they have lack of frameworks which the development is easily possible from restricted development environment. In this paper for this, we implemented a state machine framework apt for responsive systems in NanoQplus which is multi-thread-based sensor network operating system. In addition we propose an event broker module(EBM) for effective event dispatching, a message data structure for message sharing among state machines, and an execution module that handles messages and their queue and performs state transition of the machines. Furthermore, we could do the development more easily an application program with a state-based framework by developing CASE tools.