• 센서학회지
• /
• 제31권1호
• /
• pp.57-63
• /
• 2022

This study describes a system that monitors the tool and cutting state of automatic beveling operation in real time. As a signal for cutting state monitoring, a motor current detected from the spindle drive system of the automatic beveling machine is used to monitor abnormal state. Because automatic beveling is processed using a face milling cutter, the cutting force mechanism is the same as the milling process. The predicted cutting torque is obtained using a cutting force model based on specific cutting resistance. Then, the predicted cutting torque is converted into the spindle motor current value, and cutting state stability is diagnosed by comparing it with the motor current value detected during beveling operation. The experimental results show that the spindle motor current can detect abnormal cutting state such as overload and tool wear during beveling operation, and can diagnose the cutting stability using the proposed equip-current line diagram.

• ETRI Journal
• /
• 제39권4호
• /
• pp.546-557
• /
• 2017

In a long term evolution-advanced (LTE-A) system, the traffic overload of machine type communication devices is a challenge because too many devices attempt to access a base station (BS) simultaneously in a short period of time. We discuss the challenge of the gap between the theoretical maximum throughput and the actual throughput. A gap occurs when the BS cannot change the number of preambles for a random access channel (RACH) until multiple numbers of RACHs are completed. In addition, a preamble partition approach is proposed in this paper that uses two groups of preambles to reduce this gap. A performance evaluation shows that the proposed approach increases the average throughput. For 100,000 devices in a cell, the throughput is increased by 29.7% to 114.4% and 23.0% to 91.3% with uniform and Beta-distributed arrivals of devices, respectively.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 1997년도 추계학술대회 논문집
• /
• pp.88-93
• /
• 1997

Ball-end milling process is widely used in the die and mold manufacturing because of suitable for the machining of free-form surface. Pencil cutting can eliminate overload in uncut area caused by large diameter of ball-end mill before finish cutting. As the ball-end mill for pencil cutting is long and thin, it is easily deflected by cutting force. The tool deflection when pencil cutting is one of the main reason of the machining errors on a free-from surface. The purpose of the research is to find out the characteristics of deflected cutter trajectory by eddy-current sensor.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 1997년도 추계학술대회 논문집
• /
• pp.120-126
• /
• 1997

This paper examines the crack growth behavior of 7075-T651 aluminum alloy under high-low block loading condition. The cantilever beam type specimen with a chevron notch is used in this study. The crack growth and closure are investgated by compliance method. The applied initial stress ratios are R=-0.5, R=0.0 and R=0.25 Crack length($\alpha$), effective stress intensity factor range(ΔKeff), ratio of effective stress intensity factor range(U) and crack growth rate(d$\alpha$/dN) etc. are inspected fracture mechanics estimate.

• 한국안전학회지
• /
• 제7권4호
• /
• pp.95-99
• /
• 1992

The attraction of using expert system in operator support systems for modern plant is that it offers a way of dealing with the problem of information overload that can occur during a severe disturbance at a modern industrial plant. During such a disturance the volume of information presented to operators may be such that they are unable to decide quickly what is important and what is not. Therefore, arriving at a correct diagnosis of the initialling fault may be delayed. An expert system operator sup-port system is a means of focusing attention on what really matters and cutting out the rest. This paper presents the development of prototype expert system which detect the fault part, machine, system and decide action priority. This prototype expert system has 6 sub- system which is Interface Manager, Decision Maker, Inference Engine, Knowledge base, Simulatio, and D.P System ( Diagnosis and predictor)

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(C)
• /
• pp.258-261
• /
• 2011

Living in the age of information people face problems related to information overload. Information is easy to produce, store and distribute through various communication channels, one of which is emails. With the appearance of the mobile devices, such as smart phones and tabs, people can have access to email inbox at any moment of time from everywhere. In this paper we present information extraction system with a specific goal of extracting meeting location from the announcement of seminar or conference. We apply a machine learning method (conditional random fields, CRF), train the system using annotated corpus of seminar and conference announcements and validate results by applying various extracted correction rules and patterns. Furthermore, we normalize extracted location, and reference using geo-coding databases, OpenStreetMap and Wikipedia resources to determine real geographical coordinates.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2009년도 춘계학술대회 논문집
• /
• pp.2023-2029
• /
• 2009

The PRT can be divided into In-Track and On-Board according to propulsion method. In process of In-Track, vehicles driven by LIMs(Linear Induction Motor) which are installed in Guideway. Central Controller, which control whole machine, must control speed and direction of all vehicles. In this case, as vehicle increases, Central Controller will overload. If Central Controller fails, all vehicle stops. To avoid this problem, processing of Central Controller must be distributed. This paper introduces method of Distributed Routing. Method of Distributed Routing will provide safety and efficiency for PRT System.

• International Journal of Contents
• /
• 제1권2호
• /
• pp.26-30
• /
• 2005

According to the fast growth of information on the Internet, it is becoming increasingly difficult to find and organize useful information. To reduce information overload, it needs to exploit automatic text classification for handling enormous documents. Support Vector Machine (SVM) is a model that is calculated as a weighted sum of kernel function outputs. This paper describes a document classifier for web documents in the fields of Information Technology and uses SVM to learn a model, which is constructed from the training sets and its representative terms. The basic idea is to exploit the representative terms meaning distribution in coherent thematic texts of each category by simple statistics methods. Vector-space model is applied to represent documents in the categories by using feature selection scheme based on TFiDF. We apply a category factor which represents effects in category of any term to the feature selection. Experiments show the results of categorization and the correlation of vector length.

• 한국멀티미디어학회논문지
• /
• 제25권8호
• /
• pp.1136-1140
• /
• 2022

This paper is a method for efficient traffic prediction in mobile edge computing, where many studies have recently been conducted. For distributed processing in mobile edge computing, tasks offloading from each mobile edge must be processed within the limited computing power of the edge. As a result, in the mobile nodes, it is necessary to efficiently select the surrounding edge server in consideration of performance dynamically. This paper aims to suggest the efficient clustering method by selecting edges in a cloud environment and predicting mobile traffic. Then, our dynamic clustering method is to reduce offloading overload to the edge server when offloading required by mobile terminals affects the performance of the edge server compared with the existing offloading schemes.

• Journal of information and communication convergence engineering
• /
• 제20권2호
• /
• pp.113-124
• /
• 2022

News in the form of web data generates increasingly large amounts of information as unstructured text. The capability of understanding the meaning of news is limited to humans; thus, it causes information overload. This hinders the effective use of embedded knowledge in such texts. Therefore, Automatic Knowledge Extraction (AKE) has now become an integral part of Semantic web and Natural Language Processing (NLP). Although recent literature shows that AKE has progressed, the results are still behind the expectations. This study proposes a method to auto-extract surface knowledge from English news into a machine-interpretable semantic format (triple). The proposed technique was designed using the grammatical structure of the sentence, and 11 original rules were discovered. The initial experiment extracted triples from the Sri Lankan news corpus, of which 83.5% were meaningful. The experiment was extended to the British Broadcasting Corporation (BBC) news dataset to prove its generic nature. This demonstrated a higher meaningful triple extraction rate of 92.6%. These results were validated using the inter-rater agreement method, which guaranteed the high reliability.