• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.140-141
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• 2017

Big data analysis, in the large amount of data stored as the data warehouse which it refers the process of discovering meaningful new correlations, patterns, trends and creating new values. Thus, Big data analysis is an effective analysis of various big data that exist all over the world such as social big data, machine to machine (M2M) sensor data, and corporate customer relationship management data. In the big data era, it has become more important to effectively analyze not only structured data that is well organized in the database, but also unstructured big data such as the internet, social network services, and explosively generated web documents, e-mails, and social data in mobile environments. By the way, a meta analysis refers to a statistical literature synthesis method from the quantitative results of many known empirical studies. We reviewed a total of 750 samples among 50 studies published on the topic related as IDT between 2000 and 2017 in Korea.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.6
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• pp.507-516
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• 2021

In this study, the machine learning which has been widely used in prediction algorithms recently was used. the research point was the CD(chudong) point which was a representative point of Daecheong Lake. Chlorophyll-a(Chl-a) concentration was used as a target variable for algae prediction. to predict the Chl-a concentration, a data set of water quality and quantity factors was consisted. we performed algorithms about random forest and gradient boosting with Python. to perform the algorithms, at first the correlation analysis between Chl-a and water quality and quantity data was studied. we extracted ten factors of high importance for water quality and quantity data. as a result of the algorithm performance index, the gradient boosting showed that RMSE was 2.72 mg/m³ and MSE was 7.40 mg/m³ and R² was 0.66. as a result of the residual analysis, the analysis result of gradient boosting was excellent. as a result of the algorithm execution, the gradient boosting algorithm was excellent. the gradient boosting algorithm was also excellent with 2.44 mg/m³ of RMSE in the machine learning hyperparameter adjustment result.

• Journal of the military operations research society of Korea
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• v.10 no.2
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• pp.75-83
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• 1984

Consider an m machine flow shop with blocking. The processing time of job j,j=1,..., n on each one of the m machines is equal to the same random variable $X_j$ and is distributed according to $F_i$. We assume that the processing times are stochastically ordered, i.e., $F_{1_{-st}}{<}F_{2_{st}}{<}cdots_{-st}{<}F_n$. We show that the sequence 1,3,5,...,n-1,n,n-2,...,6,4,2 when n is even and sequence 1,3,5,...,n-2,n,n-1 ... 6,4,2 when n is odd minimizes the expected makespan and that the sequence 1,...,n minimizes the expected flow time.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.25-31
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• 2016

Recently, with greatly improving the wireless communication technology, new services are created using smart sensors, i.e., machine-to-machine (M2M) and Internet of Things (IoT). In this paper, we propose a novel IoT device (IoTD) personalization method that adopt Small-cell Access Points (SAPs) to control IoTDs using user equipments (UEs), e.g., smart phones and tablet PC, from service users. First, we introduce a system architecture that consists of UE, IoTD, and SAP and propose the IoTD personalization method with two procedures, i.e., IoTD profile registration procedure and IoTD control procedure. Finally, through simulations, we evaluated the system performance of the proposed scheme and it is shown that the proposed scheme outperforms the conventional scheme in terms of the packet delay, packet loss probability, and normalized throughput.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1567-1577
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• 2020

Urban land cover classification is role in urban planning and management. So, it's important to improve classification accuracy on urban location. In this paper, machine learning model, Support Vector Machine (SVM) and Artificial Neural Network (ANN) are proposed for urban land cover classification based on high resolution satellite imagery (KOMPSAT-3A). Satellite image was trained based on 25 m rectangle grid to create training data, and training models used for classifying test area. During the validation process, we presented confusion matrix for each result with 250 Ground Truth Points (GTP). Of the four SVM kernels and the two activation functions ANN, the SVM Polynomial kernel model had the highest accuracy of 86%. In the process of comparing the SVM and ANN using GTP, the SVM model was more effective than the ANN model for KOMPSAT-3A classification. Among the four classes (building, road, vegetation, and bare-soil), building class showed the lowest classification accuracy due to the shadow caused by the high rise building.

• Explosives and Blasting
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• v.13 no.1
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• pp.20-31
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• 1995

Many methods and techniques to reduce ground vibrations are well known. Some of them are to adopt electric milisecond detonators with a sequential blasting machine or an initiating system with an adequate number of delay intervals. The types of electric detonators munufactured in Korea include instantaneous, decisecond and milisecond delays byt numbers of delay intervals are only limite from No.1 to No.20 respectively. It is not sufficient to control accurately milisecond time with these detonators in tunnel excavation. Sequential fire time refers to adding an external time delay to a detonators norminal firing time to obtain sequential initiation and it is determined by sequential timer setting. To reduce the vibration level, sequential blasting machine with decisecond detonatore was adopted. A total of 134 blasting was recorded at various sites. Blast-to-structure distances ranged from 20.3 to 42.0 meter, where charge weight varied from 0.25 to 0.75 kg per delay. The results can be summarized as follow : 1. The effects of sequential blasting machine on the vibration level are discussed. The vibration level by S.B.M. are decreased approximately 14.38~18.05 to compare to level of conventional blasting and cycle time per round can be saved. 2. The empirical equations of particle velocity were obtained in S,B.M. and conventional blastin. $V=K(D/W^{1/3})-n$. where the values for n and k are estimated to be 1.665 to 1.710 and 93.59 to 137 respectively. 3. The growth of cracks due to vibrations are found but the level fall to within allowable value.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.1
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• pp.34-41
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• 1993

SUS304 is wellknown as difficult-to-machine materials. It is easy to appear workhardened, and workhardening is one of the causes of groove wear on the tool. In this paper, the author would like to compare the width of flank wear with that of groove wear, and to find whether the groove wear can be used as a criterion of a tool life. The design of the twelve tests provides three levels for each variable (speed: 200m/min, 118m/min, 70m/min; feed: 0.3mm/rev, 0.17mm/rev, 0.1mm/rev; depth of cut: 0.4mm, 0.28mm, 0.2mm). The study of tool-life testing by statistical technique follows usual most scientific sequence. So the tool-life predicting equation is calculated by the method of least squares. The overall adequacy of the model can be verified by the analysis of variance. The results obtained are as follows : 1) When SUS304 is cut in 200(m/min), the width of flank wear is much larger than that of groove wear. 2) In cutting speed 118m/min, flank wear is a little larger than groove wear and in the cutting speed 70m/min, the latter is a little larger so that it is reasonable to determine the tool life according the crierion by groove wear in the low cutting speed (less than 70m/min). 3) Owing to the burr the depth of engagement along the cutting edge is extended toward the shank.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.214-214
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• 2004

공작기계가 협력의 주체가 되는 생산시스템에서는 공작기계가 다양한 내외부적 요인들과 협력을 유지하면서 스스로 지식을 진화시킬 수 있는 M2M(Machine To Machine) 환경을 만들어 갈 수 있게 될 것이다. 본 연구에서는 지식진화형 지능공작기계의 개발을 위한 대화 모듈 에이전트 설계에 대한 내용을 소개한다. 지식진화형 지능 공작기계를 개발하기 위해서는 인간 전문가를 대신할 다양한 지식과 이에 적합한 지식처리가 필요하다. 그러기 위해서는 무엇보다 기계간 협력을 위한 에이전트의 요구가 필수적이다.(중략)

• Information and Communications Magazine
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• v.27 no.7
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• pp.3-9
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• 2010

최근 인간 사물 환경 등 모든 사물이 네트워크에 연결돼 언제 어디서나 다양한 디바이스로 관련 정보를 쉽게 이용할 수 있는 사물지능통신망 서비스가 차세대 방송통신 시장의 새로운 먹거리로 전망되고 있다. 이는 기존의 방송, 통신, 인터넷 등 개별 미디어를 기반으로 한 인간 중심의 정보수집 방법에서 이들을 융합한 인간 대(對)사물, 사물 대(對)사물로의 정보 수집 방법의 진화에 의한 것으로 그 진화의 중심에 'M2M(Machine to Machine : 사물지능통신)'이 있다. 그 예로, 미국의 타임지는 지난해 최고의 발명품으로 사물 인터넷(The Internet of Things)을 채택했으며, 국내 언론에서는 2020년 1000억대가 넘는 사물들이 네트워크에 연결될 것으로 전망하고 있다. 본 고는 방송통신 인프라의 효율적인 활용을 통해 저탄소 녹색성장, 기후변화 대응, 에너지 절감, 재난 재해 방지 등 국가 정책을 뒷받침하고 미래방송 통신 융합 ICT(Information & Communication Technology)를 선도 하는 사물지능통신(M2M)의 발전과 및 관련 미래 서비스 모델을 살펴보고자 한다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.382-386
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• 2002

The tapping is machining process that makes a female screw on the parts to be assembly together. It is used for the high-speed tapping machine with synchronizing function for the high productivity. This paper describes the development of the ultra high-speed tapping machine with 10,000rpm. The key factors in the tapping speed are the acceleration/deceleration velocity and the synchronizing errors between the spindle motor and feeding motor. To minimizing acceleration/deceleration time, the low inertia spindle with synchronous built-in servo motor is developed. To minimizing synchronizing errors, the tapping cycle algorithm under open architecture CNC environment is optimized. The developed tapping machine has 0.13sec/10,000rpm in acceleration/deceleration time and the synchronizing error below 4.0%. It has 0.55sec for cycle time of one female screw, M3 tap, 2 times depth of tap diameter.