• 제목/요약/키워드: Precision machine

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손목형 웨어러블 디바이스에서 사람의 심박변화와 활동강도를 이용한 운동 검출 방법 (Exercise Detection Method by Using Heart Rate and Activity Intensity in Wrist-Worn Device)

  • 성지훈;최선탁;이주영;조위덕
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
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    • 제8권4호
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    • pp.93-102
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    • 2019
  • 웰니스에 대한 관심이 증대됨에 따라 개인의 건강상태를 웨어러블 디바이스로 모니터링하는 연구들이 늘어나고 있다. 이에 따라 웨어러블 디바이스에서 운동과 일상 활동을 구분하는 다양한 방법들이 연구되어 왔다. 이러한 기존 연구는 대부분 기계학습을 활용한 방식이다. 하지만 개인별 학습 데이터에 의존적인 과적합 문제와 연속적인 사건으로 구성되는 사람의 행동을 독립적으로 취급하여 인식 결과가 중간에 끊기고 오인행동이 생기는 문제가 있다. 이에 본 연구는 운동 시 심박이 오르내리는 생체반응 원리를 기반으로 한 운동 상태 검출 방법을 제안한다. 제안하는 방법은 3축 가속도 센서와 PPG 센서를 통해 활동강도 및 심박 수를 산출하여 심박 회복기를 판단한 후, 활동강도 검사 또는 심박 상승기 검사를 통해 운동 상태를 검출한다. 실험 결과에서 제안하는 알고리즘은 평균 정확도 98.64%, 정밀도 98.05%, 재현율 98.62%로 기존 알고리즘보다 개선된 모습을 보였다.

Influence of toothbrush abrasion and surface treatments on the color and translucency of resin infiltrated hybrid ceramics

  • Labban, Nawaf;Al Amri, Mohammad;Alhijji, Saleh;Alnafaiy, Sarah;Alfouzan, Afnan;Iskandar, Mounir;Feitosa, Sabrina
    • The Journal of Advanced Prosthodontics
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    • 제13권1호
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    • pp.1-11
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    • 2021
  • PURPOSE. The study compared the color change, lightness, and translucency of hybrid resin ceramics exposed to toothbrush abrasion and surface treatment. MATERIALS AND METHODS. Four hybrid ceramics [Lava Ultimate (LU), Vita Enamic (EN), Shofu HC (SH), and Crystal Ultra (CU)] were compared with a glass-ceramic (Vita Mark II) control. One hundred and twenty specimen blocks were prepared using a precision saw machine. Specimens in each material were divided into four subgroups based on the surface treatment (polishing or staining) and a storage medium (water or citric acid). Simulated tooth brushing with a mixture of 100 RDA (radioactive abrasives) with 0.3 ml distilled water was used for 3650 cycles (7300 strokes) for each specimen. Measurements for the color change, lightness, and translucency were measured after toothbrushing using a spectrophotometer. Statistical analysis compared outcomes using paired t-test, ANOVA, and Tukey post hoc test. RESULTS. The maximum color change was identified in SH (stained acid) [1.44 (0.40)], whereas the lowest was identified in EN (polished water) [0.66 (0.16)] material. The maximum and minimum loss of surface translucency was observed in SH (polished water) [12.3 (0.52)] and EN (stained acid) [6.5 (0.55)] specimens, respectively. Lastly, loss of lightness was the highest in VM (polished acid) [69 (0.95)], whereas the lowest was observed in CU (stained water) [56.7 (0.86)]. CONCLUSION. The comparison presented a significant effect of toothbrush abrasion on translucency and lightness of the hybrid resin ceramics. Color change was not significantly influenced irrespective of the storage medium employed. Surface staining demonstrated the preservation and stability of color and optical properties under the influence of toothbrush abrasion and chemical trauma.

Multi Label Deep Learning classification approach for False Data Injection Attacks in Smart Grid

  • Prasanna Srinivasan, V;Balasubadra, K;Saravanan, K;Arjun, V.S;Malarkodi, S
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권6호
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    • pp.2168-2187
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    • 2021
  • The smart grid replaces the traditional power structure with information inventiveness that contributes to a new physical structure. In such a field, malicious information injection can potentially lead to extreme results. Incorrect, FDI attacks will never be identified by typical residual techniques for false data identification. Most of the work on the detection of FDI attacks is based on the linearized power system model DC and does not detect attacks from the AC model. Also, the overwhelming majority of current FDIA recognition approaches focus on FDIA, whilst significant injection location data cannot be achieved. Building on the continuous developments in deep learning, we propose a Deep Learning based Locational Detection technique to continuously recognize the specific areas of FDIA. In the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN). The FDD is established enough to catch the fake information. As a multi-label classifier, the following CNN is utilized to evaluate the irregularity and cooccurrence dependency of power flow calculations due to the possible attacks. There are no earlier statistical assumptions in the architecture proposed, as they are "model-free." It is also "cost-accommodating" since it does not alter the current FDD framework and it is only several microseconds on a household computer during the identification procedure. We have shown that ANN-MLP, SVM-RBF, and CNN can conduct locational detection under different noise and attack circumstances through broad experience in IEEE 14, 30, 57, and 118 bus systems. Moreover, the multi-name classification method used successfully improves the precision of the present identification.

Drug-Drug Interaction Prediction Using Krill Herd Algorithm Based on Deep Learning Method

  • Al-Marghilani, Abdulsamad
    • International Journal of Computer Science & Network Security
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    • 제21권6호
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    • pp.319-328
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    • 2021
  • Parallel administration of numerous drugs increases Drug-Drug Interaction (DDI) because one drug might affect the activity of other drugs. DDI causes negative or positive impacts on therapeutic output. So there is a need to discover DDI to enhance the safety of consuming drugs. Though there are several DDI system exist to predict an interaction but nowadays it becomes impossible to maintain with a large number of biomedical texts which is getting increased rapidly. Mostly the existing DDI system address classification issues, and especially rely on handcrafted features, and some features which are based on particular domain tools. The objective of this paper to predict DDI in a way to avoid adverse effects caused by the consumed drugs, to predict similarities among the drug, Drug pair similarity calculation is performed. The best optimal weight is obtained with the support of KHA. LSTM function with weight obtained from KHA and makes bets prediction of DDI. Our methodology depends on (LSTM-KHA) for the detection of DDI. Similarities among the drugs are measured with the help of drug pair similarity calculation. KHA is used to find the best optimal weight which is used by LSTM to predict DDI. The experimental result was conducted on three kinds of dataset DS1 (CYP), DS2 (NCYP), and DS3 taken from the DrugBank database. To evaluate the performance of proposed work in terms of performance metrics like accuracy, recall, precision, F-measures, AUPR, AUC, and AUROC. Experimental results express that the proposed method outperforms other existing methods for predicting DDI. LSTMKHA produces reasonable performance metrics when compared to the existing DDI prediction model.

FEM 시뮬레이션을 이용한 임펠러의 구조 안전성 평가 (The Evaluation of Structural Safety of Impeller Using FEM Simulation)

  • 정종윤
    • 산업경영시스템학회지
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    • 제43권4호
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    • pp.41-47
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    • 2020
  • As modern industries are highly being developed, it is required that mechanical parts have to be manufactured with a high precision. In order to have precise parts, error-free designs have to be done before manufacturing with accuracy. For this intention being fulfilled, a mechanical analysis is essential for design proof. Nowadays, FEM simulation is a popular tool for verifying a machine design. In this paper, an impeller, being utilized in a compressor or an oil mixer as an actuator, is studied for an evaluation. The purpose of this study is to present a safety of an impeller for a proof of its mechanical stability. A static analysis for stress, strain, and deformation within a regular usage is examined. This simulation test shows 357.26×106 Pa for maximum equivalent stress and 0.207mm for total deformation. A fatigue test is carried to provide durability and its result shows that minimum safety factor is 3.2889, which guarantees that it runs without a fatigue failure in 106 cycles. The natural frequencies for the impeller is ranged from 228.09Hz to 1,253.6Hz for the 1st to the 6th mode. Total deformations at these natural frequencies are shown from 6.84mm to 12.631mm. Furthermore, Campbell diagram reveals that a critical speed is not found throughout regular rotational speeds. From the test results for the analysis, this paper concludes that the suggested impeller is proved for its mechanical safety and good to utilize at industries.

Object detection in financial reporting documents for subsequent recognition

  • Sokerin, Petr;Volkova, Alla;Kushnarev, Kirill
    • International journal of advanced smart convergence
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    • 제10권1호
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    • pp.1-11
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    • 2021
  • Document page segmentation is an important step in building a quality optical character recognition module. The study examined already existing work on the topic of page segmentation and focused on the development of a segmentation model that has greater functional significance for application in an organization, as well as broad capabilities for managing the quality of the model. The main problems of document segmentation were highlighted, which include a complex background of intersecting objects. As classes for detection, not only classic text, table and figure were selected, but also additional types, such as signature, logo and table without borders (or with partially missing borders). This made it possible to pose a non-trivial task of detecting non-standard document elements. The authors compared existing neural network architectures for object detection based on published research data. The most suitable architecture was RetinaNet. To ensure the possibility of quality control of the model, a method based on neural network modeling using the RetinaNet architecture is proposed. During the study, several models were built, the quality of which was assessed on the test sample using the Mean average Precision metric. The best result among the constructed algorithms was shown by a model that includes four neural networks: the focus of the first neural network on detecting tables and tables without borders, the second - seals and signatures, the third - pictures and logos, and the fourth - text. As a result of the analysis, it was revealed that the approach based on four neural networks showed the best results in accordance with the objectives of the study on the test sample in the context of most classes of detection. The method proposed in the article can be used to recognize other objects. A promising direction in which the analysis can be continued is the segmentation of tables; the areas of the table that differ in function will act as classes: heading, cell with a name, cell with data, empty cell.

데이터 중심 통합생산시스템 설계 및 구현: 대형항공부품가공 사례 (Design and Implementation of Integrated Production System for Large Aviation Parts)

  • 배성문;배효진;홍금석;박철순
    • 산업경영시스템학회지
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    • 제44권4호
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    • pp.208-219
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    • 2021
  • In the era of the 4th industrial revolution driven by the convergence of ICT(information and communication technology) and manufacturing, research on smart factories is being actively conducted. In particular, the manufacturing industry prefers smart factories that autonomously connect and analyze data. For the efficient implementation of smart factories, it is essential to have an integrated production system that vertically integrates separately operated production equipment and heterogeneous S/W systems such as ERP, MES. In addition, it is necessary to double-verify production data by using automatic data collection technology so that the production process can be traced transparently. In this study, we want to show a case of data-centered integration of a large aircraft parts processing factory that requires high precision, takes a long time, and has the characteristics of processing large raw materials. For this, the components of the data-oriented integrated production system were identified and the connection structure between them was explained. And we would like to share the experience gained through the design and implementation case. The integrated production system proposed in this study integrates internal components based on data, which is expected to serve as a basis for SMEs to develop into an advanced stage, and traces materials with RFID technology.

발전소 회전기기 정밀진단을 위한 휴대용 진동분석기 개발 (Development of a Portable Vibration Analyzer for Precision Diagnosis of Plant's Rotating Equipment)

  • 노형호;유호선
    • 플랜트 저널
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    • 제17권4호
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    • pp.53-60
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    • 2021
  • 본 연구에서는 국내 진동감시시스템 제작업체인 (주)나다와 발전소 회전기기 진동데이터 취득 및 분석에 효과적인 휴대용 진동분석기를 개발하고자 하였다. 개발된 휴대용 진동분석기의 하드웨어는 측정기기의 교정을 위한 측정 불확도를 통해 얻은 측정값을 시스템에서 보정함으로써 측정오차를 최소화하였고, 고속 데이터 처리로 높은 분해능을 가진 신호처리 장치로 구성되었다. 소프트웨어 구조는 다양한 진동 플롯을 구현하여 상세한 분석프로그램을 실행하며, 회전기기 운전 중 외란으로 발생하는 노이즈 측정 및 제거에 효과적인 알고리즘을 적용하였다. 개발품은 사용자의 이동 편의성 증대 및 고속 데이터 처리로 분해능을 높임으로써 성능향상은 물론, 국산화 개발에 따른 구입비용 절감에도 크게 기여하였다.

Use of measuring gauges for in vivo accuracy analysis of intraoral scanners: a pilot study

  • Iturrate, Mikel;Amezua, Xabier;Garikano, Xabier;Solaberrieta, Eneko
    • The Journal of Advanced Prosthodontics
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    • 제13권4호
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    • pp.191-204
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    • 2021
  • PURPOSE. The purpose of this study is to present a methodology to evaluate the accuracy of intraoral scanners (IOS) used in vivo. MATERIALS AND METHODS. A specific feature-based gauge was designed, manufactured, and measured in a coordinate measuring machine (CMM), obtaining reference distances and angles. Then, 10 scans were taken by an IOS with the gauge in the patient's mouth and from the obtained stereolithography (STL) files, a total of 40 distances and 150 angles were measured and compared with the gauge's reference values. In order to provide a comparison, there were defined distance and angle groups in accordance with the increasing scanning area: from a short span area to a complete-arch scanning extension. Data was analyzed using software for statistical analysis. RESULTS. Deviations in measured distances showed that accuracy worsened as the scanning area increased: trueness varied from 0.018 ± 0.021 mm in a distance equivalent to the space spanning a four-unit bridge to 0.106 ± 0.08 mm in a space equivalent to a complete arch. Precision ranged from 0.015 ± 0.03 mm to 0.077 ± 0.073 mm in the same two areas. When analyzing angles, deviations did not show such a worsening pattern. In addition, deviations in angle measurement values were low and there were no calculated significant differences among angle groups. CONCLUSION. Currently, there is no standardized procedure to assess the accuracy of IOS in vivo, and the results show that the proposed methodology can contribute to this purpose. The deviations measured in the study show a worsening accuracy when increasing the length of the scanning area.

2D 출력물 비교를 위한 PLC와 아두이노 CNC 제어 (PLC and Arduino CNC Control for Comparison of 2D Outputs)

  • 조해준;김강호;장현수;전종환;이승대
    • 한국전자통신학회논문지
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    • 제16권6호
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    • pp.1295-1302
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    • 2021
  • 3D 프린터의 시장 규모가 증가되는 시점에서 출력물에 대한 정밀도와 모터에 의한 작업속도는 매우 중요한 사항 중 하나이다. 본 논문에서는 PLC 장비와 아두이노 CNC의 동일 출력물 비교를 위해서 CURA 프로그램을 이용하여 동일 출력물의 G-code를 생성하였으며, NC File로 변환 후, 각각의 장비에 펜을 부착하여 A4 용지에 특정 결과물을 출력하였다. 그 결과, 출력 시간이 PLC 장비의 경우 1m 39s, 아두이노 CNC의 경우 2m 5s로 측정되었으며 2D 출력물이 두 장비에서 동일하게 출력되는 것을 확인하였다.