• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.3
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• pp.509-516
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• 2008

Recently, the operator modules to control external devices are concerned about automatic management system to process continuously changed signals. These signals are the stream data of which characteristics are several numbers. a short report interval and asynchronous report time. It is necessary that the system brings about high accuracy and real time process for stream data. The typical queries of these systems consist of the current query to search the latest signal value, the snapshot query at a past time, the sliding window query from a past time to current. In this paper, we propose the efficient method to manage the above signals by using a file structured database in small-size operating systems. We also propose a query model to accommodate various queries including the sliding window query. The file database in the QNX adopts a delta version and a shared memory buffering method for the resource limit of a small storage and a low computing power.

• Smart Media Journal
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• v.7 no.4
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• pp.79-89
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• 2018

In recent years, falls among elderly people have gained serious attention as a major cause of injuries. Falls often lead to fatal consequences due to lack of prompt response and rescue. Therefore, a more accurate fall detection system and an effective feature extraction technique are required to prevent and reduce the risk of such incidents. In this paper, we proposed an efficient feature extraction technique based on multiple sliding windows and validated it through a series of experiments using supervised learning algorithms. The experiments were conducted using the public datasets obtained from tri-axial accelerometers. The results depicted that extraction of the feature from adjacent sliding windows led to high accuracy in supervised machine learning-based fall detection. Also, the experiments conducted in this study suggested that the best accuracy can be achieved by keeping the window size as small as 2 seconds. With the kNN classifier and dataset from wearable sensors, the experiments achieved accuracy rates of 94%.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.449-456
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• 2021

An intrusion detection system is a technology that detects abnormal behaviors that violate security, and detects abnormal operations and prevents system attacks. Existing intrusion detection systems have been designed using statistical analysis or anomaly detection techniques for traffic patterns, but modern systems generate a variety of traffic different from existing systems due to rapidly growing technologies, so the existing methods have limitations. In order to overcome this limitation, study on intrusion detection methods applying various machine learning techniques is being actively conducted. In this study, a comparative study was conducted on data preprocessing techniques that can improve the accuracy of anomaly detection using NGIDS-DS (Next Generation IDS Database) generated by simulation equipment for traffic in various network environments. Padding and sliding window were used as data preprocessing, and an oversampling technique with Adversarial Auto-Encoder (AAE) was applied to solve the problem of imbalance between the normal data rate and the abnormal data rate. In addition, the performance improvement of detection accuracy was confirmed by using Skip-gram among the Word2Vec techniques that can extract feature vectors of preprocessed sequence data. PCA-SVM and GRU were used as models for comparative experiments, and the experimental results showed better performance when sliding window, skip-gram, AAE, and GRU were applied.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.69-72
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• 2006

The objective of this study is to find out the shear capacity of URM wall and the variables that affect the shear capacity of URM wall such as the opening and the aspect ratio, considering four kinds of failure modes, sliding shear failure, toe crushing failure, and diagonal shear failure. The main varialble is the shape of opening of URM walls. First URM has one door, second has one window, third hase one door and one window, the last has two windows. The test results of URM with openings show that the specimens are governed by rocking failure mode.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1227-1232
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• 2015

Several works help make sliding window object detection fast, nevertheless, computational demands remain prohibitive for numerous applications. This paper proposes a fast object detection method based on three strategies: cascade classifier, selective window search and fast feature extraction. Experimental results show that the proposed method outperforms the compared methods and achieves both high detection precision and low computation cost. Our approach runs at 17ms per frame on 640×480 images while attaining state-of-the-art accuracy.

• Journal of Environmental Health Sciences
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• v.44 no.4
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• pp.360-369
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• 2018

Objectives: Outdoor tobacco smoke can penetrate into the indoor environment through cracks in the building envelope. This study aimed to characterize the particle size distribution of infiltrated secondhand smoke (SHS) through the gap in a single glazed and a secondary glazed window according to pressure differences in a chamber. Methods: Two polyvinyl chloride sliding windows were evaluated for infiltration, one with a glazed window and the other with a secondary glazed window. Each window was mounted and sealed in a polycarbonate chamber. The air in the chamber was discharged to the outside to establish pressure differences in the chamber (${\Delta}P$). Outdoor smoking sources were simulated at a one-meter distance from the window side of the chamber. The particle size distribution of the infiltrated SHS was measured in the chamber using a portable aerosol spectrometer. The particle size distribution of SHS inside the chamber was normalized by the outdoor peak for fine particles. Results: The particle size distribution of SHS inside the chamber was similar regardless of window type and ${\Delta}P$. It peaked at $0.2-0.3{\mu}m$. Increases in particulate matter (PM) concentrations from SHS infiltration were higher with the glazed window than with the secondary glazed window. PM concentrations of less than $1{\mu}m$ increased as ${\Delta}P$ was increased inside the chamber. Conclusions: The majority of infiltrated SHS particles through window gap was $0.2-0.3{\mu}m$ in size. Outdoor SHS particles infiltrated more with a glazed window than with a secondary glazed window. Particle sizes of less than $1{\mu}m$ were associated with ${\Delta}P$. These findings can be a reference for further research on the measurement of infiltrated SHS in buildings.

• Journal of KIISE:Databases
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• v.33 no.2
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• pp.163-174
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• 2006

In distributed wireless sensor network, it is difficult to transmit and analyze the entire stream data depending on limited networks, power and processor. Therefore it is suitable to use alternative stream data processing after classifying the continuous stream data. We propose a classification framework for continuous multivariate stream data. The proposed approach works in two steps. In the preprocessing step, it takes input as a sliding window of multivariate stream data and discretizes the data in the window into a string of symbols that characterize the signal changes. In the classification step, it uses a standard text classification algorithm to classify the discretized data in the window. We evaluated both supervised and unsupervised classification algorithms. For supervised, we tested Bayesian classifier and SVM, and for unsupervised, we tested Jaccard, TFIDF Jaro and Jaro Winkler. In our experiments, SVM and TFIDF outperformed other classification methods. In particular, we observed that classification accuracy is improved when the correlation of attributes is also considered along with the n-gram tokens of symbols.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.42-47
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• 2021

A one-touch descending lifeline that can easily be installed and rapidly evacuated in the event of a fire accident in high-rise buildings was proposed to overcome difficulties of conventional descending lifeline such as complex installation methods and procedures. However, this lifeline exhibits limitations such as restrictions in installation location and large apparatus size. Therefore, this paper proposes a sliding-type descending lifeline, which has a similar operation to that of current one-touch descending lifeline and solves the aforementioned limitations. A double square link mechanism including a sliding four-bar linkage is proposed and the descending lifeline support is redesigned to unfold in two different planes, allowing 3D movement. Additionally, the shape of the support frame is designed to obtain two attachment surfaces that can be attached to a wall, irrespective of the angle between the window and the inner wall. FEA analysis using ABAQUS is performed to ensure that the robustness of the presented support complies with the Fire Control Act Enforcement Decree. Finally, the feasibility of the proposed sliding one-touch descending lifeline is verified through fabrication.

• Journal of Korean Association for Spatial Structures
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• v.14 no.3
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• pp.11-16
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• 2014

• 대한방사선방어학회:학술대회논문집
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• 2011.11a
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• pp.102-103
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• 2011