• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.1
• /
• pp.229-240
• /
• 2012

Advances in MEMS and CMOS technologies have motivated the development of low cost/power sensors and wireless multimedia sensor networks (WMSN). The WMSNs were created to ubiquitously harvest multimedia content. Such networks have allowed researchers and engineers to glimpse at new Machine-to-Machine (M2M) Systems, such as remote monitoring of biosignals for telemedicine networks. These systems require the acquisition of a large number of data streams that are simultaneously generated by multiple distributed devices. This paradigm of data generation and transmission is known as event-streaming. In order to be useful to the application, the collected data requires a preprocessing called data fusion, which entails the temporal alignment task of multimedia data. A practical way to perform this task is in a centralized manner, assuming that the network nodes only function as collector entities. However, by following this scheme, a considerable amount of redundant information is transmitted to the central entity. To decrease such redundancy, data fusion must be performed in a collaborative way. In this paper, we propose a collaborative data alignment approach for event-streaming. Our approach identifies temporal relationships by translating temporal dependencies based on a timeline to causal dependencies of the media involved.

• The Transactions of the Korea Information Processing Society
• /
• v.2 no.4
• /
• pp.554-560
• /
• 1995

In this paper, we suggest a parallel algorithm to merge priority queues organized in two heaps, kheap and nheap of sizes k and n, correspondingly. Employing max(2$^{-1}$, $\ulcorner$(m＋1)/4$\lrcorner$'s processors, this algorithm requires O(log(n/k)＊log(n)) on an EREW-PRAM, where i is the height of the heap and m is the summation of sizes n and k. Also, when we run it on the MasPar machine, this method achieves a 33.934-fold speedup with 64 processors to merge 8 million data items which consist of two heaps of different sizes. So our parallel algorithm's EPU is close to 1, which is considered as an optimal speedup ratio.eedup ratio.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2003.05a
• /
• pp.208-216
• /
• 2003

ISO 14649 (data model for STEP-NC) is a new interface scheme or language for CAD-CAM-CNC chain under established by ISO TC184 SCI. Up to this point, the new language is mainly made for milling and turning, and other processes such as EDM will be completed in the future. Upon completion, it will be used as the international standard language for e-manufacturing paradigm by replacing the old machine-level language, so called M&G code used since 1950's. With the rich information contents included in the new language, various intelligent functions can be made by the CNC as the CNC knows what-to-make and how-to-make. In particular, On-Machine Inspection required for quality assurance in the machine level, can be done based on the information of feature­based tolerance graph. Previously, On-Machine inspection has been investigated mainly for milling operation, and only a few researches were made for turning operation without addressing the data model. In this thesis, we present a feature-based on-machine inspection process by the 4 Tasks: 1) proposing a new schema for STEP-NC data model, 2) converting the conventional tolerance scheme into that of STEP-NC, 3) modifying the tolerance graph such that the tolerance can be effectively measured by the touch probe on the machine, and 4) generating collision-free tool path for actual measurement. Task 1 is required for the incorporation of the presented method in the ISO 14649, whose current version does not much include the detailed schema for tolerance. Based on the presented schema, the tolerance represented in the conventional drafting can be changed to that of STEP-NC (Task 2). A special emphasis was given to Task 3 to make the represented tolerance accurately measurable by the touch probe on the machine even if the part setup is changed. Finally, Task 4 is converting the result of Task into the motion of touch probe. The developed schema and algorithms were illustrated by several examples including that of ISO 14649 Part 12.

• Annual Conference of KIPS
• /
• 2016.04a
• /
• pp.283-285
• /
• 2016

최근 정보통신 기술의 발전과 함께 M2M(Machine-to-Machine) 산업분야의 시스템이 다기능 고성능화되고 있으며 IoT(Internet of Things), IoE(Internet of Everything)기술 등과 함께 많은 발전해가고 있다[1]. 가장 오래 된 정보통신 기술의 근간인 웹 애플리케이션은 점점 발전하고 고도화 되어가고 있으며 이러한 웹 애플리케이션을 해킹하는 기술도 다양한 관점에서 발전하고 있다. 웹 애플리케이션을 구성하는데 필수적인 파일인 TTF(True Type Font)파일에 대한 보안적 관심이 필요하다. TTF파일을 외부에서 받아옴으로서 웹 애플리케이션에 적용시키는 방식을 사용할 때, 다른 서버에서 URL을 통해 받아오는 TTF파일에 대해 보안적 검사가 제대로 실행되지 않는다. 본 논문에서는 TTF파일의 감염과 그 파일에 대한 대응 방법을 제안하고자 한다.

• Journal of Multimedia Information System
• /
• v.3 no.2
• /
• pp.21-26
• /
• 2016

Our networked world has been growing exponentially fast. The explosion in volume of machine-to-machine (M2M) transactions threatens to exceed the transport capacity of the networks that link them. Therefore, it is quite essential to reconsider the tradeoff between using many data sets versus using good data sets. We focus on this tradeoff in the context of the quality of information aggregated from many sensors in a noisy environment. We start with a basic theoretical model considered in the famous "CEO problem'' in the field of information theory. From a point of view of large deviations, we successfully find a simple statement for the optimal strategies under the limited network capacity condition. Moreover, we propose an open problem for a sensor network scenario and report a numerical result.

• Journal of Information Processing Systems
• /
• v.16 no.4
• /
• pp.975-990
• /
• 2020

Nowadays, the Internet of Things (IoT) network, is increasingly becoming a ubiquitous connectivity between different advanced applications such as smart cities, smart homes, smart grids, and many others. The emerging network of smart devices and objects enables people to make smart decisions through machine to machine (M2M) communication. Most real-world security and IoT-related challenges are vulnerable to various attacks that pose numerous security and privacy challenges. Therefore, IoT offers efficient and effective solutions. intrusion detection system (IDS) is a solution to address security and privacy challenges with detecting different IoT attacks. To develop an attack detection and a stable network, this paper's main objective is to provide a comprehensive overview of existing intrusion detections system for IoT environment, cyber-security threats challenges, and transparent problems and concerns are analyzed and discussed. In this paper, we propose software-defined IDS based distributed cloud architecture, that provides a secure IoT environment. Experimental evaluation of proposed architecture shows that it has better detection and accuracy than traditional methods.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.12
• /
• pp.635-640
• /
• 2016

It is important factors for a production system to get a profitable result in quality and reliability process. For this reason, there's are various type of research papers in a certain type of data acquisition and application to reliability and quality of the level of M2M devices. In general, a classification problem of slightly different signal such as sensing data is difficult to do with classical statistical methods. There's required real-time and instantaneous calculation properties in machine process. Especially a type of injection molding machine which has a property to be decided in accordance with short-term cycle process needs a solution that can be done a certain type of decision like as good or bad quality immediately. This paper presents a simple application of Kalman Filtering by single sensing data to injection molding process in order to get a correct answer from the real time sensing data.

• Journal of Korean Society of Forest Science
• /
• v.104 no.2
• /
• pp.198-205
• /
• 2015

The aim of this study was to provide the basic design parameters for developing logging residue compression machines by investigating compressive deformation characteristics of different types of logging residues. To achieve these objectives, Pinus rigida, Pinus koraensis and Quercus mongolica were selected as specimens, and compression-deformation tests by UTM(universial testing machine) were conducted. The experimental dataset were used to set up the model based on the compression-deformation ratio in the form of exponential function. The results showed that stress coefficient in terms of mechanical properties of logging residues was decreased, whereas strain coefficient tended to be increased as the number of compression increased at target density of $350kg/m^3$ and $400kg/m^3$. The model presented that the required stress was decreased as the number of compression increased, and the stress growth rate was swelled compared to the change of the deformation rate. Therefore, it showed that proper initial compression force was a significant variable in order to achieve the target density of logging residue.

• Journal of Preventive Medicine and Public Health
• /
• v.10 no.1
• /
• pp.94-101
• /
• 1977

Noise pollution, both in the environment and in the workplace, has been recognized as a major health hazard -one that can impair not only a person's hearing but also his physical and mental well-being. As industrialization progresses, the prevalence rate of occupational diseases is increasing, especially hearing loss, which has the highest prevalence rate among the occupational diseases. The major cause of noise is the construction of various large industries without any regulation of noise sources. Therefor, we must establish an enactment to control mechanical noise sources. as soon as possible. For the purpose of controlling the noise source, we must have exact data about such things as the sound level, the frequency of the peak sound and the revolutions per minute (r.p.m.) of the machine (a measure of the power of its motor). This study was undertaken in order to define the noise characteristics, the power of the machine's motor, the change of the sound level and the peak sound as the r.p.m. increases, and the permissible exposure time. The sample size of this study was 74 machines at 11 plants in 6 industries. The results are as follows; 1. The breakdown of the types of mechanical noise noted was : 63.6% continuous normal sound, 26.9% intermittent sound, 4.7% continuous repeating sound and 4.6% impulsive sound. 2. With respect to the type of industry, the overall sound level was the highest in the mechanical industry, with $103.8{\pm}2.8dB(A)$, and lowest in the textile industry, with $89.2{\pm}1.43dB(A)$. 3. With respect to the type of machine, the highest sound level was 124 dB(A) caused by Gauzing(II), in the mechanical industry, and the lowest was 76 dB(A) caused by Attachment (Jup Chack) (I) in the timber industry. 4. The shortest permissible exposure time to Gauzing(II) in the mechanical industry was less than 15 minutes. 5. Among 74 machines, 68.2% of the peak sound was situated in the high frequency range (52.7% at 2 KHz, 4.1% at 4 KHz and 1.4% at 8 KHz). 41.8% of the peak sound was in the middle frequency range (4.1% at 250Hz, 14.8% at 500Hz and 22.9% at 1KHz). 6. If one machine had two motors or more, the peak sound was shifted to the low frequency range. 7. As the r.p.m. increased, the overall and peak sound levels were increased without any change of the frequency of the peak sound. 8. Whenever the machines had the same kind and the same r.p.m., the overall and peak sounds were changed by the physicochemical characteristics of the raw materials and the management.

• Advances in materials Research
• /
• v.13 no.1
• /
• pp.63-86
• /
• 2024

Asphalt concrete (AC), is a mixture of bitumen and aggregates, which is very sensitive in the design of flexible pavement. In this study, the Marshall stability of the glass and carbon fiber bituminous concrete was predicted by using Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and M5P Tree machine learning algorithms. To predict the Marshall stability, nine inputs parameters i.e., Bitumen, Glass and Carbon fibers mixed in 100:0, 75:25, 50:50, 25:75, 0:100 percentage (designated as 100GF:0CF, 75GF:25CF, 50GF:50 CF, 25GF:75CF, 0GF:100CF), Bitumen grade (VG), Fiber length (FL), and Fiber diameter (FD) were utilized from the experimental and literary data. Seven statistical indices i.e., coefficient of correlation (CC), mean absolute error (MAE), root mean squared error (RMSE), relative absolute error (RAE), root relative squared error (RRSE), Scattering index (SI), and BIAS were applied to assess the effectiveness of the developed models. According to the performance evaluation results, Artificial neural network (ANN) was outperforming among other models with CC values as 0.9147 and 0.8648, MAE values as 1.3757 and 1.978, RMSE values as 1.843 and 2.6951, RAE values as 39.88 and 49.31, RRSE values as 40.62 and 50.50, SI values as 0.1379 and 0.2027 and BIAS value as -0.1 290 and -0.2357 in training and testing stage respectively. The Taylor diagram (testing stage) also confirmed that the ANN-based model outperforms the other models. Results of sensitivity analysis showed that the fiber length is the most influential in all nine input parameters whereas the fiber combination of 25GF:75CF was the most effective among all the fiber mixes in Marshall stability.