• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1431-1440
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• 2024

The study aimed to develop a laser-based distance meter (LDM) to improve water surface identification for clinical MeV electron beam dosimetry, as inaccurate water surface determination can lead to imprecise positioning of ionization chambers (ICs). The LDM consisted of a laser ranging sensor, a signal processing microcontroller, and a tablet PC for data acquisition. I₅₀ (the water depth at which ionization current drops to 50 % of its maximum) measurements of electron beams were performed using six different types of ICs and compared to other water surface identification methods. The LDM demonstrated reproducible I₅₀ measurements with a level of 0.01 cm for all six ICs. The uncertainty of water depth was evaluated at 0.008 cm with the LDM. The LDM also exposed discrepancies between I₅₀ measurements using different ICs, which was partially reduced by applying an optimum shift of IC's point of measurement (POM) or effective point of measurement (EPOM). However, residual discrepancies due to the energy dependency of the cylindrical chamber's EPOM caused remained. The LDM offers straightforward and efficient means for precision water surface identification, minimizing reliance on individual operator skills.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.403-411
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• 2014

In this paper, an algorithm of extracting the features of home appliances and automatically building a database to identify home appliances is designed and presented. For the verification, a software library supporting this algorithm is implemented and added to an power management system server, which was already implemented to support real-time monitoring of home appliances' power consumption status and controlling their power. The implemented system consists of a system server and clients, each of which measures the power consumed by a home appliance plugged in it and transmits the information to the server in real-time over a wireless network. Through experiments, it is verified that it is possible to identify any home appliance connected to a specific client.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.63-68
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• 2018

Recently, safety accidents that occur in laboratories have occurred in various forms, so that a system that can reduce safety accidents in laboratories is required. The existing system identifies the danger situation according to the change of the temperature and the humidity, but the type of the danger situation is not known and the operation of the device is manually performed. Therefore, in this paper, we propose a system that identifies the danger situation of a reagent cabinet using multiple sensors and automatically operates the device. The internal environment of the reagent cabinet is measured in real time through the sensors and the sensor data is used to identify the danger situation. Also, when a danger situation is identified, the appropriate device is selected and operated automatically. In this way, identification of the danger situation of the reagent cabinet and automatic operation of the device will reduce the safety accidents occurring in the reagent cabinet.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.203-209
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• 2023

The paper brings across data that is utilized in the Bring Your Own Device (BYOD) status collected between February and April of 2021 across Saudi Arabia. The data set was collected using questionnaires established through online mechanisms for the respondents. In the questionnaire, personal details included five questions while seven questions addressed the working model of personal mobile devices. Six questions addressed the awareness of employees bring your own device awareness for employees comprised seven questions and two questions addressed the benefits of business achievements. In the identification of suitable respondents for the research, two approaches were applied. The research demanded that the respondents be Saudi Arabian nationals and have attained 18 years. Snowball and purposive techniques were applied in the collection of information from a wide area of Saudi Arabia while employing social media approaches that include the use of WhatsApp and emails in the collection of data. The approach ensured the collection of data from 857 respondents used in the identification of the status as well as issues across the BYOD environment and accompanying solutions. The data was also used in the provision of awareness in the community through short-term courses, cyber security training and awareness programs. The results of the research are therefore applicable to the context of the Saudi Arabian country that is currently facing issues in dealing with the application of personal devices in the work environment.

• Journal of the Korean Wood Science and Technology
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• v.45 no.6
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• pp.797-808
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• 2017

Automatic wood species identification systems have enabled fast and accurate identification of wood species outside of specialized laboratories with well-trained experts on wood species identification. Conventional automatic wood species identification systems consist of two major parts: a feature extractor and a classifier. Feature extractors require hand-engineering to obtain optimal features to quantify the content of an image. A Convolutional Neural Network (CNN), which is one of the Deep Learning methods, trained for wood species can extract intrinsic feature representations and classify them correctly. It usually outperforms classifiers built on top of extracted features with a hand-tuning process. We developed an automatic wood species identification system utilizing CNN models such as LeNet, MiniVGGNet, and their variants. A smartphone camera was used for obtaining macroscopic images of rough sawn surfaces from cross sections of woods. Five Korean softwood species (cedar, cypress, Korean pine, Korean red pine, and larch) were under classification by the CNN models. The highest and most stable CNN model was LeNet3 that is two additional layers added to the original LeNet architecture. The accuracy of species identification by LeNet3 architecture for the five Korean softwood species was 99.3%. The result showed the automatic wood species identification system is sufficiently fast and accurate as well as small to be deployed to a mobile device such as a smartphone.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1561-1569
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• 2016

As the use of the sensor device increases in IoT environment, the need for device security is becoming more and more important When a sensor device is deployed in IEEE 802.15.4-based LoWPAN, it has to perform the join operation with PAN Coordinator and the binding operation with another device. In the join and binding process, authentication and key distribution of the device are performed using the pre-distributed network key or certificate. However, the network key used in the conventional method has problems that it's role is limited to the group authentication and individual identification is not applied in certificate issuing. In this paper, we propose a secure join and binding protocol in LoWPAN environment that solves the problems of pre-distributed network key.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.319-320
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• 2002

Numerical simulation of chip formation during high speed machining requires knowing the friction at tool/chip interface. This parameter is hardly identified and generally the loadings (temperature, force) during the identification are not similar to those encountered during machining. Thus, Coulomb friction identified with pin-on-disc device is often used to conduct numerical simulation. The used of this technique cannot leads to good numerical results of chip formation compared to the experimental tests especially in the case of low uncut chip thickness. In this contribution, we propose a new method to evaluate the friction at tool/chip interface. In fact several Coulomb friction parameters are identified corresponding to several parts of the cutting tool. Experimental tests have been conducted allowed us to determinate both the level and the distribution of the Coulomb friction. Experimental results are also compared to the results of orthogonal cutting simulation. We show that this technique allows predicting accuracy results of chip formation.

• Phonetics and Speech Sciences
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• v.4 no.3
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• pp.95-101
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• 2012

In this paper, we introduce the automatic speaker identification system 'SPO(Supreme Prosecutors Office) Verifier'. SPO Verifier is a GMM(Gaussian mixture model)-UBM(universal background model) based automatic speaker recognition system and has been developed using Korean speakers' utterances. This system uses a channel compensation algorithm to compensate recording device characteristics. The system can give the users the ability to manage reference models with utterances from various environments to get more accurate recognition results. To evaluate the performance of SPO Verifier on Korean speakers, we compared this system with one of the most widely used commercial systems in the forensic field. The results showed that SPO Verifier shows lower EER(equal error rate) than that of the commercial system.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.311-320
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• 2007

Interrogative sentences are generally used to perform speech acts of directly asking a question or making a request, but they are also used to convey such speech acts indirectly. In the utterances, such indirect uses of interrogative sentences usually carry speaker's emotion with a negative attitude, which is close to an expression of anger. The identification of such negative emotion is known as a difficult problem that requires relevant information in syntax, semantics, discourse, pragmatics, and speech signals. In this paper, we argue that the interrogatives used for indirect speech acts could serve as a dominant marker for identifying the emotional attitudes, such as anger, as compared to other emotion-related markers, such as discourse markers, adverbial words, and syntactic markers. To support such an argument, we analyze the dialogues collected from the Korean soap operas, and examine individual or cooperative influences of the emotion-related markers on emotional realization. The user study shows that the interrogatives could be utilized as a promising device for emotion identification.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2891-2894
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• 1999

This paper proposes an alternative personal identification algorithm using finger crease pattern which is assumed to overcome the disadvantages of the existing biometrics system. We used a CED camera with LED lighting as the input device. The original images were treated by employing a lowpass and highpass Jilter to get the reinforced finger boundaries and finger crease patterns, thereby threshold is applied. We tracked the boundaries of the finger and extracted the Images of the index, middle, and ring finger, thereafter applied noise reduction operation. In the last step, we performed the verifications of a person by matching one dimensional profiles of finger crease patterns. This algorithm shows the possibility of an alternative biometrics identification system to the current ones. Lastly, the comparative evaluation on our system and the other algorithm is presented.