• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.19 no.4
• /
• pp.91-103
• /
• 2009

A cryptographic module (CM) is an implementation of various cryptographic algorithms and functions by means of hardware or software, When a CM is validated or certified under the CM validation program(CMVP), a finite state model(FSM) of the CM should be developed and provided, However, guides or methods of modeling and analysis of a FSM is not well-known, because the guide is occasionally regarded as a proprietary know-how by developers as well as verifiers of the CM. In this paper, we propose a set of guides on modeling and analysis of a FSM, which is needed for validation of a CM under CMVP, and a transition test path generation algorithm, as well as implement a simple modeling tool (CM-Statecharter). A FSM of a CM is modeled by using the Statechart of UML 2.0, Statechart, overcoming weakness of a FSM, is a formal and easy specification model for finite state modeling of a CM.

• Journal of the Institute of Convergence Signal Processing
• /
• v.22 no.2
• /
• pp.45-50
• /
• 2021

With the recent development of IT technology, research and interest in various bio-signal measuring devices are increasing. But studies related to ECG(electrocardiogram), which is one of the most representative bio-signals, particularly arrhythmic signal detection, are incomplete. Since arrhythmia has various causes and has a poor prognosis after onset, preventive treatment through early diagnosis is best. However, the 24-hour Holter electrocardiogram, a tool for diagnosing arrhythmia, has disadvantages in the limitation of use time, difficulty in analyzing motion artifact due to daily life, and the user's real-time alarm function in danger. In this study, an ECG and pulse monitoring device capable of continuous measurement for a long time, a real-time monitoring app, and software for analysis were developed, and the trend of the measured values was confirmed. In future studies, research on derivation of quantitative results of ECG signal measurement analysis is required, and further research on the development of an arrhythmic signal detection algorithm based on this is required.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.35 no.3
• /
• pp.223-231
• /
• 2022

Spectroscopies are the most widely used for understanding the crystallographic, chemical, and physical aspects of materials; therefore, numerous commercial and non-commercial software have been introduced to help researchers better handling their spectroscopic data. However, not many researchers, especially early-stage ones, have a proper background knowledge on the choice of fitting functions and a technique for actual fitting, although the essence of such data analysis is peak fitting. In this regard, we present a practical guide for peak fitting for data analysis. We start with a basic-level theoretical background why and how a certain protocol for peak fitting works, followed by a step-by-step visualized demonstration how an actual fitting is performed. We expect that this contribution is sure to help many active researchers in the discipline of materials science better handle their spectroscopic data.

• International Journal of Computer Science & Network Security
• /
• v.21 no.11
• /
• pp.338-344
• /
• 2021

The recently continuous enhancement and development in the biomedical side for the betterment of human life. The Wireless Body Area Networks is a significant tool for the current researcher to design and transfer data with greater data rates among the sensors and sensor nodes for biomedical applications. The core area for research in WBANs is power efficiency, battery-driven devices for health and medical, the Charging limitation is a major and serious problem for the WBANs.this research work is proposed to find out the optimal solution for battery-friendly technology. In this research we have addressed the solution to increasing the battery lifetime with variable data transmission rates from medical equipment as Wireless Endoscopy Capsules, this device will analyze a patient's inner body gastrointestinal tract by capturing images and visualization at the workstation. The second major issue is that the Wireless Endoscopy Capsule based systems are currently not used for clinical applications due to their low data rate as well as low resolution and limited battery lifetime, in case of these devices are more enhanced in these cases it will be the best solution for the medical applications. The main objective of this research is to power optimization by reducing the power consumption of the battery in the Wireless Endoscopy Capsule to make it battery-friendly. To overcome the problem we have proposed the algorithm for "Battery Friendly Algorithm" and we have compared the different frame rates of buffer sizes for Transmissions. The proposed Battery Friendly Algorithm is to send the images on average frame rate instead of transmitting the images on maximum or minimum frame rates. The proposed algorithm extends the battery lifetime in comparison with the previous baseline proposed algorithm as well as increased the battery lifetime of the capsule.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.7
• /
• pp.17-25
• /
• 2022

Hash functions are widely used for fast equality analysis of video files because of their fixed small output sizes regardless of their input sizes. However, the hash function has the possibility of a hash collision in which different inputs derive the same output value, so there is a problem that different video files may be mistaken for the same file. In this paper, we propose an equality analysis scheme in which different video files always derive different output values using identifier information and double hash. The scheme first extracts the identifier information of an original video file, and attaches it into the end of the original file with a steganography method. Next the scheme calculates two hash output values of the original file and the extended file with attached identifier information. Finally the scheme utilizes the identifier information, the hash output value of the original file, and the hash output value of the extended file for the equality analysis of video files. For evaluation, we implement the proposed scheme into a practical software tool and show that the proposed scheme performs well the equality analysis of video files without hash collision problem and increases the resistance against the malicious hash collision attack.

• Communications for Statistical Applications and Methods
• /
• v.29 no.4
• /
• pp.421-439
• /
• 2022

Phase I dose-finding trials are essential in drug development. By finding the maximum tolerated dose (MTD) of a new drug or treatment, a Phase I trial establishes the recommended doses for later-phase testing. The primary toxicity endpoint of interest is often a binary variable, which describes an event of a patient who experiences dose-limiting toxicity. However, there is a growing interest in dose-finding studies regarding non-binary outcomes, defined by either the weighted sum of rates of various toxicity grades or a continuous outcome. Although several novel methods have been proposed in the literature, accessible software is still lacking to implement these methods. This study introduces a newly developed R package, UnifiedDoseFinding, which implements three phase I dose-finding methods with non-binary outcomes (Quasi- and Robust Quasi-CRM designs by Yuan et al. (2007) and Pan et al. (2014), gBOIN design by Mu et al. (2019), and by a method by Ivanova and Kim (2009)). For each of the methods, UnifiedDoseFinding provides corresponding functions that begin with next that determines the dose for the next cohort of patients, select, which selects the MTD defined by the non-binary toxicity endpoint when the trial is completed, and get oc, which obtains the operating characteristics. Three real examples are provided to help practitioners use these methods. The R package UnifiedDoseFinding, which is accessible in R CRAN, provides a user-friendly tool to facilitate the implementation of innovative dose-finding studies with nonbinary outcomes.

• Journal of Korean Academy of Nursing
• /
• v.52 no.5
• /
• pp.535-549
• /
• 2022

Purpose: The study aimed to design and develop an automated personalized self-care (APSC) program for patients with type 2 diabetes mellitus. The secondary aim was to present a clinical protocol as a mixed-method research to test the program effects. Methods: The APSC program was developed in the order of analysis, design, implementation, and evaluation according to the software development life cycle, and was guided by the self-regulatory theory. The content validity, heuristics, and usability of the program were verified by experts and patients with type 2 diabetes mellitus. Results: The APSC program was developed based on goal setting, education, monitoring, and feedback components corresponding to the phases of forethought, performance/volitional control, and self-reflection of self-regulatory theory. Using the mobile application, the participants are able to learn from educational materials, monitor their health behaviors, receive weekly-automated personalized goals and feedback messages, and use an automated conversation system to solve the problems related to self-care. The ongoing two-year study utilizes a mixed method design, with 180 patients having type 2 diabetes mellitus randomized to receive either the intervention or usual care. The participants will be reviewed for self-care self-efficacy, health behaviors, and health outcomes at 6, 12, 18, and 24 months. Participants in the intervention group will be interviewed about their experiences. Conclusion: The APSC program can serve as an effective tool for facilitating diabetes health behaviors by improving patients' self-care self-efficacy and self-regulation for self-care. However, the clinical effectiveness of this program requires further investigation.

• Journal of Acupuncture Research
• /
• v.39 no.4
• /
• pp.283-296
• /
• 2022

In this study, the evidence of thread embedding acupuncture (TEA) in treating cervical radiculopathy in randomized controlled trials was investigated. We searched 16 databases up to August 22, 2022. Of the 2,644 studies retrieved, 22 randomized controlled trials (2,483 participants) were selected. Quality assessments were performed using Cochrane's risk-of-bias tool and RevMan 5.4 software. Outcome measures in the included studies typically showed TEA had a significant therapeutic effect compared with simple acupuncture and other remedies, and TEA was better than sham TEA. Catgut and polydioxanone had no difference in effectiveness, however, catgut was considered to be less safe. TEA was shown to be more therapeutic when inserted deeper into the skin. Ultrasound guided TEA was more effective and safer than conventional TEA, and using a flat blade needle was better than conventional needles for TEA. No serious adverse events were reported from using TEA, and only a few mild side effects were observed. However, the limited number and heterogeneity of the included studies, together with the unclear methodological quality, indicate that higher-quality studies need to be conducted to determine the effectiveness and safety of TEA for cervical radiculopathy.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.1
• /
• pp.41-50
• /
• 2023

Recently, as the Coronavirus disease 2019 (COVID-19) prolongs along with the development of artificial intelligence technology, a non-contact society has become commonplace. Many companies are promoting digital transformation and the activation of artificial intelligence introduction to respond to this which leads to dramatic increase of demand for Chatbot. In addition, a Chatbot has reached the point of processing business transactions from responding simple inquiries. However, it is necessary to develop an API to interface with the legacy system and there are many difficulties in connecting. To solve this, it is becoming important to establish a hybrid Chatbot environment through RPA interface. Recently, the combination of RPA and Chatbot is considered an effective tool for handling many business processes. But, there are many difficulties due to the lack of interface cases and the difficulty in finding a method to development them. This study suggests a method for building a hybrid Chatbot which is an interface Chatbot(Conversational UX) and RPA(Task Automation) from the perspective of hyper-automation based on actual development cases and review of literature review is presented, so that the interface method can be understood and develop more easily. Therefore, there are implications for actively using AI Chatbot for digital transformation.

• Journal of the Korean Society of Systems Engineering
• /
• v.18 no.2
• /
• pp.75-93
• /
• 2022

Machine learning (ML) data-driven meta-model is proposed as a surrogate model to reduce the excessive computational cost of the physics-based model and facilitate the real-time prediction of a nuclear power plant's transient response. To forecast the transient response three machine learning (ML) meta-models based on recurrent neural networks (RNNs); specifically, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), and a sequence combination of Convolutional Neural Network (CNN) and LSTM are developed. The chosen accident scenario is a control element assembly withdrawal at power concurrent with the Loss Of Offsite Power (LOOP). The transient response was obtained using the best estimate thermal hydraulics code, MARS-KS, and cross-validated against the Design and control document (DCD). DAKOTA software is loosely coupled with MARS-KS code via a python interface to perform the Best Estimate Plus Uncertainty Quantification (BEPU) analysis and generate a time series database of the system response to train, test and validate the ML meta-models. Key uncertain parameters identified as required by the CASU methodology were propagated using the non-parametric Monte-Carlo (MC) random propagation and Latin Hypercube Sampling technique until a statistically significant database (181 samples) as required by Wilk's fifth order is achieved with 95% probability and 95% confidence level. The three ML RNN models were built and optimized with the help of the Talos tool and demonstrated excellent performance in forecasting the most probable NPP transient response. This research was guided by the Systems Engineering (SE) approach for the systematic and efficient planning and execution of the research.