• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.15 no.1
• /
• pp.56-61
• /
• 2022

In this paper, we classify and present AI algorithms and natural language processing methods used in chatbots. A framework that can be used to implement a chatbot is also described. A chatbot is a system with a structure that interprets the input string by constructing the user interface in a conversational manner and selects an appropriate answer to the input string from the learned data and outputs it. However, training is required to generate an appropriate set of answers to a question and hardware with considerable computational power is required. Therefore, there is a limit to the practice of not only developing companies but also students learning AI development. Currently, chatbots are replacing the existing traditional tasks, and a practice course to understand and implement the system is required. RNN and Char-CNN are used to increase the accuracy of answering questions by learning unstructured data by applying technologies such as deep learning beyond the level of responding only to standardized data. In order to implement a chatbot, it is necessary to understand such a theory. In addition, the students presented examples of implementation of the entire system by utilizing the methods that can be used for coding education and the platform where existing developers and students can implement chatbots.

• Journal of IKEEE
• /
• v.25 no.4
• /
• pp.625-633
• /
• 2021

This paper describes a scalable architecture for flexible hardware implementation of Montgomery modular multiplication. Our scalable modular multiplier architecture, which is based on a one-dimensional array of processing elements (PEs), performs word parallel operation and allows us to adjust computational performance and hardware complexity depending on the number of PEs used, N_PE. Based on the proposed architecture, we designed a scalable Montgomery modular multiplier (sMM) core supporting eight field sizes defined in SEC2. Synthesized with 180-nm CMOS cell library, our sMM core was implemented with 38,317 gate equivalents (GEs) and 139,390 GEs for N_PE=1 and N_PE=8, respectively. When operating with a 100 MHz clock, it was evaluated that 256-bit modular multiplications of 0.57 million times/sec for N_PE=1 and 3.5 million times/sec for N_PE=8 can be computed. Our sMM core has the advantage of enabling an optimized implementation by determining the number of PEs to be used in consideration of computational performance and hardware resources required in application fields, and it can be used as an IP (intellectual property) in scalable hardware design of elliptic curve cryptography (ECC).

• Journal of Convergence for Information Technology
• /
• v.12 no.5
• /
• pp.116-125
• /
• 2022

Recent aspects of terrorism varies in various ways according to means, targets, and regions. In particular, the 9/11 terrorist attacks in the United States in 2001 changed the paradigm of each country's terrorism, and the South Korea also participated in the enactment and enforcement of the Anti-Terrorism Act in 2016. Based on this, CBRN terrorism is included in general terrorism, and the National Police Agency plays the role of a control tower, and a system supported by related organizations such as the Ministry of Environment is being built and operated. However, restrictions were confirmed in the organizational system, manpower composition, and equipment and materials in operation in preparation for CBRN within the police. Based on the identified limitations, we proposed improvement plans to strengthen the capacity for CBRN terrorism: establishing a dedicated CBRN organization; creating research organization; and securing additional dedicated personnel. Based on this, as an improvement plan to strengthen the capability of CBRN, the establishment of an organization dedicated to CBRN and a research organization within the National Police Agency, and expansion of electronic equipment suitable for the characteristics of CBRN were proposed. It is expected that the police's on-site response capability system for CBRN terrorism will be strengthened via the proposed improvement measures to recover the various restrictions on the response to CBRN terrorism.

• Journal of Internet Computing and Services
• /
• v.23 no.4
• /
• pp.57-64
• /
• 2022

If the inside of a building collapses due to a disaster such as fire, collapse, or natural disaster, the physical security inside the building is likely to become ineffective. Here, physical security is needed to minimize the human casualties and physical damages in the collapsed building. Therefore, this paper proposes an algorithm to minimize the damage in a disaster situation by fusing existing research that detects obstacles and collapsed areas in the building and a deep learning-based object detection algorithm that minimizes human casualties. The existing research uses a single camera to determine whether the corridor environment in which the robot is currently located has collapsed and detects obstacles that interfere with the search and rescue operation. Here, objects inside the collapsed building have irregular shapes due to the debris or collapse of the building, and they are classified and detected as obstacles. We also propose a method to detect rescue requesters-the most important resource in the disaster situation-and minimize human casualties. To this end, we collected open-source disaster images and image data of disaster situations and calculated the accuracy of detecting rescue requesters in disaster situations through various deep learning-based object detection algorithms. In this study, as a result of analyzing the algorithms that detect rescue requesters in disaster situations, we have found that the YOLOv4 algorithm has an accuracy of 0.94, proving that it is most suitable for use in actual disaster situations. This paper will be helpful for performing efficient search and rescue in disaster situations and achieving a high level of physical security, even in collapsed buildings.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.2
• /
• pp.15-26
• /
• 2021

Recently, as the introduction of cloud, mobile, and IoT has become active, there is a growing need for technology development that can supplement the limitations of traditional security solutions based on fixed perimeters such as firewalls and Network Access Control (NAC). In response to this, SDP (Software Defined Perimeter) has recently emerged as a new base technology. Unlike existing security technologies, SDP can sets security boundaries (install Gateway S/W) regardless of the location of the protected resources (servers, IoT gateways, etc.) and neutralize most of the network-based hacking attacks that are becoming increasingly sofiscated. In particular, SDP is regarded as a security technology suitable for the cloud and IoT fields. In this study, a new access control system was proposed by combining SDP and hash tree-based large-scale data high-speed signature technology. Through the process authentication function using large-scale data high-speed signature technology, it prevents the threat of unknown malware intruding into the endpoint in advance, and implements a kernel-level security technology that makes it impossible for user-level attacks during the backup and recovery of major data. As a result, endpoint security, which is a weak part of SDP, has been strengthened. The proposed system was developed as a prototype, and the performance test was completed through a test of an authorized testing agency (TTA V&V Test). The SDP-based access control solution is a technology with high potential that can be used in smart car security.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.14 no.2
• /
• pp.128-133
• /
• 2021

Currently, autonomous vehicle markets are commercializing a third-level autonomous vehicle, but there is a possibility that an accident may occur even during fully autonomous driving due to stability issues. In fact, autonomous vehicles have recorded 81 accidents. This is because, unlike level 3, autonomous vehicles after level 4 have to judge and respond to emergency situations by themselves. Therefore, this paper proposes a vehicle crisis detection system(VCDS) that collects and stores information outside the vehicle through CNN, and uses the stored information and vehicle sensor data to output the crisis situation of the vehicle as a number between 0 and 1. The VCDS consists of two modules. The vehicle external situation collection module collects surrounding vehicle and pedestrian data using a CNN-based neural network model. The vehicle crisis situation determination module detects a crisis situation in the vehicle by using the output of the vehicle external situation collection module and the vehicle internal sensor data. As a result of the experiment, the average operation time of VESCM was 55ms, R-CNN was 74ms, and CNN was 101ms. In particular, R-CNN shows similar computation time to VESCM when the number of pedestrians is small, but it takes more computation time than VESCM as the number of pedestrians increases. On average, VESCM had 25.68% faster computation time than R-CNN and 45.54% faster than CNN, and the accuracy of all three models did not decrease below 80% and showed high accuracy.

• Journal of the Korean Recycled Construction Resources Institute
• /
• v.9 no.4
• /
• pp.492-498
• /
• 2021

In this paper, the electromagnetic wave transmittance of the reinforced concrete structure wall was analyzed using the performance measurement system of electromagnetic wave shielding. Recently, electromagnetic wave shielding technologies on the reinforced concrete wall conditions have been studied, and the shielding effectiveness have been tested on unit cell size. However, the unit cell size tests have problems on that the measurement range for shielding performance is insufficient and it is difficult to reflect the real conditions of the concrete wall. Therefore, we constructed a shielding performance measurement system using a large sample of 2.2m × 2.2m like a real wall. To verify the measurement system, general reinforced concrete test samples were selected, and real shielding performance measurements and numerical analysis were proceeded. Test and numerical analysis results showed similar tendencies in the evaluation frequency range of 75MHz to 2GHz. Thus we validated the effectiveness of this shielding performance measurement system.

• The Journal of the Acoustical Society of Korea
• /
• v.41 no.3
• /
• pp.326-334
• /
• 2022

In this paper, we propose speech enhancement algorithm as a pre-processing for robust speech recognition in noisy environments. Auxiliary-function-based Independent Vector Analysis (AuxIVA) is performed with weighted covariance matrix using time-varying variances with scaling factor from target masks representing time-frequency contributions of target speech. The mask estimates can be obtained using Neural Network (NN) pre-trained for speech extraction or diffuseness using Coherence-to-Diffuse power Ratio (CDR) to find the direct sounds component of a target speech. In addition, outputs for omni-directional noise are closely chained by sharing the time-varying variances similarly to independent subspace analysis or IVA. The speech extraction method based on AuxIVA is also performed in Independent Low-Rank Matrix Analysis (ILRMA) framework by extending the Non-negative Matrix Factorization (NMF) for noise outputs to Non-negative Tensor Factorization (NTF) to maintain the inter-channel dependency in noise output channels. Experimental results on the CHiME-4 datasets demonstrate the effectiveness of the presented algorithms.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.1
• /
• pp.49-54
• /
• 2023

The Global Positioning System (GPS) was developed for military purposes and developed as it is today by opening civilian signals (GPS L1 frequency C/A signals). The current satellite orbits the earth about twice a day to measure the position, and receives more than 3 satellite signals (initially, 4 to calculate even the time error). The three-dimensional position of the ground receiver is determined using the data from the radio wave departure time to the radio wave Time of Arrival(TOA) of the received satellite signal through trilateration. In the case of navigation using GPS in recent years, a location error of 5 to 10 m usually occurs, and quite a lot of areas, such as apartments, indoors, tunnels, factory areas, and mountainous areas, exist as blind spots or neutralized areas outside the error range of GPS. Therefore, in order to acquire one's own location information in an area where GPS satellite signal reception is impossible, another method should be proposed. In this study, IMU(Inertial Measurement Unit) combined with an acceleration and gyro sensor and a geomagnetic sensor were used to design a system to enable location recognition even in terrain where GPS signal reception is impossible. A method to track the current position by calculating the instantaneous velocity value using a 9-DOF IMU and a geomagnetic sensor was studied, and its feasibility was verified through production and experimentation.

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.32 no.1
• /
• pp.78-88
• /
• 2022

Objectives: To develop the smart sensor to protect worker's health from chemical exposure by adopting ICT (Information and Communications Technology) technologies. Methods: To develope real-time chemical exposure monitoring system, IoT (Internet of Things) sensor technology and regulations were reviewed. We developed and produced smart sensor. A smart sensor is a system consisting of a sensor unit, a communication unit, and a platform. To verify the performance of smart sensors, each sensor has been certified by the Korea Laboratory Accreditation Scheme (KOLAS). Results: Chemicals (TVOC; Total Volatile Organic Compounds, Cl₂: Chlorine, HF: Hydrogen fluoride and HCN: Hydrogen cyanide) were selected according to a priority logic (KOSHA Alert, acute poisoning statistics, literature review). Notifications were set according to OEL (occupational exposure limit). Sensors were selected based on OEL and the capabilities of the sensors. Communication is designed to use LTE (Long Term Evolution) and Wi-Fi at the same time for convenience. Electronic platform were applied to build this monitoring system. Conclusions: Real-time monitoring system for OEL of hazardous chemicals in workplace was developed. Smart sensor can detect chemicals to complement monitoring of traditional workplace environmental monitoring such as short term and peak exposure. Further research is needed to expand the scope of application, improve reliability, and systematically application.