• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.49-57
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• 2022

Currently, the problem of food shortage is emerging in our society due to climate problems and an increase population in the world. As a solution to this problem, we propose a multi-remote control smart farm that combines artificial intelligence (AI) and information and communication technology (ICT) technologies. The proposed smart farm integrates ICT technology to remotely control and manage crops without restrictions in space and time, and to multi-control the growing environment of crops. In addition, using Arduino and deep-learning technology, a smart farm capable of multiple control through a smart-phone application (APP) was proposed, and Ai technology with various data securing and diagnosis functions while observing crop growth in real-time was included. Various sensors in the smart farm are controlled by using the Arduino, and the data values of the sensors are stored in the built database, so that the user can check the stored data with the APP. For multiple control for multiple crops, each LED, COOLING FAN, and WATER PUMP for two or more growing environments were applied so that the user could control it conveniently. And by implementing an APP that diagnoses the growth stage through the Tensor-Flow framework using deep-learning technology, we developed an application that helps users to easily diagnose the growth status of the current crop.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.935-941
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• 2020

People estimation is important to provide IoT services. Most people counting technologies use camera or sensor data. However, the conventional technologies have the disadvantages of invasion of privacy and the need to install extra infrastructure. This paper proposes a method for estimating the number of people using a Wi-Fi AP. We use channel state information of Wi-Fi and analyze that using deep learning technology. It can be achieved by pre-installed Wi-Fi infrastructure that reduce cost for people estimation and privacy infringement. The proposed algorithm uses a k-binding data for pre-processing process and a 1D-CNN learning model. Two APs were installed to analyze the estimation results of six people. The result of the accurate number estimation was 64.8%, but the result of classifying the number of people into classes showed a high result of 84.5%. This algorithm is expected to be applicable to estimate the density of people in a small space.

• Journal of the Korean Solar Energy Society
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• v.28 no.6
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• pp.58-63
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• 2008

It is essential to investigate the structure and the main characteristic of Home USN (Ubiquitous Sensor Network) technologies in built ubiquitous environment while designing bio-sensors. For this study, Thermistor elements and Thermopile black body have been selected to implement ubiquitous technologies for bio-sensors and wireless network such as WiBro has been used to transfer sensing data to the BSN (Bio-Sensor Network) gateway. It is certain that efficiency of ubiquitous space design is improved if main components of each specific sensor network are analyzed precisely in digital way and corresponding communication modules are prepared accordingly. Ubiquitous technology, in conclusion, has to be applied not only with systematical mechanism or electronic setting but in human-centered atmosphere as well, keeping with deep consideration for bio-housing service factors in eco-friendly surrounding.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1452-1455
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• 2021

Recently, point clouds are generated by capturing real space in 3D, and it is actively applied and serviced for performances, exhibitions, education, and training. These point cloud data require post-correction work to be used in virtual environments due to errors caused by the capture environment with sensors and cameras. In this paper, we propose an enhancement technique for 3D point cloud data by applying generative adversarial network(GAN). Thus, we performed an approach to regenerate point clouds as an input of GAN. Through our method presented in this paper, point clouds with a lot of noise is configured in the same shape as the real object and environment, enabling precise interaction with the reconstructed content.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.70-75
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• 2023

With the recent proliferation of memory-intensive workloads such as deep learning, analyzing memory access characteristics for efficient memory management is becoming increasingly important. Since read and write operations in memory access have different characteristics, an efficient memory management policy should take into accountthe characteristics of thesetwo operationsseparately. Although some previous studies have considered the different characteristics of reads and writes, they require a modified hardware architecture supporting read bits and write bits. Unlike previous approaches, we propose a software-based management policy under the existing memory architecture for considering read/write characteristics. The proposed policy logically partitions memory space into the read/write area and the write area by making use of reference bits and dirty bits provided in modern paging systems. Simulation experiments with memory access traces show that our approach performs better than the CLOCK algorithm by 23% on average, and the effect is similar to the previous policy with hardware support.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.139-144
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• 2023

Engineers prefer deep neural networks (DNNs) for solving computer vision problems. However, DNNs pose two major problems. First, neural networks require large amounts of well-labeled data for training. Second, the covariate shift problem is common in computer vision problems. Domain adaptation has been proposed to mitigate this problem. Recent work on adversarial-learning-based unsupervised domain adaptation (UDA) has explained transferability and enabled the model to learn robust features. Despite this advantage, current methods do not guarantee the distinguishability of the latent space unless they consider class-aware information of the target domain. Furthermore, source and target examples alone cannot efficiently extract domain-invariant features from the encoded spaces. To alleviate the problems of existing UDA methods, we propose the mixup regularization in adversarial discriminative domain adaptation (ADDA) method. We validated the effectiveness and generality of the proposed method by performing experiments under three adaptation scenarios: MNIST to USPS, SVHN to MNIST, and MNIST to MNIST-M.

• Journal of IKEEE
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• v.22 no.3
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• pp.693-699
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• 2018

CNN based object recognitions have reported splendid results. However, the recognition of mobile apps raises an interesting challenge that recognition performance of similar widgets is not consistent. In order to improve the performance, we propose a noble method utilizing relations between input widgets. The recognition process flows from the Faster R-CNN based recognition to enhancement using a relation recognizer. The relations are represented as vector translation between objects in a relation space. Experiments on 323 apps show that our method significantly enhances the Faster R-CNN only approach.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.8
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• pp.1488-1494
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• 2008

This paper is to design and implement a low power noncoherent BFSK receiver intended for future deep space communication using Xilinx System generator. The receiver incorporates a 16 point Fast Fourier Transform(FFT) for symbol detection. The design units of the receiver are digital design for better efficiency and reliability. The receiver functions on one bit data processing and supports main data rate 10kbps. In addition CORDIC algorithm is used for avoiding complex multiplications while computing FFT and multiplication of twiddle factor for low power is substituted by rotators. The design and simulation of the receiver is carried out in Simulink then the Simulink model is translated to the hardware model to implement FPGA using Xilinx System Generator and to verify performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.181-187
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• 2024

There are two kinds of well-known CNN methods, the group equivariant CNN and the CNN using steerable filters, which have excellent classification performances for randomly rotated objects in image space. This paper describes their mathematical structures and introduces implementation methods. We implement them, including the existing CNN, which have the same number of filters, then compare and analyze their performances by simulating them with the randomly rotated MNIST. According to the experimental results, the steerable CNN, which shows a classification improvement over the others, has a relatively small number of parameters to learn, so performance degradation is relatively small even when the size of the training dataset is reduced.

• Korean journal of communication and information
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• v.61
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• pp.118-133
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• 2013

Lee Yeung-Hi is one of the most influential journalist in the modern history of Korea. Nevertheless, the judgement about him has been parallelized by opposite sides. He is called 'the Master of ideology', while the other calls him 'the culprit of theorization'. This thesis deduced the contemporary meaning of person Lee Yeung-Hi in order to promote communication for both sides. I compared their logical arguments and pointed out the error they missed. Also, I clarified that the criticism and anticriticism for Lee Young-Hi in the fields of both journalism and academia have fallacies, such as the fallacy of straw man, and the fallacy of question-begging. I criticized their arguments through the view of 'struggling to seek truth', which is the core value of Lee Yeung-Hi's thought. The necessity of communication between advocators and it's critics is due to the condition of Korean Journalism. Korean Journalism does not have much space to accept Lee Young-Hi in only one side. Paradoxically, the contemporary meaning of the truth that Journalist Lee Young-Hi had sought is profound and deep because of the condition where Korean Journalism is being dominated by political parallelism.