• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.4
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• pp.374-381
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• 1991

As a diagnostic image of hospitl, the utilization of digital image is steadily increasing. Image coding is indispensable for storing and compressing an enormous amount of diagnostic images economically and effectively. In this paper adaptive two stage vector quantization based on Kohonen's neural network for the compression of cardioangiography among typical angiography of radiographic image sequences is presented and the performance of the coding scheme is compare and gone over. In an attempt to exploit the known characteristics of changes in cardioangiography, relatively large blocks of image are quantized in the first stage and in the next stage the bloks subdivided by the threshold of quantization error are vector quantized employing the neural network of frequency sensitive competitive learning. The scheme is employed because the change produced in cardioangiography is due to such two types of motion as a heart itself and body motion, and a contrast dye material injected. Computer simulation shows that the good reproduction of images can be obtained at a bit rate of 0.78 bits/pixel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.3B
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• pp.565-569
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• 2000

We compose the two-stage recurrent neural network that returns both signals of a hidden and an output layer to the hidden layer. It is tested on the basis of syllables for Korean spoken digit from /gong/to /gu. For these experiments, we adjust the neuron number of the hidden layer, the predictive order of input data and self-recurrent coefficient of the decision state layer. By the experimental results, the recognition rate of this neural network is between 91% and 97.5% in the speaker-dependent case and between 80.75% and 92% in the speaker-independent case. In the speaker-dependent case, this network shows an equivalent recognition performance to Jordan and Elman network but in the speaker-independent case, it does improved performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3201-3223
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• 2020

Wireless communication has become the promising technology in the recent times because of its applications in Internet of Things( IoT) devices. The IEEE 802.15.4e has become the key technology for IoT devices which utilizes the Time-Slotted Channel Hopping (TSCH) networks for the communication between the devices. In this paper, we develop a Two Level Scheduling Algorithm (TLSA) for scheduling multiple packets with different arrival rate at the source nodes in a TSCH networks based on the link activated by a centralized scheduler. TLSA is developed by considering three types of links in a network such as link i with packets arrival type 1, link j with packets arrival type 2, link k with packets arrival type 3. For the data packets arrival, two stages in a network is considered.At the first stage, the packets are considered to be of higher priority.At the second stage, the packets are considered to be of lower priority.We introduce level 1 schedule for the packets at stage 1 and level 2 schedule for the packets at stage 2 respectively. Finally, the TLSA is validated with the two different energy functions i.e., y = e^ax - 1 and y = 0.5x² using MATLAB 2017a software for the computation of average and worst ratios of the two levels.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.10
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• pp.86-94
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• 1993

This paper presents the two-stage neural network method for efficient channel assignment of cellular mobile radio network. The first stage decomposes the region into non-adjacent groups of cells and the second stage assigns channels to the decomposed groups. The neural network model is tested with an experimental system of eighteen channels dedicated for nineteen hexagonal-cell region. When radom call requests of average density of 2 Erl/Cell to 8 Erl/Cell are presented, the real-time channel assignment method reduces the call-blocking rate up to 16% against the existing SCA(Static Channel Assignment) method.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.91-94
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• 2023

This study aims to evaluate the Higher Diploma in English for the Primary Stage from the diploma students' perspectives. A questionnaire was designed consisting of 25 items distributed in two areas: cognitive/academic preparation and professional/skill preparation. The following statistical analyses were used: means, standard deviations, t-test, and one-way analysis of variance (ANOVA). The study results showed that the level of evaluation of the two domains in the program was low. The study also showed no statistically significant differences between the means of educational diploma students when evaluating the Higher Diploma in English for the Primary Stage due to their academic specialization (Arabic language, social sciences, and Islamic studies). In conclusion, the researcher suggested a developmental mechanism derived from the study results to improve the higher Diploma in English for the Primary Stage.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.4
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• pp.87-97
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• 2009

Internet network routing system is used to prevent spread and distribution of malicious data traffic. This study is based on analysis of diagnostic weakness structure in the network security domain. We propose an improved integrated multi-level protection domain for in the internal route of groupware. This paper's protection domain is designed to handle the malicious data traffic in the groupware and finally leads to lighten the load of data traffic and improve network security in the groupware. Infrastructure of protection domain is transformed into five-stage blocking domain from two or three-stage blocking. Filtering and protections are executed for the entire server at the gateway level and internet traffic route ensures differentiated protection by dividing into five-stage. Five-stage multi-level network security domain's malicious data traffic protection performance is better than former one. In this paper, we use a trust evaluation metric for measuring the security domain's performance and suggested algorithm.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.3
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• pp.339-345
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• 2016

This paper presents a two-stage power amplifier MMIC using a $0.4{\mu}m$ GaN-HEMT process. The two-stage structure provides high gain and compact circuit size using an integrated inter-stage matching network. The size and loss of the inter-stage matching network can be reduced by including bond wires as part of the matching network. The two-stage power amplifier MMIC was fabricated with a chip size of $2.0{\times}1.9mm^2$ and was mounted on a $4{\times}4$ QFN carrier for evaluation. Using a downlink LTE signal with a PAPR of 6.5 dB and a channel bandwidth of 10 MHz for the 2.6 GHz band, the power amplifier MMIC exhibited a gain of 30 dB, a drain efficiency of 32%, and an ACLR of -31.4 dBc at an average output power of 36 dBm. Using two power amplifier MMICs for the carrier and peaking amplifiers, a Doherty power amplifier was designed and implemented. At a 6 dB back-off output power level of 39 dBm, a gain of 24.7 dB and a drain efficiency of 43.5% were achieved.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.10a
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• pp.175-184
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• 1993

Modeling the production process is a necessary and essential aspect of the production planning. This paper introduces a theoretical model of the multi-stage production process. A multi-stage production process is regarded as a network of interrelated production activities which use system exogenous inputs of goods in production and the intermediate products transfers between activities to produce final products. Our model is characterized by (1) a few of the production-related assumptions and (2) two types of elements "goods and activities" that are represented in terms of the network terminology. This model is different from the another multi-stage production models, so-called production network models in relation to the production-theoretical concept. It is not based on the concept of the production correspondence and the activity production functions, but the technology model of Koopmans. Koopmans.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3393-3412
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• 2017

As a main challenge in network virtualization, virtual network embedding problem is increasingly important and heuristic algorithms are of great interest. Aiming at the problems of poor correlation in node embedding and link embedding, long distance between adjacent virtual nodes and imbalance resource consumption of network components during embedding, we herein propose a two-stage virtual network embedding algorithm NA-PVNM. In node embedding stage, resource requirement and breadth first search algorithm are introduced to sort virtual nodes, and a node fitness function is developed to find the best substrate node. In link embedding stage, a path fitness function is developed to find the best path in which available bandwidth, CPU and path length are considered. Simulation results showed that the proposed algorithm could shorten link embedding distance, increase the acceptance ratio and revenue to cost ratio compared to previously reported algorithms. We also analyzed the impact of position constraint and substrate network attribute on algorithm performance, as well as the utilization of the substrate network resources during embedding via simulation. The results showed that, under the constraint of substrate resource distribution and virtual network requests, the critical factor of improving success ratio is to reduce resource consumption during embedding.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.12
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• pp.643-650
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• 2000

Using neural network approach, the diagnosis of faults in industrial process that requires observing multiple data simultaneously are studied. Two-stage diagnosis is proposed to analyze system faults. By using neural network, the first stage detects the dynamic trend of each normalized date patterns by comparing a proposed pattern. Instead of using neural network, the difference between stored fault pattern and real time data is used for fault diagnosis in the second stage. This method reduces the amount of calculation and saves storing space. Also, we dealt with unknown faults by normalizing the data and calculating the difference between the value of steady state and the data in case of fault. A model of tank reactor is given to verify that the proposed method is useful and effective to noise.