• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1939_1941
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• 2009

The modulation quality of the RF transmitter in a wireless communication system usually affects system performance and it mostly depends on both a nonlinearity and a distortion, from the intermodulation products and the I/Q mismatch such as I/Q amplitude error and a local phase error, respectively. This paper focused on how much the error vector magnitude(EVM) which describes the modulation accuracy changes according to the variation of the I/Q mismatch components at I/Q modulator. For this work, the equation for the EVM including the I/Q mismatch components can be induced and calculated in accordance with the variation of the I/Q mismatch components. Consequently, the effect of I/Q mismatch components on the EVM, which is required in the transmitter specification of Personal Area Network, can be clearly analyzed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1940-1946
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• 2015

An optical coherent system is considered for the next-generation optical access networks in enhancing the data rate and transmission distance. In this system, however, I/Q amplitude imbalance may occur at several parts of the system, leading to serious performance degradation. Asymmetric structure of a coherent receiver at the location of subscriber is one of the sources of I/Q imbalance. Therefore, this imbalance parameters must be removed or compensated to secure the transmission performance. In this paper, the source of I/Q amplitude imbalance is analyzed, and then the way to compensate for the imbalance at the receiver side is suggested. Performance after the compensation is estimated using simulation.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.3
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• pp.170-175
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• 2001

Q-learning is a kind of reinforcement learning where the agent solves the given task based on rewards received from the environment. Most research done in the field of Q-learning has focused on discrete domains, although the environment with which the agent must interact is generally continuous. Thus we need to devise some methods that enable Q-learning to be applicable to the continuous problem domain. In this paper, an extended fuzzy rule is proposed so that it can incorporate Q-learning. The interpolation technique, which is widely used in memory-based learning, is adopted to represent the appropriate Q value for current state and action pair in each extended fuzzy rule. The resulting structure based on the fuzzy inference system has the capability of solving the continuous state about the environment. The effectiveness of the proposed structure is shown through simulation on the cart-pole system.

• Smart Media Journal
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• v.4 no.3
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• pp.9-15
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• 2015

A pub(lish)/sub(scribe) system is a data forwarding system which forwards only interesting data among the whole published data, which is related to the subscriptions registered by end users. Classical pub/sub systems are realized by constructing a network of brokers which are responsible for storing or forwarding data. Along with the substantial increase of the population mobile users, it is required that the pub/sub system handles the subscriptions of user locations which changes continuously and frequently. In this paper, a new broker network based pub/sub system which efficiently handles the frequent changes of subscriptions related to user locations is proposed. In consideration of moving patterns of users and geographical property, the proposed pub/sub system categorize the entire data space into Slow Moving Region and Normal Moving Region, and manages the brokers which are responsible for these regions by using Q+R tree in order to handle user requests more efficiently. Through the extensive simulation, it is presented that the proposed Q+R tree based pub/sub system can reduce unnecessary needs of brokers and network traffic and can support the dynamic subscription related to user location.

• Journal of Internet Computing and Services
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• v.2 no.4
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• pp.83-90
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• 2001

Q+-reader, an E-Book reader system for XML based contents is introduced, The system is developed for the embedded platform, called Q+, which targets for the digital home electronics systems, The system supports XML contents and CSS based styling as described in Open e-book standard. The system renders the e-book contents for users, sc the contents are secured for a proper use. This will found an essential part of business infra for electronic books with copyright protection, The system was developed in Java language to be used in various platform;, and has an open architecture to be reusable for other standards as well.

• Geomechanics and Engineering
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• v.30 no.5
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• pp.449-460
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• 2022

Safe underground construction in a rock mass requires adequate ground investigation and effective determination of rock conditions. The estimation of rock mass behavior is difficult, because rock masses are innately anisotropic and heterogeneous at different scales and are affected by various environmental factors. Quantitative rock mass classification systems, such as the Q-system and rock mass rating, are widely used for characterization and engineering design. The measurement of rock classification parameters is subjective and can vary among observers, resulting in questionable accuracy. Geophysical investigation methods, such as seismic surveys, have also been used for ground characterization. Torsional shear wave propagation characteristics in cylindrical rods are equal to that in an infinite media. A probabilistic quantitative relationship between the Q-value and shear wave velocity is thus investigated considering long-wavelength wave propagation in equivalent continuum jointed rock masses. Individual Q-system parameters are correlated with stress-dependent shear wave velocities in jointed rocks using experimental and numerical methods. The relationship between the Q-value and the shear wave velocity is normalized using a defined reference condition. This relationship is further improved using probabilistic analysis to remove unrealistic data and to suggest a range of Q-values for a given wave velocity. The proposed probabilistic Q-value estimation is then compared with field measurements and cross-hole seismic test data to verify its applicability.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.165-172
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• 2011

In this paper, we propose Ant-Q learning Algorithm[1], which uses the habits of biological ants, to find a new way to solve Stable Marriage Problem(SMP)[3] presented by Gale-Shapley[2]. The issue of SMP is to find optimum matching for a stable marriage based on their preference lists (PL). The problem of Gale-Shapley algorithm is to get a stable matching for only male (or female). We propose other way to satisfy various requirements for SMP. ACS(Ant colony system) is an swarm intelligence method to find optimal solution by using phermone of ants. We try to improve ACS technique by adding Q learning[9] concept. This Ant-Q method can solve SMP problem for various requirements. The experiment results shows the proposed method is good for the problem.

• The Journal of the Korea Contents Association
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• v.14 no.8
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• pp.172-184
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• 2014

The purpose of this study is to find out subjective perception types and needs of interested group on manpower training system with long-term care service by Q methodology, then to search for political measures to improve long-term care system in the implication of the sorted subjective perception types. The result of the study showed that there are five major sorts of subjectivities on manpower training system with long-term care service: emphasizes retraining of existing care worker(Type1), emphasizes ethics of public service provider(Type2), emphasizes practice-oriented education(Type3), emphasizes policy judgement of government(Type4), emphasizes training of long-term care worker in demand(Type5). And to try quantity approach methods, this study was developed Q-Block as a assessment tool to enhance validity and reliability of Q-types. The results of the survey showed high conformity.

• Progress in Superconductivity and Cryogenics
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• v.18 no.4
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• pp.40-43
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• 2016

Beam trajectory is needed to be controlled in heavy ion accelerator system. Quadruple magnets are widely used in heavy ion accelerator for focusing the transporting particles. A quadruple triplet system which consists of three consecutive quadrupoles, Q1, Q2 and Q3, is used to control beam trajectory at a focused position. Q1 and Q3 have symmetry with respect to Q2. The beam trajectory in magnet system is affected by higher order fields existed in real fields. For quadrupoles, the representation simulation of beam trajectory was carried out to study the beam trajectory and to estimate an effect of higher order field in triplet system. SCALA program was used to simulate the beam trajectory in $Opera^{TM}$. SCALA can analyze a large number of beam trajectories at the same time by adjusting the size of finite element of the emitter. With $Opera^{TM}$ and $Matlab^{TM}$ programs, the position of focused beam spot in quadruple triplet system can be increased or decreased using evolution strategy (ES) method, therefore the length of triplet system can be controlled. Finally, the quadruple triplet system with the appropriate length and expected beam spot range was suggested in this paper.

• The Journal of Information Systems
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• v.29 no.2
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• pp.131-147
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• 2020

Purpose The purpose of this study is to develop intelligent vehicle parking distribution system based on LoRa network at the circumstance of traffic congestion during cultural festival in a local city. This paper proposes a parking dispatch and distribution system using a Q-learning algorithm to rapidly disperse traffics that increases suddenly because of in-bound traffics from the outside of a city in the real-time base as well as to increase parking probability in a parking lot which is widely located in a city. Design/methodology/approach The system get information on realtime-base from the sensor network of IoT (LoRa network). It will contribute to solve the sudden increase in traffic and parking bottlenecks during local cultural festival. We applied the simulation system with Queuing model to the Yudeung Festival in Jinju, Korea. We proposed a Q-learning algorithm that could change the learning policy by setting the acceptability value of each parking lot as a threshold from the Jinju highway IC (Interchange) to the 7 parking lots. LoRa Network platform supports to browse parking resource information to each vehicle in realtime. The system updates Q-table periodically using Q-learning algorithm as soon as get information from parking lots. The Queuing Theory with Poisson arrival distribution is used to get probability distribution function. The Dijkstra algorithm is used to find the shortest distance. Findings This paper suggest a simulation test to verify the efficiency of Q-learning algorithm at the circumstance of high traffic jam in a city during local festival. As a result of the simulation, the proposed algorithm performed well even when each parking lot was somewhat saturated. When an intelligent learning system such as an O-learning algorithm is applied, it is possible to more effectively distribute the vehicle to a lot with a high parking probability when the vehicle inflow from the outside rapidly increases at a specific time, such as a local city cultural festival.