• Steel and Composite Structures
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• v.6 no.5
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• pp.435-457
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• 2006

The paper presents the cost optimization of composite floor trusses composed from a reinforced concrete slab of constant depth and steel trusses consisting of hot rolled channel sections. The optimization was performed by the nonlinear programming approach, NLP. Accordingly, a NLP optimization model for composite floor trusses was developed. An accurate objective function of the manufacturing material, power and labour costs was proposed to be defined for the optimization. Alongside the costs, the objective function also considers the fabrication times, and the electrical power and material consumption. Composite trusses were optimized according to Eurocode 4 for the conditions of both the ultimate and the serviceability limit states. A numerical example of the optimization of the composite truss system presented at the end of the paper demonstrates the applicability of the proposed approach.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.29-34
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• 2014

We introduce a number of antenna optimization problem for the zero-forcing beamforming (ZFBF) scheme to enhance energy-efficiency (EE) of the multiple-input-multiple-output broadcast channel. For proposed optimization problem, we assume an instantaneous channel gain of the ZFBF scheme as an average channel gain, given by $N_a-K+1$, in order to reduce a computational complexity of finding the number of active antennas $N_a$. Then, we convert a fractional-form objective function into a subtractive-form, and find a solution of $N_a$ and the maximum EE by an iterative process. Simulation results show that the maximum EE value obtained by proposed algorithm is almost identical to the optimal EE value by the exhaustive search method.

• Journal of Korea Water Resources Association
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• v.35 no.4 s.129
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• pp.345-358
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• 2002

The flow apportioning algorithms with digital elevation models have been developed to reflect reasonable flow divergence properties but they showed several defects related to the connectivity of channel cells, various divergence features along to local topography and channel cells' size etc. Topographic data used by existing flow apportioning algorithms are flow accumulation area and local slope. However, the size and location of channel cells which play the dominant role in the flow pathway were not properly considered. Therefore, a new flow apportioning algorithm considering various flow divergence characteristics in the complicate terrain is proposed. The GA optimization scheme is used to represent the location and scale of the channel pixel. Improved result can be obtained by using both a new flow apportioning algorithm and optimization.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.11
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• pp.1773-1785
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• 1997

The cooling stage is the very critical and most time consuming stage of the injection molding process, thus it cleary affects both the productivity and the part quality. Even through there are several commercialized package programs available in the injection molding industry to analyze the cooling performance of the injection molding coling stage, optimization of the cooling system has npt yet been accomplished in the literature due to the difficulty in the sensitivity analysis. However, it would be greatly desirable for the mold cooling system designers to have a computer aided design system for the cooling stage. With this in mind, the present study has successfully developed an interated computer aided design system for the injection molding cooling system. The CAD system utilizes the sensitivity analysis via a Boundary Element Method, which we recently developed, and the well-known CONMIN alforuthm as an optimization technique to minimize a weighted combination (objective function) of the temperature non-uniformity over the part surface and the cooling time related to the productivity with side constranits for the design reality. In the proposed objective function , the weighting parameter between the temperature non-uniiformity abd the cooling time can be adjusted according to user's interest. In this cooling system optimization, various design variable are considered as follows : (i) (design variables related to processing conditions) inlet coolant bulk temperature and volumetric flow rate of each cooling channel, and (ii) (design variables related to mold cooling system design) radius and location of each cooling channel. For this optimum design problem, three different radius and location of each cooling channel. For this optimum design problem, three different strategies are suffested based upon the nature of design variables. Three sample problems were successfully solved to demonstrated the efficiency and the usefulness of the CAD system.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.300-302
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• 2012

In this paper, we investigate the performance of multi-channel cognitive radio networks (CRNs) by taking into consideration the problem of channel assignment and link scheduling. We assume that secondary nodes are equipped with multiple radios and can switch among multiple channels. How to allocate channels to links and how much power used on each channel to avoid mutual interference among secondary links are the key problem for such CRNs. We formulate the problem of channel assignment and link scheduling as a combinatorial optimization problem. Then, we propose a the optimal solution and show that it converges to maximum optimum in some iterations by using numerical results.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.49-58
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• 2020

Non-orthogonal multiple access (NOMA) has been recognized as a significant technology in the fifth generation (5G) and beyond mobile communication, which encompasses the advanced smart convergence of the artificial intelligence (AI) and the internet of things (IoT). In NOMA, since the channel resources are shared by many users, it is essential to establish the user fairness. Such fairness is achieved by the power allocation among the users, and in turn, the less power is allocated to the stronger channel users. Especially, the first and second strong channel users have to share the extremely small amount of power. In this paper, we consider the power optimization for the two users with the small power. First, the closed-form expression for the power allocation is derived and then the results are validated by the numerical results. Furthermore, with the derived analytical expression, for the various channel environments, the optimal power allocation is investigated and the impact of the channel gain difference on the power allocation is analyzed.

• JSTS:Journal of Semiconductor Technology and Science
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• v.8 no.4
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• pp.302-310
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• 2008

This paper puts forward an advanced consideration on the design of scaled multiple-gate FET (MuGFET); the aspect ratio ($R_{h/w}$) of the fin height (h) to fin width (w) of MuGFET is considered with the aid of 3-D device simulations. Since any change in the aspect ratio must consider the trade-off between drivability and short-channel effects, it is shown that optimization of the aspect ratio is essential in designing MuGFET's. It is clearly seen that the triple-gate (TG) FET is superior to the conventional FinFET from the viewpoints of drivability and short-channel effects as was to be expected. It can be concluded that the guideline of w < L/3, where L is the channel length, is essential to suppress the short-channel effects of TG-FET.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1588-1603
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• 2014

In space diversity combining, conventional methods such as maximal ratio combining (MRC), equal gain combining (EGC) and selection combining (SC) are commonly used to improve the output signal-to-noise ratio (SNR) provided that the channel is perfectly estimated at the receiver. However, in practice, channel estimation is often imperfect and this indeed deteriorates the system performance. In this paper, diversity combining techniques based on two evolutionary algorithms, namely genetic algorithm (GA) and particle swarm optimization (PSO) are proposed and compared. Numerical results indicate that the proposed methods outperform the conventional MRC, EGC and SC methods when the channel estimation is imperfect while it shows similar performance as that of MRC when the channel is perfectly estimated.

• ETRI Journal
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• v.38 no.1
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• pp.30-40
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• 2016

Co-channel interference between macro-femtocell networks is an unresolved problem, due to the frequency reuse phenomenon. To mitigate such interference, a secondary femtocell must acquire channel-state knowledge about a co-channel macrocell user and accordingly condition the maximum transmit power of femtocell user. This paper proposes a pilot-based spectrum sensing (PSS) algorithm for overlaid femtocell networks to sense the presence of a macrocell user over a channel of interest. The PSS algorithm senses the pilot tones in the received signal through the power level and the correlation metric comparisons between the received signal and the local reference pilots. On ensuring the existence of a co-channel macrocell user, the maximum transmit power of the corresponding femtocell user is optimized so as to avoid interference. Time and frequency offsets are carefully handled in our proposal. Simulation results show that the PSS algorithm outperforms existing sensing techniques, even at poor received signal quality. It requires less sensing time and provides better detection probability over existing techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1369-1389
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• 2024

In the era of 6G, the rapid increase in communication data volume poses higher demands on traditional channel estimation techniques and those based on deep learning, especially when processing large-scale data as their computational load and real-time performance often fail to meet practical requirements. To overcome this bottleneck, this paper introduces quantum computing techniques, exploring for the first time the application of Quantum Generative Adversarial Networks (QGAN) to broadband channel estimation challenges. Although generative adversarial technology has been applied to channel estimation, obtaining instantaneous channel information remains a significant challenge. To address the issue of instantaneous channel estimation, this paper proposes an innovative QGAN with a dual-module design in the generator. The adversarial loss function and the Mean Squared Error (MSE) loss function are separately applied for the parameter updates of these two modules, facilitating the learning of statistical channel information and the generation of instantaneous channel details. Experimental results demonstrate the efficiency and accuracy of the proposed dual-module QGAN technique in channel estimation on the Pennylane quantum computing simulation platform. This research opens a new direction for physical layer techniques in wireless communication and offers expanded possibilities for the future development of wireless communication technologies.