• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3887-3907
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• 2015

This paper introduces a full duplex single secondary user multiple-input multiple-output (FD-SSU-MIMO) cognitive radio network, where secondary user (SU) opportunistically accesses the authorized spectrum unoccupied by primary user (PU) and transmits data based on FD-MIMO mode. Then we study the network achievable average sum-rate maximization problem under sum transmit power budget constraint at SU communication nodes. In order to solve the trade-off problem between SU's sensing time and data transmission time based on opportunistic spectrum access (OSA) and the power allocation problem based on FD-MIMO transmit mode, we propose a simple trisection algorithm to obtain the optimal sensing time and apply an alternating optimization (AO) algorithm to tackle the FD-MIMO based network achievable sum-rate maximization problem. Simulation results show that our proposed sensing time optimization and AO-based optimal power allocation strategies obtain a higher achievable average sum-rate than sequential convex approximations for matrix-variable programming (SCAMP)-based power allocation for the FD transmission mode, as well as equal power allocation for the half duplex (HD) transmission mode.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2063-2081
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• 2018

A resource allocation algorithm is proposed in this paper to simultaneously minimize the total system power consumption and maximize the system throughput for the downlink of multi-user multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems. With the Lagrange dual decomposition method, we transform the original problem to its convex dual problem and prove that the duality gap between the two problems is zero, which means the optimal solution of the original problem can be obtained by solving its dual problem. Then, we use convex optimization method to solve the dual problem and utilize bisection method to obtain the optimal dual variable. The numerical results show that the proposed algorithm is superior to traditional single-objective optimization method in both the system throughput and the system energy consumption.

• Advances in concrete construction
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• v.3 no.3
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• pp.237-250
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• 2015

Beam-column joints are highly vulnerable locations which are to be designed for high ductility in order to take care of unexpected lateral forces such as wind and earthquake. Previous investigations reveal that the addition of steel fibres to concrete improves its ductility significantly. Also, due to presence of slab the strength and ductility of the beam increases considerably and ignoring the effect of slab can lead to underestimation of beam capacity and defiance of strong column weak beam concept. The influence of addition of steel fibres on the strength and behaviour of steel fibre reinforced high performance concrete (SFRHPC) interior beam-column-slab joints was investigated experimentally. The specimens were subjected to reverse cyclic loading. The variable considered was the volume fraction of crimped steel fibres i.e., 0%, 0.5% and 1.0%. The results show that the addition of steel fibres improves the first crack load, strength, ductility, energy absorption capacity and initial stiffness of the beam.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2400-2413
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• 2019

Doubly-selective (DS) fading channel is often occurred in many orthogonal frequency division multiplexing (OFDM) communication systems, such as high-speed rail communication systems and underwater acoustic (UWA) wireless networks. It is challenging to provide an accurate and fast estimation over the doubly-selective channel, due to the strong Doppler shift. This paper addresses the doubly selective channel estimation problem based on complex exponential basis expansion model (CE-BEM) in OFDM systems from the perspective of distributed compressive sensing (DCS). We propose a novel DCS-based improved sparsity adaptive matching pursuit (DCS-IMSAMP) algorithm. The advantage of the proposed algorithm is that it can exploit the joint channel sparsity information using dynamic threshold, variable step size and tailoring mechanism. Simulation results show that the proposed algorithm achieves 5dB performance gain with faster operation speed, in comparison with traditional DCS-based sparsity adaptive matching pursuit (DCS-SAMP) algorithm.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.1009-1016
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• 2021

Productive human resources are important assets for companies in facing the global economic competition. The purpose of this study is to examine the effect of economic attitudes toward employees' job satisfaction as well as understanding the impact of economic attitudes toward employee productive behavior at "Sentra Tenun Ikat" in East Java. The research method applied in this study is quantitative research with an explanatory design, which is intended to gain a better understanding of the relationship between variables. The population in this study amounted to 394 participants from SMEs and joint business groups. Meanwhile, the sample was 197 people and collected using a proportional random sampling technique. The variable measurement was carried out by a questionnaire distributed to respondents, which consisted of thirty-five closed questions. Each question item provides five alternative answers. Furthermore, it is calculated using Structural Equation Modeling (SEM) undergoing the LISREL 8.80 program. The findings indicated that there was a positive influence of economic attitudes on employees' job satisfaction. Indeed, the positive value coefficient indicates that there is an effect that is directly proportional to economic attitudes toward employees' productive behavior through employee performance satisfaction, namely, the better the economic attitude taken, the higher the productive behavior of employees.

• Earthquakes and Structures
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• v.19 no.6
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• pp.411-425
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• 2020

Unreinforced masonry (URM) walls present low shear strength and are prone to brittle failure when subjected to inplane seismic overloads. This paper discusses the shear strengthening of URM walls with Textile Reinforced Mortar (TRM) jackets. The available literature is thoroughly reviewed and an extended database is developed including available brick, concrete and stone URM walls retrofitted and subjected to shear tests to assess their strength. Further, the experimental results of the database are compared against the available shear strength design models from ACI 549.4R-13, CNR DT 215 2018, CNR DT 200 R1/2013, Eurocode 6 and Eurocode 8 guidelines as well as Triantafillou and Antonopoulos 2000, Triantafillou 1998, Triantafillou 2016. The performance of the available models is investigated and the prediction average absolute error (AAE) is as high as 40%. A new model is proposed that takes into account the additional contribution of the reinforcing mortar layer of the TRM jacket that is usually neglected. Further, the approach identifies the plethora of different block materials, joint mortars and TRM mortars and grids and introduces rational calibration of their variable contributions on the shear strength. The proposed model provides more accurate shear strength predictions than the existing models for all different types of the URM substrates, with a low AAE equal to 22.95%.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1343-1358
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• 2020

In the stagewise arithmetic orthogonal matching pursuit algorithm, the weak threshold used in sparsity estimation is determined via maximum iterations. Different maximum iterations correspond to different thresholds and affect the performance of the algorithm. To solve this problem, we propose an improved variable weak threshold based on the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the residual error value to control the weak threshold. When the residual value decreases, the threshold value continuously increases, so that the atoms contained in the atomic set are closer to the real sparsity value, making it possible to improve the reconstruction accuracy. In addition, we improved the generalized Jaccard coefficient in order to replace the inner product method that is used in the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the covariance to replace the joint expectation for two variables based on the generalized Jaccard coefficient. The improved generalized Jaccard coefficient can be used to generate a more accurate calculation of the correlation between the measurement matrixes. In addition, the residual is more accurate, which can reduce the possibility of selecting the wrong atoms. We demonstrate using simulations that the proposed algorithm produces a better reconstruction result in the reconstruction of a one-dimensional signal and two-dimensional image signal.

• Journal of Yeungnam Medical Science
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• v.39 no.3
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• pp.181-189
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• 2022

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive neurodegenerative condition characterized by loss of motor neurons, resulting in motor weakness of the limbs and/or bulbar muscles. Pain is a prevalent but neglected symptom of ALS, and it has a significant negative impact on the quality of life of patients and their caregivers. This review outlines the epidemiology, clinical characteristics, underlying mechanisms, and management strategies of pain in ALS to improve clinical practice and patient outcomes related to pain. Pain is a prevalent symptom among patients with ALS, with a variable reported prevalence. It may occur at any stage of the disease and can involve any part of the body without a specific pattern. Primary pain includes neuropathic pain and pain from spasticity or cramps, while secondary pain is mainly nociceptive, occurring with the progression of muscle weakness and atrophy, prolonged immobility causing degenerative changes in joints and connective tissue, and long-term home mechanical ventilation. Prior to treatment, the exact patterns and causes of pain must first be identified, and the treatment should be tailored to each patient. Treatment options can be classified into pharmacological treatments, including nonsteroidal anti-inflammatory drugs, antiepileptic drugs, drugs for cramps or spasticity, and opioid; and nonpharmacological treatments, including positioning, splints, joint injections, and physical therapy. The development of standardized and specific assessment tools for pain-specific to ALS is required, as are further studies on treatments to reduce pain, diminish suffering, and improve the quality of life of patients with ALS.

• Genomics & Informatics
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• v.20 no.4
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• pp.48.1-48.7
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• 2022

Penalized regression has been widely used in genome-wide association studies for joint analyses to find genetic associations. Among penalized regression models, the least absolute shrinkage and selection operator (Lasso) method effectively removes some coefficients from the model by shrinking them to zero. To handle group structures, such as genes and pathways, several modified Lasso penalties have been proposed, including group Lasso and sparse group Lasso. Group Lasso ensures sparsity at the level of pre-defined groups, eliminating unimportant groups. Sparse group Lasso performs group selection as in group Lasso, but also performs individual selection as in Lasso. While these sparse methods are useful in high-dimensional genetic studies, interpreting the results with many groups and coefficients is not straightforward. Lasso's results are often expressed as trace plots of regression coefficients. However, few studies have explored the systematic visualization of group information. In this study, we propose a multi-level polar Lasso (MP-Lasso) chart, which can effectively represent the results from group Lasso and sparse group Lasso analyses. An R package to draw MP-Lasso charts was developed. Through a real-world genetic data application, we demonstrated that our MP-Lasso chart package effectively visualizes the results of Lasso, group Lasso, and sparse group Lasso.

• Korean Security Journal
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• no.31
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• pp.187-207
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• 2012

The purpose of this study was to analyze the punching movement at the horseback riding stance, one of the basic movements in Taekwondo, with 3D images and further the kinetic variables such as time, velocity, angle, angular velocity, and angular acceleration according to the types. It also aimed to examine the characteristics of each type and suggest instructional methods for the right punching movement. For those purposes, three members from the College Taekwondo Poomse Demonstration Squad were put to the test. The research findings led to the following conclusions: 1. Performance Time of the Punching Movement : In Section 1, Type 1 and 2 recorded $0.24{\pm}0.07s$ and $0.42{\pm}0.08s$, respectively, for the punching movement at the horseback riding stance. While Type 1 took less performance time in the punching movement, Type 2 took less time for take back according to each section's percentage in the total performance time. 2. Variables of Linear Velocity and Linear Acceleration : Each type recorded different linear velocity for each aspect, but the highest linear velocity represented the moment of impact for each type. Type 2 recorded the highest linear velocity in Aspect 4, which was the moment of impact. 3. Variable of Joint Angle : There were no big outer differences in the joint angle during the punching movement between Type 1 in the aspect of impact and Type 2, but the individuals assumed dynamic positions in the punching movement of Type 2 with more diverse changes to the joint angle. 4. Variables of Angular Velocity and Angular Acceleration During the punching movement of Type 1, the Aspect 3 in the moment of impact recorded angular velocity of $0.79{\pm}0.02deg/s$, $0.91{\pm}0.04deg/s$, and $5.24{\pm}0.09deg/s$ at the pelvis, shoulder, and wrist respectively. During the punching movement of Type 2, the Aspect 3 in the moment of impact recorded angular velocity of $1.32{\pm}0.03deg/s$, $0.21{\pm}0.03deg/s$, and $4.98{\pm}0.08deg/$ at the shoulder, wrist, and pelvis, respectively. In the Aspect 3 in the moment of impact in Type 2, the angular acceleration at the right wrist joint was $176.24{\pm}1.11deg/s^2$, which was bigger than that in the moment of impact in Type 1.