• Computers and Concrete
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• v.33 no.1
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• pp.55-75
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• 2024

The present study introduces an optimum performance soft computing model for predicting the compressive strength of high-performance concrete (HPC) by comparing models based on conventional (kernel-based, covariance function-based, and tree-based), advanced machine (least square support vector machine-LSSVM and minimax probability machine regressor-MPMR), and deep (artificial neural network-ANN) learning approaches using a common database for the first time. A compressive strength database, having results of 1030 concrete samples, has been compiled from the literature and preprocessed. For the purpose of training, testing, and validation of soft computing models, 803, 101, and 101 data points have been selected arbitrarily from preprocessed data points, i.e., 1005. Thirteen performance metrics, including three new metrics, i.e., a20-index, index of agreement, and index of scatter, have been implemented for each model. The performance comparison reveals that the SVM (kernel-based), ET (tree-based), MPMR (advanced), and ANN (deep) models have achieved higher performance in predicting the compressive strength of HPC. From the overall analysis of performance, accuracy, Taylor plot, accuracy metric, regression error characteristics curve, Anderson-Darling, Wilcoxon, Uncertainty, and reliability, it has been observed that model CS4 based on the ensemble tree has been recognized as an optimum performance model with higher performance, i.e., a correlation coefficient of 0.9352, root mean square error of 5.76 MPa, and mean absolute error of 4.1069 MPa. The present study also reveals that multicollinearity affects the prediction accuracy of Gaussian process regression, decision tree, multilinear regression, and adaptive boosting regressor models, novel research in compressive strength prediction of HPC. The cosine sensitivity analysis reveals that the prediction of compressive strength of HPC is highly affected by cement content, fine aggregate, coarse aggregate, and water content.

• IMMUNE NETWORK
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• v.23 no.6
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• pp.47.1-47.16
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• 2023

Scrub typhus, a mite-borne infectious disease, is caused by Orientia tsutsugamushi. Despite many attempts to develop a protective strategy, an effective preventive vaccine has not been developed. The identification of appropriate Ags that cover diverse antigenic strains and provide long-lasting immunity is a fundamental challenge in the development of a scrub typhus vaccine. We investigated whether this limitation could be overcome by harnessing the nanoparticle-forming polysorbitol transporter (PST) for an O. tsutsugamushi vaccine strategy. Two target proteins, 56-kDa type-specific Ag (TSA56) and surface cell Ag A (ScaA) were used as vaccine candidates. PST formed stable nano-size complexes with TSA56 (TSA56-PST) and ScaA (ScaA-PST); neither exhibited cytotoxicity. The formation of Ag-specific IgG2a, IgG2b, and IgA in mice was enhanced by intranasal vaccination with TSA56-PST or ScaA-PST. The vaccines containing PST induced Ag-specific proliferation of CD8⁺ and CD4⁺ T cells. Furthermore, the vaccines containing PST improved the mouse survival against O. tsutsugamushi infection. Collectively, the present study indicated that PST could enhance both Ag-specific humoral immunity and T cell response, which are essential to effectively confer protective immunity against O. tsutsugamushi infection. These findings suggest that PST has potential for use in an intranasal vaccination strategy.

• IMMUNE NETWORK
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• v.21 no.6
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• pp.42.1-42.20
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• 2021

Eosinophils play critical roles in the maintenance of homeostasis in innate and adaptive immunity. Although primarily known for their roles in parasitic infections and the development of Th2 cell responses, eosinophils also play complex roles in other immune responses ranging from anti-inflammation to defense against viral and bacterial infections. However, the contributions of pattern recognition receptors in general, and NOD-like receptors (NLRs) in particular, to eosinophil involvement in these immune responses remain relatively underappreciated. Our in vivo studies demonstrated that NLRC4 deficient mice had a decreased number of eosinophils and impaired Th2 responses after induction of an allergic airway disease model. Our in vitro data, utilizing human eosinophilic EoL-1 cells, suggested that TLR2 induction markedly induced pro-inflammatory responses and inflammasome forming NLRC4 and NLRP3. Moreover, activation by their specific ligands resulted in caspase-1 cleavage and mature IL-1β secretion. Interestingly, Th2 responses such as secretion of IL-5 and IL-13 decreased after transfection of EoL-1 cells with short interfering RNAs targeting human NLRC4. Specific induction of NLRC4 with PAM3CSK4 and flagellin upregulated the expression of IL-5 receptor and expression of Fc epsilon receptors (FcεR1α, FcεR2). Strikingly, activation of the NLRC4 inflammasome also promoted expression of the costimulatory receptor CD80 as well as expression of immunoregulatory receptors PD-L1 and Siglec-8. Concomitant with NLRC4 upregulation, we found an increase in expression and activation of matrix metalloproteinase (MMP)-9, but not MMP-2. Collectively, our results present new potential roles of NLRC4 in mediating a variety of eosinopilic functions.

• IMMUNE NETWORK
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• v.20 no.1
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• pp.5.1-5.15
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• 2020

The γδ T cells are unconventional lymphocytes that function in both innate and adaptive immune responses against various intracellular and infectious stresses. The γδ T cells can be exploited as cancer-killing effector cells since γδ TCRs recognize MHC-like molecules and growth factor receptors that are upregulated in cancer cells, and γδ T cells can differentiate into cytotoxic effector cells. However, γδ T cells may also promote tumor progression by secreting IL-17 or other cytokines. Therefore, it is essential to understand how the differentiation and homeostasis of γδ T cells are regulated and whether distinct γδ T cell subsets have different functions. Human γδ T cells are classified into Vδ2 and non-Vδ2 γδ T cells. The majority of Vδ2 γδ T cells are Vγ9δ2 T cells that recognize pyrophosphorylated isoprenoids generated by the dysregulated mevalonate pathway. In contrast, Vδ1 T cells expand from initially diverse TCR repertoire in patients with infectious diseases and cancers. The ligands of Vδ1 T cells are diverse and include the growth factor receptors such as endothelial protein C receptor. Both Vδ1 and Vδ2 γδ T cells are implicated to have immunotherapeutic potentials for cancers, but the detailed elucidation of the distinct characteristics of 2 populations will be required to enhance the immunotherapeutic potential of γδ T cells. Here, we summarize recent progress regarding cancer immunology of human γδ T cells, including their development, heterogeneity, and plasticity, the putative mechanisms underlying ligand recognition and activation, and their dual effects on tumor progression in the tumor microenvironment.

• Structural Engineering and Mechanics
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• v.90 no.1
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• pp.19-26
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• 2024

In recent years, an increasing number of experimental studies have shown that the practical application of mature active control systems requires consideration of robustness criteria in the design process, including the reduction of tracking errors, operational resistance to external disturbances, and measurement noise, as well as robustness and stability. Good uncertainty prediction is thus proposed to solve problems caused by poor parameter selection and to remove the effects of dynamic coupling between degrees of freedom (DOF) in nonlinear systems. To overcome the stability problem, this study develops an advanced adaptive predictive fuzzy controller, which not only solves the programming problem of determining system stability but also uses the law of linear matrix inequality (LMI) to modify the fuzzy problem. The following parameters are used to manipulate the fuzzy controller of the robotic system to improve its control performance. The simulations for system uncertainty in the controller design emphasized the use of acceleration feedback for practical reasons. The simulation results also show that the proposed H∞ controller has excellent performance and reliability, and the effectiveness of the LMI-based method is also recognized. Therefore, this dynamic control method is suitable for seismic protection of civil buildings. The objectives of this document are access to adequate, safe, and affordable housing and basic services, promotion of inclusive and sustainable urbanization, implementation of sustainable disaster-resilient construction, sustainable planning, and sustainable management of human settlements. Simulation results of linear and non-linear structures demonstrate the ability of this method to identify structures and their changes due to damage. Therefore, with the continuous development of artificial intelligence and fuzzy theory, it seems that this goal will be achieved in the near future.

• Journal of Korea Water Resources Association
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• v.33 no.2
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• pp.247-262
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• 2000

In this paper, the WSANN(Water Stage Analysis with Neural Network) model was presented so as to predict flood water stage at Jindong which has been the major stream gauging station in Nakdong river basin. The WSANN model used the improved backpropagation training algorithm which was complemented by the momentum method, improvement of initial condition and adaptive-learning rate and the data which were used for this study were classified into training and testing data sets. An empirical equation was derived to determine optimal hidden layer node between the hidden layer node and threshold iteration number. And, the calibration of the WSANN model was performed by the four training data sets. As a result of calibration, the WSANN22 and WSANN32 model were selected for the optimal models which would be used for model verification. The model verification was carried out so as to evaluate model fitness with the two-untrained testing data sets. And, flood water stages were reasonably predicted through the results of statistical analysis. As results of this study, further research activities are needed for the construction of a real-time warning of the impending flood and for the control of flood water stage with neural network method in river basin. basin.

• The KIPS Transactions:PartC
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• v.11C no.2
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• pp.263-268
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• 2004

The end-to-end characteristic Is an important factor for QoS support. Since network users and required bandwidths for applications increase, the efficient usage of networks has been intensively investigated for the better utilization of network resources. The distributed adaptive routing is the typical routing algorithm that is used in the current Internet. The DCLC(Delay Constrained 1.east Cost) path problem has been shown to be NP-hard problem. The path cost of LD path is relatively more expensive than that of LC path, and the path delay of LC path is relatively higher than that of LD path in DCLC problem. In this paper, we investigate the performance of heuristic algorithm for the DCLC problem with new factor which is probabilistic combination of cost and delay. Recently Dr. Salama proposed a polynomial time algorithm called DCUR. The algorithm always computes a path, where the cost of the path is always within 10% from the optimal CBF. Our evaluation showed that heuristic we propose is more than 38% better than DCUR with cost when number of nodes is more than 200. The new factor takes in account both cost and delay at the same time.

• The KIPS Transactions:PartC
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• v.17C no.6
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• pp.471-484
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• 2010

In the wireless communication systems, the power consumption of a mobile device is very important issue due to its battery limitations. Hence most of the standards for wireless networks including a mobile WiMAX system are supporting their own power saving mode in way that a mobile device is able to reduce its energy usage while in the mode. However, those standards just define the arrangement of special time intervals, called a paging listening interval, during which the device needs to receive the paging-related control messages, and they do not specify how to effectively reduce the power in many different network environments. This means the amount of power spent by the device is very dependent on the implementations of individual device-vendors, and undesirable paging loss may happen according to the channel conditions. To reduce unnecessary power usage and the risk of paging loss, this paper proposes the effective frequency/BS selection algorithm applicable to a mobile device operating in the power saving mode, which serves the device with better BS based on the tracking for channel variation. This algorithm consists of the channel estimation phase during each paging listening interval, the tracking phase for the measured results, the frequency reselection phase based on the tracking activity, and the preferred BS reselection phase. Thus the proposed method can improve the paging performance while the device is moving in the network. Also the simulation result shows that the presented scheme is superior to other candidates in energy efficiency due to the channel-adaptive frequency/BS selection.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.8
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• pp.984-998
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• 1999

최근 개인 휴대 통신에 대한 관심도가 증가하면서 B-ISDN (Broadband Integrated Services Digital Network)과 같은 기존의 유선 망에서 제공하던 다양한 멀티미디어 응용 지원을 무선 망으로 확장시키기 위한 연구가 활발히 진행되고 있다. 그러나 기존의 유선 망에서는 멀티미디어 응용 지원을 위해 QoS (Quality of Service) Provisioning에 관한 많은 연구가 되어 있으나 무선 망에서는 이동성과 무선 전파의 열악한 전송으로 인해 새로운 QoS Provisioning 방법에 관한 연구가 필수적이다. 본 논문에서는 이러한 무선 망의 특수성으로 인해 발생할 수 있는 서비스의 질 저하와 강제 종료를 줄임으로써 지속적인 QoS를 보장해 주고 한정된 무선 자원을 효율적으로 사용하며 처리에 의한 오버헤드를 줄이기 위하여 다음과 같은 세 가지 방법을 제안하였다. 첫째, 핸드오프 강제 종료율을 줄이기 위하여 대역폭 예약 방법을 사용하되 특정 셀의 트래픽 특성에 맞게 또한 시간대에 따른 트래픽 특성에 따라 예약 대역폭의 양을 조절하는 적응적 대역폭 예약 방법이다. 둘째, 많은 경우 각 셀의 트랙픽 변화는 일정한 주기로 변화한다는 특성에 따라 과거의 트래픽 정보를 이용하는 예측 기반의 대역폭 예약 방법이다. 마지막으로 호의 종류, 트래픽 특성, 단말기의 이동 속도에 따라 다른 우선 순위에 의해 호 수락 제어를 수행하는 우선 순위 기반의 호 수락 제어를 제안하였다. 시뮬레이션을 통하여 기존에 제안된 방법과 성능 비교하여, 요구되는 수준의 QoS 보장과 효율적인 자원의 사용, 요구되는 처리비용의 최소화를 통해 전체 시스템의 성능 향상을 입증하였다.Abstract As interest in wireless hand-held terminals and in personal communications services increases recently, there have been broad studies on the ways to support multimedia applications provided in wired networks such as B-ISDN (Broadband Integrated Services Digital Network) in wireless networks. However, since many studies have focused on Quality of Service (QoS) Provisioning in wired networks to provide multimedia applications, new methods of QoS Provisioning are needed in wireless networks to resolve the problem of wireless channel fading and the difficulty of mobility occurred in wireless networks. This paper proposes three schemes of QoS Provisioning in wireless networks which will make continuous QoS guarantee and efficient use of limited wireless resources possible. The first scheme reserves bandwidth in proportion to the amount of real-time traffic in the neighbor cells to decrease the handoff dropping rate of delay sensitive real-time connections, adapting reserved bandwidth for efficient resource utilization. The second scheme is predictive bandwidth reservation scheme that utilizes the past handoff information. It can decrease overheads required to adapt bandwidth reservation. The last scheme is priority-based call admission control prioritizing traffic type (real-time traffic/ non-real-time traffic), connection type (new connection /handoff connection), and mobile terminal speed (fast mobile/slow mobile). Simulation results show that the proposed QoS Provisioning schemes improve the total system performance by achieving three goals - required QoS guarantee, higher bandwidth utilization and less overhead.

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.83-97
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• 2000

The traffic management schemes through traffic signal control and information provision could be effective when the link-level data and trip-level data were used simultaneously in analysis Procedures. But, because the trip-level data. such as origin, destination and departure time, can not be obtained through the existing surveillance systems directly. It is needed to estimate it using the link-level data which can be obtained easily. Therefore the objective of this study is to develop the model to estimate O-D demand using only the link flows in highway network as a real time. The methodological approaches in this study are kalman filer, least-square method and normalized least-square method. The kalman filter is developed in the basis of the bayesian update. The normalized least-square method is developed in the basis of the least-square method and the natural constraint equation. These three models were experimented using two kinds of simulated data. The one has two abrupt changing Patterns in traffic flow rates The other is a 24 hours data that has three Peak times in a day Among these models, kalman filer has Produced more accurate and adaptive results than others. Therefore it is seemed that this model could be used in traffic demand management. control, travel time forecasting and dynamic assignment, and so forth.