• International Journal of Automotive Technology
• /
• v.8 no.5
• /
• pp.575-581
• /
• 2007

As current and future automobile emission regulations become more stringent, the research on flow distribution for an exhaust manifold and close-coupled catalyst(CCC) has become an interesting and remarkable subjects. The design of a CCC and exhaust manifold is a formidable task due to the complexity of the flow distribution caused by the pulsating flows from piston motion and engine combustion. Transient flow at the exhaust manifold can be analyzed with various computational fluid dynamics(CFD) tools. However, the results of such simulations must be verified with appropriate experimental data from real engine operating condition. In this study, an experimental approach was performed to investigate the flow distribution of exhaust gases for conventional cast types and stainless steel bending types of a four-cylinder engine. The pressure distribution of each exhaust sub-component was measured using a simulated dynamic flow bench and five-hole pitot probe. Moreover, using the results of the pitot tube measurement at the exit of the CCC, the flow distribution for two types of manifolds(cast type and bending type) was compared in terms of flow uniformity. Based on these experimental techniques, this study can be highly applicable to the design and optimization of exhaust for the better use of catalytic converters to meet the PZEV emission regulation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.2
• /
• pp.344-358
• /
• 2011

Wireless tactical network (WTN) is the most important present-day technology enabling modern network centric warfare. It inherits many features from WMNs, since the WTN is based on existing wireless mesh networks (WMNs). However, it also has distinctive characteristics, such as hierarchical structures and tight QoS (Quality-of-Service) requirements. Little research has been conducted on hierarchical protocols to support various QoS in WMN. We require new protocols specifically optimized for WTNs. Control packets are generally required to find paths and reserve resources for QoS requirements, so data throughput is not degraded due to overhead. The fundamental solution is to adopt topology aggregation, in which a low tier node aggregates and simplifies the topology information and delivers it to a high tier node. The overhead from control packet exchange can be reduced greatly due to decreased information size. Although topology aggregation is effective for low overhead, it also causes the inaccuracy of topology information; thus, incurring low QoS support capability. Therefore, we need a new topology aggregation algorithm to achieve high accuracy. In this paper, we propose a new aggregation algorithm based on star topology. Noting the hierarchical characteristics in military and hierarchical networks, star topology aggregation can be used effectively. Our algorithm uses a limited number of bypasses to increase the exactness of the star topology aggregation. It adjusts topology parameters whenever it adds a bypass. Consequently, the result is highly accurate and has low computational complexity.

• Advances in concrete construction
• /
• v.11 no.3
• /
• pp.231-238
• /
• 2021

The present work aims at investigating the effects of using various fine mineral additions as partial replacement to Portland cement on the tribological properties of concrete. To achieve this goal, concrete mixtures were prepared with different percentages (10, 20 and 30%) of limestone fillers (LF) and natural pozzolana (NP), and (20, 40 and 60%) of blast furnace slag (BFS). The interface yield stress (τ0) and viscous constants (η) that allow characterizing friction at the concrete-pipe wall interface were determined using a rotational tribometer. In addition, the compositions of the boundary layers that formed in the pumping pipes of the different concretes under study were also identified and analyzed. The experimental results obtained showed that the concretes studied have a linear tribological behavior that can be described by the Bingham model. Furthermore, the use of different mineral additions, especially limestone fillers and blast furnace slags, even at high rates, had a beneficial effect on the optimization of the volume of paste present in the boundary layer, which made it possible to significantly reduce the viscous constant of concrete. However, a maximum rate of 10% of natural pozzolana was recommended to achieve tribological properties that are favorable to the pumpability of concrete.

• International Journal of Computer Science & Network Security
• /
• v.22 no.10
• /
• pp.171-176
• /
• 2022

A dramatic rise in the number of people dying from heart disease has prompted efforts to find a way to identify it sooner using efficient approaches. A variety of variables contribute to the condition and even hereditary factors. The current estimate approaches use an automated diagnostic system that fails to attain a high level of accuracy because it includes irrelevant dataset information. This paper presents an effective neural network with convolutional layers for classifying clinical data that is highly class-imbalanced. Traditional approaches rely on massive amounts of data rather than precise predictions. Data must be picked carefully in order to achieve an earlier prediction process. It's a setback for analysis if the data obtained is just partially complete. However, feature extraction is a major challenge in classification and prediction since increased data increases the training time of traditional machine learning classifiers. The work integrates the CNN-MDRP classifier (convolutional neural network (CNN)-based efficient multimodal disease risk prediction with TANFIS (tuned adaptive neuro-fuzzy inference system) for earlier accurate prediction. Perform data cleaning by transforming partial data to informative data from the dataset in this project. The recommended TANFIS tuning parameters are then improved using a Laplace Gaussian mutation-based grasshopper and moth flame optimization approach (LGM²G). The proposed approach yields a prediction accuracy of 98.40 percent when compared to current algorithms.

• Nuclear Engineering and Technology
• /
• v.55 no.7
• /
• pp.2432-2437
• /
• 2023

Methodology for suppressing or recovering the distorted spectra, which may occur due to mutual non-uniformity and nonlinear response when a multi-detector is simultaneously operated for gamma spectroscopy, is presented with respect to its applicability to stabilization of spectra having the non-identical feature using modified full spectrum reallocation method. The modified full-spectrum reallocation method is extended to provide multiple coefficients that describe the gain drift for multi-division of the spectrum and they were incorporated into an optimization process utilizing a random sampling algorithm. Significant performance improvements were observed with the use of multiple coefficients for solving partial peak dislocation. In this study, our achievements to confirm the stabilization of spectrum having differences in moments and modify the full spectrum reallocation method provide the feasibility of the method and ways to minimize the implication of the non-linear responses normally associated with inherent characteristics of the detector system. We believe that this study will not only simplify the calibration process by using an identical response curve but will also contribute to simplifying data pre-processing for various studies as all spectra can be stabilized with identical channel widths and numbers.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.336-343
• /
• 2022

Industrial robotic arms are widely adopted in numerous industries for manufacturing automation under factory settings, which eliminates the limitations of manual labor and provides significant productivity and quality benefits. The U.S. modular construction industry, despite having similar controlled factory environments, still heavily relies on manual labor. Thus, this study investigates the U.S., Canada, and Europe-based leading modular construction companies and research labs implementing industrial robotic arms for manufacturing automation. The investigation mainly considered the current research scope, industry state, and constraints, as well as identifying the types and specifications of the robotic arms in use. First, the study investigated well-recognized modular building associations, the Modular Building Institute (MBI), and renowned architecture design magazine, Dezeen to gather industry updates. The authors discovered one university lab and a few companies that adopted Switzerland-based robotic arms, ABB. Researching ABB robotics led to the discovery of ABB's competitor, Germany-based KUKA robotic arms. Consequently, research extended to the companies and labs adopting KUKA models. In total, this study has identified seven modular companies and four research labs. All companies employed robotic arms and gantry robot combinations in a production-line-like system for partial automation, and some adopted design standardization for optimization. The common goal among the labs was to achieve greater flexibility and full automation with robotic arms. This study will help companies better implement robotic arm automation by providing recommendations from investigating its current industry status.

• International Journal of Computer Science & Network Security
• /
• v.24 no.9
• /
• pp.105-110
• /
• 2024

Nowadays, permutation problems with large state spaces and the path to solution is irrelevant such as N-Queens problem has the same general property for many important applications such as integrated-circuit design, factory-floor layout, job-shop scheduling, automatic programming, telecommunications network optimization, vehicle routing, and portfolio management. Therefore, methods which are able to find a solution are very important. Genetic algorithm (GA) is one the most well-known methods for solving N-Queens problem and applicable to a wide range of permutation problems. In the absence of specialized solution for a particular problem, genetic algorithm would be efficient. But holism and random choices cause problem for genetic algorithm in searching large state spaces. So, the efficiency of this algorithm would be demoted when the size of state space of the problem grows exponentially. In this paper, the new method presented based on genetic algorithm to cover this weakness. This new method is trying to provide partial view for genetic algorithm by locally searching the state space. This may cause genetic algorithm to take shorter steps toward the solution. To find the first solution and other solutions in N-Queens problem using proposed method: dividing N-Queens problem into subproblems, which configuring initial population of genetic algorithm. The proposed method is evaluated and compares it with two similar methods that indicate the amount of performance improvement.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.32 no.4
• /
• pp.249-256
• /
• 2019

This paper presents an optimization framework of electrical impedance tomography for characterizing electrical conductivity profiles of concrete structures in two dimensions. The framework utilizes a partial-differential-equation(PDE)-constrained optimization approach that can obtain the spatial distribution of electrical conductivity using measured electrical potentials from several electrodes located on the boundary of the concrete domain. The forward problem is formulated based on a complete electrode model(CEM) for the electrical potential of a medium due to current input. The CEM consists of a Laplace equation for electrical potential and boundary conditions to represent the current inputs to the electrodes on the surface. To validate the forward solution, electrical potential calculated by the finite element method is compared with that obtained using TCAD software. The PDE-constrained optimization approach seeks the optimal values of electrical conductivity on the domain of investigation while minimizing the Lagrangian function. The Lagrangian consists of least-squares objective functional and regularization terms augmented by the weak imposition of the governing equation and boundary conditions via Lagrange multipliers. Enforcing the stationarity of the Lagrangian leads to the Karush-Kuhn-Tucker condition to obtain an optimal solution for electrical conductivity within the target medium. Numerical inversion results are reported showing the reconstruction of the electrical conductivity profile of a concrete specimen in two dimensions.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.14 no.1
• /
• pp.13-17
• /
• 2010

Purpose: Partial volume effect (PVE) is the phenomenon to lower the accuracy of image due to low estimate, which is to occur from PET/CT 3D image acquisition. The more resolution is declined and the lesion is small, the more it causes a big error. So that it can influence the test result. Studied the optimum image reconstruction method by using variation of parameter, which can influence the PVE. Materials and Methods: It acquires the image in each size spheres which is injected $^{18}F$-FDG to hot site and background in the ratio 4:1 for 10 minutes by using NEMA 2001 IEC phantom in GE Discovey STE 16. The iterative reconstruction is used and gives variety to iteration 2-50 times, subset number 1-56. The analysis's fixed region of interest in detail part of image and compute % difference and signal to noise ratio (SNR) using $SUV_{max}$. Results: It's measured that $SUV_{max}$ of 10 mm spheres, which is changed subset number to 2, 5, 8, 20, 56 in fixed iteration to times, SNR is indicated 0.19, 0.30, 0.40, 0.48, 0.45. As well as each sphere's of total SNR is measured 2.73, 3.38, 3.64, 3.63, 3.38. Conclusion: In iteration 6th to 20th, it indicates similar value in % difference and SNR ($3.47{\pm}0.09$). Over 20th, it increases the phenomenon, which is placed low value on $SUV_{max}$ through the influence of noise. In addition, the identical iteration, it indicates that SNR is high value in 8th to 20th in variation of subset number. Therefore, to reduce partial volume effect of small lesion, it can be declined the partial volume effect in iteration 6 times, subset number 8~20 times, considering reconstruction time.

• Journal of Microbiology and Biotechnology
• /
• v.14 no.6
• /
• pp.1239-1248
• /
• 2004

The methylotrophic yeast Hansenula polymorpha has been extensively studied as a model organism for methanol metabolism and peroxisome biogenesis. Recently, this yeast has also attracted attention as a promising host organism for recombinant protein production. Here, we describe the fabrication and evaluation of a DNA chip spotted with 382 open reading frames (ORFs) of H. polymorpha. Each ORF was PCR-amplified using gene-specific primer sets, of which the forward primers had 5'-aminolink. The PCR products were printed in duplicate onto the aldehyde-coated slide glasses to link only the coding strands to the surface of the slide via covalent coupling between amine and aldehyde groups. With the partial genome DNA chip, we compared efficiency of direct and indirect cDNA target labeling methods, and found that the indirect method, using fluorescent-labeled dendrimers, generated a higher hybridization signal-to-noise ratio than the direct method, using cDNA targets labeled by incorporation of fluorescence-labeled nucIeotides during reverse transcription. In addition, to assess the quality of this DNA chip, we analyzed the expression profiles of H. polymorpha cells grown on different carbon sources, such as glucose and methanol, and also those of cells treated with the superoxide­generating drug, menadione. The profiles obtained showed a high-level induction of a set of ORFs involved in methanol metabolism and oxidative stress response in the presence of methanol and menadione, respectively. The results demonstrate the sensitivity and reliability of our arrays to analyze global gene expression changes of H. polymorpha under defined environmental conditions.