• Journal of Biomedical Engineering Research
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• v.42 no.6
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• pp.268-276
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• 2021

Functional near-infrared spectroscopy-based brain-computer interface (fNIRS-based BCI) has been receiving much attention. However, we are practically constrained to obtain a lot of fNIRS data by inherent hemodynamic delay. For this reason, when employing machine learning techniques, a problem due to the high-dimensional feature vector may be encountered, such as deteriorated classification accuracy. In this study, we employ an elastic net-based feature selection which is one of the embedded methods and demonstrate the utility of which by analyzing the results. Using the fNIRS dataset obtained from 18 participants for classifying brain activation induced by mental arithmetic and idle state, we calculated classification accuracies after performing feature selection while changing the parameter α (weight of lasso vs. ridge regularization). Grand averages of classification accuracy are 80.0 ± 9.4%, 79.3 ± 9.6%, 79.0 ± 9.2%, 79.7 ± 10.1%, 77.6 ± 10.3%, 79.2 ± 8.9%, and 80.0 ± 7.8% for the various values of α = 0.001, 0.005, 0.01, 0.05, 0.1, 0.2, and 0.5, respectively, and are not statistically different from the grand average of classification accuracy estimated with all features (80.1 ± 9.5%). As a result, no difference in classification accuracy is revealed for all considered parameter α values. Especially for α = 0.5, we are able to achieve the statistically same level of classification accuracy with even 16.4% features of the total features. Since elastic net-based feature selection can be easily applied to other cases without complicated initialization and parameter fine-tuning, we can be looking forward to seeing that the elastic-based feature selection can be actively applied to fNIRS data.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.12
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• pp.437-444
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• 2022

Recently, research on mobile edge services has been conducted to handle computationally intensive and latency-sensitive tasks occurring in wireless networks. However, MEC, which is fixed on the ground, cannot flexibly cope with situations where task processing requests increase sharply, such as commuting time. To solve this problem, a technology that provides edge services using UAVs (Unmanned Aerial Vehicles) has emerged. Unlike ground MEC servers, UAVs have limited battery capacity, so it is necessary to optimize energy efficiency through load balancing between UAV MEC servers. Therefore, in this paper, we propose a load balancing technique with consideration of the energy state of UAVs and the mobility of vehicles. The proposed technique is composed of task offloading scheme using genetic algorithm and task migration scheme using Q-learning. To evaluate the performance of the proposed technique, experiments were conducted with varying mobility speed and number of vehicles, and performance was analyzed in terms of load variance, energy consumption, communication overhead, and delay constraint satisfaction rate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.17-22
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• 2022

With the spread of web services, data types are becoming more diversified. In addition to the form of storing data such as images, videos, and texts, the number and form of properties and metadata expressing the data are different for each data. In order to efficiently process such unstructured data, a key-value store is widely used for state-of-the-art applications. LSM-Tree (Log Structured Merge Tree) is the core data structure of various commercial key-value stores. LSM-Tree is optimized to provide high performance for small writes by recording all write and delete operations in a log manner. However, there is a problem in that the delay time and processing speed of user requests are lowered as batches of deletion operations for expired data are inserted into the LSM-Tree as special key-value data. This paper presents a Filtered LSM-Tree (FLSM-Tree) that solves the above problem by separating the deleted key from the main tree structure while maintaining all the advantages of the existing LSM-Tree. The proposed method is implemented in LevelDB, a commercial key-value store and it shows that the read performance is improved by up to 47% in performance evaluation.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.25 no.6
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• pp.441-452
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• 2022

Congenital diarrheal disorders (CDDs) with genetic etiology are uncommon hereditary intestinal diseases characterized by chronic, life-threatening, intractable watery diarrhea that starts in infancy. CDDs can be mechanistically divided into osmotic and secretory diarrhea. Congenital tufting enteropathy (CTE), also known as intestinal epithelial dysplasia, is a type of secretory CDD. CTE is a rare autosomal recessive enteropathy that presents with intractable neonatal-onset diarrhea, intestinal failure, severe malnutrition, and parenteral nutrition dependence. Villous atrophy of the intestinal epithelium, crypt hyperplasia, and irregularity of surface enterocytes are the specific pathological findings of CTE. The small intestine and occasionally the colonic mucosa include focal epithelial tufts. In 2008, Sivagnanam et al. discovered that mutations in the epithelial cell adhesion molecule (EpCAM, MIM# 185535) were the genetic cause of CTE (MIM# 613217). More than a hundred mutations have been reported to date. Furthermore, mutations in the serine peptidase inhibitor Kunitz type 2 (SPINT2, MIM# 605124) have been linked to syndromic CTE. In this study, we report the case of a 17-month-old male infant with congenital diarrhea. Despite extensive etiological workup, no etiology could be established before admission to our center. The patient died 15 hours after being admitted to our center in a metabolically decompensated state, probably due to a delay in admission and diagnosis. Molecular autopsy with exome sequencing revealed a previously reported homozygous missense variant, c.757G>A, in EpCAM, which was confirmed by histopathological examination.

• Molecules and Cells
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• v.45 no.8
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• pp.588-602
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• 2022

Various RNA-binding proteins (RBPs) are key components in RNA metabolism and contribute to several neurodevelopmental disorders. To date, only a few of such RBPs have been characterized for their roles in neocortex development. Here, we show that the RBP, Rbms1, is required for radial migration, polarization and differentiation of neuronal progenitors to neurons in the neocortex development. Rbms1 expression is highest in the early development in the developing cortex, with its expression gradually diminishing from embryonic day 13.5 (E13.5) to postnatal day 0 (P0). From in utero electroporation (IUE) experiments when Rbms1 levels are knocked down in neuronal progenitors, their transition from multipolar to bipolar state is delayed and this is accompanied by a delay in radial migration of these cells. Reduced Rbms1 levels in vivo also reduces differentiation as evidenced by a decrease in levels of several differentiation markers, meanwhile having no significant effects on proliferation and cell cycle rates of these cells. As an RNA binding protein, we profiled the RNA binders of Rbms1 by a cross-linked-RIP sequencing assay, followed by quantitative real-time polymerase chain reaction verification and showed that Rbms1 binds and stabilizes the mRNA for Efr3a, a signaling adapter protein. We also demonstrate that ectopic Efr3a can recover the cells from the migration defects due to loss of Rbms1, both in vivo and in vitro migration assays with cultured cells. These imply that one of the functions of Rbms1 involves the stabilization of Efr3a RNA message, required for migration and maturation of neuronal progenitors in radial migration in the developing neocortex.

• Environmental Mutagens and Carcinogens
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• v.23 no.2
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• pp.56-62
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• 2003

The liver progenitor cells could form a potential target cell population fore both tumor-initiating and -promoting chemicals. Induction of drug-metabolizing and antioxidant enzymes, including AhR-dependent CYP1A1, NQO-1 and AKR1C9, was detected in the rat liver epithelial WB-F344 "stem-like" cells. Additionally, WB-F344 cells express a functional, wild-type form of p53 protein, a biomarker of genotoxic events, and connexin 43, a basic structural unit of gap junctions forming an important type of intercellular communication. In this cellular model, two complementary assays have been established for detection of the modes of action associated with tumor promotion: inhibition of gap junctional intercellular communication (GJIC) and proliferative activity in confluent cells. We found that the PAHs and PCBs, which are AhR agonists, released WB-F344 cells from contact inhibition, increasing both DNA synthesis and cell numbers. Genotoxic effects of some PAHs that lead to apoptosis and cell cycle delay might interfere with the proliferative activity of PAHs. Contrary to that, the nongenotoxic low-molecular-weight PAHs and non-dioxin-like PCB congeners, abundant in the environment, did not significantly affect cell cycle and cell proliferation; however both groups of compounds inhibited GJIC in WB-F344 cells. The release from contact inhibiton by a mechanism that possibly involves the AhR activation, inhibition of GJIC and genotoxic events induced by environmental contaminants are three important modes of action that could play an important role in carcinogenic effects of toxic compounds. The relative potencies to inhibit GJIC, to induce AhR-mediated activity, and to release cells from contact inhibition were determined for a large series of PAHs and PCBs and their metabolites. In vitro bioassays based on detection of events on cellular level (deregulation of GJIC and/or proliferation) or determination of receptor-mediated activities in both ?$stem-like^{\circ}{\times}$ and hepatocyte-like liver cellular models are valuable tools for detection of modes of action of polyaromatic hydrocarbons. They may serve, together with concentration data, as a first step in their risk assessment.

• Journal of Aerospace System Engineering
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• v.17 no.1
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• pp.51-58
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• 2023

Hypergolic propellants, which can ignite themselves without an ignition source, are difficult to handle due to their corrosiveness and toxicity. Therefore, it is necessary to develop green hypergolic propellants with little or no toxicity. In this study, basic research on green hypergolic ignition propellants was conducted. With 95% hydrogen peroxide as an oxidizer and CNU_HGFv1 as a fuel, ignition and combustion characteristics of propellants were evaluated through a drop test, an ignition test, and a combustion test. As a result of the drop test, the ignition delay time was 9.7 ms. It was 27 ms in the ignition test, which was fast enough to be used as a propellant. As a result of the combustion test, a combustion efficiency of 95.4~98.1% was achieved at about 11.7 bar. It was confirmed that fast and stable combustion was possible without hard start or combustion instability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2140-2156
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• 2023

The Wireless Sensor Network (WSN), is constructed out of teeny-tiny sensor nodes that are very low-cost, have a low impact on the environment in terms of the amount of power they consume, and are able to successfully transmit data to the base station. The primary challenges that are presented by WSN are those that are posed by the distance between nodes, the amount of energy that is consumed, and the delay in time. The sensor node's source of power supply is a battery, and this particular battery is not capable of being recharged. In this scenario, the amount of energy that is consumed rises in direct proportion to the distance that separates the nodes. Here, we present a Hybrid Firefly Glow-Worm Swarm Optimization (HF-GSO) guided routing strategy for preserving WSNs' low power footprint. An efficient fitness function based on firefly optimization is used to select the Cluster Head (CH) in this procedure. It aids in minimising power consumption and the occurrence of dead sensor nodes. After a cluster head (CH) has been chosen, the Glow-Worm Swarm Optimization (GSO) algorithm is used to figure out the best path for sending data to the sink node. Power consumption, throughput, packet delivery ratio, and network lifetime are just some of the metrics measured and compared between the proposed method and methods that are conceptually similar to those already in use. Simulation results showed that the proposed method significantly reduced energy consumption compared to the state-of-the-art methods, while simultaneously increasing the number of functioning sensor nodes by 2.4%. Proposed method produces superior outcomes compared to alternative optimization-based methods.

• Annual Conference of KIPS
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• 2008.11a
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• pp.1332-1335
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• 2008

In order to various service types of real time and non-real time traffic with varying requirements are transmitted over the IEEE 802.16 standard is expected to provide quality of service(QoS) researchers have explored to provide a queue management scheme with differentiated loss guarantees for the future Internet. The sides of a packet drop rate, an each class to differential drop probability on achieving a low delay and high traffic intensity. Improved a queue management scheme to be enhanced to offer a drop probability is desired necessarily. This paper considers multiple random early detection with differential drop probability which is a slightly modified version of the Multiple-RED(Random Early Detection) model, to get the performance of the best suited, we analyzes its main control parameters (max_th, min_th, max_p) for achieving the proportional loss differentiation (PLD) model, and gives their setting guidance from the analytic approach. we propose Dynamic-multiple queue management scheme based on differential drop probability, called Dynamic-VQSDDP(Variable Queue State Differential Drop Probability)T, is proposed to overcome M-RED's shortcoming as well as supports static max_p parameter setting values for relative and each class proportional loss differentiation. M-RED is static according to the situation of the network traffic, Network environment is very dynamic situation. Therefore max_p parameter values needs to modify too to the constantly and dynamic. The verification of the guidance is shown with figuring out loss probability using a proposed algorithm under dynamic offered load and is also selection problem of optimal values of parameters for high traffic intensity and show that Dynamic-VQSDDP has the better performance in terms of packet drop rate. We also demonstrated using an ns-2 network simulation.

• Advances in materials Research
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• v.12 no.4
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• pp.263-271
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• 2023

In this study, AA1060/Alumina composites were fabricated by combined stir casting and accumulative press bonding (APB). The APB process was repeated up to six press bonding steps at 300Ċ. As the novelty, potential dynamic polarization in 3.5Wt% NaCl solution was used to study the corrosion properties of these composites. The corrosion behavior of these samples was compared and studied with that of the annealed aluminum alloy 1060 and versus the number of APB steps. So, as a result of enhancing influence on the number of APB process, this experimental investigation showed a significant enhancement in the main electrochemical parameters and the inert character of the Alumina particles. Together with Reducing the active zones of the material surfaces could delay the corrosion process. Also, at higher number of steps, the corrosion resistance of composites improved. The sample produced after six number of steps had a low corrosion density in comparison with high corrosion density of annealed specimens. Also, the scanning electron microscopy (SEM), was used to study the corrosion surface of samples.