• Journal of KIISE:Computing Practices and Letters
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• v.10 no.6
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• pp.484-498
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• 2004

In this paper. we propose a novel performance monitoring scheme for heterogeneous SOAP nodes. The scheme is basically based on two-level (kernel-level and user-level) packet filtering of TCP flows. By TCP flow, we mean a sequence of raw packet streams on a TCP transaction. In this scheme, we detect and extract SOAP operations embedded in SOAP messages from TCP flows. Therefore, it becomes possible to monitor heterogeneous SOAP nodes deployed on diverse SOAP-based middlewares such as .Net and Apache AXIS. We present two implementation mechanisms for the proposed scheme. The first mechanism tries to identify SOAP operations by analyzing all fragmented SOAP messages on TCP flows. However, a naive policy would incur untolerable overhead since it needs to copy all packets from kernel to user space. The second mechanism overcomes this problem by selectively copying packets from kernel to user space. For selective copying, we use a kernel-level packet filtering method that makes use of some representative TCP flags.(e.g. SIN, FIN and PSH). In this mechanism, we can detect SOAP operations only from the last fragment of SOAP messages in most cases. Finally, we implement a SOAP monitoring system using a component ca]led SOAP Sniffer that realizes our proposed scheme, and show experimental results. We strongly believe that our system will play a vital role as a tool for various services such as transaction monitoring and load balancing among heterogeneous SOAP nodes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.81-88
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• 2021

Structural health monitoring (SHM) systems have attracted considerable interest owing to the frequent earthquakes over the last decade. Smart concrete is a technology that can analyze the state of structures based on their electro-mechanical behavior. On the other hand, most research on the self-sensing response of smart concrete generally investigated the electro-mechanical behavior of smart concrete under a static loading rate, even though the loading rate under an earthquake would be much faster than the static rate. Thus, this study evaluated the electro-mechanical behavior of smart ultra-high-performance concrete (S-UHPC) at three different loading rates (1, 4, and 8 mm/min) using a Universal Testing Machine (UTM). The stress-sensitive coefficient (SC) at the maximum compressive strength of S-UHPC was -0.140 %/MPa based on a loading rate of 1 mm/min but decreased by 42.8% and 72.7% as the loading rate was increased to 4 and 8 mm/min, respectively. Although the sensing capability of S-UHPC decreased with increased load speed due to the reduced deformation of conductive materials and increased microcrack, it was available for SHM systems for earthquake detection in structures.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.345-353
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• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.12 no.2
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• pp.199-206
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• 2009

Purpose: To analyze the clinical spectrum of posttransplantation lymphoproliferative disorder (PTLD) after liver transplantation in children. Methods: From January 1988 to June 2009, we retrospectively reviewed the medical records of 8 PTLD cases among 148 pediatric patients underwent liver transplantation. The age at transplantation, time of presentation after transplantation, clinical manifestations, histologic diagnosis, results of EBV (Epstein-Barr virus) assessments, managements and outcomes of PTLD were investigated. Results: The prevalence of PTLD in liver transplant pediatric recipients was 5.4% (8 of 148). The mean age of patients was 25.4${\pm}$21.3 months (range 10 to 67 months). Seven of 8 patients (87.5%) underwent liver transplantation before 1 year of age. The common clinical presentations were persistent fever (8 of 8, 100%) and bloody diarrhea (6 of 8, 75%). PTLD was diagnosed with gastrointestinal endoscopic biopsies in five patients and surgical biopsies in three. Histologic findings showed early lesion in three patients, polymorphic in two, and monomorphic in three. Burkitt lymphoma and lymphoblastic lymphoma were found in two of 3 monomorphic patients. Seven of 8 patients were found with EBV-positive. Eight patients were treated with dose reduction of immunosuppressants and infusion of ganciclovir. Rituximab was added to four patients. PTLD were successfully managed in all patients except one who died of sepsis during chemotherapy. Conclusion: Major risk factor of PTLD was to undergo liver transplantation before 1 year of age. Continuous monitoring for EBV viral load and gastrointestinal endoscopic biopsy may be useful to early detection of PTLD.

• Tuberculosis and Respiratory Diseases
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• v.44 no.2
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• pp.309-320
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• 1997

Background : There are many suggested methods for the indirect determination of anaerobic threshold(AT) using the changes of ventilatory parameters in response to ventilatory load accompanying the increase of blood lactic acid level during exercise and the threshold derived from them is called ventilatory threshold(VT). They include ventilatory equivalent method(VEM), End-tidal $PO_2$ method($PETO_2$). V-slope method(VSM), and respiratory quotient method(RQ). But in the patients with chronic airway obstruction(CAO), the AT determined by ventilatory methods may not reflect true AT because the patients with CAO show inadequate ventilatory response to the increase of blood lactic acid level during excercise. Methods : For the investigation of detection rate and reliability of above four VT determination methods in the patients with CAO, we performed the symptom-limited and maximal incremental exercise test in 17 patients with CAO and 12 normal controls. The incremental workload was 10 W /min in CAO group and 25 W/min in control group. The reliability of VT in each group was investigated by the calculation of Spearman correlation coefficient. Results : The detection rates of VT were 100% by RQ, 91.7% by both VEM and $POETO_2$, and 83.3% by VSM in normal control group, while 94.1% by RQ, 64.7% by VEM and $PETO_2$, and 83.3% by VSM in CAO group. Good correlations were noted among VEM, $POETO_2$, and VSM except RQ in normal control group. But there was no significant correlation except between VEM and $PETO_2$ in CAO group. Conclusions : RQ is very sensitive but crude and VEM is near similar to $PETO_2$. The clinical usefulness of VT determined by ventilatory method might be limited in patients with severe CAO.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7825-7829
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• 2015

Background: Egypt has the highest prevalence of HCV infection in the world (~14.7%). Around 10-15% of HCV-infected persons will advance to cirrhosis within the first 20 years. The incidence of HCC is expected to grow in the next two decades, largely due to HCV related cirrhosis, and detection of HCC at an early stage is critical for a favorable clinical outcome. No simple reliable non-invasive marker has been available till now. B2M, a non-glycosylated polypeptide composed of 99 amino acids, is one of the components of HLA class I molecules on the surfaces of all nucleated cells. It has been reported that the level of serum B2M is elevated in patients with chronic hepatitis C and HCV-related HCC when compared to HCV-negative patients or healthy donors. Determining the clinical utility of serum B2M as a marker for disease progression in Egyptian patients with HCV related chronic hepatitis, cirrhosis and hepatocellular carcinoma was the aim of the present study. Materials and Methods: In this analytical cross sectional study 92 participants were included in 4 equal groups: Group (1) non cirrhotic chronic HCV; Group (2) HCV related liver cirrhosis; Group (3) HCC on top of HCV,; and Group (4) healthy controls. History taking, clinical examination, routine labs and abdominal ultrasound were conducted for all patients, PCR and Metavir scores for group (1) patients, and triphasic CT abdomen and AFP for Group (3) patients. B2M levels were measured in serum with a fully-automated IMX system. Results: The mean serum B2M level of Group (1) was $4.25{\pm}1.48{\mu}g/ml$., Group (2) was $7.48{\pm}3.04$, Group (3) was $6.62{\pm}2.49$ and Group (4) was $1.62{\pm}0.63$. Serum B2M levels were significantly higher in diseased than control group (p<0.01) being significantly higher in cirrhosis ($7.48{\pm}3.04$) and HCC groups ($6.62{\pm}2.49$) than the HCV group ($4.25{\pm}1.48$) (p<0.01). There was a significant correlation between B2M Level and ALK, total and direct bilirubin and INR (p<0.05), and a significant inverse correlation between B2M level and albumin, total proteins, HB andWBCS values (p<0.05). There was no significant correlation between B2M level and viral load or Metavir score, largest tumour size or AFP (p>0.05). The best B2M cut-off for HCV diagnosis was 2.6 with a sensitivity of 100%, a specificity of 92%, a positive predictive value (PPV) of 97% and a negative predictive value (NPV) of 100%. The best B2M cut-off for HCC diagnosis was 4.55 which yielded sensitivity, specificity, positive predictive value, negative predictive values of 74%, 62%, 39.5, 87.8% respectively (p-value <0.01) while best cut-off for cirrhosis was 4.9, with sensitivity 74 % and specificity 74%.The sensitivity for HCC diagnosis increased upon B2M and AFP combined estimation to 91%, specificity to 79%, NPV to 95% and accuracy to 83%. Conclusions: Serum B2M level is elevated in HCV related chronic liver diseases and may be used as a marker for HCV disease progression towards cirrhosis and carcinoma.

• Journal of Food Hygiene and Safety
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• v.34 no.5
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• pp.447-453
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• 2019

In this study, the contamination of 4 types of heavy metals (lead, cadmium, arsenic, and mercury) was monitored in 80 seaweeds and their processed products, and a food safety assessment was also carried out for these heavy metals. Lead, cadmium and arsenic were analyzed by ICP-OES and mercury was analyzed by mercury analyzer. The detection ranges of heavy metals were found as follows: Pb (N.D-0.802 mg/kg), Cd (N.D-0.759 mg/kg), As (0.134-17.296 mg/kg), and Hg (0.0005-0.0331 mg/kg). Pb and Hg showed no significant differences among seaweeds whereas Cd and As were significantly higher in the species hizikia fusiforme (P<0.05). Food safety assessment from seaweed intake was measured by PTWI (Provisional Tolerable Weekly Intake), PTMI (Provisional Tolerable Monthly Intake), and MADL (Maximum Allowable Daily Body Load) as set by JECFA (Joint FAO/WHO Expert Committee on Food Additives). Pb and Hg were 0.197%, 0.036% of PTWI respectively, while Cd was 1.877% of PTMI and As was 0.619% of MADL. Therefore, it was found that heavy metal levels of seaweed were low and was considered to be safe for consumption.

• Pediatric Infection and Vaccine
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• v.29 no.3
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• pp.131-140
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• 2022

Purpose: Since the coronavirus disease 2019 (COVID-19) pandemic began, new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged, and distinct epidemic waves of COVID-19 have occurred for an extended period. This study aimed to analyze the clinical and epidemiological characteristics of children with COVID-19 from the third wave to the middle of the fourth epidemic wave in Korea. Methods: We retrospectively reviewed the medical records of hospitalized patients aged ≤18 years with laboratory-confirmed COVID-19. The study periods were divided into the third wave (from November 13, 2020 to July 6, 2021) and the fourth wave (from July 7 to October 31, 2021). Results: Ninety-three patients were included in the analysis (33 in the third and 60 in the fourth waves). Compared with the third wave, the median age of patients was significantly older during the fourth wave (6.7 vs. 2.8 years, P=0.014). Household contacts was reported in 60.2% of total patients, similar in both periods (69.7 vs. 55.0%, P=0.190). Eighty-one (87.1%) had symptomatic SARS-CoV-2 infection. Among these, 10 (12.3%) had no respiratory symptoms. Anosmia or ageusia were more commonly observed in the fourth epidemic wave (10.7 vs. 34.0%, P=0.032). Most respiratory illness were upper respiratory tract infections (94.4%, 67/71), 4 had pneumonia. The median cycle threshold values (detection threshold, 40) for RNA-dependent RNA polymerase (RdRp) and envelope (E) genes of SARS-CoV-2 were 21.3 and 19.3, respectively. There was no significant difference in viral load during 2 epidemic waves. Conclusions: There were different characteristics during the two epidemic waves of COVID-19.