Qualified Data Research Articles

Quality registries: exciting opportunities.

Quality registries: exciting opportunities.

An Analysis of Groudwater Budget in a Water Curtain Cultivation Site

In Korea, rural groundwater development faces new challenge, which have not been experienced so far. The problem is a groundwater depletion by the water curtain cultivation (WCC) during winter season. This study investigates the groundwater depletion using three-dimensional finite difference groundwater flow program, MODFLOW to verify the water budget of the shallow aquifer of Cheongweon area. Interdisciplinary research, which has become a worldwide trend, has been adopted in studying groundwater modeling in field scale. In particular, the method of groundwater recharge estimation adopted precise modeling techniques, SWAT to groundwater flow modeling. Based on qualified field data, the model calibrated and validated its reliability. The objective of this study is to simulate various stream-aquifer interactions according to groundwater pumping with artificial boundaries, such as weirs and drainage system. We also analyzed a seasonal variation of cumulative water budget of the site to quantify the groundwater depletion and recovery in the pumping field.

Particle image velocimetry measurements of the flow in the converging region of two parallel jets

The interaction between parallel jets plays a critical role in determining the characteristics of the momentum and heat transfer in the flow. Specifically for next generation VHTR, the output temperature will be about 900°C, and any thermal oscillations will create safety issues. The mixing variations of the coolants in the reactor core may influence these power oscillations. Numerous numerical tools such as computational fluid dynamics (CFD) simulations have been used to support the reactor design. The validation of CFD method is important to ensure the fidelity of the calculations. This requires high-fidelity, qualified benchmark data. Particle image velocimetry (PIV), a non-intrusive measuring technique, was used to provide benchmark data for resolving a simultaneous flow field in the converging region of two submerged parallel jets issued from rectangular channels. The jets studied in this work had an equal discharge velocity at room temperature. The turbulent characteristics including the distributions of mean velocities, turbulence intensities, Reynolds stresses and z-component vorticity were studied. The streamwise mean velocity measured by PIV and LDV were compared, and they agreed very well.

Incidence and mortality of liver cancer in China in 2011.

BackgroundLiver cancer is a common cancer with poor prognosis in China. In this study, the national population-based cancer registration data were used to evaluate and analyze liver cancer incidence and mortality in China in 2011 and provide a reference for liver cancer prevention and control.MethodsWe collected and evaluated the incidence and mortality data of liver cancer in 2011 from 177 cancer registries with qualified data. These data were used in the final analysis including calculating crude, standardized, and truncated incidences and mortalities, and estimated new liver cancer cases and deaths using age-specific rates and the corresponding populations. The national census in 2000 and Segi’s population were used for age-standardized rates.ResultsThe estimates of new liver cancer cases and deaths were 355,595 and 322,416, respectively, in China in 2011. The crude incidence, age-standardized rate of incidence by Chinese standard population (ASRIC), and age-standardized rate of incidence by world standard population (ASRIW) of liver cancer were 26.39/100,000, 19.48/100,000, and 19.10/100,000, respectively; the crude mortality, age-standardized rate of mortality by Chinese standard population (ASRMC), and age-standardized rate of mortality by world standard population (ASRMW) of liver cancer were 23.93/100,000,17.48/100,000, and 17.17/100,000, respectively. The incidence and mortality were higher in rural areas than in urban areas and higher in males than in females. The age-specific incidence and mortality of liver cancer increased greatly with age, particularly after 30 years and peaked at 80–84 or 85+ years.ConclusionsLiver cancer is a common cancer in China, particularly for males and residents in rural areas. Targeted prevention, early detection, and treatment programs should be carried out.

Literature review and meta-analysis of translaminar pressure difference in open-angle glaucoma.

There is increasing evidence in the literature regarding translaminar pressure difference's (TPD) role in the pathophysiology of glaucoma. The optic nerve is exposed not only to intraocular pressure in the eye, but also to intracranial pressure (ICP), as it is surrounded by cerebrospinal fluid in the subarachnoid space. Although pilot studies have identified the potential importance of TPD in glaucoma, limited available data currently prevent a comprehensive description of the role that TPD may have in glaucomatous pathophysiology. In this review, we present all available qualified data from a systematic review of the literature of the role of TPD in open-angle glaucoma (OAG). PubMed (Medline), OVID Medline, ScienceDirect, SpringerLink, and all available library databases were reviewed and subsequent meta-analysis of pooled mean differences are presented where appropriate. Five papers including 396 patients met criteria for inclusion to the analysis. Importantly, we included all observational studies despite differences in ICP measurement methods, as there is no consensus regarding best-practice ICP measurements in glaucoma. Our results show that not only TPD is higher in glaucoma patients compared with healthy subjects, it is related to structural glaucomatous changes of the optic disc. Our analysis suggests further longitudinal prospective studies are needed to investigate the influence of TPD in OAG, with a goal of overcoming methodological weaknesses of previous studies.

Efficient Verifiable Top-k Queries in Two-tiered Wireless Sensor Networks

Tiered wireless sensor network is a network model of flexibility and robustness, which consists of the traditional resource-limited sensor nodes and the resource-abundant storage nodes. In such architecture, collected data from the sensor nodes are periodically submitted to the nearby storage nodes for archive purpose. When a query is requested, storage nodes also process the query and return qualified data as the result to the base station. The role of the storage nodes leads to an attack prone situation and leaves them more vulnerable in a hostile environment. If any of them is compromised, fake data may be injected into and/or qualified data may be discarded. And the base station would receive incorrect answers incurring malfunction to applications. In this paper, an efficient verifiable top-k query processing scheme called EVTQ is proposed, which is capable of verifying the authentication and completeness of the results. Collected data items with the embedded information of ordering and adjacent relationship through a hashed message authentication coding function, which serves as a validation code, are submitted from the sensor nodes to the storage nodes. Any injected or incomplete data in the returned result from a corresponded storage node is detected by the validation code at the base station. For saving communication cost, two optimized solutions that fuse and compress validation codes are presented. Experiments on communication cost show the proposed method is more efficiency than previous works.

Estimating time series of land surface energy fluxes using optimized two source energy balance schemes: Model formulation, calibration, and validation

Due to the limited availability of land surface temperature (LST) images, thermal-based evapotranspiration (ET) models can only provide instantaneous ET snapshots. In contrast, models that are based on near surface soil moisture (SM) and leaf area index (LAI) can operate at daily scales. However, their transpiration schemes need to be more physically realistic and their model parameters usually need to be calibrated by flux measurements. In this study, we incorporated a biophysical canopy conductance (Gc) model into a two source energy balance (TSEB) scheme to replace the original Priestly–Taylor (PT) approximation and then optimized both models (Gc-TSEB and PT-TSEB) at pixel scales using qualified MODIS LST data. The results show that using LST is almost as effective in the calibration as using flux measurements. This is promising because unlike flux measurements, LST can be acquired at various spatial resolutions by remote sensing, which makes model calibration feasible for any land pixel. In addition, ET and its partitioning between the canopy and soil layers were found to be reasonable at both validation sites. The day to day and diurnal variations of the predicted ET generally matched the trends and peaks of the flux measurements, although systematic biases were also found due to the decoupling effect of soil moisture at different depths. Furthermore, both models are robust with ±50% changes of SM or LAI because the parameters were automatically adjusted by the LST-calibration. The models are sensitive to LST. However, if the added noise of the LST is less significant than N(±1, 2.52), the medians of the RMSEs in the LE predictions from the LST-calibrated models were quite similar to those from the flux-calibrated models. Both models were found to be accurate, but Gc-TSEB provides slightly more precise and robust predictions than PT-TSEB.

Clinicopathological and prognostic significance of programmed cell death ligand1 (PD-L1) expression in patients with non-small cell lung cancer: a meta-analysis.

Programmed cell death 1 (PD-1) and one of its ligands, PD-L1, are key immune checkpoint proteins. Evidences showed PD-L1 is an emerging biomarker for immunotherapy by anti-PD-1 and anti-PD-L1 antibody in non-small cell lung cancer (NSCLC). To investigate the association of PD-L1 protein expression with clinicopathological features and its impact on survival outcome, we conducted a meta-analysis. A comprehensive literature search of electronic databases (up to July 10, 2014) was performed. Correlation between PD-L1 expression and clinicopathological features and overall survival (OS) was analyzed by synthesizing the qualified data. Publication biases were examined. A total of 1,550 NSCLC patients from 9 studies were included. The pooled odds ratios (ORs) indicated high PD-L1 expression was associated with poor tumor differentiation [OR =0.53, 95% confidence interval (CI): 0.39-0.72, P<0.0001]. Whereas, none of other clinicopathological characteristics [gender, smoking status, histological type, invasive depth of tumor, status of lymph node metastasis and tumor node metastasis (TNM) stage] were correlated with PD-L1 expression in current analysis. The combined hazard ratio (HR) for OS showed high expression of PD-L1 impaired the OS in NSCLC (HRpositive/negative =1.47, 95% CI: 1.19-1.83, P=0.0004). Our meta-analysis indicated PD-L1 protein expression in NSCLC was not associated with common clinicopathological characteristics, except tumor differentiation. It was a poor prognostic biomarker for NSCLC. Further research should be performed to investigate the precise clinicopathological and prognostic significance of PD-L1 in NSCLC under uniform testing standard.

The precipitation driven correlation based mapping method (PCM) for identifying the critical source areas of non-point source pollution

Summary Critical source areas (CSAs) are the areas that are relatively more erosion-prone and contribute significantly more pollutants per unit area. They have been widely recognized as optimal locations for the control of non-point source (NPS) pollution. Modeling approach has been frequently used to identify the CSAs of NPS pollution on a basin scale. In previous studies, CSAs were identified based on the simulated average annual nutrient yields for the simulation period at the levels of sub-basin or hydrologic response unit (HRU). However, this method did not consider the impact of uneven spatial distribution of precipitation, which is considered to be the driven force of NPS pollution. In many cases, due to limited length of qualified monitoring data collected, the simulation period may not cover a full spectrum of the precipitation characteristics so that some potential CSAs may be missed. In the present study, the precipitation driven correlation based mapping method (PCM) was proposed, which can reduce the impact of uncertain spatial–temporal distribution of precipitation and identify the CSAs of NPS pollution with a better coverage. This method was applied to the Zhang River Basin, a watershed in North China that occupies an area of 18,072 km 2 . The SWAT (Soil and Water Assessment Tool) was used for simulation purposes. By using PCM, the maps of CSAs for controlling total nitrogen (TN) and total phosphorus (TP) were produced. This study has found that the monthly precipitation is highly correlated with the TN and TP yields. It was observed that TN yields have slightly higher correlation value with the precipitation than TP yields. Hence, the precipitation has more impacts on TN yields than TP yields. The impact is more substantial in urban areas than other areas.

Nickel and Copper Toxicity to Embryos of the Long-Spined Sea Urchin, Diadema savignyi.

The sensitivity of long-spined sea urchins (Diadema savignyi) collected from Guam (Northern Marianas Islands), USA, to nickel and copper in seawater was explored using 48-h embryo-larval development toxicity tests. The median effective concentrations (EC50) averaged 94 µg L(-1) for nickel, and 19 µg L(-1) from a single exposure to copper, and suggest relatively high sensitivity of this species to nickel compared with other sea urchin genera, but similar sensitivity to copper. Ambient nickel and copper concentrations concurrently sampled from 16 near-shore locations around Guam were one to two orders of magnitude lower than those that would be expected to result in adverse effects to D. savignyi embryos. Although nationally recommended chronic ambient water quality criteria, currently 8.2 and 3.1 µg L(-1) for nickel and copper, respectively, were not exceeded, recently derived qualifying toxicity data should be considered for updating these criteria to ensure protectiveness of sensitive tropical species.

Structural analysis of issues in exchanging qualified master data under cloud computing

Various applications including the data quality management DQM have been forced to reconsider their structural aspects for deployment since the figures of cloud computing have been revealed more clearly. In enterprise computing, huge efforts to apply service-oriented architecture SOA and business process integration BPI have been spent to make their information systems more agile and flexible. However, generic principles for implementing the enterprise systems should be updated owing to the advent of cloud computing. Under the practical operations with cloud computing, redeploying qualified data after cleansing, ordering and integration at prior stages depends on commissioning commercial services, despite their features as assets. Therefore, another issue could occur for example, security scope under licensing which is distinguished from the traditional security framework. In this paper, we present the operational issues of master data management MDM as one of the sub-fields of DQM. We will touch on the relationship with security requirements under cloud computing and will sketch the formularisation which will become the foundation when considering suitable operational rules.

Fundamentals in Façade Retrofit Practice

This paper describes fundamental aspects of building façade retrofit practice using field-based research. A major challenge of sustainability is to require buildings to be resilient assets in a life cycle perspective. Building retrofit, a growing research area during the last decade, finds its fundament on the urgency of decreasing the harmful effect of buildings in the environment, and improving them as healthier places for occupants. For these reasons, façade retrofit is rapidly expanding as a research area. Historically, facades have been modified for numerous reasons, such as fixing failures or accommodating aesthetic trends. Currently, the central role of the façade in building energy efficiency is driving an assessment of the potential impact of widespread façade retrofit as a means to improve building sector energy performance. Two online surveys were performed between 2013 and 2014 among building façade professionals. The first survey was intended to identify predominant broad stroke façade retrofit practices. The second survey drilled down to a deeper level of design and construction, as well as motivations and goals. Respondents were highly linked to façade consultancies, façade contractors, and material suppliers. The results included a high percentage of buildings located in the United States. The information is presented in this paper using descriptive statistics to represent façade retrofit demographics, motivations and scopes, and techniques. This aim is to contribute qualified survey data for a better understanding of the fundamental aspects of current façade retrofits practices.

소셜미디어 콘텐츠의 오피니언 마이닝결과 시각화: N라면 사례 분석 연구

소셜미디어 콘텐츠의 오피니언 마이닝결과 시각화: N라면 사례 분석 연구

Application of Quality Control Results: How to Qualify Data

Application of Quality Control Results: How to Qualify Data

Automatic Training Data Synthesis for Handwriting Recognition using the Structural Crossing-Over Technique

The paper presents a novel technique called “Structural Crossing-Over” to synthesize qualified data for training machine learning-based handwriting recognition. The proposed technique can provide a greater variety of patterns of training data than the existing approaches such as elastic distortion and tangentbased affine transformation. A couple of training characters are chosen, then they are analyzed by their similar and different structures, and finally are crossed over to generate the new characters. The experiments are set to compare the performances of tangent-based affine transformation and the proposed approach in terms of the variety of generated characters and percent of recognition errors. The standard MNIST corpus including 60,000 training characters and 10,000 test characters is employed in the experiments. The proposed technique uses 1,000 characters to synthesize 60,000 characters, and then uses these data to train and test the benchmark handwriting recognition system that exploits Histogram of Gradient: HOG as features and Support Vector Machine: SVM as recognizer. The experimental result yields 8.06% of errors. It significantly outperforms the tangent-based affine transformation and the original MNIST training data, which are 11.74% and 16.55%, respectively.

Measles Surveillance Attributes Assessment Based on The Puskesmas Surveilance Officers’ Perception in Surabaya

ABSTRACTMeasles is one of infectious diseases that potentially lead to death when complications occur. Based on the data from East Java Health Department, Surabaya is the area where the most measles cases occur in East Java and increase in the last three years. As one of measles controlling efforts, surveillance has been expected to provide qualified data and information as the basis for any decision making for a treatment or intervention. Therefore, an evaluation is needed in order to assure the effectiveness and efficiency of the surveillance application in achieving the goals. This study is a descriptive research aiming at evaluating the attributes of measles epidemiology surveillance system in Surabaya on 2012. The evaluation was done by assessing the attributes of surveillance then compared to Technical Guide for Measles Surveillance 2012, The Decree of The Health Ministry of The Republic of Indonesia No.1116/MENKES/SK/VIII/2003 On Guide for Conducting Surveillance System of Health Epidemiology and Guidelines for Evaluating Surveillance Systems from Center for Disease Control and Prevention 2001. The data collection method employed interview and observation or study documentation. The respondents of this study were 39 surveillance officers at 39 Puskesmas in Health Department Surabaya working area. The variabels of this study were simplicity, flexibility, data quality, acceptability, sensitivity, predictive value positive, representativeness, timeliness, and stability. The results of this study showed that the simplicity is complicated. The flexibility from CBMS is not flexible whereas the flexibility from EWARS is flexible. The data quality, acceptability, sensitivity and representativeness are low. The predictive value positive has not been able to be scored. The stability is high and the timeliness is punctual.Keywords: surveillance, evaluation, attribute, measles

Measles Surveillance Attributes Assessment Based on The Puskesmas Surveilance Officers’ Perception in Surabaya

ABSTRACTMeasles is one of infectious diseases that potentially lead to death when complications occur. Based on the data from East Java Health Department, Surabaya is the area where the most measles cases occur in East Java and increase in the last three years. As one of measles controlling efforts, surveillance has been expected to provide qualified data and information as the basis for any decision making for a treatment or intervention. Therefore, an evaluation is needed in order to assure the effectiveness and efficiency of the surveillance application in achieving the goals. This study is a descriptive research aiming at evaluating the attributes of measles epidemiology surveillance system in Surabaya on 2012. The evaluation was done by assessing the attributes of surveillance then compared to Technical Guide for Measles Surveillance 2012, The Decree of The Health Ministry of The Republic of Indonesia No.1116/MENKES/SK/VIII/2003 On Guide for Conducting Surveillance System of Health Epidemiology and Guidelines for Evaluating Surveillance Systems from Center for Disease Control and Prevention 2001. The data collection method employed interview and observation or study documentation. The respondents of this study were 39 surveillance officers at 39 Puskesmas in Health Department Surabaya working area. The variabels of this study were simplicity, flexibility, data quality, acceptability, sensitivity, predictive value positive, representativeness, timeliness, and stability. The results of this study showed that the simplicity is complicated. The flexibility from CBMS is not flexible whereas the flexibility from EWARS is flexible. The data quality, acceptability, sensitivity and representativeness are low. The predictive value positive has not been able to be scored. The stability is high and the timeliness is punctual.Keywords: surveillance, evaluation, attribute, measles

Dual‐expansion indexing for moving objects

With the development of wireless communications and mobile computing technologies, the applications of moving objects have been developed in many topics, for example, traffic monitoring. Such applications need to track the current and near-future locations of the moving objects. This motivates the development of spatial-temporal indices to support efficient querying about such locations of the moving objects. Therefore, in this study, the authors propose a dual-expansion indexing (DEI) to support the current and near-future prediction of the moving objects. To filter out more number of the data blocks that do not contain the final result, the query region can be expanded in each of eight directions individually. To further reduce the number of the data blocks that should be examined, the qualified data blocks can be expanded according to the direction towards the query region. Moreover, only the objects moving to the query region will be checked in the query process of DEI. Therefore our method can reduce more number of retrieved data blocks and that of input/output operations than the existing method. Experimental results show that the query process of DEI is more efficient than that of the existing method.

표면분석 장비를 활용한 차세대 나노소자 물성분석

Jouhahn Lee The new materials such as graphene and other nano scale structured materials are attracting great attention due to its expandability for the future electronic devices. In this presentation, a variety of analysis techniques will be introduced for the latest new material applications such as graphene and organic materials with number of metals. The basic properties of next generation device should be carefully analyzed without being exposed to ambient surrounding since the physical and chemical properties of new material or interface states are easily and drastically changed by ambient condition. With the combination of the fabrication process and precise analysis instruments, it is expected to set the facilities supporting the nanotechnology industry and other research groups. This system will give strong support nanotechnology and other complex science with qualified data and information on basic knowledge on the new-forthcoming materials for the future.

Big data analysis in healthcare.

The rise of big data is promising new opportunities to understand and forecast contexts or problems in the healthcare area. Big data related to healthcare has explosively expanded with the development of the Internet. It is not only accumulated in purely healthcare service settings but also in cyber-digital space, such as traditional and mobile Internet, smartphones, smart TVs, sensor and RFID-based ubiquitous networks, and social media [1]. Information and communication technology is the main driver of voluminous and varying big data to be managed and analyzed. These big data, including text, audio, video, or any other digital medium can be analyzed to provide new and useful information. Big data analytics has opened a new era to improve services and solve problems in the healthcare area. Big data analytics has recently attracted interest because it couples social data analytics to traditional analytics, though data analytics has long been important in science and healthcare practice. Forecasting using Google Flu Trends (GFT), beginning in February 2013, has attracted interest beyond the healthcare area, and it illustrates the new usefulness and value of social data and big data analytics. This innovative estimation of flu prevalence of GFT has opened up and motivated new possibilities of handling long-lasting problems in the healthcare area by using social data in cyber space. Many stakeholders recognize that big data analytics may provide opportunities for forecasting, discovering tentative needs, and reducing risks, as well as providing personalized services, real-time sensing and counter-measures more appropriately. New applications of big data analytics in the healthcare area are being developed and introduced all over the world. Seton Healthcare, working with predictive analytics, sought to address the need to reduce the occurrence of high-cost congestive heart failure readmissions [2]. The European Commission has developed 'MediSys', an information scanning tool, to reinforce the network for the surveillance of communicable diseases and the early detection of bioterrorist activities. Breaking news can be detected by algorithm of MediSys using over 20,000 Internet articles per day produced by the Europe Media Monitor and can be sent to key persons by email and SMS. Many successful big data applications are being introduced [3]. Many healthcare institutions and countries have done many trials and made many successful cases of big data analysis to solve traditional problems in healthcare, such as reducing readmissions, increasing the effectiveness and efficiency of healthcare, improving the quality of care, and forecasting demands for healthcare services. There are several factors that must be taken into consideration in using big data analytics for healthcare, although it has the potential to provide insights to enhance our understand of changing phenomena. Big data must be prepared systematically and must be of good quality. Regarding big data analytics, we should remember the popular saying 'garbage in, garbage out'. Proper big data analytics using highly qualified big data would produce useful and valuable results for understanding contexts and forecasting the future of healthcare. Next, we have not to think and use the results of big data analytics as being one and powerful information to understand and forecast something interested. The interpretation of results must be done cautiously by experts who come from diverse fields of expertise and have a wide variety of perspectives. We have to use big data analytics cautiously even after strategic consideration, though it has much potential to improve our understanding of phenomena and strengthen our ability to accurately forecast the future. Finally, we think that academic study of big data analysis could contribute to and expand the practical implementation of big data analytics. Such study should focus on any meaningful and objective criteria, such as clinical and social effectiveness, efficiency, usefulness, and adoption of big data analysis.