Results Of Quality Evaluation Research Articles

ANALISIS PEMASARAN DAN DESAIN SISTEM PERBAIKAN KUALITAS TEPUNG TALAS BENENG

Problems faced in the beneng taro flour production system is quality and quantity. Therefore, it is necessary to analyze and design the improvement of the quality of beneng taro flour. The purpose of this paper is to analyze and design a quality improvement model in taro beneng. The system design stage begins with analyzed the entities of beneng taro flour production, analyzed the market, determined the quality performance indicators of the beneng taro flour, evaluated the quality, and improvements designed of the beneng taro flour. In the needs analysis, it produces input, output, stakeholder roles, control, and resources. The quality performance indicators is done by listing the quality attributes that determine quality performance. In this model, there are 8 quality dimensions and 16 of quality attributes. Quality evaluation is then carried out by comparing product performance and consumer expectations. Design improvement is done by analyzing the results of quality evaluation. Based on the analysis, there are 6 product attributes that need improvement including texture, color, suitability of product information, price suitability, ease of access and product popularity.

Understanding the water quality change of the Yilong Lake based on comprehensive assessment methods

To understand the water quality changes of the Yilong Lake and reveal the driving factors of water quality changes in different periods, in this study, based on 13 water quality parameters, the water quality of Yilong Lake from 2008 to 2018 was comprehensively evaluated by water quality health comprehensive assessment method (ETI) and water quality index method (WQI), and 6 key parameters were determined by WQI method to develop a more convenient WQImin comprehensive evaluation model. The results showed that: (1) Yilong Lake’s single-factor water quality evaluation result was inferior to category V, CODCr and TN had a greater impact on the water quality evaluation results; while the ETI and WQI evaluation methods show the water quality of Yilong Lake is at a moderate level (53.58 ± 7.46 and 0.53 ± 0.13). Among them, nutrients such as nitrogen and phosphorus have the greatest impact on WQI and ETI values. (2) The comprehensive evaluation method reveals that the water quality changes of Yilong Lake can be divided into two stages. Among them, the water quality of lakes declined from 2008 to 2013, and the main driving factors are the increase in industrial sewage discharge and the increase in pollution load caused by tourism development; and from 2014 to 2018, lake water quality showed an improving trend, and the spatial change shows that the water quality of the west is slightly better than the middle and the east, which is mainly due to the increase of the lake's self-purification ability, the implementation of various treatment measures, the water supplement project and the location of pollutant discharge; (3) Based on the WQI method, six key parameters of DO, CODMn, EC, TN, Hg, and Chla were determined and the Yilong Lake WQImin model was developed. The water quality evaluation results of the WQImin model considering the weight are more accurate, and the water quality change characteristics of Yilong Lake can be understood simply and quickly.

RETRACTED ARTICLE: Research on Construction Engineering Quality Management Based on Building Information Model and Computer Big Data Mining

Data mining-based scenarios in construction engineering management have become the mainstream, but in the actual application process, big data mining is still affected by many factors, and some construction enterprises have not realized the importance of big data mining for project management. In this paper, aiming at the problems existing in the quality evaluation of construction projects, this paper combines the analytic hierarchy process and entropy (entropy) to carry out joint weighting, and uses the fitting algorithm of support vector machine and BP neural network to form an expert decision-making model, which is applied to practical work. In view of the current construction engineering quality evaluation results are not objective and low credibility, quality of construction engineer model based on genetic algorithm is proposed. Finally, the genetic algorithm is used to optimize the parameters of the construction quality evaluation model, and the model is applied to the specific construction quality evaluation. The results show that the accuracy of the model is higher than that of other models, and the evaluation results of construction engineering quality are more credible and have strong practical application value.

An Investigation of the E-Services Quality provided by Kuwait Government Portal

The unlimited development and extensive use of ICT has helped governments around the world to innovate and improve public services through the advantages of egovernment services. First step of this study was an attempt to measure the quality of e-services provided by the usercentric Kuwait Government Online Portal through investigating the quality standards of e-government services and different quality dimensions of e-government services as identified in the literature. Post examining E-service quality models one model was selected and used to validate the quality of e-services provided by the Kuwait Government Online Portal. A survey was presented to 486 valid participants through an online questionnaire. The result of the survey in general showed a diverse quality results which was around the range of “Neutral”. This could be due to having a large number of diverse e-services provided by more than 60 government agencies all enclosed in the Kuwait Government Online Portal. The second step of this study was to validate the result from the survey through conducting a semi-structured interviews by the authors with three top management officials at the government entity responsible for implementing e-government program in Kuwait. The interviews have revealed interesting insights, namely the existence of strong presence of silo-mentality in government entities which could be the main cause for not achieving integrated e-services. Future work will include studying specific e-services and defining suitable categorization that helps in determining their quality. The model that was used in this study was based on high-level dimensions that needs to be broken down into subdiminutions that could contribute to increasing the accuracy of the results of e-service quality evaluation. In addition, measuring the effect of silo-mentality of the government over the quality of e-services in Kuwait is desirable.

Evaluation of college English classroom teaching quality dependent on triangular fuzzy number

With economic globalization and the informatization of social life, English has become a language extensively used around the globe. The research on the evaluation of English teaching quality is of crucial practical significance and theoretical value. Hence, student evaluation form for the college English classroom teaching quality that has been evaluated and has good reliability is used in this paper to expound the principles of the triangular fuzzy number evaluation method and the range method based on the analytic hierarchy process (AHP). Examples are used to analyze the differences between the two methods as well as their advantages and disadvantages. The comprehensive evaluation result of the teaching quality evaluation of a teacher by using the range method is excellent (85.500 points), and the comprehensive evaluation result by using the triangular fuzzy number method based on the analytic hierarchy process is good (64.818 points). The results show that the range method is better for the comprehensive evaluation of teachers' teaching quality. The statistical analysis results suggest that there are differences between the two methods in the evaluation of the classroom teaching quality in colleges and universities (t = 11.197, P < 0.0001). In the evaluation of the teaching quality by using the triangular fuzzy number evaluation method based on the analytic hierarchy process, the non-linear and fuzzy features of evaluation factors are taken into consideration comprehensively. The weight values of various evaluation indexes are calculated scientifically. The qualitative and quantitative evaluations are combined to obtain the evaluation result of the classroom teaching quality of teachers more objectively, which is of great significance in the practical teaching quality evaluation process.

Quality evaluation of online courses during COVID-19 pandemic based on integrated FCE-AHP method

After sudden outbreak of COVID-19 pandemic, the university campuses were closed and millions of university teachers and students had to shift teaching and learning activities from the classrooms to online courses in China. The COVID-19 pandemic undoubtedly brought significant negative effects to university education activities. How does COVID-19 influenced teaching quality and the degree of influences have been studied by many researches. However, the online course quality which is influences by COVID-19 pandemic was commonly evaluated qualitatively rather than quantitatively. In order to obtain quantitative evaluation results of online course quality during the pandemic period, the integrated FCE-AHP evaluation was applied. Based on real case of online courses, the influence factors of online course quality were divided into four first-level indicators and further subdivided into 14 second level indicators. The weight vectors of evaluation indicators were determined based on experts’ comments from the Teaching Affairs Committee and the fuzzy evaluation memberships were calculated based on questionnaire results of 2021 students. The evaluation results revealed that the integral performance of online courses is acceptable and the performances of students and hardware are relative weaker. Finally, some improvement measures were conducted to deal with difficulties encountered in online courses during COVID-19 pandemic period.

Health Management Quality Assessment Of Complex Communication System

In order to verify the quality of health management of communication system and determine the application of health management in the field of communication system, the quality evaluation method is used to verify the operation effect. According to the analysis of the main functions and components of complex communication system health management, the evaluation index system is constructed, and the steps of quantitative evaluation of the evaluation index system by grey analytic hierarchy process are elaborated in detail. Combined with an example, the feasibility and rationality of the model algorithm are verified. The example proves that the evaluation results of health management quality of complex communication system based on grey analytic hierarchy process are accurate and feasible, which can provide direction and basis for the development of health management in communication field.

Early mobilization on mortality of patients with mechanical ventilation in intensive care unit after discharge: a Meta-analysis

To evaluate the effect of early mobilization on mortality in intensive care unit (ICU) patients with mechanical ventilation after discharge by Meta-analysis. Databases including SinoMed, China National Knowledge Infrastructure (CNKI), Wanfang data, PubMed, the Cochrane Library, Web of Science, and Embase were searched from inception to September 17th, 2020, to collect randomized controlled trials (RCT) about early mobilization on mortality of patients with mechanical ventilation in ICU after discharge, the references included in the literature were traced. The control group was given routine care, the experimental group was given early mobilization on the basis of the control group, including passive or active mobilization on the bed, sitting on the bed, standing by the bed, transferring to the bedside chair and assisting walking. The literature screening, data extracting, and the bias risk assessment of included studies were conducted independently by two reviewers. Stata 12.0 software was then used to perform Meta-analysis. Funnel plot was used to test publication bias. A total of 10 RCT studies involving 1 323 patients were included, with 660 patients in the control group and 663 patients in the experimental group. The results of literature quality evaluation showed that 7 studies were grade A and 3 studies were grade B, indicating that the overall quality of included literatures was high. The Meta-analysis results showed that early mobilization did not increase the mortality of patients with mechanical ventilation in ICU after discharge [odds ratio (OR) = 0.92, 95% confidence interval (95%CI) was 0.75-1.13, P = 0.449]. Subgroup analysis results showed that early mobilization had a tendency to reduce the mortality of ICU patients with mechanical ventilation at 3, 6 and 12 months after discharge, but the difference was not statistically significant (3-month mortality: OR = 1.02, 95%CI was 0.74-1.40, P = 0.927; 6-month mortality: OR = 0.95, 95%CI was 0.70-1.27, P = 0.712; 12-month mortality: OR = 0.60, 95%CI was 0.33-1.10, P = 0.101). Funnel plot showed that the distribution of included literatures was not completely symmetrical, suggesting that publication bias might exist. Early mobilization does not increase the mortality of ICU patients with mechanical ventilation after discharge. Although it tends to have a favorable outcome in reducing mortality, and has a trend to reduce the mortality. However, due to the small number of included literatures, small sample size and differences in the specific implementation of early mobilization among various studies, a large number of high-quality RCT studies are still needed for further verification.

Deep Learning-Based Compression for Phase-Only Hologram

With the aid of rapid development in optical and display devices, Holography has become an emerging technology to represent 3D objects providing the most natural and realistic depth illusion to the users. To reproduce a light field of objects, a hologram records the interference patterns between the object and reference wavefields. Especially for computer-generated holograms, they contain vast amount of data and must be efficiently compressed for storage or transmission. Although several coding solutions, including standardized compression tools and their variations, have been tried in the literature, the coding efficiency is not satisfactory because holograms have completely different unique properties from those observed in natural images, whereas the legacy coding solutions are optimized for the latter. In this work, we propose a deep-learning based image compression network for phase-only holograms. The proposed network is trained in an end-to-end manner with the help of data augmentation technique and aims at minimizing the entropy of the input hologram. In comprehensive experiments, we demonstrate that our compression network shows the state-of-the-art coding performance that even surpasses the latest compression standard Versatile Video Coding by up to 39% in terms of BD-rate gain. Furthermore, we provide in-depth analysis for experimental results in both holographic and numerical reconstruction domains, such as individual performances of the test codecs, a performance comparison with different objective image fidelity metrics, and subjective quality evaluation results.

An Efficient and Secure Malicious User Detection Scheme Based on Reputation Mechanism for Mobile Crowdsensing VANET

With the increasing development of wireless communication technology and Vehicular Ad hoc Network (VANET), as well as the continuous popularization of various sensors, Mobile Crowdsensing (MCS) paradigm has been widely concerned in the field of transportation. As a currently popular data sensing way, it mainly relies on wireless sensing devices to complete large‐scale and complex sensing tasks. However, since vehicles are highly mobile in this scenario and the sensing system is open, that is, any vehicle equipped with sensing device can join the system, the credibility of all participating vehicles cannot be guaranteed. In addition, malicious users will upload false data in the sensing system, which makes the sensing data not meet the needs of the sensing tasks and will threaten traffic safety in some serious cases. There are many solutions to the above problems, such as cryptography, incentive mechanism, and reputation mechanisms. Unfortunately, although these schemes guaranteed the credibility of users, they did not give much thought to the reliability of data. In addition, some schemes brought a lot of overhead, some used a centralized server management architecture, and some were not suitable for the scenario of VANET. Therefore, this paper firstly proposes the MCS‐VANET architecture‐based blockchain, which consists of participating vehicles (PVs), road side units (RSUs), cloud server (CS), and the blockchain (BC), and then designs a malicious user detection scheme composed of three phases. In the data collecting phase, to reduce the data uploading overhead, data aggregation and machine learning technologies are combined by fully considering the historical reputation value of PVs, and the proportion of data uploading is determined based on the historical data quality evaluation result of PVs. In the data quality evaluation phase, a new reputation computational model is proposed to effectively evaluate the sensing data, which contains four indicators: the reputation history of PVs, the data unbiasedness, the leadership of PVs, and the spatial force of PVs. In the reputation updating phase, to achieve the effective change of reputation values, the logistic model function curve is introduced and the result of the reputation updating is stored in the blockchain for security publicity. Finally, on real datasets, the feasibility and effectiveness of our proposed scheme are demonstrated through the experimental simulation and security analysis. Compared with existing schemes, the proposed scheme not only reduces the cost of data uploading but also has better performance.

Research on Marine Water Quality Evaluation Model Based on Improved Harmony Search Algorithm by Gaussian Disturbance to Optimize Takagi-Sugeno Fuzzy Neural Network

Shen, G., 2020. Research on marine water quality evaluation model based on improved harmony search algorithm by Gaussian disturbance to optimize Takagi-Sugeno fuzzy neural network. In: Liu, X. and Zhao, L. (eds.), Today's Modern Coastal Society: Technical and Sociological Aspects of Coastal Research. Journal of Coastal Research, Special Issue No. 111, pp. 283–287. Coconut Creek (Florida), ISSN 0749-0208.Marine water quality is affected by many factors and is difficult to evaluate accurately. An improved harmony search algorithm based on Gaussian disturbance (GDHS) is proposed to optimize the Takagi-Sugeno (T-S) fuzzy neural network (TSFNN) model of marine water quality evaluation. First, the basic harmony search algorithm is improved by the Gaussian disturbance global optimal harmony strategy and dynamic adjustment parameters. Second, the parameters of the T-S fuzzy neural network are optimized by GDHS to improve the stability and global convergence speed of the TSFNN. Finally, China's marine water quality standards and the actual conditions of the marine area to which the experimental data belong are considered, five indicators are selected to construct a neural network, and the water quality evaluation results of the data of 10 monitoring stations in the eastern waters of Qingdao show that the smaller the evaluation error of the GDHS-TSFNN model, the higher the accuracy.

An investigation into the hydrochemistry, quality and risk to human health of groundwater in the central region of Shandong Province, North China

This study aimed to characterize the hydrochemistry and risk to human health of groundwater in the central region of Shandong Province (CRSP) as well as to investigate the factors controlling groundwater quality. Methods applied included traditional hydrochemical analysis methods, the water quality index (WQI) and a health risk model. The results showed that groundwater of the CRSP is weakly alkaline, with average concentrations of total dissolved solids (TDS) over the wet and dry seasons of 666.2 mg·L−1 and 653.9 mg·L−1, respectively. The southeast part of the study region and Laiwu, Xintai and Taian showed higher concentrations of TDS and NO3−. The dominant hydrochemical types of groundwater in the CRSP were identified to be HCO3–Ca·Mg and SO4·Cl–Ca·Mg. The main factors influencing the hydrochemical composition of groundwater in CRSP were identified to include rock weathering, cation exchange and anthropogenic inputs, and the main source of nitrate in groundwater was identified as agricultural activities. The results of the water quality evaluation showed that most groundwater samples of the CRSP were suitable for drinking and agricultural irrigation. However, the non-carcinogenic risk index (HQ) values calculated for groundwater of the CRSP over both the dry and wet seasons indicated unacceptable risk to the health of both children and adults. The contradicting results between the water quality evaluation and health risk assessment were due to differences in the water quality standard limits used. It is suggested that permissible limits of water quality variables be adjusted according to local conditions and that a water quality evaluation system be established that is suitable for Chinese residents, so as to ensure the sustainable management of groundwater and the safety of drinking water.

Evaluation and Treatment Analysis of Air Quality Including Particulate Pollutants: A Case Study of Shandong Province, China.

At present, China’s air pollution and its treatment effect are issues of general concern in the academic circles. Based on the analysis of the development stages of air pollution in China and the development history of China’s air quality standards, we selected 17 cities of Shandong Province, China as the research objects. By expanding China’s existing Air Quality Index System, the air quality of six major pollutants including PM2.5 and PM10 in 17 cities from February 2017 to January 2020 is comprehensively evaluated. Then, with a forecast model, the air quality of the above cities in the absence of air pollution control policies since June 2018 was simulated. The results of the error test show that the model has a maximum error of 4.67% when simulating monthly assessment scores, and the maximum mean error of the four months is 3.17%. Through the comparison between the simulation results and the real evaluation results of air quality, we found that since June 2018, the air pollution control policies of six cities have achieved more than 10% improvement, while the air quality of the other 11 cities declined. The different characteristics of pollutants and the implementation of governance policies are perhaps the main reasons for the above differences. Finally, policy recommendations for the future air pollution control in Shandong and China were provided.

Spatial Assessment of Groundwater Quality and Health Risk of Nitrogen Pollution for Shallow Groundwater Aquifer around Fuyang City, China

Prolonged exposure to intensive and extensive agricultural and industrial activities is leading to an increased deterioration of groundwater quality, especially nitrogen pollution in shallow groundwater aquifers. This study was carried out using the fuzzy comprehensive method to assess the overall groundwater quality, and the noncarcinogenic risks were estimated using the human health risk assessment method recommended by the United States Environmental Protection Agency (USEPA) via drinking water intake pathways around Fuyang City, China. A total of 34 samples were collected from shallow groundwater private wells, and 16 parameters were analyzed for each groundwater sample. The evaluation results of groundwater quality show 14.7% of groundwater samples classified as poor and very poor quality, and NO3-N, TH, TDS, Fe3+, and Mn are of high potential to affect the quality of potable drinking water. These are mainly derived from anthropogenic pollutants, predominantly due to uncontrolled agricultural and industrial activities, as well as some natural processes. The noncarcinogenic risk of nitrate indicates that 8.82% of groundwater samples surpass the permissible limit recommended by the USEPA for both adults and children. This study may provide the local authority with insights into making scientific decisions for exploiting groundwater in a sustainable manner so as to protect public health.

Cross-border e-commerce platform for commodity automatic pricing model based on deep learning

With the innovation of information technology and the rise of the Internet economy, cross-border e-commerce has grown up to be an important means and strategy for enterprises to seek rapid development. This paper proposes a model that fuses CNN (Convolutional Neural Network) and attention mechanism to encode image features, and selects the image features of commodities. A 5-layer CNN without a fully connected layer is constructed to initially extract image features, and then a set of attention mechanism strategies is designed. This strategy is used to select the image features that have the greatest impact when generating words at different times. Considering the characteristics of quantitative indicators of the pricing model, this paper transforms this evaluation process of consumers into price perception. Corresponding mathematical model is set up to improve and expand the original probability unit model. The consumer selection model is utilized to obtain a prediction of product market share, and a nonlinear constraint programming is established to determine the optimal price. The strategy takes into account the changed market shares of consumer characteristics and product quality evaluation results. In the two-layer hybrid channel supply chain model, retailers and manufacturers all use third-party platforms when they achieve maximum benefits; when price cross-elasticity coefficients and third-party platform usage fees are independent variables of influencing factors, retailers are dispersed on CNN to get the most profit under the pricing strategy. Similarly, when the unit product tax difference is the independent variable of the influencing factors, the manufacturer is also the most profitable under the CNN decentralized pricing strategy.

Application research of entropy weight-based grey systematic theory in quality evaluation of Angelicae Sinensis Radix slices

In order to discuss the "entropy weight method" for weighting various indicators in the comprehensive evaluation of Angelicae Sinensis Radix slices(ASR), the quality of ASR was comprehensively evaluated by entropy weight-based gray systematic theory and cluster analysis. In this study, the contents of ferulic acid, volatile oil, polysaccharide, alcohol extract, water extract, moisture, total ash and acid-insoluble ash in 44 batches of ASR from different sources were determined. The entropy weight method was used for objective weighting. With relative correlation(r_i) as a measure, a multi-index comprehensive evaluation model was constructed for the quality of ASR. The results showed that the relative correlation value of 44 batches of ASR ranged from 0.301 9 to 0.662 9. There were certain differences in the quality of ASR from different sources. The ASR S1-S8, traceable and standardized in processing techno-logy, showed a high relative correlation degree and high quality ranking, indicating that the implementation of systemic management of the production chain of Chinese herbal pieces was beneficial to the quality control of ASR. The quality evaluation results of 44 batches of ASR were consistent with those of traditional geo-authentic habitats for ASR and the mainstream varieties of ASR on market, and basically consistent with the results of cluster analysis. This study suggests that the gray systematic theory based on the entropy weighting method can be used for the quality evaluation of ASR. The objective weighting of the entropy weight method improves the reliability of the gray correlation method and the scientificity of ASR quality evaluation.

Quality Evaluation of Ecological Restoration of Urban Water Pollution based on Analytic Hierarchy Process

Ye, Q.Q., 2020. Quality evaluation of ecological restoration of urban water pollution based on analytic hierarchy process. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 10–13. Coconut Creek (Florida), ISSN 0749-0208.In view of the problem that the traditional methods cannot comprehensively select the indicators of urban water pollution ecological restoration, which leads to the inaccurate evaluation results of urban water pollution ecological restoration quality, this paper proposes the quality evaluation of urban water pollution ecological restoration based on AHP. Based on the analysis of the current situation of urban water pollution, the comprehensive evaluation index system of urban water pollution ecological restoration effect is constructed based on the multi quantitative method of AHP, and different types of urban water pollution ecological restoration indicators are obtained. The comprehensive evaluation model of AHP is given, the judgment matrix is constructed, and the weight of evaluation index is determined by single ranking of different levels. The fuzzy comprehensive evaluation standard of urban water pollution ecological restoration quality is designed to complete the evaluation of urban water pollution ecological restoration quality. Taking the water pollution ecological restoration of a city as an example, the analytic hierarchy process (AHP) is used to evaluate the quality of water pollution ecological restoration. The weight of different indicators on the ecological restoration of water pollution can be accurately obtained, and the accurate evaluation results of urban water pollution ecological restoration quality can be obtained.

Evaluating the Characteristics, Reporting and Methodological Quality of Systematic Reviews of Acupuncture for Low Back Pain by Using the Veritas Plot.

ObjectiveTo evaluate systematic reviews (SRs) of acupuncture for low back pain (LBP) in terms of characteristics, reporting and methodological quality using a Veritas plot and to explore factors that may be associated with methodological quality and reporting quality.Study Design and SettingWe searched 8 electronic bibliographic databases to find all SRs, and we evaluated the SRs’ quality in 6 dimensions, including publication year, design type, homogeneity, risk of publication bias, methodological quality by Assessment of Multiple Systematic Reviews (AMSTAR) 2 and reporting quality by Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Excel 2010 and Adobe Illustrator CC were used to draw and optimize Veritas plots. Exploratory analysis was done using SPSS software version 23.0 to explore factors related to AMSTAR-2 and PRISMA scores. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) evidence quality evaluation tool was used to grade all the outcome indicators in the included literature.ResultsWe included 19 SRs in the analysis. Literature quality rank scores ranged from 9.67 to 17.00, with an average score of 13.18 ± 2.35. The average score of AMSTAR-2 was 7.47, and the average score of PRISMA was 18.47. Overall, the main issues were research strategies, inclusion and exclusion criteria, publication bias, and registration in PROSPERO. The results of exploratory analysis showed that duplication of literature selected and appropriate tools to assess the risk of bias were related to the AMSTAR-2 score, and the summary of evidence was related to the PRISMA score. The GRADE quality evaluation results showed mainly low quality.ConclusionThe quality of SRs on acupuncture for low back pain should be improved, mainly by strengthening the methodological quality and reporting quality. The Veritas plot is an effective graphical evaluation method that is worth popularizing.

Image quality of 4D in-treatment CBCT acquired during lung SBRT using FFF beam: a phantom study

BackgroundRotational beam delivery enables concurrent acquisition of cone-beam CT (CBCT), thereby facilitating further geometric verification of patient setup during radiation treatment. However, it is challenging to acquire CBCT during stereotactic body radiation therapy (SBRT) using flattening-filter free X-ray beams, in which a high radiation dose is delivered. This study presents quantitative evaluation results of the image quality in four-dimensional (4D) in-treatment CBCT acquired during SBRT delivery.MethodsThe impact of megavoltage (MV) scatter and acquisition parameters on the image quality was evaluated using Catphan 503 and XSight lung tracking phantoms. The in-treatment CBCT images of the phantoms were acquired while delivering 16 SBRT plans. The uniformity, contrast, and contrast-to-noise ratio (CNR) of the in-treatment CBCT images were calculated and compared to those of CBCT images acquired without SBRT delivery. Furthermore, the localizing accuracy of the moving target in the XSight lung phantom was evaluated for 10 respiratory phases.ResultsThe CNR of the 3D-reconstucted Catphan CBCT images was reduced from 6.3 to 2.6 due to the effect of MV treatment scatter. Both for the Catphan and XSight phantoms, the CBCT image quality was affected by the tube current and monitor units (MUs) of the treatment plan. The lung target in the XSight tracking phantom was most visible for extreme phases; the mean CNRs of the lung target in the in-treatment CBCT images (with 40 mA tube current) across the SBRT plans were 3.2 for the end-of-exhalation phase and 3.0 for the end-of-inhalation phase. The lung target was localized with sub-millimeter accuracy for the extreme respiratory phases.ConclusionsFull-arc acquisition with an increased tube current (e.g. 40 mA) is recommended to compensate for degradation in the CBCT image quality due to unflattened MV beam scatter. Acquiring in-treatment CBCT with a high-MU treatment beam is also suggested to improve the resulting CBCT image quality.

QUALITY INSPECTION OF SATELLITE IMAGERY BLOCK ADJUSTMENT WITHOUT GCP

Abstract. The current status of insufficient research on production technology and quality inspection methods for uncontrolled mapping of block adjustment results for global project. This paper proposes a set of quality inspection process and technical methods for large-scale production, lack of field checkpoints and difficult to verify in the field based on the analysis of the characteristics of the results: First, analyze the quality elements and inspection contents to be inspected, determine the inspection methods for different inspection contents; Then, extract items that can be automatically checked or need to be verified the production process data, establish inspection rules, implement batch automatic inspection and production data verification for some check items; study the inspection methods for the remaining items and implement human-computer interaction check. Finally, 4 test-fields were checked and the results showed that the technical route proposed in this paper is feasible, and the quality evaluation results are objective and reliable.