Quality Evaluation Method Research Articles

Fruit Export and Advisory App using Deep Learning

Because of the agriculture sector’s vital role in global food production and sustainability, fruit quality is critical. Traditional methods of fruit quality evaluation are time consuming and subjective, resulting in inefficiencies in the supply chain and significant food loss. Our research provides a novel solution. By evaluating fruit photos, our algorithm detects fresh versus sub optimal quality fruits using cutting-edge machine learning techniques. Our model correctly identifies ripeness, flaws, and deformities across multiple fruit varieties using deep learning with CNNs at its heart and transfer learning. Implementing this technology reduces food waste and promotes sustainable agriculture by streamlining fruit quality testing. It helps farmers, distributors, and consumers by guaranteeing that only the best fruits make it to market. Our study provides a cost effective, environmentally friendly, and long-term solution

The Clinical Value of the MAR+ Metal Artifact Reduction Algorithm for Postoperative Assessment of Lumbar Internal Fixation.

With the widespread use of lumbar pedicle screws for internal fixation, the morphology of the screws and the surrounding tissues should be evaluated. The metal artifact reduction (MAR) technique can reduce the artifacts caused by pedicle screws, improve the quality of computed tomography (CT) images after pedicle fixation, and provide more imaging information to the clinic. To explore whether the MAR+ method, a projection-based algorithm for correcting metal artifacts through multiple iterative operations, can reduce metal artifacts and have an impact on the structure of the surrounding metal. A total of 57 patients who underwent lumbar spine CT examination after lumbar internal fixation from January to December 2023 in our hospital were retrospectively enrolled. The CT images were reconstructed using MAR+ and non-MAR+ techniques and were subdivided into MAR+ and non-MAR+ groups. The CT number (in Hounsfield units) and the SD noise values of the spinal canal, vertebral body, psoas major muscle, and adjacent fat were measured in the 2 groups of CT images, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The subjective score was evaluated by two diagnostic radiologists using a double-blind method for image quality evaluation of the MAR+ group and the non-MAR+ group, and the image quality was classified on a 5-point scale. The rank-sum test was utilized to compare the subjective and objective scores of the 2 groups. The SD values of the spinal canal (Z=-4.12, P<0.01), vertebral body (Z=-3.81, P<0.01), and psoas major muscle (Z=-3.87, P<0.01) in the MAR+ group were significantly lower than those in the non-MAR+ group (P<0.05). However, the SD values of the adjacent fat (Z=-2.03, P=0.42) in the MAR+ group, although smaller than those in the non-MAR+ group, were not statistically significant. The CNR values of vertebral canal (Z=-2.67, P=0.008) and fat (Z=-2.60, P=0.009) were higher in the MAR+ group than in the non-MAR+ group, whereas the CNR values of the vertebral body (Z=-6.74, P<0.01) in the MAR+ group were smaller than those in the non-MAR+ group, and the difference of all of them was statistically significant (P<0.05). Furthermore, for both CT and SNR values, the MAR group's values were all less than those of the non-MAR group and were statistically significant (P<0.05). The subjective scores of the measurement points were all higher in the MAR+ group than in the non-MAR+ group. The MAR+ technique has a noise reduction effect on different tissues and artifacts are significantly reduced. Although the artifacts caused by metal screws were not completely eliminated, the MAR+ technique was able to reduce the interference of artifacts in the diagnosis of CT images, thus improving their diagnostic quality.

Double weighted combat data quality evaluation method based on CVF optimized FAHP

During multi-agent combat simulation exercises, accurately assessing the quality of collected combat data is a critical step. Addressing the current issue of low accuracy in combat data quality evaluation, which fails to effectively support simulation exercises, this paper proposes a Double-Weighted FAHP optimized by CVF (comparative value function) method for assessing combat data quality. First, a three-tiered evaluation framework for combat data quality indicators is established, with threshold values determined for each indicator. The weights obtained from the FAHP method are optimized using the Satisfaction Consistency Approach to derive the first-tier weights. Subsequently, the CVF is constructed to obtain the second-tier weights. The double-weighted evaluation theory combines these two tiers of weights to produce the final assessment. Analysis of the experimental results indicates that the proposed method reduces the mean squared error to 5.35 when compared to results obtained using FAHP, interval intuitionistic fuzzy methods, and artificial neural networks, bringing it closer to actual standard values. This method provides a more accurate evaluation of the quality of multi-agent combat data, offering robust data support for future combat simulation exercises and military drills.

A New Method of Quality Evaluation for Electromagnet Products Based on SOM‐Kmeans and Enhanced TODIM

A New Method of Quality Evaluation for Electromagnet Products Based on SOM‐Kmeans and Enhanced TODIM

Harmonized technical standard test methods for quality evaluation of medical fluorescence endoscopic imaging systems

Fluorescence endoscopy technology utilizes a light source of a specific wavelength to excite the fluorescence signals of biological tissues. This capability is extremely valuable for the early detection and precise diagnosis of pathological changes. Identifying a suitable experimental approach and metric for objectively and quantitatively assessing the imaging quality of fluorescence endoscopy is imperative to enhance the image evaluation criteria of fluorescence imaging technology. In this study, we propose a new set of standards for fluorescence endoscopy technology to evaluate the optical performance and image quality of fluorescence imaging objectively and quantitatively. This comprehensive set of standards encompasses fluorescence test models and imaging quality assessment protocols to ensure that the performance of fluorescence endoscopy systems meets the required standards. In addition, it aims to enhance the accuracy and uniformity of the results by standardizing testing procedures. The formulation of pivotal metrics and testing methodologies is anticipated to facilitate direct quantitative comparisons of the performance of fluorescence endoscopy devices. This advancement is expected to foster the harmonization of clinical and preclinical evaluations using fluorescence endoscopy imaging systems, thereby improving diagnostic precision and efficiency.

Evaluation method of service quality of college students' innovation and entrepreneurship education based on AHP-DEA method

Evaluation method of service quality of college students' innovation and entrepreneurship education based on AHP-DEA method

An immersive subjective evaluation method for the sound quality in civil aircraft cabins

An immersive subjective evaluation method for the sound quality in civil aircraft cabins

Research on objective evaluation methods for air conditioning sound quality

Research on objective evaluation methods for air conditioning sound quality

An evaluation method of government digital service quality based on big data

An evaluation method of government digital service quality based on big data

Evaluation method of innovation and entrepreneurship education quality in colleges and universities based on entropy weight method

Evaluation method of innovation and entrepreneurship education quality in colleges and universities based on entropy weight method

Quality Evaluation Index System and Evaluation Method for Pine Forest Stands in Guangxi

Quality Evaluation Index System and Evaluation Method for Pine Forest Stands in Guangxi

Comprehensive Quality Evaluation of Traditional Chinese Medicine Guanxinjing Capsule Based on Fingerprint and Multicomponent Simultaneous Quantitative Method.

A novel dual-wavelength ultrahigh performance liquid chromatography (UHPLC) fingerprint was established, 56 common peaks were confirmed and attributed to the source of the medicinal materials, and 13 chromatographic peaks of them were identified by UHPLC quadrupole time-of-flight (Q-TOF)-MS/MS and UHPLC-UV method. Furthermore, a simple and sensitive HPLC-quadrupole trap (Q-TRAP)-MS/MS was developed for the simultaneous determination of 16 active components with electrospray ionization (ESI) source switching between positive and negative modes in a single run. The above two methods were successfully applied for the quality evaluation of Guanxinjing capsule (GXJC). Finally, statistical analysis including principal component analysis (PCA), hierarchical cluster analysis (HCA), and orthogonal partial least squares discriminate analysis (OPLS-DA) were applied, and 13 variables with great contribution to different groups of samples were screened. This study not only provides a rapid, accurate, and comprehensive qualitative and quantitative method for quality evaluation of GXJC but it also provides a reference workflow for the other traditional Chinese medicines.

Research on the Relationship Between Urban Visual Quality and Students’ Emotional Experience Driven by Multimodal Data: A Case Study of Beijing Olympic Park Museum Group

The technological leap in the digital age has triggered a higher demand for emotional experiences. Since vision has long been recognized as the most important source of information for people to perceive the city, the visual characteristics of the urban built environment have an important impact on the emotional experience it creates. This study takes the facades and external environments of the representative urban public building category, museums, as the research objects, to explore how different types of built environment elements that make up the museum’s facade and surrounding environment affect the people’s emotional experience by affecting the urban visual quality. Tobii Pro Fusion devices and emotion scales are used for the collection of multimodal data. A total of 298 participants aged between 20 and 25 were recruited to participate in the experiment voluntarily and 229 valid data were finally obtained. The results show that different types of museum facades and external environmental elements have different effects on visual quality and people’s emotional experience: (1) Interactive elements show the most significant impact on visual quality and emotional experience. (2) The impact of artificial elements on visual quality is related to their size and spatial composition on the museum facade. When artificial elements have uniqueness, regionality, and symbolism associated with the museum, they are more likely to trigger people’s emotional experiences. (3) Visual quality is significantly correlated with people’s emotional experience through both preconscious and conscious emotional cognition. The results reveal the impact of different types and characteristics of built environment elements on the visual quality of the urban environment and proves the important role of visual quality in students’ emotional experience, further illustrating that designing and creating a good visual environment is conducive to promoting a humanistic urban environment. Meanwhile, this study also promotes a method of urban visual quality research and evaluation from an emotional perspective, providing a more scientific and objective way for the intervention of “emotions” in built environment research.

Quality Markers of Fufang Shenqi Oral Liquid Based on Integrated Fingerprint Analysis, Chemical Pattern Recognition, and Quantification.

Fufang Shenqi Oral Liquid (FFSQOL) is an important Chinese medicine compound preparation with a wide range of clinical applications, which is mainly used to regulate immune function, improve cardiovascular function, and have anti-inflammatory and antibacterial effects. At present, it is of great importance to establish the quality evaluation method of FFSQOL and to investigate its quality markers (Q-markers). The aim of this study is to establish a quality evaluation method for FFSQOL and screen its Q-markers to provide a scientific basis for its quality control. Fourteen batches of FFSQOL were subjected to high-performance liquid chromatography (HPLC) fingerprint and similarity analysis. The components of FFSQOL were identified, and their content was determined. This was combined with cluster analysis (CA) and principal component analysis (PCA) to determine the Q-markers of FFSQOL. In this study, an HPLC fingerprint was established for 14 batches of FFSQOL, identifying 12 common peaks and six major components. Four components were identified as stable and reproducible: gallic acid (504.94 ~ 1219.04 μg/mL), caffeic acid (452.15 ~ 783.01 μg/mL), 7-O-glucoside (1097.72 ~ 2440.41 μg/mL), and formononetin (176.2 ~ 177.51 μg/mL). Quality evaluation of the 14 batches was conducted using chemical pattern recognition analysis. CA results indicated two distinct groups, and PCA revealed that principal components 1 and 2 were the main factors influencing batch differences. A combination of HPLC fingerprint, content determination results, and chemical pattern recognition analysis was employed to identify Q-markers for FFSQOL. The markers identified were gallic acid, caffeic acid, calycosin 7-O-glucoside, and formononetin. In this study, a quality evaluation method for FFSQOL was established through the implementation of fingerprint, content determination, and chemical pattern recognition analysis, resulting in the identification of four Q-Markers of FFSQOL, which laid the foundation for the formulation of FFSQOL quality standards.

A Review of the Current Status and Prospects of Improving Indoor Environment for Lightweight Buildings in High-Altitude Cold Regions

Lightweight structures, characterized by rapid assembly, are vital for creating habitats in outdoor environments, but their implementation in high-plateau cold regions encounters significant challenges in heating and ventilation. This paper systematically introduces the environmental characteristics and reviews the demands and primary influencing factors of indoor environments in these regions. The advantages and limitations of underground lightweight construction are also discussed. Current research indicates that evaluation methods for air quality in high-altitude cold regions require further development. Reducing building heat loss and minimizing cold air infiltration can enhance indoor environments and lower energy consumption. However, it is essential to establish effective ventilation strategies to prevent the accumulation of air pollutants. Then, potential passive ventilation improvement measures suitable for the environmental characteristics of high-cold plateaus are outlined. The application potential and possible limitations of these measures are summarized, providing references for future research. Finally, the main research methods for ventilation and heating within building interiors are organized and discussed. Findings indicate that computational fluid dynamics models are predominantly used, but they demonstrate low efficiency and high resource consumption for medium- to large-scale applications. Integrating these models with network models can achieve a balance of high computational accuracy and efficiency.

HPLC Fingerprint Combined With Chemometrics and Multicomponent Content Determination for Quality Evaluation and Control of Huangma Tincture.

Huangma Tincture (HMT) is a Chinese patent medicine with a history of clinical use for more than 60 years, widely used for treating dermal chronic ulcer such as diabetic foot ulcer. However, the overall quality evaluation and control method of HMT has not yet been researched. The aim of this study is to establish a comprehensive quality evaluation and control method for HMT based on high-performance liquid chromatography (HPLC) fingerprint, chemometrics, and multicomponent content determination. Establishing chemical fingerprint of HMT and carrying out similarity analysis comprehensively reflect the consistency of the formulation in terms of chemical composition. Chemometrics analyses, including hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA), were performed to identify components crucial to quality differences. The content of five potential bioactive ingredients (brucine, strychnine, jatrorrhizine, coptisine, and berberine hydrochloride) was determined as a supplementary quality control measure. HPLC fingerprint of HMT with similarity index > 0.990 was established, in which five common compounds (brucine, strychnine, jatrorrhizine, coptisine, and berberine hydrochloride) were identified. HCA, PCA, and OPLS-DA results, validated through 200 permutation tests, were basically consistent. The contents of brucine, strychnine, jatrorrhizine, coptisine, and berberine hydrochloride in 20 batches of HMT samples were 0.2088-0.5556, 0.2599-0.9868, 0.1358-0.2092, 0.2634-0.6843, and 1.8301-2.7826 mg/mL, respectively. HPLC fingerprint combined with chemometrics and multicomponent content determination considering both effect and toxicity provides a robust method for the comprehensive quality evaluation and control of HMT.

Evaluating the water quality of the rice–fish co-culture pattern based on the modified NSF water quality index model

The rice–fish co-culture pattern, a sustainable agricultural production method, plays a significant role in enhancing farmland ecological and economic benefits. However, few studies have evaluated the water quality of this system using the water quality index (WQI). In this study, improvements were made to the United States National Sanitation Foundation WQI (NSFWQI), including indicator selection, weight calculation, and sub-indexing, using principal component analysis (PCA), a minimum data set (MDS), linear function equations, and a comprehensive water quality assessment of the double-cropping rice–fish (DRF) co-culture and (DR) rice patterns. The results showed that using PCA; pH, dissolved oxygen (DO), ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), and the Shannon–Wiener index were selected from 11 water quality indicators to construct the MDS for WQI calculation. Based on the WQI results, the DRF had a negative impact on water quality, with the Shannon–Wiener index the greatest contributor to the WQI (22.9 %), consistently ranging between 1 and 3. Although total phosphorus (TP) and chemical oxygen demand (COD) were not included in the MDS for the WQI calculation, their significant increase during the late rice season in the DRF indicated water quality deterioration, further validating the accuracy of the improved NSFWQI. The improved NSFWQI model provides a more objective analysis of water quality under the rice–fish co-culture pattern. Compared with existing water quality evaluation methods, this approach offers advantages such as comprehensiveness, low cost, and standardization, and presents an effective alternative for water quality assessment.

Dynamic response and tension estimation of stay cables with disturbed images acquired from vision sensors

ABSTRACT This study introduces a novel approach to measure cable responses of such bridges using a vision sensor comprising a digital camcorder mounted on a tripod. Prioritizing simplicity and efficiency, this setup requires minimal equipment. The sensor is strategically positioned to ensure the target cable remains within the camcorder’s field of view. However, operational bridge imagery is frequently disturbed by vehicular traffic, leading to defocusing and blurring due to the camcorder’s automatic focus adjustments. These disturbances complicate the identification of reference points essential for accurate cable response measurements, potentially skewing results. To address this, we apply an image quality evaluation method to distinguish reference points from disturbed images, mitigating the impact of these disturbances on measurement accuracy. We evaluated the method’s effectiveness in estimating cable tension under disturbances by capturing images of an operational cable-stayed bridge experiencing ambient vibrations. Cable tension estimations were derived from the analysed responses using the vibration method and validated against data from a long-term monitoring accelerometer. This comparison highlights the potential of the proposed vision sensor method to enhance the accuracy of cable tension measurements in cable-stayed bridges, even in the presence of disturbed images.

Applications and Challenges of Protein Quality Assessment in Food

As a key nutrient to maintain normal physiological functions of the human body, protein plays an increasingly important role in people's pursuit of a healthy life. With the growing demand for healthy dietary standards, the evaluation of protein quality in food has become particularly critical, providing a scientific basis for the innovation and development of healthy foods. Given the diversity of protein sources, fluctuations in content, and the complexity of amino acid composition, it is crucial to choose appropriate evaluation methods to accurately analyze the protein quality in food. This article deeply explores the protein quality evaluation methods widely used internationally, with a particular focus on the two evaluation systems of digestible amino acid score (DIAAS) and protein digestibility corrected amino acid score (PDCAAS). This article analyzes in detail the application scope, advantages, and challenges that may be encountered in practical applications of these two methods, aiming to provide a solid theoretical support for the development of high-quality protein foods.

Research on SAR image quality evaluation method based on improved harris hawk optimization algorithm and XGBoost

Synthetic aperture radar (SAR) is crucial for military reconnaissance and remote sensing, but image quality can be affected by various factors, impacting target detection performance. Thus, pre-evaluation of SAR image quality is essential to filter out poor-quality images, optimize resource allocation, and enhance detection accuracy and efficiency. This paper proposes a comprehensive SAR image quality evaluation method combining objective and subjective approaches. Specifically, the processes encompassing the generation of a series of disturbed SAR images on the SAR ship detection dataset (SSDD), the calculation of various objective quality indicators for those images, and the assignment of a subjective quality label to each image through subjective evaluation. Based on the dataset constructed by the above evaluation methods, the IHHO-XGBoost model was developed. This model uses an improved harris hawk optimization (IHHO) algorithm to optimize extreme gradient boosting (XGBoost) hyperparameters. The IHHO algorithm effectively alleviates the problem of getting trapped in local optima by improving the escape energy calculation strategy and integrating the average difference evolution mechanism while maintaining the diversity of the population, showing significant advantages over the traditional HHO algorithm. Comparative experiments demonstrate the model’s superiority in SAR image quality evaluation. This study validates the scientificity and practicability of the proposed method, offering new tools for SAR image quality research.