Typical Evaluation Methods Research Articles

A novel spectrogram visual security encryption algorithm based on block compressed sensing and five-dimensional chaotic system

Based on block compressed sensing theory, combined with a five-dimensional chaotic system, we propose and analyze a novel spectrogram visual security encryption algorithm. This research is devoted to solving the compression, encryption and steganography problems of spectrograms involving large data volumes and high complexity. First, the discrete wavelet transform is applied to the spectrogram to generate the coefficient matrix. Then, block compressed sensing is applied to compress and preencrypt the spectrogram. Second, we design a new five-dimensional chaotic system. Then, several typical evaluation methods, such as the phase diagram, Lyapunov exponent, bifurcation diagram and sample entropy, are applied to deeply analyze the chaotic behavior and dynamic performance of the system. Moreover, the corresponding Simulink model has been built, which proves the realizability of the chaotic system. Importantly, the measurement matrix required for compressed sensing is constructed by the chaotic sequence. Third, dynamic Josephus scrambling and annular diffusion are performed on the secret image to obtain the cipher image. Finally, an improved least significant bit embedding method and alpha channel synchronous embedding are designed to obtain a steganographic image with visual security properties. To make the initial keys of each image completely different from other images, the required keys are produced using the SHA-256 algorithm. The experimental results confirm that the visual security cryptosystem designed in this study has better compression performance, visual security and reconstruction quality. Furthermore, it is able to effectively defend against a variety of conventional attack methods, such as statistical attacks and entropy attacks.

Development of a Machine Learning-Based Screening Method for Thyroid Nodules Classification by Solving the Imbalance Challenge in Thyroid Nodules Data.

This study aims to show the impact of imbalanced data and the typical evaluation methods in developing and misleading assessments of machine learning-based models for preoperative thyroid nodules screening. A retrospective study. The ultrasonography features for 431 thyroid nodules cases were extracted from medical records of 313 patients in Babol, Iran. Since thyroid nodules are commonly benign, the relevant data are usually unbalanced in classes. It can lead to the bias of learning models toward the majority class. To solve it, a hybrid resampling method called the Smote-was used to creating balance data. Following that, the support vector classification (SVC) algorithm was trained by balance and unbalanced datasets as Models 2 and 3, respectively, in Python language programming. Their performance was then compared with the logistic regression model as Model 1 that fitted traditionally. The prevalence of malignant nodules was obtained at 14% (n = 61). In addition, 87% of the patients in this study were women. However, there was no difference in the prevalence of malignancy for gender. Furthermore, the accuracy, area under the curve, and geometric mean values were estimated at 92.1%, 93.2%, and 76.8% for Model 1, 91.3%, 93%, and 77.6% for Model 2, and finally, 91%, 92.6% and 84.2% for Model 3, respectively. Similarly, the results identified Micro calcification, Taller than wide shape, as well as lack of ISO and hyperechogenicity features as the most effective malignant variables. Paying attention to data challenges, such as data imbalances, and using proper criteria measures can improve the performance of machine learning models for preoperative thyroid nodules screening.

Numerical study on flow and heat transfer characteristics of a novel Tesla valve with improved evaluation method

Tesla valve is check valve with no-moving-part, which cannot completely suppress reverse flow but has better reliability and flexibility than check valve with moving-part. Diodicity is most traditional and typical evaluation method used to evaluate the performance of Tesla valve. However, Diodicity decreases with increase of inlet/outlet section length, which fails to normatively evaluate performance of different Tesla valves. Therefore, standardized evaluation method for Tesla valve is conducive to its further application. In this paper, two improved parameters (Relative pressure drop ratio and Absolute pressure drop ratio) are proposed to make up for defect of Diodicity. Besides, a novel Tesla valve with special tapering/widening structure is designed, analyzed and compared with other type of Tesla valves, which shows superior absolute pressure drop ratio. Influences of multi related factors (inlet/outlet section length, inlet velocity, number of stage, property of fluid) on flow characteristics of fluid inside Tesla valve are investigated based on ANSYS Fluent 19.0 with realizable k-epsilon model and verified by experiments. Heat transfer performance of Tesla valve is also sufficiently studied and maximum temperature difference between forward and reverse flows can be 12.10 K, which has the potential to realize a new way for real-time thermal management.

Energy and exergy analyses of PV, solar thermal and photovoltaic/thermal systems: a comparison study

ABSTRACT Compared with photovoltaic (PV) or solar thermal (ST) system alone, the hybrid photovoltaic/thermal (PV/T) system has many advantages such as simultaneous production of electrical and thermal energies, efficient utilization on solar energy, space reduction and so on. However, there is limited data on both the energy and exergy performance comparisons of these three solar systems, especially for annual performance data. This paper aims to present a comparative study on the performances of the PV, ST and PV/T systems by a series of full-day experiments. Energy and exergy performances of these three solar utilization systems were all calculated and analyzed. Moreover, two typical evaluation methods, i.e. semi-empirical system efficiency model method and input–output method, were also used for evaluating the performances of these systems. Finally, based on the input–output method, the annual performances of the PV, ST and PV/T systems under typical meteorological conditions of Hong Kong region were predicted. The results show that the ST system has the highest total energy gain and energy efficiency and the PV system has the highest total exergy gain and exergy efficiency of these three systems. However, by a comprehensive consideration on the energy and exergy performances, the PV/T system has the best overall performance of these three solar systems.

'University is a place of imagination where anything can happen': evaluating widening participation initiatives with young children

There is increasing awareness of the importance of working with younger children in widening participation initiatives. While typical evaluation methods, such as feedback questionnaires, may be appropriate for collating evidence of the impact of initiatives with older children and teenagers, these tools are less appropriate for younger children. In the context of the evaluation of a campus-based creative writing programme for 9- to 10-year-old children, this paper discusses the utility of creative approaches to evaluation. Prior to and following their visit to a university campus, children completed a worksheet to gain their perspectives of university through sentence completion, comparison and drawing tasks. These methods provide insight into how children's perspectives are shaped by visiting a university campus, as well as differences between those who do and do not know someone who has attended university. We present snapshots of the evaluation data and discuss the implications for evaluation of widening participation initiatives with young children.

A virtual hydrological framework for evaluation of stochastic rainfall models

Abstract. Stochastic rainfall modelling is a commonly used technique for evaluating the impact of flooding, drought, or climate change in a catchment. While considerable attention has been given to the development of stochastic rainfall models (SRMs), significantly less attention has been paid to developing methods to evaluate their performance. Typical evaluation methods employ a wide range of rainfall statistics. However, they give limited understanding about which rainfall statistical characteristics are most important for reliable streamflow prediction. To address this issue a formal evaluation framework is introduced, with three key features: (i) streamflow-based, to give a direct evaluation of modelled streamflow performance, (ii) virtual, to avoid the issue of confounding errors in hydrological models or data, and (iii) targeted, to isolate the source of errors according to specific sites and seasons. The virtual hydrological evaluation framework uses two types of tests, integrated tests and unit tests, to attribute deficiencies that impact on streamflow to their original source in the SRM according to site and season. The framework is applied to a case study of 22 sites in South Australia with a strong seasonal cycle. In this case study, the framework demonstrated the surprising result that apparently “good” modelled rainfall can produce “poor” streamflow predictions, whilst “poor” modelled rainfall may lead to “good” streamflow predictions. This is due to the representation of highly seasonal catchment processes within the hydrological model that can dampen or amplify rainfall errors when converted to streamflow. The framework identified the importance of rainfall in the “wetting-up” months (months where the rainfall is high but streamflow low) of the annual hydrologic cycle (May and June in this case study) for providing reliable predictions of streamflow over the entire year despite their low monthly flow volume. This insight would not have been found using existing methods and highlights the importance of the virtual hydrological evaluation framework for SRM evaluation.

Tool for Purchasing Positioning – Assessment of Purchasing Maturity and Performance Level

This article provides a practical approach to evaluate the performance level of a purchasing organization before (ex ante) and after (ex post) the execution of a cost optimization project.A purchasing organization is often questioned, when performance (output) is not provided at the expected level (for example poor EBIT contribution). Provided there is a connection between performance level and the positioning of a purchasing organization, the interesting questions are: which aspects influence the performance level (output) and subsequently how can the effectiveness (input) of a purchasing organization be measured.The aim of this paper is to examine an applicable positioning tool, that helps to analyse and assess performance level and supports the selection of appropriate and tangible measures for sustainable cost optimization as an integrated tool of a cost optimization approach in the analysis phase.The utilized methodology considers an internet and literature research of typical evaluation methods and approaches, authors observation and synthesis of knowledge.Based on the research and subsequently logical reasoning a positioning tool is derived. Initially two formulated hypotheses are tested and confirmed through the application of the tool in three executed cost optimization projects and finally validated by semi-structured interviews with six purchasing experts.More accurate and precise evaluation of a purchasing organization prior to execution of a cost optimization project could lead to a better selection of cost optimization approaches and can help to reduce waste of time, capacity and expenditures. Assessment after project closure help to demonstrate the lift in performance.

Nondestructive Degradation Evaluation for Organic Coated Steels By Surface Potential Measurement

Organic coatings have been widely used for most steel structures as a cost-effective way for corrosion protection and ornamental design. Various methods have been suggested in order to check a degree of corrosion of organic coated metals. For example, visual observation and gloss measurement are well known as typical evaluation methods for organic coated metals.In this study, the corrosion performance of organic coated steels exposed to corrosive environment was estimated by surface potential measurement. In this study, the corrosion behavior of organic coated steels exposed to corrosive environment was monitored by surface potential measurement. In addition, the change in surface potential distribution was compared with the result of electrochemical impedance measurement in 0.5 M NaCl solution after measuring the surface potential. Carbon steel of the size of 3cm x 5cm was used as a substrate, and the organic coated steel samples were prepared by spraying a clear acrylic lacquer coating. Wet-dry cyclic corrosion test was conducted by alternating the condition of adding 20μl droplet of 0.5M NaCl solution and drying at 293K and 40%RH. After several cycles, a part of the surface exposed to corrosive environment showed lower potential than the other area. As the corrosion proceed, the change area grew up and the surface potential further declined. The electrochemical impedance characteristics also changed with an increase of wet and dry cycle number. The change in surface potential corresponds to that in the impedance characteristics, indicating that the deterioration process of the coated steel can be monitored by the surface potential measurement from the stage of the coating film deterioration.

Surface Potential Distribution in Corrosion Degradation Process of Organic Coated Steel

Organic coated steels are generally used in many applications such as cars, appliances and construction. Various methods to evaluate corrosion performance of organic coated metal have been suggested in the past, and for example, visual observation and gross measurement are well known as typical evaluation methods. Electrochemical impedance technique has been widely used for evaluation of under-film corrosion as subjective and quantitative evaluation method. However, the normal technique provides little information on the shape and the location of deteriorated area of organic coated metals. In this work, we focused attention on surface potential measurement which can detect surface reactivity. The purpose of this study is to evaluate the usefulness of surface potential measurement as a non-destructive evaluation method for degradation of coated steels. Carbon steel plates (50mm×50mm×2mm) were used as substrate metals. The metals were coated with clear acrylic lacquer spray. The surface potential was measured by surface reaction measurement device (RM201, Hirocon) having a X-Y stage. The surface potential of the sample with the coating thickness of approximately 10µm was measured at different distance between the sample and Au-probe in order to examine an influence of the distance.Surface potential distribution measurement was performed on the model sample for under-film corrosion. Wet-dry cyclic corrosion test was carried out on the substrate metal by alternating conditions of adding 100µL droplet of 0.5M NaCl solution and drying at 293K and 20%R.H. After 8 cycles, the surface was coated. The coating thickness was approximately 90µm. Surface potential distribution was measured on the sample in laboratory environment (293K, 30%R.H.). The measurement range was 30mm×30mm including the corroded area. The surface profile was also measured with Laser Displacement Sensor (LK-G3000, KEYENCE).Organic coated samples were prepared with about 20µm in thickness. The wet-dry cyclic corrosion test was carried out to these samples. The degradation degree of each sample was different by the repeated cycle number of the corrosion test. The surface potential and profile distribution were measured after corrosion test. For comparison, electrochemical impedance (EIS) measurement was conducted. The sample surface exposed to corrosive environment changed to lower surface potential than the other area. The size and position of the area where surface potential changed corresponded to degradation area. It means that surface potential measurement can detect degradation areas of coated steel even under organic coating.The wet-dry cyclic corrosion test of the organic coated samples was carried out. After several cycles, a part of the surface showed lower potential than the surrounding area. There were a good correlation between the surface potential change area and the organic coating degradation area. The surface potential changed in two stages in degradation process. The first stage corresponds to the gradual change to -0.1V, and the surface potential decreased down to -0.6V. EIS result showed that coating degradation and under-film corrosion occur in the first and second stage, respectively. This result suggests that the degradation process of coated steels can be monitored by surface potential measurement. It is concluded that surface potential measurement is an useful tool to evaluate degradation of coated steels.

Evaluation Methods in Process-Aware Information Systems Research with a Perspective on Human Orientation

Research on process-aware information systems (PAIS) has experienced a dramatic growth in recent years. Lately, a particular increase of empirical studies and focus on human oriented research questions could be observed, leading to an expansion of applied evaluation methods in PAIS research. At the same time, it can be observed that evaluation methods are not always applied in a systematic manner and related terminology is at times used in an ambiguous way. Hence, the paper aims at investigating evaluation methods that are typically employed in PAIS research with a special focus on human orientation. The applied methodology includes a literature review, an expert survey, and a focus group. The authors present their findings as a collection of typical evaluation methods and the related PAIS artifacts. They highlight which evaluation methods are currently used and which evaluation methods could be of interest for future PAIS research efforts.

Investigation on the performance evaluation method of flow batteries

Performance evaluation method is very important for the research on flow batteries. Charging–discharging test is the most typical evaluation method for flow batteries. Recently, the polarization curves, together with the associated power density curves, which are commonly employed in fuel cells, have come into use for flow batteries' performance evaluation. Based on the investigation of performance evaluation method, it is confirmed charging–discharging test is optimal for flow batteries' performance evaluation. A comparison of voltage losses (voltage efficiency, VE) can be clearly delivered from the polarization curves, which are quite practical for fuel cells' performance evaluation. While for flow batteries, apart from VE, coulombic efficiency (CE), energy efficiency (EE), utilization of electrolyte (UE) and capacity stability should be seriously considered during charging–discharging process. However, CE and UE are inaccessible; accordingly EE and capacity stability can't be detected from polarization curves. Therefore, the polarization curve is improper to serve as a performance evaluation method for flow batteries. On the premise of a proper CE, a rough performance evaluation for flow batteries can be achieved via the polarization curves. The peak power density is of limited significance in practical use due to the extremely low EE obtained at that point.

Comparison of typical evaluation methods for computer‐aided diagnostic schemes: Monte Carlo simulation study

Computer-aided diagnostic (CAD) schemes have been developed for assisting radiologists in the detection of various lesions in medical images. Many evaluation approaches, such as the resubstitution, leave-one-out, cross-validation, and hold-out methods, have been employed for the assessment of the performance of various CAD schemes. For these evaluation methods, some investigators have studied their bias in the estimated performance levels of CAD schemes trained with finite samples. However, systematical study has not been conducted for the comparison of these common evaluation methods in terms of multiple important characteristics such as the bias of the estimated performance, the generalization performance, and the uniqueness of the trained CAD scheme. Therefore, in this study, we examined and compared these important characteristics for various evaluation methods and attempted to provide a guideline for investigators to select appropriate evaluation methods for the assessment of CAD schemes in typical practical situations.

Documentation as evaluation: Capturing context, process, obstacles, and success

Summary The purpose of this article was to explain how documentation can be applied as an evaluation method by education researchers and evaluators studying the implementation of program innovations. Although the methods employed in documenting programs are quite similar to typical evaluation methods, the goals are distinguished primarily by (1) an emphasis on the information needs of program implementers as well as policymakers and funders and (2) the use of a variety of data collection mechanisms to capture context, processes, obstacles, and successes of individual program components that are considered to be critical in the implementation process. Experience in documenting a number of recent large-scale innovations provides evidence that documentation is a viable and potentially potent form of evaluation, for both midcourse corrections and the overall improvements of program innovation in an educational system.