Final Evaluation Results Research Articles

The Clinical Outcome of Arthroscopic Versus Open Popliteal Tendon Reconstruction Combined With Posterior Cruciate Ligament Reconstruction in Patients With Type A Posterolateral Rotational Instability

To compare the objective and subjective clinical outcomes of arthroscopic versus open popliteal tendon (PT) reconstruction combined with posterior cruciate ligament reconstruction in patients with type A posterolateral corner injury. From January 2012 to March 2016, patients were eligible for inclusion in this study if they (1) had type A posterolateral rotational instability according to Fanelli's classification, (2) underwent arthroscopic (group A) or open PT (group B) reconstruction, and (3) were followed for a minimum of 2years with second-look arthroscopic findings. For evaluation, this study used subjective scoring systems (Lysholm, Tegner, and International Knee Documentation Committee subjective scores), knee stability examinations (side-to-side differences of tibial external rotation angle by dial test and posterior and varus stress radiographs), and second-look arthroscopic lateral gutter drive-through tests during hardware removal operations. A total of 38 patients were included in the study. The mean follow-up period was 31.0 ± 5.8months in group A (n= 21) and 34.8 ± 12.7months in group B (n= 17). At the final follow-up, all subjective and objective evaluation results were significantly improved compared with the preoperative condition. There were no significant intergroup differences in Lysholm score (group A, 72.7 ± 17.2; group B, 67.2 ± 14.2; P= .818), Tegner score (group A, 2; group B, 2; P= .710), or International Knee Documentation Committee subjective score (group A, 73.0 ± 13.8; group B, 69.7 ± 20.7; P= .561) at the final follow-up. In terms of objective evaluations, there was no difference in side-to-side difference of posterior stress radiography (group A, 4.0 ± 3.2mm; group B, 5.0 ± 2.9mm; P= .336) or lateral gutter drive-through test positive rate (group A, 1/21, 4.8%; group B, 2/17, 11.8%; P= .426). Both arthroscopic and open PT reconstruction significantly improved the knee stability and subjective outcome of patients with type A posterolateral rotational instability. In comparison with the open procedure, the arthroscopic PT reconstruction showed similar subjective and objective clinical outcomes. Level III, retrospective cohort study.

A hesitant fuzzy multi-criteria group decision making method for college applicants’ learning potential evaluation

The evaluation of applicants’ learning potential is important to college admission process. This paper develops a multi-criteria decision making method for a comprehensive evaluation of high school graduates’ learning potential in college, in which both entrance examination marks and expert remarks are considered in the indicator system. Experts’ opinions towards indicator importance are expressed by hesitant fuzzy numbers. By using hesitant fuzzy linguistic judgments, the flexibility of expressions is increased. A minimized divergence and hesitant degree model is established to calculate the experts’ weights. Then to determine indicators’ weights, a weighted average operator is applied. To aggregate the final evaluation results, a TOPSIS method is adopted. The proposed methodology is applied to evaluate students’ learning potential in one of the top universities in China. Ten years’ real enrollment data is collected in Business and Economic School. Based on the evaluation results, some suggestions are given for the admission process.

Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence

BackgroundA deep learning computer artificial intelligence system is helpful for early identification of ground glass opacities (GGOs).MethodsImages from the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) database were used in AlexNet and GoogLeNet to detect pulmonary nodules, and 221 GGO images provided by Xinhua Hospital were used in ResNet50 for detecting GGOs. We used computed tomography image radial reorganization to create the input image of the three-dimensional features, and used the extracted features for deep learning, network training, testing, and analysis.ResultsIn the final evaluation results, we found that the accuracy of identification of lung nodule could reach 88.0%, with an F-score of 0.891. In terms of performance and accuracy, our method was better than the existing solutions. The GGO nodule classification achieved the best F-score of 0.87805. We propose a preprocessing method of red, green, and blue (RGB) superposition in the region of interest to effectively increase the differentiation between nodules and normal tissues, and that is the innovation of our research.ConclusionsThe method of deep learning proposed in this study is more sensitive than other systems in recent years, and the average false positive is lower than that of others.

A Shared Task for the Digital Humanities Chapter 3: Description of Submitted Guidelines and Final Evaluation Results

In this chapter, we give a descriptive overview of the annotation guidelines, their use of narrative level concepts, and the results of their quantitative evaluation. We will also connect some of the results to qualitative findings we uncovered during the workshop, although some references to the participants’ objectives are conjecture. Finally, the chapter contains a reflection on the annotation and evaluation procedure.

Nondestructive detection of chilled mutton freshness based on multi-label information fusion and adaptive BP neural network

Nondestructive detection of mutton freshness based on a single indicator has limitations and poor applicability. Hyperspectral imaging technology can detect a variety of information in the process of mutton freshness changes, but the establishments of spectral feature extraction and evaluation model have greater impacts on the final evaluation results. To improve the applicability and accuracy of nondestructive detection of mutton freshness, this paper proposes a multi-indicator correlation maximization spectral feature extraction algorithm and self-adaptive BP neural network classification model to detect mutton freshness nondestructively. In the experiments, 400–1000 nm hyperspectral images are collected from 140 mutton samples, and the standard values of total volatile basic nitrogen (TVB-N) and total aerobic plate count (TAC) are determined by laboratory methods. The representative spectra of mutton samples are extracted in the region of interests (ROIs). The spectral feature information is extracted using the feature of multi-indicator correlation maximization, which is proposed in this paper. The samples of calibration set and the prediction set are divided at a ratio of 3:1, and the improved three-layer BP neural network is used to evaluate the freshness of mutton. The results show that the final overall classification accuracy (OA) is 0.9378, the Kappa coefficient is 0.9096, and the AUC values for the three freshness classification results are 0.8192, 0.6766 and 0.7483, respectively. The root means square error (RMSE) of the evaluation results is 0.279. The research shows that the method proposed in this paper can achieve more accurate nondestructive detection of mutton freshness. Moreover, the research provides a new method to obtain spectral information of multiple detection indicators with hyperspectral imaging technology, which can improve the applicability and robustness of the evaluation model of single indicator.

Teaching Quality Evaluation and Scheme Prediction Model Based on Improved Decision Tree Algorithm

Vast data in the higher education system are used to analyse and evaluate the teaching quality, so that the key factors that affect the quality of teaching can be predicted. Besides, the learner’s personalized behaviour can also become the data source for teaching result prediction. This paper proposes a decision tree model by taking the teaching quality data and the statistical analysis results of the learn-er’s personalized behaviour as inputs. This model was based on the improved C4.5 decision tree algorithm, which used the FAYYAD boundary point decision theorem for effectively reducing the computation time to the most threshold. In this algorithm, the iterative analysis mechanism was introduced in combination with the data change of the learner’s personalized behaviour, so as to dynamically adjust the final teaching evaluation result. Finally, according to the actual statisti-cal data of one academic year, the teaching quality evaluation was effectively completed and the direction of future teaching prediction was proposed.

(Invited) Investigation of Thermal Propagation Test Methods of Lithium-Ion Batteries for Vehicles

Introduction The thermal propagation test is conducted to evaluate the influence of ignition or rupture of the battery pack on its surroundings in case of the thermal runaway due to an internal short circuit etc. of a single cell in the battery pack. One of the issues to be considered regarding the thermal propagation test is the unclearness of the method of appropriately inducing thermal runaway of a single cell in the battery pack. Even if the same packs are tested, the final evaluation result may be affected by different situations in the initiation cell (heat generation only, smoke, fire, etc.) depending on different methods of induction. In addition, applicable initiation methods may differ according to the type of cell. Accordingly, it is necessary to investigate appropriate initiation methods in order to establish the thermal propagation test method that provides fair evaluations. Therefore, the applicability of thermal runaway generation methods such as overcharge, heater heating, and nail penetration was investigated by using several kinds of cells. Experimental At first, overcharge, nail penetration, and heater heating tests were conducted using a single cell to investigate the reproducibility of such methods and the applicability to each type of cell. Three types of single cell were tested: pouch type, prismatic type, and cylindrical type. For the overcharge test, it was charged at a rate of 1C or 2C from the 100% state of charge. For the nail penetration test, all electrode layers in the cell were penetrated at a penetration speed of 0.1 mm/s by a steel nail with a diameter of 3 mm and a tip angle of 60°. For the heater heating test, it was heated at a heating rate of approximately 100°C/min using a ceramic heater for the pouch and prismatic cells, and a wire heater for the cylindrical cells. Furthermore, a battery pack composed of pouch cells was evaluated by the method that showed good applicability in the single cell test, in order to confirm whether a single initiation cell thermal runaway can occur in the battery pack. Results and discussion In the single cell tests, applicability of the each initiation method was evaluated with regard to the following three points: 1) good reproducibility of the occurrence event, 2) cell temperature exceeding the upper limit of operating temperature (about 60 to 80°C) in the battery pack which indicates thermal runaway occurring, and 3) upper limit of the calorific value during thermal runaway almost equivalent to the original value of a single cell. Evaluation item of 3) was adopted because of the possibility that the sound battery pack may fail if thermal runaway of the initiation cell causes excessive heat generation. As a result of evaluating the applicability of the initiation methods based on the data obtained from the test, only the heater heating method proved to be applicable to any of the cell types in this study. A battery pack composed of pouch cells was tested using a heater heating method which showed good applicability in the single cell test. Fig. 1 presents the test results. The initiation cell reached thermal runaway appropriately 35 seconds after the start of heating. The cell voltage was measured for two cells connected in parallel. Since the cell temperature rapidly increased immediately after the voltage decreased by approximately 0.6 V, it was confirmed that the thermal runaway of the first one cell occurred at this point. From the above, it was confirmed that thermal runaway of a single initiation cell can occur even in a battery pack composed of pouch cells. AcknowledgmentsThis paper is based on results obtained from a project commissioned by the New Energy and Industrial Technology Development Organization (NEDO). Figure 1

Efficient-equitable-ecological evaluation of regional water resource coordination considering both visible and virtual water

Efficient-equitable-ecological (3E) regional water resource coordination that includes virtual water is critical for long-term sustainability. This paper develops a methodology for a comprehensive 3E evaluation of regional water resource coordination, in which both visible and virtual water are considered in the indicator system. Experts’ opinions towards indicator importance are expressed by hesitant fuzzy numbers. By using hesitant fuzzy linguistic judgments, the flexibility of expressions is increased. A minimized divergence and hesitant degree model is established to calculate the experts’ weights. Then to determine indicators’ weights, a weighted average operator is used. To aggregate the final evaluation results, a TOPSIS method is adopted. The presented methodology is applied to the water resource coordination evaluation in the Northwestern District of China. Based on the evaluation results, some suggestions are proposed to enhance the water resource coordination in the study area. Finally, to illustrate the effectiveness of the proposed methodology, the method is compared with the equal weights method.

Physical Fitness Results of Soldiers Of Different Age Groups in the Land Force of the Lithuanian Professional Armed Forces in 2010–2011

Research background and hypothesis. Since 2009 Lithuanian Armed Forces have been formed from soldiers in professional service. Research on military physical fitness in the Lithuanian Armed Forces is scarce. This research aims at verifying the hypothesis that physical fitness indices of soldiers in the Land Force of the professional Lithuanian Armed Forces match the established physical fitness normative requirements.Research aim was to study peculiarities of changes in physical fitness results of soldiers of different age groups in the Land Force of the Lithuanian Professional Armed Forces in the period of two years. Research methods: literature review, physical fitness testing, statistical analysis of physical fitness indices. Results in each physical fitness exercise were evaluated in points according to physical fitness normative scales. The sum of points for all exercises was the final physical fitness evaluation result. Research results. In the period of half a year, from spring to autumn and from autumn to spring, physical fitness of soldiers in all age groups changed only slightly (p > 0.05). During the period of one year, from testing in spring till testing in spring of the following year, physical fitness indices improved (p < 0.05). Even 2–4% of soldiers failed physical fitness normative tests. Discussion and conclusions. Physical fitness indices of different exercise for soldiers in the Land Force of the professional Lithuanian Armed Forces were higher than the established minimal normative requirements. The highest physical fitness indices were achieved in the age groups of 18–21, 22–26, 27–31 and 30–36 years, however, the differences between the age groups were insignificant. In perspective, while developing military physical fitness control system, the evaluation of physical fitness should be differentiated according to the normative scale which includes such evaluations as “excellent”, “good”, “fair”.Keywords: Land Force, physical fitness, testing, physical fitness test, age group, points.

Black-start decision making based on collaborative filtering for power system restoration

Black-start decision making plays an important role in power system restoration after a large-area blackout. The entropy method is one of the most popular methods for determining the weights of indexes in black-start decision making. In spite of its success, the entropy method is affected significantly by normalization methods, which makes the final evaluation results of black-start schemes not reliable. To address this issue, in this article, we propose a novel black-start decision making method based on collaborative filtering. In the proposed method, the values in the decision matrix are withheld, and the collaborative filtering technique is adopted to predict the withheld values. Based on the prediction values and true values, the MAE weights of all the indexes are obtained. Finally, the MAE weights are used to compute the overall assessment value of each black-start scheme. Based on the data of Guangdong power system of China, experiments were carried out to evaluate the performance of the proposed method. Experimental results show that the proposed method is more stable and superior to the existing methods.

Evaluating the performance of suppliers based on using the R'AMATEL-MAIRCA method for green supply chain implementation in electronics industry

Abstract Green supply chain management (GSCM) practitioners striving to create a healthier environment should first identify the key criteria pertinent to the process of implementing the appropriate sustainable policies, particularly in the most rapidly growing electronics sector. Since the decision to adopt GSCM in electronics industry is associated with the use of a multi-dimensional approach involving a number of qualitative criteria, the paper examines GSCM based on fifteen criteria expressed in five dimensions and proposes a multi-criteria evaluation framework for selecting suitable green suppliers. In real life, the assessment of this decision is based on vague information or imprecise data of the expert's subjective judgements, including the feedback from the criteria and their interdependence. Thus to treat this uncertainty in multi-criteria decision making (MCDM) process, rough number (RN) is applied here using only the internal knowledge in the operative data available to the decision-makers. In this way objective imprecisions and uncertainties are used and there is no need to rely on models of assumptions. Instead of different external parameters in the application of RN, the structure of the given data is used. Therefore, the identified components are incorporated into a rough DEMATEL-ANP (R'AMATEL) method, combining the Decision Making Trial and Evaluation Laboratory Model (DEMATEL) and the Analytical Network Process (ANP) in a rough context. In group decision making, a rough number-based approach aggregates individual judgements and handles imprecision. The structure of the relationships between the criteria expressed in different dimensions is determined by using the rough DEMATEL (R'DAMETEL) method and building an influential network relation mapping, based on which the rough ANP (R'ANP) method is implemented to obtain the respective criteria weights. Then, the rough multi-attribute Ideal-Real Comparative Analysis (R'MAIRCA) is used to evaluate the environmental performance of suppliers for each evaluation criterion. Sensitivity analysis is performed to determine the impact of the weights of criteria and the influence of the decision maker's preferences on the final evaluation results. Applying the Spearman's rank correlation coefficient and other ranking methods, the stability of the alternative rankings based on the variation in the criteria weights is checked. The results obtained in the study show that the proposed method significantly increases the objectivity of supplier assessment in a subjective environment.

Film Music Teaching Effect Evaluation from the Perspective of Audience Immersion

With the continuous improvement of national education level and system, film music teaching method has been greatly promoted in the classroom, especially the audience immersion, as the standard of classroom quality and effect evaluation, which has been recognized by experts inside and outside the education circle. Therefore, this paper uses the analytic hierarchy process to analyze and calculate the teaching objective, content, structure, method and effect, and establishes a reasonable teaching effect evaluation hierarchy model, obtaining the weight and consistency test results of each index element. Finally, the paper quantitatively summarizes the synthetic weight of index layer and obtains the final teaching evaluation results, which have a certain practical reference value to improve the teaching results of education workers.

Well-to-wheel life cycle assessment of Eruca Sativa-based biorefinery

Abstract Renewable energy generation through biorefineries is increasingly considered as more sustainable in comparison with fossil-based fuels as well as single-product renewable energy systems. However, biorefineries have many system variations, and therefore, the evaluation of their environmental performance and comparison with conventional systems before large-scale deployment is essential. In this paper, the sustainability of three different biorefiney scenarios (Sc-1, Sc-2, and Sc-3) based on Eruca sativa ( ES ) as feedstock were investigated using a life cycle assessment approach from energy balance and environmental point of views. Biodiesel, electricity, ethanol, heat, glycerol, and/or biomethane were the marketable products taken into account under the conditions of these scenarios. According to the results obtained, we argue that although biorefineries offer unique features as most effective alternatives for mitigating climate change and reducing dependence on fossil fuels, the selection of biomass processing options and management decisions can widely affect the final evaluation results. Overall, providing transportation fuel through Sc-2 in which biodiesel, electricity, ethanol, heat, and glycerol were produced could decrease GHG emissions by approximately 140% compared with the combustion of neat diesel while also offering a total net energy gain (NEG) of 4.94E+08 MJ/yr. Nevertheless, if biorefineries are to be used for future transportation fuel production, a great deal of efforts should still be made to achieve better environmental performance in the Human Health and Ecosystem quality damage categories.

Urban Water Conservation Evaluation Based on Multi-grade Uncertain Comprehensive Evaluation Method

Water is not only the resource of life but also the important resource for a nation survival and development. Nowadays, the water crisis has become one of the most essential factors to restrict urban development. In this case, taking reasonable and effective method for comprehensive evaluation of urban water conservation level is helpful for promoting the construction of water-saving city. The main contribution of this paper is providing a new evaluation method for urban water saving. First, an urban water-saving evaluation index system is built. And the index system takes six water-saving standards including comprehensive water saving, domestic water saving, ecological water saving, industrial water saving, agricultural water saving and social economy as criteria. Then, the water-saving assessment model is proposed based on the Multi-grade Uncertain Comprehensive Evaluation (MUCE) Method. In this method, the important degree and the corresponding remark of each evaluation index are both considered to be uncertain variables due to the human uncertainty. The weights as well as the final evaluation result are obtained according to their uncertainty distributions and the votes of experts. At last, the comprehensive evaluation for water-saving level of Handan City located in North China is studied.

Neuropsychological Treatment of Attention Deficit Disorder in Infancy

The syndrome of attention deficit disorder is one of the most frequent pictures of disabilities in pre-scholars. The present study analyses the results of fulfillment of tasks for mechanisms of control and spatial functions. 14 pre-scholars with attention deficit disorder took part in the study. The neuropsychological evaluation was applied before and after application the correction program. The most significant differences were obtained for the functions of voluntary regulation and spatial functions. The program of neuropsychological correction was elaborated and applied 64 sessions. The main goals of the program were to form the action of material external control by introducing activity of role games. The program included orientation in games, perception, spatial relations and solving problems at the level of concrete actions and concrete images and drawing. The results of final neuropsychological evaluation pointed out significant differences between initial and final evaluation for functions of regulation and spatial functions. The comparison of initial and final assessment shows the disappearance of difficulties in some tasks. The discussion establishes positive effects of neuropsychological correction without medication. The results permit to complete the comprehension of the syndrome and propose the original treatment according to the concept of central mechanisms considered in neuropsychology.

Measuring air traffic complexity based on small samples

Air traffic complexity is an objective metric for evaluating the operational condition of the airspace. It has several applications, such as airspace design and traffic flow management. Therefore, identifying a reliable method to accurately measure traffic complexity is important. Considering that many factors correlate with traffic complexity in complicated nonlinear ways, researchers have proposed several complexity evaluation methods based on machine learning models which were trained with large samples. However, the high cost of sample collection usually results in limited training set. In this paper, an ensemble learning model is proposed for measuring air traffic complexity within a sector based on small samples. To exploit the classification information within each factor, multiple diverse factor subsets (FSSs) are generated under guidance from factor noise and independence analysis. Then, a base complexity evaluator is built corresponding to each FSS. The final complexity evaluation result is obtained by integrating all results from the base evaluators. Experimental studies using real-world air traffic operation data demonstrate the advantages of our model for small-sample-based traffic complexity evaluation over other state-of-the-art methods.

Directional geometric histogram feature extraction and applications

Image feature has been a hot research topic within the field of computer vision, with a wide scope of direct impacts on detection, recognition, image retrieval and pose estimation, etc. In this paper, we propose a novel image feature: Directional Geometric Histogram (DGH) which adopts directional geometric approximation from the geometric Bandelet transform to enhance the description distinctiveness and selectivity among monocular images, particularly by renovating the histogram of geometric regularity to characterize local image context with human objects. Other than the image geometry defined over edges, our approach can well preserve inner and outer patterns of contours with strict geometry. We have compared the proposed method with classic global features and conducted comprehensive experiments in human detection, pose estimation as well as scene recognition tasks on various datasets. Final evaluation results show that the dimensionality of the DGH feature can be reduced to less than half of the original size, which is also sparse while keeping competitive discriminatory effectiveness and distinctiveness in such visual tasks. Besides its relaxed computational requirement and off-the-shelf theoretical backup, the method is in the meanwhile quite promising for potential fields in video surveillance, pattern identification, etc.

Probabilistic dual hesitant fuzzy set and its application in risk evaluation

The concurrence of randomness and imprecision widely exists in real-world problems. To describe the aleatory and epistemic uncertainty in a single framework and take more information into account, in this paper, we propose the concept of probabilistic dual hesitant fuzzy set (PDHFS) and define the basic operation laws of PDHFSs. For the purpose of applications, we also develop the basic aggregation operator for PDHFSs and give the general procedures for information fusion. Next, we propose a visualization method based on the entropy of PDHFSs so as to analyze the aggregated information and improve the final evaluation results. The proposed method is then applied to the risk evaluations. A case study of the Arctic geopolitical risk evaluation is presented to illustrate the validity and effectiveness. Finally, we discuss the advantages and the limitations of the PDHFS in detail.

Blended learning effectiveness: the relationship between student characteristics, design features and outcomes

This paper investigates the effectiveness of a blended learning environment through analyzing the relationship between student characteristics/background, design features and learning outcomes. It is aimed at determining the significant predictors of blended learning effectiveness taking student characteristics/background and design features as independent variables and learning outcomes as dependent variables. A survey was administered to 238 respondents to gather data on student characteristics/background, design features and learning outcomes. The final semester evaluation results were used as a measure for performance as an outcome. We applied the online self regulatory learning questionnaire for data on learner self regulation, the intrinsic motivation inventory for data on intrinsic motivation and other self-developed instruments for measuring the other constructs. Multiple regression analysis results showed that blended learning design features (technology quality, online tools and face-to-face support) and student characteristics (attitudes and self-regulation) predicted student satisfaction as an outcome. The results indicate that some of the student characteristics/backgrounds and design features are significant predictors for student learning outcomes in blended learning.

Does an expert-based evaluation allow us to go beyond the Impact Factor? Experiences from building a ranking of national journals in Poland

This article discusses the Polish Journal Ranking, which is used in the research evaluation system in Poland. In 2015, the ranking, which represents all disciplines, allocated 17,437 journals into three lists: A, B, and C. The B list constitutes a ranking of Polish journals that are indexed neither in the Web of Science nor the European Reference Index for the Humanities. This ranking was built by evaluating journals in three dimensions: formal, bibliometric, and expert-based. We have analysed data on 2035 Polish journals from the B list. Our study aims to determine how an expert-based evaluation influenced the results of final evaluation. In our study, we used structural equation modelling, which is regression based, and we designed three pairs of theoretical models for three fields of science: (1) humanities, (2) social sciences, and (3) engineering, natural sciences, and medical sciences. Each pair consisted of the full model and the reduced model (i.e., the model without the expert-based evaluation). Our analysis revealed that the multidimensional evaluation of local journals should not rely only on the bibliometric indicators, which are based on the Web of Science or Scopus. Moreover, we have shown that the expert-based evaluation plays a major role in all fields of science. We conclude with recommendations that the formal evaluation should be reduced to verifiable parameters and that the expert-based evaluation should be based on common guidelines for the experts.