An Approach to Detect Structural Development Defects in Object-Oriented Programs

Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.

Cell structure of microcellular combustible object foamed by supercritical carbon dioxide

In order to solve the issue that the combustible objects for cased telescoped ammunition (CTA) didn't burn completely during the combustion process, the microcellular combustible objects were foamed with numerous cells in the micron order to improve the combustion performance by the supercritical carbon dioxide (SCeCO2) foaming technology. As the cell structure determined the combustion properties of microcellular combustible objects, the solubility of SCeCO2 dissolved into the combustible objects was obtained from the gravimetric method, and scanning electron microscope (SEM) was applied to characterize the cell structure under various process conditions of solubility, foaming temperature and foaming time. SEM images indicate that the cell diameter of microcellular combustible objects is in the level of 1 mm and the cell density is about 1011 cell,cm^-3. The microcellular combustible objects fabricated by the SCeCO2 foaming technology are smooth and uniform, and the high specific surface area of cell structure can lead to the significant combustion performance of microcellular combustible object for CTA in the future.

Subtle skills: Using objective structured clinical examinations to assess gastroenterology fellow performance in system based practice milestones

BACKGROUND System based practice(SBP) milestones require trainees to effectively navigate the larger health care system for optimal patient care. In gastroenterology training programs, the assessment of SBP is difficult due to high volume, high acuity inpatient care, as well as inconsistent direct supervision. Nevertheless,structured assessment is required for training programs. We hypothesized that objective structured clinical examination(OSCE) would be an effective tool for assessment of SBP.AIM To develop a novel method for SBP milestone assessment of gastroenterology fellows using the OSCE.METHODS For this observational study, we created 4 OSCE stations: Counseling an impaired colleague, handoff after overnight call, a feeding tube placement discussion, and giving feedback to a medical student on a progress note. Twentysix first year fellows from 7 programs participated. All fellows encountered identical case presentations. Checklists were completed by trained standardized patients who interacted with each fellow participant. A report with individual and composite scores was generated and forwarded to program directors to utilize in formative assessment. Fellows also received immediate feedback from a faculty observer and completed a post-session program evaluation survey.RESULTS Survey response rate was 100%. The average composite score across SBP milestones for all cases were 6.22(SBP1), 4.34(SBP2), 3.35(SBP3), and 6.42(SBP4)out of 9. The lowest composite score was in SBP 3, which asks fellows to advocate for cost effective care. This highest score was in patient care 2, which asks fellows to develop comprehensive management plans. Discrepancies were identified between the fellows’ perceived performance in their self-assessments and Standardized Patient checklist evaluations for each case. Eighty-seven percent of fellows agreed that OSCEs are an important component of their clinical training,and 83% stated that the cases were similar to actual clinical encounters. All participating fellows stated that the immediate feedback was "very useful." One hundred percent of the fellows stated they would incorporate OSCE learning into their clinical practice.CONCLUSION OSCEs may be used for standardized evaluation of SBP milestones. Trainees scored lower on SBP milestones than other more concrete milestones. Training programs should consider OSCEs for assessment of SBP.

Attitudes of undergraduate nursing students toward Objective Structure Practical Examination: An Exploratory study

Background: Objective Structured Practical Examination (OSPE) is a method of assessment of clinical competence.The examination is conducted at multiple stations.Besides practical and problem-solving skills,theoretical knowledge is also tested.OSPE can be traced back more than 40 years.OSPE has been included more than two decades,as a part of assessment in the College of Nursing,All India Institute of Medical Sciences (AIIMS),New Delhi.Objectives: This study was carried out to determine nursing students' attitudes towards OSPE as an assessment tool.Participants: The responses of all the 252 Undergraduate nursing students studying at the College of Nursing,AIIMS were obtained for this study (77 from B.Sc.(H) Nursing first year,61 from the second year,69 from the third year and 45 from the fourth year).Methods: The students attitudes towards OSPE were assessed by using a validated questionnaire containing 28 item statements on Likert's 5-point scale (LS) and 11 bipolar adjectives on Osgood's 7-point Semantic'Differential Scale (OSDS).Result: Most of the students approved of OSPE and felt that it was fair,useful,good,effective,exciting,interesting,practical,skill oriented but also taxing.The study also revealed that amongst the second years' students there was a strong correlation between Overall Rank in the Class and Assessment of OSPE.Conclusion: The study supports the introduction of OSPE as one of the methods of assessment of B.Sc.(Hons.) Nursing students.

Multi-objective optimization of membrane structures based on Pareto Genetic Algorithm

A multi-objective optimization method based on Pareto Genetic Algorithm is presented for shape design of membrane structures from a structural view point.Several non-dimensional variables are defined as optimization variables,which are decision factors of shapes of membrane structures.Three objectives are proposed including maximization of stiffness,maximum uniformity of stress and minimum reaction under external loads.Pareto Multi-objective Genetic Algorithm is introduced to solve the Pareto solutions.Consequently,the dependence of the optimality upon the optimization variables is derived to provide guidelines on how to determine design parameters.Moreover,several examples illustrate the proposed methods and applications.The study shows that the multi-objective optimization method in this paper is feasible and efficient for membrane structures;the research on Pareto solutions can provide explicit and useful guidelines for shape design of membrane structures.

Interactive Multi-objective Optimization Design for the Pylon Structure of an Airplane

The pylon structure of an airplane is very complex, and its high-fidelity analysis is quite time-consuming. If posterior preference optimization algorithm is used to solve this problem, the huge time consumption will be unacceptable in engineering practice due to the large amount of evaluation needed for the algorithm. So, a new interactive optimization algorithm-interactive multi-objective particle swarm optimization （IMOPSO） is presented. IMOPSO is efficient, simple and operable. The decision-maker can expediently determine the accurate preference in IMOPSO. IMOPSO is used to perform the pylon structure optimization design of an airplane, and a satisfactory design is achieved after only 12 generations of IMOPSO evolutions. Compared with original design, the maximum displacement of the satisfactory design is reduced, and the mass of the satisfactory design is decreased for 22%.

Test anxiety in objective structured clinical examinations (OSCEs) compared with traditional assessment methods in undergraduate midwifery students

BACKGROUND: Final comprehensive exam is the most important examination for midwifery students to evaluate their professional ability and Test anxiety is a common phenomenon among college students. Because test anxiety is one of the problems of educational systems, this study was performed to compare test anxiety in objective structured clinical examinations (OS-CEs) and traditional assessment methods (TAM) among Undergraduate Midwifery Students. Methods: In this descriptive-analytical study, 52 students of Babol Midwifery College were participated in the study. 20 students were evaluated using TAM in November 2010, and 32 students were evaluated using the OSCE method in July 2011. Data were collected via a two-component questionnaire including demographic data and the test anxiety inventory (TAI). Results: All of midwifery students were women;the mean age of students, ages of father and mother’s were 23.1 ± 0.7, 52.3 ± 3.5 and 47.8 ± 4.9 years, respectively. Most of the students were single (61.5%). The mean education levels of father and mother’s were 11.6 ± 4.5 and 9.9 ± 4.0 years, respectively. The mean score of test anxiety in students was 42.51 ± 13.16. The most of participants did have moderate test anxiety (56.9%), two present not had any test anxiety, 37.3% had low test anxiety, and 3.9% had severe test anxiety. In sum, 98% had some degrees of test anxiety. There were the statistical differences in the mean score of text anxiety in OSCEs Compared with TAM in Undergraduate Midwifery Students (39.38 ± 13.81 vs. 47.35 ± 10.67, P = 0.033). Also, the mean severity of anxiety was different in two groups. The mean of moderate/severe test anxiety was more in TAM compared with OSCEs (52.57% vs. 49.56%, p = 0.000). The test anxiety had a positive correlation with father’s education, mother’s education (0.286, p = 0.042), father’s age, mother’s age, marital status, residency (0.292, p = 0.042). Also, there are negative correlations with student age, satisfaction, total Grade Point Average (GPA) (-0.387, p = 0.007), final score, type of assessment (-0.298, p = 0.033). There is a significant difference between the severity anxiety residency in total (p = 0.10) and OSCEs (p = 0.049) groups, mother’s education in total (p = 0.005) and OSCEs groups (0.012) and GPA (p = 0.028). Conclusion: OSCEs were superior to TAM in the reduction of test anxiety in midwifery students. The prevalence of test anxiety was in TAM than OSCEs method;therefore, using OSCEs is acknowledged as an effective assessment tool and is seen as the gold standard for evaluating clinical performance.

Feature-based and objectoriented product information model for welding structure

Product information model for welding structure plays an important role for the integration of welding CAD/CAPP/CAM. However, existing CAD modeling systems are not capable of providing enough information for subsequent manufacturing activities such as CAPP and CAM. A new design approach using feature technique and object oriented programming method is put forward in this paper in order to create the product information model of welding structure. With this approach, the product information model is able to effectively support computer aided welding process planning, fixturing, assembling, path planning of welding robot and other manufacturing activities. The feature classification and representing scheme of welding structure are discussed. A prototype system is developed based on feature and object oriented programming. Its structure and functions are given in detail.

Optimization of Uncertain Structures with Interval Parameters Considering Objective and Feasibility Robustness

For the purpose of improving the mechanical performance indices of uncertain structures with interval parameters and ensure their robustness when fluctuating under interval parameters, a constrained interval robust optimization model is constructed with both the center and halfwidth of the most important mechanical performance index described as objective functions and the other requirements on the mechanical performance indices described as constraint functions. To locate the optimal solution of objective and feasibility robustness, a new concept of interval violation vector and its calculation formulae corresponding to different constraint functions are proposed. The math?ematical formulae for calculating the feasibility and objective robustness indices and the robustness?based preferential guidelines are proposed for directly ranking various design vectors, which is realized by an algorithm integrating Kriging and nested genetic algorithm. The validity of the proposed method and its superiority to present interval optimization approaches are demonstrated by a numerical example. The robust optimization of the upper beam in a high?speed press with interval material properties demonstrated the applicability and effectiveness of the proposed method in engineering.

Application of the Objective Structure Clinical Evaluation in Evaluating Clinical Competence for a BSN Program

Given the complex clinical situations and the dynamic nature of nursing, the greatest challenge for nursing educators is performing objective evaluation of students’ clinical competence. The Objective Structured Clinical Evaluation (OSCE) is designed to address this challenge and it has been widely used in nursing education. However, its implementation in nursing education in Taiwan has been limited. Accordingly, a quasi-experimental design was utilized to examine students’ clinical performance and stress levels using a 12-station OSCE assessment. Further, we investigated the inter-rater reliability and internal consistency of the OSCE. After controlling for scores of clinical performance, overall differences in pre- and post-practicum stress in the OSCE group were significantly higher than in the control group (F (1, 89) = 4.89, p = 0.03). There was no group effect on practicum performance after controlling for grade point average (F (1, 89) = 2.69, p = 0.14). Cronbach’s alpha for 12 OSCE stations ranged from 0.22 to 0.80 and inter-rater reliability for all 12 stations showed Pearson’s r ranging between 0.76 and 1.00. Cohen’s kappa ranged from 0.70 to 1.00

Attitudes of Nursing Faculty Members and Graduates towards the Objective Structured Clinical Examination (OSCE)

The aim of this study was to evaluate the attitudes of faculty and graduates of college of nursing towards Objective Structured Clinical Examination (OSCE) as a valid and reliable method of clinical competency assessment in nursing ten years after its inception. Core nursing courses are based on instructional teaching methods and “hands-on” approach to impact cognitive, psychomotor skills and clinical judgments. Different clinical competency assessment methods are used globally;however, most of them are subjective. A descriptive survey using 16-item five-point likert scale questionnaire was conducted. The study sample consisted of 140 participants: 20 faculty members, 27 graduates of the Bachelor of Science in Nursing (BSN) Degree and 93 graduates of the Associate Degree of Nursing (ADN) programs with OSCE experience during their training. Data collection was carried out between October and November 2015. Eighty percent of faculty members, 74% of BSN and 62.3% of ADN graduates agreed that OSCE represented an objective evaluation method for psychomotor skills. Majority of the graduates perceived their OSCE experience positively although stressful. However, they have suggested the introduction of trial/mock OSCE prior to each exam to minimize the stress associated with it. In conclusion, there appears to be no single “gold-standard” assessment tool for clinical competency. OSCE assesses student nurses’ psychomotor skills in a non-clinical environment, therefore without risks to real patients. In combination with other assessment methods in the clinical settings, OSCE will provide a more comprehensive student psychomotor skill evaluation. OSCE experiences gave new nursing graduates confidence to work as registered nurses in health care settings.

Multi-objective optimization design of radar absorbing sandwich structure

By introducing a dimensionless parameter to couple the two objectives, weight and radar absorbing performance, into a single objective function, a multi-objective optimization procedure for the radar absorbing sandwich structure （RASS） with a cellular core is proposed. The optimization models considered are one-side clamped sandwich panels with four kinds of cores subject to uniformly distributed loads. The average specular reflectivity calculated with the transfer matrix method and the periodic moment method is utilized to characterize the radar absorbing performance, while the mechanical constraints include the facesheet yielding, core shearing, and facesheet wrinkling. The optimization analysis indicates that the sandwich structure with a two-dimensional （2D） composite lattice core filled with ultra-lightweight sponge may be a better candidate of lightweight RASS than those with cellular foam or hexagonal honeycomb cores. The 2D Kagome lattice is found to outperform the square lattice with respect to radar absorbing.

The column density structure of Orion A depicted by N-PDF

We have conducted a large-field simultaneous survey of 12 CO,13 CO and C18O J=1-0 emission toward the Orion A giant molecular cloud(GMC)with a sky coverage of4.4 deg2 using the Purple Mountain Observatory(PMO)-13.7 m millimeter-wavelength telescope.We use the probability distribution function of the column density(N-PDF)to investigate the distribution of molecular hydrogen in the Orion A GMC.The H2 column density,derived from the 13CO emission,of the GMC is dominated by a log-normal distribution in the range from4×1021 to1.5×1023 cm-2 with excesses both at the low-density and high-density ends.The excess of the low-density end is possibly caused by an extended and low-temperature(10 K)component with velocities in the range of 5-8 km s-1.Compared with the northern sub-regions,the southern sub-regions of the Orion A GMC contain less gas with column density in NH2>1.25×1022 cm-2.The dispersions of the N-PDFs of the sub-regions are found to correlate with the evolutionary stages of the clouds across the Orion A GMC.The structure hierarchy of Orion A GMC is explored with the DENDROGRAM algorithm,and it is found that the GMC is composed of two branches.All structures except one in the tree have virial parameters less than 2,indicating self-gravity is important on the spatial scales from0.3 to4 pc.Although power-laws and departures from lognormal distributions are found at the high-density end of N-PDFs for active star-forming regions,the N-PDFs of structures in the Orion A GMC are predominantly lognormal on scales from R0.4 to 4 pc.

Coach Simplified Structure Modeling and Optimization Study Based on the PBM Method

For the coach industry, rapid modeling and efficient optimization methods are desirable for structure modeling and optimization based on simplified structures, especially for use early in the concept phase and with capabilities of accurately expressing the mechanical properties of structure and with flexible section forms. However, the present dimension-based methods cannot easily meet these requirements. To achieve these goals, the property-based modeling （PBM） beam modeling method is studied based on the PBM theory and in conjunction with the characteristics of coach structure of taking beam as the main component. For a beam component of concrete length, its mechanical characteristics are primarily affected by the section properties. Four section parameters are adopted to describe the mechanical properties of a beam, including the section area, the principal moments of inertia about the two principal axles, and the torsion constant of the section. Based on the equivalent stiffness strategy, expressions for the above section parameters are derived, and the PBM beam element is implemented in HyperMesh software. A case is realized using this method, in which the structure of a passenger coach is simplified. The model precision is validated by comparing the basic performance of the total structure with that of the original structure, including the bending and torsion stiffness and the first-order bending and torsional modal frequencies. Sensitivity analysis is conducted to choose design variables. The optimal Latin hypercube experiment design is adopted to sample the test points, and polynomial response surfaces are used to fit these points. To improve the bending and torsion stiffness and the first-order torsional frequency and taking the allowable maximum stresses of the braking and left turning conditions as constraints, the multi-objective optimization of the structure is conducted using the NSGA-II genetic algorithm on the ISIGHT platform. The result of the Pareto solution set is acquired, and the selection strategy of the final solution is discussed. The case study demonstrates that the mechanical performances of the structure can be well-modeled and simulated by PBM beam. Because of the merits of fewer parameters and convenience of use, this method is suitable to be applied in the concept stage. Another merit is that the optimization results are the requirements for the mechanical performance of the beam section instead of those of the shape and dimensions, bringing flexibility to the succeeding design.

A graph theory model using human nature structure

A graph theory model of the human nature structure( GMH) for machine vision and image/graphics processing is described in this paper. Independent from the motion and deformation of contours,the human nature structure( HNS) embodies the most basic movement characteristics of the body. The human body can be divided into basic units like head,torso,and limbs. Using these basic units,a graph theory model for the HNS can be constructed. GMH provides a basic model for human posture processing,and the outline in the perspective projection plane is the body contour of an image. In addition,the GMH can be applied to articulated motion and deformable objects,e. g.,in the design and analysis of body posture,by modifying mapping parameters of the GMH.

Novel Models and Algorithms of Load Balancing for Variable-structured Collaborative Simulation under HLA/RTI

High level architecture(HLA) is the open standard in the collaborative simulation field. Scholars have been paying close attention to theoretical research on and engineering applications of collaborative simulation based on HLA/RTI, which extends HLA in various aspects like functionality and efficiency. However, related study on the load balancing problem of HLA collaborative simulation is insufficient. Without load balancing, collaborative simulation under HLA/RTI may encounter performance reduction or even fatal errors. In this paper, load balancing is further divided into static problems and dynamic problems. A multi-objective model is established and the randomness of model parameters is taken into consideration for static load balancing, which makes the model more credible. The Monte Carlo based optimization algorithm(MCOA) is excogitated to gain static load balance. For dynamic load balancing, a new type of dynamic load balancing problem is put forward with regards to the variable-structured collaborative simulation under HLA/RTI. In order to minimize the influence against the running collaborative simulation, the ordinal optimization based algorithm(OOA) is devised to shorten the optimization time. Furthermore, the two algorithms are adopted in simulation experiments of different scenarios, which demonstrate their effectiveness and efficiency. An engineering experiment about collaborative simulation under HLA/RTI of high speed electricity multiple units(EMU) is also conducted to indentify credibility of the proposed models and supportive utility of MCOA and OOA to practical engineering systems. The proposed research ensures compatibility of traditional HLA, enhances the ability for assigning simulation loads onto computing units both statically and dynamically, improves the performance of collaborative simulation system and makes full use of the hardware resources.

Structures of GMC W37

We carried out observations toward the giant molecular cloud W 37 with the J = 1 - 0 transitions of 12CO, 13CO and C180 using the 13.7 m single-dish telescope at the Delingha station of Purple Mountain Observatory. Based on these CO lines, we calculated the column densities and cloud masses for molecular clouds with radial velocities around ＋20 km s-1. The gas mass of W 37, calculated from 13CO emission, is 1.7 × 10^5 M, above the criterion to be considered a giant molecular cloud. The dense ridge of W 37 is a dense filament, which is supercritical in terms of linear mass ratio. Dense clumps found by C180 emission are aligned along the dense ridge at regular intervals of about 2.8 pc, similar to the clump separation caused by large-scale ＇sausage instability＇. We confirm the identification of the giant molecular filament （GMF） G 18.0-16.8 and find a new giant filament, G 16.5-15.8, located ~ 0.7° to the west of G 18.0-16.8. Both GMFs are not gravitationally bound, as indicated by their low linear mass ratio （- 80 M pc-l）. We compared the gas temperature map with the dust temperature map from Herschel images, and found similar structures. The spatial distributions of class I objects and the dense clumps are reminiscent of triggered star formation occurring in the northwestern part of W 37, which is close to NGC 6611.

Symmetry properties and widths of the filamentary structures in the Orion A giant molecular cloud

We identify 225 filaments from an H2 column density map constructed using simultaneous 12CO,13CO and C18O(J=1-0) observations carried out as a part of the Milky Way Imaging Scroll Painting(MWISP) project.We select 46 long filaments with lengths above 1.2 pc to analyze the filament column density profiles.We divide the selected filaments into 397 segments and calculate the column density profiles for each segment.The symmetries of the profiles are investigated.The proportion of intrinsically asymmetrical segments is 65.3%,and that of intrinsically symmetrical ones is 21.4%.The typical full width at half maximum(FWHM) of the intrinsically symmetrical filament segments is - 0.67 pc with the Plummer-like fitting,and - 0.50 pc with the Gaussian fitting,respectively.The median FWHMs derived from the second-moment method for intrinsically symmetrical and asymmetrical profiles are - 0.44 and 0.46 pc,respectively.Close association exists between the filamentary structures and the YSOs in the region.

Abnormal Behavior Detection Using Deep-Learning-Based Video Data Structuring

With the increasing number of digital devices generating a vast amount of video data,the recognition of abnormal image patterns has become more important.Accordingly,it is necessary to develop a method that achieves this task using object and behavior information within video data.Existing methods for detecting abnormal behaviors only focus on simple motions,therefore they cannot determine the overall behavior occurring throughout a video.In this study,an abnormal behavior detection method that uses deep learning(DL)-based video-data structuring is proposed.Objects and motions are first extracted from continuous images by combining existing DL-based image analysis models.The weight of the continuous data pattern is then analyzed through data structuring to classify the overall video.The performance of the proposed method was evaluated using varying parameter settings,such as the size of the action clip and interval between action clips.The model achieved an accuracy of 0.9817,indicating excellent performance.Therefore,we conclude that the proposed data structuring method is useful in detecting and classifying abnormal behaviors.