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.

基于改进Oriented R-CNN的旋转框麦穗检测与计数模型

为对干扰、遮挡等复杂的田野环境中麦穗进行精准定位与计数,该研究提出了一种改进的Oriented R-CNN麦穗旋转框检测与计数方法,首先在主干网络中引入跨阶段局部空间金字塔(spatial pyramid pooling cross stage partial networks,SPPCSPC)模块扩大模型感受野,增强网络感知能力;其次,在颈网络中结合路径聚合网络(PANet,path aggregation network)和混合注意力机制(E2CBAM,efficient two convolutional block attention module),丰富特征图包含的特征信息;最后采用柔性非极大值抑制算法(Soft-NMS,soft-non maximum suppression)优化预测框筛选过程。试验结果显示,改进的模型对复杂环境中的麦穗检测效果良好。相较原模型,平均精确度均值mAP提高了2.02个百分点,与主流的旋转目标检测模型Gliding vertex、R3det、Rotated Faster R-CNN、S2anet和Rotated Retinanet相比,mAP分别提高了4.99、2.49、3.94、2.25和4.12个百分点。该研究方法利用旋转框准确定位麦穗位置,使得框内背景区域面积大幅度减少,为实际观察麦穗生长状况和统计数量提供了一种有效的方法。

Estimation of cancer cell migration in biomimetic random/oriented collagen fiber microenvironments

Increasing data indicate that cancer cell migration is regulated by extracellular matrixes and their surrounding biochemical microenvironment,playing a crucial role in pathological processes such as tumor invasion and metastasis.However,conventional two-dimensional cell culture and animal models have limitations in studying the influence of tumor microenvironment on cancer cell migration.Fortunately,the further development of microfluidic technology has provided solutions for the study of such questions.We utilize microfluidic chip to build a random collagen fiber microenvironment(RFM)model and an oriented collagen fiber microenvironment(OFM)model that resemble early stage and late stage breast cancer microenvironments,respectively.By combining cell culture,biochemical concentration gradient construction,and microscopic imaging techniques,we investigate the impact of different collagen fiber biochemical microenvironments on the migration of breast cancer MDA-MB-231-RFP cells.The results show that MDA-MB-231-RFP cells migrate further in the OFM model compared to the RFM model,with significant differences observed.Furthermore,we establish concentration gradients of the anticancer drug paclitaxel in both the RFM and OFM models and find that paclitaxel significantly inhibits the migration of MDA-MB-231-RFP cells in the RFM model,with stronger inhibition on the high concentration side compared to the low concentration side.However,the inhibitory effect of paclitaxel on the migration of MDA-MB-231-RFP cells in the OFM model is weak.These findings suggest that the oriented collagen fiber microenvironment resembling the late-stage tumor microenvironment is more favorable for cancer cell migration and that the effectiveness of anticancer drugs is diminished.The RFM and OFM models constructed in this study not only provide a platform for studying the mechanism of cancer development,but also serve as a tool for the initial measurement of drug screening.

Analysis of the Effect of Problem-Oriented Nursing Intervention on Patients with Lower Extremity Arteriosclerosis Obliterans in Vascular Surgery

Objective: To analyze the effect of problem-oriented nursing intervention on patients with lower extremity arteriosclerosis obliterans (ASO) in vascular surgery. Methods: The clinical data of 128 patients with lower extremity ASO in vascular surgery were selected and randomly divided into groups A and B, with 64 cases each. Group A is the control group, and Group B is the observation group. Group A received the routine nursing intervention, and Group B received the problem-oriented nursing intervention. The compliance, self-care ability, psychological state, quality of life, and nursing satisfaction of the two groups of patients were evaluated based on various indicators. Results: After the intervention, the evaluation of self-care ability (ESCA) score of the patients in Group B was higher than that of Group A, and the symptom checklist-90 (SCL-90) score was lower than that of Group A. The differences were significant (t = 10.019, t = 3.118, P < 0.01). After the intervention, the World Health Organization Quality of Life Brief (WHOQOL-BREF) index scores of the two groups increased and the increase in Group B was significantly higher than Group A (P < 0.001). The compliance rate of Group B (62/ 96.88%) was higher than that of Group A (52/ 81.25%), and the difference was extremely significant (χ2 = 8.020, P < 0.01). Conclusion: Problem-oriented nursing intervention for patients with lower extremity ASO in vascular surgery improved the patient’s self-care ability, and quality of life, reduced the patient’s negative emotions, and enhanced their overall satisfaction.

Performance releaser with smart anchor learning for arbitrary‐oriented object detection

Arbitrary‐oriented object detection is widely used in aerial image applications because of its efficient object representation.However,the use of oriented bounding box aggravates the imbalance between positive and negative samples when using one‐stage object detectors,which seriously decreases the detection accuracy.We believe that it is the anchor learning strategy(ALS)used by such detectors that needs to take the responsibility.In this study,three perspectives on ALS design were summarised and ALS—Performance Releaser with Smart Anchor Learning(PRSAL)was proposed.Performance Releaser with Smart Anchor Learning is a dynamic ALS that utilises anchor classification ability as an equivalent indicator to anchor box regression ability,this allows anchors with high detection potential to be filtered out in a more reasonable way.At the same time,PRSAL focuses more on anchor potential and it is able to automatically select a number of positive samples that far exceed that of other methods by activating anchors that previously had a low spatial overlap,thereby releasing the detection performance.We validate the PRSAL using three remote sensing datasets—HRSC2016,DOTA and UCAS‐AOD as well as one scene text dataset—ICDAR 2013.The experimental results show that the proposed method gives substantially better results than existing models.

Object-Oriented Modeling of the Variation of Acceleration and Deceleration Characteristics in Relation to Speed Bands for Railway Vehicles

Automated operation and artificial intelligence technology have become essential for ensuring the safety, efficiency, and punctuality of railways, with applications such as ATO (Automatic Train Operation). In this study, the authors propose a method to efficiently simulate the kinematic characteristics of railroad vehicles depending on their speed zone. They utilized the function overloading function supported by a programming language and applied the fourth-order Lunge-Kutta method for dynamic simulation. By constructing an object model, the authors calculated vehicle characteristics and TPS and compared them with actual values, verifying that the developed model represents the real-life vehicle characteristics accurately. The study highlights potential improvements in automated driving and energy consumption optimization in the railway industry.

厄瓜多尔Oriente盆地白垩系Napo组LU亚段沉积模式

厄瓜多尔Oriente盆地北部白垩系Napo组LU亚段地层油气资源极其丰富,具有较大的油气勘探潜力,由于目前对LU亚段地层沉积模式认识不清晰,极大程度上限制了研究区进一步勘探开发。依据LU亚段岩芯观察、测井、成熟度分析以及镜下薄片等资料,通过岩芯岩性、结构等岩石学特征,沉积构造、生物遗迹化石、沉积韵律等沉积学特征,以及测井相标志认为,研究区LU亚段地层发育于潮汐作用为主的海陆过渡环境,并在前人研究基础上提出潮控河口湾与陆棚之间存在过渡带沉积,形成了潮控河口湾-过渡带-陆棚沉积体系,识别出潮汐水道、潮汐砂坝、砂坪、海绿石砂席、混合坪、陆棚泥和灰质滩共7种沉积微相,其中,优势储层相带为潮汐水道和潮汐砂坝,砂坪次之。建立研究区潮控河口湾-过渡带-陆棚沉积模式,以期对Oriente盆地白垩系Napo组油气勘探提供有利的科学依据。

Object oriented land cover classification using ALS and GeoEye imagery over mining area

An object oriented coal mining land cover classification method based on semantically meaningful image segmentation and image combination of GeoEye imagery and airborne laser scanning (ALS) data was presented. First, DEM, DSM and nDSM (normalized Digital Surface Model, nDSM) were extracted from ALS data. The GeoEye imagery and DSM data were combined to create segmented objects based on neighbor regions merge method. Then 10 kinds of objects were extracted. Different kinds of vegetation objects, including crop, grass, shrub and tree, can be extracted by using NDVI and height value of nDSM. Water and coal pile field was extracted by using NDWI and the standard deviation of DSM method. Height differences also can be used to distinguish buildings from road and vacant land, and accurate building contour information can be extracted by using relationship of neighbor objects and morphological method. The test result shows that the total classification accuracy of the presented method is 90.78% and the kappa coefficient is 0.891 4.

A Study on the Design for Object-Oriented Adaptive Decision-Making Teams

The modern war features a highly distributed coordination. In the face of great time constrains, it is important to change command organizations to adapt to the real environment. Therefore it's a key step to set up adaptive C2 teams. In this paper, the relational problems about distributed C2 organizational structure adaptation are discussed, and the methodology for team decision making design based on the object oriented technique is studied.

A Comprehensive Review on Pixel Oriented and Object Oriented Methods for Information Extraction from Remotely Sensed Satellite Images with a Special Emphasis on Cryospheric Applications

Image classification is one of the most basic operations of digital image processing. The present review focuses on the strengths and weaknesses of traditional pixel-based classification (PBC) and the advances of object-oriented classification (OOC) algorithms employed for the extraction of information from remotely sensed satellite imageries. The state-of-the-art classifiers are reviewed for their potential usage in urban remote sensing (RS), with a special focus on cryospheric applications. Generally, classifiers for information extraction can be divided into three catalogues: 1) based on the type of learning (supervised and unsupervised), 2) based on assumptions on data distribution (parametric and non-parametric) and, 3) based on the number of outputs for each spatial unit (hard and soft). The classification methods are broadly based on the PBC or the OOC approaches. Both methods have their own advantages and disadvantages depending upon their area of application and most importantly the RS datasets that are used for information extraction. Classification algorithms are variedly explored in the cryosphere for extracting geospatial information for various logistic and scientific applications, such as to understand temporal changes in geographical phenomena. Information extraction in cryospheric regions is challenging, accounting to the very similar and conflicting spectral responses of the features present in the region. The spectral responses of snow and ice, water, and blue ice, rock and shadow are a big challenge for the pixel-based classifiers. Thus, in such cases, OOC approach is superior for extracting information from the cryospheric regions. Also, ensemble classifiers and customized spectral index ratios (CSIR) proved extremely good approaches for information extraction from cryospheric regions. The present review would be beneficial for developing new classifiers in the cryospheric environment for better understanding of spatial-temporal changes over long time scales.

Analysis and Design of Soils and Terrain Digital Database (SOTER) Management System Based on Object-Oriented Method

A SOTER management system was developed by analyzing, designing, programming, testing, repeated proceeding and progressing based on the object-oriented method. The function of the attribute database management is inherited and expanded in the new system. The integrity and security of the SOTER database are enhanced. The attribute database management, the spatial database management and the model base are integrated into SOTER based on the component object model (COM), and the graphical user interface (GUI) for Windows is used to interact with clients, thus being easy to create and maintain the SOTER, and convenient to promote the quantification and automation of soil information application.

Research on Modeling and Reusing of Computer Numerical Control Software with Object-oriented Technology

To improve the reusable and configurable ability of computer numerical control ( CNC ) software, a new method to construct reusable model of CNC software with object-oriented (OO) technology is proposed. Based on analyzing function of CNC software, the article presents how to construct a general class library of CNC software with OO technology. Most function modules of CNC software can he reused because of inheritable capability of classes. Besides, the article analyzes the object relational model in request/report mode, and multitask concurrent management model, which can he applied on double-CPU hardware platform and Windows 95/NT environment. Finally, the method has been successfully applied on a turning CNC system and a milling CNC system, and some function modules have been reused.

Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

With the wide use of high-resolution remotely sensed imagery, the object-oriented remotely sensed informa- tion classification pattern has been intensively studied. Starting with the definition of object-oriented remotely sensed information classification pattern and a literature review of related research progress, this paper sums up 4 developing phases of object-oriented classification pattern during the past 20 years. Then, we discuss the three aspects of method- ology in detail, namely remotely sensed imagery segmentation, feature analysis and feature selection, and classification rule generation, through comparing them with remotely sensed information classification method based on per-pixel. At last, this paper presents several points that need to be paid attention to in the future studies on object-oriented RS in- formation classification pattern: 1) developing robust and highly effective image segmentation algorithm for multi-spectral RS imagery; 2) improving the feature-set including edge, spatial-adjacent and temporal characteristics; 3) discussing the classification rule generation classifier based on the decision tree; 4) presenting evaluation methods for classification result by object-oriented classification pattern.

FRAMEWORKS FOR GENERALIZATION CONSTRAINTS AND OPERATIONS BASED ON OBJECT-ORIENTED DATA STRUCTURE IN DATABASE GENERALIZATION

The constraints and the operations play an important role in database generalization.They guide and govern database generalization.The constraints are translation of the required conditions that should take into account not only the objects and relationships among objects but also spatial data schema (classification and aggregation hierarchy) associated with the final existing database.The operations perform the actions of generalization in support of data reduction in the database.The constraints in database generalization are still lack of research.There is still the lack of frameworks to express the constraints and the operations on the basis of object_oriented data structure in database generalization.This paper focuses on the frameworks for generalization operations and constraints on the basis of object_oriented data structure in database generalization.The constraints as the attributes of the object and the operations as the methods of the object can be encapsulated in classes.They have the inheritance and polymorphism property.So the framework of the constraints and the operations which are based on object_oriented data structure can be easily understood and implemented.The constraint and the operations based on object_oriented database are proposed based on object_oriented database.The frameworks for generalization operations,constraints and relations among objects based on object_oriented data structure in database generalization are designed.The categorical database generalization is concentrated on in this paper.

A Universal Object Oriented Expert System Frame Work for Fault Diagnosis

The paper presents a universal fault diagnostic expert system frame work. The frame work is characterized by two basic features. The first includes a fault diagnostic strategy which utilizes the fault classification and checks knowledge about unit under test. The degree of accuracy to which faults are located is improved by using fault classification knowledge. The second characteristic is object oriented inference mechanism using message passing. Object orientation in inference mechanism improved inference efficiency. The developed framework demonstrates its effectiveness and superiority compared to earlier approaches using case studies.

The IRIS Development Platform and Proposed Object-Oriented Data Base

Various code development platforms, such as the ATHENA Framework [1] of the ATLAS [2] experiment encounter lengthy compilation/linking times. To augment this situation, the IRIS Development Platform was built as a software development framework acting as compiler, cross-project linker and data fetcher, which allow hot-swaps in order to compare various versions of software under test. The flexibility fostered by IRIS allowed modular exchange of software libraries among developers, making it a powerful development tool. The IRIS platform used input data ROOT-ntuples [3];however a new data model is sought, in line with the facilities offered by IRIS. The schematic of a possible new data structuring—as a user implemented object oriented data base, is presented.

Exploring heteroepitaxial growth and electrical properties of α-Ga_(2)O_(3) films on differently oriented sapphire substrates

This study explores the epitaxial relationship and electrical properties of α-Ga_(2)O_(3) thin films deposited on a-plane, mplane, and r-plane sapphire substrates. We characterize the thin films by X-ray diffraction and Raman spectroscopy, and elucidate thin film epitaxial relationships with the underlying sapphire substrates. The oxygen vacancy concentration of α-Ga_(2)O_(3) thin films on m-plane and r-plane sapphire substrates are higher than α-Ga_(2)O_(3) thin film on a-plane sapphire substrates. All three thin films have a high transmission of over 80% in the visible and near-ultraviolet regions, and their optical bandgaps stay around 5.02–5.16 eV. Hall measurements show that the α-Ga_(2)O_(3) thin film grown on r-plane sapphire has the highest conductivity of 2.71 S/cm, which is at least 90 times higher than the film on a-plane sapphire. A similar orientation-dependence is seen in their activation energy as revealed by temperature-dependent conductivity measurements, with 0.266, 0.079, and 0.075eV for the film on a-, m-, r-plane, respectively. The origin of the distinct transport behavior of films on differently oriented substrates is suggested to relate with the distinct evolution of oxygen vacancies at differently oriented substrates. This study provides insights for the substrate selection when growing α-Ga_(2)O_(3) films with tunable transport properties.

Constructing an ion‐oriented channel on a zinc electrode through surface engineering

The inherent shortcomings of a zinc anode in aqueous zinc‐ion batteries(ZIBs)such as zinc dendrites and side reactions severely limit their practical application.Herein,to address these issues,an ion‐oriented transport channel constructed by graphdiyne(GDY)nanowalls is designed and grown in situ on the surface of a zinc electrode.The vertically stacked GDY nanowalls with a unique hierarchical porous structure and mechanical properties form a nanomesh‐like interface on the zinc electrode,acting as an ion‐oriented channel,which can efficiently confine the segmented growth of zinc metal in microscopic regions of hundreds of nanometers.In those microscopic regions,the uniform domain current density is effortlessly maintained compared with a large surface area,thereby inhibiting zinc dendrites effectively.Besides,due to the presence of the ion‐oriented channel,the modified zinc anode demonstrates long‐term stable zinc plating/stripping performance for more than 600 h at 1 mAh cm^(−2)in an aqueous electrolyte.In addition,full‐cells coupled with MnO2 show high specific capacity and power density,as well as excellent cycling stability with a capacity retention of 82%after 5000 cycles at 1 A g^(−1).This work provides a feasible and accessible surface engineering approach to modify the electrode interface for confined and dendrite‐free zinc deposition in aqueous ZIBs.

Complexity of Injective Homomorphisms to Small Tournaments, and of Injective Oriented Colourings

Several possible definitions of local injectivity for a homomorphism of an oriented graph G to an oriented graph H are considered. In each case, we determine the complexity of deciding whether there exists such a homomorphism when G is given and H is a fixed tournament on three or fewer vertices. Each possible definition leads to a locally-injective oriented colouring problem. A dichotomy theorem is proved in each case.

The Building Extraction Based on Object Oriented Classification Method in High Vegetation Coverage Area

Quickly extraction of building information technology is an important application in urban development planning, electronic information, national defense and others. This paper takes Landsat-8 multispectral and panchromatic data as data source, using the local variance method to select the optimal segmentation scale, normalized difference vegetation index (NDVI) and the normalized building index (NDBI) and panchromatic brightness value of an object oriented classification rule extraction. The high vegetation coverage area of buildings, and through the spatial relationships and distinguishing feature of collections of buildings independent buildings and villages. The results showed that Google earth high resolution image analysis and accuracy evaluation. the results of the extraction based on the overall accuracy of village extraction was 83%, the accuracy of extraction of independent buildings was 70%, according to the L8 remote sensing data, object oriented classification method can quickly and accurately extract the high vegetation coverage area of the building.