Oriented Bounding Box Object Detection Model Based on Improved YOLOv8

In the study of oriented bounding boxes(OBB)object detection in high-resolution remote sensing images,the problem of missed and wrong detection of small targets occurs because the targets are too small and have different orientations.Existing OBB object detection for remote sensing images,although making good progress,mainly focuses on directional modeling,while less consideration is given to the size of the object as well as the problem of missed detection.In this study,a method based on improved YOLOv8 was proposed for detecting oriented objects in remote sensing images,which can improve the detection precision of oriented objects in remote sensing images.Firstly,the ResCBAMG module was innovatively designed,which could better extract channel and spatial correlation information.Secondly,the innovative top-down feature fusion layer network structure was proposed in conjunction with the Efficient Channel Attention(ECA)attention module,which helped to capture inter-local cross-channel interaction information appropriately.Finally,we introduced an innovative ResCBAMG module between the different C2f modules and detection heads of the bottom-up feature fusion layer.This innovative structure helped the model to better focus on the target area.The precision and robustness of oriented target detection were also improved.Experimental results on the DOTA-v1.5 dataset showed that the detection Precision,mAP@0.5,and mAP@0.5:0.95 metrics of the improved model are better compared to the original model.This improvement is effective in detecting small targets and complex scenes.

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.

一种改进Oriented RepPoints的遥感图像有向目标检测

为解决Oriented RepPoints算法在遥感图像有向目标检测中因遥感图像背景干扰信息较多和目标尺度大小不一所导致的检测精度不高、易漏检误检等问题,提出一种改进Oriented RepPoints的遥感图像有向目标检测方法MA-RPDet(Mixed Attention RepPoints Detector).首先,采用了PVTv2作为主干网络,该网络利用线性空间缩减自注意力机制提取出更具局部连续性的特征图,并保持与卷积运算类似的线性复杂度.其次,在特征融合阶段设计了串联性混合注意力模块,进一步强化了重要特征,促进了多尺度特征的高效交互.最后,引入平滑GIoU损失函数对模型学习策略进行优化,提高了检测精度.在两个遥感图像目标检测数据集DOTA和HRSC2016上的实验结果表明,所提方法的检测精度mAP分别达到了77.19%和90.3%,均高于其他对比算法,证明了本文方法的有效性.

DESIGN OF WINDOW BASED AND OBJECT ORIENTED GUI

This paper discusses the design concept and method about window based and object oriented Graphic User Interface(GUI),and describes the definition of each class in detail. It is developed with Watcom C ++ in DOS environment.The GUI can be redeveloped conveniently and effectively by users.It consists of window,popup menu,icon,button and other components.

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.

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.

Detecting Design Patterns in Object-Oriented Program Source Code by Using Metrics and Machine Learning

Detecting well-known design patterns in object-oriented program source code can help maintainers understand the design of a program. Through the detection, the understandability, maintainability, and reusability of object-oriented programs can be improved. There are automated detection techniques;however, many existing techniques are based on static analysis and use strict conditions composed on class structure data. Hence, it is difficult for them to detect and distinguish design patterns in which the class structures are similar. Moreover, it is difficult for them to deal with diversity in design pattern applications. To solve these problems in existing techniques, we propose a design pattern detection technique using source code metrics and machine learning. Our technique judges candidates for the roles that compose design patterns by using machine learning and measurements of several metrics, and it detects design patterns by analyzing the relations between candidates. It suppresses false negatives and distinguishes patterns in which the class structures are similar. As a result of experimental evaluations with a set of programs, we confirmed that our technique is more accurate than two conventional techniques.

Product Family Design Methodology Using Object-Oriented Approach

The serious competition environment of global marke t requests the enterprise to change traditional product development strategy and a dopt new theory in order to meet diverse customer needs while maintaining near m ass production efficiency, which is the main philosophy of mass customization. P roduct family design is research focus at present and also is the core technolog y of DFMC (design for mass customization). Firstly, this paper explores the fund amental issues of product family, such as concepts of modularity, commonality/di versity, product platform and product family architecture etc. We compare the te rminology between product family and object-oriented approach in the next step. Thirdly, this paper puts forwards one product family design methodology based o n product platform and under different phase of product life cycle constrains, f or example, functional, assembly and service etc. At the end section of this pap er, we applied, the object-oriented approach in above mentioned product family design methodology to realize the design process. In one word, this paper propos ed one product family design methodology based on object oriented approach and p roduct life cycle consideration, especially the conjointness of characteristic o f OOA and concepts of product family. The main property of OOA are encapsulation , inherence and polymorphism. Encapsulation can represent the module or building blocks of product family. Inherence can be extended to describe the modularity and commonality, and also be used to construct variant space. Alternative specif ic of product family architecture can be embodied with polymorphism. And fin aly, we give the future work contents. In order to derive the product platform a nd achieve modularity and commonality/diversity, interface management between bu ilding block is necessary. The question is how the OOA can be applied in interfa ce management to get our aim OOA is the basis of many information management sy stem, then the question is how to build one system to manage the information of product family and support mass customization The third question is how to deve lop one computer aided tool to facilitate the application of OOA for product fam ily design, even be used to category of design for mass customization.

Object-Oriented Design for FDTD Visual Scientific Computing

A scheme for general purposed FDTD visual scientific computing software is introduced in this paper using object-oriented design (OOD) method. By abstracting the parameters of FDTD grids to an individual class and separating from the iteration procedure, the visual software can be adapted to more comprehensive computing problems. Real-time gray degree graphic and wave curve of the results can be achieved using DirectX technique. The special difference equation and data structure in dispersive medium are considered, and the peculiarity of parameters in perfectly matched layer are also discussed.

Quantifying Reusability of Object Oriented Design: A Testability Perspective

The quality factor of class diagram is critical because it has a significant influence on overall quality of the product, delivered finally. Testability analysis, when done early in the software creation process, is a criterion of critical importance to software quality. Reusability is an important quality factor to testability. Its early measurement in object oriented software especially at design phase, allows a design to be reapplied to a new problem without much extra effort. This research paper proposes a research framework for quantification process and does an extensive review on reusability of object oriented software. A metrics based model “Reusability Quantification of Object Oriented Design” has been proposed by establishing the relationship among design properties and reusability and justifying the correlation with the help of statistical measures. Also, “Reusability Quantification Model” is empirically validated and contextual significance of the study shows the high correlation for model acceptance. This research paper facilitates to software developers and designer, the inclusion of reusability quantification model to access and quantify software reusability for quality product.

Dynamic Object-Oriented Model of Concurrent Design Process

This article reports our research progress in concurrent design theory and methodology.The idea of Micro-Design-Cycle is introduced to provide a mechanism of coordinating variousdesign activities in parallel as much as possible.An Object-Life-Cycle diagram is developedas an instrument to visualize the Micro-Design-Cycle and as a practical tool of timing variousactivities being performed in Micro-Design-Cycles.

ORDERED-OBJECT-ORIENTED METHOD:A NEW APPROACH OF SAMPLE PART CALCULATION AND DESIGN

This paper proposed a new approach of sample part classification and design, a so called Or-dered-object-oriented method (O-O-O method). Based on the theory of neural networks, fuzzy clustering algorithm and adaptive pattern recognition, O-O-O method can be used to classify and design the sample parts automatically. The basic theory, the main step as well as the characteristics of the method are analysed. The construction of the ordered object in application is also presented in this paper.

Method of Establishing Object-Oriented System Structure for Decision Support System

In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, and a new method of eight specific steps is proposed to establish object oriented system structure of DSS by using the method of O S chart, which is applied successfully to the development of the DSS for the energy system ecology engineering research of the Wangheqiu country. Supplying many scientific effective computing models, decision support ways and a lot of accurate reliable decision data, the DSS plays a critical part in helping engineering researchers to make correct decisions. Because the period for developing the DSS is relatively shorter, the new way improves the efficiency of establishing DSS greatly. It also makes the DSS of system structure more flexible and easy to expand.

GEAR BOX CONCEPT DESIGN EXPERT SYSTEM OF NC MILLER BASED ON OBJECT─ORIENTED TECHNOLOGY

The method and basic structure of object─oriented knowledge representation are presented in detail and the hierarchical structurc of object description is explained Based on object─oriented technology.the gear box concept design expert cistem of NC miller (GBCDLS) has been developed and applied to practical use.Moreover. the design principlc and techniques of GBCDES are discussed and analyzed. and the main functions of GBCDES are described. From the results of applications.it can be seen that GBCDES is effective and successful.

OBJECT ORIENTED DATA MODELLING WITH APPLICATIONS TO CAD

An object oriented data modelling in computer aided design (CAD) databases is focused. Starting with the discussion of data modelling requirements for CAD applications, appropriate data modelling features are introduced herewith. A feasible approach to select the “best” data model for an application is to analyze the data which has to be stored in the database. A data model is appropriate for modelling a given task if the information of the application environment can be easily mapped to the data model. Thus, the involved data are analyzed and then object oriented data model appropriate for CAD applications are derived. Based on the reviewed object oriented techniques applied in CAD, object oriented data modelling in CAD is addressed in details. At last 3D geometrical data models and implementation of their data model using the object oriented method are presented.

Modeling of Intelligent Integrated Network Management System Using Object Oriented Approach *

The concept of intelligent integrated network management (IINM) is briefly introduced. In order to analyze, design and implement IINM successfully, object oriented approach is testified to be an effective and efficient way. In this paper, object oriented technique is applied to the structural model of IINM system, The Domain object class and the MU object class are used to represent the manager and the managed resources. Especially, NM IA is introduced which is a special object class with intelligent behaviors to manage the resources efficiently.

Discussion and Practice of Exam-oriented Skills in Landscape "Quick Design"

Landscape quick design is an important approach to test students' scheme performance ability,and also a vital issue in current landscape design teaching.The study has discussed methods to improve ability for quick design in short time and employment competition of students of landscape major.By taking landscaping skill competition training in higher vocational schools of Zhejiang Province for example,from the perspective of characteristics of quick design,quick design training has been divided into six modules which are basic quality,schematic design,design theme,plants disposition,drawing effect and exam-oriented strategies;key points of training and exam-oriented strategies of each module have been illustrated at length;and finally five stages of training process have been listed,providing new thought for teaching of landscape quick design.

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 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.

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.