Integration of object-oriented analysis and performance simulation for engineering computer-based systems

Change Vector Analysis (CVA) is an important change detection method for remote sensing imagery with medium and low resolution. Traditional CVA is a pixel-based method, which is insufficient for high-resolution (HR) imagery. An object-oriented change vector analysis method (OCVA) is proposed in the paper. Image segmentation method was used to get image objects. The object histogtam was extracted as the feature of the image object at different bands. G statistic was employed to measure the distance between the object histograms at two times. Change vector of the object was built by the histogram distance at different bands. The heterogeneity of the object was measured by the magnitude of the object change vector. The threshold to detect change/no change objects was decided by Otsu method which maximizes the variance between change objects and unchanged objects. The experimental results on QuickBird images show that OCVA can make full use of the spatial information in HR images and get higher accuracy than pixel-based CVA.

Smart City is one of the Smart Initiatives that tries to provide solutions to parking problems that are found in big cities. The growth of the vehicle population is not matched by the growth of parking infrastructure, which raises various problems such as illegal parking, traffic jams, and driving safety. Thanks to the massive evolution of the Internet of Things, the Smart Parking idea became a breakthrough in solving the growing parking problem. In this paper, we explain the prototype development of the Smart Parking System using the Internet of Things which has three subsystems, namely embedded systems, as well as Android and web-based applications. Smart Parking System’s software was developed using the Object-Oriented Analysis and Design (OOAD) method and has been tested using black-box testing with 41 test cases that were successfully received.

In the paper, we adopted an object-oriented image analysis method to detect and classify road vehicles from airborne color digital orthoimagery at a ground pixel resolution of 20cm. Firstly; a vector-generated road mask was used to constrain detection and classification of vehicles to road region. Secondly, image segmentation and edge detection algorithms were performed to separate vehicles from the background in the road region. Then, a fuzzy logic classifier was constructed to classify the extracted object regions into the vehicle and the non-vehicle regions by using the feature information of image objects. Finally, based on the calculated average length and width of vehicles, we classified vehicles into three categories, that is, small, medium and big. And the counts of the three vehicle classes were derived. The automatic counts match manual counts very well.

This study aims at improving the constructability of design solutions by inte grating site construction problems, which are related to the design, with the design's main functions. A full process analysis was carried out on the design functions of concrete framed office buildings whereby site problems were traced back to the relevant design stages. Design processes that significantly contribute to these problems were highlighted, along with their data flows. An object‐oriented analysis (OOA) method was then applied to model those processes. Proceedings through the five major activities of Coad & Yourdon's OOA method, a complete OOA model was developed. This technique has proved to be very effective in producing a well structured data model with the consequence of being easily mapped into an object‐oriented development environment. An integrated object‐oriented system was also developed, which attempts to use essential design information, at an early stage of the design process, to improve the constructability of the design.

In recent years, there has been a demand for Web applications with complex functions. In addition, most web applications efficiently manage data based on databases. While the key and critical dimension of developing these Web applications is analysis and design, most object-oriented analysis and design methods do not have a consistent view of the database. In addition, Java Enterprise Edition (EE) -based technologies are used in Web application implementations, but they do not provide any correlation with the database. On the other hand, as users' demands for security increase, security becomes more important. To this end, Java EE and database systems provide security solutions. However, it does not provide any correlation with object-oriented analysis and design methodology. As a result, it is difficult to develop secure web applications in a consistent way from analysis to implementation. In this paper, we propose a consistent software development methodology from analysis to implementation of secure web applications. The proposed software development methodology for web application development uses UMLsec, a security-emphasized modeling language, and object-relational (O-R) mapping for relational database design. It also uses Java servlets and SQL to implement analysis and design results based on role-based access control (RBAC). The software development methodology for the secure web application proposed in this paper has been applied to the development of the online banking system, from the design stage of the user's requirements analysis to the implementation of the web application.

Object-oriented structural and geometric analysis methods for truss structures are proposed. The methods are based on the iterative relaxation of nodal unbalanced forces by moving the nodes. The entities appeared in truss analysis are modeled as classes, and their class hierarchy is established. The knowledge about a truss node, a truss member, a material, and a sectional shape of the member are extracted and constructed as a knowledge base in an object-oriented manner. The object-oriented structural analysis is found to be valid for material and geometric nonlinearities, and the object-oriented geometric analysis where a kinematic problem is converted into a problem for a force equilibrium at the nodes is also found to be effective for determining the geometry of variable geometry trusses. The whole system is written in an object-oriented language, Smalltalk, and several results on structural and geometric analysis are presented. The speed of the computation is discussed along with the size of the structures and the over-relaxation factor. The extension of the knowledge base is also discussed.

We present a modelling approach for a decision support system to support interactive production scheduling. The architecture of the model can be subdivided in an offline planning and an online control module. We concentrate on the offline planning in this paper. This module consists of three components: analysis, construction and evaluation used within a loop. In the analysis stage a model describing the problem at hand is interactively developed. For the scheduling problem described by this model a solution is generated in the construction phase. The solution is evaluated interactively. We use object-oriented analysis and design methods to integrate declarative representations and algorithmic solutions. A first prototype is developed to evaluate this approach.

This article introduces the design and implementation of a fishery forecasting system based on Radial Basis Function (RBF) neural network. The system was developed using the CLient/Server architecture, the C# programming language in the environment of Visual Studio 2008 on the Windows7 platform. It draws knowledge from RBF neural network theory, the production historical data of pelagic fishery and the marine environment data. The system uses the Object-Oriented analysis and design method. It can quickly obtain the forecast results available to users through inputting marine environment data information and the RBF neural network model. The forecasting system includes three major functional modules, namely preprocessing fishery production data, matching production data and environmental data, training RBF neural network and making predictions. Experiments have shown that this forecasting system can generate accurate and effective pelagic fishery knowledge.

This paper compares the current situation of development ,clarifies the problems that need to be solved by the information platform of rural land sublease, and then constructs a smartphone-based information platform and draws conclusions and suggestions, firstly, based on the analysis of rural land sublease policy and platform as a realistic basis, the design of rural land sublease information platform is carried out by using comparative analysis method and object-oriented analysis and design method. By constructing and analyzing the rural land sublease information platform, we deepen the informationization of land sublease government services and enhance the dynamic land title registration function. Based on the construction of the rural land sublease information platform, the government is promoted to explore the orderly opening and utilization of information resources, and provide all-in-one land sublease governmental information services in line with the needs and user habits of the new era. In today's new era of mobile network, the cell phone platform can better serve to realize the rights and obligations of land sublease regulated by the Land Contract Law of the People's Republic of China, improve the efficiency of rural land resources, and promote rural revitalization. With the gradual establishment of land sublease management information systems in various places, government information services such as land title registration inquiries are gradually standardized. However, there are still problems such as fragmentation of information on land sublease management and transactions, asymmetry of land sublease information, and low technical level.

Road blockage information extraction from a single-phase postdisaster image is difficult because roads are narrow and easily covered by vegetation. The traditional object-oriented image analysis method is restrictive, and its detection is slow. A deep learning algorithm, i.e., the convolution neural network (CNN), is applied to rapidly extract road blockage information. An algorithm for sample generation is designed to construct a typical sample library for CNN training, and an appropriate CNN structure and a complete detection process are designed to extract road blockage information. Finally, by taking the Jiuzhaigou earthquake on August 8, 2017, as an example, experimental verification is carried out. The kappa coefficient and the F1 score of the results are 77.60% and 87.95%, respectively. The extraction of road blockages can be completed with an efficiency of 14.59 km2 per hour. The requirements for disaster emergency monitoring can be met by the accuracy and efficiency of this method, which are better than those of the traditional object-oriented method.

This research proposed an object-oriented method to obtain the distribution of tree coverage in urban environment using 0.6m aerial multi-spectral images. With the support of eCognition Software, the whole tree coverage mapping process included the following steps. Firstly, selecting a set of appropriate parameters by trial and error process to obtain an optimal segmentation result for tree coverage. Then, a two-level class hierarchy was constructed combining the Nearest-Neighbor Classifier and the Fuzzy logic classifier. After classification, we created two abstract classes (tree and non-tree) and selected Error Matrix Based on Samples to perform accuracy assessment for tree coverage mapping. The result of accuracy assessment showed that the proposed method had produced 96.4% overall accuracy and 92.6% KIA. Finally, we calculated the tree coverage rate based on the statistical result of sum area of tree coverage classification.

Perhaps the most important reason Systems Engineering exists as a discipline lies in the observation that complex systems cannot be treated merely as an assemblage of so many building blocks. Systems Engineering employs techniques and practices that attempt to consider the whole throughout the design process. Systems Engineering offers quite an assortment of processes, and tools devices to capture, describe, derive, and otherwise characterize various aspects of systems under design or analysis. There are many evolving Systems Engineering processes and practices, including processes in which the object‐oriented paradigm dominates. Unfortunately, the set of available processes, models, and tools remains weakest where they are needed the most: where decision tradeoffs are most negotiable, where “requirements” are not yet firmly established, where the use of legacy systems can have the greatest impact, and where the (projected) life cycle impacts of such decisions are greatest.This paper describes a new system development practice named Decision Oriented Systems Engineering (DOSE). If consistently and diligently applied in tandem with other more conventional practices, DOSE provides a solid Systems Engineering “hook” to the application of Human Systems Integration principles and offers considerable promise in simplifying the design of even the most complex systems involving teams working with mixes of new, evolving, and legacy systems.

Systems engineering is the branch of engineering concerned with the development of large and complex systems, where a system is understood to be an assembly or combination of interrelated elements or parts working together toward a common objective. Past experience has shown that formal systems engineering methodologies have not always been successfully applied to large and complex cybersecurity systems. These complex systems have become commonplace when applying cyberstrategies in cybersecurity operations. The ability to build, operate and maintain such systems is crucial to the effectiveness of cybersecurity operations. Most importantly, a cyberstrategy program must surround these systems on a global scale across multiple inter-related platforms. In this chapter, the authors demonstrate why a systems engineering approach is best suited for large and complex information systems used in cybersecurity, as well as the overall cyberstrategies that must also reside over these systems.

Recently, laminated composite plates have been applied to many aircraft structures because their mechanical properties are superior to the conventional materials. Since the laminates have anisotropic elastic properties, the optimum design is reqired to make the best use of the composite laminates. The authors have proposed a successful object-oriented expert system to design the laminated composites with actual constraints. A solution to optimize the fiber orientation of stiffeners around the open hole, however, has not been developed because it is very difficult and reqires stress redistribution analysis. In this study, therefore, the genetic algorithms were applied to solve the optimization problem with the object-oriented finite-element stress analysis method. Results obtained were as follows. (1) The GA method is applicable to an open hole model. (2) The random search method is applicable to any model.

this paper is based on the analyses of current logistics vehicles dispatching system at home and abroad as well as a contrast between its implementation techniques. It uses genetic algorithm to solve vehicles dispatching problems in logistics. Genetic algorithm has always had its advantage in overall searching and is therefore adopted in this case. But in order to overcome the precocity of basic genetic algorithm and at the same time improve the quality of the optimum solution and cut searching time, the paper adopts the Parallel Genetic Algorithm (PGA). Based on the above theoretical research, together with an object-oriented system analysis and design method, this study designed and developed an intelligent dispatching system based on PGA and carried out a series of experimental tests. The test results show this PGA dispatching system can effectively fulfill the dispatching tasks and meet the demand of logistics dispatching center. This dispatching system is highly effective in elevating the competitiveness of small and medium-sized logistics companies.