An AI Embedded Object-Oriented Approach for Formulating Computable General Equilibrium

This paper proposes and illustrates an AI embedded object-oriented methodology to formulate the computable general equilibrium (CGE) models. In this framework, a CGE model is viewed as a collection of objects embedded AI or namely agents in computer world, corresponding to economic agents and entities in real world, such as government, households, markets and so on. A frame representation of major objects in CGE model is used for trade and environment. Embedded Al object-oriented approach (or software agent) is used in the CGE model representation can able to narrow the gap among the semantic representation, formal CGE (mathematical) representation and computer and algorithm representation, and to improve CGE in understanding and maintenance etc. In such a system, constructing a CGE model to appear an intuitive process rather than an abstract process. This intuitive process needs more understanding of the substance of economics and the logic underlying the problem rather than mathematical notation.

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.

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.

Induced pluripotent stem cell-related approaches to generate dopaminergic neurons for Parkinson's disease

The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative disease.Although the detailed pathogenesis accounting for dopaminergic neuron degeneration in Parkinson's disease is still unclear,the advancement of stem cell approaches has shown promise for Parkinson's disease research and therapy.The induced pluripotent stem cells have been commonly used to generate dopaminergic neurons,which has provided valuable insights to improve our understanding of Parkinson's disease pathogenesis and contributed to anti-Parkinson's disease therapies.The current review discusses the practical approaches and potential applications of induced pluripotent stem cell techniques for generating and differentiating dopaminergic neurons from induced pluripotent stem cells.The benefits of induced pluripotent stem cell-based research are highlighted.Various dopaminergic neuron differentiation protocols from induced pluripotent stem cells are compared.The emerging three-dimension-based brain organoid models compared with conventional two-dimensional cell culture are evaluated.Finally,limitations,challenges,and future directions of induced pluripotent stem cell–based approaches are analyzed and proposed,which will be significant to the future application of induced pluripotent stem cell-related techniques for Parkinson's disease.

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.

Enhancing perianal disease management with integrated physical and psychological approaches

This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal diseases.The study sheds light on how illness perception,anxiety,and depression significantly influence recovery outcomes.Hou et al developed a predictive model that demonstrated high accuracy in identifying patients at risk of poor recovery.The article explores the critical role of pre-operative psychological assessment,highlighting the need for mental health support and personalized recovery plans in enhancing POR quality.A multidisciplinary approach,integrating mental health professionals with surgeons,anesthesiologists,and other specialists,is emphasized to ensure comprehensive care for patients.The study’s findings serve as a call to integrate psychological care into surgical practice to optimize outcomes for patients with perianal diseases.

An Edge-assisted, Object-oriented Random Forest Approach for Refined Extraction of Tea Plantations Using Multi-temporal Sentinel-2 and High-resolution Gaofen-2 Imagery

As a consumed and influential natural plant beverage,tea is widely planted in subtropical and tropical areas all over the world.Affected by(sub)tropical climate characteristics,the underlying surface of the tea distribution area is extremely complex,with a variety of vegetation types.In addition,tea distribution is scattered and fragmentized in most of China.Therefore,it is difficult to obtain accurate tea information based on coarse resolution remote sensing data and existing feature extraction methods.This study proposed a boundary-enhanced,object-oriented random forest method on the basis of high-resolution GF-2 and multi-temporal Sentinel-2 data.This method uses multispectral indexes,textures,vegetable indices,and variation characteristics of time-series NDVI from the multi-temporal Sentinel-2 imageries to obtain abundant features related to the growth of tea plantations.To reduce feature redundancy and computation time,the feature elimination algorithm based on Mean Decrease Accuracy(MDA)was used to generate the optimal feature set.Considering the serious boundary inconsistency problem caused by the complex and fragmented land cover types,high resolution GF-2 image was segmented based on the MultiResolution Segmentation(MRS)algorithm to assist the segmentation of Sentinel-2,which contributes to delineating meaningful objects and enhancing the reliability of the boundary for tea plantations.Finally,the object-oriented random forest method was utilized to extract the tea information based on the optimal feature combination in the Jingmai Mountain,Yunnan Province.The resulting tea plantation map had high accuracy,with a 95.38%overall accuracy and 0.91 kappa coefficient.We conclude that the proposed method is effective for mapping tea plantations in high heterogeneity mountainous areas and has the potential for mapping tea plantations in large areas.

OBJECT-ORIENTED IMPLEMENTATION OF EXPERT SYSTEMS FOR ENGINE LUBRICATING OIL INSPECTION

The inspection of engine lubricating oil can give an indication of the internal condition of an engine. By means of the Object-Oriented Programming (OOP), an expert system is developed in this paper to computerize the inspection. The traditional components of an expert system, such us knowledge base, inference engine and user interface are reconstructed and integrated, based on the Microsoft Foundation Class (MFC) library. To testify the expert system, an inspection example is given at the end of this paper.

Meta-analysis of potentially confounding effect of class size on associations between object-oriented metrics and maintainability

This paper uses three size metrics,which are collectable during the design phase,to analyze the potentially confounding effect of class size on the associations between object-oriented（OO）metrics and maintainability.To draw as many general conclusions as possible,the confounding effect of class size is analyzed on 127 C＋＋ systems and 113 Java systems.For each OO metric,the indirect effect that represents the distortion of the association caused by class size and its variance for individual systems is first computed.Then,a statistical meta-analysis technique is used to compute the average indirect effect over all the systems and to determine if it is significantly different from zero.The experimental results show that the confounding effects of class size on the associations between OO metrics and maintainability generally exist,regardless of whatever size metric is used.Therefore,empirical studies validating OO metrics on maintainability should consider class size as a confounding variable.

REALIZATION OF OBJECT-ORIENTED RULE-TYPE EXPERT SYSTEM TEMPLATE

Expert systems (ESs) are being increasingly applied to the fault diagnosis of engines. Based on the idea of ES template (EST), an object-oriented rule-type EST is emphatically studied on such aspects as the object-oriented knowledge representation, the heuristic inference engine with an improved depth-first search (DFS) and the graphical user interface. A diagnositic ES instance for debris on magnetic chip detectors (MCDs) is then created with the EST. The spot running shows that the rule-type EST enhances the abilities of knowledge representation and heuristic inference, and breaks a new way for the rapid construction and implementation of ES.

Visual object-oriented application for lane following on intelligent highway system

A visual object-oriented software for lane following on intelligent highway system (IHS) is proposed. According to object-oriented theory, 3 typical user services of self-check, transfer of human driving and automatic running and abnormal information input from the sensors are chosen out. In addition, the functions of real-time display, information exchanging interface, determination and operation interweaving in the 3 user services are separated into 5 object-oriented classes. Moreover, the 5 classes are organized in the visual development environment. At last, experimental result proves the validity and reliability of the control application.

The Design and Implementation of an Object-Oriented Hypermedia System

Presents an object-oriented NBO(node-block-object)data model for hypermedia system.It takes advantage of object-oriented method,encapsulates all multimedia information as well as link functions in one unit,It has successfully achieved cross link to offer much better flexibility and two-way link to realize forward and backward searching in hypermedia system navigation.A conditional relation on links has also been realized,that is very helpful for time sensitive multimedia information processing and multimedia object cooperation.

Object-Oriented Modeling of Virtual Assembly Process

Virtual assembly is a Virtual Reality (VR) based engineering application which allows engineers to evaluate, analyze, and plan the assembly of mechanical systems. To model the virtual assembly process, new methodology must be applied. Based on the idea that the virtual assembly system is an event driven system, the interactive behavior and information model is proposed to describe the dynamic process of virtual assembly. Definition of the object-oriented model of virtual assembly is put forward.

Shrek:a dynamic object-oriented programming language

From a perspective of theoretical study, there are some faults in the models of the existing object-oriented programming languages. For example, C# does not support metaclasses, the primitive types of Java and C# are not objects, etc. So, this paper designs a programming language, Shrek, which integrates many language features and constructions in a compact and consistent model. The Shrek language is a class-based purely object-oriented language. It has a dynamical strong type system, and adopts a single-inheritance mechanism with Mixin as its complement. It has a consistent class instantiation and inheritance structure, and the ability of intercessive structural computational reflection, which enables it to support safe metaclass programming. It also supports multi-thread programming and automatic garbage collection, and enforces its expressive power by adopting a native method mechanism. The prototype system of the Shrek language is implemented and anticipated design goals are achieved.

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.

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.

Modeling Method of Automotive Body CAN/LIN Nets Application Protocol Based on Object-oriented Colored Petri Net

Recently automotive nets are adopted to solve increasing problems in automotive electronic systems.Technologies of automotive local area network from CAN and LIN can solve the problems of the increasing of wire bunch weight and lack in module installation space.However,the multilayer automotive nets software becomes more and more complex,and the development expense is difficult to predict and to keep in check.In this paper,the modeling method of hierarchical automotive nets and the substitution operation based on object-oriented colored Petri net(OOCPN) are proposed.The OOCPN model which analyzes the software structure and validates the collision mechanism of CAN/LIN bus can speed the automobile system development.First,the subsystems are divided and modeled by object-oriented Petri net(OOPN).According to the sets of message sharing relations,the message ports among them are set and the communication gate transitions are defined.Second,the OOPN model is substituted step by step until the inner objects in the automotive body control modules(BCM) are indivisible and colored by colored Petri net(CPN).And the color subsets mark the node messages for the collision mechanism.Third,the OOCPN model of the automotive body CAN/LIN nets is assembled,which keeps the message sets and the system can be expanded.The proposed model is used to analyze features of information sharing among the objects,and it is also used to describe each subsystem real-time behavior of processing messages and implemental device controllers operating,and puts forward a reasonable software framework for the automotive body control subsystem.The research can help to design the communication model in the automotive body system effectively and provide a convenient and rapid way for developing the logical hierarchy software.

Object-oriented Urban Dynamic Monitoring——A Case Study of Haidian District of Beijing

It is crucial to conduct the land use/cover research to obtain the global change information.Urban area is one of the most sensitive areas in land use/cover change.Therefore land use/cover change in urban areas is very im-portant in global change.It is vital to incorporate the information of urban land use/cover change into the process of decision-making about urban area development.In this paper,a new urban change detection approach,urban dynamic monitoring based on objects,is introduced.This approach includes four steps:1)producing multi-scale objects from multi-temporal remotely sensed images with spectrum,texture and context information;2)extracting possible changed objects adopting object-oriented classification;3)obtaining shared objects as the basic units for urban change detection;4)determining the threshold to segment the changed objects from the possible changed objects using Otsu method.In this paper,the object-based approach was applied to detecting the urban expansion in Haidian District,Beijing,China with two Landsat Thematic Mapper(TM)data in 1997 and 2004.The results indicated that the overall accuracy was about 84.83%,and Kappa about 0.785.Compared with other conventional approaches,the object-based approach was advantageous in reducing the error accumulation of image classification of each datum and in independence to the radiometric correction and image registration accuracy.

NDVI-Based Lacunarity Texture for Improving Identification of Torreya Using Object-Oriented Method

Normalized Difference Vegetation Index （NDVI） is a very useful feature for differentiating vegetation and non-vegetation in remote sensed imagery. In the light of the function of NDVI and the spatial patterns of the vegetation landscapes, we proposed the lacunarity texture derived from NDVI to characterize the spatial patterns of vegetation landscapes concerning the ＂gappiness＂ or ＂emptiness＂ characteristics. The NDVI-based lacunarity texture was incorporated into object-oriented classification for improving the identification of vegetation categories, especially Torreya which was the targeted tree species in the present research. A three-level hierarchical network of image objects was defined and the proposed texture was integrated as potential sources of information in the rules base. A knowledge base of rules created by classifier C5.0 indicated that the texture could potentially be applied in object-oriented classification. It was found that the addition of such texture improved the identification of every vegetation category. The results demonstrated that the texture could characterize the spatial patterns of vegetation structures, which could be a promising approach for vegetation identification.