Object-oriented Approach Research Articles

Logistic-information system based on object-oriented approach

The article deals with the issue of creating an information system through an object-oriented approach, which is suitable for ensuring an efficient and properly functioning logistics network. An object-oriented approach to the creation of a business information system pays attention to a set of cooperating objects and reacts more flexibly to events in the environment. The main effort within the object-oriented approach is the reuse of created objects for a new system, which significantly contributes to shortening the development of new systems. For this fact and based on practical experience, the mentioned approach was chosen by the authors of the article. The overall design and functionality of the information system were influenced by the strategic direction of the company, which was also necessary to consider when preparing the article. In the end, a comparison of specific and object-oriented approaches to the creation of information systems for the company is processed.

Object-Oriented Classification Approach (OBIA) in Extracting Burial Plot for Muslim Cemeteries Management

Object-Oriented Classification Approach (OBIA) in Extracting Burial Plot for Muslim Cemeteries Management

Ecological analysis and multi-scenario simulation of Yellow River Delta wetland under clearing of Spartina alterniflora

In 2022, China released the Special Action Plan for the Control of Spartina alterniflora (2022-2025) with the goal of completely clearing S. alterniflora from China's coastal wetlands. It is crucial to conduct a thorough analysis of wetlands under artificial intervention and obtain reliable future wetland simulation results. The Yellow River Delta wetland is one of China's important wetland reserves, has faced severe impacts from S. alterniflora invasion over the past decade. This study focuses on the Yellow River Delta wetland, utilizing Landsat imagery and a combined object-oriented and pixel-based approach to achieve wetland mapping from 2013 to 2023. Through wetland analysis, we designed scenarios for natural development, ecological priority, farmland protection, and combined development. The patch generating land use simulation model was used to simulate wetland scenarios for 2030 and analyze factors influencing wetland use cover change and future conversion patterns. The results indicate that between 2013 and 2022, native vegetation was impacted by the invasion of S. alterniflora, with Suaeda glauca being the most affected. In 2023, the removal of S. alterniflora was effective, reducing its area by 42.37km2 compared to pre-removal conditions. In all three scenarios, the area of Phragmites australis increased and is expected to dominate the wetlands, while the live space of other native salt marsh vegetation has also been restored. However, the predictions indicate that S. alterniflora still poses a potential threat of expansion in the future, necessitating continuous monitoring of its dynamics. We recommend implementing zoned management of the wetland, balancing ecological restoration in coastal areas with agricultural development in the western regions.

Object-Oriented Approach to Script Support in Optical CAD Systems

Object-Oriented Approach to Script Support in Optical CAD Systems

Класифициране на трудностите при обучение на студенти по учебната дисциплина „Програмиране на Java“

Students experience multiple difficulties in learning the Java programming language. This report attempts to classify these difficulties based on the author's experience from the laboratory classes in the Java Programming course with the Computer Science and Software Engineering majors. The classification will help to suggest workable methods and means to overcome or at least minimize these difficulties. Observations show that the main difficulties are related to the transition from the already studied language (C++ or C#) to the new syntactic constructions and abstractions of Java, the different implementation of the key concepts and mechanisms, and the application of the object-oriented approach when solving specific tasks

Categories of training to improve empathy: A systematic review and meta-analysis.

Due to the vital role of empathy in promoting prosocial behaviors and nurturing social bonds, there is a growing interest in cultivating empathy. Yet, the effectiveness of existing training methods on empathy, especially on different dimensions of empathy (i.e., affective, cognitive, motivational, and behavioral empathy), varies tremendously, and the underlying causes for this heterogeneity remain insufficiently explored. To address this issue, we categorized various training methods into three distinct approaches based on the premise that empathy can be influenced by factors associated with the subject, the object, and their relationship. Respectively, these are Subject-Oriented, Object-Oriented, and Socially Oriented approaches. To examine the effects of training and sustainability of these approaches on different dimensions of empathy, we conducted a meta-analysis encompassing 110 eligible studies with 32, 44, 39, 39, and 91 samples for affective, cognitive, motivational, behavioral, and composite empathy, respectively. Results showed that trainings produced small and unsustainable effects on affective empathy, moderate and unsustainable effects on cognitive empathy, small and sustainable effects on motivational empathy, and moderate and sustainable effects on behavioral empathy. The effects of training on composite empathy were robust but decreased over time. Among the three training approaches, Socially Oriented approaches were the most effective in improving all dimensions of empathy. Subject-Oriented and Object-Oriented approaches were effective only in improving cognitive and composite empathy. Altogether, our study offers practical guidance for selecting appropriate training approaches and proposes theoretical principles for developing optimal training strategies in both basic research and clinical applications. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Integration of Business Unit Financial Reporting Systems in Village-Owned Enterprises (BUMDes)

BUMDes is a village government-owned business institution established in an effort to strengthen the village economy, based on the needs and potential of the village concerned. In its operations, BUMDes can have various business units with autonomous management in one business entity. Each business unit makes its own financial report according to the type of business it runs. The resulting financial report will be submitted to the head office for merger and consolidation. Although each business unit has a different type of business, the process and provisions for preparing financial reports in each business unit are the same, because they are regulated in government regulations. The only differences are related to operational reporting and components/account names in the financial report. To improve the ease of preparation and accountability of its financial reports, the existence of an integrated accounting information system is a must. As an initial step, a design process is carried out which will be used as the basis or technical reference for the development process. The design process is carried out with an object-oriented approach, with the results in the form of classes/components and interactions between them which are the foundation of the system building. This will facilitate the development process and this integrated system can then be built/developed in stages according to the development/addition of business units from BUMDes.

Modeling and supporting adaptive Complex Data-Intensive Web Systems via XML and the O-O paradigm: The OO-XAHM model

The data model is a critical component of an Adaptive Web System (AWS). The major goals of such a data model are describing the application domain of the AWS and capturing data about the user in order to support the “adaptation effect”. There have been many proposals for data models, principally based on knowledge representation, machine learning, logic and reasoning, and, recently, ontologies. These models are focused on the implementation of the core layer of AWS, that is realizing the adaptation of contents and presentations of the system, but sometimes they are poor with respect to the application domain design. In this paper, we present an extension of the state-of-the-art XML Adaptive Hypermedia Model (XAHM), Object-Oriented XAHM (OO-XAHM) that supports the application domain modeling using an object-oriented approach. We also provide the formal definition of the model, its description via Unified Modeling Language (UML), and its implementation using XML Schema. Finally, we provide a complete case study that focuses the attention on the well-known Italian archaeological site Pompeii.

Comparison of Algorithms and Optimal Feature Combinations for Identifying Forest Type in Subtropical Forests Using GF-2 and UAV Multispectral Images

The composition and spatial distribution of tree species are pivotal for biodiversity conservation, ecosystem productivity, and carbon sequestration. However, the accurate classification of tree species in subtropical forests remains a formidable challenge due to their complex canopy structures and dense vegetation. This study addresses these challenges within the Jiangxi Lushan National Nature Reserve by leveraging high-resolution GF-2 remote sensing imagery and UAV multispectral images collected in 2018 and 2022. We extracted spectral, texture, vegetation indices, geometric, and topographic features to devise 12 classification schemes. Utilizing an object-oriented approach, we employed three machine learning algorithms—Random Forest (RF), k-Nearest Neighbor (KNN), and Classification and Regression Tree (CART)—to identify 12 forest types in these regions. Our findings indicate that all three algorithms were effective in identifying forest type in subtropical forests, and the optimal overall accuracy (OA) was more than 72%; RF outperformed KNN and CART; S12 based on feature selection was the optimal feature combination scheme; and the combination of RF and Scheme S12 (S12) yielded the highest classification accuracy, with OA and Kappa coefficients for 2018-RF-S12 of 90.33% and 0.82 and OA and Kappa coefficients for 2022-RF-S12 of 89.59% and 0.81. This study underscores the utility of combining multiple feature types and feature selection for enhanced forest type recognition, noting that topographic features significantly improved accuracy, whereas geometric features detracted from it. Altitude emerged as the most influential characteristic, alongside significant variables such as the Normalized Difference Greenness Index (NDVI) and the mean value of reflectance in the blue band of the GF-2 image (Mean_B). Species such as Masson pine, shrub, and moso bamboo were accurately classified, with the optimal F1-Scores surpassing 89.50%. Notably, a shift from single-species to mixed-species stands was observed over the study period, enhancing ecological diversity and stability. These results highlight the effectiveness of GF-2 imagery for refined, large-scale forest-type identification and dynamic diversity monitoring in complex subtropical forests.

What is race? Epistemic ambiguity and liberal international order

Abstract There is increasing interest in how anticolonial actors advanced a norm of racial equality in mid-century formations of liberal international order (LIO). Less attention, however, is afforded to simultaneous epistemic conflicts over the scientific object of ‘race’ and their political effects. During postwar order-building and alongside political struggles for racial equality, there was wide and deep scientific debate on the analytical utility of race as a means to categorize human diversity. Race, I demonstrate, was rendered as epistemically ambiguous, caught between social scientists and philosophers who understood it as a social construct akin to ethnicity and natural scientists who maintained a biological basis. This split was not confined to academic debate but shaped political and normative struggles over the institutionalization of racial equality in LIO. Adopting an object-oriented approach, I argue that the epistemic ambiguity of race generated political effects, at once permitting the reproduction of colonial logics in LIO as well as providing latitude for strategies of resistance. Rather than a linear causal effect, I empirically map the work that epistemic ambiguity performed in the creation of mid-century international order.

(What) Do We Owe Beautiful Objects? A Case for Aesthetic Obligations

Abstract This paper has two main aims. The first is to examine our normative relations to artworks and cultural artefacts threatened by damage or destruction. The second aim is to develop an argument for the notion of aesthetic obligation, offering an alternative model of explanation of our normative relations to artworks and cultural artefacts which relies neither exclusively on the object of appreciation (‘object-oriented approach’) nor on the appreciating subject (‘subject-oriented approach’). Instead, an aesthetic obligation is held to be directed primarily towards the community which appreciates the object on the grounds of its aesthetic value. That which unites an aesthetic community is the practice of valuing an object for its aesthetic character. The notion of aesthetic obligation thus relies both on the community of subjects which holds an object in high aesthetic regard and that same object’s aesthetic value.

Исследование алгоритмов организации сетей АНПА с использованием программной среды моделирования

Development of a network of autonomous underwater vehicles (AUV) is a complex multifactorial task. Solution of this problem requires the fulfillment of a number of stringent requirements, including, requirements for fault tolerance, efficiency of information exchanges, energy efficiency, etc. As a result, it is very important to use simulation for test proposed solutions of AUV network design. The purpose of current research is development and test a software environment for designing AUV networks. The simulation environment is implemented within the framework of an object-oriented approach in Python. The main results obtained include the established principles for implementing a software environment for simulation of AUV networks. The layout of the hardware and software for underwater communication network developed in Concern CSRI Elektropribor is the basis of the developed simulation model. The results of testing the software are presented using the example of solving the problem of ensuring the efficiency of information exchanges. The developed software environment makes it possible to increase the efficiency of AUV network development.

Conceptual model of digital nitrogen management in agricultural crops

The research was aimed at developing a conceptual model of digital nitrogen management in crops. Cognitive analysis of the knowledge structure in this subject area, conceptual modeling of digital nitrogen management in agrophytocenoses using object-oriented approach and Unified Modeling Language (UML) were used. A detailed system of diagrams was created, encompassing class, process, and interaction diagrams. The model is anchored on three abstract objects: class (7 in total), attribute (32), and inter-class relationships (18), which distribute the main concepts, emphasizing the complexity and multifaceted approaches to digital nitrogen management. The central class is «Agrophytocenosis», which directly interacts with 5 classes and indirectly with 1 class. Attributes are integral to the classes and reflect their specific characteristics. To depict the interaction between the classes and their attributes, four types of relationships are employed in the model: «dependency», «association», «aggregation», and «inner class». In the process diagram of the digital nitrogen management system, two primary subsystems are highlighted: the analysis and planning subsystem and the adjustment subsystem, as well as tools and sources for data acquisition and processing. A distinctive feature of the developed conceptual model is the application of the temporality principle, integrating static and dynamic processes in the digital nitrogen management system within the agrophytocenosis.Subsystems for analysis, planning and adjustment of emerging conditions in the management areas allow ensuring more efficient use of nitrogen fertilizers in crops.The conceptual model is aimed at developing a hardware-software complex for diagnostics of nitrogen nutrition of cultivated plants and management of fertilizer application based on modern digital monitoring and data processing tools.

Analysis and Design of Customer Service Information Systems at Bersaudara Car Repair Shop Of Pangkalpinang

Bersaudara Car Repair Shop of Pangkalpinang is a business that operates in the field of automotive services, specializing in car maintenance and repair. Currently, customer service data processing still uses a manual system with Microsoft Office tools. In its application, this application cannot support fast and easy work. This can have implications for service providers towards customers, because they often encounter obstacles in the process of handling repairs and making reports. The aim of this research is to provide a solution in forming a needs analysis and documented information system design which will be developed into an information system application at the brothers' car repair shop. Based on the SDLC (Software Development Life Cycle) concept, the initial thing needed to produce an information system is to create a needs analysis and documented system design. The system analysis and design carried out here goes through the stages of data collection, carrying out analysis using the PIECES (Performance, Information, Economic, Control, Efficiency, Service) framework and carrying out system design using an object-oriented approach using UML (Unified Modeling Language) notation. The results of the analysis and design were tested in the form of a design evaluation using the consistency analysis method which was proven to have a consistent percentage value of 100%. The results of this design are included in the correctness category which proves that the system requirements and system design are consistent and correct.

A Smart Application Frame of Remote Sensing in Non-grain Production Data Governance

Abstract. This study addresses the intricate challenges encountered in the data governance process of Non-grain Production (NGP) on Arable land. This involves managing data from diverse sources, with varying accuracies and formats, and utilizing multiple specialized software tools. An object-oriented approach is adopted to encapsulate experiential knowledge related to the data and associated processing methods, thus creating an Application Knowledge Body Model (AKBM). This model acts as a conduit between users and computational resources, encompassing various types of data and their corresponding processing and analysis methods. Moreover, by employing model inference techniques to devise methods for transitioning from raw data models to target models, a foundation is laid for the accumulation, sharing, and intelligent application of expertise on data, methods, models, and knowledge.The application examples demonstrate that users can directly construct new solutions containing relevant data and associated processing methods, rather than grappling with a multitude of data files and complex specialized software when encountering novel challenges. This promotes collaborative development in data governance on geospatial big data platforms, significantly enhancing governance efficiency, improving the quality of information support in NGP cultivation management, advancing current technological capabilities, and fostering the progression of related technologies.

National-scale nighttime high-temperature anomalies from Landsat-8 OLI images

Identifying and characterizing the distribution, abundance, and structural composition of national high-temperature anomalies (HTAs) are essential for mitigating natural disasters, regulating industrial emissions, and assessing societal impacts. The Landsat-8 Operational Land Imager (OLI) provides a unique capability for monitoring nighttime HTAs (N-HTAs) at high spatial resolutions without contamination from reflected solar radiation. However, the extraction of N-HTAs from nighttime OLI imagery poses significant challenges due to the interference of bright up-light, especially for smaller and cooler hotspots, and the absence of spectral information on backgrounds complicates the classification of N-HTAs at night. Here, we explored the background noise characteristics of Bands 2–7 in nighttime OLI imagery and developed an object-oriented approach for the enhanced detection of small and cool N-HTAs. Furthermore, we introduced a deep learning model that leverages high-resolution aerial imagery and land cover data to categorize N-HTAs into industrial sources, living sources, vegetation fires, and others. Applying these methodologies to nighttime OLI imagery from 2013 to 2020 allowed us to map and classify N-HTAs across the contiguous United States (CONUS), facilitating the creation of a detailed spatiotemporal inventory of industrial N-HTAs. Our analysis revealed that N-HTAs from living sources dominate the total N-HTAs, with a pronounced holiday effect, and gas flaring activities in oil and gas development areas account for >85 % of industrial N-HTAs. The outcomes of this national-scale investigation underscore the significant potential and practical utility of nighttime OLI imagery for N-HTA monitoring and advocate for expanding the spatial and temporal coverage of nighttime OLI observations globally.

SynergyAnalyzer: A Matlab toolbox implementing mixed-matrix factorization to identify kinematic-muscular synergies

Background and ObjectiveA new direction in the study of motor control was opened about two decades ago with the introduction of a model for the generation of motor commands as combination of muscle synergies. Muscle synergies provide a simple yet quantitative framework for analyzing the hierarchical and modular architecture of the human motor system. However, to gain insights on the functional role of muscle synergies, they should be related to the task space. The recently introduced mixed-matrix factorization (MMF) algorithm extends the standard approach for synergy extraction based on non-negative matrix factorization (NMF) allowing to factorize data constituted by a mixture of non-negative variables (e.g. EMGs) and unconstrained variables (e.g. kinematics, naturally including both positive and negative values). The kinematic-muscular synergies identified by MMF provide a direct link between muscle synergies and the task space. In this contribution, we support the adoption of MMF through a Matlab toolbox for the extraction of kinematic-muscular synergies and a set of practical guidelines to allow biomedical researchers and clinicians to exploit the potential of this novel approach. MethodsMMF is implemented in the SynergyAnalyzer toolbox using an object-oriented approach. In addition to the MMF algorithm, the toolbox includes standard methods for synergy extraction (NMF and PCA), as well as methods for pre-processing EMG and kinematic data, and for plotting data and synergies. ResultsAs an example of MMF application, kinematic-muscular synergies were extracted from EMG and kinematic data collected during reaching movements towards 8 targets on the sagittal plane. Instructions and command lines to achieve such results are illustrated in detail. The toolbox has been released as an open-source software on GitHub under the GNU General Public License. ConclusionsThanks to its ease of use and adaptability to a variety of datasets, SynergyAnalyzer will facilitate the adoption of MMF to extract kinematic-muscular synergies from mixed EMG and kinematic data, a useful approach in biomedical research to better understand and characterize the functional role of muscle synergies.

Winter Wheat Mapping in Shandong Province of China with Multi-Temporal Sentinel-2 Images

Wheat plays an important role in China’s and the world’s food supply, and it is closely related to economy, culture and life. The spatial distribution of wheat is of great significance to the rational planning of wheat cultivation areas and the improvement of wheat yield and quality. The current rapid development of remote sensing technology has greatly improved the efficiency of traditional agricultural surveys. The extraction of crop planting structure based on remote sensing images and technology is a popular topic in many researches. In response to the shortcomings of traditional methods, this research proposed a method based on the fusion of the pixel-based and object-oriented methods to map the spatial distribution of winter wheat. This method was experimented and achieved good results within Shandong Province. The resulting spatial distribution map of winter wheat has an overall accuracy of 92.2% with a kappa coefficient of 0.84. The comparison with the actual situation shows that the accuracy of the actual recognition of winter wheat is higher and better than the traditional pixel-based classification method. On this basis, the spatial pattern of winter wheat in Shandong was analyzed, and it was found that the topographic undulations had a great influence on the spatial distribution of wheat. This study vividly demonstrates the advantages and possibilities of combining pixel-based and object-oriented approaches through experiments, and also provides a reference for the next related research. Moreover, the winter wheat map of Shandong produced in this research is important for yield assessment, crop planting structure adjustment and the rational use of land resources.

SISTEM APLIKASI POIN OF SALE (POS) UNTUK PENJUALAN TOKO NAILA COOKIES BERBASIS JAVA

The Java-based Point of Sale (POS) application system was created to increase operational efficiency and transaction accuracy at Naila Cookies Shop. This system automates sales processes, inventory management, and financial reporting, aiming to speed up the checkout process, minimize errors, and provide real-time sales data. Utilizing Java as the main programming language with an object-oriented approach ensures scalability and ease of maintenance. Additionally, the system has a user-friendly interface to facilitate fast and efficient transactions for store staff. Testing shows important improvements in transaction speed and accuracy, potentially reducing long-term operational costs. These findings show the positive impact of the appropriate use of information technology on retail store operations.

Implementasi Metode Backward Chaining untuk Mendiagnosa Penyakit pada Bayi Pasca Kelahiran

The critical period for the growth and development of infants can be referred to as a critical period. It is said that this critical period in infancy will be very detrimental to the environment around it and it is said that the future due to infancy is very short and cannot be repeated. Newborns are more susceptible to various diseases. Diseases in infants can be identified based on the symptoms that arise. This is caused by several factors including the lack of information about diseases in infants after birth that is known to the general public. Therefore, research is needed on diseases and symptoms that affect babies after birth. One alternative in order to find out the disease in the baby after birth can use an expert system. In building the system, the author uses the Backward Chaining method, uses the Waterfall system development method (SDLC) and the Object Oriented Approach (OOA). The result of this research is a web-based application that can later be accessed or used to make it easier for the public, especially parents of babies, to diagnose symptoms or diseases in babies after birth as early as possible.