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The reduction of in situ observations over the last few decades poses a potential risk of losing important information in regions where local effects dominate the climatology. Reanalyses face challenges in representing climatologies with highly localized effects, especially in regions with complex orography. Empirical downscaling methods offer a cost-effective and easier-to-implement alternative to dynamic downscaling methods and can partially overcome the aforementioned limitations of reanalyses by taking into account the local effects through statistical relationships. This article introduces RASCAL (Reconstruction by AnalogS of ClimatologicAL time series), an open-source Python tool designed to extend time series and fill gaps in observational climate data, especially in regions with limited long-term data and significant local effects, such as mountainous areas. Employing an object-oriented programming style, RASCAL's methodology effectively links large-scale circulation patterns with local atmospheric features using the analog method in combination with principal component analysis (PCA). The package contains routines for preprocessing observations and reanalysis data, generating reconstructions using various methods, and evaluating the reconstruction's performance in reproducing the time series of observations, statistical properties, and relevant climatic indices. Its high modularity and flexibility allow fast and reproducible downscaling. The evaluations carried out in central Spain, in mountainous and urbanized areas, demonstrate that RASCAL performs better than the ERA20C and ERA20CM reanalysis, as expected, in terms of R2 , standard deviation, and bias. When analyzing reconstructions against observations, RASCAL generates series with statistical properties, such as seasonality and daily distributions, that closely resemble observations. This confirms the potential of this method for conducting robust climate research. The adaptability of RASCAL to diverse scientific objectives is also highlighted. However, as with any other method based on empirical training, this method requires the availability of sufficiently long-term data series. Furthermore, it is susceptible to disruption caused by changes in land use or urbanization processes that might compromise the homogeneity of the training data. Despite these limitations, RASCAL's positive outcomes offer opportunities for comprehensive climate variability analyses and potential applications in downscaling short-term forecasts, seasonal predictions, and climate change scenarios. The Python code and the Jupyter Notebook for the reconstruction validation are publicly available as an open project. [ABSTRACT FROM AUTHOR]

HDLRuby is a new hardware description language defined as an extension of the Ruby programming language aiming to improve circuit design productivity. HDLRuby allows to model digital circuits at the register transfer level while supporting high-level paradigms comprising object-oriented programming, genericity, metaprogramming, and reflection. By construction, HDLRuby can also execute any code in Ruby and supports all of its libraries. Yet, even if high-level features are beneficial for design productivity, such advantages can be negated if the design tools are not efficient enough for producing in reasonable time quality hardware. This article investigates this issue by presenting the techniques used for compiling HDLRuby descriptions and by evaluating their performance. In detail, it explains how the language has been implemented and how it is translated to synthesizable Verilog HDL. Experiments are then presented for confirming the productivity gain of using HDLRuby and for evaluating the performance of the translation, the size of the resulting code, and the time required by a commercially available synthesis tool to produce an FPGA configuration from it. The HDLRuby descriptions used for the experiments include a set of repetitive designs for single construct evaluations and the implementation of generic convolution neural networks for real-life applications. For these evaluations, the translation time proves to be more than 10 times shorter than the synthesis time. [ABSTRACT FROM AUTHOR]

This paper addresses the necessity to enhance the effectiveness of online learning (OL) environments by examining the influence of social interactions on learner motivation, engagement, and success, specifically focusing on online computer science education (CSE). Acknowledging the limitations of peer-to-peer and learner-to-teacher interactions on online platforms, this paper delves into the potential of social learning (SL) organized through learner groups, communities, or networks to significantly enrich the learning experience. To test the hypothesis that SL positively impacts student outcomes, an experiment was conducted with 49 engineering students divided into two groups. The first group undertook an object-oriented programming course in C++ using the Moodle platform, while the second group, in addition to the online course, participated in asynchronous group activities through forums and synchronous interactions via chat. The results reveal a notable positive impact of SL on student outcomes, with participants in the second group reporting higher satisfaction levels and achieving superior results compared to those in the first group. The findings underscore the significance of integrating social interaction into OL environments, with potential implications for enhancing the overall quality of education and student performance in society. [ABSTRACT FROM AUTHOR]

Currently, a large amount of man-made waste has been stored on the territory of the Republic of Kazakhstan, which, by their chemical and mineral properties, are a serious raw material base for the production of building materials. The quality indicators of raw materials affect not only the physical and strength characteristics of the finished product, but also the cost. In our study, we use man-made raw materials for the production of construction products, as additives to clay for the semi-dry method of producing ceramic products, since this method is less labor-intensive and does not require large financial investments. One of the most important characteristics of technological equipment is performance. Technological equipment for the production of construction products is represented on the market of Kazakhstan by leading foreign companies, including Chinese, Russian, Turkish, Spanish, Kazakh manufacturers are not included in this list. Technological equipment can produce products from a certain type of raw materials, for which such parameters as productivity, quality indicators of raw materials and others are indicated in the technical documentation. That is, when using technogenic raw materials as additives to the charge, it is not possible to determine productivity, for objective reasons. In this regard, the task of calculating the productivity of the technological line for the production of ceramic products using information technology is relevant. As a software tool in the study, the program "Simulation model of a technological line for the production of construction products using industrial waste" is used, written in C++, in accordance with the principles of object-oriented programming. Performance calculations were performed for technological equipment Titanium 900-120 DHEX press, Titanium 80 D press. The presented program can be used by individual entrepreneurs not only to calculate productivity, output volume, but also to justify the choice of technological equipment for the production of ceramic products. [ABSTRACT FROM AUTHOR]

This paper presents a novel, robust, efficient, and simple optimization algorithm called the Object-Oriented Programming Optimization Algorithm (OOPOA) for tackling constrained and unconstrained optimization problems. The algorithm is inspired by the inheritance concept of Object-Oriented programming languages, where the features of a class are classified into three types according to inheritance probability: public, private, and protected. The object-oriented programming inheritance concept is implemented in the algorithm to update the population for the next generations. The proposed algorithm ensures exploitation by selecting the solution with the highest fitness to be inherited in each iteration. It ensures exploration by applying a mutation process that helps explore wide regions in the search space. The performance of this technique is demonstrated by solving 34 different optimization tasks, including 20 standard benchmark problems, ten IEEE Congress of Evolutionary Computation benchmark test functions, and four constrained real-world engineering design problems. [Display omitted] [ABSTRACT FROM AUTHOR]

Object-oriented programming (OOP) features program extensibility which is obtained through basic concepts such as inheritance and polymorphism. To foster organization of knowledge about OOP, we investigate a learning design for learners to understand the “causal relationship” between the extensibility and the basic concepts. Since the extensibility of OOP is an “invisible nature” that it is not necessary to modify the higher-level program when extending the function, the design features comparison of OOP with procedural programing requiring “explicit” modification of higher-level program, intending the learners to be aware of the invisible nature of OOP. In addition, according to the first principle of instructional design, learners are asked to perform two program extension tasks: one in demonstration phase incorporating OOP/proceduralprograming comparison and another in application phase in which learners are expected to reflect on the “causal relationship” between extensibility and basic concepts. As a result of control experiment concerning OOP/ procedural-programing comparison, a significant difference in the understanding of the causal relationship was observed, suggesting the usefulness of the comparison. [ABSTRACT FROM AUTHOR]

In the field of geotechnical engineering, creating and successfully cutting a three-dimensional geological model is a crucial task for digital and visual analysis. However, using commonly available software for 3D model cutting can be time-consuming. Moreover, mainstream cutting algorithms have limitations that can impact real-time performance, such as high computing requirements and complex testing. To address these issues, with the help of the Three.js library, based on the stencil test function module and the cutting operation, this paper presents a real-time rendering closure method for the continuous cutting of a TIN model. This method is implemented by object-oriented programming. When using this method to cut a model, there is no need to intersect and triangulate each point of the section, thereby improving real-time performance. Furthermore, this method enables the real-time rendering of a closed section in the hollow model, resolving issues related to displaying hollow sections in a multilevel TIN geological model, which can serve as another exploratory approach for closed cutting of internal hollow models. The method was applied to a project in southern China and yielded positive results. The time consumption of this cutting process was less than 1 s, and compared to the 3dsMax method under the same conditions, it reduced the time consumption by 6.85 s and improved efficiency by 87%. It can effectively support visual analysis tasks for similar processes, such as smart mines, oil and gas resource distribution, and internal visualization analysis of mechanical parts. [ABSTRACT FROM AUTHOR]

This article presents an integrated educational module for undergraduate traffic engineering at the microscale level. When dealing with a complex transportation system, the education program should cultivate students' acquisition of both in‐depth traffic specialization and breadth of engineering knowledge. For the educational instruction of the signal phase design, this article presents an integrated design that includes several engineering subjects: signal phase design, circuits and electronics, and object‐oriented programming (OOP). Due to the lengthy evolution of signal phase design and the high‐end industrial standards for this issue, this well‐structured problem requires an instructional design to adopt a worked example that integrates varied engineering domains. The integrated design session is intended to deliver education through designing a miniature signal controller while creating an immersive situation and encouraging social teamwork. Feedback from participating students has been positive, indicating the achievement of the planned learning objectives and better mastery of engineering practices. [ABSTRACT FROM AUTHOR]

Featured Application: This software design pattern can be used in OOP programming in order to promote conceptual clarity, reduce coupling, and facilitate system scalability. Object-oriented programming (OOP) has long been a dominant paradigm in software development, but it is not without its challenges. One major issue is the problem of tight coupling between objects, which can hinder flexibility and make it difficult to modify or extend code. Additionally, the complexity of managing inheritance hierarchies can lead to rigid and fragile designs, making it hard to maintain and evolve the software over time. This paper introduces a software development pattern that seeks to offer a renewed approach to writing code in object-oriented (OO) environments. Addressing some of the limitations of the traditional approach, the Puzzle Pattern focuses on extreme modularity, favoring writing code exclusively in building blocks that do not possess a state (e.g., Java interfaces that support concrete methods definitions in interfaces starting from version 8). Concrete classes are subsequently assembled through the implementation of those interfaces, reducing coupling and introducing a new level of flexibility and adaptability in software construction. The highlighted pattern offers significant benefits in software development, promoting extreme modularity through interface-based coding, enhancing adaptability via multiple inheritance, and upholding the SOLID principles, though it may pose challenges such as complexity and a learning curve for teams. [ABSTRACT FROM AUTHOR]

Nowadays, large numbers of organizations may opt for Aspect-Oriented Programming (AOP), which is an enhancement to Object-Oriented Programming (OOP). This is due to the addition of a number of concepts that have assisted in the production of more flexible and reusable components. One of the most important elements added by AOP is software reuse, which is based on reusability attributes. These attributes indicate the possibility of reusing one or more components in the development of a new system. It is one of the most essential attributes to evaluate the quality of a system's components. Thus far, little attention has been paid to the process of measuring AOP reusability, and it has not yet been standardized. The objective of the current study is to come up with a reasonable measurement for AOP software reuse, which is simultaneously a significant topic for researchers while offering several advantages for organizations. Although numerous models have been built to estimate the reusability of software, most of them are not dedicated to Aspect-Oriented Software (AOS). In this study, a model has been designed for AOS reusability estimation and measurement based on a new equation depending on five attributes that have a range of positive and negative impacts on AOS reusability. Three of those attributes, namely coupling, cohesion, and design size, have been included in previous studies. This study proposes complexity and generality as two new attributes to be considered. Each of these attributes was measured based on the metrics also proposed in this study. A new equation to calculate AOS reusability was constructed based on the most important reusability attributes and metrics. Seven aspect projects were employed as a case study to apply the proposed equation. After the proposed equation was applied to the selected projects, we obtained new values of reusability to compare with the values that resulted from applying the previous equation. The fact that new values emerged indicates that the proposed reusability metrics and attributes had a significant effect. [ABSTRACT FROM AUTHOR]

Summary: Software evolution is the process of adapting, maintaining, and updating a software system. This process concentrates the most significant part of the software costs. Many works have studied software evolution and found relevant insights, such as Lehman's laws. However, there is a gap in how software systems evolve from an internal dimensions point of view. For instance, the literature has indicated how systems grow, for example, linearly, sub‐linearly, super‐linearly, or following the Pareto distribution. However, a well‐defined pattern of how this phenomenon occurs has not been established. This work aims to define a novel method to analyze and predict software evolution. We based our strategy on time series analysis, linear regression techniques, and trend tests. In this study, we applied the proposed model to investigate how the internal structure of object‐oriented software systems evolves in terms of four dimensions: coupling, inheritance hierarchy, cohesion, and class size. Applying the proposed method, we identify the functions that better explain how the analyzed dimensions evolve. Besides, we investigate how the relationship between dimension metrics behave over the systems' evolution and the set of classes existing in the systems that affect the evolution of these dimensions. We mined and analyzed data from 46 Java‐based open‐source projects. We used eight software metrics regarding the dimensions analyzed in this study. The main results of this study reveal ten software evolution properties, among them: coupling, cohesion, and inheritance evolve linearly; a relevant percentage of classes contributes to coupling and size evolution; a small percentage of classes contributes to cohesion evolution; there is no relation between the software internal dimensions' evolution. The results also indicate that our method can accurately predict how the software system will evolve in short‐term and long‐term predictions. [ABSTRACT FROM AUTHOR]

Seismic consequences estimation for individual buildings is valuable for various stakeholders, including government entities, building owners, and insurers. The robustness of estimation results in the presence of incomplete input information can typically be investigated through sensitivity analysis. However, the estimation process's complexity and the sensitivity analysis's computational burden hinder its practical application, which requires a more efficient procedure to facilitate broader use. This paper proposes a novel framework for sensitivity analysis of seismic consequences estimation to improve the efficiency and reliability of such analysis. The proposed approach encompasses three key components: (1) stochastic ground motion modeling (SGMM)‐based seismic consequences estimation to evaluate the economic, environmental, and social consequences given specific buildings by considering different hazard levels, (2) the training of surrogate model (Gaussian process model) for structural analysis to reduce the computational cost of the evaluation process, and (3) variance‐based global sensitivity analysis to investigate the importance of parameters of concern in the estimation process. The entire procedure is implemented in Python, adhering to object‐oriented programming, and does not rely on external software. Then, the proposed methodology is applied to two distinct three‐story steel moment‐resistant frames (SMRFs) subjected to four different hazard levels to demonstrate its effectiveness. The SGMM method can generate specific ground motions for each hazard level, mitigating the potential for result bias from using ground motions with unrealistic characteristics. Furthermore, the SGMM method is particularly suitable for automated analysis processes reducing the laborious task of screening ground motions from the database. Comparative analysis with surrogate‐free estimation reveals that the surrogate‐based analysis delivers reliable results with significantly reduced computational cost. The results of analyzing different structures under varying hazard levels reflect the variability in sensitivity analysis of consequences estimation, highlighting the necessity of the proposed flexible and efficient framework. Furthermore, the proposed framework's advantages, limitations, and future research needs are discussed. [ABSTRACT FROM AUTHOR]

Artificial neural networks are inspired by biologic processes. Artificial neural networks are important because they can be used to deduct a function from observations, in other words artificial neural networks can learn from experience. Artificial neural network simulator to fulfill a need into the growing interest of neural network education is introduced in this study. NeuroQuick Laboratory simulator is implemented using object-oriented programming by Delphi programming and these classes can be used to create a standalone application with artificial neural networks. The NeuroQuick Laboratory Simulator is designed for a broad range of users, including beginning graduate/advanced undergraduate students, engineers, and scientists. It is particularly well-suited for use in individual student projects or as a simulation tool in one- or two-semester neural network-related courses at universities. [ABSTRACT FROM AUTHOR]

[Context:] Failure to predict vulnerability in the earlier stage of development can cause vulnerable code being written and deployed in the final software product. Vulnerability prediction using software metrics as features can support the discovery process by localizing vulnerable code. Existing studies have successfully employed metrics for vulnerability prediction for some platforms (C/C++ or Java projects). We propose that a comparative evaluation of how these metrics perform in projects of different languages can help the developers in deciding whether metrics-based prediction approach can be effective in their own project's context. [Objective:] The purpose of this research is to analyze/compare the performance of software metrics in vulnerability-prediction for different programming language contexts (Java vs. Python). [Method:] We conducted experiments on vulnerabilities reported for Apache Tomcat (releases 6 and 7), Apache CXF, and two Python projects (Django and Keystone). We applied machine learning for predicting a particular type of code component (Java and Python classes) as vulnerable/non-vulnerable. [Results:] We found that metrics-based prediction can predict Java vulnerable classes with higher recall and precision than the Python vulnerable classes. [Conclusion:] This study at class-level will help developers to predict vulnerabilities at the class-level and assist in secure coding in object-oriented programming. [ABSTRACT FROM AUTHOR]

Context. Using the composition relation is one of the most effective and commonly used ways to specialize classes in object-oriented programming. Objective. Problems arise when “redundant” attributes are detected in an inner class, which are not necessary for solving the tasks of a specialized class. To work with such attributes, the inner class has corresponding program methods, whose usage not only does not solve the tasks of the specialized class, but can lead to errors in its work. The purpose of this work is to remove “redundant” attributes from the inner class, as well as all methods of the class directly or indirectly (through other methods) using these attributes. Method. A mathematical model of the inner class was developed, which allowed us to identify “redundant” elements of the class. The method of internal class transformation is proposed, which, based on the analysis of the class code, provides the developer with information to make a decision about “redundant” attributes, and then in the automated mode gradually removes and transforms the class elements. Result. To approbate the proposed solutions, a software product Composition Converter was developed. Experiments were carried out to compare the conversion of classes in “manual” and automated modes. The results showed a multiple reduction of conversion time in the automated mode. Conclusions. The proposed method of automated transformation of the inner class according to the tasks of the outer class when implementing composition allows to significantly reduce the time or the number of errors when editing the code of the inner class. The method can be used for various object-oriented languages. [ABSTRACT FROM AUTHOR]

Recent research shows that the source code of smart contracts is often cloned. The processing of related types of transactions in blockchain networks results in the implementation of many similar smart contracts. The rules verifying transactions are therefore duplicated many times. The article introduces the AdapT v2.0 smart contract design pattern. The design pattern employs a distinct configuration for each transaction type, and verification rule objects are shared among configurations. The redundancy of logical conditions was eliminated at two levels. Firstly, it is possible to combine similar smart contracts into one. Secondly, a configuration in a smart contract reuses verification rule objects at runtime. As a result, only one object is instantiated for each verification rule. It allows for the effective use of operating memory by the smart contract. The article presents the implementation of the pattern using object-oriented and functional programming mechanisms. Applying the pattern ensures the self-adaptability of a smart contract to any number of transaction types. The performance tests were carried out for various numbers of verification rules in a smart contract and a different number of checked transactions. The obtained evaluation time of 10,000,000 transactions is less than 0.25 s. [ABSTRACT FROM AUTHOR]

Choreographies are coordination plans for concurrent and distributed systems, which define the roles of the involved participants and how they are supposed to work together. In the paradigm of choreographic programming, choreographies are programs that can be compiled into executable implementations. In this article, we present Choral, the first choreographic programming language based on mainstream abstractions. The key idea in Choral is a new notion of data type, which allows for expressing that data is distributed over different roles. We use this idea to reconstruct the paradigm of choreographic programming through object-oriented abstractions. Choreographies are classes, and instances of choreographies are objects with states and behaviours implemented collaboratively by roles. Choral comes with a compiler that, given a choreography, generates an implementation for each of its roles. These implementations are libraries in pure Java, whose types are under the control of the Choral programmer. Developers can then modularly compose these libraries in their programs, to participate correctly in choreographies. Choral is the first incarnation of choreographic programming offering such modularity, which finally connects more than a decade of research on the paradigm to practical software development. The integration of choreographic and object-oriented programming yields other powerful advantages, where the features of one paradigm benefit the other in ways that go beyond the sum of the parts. On the one hand, the high-level abstractions and static checks from the world of choreographies can be used to write concurrent and distributed object-oriented software more concisely and correctly. On the other hand, we obtain a much more expressive choreographic language from object-oriented abstractions than in previous work. This expressivity allows for writing more reusable and flexible choreographies. For example, object passing makes Choral the first higher-order choreographic programming language, whereby choreographies can be parameterised over other choreographies without any need for central coordination. We also extend method overloading to a new dimension: specialisation based on data location. Together with subtyping and generics, this allows Choral to elegantly support user-defined communication mechanisms and middleware. [ABSTRACT FROM AUTHOR]

The use of large language models with chatbots like ChatGPT has become increasingly popular among students, especially in Computer Science education. However, significant debates exist in the education community on the role of ChatGPT in learning. Therefore, it is critical to understand the potential impact of ChatGPT on the learning, engagement, and overall success of students in classrooms. In this empirical study, we report on a controlled experiment with 182 participants in a first-year undergraduate course on object-oriented programming. Our differential study divided students into two groups, one using ChatGPT and the other not using it for practical programming assignments. The study results showed that the students' performance is not influenced by ChatGPT usage (no statistical significance between groups with a p-value of 0.730), nor are the grading results of practical assignments (p-value 0.760) and midterm exams (p-value 0.856). Our findings from the controlled experiment suggest that it is safe for novice programmers to use ChatGPT if specific measures and adjustments are adopted in the education process. [ABSTRACT FROM AUTHOR]

The paper shows how to estimate the three parameters of the generalized exponential Rayleigh distribution by utilizing the three estimation methods, namely, the moment employing estimation method (MEM), ordinary least squares estimation method (OLSEM), and maximum entropy estimation method (MEEM). The simulation technique is used for all these estimation methods to find the parameters for the generalized exponential Rayleigh distribution. In order to find the best method, we use the mean squares error criterion. Finally, in order to extract the experimental results, one of object oriented programming languages visual basic. net was used. [ABSTRACT FROM AUTHOR]

Teaching and learning programming, and especially Object-Oriented Programming (OOP), is a complicated and challenging task. Students have to comprehend various OOP concepts and utilize them for designing object-oriented programs. Various types of educational programming environments, such as microworlds and educational games, have been devised for supporting novices mainly in comprehending OOP concepts. However, such environments do not usually support students in the conceptual design of object-oriented programs of a considerable length and complexity. In this paper, we focus on a systematic mapping study (SMS) of educational programming environments for enhancing the conceptual design in OOP, which relies on modularity, abstraction and encapsulation. The research questions investigate the intended learning outcomes, the empirical evidence on the effectiveness, and the teaching/learning technologies used by educational programming environments for enhancing the conceptual design in OOP. The findings can support instructors in selecting appropriate tools for their courses and researchers in the field of educational programming environments for OOP. [ABSTRACT FROM AUTHOR]

This research paper explores the effectiveness of live coding as an active learning methodology in teaching programming, particularly in the context of diverse learning styles. Live coding, characterized by real-time coding demonstrations by instructors, has been increasingly adopted to enhance the learning experience in programming education. It offers immediate feedback, demonstrates problem-solving in action, and allows instructors to incorporate student suggestions, making it a dynamic and engaging teaching tool. However, its effectiveness varies among students with different learning preferences. This study investigates the impact of various learning style dimensions, as defined by the Felder–Silverman model, on the effectiveness of live coding in an introductory object-oriented programming course. The study was conducted at Aalborg University, Denmark, with students from the BSc Software program. It aims to provide empirical evidence on how different learning style dimensions influence student preferences and the effectiveness of live coding, offering insights to educators for tailoring active learning methodologies in programming courses to diverse learner needs. [ABSTRACT FROM AUTHOR]

The object of research is the Mixed Mode Stress Intensity Factor (MMSIF) of a two-dimensional (2D) plate. With the emergence of modern technologies and advanced innovations which contribute to the development and improvement of the design, implementation and management of construction projects, it has become easier. However, it is very difficult to manufacture components free from unavoidable defects, such as cracks, which lead to material deterioration and ultimately shorten its service life. Based on the process of local enrichment region using partition of unity concept, the extended finite element method (XFEM) has overcome the limitations of the standard FEM method in terms of modeling and numerical simulation of discontinuities (cracks) while gaining its general advantages. This makes XFEM a powerful and widely used digital tool in recent years. One of the most frequently raised problems in the discontinuities field (cracks) is the phenomenon of juxtaposition of multiple cracks in a cracked isotropic plate, which must be studied to determine the extent of its effect on the crack stress intensity factor in order to obtain higher safety reliability. On this basis, an improved object-oriented programming (OOP) with extended finite elements was used because of its great importance and well-known benefits. In this paper, the MMSIF of a 2D plate is determined to show the effect of the out-of-phase orientation of the angle, as well as the effect of the juxtaposition of two inclined cracks. As a result of the research, it is shown that, the convergence between the results obtained in this study with those reported in the literature, and to theoretical values is remarkable and their close agreement was noted. In the future, based on the object-oriented approach characteristics represented by flexibility, scalability, and modularity, which were explained in this research, this proposed approach can be enriched to include heterogeneous materials modeling, whether linear or nonlinear, crack propagation in dynamics, in addition to Complex 3D industrial problems [ABSTRACT FROM AUTHOR]

In recent years, there has been a rising interest in potentially complex software and financial industries with applications in many engineering fields. With this rise comes a host of developing a usable and consistent Application Programming Interface (API). Prioritize designing and building the software ensures to enrich the platform and emphasize inventorying APIs. In this paper, we proposed a high-quality API to implement the continuous-in-time financial model. The existing discrete framework cannot be evaluated at any time period, involving drawbacks in operating the data structures. Then, the continuous framework is implemented based on the measure theory paradigm. Our proposal uses mathematical modeling, which consists of some objects as measures and fields. It is suitable to develop this API in C# to provide the requirement quality in programming language professionally. This also integrates demands, codes, and verification in the system development life cycle. The advantages are aimed at increasing the structuring and readability. The presented work provides an overview of the design, implementation, testing, and delivery aspects of the API, highlighting the importance of architecture, testing, and numerical choices. The article gives an overview of the API by describing the implementation concerning the data structures and algorithms. These algorithms are based on using the Task Parallel Library (TPL) that makes the API easier and more fruitful for data parallel to benefit from the advantages provided by the .NET Framework.

Test suite reduction methods are a current research topic. In particular, continuous practices and regression testing demand minimizing the number of test cases. Recently, many smart contracts have been deployed in blockchain implementations. Due to their immutability, tests play an even more important role in smart contract development. The SmarTS package implements the k+1 test suite reduction method. The developed software generates and runs a minimal set of test cases for the smart contract. The layered construction of the package ensures the ability to test any smart contract whose implementation follows a specific design pattern.

Abstract Different from object detection in natural images, aerial‐view object detection faces special challenges with large changes in object orientation and wide multi‐scale distribution. Many methods based on Oriented Bounding Boxes (OBB) can reach accurate results, yet may face the problem of parameter mutation and axis prediction deviation. To address these problems, a two‐stage detection framework is proposed for arbitrary‐oriented traffic participant detection and axis prediction, named Axis Prediction Network. First, a Deformable Convolution Fusion Module (DCF‐Module) is proposed to enhance the ability of FPN to extract multi‐scale semantic features, for dealing with the multi‐scale change of objects. Then, the axis heat‐map prediction head network is proposed to fit the long axis of oriented objects labeled with Gaussian model, which uses pixel‐by‐pixel prediction heatmap to calculate the long axis of the object, avoiding the angle mutation of an OBB. Last, the long and short side prediction head network is proposed to predict the shape of an oriented object, avoiding the mutation of the width and height of an OBB. The experiments are conducted on the new built Crossroad dataset and the public DOTA dataset. Experiment results show that the proposed method achieve good performance in arbitrary‐oriented traffic participant detection and axis prediction in aerial view.

Object-Oriented Programming (OOP) in PHP is gaining traction due to its flexibility and control. This research paper delves into the best practices for optimizing OOP in PHP. The primary focus is on strategies such as designing classes, leveraging inheritance, and implementing caching to expedite processes. The paper also emphasizes the importance of other optimization techniques such as polymorphism, method access optimization, property access optimization, and memory management. Polymorphism allows objects of different classes to be treated as objects of a common superclass, enabling more flexible and dynamic code. Method and property access optimization involve using the most efficient ways to access methods and properties of objects, while memory management ensures that resources are used effectively. Overall, this research provides a comprehensive guide to optimizing PHP OOP, covering a wide range of techniques and strategies. It serves as a valuable resource for PHP developers looking to improve the performance and efficiency of their object-oriented applications. By employing tactics like class design, inheritance, caching, and profiling, developers can harness the full potential of OOP in PHP and build robust, high-performing applications. This paper is a must-read for anyone interested in PHP OOP and its optimization. [ABSTRACT FROM AUTHOR]

Industry 4.0 brings a revolution in the way to create and think of products. Consumer needs change rapidly and production systems must adapt quickly to market changes by changing processes, resources, and configurations. In this context, as real manufacturing systems are subject to constant change, simulations can easily become obsolete. This reduces the lifetime of the simulation model, causes repeated disruption in industrial planning support, and consequently continuous maintenance by experts. Within this framework, the novelty of the following research is the development of a flexible and resilient simulation model able to adapt according to its physical counterpart. Through advanced modeling, based on the object-oriented programming paradigm, an automated simulation model has been developed. This model adapts based on input data, ensuring accuracy and real-time planning support. The research is applied to a real case study of the production system of a world leader in the energy technology sector. The results show that the applied simulation tool can analyze different configurations and enhance production planning. [ABSTRACT FROM AUTHOR]

Globally, the number of online courses offered as electronic versions of conventional learning courses has increased annually over the past decade. A critical variable for measuring the success or failure of these courses is student satisfaction. This paper presents a study which aims to investigate the students’ satisfaction with the quality of an online course supporting training in Object-Oriented Programming performed in blended learning mode. The developed questionnaire allows students to assess the course content and design, course organization, communication and support, and evaluation. Based on the summarized result, recommendations for improving the course quality to meet students’ expectations and needs have been done. [ABSTRACT FROM AUTHOR]

This article explores the origins, development, and future of Scandinavian information systems (IS) research. It discusses the unique characteristics of the Scandinavian tradition, such as its focus on social aspects and its use of emancipatory and egalitarian approaches. The article also examines the factors that have shaped the Scandinavian school, including language, cultural beliefs, and political stability. The author concludes by discussing the impact and relevance of Scandinavian research in the IS discipline, emphasizing the potential for future contributions in the era of pervasive digital technology. [Extracted from the article]

In the currently existing distributed architectures, there are different components that are optimized to fulfill different roles (e.g. databases, message brokers, load-balancers) in the whole architecture. Distributed architectures are highly complex. Several competencies are needed to be able to create and maintain such an environment. Furthermore, these systems have strict limitations in performance optimization as well because the interaction between the components is limited to their interfaces. The Object-oriented programming (OOP) paradigm uses encapsulation to bind together the data and the functions that manipulate the data. However, OOP does not encapsulate one very important factor, the process that executes the functions themselves. (They are executed simply on threads.) On the other hand, the actor model binds the process to the data, but it does not have the high-level programming features of the OOP paradigm. COP aims to encapsulate the process as well to the corresponding data and functions and bring the best from these two approaches. With this new programming approach, the COP aims to make it possible to create a homogeneous system where all the nodes can form one single huge logical computer, which makes the whole architecture much more simple. COP aims to make it possible to write code to a distributed system as easy as we would to one single computer and make distributed computing magnitudes more effective, reliable, safe, and easier to code. [ABSTRACT FROM AUTHOR]

The finite element method (FEM) is widely recognized as a powerful numerical analysis technique for approximating solutions in structural mechanics. Addressing the configuration of plate-type structures, particularly those with discontinuities, is crucial not only in ship and aircraft construction but also in various other fields. Structural discontinuities occur when there are sudden changes in the cross-section of structural members due to material imperfections or high-stress areas. This paper focuses on the fundamental principles of FEM for solving two-dimensional plane stress problems and analyzing stresses such as normal stress, shear stress, and von-Mises stress at the four integration points (Gauss points) in different sections of ship structures, particularly in vulnerable regions. To address structural discontinuity problems in various ship structures, a finite element program utilizing object-oriented techniques was developed, employing four-node quadrilateral elements. The analysis results of gauss point stresses obtained from the developed program were validated against a commercial finite element analysis software to ensure accuracy and reliability. Additionally, a mesh viewing program has been developed in the Python programming language to enable the visualization and analysis of the generated mesh using the developed object-oriented finite element program. [ABSTRACT FROM AUTHOR]

Feature selection (FS) is a crucial task in machine learning applications, which aims to select the most appropriate feature subset while maintaining high classification accuracy with the minimum number of selected features. Despite the widespread usage of metaheuristics as wrapper-based FS techniques, they show reduced effectiveness and increased computational cost when applied to high-dimensional datasets. This paper presents a novel Binary Object-Oriented Programming Optimization Algorithm (BOOPOA) for FS of high dimensional datasets, where the Object-Oriented Programming Optimization Algorithm (OOPOA) is a novel optimization technique inspired by the inheritance concept of Object-Oriented programming (OOP) languages. The effectiveness of this method in solving high dimensional FS problems is validated by using 26 datasets, most of which are of high dimension (large number of features). Seven existing FS algorithms are compared with the proposed OOPOA using various metrics, including best fitness, average fitness (AVG), selection size, and computational time. The results prove the superiority of the proposed algorithm over the other FS algorithms, having an average performance of %92.5, 0.078, 0.084, %38.9, and 8.6 min for classification accuracy, best fitness, average fitness, size reduction ratio, and computational time. The outcomes demonstrate the proposed FS approach's superiority over currently used methods. [Display omitted] [ABSTRACT FROM AUTHOR]

The paper analyzes the possibilities of transforming C programming language constructs into objects of EO programming language. The key challenge of the method is the transpilation from a system programming language into a language of a higher level of abstraction, which does not allow direct manipulations with computer memory. Almost all application and domain-oriented programming languages disable such direct access to memory. Operations that need to be supported in this case include the use of dereferenced pointers, the imposition of data of different types in the same memory area, and different interpretation of the same data which is located in the same memory address space. A decision was made to create additional EO-objects that directly simulate the interaction with computer memory as in C language. These objects encapsulate unreliable data operations which use pointers. An abstract memory object was proposed for simulating the capabilities of C language to provide interaction with computer memory. The memory object is essentially an array of bytes. It is possible to write into memory and read from memory at a given index. The number of bytes read or written depends on which object is being used. The transformation of various C language constructs into EO code is considered at the level of the compilation unit. To study the variants and analyze the results a transpiler was developed that provides necessary transformations. It is implemented on the basis of Clang, which forms an abstract syntax tree. This tree is processed using LibTooling and LibASTMatchers libraries. As a result of compiling a C program, code in EO language is generated. The considered approach turns out to be appropriate for solving different problems. One of such problems is static code analysis. Such solutions make it possible to isolate low-level code fragments into separate program objects, focusing on their study and possible transformations into more reliable code. [ABSTRACT FROM AUTHOR]

Different from object detection in natural images, aerial‐view object detection faces special challenges with large changes in object orientation and wide multi‐scale distribution. Many methods based on Oriented Bounding Boxes (OBB) can reach accurate results, yet may face the problem of parameter mutation and axis prediction deviation. To address these problems, a two‐stage detection framework is proposed for arbitrary‐oriented traffic participant detection and axis prediction, named Axis Prediction Network. First, a Deformable Convolution Fusion Module (DCF‐Module) is proposed to enhance the ability of FPN to extract multi‐scale semantic features, for dealing with the multi‐scale change of objects. Then, the axis heat‐map prediction head network is proposed to fit the long axis of oriented objects labeled with Gaussian model, which uses pixel‐by‐pixel prediction heatmap to calculate the long axis of the object, avoiding the angle mutation of an OBB. Last, the long and short side prediction head network is proposed to predict the shape of an oriented object, avoiding the mutation of the width and height of an OBB. The experiments are conducted on the new built Crossroad dataset and the public DOTA dataset. Experiment results show that the proposed method achieve good performance in arbitrary‐oriented traffic participant detection and axis prediction in aerial view. [ABSTRACT FROM AUTHOR]

Many empirical studies have shown that educational games and recent technologies impact education and increase learning effectiveness, students' motivation and engagement. The overall aim of this study is to evaluate the usability of Imikode, a virtual reality (VR) game that was developed to introduce the concepts of object-oriented programming to novices. The improved version of the Imikode VR game consists of three features: An artificial intelligence component designed to provide real-time error feedback to users, an intelligent agent that guides and teaches users how to play the game and finally, the integration of multiple game play that gives learners more opportunities to explore the VR environment for greater immersive learning experience. This study adopted a survey approach and recruited first-year computer science students to measure learner satisfaction with educational virtual reality games and examined the correlations among the attributes of the Usefulness, Satisfaction and Ease of Use questionnaire of usage of Imikode. The results showed that the students were satisfied with Imikode and perceived the virtual reality educational game as very useful for learning object-oriented programming concepts. In addition, there was a correlation among the questionnaire variables, which means that researchers can use the instrument for future usability studies in the context. We further proffered some design recommendations for building software tools. [ABSTRACT FROM AUTHOR]

Coupling hydrological modelling systems (HMS) with a geographic information system (GIS) can significantly enhance hydrological research and expand its applications. The calculation for HMS requires geographic information data; however, the current GIS data structure is not equipped to support the object-oriented hydrological modelling. Due to different objectives and design concepts, the differences between HMS and GIS have been profound, especially in their data structures from the perspective of object-oriented programming (OOP). This research introduces a novel approach to extend ArcGIS data structures for HMS, facilitating seamless coupling. This approach employs Microsoft Component Object Model (COM) technology to construct custom data structures that align with hydrological OOP principles. These can then be integrated into ArcGIS through a custom ArcGIS layer as an add-on. As a result, the HMS can leverage the full functionality of ArcGIS without the need for re-coding existing modelling systems. Moreover, HMS can be readily developed by using COM compatible computer languages, enabling the easy adaptation of this coupling approach to other HMS to ensure computational efficiency and to maximise the benefits of ArcGIS features. This new approach has been successfully implemented with the Xin'anjiang model, and the results validate its effectiveness in coastal areas. [ABSTRACT FROM AUTHOR]

Method naming is a challenging development task in object-oriented programming. In recent years, several research efforts have been undertaken to provide automated tool support for assisting developers in this task. In general, literature approaches assume the availability of method implementation to infer its name. Methods, however, are usually named before their implementations. In this work, we fill the gap in the literature about method name prediction by developing an approach that predicts the names of all methods to be implemented within a class. Our work considers the class name as the input: The overall intuition is that classes with semantically similar names tend to provide similar functionalities, and hence similar method names. We first conduct a large-scale empirical analysis on 258K+ classes from real-world projects to validate our hypotheses. Then, we propose a hybrid big code-driven approach, Mario, to predict method names based on the class name: We combine a deep learning model with heuristics summarized from code analysis. Extensive experiments on 22K+ classes yielded promising results: compared to the state-of-the-art code2seq model (which leverages method implementation data), our approach achieves comparable results in terms of F-score at token-level prediction; our approach, additionally, outperforms code2seq in prediction at the name level. We further show that our approach significantly outperforms several other baselines. [ABSTRACT FROM AUTHOR]

While the complicated scheme of the philosophical sublime may at first hand seem mere platitude when brought to life in computer games, this article claims that the action/adventure game World of Warcraft wedges open a space in which to operate the sublime and navigate radically "other" subjectivities. The hypothesis is that the assembly of fantastic elements in World of Warcraft duplicates the Kantian sublime while at the same time commenting upon and even radicalizing it. The Romantic tradition of the sublime as it unfolds in Immanuel Kant's third Critique is outlined followed by an attempt to topologize elements of the fantastic in Blizzard's game design philosophy leading to a clarification of what we call "the knotted point of play" where game object, game interaction, and game subject intervene. Finally, we explore how the notion of the technological sublime relates to World of Warcraft and beyond. [ABSTRACT FROM AUTHOR]