Modular Object Research Articles

ANALISIS KEPUASAN MAHASISWA DALAM MENGGUNAKAN MOODLE LEARNING MANAGEMENT SYSTEM

The research aims to determine the level of student satisfaction in using Maranatha Online Learning (Morning) which is Learning Management System (LMS) based on the Modular Object Oriented Dynamic Learning Environment (Moodle) platform, and to find out the things that influence it to serve as a basis for making efforts to increase or improve those aplication. Data collection was carried out through questionnaires which were distributed directly to 95 students and processed using the Multiple Linear Regression and Descriptive Statistics methods. The results of the study show that there are several things that directly influence student satisfaction in using the Morning aplication, namely the attractiveness of the student's main page (dashboard), the ease of carrying out the log-in process, and the ease of filling in attendance. Quality improvements to these features are expected to be increase student satisfaction in conducting online learning.

Improving the quality of medical education throught the introduction of moodle system for the formation of terminological competence of medical students.

Aim is to analyze the possibilities of using the electronic system Moodle for the formation of professional and terminological competence of medical students during the study of terminological competence for improving the quality of medical education. Materials and Methods: The research used a number of scientific methods: general scientific (analysis, synthesis, generalization), specific research and others which ensured the selection and analysis of the source base, made it possible to determine the general trends in the study of the problem of using the electronic system Moodle for the formation of professional and terminological competence of medical students during the study of terminological competence for improving the quality of medical education. Conclusions: At I. Horbachevsky Ternopil National Medical University we actively use the e-learning system Moodle (Modular Object Oriented Distance Learning Environment), to which there is free and unrestricted access. Using this program, the student takes on the role of an active subject who independently acquires knowledge, forms his/her own system of skills, of course with the help of certain sources, and the role of the teacher in this scheme is to motivate and suport learners, prepare information sources used in self-study, etc. This is due to a significant increase in the requirements for quality training of future specialists n the medical field and market conditions in Ukraine, which set before the higher school the task of training specialists of the new generation who would be highly qualified, competitive, literate, and have perfect command of their professional terminology. The Moodle system is able to optimize the learning process, promote the formation of terminological competence and master professional vocabulary. When creating educational and methodological complexes for the formation of terminological competence, the means of teaching, as well as the ways of presenting educational material and the principles of organizing the educational activities of students become important. The electronic platform Moodle, which has a wide range of resources for teaching and testing, is able to expand the communicative competencies and skills of students needed to effectively master professional Latin terminology. The Moodle system has the optimal set of resource opportunities for the implementation of blended learning - classroom and extracurricular, which is its main advantage.

Log concavity for unimodal sequences

In this paper, we prove that the number of unimodal sequences of size n is log-concave. These are coefficients of a mixed false modular form and have a Rademacher-type exact formula due to recent work of the second author and Nazaroglu on false theta functions. Log-concavity and higher Turán inequalities have been well-studied for (restricted) partitions and coefficients of weakly holomorphic modular forms, and analytic proofs generally require precise asymptotic series with error term. In this paper, we proceed from the exact formula for unimodal sequences to carry out this calculation. We expect our method applies to other exact formulas for coefficients of mixed mock/false modular objects.

Автоматизация построения комплексной информационной модели на основе модульных элементов максимальной готовности

The article raises the problem of the need to develop specialized functionality of software complexes of information modeling technologies for the development of models of objects of modular buildings in order to minimize manual actions when solving routine tasks. The general concept of the tool is defined, the main functional requirements are formulated and the development of a specialized script is carried out. Based on the initial data in the form of information models of modular elements and basic technical and economic indicators, the construction of a complex information model of a modular object with the possibility of instantaneous adjustment and variable operation is formed in an automated mode. The purpose of this study is to develop a means of automating the construction of a complex information model based on modular elements of maximum readiness, tasks: analysis of the features of modular design, study of the possibilities of visual programming tools and script development.

Hodge-Elliptic Genera, K3 Surfaces and Enumerative Geometry

K3 surfaces play a prominent role in string theory and algebraic geometry. The properties of their enumerative invariants have important consequences in black hole physics and in number theory. To a K3 surface, string theory associates an Elliptic genus, a certain partition function directly related to the theory of Jacobi modular forms. A multiplicative lift of the Elliptic genus produces another modular object, an Igusa cusp form, which is the generating function of BPS invariants of K3×E\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{K3} \ imes E$$\\end{document}. In this note, we will discuss a refinement of this chain of ideas. The Elliptic genus can be generalized to the so-called Hodge-Elliptic genus which is then related to the counting of refined BPS states of K3×E\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{K3} \ imes E$$\\end{document}. We show how such BPS invariants can be computed explicitly in terms of different versions of the Hodge-Elliptic genus, sometimes in closed form, and discuss some generalizations.

The effect of moodle-based learning in learning studios with the TPACK approach on high school students' learning outcomes

In the 21st century learning must be integrated with various technological devices in the entire process, this also supports the industrial revolution 4.0 program. The TPACK approach is the answer to these demands, where learning is based on knowledge of teaching materials (content knowledge), how to teach material (pedagogical knowledge), and knowledge of how to use technology (technological knowledge). One example of the application of technology in learning is the Modular Object Oriented Dynamic Learning Environment (moodle), at the research site, namely SMAN 8 Serang City, there is a moodle-based learning studio website. The sample of this study were students of class X at SMAN 8 Kota Serang. The research method used in this study was quantitative pre-experimental design, with a one-group pretest-posttest research design. The results of the study showed that there was an increase in the learning outcomes of students who had studied using the moodle sanggar belajar by 52.3%. The n-gain score obtained was 61.62% which was categorized as "effective enough", which means that learning achieves learning objectives with proven significant mathematics learning outcomes.

Формирование данных информационной модели модульного здания в формате olap

The article provides an analysis of the use of OLAP technology in the design of modular objects based on information modeling technologies, presents the classification and systematization of information models of modular elements of maximum readiness. The purpose of this study is to develop and analyze a data model for the most effective data management of an information model of a capital construction object both at the design stage and at subsequent stages of the life cycle. In order to achieve this goal, it is necessary to take into account not only the features and attributes of information models, but also the key characteristics of modular design, including elements of the MEG within the existing tools for systematization of digital data. As a result, the impact of using OLAP cubes to represent a modular object at all stages of the life cycle is considered. New possibilities and advantages of using the OLAP data management model of the information model of the capital construction object are presented. The directions of further research are formulated.

Design in the service of topology and the classification theorem

Topology is considered an advanced field in mathematics, and it might seem off-putting to people with no previous experience in mathematics. The classification theorem, which lies within the field of algebraic topology, is fascinating, but understanding it requires extensive mathematical knowledge. In this manuscript, we present a modular object that provides a glimpse into the construction of surfaces as defined by the classification theorem. This allows any user to explore different options and discover possible surfaces with three holes or fewer. This tactile experience of exploration grants the user intuition about the meaning of the theorem, without needing the rigorous proof; thus, it simplifies the depth of the classification theorem and its respective proof for non-mathematical audiences. We strive to accurately illustrate these esoteric concepts by giving them a form and to describe the modeling process of creating a tangible, touchable sculpture designed to intrigue and invite simple understanding. We believe that this playful object will be exciting for a variety of communities: university students, graduate students, teachers, professional mathematicians, and especially designers, who can use it to produce new tools.

Selecting Context-Sensitivity Modularly for Accelerating Object-Sensitive Pointer Analysis

Object-sensitive pointer analysis (denoted <i>k</i> <small>obj</small> under <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> -limiting) for an object-oriented program can be accelerated if context-sensitivity can be selectively applied to only some precision-critical variables/objects in a program. Existing pre-analyses for making such selections, which are performed as whole-program analyses to a program, are developed based on two broad approaches. One approach preserves the precision of object-sensitive pointer analysis but achieves limited speedups by reasoning about all the possible value flows in the program conservatively, while the other approach achieves greater speedups but sacrifices precision (often unduly) by examining only some but not all the value flows in the program heuristically. In this paper, we introduce a new pre-analysis approach, <small>Turner</small> <inline-formula><tex-math notation="LaTeX">$^{\mathcal{m}}$</tex-math></inline-formula> (where <inline-formula><tex-math notation="LaTeX">$\mathcal {m}$</tex-math></inline-formula> stands for modularity), that represents a sweet spot between these two existing ones, as it is designed to enable <i>k</i> <small>obj</small> to run significantly faster than the former approach and achieve significantly better precision than the latter approach. <small>Turner</small> <inline-formula><tex-math notation="LaTeX">$^{\mathcal{m}}$</tex-math></inline-formula> is simple, lightweight yet effective due to two novel aspects in its design. First, we exploit a key observation that some precision-uncritical objects in the program can be approximated based on the object-containment relationship pre-established (from Andersen's analysis). In practice, this approximation introduces only a small degree of imprecision into <i>k</i> <small>obj</small> . Second, leveraging this initial approximation, we apply a novel object reachability analysis to the program by pre-analyzing its methods according to a reverse topological order of its call graph. When pre-analyzing each method, we make use of a simple DFA (Deterministic Finite Automaton) to reason about object reachability intra-procedurally from its entry to its exit along all the possible value flows established by its statements to identify its precision-critical variables/objects. In practice, this new modular object reachability analysis, which runs linearly in terms of the number of statements in the program, introduces again only a small loss of precision into <i>k</i> <small>obj</small> . We have validated <small>Turner</small> <inline-formula><tex-math notation="LaTeX">$^{\mathcal{m}}$</tex-math></inline-formula> with an open-source implementation in <small>Soot</small> (already publicly available) against the state of the art by using a set of 12 widely used Java benchmarks and applications.

Sustainability of construction based on digital and modular technologies

The XXI century has confronted humanity with a number of global environmental and social problems. Some of them depend on the construction industry. The tasks of ensuring the sustainability of construction have become relevant. The article discusses modular construction as one of the most promising ways to achieve the requirements of sustainable construction. The purpose of the study is to analyze the prospects for the implementation of modular construction technology based on modern digital technologies to achieve the objectives of sustainable construction. The analysis of modular construction materials is carried out. The main advantages of using modular technologies (efficiency, quality, speed, environmental friendliness) are determined. Increasing the degree of automation and the introduction of modern digital technologies is a promising direction for the development of modular construction. It is noted that the promising areas of production automation are robotic machines, manipulators and 3D printers. It is noted that the use of BIM technologies is necessary to automate the design process. The digital information model allows to collect all the information about a modular object and its components and to use it at all stages, including the manufacture of structures. Generative design in combination with BIM allows to automate the synthesis of design solutions according to specified requirements. As a result of the research, a scheme for integrating BIM, generative design and modern factory production facilities into a single digital production chain of modular construction is proposed. Such chain is a bundle of a virtual conveyor of information models based on generative design and a factory production system with the use of 3D printing to manufacture structures according to the specifications of the information model. The system of synthesis of design solutions on the base of the system of generative algorithms is proposed. Examples of local optimization problems of generative design for modular construction are presented. The conclusion is made about the need for a comprehensive application of the considered technologies to achieve the greatest efficiency of construction.

The 𝒫(𝜑)₂ Model on de Sitter Space

In 1975 Figari, Høegh-Krohn and Nappi constructed theP(φ)2{\mathscr P}(\varphi )_2model on the de Sitter space. Here we complement their work with new results, which connect this model to various areas of mathematics. In particular, i.) we discuss the causal structure of de Sitter space and the induces representations of the Lorentz group. We show that the UIRs ofSO0(1,2)SO_0(1,2)for both the principal and the complementary series can be formulated on Hilbert spaces whose functions are supported on a Cauchy surface. We describe the free classical dynamical system in both its covariant and canonical form, and present the associated quantum one-particle KMS structures in the sense of Kay (1985). Furthermore, we discuss the localisation properties of one-particle wave functions and how these properties are inherited by the algebras of local observables.ii.) we describe the relations between the modular objects (in the sense of Tomita-Takesaki theory) associated to wedge algebras and the representations of the Lorentz group. We connect the representations of SO(1,2) to unitary representations ofSO(3)SO(3)on the Euclidean sphere, and discuss how theP(φ)2{\mathscr P}(\varphi )_2interaction can be represented by a rotation invariant vector in the Euclidean Fock space. We present a novel Osterwalder-Schrader reconstruction theorem, which shows that physicalinfrared problemsare absent on de Sitter space. As shown in Figari, Høegh-Krohn, and Nappi (1975), the ultraviolet problems are resolved just like on flat Minkowski space. We state the Haag–Kastler axioms for theP(φ)2{\mathscr P}(\varphi )_2model and we explain how thegeneratorsof the boosts and the rotations for the interacting quantum field theory arise from thestress-energy tensor. Finally, we show that the interacting quantum fields satisfy theequations of motionin their covariant form. In summary, we argue that the de SitterP(φ)2{\mathscr P}(\varphi )_2model is the simplest and most explicit relativistic quantum field theory, which satisfies basic expectations, like covariance, particle creation, stability and finite speed of propagation.

A modular visuo-haptic mixed reality (VHMR) aided prototype technique for in-vehicle human-machine interaction (HMI) evaluations

Virtual Prototyping is a robust method to greatly reduce the labour cost and time required of the vehicle prototype. Still, the absence of the haptic sensory channel degrades the immersive experience evaluation, especially in terms of in-vehicle human-machine interaction (HMI). Hence, this study proposed a modular visuo-haptic mixed reality (VHMR) aided prototype technique suitable for in-vehicle HMI evaluations, which positions itself between pure VR technology and physical object assessment. Technology acceptance model (TAM) was also introduced to empirically investigate the perceived usefulness, ease of use, presence, risk, as well as the behavioural intention of the prototype technique separately. Results revealed that the modular visuo-physical object prototype technique has certain advantages in terms of positioning, usability and user acceptance among the VHMR solutions, and could be adopted as a low-fidelity prototype to build common ground in the R&D team and get quick feedback from users for the agile in-vehicle HMI development.

AUTOMATED CHECKING SYSTEM FOR MODULAR BIM OBJECTS

With the increasing popularity of modular buildings, many manufacturers have made BIM objects for use by designers. However, these BIM objects must satisfy specific regulations and requirements, and their quality needs to be verified. In this study, the authors propose an automated checking system for modular BIM object quality verification. The system includes three parts, which are modular BIM object guideline, pre-checking module and automated code checking module. The modular BIM object quality verification system is proposed to be applied to government modular product certification site for checking the modular BIM objects. It is expected that the use of this automated checking system will make it possible to connect users and manufacturers to promote the circulation of modular building products, as well as provide designers with standardized modular BIM objects for design purposes.

NeROIC

We present a novel method to acquire object representations from online image collections, capturing high-quality geometry and material properties of arbitrary objects from photographs with varying cameras, illumination, and backgrounds. This enables various object-centric rendering applications such as novel-view synthesis, relighting, and harmonized background composition from challenging in-the-wild input. Using a multi-stage approach extending neural radiance fields, we first infer the surface geometry and refine the coarsely estimated initial camera parameters, while leveraging coarse foreground object masks to improve the training efficiency and geometry quality. We also introduce a robust normal estimation technique which eliminates the effect of geometric noise while retaining crucial details. Lastly, we extract surface material properties and ambient illumination, represented in spherical harmonics with extensions that handle transient elements, e.g. sharp shadows. The union of these components results in a highly modular and efficient object acquisition framework. Extensive evaluations and comparisons demonstrate the advantages of our approach in capturing high-quality geometry and appearance properties useful for rendering applications.

HS‐IDEOR—A tool for conceptual modeling and designing of hardware architectures focused on object recognition

AbstractConsidering the increasing demand for object recognition systems, it is crucial that modern engineering courses include tools and methods to ensure that students acquire the theoretical and practical skills necessary to become specialists in designing such systems. This paper introduces a hardware‐software integrated development environment to support and accelerate the teaching/learning process of conceptual modeling and hardware architectures design focused on object recognition. In addition, our proposal facilitates the implementation of modular and hybrid object recognition schemes, offering great flexibility in the study of such systems. An empirical evaluation was conducted with 30 fourth‐year undergraduate students who designed and implemented an object recognition system in the Computer Vision course of the Bachelor's Degree in Computer Science and Engineering at the Universidad Tecnológica de la Mixteca, Mexico. The results achieved from designing, modeling, and implementing a hardware architecture of the convolution process applied to edge detection in an image provided evidence that this approach empowered students with a more dynamic learning process.

The Designing of a Learning Theory to Promote a Classroom Pedagogy for Moodle Self-Directed Learning

The higher education institutions across the world have changed their teaching and learning methods due to the Covid19 pandemic. They are now using different learning management systems like Moodle. The implication of the sudden transition to online learning is that students now have to become more independent, and self-directed in their learning. The aim of this paper is therefore to develop a Moodle (Modular Object Oriented Dynamic Learning Environment) Self-Directed Learning Theory. It explores some of the learning aspects related to the development of students towards Moodle self-directed learning and proposes a framework of skills that lecturers and teachers can use as a guide to increasing student responsibility. This study is situated within the theory of Instrumental Genesis (IG). The researchers employed the design-based research method when developing this learning theory. The process of developing this learning framework involved a literature review of Moodle and self-directed learning theories. The study of the learning theories revealed various Moodle and self-directed perspectives which were used to develop this learning theory. The outcome of this study is a learning theory that will hopefully promote self-directed learning within the context of Moodle teaching and learning.

МОДУЛЬНЫЕ СТРУКТУРЫ КАК МЕТОД ОРГАНИЗАЦИИ АРХИТЕКТУРНОЙ СРЕДЫ

key versions of the concept «module» in the sphere of architectural design are considered. Modular structures are defined as a means of creating a flexible and dynamic architectural environment with variable functional parameters, the main potential of which is expressed in the speed of erection, autonomy, economical efficiency, transformative possibilities. The main features and advantages of the modular structures as well as the most effective fields of their application are considered. Examples are given of modular objects from current construction practices that illustrate the possibilities and specific means of their formation. Special emphasis has been placed on the ecological feasibility of modular facilities, as well as on the possibility of their interaction with the established architectural context. The use of the modular method in extreme conditions, including the formation of a habitable environment in outer space, is considered.

Applications of object detection in modular construction based on a comparative evaluation of deep learning algorithms

Purpose The practice of artificial intelligence (AI) is increasingly being promoted by technology developers. However, its adoption rate is still reported as low in the construction industry due to a lack of expertise and the limited reliable applications for AI technology. Hence, this paper aims to present the detailed outcome of experimentations evaluating the applicability and the performance of AI object detection algorithms for construction modular object detection. Design/methodology/approach This paper provides a thorough evaluation of two deep learning algorithms for object detection, including the faster region-based convolutional neural network (faster RCNN) and single shot multi-box detector (SSD). Two types of metrics are also presented; first, the average recall and mean average precision by image pixels; second, the recall and precision by counting. To conduct the experiments using the selected algorithms, four infrastructure and building construction sites are chosen to collect the required data, including a total of 990 images of three different but common modular objects, including modular panels, safety barricades and site fences. Findings The results of the comprehensive evaluation of the algorithms show that the performance of faster RCNN and SSD depends on the context that detection occurs. Indeed, surrounding objects and the backgrounds of the objects affect the level of accuracy obtained from the AI analysis and may particularly effect precision and recall. The analysis of loss lines shows that the loss lines for selected objects depend on both their geometry and the image background. The results on selected objects show that faster RCNN offers higher accuracy than SSD for detection of selected objects. Research limitations/implications The results show that modular object detection is crucial in construction for the achievement of the required information for project quality and safety objectives. The detection process can significantly improve monitoring object installation progress in an accurate and machine-based manner avoiding human errors. The results of this paper are limited to three construction sites, but future investigations can cover more tasks or objects from different construction sites in a fully automated manner. Originality/value This paper’s originality lies in offering new AI applications in modular construction, using a large first-hand data set collected from three construction sites. Furthermore, the paper presents the scientific evaluation results of implementing recent object detection algorithms across a set of extended metrics using the original training and validation data sets to improve the generalisability of the experimentation. This paper also provides the practitioners and scholars with a workflow on AI applications in the modular context and the first-hand referencing data.

Views of Turkish EFL teacher trainees toward technology-integrated PBL practices

Problem-Based Learning (PBL) is increasingly becoming popular in teacher education, just like the prevalence in the use of Modular Object Oriented Dynamic Learning Environment (Moodle) which is an instructional socio-constructivist online tool providing collaborative learning. PBL where learning occurs through real-life problem solving practices is also included in the constructivist approach. This study was designed as a mixed methods research which English as Foreign Language (EFL) teacher trainees were involved in PBL through Moodle with the aim of solving problems related to language teaching and learning which they encountered at practicum schools. Participants were 93 EFL teacher trainees studying at a state university in Turkey. The study aimed to reveal the participants’ views of their PBL experiences within the scope of a Materials Evaluation and Adaptation Course. Data were collected through questionnaires and interviews; and analyzed through descriptive statistics and content analysis consecutively. Results demonstrated that the teacher training activities delivered through PBL yielded promising benefits for EFL teacher trainees’ professional development despite some minor flaws faced in the process. Thus, PBL can be considered as a useful method to deliver such courses offered in any branches of teacher education.

Foveal avascular zone segmentation in optical coherence tomography angiography images using a deep learning approach

The purpose of this study was to introduce a new deep learning (DL) model for segmentation of the fovea avascular zone (FAZ) in en face optical coherence tomography angiography (OCTA) and compare the results with those of the device’s built-in software and manual measurements in healthy subjects and diabetic patients. In this retrospective study, FAZ borders were delineated in the inner retinal slab of 3 × 3 enface OCTA images of 131 eyes of 88 diabetic patients and 32 eyes of 18 healthy subjects. To train a deep convolutional neural network (CNN) model, 126 enface OCTA images (104 eyes with diabetic retinopathy and 22 normal eyes) were used as training/validation dataset. Then, the accuracy of the model was evaluated using a dataset consisting of OCTA images of 10 normal eyes and 27 eyes with diabetic retinopathy. The CNN model was based on Detectron2, an open-source modular object detection library. In addition, automated FAZ measurements were conducted using the device’s built-in commercial software, and manual FAZ delineation was performed using ImageJ software. Bland–Altman analysis was used to show 95% limit of agreement (95% LoA) between different methods. The mean dice similarity coefficient of the DL model was 0.94 ± 0.04 in the testing dataset. There was excellent agreement between automated, DL model and manual measurements of FAZ in healthy subjects (95% LoA of − 0.005 to 0.026 mm2 between automated and manual measurement and 0.000 to 0.009 mm2 between DL and manual FAZ area). In diabetic eyes, the agreement between DL and manual measurements was excellent (95% LoA of − 0.063 to 0.095), however, there was a poor agreement between the automated and manual method (95% LoA of − 0.186 to 0.331). The presence of diabetic macular edema and intraretinal cysts at the fovea were associated with erroneous FAZ measurements by the device’s built-in software. In conclusion, the DL model showed an excellent accuracy in detection of FAZ border in enfaces OCTA images of both diabetic patients and healthy subjects. The DL and manual measurements outperformed the automated measurements of the built-in software.