Library Of Modules Research Articles

Creation and Diversified Applications of Plane Module Libraries for Prefabricated Houses Based on BIM

In recent years, due to the advantages of high construction efficiency and less environmental pollution, prefabricated housing has been of increasing interest and vigorously promoted. However at present, most prefabricated houses simply pursue an increase in assembly rate, and the floor plan design still continues to follow the traditional design method of housing, which does not meet the requirements of industrialization and cannot achieve the goal of product diversification. This paper puts forward a method for floor plan designs of prefabricated houses whose core is building plane module libraries. The modules in module libraries all conform to standardized and refined designs. A new residential floor plan can be obtained by selecting and recombining modules in module libraries. The richer the module library, the more diverse the results will be under the same combinatorial logic, which can greatly improve design efficiency. In addition, this paper probes the method of creation and applications of plane module libraries in detail, so as to provide a new idea for floor plan designs of prefabricated houses. This research is of great significance for improving the efficiency of floor plan design of prefabricated housing and realizing goals of standardization and diversification of prefabricated housing development.

Possibilities of artificial intelligence in assessing the impact of potentially dangerous texts in modern news discourse: problem of statement

The relevance of the stated problem reflects the study of the “friend-foe” dichotomy, which is clearly represented in the modern news discourse, since it reflects the most significant problems for society: migration, the COVID-19 pandemic, crime, various confrontations, problems of socially vulnerable citizens, etc. The subject of the research is to Refine the parameters for evaluating potentially dangerous texts for the subsequent creation of a library of software modules for theming and classifying news messages, including using AI technologies. Hypothesis: the proposed parameters of the system of interpretation of potentially dangerous text increase the chances of determining the prognostic level of the degree of propensity to illegal actions, so the creation of a digital library will help to quickly analyze the levels of potential dangers for the recipient. The use of digital technologies for psycholinguistic assessment of potentially dangerous texts optimizes the search and tracking of such texts, contributing to the development of measures to ensure the safety of the human psyche in conditions of massive impact on the recipient in order to change his personal attitudes. The author raises the problem of creating a single digital platform for evaluating such texts, noting the need for linguistic priority when creating semantic markup, which will allow us to qualitatively rank potentially dangerous texts. Such work requires the application of interdisciplinary efforts of specialists in the fields of linguistics, psychology, mythology, history, sociology, political science, cultural studies, mathematics, computer science and Digital Humanities. The practical value is unquestionable, since psycholinguodiagnostics of a person does not correlate with the potential danger of texts produced by such a person in society.

Three-dimensional limit equilibrium method based on a TIN sliding surface

The three-dimensional limit equilibrium method (3D LEM) is an important approach for analysing slope stability, and the rationality of simulations for sliding surfaces directly affects the factor of safety (FoS) accuracy. Typically, the grid model containing grid elements with fixed size and uniform distribution in a digital elevation model (DEM) is used to simulate sliding surfaces. However, it is difficult to accurately express the real sliding surface shape unless a sufficient number of grid elements are used. Moreover, the four vertexes in each grid with different elevations are assumed to be located in the same plane, which may result in incorrect slope parameters and degraded FoS accuracy. To overcome these shortcomings, the triangulated irregular network (TIN) model is adopted to construct sliding surfaces, making full use of the flexibility and accuracy of triangular elements in describing surfaces and the uniqueness of the plane determined by three vertexes. A method to generalize and simplify TIN sliding surfaces is proposed based on Visualization Toolkit (VTK) open source library modules. Furthermore, combined with the Hovland method, a 3D LEM model based on a TIN is presented, and the corresponding calculation module is written and compiled in Python. To compare the FoS precision and computational efficiency, several classic examples with ellipsoidal and planar sliding surfaces are used to analyse the slope stability. The results show that, under the condition of obtaining nearly the same FoS, the number of triangles needed can be ordered from lowest to highest as follows: the simplified TIN sliding surface, unsimplified TIN, and grid model. In addition, the computation time required for the grid model is many times higher than that of the TIN sliding surface. Therefore, compared with the grid model, the TIN sliding surface adopted in the 3D LEM can effectively improve the accuracy and efficiency of FoS calculations.

A conceptual development of reconfigurable drill machine tool (RDMT)

Reconfigurable machine tools are emerging as new generation machine tools for dealing with the fluctuating market scenario and immense competition between original equipment manufacturers. New approaches, mechanism and designs principles are required for the development of these machine tools in manufacturing systems. A lot of research work has been done in reconfigurable machine tool (i.e. lathe, milling, shaper, NC, CNC etc.) but still less work has been conducted to develop reconfigurable drilling machine. This paper presents a modular approach to develop Reconfigurable Drilling Machine Tool, which will allow the machine not only to reconfigure the modules in a certain way for performing a specific task but also to develop a new type of machine which can incorporate all the features of reconfiguration for the production of multiple part families on a single platform. A module library, which includes basic and auxiliary modules, is implemented on this machine tool to explain the core features (i.e. scalability, modularity, convertibility and flexibility). Probably, this proposed design contributes a theoretical approach for the reconfiguration features of drilling machine in Reconfigurable Manufacturing System and this proposed design is illustrated through a figure, which is developed on design software (i.e. solid works platform).

Live interactive queries to a software application's memory profile

Memory operations are critical to an application's reliability and performance. To reason about their correctness and track opportunities for optimisations, sophisticated instrumentation frameworks, such as Valgrind and Pin, have been developed. Both provide only limited facilities for analysing the collected data. This work presents a Valgrind's extension for examining a software applications’ dynamic memory profile through live interactive analysis with SQL. The Pico COllections Query Library (pico ql) module maps Valgrind's data structures that contain the instrumented application's memory operations metadata to a relational interface. Queries are type-safe and the module imposes only a trivial overhead when idle. The authors evaluate the proposed approach on ten applications and through a qualitative study. They find 900 kb of undefined bytes in bzip2 that account for 12% of its total memory use and a performance-critical code execution path in the Unix commands sort and uniq. The referenced functions are part of glibc and have been independently modified to boost the library's performance. The qualitative study has users rate the usefulness, usability, effort, correctness, and expressiveness of pico ql queries compared to Python scripts. The findings indicate that querying with pico ql incurs lower user effort.

Welcome to Normalton

This design case details the critical design decisions used in the development of an e-learning module library for North Carolina local government officials focused on land use regulations. These modules cover topics from an introduction to land use regulations, to evidentiary hearing conduct guidelines, defining vested rights, and explaining how to adopt and amend an ordinance. This project was in response to the North Carolina League of Municipalities (NCLM) members’ increased requests for training in this subject area. This organization requested the assistance of the two faculty members at the University of North Carolina at Chapel Hill School of Government (SOG) who specialize in this content area. Additionally, the professional organization wanted to mitigate risk from cases going to litigation for improper land use decisions. The Target Accomplishment Past Prototype Artifact (TAPPA) Process (Moore, 2016) was used for the module development. This five-step process emphasizes the rapid development of distance education content artifacts in close collaboration with subject matter experts. Between 2013 and 2018, the TAPPA iterative design process guided the development of sixteen modules moving from initial script to finished modules. This design case is relevant for instructional designers who need to develop comprehensive e-learning modules covering complex and often complicated tasks. Examples of design decisions, informed by Clark and Mayer (2016)’s principles of multimedia design, are dispersed through the design case.

Quantitative high-throughput screening assays for the discovery and development of SIRPα-CD47 interaction inhibitors.

CD47 is an immune checkpoint molecule that downregulates key aspects of both the innate and adaptive anti-tumor immune response via its counter receptor SIRPα, and it is expressed at high levels in a wide variety of tumor types. This has led to the development of biologics that inhibit SIRPα engagement including humanized CD47 antibodies and a soluble SIRPα decoy receptor that are currently undergoing clinical trials. Unfortunately, toxicological issues, including anemia related to on-target mechanisms, are barriers to their clinical advancement. Another potential issue with large biologics that bind CD47 is perturbation of CD47 signaling through its high-affinity interaction with the matricellular protein thrombospondin-1 (TSP1). One approach to avoid these shortcomings is to identify and develop small molecule molecular probes and pretherapeutic agents that would (1) selectively target SIRPα or TSP1 interactions with CD47, (2) provide a route to optimize pharmacokinetics, reduce on-target toxicity and maximize tissue penetration, and (3) allow more flexible routes of administration. As the first step toward this goal, we report the development of an automated quantitative high-throughput screening (qHTS) assay platform capable of screening large diverse drug-like chemical libraries to discover novel small molecules that inhibit CD47-SIRPα interaction. Using time-resolved Förster resonance energy transfer (TR-FRET) and bead-based luminescent oxygen channeling assay formats (AlphaScreen), we developed biochemical assays, optimized their performance, and individually tested them in small-molecule library screening. Based on performance and low false positive rate, the LANCE TR-FRET assay was employed in a ~90,000 compound library qHTS, while the AlphaScreen oxygen channeling assay served as a cross-validation orthogonal assay for follow-up characterization. With this multi-assay strategy, we successfully eliminated compounds that interfered with the assays and identified five compounds that inhibit the CD47-SIRPα interaction; these compounds will be further characterized and later disclosed. Importantly, our results validate the large library qHTS for antagonists of CD47-SIRPα interaction and suggest broad applicability of this approach to screen chemical libraries for other protein-protein interaction modulators.

Modular Hardware Implementation of SOM Neural Network Based on FPGA

With the development of artificial intelligence technology, artificial neural networks have been widely used in many fields. And traditional artificial neural network implementation methods generally have the disadvantages of poor flexibility and low real-time performance. To solve these problems, this paper presents a modular hardware implementation method of SOM neural network based on FPGA. Firstly, based on the analysis of the model structure, operation process and learning algorithm of SOM neural network, combined with the conditions and limitations of FPGA hardware implementation, the network model is divided into five modules with relatively independent structure and function. Secondly, VHDL is used to describe the RTL of each module to build a common module library. Finally, in practical applications, the target hardware of the SOM neural network can be constructed by combining the modules according to requirements. When building a hardware network, flexible configuration of the arithmetic structure is achieved by setting and passing parameters. The performance test results show that compared with the software simulation method and the traditional hardware implementation method, this method has higher running speed and more flexible operation structure, and can meet the application requirements of high-speed and miniaturized intelligent information processing system.

An investigation of the structural properties of Li and Na fast ion conductors using high-throughput bond-valence calculations and machine learning

Progress in energy-related technologies demands new and improved materials with high ionic conductivities. Na- and Li-based compounds have high priority in this regard owing to their importance for batteries. This work presents a high-throughput exploration of the chemical space for such compounds. The results suggest that there are significantly fewer Na-based conductors with low migration energies as compared to Li-based ones. This is traced to the fact that, in contrast to Li, the low diffusion barriers hinge on unusual values of some structural properties. Crystal structures are characterized through descriptors derived from bond-valence theory, graph percolation and geometric analysis. A machine-learning analysis reveals that the ion migration energy is mainly determined by the global bottleneck for ion migration, by the coordination number of the cation and by the volume fraction of the mobile species. This workflow has been implemented in the open-source Crystallographic Fortran Modules Library (CrysFML) and the program BondStr. A ranking of Li- and Na-based ionic compounds with low migration energies is provided.

Introduction to Machine Learning and Its Basic Application in Python

Artificial Intelligence, Machine Learning and Deep Learning are the buzzwords that have been able to grasp the interest of many researchers since various numbers of years. Enabling computers to think, decide and act like humans has been one of the most significant and noteworthy developments in the field of computer science. Various algorithms have been designed over time to make machines impersonate the human brain and many programming languages have been used to implement those algorithms. Python is one such programming language that provides a rich library of modules and packages for use in scientific computing and machine learning. This paper aims at exploring the basic concepts related to machine learning and attempts to implement a few of its applications using python. This paper majorly used Scikit-Learn library of Python for implementing the applications developed for the purpose of research.

Optimization Design and Application of Active Disturbance Rejection Controller Based on Intelligent Algorithm

The parameter tuning optimization design is realized for an active disturbance rejection controller (ADRC) in combination with the improvement of the existing swarm intelligence algorithm. Taking the optimization design and application of ADRC as an example, this paper is focused on investigating the improvement of the hybrid algorithm composed of fish swarm algorithm and particle swarm optimization algorithm and its application in parameter tuning of ADRC. The main contents are as follows. First, the parameters that need to be tuned are determined based on the composition and principle of the ADRC. The module building technology of S-function is adopted to create the module library of ARDC in terms of the modular construction idea and a complete simulation example of ADRC is built in Simulink. Second, the parameters are improved according to the proposed hybrid algorithm composed of the artificial fish swarm algorithm and the standard particle swarm optimization algorithm, and the control performance is tested by the MATLAB simulation of the ADRC whose parameters are optimized by using the algorithm. Finally, the flight attitude control of the unmanned aerial vehicle (UAV) is taken as an application example, and the fixed-wing UAV is selected as the research object. Through the analysis of the experimental results, the effectiveness of the optimized design is verified for the ADRC in the attitude control of the UAV.

Utilization of an online module bank for a research training curriculum: development, implementation, evolution, evaluation, and lessons learned

ABSTRACTBackground: Students enter Oakland University William Beaumont School of Medicine’s required research program, Embark, with variable levels of experience. Recognizing this, Embark allows for progression through the individual research project with flexibility. Since 2014, student self-directed curriculum personalization is promoted through a menu of online modules.Objective: This evaluation sought to understand student usage of the modules, identified strengths of the modules and preferred attributes of the modules. Gaining this evidence will provide information on how to best meet students’ needs in a just-in-time format.Methods: A retrospective mixed methods analysis of the module library was conducted. The library was constructed using best practices as an educational tool. The retrospective evaluation included analysis of students’ viewing patterns and answers to required course evaluations during the fall semesters of 2014 to 2017. Students’ preference for modules was determined by viewing records and conjoint analysis.Results: Students’ milestone preparation was not negatively impacted by relocation of curricular content from lecture to modules. Changes in module implementation within the course (2016) resulted in an increase of students viewing modules beyond only the minimum course requirements (71% (2016) from 10% (2014)). Data from both quantitative and qualitative evaluation questions show an increase in students’ identifying the modules as a strength to individualize the course. The identified module strengths include content individualization, just-in-time access, while identified needs included a desire for additional modules. Students preferred modules that were animated, shorter in duration and curated from an external source.Conclusions: Online modules provide students with a rich set of resources allowing for individualized learning. Lessons learned in the implementation of the online modules may be transferable to many educational topics. When implementing similar technology projects, usage rates, learner feedback, and effect on appreciation of the content are important to frequently monitor.

Innovating and diffusing Internet commerce through user engagement: an empirical study of massively multiplayer online games

ABSTRACTBy embedding marketing tools in systems, this study investigates the effect of user engagement on the innovation and diffusion of online games. The associated marketing tools are related sets of toolkits, which are basic building units that empower users to operate interfaces efficiently, thus making the interfaces user-friendly. The distinct types of engaging toolkits (trial-and-error, solution-space, user-friendly, module library, translation and diffusion) promote online performance by enhancing word-of-mouth (WOM) reputation and versioning speed. A widely used social networking website in Taiwan dedicated to online games, www.gamer.com.tw, is investigated in this study. The results indicate that WOM reputation is higher for online games that have engaged players by providing more module-library, translation and diffusion marketing toolkits compared to those with fewer toolkits. Moreover, versioning speed was higher for online games embedded with more trial-and-error, solution-space, user-friendly and translation toolkits compared to those with fewer toolkits. These results reveal the unequal efficacy of embedded marketing tools for user engagement in the online context and have implications for research and practice related to online product development and Internet service marketing strategies. These results can be referenced in strategies for creating interfaces that facilitate user-generated creativeness, innovations and communications.

Efficiency increase of the manufacture technological preparation on the basis of CAD/CAM/CNC systems

Problems and prospects for CNC machines programs preparation have been considered, ways of their development and further prosecution have been established, which are recommended to be followed by specialists of a particular enterprise when organizing production preparation structures. The analysis of the organization of technological preparation of production carried out in this work is aimed at obtaining the answer to the main question: whether a technologist is developing a technology and a program or the CNC machine operator is responsible for developing a program for the approved technology. Parameterization of the program, the next stage of which is the creation of programs for object-oriented technology is offered as the solution of the given dilemma - in full accordance with the CAD models of parts.Such an approach is the foundation for an object-oriented projecting that is the next stage in developing programming for CNC machines. Attention is paid to the development of parametrized object-oriented modules for programs, making up "classes" and "class methods" for processing surfaces with identical geometry. In this case, the task of the technologist is to create a library of parameterized modules for control programs for processing typical surfaces for a particular production. Then it becomes possible to transfer a program assembled from the modules to the workshop, where the CNC machine operator will record the actual parameters for that particular part. The implementation of such an interrelationship "technologist-NC operator" necessitates a qualitatively new approach to the development of control programs that provide not only the proper shaping trajectory, but control the accuracy and roughness of the surfaces to be machined proceeding from the elements of the program and the disturbances compensation

Library Staffs Perception on Library Automation in University Libraries: A Comparative Study in Karnataka and Tamil Nadu

The present study deals with an opinion of university library staff on library automation in selected university libraries in Karnataka and Tamil Nadu. The study reveals that, staff education and qualification for library automation process and modules handling the library automation process is dealt. Explains the library staff’s training they have undergone in handling library automation software and to know that necessary training requirement for handling the modules in library automation software as well as improving the overall performance of library computerised services. The study further explains housekeeping activities for create a library database in the university library automation process.

Legal Engineering on the Blockchain: ‘Smart Contracts’ as Legal Conduct

A new legal field is emerging around blockchain platforms and automated transactions. Understanding the relationships between law, legal enforcement, and these technological systems has become critical for scaling blockchain applications. Because ‘smart contracts’ do not themselves constitute agreements, the first necessary ‘legal’ development for transacting with these technologies involves linking computational transactions to natural language contracts. Various groups have accordingly begun building libraries of machine readable transaction modules that correspond to natural language contracting elements. In doing so, they are creating the building blocks for ever more complex transactions that will ultimately define the entire envelope of computational legal conduct in these environments, and likely standardise the field. However, also critical to emerging blockchain ‘legalities’, is the capacity for dispute resolution and legal enforcement. Beyond the performance of parties, or the quality of goods and services transacted, new mechanisms are also needed to address the performance of the computational transaction systems themselves. Such mechanisms are necessary to address the reality that smart contracts cannot be forced to perform actions beyond the parameters of their coding, even by a judicial order. Legal tools, both technological and institutional, are thus being developed to ‘soften’ the effects of self-executing transactions. In this article we treat these developments as law-making practices that are constitutive of an emerging legal field. Legal engineering exercises of this kind are not novel, and by drawing on historic examples from the common law and international arbitration, we gain insights into the competitive dynamics likely to be shaping legal engagements on the blockchain.

Automatic Modeling and Simulation of Modular Robots

The ability of reconfiguration makes modular robots have the ability of adaptable, low-cost, self-healing and fault-tolerant. It can also be applied to a variety of mission situations. In this manuscript, a robot platform which relied on the module library was designed, based on the screw theory and module theory. Then, the configuration design method of the modular robot was proposed. And the different configurations of modular robot system have been built, including industrial mechanical arms, the mobile platform, six-legged robot and 3D exoskeleton manipulator. Finally, the simulation and verification of one system among them have been made, using the analyses of screw kinematics and polynomial planning. The results of experiments demonstrate the feasibility and superiority of this modular system.

Modeling and Simulation of Linear Active Disturbance Rejection Controller in Simulink

The principle and structure of linear active disturbance rejection controller(LADRC) are analyzed, and the algorithm of the controller is clarified and the parameter setting process is simplified. Completing the creation and packaging of functional modules of linear active disturbance rejection controller by Simulink modeling idea and creating a module library of linear active disturbance rejection controller. The validity of linear active disturbance rejection controller and the effectiveness of the modeling method are described by linear active disturbance rejection control simulation of a second—order nonlinear time—varying object.

Key maturity indicators for module libraries for PLC-based control software in the domain of automated Production Systems

As module libraries in PLC-based control application in automated Production Systems (aPS) are the key to more efficient engineering, the quality maturity of these modules should be measurable. Such maturity indicators help to convince application engineers and start-up personnel to use existing modules instead of re-inventing the wheel, resulting in huge savings of money and time. This paper proposes quality metrics for such module libraries and their visualization for the domain of aPS.

High-Throughput Screening of Chemical Compound Libraries for Modulators of Salicylic Acid Signaling by In Situ Monitoring of Glucuronidase-Based Reporter Gene Expression.

Salicylic acid (SA) is a vital phytohormone that is intimately involved in coordination of the complex plant defense response to pathogen attack. Many aspects of SA signaling have been unraveled by classical genetic and biochemical methods using the model plant Arabidopsis thaliana, but many details remain unknown, owing to the inherent limitations of these methods. In recent years, chemical genetics has emerged as an alternative scientific strategy to complement classical genetics by virtue of identifying bioactive chemicals or probes that act selectively on their protein targets causing either activation or inhibition. Such selective tools have the potential to create conditional and reversible chemical mutant phenotypes that may be combined with genetic mutants. Here, we describe a facile chemical screening methodology for intact Arabidopsis seedlings harboring the β-glucuronidase (GUS) reporter by directly quantifying GUS activity in situ with 4-methylumbelliferyl-β-D-glucuronide (4-MUG) as substrate. The quantitative nature of this screening assay has an obvious advantage over the also convenient histochemical GUS staining method, as it allows application of statistical procedures and unbiased hit selection based on threshold values as well as distinction between compounds with strong or weak bioactivity. We show pilot screens for chemical activators or inhibitors of salicylic acid-mediated defense signaling using the Arabidopsis line expressing the SA-inducible PR1p::GUS reporter gene. Importantly, the screening methodology provided here can be adopted for any inducible GUS reporter line.