Logic Design Research Articles

Design of remote acquisition system for ecological water demand information of an estuarine wetland

In order to improve data coverage and data collection efficiency, the design method for a remote collection system of ecological water demand information of an estuarine wetland is proposed. The hardware design of the remote information acquisition system is realized through the overall structure design, the Unified Modeling Language (UML), system outline design, system logic design, and system module division. The information is acquired by polling, and the acquisition frequency is adjusted according to the actual situation and user needs. In the system software design, the Scale-invariant feature transform algorithm (SIFT) is used to extract the image features of the estuarine wetland, and a support vector machine is used to cluster the collected information according to the image features to realize the remote acquisition of water demand information of the estuarine wetland. The experimental results show that the maximum data coverage of the proposed method is 95%, and the data acquisition time is less than 0.2 h, indicating that the proposed method has high information acquisition efficiency and high data coverage.

3D Cadastral Database Systems—A Systematic Literature Review

Cadastral databases have been used for over 20 years, but most contain 2D data. The increasing presence of high-rise buildings with modern architecture complicates the process of determining property rights, restrictions, and responsibilities. It is, therefore, necessary to develop an efficient system for storing and managing multidimensional cadastral data. While there have been attempts to develop 3D cadastral database schemas, a comprehensive solution that meets all the requirements for effective data storage, manipulation, and retrieval has not yet been presented. This study aims to analyse the literature on 3D cadastral databases to identify approaches and technologies for storing and managing these data. Based on a systematic literature review integrated with a snowballing methodology, 108 documents were identified. During the analysis of the related documents, different parameters were extracted, including the conceptual data model, query type, and evaluation metrics, as well as the database management system (DBMS) used and technologies for visualisation, data preparation, data transformation, and the ETL (extract, transform, and load) process. The study emphasised the importance of adhering to database design principles and identified challenges associated with conceptual design, DBMS selection, logical design, and physical design. The study results provide insights for selecting the appropriate standards, technologies, and DBMSs for designing a 3D cadastral database system.

Grinding preparation of 2D/2D g-C3N4/BiOCl with oxygen vacancy heterostructure for improved visible-light-driven photocatalysis

A novel 2D/2D g-C3N4/BiOCl (CN/BOC) heterojunction photocatalyst was synthesized by grinding appropriate amounts of CN, Bi(NO3)3·5H2O, glacial acetic acid and KCl at room temperature. The porous CN nanosheets not only facilitate the in situ nucleation and growth of BOC to form thin nanosheets and constitute an intimate contact interface, but also introduce more oxygen vacancies (OVs) in the grinding process. The 2D/2D CN/BOC heterojunction had a good interface and generates a built-in electric field, which can improve the separation of e− and h+. The synergistic effect of the heterostructure and OVs made the photocatalyst have significantly better performance than CN and BOC alone under visible light. The most efficient CN/BOC-5 could achieve a tetracycline (TC) degradation rate of 89.8% within 2 h, which was 1.9 and 1.2 times faster than CN and BOC, respectively. It catalyzed the reduction of CO2 to CO at a rate of 2.00 μ mol h−1 g−1, 1.1 and 3.2 times faster than CN and BOC, respectively. The mechanism for the photocatalysis of CN/BOC-5 was revealed. It was confirmed that the efficiency of photo-induced carrier separation and visible-light photo-absorption were both considerably increased by the synergistic interaction between OVs and 2D/2D heterojunction. This research may open up new possibilities for the logical design of efficient photocatalysts through combining 2D/2D heterojunctions with OVs for environmental remediation.Graphical

Forensic Engineering Investigation of a Machine Guarding-Related Injury

OSHA regulations and industry-accepted standards are intended to be used in conjunction to help prevent worker injury. Despite the aforementioned intention, a point of operation injury occurred to an employee while he was operating a hydraulic rotary bending machine. The machine had been retrofitted with a two-hand control device that was intended to act as a means of point of operation safeguarding. A forensic engineering analysis of both the electromechanical design and programmable logic code — combined with a performance and prescriptive requirement analysis — ultimately revealed flaws in the design of the electromechanical system and software design. It also demonstrated a lack of adherence to the applicable industry-accepted standards related to machine guarding. These factors led to the point of operation injury.

Working with algorithmic management: Design logic, algorithmic unfitness, and labor repair behind the wall

The current literature on algorithmic management primarily explores its external ramifications for workers. Drawing upon the case of Meituan Waimai, China’s dominant food-delivery platform, this article delves into the internal logic that guides the design of algorithmic management. I highlight how an optimal mindset and a mechanized view of human labor drive the formulation of algorithmic management, leading to what I call “algorithmic unfitness.” This concept represents a dissonance between algorithmically programmed, reductionist visions of food delivery and real-world experiences on the ground. In response, the platform constantly delegates tasks from machines to laborers who engage in repair work. The design logic positions couriers as adaptable robots, whose compliance and flexibility are simultaneously requested by the platform. By shedding light on the design choices behind algorithmic management, the article also offers methodological insights for scholars researching algorithmic power in general.

Resource Management Solutions for Modern Law Firms: A Comprehensive Database

In the modern legal landscape, resource management plays a crucial role in the sustained development of law firms and in delivering high-quality legal services to clients. However, there are still law firms that have deviated from database technology and continue to rely on traditional resource management models, which cannot meet the needs of modern enterprise management. This paper aims to explore the current status of resource management in law firms and introduces the design of a universal resource database tailored to the needs of law firms, lawyers, and clients. This paper provides a detailed introduction to the design of the comprehensive resource management database from the perspectives of requirement analysis, conceptual level design, logical level design and physical level design. The comprehensive database primarily store data related to staffs, orders, and clients, providing efficient resource management, and allowing for further expansion on this foundation. Effective resource management is paramount for law firms to maintain their competitiveness and provide excellent legal services, ultimately enhancing the overall client experience.

Research on the design and model of ideological and political teaching of the “Digital Circuit and Logic Design” course

Since the Ministry of Education put forward the requirements of promoting the ideological and political construction of college courses, colleges, and universities have actively designed and explored various professional courses’ ideological and political teaching construction. Taking “Digital Circuit and Logic Design” as an example, this paper constructs the teaching design, teaching model reforms, and the evaluation method of the practical approach by analysing the course’s characteristics, objectives, and current situation. It discusses the implementation path of promoting the ideological and political education of the “Digital Circuit and Logic Design” course.

Memristor-Inspired Digital Logic Circuits and Comparison With 90-/180-nm CMOS Technologies

Compact low-power devices with ultrafast processing speed are the fundamental building blocks for the development of the state-of-the-art logic systems and memristor prominently fulfills these demands and plays a major role in digital circuit design. In this work, design, implementation, and performance evaluation of memristor-based logic gates, such as NOT, AND, NAND, OR, NOR, XOR, and XNOR, and combinational logic circuits, such as adder, subtractor, and 2 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> 1 mux, are presented via SPECTRE in Cadence Virtuoso. Herein, we propose an optimized design of memristor-based logic gates and combinational logic circuits and draw a comparative analysis with the conventional 180-nm complementary metal–oxide–semiconductor (CMOS) technology. The utilized memristor model is thoroughly validated with the experimental results of a high-density Y <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{\text{2}}$</tex-math> </inline-formula> O <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{\text{3}}$</tex-math> </inline-formula> -based memristive crossbar array (MCA), which shows a significantly low values of coefficient of variabilities in device-to-device (D2D) and cycle-to-cycle (C2C) operation. The area, power, and delay calculated from these combinational circuits are found to be reduced by more than 71.4%, 40%, and 54%, respectively, as compared to the conventional 180-nm CMOS technology. The impact of multiple CMOS technology nodes (90 and 180 nm) on the power consumption at the chip-level logic circuit implementation has also been investigated. The adopted memristor-based design significantly improves the performance of various logic designs, which makes it area and power efficient and enables a major breakthrough in designing various low-power, low-cost, ultrafast, and compact circuits.

Engineered extracellular vesicles for tissue repair and regeneration.

Extracellular vesicles (EVs) are heterogeneous membrane-like vesicles secreted by living cells that are involved in many physiological and pathological processes and act as intermediaries of intercellular communication and molecular transfer. Recent studies have shown that EVs from specific sources regulate tissue repair and regeneration by delivering proteins, lipids, and nucleic acids to target cells as signaling molecules. Nanotechnology breakthroughs have facilitated the development and exploration of engineered EVs for tissue repair. Enhancements through gene editing, surface modification, and content modification have further improved their therapeutic efficacy. This review summarizes the potential of EVs in tissue repair and regeneration, their mechanisms of action, and their research progress in regenerative medicine. This review highlights their design logic through typical examples and explores the development prospects of EVs in tissue repair. The aim of this review is to provide new insights into the design of EVs for tissue repair and regeneration applications, thereby expanding their use in regenerative medicine.

Preeminent Designing of Complementary Ternary TRANSFER and COMPLEMENT alongside excitation Modulated Molecular logic systems

The article describes an optically adjustable, dual complementary ternary molecular TRANSFER &amp; COMPLEMENT logic gate as well as an extremely rare design of excitation-modulated logic systems using pyrene coupled bis(indolyl)methane...

Complex Design of CMOS Logic With Tolerance to Particle and Cumulative Radiation

Complex Design of CMOS Logic With Tolerance to Particle and Cumulative Radiation

A127: Difficulties Facing and Coping Strategies of Physical Education and Health Interdisciplinary Teaching in China

Purpose: In response to the national demand for compound talents, “Physical Education (PE) and Health Curriculum (2022 version) for Compulsory Education” proposes to include interdisciplinary teaching in five major courses in China. Due to the lack of course cases for reference, there’s a certain gap between interdisciplinary theory and practice. Therefore, it’s urgent to analyze the difficulties faced by interdisciplinary teaching and find out the coping strategies. Methods: By using keywords such as "interdisciplinary teaching," "PE and health curriculum," and "interdisciplinary," this study collected and studied 39 articles from CNKI, Web of Science, Scopus, and other databases, and analyzed the development process, problems, and countermeasures of interdisciplinary teaching in various countries. Results: Analyses revealed difficulties of implementing interdisciplinary teaching, including (1) unbalanced instructional materials and resources, (2) teachers’ lack of understanding of theory and practice regarding interdisciplinary teaching, (3) overlapped curriculum content, (4) lack of real integration in the classroom, and (5) lack of scientific evaluations. Coping strategies were: (1) Cooperation between internal and external organizations responsible for resource supply, (2) Carry out pre-service and in-service teachers’ training, (3) modifications of PE Curriculum, and (4) establish an evaluation system. Conclusion: To promote interdisciplinary teaching in physical education and health in the future, schools are recommended to cooperate with external institutions and universities to explore the theoretical basis and internal logic of thematic learning design of interdisciplinary projects. Also, schools may build a solid learning community for PE teachers, innovate PE curriculum models, share instructional examples, and create evaluation mechanisms to solve current problems.

Managing Technological Innovation: Dynamic Capabilities, Collaborative Innovation, and Born-Digital SMEs' Performance

In contrast to the digital transformation of the incumbents, born-digital small- and medium-sized enterprises (SMEs) embrace digital logic in the organization's design, processes, and governance from the very start. So far, scholars have focused on the digital transformation of the incumbents; thus, little is known about how dynamic capabilities, collaborative innovation, and firm performance interact in the context of born-digital SMEs—a new generation of digital firms with no legacy of the incumbent firm. Therefore, the study's research question is how dynamic capabilities and collaborative innovation affect the performance of born-digital SMEs. We aim to investigate the impact of the dynamic capabilities of born-digital SMEs on their performance when collaborative innovations mediate it. The empirical research was based on 268 complete viable responses from born-digital SMEs in the U.S., Sweden, and Lithuania. The study results show that dynamic capabilities' effect on born-digital SMEs' performance is more potent when mediated by collaborative innovations. Furthermore, the study highlights that although the impact of dynamic capabilities on partnership networks and relational collaboration is significant, only relational collaboration significantly affects the performance of born-digital SMEs. Our study contributes to the management of technology literature by advancing knowledge on dynamic capabilities and collaborative innovation of born-digital SMEs. In addition, we are exposing the limited role of partnership networks in born-digital SMEs' superior performance and spotlighting the significance of relational collaboration—cocreating innovative products and services and sharing the cocreated value among the relevant partners.

A revised Girvan-Newman clustering algorithm for cooperative groups detection in programming learning

Learning to program is a challenging task for novices. Students vary substantially in their ability to understand complex and abstract topics in computer programming logic, such as loop logic, function recursion, arrays, passing parameters, and program structure design. Cooperative learning is an effective method of learning and teaching programming. In traditional cooperative learning, students group themselves, or teachers group students intuitively. This paper proposes a clustering method based on item response theory (IRT) and the revised Girvan?Newman clustering for clustering students by learning ability. Item response theory calculated the learner?s ability and interpersonal relationship questionnaire generated by the social network analysis. The proposed method was validated by conducting a quasi-experimental test in a freshmen programming course, and the method significantly improved learning outcomes in this course.

Gesture recognition of the Kazakh alphabet based on machine and deep learning models

Currently, a growing body of research focuses on addressing problems using computer vision libraries and artificial intelligence tools. The predominant approaches involve employing machine and deep learning models of artificial neural networks to recognize gestures in the Kazakh Sign Alphabet (KSA) via supervised and deep learning techniques for sequential data processing. Pattern recognition in this context involves identifying an object within an image, where the object can be abstract and vary in shape. We have chosen to investigate the field of gesture recognition, specifically. For recognizing Kazakh Sign Language (KSL), the initial step involves mastering the KSA. Training a neural network to recognize KSL necessitates the collection of datasets in the form of images depicting hand gestures. In this research, prominent hand gesture recognition models such as the Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Support Vector Machine (SVM) were analyzed. These models differ in their methodologies, processing times, and training data requirements. A significant aspect of this study is the application of unsupervised and supervised learning techniques including CNN, LSTM, and SVM. The experiments yielded diverse results when training neural networks for recognizing gestures in Kazakh sign language based on the dactyl alphabet. This article provides a comprehensive overview of each method, their specific purposes, and their effectiveness in terms of performance and training. Numerous experimental outcomes were documented in a table, showcasing the accuracy of recognizing each gesture. Additionally, specific hand gestures were tested in front of a camera to identify the gesture and display the result on the screen. A notable feature was the use of mathematical formulas and functions to elucidate the operating principles of the machine learning methods, as well as the logical structure and design of the LSTM model.

Study of Existing Combination Circuits using CMOS and QCA Technology to Compare Their Efficacy

The potential limitations on the future advancement of microelectronics regular circuit scaling may arise from high power consumption and design intricacy. Therefore, it is imperative to introduce elective innovation to enhance future designs. The utilization of QCA for combinational circuit implementation represents a cutting-edge technological advancement that aims to address the scaling challenges faced by modern electronic devices. The circuit is characterized by the configuration of quantum cells in this logic design technique. This technique relies on the concept of computing through a field connection The utilization of QCA offers many benefits, such as reduced spatial requirements, elimination of interconnects, increased clock frequency, and the potential for low-power processing due to the absence of electron movement. This paper offers a comprehensive comparative analysis of various combinational circuits such as Full adder, MUX, XOR etc. that are considered essential in the field, by utilizing CMOS innovation and QCA nanotechnology.

Comparison of Fuzzy Logic Control and Model Predictive Control for a Smart Adaptive Cruise Control Vehicle System

Adaptive Cruise Control (ACC), Cruise Control (CC), and Automatic Emergency Braking (AEB) serve as the basis of longitudinal automated driving, and as Adaptive cruise control (ACC), cruise control (CC), and automatic emergency braking (AEB) serve as the basis of longitudinal automated driving, and as such have been the subject of much research. Model predictive control (MPC) and fuzzy logic are often considered to be the next steps in improving the capability of these systems, but the two control strategies have not been compared to each other in the ACC, CC and AEB applications. Also, the three features (ACC, CC and AEB) have never been compiled into a single fuzzy logic controller. The purpose of this paper is to design a fuzzy logic-based ACC, CC, and AEB controller and compare it to an equivalent MPC controller. All three controllers control the desired longitudinal acceleration, and their functionality is tested using Matlab’s Fuzzy Logic Designer and other Simulink toolboxes. Ultimately, the results of the analysis demonstrate that the proposed fuzzy controller operates just as well if not better than the MPC controller and that the fuzzy controller is able to operate well in all tested scenarios.

The Applications of Machine Learning to Novel Drug Discovery

Drug discovery is a time-consuming, costly and often off-target discovery pipeline that nonetheless plays a crucial part in medical treatment field. In the past few decades, experimental assays remain the most reliable approach to screen compounds with huge cost. However, many artificial intelligence and machine learning algorithms have been implemented to modernize this field, such as through predicting molecular interactions or properties and analyzing biological data to identify potential drug targets, drug monitoring, and toxicity prediction. In summary, machine learning advancements provide critical support for logical drug design and discovery process, which could finally benefit all of humankind.

Learning efficacy of understanding by design-Internet of Things (UbD-IoT) education integrated with design thinking and computational thinking

PurposeThe study integrated understanding by design-Internet of Things (UbD-IoT) education with design thinking and computational thinking to plan and design an IoT course. Cross-domain application examples were employed to train students in problem-understanding, deep thinking and logical design for IoT applications.Design/methodology/approachIn this study, the UbD model was integrated with design thinking and computational thinking in the planning and design of an IoT course. The examples of cross-domain applications were used to train students to understand a problem by engaging themselves in deep thinking and helping them think and design logically for an IoT application.FindingsThe UbD-IoT learning design greatly decreased students' overall cognitive load. UbD-IoT learning has a significant impact on the performance of computational thinking in problem-solving and problem-understanding. The impact of UbD-IoT learning on logical thinking and program learning cognition in students needs to be verified.Originality/valueThe results of this study have shown that the UbD model is effective in reducing the cognitive load of a learning course and also strengthens T-competencies in the lateral skills of computational thinking, critical problem-solving, logical thinking and creative thinking.

FPGA-Based Implementation of SCADA System for Fuel Management

With the emergence of Digital Processors and Logic Design technologies, like FPGAs, the trend of using IC-based plug-and-play modules has been minimized. The focus is commercial off-shelf designing and developing modules and sub-modules on new FPGA technology. Some of the critical factors that make FPGA more suitable include enormous computational power, capabilities to perform logic operations, high-speed clocks, fast memory, and various built-in primitives for computation-intensive arithmetic operations. FPGA becomes suitable for implementing data capturing and processing systems with these characteristics. This paper is about designing and developing an FPGA-based Supervisory Control and Data Acquisition (SCADA) System to monitor and control the fuel level transition between two tanks that generally are designed using PLC. PLC-based SCADA systems are easy to implement, but when discussing performance, PLC cannot replace FPGA. The FPGA chosen is Spartan-3 due to its low cost and meeting the industrial temperature needs. At the same time, it may be translated into any advanced FPGA, producing fewer sources and power consumption benefits. The simulator is Xilinx 14.7 ISE, along with SDK. The implemented system provides the inherent amenities of SCADA along with the benefits of high speed, more accuracy, reduced and predictable delay, and a purely digitized system facilitated by the FPGA.