Design Of Digital Systems Research Articles

Design of Digital Economy Industry Investment Decision Support System Based on Fuzzy Comprehensive Evaluation Method

Design of Digital Economy Industry Investment Decision Support System Based on Fuzzy Comprehensive Evaluation Method

Investigating the Impact of Digital Leadership Dimensions on Service Economics Dimensions: An Empirical Study of Service Ministries in the Kingdom of Saudi Arabia

This study examines the influence of various aspects of digital leadership (such as digital culture, visionary planning, system design, empowering leadership, employee development, innovation, persuasion, and knowledge) on different dimensions of service economics (including innovative economic ideas, efficient use of economic resources, leadership behaviors, and economic learning) within service ministries in the Kingdom of Saudi Arabia. We used a quantitative technique to collect data from a sample of 475 workers involved in service ministries via the use of a survey questionnaire. We conducted a thorough study of the data using the method of multiple regression analysis. The findings indicate that the different components of digital leadership have a significant and advantageous impact on the variables associated with service economics. The research determined that digital culture, innovation, and employee professional development are the main characteristics that have a major impact on digital leadership. This study contributes to the current literature by providing empirical evidence on the relationship between digital leadership and service economics. Additionally, it offers practical suggestions for service ministries in Saudi Arabia to enhance their service economics via the implementation of effective digital leadership methods. Nevertheless, the study is subject to many limitations, including its cross-sectional design and its narrow emphasis on a particular environment. It is recommended that future research endeavors address these constraints.

Reliable Synchronous and Asynchronous Counter Design in QCA

Due to rapid growth in the integrated circuit (IC) industry, the demand for compact digital system design is high. However, the continued technology reductions made the feasibility of further scaling down transistor size more challenging. In response to the growing demand for ultra-compact IC designs, the revolutionary quantum-dot cellular automata (QCA) technology has emerged as a promising solution. In a digital era, the counters are widely adopted in the peer-to-peer process flow to establish a mechanism for generating unique values for each identifier/number. In this work, a unique synchronous and asynchronous counters architecture is proposed with a reliable D and T flip-flop design. The proposed QCA architecture is implemented and validated with the QCA designer tool. Furthermore, in QCA technology, unreliable QCA designs can lead to frequent errors and malfunctions in the implemented logic. To overcome this challenge, the proposed design prioritizes cell placement (the relative positions of QCA cells) to make the circuit more robust. As a result, the circuit can still produce the expected functionality even if some QCA cells malfunction. Hence, to ensure the reliability of the proposed QCA architecture, the missing cell defect analysis is carried out in comparison with existing state-of-the-art designs. Based on comparison results, the unique designs like the proposed multiplexer, D flip-flop and T flip-flop design exhibit success rates of 67.28, 77.04 and 85.15%, respectively. The experimental results demonstrate that the proposed counter-architecture outperforms existing architectures.

Design and Implementation of a 7-Person Voting Device based on Quartus

As the complexity of digital system design continues to increase, efficient and precise decision support systems have become increasingly important. This paper presents the design and implementation of a 7-voter decision system based on Altera’s Quartus software. The voter is applied in the core decision-making process to ensure the accuracy and efficiency of decisions. The study begins by outlining the design principles of the 7-voter decision system, using a design philosophy that minimizes timing delays and optimizes hardware resource utilization. A complex majority voting logic circuit is implemented using high-level hardware description languages (VHDL/Verilog), ensuring the advanced nature and applicability of the voting circuit. In terms of the logical implementation of the voting circuit, the paper conducts an in-depth analysis of the optimization of combinational and sequential logic and standardizes the input and output to enhance the signal stability and the system’s resistance to interference. On the Quartus platform, the design process of the voting system is elaborated in detail, with careful consideration given to boundary conditions and hardware compatibility. The implementation of the voter has undergone rigorous simulation and testing. Strict parameter setting for simulations and waveform analysis confirm the correctness of the circuit, and fault simulation tests further confirm its reliability. Performance indicators such as response time and percentage of resource utilization have been quantitatively analyzed and meet the design objectives set beforehand. Overall, this research not only realizes a highperformance 7-voter decision system but also provides an effective case study for applications on the high-performance Quartus design platform. Future research can build on the current work to further optimize algorithms and hardware, explore the potential for the application of the voter in a broader range of fields, and adapt to the new features of the Quartus platform to achieve more powerful decision support functions.

Frontiers in construction 3D printing: self-monitoring, multi-robot, drone-assisted processes

AbstractTo overcome productivity issues and revolutionize the stagnating construction industry, a large amount of research efforts has been devoted to robot-assisted construction technology. The advancements in robotics including mechanical system design, tool design, digital system design, and numerical control systems design enabled engineers to create complex geometries that are infeasible for conventional construction methods. In addition, innovative robotic systems that utilize mobile platforms, multiple robots, and unmanned aerial vehicles have demonstrated significant promise in fully automating the construction process. This work will provide a perspective on the state-of-the-art applications of robotics in the revolution of construction, where a comprehensive review of the current development of the relevant software and hardware, 3D concrete printing (3DCP), robot-assisted assembly of discrete prefabricated blocks, real-time quality monitoring and feedback control systems, and typical innovative robot-assisted structural designs are conducted. Finally, the limitations of existing robot-assisted construction technology are identified, which leads to several recommendations for future research toward fully automatic construction.

Human factors methods in the design of digital decision support systems for population health: a scoping review

BackgroundWhile Human Factors (HF) methods have been applied to the design of decision support systems (DSS) to aid clinical decision-making, the role of HF to improve decision-support for population health outcomes is less understood. We sought to comprehensively understand how HF methods have been used in designing digital population health DSS.Materials and methodsWe searched English documents published in health sciences and engineering databases (Medline, Embase, PsychINFO, Scopus, Comendex, Inspec, IEEE Xplore) between January 1990 and September 2023 describing the development, validation or application of HF principles to decision support tools in population health.ResultsWe identified 21,581 unique records and included 153 studies for data extraction and synthesis. We included research articles that had a target end-user in population health and that used HF. HF methods were applied throughout the design lifecycle. Users were engaged early in the design lifecycle in the needs assessment and requirements gathering phase and design and prototyping phase with qualitative methods such as interviews. In later stages in the lifecycle, during user testing and evaluation, and post deployment evaluation, quantitative methods were more frequently used. However, only three studies used an experimental framework or conducted A/B testing.ConclusionsWhile HF have been applied in a variety of contexts in the design of data-driven DSSs for population health, few have used Human Factors to its full potential. We offer recommendations for how HF can be leveraged throughout the design lifecycle. Most crucially, system designers should engage with users early on and throughout the design process. Our findings can support stakeholders to further empower public health systems.

A review of the design and research of asynchronous FIFOs

Asynchronous FIFO (First In First Out) is a hardware structure for data transfer across clock domains. It is very important in the design of digital systems, especially when data needs to be exchanged between different modules or subsystems. The main function of an asynchronous FIFO is to solve the data transfer problem due to the unsynchronization of the clock domain, so as to ensure the integrity of the data and the stability of the system. Asynchronous FIFO is widely used in such fields as data acquisition systems, communication systems, and multiprocessor systems. It ensures the stability of data transmission between different modules and the overall system performance through reliable clock domain synchronization and effective read/write management. This paper provides a comprehensive review and analysis of the design principles, implementation methods, and applications of asynchronous FIFO memory. By examining the foundational concepts, various design techniques, and practical applications, this paper aims to offer valuable reference and guidance for digital system designers.

An FPGA-based parallel deconvolution application envisaging high-energy calorimeters operating under severe pile-up conditions

Signal pileup may arise when the system response time is larger than what would be required by the event rate in the application. In this condition, information superposition occurs, and signal estimation is deteriorated due to such information distortion. For online applications, mitigating such a pileup distortion usually requires embedded digital signal processing, which often involves FPGA-based designs when high event rates are a concern. Recently, high-energy particle experiments started facing an unprecedented increase in pileup conditions, which demanded new approaches for signal estimation. This work proposes a dedicated parallel signal processing system embedded on an FPGA platform that implements different filtering techniques for online energy reconstruction in calorimeters (energy measurement) operating under severe pileup conditions. Each designed filter is an inverse approximation of the calorimeter readout channel's impulse response, performing deconvolution of the incoming signals. Such a deconvolution approach for energy estimation was recently introduced, and the proposed filters were implemented in this work. Evaluation of the digital system design was performed using a data set that considers a typical high-energy calorimeter front-end response, as high-luminosity particle collider experiments produce high pileup distortions in calorimeter signals when processing the subproducts of the collisions. As the Large Hadron Collider (LHC) provides the most demanding conditions in terms of signal pileup, the acquisition system of the proposed solution is synchronous with its collision rate (40 MHz). The results showed that the proposed implementation may be applied as a preprocessing (pileup reduction) step in calorimeter instrumentation and could reduce the signal pileup within the fast response time required by such experiments.

Gender Harmony: A Case for Nursing Informatics.

The design of digital health information systems around a conflated gender/sex binary contributes to health inequities. Lack of specific information that supports affirming communication lead to inappropriate care, disrespectful encounters with healthcare staff, and avoidance of health services by clients who have been harmed by misgendering, deadnaming and being outed. The HL7 International Gender Harmony Model (HL7 GHM) supports the design, implementation and use of DHIS that enable affirming clinical interactions and care. This case study will demonstrate how applying the HL7 GHM can address the harms reported in a recently published account of one patient in Canada.

Teaching content model for designing digital systems of power grid relay protection and automation

It was found that the effective formation of conceptual-analytical and productive-synthetic levels of formation of professional knowledge and skills regarding the design of digital systems of power grid relay protection and automation is possible with the systematic development and use of a generalized model of the teaching content. Based on the study of information models of technical systems, a feature model was adopted as a basic invariant, which includes a set of features of the purpose, construction, principle of operation and parameters of the technical system. It was found that the design process of digital systems of power grid relay protection and automation can be conventionally divided into three stages, namely, the development of the design task, the direct implementation of the design, and the determination of the parameters of operation. Causal chains of knowledge that form the basis of problem solving at these three stages are determined. It was found that the methods of step-by-step decomposition and aggregation are key in building the content of teaching the design of digital systems of power grid relay protection and automation based on causal chains of knowledge. A generalized model of the teaching content design of digital systems of power grid relay protection and automation based on causal chains of knowledge is substantiated. According to the generalized model, the teaching content design of specific microprocessor l systems of power grid relay protection and automation has been developed. With the help of experimental verification, the effectiveness of the teaching content design of digital systems of relay protection and automation based on causal chains of knowledge has been proven. The results of the research can be used in the educational process of professional training of future engineers in the specialty 141 Electric power, electrical engineering and electromechanics.

Enhanced Medical Image Segmentation using Transfer Learning with Res101_UNet: Experimental Insights and Comparative Performance Analysis

Throughout the past few decades, artificial intelligence and machine learning have seen a lot of active research in areas such as computer vision, natural language processing, and speech processing. As a result, deep learning models became state-of-the-art for computer vision tasks such as object detection, classification, segmentation, and other allied tasks. Of course, the fruits of this research are extended to the design of robust and reliable digital health systems as well as other applications in the healthcare sector. Many clinical applications require the automatic segmentation of medical images. Recent deep learning-based approaches have demonstrated state-of-the-art performance in medical image segmentation tasks. In addition to their ability to automatically extract features and generalize over large amounts of data, transfer learning based deep learning models have proven to be handy for data scared areas like medical domains. In this research, we investigate and demonstrate the efficacy of a DCNN-based transfer learning model -Res101_Unet, which has been trained and/or fine-tuned to execute tumor tissue segmentation tasks in MRI, CT, PET, and X-RAY pictures of medical organ scans with little data. For our experimental study, we employed two image datasets: 'Liver Tumor' and 'Gland Colon Cancer', both obtained from the Kaggle portal. This experimental setup includes an Open-Source segmentation model API. Our findings indicate that domain similarity-based transfer learning can be used to data-scarce sectors. We achieved 98.47% accuracy and a IoU score of 0.9891 on Liver Tumor data and 0.6956 accuracy and a IoU score of 0.7043 on gland colon dataset.

The Digital Media Art and Design System under the Integration of Computer Big Data ChatGPT Technology

Traditional digital media art and design systems take a long time to run and cannot handle a large number of objects simultaneously. Therefore, the author proposes a digital media art and design method based on ChatGPT technology. ChatGPT technology is an important part of networking.Prepare to provide conference support for various applications such as customer service, personal assistant, robotic interview, and so on. ChatGPT can not only answer the question that is set, but also solve the question openly.The comprehensiveness and intelligence of ChatGPT have attracted widespread attention since its launch. The hardware system adopts dual core TMS320C6657 and DDR3Thel1333 series processors as the core circuit, together with high speed external storage, to expand the image transmission line of multi-data; System software uses module architecture to design image modules, video modules, and voice modules, all of which are integrated into the core of the system as modules. In this experiment, 10 images were transferred and the running time was tested. Experimental results showed that, the traditional digital media art and design system had three errors, which took more time to run.

Health Care Digital Strategy: Designing the New Norm

The time has arrived when oral and maxillofacial surgery (OMS) teams must redesign patient care by offering high-quality, easy, and cost-effective virtual care services through digital tools and telemedicine. Only a few pilot programs have been established to date, but now, the new norm requests large-scale routine services. The healthcare institutions should build this strategy based on their long-term goals. A prime example of its successful implementation is our unit at the National Institute of Children's Diseases (Bratislava, Slovak Republic), where a reliable telemedicine program was implemented for the outpatient follow-up visits of patients operated on for craniosynostosis. This program was instrumental in maintaining the long-lasting and high-impact character of craniosynostosis care during the coronavirus disease 2019 (COVID-19) crisis. The parents of the children were surveyed to evaluate the new program's effectiveness. The results were overwhelmingly positive, with an overall parental satisfaction rate of 72.3% and a 67.2% convenience rate for the services. The returned questionnaires revealed that 79.3% of parents were satisfied with physicians' communication, and 88.7% agreed that the virtual meetings adequately addressed their clinical needs. Moving forward, healthcare centers and physicians should organize their time and resources to experiment with the rapidly growing list of digital tools. The organizations should prioritize adapting their clinical information technology (IT) systems for optimal telemedicine practices. With the rapid technological advancements, new digital clinical systems should incorporate the capabilities of generative artificial intelligence (AI) in sophisticated virtual systems. This will require an even closer collaboration between clinicians, scholars, allied healthcare providers, healthcare leaders, and digital system designers. It is clear that in today´s complex healthcare ecosystem, the present and future of care delivery is digital. Will modern OMS teams adopt these strategies? It is something that all of us anticipate with huge interest.

인공지능 기반 중독 질환자 대상 디지털 치료제 시스템 설계

인공지능 기반 중독 질환자 대상 디지털 치료제 시스템 설계

Humanzentrierte Gestaltung von digitalen Assistenzsystemen für Menschen mit Behinderung: Erprobung und Evaluation des Workshopprogramms „friendlyAI@work“

ZusammenfassungDigitalen Assistenzsystemen wird das Potenzial zugeschrieben, Menschen mit Behinderungen eine selbstbestimmtere Teilhabe am Arbeitsleben zu ermöglichen. Eine solche potenzialerschließende Wirkung dieser Assistenztechnologien setzt in betrieblichen Anwendungskontexten fundiertes arbeitswissenschaftliches Gestaltungswissen für eine menschzentrierte Arbeitssystemgestaltung voraus. Das im Rahmen des Projektes „HUMAINE“ entwickelte Workshopkonzept „friendlyAI@work“ zielt darauf ab, betrieblichen Akteuren digitale Gestaltungskompetenz für eine humangerechte KI-Implementierung zu vermitteln. Es basiert auf Prinzipien des Aktionslernens, bei dem ein kollektiver, an Umsetzungsbeispielen ausgerichteter Kompetenzerwerb im Fokus steht. Im Beitrag berichten wir über erste Befunde zur Wirksamkeit des Workshopprogramms, die wir im Kontext der Einführung digitaler Assistenzsysteme in einer Werkstatt für Menschen mit Behinderung (WfbM) ermittelten. Die Evaluation des 18-monatigen Programms im Rahmen einer interventionsbasierten Fallstudie mit zwischen fünf und elf Teilnehmenden deutet auf positive Effekte sowohl im Hinblick auf einen Zuwachs individueller digitaler Gestaltungskompetenz wie auch der Fähigkeit zur humanzentrierten Arbeitssystemgestaltung hin. Darüber hinaus konnten im Rahmen des Programms Maßnahmen zur nachhaltigen Sicherung der erworbenen digitalen Gestaltungskompetenz umgesetzt werden (z. B. Einführung einer ganzheitlichen Gefährdungsbeurteilung bei der Planung technischer Systeme). Als wichtige Erfolgsfaktoren für den Lernerfolg erwies sich die cross-funktionale Zusammensetzung der Teilnehmenden, das an Praxisbeispielen ausgerichtete Lernkonzept und das agile Moderationsverfahren. Im Rahmen des auf Mixed-Method basierenden Evaluationsdesigns stellte sich darüber hinaus die Berücksichtigung individueller Lernvoraussetzungen in diversen Lerngruppen als kritischer Erfolgsfaktor heraus.Praktische Relevanz: Damit intelligente Technologien Menschen mit Behinderung bei der Arbeit sinnvoll unterstützen können, sind Kenntnisse über eine humanzentrierte Arbeitsgestaltung von hoher Bedeutung. Die digitalen Assistenten müssen so gestaltet sein, dass sie die persönlichen Ressourcen der Arbeitenden stärken und negative Beanspruchungsfolgen verhindert werden. Das Workshopprogramm „friendlyAI@work“ will Gestaltungsverantwortliche befähigen, digitale Assistenzsysteme in ihren Organisationen humanzentriert und nutzerfreundlich zu implementieren. Im Workshop werden Kenntnisse über die Funktionalitäten von Künstlicher Intelligenz und ihre Anwendung in Assistenzsystemen vermittelt. Darüber hinaus werden die Teilnehmenden an die Prinzipien humangerechter Technik- und Arbeitsgestaltung herangeführt und ihre Handlungskompetenz im Rahmen konkreter betrieblicher Umsetzungsbeispiele gefördert. Eine 18-monatige Erprobung des Workshopprogramms bei der Iserlohner Werkstätten gGmbH ergab eine gute Teilnehmendenakzeptanz und Erfolge bei der humangerechten Gestaltung ihrer Assistenz-Arbeitsplätze.

Multi-camera vision-based synchronous positioning and mapping for green construction of electric substations

Accurate CO2 tracking in electric substation construction is vital for climate efforts, using monocular SLAM for monitoring despite challenges like sunlight and complex terrain. Additionally, these methods typically yield only aggregate carbon emission data, thereby lacking the granularity necessary for precise monitoring throughout the construction process. These limitations compromise mapping accuracy and impede the integration of digital twins and IoT technologies. Addressing these issues, this paper proposed a methodology combining red, green, and blue (RGB) cameras and multi-camera collaboration with digital design systems, enhancing SLAM capabilities. The advanced technique integrated methods including overlap estimation, depth reasoning, noise reduction, and surface reconstruction to create accurate 3D models, enhancing scene reconstruction and real-time CO2 tracking during construction and operation. Leveraging continuous on-site camera monitoring as a substitute for manual inspections, it significantly contributes to the compilation of a comprehensive carbon emission database within a digital twin framework. Experimental results confirmed the proposed method’s superiority over previous works in real-time CO2 estimation, enhancing decision-making, resource management, and sustainable energy development. Overall, besides its application in substation construction for CO2 monitoring, this methodology can also be applied to carbon tracking in various other construction projects.

Tri-state GNRFET-based fast and energy-efficient ternary multiplier

As silicon field-effect transistors encounter increasing scaling challenges, digital system designers are shifting their attention towards multi-valued logic (MVL), specifically ternary logic. The graphene nanoribbon field-effect transistor (GNRFET) emerges as a compelling alternative among post-MOSFET technologies for the implementation of ternary logic. This paper delves into the computational intricacies of ternary logic, underscores the outstanding features of GNRFET technology, and introduces a novel GNRFET-based 1-trit ternary multiplier (TMUL) requiring only 26 transistors. The performance of the design is assessed using the Synopsis HSPICE simulator with a 32-nm GNRFET model file operating at VDD = 0.9 V. The proposed TMUL surpasses existing designs due to its efficient paths with a minimal number of transistors for each output transition, a singular power supply voltage, and an extended voltage division scheme. In comparison to other contemporary TMUL designs, the proposed design exhibits a notable enhancement, showcasing a 21.42 % reduction in delay, a 33.11 % decrease in power-delay-product (PDP), and a 58.17 % decrease in energy-delay-product (EDP). Additionally, the design is subjected to thorough testing under diverse conditions including process, voltage, temperature (PVT) fluctuations, and load variations, validating its reliability and robustness.

CMOS full adder cells based on modified full swing restored complementary pass transistor logic for energy efficient high speed arithmetic applications

In modern Digital System design, adders are widely used in many applications including Microprocessors, Digital Signal Processors, Arithmetic Logic Units and digital signal processing. Power efficiency is an important key factor for any integrated circuits. By considering the importance of Full Adder (FA) cells, their power consumption may play significant role in overall power consumption. So designing a low-power full adder is important to achieve the high-performance computing. Swing restored technique is commonly used method to reduce the signal swing at the internal nodes and it helps to reduce the power consumption and improves the circuit's speed. This paper presents a novel hybrid full adder cell design using the modified swing restored technique and complementary pass transistor logic. The Full Adder circuit was implemented using Cadence Virtuoso tool on gptk 180nm CMOS process technology. The proposed full adder was compared with earlier reported circuits based on Delay, Power and PDP. The comparison shows that proposed circuit consumes less power with high performance. Also various process corners and noise immunity were analyzed to find the sensitivity of the circuit. Further an 8-bit Ripple Carry Adder was designed using the proposed full adder to verify the functionality in higher order bits. Simulations were performed and analysed using the Cadence Spectre.

DESIGN AND APPLICATION OF LOW-COST FUSE CURRENT TESTER IN CARS

By measuring the voltage drop on the fuses in vehicles with a multimeter and using the fuse voltage drop cards, it is possible to determine the current drawn by the load based on the color, type, and current value listed on the fuse label. Arduino is a family of microcontroller development devices that are utilized in numerous digital system design applications. In this study, a fuse current analyzer is proposed for measuring the voltage drop across the fuses in a vehicle using an Arduino development board and obtaining the load current. The developed current analyzer can be utilized in automotive electricity and electronics courses, circuit studies, and for determining whether the fuse value on vehicles is sufficient and detecting load current leakage. The proposed system is tested on vehicle fuses, and an approximate 4% mean error rate is determined. This system can be used to perform tests in automotive electrical laboratories, or it can be implemented in the classroom to give students hands-on experience.

Enhancing High-Speed Data Transfer in Fpga-Based Systems: An Innovative Usb 3.0 Communication Interface Design

This study introduces an innovative design for a USB 3.0 communication interface, specifically tailored for Field-Programmable Gate Arrays (FPGAs). Given the escalating requirements for rapid data transmission in contemporary computer applications, USB 3.0 provides substantial enhancements over its antecedents. Nonetheless, extant USB communication interfaces inadequately cater to FPGA development, leading to diminished productivity for developers. To reconcile this discrepancy, this paper advocate for an Intellectual Property (IP) core interface that capitalizes on the concurrent data transmission proficiency of FPGAs, in conjunction with the superior speed transfer of USB 3.0. This design employs the CYUSB3014 chip, amalgamating the Physical Layer (PHY), Serial Interface Engine (SIE), and driver software into a singular entity. Herein, the FPGA serves as the nexus of control, streamlining data interchange and interface coordination among diverse modules within the system. The design put forth not only enables expeditious data communication in FPGA-centric systems, thereby surmounting the constraints of conventional USB interfaces, but also promotes accelerated data conveyance and augmented development efficiency. Consequently, this design harbors extensive applicability across spheres of digital system design and communications.