System Design Research Articles

Improving outcomes of type 2 diabetes mellitus patients in primary care with Chronic Care Model: A narrative review

AbstractDesigned and implemented over two decades ago, the Chronic Care Model is a well‐established chronic disease management framework that has steered several healthcare systems in successfully improving the clinical outcomes of patients with type 2 diabetes mellitus. Research evidence cements the role of the Chronic Care Model (with its six key elements of organization of healthcare delivery system, self‐management support, decision support, delivery system design, clinical information systems, and community resources and policies) as an integrated framework to revamp the type 2 diabetes mellitus‐related clinical practice and care that betters the patient care and clinical outcomes. The current review is an evidence‐lit summary of importance of use of Chronic Care Model in primary care and their impact on clinical outcomes for patients afflicted with one of the most debilitating metabolic diseases, type 2 diabetes mellitus.

Potential Gradient-Driven Dual-Functional Electrochromic and Electrochemical Device Based on a Shared Electrode Design.

The integration of electrochromic devices and energy storage systems in wearable electronics is highly desirable yet challenging, because self-powered electrochromic devices often require an open system design for continuous replenishment of the strong oxidants to enable the coloring/bleaching processes. A self-powered electrochromic device has been developed with a close configuration by integrating a Zn/MnO2 ionic battery into the Prussian blue (PB)-based electrochromic system. Zn and MnO2 electrodes, as dual shared electrodes, the former one can reduce the PB electrode to the Prussian white (PW) electrode and serves as the anode in the battery; the latter electrode can oxidize the PW electrode to its initial state and acts as the cathode in the battery. The bleaching/coloring processes are driven by the gradient potential between Zn/PB and PW/MnO2 electrodes. The as-prepared Zn||PB||MnO2 system demonstrates superior electrochromic performance, including excellent optical contrast (80.6%), fast self-bleaching/coloring speed (2.0/3.2 s for bleaching/coloring), and long-term self-powered electrochromic cycles. An air-working Zn||PB||MnO2 device is also developed with a 70.3% optical contrast, fast switching speed (2.2/4.8 s for bleaching/coloring), and over 80 self-bleaching/coloring cycles. Furthermore, the closed nature enables the fabrication of various flexible electrochromic devices, exhibiting great potentials for the next-generation wearable electrochromic devices.

Digital Twin-Enabled Response Function Analysis: A Synthetic Approach to Ship's Propulsion System Assessment

Analyzing the behavior of vessels in actual sea conditions is crucial for conceptual system design, safety and energy efficiency considerations. However, the essential seakeeping problem is reduced to the analysis of wave-hull interactions often neglecting consideration of the propulsion. But in the meantime, the synthetic consideration of wave–propulsion interactions is a key for safety and energy efficiency. Furthermore, safety evaluation of a ship's design with reduced propulsion power in adverse seas is vital for risk management. Response functions are commonly used to estimate propulsion system responses in incoming seaways. This paper proposes a synthetic approach using digital twin technology for rapid response function estimation. It introduces a companion linearized state-space model linked with the digital twin, enabling immediate retrieval of coefficients for response function analysis at the desired operating point. This integrated methodology provides a comprehensive representation of ship propulsion behavior in wave environments, offering a comprehensive framework for system performance assessment.

Designing Inclusive AI Certifications

For decades, the route to familiarity in AI was through technical studies such as computer science. Yet AI has infiltrated many areas of our society. Many fields are rightfully now demanding at least a passing familiarity with machine learning: understanding the standard architectures, knowledge on how to use them, and addressing common concerns. A few such fields look at the standard ethical issues such as fairness, accountability, and transparency. Very few fields situate AI technologies in sociotechnical system analysis, nor give a rigorous foundation in ethical analysis applied to the design, development, and use of the technologies. We have proposed an undergraduate certificate in AI that gives equal weight to social and ethical issues and to technical matters of AI system design and use, aimed at students outside of the traditional AI-related disciplines. By including social and ethical issues in our AI certificate requirements, we expect to attract a broader population of students. By creating an accessible AI certification, we create an opportunity for individuals from diverse experiences to contribute to the discussion of what AI is, what its impact is, and where it should go in the future.

Discrepancies of Functional Requirements of Façade Opening System between Real-Life Public and Built Environment Experts Focusing on Thermal Comfort and Ventilation

A survey was conducted to analyze the discrepancies of the functional requirements of the façade system in residential units among 605 of the real-life public and 73 experts. Personal and housing information, resident life patterns, public façade usage behavior, and functional requirements were collected from the respondents. Both the public and experts recognized insulation as the main function of façade opening systems. More than 85% of the public and experts opened windows for ventilation, but ventilation was ranked 3rd amongst the public and 4th amongst experts in the main functions list of façade systems. The public cited the inflow of fine dust as the main reason for dissatisfaction with opening windows. In contrast, the experts cited a decrease in thermal comfort due to the inflow of external moisture as the reason for dissatisfaction with opening windows. The results showed that discrepancies exist between the public and experts’ perceptions of the main function of housing façade systems. Analyzing the common points and differences between the public and experts’ perception can help in developing façade system design and control technology.

Air-conditioning load characteristics and grey box predicting model in subway stations

With the continuous expansion of metro, energy conservation of air-conditioning system in subway stations draws the attention of the whole world. Most of the researches are focused on improving the energy efficiency of the system, while the load characteristics of subway stations are paid little attention. The inaccurate load prediction in the designing of air-conditioning system results in redundancy and low operating efficiency. Therefore, accurately predicting the air-conditioning load is crucial for energy saving in subway stations. In this paper, an innovative three-stage subway air-conditioning load test method was proposed and implemented in nine subway stations in Qingdao. Based on the test data, the special air-conditioning load characteristics of subway stations as underground buildings were analyzed. The results showed that electrical equipment load accounted for the largest part, reaching 53.7 %, while only 42 % of the equipment power was converted into air-conditioning load. The positive role of the envelope should not be ignored, especially in the case of entrance and exit walls, which bore almost all of the fresh air load. Based on the three-stage test, a grey box model was established and the error was validated to be within 6 %. With this model, the load of air-conditioning system can be calculated by inputting passenger flow, power of electrical equipment and public area. This paper provides a reference for the design and operation of air-conditioning system in subway stations.

Camera-Based Crime Behavior Detection and Classification

Increasing numbers of public and private locations now have surveillance cameras installed to make those areas more secure. Even though many organizations still hire someone to monitor the cameras, the person hired is more likely to miss some unexpected events in the video feeds because of human error. Several researchers have worked on surveillance data and have presented a number of approaches for automatically detecting aberrant events. To keep track of all the video data that accumulate, a supervisor is often required. To analyze the video data automatically, we recommend using neural networks to identify the crimes happening in the real world. Through our approach, it will be easier for police agencies to discover and assess criminal activity more quickly using our method, which will reduce the burden on their staff. In this paper, we aim to provide anomaly detection using surveillance videos as input specifically for the crimes of arson, burglary, stealing, and vandalism. It will provide an efficient and adaptable crime-detection system if integrated across the smart city infrastructure. In our project, we trained multiple accurate deep learning models for object detection and crime classification for arson, burglary and vandalism. For arson, the videos were trained using YOLOv5. Similarly for burglary and vandalism, we trained using YOLOv7 and YOLOv6, respectively. When the models were compared, YOLOv7 performed better with the highest mAP of 87. In this, we could not compare the model’s performance based on crime type because all the datasets for each crime type varied. So, for arson YOLOv5 performed well with 80% mAP and for vandalism, YOLOv6 performed well with 86% mAP. This paper designed an automatic identification of crime types based on camera or surveillance video in the absence of a monitoring person, and alerts registered users about crimes such as arson, burglary, and vandalism through an SMS service. To detect the object of the crime in the video, we trained five different machine learning models: Improved YOLOv5 for arson, Faster RCNN and YOLOv7 for burglary, and SSD MobileNet and YOLOv6 for vandalism. Other than improved models,we innovated by building ensemble models of all three crime types. The main aim of the project is to provide security to the society without human involvement and make affordable surveillance cameras to detect and classify crimes. In addition, we implemented the Web system design using the built package in Python, which is Gradio. This helps the registered user of the Twilio communication tool to receive alert messages when any suspicious activity happens around their communities.

Design and performance evaluation of Front glass-covered photovoltaics-thermal hybrid system for enhanced electrical output and hot water production

Proof of concept is established for the thermal management of PV modules for the simultaneous benefit of electrical and thermal efficiency. It was achieved by designing the controlled open-loop water-based hybrid PV-T system and demonstrated for thermal management of 150W photovoltaic panel at natural solar conditions. In this integrated front glass-covered PV-T hybrid (IFG-PV-T) system, the PV panel is clipped between the front glass and rear aluminium collector without causing any permanent changes in the existing panel. The flow of water from the source tank is controlled by automated solenoid valve assembly coupled with thermocouples. The solenoid operational temperature is fixed at 40°C to controlled the PV surface temperature at an optimum range to mitigate the adverse effect on voltage and current output. The water layer thickness in the front glass box is optimized to filter the maximum infrared radiations and the collector's toughened glass feature allows the maximum light transmittance with super safety. The performance of the IFG-PV-T system has been evaluated in terms of variation in open circuit voltage, short circuit current, maximum power output, electric and thermal efficiency under the natural solar insolation for a week. Experimental investigations revealed that the open-circuit voltage is increased by ∼16.1 % with IFG-PV-T as compared to conventional PV panel. The increment can be attributed to the synergy of the front glass collector and solenoid valve operation at 40oC that regulates PV surface temperature and boost the current output. These factors have ameliorated the electrical efficiency of IFG-PV-T compared to conventional PV panel. The average thermal efficiency was 39.4 ​% wherein the IFG-PV-T system provides ∼100 ​L of hot water (38–41 ​°C) per day. The present controlled loop operation system and collector configuration have proven their significance for electrical power increment and concomitantly able to deliver moderate hot water which can be useful for any household or commercial application.

The Best Design for a Direct Evaporative Cooling System Based on Pressure Drop at Desired Saturation Efficiency: A Cost–Benefit Optimization

The Best Design for a Direct Evaporative Cooling System Based on Pressure Drop at Desired Saturation Efficiency: A Cost–Benefit Optimization

Research on electronic optical monitoring technology and system design for vacuum electron beam welding process

Electron beam welding technology is increasingly used in industrial manufacturing due to its high power density and the purity of welded joints. In vacuum environments, traditional optical and machine vision monitoring methods are susceptible to contamination by metal vapors, which hinders the monitoring effect. Due to the limitations of optical monitoring methods, electronic optical imaging technology is a new alternative monitoring method that has been introduced into the electron beam processing in recent years, but the complexity of the industrial electron beam welding environment makes it relatively less studied in the field of electron beam welding. In this study, a YAG scintillator detector is proposed to collect the backscattered electron information generated by the interaction of electrons with the sample, and an FPGA real-time processing system is used to realize the weld quality monitoring in the industrial electron beam welding processes. The distribution law of backscattered electrons in space is simulated by Monte Carlo method, and the results show that the number of distribution in the 40°∼60° angle region is more, the backscattering coefficient increases with the increase of the incident angle of the electron beam, and the backscattering coefficient of the samples with large atomic numbers is relatively high. The field monitoring experiments show that the designed system exhibits good sensitivity to the characteristic morphology, and the imaging resolution reaches more than 200 μm, and the weld hole defects are clearly visible. A good linear correlation between the current change curve during scanning and the actual shape profile is shown, while the image resolution is better when the spot current is 1 mA.

Adaptive output feedback control system design for nonlinear systems via neural networks

AbstractAdaptive output feedback control based on output feedback exponential passivity (OFEP) has a simple structure and strong robustness in regard to disturbances and system uncertainties. However, it is difficult for most nonlinear systems to satisfy the conditions of OFEP. Thus, the introduction of a suitable parallel feedforward compensator (PFC) to construct an OFEP‐augmented system with the controlled system has been used, but the control output cannot achieve perfect tracking because of the output of the introduced PFC. As a solution, introducing a feedforward (FF) input to build a 2 degree of freedom (2‐DOF) is a simple and effective way to solve this problem. In this paper, we propose the design schemes for suitable PFC and FF input of nonlinear systems via the use of neural networks (NN), respectively. Besides, to cope with possibly present input disturbances, we also provide a method to achieve disturbance compensation based on NN to reduce their interference. Finally, the effectiveness of all proposed design schemes is confirmed through numerical simulations.

A Zero-Voltage-Writing Artificial Nervous System Based on Biosensor Integrated on Ferroelectric Tunnel Junction.

The artificial nervous system proves the great potential for the emulation of complex neural signal transduction. However, a more bionic system design for bio-signal transduction still lags behind that of physical signals, and relies on additional external sources. Here, we present a zero-voltage-writing artificial nervous system (ZANS) that integrates a bio-source-sensing device (BSSD) for ion-based sensing and power generation with a hafnium-zirconium oxide-ferroelectric tunnel junction (HZO-FTJ) for the continuously adjustable resistance state. The BSSD can use ion bio-source as both perception and energy source, and then output voltage signals varied with the change of ion concentrations to the HZO-FTJ, which completes the zero-voltage-writing neuromorphic bio-signal modulation. In view of in-/ex-vivo biocompatibility, we show the precise muscle control of a rabbit leg by integrating the ZANS with a flexible nerve stimulation electrode. The independence on external source enhances the application potential of ZANS in robotics and prosthetics. This article is protected by copyright. All rights reserved.

Analysis and Design of Customer Service Information Systems at Bersaudara Car Repair Shop Of Pangkalpinang

Bersaudara Car Repair Shop of Pangkalpinang is a business that operates in the field of automotive services, specializing in car maintenance and repair. Currently, customer service data processing still uses a manual system with Microsoft Office tools. In its application, this application cannot support fast and easy work. This can have implications for service providers towards customers, because they often encounter obstacles in the process of handling repairs and making reports. The aim of this research is to provide a solution in forming a needs analysis and documented information system design which will be developed into an information system application at the brothers' car repair shop. Based on the SDLC (Software Development Life Cycle) concept, the initial thing needed to produce an information system is to create a needs analysis and documented system design. The system analysis and design carried out here goes through the stages of data collection, carrying out analysis using the PIECES (Performance, Information, Economic, Control, Efficiency, Service) framework and carrying out system design using an object-oriented approach using UML (Unified Modeling Language) notation. The results of the analysis and design were tested in the form of a design evaluation using the consistency analysis method which was proven to have a consistent percentage value of 100%. The results of this design are included in the correctness category which proves that the system requirements and system design are consistent and correct.

Comprehensive Analysis of DC Link Capacitors Used in Cascaded H-Bridge Motor Driver

An essential part of inverter design is selecting direct current-Link Capacitors (DCLC) for Medium-Voltage Cascaded H-bridge motor Drivers (MV-CHBMD). This article analyzes capacitor configuration for MV-CHBMD to improve the quality of driver output and input current depending on an analysis of DCLC current effects. The techniques were employed with two-level converters to find the harmonics, and the root mean square (RMS) value of the capacitor current has been expanded to seven-level MV-CHBMD. Additionally, a novel mathematical technique has been recommended for determining the RMS current and voltage ripple of the DCLC. The proposed MATLAB simulation technique provides a comprehensive analysis of the outcome results. This allows for easy customization to other modulation methods and application to higher-level MV-CHBMD. Specifically, it calculates the worst-case scenario for the DC-link voltage in a 1000-horsepower and 3.3-kV system. The study also presents empirical evidence that specific system components endure excessive stress. This information is valuable for accurately specifying system components and ensuring optimal system design in the MV-CHBMD system. This article examines the potential impact of standard mode voltage on the bearings of medium-voltage motors. In addition, an optimal approach for selecting DCLCs in a multilevel cascaded H-bridge (CHB) motor driver strategy is proposed, effectively eliminating voltage stress on switching devices. The effectiveness of these systems is demonstrated by presenting simulation results. A comprehensive study analyzed the performance of various inverter levels, including total harmonic distortion (THD) and efficiency. The DC link was constructed using the MATLAB platform to conduct a thorough analysis. The proposed approach exhibits superior performance and lower costs compared to traditional methods. The experimental work and test confirm the simulation results. The test result showed that selecting DCLCs in a CHB provides a higher-quality output waveform into CHB, which supports the controlling structure and reduces the probability of malfunctions.

Design and implementation of RF power levels measurement system from indoor to outdoor in Isparta province

This paper presents a novel, low-cost, and portable RF power measurement system, operating in GSM 900 and GSM 1800 frequency bands. This measurement model consists of four basic circuits; microstrip folded dipole antenna (MFDA) that received the ambient RF signals, a power meter that generates DC output voltage according to received RF signal power level, a microprocessor that converts the data's analog to digital, and a computer to record and screen the time-varying data. Seventeen measurements, each for six hours, were performed in nine locations in Isparta for the indoor-to-outdoor scenario. The range between the minimum and maximum power values of the average RF power levels obtained in time-dependent measurements was calculated as approximately 15 dB, 18 dB, and 33 dB for indoor, semi-indoor, and outdoor ambients, respectively. The indoor/semi-indoor/outdoor ambient RF power levels were respectively varied between −55.1 dBm to −4.13 dBm, −43.92 dBm to −6.12 dBm, −44.89 dBm to 0.1 dBm in all measurements.

Design of Reversible Serial Adder Based on EPOE Expressions for Computational Applications

Considering the growing trend toward reducing the size of electronic devices, reducing power consumption has become one of the major concerns of circuit designers. One of the solutions to reduce power consumption is the design of reversible circuits. This paper proposed the design of a low-cost self-control serial adder system. In the proposed circuit, EPOE expressions have been used for the direct and compact design of sequential circuits to reduce the fixed inputs of sequential logic circuits. In addition, to reduce the quantum cost, common terms between the outputs are optimally used. Also, limiting the use of Tofoli gates with a size larger than three inputs in the implementation of the final circuit will reduce the quantum cost of the resulting circuit. The results and comparisons showed that the proposed design has improved efficiency measures including quantum cost, garbage outputs, and fixed inputs compared to existing works.

Development of Smart Fire Safety System for Vehicles Using IOT

Today, fire accidents often occur in homes and industrial environments, where climate change and human negligence can be predicted. The proposed prototype is designed to detect such fire accidents and remotely extinguish the fire from the user, thus reducing the risk to firefighters. The main idea of ​​this concept is to propose a model that focuses on the cost-effective design and implementation of an automatic fire protection system for electric vehicles. In this system, the fire extinguisher is activated when it detects flame/smoke in the vehicle fire area and extinguishes the fire automatically. There are many reasons for an electric vehicle that can cause fire accidents. The main cause of electric car fires is the battery used in them. There have been many cases of cars catching fire for the reasons mentioned above and ending with the entire vehicle reduced to ashes. The installation of an automatic extinguishing system allows to minimize the financial losses that can arise from a fire and to increase the safety level of the vehicle, passengers and other road users. Keywords : Fire Situation, Controller, Emergency Alert, Accident Prevention, IOT Technology etc.

Robotic Assistance and Haptic Feedback in Arthroscopic Procedures: Design and Preliminary Evaluation of a Two-Arm System

Robotic Assistance and Haptic Feedback in Arthroscopic Procedures: Design and Preliminary Evaluation of a Two-Arm System

Experimental Investigation of Effect of Orifice Diameter on Volumetric Efficiency of Two-Stage Reciprocating Air Compressor

The volumetric efficiency is an important parameter commonly adopted to quantify the performance of air compressors. The present work is concerned with the design of an optimum air intake system for a single acting two stage reciprocating air compressor. The intake air system comprised of different diameter of orifice which affect the quantity, pressure of air to the compressor. The study approaches the effect of change in the intake orifice opening, affects the volumetric efficiency of air compressor. In this we used the standard procedure to find the efficiency, and it shows us the as orifice diameter increases the volumetric efficiency changes with increasing order to some extent

Design and Characterisation of a Read-Out System for Wireless Monitoring of a Novel Implantable Sensor for Abdominal Aortic Aneurysm Monitoring.

Abdominal aortic aneurysm (AAA) is a dilation of the aorta artery larger than its normal diameter (>3 cm). Endovascular aneurysm repair (EVAR) is a minimally invasive treatment option that involves the placement of a graft in the aneurysmal portion of the aorta artery. This treatment requires multiple follow-ups with medical imaging, which is expensive, time-consuming, and resource-demanding for healthcare systems. An alternative solution is the use of wireless implantable sensors (WIMSs) to monitor the growth of the aneurysm. A WIMS capable of monitoring aneurysm size longitudinally could serve as an alternative monitoring approach for post-EVAR patients. This study has developed and characterised a three-coil inductive read-out system to detect variations in the resonance frequency of the novel Z-shaped WIMS implanted within the AAA sac. Specifically, the spacing between the transmitter and the repeater inductors was optimised to maximise the detection of the sensor by the transmitter inductor. Moreover, an experimental evaluation was also performed for different orientations of the transmitter coil with reference to the WIMS. Finally, the FDA-approved material nitinol was used to develop the WIMS, the transmitter, and repeater inductors as a proof of concept for further studies. The findings of the characterisation from the air medium suggest that the read-out system can detect the WIMS up to 5 cm, regardless of the orientation of the Z-shape WIMS, with the detection range increasing as the orientation approaches 0°. This study provides sufficient evidence that the proposed WIMS and the read-out system can be used for AAA expansion over time.