Sustainable Engineering and Innovation (SEI - E-Journal)
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142 research outputs found
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Development of a novel hybrid model (PDES–ANFIS) for time series applications
Full text linkMost time series with a clear overall trend in their data and graphs require a model that effectively addresses the overall trend. If the time series also includes various fluctuations and random variations, nonlinear models are the ideal approach. To improve the prediction error and make it very small, a new model was applied to the time series of annual cancer cases in Iraq for the period from 1976 to 2023. This series contains a general trend covering more than 85% of the data, in addition to various random fluctuations and variations. The proposed hybrid model consists of two parts: the first part addresses the strong overall trend in a linear manner by partitioning the series into an optimal number of parts according to the optimal division that gives the lowest value for RMSE and MAPE, and applying a double exponential smoothing method to all parts to address the upward trend. The second part detects nonlinear patterns in the residuals of the first model using an adaptive network-based fuzzy inference system (ANFIS). The proposed hybrid model, Partitioned Double Exponential Smoothing (PDES-ANFIS), has proven to be more efficient compared to the unpartitioned hybrid model and single models by using the root mean square error (RMSE)
Performance evaluation of systematic and nonsystematic polar encoding using FPGA under a practical multipath channel
Full text linkPolar code is currently implemented in high-speed high performance modern communication systems. The polar code enabled these systems to transmit near Shannon’s limit with minimum bit error rate (BER). However, the performance of polar encoding is enhanced using a systematic encoding technique that convolves the data, providing higher noise immunity. This paper provides the hardware implementation of systematic and nonsystematic encoding using an FPGA to provide fully parallel operation for maximum processing speed. Both techniques' performance is evaluated under the additive white Gaussian noise (AWGN) channel and a practical indoor multipath channel. Both techniques showed a significant BER improvement compared to BPSK. The tests showed that the systematic performance is superior to the nonsystematic technique
Wavelet decomposition and statistical characterization for unbalance detection in rotating systems
Full text linkVibration analysis is a crucial tool for the early detection of faults in rotating machines, as it allows for the prevention of major damage and avoids significant costs associated with these faults. This study examines the phenomenon of imbalance in rotating machines, using signals generated on a test bench at the Santander Technological Units, where specific fault conditions were replicated. The signals obtained were analyzed using wavelet decomposition, from which key characteristics were extracted, such as root mean square (RMS), peak value, kurtosis, and mean absolute value (MAV). These characteristics were then compared using box plots to evaluate the separation between signals from unbalanced machines and those in a fault-free state. This analysis allowed us to identify significant differences between the two conditions, demonstrating the effectiveness of the approach in detecting faults due to imbalance
Engineering a low-cost, expendable fixed-wing drone for search and rescue missions using readily available components
Full text linkThis paper describes the design and aerodynamic performance evaluation of a low-cost, expendable fixed-wing UAV for humanitarian purposes built with off-the-shelf components. The drone is designed for quick deployment in disaster relief, search and rescue, and medical delivery operations. The aerodynamic performance, stability, and flight performance were evaluated using DATCOM, XFLR5, and Computational Fluid Dynamics (CFD) analyses. Results indicate that the wing and fuselage of the UAV are well designed, which significantly enhanced the lift-to-drag ratio, endurance, and efficiency. The employment of commercially available parts allows for cost-effective, scalable, and replicable platforms. The payload can be adapted and, since the drone is modular, it is also versatile. Future work will focus on enhancing structural integrity while maintaining cost efficiency, incorporating vision-based survivor detection for search and rescue operations, and conducting field tests to validate performance under diverse conditions. This study is part of the design effort towards accessible and cost-efficient UAV solutions for humanitarian operations, bridging the gap between affordability and performance
Risks of cyberattacks on accounting: Analysis of modern threats and preventive measures
Full text linkThe increasing digitalization of accounting systems has amplified vulnerabilities to cyberattacks, yet practical strategies to address sector-specific risks remain underexplored. This study explored prevalent cyber threats in the accounting industry, such as phishing directed at enterprise resource planning systems, unauthorized access utilizing mobile devices, and invoice fraud. The investigation was conducted in a manner that combined interviews with accounting and cybersecurity professionals and comparative case reviews of organizational practices. A statistical analysis showed that multi-factor authentication reduced cyber-attack likelihood by 58% while regular employee training reduced the risk by 37%. Organizations with combined Information Technologies (IT) and accounting teams took 40 percent less time resolving security incidents than organizations with separate departments. The results showed that mid-sized firms generally had poor preparedness, while bigger firms showed adherence to international security standards. They also highlighted the need for mandatory cybersecurity training, collaboration across departments, and strategic investments in adaptive security frameworks. Regulatory incentives for small and medium enterprises to adopt cost-effective mitigating safeguards are also a policy implication. The results help bridge theoretical cybersecurity models and real accounting practice by providing actionable advice on making operations more sustainable while mitigating the increasing threat of cyber incidents
A programmable multi-bit fault injection for embedded system
Full text linkFault injection technique is commonly used to intentionally introducing attack on embedded systems, specifically advanced FPGAs and microcontrollers. The FPGA-based embedded system uses SRAM for storage of configuration data. Due to technology scaling and growing complexity in FPGA bit files, multiple-bit upset is a primary threat to FPGAs. These devices are also vulnerable to radiation threats in space environments. To address these issues, this paper proposes burst error modeling and a Fault Injection Server (FIS). FPGA is utilized in the proposed fault injection architecture to efficiently inject Multiple-Bit Upset (MBUs) onto the design's interconnect without altering the value of flip-flops associated with the design path. There is no need to reload the same flops and memory with correct values since their values are unchanged. The Xilinx Zynq-7000 FPGA has been used to evaluate the proposed FIS architecture, and It is able to perform two times faster than existing techniques. The FPGA resource utilization overhead also less as compared to other exiting design but it depends on number of fault injection points used
Reconfigurable metasurface based on graphene optical antennas for dynamic beam steering
Full text linkMetasurface represents a transformative advancement in photonics due to its exotic abilities to control electromagnetic wave properties. The integration of graphene and metasurface propels metasurface to new heights of compact footprint, reconfigurability, and multi-functionality. In this article, a reconfigurable metasurface based on graphene optical antennas is designed as a reflective surface that controls the beam steering by tuning graphene’s Fermi energy based on the concept of a phase-shifting surface. The results demonstrated that the designed metasurface can dynamically steer the reflected beam at different reflection angles, in addition to their capability to reflect a single beam and three beams. The metasurface exhibits high gain and directivity at different reflection angles. These steering capabilities provide a potentially efficient method for developing and simplifying dynamic reconfigurable beam-steering systems
Integration of cloud computing and artificial intelligence to optimize economic management processes: a systematic review
Full text linkThis systematic review examines existing literature on the role of AI-driven cloud computing in optimizing economic management processes, identifying key trends, benefits, challenges, and future research directions. The study adheres to the PRISMA framework to systematically collect and analyze research from academic databases, including Scopus, Web of Science, IEEE Xplore, and Google Scholar. Findings reveal that AI-powered cloud solutions offer scalability, real-time data analytics, cost reduction, and automation of business processes. However, challenges such as data security risks, ethical concerns, and regulatory constraints hinder full-scale adoption. The study also highlights emerging trends, including AI-driven financial forecasting, intelligent automation, and Explainable AI (XAI) models, which facilitate transparent decision-making. Additionally, the research identifies gaps in the literature, particularly in the adoption of AI within public sector economic management and regulatory frameworks. The discussion compares these findings with existing studies, exploring theoretical and practical implications for businesses, policymakers, and researchers. Key recommendations include the need for robust cyber-security frameworks, ethical AI governance, and industry-specific AI applications. Future research should focus on longitudinal studies, cross-sectoral analyses, and the role of AI in sustainable economic growth. This review contributes to the growing body of knowledge on AI-cloud integration, offering insights to drive effective and responsible adoption in economic management
Using IoT applications for detection of the overvoltage and undervoltage in electrical systems
Full text linkA significant advancement in managing systems is the development and implementation of an IoT-based voltage monitoring system. The study aims to treat the issue of voltage fluctuations, including overvoltages and undervoltages, which pose risks to electrical devices and infrastructure. Utilizing the ZMPT101B voltage sensor on the Blynk platform and the ESP 32 microcontroller unit, this system offers a solution for real-time monitoring and alerting of voltage situations. The system's structure allows for data collection, processing, and transmission, enabling users to receive notifications on their mobile phones through a user-friendly interface. Extensive testing at voltage levels has confirmed the accuracy and reliability of the system in detecting voltage differences. The results showed a high level of reactivity and efficacy in warning users about possible hazards, which improved electricity efficiency and safety. Further developments in proactive electrical system management are anticipated as future work concentrates on enhancing the system's scalability, predictive capabilities, and integration with smart grid technology. This study demonstrates how IoT technologies have the power to completely transform electrical system monitoring and maintenance, with major advantages for sustainability, safety, and dependability
A new compact CPW-UWB antenna for advanced healthcare monitoring applications
Full text linkThis paper presents the design and simulation for a microstrip antenna, specifically designed to operate within the ultra-wideband (UWB) frequency range of 3.4226 GHz to 13.4 GHz. The antenna employs a coplanar waveguide (CPW) feeding technique and features a slotted patch mounted on an FR4 substrate. The findings of this study indicate that the antenna effectively spans the entire UWB frequency spectrum, achieving an operational bandwidth of 9.9774 GHz while upholding an input reflection coefficient of less than -10 dB. Notably, this design exhibits bidirectional radiation patterns, distinguishing it from traditional planar or microstrip patch antennas. Its lightweight construction, advantageous emission characteristics, and broad frequency range render this compact antenna highly suitable for various medical applications, including Wireless Body Area Networks (WBANs) and healthcare stations. Accordingly, it presents a promising technological solution for enhancing wireless communication and sensing capabilities in future healthcare initiatives