Central Unit Research Articles

Design and Development of an IoT-Based Leakage Detection System for Kitchens

In Nigeria, the frequent loss of lives and properties due to LPG usage for cooking necessitates urgent intervention. This paper presents an Internet of Things (IoT) based detection system to monitor LPG leakage in kitchens. Key components include a solenoid valve for gas flow control, an MQ6 sensor for LPG monitoring, and an STM32F411CEU6 microcontroller, programmed in embedded C, as the central processing unit of the system. The system introduces an emergency shutdown mechanism using an MMBT3904 NPN transistor. Upon detecting a leak, the MQ6 sensor informs the microcontroller, which prompts the user with a Short Message Service (SMS) and calls, and then triggers the transistor to close the solenoid valve if the leakage poses an explosion risk, thus preventing potential disasters. Additionally, a custom mobile app allows for remote monitoring and control of LPG leakage. To address Nigeria's unreliable electricity supply, the system includes a 5V power pack, a solar panel, and a battery for continuous power supply to the system. Deploying this system will significantly reduce the risks associated with LPG leaks in kitchens across Nigeria.

75% Reduction in Packing Variation of in-House Central Sterile Supply Unit Products in a Restructured Hospital in Singapore

75% Reduction in Packing Variation of in-House Central Sterile Supply Unit Products in a Restructured Hospital in Singapore

Distributed Joint Beamforming for RIS-assisted Cell-Free MIMO with Discrete Phase Shifts

Abstract Both reconfiurable intelligent surface (RIS) and cell-free multiple-input multiple-output (CF-MIMO) system are holding promise to become the predominant research direction in 6G networks. This paper studies the problem of weighted sum-rate maximization(WSR) in RIS-assisted CF-MIMO networks with discrete phase shifts. We utilize alternating optimization (AO) to iteratively calculate active and passive beamforming. At access points (APs) side, we employ a distributed algorithm to design the active beamforming, leveraging information interact among APs without centralized designing at central processing unit(CPU). Facing the constraint of discrete phase shift in RIS, we adopt semidefinite relaxation(SDR) projection and proximal gradient descent(PGD) to design the passive beamforming respectively. Simulation results indicate that our proposed algorithms achieve performance comparable to the distributed framework with continuous phase shift while reducing the computational time.

Design and Development of an Intelligent Laboratory Management System Based on STM Processors

Abstract In response to the escalating inventory of laboratory equipment, the inadequacy of traditional manual management practices has become increasingly apparent. Current management challenges are underscored by historical data, which reveals a borrowing rate of approximately 30%, a concerning return rate of only about 5%, and an equipment loss rate of 10%. To address these inefficiencies, this paper introduces an advanced, intelligent laboratory equipment management system leveraging STM32 and GM65 technologies, designed to significantly enhance the return rate and minimize equipment loss. The system is meticulously engineered, featuring three integral modules: the scanning module, the core board module, and the communication module. The scanning module employs GM65 technology to rapidly scan and decode QR codes, facilitating the swift transmission of critical data to the core board for intelligent processing and interaction with the laboratory equipment. At the heart of the system, the core board module serves as the central processing unit, adeptly managing data from the scanning module. It intelligently discerns various information types and dynamically updates the TFT-LCD screen with the current status of equipment, ensuring that all users have access to real-time and accurate information regarding the borrowing and returning of equipment. The communication module is pivotal in bolstering the system's connectivity capabilities. Designed with a robust structure, the system is characterized by its simplicity of operation and robust practicality. It not only significantly improves the efficiency of laboratory equipment management but also plays a transformative role in modernizing laboratory management practices. By streamlining the management process and ensuring the optimal utilization of resources, this system provides a solid foundation for the sustainable advancement of laboratory operations.

Cloud-fog architecture-based control of smart island microgrid in master-slave organization using disturbance observer-based hybrid backstepping sliding mode controller

Distributed control is an effective method to coordinate the microgrid with various components, and also in a smart microgrid, communication graph layouts are essential since changing the topology unexpectedly could disrupt the operation of the distributed controllers, and also an imbalance may occur between the production and load. Hence, reducing the exchanged data between units and system operator is essential in order to reduce the transmitted data volume and computational burden. For this purpose, an islanded microgrid with multiple agents which is using cloud-fog computing is proposed here, in order to reduce the computing burden on the central control unit as well as reducing data exchange among units. To balance the production power and loads in a smart island with a stable voltage/frequency, a hybrid backstepping sliding mode controller (BSMC) with disturbance observer (DO) is suggested to control voltage/frequency and current in the MG-based master-slave organization. Therefore, this paper proposes a DO-driven BSMC for controlling voltage/frequency, and power of energy sources within a Master-Slave organization; in addition, the study proposes a clod-fog computing for enhancing performance, reducing transferred data volume, and processing information on time. In the extensive simulations, the suggested controller shows a reduction in steady-state error, a fast response, and a lower total harmonic distortion (THD) for nonlinear and linear loads less than 0.33 %. The fog layer serves as a local processing level, so it reduces the exchanged data between cloud and fog nodes.

Home Automation System using OpenCV and Arduino

The research focuses on the integration of computer vision capabilities through OpenCV with Arduino-based hardware to create an efficient and versatile home automation system. The system employs cameras for image processing, allowing it to recognize and respond to various environmental changes within the home. The hardware setup utilizes Arduino microcontrollers as the central processing units, enabling seamless communication between the OpenCV algorithms and the connected devices. A user-friendly interface facilitates remote monitoring and control of home appliances through a mobile or web application. By combining the power of OpenCV for image processing and Arduino for real-time control, this home automation system provides a smart and adaptive solution for enhancing security, energy efficiency, and overall convenience within a household. The research’s modular design allows for future expansions and integration with emerging technologies, ensuring scalability and relevance in the rapidly evolving field of smart home automation.

Analysis of Policy Implementation and Availability of Infrastructure on the Implementation of Early Breastfeeding Initiation After Cesarean Section Delivery in Private Hospitals in Kudus District

Early initiation of breastfeeding (IMD) is placing the infant on the mother's chest or abdomen and allowing the infant to seek the mother's nipple within the first hour of birth. Caesarean section (SC) poses challenges to the implementation of Early Breastfeeding Initiation (IMD) in both internationally and nationally recommended hospital programs for maternal and infant care. The purpose of this study was to analyze policy implementation and analyze the availability of hospital facilities in the implementation of Early Breastfeeding Initiation (IMD) after Sectio Caesarean delivery. The research design was descriptive qualitative. The main informants of the study were SPOg doctors, implementing midwives and the Head of the Central Surgical Unit. Supporting informants are laboring mothers, central surgery unit nurses, pediatricians, hospital management. Data collection using in-depth interviews and observation. Data validity strategy using source triangulation. There is a policy contained in the decree of the hospital director and the hospital SOP as a work instruction for the implementing unit, monitoring is carried out every delivery and the division of tasks is carried out situationally. The number, competence and infrastructure are available well enough to support the implementation of IMD after Sectio Caesarea delivery in the hospital

An IoT-Based Smart Street Lighting System to Lower Energy Consumption

Smart Lighting System is an automated and intelligent lighting control system that can be deployed across multiple locations or in one location, utilizing various IoT connection protocols, devices, and sensors. The system is able to intelligently adjust to changes in ambient light conditions, traffic patterns, and pedestrian activity through the integration of Internet of Things (IoT) technologies. IoT-enabled sensors are installed in every street light, creating a network that connects to a central control unit. Using real-time data, this system dynamically modifies street light brightness to maximize energy efficiency and improve safety. It provides a simulation and optimization tool for street light placement, considering factors such as street length, light distance, and the number of lights ahead. This tool aids in visualizing the power consumption implications of different configurations, promoting efficient urban planning. Demonstrates the energy-saving potential of the proposed system. As the street light intervals and the number of lights ahead decreases, the optimal street light power significantly reduces, leading to substantial energy savings. The system's ability to dim or turn off lights during low-traffic or well-lit periods contributes to reduced operational costs and enhanced sustainability.

Genome-wide analysis of the biophysical properties of chromatin and nuclear proteins in living cells with Hi-D.

To understand the dynamic nature of the genome, the localization and rearrangement of DNA and DNA-binding proteins must be analyzed across the entire nucleus of single living cells. Recently, we developed a computational light microscopy technique, called high-resolution diffusion (Hi-D) mapping, which can accurately detect, classify and map diffusion dynamics and biophysical parameters such as the diffusion constant, the anomalous exponent, drift velocity and model physical diffusion from the data at a high spatial resolution across the genome in living cells. Hi-D combines dense optical flow to detect and track local chromatin and nuclear protein motion genome-wide and Bayesian inference to characterize this local movement at nanoscale resolution. Here we present the Python implementation of Hi-D, with an option for parallelizing the calculations to run on multicore central processing units (CPUs). The functionality of Hi-D is presented to the users via user-friendly documented Python notebooks. Hi-D reduces the analysis time to less than 1 h using a multicore CPU with a single compute node. We also present different applications of Hi-D for live-imaging of DNA, histone H2B and RNA polymerase II sequences acquired with spinning disk confocal and super-resolution structured illumination microscopy.

Microwave Hyperthermia Technology Based on Near‐Field Focused Metasurfaces: Design and Implementation

AbstractThis paper presents a near‐field focused metasurface design method for microwave hyperthermia. Utilizing full‐wave electromagnetic simulation, a novel dual‐layer metasurface unit with the following characteristics is developed: transmission efficiency higher than −1 dB, adjustable transmission phase from 0° to 360°, and insensitivity to the polarization and incident angle of the incoming wave. Leveraging phase compensation theory, the units at different positions in the array to achieve near‐field focusing functionality is meticulously designed. To further optimize transmission efficiency, the transmission phase of the central unit of the metasurface to 76° is tuned. When applying this near‐field focused metasurface to microwave hyperthermia, the electromagnetic and thermal effects in biological tissues is conducted simulations and experiments to analyzed. The results demonstrate that the proposed metasurface can effectively focus microwave energy, achieving efficient microwave transmission in pork tissue and generating localized high temperatures in the target area. This research introduces new design concepts and implementation strategies for the development of microwave hyperthermia technology.

Revealing Hidden Features of Chaotic Systems Using High-Performance Bifurcation Analysis Tools Based on CUDA Technology

Bifurcation analysis is an essential tool in nonlinear dynamics. Bifurcation diagrams help to discover subtle features of investigated dynamics such as chaotic and periodic regimes, hidden attractors and fixed points. However, plotting high-resolution bifurcation diagrams can be a computationally challenging task, especially in multiparametric evaluation. It should be noted that the bifurcation analysis is a task with natural parallelism and thus can be efficiently solved using hybrid central-graphics processing architectures. In this paper, we propose an advanced algorithm and special software for plotting bifurcation diagrams using calculations accelerated by graphics processing unit in combination with a highly efficient semi-implicit ordinary differential equation solver. Time series processing is based on the extraction of amplitude and phase features for the density-based spatial clustering of applications with noise to determine oscillation periodicity. We showcase the features of the application of proposed solutions on a set of test chaotic systems. The performance of the analysis algorithms is investigated in comparison with conventional solutions based on central processing unit and several approaches known from the literature. We explicitly show that the proposed algorithm outperforms known solutions in both calculation speed and precision.

Drought-induced seismicity modulation in the New Madrid Seismic Zone, central United States

The New Madrid Seismic Zone (NMSZ) in the central United States is a seismically active intraplate region composed of two fault segments: the Reelfoot and Cottonwood Grove fault segments. It has witnessed several major earthquakes, including a devastating 1811–1812 earthquake sequence of three ~M7 events. Nearly 200 years later, earthquakes still continue today in this complex seismic zone. This seismic zone is located in a domain with higher hydrological load than surrounding regions, which may play a crucial role in seismicity modulation. However, the hydrological unloading or loading-induced seismicity modulation and the underlying earthquake dynamics on this stable plate interior remain equivocal. Our study demonstrates that increased climate variability and drought-induced hydrological unloading can be potential drivers for the crustal stress change in the upper Mississippi embayment and seismicity modulation in the NMSZ. The seismicity rate associated with the Reelfoot fault segment shows ~60% increase during drought-induced prolonged drier periods, linked to La Niña cycles, than during the relatively wetter periods. However, such a feature is lacking for the seismicity associated with the Cottonwood Grove fault segment. We argue that the near-lithostatic pore pressure condition explicitly on the Reelfoot fault segment leads to an increase in the amplitude of the velocity perturbation, making this fault segment more susceptible to seismicity modulation on a multi-annual or annual time scale by the resonance destabilization process.

Exploring the Role of Internal Control Systems in Financial Statement Quality under Coercive Pressure in Government Entities

Objective - This study examines the influence of coercive pressure on financial statement quality and the mediating role of internal control systems in central government accounting entities of ministries/institutions partnering with the State Treasury Service Office of Malang (KPPN Malang).Design/Methodology - The research sample was collected by purposive sampling questionnaire with an 84.38% return rate. It comprised 216 respondents of staff and managers responsible for preparing financial statements in central government work units of ministries/institutions partnering with KPPN Malang. Research data were analyzed using the Partial Least Squares (PLS) technique to predict the relationships between coercive pressure, financial statement quality, and the mediating role of internal control systems.Results - It was found that coercive pressure positively influences financial statement quality. Coercive pressure has a positive effect on internal control systems, and internal control systems have a positive impact on financial statement quality. Meanwhile, internal control systems can mediate the relationship between coercive pressure and financial statement quality.Research limitations/implications - The research findings have practical implications that suggest coercive pressures from stakeholders demanding high-quality financial statements should be responded to by implementing effective internal control systems to ensure the quality of presented financial statements.Novelty/Originality - The novelty of this research lies in examining the mediating role of internal control systems in the relationship between coercive pressure and financial statement quality, which has not been discussed in existing studies.

Deep learning and optimization enabled multi-objective for task scheduling in cloud computing

ABSTRACT In cloud computing (CC), task scheduling allocates the task to best suitable resource for execution. This article proposes a model for task scheduling utilizing the multi-objective optimization and deep learning (DL) model. Initially, the multi-objective task scheduling is carried out by the incoming user utilizing the proposed hybrid fractional flamingo beetle optimization (FFBO) which is formed by integrating dung beetle optimization (DBO), flamingo search algorithm (FSA) and fractional calculus (FC). Here, the fitness function depends on reliability, cost, predicted energy, and makespan, the predicted energy is forecasted by a deep residual network (DRN). Thereafter, task scheduling is accomplished based on DL using the proposed deep feedforward neural network fused long short-term memory (DFNN-LSTM), which is the combination of DFNN and LSTM. Moreover, when scheduling the workflow, the task parameters and the virtual machine’s (VM) live parameters are taken into consideration. Task parameters are earliest finish time (EFT), earliest start time (EST), task length, task priority, and actual task running time, whereas VM parameters include memory utilization, bandwidth utilization, capacity, and central processing unit (CPU). The proposed model DFNN-LSTM+FFBO has achieved superior makespan, energy, and resource utilization of 0.188, 0.950J, and 0.238, respectively.

Carbon Nanotube Supported Fluorine Substituted Iron Phthalocyanine Enabling Boosted Polysulfide Redox Conversion Kinetics and Cyclic Stability.

The sluggish transition and shuttle of polysulfides (LiPS) significantly hinder the application and commercialization of Li-S batteries. Herein, carbon nanotubes (CNTs) supported 10 nm sized iron Hexadecafluorophthalocyanine (FePcF16/CNTs) are prepared using a solid synthesis approach. The well-exposed FePcF16 molecular improve the LiPS capture efficiency and redox kinetics by its central Fe-N4 units and F functional groups. The strong electron withdraw F groups significantly promote the conjugate effect and decrease the steric hindrance during mass migration procedure. Distribution of relaxation time (DRT) analysis shows that the Fe-N4 units exhibit strong affinity towards LiPS and the F groups further improve the Li+ diffusion rate in Li2S nucleation and oxidation procedure, accomplishing a porous surface on cathode. As a result, the FePcF16/CNTs separator exhibits a high initial capacity of 1136.2 mAh g-1 at 0.2 C, outstanding rate capacity of 624.9 mAh g-1 at 5 C and superior long-term stability at 2 C surviving 300 cycles with a low capacity decay of 0.43 ‰ per cycle.

Enhancing Productivity and Innovation Through Strengthening Occupational Health and Safety Management

This research aims to analyze the effectiveness of occupational safety and health management in enhancing employee productivity and innovation at PT XYZ (Persero) Central Java Transmission Implementation Unit (UPT), specifically in the West Java area including UPT A, UPT B, UPT C, and UPT D. The study finds that current occupational safety and health management and achievement motivation variables have not fully contributed to employee productivity and innovation, indicating high epsilon coefficients. The research employs both quantitative and qualitative methods, using surveys and in-depth interviews. The analysis of structure 1 and structure 2 shows that the epsilon coefficient is high, suggesting that occupational health and safety management effectiveness and achievement motivation have not fully contributed to employee productivity. Additionally, these variables have not fully contributed to employee innovation, with many other factors influencing these outcomes. The findings highlight that effective occupational safety and health management positively influences employee productivity and innovation. However, other variables, such as the work environment and leadership style, also significantly impact these outcomes. The study suggests that strengthening occupational health and safety management—including management commitment, communication, monitoring, training, and implementation—can lead to better employee performance and innovation. The implications of this research are significant for improving safety and productivity in similar organizational settings. Enhanced occupational health and safety management practices can foster a more productive and innovative workforce, but attention must also be paid to other influential factors.

Three-dimensional computer navigation in the reconstruction of complex unilateral orbital fractures: evaluation and review of applications.

The eyes are the central aesthetic unit of the face. Maxillofacial trauma can alter facial proportions and affect visual function with varying degrees of severity. Conventional approaches to reconstruction have numerous limitations, making the process challenging. The primary objective of this study was to evaluate the application of three-dimensional (3D) navigation in complex unilateral orbital reconstruction. A prospective cohort study was conducted over 19 months (January 2020 to July 2021), with consecutive enrollment of 12 patients who met the inclusion criteria. Each patient was followed for a minimum period of 6 months. The principal investigator carried out a comparative analysis of several factors, including fracture morphology, orbital volume, globe projection, diplopia, facial morphic changes, lid retraction, and infraorbital nerve hypoesthesia. Nine patients had impure orbital fractures, while the remainder had pure fractures. The median orbital volume on the normal side (30.12 cm3; interquartile range [IQR], 28.45-30.64) was comparable to that of the reconstructed orbit (29.67 cm3; IQR, 27.92-31.52). Diplopia improved significantly (T(10) = 2.667, p = 0.02), although there was no statistically significant improvement in globe projection. Gross symmetry of facial landmarks was achieved, with comparable facial width-to-height ratio and palpebral fissure lengths. Two patients reported infraorbital hypoesthesia at presentation, which persisted at the 6-month follow-up. Additionally, five patients developed lower lid retraction (1-2 mm), and one experienced implant impingement at the infraorbital border. Our study provides level II evidence supporting the use of 3D navigation to improve surgical outcomes in complex orbital reconstruction.

CuGBasis: High-performance CUDA/Python library for efficient computation of quantum chemistry density-based descriptors for larger systems.

CuGBasis is a free and open-source CUDA®/Python library for efficient computation of scalar, vector, and matrix quantities crucial for the post-processing of electronic structure calculations. CuGBasis integrates high-performance Graphical Processing Unit (GPU) computing with the ease and flexibility of Python programming, making it compatible with a vast ecosystem of libraries. We showcase its utility as a Python library and demonstrate its seamless interoperability with existing Python software to gain chemical insight from quantum chemistry calculations. Leveraging GPU-accelerated code, cuGBasis exhibits remarkable performance, making it highly applicable to larger systems or large databases. Our benchmarks reveal a 100-fold performance gain compared to alternative software packages, including serial/multi-threaded Central Processing Unit and GPU implementations. This paper outlines various features and computational strategies that lead to cuGBasis's enhanced performance, guiding developers of GPU-accelerated code.

Non-fused ring electron acceptor based on phenyl-substituted benzodithiophenedione unit via chlorinated terminal groups for constructing efficient organic solar cells

Non-fused ring electron acceptors (NFREAs) have displayed promising candidates for practical application of organic solar cells (OSCs) owing to their short synthesis routes and cost effectiveness. The terminal groups halogenation have facilitated the optimization the physicochemical properties of NFREAs. In this work, we developed two NFREAs using a phenyl-substituted benzodithiophenedione unit as central core and electron-withdrawing groups 2-(3-oxo-2,3-dihydro-1 H-inden-1-ylidene) malononitrile (IC) or chlorinated IC (IC-2Cl) as the terminal groups. These NFREAs were designated as BDDPh-H and BDDPh-Cl, respectively. DFT calculations revealing that both NFREAs exhibited good backbone coplanarity due to S…O noncovalent interactions, and BDDPh-Cl exhibited red-shifted absorption compared with BDDPh-H owing to the stronger molecular stacking caused by chlorinated terminal groups. Moreover, BDDPh-Cl-based blended film demonstrated better nano-scale morphology, facilitating exciton dissociation and charge transport. Thus, PM6: BDDPh-Cl-based OSCs achieved a higher power conversion efficiency (PCE) of 12.69 %, outperforming BDDPh-H-based device (3.20 %) due to the enhanced short-circuit current and fill factor. Our findings indicate that combining phenyl-substituted benzodithiophenedione as central unit with chlorinated terminal groups showed great potential to construct highly efficient NFREAs.

Achieving 19.5% Efficiency via Modulating Electronic Properties of Peripheral Aryl-Substituted Small-Molecule Acceptors.

The advancement of acceptors plays a pivotal role in determining photovoltaic performance. While previous efforts have focused on optimizing acceptor-donor-acceptor1-donor-acceptor (A-DA1-D-A)-typed acceptors by adjusting side chains, end groups, and conjugated extension of the electron-deficient central A1 unit, the systematic exploration of the impact of peripheral aryl substitutions, particularly with different electron groups, on the A1 unit and its influence on device performance is still lacking. In this study, three novel acceptors - QxTh, QxPh, and QxPy - with distinct substitutions on the quinoxaline (Qx) are designed and synthesized. Density functional theory (DFT) analyses reveal that QxPh, featuring a phenyl-substituted Qx, exhibits the smallest molecular binding energies and a tightest π···π stacking distance. Consequently, the PM6:QxPh device demonstrates a better power conversion efficiency (PCE) of 17.1% compared to the blends incorporating QxTh (16.4%) and QxPy (15.7%). This enhancement is primarily attributed to suppressed charge recombination, improved charge extraction, and more favorable molecular stacking and morphology. Importantly, introducing QxPh as a guest acceptor into the PM6:BTP-eC9 binary system yields an outstanding PCE of 19.5%, indicating the substantial potential of QxPh in advancing ternary device performance. The work provides deep insights into the expansion of high-performance organic photovoltaic materials through peripheral aryl substitution strategy.