Programmable Module Research Articles

Measures to increase the reliability and efficiency of water supply and wastewater disposal systems

The reliability of water supply and wastewater disposal systems has a significant impact on the environment: therefore, it is essential to implement new methods and approaches that reduce the risk of emergency situations. Based on the experience in automation, maintenance and modernization of wastewater disposal and water supply systems, the study suggests introducing additional programmable modules into automated control systems that provide control and regulation directly on the actuator. For this purpose, the study involves OWEN Logic programming environment, which manages pumping stations through programmable relays. The paper presents functional diagrams that have been introduced into standard macros to increase the reliability of pumping units. In addition, the paper demonstrates that the implementation of multi-level management facilitates the improvement of existing water supply and wastewater disposal systems, thereby increasing their functional capabilities and ensuring the efficient operation of technological equipment. The conducted analysis shows that the adoption of this method for managing technological processes will enhance the reliability and durability of the equipment, ensuring uninterrupted operation of pumping stations. With a change in the performance of water supply and wastewater disposal systems, the installed devices will allow for modernization with minimal economic costs, and reprogramming the operation of the low-level automation without affecting the performance of other levels.

High-spatiotemporal resolution microwave-induced thermoacoustic tomography for imaging biological dynamics in deep tissue

Biological systems undergo constant dynamic changes across various spatial and temporal scales. To investigate the intricate biological dynamics in living organisms, there is a strong need for high-speed and high-resolution imaging capabilities with significant imaging depth. In this work, we present high-spatiotemporal resolution microwave-induced thermoacoustic tomography (HR-MTAT) as a method for imaging biological dynamics in deep tissues. HR-MTAT utilizes nanosecond pulsed microwave excitation and ultrasound detection, with appropriate spatial configurations, to achieve high coupling of the sample to the microwaves, to produce images in soft tissue with dielectric contrast and sub-millimeter spatial resolution (230 μm), to a depth of a few centimeters. Notably, by employing a 128-channel parallel signal acquisition and digitization strategy, the field programmable gate array module manages data synthesis, and GPU-based parallel pixel reconstruction facilitates HR-MTAT to accomplish single-frame image reconstruction in an impressive 50 μs. The practical feasibility of HR-MTAT was evaluated in live mice. The results show that HR-MTAT can noninvasively image whole-body small animals (up to 60 mm in depth) with clear resolution of internal organ structures at a frame rate of 100 Hz, without the need for labeling. At this high spatiotemporal resolution, HR-MTAT can capture respiration, heartbeat, and arterial pulse propagation without motion artifacts and track bio-nanoprobes in livers and tumors. These findings demonstrate HR-MTAT's ability to perform dynamic imaging with high contrast and resolution in deep tissues.

Adaptive laboratory evolution in a novel parallel shaken pH-auxostat.

Adaptive laboratory evolution (ALE) is a widely used microbial strain development and optimization method. ALE experiments, to select for faster-growing strains, are commonly performed as serial batch cultivations in shake flasks, serum bottles, or microtiter plates or as continuous cultivations in bioreactors on a laboratory scale. To combine the advantages of higher throughput in parallel shaken cultures with continuous fermentations for conducting ALE experiments, a new Continuous parallel shaken pH-auxostat (CPA) was developed. The CPA consists of six autonomous parallel shaken cylindrical reactors, equipped with real-time pH control of the culture medium. The noninvasive pH measurement and control are realized by biocompatible pH sensor spots and a programmable pump module, to adjust the dilution rate of fresh medium for each reactor separately. Two different strains of the methylotrophic yeast Ogataea polymorpha were used as microbial model systems for parallel chemostat and pH-auxostat cultivations. During cultivation, the medium is acidified by the microbial activity of the yeast. For pH-auxostat cultivations, the growth-dependent acidification triggers the addition of fresh feed medium into the reactors, leading to a pH increase and thereby to the control of the pH to a predetermined set value. By controlling the pH to a predetermined set value, the dilution rate of the continuous cultivation is adjusted to values close to the washout point, in the range of the maximum specific growth rate of the yeast. The pH control was optimized by conducting a step-response experiment and obtaining tuned PI controller parameters by the Chien-Hrones-Reswick (CHR) PID tuning method. Two pH-auxostat cultivations were performed with two different O. polymorpha strains at high dilution rates for up to 18 days. As a result, up to 4.8-fold faster-growing strains were selected. The increased specific maximum growth rates of the selected strains were confirmed in subsequent batch cultivations.

Research on Ai Technology of Intelligent Information Visualization Based on Rtos System Service

In order to improve the visual interaction ability of intelligent information, an intelligent information visualization artificial intelligence technology based on RTOS system service is proposed in this paper. Based on embedded integrated control, this paper constructs the system design scheme, client and host system of intelligent information visualization artificial intelligence RTOS service system. The information monitoring module, artificial intelligence programmable logic control module, artificial intelligence processing module and human-computer interaction module of intelligent information visualization artificial intelligence RTOS service system are established to realize the label identification and identification in the process of intelligent information visualization artificial intelligence RTOS service system based on unified resource locator sipur, The communication system model of intelligent information visualization artificial intelligence RTOS service system under the transmission mode of multimedia communication channel is established to realize the automatic information processing of intelligent information visualization RTOS system. The test results show that the design has good stability, strong intelligent information visualization and interaction ability, low memory and time cost.

Peptide Nucleic Acid Clamp-Assisted Photothermal Multiplexed Digital PCR for Identifying SARS-CoV-2 Variants of Concern.

The unprecedented demand for variants diagnosis in response to the COVID-19 epidemic has brought the spotlight onto rapid and accurate detection assays for single nucleotide polymorphisms (SNPs) at multiple locations. However, it is still challenging to ensure simplicity, affordability, and compatibility with multiplexing. Here, a novel technique is presented that combines peptide nucleic acid (PNA) clamps and near-infrared (NIR)-driven digital polymerase chain reaction (dPCR) to identify the Omicron and Delta variants. This is achieved by simultaneously identifying highly conserved mutated signatures at codons 19, 614, and 655 of the spike protein gene. By microfluidically introducing graphene-oxide-nanocomposite into the assembled gelatin microcarriers, they achieved a rapid temperature ramping-up rate and switchable gel-to-sol phase transformation synchronized with PCR activation under NIR irradiation. Two sets of duplex PCR reactions, each classifying respective PNA probes, are emulsified in parallel and illuminated together using a homemade vacuum-based droplet generation device and a programmable NIR control module. This allowed for selective amplification of mutant sequences due to single-base-pair mismatch with PNA blockers. Sequence-recognized bioreactions and fluorescent-color scoring enabled quick identification of variants. This technique achieved a detection limit of 5,100 copies and a 5-fold quantitative resolution, which is promising to unfold minor differences and dynamic changes.

Thermal Optimization Design of a Intelligent Programmable Controller Based on CFD Software

With the increasing functionality of intelligent programmable controllers and the continuous improvement in power and component density, the problem of rapidly rising temperatures during operation has become increasingly prominent, directly affecting the controller's lifespan and stability[1]. Therefore, improving the heat dissipation efficiency of intelligent programmable controller modules has become a key focus of research. This paper introduces a method of installing aluminum alloy heat sinks on the core chip of the controller and carefully designing the fin shape and size of the heat sink to enhance heat conduction and heat convection effects, improving heat dissipation performance. This paper also constructs a thermal equivalent model of the controller and simulates the impact of different fin parameters on heat dissipation performance. Experimental results show that when the fin height is 5 millimeters, thickness is 2 millimeters, and spacing is 4 millimeters, the heat sink exhibits the highest thermal conductivity and the lowest thermal resistance, achieving optimal heat dissipation effectiveness.

A Novel Resistive Sensor Network Utilizing an SAP-Enhanced Ionic Layer and CNT Doping for Multipoint Pressure Measurement.

Amidst the rapid advancements in flexible electronics, flexible pressure sensors have achieved widespread applications in fields such as wearable devices and motion monitoring. Nevertheless, it is still a challenge to design a sensor with high sensitivity, cost-effectiveness, and a simplified manufacturing process. This paper introduces a piezoresistive sensor built upon a composite conductive filler. The sensor incorporates a super absorbent polymer (SAP) to absorb a phosphoric acid solution and doped carbon nanotubes as the composite conductive filler. In contrast to conventional rigid conductive fillers, the elastic polymer SAP enhances the sensor's stability significantly by exhibiting superior compatibility with the polydimethylsiloxane matrix, all the while reducing its Young's modulus. This work aims to theoretically elucidate the underlying principles that enable the sensor to achieve high sensitivity. It focuses on the induction of charge carriers due to pressure, which leads to the formation of a conductive pathway and subsequent changes in resistance, thus facilitating precise pressure detection. The paper also discusses the effects of piezoresistive layers with varying thicknesses and conductive fillers on the sensor's output performance. The results highlight the sensor's high sensitivity (0.094 kPa-1), rapid response time (105 ms), and exceptional cyclic load/unload stability (>5000 cycles). Furthermore, this paper establishes a versatile sensing network by integrating a portable inductance, capacitance, and resistance instrument with a programmable logic controller module. Compared to individual sensors, this system enables multipoint measurements, offering high spatial resolution and real-time monitoring capabilities, significantly expanding its overall practicality.

Implementation of a 4G/5G Base Station Using the srsRAN Software and the USRP Software Radio Module

This article presents the potential applications and scenarios for the implementation of a software-defined radio (SDR) module operating as a base station in 4G/5G networks. The paper presents test configurations of the srsRAN software environment in conjunction with various types of programmable radio modules. Then, the key performance metrics of the mobile telephony system and potential problems that may be encountered while implementing hardware and software layers are presented.

IoT based Green House Monitoring and Controlling System

The greenhouse business is the quickest developing area around the world. The smart greenhouse helps in isolating the harvest from the climatic changes. It shelters the plant growth from immediate sunlight and outside weather conditions. To provide a monitoring and control facility within the greenhouse, a framework based on the Internet of Things will be more flexible and sensible. The research focuses on developing a smart, climate-controlled greenhouse for vegetable cultivation. This is achieved by using a low-cost, highly efficient programmable module to monitor and control the greenhouse's climate. The boundaries of the greenhouse are adjusted based on the specific requirements for optimal harvest production. The ESP12F NodeMCU module is utilized for this purpose. The areas that require improvement include the soil's water content, the temperature, and the moisture levels of the field. The plan involves checking with a soil sensor and a DHT11 sensor. The information gathered through the sensors are sent to the NodeMCU that is connected to the IoT or the web connection through a HTTP convention. The farmer is capable of receiving the information in his mobile phone with the help of the IoT. In the field of agriculture, innovation has rapidly advanced and continues to evolve, aiming to enhance and achieve optimal plant growth in the agricultural sector. A precise framework would undoubtedly have an impact on the world of Android/IDS smartphone applications.

ADVANTAGES OF USING HYDROPONIC PLANTS OF CYLINDRICAL FORM WITH AUTOMATED GROWING PROCESS

The article raises the question of the use of hydroponics for growing agricultural crops in modern conditions - this is the growth of plants under the condition of limiting the area and lighting of the premises for cultivation. This approach makes it possible to implement hydroponic systems on an industrial scale in conditions of urban population growth and urbanization. Solving the issue simplifies the chain "agricultural enterprise - consumer" and provides an opportunity to reduce the cost of final products. The main modern cultivation methods and schemes were analyzed, the shortcomings of such systems were identified, and a solution was proposed that would lead to the minimization of costs. This will preserve all the advantages of growing plants in a soilless environment using nutrient solutions. From a large list of options for hydroponic plants and different ways of arranging plants and their root systems in the growing process, the one proposed for use of the equipment based on the technique of using a nutrient layer flowing in the middle of the plant with a cylindrical arrangement of plants in the complex prevails in terms of the use of space and consumption of energy resources. The cultivation process when using such equipment by the position of the plants on the periphery effectively combines almost all the advantages of the technology. The cylindrical rotary hydroponic system proposed for use makes it possible to obtain a larger number of planting places for cultivation on a smaller area of coverage than with the vertical method of cultivation using a multi-tiered method. At the same time, energy costs for the use of lighting and additional lighting are reduced. Due to the automation of the growing process in hydroponic systems, the required amount of human labor is reduced. The use of a modern complex microcontroller control system, consisting of programmable modules controlling individual systems, allows almost complete automation of the growing process and completely excludes the influence of the human factor on the course of events. Therefore, automation in hydroponic systems is an important step towards increasing the efficiency and sustainability of plant cultivation in modern agriculture.

Real-Time Monitoring of Human Breathing Using Wearable Tilted Fiber Grating Curvature Sensors

Respiration rate and volume are important physiological indicators of human health. They can indicate cardiovascular health status and cardiopulmonary function. Here, we demonstrate a compact breath monitoring system based on a wearable tilted fiber Bragg grating (TFBG) curvature sensor for human respiration monitoring. With the assistance of a custom designed breathing tube, TFBGs provide a very reproducible highly sensitive, real time response to curvature changes during respiration. The miniaturized and cost effective sensing system which we propose consists of a tunable laser module, a field programmable gate array acquisition control circuit module, and a sensor module. Different breathing patterns can be successfully identified from the optical amplitude and frequency output of the sensor. The robust instrument displays high repeatability and real-time tracking.

Quality of Service Management for Fast Data Transmission in Industrial Mobile Communications Using PSO-Based Computer Vision Technique

Mobile ad hoc networks (MANETs) have rapidly expanded in recent years, mostly as a result of the mobile devices’ obvious low cost, heterogeneity, and flexibility. When communication networks are down or inaccessible, sensors can quickly create a reliable network that can be used as a rescue data system. Industrial mobile communication has developed into a significant study area for both industry and academia in recent years. The need for data interchange between various smart devices with various latency flows is enormous. Nevertheless, there has not been as much research done in this area. The suggested work suggests a fuzzy-based improved PSO optimized in MANET to alleviate the drawbacks of the conventional routing approach. The suggested study offers a numerical modelling that can be used to carry out adaptive transmission optimization with a variety of programmable module structures and guarantee cost-effective route establishment with greater throughput, goodput, and lowest delay requirements. To find the best route, the proposed approach combines energy-optimized route construction with data-driven cluster head (CH) selection based on swarm intelligence. Particle swarm optimization- (PSO-) based clustering achieves improved delay, goodput, throughput, and path difference degree as compared to other conventional approaches, according to the extensive simulation results. The energy efficiency of a network that is decentralized is more important. The MANET device’s energy efficiency helps to extend battery life and improve network performance. This research demonstrates how the fuzzy-based improved PSO optimized in MANET helps to raise the network’s energy efficiency. As a result, network energy conservation improves network performance and battery life. Additionally, this method enhances the quality of service methodology. End-to-end delay, energy consumption, packet delivery ratio, and normalized routing overhead are measured and compared between the simulation and conventional routing protocols.

Design of programmable hardware security modules for enhancing blockchain based security framework

Globalization of the chip design and manufacturing industry has imposed significant threats to the hardware security of integrated circuits (ICs). It has made ICs more susceptible to various hardware attacks. Blockchain provides a trustworthy and distributed platform to store immutable records related to the evidence of intellectual property (IP) creation, authentication of provenance, and confidential data storage. However, blockchain encounters major security challenges due to its decentralized nature of ledgers that contain sensitive data. The research objective is to design a dedicated programmable hardware security modules scheme to safeguard and maintain sensitive information contained in the blockchain networks in the context of the IC supply chain. Thus, the blockchain framework could rely on the proposed hardware security modules and separate the entire cryptographic operations within the system as stand-alone hardware units. This work put forth a novel approach that could be considered and utilized to enhance blockchain security in real-time. The critical cryptographic components in blockchain secure hash algorithm-256 (SHA-256) and the elliptic curve digital signature algorithm are designed as separate entities to enhance the security of the blockchain framework. Physical unclonable functions are adopted to perform authentication of transactions in the blockchain. Relative comparison of designed modules with existing works clearly depicts the upper hand of the former in terms of performance parameters.

Programmable Aperture Light‐Field Microscopy

AbstractA computational three‐dimensional (3D) microscopy technique, termed programmable aperture light‐field microscopy (PALFM), for motion‐free, high‐resolution volumetric imaging of fluorescent or self‐luminous samples is proposed. The well‐known Fourier slice theorem is extended to incoherent tomographic imaging, which states that a detected image under an ideal aperture corresponds to a central slice in the 3D object spectrum, so the spectrum coverage can be accomplished based on the motion‐free aperture modulation. When further considering frequency extension and coverage, a hybrid aperture modulation scheme is designed consisting of non‐centrosymmetric circular and annular apertures for high‐efficiency, non‐ambiguous depth discrimination. A PALFM system with an easy‐to‐build programmable aperture module attached to an off‐the‐shelf inverted fluorescence microscope is constructed, where annular apertures can manipulate Bessel‐like beams for spectrum modulation. Experimental results on near‐diffraction‐limited imaging of a resolution target across a large depth range and high‐resolution, multi‐color 3D imaging of a mouse kidney section verify the validity and effectiveness of PALFM. High‐speed, long‐term time‐lapse volumetric imaging of HeLa cells in vitro further demonstrates that PALFM is a promising tomographic imaging tool for studying dynamic cellular processes and events without requiring complicated sample rotation or beam scanning.

DycSe: A Low-Power, Dynamic Reconfiguration Column Streaming-Based Convolution Engine for Resource-Aware Edge AI Accelerators

Edge AI accelerators are utilized to accelerate the computation in edge AI devices such as image recognition sensors on robotics, door lockers, drones, and remote sensing satellites. Instead of using a general-purpose processor (GPP) or graphic processing unit (GPU), an edge AI accelerator brings a customized design to meet the requirements of the edge environment. The requirements include real-time processing, low-power consumption, and resource-awareness, including resources on field programmable gate array (FPGA) or limited application-specific integrated circuit (ASIC) area. The system’s reliability (e.g., permanent fault tolerance) is essential if the devices target radiation fields such as space and nuclear power stations. This paper proposes a dynamic reconfigurable column streaming-based convolution engine (DycSe) with programmable adder modules for low-power and resource-aware edge AI accelerators to meet the requirements. The proposed DycSe design does not target the FPGA platform only. Instead, it is an intellectual property (IP) core design. The FPGA platform used in this paper is for prototyping the design evaluation. This paper uses the Vivado synthesis tool to evaluate the power consumption and resource usage of DycSe. Since the synthesis tool is limited to giving the final complete system result in the designing stage, we compare DycSe to a commercial edge AI accelerator for cross-reference with other state-of-the-art works. The commercial architecture shares the competitive performance within the low-power ultra-small (LPUS) edge AI scopes. The result shows that DycSe contains 3.56% less power consumption and slight resources (1%) overhead with reconfigurable flexibility.

Home Surveillance System Based on Internet of Things and Thermal Sensors

A home security system's primary purpose is to protect and monitor areas that are vulnerable to intruders. The cameras can continuously monitor location; however, it’s had drawbacks such as high installation costs, significant electricity consumption, high memory space utilization of the recording system, and complexity of the hardware circuits, in low light condition it need a night vision camera to obtain clear images. The purpose of the research, is to develop a prototype of surveillance system that uses the PIR sensor and night vision camera to detected intruder in low light condition. The methodology used in this research is prototyping. It started with objectives determination of surveillance system, develop, refine and demonstrate the hardware and software, testing and implement the system. The Arduino Board, programmable Arduino IDE microcontroller, battery, RF module, camera, WIFI module, NodeMCU and PIR sensor are all included in this prototype. An application will be loaded on the user's android device, which will be utilized as the security system monitoring and controller. The WIFI module allows remote control by connecting the system to the internet via the cloud. A PIR sensor will be used to monitor the temperature around for the detecting the presence of human. If the sensor detects the thermal imaging, it will trigger the night vision camera to record. The result of the system testing, shows that the system was working perfectly. The testing on camera operability shows that the night vision camera gets a clear image at maximum 10 m. The limitations of this system are unable to detect the thermal objects at more than 10 m clearly. This weakness can be improved by more complete hardware in future research.

Анализ возможности использования программируемых контроллеров при управлении водораспределением в Донском магистральном канале

Purpose: to analyze the possibilities of using programmable logic controllers (PLC) in water distribution management in the Don Main Canal. The work is an analytical study based on the principles of automation and optimization of water resources control. Discussion. The architecture of the control system, including programmable logic controllers, network modules and water level sensors in the main canal is discussed. The main attention is paid to justifying the use of PLC in the design and development of a water distribution control system, which allows control and regulate the water level in the channel using the upstream control scheme. The software offers possibility for monitoring water parameters, calculating optimal values and automatic adjustment of control signals. The advantages of using PLC in water distribution control system, including high flexibility, reliability and the possibility of easy integration with other systems are also analyzed. The methods of PLC setting, regulator optimization and energy management to achieve efficient and economical water resources management are described. The research confirms the effectiveness and applicability of using the programmable controllers in water distribution management system in the Don Main Canal. Conclusions: the results obtained make it possible to increase the efficiency of water resources use, reduce energy consumption and ensure stable control of water level in the irrigation canal.

DNA Nanostructure-Guided Plasmon Coupling Architectures

DNA Nanostructure-Guided Plasmon Coupling Architectures

A Framework to Build a Big Data Ecosystem Oriented to the Collaborative Networked Organization

A Collaborative Networked Organization (CNO) is a set of entities that operate in heterogeneous contexts and aim to collaborate to take advantage of a business opportunity or solve a problem. Big data allows CNOs to be more competitive by improving their strategy, management and business processes. To support the development of big data ecosystems in CNOs, several frameworks have been reported in the literature. However, these frameworks limit their application to a specific CNO manifestation and cannot conduct intelligent processing of big data to support decision making at the CNO. This paper makes two main contributions: (1) the proposal of a metaframework to analyze existing and future frameworks for the development of big data ecosystems in CNOs and (2) to show the Collaborative Networked Organizations–big data (CNO-BD) framework, which includes guidelines, tools, techniques, conceptual solutions and good practices for the building of a big data ecosystem in different kinds of Collaborative Networked Organizations, overcoming the weaknesses of previous issues. The CNO-BD framework consists of seven dimensions: levels, approaches, data fusion, interoperability, data sources, big data assurance and programmable modules. The framework was validated through expert assessment and a case study.

Programmable Photovoltaics of Metal‐Oxide‐Semiconductor Junction

AbstractProgrammability, fundamental to the computing of electronic systems, is traditionally achieved in processing and memory modules. Recently, the emergence of in‐sensor computing allows the programmability of the sensing modules and the process of raw data upon the sensor edge, which reduces data transport and energy consumption. Here, a programmable photodetector module with a tunable photoelectric response based on molybdenum sulfide (MoS2) metal‐oxide‐semiconductor (MOS) junction for visible detection is reported. The sensor takes advantage of the tunable band alignment at the MOS junction and generates an adjustable or even reversible out‐of‐plane photovoltaic effect with high efficiency. This work provides new device configurations to architect the programmability of the photodetectors, and pave the way toward in‐sensor computing at the application edge.