Computer Processing System Research Articles

Research on on-site real-time detection technology of transmission line pulling force based on sensors

During the transmission process, the stay wire tower plays an important role in supporting and stabilizing. By monitoring the tension of the stay wire, the deformation and abnormal force of the stay wire tower structure can be detected in a timely manner, and measures can be taken to adjust and repair it. In terms of wire tension monitoring, the main methods currently used include various monitoring technologies such as electronic, mechanical, and optical. However, traditional cable force monitoring methods have problems such as low monitoring accuracy and poor real-time performance, so it is necessary to develop a real-time detection technology based on sensors. This article uses computer technology to achieve real-time detection of transmission line pulling force based on sensors. Firstly, select a suitable sensor for measuring the pulling force. Then, the sensor data is transmitted to the computer system for real-time processing and analysis. Finally, the results are displayed through the interface, facilitating real-time monitoring and control by monitoring personnel. After experimental verification, the real-time detection technology based on sensors proposed in this article can accurately monitor the pulling force of transmission lines. The monitoring results show that this technology has high accuracy and good real-time performance, and can timely detect and handle abnormal wire force situations.

Advanced image analysis for medical diagnostics: a system for segmentation and classification using level set methods and AI algorithms

This work aims to implement and utilize an advanced computer system for image analysis and processing through artificial intelligence. The system will evaluate images from multiple sources. As a result, a comprehensive e-Medicus system will be developed to capture and analyze X-ray data and classify cancer cells. This innovative tool, with its unique features tailored for medical facilities, will assist them in capturing and analyzing X-ray images and CT scan results. The e-Medicus system offers several benefits for medical facilities, including efficient automation of photo analysis, tracking changes in a patient's condition over time, and facilitating the identification of medical changes and data classification. A multimedia presentation of the change process will use the contour set function, allowing for topological changes in solution properties. The system integrates novel procedures and algorithms from theoretical computer science and numerical mathematics, leveraging neural networks, genetic algorithms, semantic networks, image ontology, rough set theory, contour set methods, and hybrid algorithms. These developed algorithms enhance methods and concepts in image segmentation, gathering, transmitting, storing, extracting, and effectively presenting information.

A numerical method for ergodic optimal control of switching diffusions with reflection

The ergodic or long run average cost control problem for diffusions is one of the classical problems of stochastic control that still eludes a completely satisfactory treatment. This is certainly true for the setting in which the systems to be controlled is modeled by the solution of a switching stochastic differential equation with reflection (SSDER). In this paper, we advance in this rather difficult problem by setting forth preliminary results for the unidimensional case. Besides carving out a numerical method, our treatment of the ergodic control in this scenario straddles issues of existence and uniqueness of solution of the SSDER and a verification theorem for the associated HJB equation. We conclude by illustrating the effectiveness of the method considering the control of energy consumption in a large parallel processing computer system composed of one queue and several processing stations.

Bidynamical all-optical reservoir computing for parallel task processing.

A bidynamical all-optical reservoir computing (RC) system for parallel task processing is proposed based on a unidirectional semiconductor optical amplifier optical fiber loop. The polarization dynamics and intensity dynamics are excited by the input signals injected into the reservoir via phase modulation and intensity modulation, respectively. Simultaneous computation of two independent tasks is implemented based on the dynamical responses in polarization and intensity of the optical fiber loop. To our knowledge, this is the first time that two kinds of dynamical responses of an all-optical RC system are used as independent task processing channels to implement parallel task processing. The proposed RC system can achieve good parallel task processing performance with low system cost.

50% reduction in energy consumption in an actual cold storage facility using a deep reinforcement learning-based control algorithm

This study presents a unique application of a temperature control algorithm, specifically modified deep deterministic policy gradient (DDPG), in an actual 2.8 m2 cold storage facility, contrasting the majority of research that leverages theoretical validations using simulation tools. The primary goal was to minimize energy consumption while maintaining the desired temperature range. To achieve this, thermocouples and a watt-hour meter were installed to collect real-time data on temperature and power consumption, subsequently transmitted to a deep-learning computing and control system for processing. Utilizing the gathered data, the algorithm was trained to simultaneously maintain the temperature and minimize power consumption. The temperature setting served as a control variable, and a deep deterministic policy gradient algorithm was used. A hyperparameter with a dominant influence on learning outcomes was optimized. Furthermore, the algorithm was exposed to various complex scenarios that occur during actual cold storage operations, such as door opening, reinforcing its practical viability. The study findings revealed that our real-world application of the DDPG algorithm significantly reduced energy consumption by 47.64% compared to conventional proportional-integral-derivative control algorithms, whilst maintaining the target temperature range.

Design and Implementation of a Distributed Computing System for Scalable Data Processing

Design and Implementation of a Distributed Computing System for Scalable Data Processing

Web-Based System for Remote Mammogram Processing

This paper presents a web-based system for remote processing of mammographic images (mammograms) using Matlab Web Service. The Matlab Web Service is a toolbox for accessing Matlab applications from the internet. We created an image processing system that combines the computational and graphical abilities of Matlab with remote access through the internet. Our system for mammogram processing is a Matlab application stored on a local workstation. By using a web browser users can upload their data (mammogram and parameters necessary for image processing) and view the results obtained after processing (notification about the breast cancer existence). The presented computer system for mammogram processing includes three modules: image preprocessing, feature extraction, and classification. The preprocessing phase consists of the image de-noising, region of interest extraction and image contrast enhancement. The second phase is based on feature extraction techniques for detecting abnormalities in digital mammograms. A total of 20 texture features based on gray-level co-occurrence matrices are used to evaluate the effectiveness of textural information possessed by mass regions. To investigate the ability of the feature set in differentiating abnormal from normal tissue, we employed three different classifiers: Support vector machine classifier, Naive Bayes classifier and K-Nearest Neighbor classifier. The efficiency of classification is provided using a cross-validation technique. The main characteristics of the proposed web-based diagnostic system are that users can use application written in Matlab without installing Matlab software, and they do not need to have any knowledge about programming in Matlab to run application.

CONCEPTS OF A SYNERGISTIC APPROACH TO THE FORMATION OF A SECURITY-ORIENTED INFORMATION ENVIRONMENT IN UKRAINE

The article is devoted to the issues of forming a security-oriented information environment in Ukraine. In the context of increasing influence of internal and external destabilizing factors, realization of unprecedented threats to all components of national security caused by the military aggression of the Russian Federation, ensuring the formation of a security-oriented information environment is the basis for the realization of national interests, which creates new opportunities for strengthening the security of the national economy. The methodological content of the concepts of scientific approaches to ensuring the security of the national economy is investigated. It is proved that the information security of Ukraine’s economy is a complex, non-equilibrium, non-linear, self-organizing system, which justifies the use of a synergistic approach in its research. The concepts of forming a security-oriented information environment substantiated in the study are based on the provisions of a new paradigm of using the opportunities associated with the development of information technology and preventing and countering new threats to information security by protecting information, ensuring the reliability, integrity and availability of public information resources, restricted information, in particular, the one circulating in the economic information infrastructure facilities and determining the further secure development of the state by creating a security system for computer systems for economic data processing (CSEDP) and taking into account external and internal threats realized as a result of the military aggression of the russian federation. The authors have developed a model for the formation of a security-oriented information environment in Ukraine aimed at protecting national economic interests and ensuring the security of the national economy. These key conceptual provisions should serve as a theoretical basis for further development of the methodology for ensuring information security of the national economy.

Conjugated Polymer-Based Nanocomposites for Pressure Sensors.

Flexible sensors are the essential foundations of pressure sensing, microcomputer sensing systems, and wearable devices. The flexible tactile sensor can sense stimuli by converting external forces into electrical signals. The electrical signals are transmitted to a computer processing system for analysis, realizing real-time health monitoring and human motion detection. According to the working mechanism, tactile sensors are mainly divided into four types-piezoresistive, capacitive, piezoelectric, and triboelectric tactile sensors. Conventional silicon-based tactile sensors are often inadequate for flexible electronics due to their limited mechanical flexibility. In comparison, polymeric nanocomposites are flexible and stretchable, which makes them excellent candidates for flexible and wearable tactile sensors. Among the promising polymers, conjugated polymers (CPs), due to their unique chemical structures and electronic properties that contribute to their high electrical and mechanical conductivity, show great potential for flexible sensors and wearable devices. In this paper, we first introduce the parameters of pressure sensors. Then, we describe the operating principles of resistive, capacitive, piezoelectric, and triboelectric sensors, and review the pressure sensors based on conjugated polymer nanocomposites that were reported in recent years. After that, we introduce the performance characteristics of flexible sensors, regarding their applications in healthcare, human motion monitoring, electronic skin, wearable devices, and artificial intelligence. In addition, we summarize and compare the performances of conjugated polymer nanocomposite-based pressure sensors that were reported in recent years. Finally, we summarize the challenges and future directions of conjugated polymer nanocomposite-based sensors.

Use of unmanned aerial vehicle (UAV) for mapping, and accuracy assessment of the orthophoto with and without using GCPs: A case study in Nepal

The conventional methods of aerial photogrammetry using helicopters or airplanes are costly and challenging for small areas. For a developing country like Nepal, where Geospatial data is in high demand, a new competitive approach is essential for rapid spatial data acquisition at a low cost and time. This article demonstrates how this can be achieved using one of the evolving remote sensing technology, Unmanned Aerial Vehicles (UAVs). The application of UAVs is rapidly increasing in Nepal due to its capability of acquiring images remotely and the potential to provide data with a very high spatial and temporal resolution even in inaccessible terrain at a relatively low cost. Here, the performance of UAVs for topographical surveying and mapping has been investigated, along with the comparison between orthophoto obtained using GCPs, and without using GCPs. For this study, a DJI Phantom 3 Advanced quadcopter collected about 700 images at a flying height of 50 m above the settlement area. An orthophoto of 3.78 cm GSD covering 40.83 hectares of area was produced. With appropriate ground control points, an absolute positional accuracy of 0.035 m RMSE was achieved, whereas the output obtained without using GCPs was satisfactory. This study also highlights the use of a High-Performance Computing (HPC) system and open-source platform for rapid image processing.

Application of Embedded Intelligent Target Detection System in Basketball Movement Test

With the development of society, basketball has been deeply loved by people all over the world. Meanwhile, basketball has become one of the most watched events in the world. In order to adapt to the development of basketball and make people better understand the laws of basketball, this paper aims to study the application of embedded intelligent object detection system in basketball sports test and use the embedded intelligent object detection system to separate basketball sports. Compared with the general computer processing system, the embedded system has great differences. It cannot realize the large-capacity storage function because there is no matching large-capacity medium. Strengthen the learning of basketball theoretical knowledge through learning rules. Firstly, the research background of basketball and the research significance of moving target detection are introduced, and the embedded Linus operating system is introduced, including hardware design and software design. Then, four moving target detection algorithms are proposed. Object detection, also called object extraction, is an image segmentation based on the geometric and statistical features of objects, and its accuracy and real-time performance are an important capability of the entire system. Experiments show that when using the YCrCb domain detection algorithm, the average time-consuming is 292 ms, and the conversion frame rate is about 3.5fps. The YCrCb domain detection algorithm has good detection effect and high efficiency.

Multivalued Logic for Optical Computing with Photonically Enabled Chiral Bio-organic Structures.

Photonic bio-organic multiphase structures are suggested here for integrated thin-film electronic nets with multilevel logic elements for multilevel computing via a reconfigurable photonic bandgap of chiral biomaterials. Herein, inspired by an artificial intelligence system with efficient information integration and computing capability, the photonically active dielectric layer of chiral nematic cellulose nanocrystals is combined with printed-in p- and n-type organic semiconductors as a bifunctional logical element. These adaptive logic elements are capable of triggering tailored quantized electrical output signals under light with different photon energy and at the different photonic bandgaps of the active dielectric layer. The bifunctional structures enable complex memory behavior upon repetitive changes of photonic bandgap (controlled by expansion/contraction of chiral nematic pitch) and photon energy (controlled by light absorption wavelength of complementary organic semiconductor layers), exhibiting effectively a reconfigurable ternary logic response. This proof-of-concept bio-assisted multivalued logic structure facilitates an optical computing system for low-power optical information processing integrated with human-machine interfaces.

Comparative analysis of evaluation models of universities in Latin America

There are processes that have been developed in Latin America to improve the quality of higher education. There have been qualitative and quantitative models, which at the beginning have served as a basis for processing the information generated by higher education institutions, factors that have helped to improve the generation of continuous improvement processes, control, and evaluation of the level of university quality, a means for accountability, among others. In the present study, it was observed that the dimensions used by the different higher education systems are the same to be evaluated, that is, they are based on the substantive elements of higher education: teaching, research, social interaction, institutional management. In addition, they use self-assessment as a diagnostic tool, peer assessment for the development of external assessment, and computer systems for information gathering and processing.

Edge-cloud Computing Systems for Smart Grid: State-of-the-art, Architecture, and Applications

The quantity and heterogeneity of intelligent energy generation and consumption terminals in the smart grid are increasing drastically over the years. These edge devices have created significant pressures on cloud computing (CC) system and centralised control for data storage and processing in real-time operation and control. The integration of edge computing (EC) can effectively alleviate the pressure and conduct real-time processing while ensuring data security. This paper conducts an extensive review of the EC-CC computing system and its Application to the smart grid, which will integrate a vast number of dispersed devices. It first comprehensively describes the relationship among CC, fog computing (FC), and EC to provide a theoretical basis for the differentiation. It then introduces the architecture of the EC-CC computing system in the smart grid, where the architecture consists of both hardware structure and software platforms, and key technologies are introduced to support functionalities. Thereafter, the application to the smart grid is discussed across the whole supply chain, including energy generation, transportation (transmission and distribution networks)., and consumption. Finally, future research opportunities and challenges of EC-CC while being applied to the smart grid are outlined. This paper can inform future research and industrial exploitations of these new technologies to enable a highly efficient smart grid under decarbonisation, digitalisation, and decentralisation transitions.

Memristive System Based Image Processing Technology: A Review and Perspective

As the acquisition, transmission, storage and conversion of images become more efficient, image data are increasing explosively. At the same time, the limitations of conventional computational processing systems based on the Von Neumann architecture continue to emerge, and thus, improving the efficiency of image processing has become a key issue that has bothered scholars working on images for a long time. Memristors with non-volatile, synapse-like, as well as integrated storage-and-computation properties can be used to build intelligent processing systems that are closer to the structure and function of biological brains. They are also of great significance when constructing new intelligent image processing systems with non-Von Neumann architecture and for achieving the integrated storage and computation of image data. Based on this, this paper analyses the mathematical models of memristors and discusses their applications in conventional image processing based on memristive systems as well as image processing based on memristive neural networks, to investigate the potential of memristive systems in image processing. In addition, recent advances and implications of memristive system-based image processing are presented comprehensively, and its development opportunities and challenges in different major areas are explored as well. By establishing a complete spectrum of image processing technologies based on memristive systems, this review attempts to provide a reference for future studies in the field, and it is hoped that scholars can promote its development through interdisciplinary academic exchanges and cooperation.

A correction score to compare aortic calcification in contrast enhanced and non-contrast measurements from computed tomography scans

BackgroundAortic wall calcification shows strong promise as a cardiovascular risk factor. While useful for visual enhancement of vascular tissue, enhancement creates heterogeneity between scans with and without contrast. We evaluated the relationship between aortic calcification in routine abdominal computed tomography scans (CT) with and without contrast. MethodsInclusion was limited to those with abdominal CT-scans with and without contrast enhancement within 120 days. Analytic Morphomics, a semi-automated computational image processing system, was used to provide standardized, granular, anatomically indexed measurements of aortic wall calcification from abdominal CT-scans. Aortic calcification area (ACA) and aortic wall calcification percent (ACP) and were the outcomes of interest. Multiple linear regression was used to evaluate the relationship of aortic measurements. Models were further controlled for age and sex. Stratification of measurements by vertebral level was also performed. ResultsA positive association was observed for non-contrast calcification in ACP β 0.74 (95% CI 0.72, 0.76) and ACA β 0.44 (95% 0.43, 0.45). Stratified results demonstrated the highest coefficient of determination at L2 for percent and L3 for area models [R2 0.91 (ACP) 0.74 (ACA)]. Adjusted lumber-level associations between non-contrast and contrast measurements ranged from (β 0.69–0.82) in ACP and (β 0.37–0.54) in ACA. ConclusionA straightforward correction score for comparison of abdominal aortic calcification measurements in contrast-enhanced and non-contrast scans is discussed. Correction of aortic calcification from CT scans can reduce scan heterogeneity and will be instrumental in creating larger cardiovascular cohorts as well as cardiovascular risk surveillance programs.

Readout for simple and precise analog acoustic impact initialization

An economic concept of acoustic shock wave sensing readout system for simple computer processing is introduced in this work. Its application can be found in precise initialization of the stopwatch from the starter sound, handclap or gun in competitive sport races but also in many other places. The proposed device consists of several low-cost commercially available components and it is powered by a 9 V battery. The proposed device reliably reacts on incoming acoustic shock wave by generation of explicit impulse having controllable duration. It significantly overcomes basic implementations using only a microphone and amplifier (generating parasitic burst instead of defined and distinct impulse) or systems allowing a limited number of adjustable features (gain and/or threshold of the comparator—our concept offers the adjustment of gain, cut-off frequency, threshold level and time duration of active state). In comparison with standard methods, the proposed approach simplifies and makes sensing device less expensive and universal for any powder-based starting gun (without necessity to adapt starting gun). The proposed device, among others, has the following features: impulse duration can be controlled from hundreds of μs up to 2.3 s, the gain range of linear part of processing from 6 to 40 dB and open-collector output compatible with 5 V TTL or 3.3 V CMOS logic. The initialization has been tested in the range from tens of centimeters up to four meters. In order to highlight the important spectral components, the spectral character of the signal can be optimally reduced by a low-pass filter. The quiescent power consumption of the designed simple analog circuit reaches 90 mW. Several use cases, response of the designed system on gunshot signature, talking, hand-clapping and hit on the sensing microphone, are studied and compared to each other. Simulation and experimental results confirm functionality of the realized system.

APPLICATION OF DISTRIBUTED COMPUTING SYSTEMS FOR IMAGE PROCESSING IN ORDER TO SEARCH FOR UNMANNED AERIAL VEHICLES

This article describes an approach to solving the problem of searching, identifying and tracking UAVs (Unmanned Aerial Vehicles) using a distributed computing system for processing images from multiple surveillance cameras. Today, the problem of finding UAVs is becoming especially relevant due to their widespread distribution and low cost, which gives a wide scope for illegal use: the implementation of terrorist attacks in crowded places and critical infrastructure, as well as unauthorized tracking of specially protected areas. At the same time, modern radars have low efficiency for searching for UAVs, so today visual detection tools are used, for which effective work requires complex calculations. In this article, it is proposed to use distributed computing systems to solve these complex problems of processing a video stream for the purpose of searching, identifying and tracking objects (UAVs). For this, the author of the article, proceeding from the potential areas of application of such systems, decided to apply a multiagent approach, which makes it possible to create fault-tolerant and scalable systems. In the course of work on the article, softwarefor a distributed computing system for image processing in order to search for unmanned aerial vehicleswas created, a hardware stand was assembled to test it. While performing tests, it was concluded that the proposed method can be applied to implement high-resolution video processing and frame rate in a distributed computing system.

Medical costs according to the stages of colorectal cancer: an analysis of health insurance claims in Hachioji, Japan

Although the effect of the early detection of colorectal cancer (CRC) on medical costs needs to be clarified, there are few reports on the actual medical costs of CRC patients in Japan. We aimed to identify medical costs according to CRC stage, using health insurance claims. This observational study included CRC patients who had received specific treatment for CRC, which was defined by the procedure code and the claim computer processing system code associated with the treatment of CRC. CRC patients who underwent endoscopic or radical surgical treatment were defined as the curable group and those with palliative treatment, including palliative chemotherapy, as the non-curable group. Total medical costs and medical costs of specific treatments for CRC for 3years were measured using the claims held by Hachioji City from May 2014 to July 2019. This study included 442 patients in the curable group, including 267 patients who underwent endoscopic treatment, and 175 patients who underwent radical surgical treatment, and 161 patients in the non-curable group. The mean (standard deviation) total medical costs in the curable and non-curable groups were 2,130 (2,494) and 8,279 (5,600) thousand Japanese Yen (JPY), respectively. The mean (standard deviation) medical costs for the specific treatment of CRC in the curable and non-curable groups were 408 (352) and 3,685 (3,479) thousand JPY, respectively. We clarified the actual medical costs of CRC in curable and non-curable groups. These results suggest the effect of early detection of CRC in reducing medical costs.

High speed modified carry save adder using a structure of multiplexers

Adders are the heart of data path circuits for any processor in digital computer and signal processing systems. Growth in technology keeps supporting efficient design of binary adders for high speed applications. In this paper, a fast and area-efficient modified carry save adder (CSA) is presented. A multiplexer based design of full adder is proposed to implement the structure of the CSA. The proposed design of full adder is employed in designing all stages of traditional CSA. By modifying the design of full adder in CSA, the complexity and area of the design can be reduced, resulting in reduced delay time. The VHDL implementations of CSA adders including (the proposed version, traditional CSA, and modified CSAs presented in literature) are simulated using Quartus II synthesis software tool with the altera FPGA EP2C5T144C6 device (Cyclone II). Simulation results of 64-bit adder designs demonstrate the average improvement of 17.75%, 1.60%, and 8.81% respectively for the worst case time, thermal power dissipation and number of FPGA logic elements.