A secure, scalable and versatile multi-layer client–server architecture for remote intelligent data processing

Remote calculation, data processing and visualization functions over WWW have been designed and implemented for use in PBL (problem-based learning) supporting system. This system is supposed to provide a supporting capability for students to find theoretical approaches to their goal for solving a given problem in the field of electrical engineering. For the purpose, the functions were implemented, and the performance was examined. Numerical values can be obtained by selecting mathematical functions and giving the calculation range. The obtained data can be saved as a file in the server. Any numerical data, including calculated or measured data, can be processed by the processing function. All the numerical data can be visualized in a graph format on a web browser. As a result, the implemented functions can be used to support the PBL in an effective way.

In this study, we demonstrate an application for 5G networks in mobile and remote GPR scanning situations to detect buried objects by experts while the operator is performing the scans. Using a GSSI SIR-30 system in conjunction with the RealSense camera for visual mapping of the surveyed area, subsurface GPR scans were created and transmitted for remote processing. Using mobile networks, the raw B-scan files were transmitted at a sufficient rate, a maximum of 0.034 ms mean latency, to enable near real-time edge processing. The performance of 5G networks in handling the data transmission for the GPR scans and edge computing was compared to the performance of 4G networks. In addition, long-range low-power devices, namely Wi-Fi HaLow and Wi-Fi hotspots, were compared as local alternatives to cellular networks. Augmented reality headset representation of the F-scans is proposed as a method of assisting the operator in using the edge-processed scans. These promising results bode well for the potential of remote processing of GPR data in augmented reality applications.

Based on Xilinx's Virtex-II Pro series device XC2VP30 FPGA (Field Programmable Gate Array) chip, we have designed the system to implement remote high-precision time data acquisition, control and processing using TCP/IP communication protocol. This paper describes the design and implement of the FPGA-based hardware platform and software, and the design of ethernet human-computer interaction interface in detail. FPGA-based SOPC (system on programmable chip) technology is the core of the system. Making full use of the FPGA logic cells and related peripheral controller can implement a reconfigurable chip system on FPGA, which can conduct data transmission with a remote control interface.

1. Towards the information technology for environmental monitoring.- 2. Survivability and biocomplexity.- 3. The NSS model as the GIMS component.- 4. The GIMS-based study of ocean and sea ecosystems.- 5. Decision making procedure in the GIMS.- 6. Passive remote technologe and data processing algorithms.- 7. GIMS- based method for vegetation microwave monitoring.- 8. Remote sensing instruments and carrying platforms that realize the GIMS- technology

The last few years have seen Internet applications evolve towards remote and distributed data processing, storage and visualisation. These applications termed Grid and Cloud applications require scalable, yet efficient coordination of resources across infrastructure providers that own the heterogeneous network and IT resources. In addition, emerging applications demand more in terms of type and quality of service delivery and place more diverse, intensive and yet unpredictable demands for data and resources. Photonic networks play a crucial role in supporting this ever more network-centric application model. The photonic network with an agile control plane is the transport medium that can provide the high bandwidth, agility and speed to offer end-to-end QoS-guaranteed network bandwidth services needed to perform the required data transfer, which is the core of Grid and Cloud applications.

Predictive performance and impact of algorithms in remote monitoring of chronic conditions: A systematic review and meta-analysis

PD52-09 TENDENCIES OF CENTRALIZATION FOR RADICAL RETROPERITONEAL LYMPH NODE DISSECTION FOR TESTICULAR CANCER: RESULTS OF TOTAL-POPULATION-DATA ANALYSIS IN GERMANY FROM 2006 TO 2014

To assess trends in the distribution of patients for radical prostatectomy in Germany from 2006 to 2013 and the impact of robotic surgery on annual caseloads. We hypothesized that the advent of robotics and the establishment of certified prostate cancer centers caused centralization in the German radical prostatectomy market. Using remote data processing we analyzed the nationwide German billing data from 2006 to 2013. We supplemented this database with additional hospital characteristics like the prostate cancer center certification status. Inclusion criteria were a prostate cancer diagnosis combined with radical prostatectomy. Hospitals with certification or a surgical robot in 2009 were defined as 'early' group. Linear covariant-analytic models were applied to describe trends over time. Annual radical prostatectomy numbers declined from 28 374 (2006) to 21 850 (2013). High-volume hospitals (⩾100 cases) decreased from 87 (22.0%) in 2006 to 43 (10.4%) in 2013. Low-volume hospitals (<50 cases) increased from 193 (48.7%) to 280 (67.4%). Mean radical prostatectomy caseloads of hospitals with early vs without certification declined from 155 to 130 vs 77 to 39 (P=0.021 for trend comparison). Early robotic hospitals maintained their volume >200 cases per year contrary to the overall trend (P<0.001 for trend comparison). A multivariate model for caseload numbers of 2013 indicated a robotic system to be the most important factor for higher caseloads (multiplication factor 7.3; 95% confidence interval: 6.6-8.0). A prostate cancer center certification (multiplication factor 1.6; 95% confidence interval: 1.50-1.59) had a much smaller impact. We found decentralization of radical prostatectomy in Germany. The driving force for this development might consist in the overall decline of radical prostatectomy numbers. The most important factor for achieving higher caseloads was the presence of a robotic system. In order to optimize outcomes of radical prostatectomy additional health policy measures might be necessary.

Utomotive Transmission Test Line Is One of Sub-lines of Automotive Transmission Assembly Line Used for Testing the Quality of Assembly. some Automotive Transmission Enterprise Is Taken as Research Content and Application Background. this Paper Puts Forward a Control System of Automotive Transmission Test Line Based on Wincc Flexible and S7-300PLC.Here Contents Including Program Planning, Supervisory System Developing, Control System Programming and Communication Network Configuring Are Shown. by Using RFID Information Collection of the Online Products Is Achieved. Besides, Remote Data Acquisition and Processing Is Carried Out by Using Profibus-DP. the Control System Represents Advantages such as Good Interface, Well-staged Control Program, Satisfactory Stability and High Quality of Automation.

An accurate tensor estimation function is a guarantee for acquiring a reliable underground electrical structure model. The past studies regarding transmission functions aim at obtaining smooth and continuous sounding curves through the time domain by data screening means such as least square, robust and remote reference processing methods as well as digital filtering techniques such as wavelet denoising, empirical mode decomposition and Hilbert–Huang transform denoising. As SNRs in different field measurement sites are different, if different data processing algorithms like single-site processing, remote reference processing, magnetic field correlation-based remote reference processing and magnetic channel sharing are used for data processing at the same measuring site, 3N-2 groups of sounding curves with different qualities will be obtained. Manual screening method has been mainly used in the past for screening of the abovementioned 3N-2 groups of sounding curves. If the quantity of sounding site is large, this manual screening method is of low efficiency without quantitative screening indexes. In this paper, discrete Frechet distance is mainly utilized to carry out quantitative screening of 3N-2 groups of sounding curves processed through the abovementioned four processing methods in order to obtain smooth, continuous and reliable sounding curves, thus avoiding subjectivity and low efficiency problems in the past manual screening. A quantitative sorting of all kinds of data processing results can be conducted, and the optimal sounding curve is finally picked out for data inversion. The above sounding curve selection result has improved processing accuracy of magnetotelluric data.

The purpose of the work is to study the current problems and prospects of the solution for processing big data received or stored in the Internet (web data), as well as the possibility of practical realization of Data Mining technology for big web data on practical example. Materials and methods. The study included a review of bibliographic sources on big data analysis problems.Data Mining technology was used to analyze large web data, as well as computer modeling of a practical problem using the C # programming language and creating a DDL database structure for accumulating web data.Results. In the course of the work, the specifics of big data were described, the main characteristics of big data were highlighted, and modern approaches to processing big data were analyzed. A brief description of the horizontal-scalable architecture and the BI-solution architecture for big data processing is given. The problems of processing large web data are formulated: limiting the speed of access to data, providing access via network protocols through general-purpose networks.An example showing the approach to processing large web data was also implemented. Based on the idea of big data, the described complexities of web data processing and the methods of Data Mining, techniques were proposed for effectively solving the practical problem of processing and searching patterns in a large data array.The following classes have been developed in the C # programming language:Class of receiving web data via the Internet; Data conversion class;Intelligent data processing class;Created DDL script that creates a structure for the accumulation of web data.A single UML class diagram has been developed.The constructed system of data and classes allows to solve the main part of the problems of processing large web data and perform intelligent processing using Data Mining technology in order to solve the problem posed of identifying certain records in a large array. The combination of object-oriented approach, neural networks and BI-analysis to filter data will speed up the process of data processing and obtaining the result of the studyConclusion. According to the results of the study, it can be argued that the current state of technology for analyzing large web data allows you to efficiently process data objects, identify patterns, get hidden data and get full-fledged statistical data.The obtained results can be used both for the purpose of the initial study of big data processing technologies, and as a basis for developing an already real application for analyzing web data. The use of neural networks and the created universal classes-handlers makes the created architecture flexible and self-learning, and the class declarations and the base DDL structure will greatly simplify the development of program code.

It is crucial for organizations to secure their data in the internet era. The use of Intrusion Detection Systems (IDS) implies this security. Several researchers used various tools and methods to implement various IDS models. However, a few performance concerns that must be resolved are crucial from a security standpoint. The problems pertain to the IDS time efficiency referred as timeliness, accuracy as well as the fault tolerance. The proposed model of intrusion detection has two phases of detection. Every phase uses a different set of machine learning algorithms. Phase I employs Support Vector Machine (SVM) and k nearest neighbor (kNN), whereas Phase II uses Decision Tree and Naïve Bayes. This two phase detection takes care of reducing false positives and false negatives. To compensate the execution time of these four techniques, the big data environment—Hadoop Distributed File System (HDFS)—is utilized as the underlying storage and processing structure. With such arrangement of two phases, the model gives accuracy of 97.29% overall for known and unknown attacks. For known attacks it gives 99.49% and for unknown attacks it gives 96.28% accuracy in detecting intrusion. Also, the time efficiency is measured for training and testing of the model, for training with 10,000 records, it took 0.7 seconds which is very efficient as considered to existing systems. The detailed performance achievements are discussed in results section. Also, because of HDFS, it becomes distributed and fault tolerant intrusion detection system.

The Space-based multi-band astronomical Variable Objects Monitor (SVOM) mission requires a scalable and efficient data processing and management system to support multi-band data processing, storage, sharing, and operational monitoring. Key technologies to potentially address the demands of this mission include a multi-station Level 0 data fusion algorithm, a data quality assessment algorithm based on orbit and observation number, and a Level 1A science data product processing algorithm for the Gamma Ray Monitor payload. A layered and modular system architecture can support end-to-end automated processing, distribution, archiving, and publication of satellite downlink data across four transmission channels (X-band, S-band, very high frequency, and BeiDou). In-orbit operational validation shows that the system achieves excellent performance in stability, high throughput, and robust adaptability to mission dynamics.

The Local Government Unit (LGU) of Cabagan, Isabela targets to enhance transparency and public service delivery. To achieve these goals, a dynamic web-based information system was developed with three primary objectives: promoting transparency, showcasing municipal accomplishments, and providing easy access to essential services and financial data. The web development process was employed to create the system, utilizing a client-server architecture for efficient data management and processing. Open-source tools such as PHP, HTML, JavaScript, Bootstrap, MySQL, and web browsers were used in the website's development. The site featured a user-friendly, responsive interface and included data uploaded from the municipal level via cPanel web hosting, with the domain registered at www.lgucabagan.gov.ph. The web hosting company ensured reliable data management and website maintenance. Furthermore, a user-end evaluation using a 5-point Likert scale rated the website's design and layout as very satisfactory. Users appreciated the logical structure, easy navigation, and accurate information presentation of the system. The forum page facilitated user feedback, enabling continuous improvement based on community input. The findings from this study demonstrate the potential of open-source technologies to improve local governance and public service delivery. The results highlight the importance of user-centered design in creating effective digital platforms for local government units. The successful implementation of this system in Cabagan underscores its potential for replication in other municipalities, promoting transparency and enhancing public service delivery across the Philippines.

This article outlines the military applications of wireless sensor networks (WSN). The combat activities in modern military operations are divided into different categories, which give the requirements and restrictions for wireless sensor networks. The type of sensor and its function can adjust and limit the use of WSN. A WSN military application's capacity depends on various factors, including capabilities of sensors, type of sensors, the architecture of wireless communications, its range, and appropriate data processing. We performed a categorization of WSN applications used in the military according to the strategic scenario and sensor type. In this paper, military WSN is classified, involving military combat, the sensor type, and defines the vital kind of WSN. This article introduces the research and engineering issues of next-generation WSN military applications.