Data Processing Operations Research Articles

A Novel Detection Algorithm for Impulse Spike Interferences in Cross-Track Infrared Sounder Short-Wave Spectral Radiance

Due to deficiencies in the operational spike detection, many moderate and strong impulse spike interferences constantly remain nondetected in the cross-track infrared sounder (CrIS) sensor data record (SDR) data at the short-wave infrared (SWIR) band over the South Atlantic Anomaly (SAA) region. This study characterizes imaginary radiance spectrum features in the presence of four intensities of spikes at three different hitting locations through radiative transfer model simulations. It is found that periodic ringing patterns appear in the imaginary spectral radiance. Following it, we establish a novel spike detection algorithm based on the spiky feature of power spectral density (PSD) in detrended and normalized imaginary SWIR CrIS spectral radiances. The performance of the algorithm is assessed by applying it to the multiple years of the SNPP and NOAA-20 CrIS full spectral resolution (FSR) radiance data. Approximate 300 and 500 spike events per day are detected for SNPP and NOAA-20 CrIS individually. The spikes can obviously increase the uncertainty in brightness temperature measurements at SWIR window channels that is determined by hitting location of the interferogram arms and the impulse intensities. Strong impulse spikes can trigger spectral radiance uncertainty by several times in SWIR window channels. Even the weakest impulse event can increase spectral radiance uncertainty by 4% in SWIR window channels. In addition, our simulations and one case study of CrIS data show that the spikes can degrade the quality of the CrIS data at the SWIR band with the largest impact at absorbing channels and the smallest at the window channels. The resultant brightness temperature change are 3 K for absorbing channels and up to 1 K for window channels in the SWIR band, demonstrating the significance flagging the CrIS data that are contaminated by the moderate and strong spikes that are missed in the operational data processing.

Composition Form and Function Configuration of Intelligent Terminal Based on Edge Computing for Power Internet of Things

The intelligent terminal is a key device in the Power Internet of Things (PIOT), which plays a core role in the process of accurately sensing the state of power equipment and adjusting the user’s electricity behaviour in real time. As a decentralized computing architecture, edge computing plays an important role in improving the data processing capacity and operation reliability of PIOT. This paper describes the operation process of PIOT based on edge computing, by studying the form of intelligent terminals in the field of power transmission, distribution and consumption, putting forward the basic configuration, specific function and principles of intelligent terminal. Combined with the operation characteristics and actual demand of power system, the application analysis of information perception ability and online control ability of intelligent terminal is carried out.

РОССИЙСКАЯ ВЫСОКОШИРОТНАЯ СЕТЬ НАКЛОННОГО ЗОНДИРОВАНИЯ ИОНОСФЕРЫ

The network for monitoring the high-latitude ionosphere by the method of oblique ionospheric sounding deployed in the Russian Arctic region is considered. The study describes the main results of operational data processing for studying the high-latitude ionosphere and determining the conditions for the optimum operation of radio communication systems and over-the-horizon radars in this region. The study demonstrates the potential of the network as a tool for the remote diagnostics of parameters of small-scale artificial ionospheric irregularities induced by powerful HF radio waves in the mid-latitude ionospheric F-region.

Ambiguities Suppression for Azimuth Multichannel SAR Based on ${L_{2,q}}$ Regularization With Application to Gaofen-3 Ultra-Fine Stripmap Mode

The azimuth multichannel synthetic aperture radar (SAR) technology is capable of overcoming the minimum antenna area constraint and achieving high-resolution and wideswath (HRWS) imaging. Generally speaking, the pulse repetition frequency (PRF) of the spaceborne multichannel SAR systems should satisfy the azimuthal uniform sampling condition, but it is sometimes impossible due to the limitation of radar system timing conditions, which is often referred as “coverage diagram.” For the Gaofen-3 system, the PRF of each channel at some beam positions is slightly less than that of uniform sampling in the dual-channel mode, leading to the nonuniform undersampling, hence, resulting the azimuth ambiguities in the recovered images. Although the ambiguous energy in Gaofen-3 images is not high in general, it is still noticeable amid surrounding weak clutters of strong targets. In this article, a novel multichannel SAR imaging method for nonuniform undersampling based on L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2,q</sub> regularization (0 <; q ≤ 1) is proposed. By analyzing the reasons of azimuth ambiguities in the multichannel SAR system, the imaging model is established with emphasizing the difference from conventional single-channel SAR. Then, we combine the multichannel SAR data processing operators with the group sparsity property to construct the novel imaging method. The group sparsity property is modeled by the 2, q-norm, and the L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2,q</sub> regularization problem can be solved via sparse group thresholding function. It is shown that the proposed method can efficiently suppress the azimuth ambiguities caused by nonuniform undersampling. Simulations and Gaofen-3 real data experiments are exploited to verify the effectiveness of the proposed method.

Process Drive Sizing Methodology and Multi-Level Modeling Linking MATLAB® and Aspen Plus® Environment

Optimal steam process drive sizing is crucial for efficient and sustainable operation of energy-intense industries. Recent years have brought several methods assessing this problem, which differ in complexity and user-friendliness. In this paper, a novel complex method was developed and presented and its superiority over other approaches was documented on an industrial case study. Both the process-side and steam-side characteristics were analyzed to obtain correct model input data: Driven equipment performance and efficiency maps were considered, off-design and seasonal operation was studied, and steam network topology was included. Operational data processing and sizing calculations were performed in a linked MATLAB®–Aspen Plus® environment, exploiting the strong sides of both software tools. The case study aimed to replace a condensing steam turbine by a backpressure one, revealing that: 1. Simpler methods neglecting frictional pressure losses and off-design turbine operation efficiency loss undersized the drive and led to unacceptable loss of deliverable power to the process; 2. the associated process production loss amounted up to 20%; 3. existing bottlenecks in refinery steam pipelines operation were removed; however, new ones were created; and 4. the effect on the marginal steam source operation may vary seasonally. These findings accentuate the value and viability of the presented method.

SPCOR: a secure and privacy‐preserving protocol for mobile‐healthcare emergency to reap computing opportunities at remote and nearby

This study proposes a secure and privacy-preserving protocol for outsourcing health data processing operations during the emergency in the mobile healthcare network. The proposed protocol provides a practical solution to utilise smartphone resources at both remote and nearby for processing the overwhelming personal health information (PHI) of a user in healthcare emergency opportunistically and securely. The patients with symptoms matching with those of the user in an emergency are considered as opportunities to minimise the privacy disclosure of the user. Opportunities at both remote and nearby are exploited with the help of a base station in the 4G network. Moreover, novel and efficient outsourced privacy access control schemes are developed to minimise the power drain of the user in an emergency without compromising his privacy. The outsourced privacy access control is facilitated through the design of innovative schemes for outsourced attribute-based access mechanism and an outsourced privacy-preserving scalar product computation. Detailed performance evaluations through implementations on Raspberry Pi 3B + board and simulations using NS3 network simulator and Scyther tool confirm the efficiency of the proposed protocol in providing highly reliable PHI processing and transmissions with reasonably low delay and energy consumption while maintaining user privacy.

Operational tool for characterizing high-frequency sea level oscillations

The progressive upgrade of tide gauges to match tsunami warning requirements, tied with an upgrade of tide gauges with 1-min or less sampling and latency, has led to a huge amount of data available worldwide for studies of coastal hazards related to high-frequency sea level oscillations. This upgrade in the observation network poses a challenge in matching the operational data flow, quality control and processing, as well as an opportunity for a more immediate evaluation and understanding of the physical phenomena contained in the raw data, such as meteotsunamis and infragravity waves. The main purpose of this study is to present a new operational tool that enables, for the first time, user-friendly and fast exploitation of an up to now hidden information on high-frequency sea level oscillations. Developed and implemented for 40 tide gauges at the main ports of the Spanish coast, the new tool is based on the automatic analysis of 2-Hz raw data and the online publication of relevant products in near real time. It includes an event detection algorithm and a display calendar to select and review historical events, resulting in a revolutionary advanced toolbox, a new window to phenomena that affects ports operations and infrastructures. This toolbox, combined with the open dataset, provides the first steps for considering HFSLO in the definition of operational risk management. Dealing with these raw data in near real time requires careful selection of appropriate algorithms and quality control procedures, with therefore additional difficulties, that are discussed in this paper.

THE PROBLEM OF PROTECTION OF PERSONAL DATA IN LOCAL GOVERNMENT ELECTIONS IN 2018

This article is intended by the author as an attempt to review and assess the adaptation of the provisions of broadly defined electoral law in terms of its adaptation and the effectiveness of personal data protection. The author indicates in this study how extensive the scope of personal data collected in the electoral process is, and also how many data processing operations are performed on the data collected during this process. It rises and indicates imperfections of regulations – more accurately, consisting in their imprecision, which may result in a decrease in the effectiveness of actions aimed at protecting personal data of both voters and candidates in elections.

A radix sorting parallel algorithm suitable for graphic processing unit computing

SummaryRadix sorting is an essential basic data processing operation in many computer fields. It has important practical significance to accelerate its performance through Graphic Processing Unit (GPU). The heterogeneous parallel computing technology attracts much attention and is widely applied for its effective computation efficiency and parallel real‐time data processing capability. Taking advantage of the parallelism of GPU in numerical computation processing, a parallelization design method of the Binary_Least Significant Digit (LSD) first Radix Sorting (B_LSD_RS) algorithm based on Open Computing Language (OpenCL) is proposed. The radix sorting algorithm is divided into multiple kernel tasks, and the kernels are sequentially controlled by the event information transfer. The parallel algorithm is implemented and verified on the GPU + CPU heterogeneous platform. The experimental results show that compared with the performance of the B_LSD_RS sequential algorithm based on AMD Ryzen5 1600X CPU, B_LSD_RS parallel algorithm based on Open Multi‐Processing (OpenMP) and B_LSD_RS parallel algorithm based on Compute Unified Device Architecture (CUDA), the B_LSD_RS parallel algorithm based on OpenCL obtained 28.86 times, 11.01 times and 2.14 times speedup in the NVIDIA GTX 1070 computing platform respectively, not only achieves high performance but also achieves performance portability among different GPU computing platforms.

Flood Mapping Using Relevance Vector Machine and SAR Data: A Case Study from Aqqala, Iran

The use of satellite imagery to monitor flood areas is essential to determine the damage and prevent related problems in the future. This paper examines thresholding and unsupervised classification for flood mapping using Sentinel-1 SAR image. Thresholding helps us to determine over-detection and under-detection regions in the flooded areas, and so, gamma distribution is used to select the thresholds. Also, the relevance vector machine (RVM) and the object-based classification method have been used for classification. The RVM algorithm obtained better results with overall accuracy = 0.89 and k = 0.95, while for the object-based classification method, these values were 0.87 and 0.91, respectively. According to the results, over- and under-detection occurred in flat areas and man-made structures, respectively. The results demonstrate a great potential of radar imagery for operational detection and delimitation of water in flood risk areas. The automation of satellite radar data processing operation has been tested, and it shows a potential for optimising the system of monitoring and early detection of flood risk.

GDPR Requirements on Data Protection Impact Assessments &amp;amp; Methodologies for DPIAs

The GDPR imposes a general duty on controllers of personal data processing operations to “[take] into account the nature, scope, context and purposes of processing as well as the risks of varying likelihood and severity for the rights and freedoms of natural persons” posed by each personal data processing operation, and to “implement appropriate technical and organisational measures to ensure and to be able to demonstrate that processing is performed in accordance with this Regulation” (Art. 24(1); cf. also Art. 25(1))). Compliance with these requirements demand that the relevant risks be ascertained, recorded and addressed (mitigated). This applies a fortiori to personal data processing operations which, on the basis of such a general risk assessment, are held to pose a likely “high risk to the rights and freedoms of natural persons” (Art. 35(1)). In such a case, the controller is required to carry out, and record, a formal Data Protection Impact Assessment (DPIA) before going ahead with the operation (idem). This paper (which draws on The DPO Handbook I wrote with Marie Georges, https://ssrn.com/abstract=3428957) sets out the GDPR requirements and methodologies recommended by EU data protection authorities (supervisory authorities) in these respects.

3D DIGITISATION IN CULTURAL HERITAGE KNOWLEDGE AND PRESERVATION: THE CASE OF THE NEPTUNE STATUE IN BOLOGNA AND ITS ARCHETYPE

Abstract. In the field of Cultural Heritage, the availability of a complete, detailed and photo-realistic 3D model of the objects of interest permits to describe all the aspects related to geometry, colours and materials, as well as the work techniques and the decay state. Besides, it offers multiple possibilities for the documentation, the analysis and the study.This paper describes the experience, carried out by the DICAM Geomatics group of the University of Bologna, about the 3D digitisation of two important statues of Neptune, by means of the integration of 3D image-based and range-based techniques. The two artworks, both realized by the sculptor Giambologna, are the big bronze statue of the god adorning the homonymous fountain, one of the most symbolic monuments of the city of Bologna, and its archetype, exhibited in one of the civic museums.The obtained 3D models, beyond the important function of documentation, knowledge and preservation of the two objects, also permit a comparison between the small archetype, conveniently scaled, and the big final statue. In the manuscript all the surveying and data processing operations concerning the objects digitisation are described. Particular attention is paid to the problems related to the scale of the archetype and the comparison between the two obtained 3D models, with the aim to evaluate and represent the occurred changes.

How Does HIV Env Structure Informs Vaccine Design?

BackgroundThe DHVI Division of Structural Biology seeks to use atomic level structural information for design of an effective HIV-1 vaccine. Through visualization of the HIV-1 envelope (Env) and its interactions with the human immune system, we obtain structural information that we translate into the rational development vaccine immunogensMethodsWe use negative stain electron microscopy (NSEM), cryo-electron microscopy (cryo-EM), and x-ray crystallography as the major structural techniques for visualization of HIV-1 Env, and combine these with biochemical and biophysical studies, as well as computational methods to obtain a basic understanding of the functions and interactions of the HIV-1 Env.Results:1.The DHVI NSEM pipeline runs on a daily basis to quality control vaccine immunogens for animal studies and other applications. Offering rapid sample turnover and economical operations, the NSEM pipeline is the most widely utilized resource of the DHVI Division of Structural Biology. Over the last year, the NSEM team has focused efforts on improving operational speed and data processing allowing high-quality visualization of a large variety of samples including HIV-1 Env immunogens, antibodies, nanoparticles, and VLPs. In the last year we have also expanded our NSEM studies to the analyses of serum samples and mucosal fluids.2.To understand the mechanism of HIV-1 entry we have determined structures of HIV-1 entry intermediates. We have determined a 3.8 Å resolution structure of a single CD4 bound to a closed HIV-1 Env trimer revealing new contacts of CD4 with Env. We have also structurally characterized an Env designed to prevent CD4-induced rearrangements by targeted disruption of an allosteric network modulating Env conformational changes.3.We have structurally characterized the HIV-1 glycan-V3 targeting DH270 Broadly Neutralizing Antibody Lineage. The structures revealed movements in the V1 loop and interactive glycans, shifts in antibody orientations, antibody VH-VL orientations, and antibody elbow angles, as the lineage progressed to maturation.4.We have solved a structure in complex with the HIV-1 Env immunogen Man5-enriched CH505.N279K.G458Y.SOSIP.664 of the unmutated common ancestor (UCA) of the HIV-1 CD4-binding site targeting CH235 Broadly Neutralizing Antibody Lineage. The structure revealed interactions of the N279K and G458Y mutations with the CDR L3 loop of CH235 UCA thus providing a structural understanding of the role of these mutations in facilitating binding to the CH235 UCA. (see also Henderson et al abstract)5.Using NSEM and cryo-EM we have characterized the structural properties of a novel class of 2G12-mimetic, yet non domain-swapped Fab dimer glycan-reactive (FDG) antibodies. These studies showed that the Fab-dimerized 2G12-like motif is more common than previously thought, and that creation of a Fab-dimerized paratope for an HIV-1 neutralizing antibody does not require VH domain-swapping.6.Finally, the structural team is an integral part of the CHAVD Kalma Immunogen Design Team, wherein we are defining the structural basis of bnAb affinity maturation to guide sequential immunogen design.Conclusions:These results highlight the power of structural information on HIV-1 vaccine design, from leveraging a basic understanding of HIV-1 entry mechanism for immunogen design, to rapid visualization of Env immunogens by NSEM for quality control, discovery of novel antibody interactions, and atomic level visualization of antibody/Env interactions.

Comparing definitions of data and information in data protection law and machine learning: A useful way forward to meaningfully regulate algorithms?

The notion of information is central to data protection law, and to algorithms/machine learning. This centrality gives the impressions that algorithms are just yet another data processing operation to be regulated. A more careful analysis reveals a number of issues. The notion of personal data is notoriously under‐defined, and attempts at clarification from an information theory perspective are also equivocal. The paper therefore attempts a clarification of the meaning of data and information in the context of information theory, which it uses in order to clarify the notion of personal data. In doing so, it shows that data protection law is grounded in the logic of knowledge communication, which stands in stark contrast with machine learning, which is predicated upon the logic of knowledge production, and hence, upon different definitions of data and information. This is what ultimately explains the failure of data protection to adequately regulate machine learning algorithms.

Elosztott mesterséges intelligencia fejlesztés blokklánc alapon az adatvédelem érvényesülése érdekében

A tanulmány célja bemutatni néhány olyan alapvető adatvédelmi jogi elvet, amelyek alkalmazásával megfeleltethető lehet a blokkláncban kezelt személyes adatok és azokkal végzett automatikus döntéshozatal technológiája az Európai Unió általános adatvédelmi rendelete (GDPR) előírásainak. Az ilyen típusú rendszerek fejlesztése során a „beépített adatvédelem” elvére helyezi az elemzés a hangsúlyt. Feltevésem, hogy mivel a blokklánc elosztott alapú adatkezelést lehetővé tévő hálózat, ezért az abban résztvevő minden egyes csomópont adatkezelése vagy adatfeldolgozása során érvényesülnie kell bizonyos előre meghatározott, már a fejlesztés során kollektívan beépített és jelen lévő absztrakt adatkezelési mintázatoknak. A jobb megértés érdekében az emberi tudatot és annak tudatos és tudattalan tartalmakkal való „feltöltését” hoztam analógiaként. Fő célom ezáltal rávilágítani arra, hogy a blokklánc és a gépi tanuláson alapuló mesterséges intelligencia két olyan technológia, amelyek összekapcsolása alkalmas komoly automatikus döntéshozó rendszerek (ún. „elosztott MI”) fejlesztésére. Ezen elosztott MI-t használó rendszerek adatvédelmi jogi megfelelése a nagyon komoly kockázatok miatt olyan kulcskérdés, amivel – a technológia fejlődési irányait szem előtt tartva – érdemes komolyabban is foglalkozni.

Ocena skutków dla ochrony danych

This article deals with the issue of impact assessment for the protection of personal data. This is a new obligation for the controller. The article presents the essence of impact assessment (DPIA), exclusion from the obligation to carry it out, the prerequisite for mandatory DPIA, the role of the data protection officer and the powers of the supervisory authority. The analysis of legal provisions related to the impact assessment presented here does not refer to specific situations, due to the wide scope for interpreting specific phrases contained in the General Regulation. Nevertheless, the article discusses the issue of conducting data protection impact assessments as one of the most problematic obligations incumbent on the controller, who in practice raises many doubts. The DPIA has been imprecisely regulated by the EU legislator, thus leaving controllers plenty of leeway to interpret the terms used in the General Regulation. In addition, carrying out a DPIA in practice (as a new obligation on entities setting the purposes and means of data processing) can be problematic due to the lack of harmonized methods for conducting a data protection impact assessment. However, controllers cannot assign DPIA implementation to other entities involved in data processing, such as an entity processing personal data on behalf of another. Entities setting the purposes and methods of data processing should not only take into account the provisions of the General Regulation but also a list of data processing operations that are obligatorily subject to DPIA. Controllers fulfilling the obligation to carry out a data protection impact assessment will be obliged by the supervisory authority to demonstrate how to carry out a data protection impact assessment.

Census Technology, Politics, and Institutional Change, 1790-2020.

This article traces the history of the methods and technology used by the Census Bureau to convert individual census responses into published tabulations. We argue that political considerations not only shaped the content and applications of the census, but also the mechanics of census taking. By focusing on federal responses to a specific technical challenge over a very long span, our narrative illuminates the long-run effects of shifting societal preoccupations on bureaucratic decision-making. The case study of the census reflects the critical and shifting role of the state and the private sector in the development of technology. For most of the twentieth century, Census Bureau administrators resisted private-sector intrusion into data capture and processing operations, but beginning in the mid-1990s, the Census Bureau increasingly turned to outside vendors from the private sector for data capture and processing. This privatization led to rapidly escalating costs, reduced productivity, near catastrophic failures of the 2000 and 2010 censuses, and high risks for the 2020 census.

PERANCANGAN SISTEM INFORMASI ADMINISTRASI KELURAHAN PADA KELURAHAN PASAR BARU KOTA TANGERANG

The development of information from time to time continues to increase` this is supported by the development of more advanced and adequate technology so that information can be accessed quickly and precisely. Based on the 2014-2018 Pasar Baru Kelurahan Vision that has been established and efforts to support the achievement of the Tangerang City mission by optimizing the authority of information technology-based public services through improving the quality of population administration and civil registration services. In fact in the process of storing data from the results of each work unit is still storing files in the ordner so it takes a long time to find the file that will be needed. To overcome the problems that occur, the authors make the design of a new village market administration information system The system will be built using the PHP programming language and Microsoft Access database. This application can simplify and speed up section heads and employees in accessing their documents independently so that administrative services become more effective and efficient and provide convenience in the processing of urban operational data in data storage services.

PERANCANGAN SISTEM INFORMASI ADMINISTRASI KELURAHAN PADA KELURAHAN PASAR BARU KOTA TANGERANG

The development of information from time to time continues to increase` this is supported by the development of more advanced and adequate technology so that information can be accessed quickly and precisely. Based on the 2014-2018 Pasar Baru Kelurahan Vision that has been established and efforts to support the achievement of the Tangerang City mission by optimizing the authority of information technology-based public services through improving the quality of population administration and civil registration services. In fact in the process of storing data from the results of each work unit is still storing files in the ordner so it takes a long time to find the file that will be needed. To overcome the problems that occur, the authors make the design of a new village market administration information system The system will be built using the PHP programming language and Microsoft Access database. This application can simplify and speed up section heads and employees in accessing their documents independently so that administrative services become more effective and efficient and provide convenience in the processing of urban operational data in data storage services.

Fault Diagnosis and Detection Based on Efficiency Loss Test of Photovoltaic Power Station

The existing operation and maintenance system of photovoltaic power station can analyze partial equipment problems, but due to the data storage, processing and transmission capacity can hardly meet the requirements of a large number of operation data acquisitions and processing of photovoltaic power station, the operation status of photovoltaic power station cannot be comprehensively evaluated. This paper proposes to analyze the overall efficiency and key link efficiency of the photovoltaic system through long-term monitoring, extract the efficiency model parameters of the key components and important links of the photovoltaic power station, and establish the performance evaluation implementation process. At the same time, based on different actual detection conditions, photovoltaic fault diagnosis is carried out by time domain reflectometry, prediction theory comparison and sensor optimization.