Software Implementation Research Articles

Improving data interpretability with new differential sample variance gene set tests.

Gene set analysis methods have played a major role in generating biological interpretations from omics data such as gene expression datasets. However, most methods focus on detecting homogenous pattern changes in mean expression and methods detecting pattern changes in variance remain poorly explored. While a few studies attempted to use gene-level variance analysis, such approach remains under-utilized. When comparing two phenotypes, gene sets with distinct changes in subgroups under one phenotype are overlooked by available methods although they reflect meaningful biological differences between two phenotypes. Multivariate sample-level variance analysis methods are needed to detect such pattern changes. We use ranking schemes based on minimum spanning tree to generalize the Cramer-Von Mises and Anderson-Darling univariate statistics into multivariate gene set analysis methods to detect differential sample variance or mean. We characterize these methods in addition to two methods developed earlier using simulation results with different parameters. We apply the developed methods to microarray gene expression dataset of prednisolone-resistant and prednisolone-sensitive children diagnosed with B-lineage acute lymphoblastic leukemia and bulk RNA-sequencing gene expression dataset of benign hyperplastic polyps and potentially malignant sessile serrated adenoma/polyps. One or both of the two compared phenotypes in each of these datasets have distinct molecular subtypes that contribute to heterogeneous differences. Our results show that methods designed to detect differential sample variance are able to detect specific hallmark signaling pathways associated with the two compared phenotypes as documented in available literature. The results in this study demonstrate the usefulness of methods designed to detect differential sample variance in providing biological interpretations when biologically relevant but heterogeneous changes between two phenotypes are prevalent in specific signaling pathways. Software implementation of the developed methods is available with detailed documentation from Bioconductor package GSAR. The available methods are applicable to gene expression datasets in a normalized matrix form and could be used with other omics datasets in a normalized matrix form with available collection of feature sets.

IMPROVEMENT OF THE TECHNOLOGICAL PROCESS OF PERISHABLE GOODS DELIVERY IN THE CITY OF KHARKIV

The article analyses the existing methods for building perishable goods delivery technologies and identifies strategies to study the prospects for developing perishable goods delivery systems, which allowed the authors to formulate the research objective in this development. The chosen topic is quite relevant since the formation of rational transport and technological schemes for the delivery of perishable goods allows for increasing the efficiency of resource use, decreasing the cost of their delivery, and reducing the delivery time of perishable goods. One of the ways to improve the efficiency of perishable goods delivery and reduce delivery time is to determine rational distribution routes and rational brands of rolling stock. The study established that foreign scientists have proposed solutions related to the construction of transport and technological schemes for the delivery of perishable goods, taking into account the choice of vehicles and routes for the delivery of goods. Most of these solutions focused on determining the appropriate loading capacity of rolling stock and the optimal delivery routes for perishable goods. A result of the conducted research was a proposed methodology for a comprehensive improvement of the perishable goods delivery process, consisting of determining rational distribution routes for a selected set of vehicles with different loadings. The authors implemented the software for the algorithm for choosing routes for vehicles of various capacities with the definition of the core technical and operational and technical and economic indicators of efficiency of the delivery process of perishable goods. The software implementation of the algorithm for selecting routes for vehicles of different capacities with the determination of the core technical and operational and technical and economic indicators of the efficiency of the delivery process of perishable goods allows one to quickly, in real-time, perform calculations and determine the rational parameters of the transport process and choose the appropriate routes and rolling stock. Keywords: perishable goods, cargo delivery, distribution routes, truck capacity, costs.

SPA-GPT: General Pulse Tailor for Simple Power Analysis Based on Reinforcement Learning

In side-channel analysis of public-key algorithms, we usually classify operations based on the differences in power traces produced by different basic operations (such as modular square or modular multiplication) to recover secret information like private keys. The more accurate the segmentation of power traces, the higher the efficiency of their classification. There exist two commonly used methods: one is equidistant segmentation, which requires a fixed number of basic operations and similar trace lengths for each type of operation, leading to limited application scenarios; the other is peak-based segmentation, which relies on personal experience to configure parameters, resulting in insufficient flexibility and poor universality. In this paper, we propose an automated trace segmentation method based on reinforcement learning applicable to a wide range of common implementation of public-key algorithms. The introduction of reinforcement learning, which doesn’t need labels, into trace processing for side-channel analysis marks its debut in this field. Our method has good universality on the traces with varying segment lengths and differing peak heights. By using prioritized experience replay optimized Deep Q-Network algorithm, we reduce the required number of parameters to one, which is the key length. We also employ various techniques to improve the segmentation effectiveness, such as clustering algorithm and enveloped-based feature enhancement. We validate the effectiveness of the new method in nine scenarios involving hardware and software implementations of different public-key algorithms executed on diverse platforms such as microcontrollers, SAKURA-G, and smart cards. Specifically, one of these implementations is protected by time randomization countermeasures. Experimental results show that a basic version of our method can correctly segment most traces. The enhanced version is capable of reconstructing the sequence of operations during trace segmentation, achieving an accuracy rate of 100% for the majority of the traces. For traces that cannot be entirely restored, we utilize reward values of reinforcement learning to correct errors and achieve fully recovery. We also conducted comparative experiments with supervised seq2seq methods, revealing our approach’s 42% higher accuracy in operation recovery and 96% faster time efficiency. In addition, we applied our method to the post-quantum cryptography Kyber, and successfully recovered an intermediate value crucial for deriving the secret key. Besides, power traces collected from these devices have been uploaded as open databases, which are available for researchers engaged in public-key algorithms to conduct related experiments or verify our method.

Closing the Gap: Leakage Contracts for Processors with Transitions and Glitches

Security verification of masked software implementations of cryptographic algorithms must account for microarchitectural side-effects of CPUs. Leakage contracts were proposed to provide a formal separation between hardware and software verification, ensuring interoperability and end-to-end security for independently verified components. However, previously proposed leakage contracts did not consider a class of ephemeral hardware effects called glitches, which leaves a considerable gap between security models and the capabilities of real-world attackers. We address this issue by extending the model for leakage contracts to account for glitches and transitions. We further present the first end-to-end verification tool for transient leakage contracts. Our hardware and software verification rely on the same contract as a single source of truth, facilitating fully machine-checked verification from the hardware gate level to the software. By allowing contracts to be written in the C programming language we make power contracts more accessible and intuitive for system-level engineers. To showcase the efficacy of our approach, we apply it to the RISC-V Ibex core. We show that it is possible to write a power contract for Ibex without any modifications to the hardware design. Using this contract, we prove end-to-end security between masked software and gate-level hardware.

Two-stage algorithm of spectral analysis for automatic speech recognition systems

Within the framework of a dynamically developing direction of research in the field of acoustic measurements, the task of spectral analysis of speech signals in automatic speech recognition systems is considered. The low efficiency of the systems in unfavorable speech production conditions (noise, insufficient intelligibility of speech sounds) compared to human perception of oral speech is noted. To improve the efficiency of automatic speech recognition systems, a two-stage algorithm for spectral analysis of speech signals is proposed. The first stage of speech signal processing consists of its parametric spectral analysis using an autoregressive model of the vocal tract of a conditional speaker. The second stage of processing is the transformation (modification) of the obtained spectral estimate according to the principle of frequency-selective amplification of the amplitude of the main formants of the intra-periodic power spectrum. The software implementation of the proposed algorithm based on the high-speed computational procedure of the fast Fourier transform is described. Using the author’s software, a full-scale experiment was carried out: an additive mixture of vowel sounds of the control speaker’s speech with white Gaussian noise was studied. Based on the results of the experiment, it was concluded that the amplitude of the main speech signal formants were amplified by 10–20 dB and, accordingly, a significant improvement in the speech sounds intelligibility. The scope of possible application of the developed algorithm covers automatic speech recognition systems based on speech signal processing in the frequency domain, including the use of artificial neural networks.

Эргономическая оптимизация и гармонизация комплектов электронных заданий на основе идеализированной выборки

This article is devoted to harmonizing sets of electronic tasks offered for completing in the classroom and at a distance. The aim of the study is to develop a universal algorithm for selecting the “ideal”, that is, the most comfortable set, balanced in terms of colour scheme, number of illustrations, explanations and other characteristics. The methodology involves the active use of search algorithms. Currently, one has accumulated a great number of examples for many information disciplines, including online ones, varying in complexity, design, software implementation and the range of the acquired skills and abilities. The problem is in choosing the best of them, as well as in combining diverse electronic material into the most comfortable and harmonious set in terms of content and characteristics. The method allows taking into account students’ opinion, the actual number and speed of completing examples in practice; assess the impact of probable factors (colour, shape, help system, video and sound prompts, etc.) that directly or indirectly affect the ergonomics of electronic tasks. As a theoretical platform, the paper uses the aspects of the methods and experience of mass selections from V.A. Savitskaya’s creative heritage.

A set of Models for Device Positioning in Sixth Generation Networks. Part 1. Methods Survey and Problem Statement

Relevance. Today, terahertz radio systems are considered as a technological basis for integrating methods and means of radio communication and radar in promising sixth-generation networks. If in 4G LTE networks the capabilities of positioning user equipment using the infrastructure of base stations were considered as auxiliary options, then in 5G NR networks, location determination technologies (LDTs) have become full-fledged services, the requirements for which are specified along with communication services. A new trend in positioning in 5G NR networks, compared to 4G LTE networks, has become a single-position assessment of the coordinates and orientation of the user equipment based on signals from a single base station with the ability to distinguish between direct and reflected signals. 6G networks are still in their infancy, but it can already be stated that they mark the next stage in the evolution of digital ecosystems, which is characterized by the convergence of communication technologies, localization and sensing of radio air and the surrounding space by radio engineering means.Purpose. This work opens a research cycle devoted to the review of models, methods and algorithms for positioning devices in 6G networks. The goal of the cycle is to find and justify new radio engineering means for achieving decimeter accuracy in 6G device coordinate estimates. The first part of the cycle provides an overview of the methods and formalization of the model for collecting primary measurements.Method is an analytical review of the state of the problem based on current scientific publications, conceptual modeling, categorical approach, expert combination, comparative analysis, formalization, mathematical and simulation modeling.Results. As a result of the review of device positioning methods during the transition to 6G networks, key performance indicators and LDT scenarios are updated. As a result of the comparative analysis of 5G and 6G networks, new factors, advantages and disadvantages of positioning technologies during the transition from millimeter wave networks to terahertz networks are systematized. A formalized mathematical model for collecting primary measurements is used in the simulation model for assessing the accuracy of device positioning in the second part of the cycle.Novelty. This cycle is the first such study in the Russian scientific segment on network positioning of the sixth generation of the terahertz range, in which the author's version provides an overview of methods and a systematization of a set of new factors of the OMP in communication networks.The theoretical significance of the review-analysis lies in the establishment of both technological obstacles and new opportunities for increasing positioning accuracy during the transition to 6G networks.The practical significance of the formalized mathematical model lies in its subsequent software implementation for numerical justification of the limits of positioning accuracy in 6G networks.

A Scalable Multi-FPGA Platform for Hybrid Intelligent Optimization Algorithms

The Intelligent Optimization Algorithm (IOA) is widely focused due to its ability to search for approximate solutions to the NP-Hard problem. To enhance applicability to practical scenarios and leverage advantages from diverse intelligent optimization algorithms, the Hybrid Intelligent Optimization Algorithm (H-IOA) is employed. However, IOA typically requires numerous iterations and substantial computing resources, resulting in poor execution efficiency. In complex optimization scenarios, IOA traditionally relies on population partitioning and periodic communication, highlighting the feasibility and necessity of parallelization. To address the challenges above, this paper proposes a general hardware design approach for H-IOA based on multi-FPGA. The approach includes the hardware architecture of multi-FPGA, inter-board communication protocols, population storage strategies, complex hardware functions, and parallelization methodologies, which enhance the computing capabilities of H-IOA. To validate the proposed approach, a case study is conducted, in which an H-IOA integrating genetic algorithm (GA), a simulated annealing algorithm (SA), and a pigeon-inspired optimization algorithm (PIO) are implemented on a multi-FPGA platform. Specifically, the flexible job-shop scheduling problem (FJSP) is employed to verify the potential in industrial applications. Two Xilinx XC6SLX16 FPGA chips are used for hardware implementation, encoded in VHDL, and an AMD Ryzen 7 5800U was used for the software implementation of Python programs (version 3.12.4). The results indicate that hardware implementation is 13.4 times faster than software, which illustrates that the proposed approach effectively improves the execution performance of H-IOA.

SmithHunter: a workflow for the identification of candidate smithRNAs and their targets

BackgroundSmithRNAs (Small MITochondrial Highly-transcribed RNAs) are a novel class of small RNA molecules that are encoded in the mitochondrial genome and regulate the expression of nuclear transcripts. Initial evidence for their existence came from the Manila clam Ruditapes philippinarum, where they have been described and whose activity has been biologically validated through RNA injection experiments. Current evidence on the existence of these RNAs in other species is based only on small RNA sequencing. As a preliminary step to characterize smithRNAs across different metazoan lineages, a dedicated, unified, analytical workflow is needed.ResultsWe propose a novel workflow specifically designed for smithRNAs. Sequence data (from small RNA sequencing) uniquely mapping to the mitochondrial genome are clustered into putative smithRNAs and prefiltered based on their abundance, presence in replicate libraries and 5′ and 3′ transcription boundary conservation. The surviving sequences are subsequently compared to the untranslated regions of nuclear transcripts based on seed pairing, overall match and thermodynamic stability to identify possible targets. Ample collateral information and graphics are produced to help characterize these molecules in the species of choice and guide the operator through the analysis. The workflow was tested on the original Manila clam data. Under basic settings, the results of the original study are largely replicated. The effect of additional parameter customization (clustering threshold, stringency, minimum number of replicates, seed matching) was further evaluated.ConclusionsThe study of smithRNAs is still in its infancy and no dedicated analytical workflow is currently available. At its core, the SmithHunter workflow builds over the bioinformatic procedure originally applied to identify candidate smithRNAs in the Manila clam. In fact, this is currently the only evidence for smithRNAs that has been biologically validated and, therefore, the elective starting point for characterizing smithRNAs in other species. The original analysis was readapted using current software implementations and some minor issues were solved. Moreover, the workflow was improved by allowing the customization of different analytical parameters, mostly focusing on stringency and the possibility of accounting for a minimal level of genetic differentiation among samples.

440. QUANTIFICATION OF FLUORESCENCE ANGIOGRAPHY FOR ESOPHAGEAL PERFUSION ASSESSMENT: MEASURING AGREEMENT BETWEEN TWO SOFTWARE ALGORITHMS

Abstract Background Indocyanine green fluorescence angiography (ICG-FA) may reduce perfusion related complications after esophagectomy with gastric conduit reconstruction. Software implementations for quantifying ICG-FA are emerging to overcome a subjective interpretation of the technology. Comparison between quantification algorithms is needed to judge its external validity. This study aimed to measure the agreement for esophageal perfusion assessment between two independently developed quantification software implementations. Methods This retrospective cohort analysis included standardized ICG-FA video recordings of patients who underwent esophagectomy with gastric conduit reconstruction between August 2020 until February 2022. Recordings were analysed by two quantification software implementations: AMS and CPH. The quantitative parameter used to measure visceral perfusion was the normalized maximum slope derived from fluorescence time curves. The agreement between AMS and CPH was evaluated in a Bland-Altman analysis. The relation between the intraoperative measurement of perfusion and the incidence of anastomotic leakage was determined for both software implementations. Results Seventy pre-anastomosis ICG-FA recordings were included in the study. The Bland-Altman analysis indicated a mean relative difference of +58.2% in the measurement of the normalized maximum slope when comparing the AMS software to CPH. The agreement between AMS and CPH deteriorated as the magnitude of the measured values increased, revealing a proportional (linear) bias (R2 = 0.512, p < .001). Neither the AMS nor the CPH measurements of the normalized maximum slope held a significant relationship with the occurrence of anastomotic leakage (median of 0.081 versus 0.074, p = 0.32 and 0.041 vs 0.042, p = 0.51, respectively). Divergent approaches in maximum slope determination and raw signal filtering were identified as contributing factors to the differences in outcome. Conclusion This is the first study to demonstrate technical differences in software implementations that can lead to discrepancies in ICG-FA quantification in human clinical cases. The possible variation among software-based quantification methods should be considered when interpreting studies that report quantitative ICG-FA parameters and derived thresholds, as there may be a limited external validity.

Enterprise Resource Planning Implementation: Challenges and Barriers

The goal of this study is to ascertain how Enterprise Resource Planning (ERP) adoption software is affected in small and medium-sized businesses in Jordan by the problems and barriers represented by (low knowledge of ERP, misperception, lack of resources, financial worries, and employee resistance). The following titles of employees in Jordanian small and medium-sized businesses' departments of information technology made up the study population: (Department Manager, Assistant Department Manager, Head of Department, and Software Officer). To accomplish the goals of the study, the investigator employed a basic random sample of the study population, wherein (160) questionnaires were distributed and (152) were retrieved. The descriptiveanalytic approach was employed in conjunction with various statistical techniques, the most notable of which was the "T" test for one sample (One SampleT–test), and the statistical package program was utilized for statistical analysis and testing of hypotheses. Use SPSS. The study's conclusions include the existence of a statistically significant relationship between Jordanian SMEs' software implementation and their lack of resources, financial concerns, and inadequate ERP understanding. On the other hand, misperception and employee resistance had no statistically significant effect on the implementation of software in Jordanian SMEs. In light of this, the study made several recommendations, the most significant of which is the establishment of an independent committee of senior management experts in information systems and information technology to monitor a variety of data regarding the readiness and effectiveness of the software. As well as involving the user in the ERP implementation from the beginning, because operations management may clearly and effectively benefit from the end-user's assistance in formulating operations that accurately and firmly fulfil daily work needs

Mathematical softgauges for material ratio parameters

Editors of surface texture analysis software need to validate their parameter calculations, ideally in an implementation-independent way. Today, there is no universal reference method for validating parameter compliance and more specifically with regard to material ratio parameters, Rk parameters, and volume parameters that are based on the Abbott curve. Several years ago, at Digital Surf, we developed parameter validation methods that are based on mathematics. A mathematical softgauge, defined by an equation, is injected through the mathematical parameter definition, to obtain a mathematical true value of the parameter value. In a parallel path, a discrete softgauge, derived from the mathematical softgauge, is injected through an algorithm and the resulting value is compared to the approximated true value. This method makes it possible to check the accuracy of an algorithm for calculating a particular parameter. For this study, two families of mathematical softgauges were specifically designed to test material ratio parameters. More precisely, the two main goals of this study are, (1) to advocate an algorithm validation approach that is independent from any software implementation, and (2) to obtain true values for all parameters based on the Abbott curve.

Impact of a Novel Virtual Rounding Queue Software on Nurse and Family Presence for Rounds in the Neonatal Intensive Care Unit: A Pilot Study

ObjectiveCoordinating getting everyone in the room at the same time for family-centered rounds (FCR) is challenging. The objective of this study was to determine if using a virtual queue that notifies nurses and families in real time when to expect the rounding team could impact their presence on rounds. MethodsWe observed rounds on two NICU teams for six weeks before and after implementation of a novel rounding software, Q-rounds™, that shares real-time updates on when the team will arrive and allows families to RSVP to join remotely when they can’t be there in person. Observers collected metrics pertinent to FCR including nurse and family presence (in-person or remotely) and duration of rounds and used chi-squared and two group t-tests for analysis. ResultsRounds were observed for 165 patient encounters pre-implementation and 179 patient encounters post-implementation, with an average rounding duration of 10.3 minutes (SD 6.5) and 10.4 minutes (SD 6.3) per patient respectively (P =0.91). The proportion of nurses who were present for the entirety of the rounding discussion increased from 18.8% to 58.2% (P < 0.001). Family presence on rounds increased from 20.0% (95% CI, 13.9-26.1) to 43.0% (95% CI, 35.8-50.3; P < 0.001). The percentage of families that participated in rounds remotely increased from 15.2% to 55.8% (P < 0.001). ConclusionsThis observational study showed that the use of a novel rounding software was associated with a significant increase in family presence for rounds and nurse presence for the entirety of rounds without increasing rounding duration.

Ứng dụng công nghệ trong quy trình cho vay của các ngân hàng thương mại Việt Nam

Adapting to the digital transformation trend, Vietnamese commercial banks in recent years have quickly caught up and implemented various software and applications to support the lending process. However, there are not many studies that focus on analyzing the detailed activities and the level of digitization in the lending process at Vietnamese commercial banks. Therefore, this article looks at the current situation of technology application at each stage of the lending process for three groups of commercial banks (large scale, medium sized, and small sized) and for two different customer groups (individuals and businesses). The research utilizes a survey method to collect data from employees currently working at commercial banks. The descriptive analysis results show that the level of technology application in improving the lending process is uneven across stages (primarily focusing on the document creation and decision making stage). Moreover, digital transformation in the lending process is implemented more rapidly in medium sized banks and primarily focuses on individual customers.

Algorithm and Software Implementation of an Optimization Method

Algorithm and Software Implementation of an Optimization Method

Optimizing High-Speed Serial Links for Multicore Processors and Network Interfaces

In modern computing environments, high-speed serial links have become a critical component for ensuring efficient data transfer between multicore processors and network interfaces. These links, characterized by their ability to transmit data at very high rates over single or multiple lanes, are essential for meeting the increasing bandwidth demands of contemporary applications. The optimization of these serial links is crucial for maintaining performance, reliability, and energy efficiency in systems that leverage multicore processors and advanced network interfaces. This paper explores the key strategies for optimizing high-speed serial links in the context of multicore processors and network interfaces. We begin by examining the architectural considerations and design principles that influence the performance of serial links, including signal integrity, power consumption, and thermal management. We also discuss the impact of link speed and data encoding techniques on overall system efficiency. One of the central challenges in optimizing high-speed serial links is managing signal integrity across different operating conditions. Techniques such as equalization and adaptive filtering are essential for mitigating the effects of signal degradation due to channel impairments and crosstalk. The paper provides a detailed analysis of these techniques, including their implementation in both hardware and software.

Can algorithms Replace Expert Knowledge for Causal Inference? A Case Study on Novice Use of Causal Discovery.

With growing interest in causal inference and machine learning among epidemiologists, there is increasing discussion of causal discovery algorithms for guiding covariate selection. We present a case study of novice application of causal discovery tools and attempt to validate the results against a well-established causal relationship. As a case study, we attempted causal discovery of relationships relevant to the effect of adherence on mortality in the placebo arm of the Coronary Drug Project (CDP) dataset. We used four algorithms available as existing software implementations and varied several model inputs. We identified 15 adjustment sets from 17 model parameterizations. When applied to a baseline covariate adjustment analysis, these 15 adjustment sets returned effect estimates with similar magnitude and direction of bias as prior published results. When using methods to control for time-varying confounding, there was generally more residual bias than compared to expert-selected adjustment sets. Although causal discovery algorithms can perform on par with expert knowledge, we do not recommend novice use of causal discovery without the input of experts in causal discovery. Expert support is recommended to aid in choosing the algorithm, selecting input parameters, assessing underlying assumptions, and finalizing selection of the adjustment variables.

Improving protection of falcon electronic signature software implementations against attacks based on floating point noise

The object of this study is digital signatures. The Falcon digital signature scheme is one of the finalists in the NIST post-quantum cryptography competition. Its distinctive feature is the use of floating-point arithmetic, which leads to the possibility of a key recovery attack with two non-matching signatures formed under special conditions. The work considers the task to improve the Falcon in order to prevent such attacks, as well as the use of fixed-point calculations instead of floating-point calculations in the Falcon scheme. The main results of the work are proposals for methods on improving Falcon's security against attacks based on the use of floating-point calculations. These methods for improving security differ from others in the use of fixed-point calculations with specific experimentally determined orders of magnitude in one case and proposals for modifying procedures during the execution of which the conditions for performing an attack on implementation level arise in the second case. As a result of the analysis, the probability of a successful attack on the recovery of the secret key for the reference implementation of the Falcon was clarified. Specific places in the code that make the attack possible have been localized and code modifications have been suggested that make the attack impossible. In addition, the necessary scale for fixed-point calculations was determined, at which it is possible to completely get rid of floating-point calculations. The results could be used to qualitatively improve the security of existing digital signatures. This will make it possible to design more reliable and secure information systems using digital signatures. In addition, the results could be implemented in existing systems to ensure their resistance to modern threats

Ampycloud: an open-source algorithm to determine cloud base heights and sky coverage fractions from ceilometer data

Abstract. Ceilometers are used routinely at aerodromes worldwide to derive the height and sky coverage fraction of cloud layers. This information, possibly combined with direct observations by human observers, contributes to the production of meteorological aerodrome reports (METARs). Here, we present ampycloud, a new algorithm, and its associated Python package for automatic processing of ceilometer data with the aim of determining the sky coverage fraction and base height of cloud layers above aerodromes. The ampycloud algorithm was developed at the Swiss Federal Office of Meteorology and Climatology (MeteoSwiss) as part of the AMAROC (AutoMETAR/AutoReport rOund the Clock) program to help in the fully automatic production of METARs at Swiss civil aerodromes. ampycloud is designed to work with no direct human supervision. The algorithm consists of three distinct, sequential steps that rely on agglomerative clustering methods and Gaussian mixture models to identify distinct cloud layers from individual cloud base hits reported by ceilometers. The robustness of the ampycloud algorithm stems from the first processing step, which is simple and reliable. It constrains the two subsequent processing steps that are more sensitive but also better suited to handling complex cloud distributions. The software implementation of the ampycloud algorithm takes the form of an eponymous, pip-installable Python package developed on GitHub and made publicly accessible.

Разработка программно-математической модели движений земной коры для территории Российской Федерации

The author considers the principles of construction, the structure of a software and mathematical model of the Earth`s crust’s movements. It is designed to ensure the maintenance of the state reference frame relevance, the establishment and maintenance of the national reference systems’ relationship with international ones for the Russian Federation’s territory. The software implementation should include mathematical models of geodynamic processes for the state’s territory and algorithms for taking them into account for determining coordinates in a given frame of reference. The author presents a general scheme of the above-mentioned model, which consists of several layers. The first base layer containing a model of the tectonic blocks movement and complemented by those of local solutions. Four stages of the model are described. The mathematical basis and software tools are considered. Employing of the first solution of the crust movements software-mathematical model for the Russian Federation’s territory is presented. It is based on that of lithospheric plates motion NNR-MORVEL56. The results of determining the Earth`s crust’s points velocities are compared with those of the Plate Motion Calculator. The coincidence of the calculated values up to hundredths of a millimeter is noted