Graphical Analysis Tool Research Articles

Применение компьютерного зрения для определения реперных точек при оценке геометрии лица

The use of computer vision to determine the geometry of a face using reference points is a relatively new approach in medicine. The relevance of this study is due not only to the need to develop new methods and approaches in determining the geometry of the face, but also to the growing interest in the development and application of artificial intelligence in medicine. The research objective. The purpose of this article is to develop mathematical and neural network algorithms that determine the geometry of a face using reference points. Material and methods. To train the neural network, a small sample of 1,000 marked-up photos in the public domain was used, which depict a full-face portrait of a man up to his shoulders. Only adult (18+) representatives of the Caucasian race were considered. The photos were marked up using the LabelImg 1.8.6 graphical image analysis tool, in which the areas of finding (classes of definition) of reference points were manually marked in the graphical interface mode. YOLO 8 was chosen as the neural network architecture. Results. It was shown that the accuracy of the point search by a neural network trained on 1000 grouped photographs reaches 98.15 %, which indicates a good definition of the boundaries of objects and their classification. Conclusion. The conducted research demonstrated the successful development and application of neural network algorithms to determine alternative reference points characterizing the geometry of the face. The results obtained confirm the effectiveness of the technique proposed by the authors in cosmetology, and also indicate its potential for use in other fields of medicine, such as dentistry, neurology and surgery.

Enhancing Data Trustworthiness in Explorative Analysis: An Interactive Approach for Data Quality Monitoring

The volume of data to be analyzed has increased tremendously in recent years. In order to extract knowledge from this data, domain experts gain new insights with the help of graphical analysis tools for explorative analyses. Here, the reliability and trustworthiness of an exploratory analysis is determined by the quality of the underlying data. Existing approaches require manual testing to ensure data quality which is often neglected. This research aims to introduce a novel interactive approach for seamlessly integrating data quality considerations into the process of explorative data analysis conducted by domain experts. We derive requirements, conduct an extensive literature review, and develop an approach that efficiently combines stakeholders’ strengths, allowing unobtrusive data quality integration in interactive analysis. Our approach enhances trustworthiness due to unobtrusive monitoring of data quality within the context of explorative data analysis. Domain experts gain insights more reliably, bridging the gap between technical requirements and domain expertise. In conclusion, our research presents a promising solution for improving the reliability and trustworthiness of explorative data analysis, especially for domain experts who may lack technical knowledge. By seamlessly integrating data quality into the analytical process, we empower domain experts to extract valuable insights from the ever-increasing volume of data, thereby advancing the field of data-driven decision-making.

PPP project price mode typologies: a China-based comparative case study

PurposePublic–Private Partnerships (PPPs) are crucial to the procurement of global infrastructure projects. Moreover, a price mode based on a cluster of core concessionary items is key to the delivery of value-for-money and successful project outcomes. However, existing research has yet to fully identify PPP concessionary items, nor yet described the range of practical price modes. This study provides taxonomy of core concessionary items impacting PPP projects, systematically classifies price modes, and assesses the applicability and risk impacts of those price modes on PPP projects.Design/methodology/approachThis study adopts a comparative case study method in analyzing core concessionary items and alternative price modes. China is taken as the context, as it is one of the world’s largest PPP markets. In ensuring research validity and reliability, diverse data sources are utilized, with a graphic content analysis tool developed to capture the structure of price modes.FindingsEight PPP price modes are identified. These are: (1) UP (Unit Price) mode, (2) ALS (Annual Lump Sum) mode, (3) IRR (Internal Rate of Return) mode, (4) RP (Return for Investing Capital (RIC) - Profit Rate of O&M (PROM)) mode, (5) RFP (RIC - Financing Interest Rate (FR) - PROM) mode, (6) RFPL (RIC - FR - PROM - Lower Limit of User Charge (LLoUC)) mode, (7) RFL (RIC - FR - Lump Sum/Fixed Unit Price O&M Contract (LSOM/FUP)) mode, and (8) RFLL (RIC - FR - LSOM/FUP - LLoUC) mode. Other main findings are as follows: (1) Five risk allocation configurations can be achieved via these price modes. Yet while different price modes enable the allocation of specific risks, these do not always align with contracting parties’ original intentions. (2) IRR and RP modes may be less applicable in general because of their vulnerability in allocating critical risks and capacity for spurring opportunistic behavior.Originality/valueBy depicting the paths by which concessionary items in price modes affect cash flow, a systematic analysis of price modes was conducted exposing structural characteristics, along with risk allocation choice implications. The study is unique in: (1) Providing a systematic classification of PPP price modes used in PPP projects, (2) Presenting a comprehensive identification and streamlining of concessionary items in PPP practice, and (3) Analyzing the risk effects of different price modes. Together, these outcomes offer a hitherto unavailable perspective on PPP project risk management. The value of the study lies in the following: (1) Existing studies employ diverse concessionary items, but their applicability varies. This study offers an overarching framework facilitating decision-making in selecting appropriate PPP price modes and in determining concessionary items. (2) This study adds to the understanding of PPP price modes in significant ways that will aid local governments and potential sponsors in crafting and administrating more workable contract designs.

Electro-osmotic impact of Williamson fluid flow induced by cilia curved walls

This paper delves into the dynamics of fluid motion powered by cilia within a curved channel. The study includes a detailed examination of chemical reactions occurring in the presence of electro-osmotic impact, with a particular emphasis on the Williamson fluid model as it experiences peristaltic motion within the curved channel. To capture the electro-osmotic phenomena, the Nernst-Planck and Poisson equations are employed. Coordinated transformations are utilized to shift these equations from a fixed reference framework to a moving one. For a comprehensive analytical solution to the electric potential function, lubrication theory and the Debye-Huckel approximation are harnessed. MATLAB is employed as a powerful tool for graphical analysis, providing clear visual insights into the behavior of various flow characteristics. The findings are vividly presented, offering a visual representation of the impact of these flow characteristics. This model not only provides an insightful framework for understanding electro-osmotic driven peristaltic flow in curved channels but is also adapted to accommodate non-Newtonian fluid models, allowing for three-dimensional simulations to enhance clarity. Furthermore, it exhibits the potential to be applied in the development of micro-vascular chips, which could play a crucial role in diagnosing blood-related issues. This versatile model finds applications in physiological transport phenomena, particularly in scenarios involving curved flow regimes. Notably, it is observed that the electro-osmotic velocity corresponds to an amplification in the pressure gradient, while chemical reactions contribute to an enhancement in the concentration profile.

Graphic modeling of radioecological data using Violinplot

Data collection of environmental radioactive chemical contaminants is information of fundamental importance for decision-making in environmental planning and management. In this case, data analyses should be performed with a high level of significance within robust statistical planning. The objective of this study was to utilize the Violinplot as a graphical modeling tool for statistical analysis of radioecology data. To achieve this, a computational algorithm was developed in the Python language. The findings clearly demonstrate that the Violinplot is an outstanding data analysis tool for robust statistical planning in environmental management.

Novel dinuclear Ni (II) Schiff base complexes induced noncovalent exchanges: Crystal structure investigation, electrochemical assessment, Hirshfeld surface analysis and SARS‐CoV‐2 docking study

In this work, novel Ni (II) complexes, namely, [Ni2(L)2(OAc)2(EtOH)2] (1a), [Ni2(L)2(OAc)2(H2O)2] (1b‐1) and [Ni2(L)2(OAc)2(EtOH)2] (1b‐2) as co‐crystal were synthesized by the 1:1 condensation (https://www.sciencedirect.com/topics/chemistry/condensation) of Ni (CH3COO)2·4H2O and Schiff base ligand (H2L) (2‐hydroxy‐4‐methoxybenzaldehyde and 2‐amino‐2‐methylpropanol). The ligand based on Schiff base and fabricated complexes (1a) and (1b‐1 and 1b‐2) were successfully identified by CHN assessment, FT‐IR, UV–Vis spectra, melting point and CV voltammogram. The electrochemical behavior investigation shows that the nickel complexes exhibited irreversible oxidation processes in methanol solution. Additionally, the crystal structures of complexes (1a) and (1b) have been recognized by single‐crystal X‐ray diffraction investigation. It turned out that the complexes (1b‐1) and (1b‐2) crystallize together, making a co‐crystal 1b with an additional EtOH solvent molecule in the crystal structure. A detailed study of intermolecular exchanges was performed using attractive graphical analysis tools such as three‐dimensional Hirshfeld surfaces analysis, two‐dimensional fingerprint plots (FPs), and enrichment ratios (E), which make C‐H … C, C‐H … O hydrogen bond, C … O, H … H, and O … O short contacts on Hirshfeld surfaces with color code are observed. Moreover, an appraisement of the inhibitory trace against coronavirus (main protease SARS‐CoV‐2, PDB ID: 6Y2F) and molecular targets of human angiotensin‐converting enzyme‐2 (ACE‐2) was performed by a molecular docking study in which two nickel complexes performed best for PDB protein ID: 6M0J and all three complexes for PDB protein ID: 6Y2F.

Improving Students’ Dyscalculia Numeracy Ability Using Learning Media Colored Bead Montessori

This study aims to investigate the effects of colored bead Montessori learning media to students’ numeral thinking skills none of the elementary schools (SD) in Padang, Indonesia. This study used a quantitative method with a single-subject research approach, the research data was taken from a student with dyscalculia through fifteen direct lessons using colored bead Montessori learning media. Data were analyzed by using visual graphical analysis tool descriptively were analyzed descriptively using visual graphical analysis tools. The results of this study showed that the use of colored bead Montessori learning media based on the analysis can actually improve the numeracy skills of students with dyscalculia in learning. This improvement is proved by, at first the students' scores were 2, 4, 4, 4, this was the value before the researcher used the media. Furthermore, after the researcher did seven times direct treatment, it was found that the students' scores increased to 10, 13, 15, 18, 20, 20, 20, even students were able to obtain self-evaluation scores with numbers 20, 20, 20, 20. The results of this study proved that the use of colored bead Montessori media has been able to improve the numeracy skills of students in learning. Referring to the results of this research, colored bead Montessori can be used as an alternative media in learning numeracy skills of students with dyscalculia none of the elementary schools.

Networked scatter plot bidirectional coupling detection and its application in the diagnosis of depression

Identifying the bidirectional coupling of bivariate time series is a basic problem in the analysis of complex systems in contemporary science. As an intuitive statistical graphical analysis tool, scatter plot allows direct analysis of the correlation between two bivariate time series. However, the scatter plot itself have the problems of not being able to conduct bidirectional coupling analysis and data points overlap. In this work, by introducing inner composition alignment (IOTA) and ordinal pattern transition network (OPTN) into scatter plot, the limitations of scatter plot are alleviated and a new approach for measuring bivariate time series bidirectional coupling is proposed. To facilitate the integration of the three methods, the IOTA scatter plot proposed and the new scatter plot been partitioned and coded. The coded partitions are defined as network nodes and a directed weighted network is constructed based on the temporal adjacency of the nodes. For the constructed OPTN, the mean output degree that commonly used in OPTN is used as a quantitative indicator of coupling strength. To test the characteristics and performance of the new method, it is used to analyse the unidirectional coupled Lorentz model and to compare it with existing methods. The results showed the new method had the advantages of easy parameter setting, efficiency, and suitable for short time series. Finally, the real EEG dataset from depressed patients at rest are analysed and some useful and interesting results are obtained by treating the relevant brain areas as routers.

Towards preliminary design calculations with TRANSURANUS for application of Hastelloy cladding material

This study summarises the work performed to implementing the material properties for Hastelloy-N, of interest for GenIV MSRs, into the TRANSURANUS fuel performance code. The individual development of correlations on the basis of experimental data in the open literature, and the subsequent assessment with an independent dataset when available, also revealed the need for specific new experiments that have been pointed out. Following that, an integral assessment of the new code version was carried out as well. The simulation of a biaxial cladding burst tests from ORNL, with due consideration of the uncertainties and analysis by means of the new graphical output analysis tool TUPython for uncertainty and sensitivity analysis, provided encouraging results for the preliminary implementation of Hastelloy-N properties. The proposed set of material properties can therefore be readily implemented in any other fuel performance code.

CRISPR-GRANT: a cross-platform graphical analysis tool for high-throughput CRISPR-based genome editing evaluation

BackgroudCRISPR/Cas is an efficient genome editing system that has been widely used for functional genetic studies and exhibits high potential in biomedical translational applications. Indel analysis has thus become one of the most common practices in the lab to evaluate DNA editing events generated by CRISPR/Cas. Several indel analysis tools have been reported, however, it is often required that users have certain bioinformatics training and basic command-line processing capability.ResultsHere, we developed CRISPR-GRANT, a stand-alone graphical CRISPR indel analysis tool, which could be easily installed for multi-platforms, including Linux, Windows, and macOS. CRISPR-GRANT offered a straightforward GUI by simple click-and-run for genome editing analysis of single or pooled amplicons and one-step analysis for whole-genome sequencing without the need of data pre-processing, making it ideal for novice lab scientists. Moreover, it also exhibited shorter run-time compared with tools currently available.ConclusionTherefore, CRISPR-GRANT is a valuable addition to the current CRISPR toolkits that significantly lower the barrier for wet-lab researchers to conduct indel analysis from large NGS datasets. CRISPR-GRANT binaries are freely available for Linux (above Ubuntu 16.04), macOS (above High Sierra 10.13) and Windows (above Windows 7) at https://github.com/fuhuancheng/CRISPR-GRANT. CRISPR-GRANT source code is licensed under the GPLv3 license and free to download and use.

РЕАЛИЗАЦИЯ ЭФФЕКТИВНОГО МЕТОДА ТЕХНИЧЕСКОГО АНАЛИЗА ДЛЯ ОПРЕДЕЛЕНИЯ ТРЕНДА РЫНКА НА ПЛАТФОРМЕ METATRADER 5

The article discusses the possibilities of using effective methods of technical analysis to determinethe trend direction of financial assets on the multi-market platform MetaTrader 5.The advantages and expediency of using technical analysis methods in various areas of financialmarkets are shown by examples of works by Russian and foreign authors. In order to determinethe direction and strength of the trend, the insufficiency of the use of such technical indicators asBollinger bands (BB), MACD, MA, EMA, constructed according to various laws of the distributionof prices of financial assets, is justified. Graphical analysis tools are considered as a special caseof technical analysis, characterized by special visibility and visualization of the process understudy. The article provides examples of technical analysis figures, shows them to belong to thebasic types of graphical analysis. The concept of a modern trading strategy – innovative trading isconsidered, a comparative analysis of the trading strategy, its opportunities and risks is carriedout. The paper describes the developed software module in the form of a trading indicator on theMetaTrader 5 platform in Meta Quotes Language 5 (MQL5) in combination with a script in thehigh-level Python language for algotrading using technical analysis methods. The indicator isbased on the construction of support and resistance lines to determine the direction and strengthof the trend. An algorithm for determining the direction and strength of the trend with technicalanalysis tools has been developed, which as a result will improve the accuracy of the trend directionforecast by integrating a technical indicator into the system. For the experimental part of theprocess, a financial instrument was used – the EUR/USD currency pair, the total study period wassix months. As a result, the algorithm worked correctly in real time without human intervention fortwenty-four weeks. Based on the test results, it is possible to judge the prospects of research in thisarea for solving a large range of applied problems of financial mathematics and analytics.The application of the created indicator can be extended to any trading operations on variousfinancial instruments and their combinations.

AlphaPulldown-a python package for protein-protein interaction screens using AlphaFold-Multimer.

The artificial intelligence-based structure prediction program AlphaFold-Multimer enabled structural modelling of protein complexes with unprecedented accuracy. Increasingly, AlphaFold-Multimer is also used to discover new protein-protein interactions (PPIs). Here, we present AlphaPulldown, a Python package that streamlines PPI screens and high-throughput modelling of higher-order oligomers using AlphaFold-Multimer. It provides a convenient command-line interface, a variety of confidence scores and a graphical analysis tool. AlphaPulldown is freely available at https://www.embl-hamburg.de/AlphaPulldown. Supplementary note is available at Bioinformatics online.

CORUM: the comprehensive resource of mammalian protein complexes-2022.

The CORUM database has been providing comprehensive reference information about experimentally characterized, mammalian protein complexes and their associated biological and biomedical properties since 2007. Given that most catalytic and regulatory functions of the cell are carried out by protein complexes, their composition and characterization is of greatest importance in basic and disease biology. The new CORUM 4.0 release encompasses 5204 protein complexes offering the largest and most comprehensive publicly available dataset of manually curated mammalian protein complexes. The CORUM dataset is built from 5299 different genes, representing 26% of the protein coding genes in humans. Complex information from 3354 scientific articles is mainly obtained from human (70%), mouse (16%) and rat (9%) cells and tissues. Recent curation work includes sets of protein complexes, Functional Complex Groups, that offer comprehensive collections of published data in specific biological processes and molecular functions. In addition, a new graphical analysis tool was implemented that displays co-expression data from the subunits of protein complexes. CORUM is freely accessible at http://mips.helmholtz-muenchen.de/corum/.

HumanMine: advanced data searching, analysis and cross-species comparison.

HumanMine (www.humanmine.org) is an integrated database of human genomics and proteomics data that provides a powerful interface to support sophisticated exploration and analysis of data compiled from experimental, computational and curated data sources. Built using the InterMine data integration platform, HumanMine includes genes, proteins, pathways, expression levels, Single nucleotide polymorphism (SNP), diseases and more, integrated into a single searchable database. HumanMine promotes integrative analysis, a powerful approach in modern biology that allows many sources of evidence to be analysed together. The data can be accessed through a user-friendly web interface as well as a powerful, scriptable web service Application programming interface (API) to allow programmatic access to data. The web interface includes a useful identifier resolution system, sophisticated query options and interactive results tables that enable powerful exploration of data, including data summaries, filtering, browsing and export. A set of graphical analysis tools provide a rich environment for data exploration including statistical enrichment of sets of genes or other biological entities. HumanMine can be used for integrative multistaged analysis that can lead to new insights and uncover previously unknown relationships. Database URL: https://www.humanmine.org

Assessment of multiple choice question exams quality using graphical methods

Exams should be valid, reliable, and discriminative. Multiple informative methods are used for exam analysis. Displaying analysis results numerically, however, may not be easily comprehended. Using graphical analysis tools could be better for the perception of analysis results. Two such methods were employed: standardized x-bar control charts with standard error of measurement as control limits and receiver operator characteristic curves. Exams of two medical classes were analyzed. For each exam, the mean, standard deviation, reliability, and standard error of measurement were calculated. The means were standardized and plotted against the reference lines of the control chart. The means were chosen as cut-off points to calculate sensitivity and specificity. The receiver operator characteristic curve was plotted and area under the curve determined. Standardized control charts allowed clear, simultaneous comparison of multiple exams. Calculating the control limits from the standard error of measurement created acceptable limits of variability in which the standard deviation and reliability were incorporated. The receiver operator characteristic curve graphically showed the discriminative power of the exam. Observations made with the graphical and classical methods were consistent. Using graphical methods to analyse exams could make their interpretation more accessible and the identification of exams that required further investigation easier.

Ecosystem Services in Southern Africa: Current and Emerging Trends—A Bibliometric Review

The assessment of ecosystem services (ESs) is important for Africa’s sustainability and progress. Healthy ecosystems benefit humans in various forms; however, continuous anthropogenic activities have led to rapid alterations in their compositions, structures and functions worldwide. Due to the lack of understanding on the role of ES assessment in southern Africa, many ES assessment practices and methodologies have been widely debated Thus, a bibliometric analysis of ESs in southern Africa was conducted for the period of 1996–2021, to present the key features of ES assessment practices and methodologies and reveal evolutionary trends in this field. The results showed that in southern Africa, not many ES assessment studies have been published; however, South Africa was the most productive country in terms of author collaboration and publication output. Other leading countries in this field include the UK, USA, Germany and Australia. The most productive institutions in southern Africa are located in South Africa, and are the University of Cape Town, the Council for Scientific and Industrial Research (CSIR), Rhodes University, the University of KwaZulu Natal, and the University of Stellenbosch. The five funding institutions that are most active in supporting ES assessment in southern Africa are European. The main publishers of the research are either American or European and include the highly influential publishers Elsevier, Wiley, MDPI, Springer Nature and Resilience Alliance. VOS Viewer was employed as a visual analysis tool and CiteSpace as a graphic analysis tool to conduct the bibliometric analysis. A key conclusion is that most authors use qualitative methods to assess people’s livelihoods and wellbeing as they relate to provisional and cultural services, while remotely sensed imagery is used as a key tool to assess the spatial extent of provisional and regulating services. Research recommendations include promoting a transdisciplinary approach in ES assessment in southern Africa.

Toward Simplified Physics-Based Memristor Modeling of Valence Change Mechanism Devices

Memristors are promising nanoelectronic devices for the implementation of future AI-driven sensor-processor electronic systems, which are essential for the ongoing digitalization of our world. Accurate and computationally cost-effective models for the manufactured memristors are essential for the design of such systems, especially for the simulation of large circuits. In this brief we address the simplification of the JART memristor model, a generic physics-based model of Valence Change Mechanism (VCM) memristors which accurately describes the dynamic behavior of fabricated memristor devices. Furthermore, the proposed model and simplification methodology have the potential to capture the dynamics of a wide range of memristor devices. Importantly, the implicit description of the current through the memristor is replaced by an explicit mathematical relationship. The proper reproduction of memristor dynamics, verified by applying the system-theoretic Dynamic Route Map (DRM) graphical analysis tool, applicable to first-order systems, can be observed through the proposed simplified model and enables the time-efficient simulation of large arrays of VCM devices.

End Fuel Prices and Their Drivers in the Czech Republic

This paper deals with understanding drivers influencing the end price of fuels in the Czech Republic and ramifications for relevant companies. Its aim is to provide a comprehensive understanding of all relevant elements that have been influencing end prices of gasoline and diesel during last 8 years, understand their leverage and uncover which of those were the most important for this development. These are then researched using mainly graphical analysis and statistical tools. The delivery is that both prices of gasoline and diesel are highly correlated with the price development of crude oil and the prices of their respective commoditized barges expressed in the nominal value of CZK. It was also discovered that there are visible tendencies for asymmetrical pricing reaction and reaction lags, which could serve as a basis for a follow-up work. We also tried to examine the level in which Czech crown as a national currency provides cushion against up and down swings in commodity markets. Based on these findings several conclusive recommendations for relevant companies were built and delivered.

Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors

Ion Channel sensors have several applications including DNA sequencing, biothreat detection, and medical applications. Ion-channel sensors mimic the selective transport mechanism of cell membranes and can detect a wide range of analytes at the molecule level. Analytes are sensed through changes in signal patterns. Papers in the literature have described different methods for ion channel signal analysis. In this paper, we describe a series of new graphical tools for ion channel signal analysis which can be used for research and education. The paper focuses on the utility of this tools in biosensor classes. Teaching signal processing and machine learning for ion channel sensors is challenging because of the multidisciplinary content and student backgrounds which include physics, chemistry, biology and engineering. The paper describes graphical ion channel analysis tools developed for an on-line simulation environment called J-DSP. The tools are integrated and assessed in a graduate bio-sensor course through computer laboratory exercises.

Circular Economy and Industry 4.0 Technology Integration Framework for the Oil Palm Industry

Palm oil is a sustainable resource with high potential to substitute fossil fuels as the raw material for cleaner energy and chemical production. The oil palm industry is highly dependent on manual labour operation, especially its upstream operation, i.e., plantation. With the rapid development of process automation, robotic, internet-of-things (IoT) and big data analysis, adaptation of Industry Revolution 4.0 (IR4) has proven to be a great strategy to improve process efficiency. Each of the IR4 component/technology may be integrated for its specific feature, such as robotic drone with artificial intelligence data analysis to process captured image. Such technology could be further upgraded with more IR4 technologies integration. This paper proposes a novel circular economy framework to evaluate the potential of implementing IR4 technologies in the oil palm industry. Upon identify viable IR4 technologies for the industry, the cost of investment between the new and existing technologies were compared. Return on investment (ROI) and capital investment were used as the selection criteria to assist the palm oil stakeholders in the decision-making process. Graphical pinch analysis tool is adapted to identify an optimum solution. A case study involving oil palm plantation in Malaysia is analysed. An investment on spray drone for pesticide application was proven to have higher ROI, as compared to the spray tractor and existing practise of using knapsack sprayer. While another drone application for tree health and fruit monitoring has a positive ROI too, it is not possible to invest in both technologies due to budget limitation. Based on circular economy concept, investment into the spray drone and modified drone with smart spectrometer for tree health and fruit monitoring are better strategies to minimise IR4 investment.