Data Visualization System Research Articles

Поддержка принятия решения при выборе метода глобального освещения на основе кроссплатформенного приложения

Decision-making technology is considered on the example of developing a specialized DSS for developers of information visualization systems. An urgent task is to support the choice of a global illumination method from more than 60 existing ones. The formulation of this problem is based on the analysis of the subject area of global illumination methods and the accepted indicators for their evaluation. The simplest options for organizing a rational solution to the problem are given. The developed DSS is a desktop cross-platform software application based on the AvaloniaUI platform, which can be used as an example of typical solutions to such problems.

ADİL YARGILANMA HAKKI KAPSAMINDA SANIĞIN DURUŞMADA HAZIR BULUNMA HAKKI VE SEGBİS SİSTEMİ

Sanığın haklarını güvence altına alan en önemli haklardan birisi de adil yargılanma hakkıdır. Ulusal ve uluslararası mevzuata bakıldığında adil yargılanma hakkının birçok alt hak ve ilkeyi de içerisinde barındırdığı görülecektir. Avrupa İnsan Hakları Sözleşmesi ve Ceza Muhakemesi Kanunu’nda açıkça düzenlenmemişse de, bu haklardan birisi sanığın duruşmada hazır bulunma hakkıdır. Bununla birlikte gelişen teknoloji ve modernleşme sonucunda Sesli ve Görüntülü Bilişim Sistemi (SEGBİS) uygulamamıza girmiştir. Faydaları olduğu gibi sakıncalarının da olduğu belirtilen SEGBİS uygulaması ile yargılama yapılması zaman zaman eleştirilmektedir. Bu çalışmada da, sanığın duruşmada hazır bulunma hakkı ve SEGBİS sistemi arasındaki ilişki, adil yargılanma hakkı kapsamında, gerek uluslararası gerekse de ulusal mevzuat ve içtihatlar bakımından incelenmiş; doktrindeki görüşler, yargı kararları ve ulaşılan sonuçlar aktarılmaya çalışılmıştır.

The potential ecological risk assessment of soil heavy metals using self-organizing map

Heavy metal pollution control zoning aiming at the health maintenance of watershed soil ecosystem has become an important means of soil environmental protection and governance. Based on the self-organizing map (SOM), this study classifies the data sets of eight heavy metals such as Co, Cd, Zn, Cr, Cu, Pb, Ni, and Tl in 354 samples, calculates the potential ecological risk value of soil heavy metals in combination with the potential Hakansom Risk index (HRI), and uses the geographic information system (GIS) for visualization. In the research results, SOM has divided five soil ecological risk categories. The highest average ecological risk value of 85.95 is found in cluster IV, which is clustered and distributed in urban development areas in the upper reaches of the river. The average ecological risk values of cluster I and cluster V are relatively close at 79.64 and 79.19, respectively. Cluster I and cluster V are distributed in the north of the river in a linear and cluster manner, respectively, and are located on a concave bank with a relatively gentle slope. The average ecological risk of soil pollution in cluster II is 77.59, which is linearly distributed on both banks of the river. The ecological risk of soil pollution in cluster III is the lowest (74.39), mainly scattered in the south of rivers with less human activities. The study further identified the environmental factors that affect the soil ecological risk value in different cluster units and put forward the classified and differentiated management and control strategies for different cluster units. The research shows that SOM can cluster the data sets of heavy metals with high sensitivity and low threshold through competitive learning to effectively provide the distribution information of abnormal soil ecological risk areas. This information is helpful for urban environmental management departments and planning departments to take targeted management and recovery measures to avoid the health risks related to soil heavy metal pollution.

Advanced tools for guiding data‐led research processes of Upper‐Atmospheric phenomena

AbstractThis paper presents tools that help researchers implement the processes of data‐led studies of upper‐atmospheric phenomena. These tools were developed as a part of the activities of the Inter‐university Upper atmosphere Global Observation NETwork (IUGONET) of Japan, which is a project to develop infrastructure for upper‐atmospheric research data. This paper focuses on the data service named IUGONET Type‐A, which was launched in October 2016 and has since evolved. In addition to being a conventional metadata catalogue, it has many other useful functions: an easy cross‐searching system, a quick‐look data‐plotting procedure, an interactive data visualization system named UDAS web, and strong linkage with analysis software. Users can pick up relevant data from a huge number of data sets using either lists categorized by instruments/projects, observed regions and special campaigns or a world map of observatories. Users can quickly find the time, location and nature of phenomena that occurred by comparing the quick‐look plots of various data displayed by the browser. UDAS web allows researchers to interactively create stacked plots of various data types that can facilitate the understanding of the relationships among phenomena observed in different regions. Furthermore, it presents a command list for software dedicated to data analysis that can smoothly lead users to perform detailed analyses. IUGONET Type‐A provides a one‐stop data service that can assist users in searching, examining and comprehending data for advanced analysis. It is also capable of handling old data, including analogue data and written paper documents. Thus, it will provide useful support for innovative interdisciplinary scientific research on solar–terrestrial phenomena.

Level of motion sickness based on heart rate variability when reading inside a fully automated vehicle

This study investigates the level of experienced motion sickness when performing reading while being driven in fully automated driving under three different conditions. One condition was without any intervention while the other two conditions were with the visual (VPIS) and haptic (HPIS) peripheral information system. Both systems provided the upcoming navigational information in the lateral direction three seconds before the turning/cornering was done. It was hypothesized that with the peripheral information systems, the experienced motion sickness would be reduced compared to the condition where a peripheral information system was not present. Eighteen participants with severe motion sickness susceptibility were carefully chosen to undergo the conditions using an instrumented vehicle with the Wizard-of-Oz approach. The participants were required to read from a tablet during the whole 15-minutes of automated driving. Results from the heart rate variability (beats per minute, root means square of successive differences, and high-frequency component) indicated no statistically significant changes (p < 0.05) in motion sickness found with the presence of HPIS and VPIS when performing reading when being driven in automated mode. However, results from this study were mixed and inconclusive, but overall findings indicated mild motion sickness was found in both VPIS and HPIS conditions.

Facilitating the Use of Data From Multiple Sources for Formative Learning in the Context of Digital Assessments: Informing the Design and Development of Learning Analytic Dashboards

Learning analytic dashboards (LADs) are data visualization systems that use dynamic data in digital learning environments to provide students, teachers, and administrators with a wealth of information about student’s engagement, experiences, and performance on tasks. LADs have become increasingly popular, particularly in formative learning contexts, and help teachers make data-informed decisions about a student’s developing skills on a topic. LADs afford the possibility for teachers to obtain real-time data on student performance, response processes, and progress on academic learning tasks. However, data presented on LADs are often not based on an evaluation of stakeholder needs, and have been found to not be clearly interpretable and actionable for teachers to readily adapt their pedagogical actions based on these insights. We elaborate on how insights from research focused on interpretation and use of Score Reporting systems and research on open learner models (OLMs) can be used to inform a research agenda aimed at exploring the design and evaluation of LADs.

Digitally Optimizing the Information Flows Necessary to Manage Professional Athletes: A Case Study in Rugby Union.

Practical case studies elaborating end-to-end attempts to improve the quality of information flows associated with athlete management processes are scarce in the current sport literature. Therefore, guided by a Business Process Management (BPM) approach, the current study presents the outcomes from a case study to optimize the quality of strength and conditioning (S&C) information flow in the performance department of a professional rugby union club. Initially, the S&C information flow was redesigned using integral technology, activity elimination and activity automation redesign heuristics. Utilizing the Lean Startup framework, the redesigned information flow was digitally transformed by designing data collection, management and visualization systems. Statistical tests used to assess the usability of the data collection systems against industry benchmarks using the System Usability Scale (SUS) administered to 55 players highlighted that its usability (mean SUS score of 87.6 ± 10.76) was well above average industry benchmarks of similar systems (Grade A from SUS scale). In the data visualization system, 14 minor usability problems were identified from 9 cognitive walkthroughs conducted with the High-Performance Unit (HPU) staff. Pre-post optimization information quality was subjectively assessed by administering a standardized questionnaire to the HPU members. The results indicated positive improvements in all of the information quality dimensions (with major improvements to the accessibility) relating to the S&C information flow. Additionally, the methods utilized in the study would be especially beneficial for sporting environments requiring cost effective and easily adoptable information flow digitization initiatives which need to be implemented by its internal staff members.

SMART CAMPUS ELECTRICITY DATA VISUAL ANALYSIS SYSTEM

Abstract. Smart grid is the basic support of smart city development. The application of visual analytics to electricity system helps monitor and analyse the characteristic information in electricity data, which provides a strong guarantee for mastering the operation status of electricity system and achieving effective energy planning. However, as the complexity and size of electricity data continues to grow, it increases the burden on electricity workers to understand and analyse the electricity consumption situation. In response to these problems, a new type of electricity data visualisation and analysis system has been proposed, which enables interactive analysis of large amounts of electricity data. The system has the following advantages. First, A novel visualisation graphic has been designed and implemented to enable electricity workers to visualise a comprehensive picture of electricity consumption at different granularities. Second, designing appropriate visualisations to highlight the characteristics of the data itself, depending on the specific needs and type of data. Finally, the system provides a set of coupled visual views and interactions to support system users to freely explore the campus electricity situation from multiple scales.

Application for polymer industry to hold nearly 40% of the bio-based platform chemicals market; demand to grow by 8% CAGR through 2031

Today, more leaders, managers, and directors can decide, even though they cannot decide for every situation. When decisions are scattered and unstructured, decisions become complicated and so that a single decision-maker based on expertise alone cannot address them adequately. This research proposes the Electronic Decision System (EDS) for effective data visualization and analysis process. EDS helps to decide during a complicated situation using Big Data Analytics-based Artificial Neural Network Framework (BDA-ANNF). The BDA-ANNF collects and analyses the data provided, and Artificial Neural Network (ANN) is used to predict and take accurate decisions in every complicated situation. These systems allow decision-makers to understand the market, direct and indirect climate, analyze the numerous trade-offs in the sector, evaluate costs linked to the various choices for decision-making, and eventually help people improve their decision-making outcome. EDS's approaches and techniques share one key challenge that must successfully provide consumers and policymakers with an appropriate and understandable simulation solution. The finding indicates that the BDA-ANNF decides the complicated situation up to the accuracy rate of 95.23%, which is not attainable by existing methods, and the error rate is 4.77%.

Smart System Using Lora Technology to Connect Rural Areas Underserved By Existing Internet and Telecommunication Technologies

LoRa, Sigfox, and Narrowband-Internet of Things (NB-IoT) are some of the long-distance, low-power wireless communication technologies developed in the recent past. The proposed system consists of mainly nodes and a gateway as the fundamental system architecture. Nodes only communicate with the gateway individually and the gateway communicates with all the nodes separately and wirelessly. System in this proposed study, uses long range low power RF wireless communication technique for primary data communication, where an Internet connection will not be required for the communication between the gateway and the nodes. Any number of nodes can be paired with the gateway, and the gateway can individually communicate with each and every node. Furthermore, gateways have the ability of storing real-time data. Due to its unique design, the proposed system in this study, can achieve addressable, bidirectional, and continuous data communication even without the Internet connection. The bidirectional communication design of this proposed system facilitates real time and uninterrupted simultaneous handling of monitoring/sensor devices and controller devices without the need of a separate controlling system. As this system consists of those unique features, it is recommended to use in the rural areas underserved by current internet and telecommunication technologies. With the in-built option to get connected to the Internet, this system can be further expanded to an IoT based addressable data communication, processing, and visualization systems by eliminating the major technical problems in typical IoT systems such as interrupted communication and data losses during an Internet connection failure, power concerns and customization issues.

Real-time molecular imaging of near-surface tissue using Raman spectroscopy

The steady progress in medical diagnosis and treatment of diseases largely hinges on the steady development and improvement of modern imaging modalities. Raman spectroscopy has attracted increasing attention for clinical applications as it is label-free, non-invasive, and delivers molecular fingerprinting information of a sample. In combination with fiber optic probes, it also allows easy access to different body parts of a patient. However, image acquisition with fiber optic probes is currently not possible. Here, we introduce a fiber optic probe-based Raman imaging system for the real-time molecular virtual reality data visualization of chemical boundaries on a computer screen and the physical world. The approach is developed around a computer vision-based positional tracking system in conjunction with photometric stereo and augmented and mixed chemical reality, enabling molecular imaging and direct visualization of molecular boundaries of three-dimensional surfaces. The proposed approach achieves a spatial resolution of 0.5 mm in the transverse plane and a topology resolution of 0.6 mm, with a spectral sampling frequency of 10 Hz, and can be used to image large tissue areas in a few minutes, making it highly suitable for clinical tissue-boundary demarcation. A variety of applications on biological samples, i.e., distribution of pharmaceutical compounds, brain-tumor phantom, and various types of sarcoma have been characterized, showing that the system enables rapid and intuitive assessment of molecular boundaries.

Reliable e-nose for air toxicity monitoring by filter diagonalization method

This paper introduces a compact, affordable electronic nose (e-nose) device devoted to detect the presence of toxic compounds that could affect human health, such as carbon monoxide, combustible gas, hydrogen, methane, and smoke, among others. Such artificial olfaction device consists of an array of six metal oxide semiconductor (MOS) sensors and a computer-based information system for signal acquisition, processing, and visualization. This study further proposes the use of the filter diagonalization method (FDM) to extract the spectral contents of the signals obtained from the sensors. Preliminary results show that the prototype is functional and that the FDM approach is suitable for a later classification stage. Example deployment scenarios of the proposed e-nose include indoor facilities (buildings and warehouses), compromised air quality places (mines and sanitary landfills), public transportation, mobile robots, and wireless sensor networks.

Evaluation of the Effective Cognition Area (ECA) of Signage Systems with Backlighting under Smoke Conditions

Signage systems are visual information systems that indicate the direction, allow for identification, and show safety information and regulations to occupants via graphics or text during emergencies. Wayfinding is difficult in large and complex buildings, such as large shopping malls. Occupants can be disoriented while searching for their way in such buildings. This problem can be more serious in emergency situations, such as fires, than in normal situations. Signage systems can be helpful in solving this problem. Domestic and overseas standards on emergency signage systems specify that the signage should be noticeable, easy to read, and easy to understand. However, most regulations do not quantify the effectiveness of such signage systems under emergency situations. To address these issues, in this study, several experiments were conducted considering the viewing distance and angle using a backlit signage system, and changes in cognition under smoke conditions were analyzed. First, the concept of effective cognition area (ECA) was introduced to analyze the relationship between the viewing distance and angle. Experiments were conducted using a backlit emergency exit sign, and the changes in the ECA in a smoke situation were analyzed. Finally, the results of this study were compared with those of previous studies. Furthermore, the extent to which occupants can recognize the signage system was quantified. If the concept of ECA developed in this study is applied to the development of emergency signage design, more diverse evacuation scenarios could be designed.

Practice of Air Environment Quality Monitoring Data Visualization Technology Based on Adaptive Wireless Sensor Networks

This paper begins by outlining the evolution and current state of traditional wireless sensor networks, followed by an examination of the principle and architecture of wireless sensor networks, as well as the challenges that traditional wireless sensor networks face in environmental monitoring. This paper designs and develops a data visualization system for wireless sensor networks based on the visualization system and the advantages of other visualization systems, after analyzing and comparing the current visualization systems for monitoring wireless sensor networks. A real-time monitoring system for urban air quality based on wireless sensor network is designed to solve the problem that the traditional method of combining manual sampling with laboratory analysis for air quality monitoring is expensive and cannot carry out real-time online monitoring for multiple points at the same time. The system’s implementation is based primarily on air quality monitoring data collected in the Shenyang area for visual display and analysis. The air quality monitoring system proposed in this paper has a complete structure and independent modules and is simple to use. The dynamic adaptability of the monitoring system is greatly improved by utilizing the self-adaptability and self-organization of wireless sensor networks, which brings great convenience to air quality monitoring.

Research on electronic decision system for effective data visualization and analysis process

Today, more leaders, managers, and directors can decide, even though they cannot decide for every situation. When decisions are scattered and unstructured, decisions become complicated and so that a single decision-maker based on expertise alone cannot address them adequately. This research proposes the Electronic Decision System (EDS) for effective data visualization and analysis process. EDS helps to decide during a complicated situation using Big Data Analytics-based Artificial Neural Network Framework (BDA-ANNF). The BDA-ANNF collects and analyses the data provided, and Artificial Neural Network (ANN) is used to predict and take accurate decisions in every complicated situation. These systems allow decision-makers to understand the market, direct and indirect climate, analyze the numerous trade-offs in the sector, evaluate costs linked to the various choices for decision-making, and eventually help people improve their decision-making outcome. EDS's approaches and techniques share one key challenge that must successfully provide consumers and policymakers with an appropriate and understandable simulation solution. The finding indicates that the BDA-ANNF decides the complicated situation up to the accuracy rate of 95.23%, which is not attainable by existing methods, and the error rate is 4.77%.

Spatially resolved transcriptomics in immersive environments

Spatially resolved transcriptomics is an emerging class of high-throughput technologies that enable biologists to systematically investigate the expression of genes along with spatial information. Upon data acquisition, one major hurdle is the subsequent interpretation and visualization of the datasets acquired. To address this challenge, VR-Cardiomicsis presented, which is a novel data visualization system with interactive functionalities designed to help biologists interpret spatially resolved transcriptomic datasets. By implementing the system in two separate immersive environments, fish tank virtual reality (FTVR) and head-mounted display virtual reality (HMD-VR), biologists can interact with the data in novel ways not previously possible, such as visually exploring the gene expression patterns of an organ, and comparing genes based on their 3D expression profiles. Further, a biologist-driven use-case is presented, in which immersive environments facilitate biologists to explore and compare the heart expression profiles of different genes.

Dynamic and spatial variables in data visualization systems

Jacques Bertin’s groundbreaking work, Sémiologie Graphique, has remained definitive for the more than half a century since its initial publication (1967). His formal description of graphic variables is fundamental for information design because it offers a way to understand how visual entities can be used to create a semiotic system with clear and distinct categories. According to Bertin, color, texture, value, pattern, shape, position, and orientation can each be assigned a specific role within a signifying system in accord with logical rules of representation. However, given the technology of the time in which Bertin was writing, features of dynamic display were not included in his discussion. These include elements of animation (such as direction, speed, acceleration, transformation, and rate of change) as well as some features of perspectival and spatial systems (including point of view, scale, projection, folding) that did exist but were not much used. The critical question is whether these graphical features can be formalized to the same degree as Bertin’s seven graphic variables, andincluded within the operation of semiotic systems. While these variables are not associated with fixed values any more than Bertin’s original ones, their use in information display suggests that they would benefit from the same kind of descriptive analysis he applied to static ones. This paper describes dynamic and spatial variables, offers some preliminary thoughts about their specific contribution to visualization of big data, and addresses the way they produce meaning within a graphical semiotic system.

РАЗРАБОТКА ЭЛЕМЕНТОВ SCADA-СИСТЕМЫ ФОРМИРОВАНИЯ БУМАЖНОГО ПОЛОТНА ДЛЯ ДИНАМИЧЕСКОЙ ВИЗУАЛИЗАЦИИ ДАННЫХ

Nowadays the introduction of intelligent technologies is closely connected with the development of modern information and control systems. Modern SCADA systems are an enabling technology for monitoring and control of dynamic systems in many industries. The article describes the main functions and features of SCADA systems and their typical structure. Italso deals with the important network technologies in systems controlled by SCADA systems and their application. The analysis shows that an integrated SCADA system into automated control systems is the basis for ensuring high economic performance of an enterprise. Based on DataRate the SCADA system elements were developed to control the paper web casting system as part of a large industrial automated control system for dynamic data visualization. An algorithm of interaction and data transfer between elements of a virtual system using the Matrikon OPC software package is described. The use of the DataRate system for visualizing the results of the Simulink-model in forming the mass of the paper web is substantiated.

Анализ показателей противодефляционной эффективности полезащитных лесных насаждений в засушливой зоне Cтавропольского края

The problem of soil degradation is widespread in many agricultural regions of our country. The Stavropol Territory, as one of the leading agricultural regions, is no exception. It is characterized by the presence of a number of factors influencing the destructive processes in the soil, the main of which are the increase in the anthropogenic load on the soil and the regional features of climate change. In this regard, the relevance of issues related to the development of comprehensive measures to combat degradation processes is increasing every year. A key element of these activities in the Stavropol Territory is the formation of a framework of protective forest plantations, which requires regular monitoring of both their safety and effectiveness. The study was conducted on the territory of the arid zone of the Stavropol Territory. In this zone, the observed regional climatic changes can cause significant damage to the soil cover and significantly reduce the efficiency of agricultural production. Here, the increase in climate extremeness is most acute—an increase in the likelihood of droughts and heavy rainfall. Due to the fact that protective forest plantations are located on vast areas, it is most rational to use modern data processing and visualization systems for their monitoring—geographic information systems and Earth remote sensing data. The author’s technique was considered in the work, which allows analyzing various characteristics for assessing the anti-deflation efficiency of field-protective forest plantations, such as the protective forest cover of the territory and interstrip distances. As part of the study, a technological mapping scheme was proposed based on the formation of a continuous hexagonal surface with data. The presented methodology and technological scheme can be adapted for any agricultural region, taking into account their characteristics.

Design of monitoring data visualization system of water resources based on J2EE architecture

Design of monitoring data visualization system of water resources based on J2EE architecture