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Process monitoring systems, e.g., systems based on photodiodes, could be used in laser-based powder bed fusion (PBF-LB/M) to measure various process parameters and process signatures to eventually allow for a local, detailed analysis of the produced parts. Here, simple statements only concerning the occurrence of defects in parts are sufficient in many cases, especially with respect to industrial application. Therefore, a pragmatic approach to rapidly infer the occurrence of defects and their types based on in situ data obtained by commercially available process monitoring systems is introduced. In this approach, a color distribution in form of a histogram is determined for each produced part using layer-wise screenshots of the visualized data provided by the monitoring software. Assessment of the histograms of AlSi10Mg samples, which were processed with different parameter combinations, revealed characteristics depending on the prevailing defect types. These characteristics enable the prediction of the occurring defect types without the necessity to apply conventional downstream testing methods, and thus, a straightforward separation of parts with good quality from defective components. Since the approach presented uses the data visualization of the monitoring software, it can be used even when direct access to the raw data is not provided by the machine manufacturer. [ABSTRACT FROM AUTHOR]

This article explores the benefits and challenges of conducting pragmatic trials using electronic health records (EHRs). Pragmatic trials are crucial for informing clinical practice when there is limited data available. EHRs offer advantages such as accessibility and the ability to enroll large numbers of patients quickly. However, there are unique challenges in conducting EHR-enabled trials, including potential biases and contamination of treatment groups. Real-time monitoring of enrollment and safety events is also difficult. Despite these challenges, EHR-enabled trials have shown promising results in various fields. The article emphasizes the importance of careful planning, monitoring, and validation of data in EHR-enabled trials to ensure accurate and reliable results. It also discusses the potential benefits and limitations of EHR-enabled trials in improving patient care. [Extracted from the article]

• 9080 articles on electrochemical remediation were extracted from Web of Science. • The number of articles on electrochemical remediation began to increase greatly since 2007. • Electro-Fenton has advantages in synergistic effects of anodic oxidation and electro-adsorption. • Adsorption, oxidation and reduction are the major drivers of electrochemical remediation. • The topics "Advanced oxidation process" and "Nanocomposite" are in full swing. Electrochemical methods are increasingly favored for remediating polluted environments due to their environmental compatibility and reagent-saving features. However, a comprehensive understanding of recent progress, mechanisms, and trends in these methods is currently lacking. Web of Science (WoS) databases were utilized for searching the primary data to understand the knowledge structure and research trends of publications on electrochemical methods and to unveil certain hotspots and future trends of electrochemical methods research. The original data were sampled from 9080 publications in those databases with the search deadline of June 1st, 2022. CiteSpace and VOSviewer software facilitated data visualization and analysis of document quantities, source journals, institutions, authors, and keywords. We discussed principles, influencing factors, and progress related to seven major electrochemical methods. Notably, publications on this subject have experienced significant growth since 2007. The most frequently-investigated areas in electrochemical methods included novel materials development, heavy metal remediation, organic pollutant degradation, and removal mechanism identification. "Advanced oxidation process" and "Nanocomposite" are currently trending topics. The major remediation mechanisms are adsorption, oxidation, and reduction. The efficiency of electrochemical systems is influenced by material properties, system configuration, electron transfer efficiency, and power density. Electro-Fenton exhibits significant advantages in achieving synergistic effects of anodic oxidation and electro-adsorption among the seven techniques. Future research should prioritize the improvement of electron transfer efficiency, the optimization of electrode materials, the exploration of emerging technology coupling, and the reduction in system operation and maintenance costs. [Display omitted] [ABSTRACT FROM AUTHOR]

This article discusses the importance of data visuals in public health research and practice. Data visuals, such as infographics and scientific visualizations, are powerful tools for conveying information and promoting understanding. However, it is crucial for public health professionals to ensure that their visuals are clear, intuitive, and trustworthy. The article introduces a set of principles for creating effective data visuals, including evidence, efficiency, emphasis, and ethics. It also explores the limits and biases of human perception and the application of Gestalt principles in data visualization. The article concludes by introducing a new article format called Visual Brief, which combines data-driven images with supportive narratives to present key points to readers. [Extracted from the article]

Copyright of Journal of Computer Science & Technology (JOCSTEC) is the property of PT. Padang Tekno Corp and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The participation of women in sports and the management of women's sports teams have gained significant attention in recent years, underscoring the need to understand the dynamics and organizational aspects of women's sports. However, there is a noticeable lack of comprehensive bibliometric analyses in this domain, hindering a thorough exploration of the existing literature and the identification of key trends and knowledge gaps. This study aims to address this gap by conducting a rigorous bibliometric analysis of sports management competencies in women's semi-professional teams in Europe. Using the VOSviewer software, advanced data analysis techniques, including citation and co-citation analysis, were employed to gain insights into the research landscape, influential authors, seminal papers, and key research trends. The results of the analysis revealed clusters of research topics related to women's semi-professional sports, including performance, gender, football, and sports. The findings of this analysis will contribute to the advancement and success of women's semi-professional teams by informing the development of tailored training programs, educational curricula, and professional initiatives for sports management roles. Ultimately, this study aims to enhance the understanding of sports management competencies in women's semi-professional teams and guide future research endeavors in this area. [ABSTRACT FROM AUTHOR]

The landscape environment of urban blocks plays a significant role in improving the comfort of urban thermal environment and promoting green and high-quality development. The 342 papers related to the research on the impact of urban block landscape environment on thermal comfort in China, collected by CNKI (China National Knowledge Infrastructure) from 2002 to 2022, are used as the research object. Through bibliometric statistical analysis, LLR algorithm, and cluster analysis, the current research status of the impact of urban block landscape environment on thermal comfort in China is analyzed and processed, and its external characteristics are identified. Using the information visualization software CiteSpace, the research topics in the field of the impact of urban block landscape environment on thermal comfort are presented in the form of knowledge graphs. Through co-occurrence analysis of keywords and trend of word frequency changes, the development trends of research hotspots and cutting-edge fields of the impact of urban block landscape environment on thermal comfort are determined, hoping to provide reference for future research in this field. [ABSTRACT FROM AUTHOR]

This document offers guidance for reviewing educational case studies for the International Accounting Education (IAE) journal. It explains that reviewing a case study for IAE is different from reviewing other types of papers and outlines the three parts of a case study: the case, the case learning objectives and implementation guidance (CLOIG), and the teaching notes. The document provides specific guidance on assessing the case's contribution, execution problems, adoption by nonauthor faculty, and exposition. The goal of IAE is to publish well-developed cases that are useful to accounting instructors and students. Reviewers are encouraged to provide constructive criticism and suggestions for improvement, and faculty unfamiliar with educational cases are advised to read published cases to understand the format and content. [Extracted from the article]

Employers expect graduates to perform data analytics using both organizational and publicly available data. Interestingly, few teaching cases provide students with needed exposure to data analytics in managerial or governmental accounting. In this case, students assume the role of a managerial accountant employed at Municipal Consulting, LLC. Students assist the Police Commissioner in using a Balanced Scorecard approach to analyze how her department responds to crime patterns and to develop next year's budget. This case requires students to critique, analyze, and evaluate Internal Business Process Perspective Balanced Scorecard measures supported by publicly available data using data visualization software. The case includes instructions for both Tableau and Power BI. The case covers three skills: (1) extract, transform, and load data; (2) develop data visualization software experience; and (3) analyze data. The case is designed for senior level undergraduate and graduate courses in managerial, data analytics, and governmental accounting. [ABSTRACT FROM AUTHOR]

The article focuses on strategies to reduce traffic fatalities and move toward zero deaths on roadways. Topics discussed include the need for reorganization of zero fatality programs, adopting positive cultural frameworks for traffic safety, and using a systemic/proactive lens to analyze crash data to identify risk factors and implement systemic safety improvements.

Highly stretchable and robust strain sensors are rapidly emerging as promising candidates for a diverse of wearable electronics. The main challenge for the practical application of wearable electronics is the energy consumption and device aging. Energy consumption mainly depends on the conductivity of the sensor, and it is a key factor in determining device aging. Here, we design a liquid metal (LM)‐embedded hydrogel as a sensing material to overcome the barrier of energy consumption and device aging of wearable electronics. The sensing material simultaneously exhibits high conductivity (up to 22 S m−1), low elastic modulus (23 kPa), and ultrahigh stretchability (1500%) with excellent robustness (consistent performance against 12 000 mechanical cycling). A motion monitoring system is composed of intrinsically soft LM‐embedded hydrogel as sensing material, a microcontroller, signal‐processing circuits, Bluetooth transceiver, and self‐organizing map developed software for the visualization of multi‐dimensional data. This system integrating multiple functions including signal conditioning, processing, and wireless transmission achieves monitor hand gesture as well as sign‐to‐verbal translation. This approach provides an ideal strategy for deaf‐mute communicating with normal people and broadens the application of wearable electronics. [ABSTRACT FROM AUTHOR]

This article discusses laparoscopic ventral mesh rectopexy (LVMR) as a treatment for recurrent full-thickness rectal prolapse after a failed Altemeier operation. LVMR has become the gold standard procedure for rectal prolapse and has shown favorable outcomes in treating various defecation problems. The article presents a case study of a 56-year-old female patient who underwent LVMR after experiencing faecal incontinence caused by rectal prolapse. The procedure was successful, and the patient reported normal stool passage with no rectal prolapse after four weeks. The authors note that determining the selection criteria for conservative or surgical treatment remains a clinical challenge. [Extracted from the article]

Bioretention is a typical low impact development (LID) practice that helps reduce peak urban stormwater runoff and runoff pollutant concentrations (e.g., heavy metals, suspended solids, organic pollutants), which has become an important part of urban stormwater management over the past 15 years. To understand the research hotspots and frontiers in the field of bioretention facility research and provide a reference for research into bioretention facilities, we conduct a statistical analysis of global bioretention literature published during 2007–2021 using the Web of Science core database and the data visualization and analysis software VOSviewer and HistCite. The number of published articles related to bioretention facilities shows a rising trend over the study period, with research from China contributing greatly to global research on bioretention facilities. However, the influence of articles needs to be increased. Recent studies mainly focus on the hydrologic effect and water purification effect of bioretention facilities and on the removal of nitrogen and phosphorus nutrients from runoff rainwater. Further studies should focus on the interaction of fillers, microorganisms, and plants in bioretention facilities and its impact on the migration, transformation, and concentrations of nitrogen and phosphorus; the purification effect and mechanism of specific emerging contaminants in runoff; the selection and configuration optimization of filler materials and plant species; and the optimization of the design parameters of the model for bioretention systems. [ABSTRACT FROM AUTHOR]

Radiation dose tracking is becoming very important due to the popularity of computerized tomography (CT) scans. One of the challenges of radiation dose tracking is that there are several variables that affect the dose from the patient side, machine side, and procedures side. Although some tracking software programs exists, they are based on static analysis and cause integration errors due to the heterogeneity of Hospital Information Systems (HISs) and prevent users from obtaining accurate answers to their questions. In this paper, a visual analytic approach is utilized to track radiation dose data from computed tomography (CT) through the use of Tableau data visualization software. The web solution is evaluated in real-life scenarios by domain experts. The results show that the visual analytics approach improves the tracking process, as users completed the tasks with a 100% success rate. The process increased user satisfaction and also provided invaluable insight into the analytical process. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Ordnance Equipment Engineering is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recent advances in training monitoring are centered on the statistical indicators of the concentric phase of the movement. However, those studies lack consideration of the integrity of the movement. Moreover, training performance evaluation needs valid data on the movement. Thus, this study presents a full-waveform resistance training monitoring system (FRTMS) as a whole-movement-process monitoring solution to acquire and analyze the full-waveform data of resistance training. The FRTMS includes a portable data acquisition device and a data processing and visualization software platform. The data acquisition device monitors the barbell's movement data. The software platform guides users through the acquisition of training parameters and provides feedback on the training result variables. To validate the FRTMS, we compared the simultaneous measurements of 30–90% 1RM of Smith squat lifts performed by 21 subjects with the FRTMS to similar measurements obtained with a previously validated three-dimensional motion capture system. Results showed that the FRTMS produced practically identical velocity outcomes, with a high Pearson's correlation coefficient, intraclass correlation coefficient, and coefficient of multiple correlations and a low root mean square error. We also studied the applications of the FRTMS in practical training by comparing the training results of a six-week experimental intervention with velocity-based training (VBT) and percentage-based training (PBT). The current findings suggest that the proposed monitoring system can provide reliable data for refining future training monitoring and analysis. [ABSTRACT FROM AUTHOR]

Archaeological investigation of the dentoalveolar complex in situ within a human skull requires detailed measurements using non‐invasive techniques. Standard macroscopic and radiographic methods have limitations but large volume micro‐computed tomography (LV micro‐CT) scanning has the potential to acquire data at high resolution in microns. In this study, archaeological specimens are analyzed using three‐dimensional data visualization software from LV micro‐CT scans with the aims of (1) determining whether LV micro‐CT can act as a single technique to provide detailed analysis of the dentoalveolar complex and (2) how findings from the LV micro‐CT technique compare with standard methods. These aims are explored by measuring a range of human skull specimens from a rare archaeological sample requiring non‐invasive methods, for multiple dental and alveolar bone health categories. The LV micro‐CT technique was the only method to provide a full range of detailed measurements across all categories studied. A combination of macroscopic and radiographic techniques covered a number of categories, but the use of multiple methods was more time consuming, did not provide the same level of accuracy, and did not include all measurements. There were high levels of reproducibility for intra‐operator scoring and good inter‐operator agreement from four operators with one operator whose results were outliers. As a further investigation of the potential of the LV micro‐CT technique, an additional individual, a fragile, fragmented skull of an infant was studied. This investigation confirms the value of LV micro‐CT scanning as a non‐invasive, accurate, single technique for the extensive analysis of the dentoalveolar complex within archaeological skulls, which also allows the relationship of different tissues to be studied in situ. [ABSTRACT FROM AUTHOR]

Background: As the number of tumor cases significantly increases, so does the quantity of tumor data. The mining and application of large-scale data have promoted the development of tumor big data. Among them, the visualization methods of tumor big data can well show the key information in a large volume of data and facilitate the human brain to receive information. Therefore, tumor big data visualization methods are a key part of the development of tumor big data. Process: This paper first summarizes the connotation, sources, characteristics, and applications of tumor big data, and expounds the current research status of tumor big data visualization at home and abroad. Then, this paper focuses on four mainstream visualization presentation methods of tumor big data, namely the visualization of tumor spatiotemporal data, the visualization of tumor hierarchy and network data, the visualization of tumor text data, and the visualization of multidimensional tumor data, and gives specific application scenarios. After this, the paper introduces the advantages, disadvantages, and scope of the use of five data visualization websites and software that can be easily obtained by readers. Finally, this paper analyzes the problems existing in tumor big data visualization, summarizes the visualization methods, and proposes the future of tumor big data visualization. [ABSTRACT FROM AUTHOR]

The HEPS beamline software group is dedicated to the development, operation, and maintenance of unified experimental control and data acquisition software framework (Mamba, Figure 9) for high-throughput, multimodal, ultrafast, in-situ and dynamic experiments at HEPS. The High Energy Photon Source (HEPS) is a greenfield 4th-generation light source. HEPS Computing and Communication Group (HEPS-CC), provides the IT R&D and services for the facility and science communities, including IT infrastructure, network, computing, analysis software, data preservation and management, and public services. [Extracted from the article]

Academic libraries are a vital space for collaboration, socialization, research, and quiet study. To support these needs, they must offer a variety of environments, noise levels, and furniture to support varying student needs. However, it can be difficult to understand these specific needs and properly balance the types of spaces and seating alternatives to optimally meet them. This article describes a space usage study undertaken to determine patron needs and preferences and the resulting visualization of the data using Tableau Public. The project provided important insights into patron space preferences and use, and the methodology can be replicated at other institutions. [ABSTRACT FROM AUTHOR]

This article discusses the use of neoadjuvant immunotherapy as a treatment option for locally advanced microsatellite instability high/deficient mismatch repair transverse colon cancer. The authors present a case study of a 33-year-old woman who underwent laparoscopic complete mesocolic excision after receiving neoadjuvant immunotherapy. The surgery was successful, with a short operating time and minimal blood loss. The authors declare no conflicts of interest and state that the data supporting their findings are available upon request. [Extracted from the article]

The concept of carbon neutrality has been promoted and implemented in increasing countries since the twenty-first century. In-depth research on carbon neutrality has helped improve the environmental conditions and played a particular role in sustaining economic and social development. However, there is a less comprehensive review of the status in this field; therefore, this article uses the information visualization software CiteSpace to thoroughly analyze carbon neutrality research from multiple perspectives. This study aims to reveal the current research evolutions and hotspots in this field, predict future research trends, and construct the framework for better understanding. The results find that the number of papers published on carbon neutrality keeps increasing annually, and carbon neutrality has been the widely participated domain. In addition, publications by organizations and in top journals have aroused wide attention, and the hot spots on carbon neutrality have shifted to policy, recovery, and efficiency. Based on the results, a knowledge framework of this domain is constructed to give readers a clearer understanding of the evolvement and trends, which will also provide targeted references and help for future researchers. [ABSTRACT FROM AUTHOR]

The practice of review writing is an essential component of postgraduate students' academic studies for graduation requirement and especially for those who are undergoing their postgraduate studies by theses by publication. However, very few studies have focused on review genres. In this review, the researchers would like to offer an overview of different types of review articles and identify the trend in the development of the review article genre. The researchers of this study employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. They identified the published articles specific to the review genres via a structured keyword search in Web of Science, Scopus, and Google Scholar (from the years 2019–2022). A mixed analysis approach (e.g., qualitative analysis combined with quantitative analysis) was conducted to further examine the selected articles using the data visualization software CiteSpace. The results showcased that there were currently a limited number of review types in social science disciplines. The researchers call for more effort to discover new models for writing review genres in the EFL/ESL context. This study also discusses the theoretical and practical implications. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Forensic Medicine / Fayixue Zazhi is the property of Journal of Forensic Medicine Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Intracranial EEG data offer a unique spatio-temporal precision to investigate human brain functions. Large datasets have become recently accessible thanks to new iEEG data-sharing practices and tighter collaboration with clinicians. Yet, the complexity of such datasets poses new challenges, especially regarding the visualization and anatomical display of iEEG. We introduce HiBoP, a multi-modal visualization software specifically designed for large groups of patients and multiple experiments. Its main features include the dynamic display of iEEG responses induced by tasks/stimulations, the definition of Regions and electrodes Of Interest, and the shift between group-level and individual-level 3D anatomo-functional data. We provide a use-case with data from 36 patients to reveal the global cortical dynamics following tactile stimulation. We used HiBoP to visualize high-gamma responses [50–150 Hz], and define three major response components in primary somatosensory and premotor cortices and parietal operculum. Several iEEG softwares are now publicly available with outstanding analysis features. Yet, most were developed in languages (Python/Matlab) chosen to facilitate the inclusion of new analysis by users, rather than the quality of the visualization. HiBoP represents a visualization tool developed with videogame standards (Unity/C#), and performs detailed anatomical analysis rapidly, across multiple conditions, patients, and modalities with an easy export toward third-party softwares. HiBoP provides a user-friendly environment that greatly facilitates the exploration of large iEEG datasets, and helps users decipher subtle structure/function relationships. • We developed HiBoP, a Unity-based software for iEEG data visualization. • HiBoP facilitates navigation across individual patient and population levels. • HiBoP integrates time series, CCEPs and multimodal data in the same project. [ABSTRACT FROM AUTHOR]

Aims: This study aimed to conduct a bibliometric analysis of the relevant literature on the diagnosis of inflammatory bowel disease (IBD), and show its current status, hot spots, and development trends. Methods: The literature on IBD diagnosis was acquired from the Science Citation Index Expanded of the Web of Science Core Collection. Cooccurrence and cooperation relationship analysis of authors, institutions, countries, journals, references, and keywords in the literature were carried out through CiteSpace software and the Online Analysis platform of Literature Metrology. At the same time, the relevant knowledge maps were drawn, and the keywords cluster analysis and emergence analysis were performed. Results: 14,742 related articles were included, showing that the number of articles in this field has increased in recent years. The results showed that PEYRIN-BIROULET L from the University Hospital of Nancy-Brabois was the author with the most cumulative number of articles. The institution with the most articles was Mayo Clin, and the United States was far ahead in the article output and had a dominant role. Keywords analysis showed that there was a total of 818 keywords, which were mainly focused on the research of related diseases caused or coexisted by IBD, such as colorectal cancer and autoimmune diseases, and the diagnosis and treatment methods of IBD. Emerging analysis showed that future research hotspots and trends might be the treatment of IBD and precision medicine. Conclusion: This research was the first bibliometric analysis of publications in the field of IBD diagnosis using visualization software and data information mining, and obtained the current status, hotspots, and development of this field. The future research hotspot might be the precision medicine of IBD, and the mechanism needed to be explored in depth to provide a theoretical basis for its clinical application. [ABSTRACT FROM AUTHOR]

In recent years, studies have been conducted to quantify the relationship between microeconomic and macroeconomic development. Macroeconomics is the orientation of microeconomic development. Existing research hopes to quantify the relationship between macroeconomics and micro-firms, rather than just focusing on economic indicators. And some empirical studies try to use the relationship between them to discuss its usefulness for micro-firm decision-making. This article focuses on applying and developing aggregate earnings in connecting microenterprise earnings and macroeconomic development. To achieve this goal, this research did a comprehensive bibliometric analysis on macro-accounting on the two most influential databases, namely, Web of Science and Scopus. It used the information visualization software VOSviewer to draw knowledge maps to sort research lines. We also analyzed the research hotspots of macro-accounting in recent years according to the year scale and combined it with the neural network PSO-LSTM model to predict their future development. It turns out that the research on aggregate earnings related to economic growth has become a research hotspot in recent years. Scopus research and development potential is better than Web of Science in this field. [ABSTRACT FROM AUTHOR]

Objective To analyze the research status of forensic medicine in China from 2010 to 2019, obtain the development trend of forensic medicine and explore the hotspots and research frontiers. Methods The forensic medical academic papers published on China National Knowledge Infrastructure (CNKI) database from 2010 to 2019 were collected. CiteSpace 5.7. R1, an information visualization analysis software, was used to analyze publication organizations, authors, keywords, and other elements. Results The majority of the research institutions were universities, provincial and ministerial scientific research and forensic institutions. Forensic pathology was still an important branch of forensic medicine and a popular research direction. The"polymorphism"and"Y chromosome"had been the research hotspots in recent years."Medical damage"and"standard"were the most novel studies. Conclusion In order to provide scientific basis and research direction for forensic research, this paper analyzes the cooperation network, research hotspots and research innovation in forensic research. [ABSTRACT FROM AUTHOR]

The article discusses the implementation of the Spartan Experience Record (SER) at Michigan State University (MSU), which provides undergraduate students with a formal record of their co-curricular learning accomplishments. The SER aims to create a comprehensive dataset on what students learn in these co-curricular opportunities. To make the data more accessible, data visualization dashboards were created. The article offers key considerations for building data visualizations that support student learning outcomes and assessment goals. The challenges of customization in creating the dashboards are also discussed. Overall, the SER and data visualizations contribute to tracking and understanding the impact of co-curricular engagement on student success. [Extracted from the article]

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Since 2006, the Bonneville Power Administration (BPA) Technology Innovation (TI) Office has applied roadmapping processes to help articulate the federal wholesale electric utility's technology research agenda. The TI Office team has evolved its tools, templates, and process steps considerably over the years in response to implementation challenges, shortcomings in deliverables derived from the process, and maturation opportunities enabled by data management and visualization software. Practioners within the TI Office have sustained their commitment to roadmapping during an era of significant evolution of the practice within industry and academia. The practice came out of product manufacturing environments in the 1960s, 1970s, and 1980s. Increasingly since the early 2000s, roadmapping has been applied outside this “traditional” realm, requiring trial, iteration, and customization of processes, tools, and deliverables to meet different requirements. The TI Office's use of roadmapping is one “nontraditional” variant because the agency is not in the business of generating profits by creating products in response to market demands. Instead, the TI Office has used roadmapping to communicate the agency's technology research, development, and demonstration agenda to the broader community—national laboratories, universities, manufacturers, etc.—so these external organizations can respond with proposals delivering products with the desired technology characteristics. These products, in turn, enable BPA to continue to fulfill its public service mission as an electric utility and government entity in providing safe, cost-effective, and reliable electricity throughout the Pacific Northwest region of the United States. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The exponential growth of the internet and high-speed data transmission has also increased the security threat of data. The antivirus companies are providing security to this data. Cybercriminals are in continuous efforts to break security barriers to steal sensitive information and to have unauthorized access or corrupt the victim's system. There is a never-ending cycle between antivirus companies and cybercriminals. There are two ways to detect malware by using static analysis and dynamic analysis. Although static analysis provides fast results, zero-day malware can't be detected as there is a predefined set of signatures in this technique. By using obfuscation techniques malware writers can evade this technique while in dynamic analysis malware detection is based on malware behavior. So, dynamic analysis is capable of detecting new and unseen malware. Machine learning and deep learning techniques are quite effective in the classification of malware on the extracted feature set by using static or dynamic analysis. In a recent study, the malware classification is performed by using transfer learning inConvolution Neural Network (CNN) architectures based on API Call visualization. API Call visualization means converting API Calls in the form of images to detect patterns of different families of malware. After converting API Callimages,the transfer learning is performed on two customized CNN models to enhance feature vectors and made a combined set of feature vectors. The results of thisframework are compared with pre-trained models like VGG-16, ResNet-50 and AlexNet which shows that our suggested approach outperforms pre-trained models. [ABSTRACT FROM AUTHOR]

An agricultural robot system has been ever increasing to develop rapidly in the world, with the progress of the Internet of Things, big data, and artificial intelligence. This study aims to analyze the development of the global agricultural robot system using the domain knowledge map from the Web of Science core data and visualization software. Research findings were as follows: 1) Four stages were roughly divided in the agricultural robot research. 2) The United States, China, Spain, Germany, Japan, Italy, and the United Kingdom presented the most research outputs, and the closest cooperation was found between China and the United States, the United States and Spain, China and Japan. 3) The agricultural robot research in China was about 10 years later than that of the United States, but there was a rapid increase in the most achievements “quantity and quality”, especially in the fruit picking robot. The key technologies, such as stereo vision technology, have been reported almost simultaneously in China and the United States. 4) The development of the agricultural robot system followed the following path: from simple to complex, and gradually to the multi-functional, intelligent autonomous unmanned system. Correspondingly, the development of the agricultural robot system from the birth, shape and growth to a period of rapid development, was great benefit from the big data, artificial intelligence, internet of things, cloud computing, mobile Internet, as well as the new generation of information and communication technology. Now, the agricultural robot has stepped into a period of accelerated development in the new era. The future agricultural robot can be more smart and intelligent, from one single function to the integration of intelligent perception, intelligent decision-making, and intelligent execution of agricultural robot system. The more extensive development of agricultural robots can be extended from the special robots to multi-functional mechanization, automation, and intellectualization suitable for the agricultural production, particularly from the whole mechanization of the same crop production to the comprehensive large-scale intensive mechanization of different varieties of crops development needs. The application of agricultural robots has been developed from a single robot to a group operation system with the intelligent cooperation of multiple robots, such as swarm UAV, harvesting robot group, robot group, and robot team. The application scenarios have been more efficient and competitive in the large-scale cooperative operation of agricultural robots. The unmanned intelligent agricultural robot can be the development trend to cope with the agricultural labor shortage and machine generation. Man-machine cooperation and man-machine integration can also bring the respective strengths of new farmers and agricultural robots to achieve the common growth of man-machine. Consequently, some recommendations were made to strengthen basic research, and break through the restrictions and blockades of algorithms, models, materials, and processes, particularly for the high-level scientific and technological self-reliance in the field of agricultural robots. It is very necessary to accelerate the implementation of the development strategy of agricultural robots during this time. The level of intelligence of agricultural robots needs to be further improved for the stability, high quality, and high efficiency of operating performance suitable for various operating environments. In addition, the decision making on the supportive and guiding policies and the investment can also be critical to strengthen the research and talent team, thereby promoting sustainable and healthy development in the application of agricultural robot technology and equipment. [ABSTRACT FROM AUTHOR]

The paper present visualization techniques of properties of plant protection products via Tableau Data Visualization software for the purposes of safe and effective selection of pesticides towards different abiotic, biotic and antropogenic conditions. Although one plant protection product has many and different properties which determine its application, via Tableau was able all of these properties to be presented (showed) in the only one visualization, which make the process of selection of the right plant protection product extremely fast, easy and effective. Tableau Desktop is interactive data visualization software which is based on spreadsheets and relational databases. During the recent years this software founded in 2003 from Christian Chabot, Pat Hanrahan and Chris Stolte, researchers at the Department of Computer Science at Stanford University, became one of the most popular solution in the world from this type, used widely in all human areas for creation of high level graph-type data visualizations via easy to be used graphical user interface. In 2008 Tableau received award for "Best Business Intelligence Solution" by the Software and Information Industry Association. [ABSTRACT FROM AUTHOR]

Background: This paper introduces DynamoVis version 1.0, an open-source software developed to design, record and export custom animations and multivariate visualizations from movement data, enabling visual exploration and communication of patterns capturing the associations between animals' movement and its affecting internal and external factors. Proper representation of these dependencies grounded on cartographic principles and intuitive visual forms can facilitate scientific discovery, decision-making, collaborations, and foster understanding of movement. Results: DynamoVis offers a visualization platform that is accessible and easily usable for scientists and general public without a need for prior experience with data visualization or programming. The intuitive design focuses on a simple interface to apply cartographic techniques, giving ecologists of all backgrounds the power to visualize and communicate complex movement patterns. Conclusions: DynamoVis 1.0 offers a flexible platform to quickly and easily visualize and animate animal tracks to uncover hidden patterns captured in the data, and explore the effects of internal and external factors on their movement path choices and motion capacities. Hence, DynamoVis can be used as a powerful communicative and hypothesis generation tool for scientific discovery and decision-making through visual reasoning. The visual products can be used as a research and pedagogical tool in movement ecology. [ABSTRACT FROM AUTHOR]

The Grand Challenges in Assessment in Higher Education project seeks to address three significant ongoing challenges faced by assessment professionals (Singer-Freeman and Robinson 2020a; 2020b). Data storytelling shares data with stakeholders through a narrative format that answers the "who, what, where, why, and how" encapsulated in the data. The culture of assessment then became an opportunity to use data for with can experience a transformational moment when assessment data is understood as data I about i student learning that can lead to discovering I how i students learn. [Extracted from the article]

The Women of Shaheen Bagh as Muslim political actors foregrounded an alternative form of Indian nationalism defined by peaceful, artistic protest and leveraged their previous hyper-invisibility and rhetorical position as wives and mothers to advocate against the CAA-NRC. The Wire Twitter feed has an informative flowchart that explains the connection between the CAA and NRC. When the right-wing Hindu-nationalist Bharatiya Janata Party (BJP) of India passed the Citizenship Amendment Act (CAA) on December 11, 2019, and quickly followed up the legislative amendment with the implementation of the National Registry of Citizens (NRC), protests blossomed in India and across the globe.[6] As a feminist research collective based at Bowling Green State University (BGSU) - including Radhika Gajjala, Oladoyin Olubukola Abiona, and Olayombo Tejumade Raji-Oyelade, along with collaborators at other institutions - we were immediately struck by the images of a specific anti-CAA-NRC protest in Shaheen Bagh neighborhood of Delhi, a protest dominated by images of Muslim women - often mothers and grandmothers - peacefully protesting for weeks in streets. [Extracted from the article]

Interactive visualization has become a powerful insight-revealing medium. However, the close dependency of interactive visualization on its data inhibits its shareability. Users have to choose between the two extremes of (i) sharing non-interactive dataless formats such as images and videos, or (ii) giving access to their data and software to others with no control over how the data will be used. In this work, we fill the gap between the two extremes and present a new system, called Loom. Loom captures interactive visualizations as standalone dataless objects. Users can interact with Loom objects as if they still have the original software and data that created those visualizations. Yet, Loom objects are completely independent and can therefore be shared online without requiring the data or the visualization software. Loom objects are efficient to store and use, and provide privacy preserving mechanisms. We demonstrate Loom's efficacy with examples of scientific visualization using Paraview, information visualization using Tableau, and journalistic visualization from New York Times. [ABSTRACT FROM AUTHOR]

The era of big data, analysis, and artificial intelligence is a new trend in intelligent big data analysis. The present stage of the geoscience progress allows the Earth to be analyzed as an extremely dynamic structure of multiple elements, such as the hydrosphere, lithosphere, and atmosphere, interacting in and with others. To derive useful information from them, large quantities of observation and simulation data provided by numeric models need to be analyzed. Visualization is a critical feature of data analytics since it is a simple and swift way to evaluate the data and consider the specific aspects and mistakes of the dataset. A geographic information system (GIS), the most efficient meteorological data visualization software class, provides excellent capabilities for geospatial data manipulation. The processing architecture that can efficiently be used as a back-end for GIS by providing quick access to the data stored at remote storage nodes is described in this paper. Weather departments use various kinds of sensors for data collection such as temperature, humidity, etc. The number and speed of the sensors in each sensor complicate the data processing time. This paper seeks to provide a weather-temperature analysis big data forecast architecture based on the MapReduce algorithm. The suggested intelligent management system of meteorological archives based on big data (IMS-MABD) framework methodology could promote research and advancement of intelligent big data analysis, large data analytics, business intelligence, artificial intelligence, and data science. Intelligent management systems for meteorological archive systems based on large data frameworks could be used. Experimental findings show that the architecture created allows real-time data access and can support many simultaneous applications successfully with a performance of 98.1%. [ABSTRACT FROM AUTHOR]