Bird's Eye View Research Articles

Air Traffic Control software implemented in RADAR

This study presents the flight plan data related to aircraft performance and is tested against the aircraft performance database. The Significant Meteorological Information Reports - SIGMET will be generated by the system according to the selected turbulence areas by attaching different AIS data to an exercise that can change the simulation objectives. The exercise must be assigned to one or more courses to be able to attach meteorological data when viewing a data recording; changes can be made to the aircraft as in a normal exercise run, while the other instructions will be loaded from the recorded data file. A data recording is airspace dependent, changing the airspace can make the data recording fail during playback. Video Recording is only available for the RADAR Simulator. A video recording can be made at any time during a simulation session; a data recording can be selected only at the beginning of the simulation session and cannot be started during the simulation session; if the simulator is integrated with the Voice Communication System and the audio channels, then a sound recording window will automatically pop-up. For this study, an ideal case, for the configuration presentation we will assume that the 3D Tower Simulator is composed of 4 LCD/Projectors to create the out-of-the- window view, 180 degrees, 2 Pseudo-Pilots, and 1 Supervisor/FEEDER Position. The 4 image generators will be provided by SIM01, SIM02, SIM03, and SIM04. The Pseudo-Pilots positions will be provided by SIM05 and SIM06. The Supervisor/Feeder Position will be provided by SIM07. For the Tower Controller Working Positions, we will provide the following information displays: DE – Flight Data Equipment/Clearance Delivery, MET – Meteorological Information, LCP –Lights Control Panel, and a RADAR Image. Station SIM08 will be used. Stations SIM01, SIM02, SIM03, and SIM04 are equipped with one large LCD Display or a Projector; Stations SIM05 and SIM07 are equipped with 2 monitors, one for the RADAR Image and the other one for the bird-eye view over the airport; Station SIM06 is equipped with one monitor for the bird-eye view over the airport; Station SIM08 is equipped with 4 monitors providing all necessary information for the Tower Controller Working Positions. SIM07, as presented above, is the FEEDER/SUPERVISOR for the RADAR Simulator, the approach sector is “TMA” and the application will be started on the second monitor, the first monitor is used for the 3D Tower Simulator. SIM07 is also FEEDER/SUPERVIZOR for the 3D Tower Simulator, the station function will be “3DTWR” and the sector will be the previously created 3D Tower configuration, “TOWER”. On SIM08 will add a RADAR Image for the Tower Controller Working Positions, sector is “TMA”, the application will be started on monitor 4, and the station function is “TWR”. Usually, for an aircraft departing from an airport inside an approach sector, the first owner will be the tower until passing the maximum flight level/ altitude for the tower, the second owner will be the approach sector and the third owner will be the en-route sector. In this case, the tower sector has power over the approach sector, and the en-route sector, the approach sector has power over the en-route sector. The outside FIR sectors will be used in the determination of the next en-route sector, for coordination purposes. If the VFR points do not appear on the RADAR Map after the “DRAW” button has been pushed, use the “MAP MENU” – “VFR” button. The aircraft performance database is not airspace structure dependent. When a new airspace structure is created the aircraft performance database will remain unchanged.

Network Analysis and Natural Language Processing to Obtain a Landscape of the Scientific Literature on Materials Applications.

Recent progress in natural language processing (NLP) enables mining the literature in various tasks akin to knowledge discovery. Obtaining an updated birds-eye view of key research topics and their evolution in a vast, dynamic field such as materials science is challenging even for experienced researchers. In this Perspective paper, we present a landscape of the area of applied materials in selected representative journals based on a combination of methods from network science and simple NLP strategies. We found a predominance of energy-related materials, e.g., for batteries and catalysis, organic electronics, which include flexible sensors and flexible electronics, and nanomedicine with various topics of materials used in diagnosis and therapy. As for the impact calculated through standard metrics of impact factor, energy-related materials and organic electronics are again top of the list across different journals, while work in nanomedicine has been found to have a lower impact in the journals analyzed. The adequacy of the approach to identify key research topics in materials applications was verified indirectly by comparing the topics identified in journals with diverse scopes, including journals that are not specific to materials. The approach can be employed to obtain a fast overview of a given field from the papers published in related scientific journals, which can be adapted or extended to any research area.

Salivary analysis: An emerging paradigm for non‐invasive healthcare diagnosis and monitoring

AbstractAs an emerging non‐invasive and easy‐to‐use toolkit, salivary analysis has garnered significant attention recently. By leveraging the latest discoveries in salivary biomarkers, salivary analysis has the potential to revolutionize the field of healthcare by providing valuable information for monitoring an individual's health status, diagnosing disease progression, and enabling personalized treatment. However, the transitional development of breakthrough salivary analysis remains an intriguing challenge. Only a few innovations have progressed to new transformative healthcare diagnosis and monitoring tools. In this review, we attempt to illustrate a bird's eye view of the emerging field of salivary analysis by exploring an assorted selection of seminar progress that can potentially shape the developing trajectory of the field of salivary analysis. The fundamental nature of saliva and the versatile robust uses of salivary analysis as a novel non‐invasive method in various healthcare diagnostic and monitoring fields will be thoroughly discussed. To inspire next‐stage development in this thriving and fruitful field, we also crystalize key findings, pinpoint challenges that remain to be addressed and present an outlook on the future transitional development of salivary analysis, invigorating future research of groundbreaking non‐invasive healthcare diagnosis and monitoring strategies, and beyond.

MENet: Map-enhanced 3D object detection in bird’s-eye view for LiDAR point clouds

Three-dimensional (3D) object detection utilizes numerous onboard sensors to determine the position, size, and motion information of surrounding objects. Recently, some researchers have utilized HD maps in 3D object detection for LiDAR point clouds. However, existing LiDAR–map fusion detection methods simply take the HD map as an additional input and more prior information in the map is underexplored. To address this limitation, we employ the HD map in data augmentation for LiDAR 3D detection to eliminate the bias of distributions between the augmented training and test sets. Furthermore, we propose a map-enhanced 3D object detection network, called MENet, for LiDAR point clouds. Compared with the standard LiDAR-only detector in bird’s eye view (BEV), MENet extends LiDAR-based baselines by using a map encoder to encode the input rasterized HD map into a BEV feature. In addition, it uses a multimodal fuser to aggregate the map BEV feature with the LiDAR BEV feature extracted in the LiDAR stream. MENet achieved a mean average precision (mAP) of 56.90% and nuScenes detection score (NDS) of 63.43%, improving the mAP and NDS of its LiDAR-only backbone by 4.18% and 2.22%, respectively. Although the HD map is necessary at training time, the map-enhanced 3D detector can work robustly and perform better than the original baseline when there was no map input at test time. Experimental results further indicate that the proposed map plugins can improve the performance of both anchor-based and anchor-free models on different datasets. The code will be open-source at https://github.com/WHU-USI3DV/MENet.

Nanostructured bioactive glasses: A bird's eye view on cancer therapy.

Bioactive glasses (BGs) arewell known for their successful applications in tissue engineering and regenerative medicine. Recent experimental studies have shown their potential usability in oncology, either alone or in combination with other biocompatible materials, such as biopolymers. Direct contact with BG particles has been found to cause toxicity and death in specific cancer cells (bone-derived neoplastic stromal cells) in vitro. Nanostructured BGs (NBGs) can be doped with anticancer elements, such as gallium, to enhance their toxic effects against tumor cells. However, the molecular mechanisms and intracellular targets for anticancer compositions of NBGs require further clarification. NBGs have been successfully evaluated for use in various well-established cancer treatment strategies, including cancer hyperthermia, phototherapy, and anticancer drug delivery. Existing results indicate that NBGs not only enhance cancer cell death, but can also participate in the regeneration of lost healthy tissues. However, the application of NBGs in oncology is still in its early stages, and numerous unanswered questions must be addressed. For example, the impact of the composition, biodegradation, size, and morphology of NBGs on their anticancer efficacy should be defined for each type of cancer and treatment strategy. Moreover, it should be more clearly assessed whether NBGs can shrink tumors, slow/stop cancer progression, or cure cancer completely. In this regard, the use of computational studies (in silico methods) is highly recommended to design the most effective glass formulations for cancer therapy approaches and to predict, to some extent, the relevant properties, efficacy, and outcomes. This article is categorized under: Implantable Materials and Surgical Technologies > Nanomaterials and Implants Implantable Materials and Surgical Technologies > Nanotechnology in Tissue Repair and Replacement Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

Extraction of Features from a Bird's-Eye View for Path Detection

Extraction of Features from a Bird's-Eye View for Path Detection

Rethinking First Language–Second Language Similarities and Differences in English Proficiency: Insights From the ENglish Reading Online (ENRO) Project

AbstractThis article presents the ENglish Reading Online (ENRO) project that offers data on English reading and listening comprehension from 7,338 university‐level advanced learners and native speakers of English representing 19 countries. The database also includes estimates of reading rate and seven component skills of English, including vocabulary, spelling, and grammar, as well as rich demographic and language background data. We first demonstrate high reliability for ENRO tests and their convergent validity with existing meta‐analyses. We then provide a bird's‐eye view of first (L1) and second (L2) language comparisons and examine the relative role of various predictors of reading and listening comprehension and reading speed. Across analyses, we found substantially more overlap than differences between L1 and L2 speakers, suggesting that English reading proficiency is best considered across a continuum of skill, ability, and experiences spanning L1 and L2 speakers alike. We end by providing pointers for how researchers can mine ENRO data for future studies.

Surface-Engineered Extracellular Vesicles in Cancer Immunotherapy.

Extracellular vesicles (EVs) are lipid bilayer-enclosed bodies secreted by all cell types. EVs carry bioactive materials, such as proteins, lipids, metabolites, and nucleic acids, to communicate and elicit functional alterations and phenotypic changes in the counterpart stromal cells. In cancer, cells secrete EVs to shape a tumor-promoting niche. Tumor-secreted EVs mediate communications with immune cells that determine the fate of anti-tumor therapeutic effectiveness. Surface engineering of EVs has emerged as a promising tool for the modulation of tumor microenvironments for cancer immunotherapy. Modification of EVs' surface with various molecules, such as antibodies, peptides, and proteins, can enhance their targeting specificity, immunogenicity, biodistribution, and pharmacokinetics. The diverse approaches sought for engineering EV surfaces can be categorized as physical, chemical, and genetic engineering strategies. The choice of method depends on the specific application and desired outcome. Each has its advantages and disadvantages. This review lends a bird's-eye view of the recent progress in these approaches with respect to their rational implications in the immunomodulation of tumor microenvironments (TME) from pro-tumorigenic to anti-tumorigenic ones. The strategies for modulating TME using targeted EVs, their advantages, current limitations, and future directions are discussed.

Rationalising the Political: The Concept of Interest in Postmodern Public Law

References to public interest are abundant in legal scholarship, jurisprudence, and legislation. However, the meaning of interest still remains rather a common sense idea without legible standards or criteria. The article offers to conceptualize it in a broader socio-historical context, as this concept cannot be treated in isolation from the evolution of the Western scientific paradigm that aspires to rationalize the world, to rationally explain and construct a cognitive map of both social and natural environments. To explore the history of “interest” in law means to grasp and reconstruct the phases of the fundamental revolution that legal thought has undergone since the mid-XVIII century. The article offers a bird-eye view of how the concept of interest gained currency and infiltrated law. This evolutionary perspective could explain certain coherence and similarity of various meanings proposed for the concept of interest in case law and scholarship. The article argues that interest becomes socially recognizable and viable when it is perceived and interpreted as such. It acquires validity in legal argumentation if it fits into the cultural schemata of legal framing. The article purports to deconstruct interest as a category. It argues that three key assumptions underpin the concept: (1) interests are social constructs; (2) interests are generated by argumentation (to qualify as interest an existing or perceived good, purpose, motive, aspiration, or claim requires argumentation that triggers “frames of interest” - cognitive representations and constructs); (3) interests are vehicles whereby normative ideas of justice, society, and the world, generated and validated by other normative orders, are adapted, legitimized and incorporated into law. The article discusses the practical implications of these assumptions. In a judicial proceeding, public interest analysis should explore the central organizing idea of a public interest argumentation against three analytical components: (1) substantive (refers to the interest analysis); (2) quantitative (refers to the “society”/ “public” analysis); and (3) qualitative (refers to analysis focusing on whether the argumentation triggers cognitive representations and constructs that reference moral principles). Finally, the reconceptualization of interest as a social construct can shed new light on legal argumentation and the so-called “five I-s of legal reasoning”: intuitiveness, incidentality, indeterminacy, ideology, and irrationality. Though indeed often intuition-driven, interest as a social construct that fits into legal framing is not incidental, indeterminate, or irrational. Incrementing and unfolding via interaction and competition with discourses and legal frames, interests bring in certainty, predictability, and determinacy to open-ended concepts of law.

X-Align++: cross-modal cross-view alignment for Bird’s-eye-view segmentation

Bird’s-eye-view (BEV) grid is a typical representation of the perception of road components, e.g., drivable area, in autonomous driving. Most existing approaches rely on cameras only to perform segmentation in BEV space, which is fundamentally constrained by the absence of reliable depth information. The latest works leverage both camera and LiDAR modalities but suboptimally fuse their features using simple, concatenation-based mechanisms. In this paper, we address these problems by enhancing the alignment of the unimodal features in order to aid feature fusion, as well as enhancing the alignment between the cameras’ perspective view (PV) and BEV representations. We propose X-Align, a novel end-to-end cross-modal and cross-view learning framework for BEV segmentation consisting of the following components: (i) a novel Cross-Modal Feature Alignment (X-FA) loss, (ii) an attention-based Cross-Modal Feature Fusion (X-FF) module to align multi-modal BEV features implicitly, and (iii) an auxiliary PV segmentation branch with Cross-View Segmentation Alignment (X-SA) losses to improve the PV-to-BEV transformation. We evaluate our proposed method across two commonly used benchmark datasets, i.e., nuScenes and KITTI-360. Notably, X-Align significantly outperforms the state-of-the-art by 3 absolute mIoU points on nuScenes. We also provide extensive ablation studies to demonstrate the effectiveness of the individual components.

A SYSTEMATIC REVIEW ABOUT ACADEMIC INDUSTRY COLLABORATION, TECHNOLOGY TRANSFER & SKILL DEVELOPMENT: A BIBLIOMETRIC ANALYSIS USING THE SCOPUS DATABASE

The gap between new-age jobs & availability of a skilled workforce is widening have shifted focus to academic-industrial collaboration nurturing applied research innovation, technology transfer & creation of a skilled workforce. This paper attempts to analyze a birds-eye view of the research that happened from 2011 onward that had been done in this arena & explores the critical aspects of academic-industrial collaboration, technology transfer, and skill development. A systematic review of studies published between 2010 onwards is studied using the following trusted Scopus database. After the initial screening of the paper resulted in 1,534 documents, after the keywords refinement final, 121 papers were taken for the analysis, and eight exclusive papers studied the skill development parameter along with the above keywords. The result shows that most of the United States has the maximum number of documents published in AIC. In the second number, the publication is from the United Kingdom, followed by India. It signifies that a growing economy needs innovation, technology transfer & skilled workforce & AIC is the model to go ahead

Object Detection from Point Clouds for Driverless Vehicles

Point clouds offer the advantage of providing direct access to 3D data. So, utilizing solely point clouds, we present an object detection technique for driverless vehicles in this study. In this method, a graph is first constructed using the k-nearest neighbour (KNN) method, and then a graph neural network module is proposed for local information extraction. Then, depending on the coordinates of points, we utilize a pillar-based projection approach to project the locally informative feature into bird’s-eye-view (BEV). After that, residual-based networks with attention mechanisms are used for the BEV features processing. The attention system is capable of assigning appropriate weights to several nearby points, hence improving detection performance. The proposed work achieves 58.49 percent and 67.90 percent mAP (mean Average Precision) for 3D Object detection and BEV detection, respectively, on the KITTI 3D object detection benchmark. We also tested the proposed method on our driverless vehicle in our campus, and we compared it to the prior method we utilized. The experimental results reveal that the proposed method outperforms the existing methods (about 2% higher than PointPillars in BEV detection) and gives more accurate information.

Estimating vegetation index for outdoor free-range pig production using YOLO.

The objective of this study was to quantitatively estimate the level of grazing area damage in outdoor free-range pig production using a Unmanned Aerial Vehicles (UAV) with an RGB image sensor. Ten corn field images were captured by a UAV over approximately two weeks, during which gestating sows were allowed to graze freely on the corn field measuring 100 × 50 m2. The images were corrected to a bird's-eye view, and then divided into 32 segments and sequentially inputted into the YOLOv4 detector to detect the corn images according to their condition. The 43 raw training images selected randomly out of 320 segmented images were flipped to create 86 images, and then these images were further augmented by rotating them in 5-degree increments to create a total of 6,192 images. The increased 6,192 images are further augmented by applying three random color transformations to each image, resulting in 24,768 datasets. The occupancy rate of corn in the field was estimated efficiently using You Only Look Once (YOLO). As of the first day of observation (day 2), it was evident that almost all the corn had disappeared by the ninth day. When grazing 20 sows in a 50 × 100 m2 cornfield (250 m2/sow), it appears that the animals should be rotated to other grazing areas to protect the cover crop after at least five days. In agricultural technology, most of the research using machine and deep learning is related to the detection of fruits and pests, and research on other application fields is needed. In addition, large-scale image data collected by experts in the field are required as training data to apply deep learning. If the data required for deep learning is insufficient, a large number of data augmentation is required.

Multi-Modal and Multi-Scale Fusion 3D Object Detection of 4D Radar and LiDAR for Autonomous Driving

Multi-modal fusion plays a critical role in 3D object detection, overcoming the inherent limitations of single-sensor perception in autonomous driving. Most fusion methods require data from high-resolution cameras and LiDAR sensors, which are less robust and the detection accuracy drops drastically with the increase of range as the point cloud density decreases. Alternatively, the fusion of Radar and LiDAR alleviates these issues but is still a developing field, especially for 4D Radar with a more robust and broader detection range. Nevertheless, different data characteristics and noise distributions between two sensors hinder performance improvement when directly integrating them. Therefore, we are the first to propose a novel fusion method termed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$M^{2}$</tex-math></inline-formula> -Fusion for 4D Radar and LiDAR, based on Multi-modal and Multi-scale fusion. To better integrate two sensors, we propose an Interaction-based Multi-Modal Fusion (IMMF) method utilizing a self-attention mechanism to learn features from each modality and exchange intermediate layer information. Specific to the current single-resolution voxel division's precision and efficiency balance problem, we also put forward a Center-based Multi-Scale Fusion (CMSF) method to first regress the center points of objects and then extract features in multiple resolutions. Furthermore, we present a data preprocessing method based on Gaussian distribution that effectively decreases data noise to reduce errors caused by point cloud divergence of 4D Radar data in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$x$</tex-math></inline-formula> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$z$</tex-math></inline-formula> plane. To evaluate the proposed fusion method, a series of experiments were conducted using the Astyx HiRes 2019 dataset, including the calibrated 4D Radar and 16-line LiDAR data. The results demonstrated that our fusion method compared favorably with state-of-the-art algorithms. When compared to PointPillars, our method achieves mAP (mean average precision) increases of 5.64 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> and 13.57 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> for 3D and BEV (bird's eye view) detection of the car class at a moderate level, respectively.

Queer Subjects in Modern Japanese Literature: Male Love, Intimacy, and Erotics, 1886–2014 ed. by Stephen D. Miller

Reviewed by: Queer Subjects in Modern Japanese Literature: Male Love, Intimacy, and Erotics, 1886–2014 ed. by Stephen D. Miller Erik R. Lofgren Queer Subjects in Modern Japanese Literature: Male Love, Intimacy, and Erotics, 1886–2014 ED. STEPHEN D. MILLER Ann Arbor. University of Michigan Press. 2022. 474 pages. STEPHEN D. MILLER has assembled an engaging collection of fourteen short stories, numerous poems in varied forms, and two essays spanning the better part of the modern and contemporary eras (1868–present) that explore and extend our understanding of an important dimension of Japanese literature. The works are arranged in a very rough chronological order and split pretty evenly between pre- and post–World War II material. Miller has gathered a broad range of translators, many of whom are noted in this field, which gives the anthology a wonderfully eclectic feel. This helps ensure that the many authors—not all of whom are male, it should be noted—represented in this collection have palpably different voices in English, a polyphony that is one of the many pleasures of this wide-ranging work. Although it is not essential to do so, readers would be well served to read Miller's informative introduction prior to delving into the meat of this anthology. First, it explores the limitations and advantages of the contested term "queer" used in the title. The term certainly refers to "topics and people, characterized [End Page 92] by peculiarity, eccentricity, uncanniness, nonconformity, subversiveness" but also to "a pleasing and even necessary variation upon pattern." Miller seeks to encompass and enfranchise this diversity while also suggesting the difficulty inherent in providing a simplistic categorization for the works included here. Second, the introduction provides a cogent historical summary of male-male love in Japanese literature from the ninth century until the modern day, framing that undergirds the translations. This basic contextualization is supplemented by the short biography and introduction found at the beginning of each chapter, which provide context for the text to follow. In and of themselves, these briefs make for engaging reading, providing a variegated bird's-eye view of the authors and literature in Queer Subjects. It is impossible, in this limited space, to comment on each of the pieces comprising this robust sampling of male intimacy, which is a shame as many deserve a moment in the spotlight. Suffice it to say that the variation ensures that there will be something for everyone, but I will mention two in particular. "Is This Love" (1909), by Yi Kwangsu, is notable for its intersection with Japan's colonial aspirations and the "heterolingual writing" it spawned. "Worse for Love" (1960), written by Mishima Yukio under the pseudonym Sakakiyama Tamotsu, is a harrowing literary dry run for "Patriotism" written later that year. Whether you are looking for literature to accompany a morning cup of coffee, an academic seeking a text for a course on sexuality, or desire an introduction to modern Japanese literature that eschews most of the "canonical" authors, Queer Subjects should be on your shortlist of possibilities. Erik R. Lofgren Bucknell University Copyright © 2023 World Literature Today and the Board of Regents of the University of Oklahoma

Click chemistry and drug delivery: A bird's-eye view.

Click chemistry has been proven to be very useful in drug delivery. Due to the availability of a large number of click reactions with a various characteristics, selection of appropriate chemistry for a given application is often not a trivial task. This review is written for pharmaceutical researchers who are interested in click chemistry applications and yet may not be click chemistry experts. For this, the review gives an overview of available click reactions organized by application types. Further, the general understanding of click reactions being fast and high yielding sometimes overshadows the need to analyze reaction kinetics in assessing suitability of a given reaction for certain applications. For this, we highlight the need to analyze the relationship among reaction kinetics, concentration effects, and reaction time scales, knowing that lack of such analysis could easily lead to failures. Further, possible issues such as chemical stability with various click reagents are also discussed to aid experimental designs. Recent examples and extensive references are also provided to aid in-depth understanding of technical details. We hope this review will help those interested in using click chemistry in drug delivery to select the appropriate reactions/reagents and minimize the number of pitfalls.

Application of Intraoperative CT-Ultrasound Fusion Imaging in Hip Endoscopy for Treatment of Iatrogenic Impingement Due to PLLA Screw: A Novel Surgical Technique

Ultrasound-assisted surgery is becoming an established tool in the medical field. The addition of imagery to ultrasound-assisted surgery may enable one to perform a procedure in a safer and more accurate manner. This can be achieved through fusion imaging (fusion), a technology that synchronizes MRI or CT images with ultrasound images. We describe intraoperative CT-ultrasound fusion-guided (or -assisted) hip endoscopy for the removal of an impinging poly L-lactic acid screw, which was difficult to identify on fluoroscopy during surgery. The fusion technology enables merging two advantages of ultrasound: the real-time guidance capabilities and CT or MRI and the bird's eye view that makes minimally invasive arthroscopic and endoscopic surgery less invasive, precise, and safe.

Analysis of Life-Like and Bird's Eye Views in the Augmented Reality on User Perceptions

Analysis of Life-Like and Bird's Eye Views in the Augmented Reality on User Perceptions

Multi-View Joint Learning and BEV Feature-Fusion Network for 3D Object Detection

Traditional 3D object detectors use BEV (bird’s eye view) feature maps to generate 3D object proposals, but in a single BEV feature map, there are inevitably the problems of high compression and information loss. To solve this problem, we propose a multi-view joint learning and BEV feature-fusion network. In this network, we mainly propose two fusion modules: the multi-view feature-fusion module and the multi-BEV feature-fusion module. The multi-view feature fusion module performs joint learning from multiple views, fusing features learned from multiple views, and supplementing missing information in the BEV feature map. The multi-BEV feature-fusion module fuses BEV feature map outputs from different feature extractors to further enrich the feature information in the BEV feature map, in order to generate better quality 3D object proposals. We conducted experiments on a widely used KITTI dataset. The results show that our method has significantly improved the detection accuracy of the cyclist category.For cyclist detection tasks at the easy, moderate, and hard levels of the KITTI test dataset, our method improves by 1.57%, 2.03%, and 0.67%, respectively, compared to PV-RCNN.

PMIDigest: Interactive Review of Large Collections of PubMed Entries to Distill Relevant Information.

Scientific knowledge is being accumulated in the biomedical literature at an unprecedented pace. The most widely used database with biomedicine-related article abstracts, PubMed, currently contains more than 36 million entries. Users performing searches in this database for a subject of interest face thousands of entries (articles) that are difficult to process manually. In this work, we present an interactive tool for automatically digesting large sets of PubMed articles: PMIDigest (PubMed IDs digester). The system allows for classification/sorting of articles according to different criteria, including the type of article and different citation-related figures. It also calculates the distribution of MeSH (medical subject headings) terms for categories of interest, providing in a picture of the themes addressed in the set. These MeSH terms are highlighted in the article abstracts in different colors depending on the category. An interactive representation of the interarticle citation network is also presented in order to easily locate article "clusters" related to particular subjects, as well as their corresponding "hub" articles. In addition to PubMed articles, the system can also process a set of Scopus or Web of Science entries. In summary, with this system, the user can have a "bird's eye view" of a large set of articles and their main thematic tendencies and obtain additional information not evident in a plain list of abstracts.