Investigating YOLO Models Towards Outdoor Obstacle Detection For Visually Impaired People

The utilization of deep learning-based object detection is an effective approach to assist visually impaired individuals in avoiding obstacles. In this paper, we implemented seven different YOLO object detection models \textit{viz}., YOLO-NAS (small, medium, large), YOLOv8, YOLOv7, YOLOv6, and YOLOv5 and performed comprehensive evaluation with carefully tuned hyperparameters, to analyze how these models performed on images containing common daily-life objects presented on roads and sidewalks. After a systematic investigation, YOLOv8 was found to be the best model, which reached a precision of $80\%$ and a recall of $68.2\%$ on a well-known Obstacle Dataset which includes images from VOC dataset, COCO dataset, and TT100K dataset along with images collected by the researchers in the field. Despite being the latest model and demonstrating better performance in many other applications, YOLO-NAS was found to be suboptimal for the obstacle detection task

Pragmatic Radiology Report Generation

When pneumonia is not found on a chest X-ray, should the report describe this negative observation or omit it? We argue that this question cannot be answered from the X-ray alone and requires a pragmatic perspective, which captures the communicative goal that radiology reports serve between radiologists and patients. However, the standard image-to-text formulation for radiology report generation fails to incorporate such pragmatic intents. Following this pragmatic perspective, we demonstrate that the indication, which describes why a patient comes for an X-ray, drives the mentions of negative observations and introduce indications as additional input to report generation. With respect to the output, we develop a framework to identify uninferable information from the image as a source of model hallucinations, and limit them by cleaning groundtruth reports. Finally, we use indications and cleaned groundtruth reports to develop pragmatic models, and show that they outperform existing methods not only in new pragmatics-inspired metrics (+4.3 Negative F1) but also in standard metrics (+6.3 Positive F1 and +11.0 BLEU-2).Comment: 18 pages, 1 figure, 18 tables. Code at https://github.com/ChicagoHAI/llm_radiolog

Life-Cycle Building Carbon Emission Management Platform based on Building Information Modeling Technology

Buildings produce 40% of annual carbon emissions among various sectors in modern society. One of the most challenging problems of carbon management is how to monitor and calculate a building’s life-cycle energy consumption and carbon emission data during both construction and operation stages. The Building Information Modeling (BIM) technology provides a promising method to obtain and simulate buildings as-is status at different stages in the life cycle. This paper develops a framework for building a carbon emission management platform using the carbon emission factor method and BIM technology, which can derive corresponding carbon emission and measure carbon footprint with building geographic information to achieve precise positioning of carbon emission objects. The platform can achieve multi-role collaboration, equipment visualization, real-time carbon emission monitoring, and data analysis. The platform is applied to an existing building in Hohai University to assess the total carbon footprint of the building in its life cycle. This platform can greatly improve the calculation accuracy of the carbon footprint of buildings, improve data transparency, provide valuable information for building facility management personnel, and help achieve the goal of carbon neutrality

Preimage Attacks on 4-round Keccak by Solving Multivariate Quadratic Systems

In this paper, we present preimage attacks on 4-round Keccak-224/256 as well as 4-round Keccak[$r = 640,c = 160,l = 80$] in the preimage challenges. We revisit the Crossbred algorithm for solving the Boolean multivariate quadratic (MQ) system, propose a new view for the case $D = 2$ and elaborate the computational complexity. The result shows that the Crossbred algorithm outperforms brute force theoretically and practically with feasible memory costs. In our attacks, we construct Boolean MQ systems in order to make full use of variables. With the help of solving MQ systems, we successfully improve preimage attacks on Keccak-224/256 reduced to 4 rounds. Moreover, we implement the preimage attack on 4-round Keccak[$r = 640,c = 160,l = 80$], an instance in the Keccak preimage challenges, and find 78-bit matched \textit{near preimages}. Due to the fundamental rule of solving MQ systems, the complexity elaboration of Crossbred algorithm is of independent interest

Experimentally ruling out joint reality based on operational completeness

Whether the observables of a physical system admit real values is of fundamental importance to a deep understanding of nature. In this work, we report a device-independent experiment to confirm that the joint reality of two observables on a single two-level system is incompatible with the assumption of operational completeness, which is strictly weaker than that of preparation noncontextuality. We implement two observables on a trapped $^{171}{\rm Yb}^{+}$ ion to test this incompatibility via violation of certain inequalities derived from both linear and nonlinear criteria. Moreover, by introducing a highly controllable dephasing channel, we show that the nonlinear criterion is more robust against noise. Our results push the fundamental limit to delineate the quantum-classical boundary and pave the way for exploring relevant problems in other scenarios.Comment: 6 pages, 3 figure

Lifestyle and Genetic Factors Modify Parent-of-Origin Effects on the Human Methylome

BACKGROUND: parent-of-origin effects (POE) play important roles in complex disease and thus understanding their regulation and associated molecular and phenotypic variation are warranted. Previous studies mainly focused on the detection of genomic regions or phenotypes regulated by POE. Understanding whether POE may be modified by environmental or genetic exposures is important for understanding of the source of POE-associated variation, but only a few case studies addressing modifiable POE exist. METHODS: in order to understand this high order of POE regulation, we screened 101 genetic and environmental factors such as ‘predicted mRNA expression levels’ of DNA methylation/imprinting machinery genes and environmental exposures. POE-mQTL-modifier interaction models were proposed to test the potential of these factors to modify POE at DNA methylation using data from Generation Scotland: The Scottish Family Health Study(N=2315). FINDINGS: a set of vulnerable/modifiable POE-CpGs were identified (modifiable-POE-regulated CpGs, N=3). Four factors, ‘lifetime smoking status’ and ‘predicted mRNA expression levels’ of TET2, SIRT1 and KDM1A, were found to significantly modify the POE on the three CpGs in both discovery and replication datasets. We further identified plasma protein and health-related phenotypes associated with the methylation level of one of the identified CpGs. INTERPRETATION: the modifiable POE identified here revealed an important yet indirect path through which genetic background and environmental exposures introduce their effect on DNA methylation, motivating future comprehensive evaluation of the role of these modifiers in complex diseases. FUNDING: NSFC (81971270),H2020-MSCA-ITN(721815), Wellcome (204979/Z/16/Z,104036/Z/14/Z), MRC (MC_UU_00007/10, MC_PC_U127592696), CSO (CZD/16/6,CZB/4/276, CZB/4/710), SFC (HR03006), EUROSPAN (LSHG-CT-2006-018947), BBSRC (BBS/E/D/30002276), SYSU, Arthritis Research UK, NHLBI, NIH

New In Situ Synthesis Method for Fe3O4/Flake Graphite Nanosheet Composite Structure and Its Application in Anode Materials of Lithium-Ion Batteries

High-pressure torsion (HPT), a severe plastic deformation (SPD) method, is rarely used in the manufacturing process of functional materials. In the present work, the authors creatively proposed using HPT as an alternative method an approach for high energy ball-milling in the preparation of an Fe3O4 and lamellar graphite nanosheet (GNS) composite material. The corresponding electrochemical experiments verified that the in situ synthesized Fe3O4/GNS composite material has good lithium-storage performance and that it can retain good capacity (548.2 mA h g−1) even after several hundred cycles with high current density (8 C). Meanwhile, this performance has directly confirmed that SPD technique has great potential for the preparation of anode materials of lithium-ion batteries, especially in manufacturing metallic functional nanomaterials

A Feedback-Based Approach to Utilizing Embeddings for Clinical Decision Support

Abstract Clinical Decision Support (CDS) is widely seen as an information retrieval (IR) application in the medical domain. The goal of CDS is to help physicians find useful information from a collection of medical articles with respect to the given patient records, in order to take the best care of their patients. Most of the existing CDS methods do not sufficiently consider the semantic relation between texts, hence the potential in improving the performance in biomedical articles retrieval. This paper proposes a novel feedback-based approach which considers the semantic association between a retrieved biomedical article and a pseudo feedback set. Evaluation results show that our method outperforms the strong baselines and is able to improve over the best runs in the TREC CDS tasks