The value of using static code attributes to learn defect predictors has been widely debated. Prior work has explored issues like the merits of "McCabes versus Halstead versus lines of code counts" ...for generating defect predictors. We show here that such debates are irrelevant since how the attributes are used to build predictors is much more important than which particular attributes are used. Also, contrary to prior pessimism, we show that such defect predictors are demonstrably useful and, on the data studied here, yield predictors with a mean probability of detection of 71 percent and mean false alarms rates of 25 percent. These predictors would be useful for prioritizing a resource-bound exploration of code that has yet to be inspected
Weakly supervised point cloud segmentation has emerged as a prominent research area to address the problem of manual annotation costs. A crucial challenge in weakly supervised point cloud ...segmentation is the implicit augmentation of the total amount of supervision signals. In this article, we propose a novel method that utilizes the fusion of features from different networks to enhance the supervision signals. Specifically, we utilize a deep Encoder-Decoder network to capture high-level semantic features of labeled points, while a shallow Encoder network captures multi-scale detail features of labeled data. By combining these two heterogeneous networks, we acquire richer feature representations that implicitly enhance the supervision signal.Furthermore, we introduce scene-level and instance-level contrast to enhance feature representations in both coarse-grained and fine-grained manners, thus further boosting the supervisory signal. To validate the effectiveness of our approach, we conducted experiments on the large-scale indoor scene dataset, S3DIS, and the outdoor datasets, Toronto3D and Semantic3D, achieving convincing results.
•Investigated how to improve the performance of semantic segmentation of weakly supervised point clouds.•Explored the use of heterogeneous networks for feature extraction and fusion.•Found that heterogeneous network features can greatly increase the total number of supervised signals.•Can use less annotation to achieve excellent results and save the cost of manual annotation.
Technology is often an importance consideration in a state's theory of victory. States must consider how technology advances their strategic ends and the most appropriate ways to source technology. ...As states seek technological overmatch or offsets, they must also wrestle with the strategic cost, risk, and advantage of emerging technologies. Yet, technological advantage is likely to be fleeting. Successful competition depends on states' ability to scale rapidly in times of crisis, to train soldiers in network-centric and austere environments, to effectively establish norms of AI use, to compete in the diffusion of global dual-use technology, and to question assumptions of technological emergence.
Purpose
The purpose of this study was to explore the performance of different parameter combinations of deep learning (DL) models (Xception, DenseNet121, MobileNet, ResNet50 and EfficientNetB0) and ...input image resolutions (REZs) (224 × 224, 320 × 320 and 488 × 488 pixels) for breast cancer diagnosis.
Methods
This multicenter study retrospectively studied gray-scale ultrasound breast images enrolled from two Chinese hospitals. The data are divided into training, validation, internal testing and external testing set. Three-hundreds images were randomly selected for the physician-AI comparison. The Wilcoxon test was used to compare the diagnose error of physicians and models under
P
=0.05 and 0.10 significance level. The specificity, sensitivity, accuracy, area under the curve (AUC) were used as primary evaluation metrics.
Results
A total of 13,684 images of 3447 female patients are finally included. In external test the 224 and 320 REZ achieve the best performance in MobileNet and EfficientNetB0 respectively (AUC: 0.893 and 0.907). Meanwhile, 448 REZ achieve the best performance in Xception, DenseNet121 and ResNet50 (AUC: 0.900, 0.883 and 0.871 respectively). In physician-AI test set, the 320 REZ for EfficientNetB0 (AUC: 0.896,
P
< 0.1) is better than senior physicians. Besides, the 224 REZ for MobileNet (AUC: 0.878,
P
< 0.1), 448 REZ for Xception (AUC: 0.895,
P
< 0.1) are better than junior physicians. While the 448 REZ for DenseNet121 (AUC: 0.880,
P
< 0.05) and ResNet50 (AUC: 0.838,
P
< 0.05) are only better than entry physicians.
Conclusion
Based on the gray-scale ultrasound breast images, we obtained the best DL combination which was better than the physicians.
Starting from the relationship between urban planning and mobility management, TeMA has gradually expanded the view of the covered topics, always following a rigorous scientific in-depth analysis. ...This section of the Journal, Review Notes, is a continuous update about emerging topics concerning relationships among urban planning, mobility, and environment, thanks to a collection of short scientific papers written by young researchers. The Review Notes are made up of five parts. Each section examines a specific aspect of the broader information storage within the main interests of the TeMA Journal. In particular: the Town Planning International Rules and Legislation. Positive Energy Districts has entered the scientific and policy arena to accelerate urban transitions in Europe, however their implementation remains challenging in planning processes. The PED incorporates socio-economic, technological, environmental, political and institutional challenges that need to be addressed simultaneously as part of a holistic urban strategy. The theme of PEDs finds its first application implications in renewable energy communities on a local scale. This review focuses its attention on Renewable Energy Directive Recast which also provides for financial support for the production and self-consumption of electricity from renewable sources and on the Italian legislation on renewable energy communities governed by the Milleproroghe decree.
Cardiac arrest is triggered by an electrical malfunction in the heart and its pumping action is disrupted. Periodontal diseaseis an inflammatory disease of tissues that hold the teeth wherein, there ...is gradual destruction of tissues and subsequent loss of teeth. These two are interrelated and here, prediction is to prevent the disease occurrence in advance before it arise and create treatment strategies for future prevention of the disease.Prediction of cardiac arrest from periodontal dental disease is done using Artificial intelligence in cloud. Artificial intelligence is the “study and design of intelligent agents” where an intelligent agent is a system that perceives its surroundings and adapts to make the best probable action to Maximise the probability of success.. This paper highlights latest studies regarding implemented techniques such as diagnosis of Periodontal Dental Disease for all age group people, smokers and drunken people, risk assessment of periodontal dental disease for all age group people, heart disease prediction system, and heart rate monitoring using emotional intelligence.
Today, beyond being just technological objects, artificial intelligence and robots create a multidimensional relationship network within the social structure. This multidimensional network of ...relationships includes human actors such as mathematicians, engineers, bankers, doctors, soldiers, students, and teachers and non-human smart actors such as chatbots, virtual assistants, autonomous vehicles, translation programs, CCTV systems, drones, humanoid robots, and smart home robots. This study is aimed to determine the perception of function towards artificial intelligence and robots of individuals who use the said technology and follow the developments and whether this perception changes according to some variables. Some data on the perception of function towards artificial intelligence and robots are handled in line with Merton's functionality perspective. Qualitative and quantitative methods obtained the data, and it was observed that the perception of function towards the technology in question differs according to the people's expectations, needs, and positions. It is thought that the data obtained will be useful to the literature and the experts on the subject.
A digital twin (DT), originally defined as a virtual representation of a physical asset, system, or process, is a new concept in health care. A DT in health care is not a single technology but a ...domain-adapted multimodal modeling approach incorporating the acquisition, management, analysis, prediction, and interpretation of data, aiming to improve medical decision-making. However, there are many challenges and barriers that must be overcome before a DT can be used in health care. In this viewpoint paper, we build on the current literature, address these challenges, and describe a dynamic DT in health care for optimizing individual patient health care journeys, specifically for women at risk for cardiovascular complications in the preconception and pregnancy periods and across the life course. We describe how we can commit multiple domains to developing this DT. With our cross-domain definition of the DT, we aim to define future goals, trade-offs, and methods that will guide the development of the dynamic DT and implementation strategies in health care.
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