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关键词： Virtual reality  

摘要： We are at a unique moment in history where there is a confluence of technologies which will synergistically come together to transform the practice of neurosurgery. These technological transformations will be all-encompassing, including improved tools and methods for intraoperative performance of neurosurgery, scalable solutions for asynchronous neurosurgical training and simulation, as well as broad aggregation of operative data allowing fundamental changes in quality assessment, billing, outcome measures, and dissemination of surgical best practices. The ability to perform surgery more safely and more efficiently while capturing the operative details and parsing each component of the operation will open an entirely new epoch advancing our field and all surgical specialties. The digitization of all components within the operating room will allow us to leverage the various fields within computer and computational science to obtain new insights that will improve care and delivery of the highest quality neurosurgery regardless of location. The democratization of neurosurgery is at hand and will be driven by our development, extraction, and adoption of these tools of the modern world. Virtual reality provides a good example of how consumer-facing technologies are finding a clear role in industry and medicine and serves as a notable example of the confluence of various computer science technologies creating a novel paradigm for scaling human ability and interactions. The authors describe the technology ecosystem that has come and highlight a myriad of computational and data sciences that will be necessary to enable the operating room of the near future. © 2021, CC BY-NC-ND.

关键词： Information services  

摘要： Using data from a large self-initiated online survey, we find that the career interests of many current and aspiring computer scientists diverge from the official profile of computer scientists established and promoted by the U.S. government – specifically that from the Department of Labor’s Occupational Information Network (O*NET). Five distinct profiles of career interests emerged from the data. Latent profile analysis suggests that many women in the profession value social and artistic expression in a way not currently recognized by official representations of computer scientists’ interests. Better admitting to a more nuanced and comprehensive picture of those interests has important implications for career guidance and workforce development and might help to address women’s underrepresentation in this STEM discipline. © 2021, CC BY.

关键词： Computer science   Neuroscience  

摘要： AI weather forecasters, mapping the human brain, and the 2021 science Nobel prizes.

关键词： Respiratory tract diseases   Imaging   Computer science  

摘要： The main purpose of this work is to investigate and compare several deep learning enhanced techniques applied to X-ray and CT-scan medical images for the detection of COVID-19. In this paper, we used four powerful pre-trained CNN models, VGG16, DenseNet121, ResNet50,and ResNet152, for the COVID-19 CT-scan binary classification task. The proposed *** ResNet framework was designed to find out the best architecture, pre-processing, and training parameters for the models largely automatically. The accuracy and F1-score were both above 96% in the diagnosis of COVID-19 using CT-scan images. In addition, we applied transfer learning techniques to overcome the insufficient data and to improve the training time. The binary and multi-class classification of X-ray images tasks were performed by utilizing enhanced VGG16 deep transfer learning architecture. High accuracy of 99% was achieved by enhanced VGG16 in the detection of X-ray images from COVID-19 and pneumonia. The accuracy and validity of the algorithms were assessed on X-ray and CT-scan well-known public datasets. The proposed methods have better results for COVID-19 diagnosis than other related in literature. In our opinion, our work can help virologists and radiologists to make a better and faster diagnosis in the struggle against the outbreak of COVID-19.

关键词： Computerized tomography  

摘要： Osteolysis is one of the most prominent reasons of revision surgeries in total joint arthroplasty. This biological phenomenon is induced by wear particles and corrosion products that stimulate inflammatory biological response of surrounding tissues. The eventual responses of osteolysis are the activation of macrophages leading to bone resorption and prosthesis failure. Various factors are involved in the initiation of osteolysis from biological issues, design, material specifications, and model of the prosthesis to the health condition of the patient. Nevertheless, the factors leading to osteolysis are sometimes preventable. Changes in implant design and polyethylene manufacturing are striving to improve overall wear. Osteolysis is clinically asymptomatic and can be diagnosed and analyzed during follow-up sessions through various imaging modalities and methods, such as serial radiographic, CT scan, MRI, and image processing-based methods, especially with the use of artificial neural network algorithms. Deep learning algorithms with a variety of neural network structures such as CNN, U-Net, and Seg-UNet have proved to be efficient algorithms for medical image processing specifically in the field of orthopedics for the detection and segmentation of tumors. These deep learning algorithms can effectively detect and analyze osteolytic lesions well in advance during follow-up sessions in order to administer proper treatments before reaching a critical point. Osteolysis can be treated surgically or nonsurgically with medications. However, revision surgeries are the only solution for the progressive osteolysis. In this literature review, the underlying causes, mechanisms, and treatments of osteolysis are discussed with the main focus on the possible computer-based methods and algorithms that can be effectively employed for the detection of osteolysis.

关键词： History of computing   clique detection   community detection   social networks   sociometry   graph analysis   algorithm  

摘要： Community detection is a major issue in network analysis. This paper combines a socio-historical approach with an experimental reconstruction of programs to investigate the early automation of clique detection algorithms, which remains one of the unsolved NP-complete problems today. The research led by the archaeologist Jean-Claude Gardin from the 1950s on non-numerical information and graph analysis is retraced to demonstrate the early contributions of social sciences and humanities. The limited recognition and reception of Gardin's innovative computer application to the humanities are addressed through two factors, in addition to the effects of historiography and bibliographies on the recording, discoverability, and reuse of scientific productions: (1) funding policies, evidenced by the transfer of research effort on graph applications from temporary interdisciplinary spaces to disciplinary organizations related to the then-emerging field of computer science;and (2) the erratic careers of algorithms, in which efficiency, flaws, corrections, and authors' status, were determining factors.

摘要： Virtual worlds are 3D environments where educators simulate real or imagined online learning spaces and teach classes within them. During a pandemic, it was a delightful experience to teach synchronous classes on a virtual beach or within a French village and to watch the student projects come to life.

摘要： The foundational aspects of computer science are usually explained with mathematical models such as Finite Automata (FA), Pushdown Automata (PDA) and Turing Machines (TMs) because understanding the scope and limitations of computation are inherently embedded in an overlapping area of mathematics, logic and cognition. This area is one of the most challenging fields in computer science. Students tend to engage, and participate actively when the basic ideas are introduced in a tutorial with multiple perspectives in multiple representations including transition graphs, tabular forms and coded strings. Mathematical proofs are provided in a gentle introductory session in order to help beginners.

摘要： The Coronavirus (COVID-19) epidemic environment has made academic institutions evaluate alternatives to traditional onsite classroom education. One of the options being studied is a strong and effective online system with virtual classrooms using state-of-the-art Learning Management Systems (LMS). In many Science, Technology, Engineering, and Math (STEM) scenarios, especially in Computer Science (CS) curriculums, these online systems perform as good as, or better than, the traditional onsite systems. Going forward, new challenges and opportunities with this new educational paradigm must be critically examined, and CS educators must strive to learn how to effectively teach in this online setting. This research focusses on undergraduate CS classes where most of the content is delivered virtually with the aid of online technologies. As more students enroll in virtual courses, questions, and concerns about ethical teaching practices in digital classrooms continue to surface. Handling of due process, freedom of expression, diversity among students, individual rights, etc. are among the many critical issues that need to be evaluated and carefully integrated in the content delivery and evaluation processes. Teachers are ethically accountable to serve the learning needs of all learners, and to do this they must recognize, understand, and appreciate the cultural backgrounds, values, beliefs, world views, and wide-ranging experiences that students bring to the class. Instructors must understand the motivations of these culturally diverse group of students to be able to connect with them, to motivate them, and to create a positive learning environment for the learners. CS education is important because it teaches logical and evidence-based critical thinking skills and develops a desire for innovation. Beyond the benefit of learning STEM, CS curriculums help learners in the problem-solving and exploratory learning that leads to success across a variety future endeavors across d