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关键词： Indexes   Clustering methods   Shape   Principal component analysis   Computer science   Information technology   Entropy   Centroid-based clustering   cluster validity index (CVI)   fuzzy c-means (FCM)   hyperellipsoid or hyperspherical clusters  

摘要： Determining the correct number of clusters is essential for efficient clustering and cluster validity indices are widely used for the same. Generally, the effectiveness of a cluster validity index relies on two factors: first, separation, defined by the distance between a pair of cluster centroids or a pair of data points belonging to different clusters and second, compactness, which is determined in terms of the distance between a data point and a centroid or between a pair of data points belonging to the same cluster. However, the existing cluster validity indices for centroid-based clustering are unreliable when the clusters are too close, but corresponding centroids are distant. To mitigate this, a new cluster validity index, Saraswat-and-Mittal index, has been proposed in this article for hyperellipsoid or hyperspherical shape close clusters with distant centroids, generated by fuzzy c-means. The proposed index computes compactness in terms of the distance between data points and corresponding centroids, whereas the distance between data points of disjoint clusters defines separation. These parameters benefit the proposed index in the analysis of close clusters with distinct centroids efficiently. The performance of the proposed index is validated against ten state-of-the-art cluster validity indices on artificial, UCI, and image datasets, clustered by the fuzzy c-means.

关键词： Behavioral research  

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. Copyright © 2021, The Authors. All rights reserved.

关键词： Molecular orbitals  

摘要： With the rapid development of quantum technology, one of the leading applications that has been identified is the simulation of chemistry. Interestingly, even before full scale quantum computers are available, quantum computer science has exhibited a remarkable string of results that directly impact what is possible in a chemical simulation with any computer. Some of these results even impact our understanding of chemistry in the real world. In this Perspective, we take the position that direct chemical simulation is best understood as a digital experiment. While on the one hand, this clarifies the power of quantum computers to extend our reach, it also shows us the limitations of taking such an approach too directly. Leveraging results that quantum computers cannot outpace the physical world, we build to the controversial stance that some chemical problems are best viewed as problems for which no algorithm can deliver their solution, in general, known in computer science as undecidable problems. This has implications for the predictive power of thermodynamic models and topics such as the ergodic hypothesis. However, we argue that this Perspective is not defeatist but rather helps shed light on the success of existing chemical models such as transition state theory, molecular orbital theory, and thermodynamics as models that benefit from data. We contextualize recent results, showing that data-augmented models are a more powerful rote simulation. These results help us appreciate the success of traditional chemical theory and anticipate new models learned from experimental data. Not only can quantum computers provide data for such models, but they can also extend the class and power of models that utilize data in fundamental ways. These discussions culminate in speculation on new ways for quantum computing and chemistry to interact and our perspective on the eventual roles of quantum computers in the future of chemistry.

关键词： Biomedical engineering   Computer science  

摘要： Human movement researchers are often restricted to laboratory environments and data capture techniques that are time and/or resource intensive. Markerless pose estimation algorithms show great potential to facilitate large scale movement studies 'in the wild', i.e., outside of the constraints imposed by marker-based motion capture. However, the accuracy of such algorithms has not yet been fully evaluated. We computed 3D joint centre locations using several pre-trained deep-learning based pose estimation methods (OpenPose, AlphaPose, DeepLabCut) and compared to marker-based motion capture. Participants performed walking, running and jumping activities while marker-based motion capture data and multi-camera high speed images (200 Hz) were captured. The pose estimation algorithms were applied to 2D image data and 3D joint centre locations were reconstructed. Pose estimation derived joint centres demonstrated systematic differences at the hip and knee (similar to 30-50 mm), most likely due to mislabeling of ground truth data in the training datasets. Where systematic differences were lower, e.g., the ankle, differences of 1-15 mm were observed depending on the activity. Markerless motion capture represents a highly promising emerging technology that could free movement scientists from laboratory environments but 3D joint centre locations are not yet consistently comparable to marker-based motion capture.

关键词： Situated learning   Computer science   Collaborative learning   Hands-on experience   Human-robot interaction   Teamwork  

摘要： With the increasing employment of robots in multiple areas such as smart manufacturing and intelligent transportation, both undergraduate and graduate students from computing related majors (e.g., computer science and information technology) demonstrated strong interests in learning robotics technology to broaden their career opportunities. However, instilling computing students with robotics knowledge remains a challenge since most of them have limited pre-training in engineering subjects such as electronics and mechatronics. Therefore, robotics education for computing students demands an immersive real-world learning environment by considering both theories and intensive hands-on projects. Different from traditional textbook-directed robotics learning, in this study, a situated learning-based robotics education pedagogy is proposed for computing students to equip them with robotics expertise and foster their problem-solving skills in real-world human-robot interaction contexts. To create a realistic human-robot collaboration situation, a multi-modal collaborative robot is employed in the classroom-based learning community for the whole semester. Mini-project-based homework and team projects are designed for students to practice their critical thinking and hands-on experiences. The bidirectional-evaluation approach is utilized by the instructor and students to assess the quality of the proposed pedagogy. Practice results and student evaluations suggested that the proposed situated learning-based pedagogy and robotics curriculum provided computing students to learn robotics in an effective way, which was well recognized and accepted by students even most of them were beginners. Future work of this study is also discussed.

关键词： Edge computing  

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-SA.

关键词： Careers   Computer science   Machine learning   Technology  

摘要： Collaborations across disciplines are growing, and artificial intelligence is helping to make joint working more effective.

关键词： Students  

摘要： In the School of Computing at the Dublin Institute of Technologyii (DIT), Ireland, we undertook our "Computer Science for All" (CS4All) initiative, a five year strategy to implement structural reforms at Faculty level, to address recruitment and retention issues of female undergraduate computer science (CS) students. Since 2012, under CS4All we implemented a variety of reforms to improve student retention, set up a new CS programme to attract more female students, and delivered changes to promote a sense of community amongst our female students. We have made significant improvements. For example, we have achieved a dramatic improvement in retention rising from 45% to 89% in first year progression rates. Our new hybrid CS International programme has more than double the percentage of females first year enrolments in comparison to our other undergraduate programmes. As at 2018, we continue to roll out the remaining parts of CS4All within our School. © 2021, CC BY-NC-SA.

摘要： As at 2019, Technological University Dublin* Computer Science is the top university in Ireland in terms of gender balance of female academic staff in computer science schools. In an academic team of approximately 55 full-time equivalents, 36% of our academic staff are female, 50% of our senior academic leadership team (2 of 4) are female and 75% of our School Executive are female (3 of 4), including a female Head of School. This is as a result of our seven year SUCCESS programme which had a four strand approach: Source, Career, Environment and Support. The Source strand explicitly encouraged females to apply for each recruitment drive;Career focused on female career and skills development initiatives;Environment created a female-friendly culture and reputation, both within the School, across our organisation and across the third level sector in Ireland and Support addressed practical supports for the specific difficulties experienced by female staff. As a result we have had 0% turnover in female staff in the past five years (in contrast to 10% male staff turnover). We will continue to work across these four strands to preserve our pipeline of female staff and ensure their success over the coming years in an academic and ICT sector that remains challenging for females. © 2021, CC BY-NC-SA.