Trends in Mobile Computing: State-of-the-Art and Next Steps
Bibliographic record
Abstract
Computing is moving to the edge of the network. It is becoming increasingly personal and allowing people to enjoy and express themselves in unprecedented ways. The same development allows professionals and enterprises to increase quality and productivity through improved mobility. The seminar discusses the underlying technical and societal trends and the state-of-the-art of mobile computing. Examples of current developments include the transformation of mobile devices into servers, augmented reality in mobile devices and the opportunities offered by wireless sensor networks. The fusion of the physical and digital worlds enabled by mobile computing is driving industry and society to adopt new uses of digital technologies and causing the focus of development to shift from hardware products to new services. Bio:Since 2004 Prof. Jan Bosch is working as Vice President and Head of the Software and Application Technology Laboratory of Nokia Research Centre in Helsinki, Finland. The Software & Application Technologies lab explores emerging software technologies and enablers, studies user experience and behavior and innovates and prototypes novel software applications. The laboratory also carries out research and development in Nokia software platforms, tools and architectures. Before joining Nokia, Prof. Bosch was head of the software engineering research group at the University of Groningen, The Netherlands, where he held a professorship in software engineering. His research activities include software architecture design, software product families, software variability management and component-oriented programming. Speaker bio:As President and Co-CEO of Research In Motion (RIM), a company Mr. Lazaridis founded while a student at the University of Waterloo, he is responsible for product strategy, research and development, product development, and manufacturing. RIM are manufacturers of the renowned BlackBerry handheld wireless device, Mr. Lazaridis is also a leader in his community and a passionate advocate for education and scientific research. Mr. Lazaridis is also a long-standing member of the Board of Governors of the University of Waterloo and, in May 2003, was installed as its chancellor. Mr. Lazaridis supports his community and country through generous philanthropic gifts made possible by his success in business. He has donated 50 million dollars to the University of Waterloo to help establish an Institute for Quantum Computing. His most noted gift of 100 million dollars established Perimeter Institute for Theoretical Physics. Since its opening in 2001, Perimeter has attracted the attention of the world's scientific community. In 2002, Mr. Lazaridis shared Canada's most prestigious innovation prize, The Ernest C. Manning Principal Award, with RIM colleague Gary Mousseau.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".