scholarly journals System Sensitivity Analysis: Benchmark Papers in Electrical Engineering and Computer Science

1975 ◽  
Vol 97 (2) ◽  
pp. 209-209
Author(s):  
Jose´ Cruz ◽  
S. H. Johnson
Keyword(s):  
Sensitivity Analysis ◽  
Computer Science ◽  
Electrical Engineering ◽  
System Sensitivity

Dagstuhl-Seminar “Dynamically and Partially Reconfigurable Architectures” (Dynamisch und partiell rekonfigurierbare Architekturen)

2004 ◽  
Vol 46 (4) ◽  
Author(s):  
Jürgen Becker
Keyword(s):  
Information Technology ◽  
Parallel Computing ◽  
Computer Science ◽  
Mobile Communication ◽  
Data Stream ◽  
Electrical Engineering ◽  
Reconfigurable Architectures ◽  
Automotive Application ◽  
Partial Reconfiguration ◽  
Computing Technique

SummaryThe paper addresses people from information technology, electrical engineering, computer science, and related areas. It gives an introduction and classification to fine-, coarse-, as well as multi-grain reconfigurable architectures. This data-stream-based and transport-triggered parallel computing technique in combination with dynamical and partial reconfiguration features demonstrates promising perspectives for future CMOS-based microelectronic solutions in multimedia and infotainment, mobile communication, as well as automotive application domains, among others.

Your Life in Binary Digits

Digitized ◽  
2012 ◽  
Author(s):  
Peter J. Bentley
Keyword(s):  
Computer Science ◽  
Electronic Computer ◽  
Electrical Engineering ◽  
University Of Pennsylvania ◽  
Monday Morning ◽  
Lecture Room ◽  
New Ideas ◽  
The Mind ◽  
The University ◽  
Digital Computers

Your ideas, money, memories, and entertainment are dreams in the minds of computers. But the thoughts of each computer are not simple, they are layered like our own minds. Their lowest, most primitive layers are the instincts of the machine. Middle layers perform more general functions of its silicon mind. Higher layers think about overall concepts. Unlike us, the computer has languages for every layer. We can teach it new ideas by changing any one or all of its layers of thought. We can tell it to consider vast and convoluted concepts. But if we make a single mistake in our instructions, the mind of our digital slave may crash in a virtual epileptic fit. When our silicon students are so pedantic, how can we engineer their thoughts to make them reliable and trustworthy assistants? And if their thoughts become more complicated than anything we can imagine, how can we guarantee they will do what we want them to? . . . Light poured in through the large windows of the lecture room. The sound of scratching pens from nearly thirty distinguished engineers and scientists accompanied every word spoken by John Mauchly. One fellow by the name of Gard from the Wright Field’s Armament Laboratory seemed to be especially diligent, writing hundreds of pages of notes. It was Monday morning, a warm mid-summer day of 1946, some three years after his stimulating tea-time discussions with Turing. Claude Shannon was three weeks into the eight-week course at the Moore School of Electrical Engineering, in the University of Pennsylvania. It had been an honour to be one of the select few invited to hear lectures on designing electronic digital computers. This was the first ever course to be taught on computer science, and Shannon was finding many of the ideas highly stimulating. He’d recently learned a new word from Mauchly: ‘program’ used as a verb. To program an electronic computer was an interesting concept. He was also hearing about some of the politics: apparently two of the lecturers, Mauchly and his colleague Eckert, had resigned from the university just four months ago because of some form of disagreement.

Enterpreneurial Incentives, Obstacles, and Management in University-Business Co-Operation

2016 ◽  
pp. 499-518
Author(s):  
Firmansyah David ◽  
Peter van der Sijde ◽  
Peter van den Besselaar
Keyword(s):  
Computer Science ◽  
Case Studies ◽  
Electrical Engineering ◽  
Basic Research ◽  
Private University ◽  
Vice President ◽  
Structured Interviews ◽  
Managerial Implication ◽  
Business World ◽  
Common Perception

The study in this chapter aimed to explore the perception of university managers and academics towards incentives and obstacles of university-business co-operation. For this purpose, case studies were conducted in a public and a private university in Indonesia. Data was collected through semi-structured interviews with university managers: University Vice President and the Head of Research and Community Service Office; and with academics at the department of electrical engineering and computer science. The results suggest that both organizational actors at both universities share a common perception that industrial funding; organizational and individual reputation; trust from industries and applied research are the incentives in the creation of university-business co-operation; whilst bureaucracy, industrial commitment, different in vision and orientation, teaching obligation and basic research have been considered as the obstacles. This study proposes a managerial implication. University managers should ‘recognize' the ‘skills' of individual academics in business before engaging them in university-business co-operation. Furthermore, individual academics should able to manage the different vision and orientation with the business world.

The Pransky interview: Dr Ken Goldberg, Professor, Industrial Engineering and Operations Research, UC Berkeley; Inventor and Artist

2019 ◽  
Vol 46 (2) ◽  
pp. 188-191
Author(s):  
Joanne Pransky
Keyword(s):  
Computer Science ◽  
San Francisco ◽  
Operations Research ◽  
Industrial Robot ◽  
Electrical Engineering ◽  
Medical Robotics ◽  
Industrial Engineering ◽  
Science And Engineering ◽  
Content Type ◽  
The University

Purpose The following article is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business, and personal experience of a prominent, robotic industry PhD and inventor regarding his pioneering efforts and the commercialization of bringing a technological invention to market. The paper aims to discuss these issues. Design/methodology/approach The interviewee is Dr Ken Goldberg, an inventor working at the intersection of art, robotics, and social media. He joined the UC Berkeley faculty in 1995 where he is the UC Berkeley William S. Floyd Jr Distinguished Chair in Engineering and recently served as Chair of the Industrial Engineering and Operations Research Department. He has secondary appointments in UC Berkeley’s Electrical Engineering/Computer Science, Art Practice and the School of Information. Goldberg also holds an appointment at the UC San Francisco Medical School’s Department of Radiation Oncology where he pursues research in medical robotics. Goldberg is Director of the CITRIS “People and Robots” Initiative and the UC Berkeley’s Laboratory for Automation Science and Engineering (AUTOLAB) where he and his students research machine learning for robotics and automation in warehouses, homes, and operating rooms. In this interview, Goldberg shares some of his personal and business perspectives from his career-long pursuit of making robots less clumsy. Findings Goldberg earned dual BS degrees in Electrical Engineering and Economics from the University of Pennsylvania in 1984, and MS and PhD degrees in Computer Science from Carnegie Mellon University in 1990. Goldberg also studied at Edinburgh University and the Technion. From 1991-95 he taught at the University of Southern California, and in fall 2000, he was visiting faculty at the MIT Media Lab. Goldberg and his students pursue research in three primary areas: Geometric Algorithms for Automation, Cloud Robotics, and Robot Learning. Originality/value Goldberg developed the first complete algorithms for part feeding and part fixturing, and developed the first robot on the Internet. His inventions have been awarded nine US Patents. Goldberg has published over 250 peer-reviewed technical papers and edited four books. He co-founded and served as Editor-in-Chief of the IEEE Transactions on Automation Science and Engineering (T-ASE). He is also Co-Founder of the Berkeley AI Research (BAIR) Lab, the Berkeley Center for New Media (BCNM), the African Robotics Network (AFRON), the Center for Automation and Learning for Medical Robotics (CAL-MR), the CITRIS Data and Democracy Initiative (DDI), Hybrid Wisdom Labs, and Moxie Institute. He has presented over four hundred keynote and invited lectures. Goldberg's artwork, closely linked with his research, has appeared in over seventy venues. Ken was awarded the Presidential Faculty Fellowship in 1995 by Bill Clinton, the Joseph Engelberger Robotics Award in 2000, elected IEEE Fellow in 2005, and selected by the IEEE Robotics and Automation Society for the George Saridis Leadership Award in 2016.

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