scholarly journals Autonomous Computing Materials

ACS Nano ◽  
2021 ◽  
Author(s):  
Mark Bathe ◽  
Rigoberto Hernandez ◽  
Takaki Komiyama ◽  
Raghu Machiraju ◽  
Sanghamitra Neogi
Keyword(s):  
2011 ◽  
pp. 2175-2205
Author(s):  
Nima Kaviani ◽  
Dragan Gaševic ◽  
Marek Hatala

Web rule languages have recently emerged to enable different parties with different business rules and policy languages to exchange their rules and policies. Describing the concepts of a domain through using vocabularies is another feature supported by Web rule languages. Combination of these two properties makes web rule languages appropriate mediums to make a hybrid representation of both context and rules of a policy-aware system. On the other hand, policies in the domain of autonomous computing are enablers to dynamically regulate the behaviour of a system without any need to interfere with the internal code of the system. Knowing that policies are also defined through rules and facts, Web rules and policy languages come to a point of agreement, where policies can be defined through using web rules. This chapter focuses on analyzing some of the most known policy languages (especially, KAoS policy language) and describes the mappings from the concepts for KAoS policy language to those of REWERSE Rule Markup Language (R2ML), one of the two proposals to Web rule languages.


Author(s):  
Mahesh Soni ◽  
Ravinder Dahiya

Inspired by biology, significant advances have been made in the field of electronic skin (eSkin) or tactile skin. Many of these advances have come through mimicking the morphology of human skin and by distributing few touch sensors in an area. However, the complexity of human skin goes beyond mimicking few morphological features or using few sensors. For example, embedded computing (e.g. processing of tactile data at the point of contact) is centric to the human skin as some neuroscience studies show. Likewise, distributed cell or molecular energy is a key feature of human skin. The eSkin with such features, along with distributed and embedded sensors/electronics on soft substrates, is an interesting topic to explore. These features also make eSkin significantly different from conventional computing. For example, unlike conventional centralized computing enabled by miniaturized chips, the eSkin could be seen as a flexible and wearable large area computer with distributed sensors and harmonized energy. This paper discusses these advanced features in eSkin, particularly the distributed sensing harmoniously integrated with energy harvesters, storage devices and distributed computing to read and locally process the tactile sensory data. Rapid advances in neuromorphic hardware, flexible energy generation, energy-conscious electronics, flexible and printed electronics are also discussed. This article is part of the theme issue ‘Harmonizing energy-autonomous computing and intelligence’.


Author(s):  
A. Serb ◽  
I. Kobyzev ◽  
J. Wang ◽  
T. Prodromakis

One of the main, long-term objectives of artificial intelligence is the creation of thinking machines. To that end, substantial effort has been placed into designing cognitive systems; i.e. systems that can manipulate semantic-level information. A substantial part of that effort is oriented towards designing the mathematical machinery underlying cognition in a way that is very efficiently implementable in hardware. In this work, we propose a ‘semi-holographic’ representation system that can be implemented in hardware using only multiplexing and addition operations, thus avoiding the need for expensive multiplication. The resulting architecture can be readily constructed by recycling standard microprocessor elements and is capable of performing two key mathematical operations frequently used in cognition, superposition and binding, within a budget of below 6 pJ for 64-bit operands. Our proposed ‘cognitive processing unit’ is intended as just one (albeit crucial) part of much larger cognitive systems where artificial neural networks of all kinds and associative memories work in concord to give rise to intelligence. This article is part of the theme issue ‘Harmonizing energy-autonomous computing and intelligence’.


Author(s):  
O. C. Akgun ◽  
J. Mei

This paper presents the design of an ultra-low energy neural network that uses time-mode signal processing). Handwritten digit classification using a single-layer artificial neural network (ANN) with a Softmin-based activation function is described as an implementation example. To realize time-mode operation, the presented design makes use of monostable multivibrator-based multiplying analogue-to-time converters, fixed-width pulse generators and basic digital gates. The time-mode digit classification ANN was designed in a standard CMOS 0.18 μm IC process and operates from a supply voltage of 0.6 V. The system operates on the MNIST database of handwritten digits with quantized neuron weights and has a classification accuracy of 88%, which is typical for single-layer ANNs, while dissipating 65.74 pJ per classification with a speed of 2.37 k classifications per second. This article is part of the theme issue ‘Harmonizing energy-autonomous computing and intelligence’.


Author(s):  
Varatharajan Ramachandran

This special issue of the Journal of Intelligent & Fuzzy Systems contains selected articles of Fuzzy model for human autonomous computing in extreme surveillance and it’s applications


2008 ◽  
Vol 9 (3) ◽  
pp. 403-414 ◽  
Author(s):  
Bernard Dionysius Geoghegan

World War II research into cryptography and computing produced methods, instruments and research communities that informed early research into artificial intelligence (AI) and semi-autonomous computing. Alan Turing and Claude Shannon in particular adapted this research into early theories and demonstrations of AI based on computers’ abilities to track, predict and compete with opponents. This formed a loosely bound collection of techniques, paradigms, and practices I call crypto-intelligence. Subsequent researchers such as Joseph Weizenbaum adapted crypto-intelligence but also reproduced aspects of its antagonistic precepts. This was particularly true in the design and testing of chat bots. Here the ability to trick, fool, and deceive human and machine opponents was a premium, and practices of agent abuse were admired and rewarded. Recognizing the historical genesis of this particular variety of abuse can help researchers develop less antagonistic methodologies.


Nature ◽  
2001 ◽  
Vol 414 (6862) ◽  
pp. 430-434 ◽  
Author(s):  
Yaakov Benenson ◽  
Tamar Paz-Elizur ◽  
Rivka Adar ◽  
Ehud Keinan ◽  
Zvi Livneh ◽  
...  

2003 ◽  
Vol 13 (04) ◽  
pp. 615-627 ◽  
Author(s):  
IOANNIS CHATZIGIANNAKIS ◽  
TASSOS DIMITRIOU ◽  
MARIOS MAVRONICOLAS ◽  
SOTIRIS NIKOLETSEAS ◽  
PAUL SPIRAKIS

Smart Dust is comprised of a vast number of ultra-small fully autonomous computing and communication devices, with very restricted energy and computing capabilities, that co-operate to accomplish a large sensing task. Smart Dust can be very useful in practice i.e. in the local detection of a remote crucial event and the propagation of data reporting its realization to a control center. In this work, we have implemented and experimentally evaluated four protocols ( [Formula: see text], [Formula: see text] and two variations of [Formula: see text] which we here introduce ) for local detection and propagation in smart dust networks, under new, more general and realistic modelling assumptions. We comparatively study, by using extensive experiments, their behavior highlighting their relative advantages and disadvantages. All protocols are very successful. In the setting we considered here, [Formula: see text] seems to be faster while the [Formula: see text] based protocols are more energy efficient.


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