Several novel portable and wearable form factors have been prototyped at IBM over the last eight years. Each of the different form factors has some unique advantages and addresses different user needs this invited pap...
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ISBN:
(纸本)0769524206
Several novel portable and wearable form factors have been prototyped at IBM over the last eight years. Each of the different form factors has some unique advantages and addresses different user needs this invited paper will present our experience building these prototypes and describe how improvements in technology have advanced our prototypes over time. Recently we have been investigating the middleware necessary to use a collection of devices symbiotically to address some of the limitations of each form factor. Drawbacks of some form factors include battery, small screen size, limited bandwidth and limited user interface capability. However form factors with such limitations also typically come with several advantages, i.e., they are always with you and provide a private display and a trusted platform. the paper will sketch a few applications that could use devices symbiotically and outline some of the challenges that need to be overcome to enable this symbiosis.
the proceedings contain 195 papers. the topics discussed include: detecting pedestrians behavior in building based on Wi-Fi signals;e-health services for elderly care based on Google cloud messaging;on interesting pla...
ISBN:
(纸本)9781509018932
the proceedings contain 195 papers. the topics discussed include: detecting pedestrians behavior in building based on Wi-Fi signals;e-health services for elderly care based on Google cloud messaging;on interesting place finding in social sensing: an emerging smart city application paradigm;collaborative representation-based robust face recognition by discriminative low-rank representation;a self-adaptive video dual watermarking based on the motion characteristic and geometric invariant for ubiquitous multimedia;the role of big data on smart grid transition;sensing information modeling for smart city;exploration of collective pattern to improve location prediction of mobile phone users;performance modeling of preemption-based packet scheduling for data plane in software defined networks;and aspect-oriented customization of the scheduling algorithms and the resource access protocols of a real-time operating system family.
Argument detection and its representation through ontologies are important parts of today's attempt in automated recognition and processing of useful information in the vast amount of constantly produced data. How...
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ISBN:
(纸本)9789897583773
Argument detection and its representation through ontologies are important parts of today's attempt in automated recognition and processing of useful information in the vast amount of constantly produced data. However, due to the highly complex nature of an argument and its characteristics, its automated recognition is hard to implement. Given this overall challenge, as part of the objectives of the RecomRatio project, we are interested in the traceable, automated stance detection of arguments, to enable the construction of explainable pro/con argument ontologies. In our research, we design and evaluate an explainable machine learning based classifier, trained on two publicly available data sets. the evaluation results proved that explainable argument stance recognition is possible with up to .96 F1 when working within the same set of topics and .6 F1 when working with entirely different topics. this informed our hypothesis, that there are two sets of features in argument stance recognition: General features and topic specific features.
this paper presents a 'Unified Side Channel Attack Model' (USCA-M). the USCA-M model is compiled by the research undertaken of side-channel attacks (SCAs) from published journal articles and conference papers ...
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the proceedings contain 164 papers. the topics discussed include: performance comparison of IEEE 802.1Q and IEEE 802.1 AVB in an Ethernet-based in-vehicle network;a fast seat assignment algorithm based-on bucket data ...
ISBN:
(纸本)9788988678671
the proceedings contain 164 papers. the topics discussed include: performance comparison of IEEE 802.1Q and IEEE 802.1 AVB in an Ethernet-based in-vehicle network;a fast seat assignment algorithm based-on bucket data structure;a two-phase iterative pre-copy strategy for live migration of virtual machines;an empirical evaluation and improvement of the item balancing algorithm in P2P systems;towards high performance and usability programming model for heterogeneous HPC platforms;saving streaming bandwidth via wireless sharing for a tree-based live streaming system on public-shared network;a novel pattern of distributed low-rate denial of service attack disrupts Internet routing;achieving maximum performance for matrix multiplication using set associative cache;a user context recognition method for ubiquitous computing systems;the influence factors to the enterprise microblogs - a research of the restaurant enterprise microblogs on ***;and common-sense reasoning in constructive discursive logic.
this book constitutes the refereed proceedings of the 8thinternationalconference on Intelligent Data Analysis, IDA 2009, held in Lyon, France, August 31 September 2, 2009. the 33 revised papers, 18 full oral present...
ISBN:
(数字)9783642039157
ISBN:
(纸本)9783642039140
this book constitutes the refereed proceedings of the 8thinternationalconference on Intelligent Data Analysis, IDA 2009, held in Lyon, France, August 31 September 2, 2009. the 33 revised papers, 18 full oral presentations and 15 poster and short oral presentations, presented were carefully reviewed and selected from almost 80 submissions. All current aspects of this interdisciplinary field are addressed; for example interactive tools to guide and support data analysis in complex scenarios, increasing availability of automatically collected data, tools that intelligently support and assist human analysts, how to control clustering results and isotonic classification trees. In general the areas covered include statistics, machine learning, data mining, classification and patternrecognition, clustering, applications, modeling, and interactive dynamic data visualization.
the proceedings contain 164 papers. the topics discussed include: performance comparison of IEEE 802.1Q and IEEE 802.1 AVB in an Ethernet-based in-vehicle network;a fast seat assignment algorithm based-on bucket data ...
ISBN:
(纸本)9788988678671
the proceedings contain 164 papers. the topics discussed include: performance comparison of IEEE 802.1Q and IEEE 802.1 AVB in an Ethernet-based in-vehicle network;a fast seat assignment algorithm based-on bucket data structure;a two-phase iterative pre-copy strategy for live migration of virtual machines;an empirical evaluation and improvement of the item balancing algorithm in P2P systems;towards high performance and usability programming model for heterogeneous HPC platforms;saving streaming bandwidth via wireless sharing for a tree-based live streaming system on public-shared network;a novel pattern of distributed low-rate denial of service attack disrupts Internet routing;achieving maximum performance for matrix multiplication using set associative cache;a user context recognition method for ubiquitous computing systems;the influence factors to the enterprise microblogs - a research of the restaurant enterprise microblogs on ***;and common-sense reasoning in constructive discursive logic.
this paper formulates a pattern search method for nonlinear programming. A distributed parallel algorithm is given based on the pattern search method by distributing the direction to every processor. Promising experim...
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Proposed method, called Probabilistic Nodes Combination (PNC), is the method of 2D curve modeling and interpolation using the set of key points. Nodes are treated as characteristic points of unknown object for modelin...
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ISBN:
(纸本)9783319238142;9783319238135
Proposed method, called Probabilistic Nodes Combination (PNC), is the method of 2D curve modeling and interpolation using the set of key points. Nodes are treated as characteristic points of unknown object for modeling and recognition. Identification of shapes or symbols need modeling and each model of the pattern is built by a choice of probability distribution function and nodes combination. PNC modeling via nodes combination and parameter. as probability distribution function enables curve parameterization and interpolation for each specific object or symbol. Two-dimensional curve is modeled and interpolated via nodes combination and different functions as continuous probability distribution functions: polynomial, sine, cosine, tangent, cotangent, logarithm, exponent, arc sin, arc cos, arc tan, arc cot or power function.
the fuzzy min-max (FMM) neural network is one of the most powerful neural networks that combines neural network and fuzzy set theory into a common framework for tackling pattern classification problems. FMM neural net...
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