ppxscal/embedding_network huggingface dataset:
Fusing Animals and Humans
Authors: Jonathan Connell
Venue: Proceeding of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference (2008)

AI has many techniques and tools at its disposal, yet seems to be lacking some special “juice” needed to create a true being. We propose that the missing ingredients are a general theory of motivation and an operational understanding of natural language. The motivation part comes largely from our animal heritage: a real-world agent must continually respond to external events rather than depend on perfect modeling and planning. The language part, on the other hand, is what makes us human: competent participation in a social group requires one-shot learning and the ability to reason about objects and activities that are not present or on-going. In this paper we propose an architecture for self-motivation, and suggest how a language interpreter can be built on top of such a substrate. With the addition of a method for recording and internalizing dialog, we sketch how this can then be used to impart essential cultural knowledge and behaviors.
Plenary lecture VII: vision based measurement systems
Authors: Radu I. Munteanu
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

The field of food industry is nowadays governed by some of the toughest regulations ever seen in industry in order to maintain the quality of practices such as product traceability and hygiene. Beside these it is required to maintain flexible processes in order to allow alternative products specifications, while maximizing robotic utilization. It is therefore no surprise that this field is very active in introducing automated systems to perform many tasks. The recent advances in semiconductor technology allow to design and implement advanced mathematical methods on low cost hardware platforms. It is a desiderate for smart sensor systems to implement mechanisms similar to the humans mental activity of combining information for the goal of recognizing a measurand that is hardly distinguishable with a single sensor. This presentation will introduce the concept of virtual sensor. A vision based contactless weighting sensor will be presented together with the mathematical foundations required for building and calibrating it. Its real-time performance is demonstrated through the implementation of an automatic sorting system. Further improvements and optimization techniques are introduced in order to make the system able to maximize yield of edible product, reduce labor requirements of the complete system, to provide a process compatible with most current plants and to improve overall plant productivity.
A tree-to-tree model for statistical machine translation
Authors: Michael J. Collins
Venue:  (2008)

In this thesis, we take a statistical tree-to-tree approach to solving the problem of machine translation (MT). In a statistical tree-to-tree approach, first the source-language input is parsed into a syntactic tree structure; then the source-language tree is mapped to a target-language tree. This kind of approach has several advantages. For one, parsing the input generates valuable information about its meaning. In addition, the mapping from a source-language tree to a target-language tree offers a mechanism for preserving the meaning of the input. Finally, producing a target-language tree helps to ensure the grammaticality of the output. A main focus of this thesis is to develop a statistical tree-to-tree mapping algorithm. Our solution involves a novel representation called an aligned extended projection, or AEP. The AEP, inspired by ideas in linguistic theory related to tree-adjoining grammars, is a parse-tree like structure that models clause-level phenomena such as verbal argument structure and lexical word-order. The AEP also contains alignment information that links the source-language input to the target-language output. Instead of learning a mapping from a source-language tree to a target-language tree, the AEP-based approach learns a mapping from a source-language tree to a target-language AEP. The AEP is a complex structure, and learning a mapping from parse trees to AEPs presents a challenging machine learning problem. In this thesis, we use a linear structured prediction model to solve this learning problem. A human evaluation of the AEP-based translation approach in a German-to-English task shows significant improvements in the grammaticality of translations. This thesis also presents a statistical parser for Spanish that could be used as part of a Spanish/English translation system. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Degree-of-interest trees: a component of an attention-reactive user interface
Authors: Stuart K. Card, David Nation
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

This paper proposes Degree-of-Interest trees. These trees use degree-of-interest calculations and focus+context visualization methods, together with bounding constraints, to fit within pre-established bounds. The method is an instance of an emerging "attention-reactive" user interface whose components are designed to snap together in bounded spaces.
Design science as nested problem solving
Authors: Roel Wieringa
Venue: Proceedings of the 4th International Conference on Design Science Research in Information Systems and Technology (2009)

Design science emphasizes the connection between knowledge and practice by showing that we can produce scientific knowledge by designing useful things. However, without further guidelines, aspiring design science researchers tend to identify practical problems with knowledge questions, which may lead to methodologically unsound research designs. To solve a practical problem, the real world is changed to suit human purposes, but to solve a knowledge problem, we acquire knowledge about the world without necessarily changing it. In design science, these two kinds of problems are mutually nested, but this nesting should not blind us for the fact that their problem-solving and solution justification methods are different. This paper analyzes the mutual nesting of practical problems and knowledge problems, derives some methodological guidelines from this for design science researchers, and gives an example of a design science project following this problem nesting.
Application of the alternating group explicit method for convection-diffusion equations
Authors: Qinghua Feng, Bin Zheng
Venue: WSEAS Transactions on Mathematics (2009)

Based on an unconditionally stable finite difference implicit scheme, we present a concept of deriving a class of effective alternating group explicit iterative method for periodic boundary value problem of convection-diffusion equations, and then give two iterative methods. The methods are verified to be convergent, and have the property of parallelism. Furthermore we construct an alternating group explicit difference method and another iterative method. All of the methods are suitable for parallel computation. Results of numerical experiments show that the methods are of higher accuracy than the known methods in [1,2,6], and will not lead to numerical instability in convection dominant case.
Fabrication of bioceramic&#47;biopolymer bone implants using selective laser sintering
Authors: F. Cruz, T. Coole
Venue: International Journal of Computer Applications in Technology (2009)

This paper presents an overview of the research work carried out for the rapid manufacture of hydroxyapatite (HA) based components by means of Selective Laser Sintering (SLS) technique, to be used for bone tissue implantation aiming to replace and&#47;or repair bone defects due to traumatised, damaged or lost bone. SLS is a Rapid Prototyping Technology (RPT) that selectively sinters powders of engineering materials by means of a CO&lt;SUB align=right&gt;2 laser. HA is a bioceramic used since several years for medical applications although being mainly processed by conventional methods (cast, machined or manually produced). For this purpose CAD&#47;CAM, RPT and medical imaging techniques were integrated and this enabled the customised production of anatomical models. This approach provides a direct method of producing HA-based prostheses.
Long-Term Human-Robot Interaction: The Personal Exploration Rover and Museum Docents
Authors: Kristen Stubbs, Debra Bernstein, Kevin Crowley, Illah Nourbakhsh
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

As an increasing number of robots have been designed to interact with people on a regular basis, research into human-robot interaction has become more widespread. At the same time, little work has been done on the problem of long-term human-robot interaction, in which a human uses a robot for a period of weeks or months. As people spend more time with a robot, it is expected that how they make sense of the robot-their “cognitive model” of it-may change over time. In order to identify factors that will be critical to the future development of a quantitative cognitive model of long-term human-robot interaction, a study was conducted involving the Personal Exploration Rover (PER) museum exhibit and the museum employees responsible for it. Results of the study suggest that these critical factors include how people experience successes and failures with the robot (as opposed to how they understand its capabilities) and how people anthropomorphize the robot and talk about anthropomorphization.
An approach to fault diagnosis of rolling bearings
Authors: A. A. Roque, T. A. N. Silva, J. M. F. Calado, C. Q. Dias
Venue: WSEAS Transactions on Systems and Control (2009)

The present paper aims to demonstrate why usually when theoretical mathematical models are used to compute the frequencies corresponding to a faulty rolling bearing a deviation is obtained between the computed values and the real frequencies emitted by such a device. A laboratory rolling bearing test ring has been developed to perform the current studies. From the obtained results we highlight the impact of the cage rotation frequency on the referred deviation of measured values from the theoretical ones.
Recycling policy making of organic waste using analytical network process
Authors: Kazuei Ishii, Toru Furuichi
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

The Analytic Hierarchy Process (AHP) has been used widely in multicriteria selection problems. However, AHP can deal with only a simple hierarchy of elements. On the other hand, the Analytical Network Process (ANP) can deal with more complex structures that have some interdependence or feedback between elements. This study attempted to apply ANP to recycling policy making of organic waste in a region where a large amount of kitchen waste and livestock manure are generated as solid waste. Using the weightings given by interviews with five specialists who are familiar with solid waste management in the region, ANP selected alternatives that included biogasification of kitchen wastes and livestock manure, and it clarified why those alternatives were selected. In addition, a compatibility quotient was proposed as an index to promote a group discussion for the selection of recycling systems. This index was found to be useful for helping to identify the attitude of each decision maker in a group discussion.
A Hybrid Algorithm of GA Wavelet-BP Neural Networks to Predict Near Space Solar Radiation
Authors: Jianmin Su, Bifeng Song, Baofeng Li
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

Solar radiation is affected by many factors, solar radiation prediction is a highly nonlinear problem. It is hard to establish any analytical mathematical model. Considering solar radiation ray is composed of a series of different frequency bands with different characteristics, wavelet is introduced to decompose the radiation signal into high and low frequency hefts. By respectively inputting the hefts into BP neural networks, which have strong fault-tolerant ability and nonlinear mapping ability, better prediction precision can be obtained. But BP neural networks are apt to converge at local optimal point, so genetic algorithm is embedded to optimize BP neural networks' weights and threshold values,hybrid algorithm's prediction precision is receivable through these improvements.
Face recognition using principle components and linear discriminant analysis
Authors: Hatim A. Aboalsamh, Hassan I. Mathkour, Ghazy M. R. Assassa, Mona F. M. Mursi
Venue: Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation (2009)

Face recognition has recently received significant attention as one of the challenging and promising fields of computer vision and pattern recognition. It plays a significant role in many security and forensic applications such as person authentication in access control systems and person identification in real time video surveillance systems. This paper studies two appearance-based approaches for feature extraction and dimension reduction, namely, Principal Components Analysis (PCA) and Linear Discriminant Analysis (LDA). Numerical experiments were carried out on the ORL face database and many parameters were investigated, this included the effect of changing the number of training images, scaling factor, and the effect of feature vector length on the recognition rate. Classification is performed using the minimum Euclidean distance. The results suggest that the effect of increasing the number of training images has more significance on the recognition rate than changing the image scale. Correlations obtained from numerical experiments on the ORL face database suggest that as the number of training images increases, PCA would yield slightly higher recognition rates.
Towards the Big Picture: Enriching 3D Models with Information Visualisation and Vice Versa
Authors: Michael Sedlmair, Kerstin Ruhland, Fabian Hennecke, Andreas Butz, Susan Bioletti, Carol O'Sullivan
Venue: Proceedings of the 10th International Symposium on Smart Graphics (2009)

Most information visualisation methods are based on abstract visual representations without any concrete manifestation in the "real world". However, a variety of abstract datasets can indeed be related to, and hence enriched by, real-world aspects. In these cases an additional virtual representation of the 3D object can help to gain a better insight into the connection between abstract and real-world issues. We demonstrate this approach with two prototype systems that combine information visualisation with 3D models in multiple coordinated views. The first prototype involves the visualisation of in-car communication traces. The 3D model of the car serves as one view among several and provides the user with information about the car's activities. LibViz, our second prototype, is based on a full screen 3D representation of a library building. Measured data is visualised in overlaid, semi-transparent windows to allow the user interpretation of the data in its spatial context of the library's 3D model. Based on the two prototypes, we identify the benefits and drawbacks of the approach, investigate aspects of coordination between the 3D model and the abstract visualisations, and discuss principals for a general approach.
Disaggregated memory for expansion and sharing in blade servers
Authors: Kevin Lim, Jichuan Chang, Trevor Mudge, Parthasarathy Ranganathan, Steven K. Reinhardt, Thomas F. Wenisch
Venue: ACM SIGARCH Computer Architecture News (2009)

Analysis of technology and application trends reveals a growing imbalance in the peak compute-to-memory-capacity ratio for future servers. At the same time, the fraction contributed by memory systems to total datacenter costs and power consumption during typical usage is increasing. In response to these trends, this paper re-examines traditional compute-memory co-location on a single system and details the design of a new general-purpose architectural building block-a memory blade-that allows memory to be "disaggregated" across a system ensemble. This remote memory blade can be used for memory capacity expansion to improve performance and for sharing memory across servers to reduce provisioning and power costs. We use this memory blade building block to propose two new system architecture solutions-(1) page-swapped remote memory at the virtualization layer, and (2) block-access remote memory with support in the coherence hardware-that enable transparent memory expansion and sharing on commodity-based systems. Using simulations of a mix of enterprise benchmarks supplemented with traces from live datacenters, we demonstrate that memory disaggregation can provide substantial performance benefits (on average 10X) in memory constrained environments, while the sharing enabled by our solutions can improve performance-per-dollar by up to 57% when optimizing memory provisioning across multiple servers.
Intrusion detection in voice over IP environments
Authors: Yu-Sung Wu, Vinita Apte, Saurabh Bagchi, Sachin Garg, Navjot Singh
Venue: International Journal of Information Security (2009)

In this article, we present the design of an intrusion detection system for voice over IP (VoIP) networks. The first part of our work consists of a simple single- component intrusion detection system called Scidive. In the second part, we extend the design of Scidive and build a distributed and correlation-based intrusion detection system called Space Dive. We create several attack scenarios and evaluate the accuracy and efficiency of the system in the face of these attacks. To the best of our knowledge, this is the first comprehensive look at the problem of intrusion detection in VoIP systems. It includes treatment of the challenges faced due to the distributed nature of the system, the nature of the VoIP traffic, and the specific kinds of attacks at such systems.
Random projections preserving the Hamming distance between words
Authors: Stefano Arca, Alberto Bertoni, Giuseppe Lipori
Venue: Proceeding of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008 (2009)

Random projections in the Euclidean space reduce the dimensionality of the data approximately preserving the distances between points. In the hypercube it holds a weaker property: random projections approximately preserve the distances within a certain range. In this note, we show an analogous result for the metric space <Σd,dH>, where Σd is the set of words of length d on alphabet Σ and dH is the Hamming distance.
Action-specific motion prior for efficient Bayesian 3D human body tracking
Authors: Ignasi Rius, Jordi Gonzílez, Javier Varona, F. Xavier Roca
Venue: Pattern Recognition (2009)

In this paper, we aim to reconstruct the 3D motion parameters of a human body model from the known 2D positions of a reduced set of joints in the image plane. Towards this end, an action-specific motion model is trained from a database of real motion-captured performances, and used within a particle filtering framework as a priori knowledge on human motion. First, our dynamic model guides the particles according to similar situations previously learnt. Then, the state space is constrained so only feasible human postures are accepted as valid solutions at each time step. As a result, we are able to track the 3D configuration of the full human body from several cycles of walking motion sequences using only the 2D positions of a very reduced set of joints from lateral or frontal viewpoints.
A case-study on using an Automated In-process Software Engineering Measurement and Analysis system in an industrial environment
Authors: Irina Diana Coman, Alberto Sillitti, Giancarlo Succi
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

Automated systems for measurement and analysis are not adopted on a large scale in companies, despite the opportunities they offer. The fear of the “Big Brother” and the lack of reports giving insights into the real adoption process and concrete usages in industry are barriers to this adoption. We report on a case-study on the adoption and long-term usage (2 years of running system) of such a system in a company focusing on the adoption process and the related challenges we encountered.
A fair payoff distribution for myopic rational agents
Authors: Stéphane Airiau, Sandip Sen
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

We consider the case of self-interested agents that are willing to form coalitions for increasing their individual rewards. We assume that each agent knows its individual payoff when a coalition structure (CS) is formed. We consider a CS to be stable if no individual agent has an incentive to change coalition from this CS. When no stable CSs exist, rational agents will be changing coalitions forever. When stable CSs exist, they may not be unique, and choosing one over the other may give an unfair advantage to some agents. In addition, it may not be possible to reach a stable CS from any CS using a sequence of myopic rational actions. We propose a payoff distribution scheme that is based on the expected utility of a rational myopic agent (an agent that changes coalitions to maximize immediate reward) given a probability distribution over the space of coalition structures for selecting the initial CS. To compute this expected utility, we model the coalition formation process by a Markov chain. We recommend that agents share the utility from a social welfare maximizing CS proportionally to the expected utility they would receive if all agents acted in a myopic rational fashion. This scheme guarantees that agents receive at least as much as their expected utility from myopic behavior, which ensures sufficient incentives for the agents to use our proposed payoff distribution.