ppxscal/embedding_network huggingface dataset:
Porosity Prediction Using Bagging of Complementary Neural Networks
Authors: Pawalai Kraipeerapun, Chun Che Fung, Sathit Nakkrasae
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

This paper presents a novel approach to the regression problem using bagging of complementary neural networks (CMTNN). A bagging technique is applied to an ensemble of pairs of feed-forward backpropagation neural networks created to predict degrees of truth and falsity values. In our approach, uncertainties in the prediction of the truth and falsity values are quantified based on the difference among all the predicted truth values and the difference among all the predicted falsity values in the ensemble, respectively. An aggregation technique based on uncertainty values is proposed. This study is realized to the problem of porosity prediction in well log data analysis. The results obtained from our approach are compared to results obtained from three existing bagging models. These three models are an ensemble of feed-forward backpropagation neural networks, an ensemble of general regression neural networks, and an ensemble of support vector machines. We found that our approach improves performance compared to those three existing models that apply a simple averaging technique based on only the truth porosity values in the ensemble.
Sharing Moral Responsibility with Robots: A Pragmatic Approach
Authors: Gordana Dodig-Crnkovic, Daniel Persson
Venue: Proceeding of the 2008 conference on Tenth Scandinavian Conference on Artificial Intelligence: SCAI 2008 (2008)

Roboethics is a recently developed field of applied ethics which deals with the ethical aspects of technologies such as robots, ambient intelligence, direct neural interfaces and invasive nano-devices and intelligent soft bots. In this article we look specifically at the issue of (moral) responsibility in artificial intelligent systems. We argue for a pragmatic approach, where responsibility is seen as a social regulatory mechanism. We claim that having a system which takes care of certain tasks intelligently, learning from experience and making autonomous decisions gives us reasons to talk about a system (an artifact) as being “responsible” for a task. No doubt, technology is morally significant for humans, so the “responsibility for a task” with moral consequences could be seen as moral responsibility. Intelligent systems can be seen as parts of socio-technological systems with distributed responsibilities, where responsible (moral) agency is a matter of degree. Knowing that all possible abnormal conditions of a system operation can never be predicted, and no system can ever be tested for all possible situations of its use, the responsibility of a producer is to assure proper functioning of a system under reasonably foreseeable circumstances. Additional safety measures must however be in place in order to mitigate the consequences of an accident. The socio-technological system aimed at assuring a beneficial deployment of intelligent systems has several functional responsibility feedback loops which must function properly: the awareness and procedures for handling of risks and responsibilities on the side of designers, producers, implementers and maintenance personnel as well as the understanding of society at large of the values and dangers of intelligent technology. The basic precondition for developing of this socio-technological control system is education of engineers in ethics and keeping alive the democratic debate on the preferences about future society.
Psychometric properties of internet administered versions of Penn State Worry Questionnaire (PSWQ) and Depression, Anxiety, and Stress Scale (DASS)
Authors: Kimberly R. Zlomke
Venue: Computers in Human Behavior (2009)

A limited amount of research has been conducted on the psychometric properties of commonly used measures of anxious or depressive symptomatology for use on the internet, although such measures are seeing increasing use in internet administration for both clinical and research uses. A plethora of advantages exist for the use of internet administration of questionnaires, both in terms of assessment and the potential use in treatment monitoring as well as for research. The aim of this study was to examine the psychometric properties of two common clinical measures, the Penn State Worry Questionnaire and the. Depression, Anxiety, and Stress Scale, in an internet administered format (N=1138). Results suggest that these two measures may be used with confidence in an online format in terms of reliability and validity.
The hybrid position and force control of robots with compliance function
Authors: Luige Vladareanu, Ion Ion, Eugen Diaconescu, Gabriela Tont, Lucian M. Velea, Daniel Mitroi
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

This paper shows a new method for the hybrid position-force control of robots with compliance function on six axis of freedom degrees in system multi-microprocessor in order to obtain high performances. For this purpose kinematics and kinetostatics analysis are performed, and the mathematic model of the inverted kinematics is determined for controlling the main trajectory of the robot. Related to this there is presented an Open Architecture system for the robot position control in Cartesian coordinates through real time processing of the Jacobean matrix obtained out of the forward kinematics using the Denevit-Hartenberg method and calculating the Jacobean inverted matrix for feedback. The obtained results prove a significant reduction of the execution time for the real time control of robot's position in Cartesian coordinates and increased flexibility.
Audio visual system with cascade-correlation neural network for moving audio visual robot
Authors: Alexander Bekiarski
Venue: Proceedings of the 10th WSEAS international conference on Neural networks (2009)

The development of a moving robot requires many researches to gain the desired performance. An obligatory and necessary stage of these researches is to choose the appropriate methods for each robot function. One of these functions is speaker localization, implemented with an existing in the moving robot audio and visual system. There are many possibilities to choose the methods for processing of audio and video information from the corresponding audio and video robot sensors. The goal of this paper is to propose and test the audio visual robot system using cascade-correlation neural network for calculating the speaker position and sent this information to moving robot system for correct robot movements control.
Three-phase ZCZ sequence sets with good cross-correlation properties for CDMA cellular systems
Authors: Hideyuki Torii, Makoto Nakamura
Venue: Proceedings of the 13th WSEAS international conference on Applied mathematics (2008)

The present paper discusses suitable three-phase ZCZ sequence sets for AS-CDMA cellular systems that use coded TPSK. First, we comprehensively investigate the cross-correlation properties of three-phase ZCZ sequence sets and discuss methods for constructing a pair of three-phase ZCZ sequence sets with a good cross-correlation property. Next, we discuss which of the three-phase ZCZ sequence sets is the most suitable for ASCDMA cellular systems. The results are expected to be useful in the design of AS-CDMA cellular systems that use coded TPSK.
An analysis of generalized slotted-Aloha protocols
Authors: Richard T. B. Ma, Vishal Misra, Dan Rubenstein
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

Aloha and its slotted variation are commonly deployed Medium Access Control (MAC) protocols in environments where multiple transmitting devices compete for a medium, yet may have difficulty sensing each other's presence (the "hidden terminal problem"). Competing 802.11 gateways, as well as most modern digital cellular systems, like GSM, are examples. This paper models and evaluates the throughput that can be achieved in a system where nodes compete for bandwidth using a generalized version of slotted-Aloha protocols. The protocol is implemented as a two-state system, where the probability that a node transmits in a given slot depends on whether the node's prior transmission attempt was successful. Using Markov Models, we evaluate the channel utilization and fairness of this class of protocols for a variety of node objectives, including maximizing aggregate throughput of the channel, each node selfishly maximizing its own throughput, and attacker nodes attempting to jam the channel. If all nodes are selfish and strategically attempt to maximize their own throughput, a situation similar to the traditional Prisoner's Dilemma arises. Our results reveal that under heavy loads, a greedy strategy reduces the utilization, and that attackers cannot do much better than attacking during randomly selected slots.
Making e-Learning a Service Oriented Utility: The European Learning Grid Infrastructure Project
Authors: Matteo Gaeta, Pierluigi Ritrovato, Saverio Salerno
Venue: Proceeding of the 2005 conference on Towards the Learning Grid: Advances in Human Learning Services (2005)

This paper describes the ELeGI (www.elegi.org) Project. ELeGI has the ambitious goal of developing software technologies for service oriented effective human learning. ELeGI will create new potential for moving from the current information transfer paradigm focused on content and on the key authoritative figure of the teacher who provides information towards learning paradigm focused on knowledge construction using experiential based and collaborative learning approaches in a contextualised, personalised and ubiquitous way. We have chosen a synergic approach, sometimes called “human centred design”, to replace the classical, applicative approach to learning. With consideration of humans at the centre, learning is clearly a social, constructive phenomenon. It occurs as a side effect of interactions, conversations and enhanced presence in dynamic Virtual Communities created and deployed using Grid technologies.
Using the “Record-Replay” Function for Elaboration of Knowledge in Educational Games
Authors: Junjie Shang, Morris S. Y. Jong, Fong-Lok Lee, Jimmy H. M. Lee, Marti K. H. Wong, Eric T. H. Luk, Kevin K. F. Cheung
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

Some scholars argue that simply using an educational game does not ensure that learners can generate the kinds of understandings that educators might desire. In order to maintain students' interest in playing the game and, at the same time, helps them to learn, some scholars argue that reflection and debriefing during playing was the most effective approach. In this paper, we discuss the “Record-Replay” function, which is one of the technical and educational innovations in VISOLE that enables teachers and students to replay recorded gameplays, in order to help students to re-examine their decisions made while playing the game. Teachers can also guide student in making what-if analyses, making it a good tool for reflection and debriefing. Besides, “Record-Replay” allows teachers to assess students, and researchers to study and investigate the effectiveness of the game.
Learning and parameterization of recurrent neural network arrays for brain models and practical applications
Authors: Robert Kozma
Venue:  (2008)

The field of Artificial Neural Networks is inspired by the incredible abilities of human beings and animals to learn and adapt their actions to the environment. The feed-forward architectures although very powerful for statistical pattern recognition are nevertheless not able to solve challenging problems posed by the fields of reinforcement learning and image processing. At the same time, there is growing evidence that the brain is a highly recurrent structure with dynamics at the edge of stability. This work addresses the issues of parameterizations and learning in two novel types of Artificial neural networks: K sets and Cellular Simultaneous Recurrent Networks. Their commonality is in the cellular structure and recurrent connections. The differences are in the internal dynamics and in the learning paradigms employed. Both network types address the problem of intelligent control and at the same time can be used in other applications. The studies of K models focused on their stability properties, the mechanisms employed in maintaining their non-equilibrium dynamics, and the integration of information in large K models. The studies of Cellular Simultaneous Recurrent Networks focus of the issues of learning efficiency.
Short Note: A fast and stable method for rotating spherical harmonic expansions
Authors: Z. Gimbutas, L. Greengard
Venue: Journal of Computational Physics (2009)

In this paper, we present a simple and efficient method for rotating a spherical harmonic expansion. This is a well-studied problem, arising in classical scattering theory, quantum mechanics and numerical analysis, usually addressed through the explicit construction of the Wigner rotation matrices. We show that rotation can be carried out easily and stably through ''pseudospectral'' projection, without ever constructing the matrix entries themselves. Existing fast algorithms, based on recurrence relations, are subject to a variety of instabilities, limiting the effectiveness of the approach for expansions of high degree.
Versatile multi-decade CMOS voltage-controlled oscillator with accurate amplitude and pulse width control
Authors: Annajirao Garimella, Lalitha Mohana Kalyani-Garimella, Jaime Ramírez-Angulo, Antonio J. Lopez-Martin
Venue: Analog Integrated Circuits and Signal Processing (2009)

A compact, versatile and very high speed approach for waveform generation is introduced. It generates triangle and square waveforms. The VCO has a very wide range of oscillating frequencies, from fractions of Hz to 30 MHz in 0.5 μm CMOS technology. The amplitude of the oscillations can be very precisely controlled. It has linear control over frequency, amplitude and pulse-width. It can be used in frequency, amplitude and pulse-width modulation applications as well as in the accurate piecewise linear waveform synthesis. Experimental results of a MOSIS CMOS AMI 0.5 μm technology test chip are presented that validate the proposed circuit.
Correlation-based botnet detection in enterprise networks
Authors: Wenke Lee
Venue:  (2008)

Most of the attacks and fraudulent activities on the Internet are carried out by malware. In particular, botnets, as state-of-the-art malware, are now considered as the largest threat to Internet security.In this thesis, we focus on addressing the botnet detection problem in an enterprise-like network environment. We present a comprehensive correlation-based framework for multi-perspective botnet detection consisting of detection technologies demonstrated in four complementary systems: BotHunter, BotSniffer, BotMiner, and BotProbe. The common thread of these systems is correlation analysis, i.e., vertical correlation (dialog correlation), horizontal correlation, and cause-effect correlation. All these Bot* systems have been evaluated in live networks and/or real-world network traces. The evaluation results show that they can accurately detect real-world botnets for their desired detection purposes with a very low false positive rate.We find that correlation analysis techniques are of particular value for detecting advanced malware such as botnets. Dialog correlation can be effective as long as malware infections need multiple stages. Horizontal correlation can be effective as long as malware tends to be distributed and coordinated. In addition, active techniques can greatly complement passive approaches, if carefully used. We believe our experience and lessons are of great benefit to future malware detection.
Pre-image as Karcher Mean Using Diffusion Maps: Application to Shape and Image Denoising
Authors: Nicolas Thorstensen, Florent Segonne, Renaud Keriven
Venue: Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision (2009)

In the context of shape and image modeling by manifold learning, we focus on the problem of denoising. A set of shapes or images being known through given samples, we capture its structure thanks to the Diffusion Maps method. Denoising a new element classically boils down to the key-problem of pre-image determination, i.e. recovering a point, given its embedding. We propose to model the underlying manifold as the set of Karcher means of close sample points. This non-linear interpolation is particularly well-adapted to the case of shapes and images. We define the pre-image as such an interpolation having the targeted embedding. Results on synthetic 2D shapes and on real 2D images and 3D shapes are presented and demonstrate the superiority of our pre-image method compared to several state-of-the-art techniques in shape and image denoising based on statistical learning techniques.
Securing wireless localization against signal strength attacks
Authors: Richard P. Martin, Wade Trappe
Venue:  (2007)

Accurately positioning nodes in wireless and sensor networks is important because the location of devices and sensors is a critical input to many higher-level applications. However, the localization infrastructure can be subjected to non-cryptographic attacks, such as signal attenuation and amplification, that can not be addressed by traditional security services. This thesis aims to provide secure and accurate location information in wireless and sensor networks by characterizing the response of localization algorithms to attacks, detecting attacks, localizing adversaries, and additionally, improving localization performance. First we studied the robustness of localization algorithms to signal strength attacks. We found the performance of localization algorithms degrades significantly under attacks when signals are attenuated or amplified by an adversary. We then formulated a theoretical foundation for the attack detection problem using statistical significance testing. We proposed attack detection schemes for two broad localization approaches: signal strength and multilateration. We found that different localization systems all contain similar attack detection capabilities. Next, we examined the applicability of localization methods to localize adversaries participating in identity-based spoofing attacks. We proposed a spoofing detector for wireless spoofing that utilizes K-means cluster analysis. We integrated our K-means attack detector into a real-time indoor localization system, which is capable of localizing the positions of attackers. Our experiments using both an 802.11 (WiFi) network as well as an 802.15.4 (ZigBee) network in two office buildings provide strong evidence of the effectiveness of our approach in attack detection and localizing the positions of the adversaries. In addition, we investigated the impact of landmark placement on localization performance using a combination of analytic and experimental analysis. We developed a novel algorithm called maxL - minE algorithm that finds an optimized landmark deployment. Our experimental results show that our landmark placement algorithm is generic because the resulting placements improve localization performance significantly across a diverse set of algorithms, networks, and ranging modalities. Finally, we presented our general purpose real time localization infrastructure which targets to localize any radio-enabled wireless devices at anywhere and at anytime.
Single item lot-sizing with non-decreasing capacities
Authors: Yves Pochet, Laurence A. Wolsey
Venue: Mathematical Programming: Series A and B (2009)

We consider the single item lot-sizing problem with capacities that are non-decreasing over time. When the cost function is (i) non-speculative or Wagner&#x2013;Whitin (for instance, constant unit production costs and non-negative unit holding costs) and (ii) the production set-up costs are non-increasing over time, it is known that the minimum cost lot-sizing problem is polynomially solvable using dynamic programming. When the capacities are non-decreasing, we derive a compact mixed integer programming reformulation whose linear programming relaxation solves the lot-sizing problem to optimality when the objective function satisfies (i) and (ii). The formulation is based on mixing set relaxations and reduces to the (known) convex hull of solutions when the capacities are constant over time. We illustrate the use and potential effectiveness of this improved LP formulation on a few test instances, including instances with and without Wagner&#x2013;Whitin costs, and with both non-decreasing and arbitrary capacities over time.
NetPrints: diagnosing home network misconfigurations using shared knowledge
Authors: Bhavish Aggarwal, Ranjita Bhagwan, Tathagata Das, Siddharth Eswaran, Venkata N. Padmanabhan, Geoffrey M. Voelker
Venue: Proceedings of the 6th USENIX symposium on Networked systems design and implementation (2009)

Networks and networked applications depend on several pieces of configuration information to operate correctly. Such information resides in routers, firewalls, and end hosts, among other places. Incorrect information, or misconfiguration, could interfere with the running of networked applications. This problem is particularly acute in consumer settings such as home networks, where there is a huge diversity of network elements and applications coupled with the absence of network administrators. To address this problem, we present NetPrints, a system that leverages shared knowledge in a population of users to diagnose and resolve misconfigurations. Basically, if a user has a working network configuration for an application or has determined how to rectify a problem, we would like this knowledge to be made available automatically to another user who is experiencing the same problem. NetPrints accomplishes this task by applying decision tree based learning on working and nonworking configuration snapshots and by using network traffic based problem signatures to index into configuration changes made by users to fix problems. We describe the design and implementation of NetPrints, and demonstrate its effectiveness in diagnosing a variety of home networking problems reported by users.
Virtual Reality systems and CE: how to evaluate the benefits
Authors: Maura Mengoni, Michele Germani
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

Virtual Reality systems and Virtual Environments represent innovative tools to interact with the digital product model, which can be useful in various phases of the product development process. They can support an early and intensive information exchange between marketing, design, process planning and manufacturing experts, allowing an easy concurrent involvement of heterogeneous competencies and interacting with a single virtual product model. However, the fruitful adoption of VR technologies implies the rethinking of way of execution of traditional design activities in order to structure new processes. But many companies lack tools and data to estimate the achievable concrete benefits, considering also the counterpart of high investments necessary for VR systems implementation. The effective evaluation of VR systems in the CE context, in terms of product quality improvement, of time to market and cost reduction is the aim of our research. The present work proposes a methodology to measure the VR performances using a metrics-based approach. First experimental results related to the method application are reported analyzing the conceptual design process and the design reviews tasks for the styling product development.