ppxscal/embedding_network huggingface dataset:
Wot do U think? (What Do You Think?)
Authors: M. O. Thirunarayanan
Venue: Ubiquity (2008)

(NOTE TO READERS: Out of sheer curiosity I used a website that allowed me to translate text from English to the language used by those who send and receive text messages. The second part of this article contains a copy of the entire text that was thus translated.)
Binary Sequences with Three and Four Level Autocorrelation
Authors: Ying Cai, Zhen Han
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

Binary sequences with good autocorrelation in ranging systems, spread spectrum communication systems, multi-terminal system identification, code division multiple access communications systems, global positioning systems, software testing, circuit testing, computer simulation, and stream ciphers. In this paper, we present a number of classes of binary sequences with three or four level autocorrelation. Some of them have good autocorrelation.
Investigating the Relationship between Spatial Ability and Feedback Style in ITSs
Authors: Nancy Milik, Antonija Mitrovic, Michael Grimley
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

Rapid and widespread development of computerised learning tools have proven the need for further exploration of the learners' personal characteristics in order to maximise the use of the current technology. In particular, this paper looks at the potential of accounting for spatial ability in ERM-Tutor; a constraint-based tutor that teaches logical database design. Our evaluation study shows no conclusive results to support a difference in effectiveness of the textual versus multimedia feedback presentation modes with respect to the students' spatial ability. However, we observed a number of trends indicating that matching the instruction presentation mode towards the students' spatial ability influences their perception of the system and motivation to use it, more than their learning gain.
On the Longest Common Parameterized Subsequence
Authors: Orgad Keller, Tsvi Kopelowitz, Moshe Lewenstein
Venue: Proceedings of the 19th annual symposium on Combinatorial Pattern Matching (2008)

The well-known problem of the longest common subsequence (LCS), of two strings of lengths n and m respectively, is O(nm)-time solvable and is a classical distance measure for strings. Another well-studied string comparison measure is that of parameterized matching, where two equal-length strings are a parameterized-match if there exists a bijection on the alphabets such that one string matches the other under the bijection. All works associated with parameterized pattern matching present polynomial time algorithms.There have been several attempts to accommodate parameterized matching along with other distance measures, as these turn out to be natural problems, e.g., Hamming distance, and a bounded version of edit-distance. Several algorithms have been proposed for these problems.In this paper we consider the longest common parameterized subsequence problem which combines the LCS measure with parameterized matching. We prove that the problem is NP-hard, and then show a couple of approximation algorithms for the problem.
MTF Measurement Based on Interactive Live-Wire Edge Extraction
Authors: Peng Liu, Dingsheng Liu, Fang Huang
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

When we want to measure parameters of the Modulation Transfer Function (MTF) from remote sensing image directly, the sharp edges are usually used as targets. But for noise, blur and the complexity of the images, fully automatic locating the expected edge is still an unsolved problem. This paper improves the semi-auto edge extraction algorithm of live-wire [1] and introduces it into the knife-edge method [8] of MTF measuring in remote sensing image. Live-wire segmentation is a novel interactive algorithm for efficient, accurate, and reproducible boundary extraction that requires minimal user input with a mouse. The image is transformed into a weighted graph with variety restrictions. Edge searching is based on dynamic programming of Dijkstra's algorithm [5]. Optimal boundaries are computed and selected at interactive rates as the user moves the mouse starting from a manually specified seed point. In this paper, a promoted model of live-wire is proposed to measuring the on orbit Modulation Transfer Function for high spatial resolution imaging satellites. We add the no-linear diffusion filter in the local cost function to ensure the accurateness of the extraction of edges. It can both de-noise and do not affect the shape of the edges when we extracting the edges, so that the calculation of the MTF is more reasonable and precise.
Interactivity, Interfaces, and Smart Toys
Authors: Lydia Plowman, Rosemary Luckin
Venue: Computer (2004)

Despite some technical hurdles, using smart toys and software for educational play shows promise.
From ACE to the G-15
Authors: Harry D. Huskey
Venue: IEEE Annals of the History of Computing (1984)

The 1946 Turing proposal for a stored-program computer at Britain's National Physical Laboratory is briefly described. The author's participation in the Test Assembly design, NPL's design of the ACE Pilot Model, and the subsequent design of the ACE are presented. The author's return to the United States and his efforts to build a similar computer at the National Bureau of Standards are described. Finally, the design of the Bendix G-15 and how it is related to the other computers is discussed. These computers were characterized by having re-circulating memories and logical designs that permitted the execution of several instructions per memory cycle.
Accurate Human Motion Capture Using an Ergonomics-Based Anthropometric Human Model
Authors: Jan Bandouch, Florian Engstler, Michael Beetz
Venue: Proceedings of the 5th international conference on Articulated Motion and Deformable Objects (2008)

In this paper we present our work on markerless model-based 3D human motion capture using multiple cameras. We use an industry proven anthropometric human model that was modeled taking ergonomic considerations into account. The outer surface consists of a precise yet compact 3D surface mesh that is mostly rigid on body part level apart from some small but important torsion deformations. Benefits are the ability to capture a great amount of possible human appearances with high accuracy while still having a simple to use and computationally efficient model. We have introduced special optimizations such as caching into the model to improve its performance in tracking applications. Available force and comfort measures within the model provide further opportunities for future research.3D articulated pose estimation is performed in a Bayesian framework, using a set of hierarchically coupled local particle filters for tracking. This makes it possible to sample efficiently from the high dimensional space of articulated human poses without constraining the allowed movements. Sequences of tracked upper-body as well as full-body motions captured by three cameras show promising results. Despite the high dimensionality of our model (51 DOF) we succeed at tracking using only silhouette overlap as weighting function due to the precise outer appearance of our model and the hierarchical decomposition.
A Timing Attack on Blakley's Modular Multiplication Algorithm, and Applications to DSA
Authors: Bahador Bakhshi, Babak Sadeghiyan
Venue: Proceedings of the 5th international conference on Applied Cryptography and Network Security (2007)

In this paper, we introduce a timing attack scheme against a 160-bit modular multiplication with Blakley's algorithm. It is assumed that a set of public inputs are multiplied by a secret parameter and running time of each multiplication is given, but the multiplication result is not known and a machine similar to victim machine isn't available. The proposed attack extracts all 160 bits of the secret parameter. Running time of Blakley's algorithm is analyzed and it is shown that running time of each step is dependent on the running time of other steps. The dependencies make the parameters of the attack be dependent on the secret key, while it makes the attack rather complicated. A heuristic algorithm is used to find the parameters of the attack. As a real scenario, the attack is applied against on-line implementation of Digital Signature Algorithm, which employs Blakley's modular multiplication. Practical results show that secret key of DSA will be found using 1,000,000 timing samples.
Dynamical Pattern Classification of Lorenz System and Chen System
Authors: Hao Cheng, Cong Wang
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

Recently, an approach for rapid dynamical pattern recognition was proposed, by which a dynamical pattern can be locally accurately identified and rapidly recognized using localized radial basis function (RBF) networks. Further, a scheme for classification of dynamical patterns was presented. In this paper, we investigate the construction of the recognition system for classification of Lorenz system and Chen system, both of which can generate various types of dynamical patterns. Simulation studies are included to demonstrate the effectiveness of this method.
Component-Based Development of Secure Mobile Agents Applications
Authors: Alvaro Moratalla, Sergi Robles
Venue: Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V (2007)

In this paper, we present a scheme for the design of mobile agents applications based on components. There is still a paramount issue to overcome in mobile agent technology to allow its popularization: the high programming complexity. The proposed scheme enables secure mobile agent creation by the composition of code components, significantly simplifying the work for the developer. Agent features like itinerary protection, results retrieving, or fault-tolerance can be achieved through reusable components. Our proposal is a steady step forward for the promotion of mobile agent applications.
A new approach to discrete approximation of a continuous-time system model based on spline function
Authors: Sha Guangyi, Tohru Kawabe, Kazuo Toraichi, Kazuki Katagishi, Koji Nakamura
Venue: Journal of Computational Methods in Sciences and Engineering (2005)

In this paper, a new approach to discrete approximation of continuous-time system models based on fluency signal function which includes and generalizes the staircase and spline signal function is proposed. Since a continuous-time signal in the real world must be approximated within a discrete-time signal space to implement the digital devices for many applications in signal processing area, it is important to use more exact approximation method in the discretization process. The proposed method is expected to derive more accurate discrete approximated model of continuous-time systems than the preexisting methods, because it does not use the conventional numerical approximate computation, but is based on the primitive function for the integration of coefficients of the spline function.
Cooperative Online Submission: Business Analysis and a Workflow Model
Authors: Arzu Baloglu
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Online Submission System allows articles to be submitted via the internet. We have brought a new approach to optimize peer review process and have integrated it to online submission system. The main objective of Online Submission System project is to enable users to submit their manuscript, or carry out a review on an assigned manuscript, over the Internet and in a professional way. In this article online submission processes will be explained in detail first and then mentioned generally the main structure that includes different types of users such as readers, authors, editors, section editors, chief editor and reviewers. In this model will be basically operated individual control panels.
perFrames: Persuasive Picture Frames for Proper Posture
Authors: Christoph Obermair, Wolfgang Reitberger, Alexander Meschtscherjakov, Michael Lankes, Manfred Tscheligi
Venue: Proceedings of the 3rd international conference on Persuasive Technology (2008)

Poor sitting habits and bad sitting posture are often the cause for musculoskeletal disorders like back pain. Also office employees are affected, because they carry out the majority of their work sitting in front of computers. Therefore we aim at sensitizing and motivating office employees regarding preventive healthcare. We have developed a persuasive interface in form of an interactive picture frame which integrates unobtrusively into the working environment --- the perFrame. This frame contains a moving portrait of a person the employee loves or likes. It provides affective feedback in order to persuade employees for better sitting habits while working with a computer. We conducted a preliminary in-situ study, deploying these picture frames on the desktops of eight office employees. The results highlight the employees' acceptance of our application as well as its potential to foster awareness and achieve persuasion regarding healthy behavior in the office.
The Intervening Role of BPR in the ICT -- Business Performance Relationship
Authors: Euripidis Loukis, Konstantinos Pazalos
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

The critical importance of information and communication technologies (ICT) for the firms nowadays, and the big ICT investments they make, necessitate a deeper understanding of 'how' ICT affects business performance, through identification of the intervening mechanisms and variables in the relationship between ICT and business performance. This paper describes an empirical investigation of whether and to what extent Business Process Reengineering (BPR) has an intervening role in the relationship between ICT investment and business performance. Using Structural Equation Modeling (SEM), and the Cobb-Douglas production function, we constructed a model which includes a multi-item construct for measuring the extent of BPR. Our results show that BPR mediates partially the relationship between ICT investment and business performance. On the contrary BPR does not have such an intervening role in the relationship between the non-ICT investment (in 'traditional' assets) and business performance.
An Investigation on Acceptance of Ubiquitous Devices for the Elderly in a Geriatric Hospital Environment: Using the Example of Person Tracking
Authors: Andreas Holzinger, Klaus Schaupp, Walter Eder-Halbedl
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

In this study, we investigate the acceptance of radio frequency identification (RFID) technology for localizing elderly people, suffering from dementia. We discuss how, and to what extend, we can balance economic and humanistic interests versus patient privacy and other libertarian concerns. We used specifically developed questionnaires and guided interviews and investigated the opinions, attitudes and beliefs of both medical professionals and patients. For this purpose, one of the most modern equipped geriatric clinics has been examined: the Albert Schweitzer clinic of the Geriatric Center Graz. The findings showed that RFID technology provides enormous economic benefits for both medical professionals and patients, whilst at the same time; these invasive surveillance technologies threaten our patients' privacy. Most astonishing was that almost all of the people involved, were unaware of both opportunities and problems of such ubiquitous devices. Similar to many new and emerging technologies, it has the potential to both benefit and harm society.
Deriving meaningful rules from gene expression data for classification
Authors: Nikhil Ranja Pal, Animesh Sharma, Somitra Kumar Sanadhya
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2008)

Although a fuzzy rule based system offers interpretability, its application in gene expression data analysis becomes difficult due to the very high dimensional nature of the data. Here we propose an interesting scheme of combining fuzzy modeling with neural networks for designing fuzzy rule based classifiers for gene expression data analysis. A neural system is used for selecting a set of informative genes. Considering only these selected set of genes, we cluster the expression data with a fuzzy clustering algorithm. Each cluster is then converted into a fuzzy if-then rule, which models an area in the input space. These rules are tuned using a gradient descent technique to improve the classification performance. The rule base is tested on a leukemia data set containing two classes and it is found to produce good results. We propose some simple criteria to simplify membership functions and the rules. Our rule extraction scheme can be automated. Unlike other classifiers, it produces human interpretable rules which are not expected to give poor generalization because fuzzy rules do not respond to areas not represented by the training data. The last two properties are very important for problems like diagnosis of cancer.
Bounds on Powers in Strings
Authors: Maxime Crochemore, Szilárd Zsolt Fazekas, Costas Iliopoulos, Inuka Jayasekera
Venue: Proceedings of the 12th international conference on Developments in Language Theory (2008)

We show a ¿(n logn) bound on the maximal number of occurrences of primitively-rooted k-th powers occurring in a string of length n for any integer k, k ¿ 2. We also show a ¿(n 2) bound on the maximal number of primitively-rooted powers with fractional exponent e, 1 < e < 2, occurring in a string of length n. This result holds obviously for their maximal number of occurrences. The first result contrasts with the linear number of occurrences of maximal repetitions of exponent at least 2.
Software development for automated network design supporting unicast and multicast traffics in next generation network
Authors: Kalika Suksomboon, Piyanan Satayapiwat, Chaodit Aswakul
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

This paper presents a summary of our experiences in developing a software tool for IP/MPLS NGN traffic engineering computations. The developed NGN software consists of three main modules. Firstly, the NGN design module can be used to help network engineers find the minimum link capacity needed for NGN unicast (e.g. VoIP service) and multicast service (e.g. VDO conference) provision while maintaining the resultant QoS at a specified target level. Secondly, the NGN performance analysis module is based on a discrete-event simulation of sequential routing and trunk reservation CAC. This module can be used to help network engineers analyse the performance of NGN. It can also be used to predict the effect of link failure, traffic surge and new routing plan implementation. Finally, both the NGN design and performance analysis modules can be executed via the developed NGN GUI module. With GUI, network engineers can visualise the status of network components. Further, GUI permits both entering and editing all relevant network parameters efficiently. It is therefore very convenient for our developed NGN software to be utilised in practice and should be an indispensable traffic engineering tool for improving the NGN planning and operational tasks.
Boosting RVM Classifiers for Large Data Sets
Authors: Catarina Silva, Bernardete Ribeiro, Andrew H. Sung
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

Relevance Vector Machines (RVM) extend Support Vector Machines (SVM) to have probabilistic interpretations, to build sparse training models with fewer basis functions (i.e., relevance vectors or prototypes), and to realize Bayesian learning by placing priors over parameters (i.e., introducing hyperparameters). However, RVM algorithms do not scale up to large data sets. To overcome this problem, in this paper we propose a RVM boosting algorithm and demonstrate its potential with a text mining application. The idea is to build weaker classifiers, and then improve overall accuracy by using a boosting technique for document classification. The algorithm proposed is able to incorporate all the training data available; when combined with sampling techniques for choosing the working set, the boosted learning machine is able to attain high accuracy. Experiments on REUTERS benchmark show that the results achieve competitive accuracy against state-of-the-art SVM; meanwhile, the sparser solution found allows real-time implementations.
Finding a History for Software Engineering
Authors: Michael S. Mahoney
Venue: IEEE Annals of the History of Computing (2004)

Historians and software engineers are both looking for a history for software engineering. For historians, it is a matter of finding a point of perspective from which to view an enterprise that is still in the process of defining itself. For software engineers, it is the question of finding a usable past, as they have sought to ground their vision of the enterprise on historical models taken from science, engineering, industry, and the professions. The article examines some of those models and their application to software engineering.
Pricing the Foreign Currency Options with the Fuzzy Numbers Based on the Garman-Kohlhagen Model
Authors: Fan-Yong Liu
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

This paper starts from the fuzzy environments of foreign currency options markets, introduces fuzzy sets theory, and gives a fuzzy version of Garman-Kohlhagen currency options pricing model. By taking exchange rate, domestic interest rate, foreign interest rate, and volatility as triangular fuzzy numbers, the currency option price will turn into a fuzzy number. This makes the financial investors who can pick any currency option price with an acceptable belief degree for the later use. In order to obtain the belief degree, an optimization procedure has been applied. An empirical study is performed based on market data. The study result indicates the fuzzy currency options pricing method is a useful tool for modeling the imprecise problem in the real world. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Parallel Fuzzy Reasoning Models with Ensemble Learning
Authors: Hiromi Miyajima, Noritaka Shigei, Shinya Fukumoto, Toshiaki Miike
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

This paper proposes a new learning algorithm and a parallel model for fuzzy reasoning systems. The proposed learning algorithm, which is based on an ensemble learning algorithm AdaBoost, sequentially trains a series of weak learners, each of which is a fuzzy reasoning system. In the algorithm, each weak learner is trained with the learning data set that contains more data misclassified by the previous weak one than the others. The output of the ensemble system is a majority vote weighted by weak learner accuracy. Further, the parallel model is proposed in order to enhance the ensemble effect. The model is made up of more than one ensemble system, each of which consists of weak learners. In order to show the effectiveness of the proposed methods, numerical simulations are performed. The simulation result shows that the proposed parallel model with fuzzy reasoning systems constructed by AdaBoost is superior in terms of accuracy among all the methods.