ppxscal/embedding_network huggingface dataset:
Teaching Machine Learning to Design Students
Authors: Bram Vlist, Rick Westelaken, Christoph Bartneck, Jun Hu, Rene Ahn, Emilia Barakova, Frank Delbressine, Loe Feijs
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

Machine learning is a key technology to design and create intelligent systems, products, and related services. Like many other design departments, we are faced with the challenge to teach machine learning to design students, who often do not have an inherent affinity towards technology. We successfully used the Embodied Intelligence method to teach machine learning to our students. By embodying the learning system into the Lego Mindstorm NXT platform we provide the student with a tangible tool to understand and interact with a learning system. The resulting behavior of the tangible machines in combination with the positive associations with the Lego system motivated all the students. The students with less technology affinity successfully completed the course, while the students with more technology affinity excelled towards solving advanced problems. We believe that our experiences may inform and guide other teachers that intend to teach machine learning, or other computer science related topics, to design students.
Sweeping Surface Generated by a Class of Generalized Quasi-cubic Interpolation Spline
Authors: Benyue Su, Jieqing Tan
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

In this paper we present a new method for the model of interpolation sweep surfaces by the C 2-continuous generalized quasi-cubic interpolation spline. Once given some key position, orientation and some points which are passed through by the spine and initial cross-section curves, the corresponding sweep surface can be constructed by the introduced spline function without calculating control points inversely as in the cases of B-spline and Bézier methods or solving equation system as in the case of cubic polynomial interpolation spline. A local control technique is also proposed for sweep surfaces using scaling function, which allows the user to change the shape of an object intuitively and effectively. On the basis of these results, some examples are given to show how the method is used to model some interesting surfaces.
Digital Watermarking Algorithm for Print-and-Scan Process Used for Printed Matter Anti-counterfeit
Authors: Dongcheng Shi, Qi Wang, Chao Liang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

In order to solve the pixel divergence problem brought by print and scan process, propose the algorithm that applying stretching contrast grade to adjust image pixel divergence. The parameter setting of this adjusting method uses peak signal noise ratio as standard of measurement, even though using different printer and scanner, we can also get good adjusting image. Simulation results show that the method can improve the effect of watermark detection or extraction effectively. Based on the character that symbol of parts of image’s DCT coefficient will not change, we propose self-adapting resist print and scan digital watermarking algorithm based on partitioning DCT. This algorithm imbed watermark adaptively, it can improve the capability of imbedded watermark and can also maintenance image quality. Experiment result shows that this algorithm can realize anti-counterfeit of soft-cover certificate using watermark technology.
Executable Platform Independent Models for Data Intensive Applications
Authors: Grzegorz Falda, Piotr Habela, Krzysztof Kaczmarski, Krzysztof Stencel, Kazimierz Subieta
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

In this paper we investigate the capabilities and shortcomings of UML 2 in the field of executable modelling, with special focus on database applications. As envisioned in the MDA initiative, this sets the challenges like achieving platform-independence of the base model, complete specification of behaviour in an adequate way and making the model an unambiguous and suitable input for model compilers. Additionally, we need to provide sufficiently powerful and abstract means of creating expressions over data, so that our platform-independent language is not inferior in that matter compared to database query languages known from DBMSs.
Experimental comparison of RSSI-based localization algorithms for indoor wireless sensor networks
Authors: Giovanni Zanca, Francesco Zorzi, Andrea Zanella, Michele Zorzi
Venue: Proceedings of the workshop on Real-world wireless sensor networks (2008)

In this paper, we investigate the actual performance of some of the best known localization algorithms when deployed in real-world indoor environments. Among the plethora of possible localization schemes, we focus on those based on radio signal strength measurements only, since they do not require extra circuitry that would result in higher cost and energy consumption. For a fair comparison, we have first gathered thousands of radio signal strength measurements in two different indoor environments. To estimate the channel model parameters and to compare the different localization algorithms these data have been used.
Patient Sensors: A Data Quality Perspective
Authors: John O'Donoghue, John Herbert, David Sammon
Venue: Proceedings of the 6th international conference on Smart Homes and Health Telematics (2008)

Wireless sensor devices with communication capabilities are affected by data quality issues. To ensure that information transmitted by these sensing devices are of a high quality, the data needs to be processed, validated and verified to meet the data quality requirements of the end user. The sensor validation component of the Data Management System (DMS) architecture is presented. It is designed to identify if the real-time sensor is functioning within the correct operating bounds. The DMS is applied within a medical environment to assess its ability to manage real-time patient sensor readings. The effectiveness of the DMS-Validation Model (DMS-VM) is evaluated under two real world scenarios 1) Hardware variance among four Tyndall-DMS-Motes with a patient state of resting and 2) One Tyndall-DMS-Mote under three patient states. The experiments have shown the reliability of the Tyndall-DMS-Mote and the ability of the DMS-VM to ensure sensor data quality. Validating sensor reliability is essential to enable safe remote health monitoring in the home.
PHP Object-Oriented Solutions
Authors: David Powers
Venue:  (2008)

With the surge of popularity of PHP 5, and with PHP 6 just around the corner, Object-Oriented Programming is now an important consideration for PHP developers. This version-neutral book is a gentle introduction to Object-Oriented Programming (OOP) that wont overburden you with complex theory. It teaches you the essential basics of OOP that youll need to know before moving onto a more advanced level, and includes a series of pre-packaged scripts that you can incorporate into your existing sites with the minimum of effort. It shows how OOP can be used to create reusable and portable code by walking you through a series of simple projects. The projects feature the sorts of things developers run up against every day, and include a validator for filtering user input, a simple Date class that avoids the need to remember all the esoteric format codes in PHP, and an XML generator. Teaches the fundamentals of OOP Simple projects show how OOP concepts work in the real world Pre-packaged scripts can easily be added to your own projects What youll learn PHP features, such as the Standard PHP Library (SPL), that are poorly documented or ignored by existing books How to develop classes of their own OOP in easy-to-understand language without getting bogged down in dense theory Solid foundations for developers wishing to delve more deeply into OOP How to leverage the strengths of OOP as a means for creating reusable code that can be used successfully within a procedural context How to code for both PHP 5 and 6 Who is this book for? This book is aimed at intermediate-level PHP developers who want to take their skills to the next level by exploring object-oriented programming as a way of creating reusable code for a everyday website tasks. A typical reader would be someone who has read one of the authors previous title, such as PHP Solutions, or one of the PHP books for Dreamweaverand feels ready to tackle something a little more challenging.
L-class enumeration algorithms for a discrete production planning problem with interval resource quantities
Authors: M. V. Devyaterikova, A. A. Kolokolov, A. P. Kolosov
Venue: Computers and Operations Research (2009)

A discrete production planning problem which may be formulated as the multidimensional knapsack problem is considered, while resource quantities of the problem are supposed to be given as intervals. An approach for solving this problem based on using its relaxation set is suggested. Some L-class enumeration algorithms for the problem are described. Results of computational experiments are presented.
Adaptive Wavelet Matched Algorithm Based on Subband Noise
Authors: Wei Zhang, Tie Ma, Linlin Ge
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

The demand for the detection of objects with low probability of observation is increasingly needed. The reason is that noises always badly affect the measured results. The method of signal detection in low signal to noise ratio (SNR) is widely concerned. To detect the weak signals buried in noises is a fundamental and important problem. It has been found that digital filters are not suitable for processing weak signals in noises, while discrete wavelet transform (DWT) is used to analyze weak digital signal and extract small-features. DTW is a time-frequency analysis technology, which detects the subtle small changes in the signal spectrum. In this paper, we propose a new method of the weak signal acquisition based on DWT. The performance for our method is investigated by detecting the simulating weak signal in white noise. The results show that the DTW is a quite effective method for the extraction features of weak signal and improving the ratio of signal to noise.
Unsupervised Outlier Detection in Sensor Networks Using Aggregation Tree
Authors: Kejia Zhang, Shengfei Shi, Hong Gao, Jianzhong Li
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

In the applications of sensor networks, outlier detection has attracted more and more attention. The identification of outliers can be used to filter false data, find faulty nodes and discover interesting events. A few papers have been published for this issue. However some of them consume too much communication, some of them need user to pre-set correct thresholds, some of them generate approximate results rather than exact ones. In this paper, a new unsupervised approach is proposed to detect global top n outliers in the network. This approach can be used to answer both snapshot queries and continuous queries. Two novel concepts, modifier set and candidate set for the global outliers, are defined in the paper. Also a commit-disseminate-verify mechanism for outlier detection in aggregation tree is provided. Using this mechanism and the these two concepts, the global top n outliers can be detected through exchanging short messages in the whole tree. Theoretically, we prove that the results generated by our approach are exact. The experimental results show that our approach is the most communication-efficient one compared with other existing methods. Moreover, our approach does not need any pre-specified threshold. It can be easily extended to multi-dimensional data, and is suitable for detecting outliers of various definitions.
Application of Functional Decomposition in Synthesis of Boolean Function Sets
Authors: Pawel Morawiecki, Mariusz Rawski, Henry Selvaraj
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

The paper presents a new disjoint functional decomposition method for set of Boolean functions specified by separate truth tables. The functional decomposition has important applications in many fields of modern engineering and science (FPGA synthesis, information systems, neural networks and many others). The presented algorithm is dedicated to multi-output boolean functions. The concept is based on dividing the complex multi-output function into single output functions and then utilizing common information needed by these functions to construct functional decomposition. The presented method was implemented in prototype tool and the results are presented in the paper.
A fast algorithm for the elimination of common subexpressions
Authors: J. D. Ullman
Venue: Proceedings of the 13th Annual Symposium on Switching and Automata Theory (swat 1972) (1972)

There is a class of flow charts called "reducible" for which many global code optimization algorithms have been recently written. As a practical matter, one may expect the flow chart of a program appearing "in nature" to be reducible with a probability over 90% [3], and those that are not can be made reducible by "node splitting" [10]. Unfortunately, the algorithms written for reducible graphs do not really take advantage of reducibility, since they require O(n2) bit vecter steps in worst case, the same as for the obvious general algorithms of these types. In this paper we give an O(n log n) bit vecter step algorithm to determine "available expressions," [7]. This information is essential for global elimination of common subexpressions. However, the ideas discussed here carry over to other global code optimization problems such as "reaching definitions" [1], "live variables" [9] and "very busy variables" [6]. 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
Design Reviews
Authors: Bob Colwell
Venue: Computer (2003)

The best design engineers are adept at accepting valid criticisms of their ideas and proposals. 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
Open Box Protocol (OBP)
Authors: Paulo Loureiro, Saverio Mascolo, Edmundo Monteiro
Venue: Proceedings of the 3rd international conference on High Performance Computing and Communications (2007)

In this paper we propose a new explicit congestion control approach, Open Box Protocol (OBP). The OBP gives sources the capacity to look inside the network and to make their congestion control decisions, based, not only on packets loss or packets delay, but also based on another kind of information. For example, the most restricted interface capacity, the available bandwidth, the RTT variations or the presence of heterogeneous transmission means. In the paper we describe the OBP and discuss its evaluation results based on ns-2 simulations. The results show the OBP´s capacity to provide traffic sources with the required information, in static or dynamic network scenarios, and to make correct and quick congestion control decisions. Also, it is visible that the OBP avoids the full queue problem and tries to keep the queues near zero occupation.
Bounded Model Checking Real-Time Multi-agent Systems with Clock Differences: Theory and Implementation
Authors: Alessio Lomuscio, Bożena Woźna, Andrzej Zbrzezny
Venue: Model Checking and Artificial Intelligence: 4th Workshop, MoChArt IV, Riva del Garda, Italy, August 29, 2006, Revised Selected and Invited Papers (2007)

We present a methodology for verifying epistemic and real-time temporal properties of multi-agent systems. We introduce an interpreted systems semantics based on diagonal timed automata and use a real-time temporal epistemic language to describe properties of multi-agent systems. We develop a bounded model checking algorithm for this setting and present experimental results for a real-time version of the alternating bit-transmission problem obtained by means of a preliminary implementation of the technique.
Automatic Identification of Fuzzy Models with Modified Gustafson-Kessel Clustering and Least Squares Optimization Methods
Authors: Grzegorz Glowaty
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

An automated method to generate fuzzy rules and membership functions from a set of sample data is presented. Our method is based on clustering and uses a modified version of Gustafson-Kessel algorithm. The aim is to divide a product space into set of clusters for which the systems exhibits behavior close to linear. For each of the clusters we produce a fuzzy rule and generate a set of membership functions for the rule antecedent with use of an approach based on curve fitting. Weighted linear least-squares regression is used to obtain consequent functions for TSK-models.
A Study on Jitter, Shimmer and F0 of Mandarin Infant Voice by Developing an Applied Method of Voice Signal Processing
Authors: Jiangping Kong
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

This paper is concerned with a study on jitter, shimmer and F0 of Mandarin infant voice through a method of voice signal processing. It has two parts. In the first part a method of voice signal processing is introduced, which includes 1) inverse-filtering of speech voice; 2) F0 extracting; 3) glottal period detecting; 4) jitter and shimmer calculating. In the second part, the natures of infant voice in Mandarin are studied, which includes 1) the speech sounds of 100 infants, 50 males and 50 females, are sampled which are sustained vowels of /a,i u,m/ with 5 different pitches and pronounced two times for each; 2) the features of voice among vowels of /a,i,u,m/, the voice differences between male and female, and the statistical analysis are studied. The conclusions are: 1) the method of voice signal processing is an applied method in the study of infant voice. 2) jitter, shimmer and F0 have close relationship with each other. In details, a) /i/ has relatively larger Jitt than those of /a, u, m/; b) Shim of /a, i/ are larger than those of /u, m/; c) the voice is different between male infant and female infant, and F0, Jitt and Shim of female are all larger than those of male; d) small part of voice samples distribute in a relatively large range, which may have personal characteristics.
Asymptotic Law of Likelihood Ratio for Multilayer Perceptron Models
Authors: Joseph Rynkiewicz
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

We consider regression models involving multilayer perceptrons (MLP) with one hidden layer and a Gaussian noise. The data are assumed to be generated by a true MLP model and the estimation of the parameters of the MLP is done by maximizing the likelihood of the model. When the number of hidden units of the model is over-estimated, the Fischer information matrix of the model is singular and the asymptotic behavior of the LR statistic is unknown or can be divergent if the set of possible parameter is too large. This paper deals with this case, and gives the exact asymptotic law of the LR statistic. Namely, if the parameters of the MLP lie in a suitable compact set, we show that the LR statistic converges to the maximum of the square of a Gaussian process indexed by a class of limit score functions.
Discovering original motifs with different lengths from time series
Authors: Heng Tang, Stephen Shaoyi Liao
Venue: Knowledge-Based Systems (2008)

Finding previously unknown patterns in a time series has received much attention in recent years. Of the associated algorithms, the k-motif algorithm is one of the most effective and efficient. It is also widely used as a time series preprocessing routine for many other data mining tasks. However, the k-motif algorithm depends on the predefine of the parameter w, which is the length of the pattern. This paper introduces a novel k-motif-based algorithm that can solve the existing problem and, moreover, provide a way to generate the original patterns by summarizing the discovered motifs.
E-Service Delivery Pattern for Knowledge Discovery Grid
Authors: Meiqun Liu
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

The emergence of ASP hosting Grid based data mining services is being seen as a novel and feasible solution for organizations that value their knowledge resources but are constrained by the high cost of knowledge discover tools. In this paper, we present a novel E-service delivery pattern for the Grid based data mining services. This pattern has several strong suits than the present methods for delivering data mining services such as supporting clients with many kinds of choices, especially the choice of the ASP. We have developed tools to support the E-service delivery pattern. The detailed information is including: the preferences of tasks, the functionality of ASP and the information of data resource and computation resources to run the application. We have realized the map function to match the requirement of client, the capability of resource and ASP.
Probabilistic (n, n) Visual Secret Sharing Scheme for Grayscale Images
Authors: Daoshun Wang, Xiaobo Li, Feng Yi
Venue: Information Security and Cryptology: Third SKLOIS Conference, Inscrypt 2007, Xining, China, August 31 - September 5, 2007, Revised Selected Papers (2007)

Pixel expansion has been a major issue of visual secret sharing (VSS) schemes. A number of probabilistic VSS schemes with minimum pixel expansion have been proposed for black-and-white (binary) secret images. This paper presents a probabilistic (n, n)-VSS scheme for grayscale images. Its pixel expansion is significantly smaller than that of previous methods. The construction of the shadow images (shares) is based on the Boolean XOR operation.
Univalent Neural Nets and Shape Detection
Authors: Frantiek Hakl
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

We introduce a notion of so called univalent neural networks realizing injective mappingand sharing the input and output space. First, we postulate necessary and sufficient conditions of univalence and derive several models of univalent nets. Then explore learning algorithms that could be used for the defined network class - special variants of backpropagation learning.
An Agent-Based Best Effort Routing Technique for Load Balancing
Authors: Sunilkumar S. Manvi, Pallapa Venkataram
Venue: Informatica (2006)

Several best effort schemes (next-hop routing) are used to transport the data in the Internet. Some of them do not perform flexible route computations to cope up with the network dynamics. With the recent trends in programmable networks, mobile agent technology seems to support more flexible, adaptable and distributed mechanism for routing. In this paper, we propose a Mobile Agent based Routing (MAR) scheme with the objectives similar to Routing Information Protocol (RIP). A comparative study of both the schemes (MAR and RIP) in terms of communication overheads, convergence time, network bandwidth utilization and average session delays is presented. The results demonstrate that the MAR scheme performs better than RIP. MAR has comparatively less communication overheads and convergence time and also offers more flexibility and adaptability as compared to RIP. In addition, this paper also presents a MAR based network load balancing.