ppxscal/embedding_network huggingface dataset:
Parallel Realizations of the SAMANN Algorithm
Authors: Sergejus Ivanikovas, Viktor Medvedev, Gintautas Dzemyda
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

Sammon's mapping is a well-known procedure for mapping data from a higher-dimensional space onto a lower-dimensional one. But the original algorithm has a disadvantage. It lacks generalization, which means that new points cannot be added to the obtained map without recalculating it. The SAMANN neural network, that realizes Sammon's algorithm, provides a generalization capability of projecting new data. A drawback of using SAMANN is that the training process is extremely slow. One of the ways of speeding up the neural network training process is to use parallel computing. In this paper, we proposed some parallel realizations of the SAMANN.
Limits of Learning-Based Superresolution Algorithms
Authors: Zhouchen Lin, Junfeng He, Xiaoou Tang, Chi-Keung Tang
Venue: International Journal of Computer Vision (2008)

Learning-based superresolution (SR) is a popular SR technique that uses application dependent priors to infer the missing details in low resolution images (LRIs). However, their performance still deteriorates quickly when the magnification factor is only moderately large. This leads us to an important problem: "Do limits of learning-based SR algorithms exist?" This paper is the first attempt to shed some light on this problem when the SR algorithms are designed for general natural images. We first define an expected risk for the SR algorithms that is based on the root mean squared error between the superresolved images and the ground truth images. Then utilizing the statistics of general natural images, we derive a closed form estimate of the lower bound of the expected risk. The lower bound only involves the covariance matrix and the mean vector of the high resolution images (HRIs) and hence can be computed by sampling real images. We also investigate the sufficient number of samples to guarantee an accurate estimate of the lower bound. By computing the curve of the lower bound w.r.t. the magnification factor, we could estimate the limits of learning-based SR algorithms, at which the lower bound of the expected risk exceeds a relatively large threshold. We perform experiments to validate our theory. And based on our observations we conjecture that the limits may be independent of the size of either the LRIs or the HRIs.
E-Government Services Composition Using Multi-faceted Metadata Classification Structures
Authors: Fenareti Lampathaki, Yannis Charalabidis, Demetrios Sarantis, Sotirios Koussouris, Dimitris Askounis
Venue: Proceedings of the 6th International conference on Electronic Government (2007)

The connectivity generated by the Internet is opening new opportunities in service delivery since administrations are forming online alliances in order to deliver integrated value-adding services. However, due to lack of a step-by-step method for identification and further processing of services, the development of such composite e-Government services is usually ad-hoc. In this paper, we demonstrate how a systematic service composition can be accomplished: with the help of the proposed Service Description Worksheet, the e-Government Services can now be classified, searched for and composed into larger groups. This goal-driven approach can be used to understand the needs of different organizations and to depict the various functional characteristics of the cooperative processes in a declarative manner, suitable for prototyping projects in the public sector. Applying this method in the context of the Greek e-Government Services Framework, various services have been analysed, populating the worksheet database and leading to corresponding process models.
Design and implementation of DC motor speed controller using fuzzy-adaptive controllers
Authors: Hengameh Kojooyan Jafari
Venue: Proceedings of the 8th WSEAS International Conference on Robotics, Control and Manufacturing Technology (2008)

As adaptive control systems have parametric construction and high accuracy against disturbances, and fuzzy control systems can compensate deficiency of dynamic parameters in time [1], in this paper fuzzy-adaptive controllers is used. Drive method is PWM and 8955 microcontroller is used for DC motor speed controlling. Simulation studies has been performed by MATLAB SIMULINK6.1 and SIDE51 (ver1.04R11) software by C language is used for program of controller and its compiler is used for making hex file to program 8955 microcontroller by EPROM PROGRAMMER (PGM89)[6,7]. The DC motor is VGFMED-BSMIB52 and driving IC is L298 IC.
Progressive failure analysis of pin joints in composite laminates
Authors: Ali Evcil
Venue: Proceedings of the WSEAS International Conference on Applied Computing Conference (2008)

A three-dimensional, non-linear finite element code including large displacement theory, isotropic and orthotropic material properties and a contact algorithm based on transformation matrix was developed to analyze the failure of composite to metal joints. A progressive damage model was implemented to predict the extent and the failure modes of the internal damage in composite laminates as a function of applied load and to stimulate the three-dimensional response of composite laminates from initial loading to final collapse. Hashin failure criteria was used together with the fiber-matrix shear failure and Yeh delamination criterion and material properties were degraded according to the mode of failure. The progressive damage algorithm was verified using a clustered cross-ply [06/906]s laminate with a hole under compressive in-plane load. The results determined by Hashin failure criterion were found to be in good agreement with the experimental results with a deviation of as low as 2.6% from the average. Pinned joint failure analysis of same cross-ply [06/906]s laminate was conducted using two different geometries and net-tension, bearing, shear-out and mixed modes of failure of the joined was examined according to the progression of the damage.
An empirical study of the Cobb-Douglas production function properties of software development effort
Authors: Parag C. Pendharkar, James A. Rodger, Girish H. Subramanian
Venue: Information and Software Technology (2008)

In this paper we study whether software development effort exhibits Cobb-Douglas functional form with respect to team size and software size. We empirically test this relationship using real-world software engineering data set containing over 500 software projects. The results of our experiments indicate that the hypothesized Cobb-Douglas function form for software development effort with respect to team size and software size is true. We also find increasing returns to scale relationship between software size and team size with software development effort.
Multimedia Indexing and Retrieval of Unedited Audio-Visual Footage
Authors: Oliver Schreer
Venue: Proceedings of the 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services (2008)

Unedited audio‐visual footage known as rushes shares many features with general‐purpose multimedia data, but it also shows special characteristics. Rushes are often single‐shot sequences at a single location, sparsely edited, with repetitive content and soundtrack is frequently irrelevant. This leads to additional challenges beyond the existing ones in multimedia indexing and retrieval. The joint effort of a number of research groups all over the world resulted in a ‘rushes exploitation’ task in the TRECVID video analysis international benchmark organized this year. In addition, the European FP6 project RUSHES is fully dedicated to research and development of a system for indexing, accessing and delivering raw, unedited audio‐visual footage and to enable indexing, search and retrieval of rushes archives to ease in‐house postproduction or reuse in a media professional environment. In this special session, latest research results on indexing, search and retrieval with focus on raw unedited audiovisual content are presented.
Computationally Efficient Method in the Meter-Wave Radar Low-Elevation Height-Finding Applications
Authors: Xiao-qin Hu, Jian-wen Chen, Hui Chen, Yong-liang Wang, Hui Chen
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Multipath reflection has great influence on the meter-wave radar low-elevation height-finding. In this paper, a computationally efficient method is presented fully using the information included in the received data covariance matrix. This method is proposed according to the spatial smoothing concept and the propagator operator method. The presented method constructs new forward and backward matrices based on the spatial smoothing idea, and then summing the obtained forward and backward matrices obtains the noise subspace with the propagator operator method. This algorithm estimates DOAs without the need to decorrelate and eigen-decompose. Therefore, the method has good estimation performance for the meter-wave radar height-finding with a small number of snapshots and at low SNR. Simulation experiments and real data processing results both demonstrate the effectiveness of the proposed method in the meter-wave radar low-elevation height-finding applications.
Effectiveness of Scale Free Network to the Performance Improvement of a Morphological Associative Memory without a Kernel Image
Authors: Takashi Saeki, Tsutomu Miki
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

In this paper, we present a new approach of the morphological associative memory (MAM) without a kernel image to reduce the network size by using the scale free network. The MAM is one of the powerful associative memories compared to ordinary associative memories. Weak point of the MAM is to need the kernel image which is susceptibility to noise and hard to design. We have already presented the MAM without a kernel image as a practical model. However the model has a drawback that the perfect recall rate is degraded. On the other hand, it has been reported that an introduction of the scale free network to associative memories is effective in the improvement of the recall rate and the reduction of the network size. We try to reduce the network size and improve the recall rate by introducing the scale free network.
Adversarial Scheduling Analysis of Game-Theoretic Models of Norm Diffusion
Authors: Gabriel Istrate, Madhav V. Marathe, S. S. Ravi
Venue: Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms (2008)

In [IMR01] we advocated the investigation of robustness of results in the theory of learning in games under adversarial scheduling models. We provide evidence that such an analysis is feasible and can lead to nontrivial results by investigating, in an adversarial scheduling setting, Peyton Young's model of diffusion of norms [You98]. In particular, our main result incorporates contagion into Peyton Young's model.
Classification with Nominal Data Using Intuitionistic Fuzzy Sets
Authors: Eulalia Szmidt, Janusz Kacprzyk
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

The classical classification problem with nominal data is considered. First, to make the problem practically tractable, some transformation into a numerical (real) domain is performed using a frequency based analysis. Then, the use of a fuzzy sets based, and --- in particular - an intuitionistic fuzzy sets based technique is proposed. To better explain the procedure proposed, the analysis is heavily based on an example. Importance of the results obtained for other areas exemplified by decision making and case based reasoning is mentioned.
Dimensionality Reduction for Feature and Pattern Selection in Classification Problems
Authors: Zacharias Voulgaris, George D. Magoulas
Venue: Proceedings of the 2008 The Third International Multi-Conference on Computing in the Global Information Technology (iccgi 2008) (2008)

Reducing the dimensionality of a dataset is an important and often challenging task. This can be done by either reducing the number of features, a task called feature selection, or by reducing the number of patterns, called data reduction. In this paper we propose methods that employ a novel concept called Discernibility for achieving these two tasks separately, with the aim to solve classification problems. The experimental results verify our claim that the proposed methods are a viable alternative for dimensionality reduction, for various datasets and a variety of classifiers.
Non Parametric Classification of Human Interaction
Authors: Scott Blunsden, Ernesto Andrade, Robert Fisher
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

This paper presents a non parametric method for classifying interactions between two people as taken from a video camera. A nearest neighbour classifier that uses trajectory matching in feature space is introduced and shown to be superior to regular nearest neighbour classification for this problem.
Identity management of e-ID, privacy and security in Europe. A human rights view
Authors: Paul De Hert
Venue: Information Security Tech. Report (2008)

With privacy enhancing identity management, end users are given better ways for managing their identities for specific contexts. One could easily argue that the need to implement identity management systems that are privacy enhancing follows from the EU data protection regulation. One of the challenges while developing privacy enhancing identity management is getting governments to become genuinely interested, both in their capacity of data processing organisation and legislator or policy maker. Another challenge, this time for the private sector, is to find the right balance between data protection perfection and simplicity or users' convenience, while developing privacy enhancing identity management systems. After a brief discussion of these challenges we discuss the growing human rights recognition of the value of digital identity and its management. In particular, the German constitutional court seems to pave the way for a basic right to have digital identity protected and secured.
Using Neurofuzzy Models and Spectral Analysis for Prediction of the Exotic Phenomena with Catastrophic Jumps
Authors: Masoud Mirmomeni, Caro Lucas, Babak Nadjar Araabi
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

Catastrophe theory is a mathematical technique for the analysis of system equations, defining the jump phenomena and sudden changes caused by smoothed alterations in the situation. This theory has been used several times to describe many exotic phenomena in different domain of science such as biology and physics. On the other hand, recent technological progress entails high risk levels. Such progress in 21st century has made human life increasingly dependent on technologies which exotic phenomena with catastrophic behaviors seem to be a threat for them. It is meaningful to develop a long-term predictor for modern technologies to avoid such exotic phenomena. In this study, a long-term predictor based on neurofuzzy models and spectral analysis as a powerful method to describe complex phenomena is proposed as an alarm system to avoid unexpected catastrophic events. Results depict the power of this alarm system to protect technologies from undesirable sudden and catastrophic changes.
The effect of positive emotions on cognitive processes in multimedia-based learning
Authors: Jan L. Plass
Venue:  (2008)

The study examined whether the positive emotions experienced during multimedia teaming facilitate cognitive processes that leads to better learning performance and other affective experiences such as satisfaction, perception, motivation and cognitive load. One hundred eighteen college students were randomly assigned to four experimental treatment conditions These four conditions were created by two design factors, which were the manipulation of emotions by means of self-referencing mood induction procedure (positive or neutral emotions), and the manipulation of affect by means of the aesthetic design of the learning materials (positive or neutral design). A self-referencing mood induction procedure developed by Seibert Ellis (1991) was provided before a multimedia-based base learning. A computer-based lesson of 'How immunization works' was used as multimedia learning material. The 'positive emotional design' version was revised from the neutral one to have better quality in aesthetic design using emotional design principles such as color combination, anthropomorphism, and baby-face effect. Participants' emotions were measured before and after the learning using PAS (Positive Affect Schedule) questionnaire (Watson, Clark, Tellegen, 1988). Afterwards, they took comprehension and transfer tests for learning performance and answered questionnaires of other experiences. The result showed that the positive emotions experienced during the learning improved the learners' learning performance, motivation, satisfaction and perception toward the learning. It also indicated that positive emotions were generated by the aesthetic design of the learning material. The results of the study supported the facilitation hypothesis of positive emotions in the context of learning. The study implies that positive emotions should be considered as important factors in instructional design and that emotional design principles should be studied in more detail for better instructional material design.
An investigation of temperature effect on microstructure and mechanical properties of aluminum (A360) processed by thixoforging
Authors: M. K. Besharati, K. Davami, M. Shaygan
Venue: Proceedings of the 8th WSEAS International Conference on Robotics, Control and Manufacturing Technology (2008)

Thixoforging has some advantages over conventional forming processes such as die casting, squeeze casting, and hot/cold forging. Thixoforging can produce non-dendritic alloys for the semi-solid forming of complex-shaped parts in metal alloys. Since thixoforging takes place between liquidus and solidus temperature and liquid phase and solid phase exist at the same time, heating circumstances is more significant. In order to achieve homogenous microstructure during heating, eutectic must transformed to liquid completely to gain suitable mechanical properties. The solid phase percentage during forming process in semi-solid condition, has a very important effect which is affected by heating temperature. In this research, the effect of temperature on thixoforging process and mechanical properties of the work piece was investigated. The lap, which is an external defect, was observed at higher initial work piece temperature. In hardness test, it was observed that the hardness decreased at higher initial work piece temperature.
E-Learning for Secondary School Teachers: Inclusive Science and Math Instruction for Students with Disabilities
Authors: Robert L. Todd
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

The Georgia Institute of Technology (Georgia Tech) is conducting a research and development project to enhance the capacities of science, technology, engineering and mathematics (STEM) teachers to educate students with disabilities. The project has conducted online surveys, focus groups and longitudinal studies to discover the training and knowledge needs of teachers. The ongoing research has identified significant gaps in teacher knowledge about students with disabilities and the accommodations that can help them succeed. In particular, there is a pervasive lack of understanding of the uses of assistive technology, along with discomfort in the use of this technology. Findings have been used in the creation of online training courses designed to meet teacher needs in the classroom and laboratory environments. Further research will investigate the use of project resources with teachers of students with focused disability issues.
Using Linguistic Knowledge to Classify Non-functional Requirements in SRS documents
Authors: Ishrar Hussain, Leila Kosseim, Olga Ormandjieva
Venue: Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems (2008)

Non-functional Requirements (NFRs) such as software quality attributes, software design constraints and software interface requirements hold crucial information about the constraints on the software system under development and its behavior. NFRs are subjective in nature and have a broad impact on the system as a whole. Being distinct from Functional Requirements (FR), NFRs are dealt with special attention, as they play an integral role during software modeling and development. However, since Software Requirements Specification (SRS) documents, in practice, are written in natural language, solely holding the perspectives of the clients, the documents often end up with FR and NFR statements mixed together in the same paragraphs. It is, therefore, left upon the software analysts to classify and separate them manually. The research, presented in this paper, aims to automate the process of detecting NFR sentences by using a text classifier equipped with a part-of-speech (POS) tagger. The results reported in this paper outperform the recent work in the field, and achieved a higher accuracy of 98.56% using 10-folds-cross-validation over the same data used in the literature. The research reported in this paper is part of a larger project aimed at applying Natural Language Processing techniques in Software Requirements Engineering.
Heuristics for Planning with Action Costs
Authors: Emil Keyder, Hector Geffner
Venue: Current Topics in Artificial Intelligence: 12th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2007, Salamanca, Spain, November 12-16, 2007. Selected Papers (2007)

We introduce a non-admissible heuristic for planning with action costs, called the set-additive heuristic, that combines the benefits of the additive heuristic used in the HSP planner and the relaxed plan heuristic used in FF. The set-additive heuristic $h^s_a$ is defined mathematically and handles non-uniform action costs like the additive heuristic h a , and yet like FF's heuristic $h_{\textrm{\scriptsize FF}}$, it encodes the cost of a specific relaxed plan and is therefore compatible with FF's helpful action pruning and its effective enforced hill climbing search. The definition of the set-additive heuristic is obtained from the definition of the additive heuristic, but rather than propagating the value of the best supports for a precondition or goal, it propagates the supports themselves, which are then combined by set-union rather than by addition. We report then empirical results on a planner that we call FF($h^s_a$) that is like FF except that the relaxed plan is extracted from the set-additive heuristic. The results show that FF($h^s_a$) adds only a slight time overhead over FF but results in much better plans when action costs are not uniform.