ppxscal/embedding_network huggingface dataset:
An Advanced Clonal Selection Algorithm with Ad-Hoc Network-Based Hypermutation Operators for Synthesis of Topology and Sizing of Analog Electrical Circuits
Authors: Angelo Ciccazzo, Piero Conca, Giuseppe Nicosia, Giovanni Stracquadanio
Venue: Proceedings of the 7th international conference on Artificial Immune Systems (2008)

In electronics, there are two major classes of circuits, analog and digital electrical circuits. While digital circuits use discrete voltage levels, analog circuits use a continuous range of voltage. The synthesis of analog circuits is known to be a complex optimization task, due to the continuous behaviour of the output and the lack of automatic design tools; actually, the design process is almost entirely demanded to the engineers. In this research work, we introduce a new clonal selection algorithm, the elitist Immune Programming, (eIP) which uses a new class of hypermutation operators and a network-based coding. The eIP algorithm is designed for the synthesis of topology and sizing of analog electrical circuits; in particular, it has been used for the design of passive filters. To assess the effectiveness of the designed algorithm, the obtained results have been compared with the passive filter discovered by Koza and co-authors using the Genetic Programming (GP) algorithm. The circuits obtained by eIP algorithm are better than the one found by GP in terms of frequency response and number of components required to build it.
Design and Implementation of an Image CoProcessor
Authors: R. Ebrahimi Atani, S. Mirzakuchaki, S. Ebrahimi Atani
Venue: Proceedings of the 3rd international conference on Image and Signal Processing (2008)

This paper presents a novel DA based 2D DCT/DST coprocessor architecture for the synchronous design in a Xilinx FPGA device. A 1.2V, 90nm triple-oxide technology, Virtex-IV FPGA is used for final implementation and maximum operating frequency of 117 MHz is achieved. Using XPower toolbox, the total dynamic power consumption of 393 mW is measured. The paper presents the trade-offs involved in designing the architecture, and the design for performance issues.
Evaluating Text Normalization for Speech-Based Media Selection
Authors: Martin Pfeil, Dirk Buehler, Rainer Gruhn, Wolfgang Minker
Venue: Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems (2008)

In this paper, we present an approach how to evaluate text normalization for multi-lingual speech-based dialogue systems. The application of text normalization occurs within the task of music selection, which imposes several important and novel requirements on its performance. The main idea is that text normalization should determine likely user utterances from metadata that is available within a user's music collection. This is substantially different from the text preprocessing applied, for instance, in text-to-speech systems, because a) more than one normalization hypothesis may be generated, b) for media selection the information content may be reduced, which is not desirable for Text-to-speech (TTS). These factors also have an impact on evaluation.We describe an data collection effort that was carried out with the purpose of building an initial corpus of text normalization references and scorings, as well as experiments with well-known evaluation metrics from different areas of language research aiming at identifying an adequate evaluation measure.
NSF Support of Basic Research in Computer Science
Authors: J. R. Lehmann
Venue: Computer (1978)

Interestingly enough, much of the computer architecture research currently supported by the National Science Foundation is related to the theme of this issue. Below, John R. Lehmann, program director of NSF's Computer Systems Design Program, has provided a list of principal investigators and the titles of their research, as well as a brief statement on how to submit a research proposal.
MR-Less High Dimensional Spatial Normalization of 11C PiB PET Images on a Population of Elderly, Mild Cognitive Impaired and Alzheimer Disease Patients
Authors: Jurgen Fripp, Pierrick Bourgeat, Parnesh Raniga, Oscar Acosta, Victor Villemagne, Gareth Jones, Graeme O'Keefe, Christopher Rowe, Sébastien Ourselin, Olivier Salvado
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

β¿ amyloid (Aβ) plaques are one of the neuropathological hallmarks of Alzheimer's disease (AD) and can be quantified using the marker $^{11}\textnormal{C}$ PiB. As $^{11}\textnormal{C}$ PiB PET images have limited anatomical information, an Magnetic Resonance Image (MRI) is usually acquired to perform the spatial normalization needed for population analysis. We designed and evaluated a high dimensional spatial normalization approach that only uses the $^{11}\textnormal{C}$ PiB PET image. The non-rigid registration (NRR) is based on free form deformation (FFD) modelled using B-splines. To compensate for the limited anatomical information, the FFD is constrained to an allowable transform space using a model trained from MR registrations. Aβ deposition is dependent on disease staging, so a spatially normalized $^{11}\textnormal{C}$ PiB PET appearance model selects and refines the atlas. The approach was compared with MR NRR using data from healthy elderly, mild cognitive impaired and Alzheimer disease participants. Using segmentation propagation, an average Dice similarity coefficient of 0.64 and 0.73 was obtained for white and gray matter. The R-squared correlation between the uptake obtained in the frontal, parietal, occipital and temporal was 0.789, 0.843, 0.871 and 0.964. These are very promising results, considering the low resolution of $^{11}\textnormal{C}$ PiB PET images.
Tree-Structured Support Vector Machines for Multi-class Classification
Authors: Siyu Xia, Jiuxian Li, Liangzheng Xia, Chunhua Ju
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

In this paper, a non-balanced binary tree is proposed for extending support vector machines (SVM) to multi-class problems. The non-balanced binary tree is constructed based on the prior distribution of samples, which can make the more separable classes separated at the upper node of the binary tree. For an k class problem, this method only needs k-1 SVM classifiers in the training phase, while it has less than k binary test when making a decision. Further, this method can avoid the unclassifiable regions that exist in the conventional SVMs. The experimental result indicates that maintaining comparable accuracy, this method is faster than other methods in classification.
The High Road to Formal Validation
Authors: Michael Leuschel
Venue: Proceedings of the 1st international conference on Abstract State Machines, B and Z (2008)

In this paper we examine the difference between model checking high-level and low-level models. In particular, we compare the ProB model checker for the B-method and the Spin model checker for Promela. While Spin has a dramatically more efficient model checking engine, we show that in practice the performance can be disappointing compared to model checking high-level specifications with ProB. We investigate the reasons for this behaviour, examining expressivity, granularity and Spin's search algorithms. We also show that certain types of information (such as symmetry) can be more easily inferred and exploited in high-level models, leading to a considerable reduction in model checking time.
Improving EEG Analysis by Using Paraconsistent Artificial Neural Networks
Authors: Jair Minoro Abe, Helder F. Lopes, Kazumi Nakamatsu
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

In this paper we present a study of EEG by using the Paraconsistent Artificial Neural Network --- PANN that can manipulate imprecise, contradictory and paracomplete data. Some improvements for EEG analysis are discussed. Experimental results concerning Alzheimer Disease made are also reported.
A System Behavior Analysis Technique with Visualization of a Customer's Domain
Authors: Shoichi Morimoto
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Object-oriented analysis with UML is an effective process for software development. However, the process closely depends on workmanship and experience of software engineers. In order to mitigate this problem, a precedence effort, scenario-based visual analysis, has been proposed. The technique visualizes a customer's domain, thus it enables requirement analyzers and customers to communicate smoothly. The customers themselves can schematize their workflows with the technique. Consequently, the analyzers and customers can easily and exactly derive use case models via the collaborative works. Thus, this paper proposes a technique to advance the analysis further, inheriting such advantages. The extended technique can analyze initial system behavior specifications. The customers can also join and understand system behavior analysis, thus they can easily decide on specifications for developing systems.
Agent Environment and Knowledge in Distributed Join Calculus
Authors: Sławomir P. Maludziński, Grzegorz Dobrowolski
Venue: Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V (2007)

Distributed join calculus can be used to formally reason about concurrent systems. This paper introduces notion of an environment where agents interact. Based on the introduced formalisms a notion of knowledge which is exchanged by facts and common to all agents is presented. Introduction of the environment and knowledge extends number of agent system which can be expressed using join calculus algebra.
Dynamic Optimization of Load Balance in MPI Broadcast
Authors: Takesi Soga, Kouji Kurihara, Takeshi Nanri, Motoyoshi Kurokawa, Kazuaki Murakami
Venue: Proceedings of the 14th European PVM/MPI User's Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2007)

There are many algorithms that compose broadcast from point-topoint communications, such as Binary Tree and Binomial Tree. Though many implementations of these algorithms are proposed in MPI libraries like MPICH [1], most of them are based on an assumption that all processes begin the broadcast at the same time. That means the orders of the point-to-point communications in the broadcast are arranged numerically, according to the rank of each process. However, naturally each process starts broadcast at different times, mainly because of the imbalance of workload of each process. That causes unnecessary waiting time on processes. Also, in a broadcast algorithm such as binomial tree algorithm, the amount of communication is different for each process therefore load imbalance is increased by the occurrence of both heavy workload and heavy communications on a same process. Our method purposes to solve these problems dynamically. This method solves these problems by profiling the workload of each rank at runtime and adjusting the orders of point-to-point communications according to the information.
On the Optimality of MAP Bit Detection of Coded M-PSK Signals
Authors: Jun Zhang, Kai-yuan Shi, Hua Peng
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

The optimality of the maximum a posteriori probability(MAP) bit detection for differentially encoded M-PSK signals over static non-ISI channels is emphasized, in which the demodulator computes loglikelihood ratio (LLR) of individual coded bits directly, but not via transforming those successive detected symbols’ LLR into bits’ LLR as the conventional methods. As a representative, the designs and analyses focus on the convolutionally encoded π/4-DQPSK signal. In order to demonstrate the optimality comparatively, the other two types of soft demodulators derived under the MAP symbol detection criterion and the MAP sequence detection criterion are also addressed. Through simulations the noticeable performance of the MAP bit detection are illustrated, especially in low SNR scenarios.
Some Puzzles About Probability and Probabilistic Conditionals
Authors: Rohit Parikh
Venue: Proceedings of the international symposium on Logical Foundations of Computer Science (2007)

We examine some old and new paradoxes of probability, give a rough account of probabilistic conditionals, and prove a new result about non-monotonicity in probabilistic conditionals. It is well known that such conditionals are not monotonic --- a conditional which is true can become false when additional hypotheses are added. We show that nonetheless, the conditionals are usually monotonic, or roughly speaking that we do not actually have to worry about non-monotonicity in practice.
Adaptive Transmission Technique in Underwater Acoustic Wireless Communication
Authors: Guoqing Zhou, Taebo Shim
Venue: Proceedings of the 7th international conference on Evolvable Systems: From Biology to Hardware (2007)

Underwater acoustic channel (UACh) requires robust techniques to get high speed data transmission for reliable communication. If the channel can be estimated and this estimate sent back to the transmitter, the transmission scheme can be adapted to the channel variation. In this paper, we assume a fixed source and receiver configuration over a slowly-varying UACh, where the instantaneous signal to noise ratio (SNR) is constant over a large number of transmissions and then changes to a new value based on the Rayleigh fading distribution. Theoretical derivation of channel capacity (ChC) shows that we can optimize the data rate allowing the transmit power to vary with SNR, subject to an average power constraint. Simulation study also shows that using adaptive technique, we can adapt the channel variation in UACh communication. We also find that variability of the UACh capacity seems not to be negligible by the sloping condition.
Partial Reconfiguration Bitstream Compression for Virtex FPGAs
Authors: Haiyun Gu, Shurong Chen
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

An adaptive LZW algorithm for compressing partial bitstreams of Virtex FPGAs was presented. The adaptations of algorithm were based on analysis of the three-level data regularity of the configuration bitstreams. Partial bitstreams were created through Xilinx module-based partial reconfiguration flow. The experiment demonstrated down to 43.69% compression ratio for partial bitstreams of several real-world applications.
Extracting Grammars from RNA Sequences
Authors: Gabriela Andrejková, Helena Lengeňová, Michal Mati
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

In the paper, we describe an application of stochastic context-free grammars (SCFG) to modelling of the formal RNA string language. The simplification of the stochastic context-free grammar and it's conversion to Chomsky normal form was used. We present the modification of Cocke-Kasami-Younger algorithm that is used for probabilistic estimations of stochastic grammars for RNA sequences. Some better algorithms were constructed to decrease the computational complexity but still on the level of O(n 3) where n is the length of the RNA strings. The results of using the algorithms to the training sample consisted of tRNA chains of Acinetobacter sp. bactery are described.
Applying Rough Set Theory to Medical Diagnosing
Authors: Piotr Paszek, Alicja Wakulicz---Deja
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

The work contains an example of applying the rough set theory to application of support decision making - diagnose Mitochondrial Encephalomyopathies (MEM) in a child. The resulting decision support system maximally limits the indications for invasive diagnostic methods that finally decide about diagnosis. Moreover, it shortens the time necessary for making diagnosis. System has arisen using induction (machine learning from examples) --- one of the methods artificial intelligence.
Locality and Bounding-Box Quality of Two-Dimensional Space-Filling Curves
Authors: Herman Haverkort, Freek Walderveen
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

Space-filling curves can be used to organise points in the plane into bounding-box hierarchies (such as R-trees). We develop measures of the bounding-box quality of space-filling curves that express how effective different curves are for this purpose. We give general lower bounds on the bounding-box quality and on locality according to Gotsman and Lindenbaum for a large class of curves. We describe a generic algorithm to approximate these and similar quality measures for any given curve. Using our algorithm we find good approximations of the locality and bounding-box quality of several known and new space-filling curves. Surprisingly, some curves with bad locality by Gotsman and Lindenbaum's measure, have good bounding-box quality, while the curve with the best-known locality has relatively bad bounding-box quality.
Teaching students to identify common programming errors using a game
Authors: E. M. Nalaka S. Edirisinghe
Venue: Proceedings of the 9th ACM SIGITE conference on Information technology education (2008)

Introductory computer programming remains a challenging subject for many first-time students. This challenge is further compounded by the difficulty students face in identifying the errors in their own computer programs. While debuggers are helpful in locating the errors, students need to play a part in determining what went wrong and how to fix it. In addition, without a strong foundation in identifying the errors, students continue to repeat the same mistakes as they progress through their academic careers. This paper shares the processes and lessons learned from a pilot project of developing a Tetris-like game prototype using GameMaker to help students identify common syntax errors in their computer programs. This paper describes the experiences of developing this game and adopting it in an introductory Java programming classroom. It discusses the students' experiences and how such games may be a possible means of engaging and teaching students to identify programming errors.
A reactive variable neighborhood tabu search for the heterogeneous fleet vehicle routing problem with time windows
Authors: D. C. Paraskevopoulos, P. P. Repoussis, C. D. Tarantilis, G. Ioannou, G. P. Prastacos
Venue: Journal of Heuristics (2008)

This paper presents a solution methodology for the heterogeneous fleet vehicle routing problem with time windows. The objective is to minimize the total distribution costs, or similarly to determine the optimal fleet size and mix that minimizes both the total distance travelled by vehicles and the fixed vehicle costs, such that all problem's constraints are satisfied. The problem is solved using a two-phase solution framework based upon a hybridized Tabu Search, within a new Reactive Variable Neighborhood Search metaheuristic algorithm. Computational experiments on benchmark data sets yield high quality solutions, illustrating the effectiveness of the approach and its applicability to realistic routing problems.
A Multi-Classifier System for Pulmonary Nodule Classification
Authors: Michela Antonelli, Marco Cococcioni, Beatrice Lazzerini, Francesco Marcelloni, Dan Stefanescu
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

We have developed a multi-classifier system for automatic classification of pulmonary nodules in lung CT (Computed Tomography) images. The system consists of a set of independent modules, each emulating a radiologist of a team, and a further module aimed at appropriately combining theradiologists' opinions. In the experiments we obtained a sensitivity of 95% against a specificity of 91.33%, adopting a combiner based on the decision templates technique.
Monitoring the development of thermoregulation in poultry embryos and its influence by incubation temperature
Authors: B. Tzschentke
Venue: Computers and Electronics in Agriculture (2008)

The general purpose of this review is to show the stage of the development of peripheral and central nervous thermoregulatory mechanisms in poultry embryos at the end of incubation, and the impact of long-term changes in incubation temperature. Methods are described which (a) allow continuous measurement of peripheral thermoregulatory mechanisms simultaneously with the body temperature of the embryo, and (b) can be used for identification of changes in the sensitivity of the central controller of body temperature during the development as well as after prenatal temperature experiences. Further, a method for characterisation of 'critical periods' in the development of the respective body function is introduced. The results of our investigations were discussed in relation to the following general rules: (a) The development of peripheral and central nervous thermoregulatory mechanisms begins in the course of the prenatal ontogeny. At the end of incubation poultry embryos have all the prerequisites to react to changes in incubation temperature. Regarding the peripheral thermoregulatory mechanisms the most sensitive parameter for characterization of the developmental level of embryonic thermoregulation is the deep body temperature. (b) Functional systems of the organism develop from open loop system without feedback control into closed system controlled by feedback mechanism. Acute changes in the environmental conditions (e.g. incubation temperature) induce as a rule, initially uncoordinated and immediately non-adaptive reactions. Later the uncoordinated (immediately non-adaptive) reactions change into coordinated (adaptive) reactions, probably with closing of the regulatory system ('critical period'). Environmental manipulation of immature physiological mechanisms could be used for characterization of 'critical periods' of the respective system. Monitoring of changes in the reactions of thermoregulatory mechanisms on the applied changes in incubation temperature during different perinatal time windows could help to limit 'critical periods' in the development of the thermoregulatory system. (c) During this 'critical periods', the actual environment modulates the development of the respective physiological control systems for the entire life period. Perinatal epigenetic temperature adaptation could be a tool to adapt poultry embryos or hatchlings to later climatic conditions. For detection of immediate and long-term effects of perinatal epigenetic temperature adaptation ('imprinting' of the thermoregulatory system) recordings of changes in neuronal hypothalamic thermosensitivity as well as in neuronal response on temperature stress are useful and have to be verified by identification of the respective effector genes and epigenetic changes in its expression.
XTutor: An Intelligent Tutor System for Science and Math Based on Excel
Authors: Roxana Gheorghiu, Kurt Vanlehn
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

VanLehn argued that an essential feature of many intelligent tutoring systems (ITSs) is that they provide feedback and hints on every step of a multi-step solution.But if step-based feedback and hints alone suffice for strong learning gains, as Anderson et al. conjecture ([1]), then perhaps a lightweight tutoring system that employ only feedback and bottom-out hints would have advantages. This motivates the current project.Using Excel there are some immediately advantages that can be obtained: most people is familiar with its user interface and its notation for mathematical expressions, Excel already contains facilities for solving some systems of equations and it can be easy combined with many other pieces of software, making it easier for instructors to include the tutor in their course activities. Finally, web-based delivery is simple because most students already have and use Excel.