ppxscal/embedding_network huggingface dataset:
A multimode navigation system for an assistive robotics project
Authors: Andrea Cherubini, Giuseppe Oriolo, Francesco Macrí, Fabio Aloise, Febo Cincotti, Donatella Mattia
Venue: Autonomous Robots (2008)

Assistive technology is an emerging area, where robotic devices can help individuals with motor disabilities to achieve independence in daily activities. This paper deals with a system that provides remote control of Sony AIBO, a commercial mobile robot, within the assistive project ASPICE. The robot can be controlled by various input devices, including a Brain-Computer Interface. AIBO has been chosen for its friendly-looking aspect, in order to ease interaction with the patients. The development of the project is described by focusing on the design of the robot navigation system. Single step, semi-autonomous and autonomous navigation modes have been realized to provide different levels of control. Automatic collision avoidance is integrated in all cases. Other features of the system, such as the video feedback from the robotic platform to the user, and the use of AIBO as communication aid, are briefly described. The performance of the navigation system is shown by simulations as well as experiments. The system has been clinically validated, in order to obtain a definitive assessment through patient feedback.
An algorithm for fuzzy multi-objective multi-follower partial cooperative bilevel programming
Authors: Guangquan Zhang, Jie Lu, Ya Gao
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2008)

In a bilevel decision problem, both the leader and the follower may have multiple objectives to optimize under certain constraints. In the meantime, these objective functions and constraints may contain some uncertain parameters. In addition, there may have multiple followers involved in a bilevel decision problem. These followers may share their individual decision variables with each other but keep individual objectives in reacting any of the leader's decisions, which is a common situation in real bilevel decision activities. This study deals with all above three issues, fuzzy parameters, multi-objectives, and multi-followers in a partial cooperative situation, at the same time. After a set of models for describing different cases of the fuzzy multi-objective multi-follower bilevel programming with partial cooperation (FMMBP-PC) problem, this paper develops an approximation branch-and-bound algorithm to solve this problem.
Evaluating Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data for alteration zone enhancement in a semi-arid area, northern Shahr-e-Babak, SE Iran
Authors: Majid H. Tangestani, Nazi Mazhari, Bob Agar, Farid Moore
Venue: International Journal of Remote Sensing (2008)

The visible-near infrared (VNIR) and short wave infrared (SWIR) spectral bands of both the level 1B, radiance at sensor, and level 2, AST_07 surface reflectance data products of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument were evaluated and compared for mapping the alteration zones around porphyry copper deposits and occurrences at the northern Shahr-e-Babak, SE Iran. The level 1B data were converted to reflectance using internal average relative reflectance (IARR) method whereas the AST_07 dataset was processed as delivered. The porphyry copper mineralization occurs in Eocene, andesitic and basaltic rocks with zonal alteration patterns that are concentric and almost symmetrically arranged. The spectral signatures of alteration index minerals collected from field samples and the United States Geological Survey (USGS) spectral reference library, were considered in directed principal component analysis (DPCA) and spectral angle mapping (SAM) algorithms. Carrying out the DPCA method on three spectral bands enhanced the alteration haloes in the last principal component (PC) images. Generating RGB colour composite images using these PC images differentiated three alteration zones from the host rocks. The SAM results of the IARR calibrated dataset discriminated the propylitic, argillic and phyllic alteration zones. It is concluded that the higher spectral resolution of ASTER instrument is effective for mineral mapping. However, the method of conversion from radiance to reflectance is critical to the validity of the outputs and that the pseudo-reflectance method using the IARR process may be more reliable than the standard reflectance product.
Multidimensional content eXploration
Authors: Alkis Simitsis, Akanksha Baid, Yannis Sismanis, Berthold Reinwald
Venue: Proceedings of the VLDB Endowment (2008)

Content Management Systems (CMS) store enterprise data such as insurance claims, insurance policies, legal documents, patent applications, or archival data like in the case of digital libraries. Search over content allows for information retrieval, but does not provide users with great insight into the data. A more analytical view is needed through analysis, aggregations, groupings, trends, pivot tables or charts, and so on. Multidimensional Content eXploration (MCX) is about effectively analyzing and exploring large amounts of content by combining keyword search with OLAP-style aggregation, navigation, and reporting. We focus on unstructured data or generally speaking documents or content with limited metadata, as it is typically encountered in CMS. We formally present how CMS content and metadata should be organized in a well-defined multidimensional structure, so that sophisticated queries can be expressed and evaluated. The CMS metadata provide traditional OLAP static dimensions that are combined with dynamic dimensions discovered from the analyzed keyword search result, as well as measures for document scores based on the link structure between the documents. In addition, we provide means for multidimensional content exploration through traditional OLAP rollupdrilldown operations on the static and dynamic dimensions, solutions for multi-cube analysis and dynamic navigation of the content. We present our prototype, called DBPubs, which stores research publications as documents that can be searched and -most importantly-- analyzed, and explored. Finally, we present experimental results of the efficiency and effectiveness of our approach.
Self-Stabilizing Leader Election in Optimal Space
Authors: Ajoy K. Datta, Lawrence L. Larmore, Priyanka Vemula
Venue: Proceedings of the 10th International Symposium on Stabilization, Safety, and Security of Distributed Systems (2008)

A silent self-stabilizing asynchronous distributed algorithm, SSLE, for the leader election problem, in a connected unoriented network with unique IDs, is given. SSLE uses O(logn) space per process and stabilizes in O(n) rounds, where n is the number of processes in the network.
Read-optimized databases, in depth
Authors: Allison L. Holloway, David J. DeWitt
Venue: Proceedings of the VLDB Endowment (2008)

Recently, a number of papers have been published showing the benefits of column stores over row stores. However, the research comparing the two in an "apples-to-apples" way has left a number of unresolved questions. In this paper, we first discuss the factors that can affect the relative performance of each paradigm. Then, we choose points within each of the factors to study further. Our study examines five tables with various characteristics and different query workloads in order to obtain a greater understanding and quantification of the relative performance of column stores and row stores. We then add materialized views to the analysis and see how much they can help the performance of row stores. Finally, we examine the performance of hash join operations in column stores and row stores.
Smoothing human-robot speech interactions by using a blinking-light as subtle expression
Authors: Kotaro Funakoshi, Kazuki Kobayashi, Mikio Nakano, Seiji Yamada, Yasuhiko Kitamura, Hiroshi Tsujino
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

Speech overlaps, undesired collisions of utterances between systems and users, harm smooth communication and degrade the usability of systems. We propose a method to enable smooth speech interactions between a user and a robot, which enables subtle expressions by the robot in the form of a blinking LED attached to its chest. In concrete terms, we show that, by blinking an LED from the end of the user's speech until the robot's speech, the number of undesirable repetitions, which are responsible for speech overlaps, decreases, while that of desirable repetitions increases. In experiments, participants played a last-and-first game with the robot. The experimental results suggest that the blinking-light can prevent speech overlaps between a user and a robot, speed up dialogues, and improve user's impressions.
Application of fuzzy extended AHP methodology on shipping registry selection: The case of Turkish maritime industry
Authors: Metin Celik, I. Deha Er, A. Fahri Ozok
Venue: Expert Systems with Applications: An International Journal (2009)

Selection of the suitable shipping registry alternative for the existing fleet or new building ships is one of the critical decision milestones of the shipping business. The main aim of this paper is to structure a practical decision support mechanism on ensuring multiple criteria analysis of shipping registry selection. Fuzzy AHP methodology, based on Chang's extent analysis, is determined to be utilized in order to model the shipping registry selection. After structuring the fundamental hierarchy, the model is performed with a case application on Turkish maritime industry to be able to obtain illustrative results. The shipping registries of Turkiye, Panama, and Malta are determined to evaluate as the potential alternatives for Turkish ship owners. When the literature was examined for the applications of analytical methodologies on maritime business, it was seemed that they were so rare. Therefore, the originality of this study appears on modeling of the critical process under multidisciplinary philosophy in ship management.
StatAlign
Authors: Ádám Novák, István Miklós, Rune Lyngsø, Jotun Hein
Venue: Bioinformatics (2008)

Motivation: Bayesian analysis is one of the most popular methods in phylogenetic inference. The most commonly used methods fix a single multiple alignment and consider only substitutions as phylogenetically informative mutations, though alignments and phylogenies should be inferred jointly as insertions and deletions also carry informative signals. Methods addressing these issues have been developed only recently and there has not been so far a user-friendly program with a graphical interface that implements these methods. Results: We have developed an extendable software package in the Java programming language that samples from the joint posterior distribution of phylogenies, alignments and evolutionary parameters by applying the Markov chain Monte Carlo method. The package also offers tools for efficient on-the-fly summarization of the results. It has a graphical interface to configure, start and supervise the analysis, to track the status of the Markov chain and to save the results. The background model for insertions and deletions can be combined with any substitution model. It is easy to add new substitution models to the software package as plugins. The samples from the Markov chain can be summarized in several ways, and new postprocessing plugins may also be installed. Availability: The code is available from http://phylogeny-cafe.elte.hu/StatAlign/ Contact: miklosi@ramet.elte.hu
A note on the Ate pairing
Authors: Chang-An Zhao, Fangguo Zhang, Jiwu Huang
Venue: International Journal of Information Security (2008)

The Ate pairing has been suggested since it can be computed efficiently on ordinary elliptic curves with small values of the traces of Frobenius t. However, not all pairing-friendly elliptic curves have this property. In this paper, we generalize the Ate pairing and find a series of the variations of the Ate pairing. We show that the shortest Miller loop of the variations of the Ate pairing can possibly be as small as r 1/&#x03c6;(k) on some special pairing-friendly curves with large values of Frobenius trace, and hence speed up the pairing computation significantly.
A Bias-Variance Analysis of Multiple Criteria Linear Programming Classification Ensembles
Authors: Meihong Zhu, Yong Shi, Aihua Li, Peng Zhang
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03 (2008)

According to Domingos’ bias–variance decomposition framework, we study the bias–variance characteristics of the standard Multiple Criteria Linear Programming (MCLP) classification method. The experimental results show that, under Domingos’ bias–variance decomposition framework, bias is much bigger than variance, and boosting ensemble doesn’t behave better than bagging ensemble, and increasing training example can effectively reduce variance rather than bias. We conclude that MCLP intrinsically is a stable classification method, and that an appropriate ensemble method for MCLP rests with the characteristics of a specific data set. When data can be easily linearly separated, MCLP will have low bias and bagging can be employed to lessen variance. When data present complicated no-linear structure, MCLP will have high bias and boosting ensemble can be considered to reduce bias. But, when boosting is used, noises and over fitting should be considered.
Measuring the Impact of Different Categories of Software Evolution
Authors: Francesca Longo, Roberto Tiella, Paolo Tonella, Adolfo Villafiorita
Venue: Proceedings of the International Conferences on Software Process and Product Measurement (2008)

Software evolution involves different categories of interventions, having variable impact on the code. Knowledge about the expected impact of an intervention is fundamental for project planning and resource allocation. Moreover, deviations from the expected impact may hint for areas of the system having a poor design. In this paper, we investigate the relationship between evolution categories and impacted code by means of a set of metrics computed over time for a subject system.
An efficient intra-mode selection algorithm for H.264 based on edge classification and rate-distortion estimation
Authors: Zhenyu Wei, King N. Ngan, Hongliang Li
Venue: Image Communication (2008)

The H.264/AVC is the newest video coding standard recommended by ITU-T and MPEG. Compared with all existing video coding standards, H.264 can achieve superior performance by using many advanced techniques. Intra mode selection is an important feature in H.264 standard and can reduce the spatial redundancy in intra-frame significantly. An efficient rate distortion optimization (RDO) technique is employed in H.264 to choose the best mode for each MB, but the computational cost increases drastically. In this paper, a fast intra-mode selection algorithm is introduced. By using a fast edge detection method which is based on non-normalized Haar transform (NHT), edge for each sub-block can be extracted. Based on the local edge information, only few intra-modes are chosen as mode candidates. A fast RDO algorithm is also proposed in this paper which is based on accurate rate-distortion estimation model and the fast intra-mode RDO method. By combining these two methods, computational load is reduced remarkably. Experimental results show that this fast intra-mode selection scheme can lessen the encoding time significantly with little loss of bit-rate and visual quality.
Comprehensive in silico mutagenesis highlights functionally important residues in proteins
Authors: Yana Bromberg, Burkhard Rost
Venue: Bioinformatics (2008)

Motivation: Mutating residues into alanine (alanine scanning) is one of the fastest experimental means of probing hypotheses about protein function. Alanine scans can reveal functional hot spots, i.e. residues that alter function upon mutation. In vitro mutagenesis is cumbersome and costly: probing all residues in a protein is typically as impossible as substituting by all non-native amino acids. In contrast, such exhaustive mutagenesis is feasible in silico. Results: Previously, we developed SNAP to predict functional changes due to non-synonymous single nucleotide polymorphisms. Here, we applied SNAP to all experimental mutations in the ASEdb database of alanine scans; we identi.ed 70% of the hot spots (≥1 kCal/mol change in binding energy); more severe changes were predicted more accurately. Encouraged, we carried out a complete all-against-all in silico mutagenesis for human glucokinase. Many of the residues predicted as functionally important have indeed been con.rmed in the literature, others await experimental veri.cation, and our method is ready to aid in the design of in vitro mutagenesis. Availability: ASEdb and glucokinase scores are available at http://www.rostlab.org/services/SNAP. For submissions of large/whole proteins for processing please contact the author. Contact: yb2009@columbia.edu
Polynomial-Time Under-Approximation of Winning Regions in Parity Games
Authors: Adam Antonik, Nathaniel Charlton, Michael Huth
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

We propose a pattern for designing algorithms that run in polynomial time by construction and under-approximate the winning regions of both players in parity games. This approximation is achieved by the interaction of finitely many aspects governed by a common ranking function, where the choice of aspects and ranking function instantiates the design pattern. Each aspect attempts to improve the under-approximation of winning regions or decrease the rank function by simplifying the structure of the parity game. Our design pattern is incremental as aspects may operate on the residual game of yet undecided nodes. We present several aspects and one higher-order transformation of our algorithms - based on efficient, static analyses - and illustrate the benefit of their interaction as well as their relative precision within pattern instantiations. Instantiations of our design pattern can be applied for local model checking and as preprocessors for algorithms whose worst-case running time is exponential. This design pattern and its aspects have already been implemented in [H. Wang. Framework for Under-Approximating Solutions of Parity Games in Polynomial Time. MEng Thesis, Department of Computing, Imperial College London, 78 pages, June 2007].
Ubi-App: a ubiquitous application for universal access from handheld devices
Authors: Shameem Ahmed, Moushumi Sharmin, Sheikh I. Ahamed
Venue: Universal Access in the Information Society (2008)

Universal access from a handheld device (such as a PDA, cell phone) at any time or anywhere is now a reality. Ubicomp Assistant (UA) (Sharmin et al. in Proceedings of the 21st annual ACM symposium on applied computing (ACM SAC 2006), Dijon, France, pp 1013&#x2013;1017, 2006) is an integral service of MARKS (Sharmin et al. in Proceedings of the third international conference on information technology: new generations (ITNG 2006), Las Vegas, Nevada, USA, pp 306&#x2013;313, 2006). It is a middleware developed for handheld devices, and has been designed to accommodate different types of users (e.g., education, healthcare, marketing, or business). This customizable service employs the ubiquitous nature of current short range, low-power wireless connectivity and readily available, low-cost lightweight mobile devices. These devices can reach other neighbouring devices using a free short-range ad hoc network. To the best of the authors&#x2019; knowledge, the UA service is the only service designed for these devices. This paper presents the details of Ubi-App, a ubiquitous application for universal access from any handheld device, which uses UA as a service. The results of a usability test and performance evaluation of the prototype show that Ubi-App is useful, easy to use, easy to install, and does not degrade the performance of the device.
Application of neural networks to recognize profitable customers for dental services marketing-a case of dental clinics in Taiwan
Authors: Wan-I Lee, Bih-Yaw Shih
Venue: Expert Systems with Applications: An International Journal (2009)

The purpose of the research was the development of a neural networks model to recognize profitable customers for dental services marketing. Data set was built up from proprietary customer databases and survey of seven dental clinics in Taiwan. Multi-layer feed-forward neural networks with sigmoid function trained by back-propagation training algorithm were utilized to build the recognition model. The result reveals that the recognition accuracy of the test on the model is greater than that expected by chance. Meanwhile, a set of contribution weights representing the general importance of each independent variable was produced and their marketing implications were illustrated. This research confirms that the neural network model is useful in recognizing existing patterns of customers' data. The advantages of using the model are highlighted and marketing implications are demonstrated. Authors believe that the model is useful and suitable as an analyzing tool for dental marketers on market strategy planning.
Reconstruction of Partial Orders and List Representation as Random Structures
Authors: Thierry Vallée, Joseph Manning
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

MOQA is a new programming language with the unique property that the average running time of its programs can be (semi-)automatically deduced in a modular way by a static analysis of the program code. This is based on the fact that to each MOQA action there corresponds an operation on partial orders, which associates with each partial order a sequence of partial orders. All programs in MOQA use a special data structure and an associated suite of operations. This data structure consists of a pair ((X,@?),@?), where (X,@?) is a finite poset and @?:X@?L is a bijection from X to a totally ordered set of labels L, satisfying the condition x@?y@?@?(x)=
Population size reduction for the differential evolution algorithm
Authors: Janez Brest, Mirjam Sepesy Maučec
Venue: Applied Intelligence (2008)

This paper studies the efficiency of a recently defined population-based direct global optimization method called Differential Evolution with self-adaptive control parameters. The original version uses fixed population size but a method for gradually reducing population size is proposed in this paper. It improves the efficiency and robustness of the algorithm and can be applied to any variant of a Differential Evolution algorithm. The proposed modification is tested on commonly used benchmark problems for unconstrained optimization and compared with other optimization methods such as Evolutionary Algorithms and Evolution Strategies.
PHANTOM prototype: exploring the potential for learning with multimodal features in dentistry
Authors: Jonathan Padilla San Diego, Alastair Barrow, Margaret Cox, William Harwin
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

In this paper, we will demonstrate how force feedback, motion-parallax, and stereoscopic vision can enhance the opportunities for learning in the context of dentistry. A dental training workstation prototype has been developed intended for use by dental students in their introductory course to preparing a tooth cavity. The multimodal feedback from haptics, motion tracking cameras, computer generated sound and graphics are being exploited to provide 'near-realistic' learning experiences. Whilst the empirical evidence provided is preliminary, we describe the potential of multimodal interaction via these technologies for enhancing dental-clinical skills.