ppxscal/embedding_network huggingface dataset:
Efficiency of Data Distribution in BitTorrent-Like Systems
Authors: Ho-Leung Chan, Tak-Wah Lam, Prudence W. Wong
Venue: Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management (2007)

BitTorrent (BT) in practice is a very efficient method to share data over a network of clients. In this paper we extend the recent work of Arthur and Panigrahy [1] on modelling the distribution of individual data blocks in BT systems, aiming at a better understanding of why BT can achieve a high degree of parallelism. In particular, we include in our study several new network features that BT systems are using, as well as different local heuristics for routing data blocks in each client. We conduct simulations to figure out to what extent the new network features and routing heuristics would affect the distribution efficiency. Our findings confirm that for the primitive network setting studied in [1], it does require ¿(b logn) phases for n clients to download b data blocks. More interestingly, our work suggests that for the more realistic network setting, the heuristics Random and Rarest Block First both allow n clients to download b blocks in b + O(logn) phases. We believe that the latter bound better reflects the high degree of parallelism of BT observed in reality. It is also worth-mentioning that b + logn is the smallest possible number of phases needed; it is interesting to see that some simple local routing heuristics have a performance so close to the optimal.
Skills vs. Abilities
Authors: Grigori Evreinov
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

A spectrum of human abilities, which people use to communicate and socially interact with others, is narrow enough (Table 1). Moreover, even basic human abilities (sensory-motor or/and cognitive) can be lost due to an accident or an illness. Nevertheless, the key issue is not how many different tools are needed to solve a specific problem but whether a person desires to be socially included [1, 2, 4, 7, 12, 14]. Social inclusion aims to reduce inequality between the least advantaged groups and communities and the rest of society. Nevertheless, the inclusion cannot be achieved when a target group or an individual person has a lack of skills to meet social challenges and opportunities.
Potential of mobile social networks as assistive technology: a case study in supported employment for people with severe mental illness
Authors: Yao-Jen Chang, Hung-Huan Liu, Shu-Min Peng, Tsen-Yung Wang
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

In this paper, we propose a general architecture of mobile social networks where individuals of the networks form a virtual community, conversing and connecting with one another based on mobile communication. Second, mobile social networks are implemented in collaboration with a supported employment program set up for people with severe mental illness.
A Visualization Study of Fluid-Structure Interaction between a Circular Cylinder and a Channel Bed
Authors: S. K. Rao, D. Sumner, R. Balachandar
Venue: Journal of Visualization (2004)

Flow visualization was used to study the fluid-structure interaction between a circular cylinder and a shallow turbulent open channel flow. The Reynolds number ranged from R$_{eD}$=1500-4400 based on the cylinder diameter, and from R$_{eH}$=7,800-27,600 based on the channel hydraulic radius. The cylinder was mounted vertically on the channel bed and the flow depth-to-cylinder-diameter ratio was varied from d/D=7.0-11.7. Tests were carried out over smooth and rough beds, with the rough beds being either permeable or impermeable. The study showed that the horseshoe vortex forming at the cylinder-bed junction affects many of the flow structures, including the mode of vortex shedding, the shear layer dynamics, the vortex formation length, and the width of the near-wake region. The influence of the horseshoe vortex can be recognized throughout the depth of flow; however, its influence decreases with an increase in distance from the channel bed. It was also possible to discern that the bed roughness resulted in a change to the above interaction and the permeability of the bed resulted in additional changes.
Interpolating Expressions in Unit Selection
Authors: Marc Schröder
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

In expressive speech synthesis, a key challenge is the generation of flexibly varying expressive tone while maintaining the high quality achieved with unit selection speech synthesis methods. Existing approaches have either concentrated on achieving high synthesis quality with no flexibility, or they have aimed at parametric models, requiring the use of parametric synthesis technologies such as diphone, formant or HMM-based synthesis.
Hybrid Neural Network Controller Using Adaptation Algorithm
Authors: Manjun Cai, Jincun Liu, Guangjun Tian, Xuejian Zhang, Tihua Wu
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

Neural network controller using adaptation algorithm is a new and simple controller, in which a feedback network propagating the error is not required. So it can be applied to hardware easily. Nevertheless, our simulations show that while the order of controlled plant is high, some unstable phenomenon appear and we also find that sometimes the error is far from being satisfactory, although when the order of controlled plant is low. Moreover, the present adaptation algorithm can not solve this problem. In this paper we will give our derivation of adaptation algorithm used in the neural network controller and configuration of an adaptive neural network controller. Then give some simulation figures to illustrate defect for the new controller. Finally we will develop a hybrid neural network to solve the problem and improve the accuracy as well as reduce the cost to the least in the practical application.
Emotions in Speech: Juristic Implications
Authors: Erik J. Eriksson, Robert D. Rodman, Robert C. Hubal
Venue: Speaker Classification I: Fundamentals, Features, and Methods (2007)

This chapter focuses on the detection of emotion in speech and the impact that using technology to automate emotion detection would have within the legal system. The current states of the art for studies of perception and acoustics are described, and a number of implications for legal contexts are provided. We discuss, inter alia, assessment of emotion in others, witness credibility, forensic investigation, and training of law enforcement officers.
Sender-Based TCP Scheme for Improving Performance in Wireless Environment
Authors: Jahwan Koo, Sung-Gon Mun, Hyunseung Choo
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

Conventional TCP in wireless environment has a lack of ability to differentiate the packet losses caused by network congestion from those caused by wireless link error. When the packet losses are due to wireless link error, TCP performance degradation occurs because of its congestion control mechanism. This paper propose a sender-side TCP scheme for discriminating the cause of packet losses. Simulation results show that it outperforms existing TCP congestion mechanisms such as WestwoodNR, TCP New Jersey, and TCP Reno in terms of goodput performance in wireless links.
Exploratory Characterization of Outliers in a Multi-centre 1H-MRS Brain Tumour Dataset
Authors: Alfredo Vellido, Margarida Julià-Sapé, Enrique Romero, Carles Arús
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

As part of the AIDTumour research project, the analysis of MRS data corresponding to various tumour pathologies is used to assist expert diagnosis. The high dimensionality of the MR spectra might obscure atypical aspects of the data that would jeopardize their automated classification and, as a result, the process of computer-based diagnostic assistance. In this paper, we put forward a method to overcome this potential problem that combines automatic outlier detection, visualization through dimensionality reduction, and expert opinion.
Reducing Payload Scans for Attack Signature Matching Using Rule Classification
Authors: Sunghyun Kim, Heejo Lee
Venue: Proceedings of the 13th Australasian conference on Information Security and Privacy (2008)

Network intrusion detection systems rely on a signature-based detection engine. When under attack or during heavy traffic, the detection engines need to make fast decision whether a packet or a sequence of packets is normal or malicious. However, if packets have a heavy payload or the system has a great deal of attack patterns, the high cost of payload inspection severely diminishes the detection performance. Therefore, it would be better to avoid unnecessary payload scans by checking the protocol fields in the packet header first, before executing their heavy operations of payload inspection. Furthermore, when payload inspection is necessary, it is better to compare attack patterns as few as possible. In this paper, we propose a method which reduces payload scans by an integration of processing protocol fields and classifying payload signatures. While performance improvements are dependent on a given networking environment, the experimental results with the DARPA data set show that the proposed method outperforms the latest Snort over 6.5% for web traffic.
Speaker Diarization Using Direction of Arrival Estimate and Acoustic Feature Information: The I2R-NTU Submission for the NIST RT 2007 Evaluation
Authors: Eugene Chin Koh, Hanwu Sun, Tin Lay Nwe, Trung Hieu Nguyen, Bin Ma, Eng-Siong Chng, Haizhou Li, Susanto Rahardja
Venue: Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers (2008)

This paper describes the I2R/NTU system submitted for the NIST Rich Transcription 2007 (RT-07) Meeting Recognition evaluation Multiple Distant Microphone (MDM) task. In our system, speaker turn detection and clustering is done using Direction of Arrival (DOA) information. Purification of the resultant speaker clusters is then done by performing GMM modeling on acoustic features. As a final step, non-speech silence removal is done. Our system achieved a competitive overall DER of 15.32% for the NIST Rich Transcription 2007 evaluation task.
A Multi-agent Model for the Micro-to-Macro Linking Derived from a Computational View of the Social Systems Theory by Luhmann
Authors: Vera Lúcia Silva, Maria Graças Bruno Marietto, Carlos H. Ribeiro
Venue: Multi-Agent-Based Simulation VIII: International Workshop, MABS 2007, Honolulu, HI, USA, May 15, 2007, Revised and Invited Papers (2008)

Even though questions related to the micro-macro relationship are fundamentally important for understanding and modeling social systems, important theoretical gaps on this issue continue to exist in the Agent-Based Social Simulation (ABSS) area. To address it we consider a model that explicitly links the micro-level individual communications with the macro-level social phenomena, building up an important formal tool for analyzing social processes and their dynamics in a bottom-up approach. The model lays out a series of key elements from Niklas Luhmann's Systems Theory and concepts from ABSS.
Topology management protocols in ad hoc wireless sensor networks
Authors: Eun Jung Kim
Venue:  (2007)

A wireless sensor network (WSN) is comprised of a few hundred or thousand autonomous sensor nodes spatially distributed over a particular region. Each sensor node is equipped with a wireless communication device, a small microprocessor, and a battery-powered energy source. Typically, the applications of WSNs such as habitat monitoring, fire detection, and military surveillance, require data collection, processing, and transmission among the sensor nodes. Due to their energy constraints and hostile environments, the main challenge in the research of WSN lies in prolonging the lifetime of WSNs. In this dissertation, we present four different topology management protocols for K-coverage and load balancing to prolong the lifetime of WSNs. First, we present a Randomly Ordered Activation and Layering (ROAL) protocol for K-coverage in a stationary WSN. The ROAL suggests a new model of layer coverage that can construct a K-covered WSN using the layer information received from its previously activated nodes in the sensing distance. Second, we enhance the fault tolerance of layer coverage through a Circulation-ROAL (C-ROAL) protocol. Using the layer number, the C-ROAL can activate each node in a round-robin fashion during a predefined period while conserving reconfiguration energy. Next, Mobility Resilient Coverage Control (MRCC) is presented to assure K-coverage in the presence of mobility, in which a more practical and reliable model for K-coverage with nodal mobility is introduced. Finally, we present a Multiple-Connected Dominating Set (MCDS) protocol that can balance the network traffic using an on-demand routing protocol. The MCDS protocol constructs and manages multiple backbone networks, each of which is constructed with a connected dominating set (CDS) to ensure a connected backbone network. We describe each protocol, and compare the performance of our protocols with Dynamic Source Routing (DSR) and/or existing K-coverage algorithms through extensive simulations. The simulation results obtained by the ROAL protocol show that K-coverage can be guaranteed with more than 95% coverage ratio, and significantly extend network lifetime against a given WSN. We also observe that the C-ROAL protocol provides a better reconfiguration method, which consumes only less than 1% of the reconfiguration energy in the ROAL protocol, with a greatly reduced packet latency. The MRCC protocol, considering the mobility, achieves better coverage by 1.4% with 22% fewer active sensors than that of an existing coverage protocol for the mobility. The results on the MCDS protocol show that the energy depletion ratio of nodes is decreased consequently, while the network throughput is improved by 35%.
Tutorial II: high dimensional model representation (HDMR) methods in multivariate interpolation problems
Authors: M. Alper Tunga
Venue: Proceedings of the 7th WSEAS International Conference on Microelectronics, Nanoelectronics, Optoelectronics (2008)

If a multivariate data set is given to specify a multivariate function and it is asked to determine an analytical structure for the sought multivariate function, instead of using standard interpolation methods, given multivariate data can be partitioned into low-variate data and then an analytical structure is determined with the aid of these partitioned data. For this purpose, two different plain HDMR based methods, HDMR and GHDMR (Generalized HDMR) methods can be used. The algorithms for these two methods are based on the Sobol's HDMR expansion including Rabitz's and Demiralp's criteria. Because data partitioning is the main purpose of these methods Dirac delta function structure is used inside these algorithms. When a multivariate function is given by its values at a finite number of nodes of a hyperprismatic regular grid instead of its global analytical structure, HDMR can used to approximately partition this given multivariate data into low-variate data. When data for describing the multivariate function are not given at all nodes of hyperprismatic regular grid GHDMR can be used to partition the randomly chosen multivariate data. As HDMR expansion has an additive nature, to obtain better results in interpolation problems having dominantly or entirely multiplicative nature Factorized High Dimensional Model Representation (FHDMR) can be used. The components of this representation can be obtained with the aid of the HDMR or the GHDMR components of the same function. Hybrid High Dimensional Model Representation (HHDMR) method can be used when the sought function has intermediate nature, that is it has neither a dominantly additive nor a dominantly multiplicative nature. This method uses both HDMR (or GHDMR) expansion and FHDMR product in a single formula under a hybridity parameter.
Avatar Customization and Emotions in MMORPGs
Authors: Shun-An Chung, Jim Jiunde Lee
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

This paper looks at how avatar customization details affect players' emotions in MMORPGs, which aspects they prefer in the environment of creating an avatar.
A SOA-Based Framework to Support User Model Interoperability
Authors: Federica Cena, Roberto Furnari
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

This paper presents an approach to achieve User Model (UM) interoperability exploiting Web Service technologies for syntactic interoperability, and Semantic Web languages for semantic interoperability, together with negotiation techniques based on dialogue. We propose a SOA-based framework where a central UDDI registry, enhanced with UM specific capabilities, is used to support and promote the cooperation between UM-based applications.
Process Improvement in Requirements Management: A Method Engineering Approach
Authors: Sjaak Brinkkemper, Inge Weerd, Motoshi Saeki, Johan Versendaal
Venue: Proceedings of the 14th international conference on Requirements Engineering: Foundation for Software Quality (2008)

Method Engineering and Requirements Engineering are two research fields that can benefit from another. To increase process maturity in systems development, we propose an approach for incremental method evolution that combines capability-based and problem-based methods. With this method, we can assemble new methods, based on the process need of an organization. We show how this approach can be implemented using Computer Aided Method Engineering (CAME) technology. In addition, we demonstrate the utility of the Product Software Knowledge Infrastructure by showing an example of the insertion of cost-value prioritization as a method increment in software product management. This shows how isolated innovations in the Requirements Engineering domain can be embedded in software development practices.
The Role of Anticipation in the Emergence of Language
Authors: Samarth Swarup, Les Gasser
Venue: Anticipatory Behavior in Adaptive Learning Systems: From Brains to Individual and Social Behavior (2007)

We review some of the main theories about how language emerged. We suggest that including the study of the emergence of artificial languages, in simulation settings, allows us to ask a more general question, namely, what are the minimal initial conditions for the emergence of language? This is a very important question from a technological viewpoint, because it is very closely tied to questions of intelligence and autonomy. We identify anticipation as being a key underlying computational principle in the emergence of language. We suggest that this is in fact present implicitly in many of the theories in contention today. Focused simulations that address precise questions are necessary to isolate the roles of the minimal initial conditions for the emergence of language.
Automatic Diagnosis of Foot Plant Pathologies: A Neural Networks Approach
Authors: Marco Mora, Mary Carmen Jarur, Daniel Sbarbaro, Leopoldo Pavesi
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Some foot plant pathologies, like cave and flat foot, are normally detected by a human expert by means of footprint images. Nevertheless, the lack of trained personal to accomplish such massive first screening detection efforts precludes the routinely diagnostic of the above mentioned pathologies. In this work an innovative automatic system for foot plant pathologies based on neural networks (NN) is presented. We propose the use of principal components analysis to reduce the number of inputs to the NN and therefore increasing the efficiency of the training algorithm. The results achieved with this system evidence the feasibility of establishing automatic diagnosis systems based on the footprint image. These systems are of a great value specially in apart areas and are also suited to carry on massive first screening health campaigns.
Registration-Based Segmentation Using the Information Bottleneck Method
Authors: Anton Bardera, Miquel Feixas, Imma Boada, Jaume Rigau, Mateu Sbert
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

We present two new clustering algorithms for medical image segmentation based on the multimodal image registration and the information bottleneck method. In these algorithms, the histogram bins of two registered multimodal 3D-images are clustered by minimizing the loss of mutual information between them. Thus, the clustering of histogram bins is driven by the preservation of the shared information between the images, extracting from each image the structures that are more relevant to the other one. In the first algorithm, we segment only one image at a time, while in the second both images are simultaneously segmented. Experiments show the good behavior of the presented algorithms, especially the simultaneous clustering.
Preventing Collusion Attacks on the One-Way Function Tree (OFT) Scheme
Authors: Xuxin Xu, Lingyu Wang, Amr Youssef, Bo Zhu
Venue: Proceedings of the 5th international conference on Applied Cryptography and Network Security (2007)

The one-way function tree (OFT) scheme proposed by Balenson et al. is widely regarded as an efficient key management solution for multicast communication in large dynamic groups. Following Horng's claim that the original OFT scheme was vulnerable to a collusion attack, Ku et al. studied the collusion attack on OFT and proposed a solution to prevent the attack. The solution, however, requires to broadcast about h 2 + h (h is the height of the key tree) keys for every eviction operation, whereas the original OFT scheme only requires about h keys. This modified OFT scheme thus loses a key advantage that the original OFT has over the logical key hierarchy (LKH) scheme, that is a halving in broadcast size. In this paper, we revisit collusion attacks on the OFT scheme. We generalize the examples of attacks given by Horng and Ku et al. to a generic collusion attack on OFT, and derive necessary and sufficient conditions for such an attack to exist. We then show a solution for preventing collusion attacks while minimizing the average broadcast size. Our simulation results show that the proposed solution allows OFT to outperform LKH in many cases.
Matrics, a Car License Plate Recognition System
Authors: Andrés Marzal, Juan Miguel Vilar, David Llorens, Vicente Palazón, Javier Martín
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

Matrics is a system for recognition of car license plates. It works on standard PC equipment with low-priced capture devices and achieves real-time performance (10 frames per second) with state of the art accuracy: the character error rate is below 1% and the plate error rate is below 3%. The recognition process is divided in two phases: plate localization and plate decoding. The system finds the plate analyzing the connected components of the image after binarization. The decoding algorithm is a Two Level process which uses fast template-based classification techniques in its first stage and optimal segmentation in the second stage. On the whole, the system represents a significant improvement over a previous version which was based on HMM.