ppxscal/embedding_network huggingface dataset:
DR-TCP: Downloadable and reconfigurable TCP
Authors: Jae-Hyun Hwang, Jin-Hee Choi, Se-Won Kim, Chuck Yoo
Venue: Journal of Systems and Software (2008)

Advances in communication technology allow a variety of new network environments and services available very rapidly. Appearance of various network environments tends to enable a user with a mobile terminal to access among different network simultaneously. However, since new network environment affects performance of communication protocols, terminal systems should provide adaptation schemes for the protocols in order to keep the quality of network performance high. A possible solution is to make the protocol reconfigurable to be adapted to current network environment. Unfortunately, because most existing network systems are implemented monolithically, they cannot support protocol reconfiguration dynamically at runtime. This paper proposes a new reconfigurable model that enables TCP functions to be adapted whenever network environment is changed. The proposed scheme also supports binary-level protocol upgrade for extensibility by downloading new TCP variants which the terminal does not have for new network environment, and it is more suitable for mobile hand-held devices than existing source-level solution. Our model is based on a recursive state machine. We re-implement TCP Reno from scratch using our proposed model. The new implementation of TCP Reno is named DR-TCP. To demonstrate the effectiveness of DR-TCP, dynamic reconfiguration is performed over Internet, which successfully converts DR-TCP to TCP Westwood at runtime.
Classification method using fuzzy level set subgrouping
Authors: Paavo Kukkurainen, Pasi Luukka
Venue: Expert Systems with Applications: An International Journal (2008)

We present a new classification system which is based on fuzzy level sets subgrouping. This new classification system allows a fast classification method with quite accurate results. Classification runs were carried out with four different data sets. All four data sets were related to medical diagnostics. Data sets were related to thyroid and diabetes diagnostics, echocardiogram data relates to predicting patients chances of survival after acute heart attack. With lymphography data there are four classes to predict, normal find, metastases, malign lymph and fibrosis, from the existing data. Classification results are compared to some existing results in the literature and the results seem to compare well.
Understanding user behavior with new mobile applications
Authors: Raquel Benbunan-Fich, Alberto Benbunan
Venue: The Journal of Strategic Information Systems (2007)

This paper presents the results of an exploratory study designed to evaluate Microediciones^(R), a new mobile content-based application that delivers daily summaries of newspapers into cell phones. The research question underlying this study sought to understand how users, accustomed to using their handsets as talking devices, download applications and navigate through data. This question is explored from the theoretical perspective of automaticity with data collected via protocol analysis of a sample of subjects. An analysis of the problems experienced by the users provided the basis to suggest specific operational improvements to the application, bearing in mind the strategic objectives of the mobile company to obtain revenue from user subscriptions and advertising. Beyond the strategic implications for the company launching this particular service, the results of this study have significant theoretical and practical implications for researchers and developers of new mobile applications.
Improving the lazy Krivine machine
Authors: Daniel P. Friedman, Abdulaziz Ghuloum, Jeremy G. Siek, Onnie Lynn Winebarger
Venue: Higher-Order and Symbolic Computation (2007)

Krivine presents the $\mathcal {K}$ machine, which produces weak head normal form results. Sestoft introduces several call-by-need variants of the ${\mathcal {K}}$ machine that implement result sharing via pushing update markers on the stack in a way similar to the TIM and the STG machine. When a sequence of consecutive markers appears on the stack, all but the first cause redundant updates. Improvements related to these sequences have dealt with either the consumption of the markers or the removal of the markers once they appear. Here we present an improvement that eliminates the production of marker sequences of length greater than one. This improvement results in the ${\mathcal {C}}$ machine, a more space and time efficient variant of ${\mathcal {K}}$ . We then apply the classic optimization of short-circuiting operand variable dereferences to create the call-by-need ${\mathcal {S}}$ machine. Finally, we combine the two improvements in the ${\mathcal {CS}}$ machine. On our benchmarks this machine uses half the stack space, performs one quarter as many updates, and executes between 27% faster and 17% slower than our ¿ variant of Sestoft's lazy Krivine machine. More interesting is that on one benchmark ¿, ${\mathcal {S}}$ , and ${\mathcal {C}}$ consume unbounded space, but ${\mathcal {CS}}$ consumes constant space. Our comparisons to Sestoft's Mark 2 machine are not exact, however, since we restrict ourselves to unpreprocessed closed lambda terms. Our variant of his machine does no environment trimming, conversion to deBruijn-style variable access, and does not provide basic constants, data type constructors, or the recursive let. (The Y combinator is used instead.)
Varying-coefficient single-index model
Authors: Heung Wong, Wai-cheung Ip, Riquan Zhang
Venue: Computational Statistics Data Analysis (2008)

In this paper, the varying-coefficient single-index model (VCSIM) is proposed. It can be seen as a generalization of the semivarying-coefficient model by changing its constant coefficient part to a nonparametric component, or a generalization of the partially linear single-index model by replacing the constant coefficients of its linear part with varying coefficients. Based on the local linear method, average method and backfitting technique, the estimates of the unknown parameters and the unknown functions of the VCSIM are obtained and their asymptotic distributions are derived. Both simulated and real data examples are given to illustrate the model and the proposed estimation methodology.
A Modified PSVM and its Application to Unbalanced Data Classification
Authors: Xiao-yan Tao, Hong-bing Ji, Yu-xin Xie
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

A modified proximal support vector machine (MPSVM) is presented for the case of unbalanced data classification in many applications. The algorithm assigns different penalty coefficients to the positive and negative samples respectively by adding a new diagonal matrix in the primal optimization problem. And further the decision function is obtained. In addition, the real-coded immune clone algorithm (RICA) is employed to select the global optimal parameters to get the high generalization performance. The experimental results illustrate the effectiveness of the proposed method.
3d augmented mirror: a multimodal interface for string instrument learning and teaching with gesture support
Authors: Kia C. Ng, Tillman Weyde, Oliver Larkin, Kerstin Neubarth, Thijs Koerselman, Bee Ong
Venue: Proceedings of the 9th international conference on Multimodal interfaces (2007)

Multimodal interfaces can open up new possibilities for music education, where the traditional model of teaching is based predominantly on verbal feedback. This paper explores the development and use of multimodal interfaces in novel tools to support music practice training. The design of multimodal interfaces for music education presents a challenge in several respects. One is the integration of multimodal technology into the music learning process. The other is the technological development, where we present a solution that aims to support string practice training with visual and auditory feedback. Building on the traditional function of a physical mirror as a teaching aid, we describe the concept and development of an "augmented mirror" using 3D motion capture technology.
Guest Editors' Introduction: Dynamically Typed Languages
Authors: Laurence Tratt, Roel Wuyts
Venue: IEEE Software (2007)

The languages discussed in this special issue have a long history, which is perhaps why some have had several different names over the years. One such language is Lisp, the second-oldest programming language. For years, many somewhat dismissively described languages such as Lisp as "scripting languages." Today, we more commonly refer to them as dynamically typed languages, typified by Python and Ruby, and their impact is arguably greater than ever. This issue highlights the practical uses of such languages and shows how they're frequently a vehicle for innovation in the development sphere. This article is part of a special issue on dynamically typed languages.
Web- based direct instruction in mathematics for low achievers
Authors: M. Graff, M. Lebens
Venue: Proceedings of the sixth conference on IASTED International Conference Web-Based Education - Volume 2 (2007)

EFit is the first web based tutoring system for lower secondary school mathematics in Germany. It generates a systematic learning schedule to meet the individual demands of different students. In contrast to the more traditional Computer Assisted Instruction programs, the web-based eFit program is characterized by a high degree of adaptability. Given that no comparable programme currently exists in Germany, it is worth evaluating the usefulness of eFit for the target group, namely low achieving students. The study was carried out in North Rhine Westphalia (NRW), where the mathematics curricula tend to de-emphasize direct or explicit instruction in favour of open ended, exploratory methods, which can be characterised as constructivist. However, the present paper argues that the constructivist-inspired reform pedagogy does not serve the needs of all target groups and has adverse effects for low achievers. On the other hand, there is abundant evidence that direct instruction leads to significant learning gains for low achievers. This was confirmed in the present research: where students in the treatment group improved significantly compared to students who received traditional, constructivist-inspired instruction. The implications of the findings for web-based instruction of this kind are considered.
Polymorphic malware detection and identification via context-free grammar homomorphism
Authors: Gerald R. Thompson, Lori A. Flynn
Venue: Bell Labs Technical Journal (2007)

Computer viruses continue to proliferate despite the use of virus detection systems (VDS). This is due to VDS inability to detect variants not represented in signature databases. Detection systems look for contiguous byte sequences, use regular expressions for noncontiguous sequences, or detect initial behavior within a sandbox. Recent research has focused on using control-flow graph isomorphism in detection. These techniques are ineffective at detecting some polymorphs, which change their byte sequences and initial behavior and produce nonisomorphic control-flow graphs. Our approach compares program hierarchical structure. We observed that polymorphic instances are variants of the same program, these variants use the same algorithm, and a program's algorithm determines its hierarchical structure. Our technique maps a program's hierarchical structure to a context-free grammar, normalizes the grammar, and uses a fast check for homomorphism between the normalized grammars. &copy; 2007 Alcatel-Lucent.
A Nationwide Program for Software Process Improvement in Brazil
Authors: Ana Regina Cavalcanti da Rocha, Mariano Montoni, Kival Chaves Weber, Ertostenes Edson Ramalho de Araujo
Venue: Proceedings of the 6th International Conference on Quality of Information and Communications Technology (2007)

Continuous improvement of software development capability is fundamental for organizations to thrive in competitive markets. Nevertheless, Software Process Improvement (SPI) implementation based on software process reference models and standards is a complex and long-term endeavor that requires investment of large sums of money. This paper describes a national program for SPI in Brazilian organizations. The main goal of this initiative is to develop and disseminate a Brazilian software process model (named MPS Model) aiming to establish a feasible pathway for organizations to achieve benefits from implementing SPI at reasonable costs, especially SMEs. This paper presents the main components of MPS Model. The results of MPS Model adoption and dissemination in Brazilian software industry are also presented in this paper. Although the main focus of the MPS Model is on SMEs, the model demonstrated to be adequate to support SPI implementation and assessment in large organizations.
Understanding Web 2.0
Authors: San Murugesan
Venue: IT Professional (2007)

Despite its promise to transform how we use the Web, many IT professionals and businesses remain skeptical about Web 2.0's value.
An Attitude-adaptation Negotiation Strategy in Electronic Market Environments
Authors: Shujuan Ji, Yongquan Liang, Xingpeng Xiao, Jixue Li, Qijia Tian
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

The automatization of electronic commerce negotiation has become the focus of more and more attention. As one of the core of automated negotiation, strategy is the method employed by agents to maximize their own benefits. The design of negotiation strategy is affected by lots of factors, such as negotiation deadline, the type of resources, the characteristics of opponents, the numbers of competitors, etc. Though lots of work have been done on negotiation strategy, there still lack a uniform strategy framework. In this paper, a general description framework for multi-agent negotiation is proposed. Then solutions to the decision models are given and the existence of the Nash equilibrium in agents' attitude selection at the beginning of negotiations is analyzed. To enable agents to adapt their attitudes according to negotiation duration, the supply and demand ratio, and the characteristics of opponent, we introduce an adaptation function. This function is constructed on the basis of a history-based learning algorithm. Furthermore, the attitude-adaptation strategy and the fixed-attitude strategies are compared by simulation.
Poisson Representation of a Ewens Fragmentation Process
Authors: Alexander Gnedin, Jim Pitman
Venue: Combinatorics, Probability and Computing (2007)

A simple explicit construction is provided of a partition-valued fragmentation process whose distribution on partitions of [n] = 1,. . .,n at time θ ≥ 0 is governed by the Ewens sampling formula with parameter θ. These partition-valued processes are exchangeable and consistent, as n varies. They can be derived by uniform sampling from a corresponding mass fragmentation process defined by cutting a unit interval at the points of a Poisson process with intensity θx−1dx on/mathbbR+, arranged to beintensifying as θ increases.
Human-level artificial general intelligence and the possibility of a technological singularity
Authors: Ben Goertzel
Venue: Artificial Intelligence (2007)

An analysis of Ray Kurzweil's recent book The Singularity Is Near is given, along with Drew McDermott's recent critique. The conclusion is that Kurzweil does an excellent job of fleshing out one particular plausible scenario regarding the future of AI, in which human-level AI first arrives via human-brain emulation. McDermott's arguments against the notion of Singularity via iteratively self-improving AI, as described by Kurzweil, are considered and found wanting. However, it is pointed out that the scenario focused on by Kurzweil is not the only plausible one; and an alternative is discussed, in which human-level AI arrives first via non-human-like AI's operating virtual worlds.
A Security Model for Detecting Suspicious Patterns in Physical Environment
Authors: Simon Fong, Zhuang Yan
Venue: Proceedings of the Third International Symposium on Information Assurance and Security (2007)

In the view of escalating global threat in security, it is imperative to have an automated detection system that can pick up suspicious patterns of human movement in physical environments. It can give a forewarning before a planned attack happens or an ultimate security is breached. In the past, significant research on the Intrusion Detection was established, but limited to virtual environments like computer networks and operating systems. In this paper, we proposed a general security model for detecting suspicious patterns in physical environment. Suspicious patterns are subtle and we showed that they can be detected via an experiment.
An SEI Process Improvement Path to Software Quality
Authors: Philip Miller
Venue: Proceedings of the 6th International Conference on Quality of Information and Communications Technology (2007)

Software quality is growing in importance: we are increasingly dependent on software for everything from transportation to public safety. The Carnegie Mellon® Software Engineering Institute has pioneered excellent methods for software process improvement, namely its Capability Maturity Model Integration (CMMI®) and Team Software ProcessSM (TSP^SM). This paper provides a brief overview of software quality and its history, a short treatment of CMMI, and an introduction to the TSP^SM, the SEI's "how to" guide to achieving process maturity. Empirical results are presented.
Prediction of R in Sinter Process based on Grey Neural Network Algebra
Authors: Wang Ai-min, Song Qiang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

grey neural network model was proposed on the basis of the models.The fluctuation of data sequence is weakened by the grey theory and the neural network is capable of processing non-linear adaptable information, and the GNN is a combination of those advantages. The results reveal, the alkalinity of sinter can be accurately predicted through this model by reference to small sample and information. It was concluded that the GNN model is effective with the advantages of high precision, less requirement of samples and comparatively simple calculation.
Image Analysis of Grains from A Falling Stream
Authors: Weixing Wang
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

As a engineering requirements we initiated a study using an on-line computer system to analyse grains in a gravitational flow, i.e. a falling stream of particles. Compared with images from a moving conveyor belt, in gravity flow both grains and background appears more and less afflicted by overlaps. This, apart from alleviating the problems of overlapping, implies that the size and shape of grains can be measured more accurately, but one problem is how to resolve blurring. To improve the machine efficiency of the particle detection and classification system, the samples must be examined dynamically. The dynamic detection leads to an unavoidable result of image motion blur, which greatly degrades the quality of the image. So we build up the mathematics model of motion-blurred image, estimating Point Spread Function, introduce a high speed and efficient way to solute this problem and restore the blurred image.
Reliable data collection in highly disconnected environments using mobile phones
Authors: Brian DeRenzi, Yaw Anokwa, Tapan Parikh, Gaetano Borriello
Venue: Proceedings of the 2007 workshop on Networked systems for developing regions (2007)

Over four and a half billion people live in the developing world and require access to services in the financial, agricultural, business, government and healthcare sectors. Due to constraints of the existing infrastructure (power, communications, etc), it is often difficult to deliver these services to remote areas in a timely and efficient manner. The CAM framework has found success as a flexible platform for quickly developing and deploying high-impact applications for these environments. Many of the applications built with CAM have relied on a model where a field worker with a mobile phone regularly returns from a disconnected environment to one with connectivity. In this connected state, the phone and a centralized server can exchange information and get the collected data backed up on reliable media. We propose extending CAM's networking model to enable continual operation in disconnected environments. Using a set of heterogeneous paths made available through social and geographic relationships naturally present among workers, we describe a system for asynchronously routing data in a best-effort manner.
Evaluating Energy Consumption in Wireless Sensor Networks Applications
Authors: Agustin Barberis, Leonardo Barboni, Maurizio Valle
Venue: Proceedings of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools (2007)

Wireless sensor networks (WSNs) simulation is essential for the development and optimization of such kind of networks. In this paper we present modifications made to Prowler, a WSNs simulator, making its MAC protocol model compliant with the Crossbow MICAz mote running on TinyOS. Moreover, we added radio propagation models to the simulator and, most important, we implemented an energy consumption estimation model of the CC2420 radio chip. Then, the simulator is addressed to the development of WSNs applications with a particular emphasis on energy consumption optimization (and consequently battery lifetime). We present as case study the comparison between simulated results of two different physical deployments, showing how real operating conditions can affect and modify the system behavior in comparison with the results predicted by theoretical analysis.
Analysis of Time Series via their Linguistic Summarization: the Use of the Sugeno Integral
Authors: Janusz Kacprzyk, Anna Wilbik, Slawomir Zadrozny
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

We propose here some new types of linguistic summaries of time series by extending our previous works. First, the linguistic summaries of time series refer to the summaries of (partial) trends identified here with straight line segments of a piece-wise linear approximation of a time series that is proposed in the paper. To characterize the trends we use the slope of the line segment, the goodness of approxima- tion and the length of the trend. A linguistic summary of a time series is then derived by a linguistic quantifier driven aggregation of trends that is performed using the Sugeno in- tegral. We show an application to the absolute performance type analysis of time series data on daily quotations of an investment fund over an eight year period. The results are very promising.
Visualization and analysis of large graphs
Authors: Eloïse Loubier, Wahiba Bahsoun, Bernard Dousset
Venue: Proceedings of the ACM first Ph.D. workshop in CIKM (2007)

In Knowledge engineering, synthesized information has often an evolving and relational form. Information representation using graphs may ease data interpretation for non-expert users. However this graph may be complex and simplifications are useful in order to ease analysis. In this article, we present VisuGraph, a powerful tool for graph drawing. This tool gives the possibility to reduce large graph by two techniques: the Markov CLustering algorithm (MCL) application and the global graph division in time-sliced visualizations in order to specify and to simplify temporal analysis.