Miracle-dz/UniFAR-FTUs huggingface dataset:
Number of clusters in K-Means clustering : an experimental study

The issue of determining “the right number of clusters” in K-Means has attracted considerable interest, especially in the recent years. However, to the authors’ knowledge, no experimental comparison of proposed solutions have been reported so far. This paper presents results of such a comparison involving eight options for determining the right K; these options represent four different approaches to the issue. We generate data according to a version of the Gaussian-mixture distribution with clusters’ spread and spatial sizes variant. Most consistent results in reproduction of the generated partitions and their centroids are shown by an “intelligent” version of K-Means, iK-Means by Mirkin (2005), and the silhouette width based method by Kaufman and Rousseeuw (1990). However, the right K is reproduced best by the Hartigan’s (1975) method. This leads us to propose an adjusted version of iK-Means, which performs well in the current experiment setting.
Pattern Recognition of Biological Signals

This paper presents an evolutionary method for designing electronic circuits and numerical methods associated with monitoring systems. The instruments described here have been used in studies of weather and climate changes due to global warming, and also in medical patient supervision. Genetic Programming systems have been used both for designing circuits and sensors, and also for determining sensor parameters. The authors advance the thesis that the software side of such a system should be written in computer languages with a strong mathematical and logic background in order to prevent software obsolescence, and achieve program correctness. Keywords—Pattern recognition, evolutionary computation, biological signal, functional programming.
The Computation of Transcendental Functions on the IA-64 Architecture

The fast and accurate evaluation of transcendental functions (e.g. exp, log, sin, and atan) is vitally important in many fields of scientific computing. Intel provides a software library of these functions that can be called from both the C and FORTRAN programming languages. By exploiting some of the key features of the IA-64 floatingpoint architecture, we have been able to provide doubleprecision transcendental functions that are highly accurate yet can typically be evaluated in between 50 and 70 clock cycles. In this paper, we discuss some of the design principles and implementation details of these functions.
Ultrahigh-pressure phases of H2O ice predicted using an adaptive genetic algorithm

We propose three new phases of H2O under ultrahigh pressure. Our structural search was performed using an adaptive genetic algorithm which allows an extensive exploration of crystal structure. The new sequence of pressure-induced transitions beyond ice X at 0 K should be ice X! Pbcm ! Pbca ! Pmc21 ! P21 ! P21=c phases. Across the Pmc21-P21 transition, the coordination number of oxygen increases from 4 to 5 with a significant increase of density. All stable crystalline phases have nonmetallic band structures up to 7 TPa.
A Hybrid Single-Carrier/Multicarrier Transmission Scheme with Power Allocation

We propose a flexible transmission scheme which easily allows to switch between cyclic-prefixed single-carrier (CP-SC) and cyclic-prefixed multicarrier (CP-MC) transmissions. This scheme takes advantage of the best characteristic of each scheme, namely, the low peak-to-average power ratio (PAPR) of the CP-SC scheme and the robustness to channel selectivity of the CP-MC scheme. Moreover, we derive the optimum power allocation for the CP-SC transmission considering a zero-forcing (ZF) and a minimum mean-square error (MMSE) receiver. By taking the PAPR into account, we are able to make a better analysis of the overall system and the results show the advantage of the CP-SC-MMSE scheme for flat and mild selective channels due to their low PAPR and that the CP-MC scheme is more advantageous for a narrow range of channels with severe selectivity.
Interactional Metadiscourse in the Writings of Novice vs. Established Members of Academic Communities

Novice academic writers, particularly Iranian graduate students (IGSs), upon entering an academic community, are hypothesized to face probable difficulties in practicing rhetorical expectations set by the experienced (EXP) members, hence, not being able to write in a way acceptable to these professionals. To explore the probable rhetorical distance between them, this study investigated the employment of interactional metadiscourse markers (IMMs) in the writings of IGSs (MA and Ph.D.) and EXP figures in Applied Linguistics. 120 recent research articles (RAs) served as the corpus of the study. Drawing on Hyland’s (2005) model of metadiscourse, all occurrences of the five types of IMMs were functionally identified, and compared. To detect any possible significant differences between the corpora, Chi-square tests were run. The results indicated that the IGSs used far less IMMs than the EXP ones in their RAs. However, the general pattern of their metadiscourse use was similar to the EXP writers’. It can be concluded that although the IGSs are relatively aware of general rhetorical framework of the genre based on IMMs, they seem to be far away from the rhetorical standards set by the established members of the discipline. Finally, the possible justifications and implications of the study were presented.
Monocular model-based 3D vehicle tracking for autonomous vehicles in unstructured environment

In this paper we describe a novel approach to model-based monocular vehicle tracking out of a moving vehicle using active vision. The designed algorithm can cope with cluttered color images, complex lighting conditions as well as partial occlusion of the leading vehicle and is able to detect and track a vehicle even within unstructured offroad environments. Thanks to the used 3D model which describes the characteristic vehicle geometry and appearance in terms of vertexes, edges and colored surfaces, no special visual markers are required. The knowledge of vehicle's geometry and appearance gained from the model are used within a particle filter to estimate the 6DoF position relative to the ego vehicle, thereby fusing edge as well as color information. We successfully use the proposed algorithm for pure vision based autonomous offroad convoy driving.
Asymptotic Formulas for Determinants of a Sum of Finite Toeplitz and Hankel Matrices

The purpose of this paper is to describe asymptotic formulas for determinants of a sum of finite Toeplitz and Hankel matrices with singular generating functions. The formulas are similar to those of the analogous problem for finite Toeplitz matrices for a certain class of symbols. However, the appearance of the Hankel matrices changes the nature of the asymptotics in some instances depending on the location of the singularities. Several concrete examples are also described in the paper.
The Search for Provably Secure Identification Schemes

1. Introduction. An identification scheme is a protocol which enables party A to prove his identity to party B in the presence of imposters G. This is one of the fundamental problems in cryptography, and it has numerous practical applications. In fact, whenever we present a driver's license, use a passport, pay with a credit card, enter a computer password, or punch a secret code into an automatic teller machine, we execute an identification protocol. The basic problem with these practical protocols is that A proves his identity by revealing to B a constant (in the form of a printed card or a memorized value). A sophisticated adversary C who cooperates with a dishonest B can use a xerox copy of the card or a recording of the secret value to misrepresent himself successfully as A at a later stage. Our goal in this paper is to survey some of the mathematical techniques developed to solve this problem, and to propose a new identification scheme which is provably secure if factoring is difficult, and orders of magnitude faster than previous schemes of this type. The mathematical version of the identification problem assumes that A is distinguished by knowing some secret information s which no one else knows. A's goal is to prove to B that he knows s, and 5's goal is to verify the correctness of A's proof. B is assisted by the public information v revealed in advance by A. Since v is also available to G, there should be no efficient algorithm for computing s from v, even though the two values are obviously related. The authenticity of v is guaranteed by publishing it in a public key directory or by attaching to it the digital signature of a trusted center, and thus we do not consider attacks in which G replaces J4'S real v by a modified v f .
Content-based image retrieval: color and edges

One of the tools that will be essential for future electronic publishing is a powerful image retrieval system. The author should be able to search an image database for images that convey the desired information or mood; a reader should be able to search a corpus of published work for images that are relevant to his or her needs. Most commercial image retrieval systems associate keywords or text with each image and require the user to enter a keyword or textual description of the desired image. This text-based approach has numerous drawbacks -- associating keywords or text with each image is a tedious task; some image features may not be mentioned in the textual description; some features are ``nearly impossible to describe with text''''; and some features can be described in widely different ways [Niblack, 1993]. In an effort to overcome these problems and improve retrieval performance, researchers have focused more and more on content-based image retrieval in which retrieval is accomplished by comparing image features directly rather than textual descriptions of the image features. Features that are commonly used in content-based retrieval include color, shape, texture and edges. In this report we describe a simple content-based system that retrieves color images on the basis of their color distributions and edge characteristics. The system uses two retrieval techniques that have been described in the literature -- i.e. histogram intersection to compare color distributions and sketch comparison to compare edge characteristics. The performance of the system is evaluated and various extensions to the existing techniques are proposed.
The Design of a Tangible User Interface for a Real-Time Strategy Game

Tangible User Interfaces (TUIs) allow interaction with computer applications using physical objects called tangibles. TUIs have a number of latent advantages over traditional user interfaces including spatial naturalness and immediate haptic feedback where users receive both tactile and digital responses from computer systems. This paper presents the preliminary design and test results of a tabletop Tangible User Interface for a real-time strategy game. A preliminary assessment of the TUI prototype was conducted by comparison with a Graphical User Interface (GUI) version of the same real-time strategy game. The results showed that users performed better with the GUI and found it easier to use, but reported more interest and greater enjoyment when using the TUI. However, preferences were split evenly between the two interface types. Based on this initial evaluation, suggestions are made for improving the TUI design and potential future research is identified.
Querying sequential software engineering data

We propose a pattern-based approach to effectively and efficiently analyzing sequential software engineering (SE) data. Different from other types of SE data, sequential SE data preserves unique temporal properties, which cannot be easily analyzed without much programming effort. In order to facilitate the analysis of sequential SE data, we design a sequential pattern query language (SPQL), which specifies the temporal properties based on regular expressions, and is enhanced with variables and statements to store and manipulate matching states. We also propose a query engine to effectively process the SPQL queries. We have applied our approach to analyze two types of SE data, namely bug report history and source code change history. We experiment with 181,213 Eclipse bug reports and 323,989 code revisions of Android. SPQL enables us to explore interesting temporal properties underneath these sequential data with a few lines of query code and low matching overhead. The analysis results can help better under- stand a software process and identify process violations.
A Big data analytical framework for portfolio optimization

With the advent of Web 2.0, various types of data are being produced every day. This has led to the revolution of big data. Huge amount of structured and unstructured data are produced in financial markets. Processing these data could help an investor to make an informed investment decision. In this paper, a framework has been developed to incorporate both structured and unstructured data for portfolio optimization. Portfolio optimization consists of three processes: Asset selection, Asset weighting and Asset management. This framework proposes to achieve the first two processes using a 5-stage methodology. The stages include shortlisting stocks using Data Envelopment Analysis (DEA), incorporation of the qualitative factors using text mining, stock clustering, stock ranking and optimizing the portfolio using heuristics. This framework would help the investors to select appropriate assets to make portfolio, invest in them to minimize the risk and maximize the return and monitor their performance.
Integrating the CSCL Activities into Virtual Campuses: Foundations of a new Infrastructure for Distributed Collective Activities

The integration of CSCL tools inside larger platforms like Virtual Campuses is often impossible. To overcome this problem, our general assumption is that they need a common theoretical framework for their design. In this context and turning our interest into the Activity Theory, we aim at providing new systems foundations supporting large varieties of learning modes, trying to capture the contributions of the human sciences. This has been concretised in the DARE system. DARE supports the coconstructive, expansive and experience crystallization properties of human activity. It introduces a meta-level architecture supporting Distributed Collective Activities and featuring a generic activitysupport model, its meta-model, a component approach, and a distributed architecture. This provides a distributed environment where the supports for learning activities and their associated meta-activities are cohabiting, thus aiming at facilitating the development of meta-cognitive skills.
The Teacher Self-Efficacy Scale (TSES) Factorial Structure Evidence Review and New Evidence From Polish-Speaking Samples

Abstract. The Teacher Self-Efficacy Scale (TSES) is a widely accepted and enthusiastically used measurement instrument. Unfortunately, little firm evidence is available to support its factorial structure. The article reports on the results of the TSES administered to large representative samples of primary (2,083) and lower-secondary school teachers (2,382) in Poland, along with the results of reanalyzed US data, based on which the scale was developed. The results support TSES as a reliable instrument applicable across countries. However, they also highlight the importance of analyzing the factorial structure of the scale with each application, as it may require modifications when administered to different samples. Additionally, moderate evidence was found in Polish data for TSES to be invariant between primary and lower-secondary school teachers.
Constraint-Based Routing in Traffic Engineering

Traffic engineering (TE) describes a domain-wide perspective for traffic control as opposed to application-specific concerns of QoS. MPLS is today's most powerful architecture for TE. Constraint-based routing refers to the process of path assignment to flows to fulfill the TE objective which has been defined in a number of multi-constraint ways, and is the most significant component of TE. In this paper, we review constraint-based routing algorithms. We first provide an overview of MPLS/TE and place constraint-based routing within this approach. We then look into the potential path attributes and the underlying platform to characterize these algorithms before we present our review. Our study provides a comprehensive reference to the operational structure and specifications of constraint-based routing algorithms
Identifying individuals using ECG beats

In this paper, we propose a technique to identify individuals using features extracted from QRS segment of electrocardiogram (ECG) signals. A total of 2000 samples from 10 subjects from the Arrhythmia Laboratory at Boston's Beth Israel Hospital (now the Beth Israel Deaconess Medical Center) database were used. These data are available as MIT-BH Normal Sinus Rhythm database and consist of 18 hour long-term recordings with 2 ECG signals. The commonly used features like R-R interval, R amplitude, QRS interval, QR amplitude and RS amplitude were used. In addition to these features, we propose the use of form factor of the QRS segment. Form factor has been used previously in electroencephalogram analysis and it is a measure of the complexity of the signal. These six features were then used by two neural network classifiers: multilayer perceptron-backpropagation (MLP-BP) and simplified fuzzy ARTMAP (SFA). The data were split equally for MLP-BP and SFA training and testing. The results gave classification performance up to 97.6%. This indicates that ECG has the potential to be used as a biometric tool.
How Can Agents Know What to Assume When?

The work in this paper is motivated from the need for assumption-based reasoning in normative systems, where, realistically, agents will have incomplete knowledge about their environment, and about other agents. The question we seek to address is whether it is possible for agents to identify appropriate assumptions dynamically, in order to fill in informational gaps. We discuss and illustrate our proposal with reference to an e-commerce example. In our previous work, we argued that e-contracts could be represented as Default Theories and proposed a theoretical way in which such theories could be constructed automatically from initial Event Calculus representations. That proposal relied on determining what information could be proved from the agentpsilas knowledge base, in order to decide whether it would serve as an assumption or not. In this paper we present an incremental technique that can be used for this construction that enables the dynamic and ad hoc identification of candidate assumptions, without resorting to proof.
Controlling bots in a First Person Shooter game using genetic algorithms

In this paper we employ a steady state genetic algorithm to evolve different types of behaviour for bots in the Unreal Tournament 2004™ computer game. For this purpose we define three fitness functions which are based on the number of enemies killed, the lifespan of the bot and a combination of both. Long run experiments were carried out, in which the evolved bots' behaviours outperform those of standard bots supplied by the game, particularly in those cases where the fitness involves a measure of the bot's lifespan. Also, there is an increase in the number of items collected, and the behaviours tend to become less aggressive, tending instead towards a more optimised combat style. Further “short run” experiments were carried out with a further type of fitness function defined, based on the number of items picked. In these cases the bots evolve performances towards the goal they have been aimed, with no other behaviours arising, except in the case of the multiple objective one. We conclude that in order to evolve interesting behaviours more complex fitness functions are needed, and not necessarily ones that directly include the goal we are aiming for.
Evaluation of Association Between Q192R and L55M Genetic Polymorphisms of PON1 and Serum Paraoxonase-1 Activity in Healthy Individuals, a Meta-Analysis

Abstract Background and Aims: Several studies have reported the alteration of the paraoxonase 1 (PON1) enzyme activity in various diseases, including diabetes mellitus. The Q192R and L55M are two genetic variations in the coding region of PON1. To evaluate the relationship between these polymorphisms and the alteration in serum paraoxonase activity, the present meta-analysis was carried out. Material and Methods: Eligible studies published before October 2017 was identified in several databases. The paraoxonase activity in subjects with variant alleles of the study polymorphisms were normalized using the activity of the QQ or LL genotypes. The pooled mean effect of alterations in activity level and its 95% confidence intervals (95% CI) was calculated. Results: Thirty-two studies including 11532 healthy participants were used for the present meta-analysis. The paraoxonase activity was increased in the QR and RR genotypes. This elevation was greater among Caucasians than those among Asians and Africans. The activity in the LM and MM genotypes compared with the LL genotype were decreased, this reduction in Caucasians was greater than Africans. Conclusions: At least in part other PON1 polymorphisms and environmental factors may accounts for heterogeneity between studies.
Best Practices for Component-Based Development and Model-Driven Architecture Version 1 . 0 28 August 2003

Although component-based development provides the concepts and mechanisms to manage complexity in large software development efforts, most teams in practice still have to come to grips with the basics. Inexperienced teams perceive the introduction of additional interfaces and rigorously enforced subsystem boundaries as avoidable overhead. Especially when a system started out small, and initially a less rigorous approach to system design seemed to work, resistance to change is to be expected. A model-driven approach to component specification and generative techniques can help to simplify the process for component-based development, and at the same time can enforce standardised implementation of design patterns and ensure adherence to architectural guidelines. This paper summarises lessons from several projects where a model-driven approach and component based development was implemented to address productivity problems. The important issues are surprisingly non-technical and require paying careful attention to team structure and project organisation.
Radiative transfer calculations for a passive microwave satellite sensor : comparing a fast model and a line-by-line model

[1] A comparison between the fast radiative transfer model Radiative Transfer for the TIROS Operational Vertical Sounder (RTTOV-7) and the physical radiative transfer model Atmospheric Radiative Transfer Simulator (ARTS) was carried out. Radiances were simulated for the sounding channels of the Advanced Microwave Sounding Unit B (AMSU-B) for the whole globe for a single time of a single day (1 January 2000, 0000 UT). Temperature, pressure, and specific humidity profiles from the reanalysis data set ERA-40 of the European Centre for Medium-Range Weather Forecasts (ECMWF) were used as input for both models; geopotential height profiles were also used but only as input for ARTS. The simulations were made for two different surface emissivities, 0.60 and 0.95. The low surface emissivity case exhibits the larger radiance differences. Although the global values of the mean difference and standard deviation are small (for example, the global mean difference for channel 18 is 0.014 K and the standard deviation is 0.232 K), the examination of the geographical distribution of the differences shows that large positive or negative values are observed over dry regions of high northern and southern latitudes and over dry elevated regions. The origin of these differences was found to be due to errors introduced by the transmittance parametrization used in RTTOV.