Miracle-dz/UniFAR-FTUs huggingface dataset:
A Formal Framework of Hybrid Test Cases Generation Applied to Embedded Systems

In this paper, we describe a formal framework for confor- mance testing of continuous and hybrid systems, using the international standard 'Formal Methods in Conformance Testing' FMCT. We propose a novel test coverage measure for these systems, which is defined using the star discrepancy notion. This coverage measure is used to quantify the validation 'completeness'. It is also used to guide input stimulus generation by identifying the portions of the system behaviors that are not adequately examined. We then propose a test generation method, which is based on a robotic motion planning algorithm and is guided by the coverage measure. The approach is illustrated by its application to some embedded system benchmarks. nature of the state space encourages more semantic notions of coverage, namely that all system trajectories generated by the input test patterns form a kind of dense network in the reachable state space without too many big unexplored 'holes'. In this work we adopt a model-based testing approach 1 . This approach allows the engineer to perform validation during the design, where detecting and correcting errors on a model are less expensive than on an implementation. The main contri- butions of the paper can be summarized as follows. We define a formal framework for conformance testing of continuous and hybrid systems, using the international standard for formal conformance testing FMCT (24). We propose a test coverage measure for these systems, which is defined using the star discrepancy notion from statistics. This coverage measure is used to quantify the validation 'completeness'. It is also used to guide input stimulus generation by identifying the portions of the system behaviors that are not adequately examined. We propose an algorithm for generating tests from hybrid automata. This algorithm is based on the RRT (Rapidly- exploring Random Tree) algorithm (18) from robotic motion planning and guided by the coverage measure. The rest of the paper is organized as follows. We first de- scribe our conformance testing framework and our test coverage measure.We then present the test generation algorithm and show how to use the coverage measure to guide the test generation process. We also prove the completeness property of the algorithm. Finally, we describe some experimental results. Before concluding, we discuss related work.
Study on Distribution Center Locating Using the Combination Method of CGM and DP

Firstly the distribution centers locating and its study progress are introduced, and then drawbacks of the static model locating method are discussed and summarized. The initial conclusion is drawn from single-facility locating method-center-of-gravity method (CGM) as the static model locating method. Combining with the dynamic programming (DP) method, the dynamic optimal distribution center locating is then found through calculating and adjusting the demand based on the forecasted profit. The advantage of this combination method is to maximize the cumulative current value of total profit in scheduled time by relocating to other alternative sites. Finally, this combination of algorithm method is applied to analyze one specific case.
Evolving structure - optimising content

The paper describes the initial results of a new form of evolutionary system specifically designed for time series modeling. The system combines a grammatically-based genetic programming system with various optimisation techniques. The system uses the evolutionary system to construct the structure of equations and optimisation techniques to essentially fill in the details. Three forms of optimisation are described: optimisation of constants in an equation; the optimisation of both the constants and variables in an equation; and the use of a hill-climbing mutation to further tune the evolved and optimised equations. Preliminary results indicate that this combination of techniques produces significant improvements in convergence based on the training data, and produces equivalent generalisation on unseen data, for a given number of population member evaluations.
Towards Information Visualization in Cooperative , Evolutionary Knowledge Spaces

Contemporary knowledge management activities in an enterprise suffer from the discrepancy between the global benefit for the organization and the personal benefit for the individual knowledge worker. To ameliorate this divergence we investigate an evolutionary approach which automatically integrates the structures of individual knowledge workspaces into comprehensive organizational knowledge structures. To enable the individual user to keep an overview over both the personal information space and the various views and structures in the organization, we present a concept for dynamically-configured visualization of multi-layered concept spaces and information structures. This approach will be realized in the newly-started research project EPOS.
Binmaps : hybridizing bitmaps and binary trees

This paper addresses the classical problem of keeping huge bitmaps predominantly consisting of long ranges of zeros and ones. The problem is most often encountered in filesystems (free space tracking) and network protocols (transmission progress tracking). Three classical solutions to the problem are plain bitmaps (NTFS), extent lists (TCP SACK) and extent binary trees (XFS, Btrfs). Bitmaps are simple but have high fixed space requirements. Lists are able to aggregate solid ranges, but they don’t scale well with regard to search. Extent binary trees are able of aggregation, allow scalable search, but have high overhead and extremely bad worst case behavior, potentially exploding to sizes a couple orders of magnitude higher than plain bitmaps. The latter problem is sometimes resolved by ad-hoc means, e.g. by converting parts of an extent tree to bitmaps (Btrfs). Another possible workaround is to impose a divide-and-conquer multilayered unit system (BitTorrent). We introduce a new data structure named “binmap”, a hybrid of bitmap and binary tree, which resolves the shortcomings of the extent binary tree approach. Namely (a) it has lower average-case overhead (b) it is tolerant to patchy bitmaps and (c) its worst-case behavior is dramatically better.
Real-time collision avoidance in human-robot interaction based on kinetostatic safety field

This paper addresses the problem of collision avoidance in human-robot interaction. To this end, we introduce the concept of kinetostatic safety field, a novel safety assessment about the risk in the vicinity of a rigid body (including a robot link or a human body part). The safety field depends on the position and velocity of the body but it is also influenced by its real shape and size. Since all the computation can be performed in closed form, the safety field is suitable for real-time applications. Moreover, we present a safety-oriented control strategy for redundant manipulators, based on safety field and developed entirely on the kinematic level, where the kinematic redundancy is exploited for simultaneous task performance and collision avoidance, such as self-collision avoidance and human-robot coexistence. The proposed control strategy is validated through experiments performed on ABB's FRIDA dual arm robot.
Distributed Alternating Direction Method of Multipliers

We consider a network of agents that are cooperatively solving a global unconstrained optimization problem, where the objective function is the sum of privately known local objective functions of the agents. Recent literature on distributed optimization methods for solving this problem focused on subgradient based methods, which typically converge at the rate O (1/√k), where k is the number of iterations. In this paper, k we introduce a new distributed optimization algorithm based on Alternating Direction Method of Multipliers (ADMM), which is a classical method for sequentially decomposing optimization problems with coupled constraints. We show that this algorithm converges at the rate O (1/k).
PROBING THE PULSAR WIND IN THE γ-RAY BINARY SYSTEM PSR B1259−63/SS 2883

The spectral energy distribution from the X-ray to the very high energy regime (>100 GeV) has been investigated for the γ-ray binary system PSR B1259−63/SS 2883 as a function of the orbital phase within the framework of a simple model of a pulsar wind nebula. The emission model is based on the synchrotron radiation process for the X-ray regime and the inverse Compton scattering process boosting stellar photons from the Be star companion to the very high energy (100 GeV–TeV) regime. With this model, the observed temporal behavior can, in principle, be used to probe the pulsar wind properties at the shock as a function of the orbital phase. Due to theoretical uncertainties in the detailed microphysics of the acceleration process and the conversion of magnetic energy into particle kinetic energy, the observed X-ray data for the entire orbit are fitted using two different methods. In the first method, the magnetization parameter and the Lorentz factor of the wind at the shock are allowed to vary for a given power law index characterizing the accelerated particles at the shock. In this case, the observed photon index of ∼1.2 in the 1–10 keV energy band near the periastron passage can be understood provided that (1) the electron energy distribution is described by a broken power law and (2) there is a break at an energy of about 8 × 106 in units of the electron rest mass energy. In the second method, the magnetization parameter and the power law index are varied for a fixed Lorentz factor. Here, the photon index of ∼1.2 can result from a particle distribution described by a power law index of ∼1.5. The calculated emission in the energy band corresponding to 10 MeV–1 GeV from the shocked pulsar wind indicates that these two cases can be distinguished by future Fermi observations near the periastron. It is also found that the emission from the unshocked wind could be detectable by the Fermi telescope near the periastron passage if most of the kinetic energy of the flow is carried by particles with Lorentz factors of Γ ∼ 105.
An intelligent system for personalized information retrieval: a genetic approach

Personalized Information Retrieval (IR) is a research field that allows the implementation of information access systems involving the user in the search process. This is achieved by representing the user's profile in order to adapt the IR system functioning to his context. This paper presents a new IR system approach capable of integrating the user in the search process. As a first step of the approach, we focused on building user interests to better understand his information needs, by capturing his judgments about the returned results. Then, our system will optimize the user query, by re-injecting relevance using a genetic algorithm. To illustrate our approach, we have realized a prototype of our system and applied it on a case study.
Deep Deformable Part Models

The deformable parts model (DPM) [6] serves as a key component in most modern state-of-the-art object detection systems. At a high level, the DPM composes a single object model by learning to detect and assemble parts of an object. Most modern systems employing the DPM employ densely computed Histogram of Oriented Gradients [5] features at training time. Despite the success of HOG features in many applications, we believe that more sophisticated features derived from unsupervised feature learning processes can boost DPM performance. Recent work in unsupervised feature learning demonstrates that single neurons in a deep network can discriminate between object classes [10]. However, most published work on such deep learning approaches have succeeded only on simple image classification tasks (e.g. CIFAR, MNIST). In this project, we explore the empirical performance of the deep deformable parts model (D-DPM), which uses deep features in the DPM in lieu of HOG features. We evaluate the efficacy of the D-DPM on the PASCAL VOC 2007 object detection task. To the best of our knowledge, no other work has successfully employed deep features on detection tasks involving datasets with as much variation as PASCAL.
Towards a methodology for testing of business processes

Business processes naturally integrate web services implemented with different languages and technologies and executed in heterogeneous environment. Usually the integrated web services and their underlying infrastructure used to exchange messages are not under the control of process architects. This reflects the development and specifically complicates the testing. In this paper a methodology for testing of business processes is presented, which aims to enable automatic test case generation for path coverage functional testing, as well as to provide fault injection mechanisms for negative functional testing. The methodology is supported by a testing framework, called TASSA, that consists of several tools for design time testing of business process described according Web Service Business Process Execution Language (WS-BPEL) standard. The framework follows the Service-Oriented Architecture (SOA) principles and is validated through sample business process scenarios.
The role of small and medium practices in providing business support to small- and medium-sized enterprises

Small and Medium Practices Committee 2 The mission of the International Federation of Accountants (IFAC) is to serve the public interest, strengthen the accountancy profession worldwide and contribute to the development of strong international economies by establishing and promoting adherence to high-quality professional standards, furthering the international convergence of such standards and speaking out on public interest issues where the profession's expertise is most relevant. Permission is granted to make copies of this work provided that such copies are for use in academic classrooms or for personal use and are not sold or disseminated and provided that each copy bears the following credit line: " Copyright © April 2010 by the International Federation of Accountants (IFAC). All rights reserved. Used with permission of IFAC. Contact permissions@ifac.org for permission to reproduce, store or transmit this document. " Otherwise, written permission from IFAC is required to reproduce, store or transmit, or to make other similar uses of, this document, except as permitted by law. Contact permissions@ifac.org. Preface The IFAC Small and Medium Practices (SMP) Committee is pleased to issue this Information Paper. The Paper analyses the literature and evidence base on the role of accounting practices, and in particular small and medium practices (SMPs) in providing business support to small-and medium-sized enterprises (SMEs). apparent shift in the market away from traditional statutory compliance type services towards satisfying a demand from SMEs for services of a business advisory nature. The aim of the paper is to examine the evidence as to what services are being provided and to better understand the relationship between SMPs and SMEs. It is anticipated that this paper will provide a useful and helpful reference point for member bodies of IFAC in developing policy, training and products to meet the growing needs of SMPs in providing these services to SMEs. Acknowledgements We would like to acknowledge the support from IFAC to undertake the research on which this information paper is based together with the advice from Paul Thompson and the reviewers of earlier drafts of the paper. We would also like to thank the six accountants who took participated in a series of interviews designed to help us understand the nature of relations between SMPs and SMEs. Their insights and experiences have are greatly appreciated and helped shape our thinking as the research developed. The views expressed in this paper are those of the authors and as such do …
An agent-based software development method for developing an agent-based multimedia system

We proposed a rapid prototyping approach that combines the component based software engineering (CBSE) and the case-based reasoning (CBR) techniques to facilitate the development of agent-based multimedia software. This approach applies CBR to retrieve existing agent software components from an old agent design case and adapt retrieved components to construct an agent system that fulfills the user's requirements. The design of an agent-based multimedia system is divided into the group level, agent level, skill level, module level, and code level. Those levels are organized from abstract (group) level to concrete (code) level, and multiple cases in a hierarchical representation are used to represent the design of an agent system. Reusing software components as bases to construct an agent-based multimedia system is useful because designing and building an agent-based multimedia system is a complex task and to rebuild each component of such a system is time consuming and redundant. We propose an approach to help the system developer reuse the experience of designing an agent-based multimedia system. The system developer can focus their point in problem solving instead of constructing the agent software architecture.
The third open answer set programming competition

Abstract Answer Set Programming (ASP) is a well-established paradigm of declarative programming in close relationship with other declarative formalisms such as SAT Modulo Theories, Constraint Handling Rules, FO(.), PDDL and many others. Since its first informal editions, ASP systems have been compared in the now well-established ASP Competition. The Third (Open) ASP Competition, as the sequel to the ASP Competitions Series held at the University of Potsdam in Germany (2006–2007) and at the University of Leuven in Belgium in 2009, took place at the University of Calabria (Italy) in the first half of 2011. Participants competed on a pre-selected collection of benchmark problems, taken from a variety of domains as well as real world applications. The Competition ran on two tracks: the Model and Solve (M&S) Track, based on an open problem encoding, and open language, and open to any kind of system based on a declarative specification paradigm; and the System Track, run on the basis of fixed, public problem encodings, written in a standard ASP language. This paper discusses the format of the competition and the rationale behind it, then reports the results for both tracks. Comparison with the second ASP competition and state-of-the-art solutions for some of the benchmark domains is eventually discussed.
A study on text summarization techniques and implement few of them for Bangla language

Text summarization is the technique which automatically creates an abstract or summary of a text. The technique has been developed for many years. So a survey has been done on different summarization techniques. No work in this area has been done for Bangla language. This paper presents a text summarizer for Bangla, which uses some extraction methods for text summarization.
Maximizing topic propagation driven by multiple user nodes in micro-blogging

This work investigates the maximization of topic propagation jointly driven by multiple user nodes in micro-blogging. In this paper, we propose a new method to find a set of user nodes that jointly propagate topics approximately the most widely. First, we obtain multiple nodes with strong influence; Second, we exactly compute the breadth of information spread driven by a single node based on probabilistic models; Finally, we analyze the information propagation jointly driven by multiple nodes and derive an approximately optimal set of driving nodes. We find that the breadth of information propagation jointly driven by multiple nodes is approximately linear with both the breadth of information propagation of single driving nodes and the strength of tie among them, which indicates that selecting the optimal driving nodes needs to consider the link information among them as well as the ability of each node. Experimental results demonstrate the effectiveness of our method.
A Role for Transportin in the Nuclear Import of Adenovirus Core Proteins and DNA

Adenoviruses target their double‐stranded DNA genome and its associated core proteins to the interphase nucleus; this core structure then enters through the nuclear pore complex. We have used digitonin permeabilized cell import assays to study the cellular import factors involved in nuclear entry of virus DNA and the core proteins, protein V and protein VII. We show that inhibition of transportin results in aberrant localization of protein V and that transportin is necessary for protein V to accumulate in the nucleolus. Furthermore, inhibition of transportin results in inhibition of protein VII and DNA import, whereas disruption of the classical importin α–importin β import pathway has little effect. We show that mature protein VII has different import preferences from the precursor protein, preVII from which it is derived by proteolytic processing. While bacterially expressed glutathione S‐transferase (GST)‐preVII primarily utilizes the pathway mediated by importin α–importin β, bacterially expressed GST‐VII favours the transportin pathway. This is significant because while preVII is important during viral replication and assembly only mature VII is available during viral DNA import to a newly infected cell. Our results implicate transportin as a key import receptor for the nuclear localization of adenovirus core.
On the role of compression in distributed systems

Compression has been used in numerous ways for many years, but recently two factors have combined in a way to push compression to the forefront of distributed systems. First, the disparity between processor speeds and I/O rates is ever-increasing, making it possible to perform compression in software to a much greater extent than was previously feasible. Second, the growth of new applications demanding enormous data rates, such as digital video and audio, makes hardware compression increasingly desirable: I discuss the importance of compression in various environments and describe how compression may be used not only to reduce the demand for disk space, disk bandwidth, and network bandwidth, but also to appear to extend physical memory.
Forex trend classification using machine learning techniques

Foreign Currency Exchange market (Forex) is a highly volatile complex time series for which predicting the daily trend is a challenging problem. In this paper, we investigate the prediction of the High exchange rate daily trend as a binary classification problem, with uptrend and downtrend outcomes. A large number of basic features driven from the time series data, including technical analysis features are generated using multiple history time windows. Various feature selection and feature extraction techniques are used to find best subsets for the classification problem. Machine learning systems are tested for each feature subset and results are analyzed. Four important Forex currency pairs are investigated and the results show consistent success in the daily prediction and in the expected profit.