Miracle-dz/UniFAR-FTUs huggingface dataset:
Similar Execution Path Generation Based on Backward Symbolic Analysis

Similar execution paths generation is one of the fundamental tasks in code analysis and detection. The current methods usually target to the program behavior or program structure, and change the value of key predicates, but these methods has a low effectiveness due to the lack of the necessary guidance information, Meanwhile, the predicates set has a large size and usually hard to solve, thus it will reduce the analyze precision as well. A technique of similar execution paths generation based on dynamic synergy bidirectional mapping is proposed in this paper. According to extend the shape of Control Flow Graph and use the backward symbolic analysis, the weakest precondition of the candidate path is generated, which can be used as the guidance information to generate pointed similar execution paths set according to the edit distance via changing the distance factor. The experimental results show that this method has the advantage of precision and anti-inference.
SVD: a novel content-based representation technique for Web documents

Most users typically express their information need via short queries to search engines and they often have to physically sift through the search results based on relevance ranking, making the process of relevance judgement time-consuming. The structure of the Web is increasingly being used to improve organisation, search and analysis of information on the Web. In this paper, we describe how the Web structure together with our novel summarisation techniques can be applied to better represent knowledge in actual Web documents via the proposed semantic virtual documents (SVD). We will also outline our experimental design to evaluate the effectiveness of the proposed SVD with a prototype system called iSEARCH (intelligent search and review of cluster hierarchy) for Web content retrieval and mining. The experimental results confirm that the novel technique show promising qualities in content-based representation for Web documents to enhance Web content retrieval and mining.
Lexical Functions as a Tool of ETAP-3 1

The paper describes the use of lexical functions, an instrument proposed in Igor Melcuk's “Meaning Text Theory” (MTT), in advanced NLP applications as exemplified in the ETAP-3 linguistic processor, including parsers, high quality machine translation (MT), a system of paraphrasing and computer-aided learning of lexica. In parsing, collocate LFs are used to resolve or reduce syntactic and lexical ambiguity. The MT system resorts to LFs to provide idiomatic target language equivalents for source sentences in which both the argument and the value of the same LF are present. The system of paraphrasing, which automatically produces one or several synonymous transforms for a given sentence or phrase, can be used in a number of advanced NLP applications ranging from MT to authoring and text planning. The computer-aided system of learning lexica is also based on the concept of LFs as a tool of formal description of that part of vocabulary which is simultaneously systematic and idiomatic and is therefore most difficult for language acquisition.
No-reset iterative learning control

In this paper, we study the repetitive control of discrete-time linear periodically time-varying (LPTV) plants using a no-reset iterative learning control (NRILC) system, which is an iterative learning control (ILC) system where the plant is not reset at the beginning of each iteration. We apply this scheme to discrete-time LTI SISO plants; the approach can be extended to LPTV and MIMO plants. Using results from output feedback theory, we show that the closed-loop eigenvalues of the system can almost always be placed with the selection of an appropriate finite learning gain.
Bounded scheduling of process networks

We present a scheduling policy for complete, bounded execution of Kahn process network programs. A program is a set of processes that communicate through a network of first-in first-out queues. In a complete execution, the program terminates if and only if all processes block attempting to consume data from empty communication channels. We are primarily interested in programs that operate on infinite streams of data and never terminate. In a bounded execution, the number of data elements buffered in each of the communication channels remains bounded. The Kahn process network model of computation is powerful enough that the questions of termination and bounded buffering are undecidable. No finite-time algorithm can decide these questions for all Kahn process network programs. Fortunately, because we are interested in programs that never terminate, our scheduler has infinite time and can guarantee that programs execute forever with bounded buffering whenever possible. Our scheduling policy has been implemented using Ptolemy, an object-oriented simulation and prototyping environment.
A pipelined architecture of fast modular multiplication for RSA cryptography

In this paper, a fast algorithm with its corresponding VLSI architecture is proposed to speed up the modular multiplication with a large modulus. By partitioning the operand (multiplier) into several equal-sized segments, and performing the multiplication and residue calculation of each segment in a pipelined fashion, a performance improvement can be achieved by using our algorithm compared with previous work. We also show an efficient procedure to accelerate the residue calculation and use carry-save addition to implement the architecture such that the critical path is independent of the size of the modulus. Therefore, the resulting architecture and implementation are very suitable to be applied to the high-speed RSA cryptosystem and can be easily implemented in VLSI technology.
Propagation Aspects in Vehicular Networks

Traffic accidents have become an important health and social problem due to the enormous number of fatalities and injuries. The total number of deaths and injuries in the European Union (EU), United States of America (USA) and Japan has been steadily reduced over the last decade. This reduction is mainly attributed to the implementation of a set of road safety measures, such as seat-belt use, vehicle crash protection, traffic-calming interventions and traffic law enforcement. However, the number of accidents has remained uniform due to the increasing number of vehicles and total distance driven (Peden et al., 2004). In addition to passive vehicle safety systems, such as airbags, anti-lock braking system (ABS) and electronic stability control (ESP), new active safety systems have been introduced to improve vehicular safety. To this end, the last decade has witnessed the traffic management industry, engage and promote the integration of information and communications technology (wireless, computing and advanced sensor technologies) into both vehicles and the wider transport infrastructure. These proposals have led to the intelligent transportation system (ITS) concept. At present, different ITS applications have been introduced, such as variable message signs (VMS), located at strategic points (e.g., tunnels and merging highways) or spaced at given distances, to inform drivers about traffic and dangerous situations; automated toll collection systems for highways and parkings; and real-time traffic information broadcasted in the FM radio band. Besides this, onboard ITS applications have improved the assistance and protection mechanisms for drivers: navigation systems, rear and front parking radars, and cameras are extensively used in the vehicle. Vehicles now incorporate sophisticated computing systems, with several sensors interconnected. However, short-range sensors employed in emergency systems, such as forward collision warning and lane keeping assist, are insufficient, specially when these sensors need to extend their communication horizon in emergency cases due to the limitation of their operating range to line-of-sight (LOS) conditions (Vlacic et al., 2001). Therefore, there are safety applications for distance emergency situations, such as blind corners and traffic crossing, where large-range vehicular communication systems are required, e.g., operating rages of about 1000 meters, in both LOS and non-LOS (NLOS) conditions (Gallagher & Akatsuka, 2006). Wireless communications systems which can operate with these constraints are known as cooperative systems on the road. In the cooperative system concept, vehicles and infrastructure exchange safety messages to extend the distance horizon and provide more information in real time to drivers. Cooperative systems involve two
The acquisition of Jamaican Creole: The emergence and transformation of early syntactic systems

This study explores the early acquisition of Jamaican Creole (JC) syntax. There is a significant gap in linguistic research investigating the acquisition of creole languages which this research aims to repair. Six children, age ranging from 1;6 – 1;11, were recorded over an 18 month period. 60 minutes recordings were conducted every 10-15 days, thereby establishing the first longitudinal corpus of acquisition data in a creole language. The corpus was subjected to detailed analysis describing both target-consistent and target-inconsistent productions. The phenomena studied included the emergence of tense, aspectual and modal markers, null subjects, focalization, topicalization, interrogation and ‘typical creole features' such as verb serialization, double-negation, etc. The empirical findings provide evidence of early syntactic development and contribute to the on-going debate on Language Universals. This study will have a long-lasting contribution to the linguistic community as it provides an accessible corpus of natural production of JC early syntactic systems.
Paraphrasing Headlines by Machine Translation Sentential Paraphrase Acquisition and Generation using Google News

In this paper we investigate the automatic collection, generation and evaluation of sentential paraphrases. Valuable sources of paraphrases are news article headlines; they tend to describe the same event in various different ways, and can easily be obtained from the web. We describe a method for generating paraphrases by using a large aligned monolingual corpus of news headlines acquired automatically from Google News and a standard Phrase-Based Machine Translation (PBMT) framework. The output of this system is compared to a word substitution baseline. Human judges prefer the PBMT paraphrasing system over the word substitution system. We compare human judgements to automatic judgement measures and demonstrate that the BLEU metric correlates well with human judgements provided that the generated paraphrase is sufﬁciently different from the source sentence.
Classification schemes for collection mediation: work centered design and cognitive work analysis

Work domain analysis and work centered design is a new approach to design of classification schemes. Classification schemes are symbolic artefacts that inscribe and mediate concepts and structures of domain semantics. In collection mediation, classification schemes are used to search and keep order in paper-based, electronic and digital collections. Research indicates that work centered design of classification schemes is difficult, and that solutions are often based on generic conventions for detailed design, which do not build on needs analysis of the work domains. This Ph.D. thesis deals with cognitive work analysis and work centered design of classification schemes to support mediation of collections. Cognitive work analysis is a methodology, which supports empirical analysis of work domains and work centered design of information systems. As foundation for overall design of schemes, cognitive work analysis focuses on understanding structures and concepts in work domains and actors' work activities. Research in classification schemes for work domains is also addressed by other perspectives, which either emphasise actors' concept formations in work domains or structures and concept formations within communities like professional disciplines or work collectives. The thesis addresses two themes within work centered design of classification schemes for collection mediation: classification schemes as sociological phenomena and cognitive work analysis, with an emphasis on analysis of collaborative work. The themes define two research questions that shape the present research. The two research questions are answered by five individual paper contributions. There exists no generally acknowledged conceptual framework for work centered design of classification schemes. The thesis applies the framework of cognitive work analysis as a methodology for analysing collection mediation work and as a starting point for characterising the use, contents and structures of classification schemes in the work domain. The five publications are placed within the means-ends model of cognitive work analysis in order to illustrate similarities and differences between the contributions. Four empirical sources contribute to the results. Field studies of three film archives and a public library address various collaborative activities in collection mediation. Primary methods applied in field studies are participant observation and interviews. In addition, participatory design of the empirical studies and empirical evaluation of design results have been used. Results from the field studies are discussed in the light of cognitive work analysis, as well as in the light of concepts developed within research in computer-supported collaborative work and sociological theory of communicative action. The studies of collection mediation in film archives focus on cognitive work analysis of collaboration. Their aim has been
A novel channel estimation method for OFDM mobile communication systems based on pilot signals and transform-domain processing

A method of estimating the channel transfer function is presented for orthogonal frequency division multiplexing (OFDM) mobile communication systems working under time-variant radio channel conditions. The proposed method employs lowpass filtering in a transform domain so that intercarrier interference and additive white Gaussian noise components in the received pilot signals are significantly reduced. The cutoff frequency of the transform-domain filter is dynamically selected by tracking the received pilot signals. The channel transfer function for all the subcarriers is obtained by a high-resolution interpolation realized by zero-padding and DFT/IDFT. The proposed method is applicable for all linear modulation OFDM systems. It is demonstrated with a 16QAM-OFDM system which includes both amplitude and phase modulations.
A Petri-net and entity-relationship diagram based object-oriented design method for manufacturing systems control

An evolutionary object-oriented OO design method is proposed for the control software design of an automated manufacturing system. This OO approach is based upon three popular modelling tools-IDEF0, entity relationship diagram ERD and Petri-net. First, IDEF0, ERD and Petri-net models for manufacturing systems are constructed. Some transformation rules are found between these models and the OO model. Finally, simulation and control software are coded, based on the OO model. The practical significances of the proposals are the suggestion of using Petri-net, ERD and IDEF0 as the three models employed in the evolutionary OO design method, which can improve the limitations of existing methods applied in manufacturing systems. The OO paradigm can thus be considered as a suitable mechanism for combining ERD and Petri-net to give integration of information and control system design in a manufacturing system.
Remote Sensing Technology for Precision Agriculture

Agriculture methods in developed countries since the Industrial Revolution have tended to favor greater energy inputs using large tractors and increased applications of synthetic chemicals and fertilizer. While these methods of agricultural production have some negative societal and environmental implications, they have generally supported the food needs of the rapidly growing human population. However, a new mode of thought, with new technology is needed for the future. An agricultural production system that utilizes recent advances in sensor technology can fill this role, becoming an essential component of an intelligent agricultural production system. Specifically, remote sensing technology can supply information about current crop status, including maturity and weed infestations. Information gathered through vision sensors and GPS can be integrated to create field management schedules for chemical application, cultivation, and harvest. Satellites, as well as ground-based technologies have been studied in Japan for sensing the condition of field crops. While both methods have some drawbacks to utilization for crop status sensing in precision agriculture, a helicopter-base sensing system offers several solutions to common obstacles. These benefits include timeliness, spatial resolution as well as efficiency. This paper introduces current technologies, describes timely methods for remote sensing in precision agriculture using an unmanned helicopter, and discusses their impact on agricultural production systems.
Extraction automatique de collocations : Peut-on étendre le test exact de Fisher à des séquences de plus de 2 mots?

In textual statistics, as in natural language processing and corpus linguistics, the study of sequences of contiguous words that occur together more often than by chance is a major topic of interest. In the case of pairs of words, Fisher’s exact test is becoming the reference index to identify them. The objective of this study is to propose a generalization of this index to the analysis of trigrams and longer sequences using a Monte-Carlo procedure. The results of an initial evaluation suggest that this approach could complement other indices, but also that it has a major drawback: a large number of trigrams get a maximum score of collocation.
A novel neural network for temporal pattern identification with applications to control systems

A new neural architecture that can recognize and recall temporal sequences by a self-organizing method requiring little learning effort is presented. The general principle is based on a network of nodes made from groups of neurons. These nodes perform simple recognition and recall of state transitions and are arranged hierarchically so that short subsequences of an observed temporal sequence can easily be learned and then reconstructed. This hierarchy involves extensive interconnections between layers of nodes. The learning process changes the strengths of these interconnections. An application of such a network, involving the implementation of a process controller for a chemical system, is given. <<ETX>>
Online Signature Recognition Using Matlab

Signature is a behavioral trait of an individual and forms a special class of handwriting in which legible letters or words may not be exhibited. The purpose of this paper is to design a new system to make the verification of signatures size and angle invariant for cheque system. The invariance can be achieved by scaling and rotational manipulations on the target image. That is the number of crests, toughs and curves remains the same irrespective of the size and orientation of the image. The ratio between consecutive crests and troughs there by remain the same and hence can be used to determine the genuineness of a signature. This system will be used in financial and business to automatic signature verification. It also includes the verification of the account number and amount on the cheque using OCR (Optical Character Recognition) and finds out if the cheque is cleared or bounced.
Detecting thresholds and interactions among displacement, acceleration, and velocity, for young adults on a horizontally translated platform

We are interested in determining the lower limits of detectability of the control system for standing posture and balance. Our Sliding Linear Investigative Platform For Analyzing Lower Limb Stability (SLIP-FALLS) allows us to study the psychophysical thresholds for movement detection in standing without the interference of vibratory cues. Three neurologically intact young adults were recruited to determine their initial detection thresholds to five displacements using our optimized two alternative forced choice, parameter estimation by sequential testing, protocol that varied acceleration according to the previous responses of the subject. A negative log-log relationship was seen between the acceleration thresholds and displacement length. A positive log-log relationship was seen between the measured peak velocities and displacement length. When plotted on the same graph, acceleration and velocity thresholds intersect just above the mean quiet standing center-of-pressure values for length and velocity, and just below mean frequency. It appears that for displacement lengths less than normal sway, acceleration is used for detection; but above normal sway, velocity is used.
The Social Life of Nothing

Nothing really matters. All the things that we do not do, have or become in our lives can be important in shaping self-identity. From jobs turned down to great loves lost, secrets kept and truths untold, people missed and souls unborn, we understand ourselves through other, unlived lives that are imaginatively possible. This book explores the realm of negative social phenomena – no-things, no-bodies, non-events and no-where places – that lies behind the mirror of experience. Taking a symbolic interactionist perspective, the author argues that these objects are socially produced, emerging from and negotiated through our relationships with others. Nothing is interactively accomplished in two ways, through social acts of commission and omission. Existentialism and phenomenology encourage us to understand more deeply the subjective experience of nothing; this can be pursued through conscious meaning-making and reflexive self-awareness.
Key drivers of mobile commerce adoption an exploratory study of Spanish mobile users

Despite dramatic differences between non-store shoppers were discovered, very limited research has been conducted to examine them. This paper analyses the background of M-commerce and key drivers of future M-commerce decision among Spanish mobile users. Our objective is two-fold: (1) to determine the influence of relations with the Mobile (frequency of Mobile use, length of Mobile use and Mobile affinity), demographics, non-store shopping previous experience (mail, catalogue, Television and Internet) and attitude to M-commerce and its influence on the M-commerce decision and (2) to identify key drivers of future M-commerce intention. We examined data from 606 personal interviews given to Spanish mobile users (270 Mobile shoppers and 336 non Mobile-shoppers) over 14 years old. Data analysis shows that age, attitude towards M-commerce, Internet shopping previous experience and relations with the Mobile (frequency, length of Mobile use and Mobile affinity) are the main predictors of M-commerce decision while age, length of Mobile use, Mobile affinity, consumer attitude towards M-commerce and previous M-commerce experience are the most relevant factors influencing future M-commerce intention. Based on these empirical results this research enables companies to know the key drivers influencing M-commerce adoption and, therefore, what aspects to highlight in their marketing strategies.