Miracle-dz/UniFAR-FTUs huggingface dataset:
ALE : the attribute logic engine user's guide, version 2.0.1

ale 3.0 is completely compatible with ale 2.0 grammars, and adds the following new features: • A semantic-head-driven generator, based on the algorithm presented in Shieber et al. (1990). The generator was adapted to the logic of typed feature structures by Octav Popescu in his Carnegie Mellon Master's Thesis, Popescu (1996). Octav also wrote most of the generation code for this release. Grammars can be compiled for parsing only, generation only, or both. Some glue-code is also available from the ale homepage, to parse and generate with different grammars through a unix pipe. • A source-level debugger with a graphical XEmacs interface. This debugger works only with SICStus Prolog 3.0. 6 and higher. A debugger with reduced functionality will be made available to SWI Prolog users in a later release. This debugger builds on, and incorporates the functionality of the code for the SICStus source-level debugger, written by Per Mildner at Uppsala University. • a /1 atoms. There are now an infinite number of atoms (types with no appropriate features), implicitly declared in every signature. These atoms can be arbitrary Prolog terms, including unbound variables, and can be used wherever normal ale types can, e.g., f:(a p(3.7)). a /1 atoms are extensional as Prolog terms, i.e., are taken to be identical according to the Prolog predicate , ==/2. In particular, this means that ground atoms behave exactly as ale extensional types. • Optional edge subsumption checking. For completeness of parsing, one only needs to ensure that, for every pair of nodes in the chart, the most general feature structure spanning those nodes is stored in the chart. This can reduce the number of edges in many domains. • An autonomous intro/2 operator. Features can now be declared on their own in a separate part of the grammar. • Default specifications for types. These are NOT default types. If a type appears on the right-hand side of a sub/2 or intro/2 specification, but not on iii iv CONTENTS the left-hand side of one, ale will assume this type is maximal, i.e., assume the specification, T ype sub []. Similarly, if it occurs on a left-hand side, but not on a right-hand side, ale will assume the type is immediately subsumed by bot, the most general type. In both cases, ale will announce these assumptions during compilation. • Several bug corrections and more compile-time warning and error messages. • An SWI Prolog 2.9. 7 …
Interesting User Behaviour Prediction in Mobile E-commerce Environment using Constraints

ABSTRACT Mobile e-commerce has become a more emerging topic these days and is speedily increasing with the growth of internet. It is playing an essential role in our life as it helps us by using new trends and technologies to improve business and thus providing quicker information. Behaviour analysis and sequence pattern prediction provide scope for more advanced research topics. If a user finds various interesting sequences in mobile e-commerce environment, then she/he can predict lots of new information. This predicted information may be useful for defining various new services or improving on existing and may also be useful to manage service infrastructure to offer quicker responses. Today, user behaviour sequence mining is an emerging issue in mobile e-commerce environment which considers mobile user services, accessing sequences at various locations on different times. In the current scenario, the user may only be interested in the service sequences with some specific constraints. The constraint may define to the type of service or importance of a particular service. Here, we consider important or useful services for particular user in mobile e-commerce environment. We proposed an efficient framework, namely CIUBSM (Constraint based Interesting User Behaviour Sequence Mining) which deals with important constraint of services and generates an interesting behaviour sequence of mobile users. Experimental results show that the proposed framework is better than previous constraint-based frameworks.
Investigations on temporal-oriented event-based extractive summarization

Automatic summarization aims to produce a concise summary of source documents by identifying the focused topics in documents. Normally, topics are represented by some essential events. Topics may evolve or shift over time. Tracking the trend of the topics requires anchoring events on the time line. Unfortunately, both events and their associated time features are not well studied in previous work. Investigating event-based and temporal-oriented summarization techniques are primary objectives of this study. As a matter of fact, the salience of contents could hardly be evaluated from single point of view. Exploiting a framework which can effectively integrate multiple impact factors is another objective. We define events by "action" words as well as associated named entities. Events weave documents into a map built either on event instances or event concepts. Relevance between events is exploited to identify important events. To utilize temporal information associated to events, it is necessary to extract and normalize temporal expressions. We investigate rule-based approaches for these tasks. Two statistical measures are employed to evaluate the significance of events based on their temporal distributions. Sentence selection is a complicated process. Therefore we explore various features including surface, content, event and relevance features under a learning-based classification framework. Event-based and temporal-oriented approaches are incorporated as features into this framework. The contributions of this study are listed as follows. Event-based summarization approaches are proposed. They achieve competitive results when compared with successful word-based approaches. Temporal concepts are introduced into event-based summarization and temporal information is found crucial to summarization on documents which contain evolving topics. An adaptive leaning-based framework is developed to incorporate various types of features. A system for temporal expression extraction and normalization is implemented. It is an effective tool not only practical for document summarization, but also for many other applications.
On the design of devices with emergent semantic functions

This dissertation examines the functional roles symbols play in biological organisms, scientific models and adaptive learning devices, analyzing the process of how symbols acquire new functions. The semiotic categories of syntactics, semantics, and pragmatics are used to examine the functioning of symbols in organisms, models, and devices. The dissertation explores how we would go about designing self-organizing devices which adaptively construct their own relationships to the physical world (emergent semantic functions). It bears on the frame/feature-generation problem in artificial intelligence, the problem of machine creativity in philosophy, the measurement problem in physics, the problem of generating new observables in science, and the problem of emergent functions in evolutionary biology. Much of the perspective comes out of the work of theoretical biologists Howard Pattee and Robert Rosen. An analytical framework is developed for distinguishing between computation, measurement, control, and nonsymbolic functionalities. A taxonomy of adaptive cybernetic devices is proposed in which nonadaptive devices ("formal-computational" and "formal-robotic") are distinguished from computationally adaptive ones ("adaptive devices", e.g. perceptrons, neural nets, genetic algorithms) and semantically adaptive ones ("evolutionary devices"). Evolutionary devices adaptively construct their own sensors and effectors contingent upon their performance, and are thus qualitatively different from devices now in use. Evolutionary devices are analogous to the biological evolution of new sense and effector organs. Relative capacities and limitations of the device types are outlined. Three contemporary conceptions of emergence are distinguished: computational emergence, thermodynamic emergence, and emergence-relative-to-a-model. Levels of adaptivity are connected to types of emergence. Throughout, purely computational, logic-driven strategies for generating new functions (e.g. artificial intelligence, evolutionary simulation strategies, computationally-based artificial life) are criticized as being incapable of generating new primitives. It is argued that computers have completely nonemergent behavior because of their completely specified, digital, symbolic nature, while biological organisms are capable of emergent behavior because they also include analog, nonsymbolic processes. An evolutionary robotics research program is suggested as an alternative to purely computational approaches.
Optimization Protocol Based on Performance Metric

The design of high performance circuits implies the convergence of different parameters such as: short fabrication time, wide functionality, high clock frequency, low power. This induces a clever design flow for managing CAD tools with physical level defined indicators. To address this problem we used a closed form model of delay in CMOS structures to define the optimization range and set up adapted optimization circuit techniques. In this paper, we validate the design space exploration method, defining maximum and minimum delay bounds on logical paths. Then we adapt this method to a "constant sensitivity method" allowing to size a circuit at minimum area under a delay constraint. Three techniques are explored and characterized: path global sizing, local buffer insertion and mixed sizing and buffer insertion. An optimization protocol is finally defined to manage the trade-off performance constraint – circuit structure. These methods are implemented in an optimization tool (POPS) and validated by comparing the optimization results obtained on various benchmarks (ISCAS’85) to that resulting from an industrial tool.
Impact of Fatigue and Sleep Quality upon the Quality of Life of Haemodialysis Recipient Patients

Background: Patients with End-stage renal failure face many challenges due to their condition, which may leave them feel fatigued, depressed and lack in sleep quality associated with poor quality of life. Objective: Determining the impact of fatigue and sleep quality upon the quality of life of haemodialysis recipient patients. Methodology: The study was conducted in haemodialysis unit at Sohag University Hospital of January 2014 to June 2014. A purposive sample of 221 patients with ESRD were treated by Haemodialysis. Personal Information Form (PIF), QoL Short Forme-36 (SF-36), Pittsburgh Sleep Quality Index (PSQI) and Fatigue Severity Scale (FSS) tools are used for data collection. Data was analyzed through descriptive statistical approach(frequency and percentage) and inferential approach (mean of score, Pearson correlation coefficient, ANOVA test and independent samples t-test). Results: The mean age ± SD of patients was 42.3 ± 13.1 years. The study found that 87.3% of patients were poor sleepers (global PSQI ≥5), 84.2% were suffering of fatigue, and quality of life mean was 33.6 ±17.5. According to age and sex, it was found that the younger and male patients were less complaining of fatigue and poor sleep. They have better quality of life compared to other groups. There was a significant positive correlation between age and both physical and mental components scores, sleep and fatigue. Also a negative correlation was found between physical and mental components scores and sleep and fatigue. Conclusions: Haemodialysis patients had poor quality of mental and physical health. The quality of life was impaired as seen by poor sleep and fatigue. It is suggested that these patients require the attention of health caregivers for the need of possible psychological support.
Handling limits of high degree vertices in graph processing using MapReduce and Pregel

Even if Pregel scales better than MapReduce in graph processing by reducing iteration's disk I/O, while offering an easy programming model using " think like vertex " approach, large scale graph processing is still challenging in the presence of high degree vertices: Communication and load imbalance among processing nodes can have disastrous effects on performance. In this paper, we introduce a scalable MapReduce graph partitioning approach for high degree vertices using a master/slave partitioning allowing to balance communication and computation among processing nodes during all the stages of graph processing. Cost analysis and performance tests of this partitioning are given to show the effectiveness and the scalability of this approach in large scale systems.
Interventions for critical incident stress in emergency medical services: a qualitative study

Controversy over the use of Critical Incident Stress Debriefing leaves Emergency Medical Services (EMS) organizations with little direction in preventing sequelae of Critical Incident Stress (CIS) in their employees. Objectives of the study were to explore and describe Emergency Medical Technicians' (EMTs) experiences of critical incidents and views about potential interventions, in order to facilitate development of interventions that take into account EMS culture. We interviewed 60 EMT practitioners and supervisors, and examined interview transcripts using ethnographic content analysis. EMT practitioners want emotional support in their workplace soon after a critical incident, and welcome interventions that would enhance this. They also experience a brief timeout as important in preventing sequelae of CIS. Exchanges with supervisors and peers that are experienced as supportive are illustrated. Barriers to support are described, as well as ways to address them. Educating supervisors and front-line practitioners to recognize and respond supportively to critical incidents is acceptable to them. However, an organizational culture that stigmatizes vulnerability is the most insidious and challenging barrier to accessing support after a critical incident. Addressing the issue of stigma is critical to developing appropriate interventions. Copyright © 2008 John Wiley & Sons, Ltd.
Experiences using DAKOTA stochastic expansion methods in computational simulations.

Uncertainty quantification (UQ) methods bring rigorous statistical connections to the analysis of computational and experiment data, and provide a basis for probabilistically assessing margins associated with safety and reliability. The DAKOTA toolkit developed at Sandia National Laboratories implements a number of UQ methods, which are being increasingly adopted by modeling and simulation teams to facilitate these analyses. This report disseminates results as to the performance of DAKOTA's stochastic expansion methods for UQ on a representative application. Our results provide a number of insights that may be of interest to future users of these methods, including the behavior of the methods in estimating responses at varying probability levels, and the expansion levels for the methodologies that may be needed to achieve convergence.
Exploiting Optical Contrasts for Cervical Precancer Diagnosis via Diffuse Reflectance Spectroscopy

Exploiting Optical Contrasts for Cervical Precancer Diagnosis via Diffuse Reflectance Spectroscopy by Vivide Tuan-Chyan Chang Department of Biomedical Engineering Duke University Date:_______________________ Approved: ___________________________ Nimmi Ramanujam, Supervisor ___________________________ Sarah Bean ___________________________ Peter Cartwright ___________________________ David Katz ___________________________ Adam Wax An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Biomedical Engineering in the Graduate School of Duke University 2010 Copyright by Vivide Tuan-Chyan Chang 2010
An Application of Second Order Volterra Filters for Prediction of Image Sequences

Prediction of image sequences is widely used in image processing and transmission schemes such as Differential Pulse Code Modulation (DPCM). Traditional linear prediction employs linear predictors for simplicity. The nonlinear Volterra predictor can be used as an alternative to linear predictor to account for the nonlinear components in the image signals. The proposed quadratic predictor is more robust to noise. Experimental results illustrate that the nonlinear predictor yields improved mean square error performance. The proposed method can be incorporated in new predictive coding schemes for high throughput. Keywords— DPCM, image sequence, prediction error, predictor, quadratic filter, singular value decomposition, Volterra series
Unsupervised Adversarial Anomaly Detection using One-Class Support Vector Machines

Anomaly detection discovers regular patterns in unlabeled data and identifies the non-conforming data points, which in some cases are the result of malicious attacks by adversaries. Learners such as One-Class Support Vector Machines (OCSVMs) have been successfully used in anomaly detection, yet their performance may degrade significantly in adversarial conditions such as integrity attacks. This work focuses on integrity attacks, where the adversary distorts the training data in order to successfully avoid detection during evaluation. This paper presents a unique combination of anomaly detection using (1) OCSVMs in the presence of adversaries who distort training data in a targeted manner and (2) nonlinear randomized kernel methods, which facilitate computational and conceptual simplification through dimension reduction. We theoretically analyze the effects of adversarial distortions on the separating margin of OCSVMs and provide supporting empirical evidence. The proposed approach introduces a layer of uncertainty on top of the OCSVM learner, making it challenging for the adversary to guess the specific configuration of the learner.
Synchronous Smooth Sliding Mode Control for Parallel Mechanism Based on Coupling Analysis

For any multi-DOF parallel mechanism, its system model is difficult to accurately establish and high-performance control is hard to achieve because of its high nonlinearity and strong coupling characteristics. In view of this, for a 6-PTRT parallel mechanism, the coupling characteristics are first analysed and then a novel smooth sliding mode control algorithm based on synchronization error is designed and the system's stability is proven - in theory - according to the Lyapunov stability theorem. By introducing the defined synchronization error into the smooth sliding mode control, the proposed method can resist the coupling effect among the branches of the parallel mechanism and realize the coordinated, synchronous and more accurate movement of each branch of the parallel mechanism with no accurate system model, whereby the tracking error of each branch may converge on zero simultaneously. The simulation results show that the synchronous smooth sliding mode control method proposed here has a shorter response time and a higher control precision when compared with the smooth sliding mode control method. By considering the errors of the adjacent branches, the synchronous coordination among the branches of the parallel mechanism with the coupling effect is effectively improved.
A Data Placement Strategy for Data-Intensive Applications in Cloud

With the development of information technology,data-intensive applications in cloud have been used in more and more fields.Because of the decentralized data centers in cloud,these applications now are facing some new challenges in data placement which mainly include how to reduce the time cost of data movements between data centers,how to deal with the data dependencies,and how to keep a relative load balancing of data centers.This paper proposes a data placement strategy,the three stages of which address the three challenges above respectively.Simulation shows that the strategy can effectively reduce the time cost of data movements across data centers during the application's execution.
Methodology for Translation of Sign Language into Textual Version in Marathi

In later year's gesture based communication acknowledgment has turned in a standout amongst the most developing fields of examination and it is the most characteristic method of correspondence for the individuals with listening to issues. A hand signal acknowledgment framework can give a chance to hard of hearing persons speak with typical individuals without the need of a translator or middle. We are going to construct a framework and techniques for the programmed acknowledgment of the Marathi communication via gestures. Through that we are giving instructing classes to the reason for preparing the hard of hearing sign client in Marathi. The framework does oblige hand to be appropriately adjusted to the camera and does not require any wearable sensors. A substantial arrangement of tests has been utilized as a part of the proposed framework to perceive confined words from the standard Marathi communication through signing, which are taken before the camera with distinctive hard of hearing sign client. In our proposed framework, we mean to perceive some extremely essential components of gesture based communication and to make an interpretation of them to content and the other way around. The proposed framework utilizing 46 Marathi letters in order for acknowledgment.
A CASE STUDY OF NON-NATIVE ENGLISH-SPEAKING INTERNATIONAL UNIVERSITY STUDENTS PARTICIPATING IN A COMMUNITY OF PRACTICE

The social identity construction of international students studying in the United States is important to the field of second language learning and the study of identity. A Social Identity and Communities of Practice (CoP) framework were used to understand how participation in a CoP informed the identity of non-native speaking university international students studying in the U.S. The focus of this study was to investigate how participation in a CoP informed the identity of non-native speaking international university students studying in the U.S. I proposed that these frameworks provided a foundation for understanding how participation in a CoP for non-native English-speaking university students informed their international student identity. Furthermore, this study showed how participation in a CoP contributed to the participants’ sense of belonging. Data collected for this study included audio recordings of the group and individual interviews, notes from the observation of the CoP, audio recordings of the CoP observations, and notes of researcher’s thoughts. Several major themes emerged including: Identity, Language, and Aspects of Communities of Practice. These themes described why this group of students decided to belong to this
Characterizing Metastability Practical Measurement Techniques to accurately determine device dependent coefficients used to predict synchronizer MTBF

Determining metastability characteristics is challenging. Devising reliable and repeatable experiments and procedures requires time, patience, care and knowledge. This discussion presents practical measurement techniques to accurately determine the Resolving Time Constant (tau) and Metastability Window (W). Also included is a method for observing the metastability failure rate at a designated time following the Clock. By converting this failure rate to observed MTBF (Mean Time Between Failure), a comparison is made to a predicted MTBF.