Miracle-dz/UniFAR-FTUs huggingface dataset:
Online Correction of the Dynamic Errors in a Stored Overpressure Measurement System

The problem encountered in sharp shock testing as a result of inadequate bandwidth must be addressed to obtain an accurate overpressure peak value when measuring the steep signals of shockwaves during explosions. A dynamic compensator can effectively amend the dynamic errors caused by sensor system characteristics; thus, a dynamic compensation method based on improved particle swarm optimization (PSO) algorithm is proposed in this paper. This method can effectively overcome the influence of the initial value derived with PSO algorithm on compensator index. The distributed algorithm is introduced into the hardware structure design of the dynamic compensator to facilitate the application of an optimized compensator to real-time online measurement. This integration realizes the high-speed parallel of the dynamic compensator of the sensor with field-programmable gate array. Experimental results show that a high-speed parallel dynamic compensator can amend the dynamic errors in a sensor accurately and in a timely manner.
Unfolding the Future: Bifurcation in Organizing Form and Emergence in Social Systems

This paper presents a complexity science informed theory to describe how organizing forms emerge and foster innovation. The theory explores the bidirectional linkages between fine-grained interactions among human beings in a complex adaptive system and the emergent coarse-grained properties that characterize qualitatively distinct and yet stable organizing forms in social systems. By exploiting a mathematical foundation that has been successfully employed in analogous cases in the natural sciences, it opens the door to a rigorous theory of performance and adaptation in human systems by relating changing local rules of interaction to qualitative changes in emerging organizing forms. This process is mediated by evolving models of the system in the environment developed and shared among individuals. Finally, the paper explores whether this model can be used canonically and does so in the context of axiomatic hurdles that must be overcome if a practical mathematical theory of human organizing is to be realized.
Understanding Clusters in Multidimensional Spaces: Making Meaning by Combining Insights from Coordinated Views of Domain Knowledge (2004)

Cluster analysis of multidimensional data is widely used in many research areas including financial, economical, sociological, and biological analyses. Finding natural subclasses in a data set not only reveals interesting patterns but also serves as a basis for further analyses. One of the troubles with cluster analysis is that evaluating how interesting a clustering result is to researchers is subjective, application-dependent, and even difficult to measure. This problem generally gets worse as dimensionality and the number of items grows. The remedy is to enable researchers to apply domain knowledge to facilitate insight about the significance of the clustering result. This article presents a way to better understand a clustering result by combining insights from two interactively coordinated visual displays of domain knowledge. The first is a parallel coordinates view powered by a direct-manipulation search. The second is a domain knowledge view containing a well-understood and meaningful tabular or hierarchical information for the same data set. Our examples depend on hierarchical clustering of gene expression data, coordinated with a parallel coordinates view and with the gene annotation and gene ontology.
The Use of Learning Theory in the Application of Artificial Intelligence to Computer-Assisted Instruction of Physics

It was the purpose of this research, to develop and test an artificially intelligent, learner-based, computer-assisted physics tutor. The resulting expert system is named ARPHY, an acronym for ARtificially intelligent PHYsics tutor. The research was conducted in two phases. In the first phase of the research, the system was constructed using Ausubel's advance organizer as a guiding learning theory. The content of accelerated motion was encoded into this organizer after sub-classification according to the learning types identified by Gagnds. The measurement of the student's level of learning was accomplished through the development of questioning strategies based upon Bloom's taxonomy of educational objectives. The second phase of this research consisted of the testing of ARPHY. Volunteers from four levels of first-semester physics classes at North Texas State University were instructed that their goal was to solve three complex physics problems related to accelerated motion. The only students initially instructed by ARPHY were from the class of physics majors. When the threshold values of the pedagogical parameters stabilized, indicating the fact that ARPHY's instructional technique had adapted to the class' learning style, students from other classes were tutored. Nine of the ten students correctly solved the three problems after being tutored for an average of 116 minutes. ARPHY's pedagogical parameters stabilized after 6.3 students. The remaining students, each from a different class, were tutored, allowing ARPHY to self-improve, resulting in a new tutorial strategy after each session. It is recommended that future research into intelligent tutoring systems for science incorporate the principles and theories of learning which this research was based upon. An authoring system based upon the control structure of ARPHY should be developed, since the modular design of this system will allow any field which can be organized into a net-archy of problems, principles, and concepts, to be tutored.
Design experiments: Theoretical and methodological challenges in creating complex interventions in c

The lion's share of my current research program is devoted to the study of learning in the blooming, buzzing confusion of inner-city classrooms. My high-level goal is to transform grade-school classrooms from work sites where students perform assigned tasks under the management of teachers into communities of learning (Bereiter & Scardarnalia, 1989; Brown & Campione, 1990) and interpretation (Fish, 1980), where students are given significant opportunity to take charge of their own learning. In my current work, I conduct what Collins (in press) refers to as design experiments, modeled on the procedures of design sciences such as aeronautics and artificial intelligence. As a design scientist in my field, I attempt to engineer innovative educational environments and simultaneously conduct experimental studies of those innovations. This involves orchestrating all aspects of a period of daily life in classrooms, a research activity for which I was not trained. My training was that of a classic learning theorist prepared to work with "subjects" (rats, children, sophomores), in strictly controlled laboratory settings. The methods I have employed in my previous life are not readily transported to the research activities I oversee currently. In Figure 1, I illustrate the critical aspects of my current classroom research. Central to the enterprise is that the classroom must function smoothly as a learning environment before we can study anything other than the myriad possible ways that things can go wrong. Classroom life is synergistic: Aspects of it that are often treated independently, such as teacher training, curriculum selection, testing, and so forth actually form
Wideband spectrum sensing techniques for wireless sensors

The limited availability of radio frequency spectrum demands for more efficient ways to utilize it in future wireless networks. Spectrum sharing radios are an interesting solution to the spectral scarcity problem, where the available resources are adaptively used across time and frequency without affecting other user's transmissions. In this context, sensing the spectrum for its occupancy is needed to increase the awareness among technologies that share the same spectrum. In a typical wireless sensor network, each node senses and transmits data constrained by a very low power budget. At the same time, they should be capable of finding a free frequency channel with minimal latency. A solution to this problem is to make radios capable of sensing multiple frequency bands, in the order of a few hundred MHz, all at once. The technical challenge lies in the design of low-complexity wideband spectrum sensing techniques that increase context awareness at the wireless node. In this thesis, we address this problem with two approaches. The first approach is based on Compressed Sampling (CS) theory, where a new perspective is taken, different to conventional methods that estimate the spectrum and perform detection on the reconstructed spectrum. Instead a direct detection is performed on the sub-Nyquist rate sampled wideband signal. In the second part of this thesis, an alternative approach to reduce the power at an architectural level is proposed, by avoiding the Nyquist rate wideband Analog-to-Digital Converter (ADC) and pushing the conventional digital processing to the analog domain.
Extractive Based Single Document Text Summarization Using Clustering Approach

Text summarization is an old challenge in text mining but in dire need of researcher’s attention in the areas of computational intelligence, machine learning and natural language processing. We extract a set of features from each sentence that helps identify its importance in the document. Every time reading full text is time consuming. Clustering approach is useful to decide which type of data present in document. In this paper we introduce the concept of k-mean clustering for natural language processing of text for word matching and in order to extract meaningful information from large set of offline documents, data mining document clustering algorithm are adopted.
Lexical Semantics and Auditory Presentation in Virtual Storytelling Research paper for the ICAD05 workshop "Combining Speech and Sound in the User Interface"

Audio presentation is an important modality in virtual storytelling. In this paper we present our work on audio presentation in our intelligent multimodal storytelling system, CONFUCIUS, which automatically generates 3D animation speech, and non-speech audio from natural language sentences. We provide an overview of the system and describe speech and non-speech audio in virtual storytelling by using linguistic approaches. We discuss several issues in auditory display, such as its relation to verb and adjective ontology, concepts and modalities, and media allocation. Finally we conclude that introducing linguistic knowledge provides more intelligent virtual storytelling, especially in audio presentation.
Tips for Teaching Pronunciation: A Practical Approach

Introduction: Teaching Pronunciation Chapter 1 Word Stress Chapter 2 Rhythm Chapter 3 Intonation Chapter 4 Consonants Chapter 5 Vowels Appendix A Activity Worksheets Appendix B Problems of Specific Language Groups Appendix C Stress and Suffixes Appendix D Diagnostic Test Appendix E Recording a Sound File Glossary Bibliography Name Index Subject Index
Desktop Database Marketing

"Desktop Database Marketing is a masterful work that belongs on every business bookshelf. Jack Schmid and Alan Weber have succeeded in applying the KISS principle to database marketing in a way that removes the mystique and releases the power without prejudice to size of business. "­­Bob Stone Chairman Emeritus Stone & Adler, Inc. "Database marketing is what direct marketing is all about these days­­and it's going to be even more important in future years. Jack Schmid and Alan Weber have put together a really useful book on this subject, and I highly recommend it. "­­David W. Florence Chairman Direct Media, Inc. "Finally, someone has put together a book that not only shows you what you ought to be doing with your database, but how to do it. It's full of examples that reveal how to apply the principles of customer marketing to nearly any business. And it offers a virtual toolkit of ways for every marketer to have data at their fingertips. In Desktop Database Marketing, Jack Schmid and Alan Weber have produced a winner. "­­Ron Jacobs President Jacobs & Clevenger, Inc. "Schmid and Weber have put together a book easy to read . easier to understand . easier yet to use. I plan on using it. "­­Ray Jutkins Speaker/Marketing Consultant "Lean. No fat. The most practical guide I have seen so far. "­­Jimmy Cygler President RESOLVE! SYSTEMAS Sao Paulo, Brazil "Any time Jack Schmid or Alan Weber offers to write an article for Target Marketing, the editors and I jump at the opportunity and take it sight unseen. Both of them have the unique ability to take highly technical, complex ideas and make them easily understandable­­and instantly usable­­for the expert and non-expert alike. Desktop Database Marketing is a gem. "­­Denny Hatch Editor Target Marketing and Who's Mailing What! Table of contents The World of Database Marketing * Setting Up Your Day-to-Day Database Operations * Developing Your Database Strategy * Managing Your Database * Case Studies
Designing Web based training: how to teach anyone anything anywhere anytime

FAQ About This Book. Meet Web-Based Training. Evaluate WBT. Pick an Approach. Build the Framework. Organize Learning Sequences. Activate Learning. Test and Exercise Learning. Promote Collaboration. Teach in the Virtual Classroom. Motivate Learners. Go Global. Overcome Technical Hurdles. Venture Beyond Courses. Contemplate the Future. References. Index.
The Analysis of Nominal Compounds

Abstract : If one surveys the standard representational techniques for natural language that have evolved in linguistics and artificial intelligence. It is difficult to find much uniformity in the theories proposed. Distinctions are made between linguistic performance and linguistic competence, syntactic regularities and conceptual content, formal semantics and processes of common-sense inference, structural models and process models. An innocent bystander could easily come to the conclusion that the study of language is both ill-defined and lacking in systematic research methodologies. The whole business is rather reminiscent of the three blind men who conclude that an elephant is like a tree, a snake, or a wall: what you find depends a lot on where you poke around. The authors interest in language as a vehicle for communication. He is concerned with the conceptual content of sentences and the cognitive processes that extract conceptual content from a text or a discourse. These processes must be described in terms of human memory models and concerns for psychological validity or at least a healthy respect for psychological plausibility. He conducts my research by writing computer programs that simulate language processing behavior.
A MapReduce Construct for Yap Prolog

This work’s aim was to design and implement a high-level Prolog primitive, based on the MapReduce programming paradigm. MapReduce is a programming model made popular by Google in 2008, even though its origins are more remote. It is composed by two simple operations, map and reduce, which can easily be applied to numerous algorithms. On the other hand, Prolog is a firstorder logic predicate language with significant declarative power. This allowing the programmer to focus on the resolution strategies for a problem in preference to the execution technicalities. Prolog is also especially suited for data storage and processing; in fact, ILP deals with making inferences from that data. A MapReduce construct applied in these circumstances would be able to efficiently scale that process and thus significantly reduce execution times. Including a MapReduce programming primitive in Prolog has three major benefits: (i) to make available a high-level abstract construct which implements the MapReduce functional model maintaining the declarative nature of the programs; (ii) to give access to a previously non-existent Prolog construct which is relevant to applications in numerous fields of knowledge; (iii) to allow for parallelism, thus speeding-up the execution of programs using this construct. The latter is particularly relevant now that multicore processors have become the favourite choice to assemble machines, even those for personal use. This, along with the fact that there are increasingly larger data processing requirements in everyday life, renders a framework using multicore architectures for efficient data processing highly relevant. MapReduce for Prolog’s focus are multicore architectures, but our primitive supports hybrid environments (shared and distributed memory), implicitly and transparently. MapReduce for Prolog was implemented in the Yap system and it follows a master-slave paradigm, in which the master is responsible for dividing and assigning the work and the slaves for processing the chunks dispatched to them. This construct’s interface has various customisation levels, and our aim is that it will come to integrate the Yap Prolog system as built-in construct. Our system was successfully tested using four distinct applications common in the literature: two of these were numeric, and the other two were composed of Prolog terms. The test were made using two implementations for the same programming interface, one for a cluster of machines and another for a multicore architecture. It was determined that our construct scaled almost ideally for these datasets, both in shared and distributed memory. Four scheduling methods were also developed and assessed, and the two more efficient ones will be made available in the final version of the library. An evaluation of the effect of the chunk size variation for different datasets and scheduling methods was performed as well, in order to define standard parameters for MapReduce for Prolog.
Discrete-time process algebra

Interpretation and Partition Refinement for Model Checking D. R. Dams Faculty of Mathematics and Computing Science, TUE, 1996-13 Topological Dualities in Semantics M. M. Bonsangue Faculty of Mathematics and Computer Science, VUA, 1996-14 Algorithms for Graphs of Small Treewidth B. L. E. de Fluiter Faculty of Mathematics and Computer Science, UU, 1997-01 Process-algebraic Transformations in Context W. T. M. Kars Faculty of Computer Science, UT, 1997-02 A Generic Theory of Data Types P. F. Hoogendijk Faculty of Mathematics and Computing Science, TUE, 1997-03 The Evolution of Type Theory in Logic and Mathematics T. D. L. Laan Faculty of Mathematics and Computing Science, TUE, 1997-04 Preservation of Termination for Explicit Substitution C. J. Bloo Faculty of Mathematics and Computing Science, TUE, 1997-05 Discrete-Time Process Algebra J. J. Vereijken Faculty of Mathematics and Computing Science, TUE, 1997-06
SmartDocs: Document Management Inovation

In 2001 the first version of MoReq, a requirements specification for records management system (RMS), was made available online. With the introduction and spread of MoReq in Europe the RMS’s consumers started to consider its compliance a demand, leaving a problem for suppliers with products already developed: how to evaluate their software based on MoReq and what developments are necessary to meet its requirements. In this dissertation we propose a process for evaluating content management systems, class of systems where the RMS fall, according to a requirements specification as MoReq. To achieve the final results we studied and applied techniques for evaluating software in an already developed document management system (SmartDocs) who wants to evolve to a system in full compliance with the requirements of MoReq2, the second version of MoReq.
Development of automated system based on neural network algorithm for detecting defects on molds installed on casting machines

During the casting of light alloys and ligatures based on aluminum and magnesium, problems of the qualitative distribution of the metal and its crystallization in the mold arise. To monitor the defects of molds on the casting conveyor, a camera with a resolution of 780 x 580 pixels and a shooting rate of 75 frames per second was selected. Images of molds from casting machines were used as input data for neural network algorithm. On the preparation of a digital database and its analytical evaluation stage, the architecture of the convolutional neural network was chosen for the algorithm. The information flow from the local controller is transferred to the OPC server and then to the SCADA system of foundry. After the training, accuracy of neural network defect recognition was about 95.1% on a validation split. After the training, weight coefficients of the neural network were used on testing split and algorithm had identical accuracy with validation images. The proposed technical solutions make it possible to increase the efficiency of the automated process control system in the foundry by expanding the digital database.
Text-Independent Speaker Identification Utilizing Likelihood Normalization Technique

SUMMARY In this paper we describe a method, whichallows the likelihood normalization technique, widely used forspeaker veriﬁcation, to be implemented in a text-independentspeaker identiﬁcation system. The essence of this method is toapply likelihood normalization at frame level instead of, as it isusually done, at utterance level. Every frame of the test utter-ance is inputed to all the reference models in parallel. In thisprocedure, for each frame, likelihoods from all the models areavailable, hence they can be normalized at every frame. A specialkind of likelihood normalization, called Weighting Models Rank,is also experimented. We have implemented these techniques inspeaker identiﬁcation system based on VQ-distortion codebooksor Gaussian Mixture Models. Evaluation results showed thatthe frame level likelihood normalization technique gives higherspeaker identiﬁcation rates than the standard accumulated like-lihood approach.key words: speaker identiﬁcation, likelihood normalization,frame level processing
Personalized Concept Oriented Search Engine with User Profiling and Result Preference Based on Lucene

– The fundamental component of any personalization application is user profiling. A good user profiling strategy is an essential and fundamental component in search engine personalization. Evaluating user preferences of web search results is crucial for search engine development, deployment and maintenance. This paper focuses on search engine personalization and concept-based user profiling that are based on both positive and negative preferences of the users. The underlying idea of our proposed system is based on concepts and their relations extracted from the submitted queries, the Web-snippets and the click through data. Incorporating user behaviors data can significantly improve ordering of top results in web searching. The relationships between users can be mined from the concept-based user profiles to perform collaborative filtering.This allows users with the same interests to share their profiles.Finally,the concept-oriented user profiles can be integrated into the ranking algorithms of search engine so that search results can be ranked according to individual user’s interest .