Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperation using a robotic ad hoc network made from Bluetooth, JXTA, OSGi and other commercial off the shelf (COTS) products

Abstract - Mobile devices in the near future will need to collaborate to fulfill their function. Collaboration will be done by communication. We use a real world example of robotic soccer to come up with the necessary structures required for robotic communication. A review of related work is done and it is found no examples come close to providing a RANET. The robotic ad hoc network (RANET) we suggest uses existing structures pulled from the areas of wireless networks, peer to peer and software life-cycle management. Gaps are found in the existing structures so we describe how to extend some structures to satisfy the design. The RANET design supports robot cooperation by exchanging messages, discovering needed skills that other robots on the network may possess and the transfer of these skills. The network is built on top of a Bluetooth wireless network and uses JXTA to communicate and transfer skills. OSGi bundles form the skills that can be transferred. To test the nal design a reference implementation is done. Deficiencies in some third party software is found, specifically JXTA and JamVM and GNU Classpath. Lastly we look at how to fix the deciencies by porting the JXTA C implementation to the target robotic platform and potentially eliminating the TCP/IP layer, using UDP instead of TCP or using an adaptive TCP/IP stack. We also propose a future areas of investigation; how to seed the configuration for the Personal area network (PAN) Bluetooth protocol extension so a Bluetooth TCP/IP link is more quickly formed and using the STP to allow multi-hop messaging and transfer of skills.
A neural learning classifier system with self-adaptive constructivism

For artificial entities to achieve true autonomy and display complex life-like behaviour they will need to exploit appropriate adaptable learning algorithms. In this sense adaptability implies flexibility guided by the environment at any given time and an open-ended ability to learn appropriate behaviours. We examine the use of constructivism-inspired mechanisms within a neural learning classifier system architecture, which exploits parameter self-adaptation as an approach to realise such behaviour. The system uses a rule structure in which each is represented by an artificial neural network. It is shown that appropriate internal rule complexity emerges during learning at a rate controlled by the learner and that the structure indicates underlying features of the task. Results are presented in Markov, nonstationary and nonMarkov simulated mazes.
RECONFIGURABLE ANTENNA PROCESSING WITH MATRIX DECOMPOSITION USING FPGA BASED APPLICATION SPECIFIC INTEGRATED PROCESSORS

An amine-boron composition for catalyzing the urethane reaction, particularly in preparing a polyurethane foam, consisting essentially of the addition product of a tertiary amine and a boron compound of the formula RnB(OH)3-n where n=0 or 1, and R=C1-C8 alkyl, C5-C8 cycloalkyl or C6-C10 aryl. Preferred catalysts are prepared by mixing triethylenediamine or 3-quinuclidinol with boric acid.
Navigating through geometry in prekindergarten-grade 2

Focusing on the important ideas of geometry, this book shows how to investigate two- and three-dimensional shapes with very young students. It introduces methods to describe location and position, explores simple transformations and addresses visualisation, spatial reasoning and the building and drawing of constructions. Activities in each chapter pose questions that stimulate students to think more deeply about mathematical ideas. The CD-ROM features fourteen articles from NCTM publications. The supplemental CD-ROM also features interactive electronic activities, master copies of activity pages for students and additional readings for teachers.
Intervention Research: Developing Social Programs

1. What is Intervention Research 2. Stages in Intervention Research 3. Step 1: Specify the Problem and Develop a Program Theory 4. Step 2: Create and Revise Program Materials 5. Step 3 & Step 4: From Refining Program Components to Testing Effectiveness 6. Step 5: Dissemination of Findings and Program Materials 7. Challenges in Intervention Research Appendix Glossary References
Landslide Susceptibility Assessment using Skyline Operator and Majority Voting

Landslide susceptibility assessment is the problem of determining the likelihood of a landslide to occur in a particular area based on the geological and morphological properties of the area. In this study we propose a method wherein skyline operator is used to model landslides and majority voting is used to assess landslide susceptibility. Experiments conducted on a real life data set show that the proposed method achieves 83.07% classification accuracy and is superior over logistic regression, support vector machine and neural network based approaches and achieves similar results when compared to a decision trees-based model.
Rule-Based Morphological Processing in a Second Language: A Behavioural Investigation

According to dual-system accounts of English past-tense processing, regular forms are decomposed into their stem and affix (played=play+ed) based on an implicit linguistic rule, whereas irregular forms (kept) are retrieved directly from the mental lexicon. In second language (L2) processing research, it has been suggested that L2 learners do not have rule-based decomposing abilities, so they process regular past-tense forms similarly to irregular ones (Silva & Clahsen 2008), without applying the morphological rule. The present study investigates morphological processing of regular and irregular verbs in Greek-English L2 learners and native English speakers. In a masked-priming experiment with regular and irregular prime-target verb pairs (playedplay/kept-keep), native speakers showed priming effects for regular pairs, compared to unrelated pairs, indicating decomposition; conversely, L2 learners showed inhibitory effects. At the same time, both groups revealed priming effects for irregular pairs. We discuss these findings in the light of available theories on L2 morphological processing.
Extending the Wizard of Oz Technique for Multimodal Language-enabled Systems

In this paper we present a proposal for extending the standard Wizard of Oz experimental methodology to language-enabled multimodal systems. We first discuss how Wizard of Oz experiments involving multimodal systems differ from those involving voice-only systems. We then go on to discuss the Extended Wizard of Oz methodology and the Wizard of Oz testing environment and protocol that we have developed. We then describe an example of applying this methodology to Archivus, a multimodal system for multimedia meeting retrieval and browsing. We focus in particular on the tools that the wizards would need to successfully and efficiently perform their tasks in a multimodal context. We conclude with some general comments about which questions need to be addressed when developing and using the Wizard of Oz methodology for testing multimodal systems.
Algorithms for Wireless Communication and Sensor Networks

In this thesis we will address four problems concerned with algorithmic issues that arise from communication and sensor networks. The problem of scheduling wireless transmissions under SINR constraints has received much attention for unicast (one to one) transmissions. We consider the scheduling problem for multicast requests of one sender to many receivers, and present a logarithmic approximation algorithm and an online lower bound for arbitrary power assignments. We study the problem of maximising the lifetime of a sensor network for fault-tolerant target coverage in a setting with composite events, where a composite event is the simultaneous occurrence of one or more atomic events. We are the first to study this variation of the problem from a theoretical perspective, where each event must be covered twice and there are several event types, and we present a (6 + ε)-approximation algorithm for the problem. The online strongly connected dominating set problem concerns the construction of a dominating set that is strongly connected at all times, and for every vertex not in the dominating set, there exists an edge to some vertex in the dominating set, and an edge from a vertex in the dominating set. We present a lower bound for deterministic online algorithms and present an algorithm that achieves competitive ratio matching the lower bound. The monotone barrier resilience problem is to determine how many sensors must be removed from a sensor network, such that a monotone path can exist between two points that does not intersect any sensor. We present a polynomial time algorithm that can determine the monotone barrier resilience for sensor networks of convex pseudo-disks of equal width.
An LR parser-based probabilistic language model for spoken language systems

Language models are an important component of modern spoken language systems. A major function of these language models is to provide constraints for the speech recognition process, reducing the recognition error rate. These constraints include both local word co-occurrence constraints and non-local syntactic constraints. In addition, language models produce semantic interpretations of spoken utterances for speech understanding. In many current systems, these functions are split among multiple language models; one model to apply local constraints during lexical access, another, used as a post-processor, to provide non-local constraints and generate semantic interpretations. The goal of this work is to develop a language model which can provide both local and long-distance language constraints and which can be efficiently integrated into lexical access search algorithms. This thesis presents a probabilistic language model, the PLR language model, which uses an LR parser to map sentence prefixes into equivalence classes. These classes are used to compute next-word probabilities for speech recognition. The model combines the ability to apply long-distance syntactic constraints and the ability to acquire co-occurrence information from a corpus of training data. The PLR model generalizes the familiar n-gram models and reduces to these models in the absence of grammatical knowledge. This thesis introduces the PLR model and investigates its relationship to other probabilistic language models. The model is evaluated in two different spoken language system domains. Among the issues addressed are: the performance of the PLR model in speech recognition and understanding tasks, the full integration of the PLR language model with lexical access, and the development of a language model with 100% coverage of the task domain from a grammar-based model with incomplete coverage. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Ant colony algorithm for multi-criteria job shop scheduling to minimize makespan, mean flow time and mean tardiness

Abstract In the real world situation many scheduling problems faced by decision maker are involved more than one aspect and therefore multiple criteria analysis is required. This paper presents ant colony algorithm for solving the multi-objective Job Shop Scheduling Problem (JSP). The objectives considered in this study include the minimization of makespan, mean flow time, and mean tardiness. The proposed algorithm is tested on many benchmark problems up to 15 jobs × 10 machine. The results obtained have shown that the proposed algorithm is a feasible and effective approach for the multiple-objective problem.
Stability investigation of the cascade two-stage PFC converter

A stability of the cascade two-stage power-factor-correction converter is investigated. The first stage is boost PFC converter to achieve a near unity power factor and the second stage is forward converter to regulate the output voltage. In this issue, low-frequency instability is detected for some operating conditions that can not be detected by the prior linear models. Therefore, nonlinear model is proposed to detected and explain these instabilities. The borderlines between stable and unstable operation is made clear. It is cleared that feedback gain of the first stage PFC and the second stage DC/DC converters are large contribution parts of the total system stability.
Hierarchical task analysis

PART ONE: Introduction to Hierarchical Task Analysis 1. Introduction 2. HTA- A Description of Method 3. Plans the Key to Describing Task Complexity 4. How to Analyse Tasks Using HTA 5. HTA in Different Work Domains 6. Recording the Analysis PART TWO: Application 7. Articulating the Task 8. Team and Job Design 9. Human Resource Issues 10. Interface Design 11. Developing Documentation 12. Training Design and Development 13. Human Error Analysis 14. Integrating Solutions 15. Evaluating the System 16. Managing a Task Analysis Project 17. HTA as a Human Factors Framework Description of Method
PEDESTRIAN GAP-ACCEPTANCE

RESEARCH WAS CONDUCTED TO INVESTIGATE THE GAP ACCEPTANCE OF PEDESTRIANS AT AN UNMARKED MIDBLOCK CROSSING. DATA WERE COLLECTED BY MEANS OF TIME-LAPSE PHOTOGRAPHY AND ANALYZED WITH THE AID OF A PHOTO-OPTICAL DATA ANALYZER. STATISTICAL TESTS, SUCH AS THE KOLMOGOROV-SMIRNOV TEST, THE CHI-SQUARE TEST, AND ANALYSIS OF VARIANCE, WERE UTILIZED TO INVESTIGATE THE RELATIONSHIP BETWEEN SIZE OF GAP ACCEPTED AND VARIOUS FACTORS SUCH AS TIME WAITED AT CURBSIDE, VOLUME OF TRAFFIC, NUMBER OF PERSONS WAITING AT CURBSIDE, SPEED OF APPROACHING VEHICLE, AND WALKING SPEED OF THE PEDESTRIAN. SOME CONCLUSIONS DRAWN FROM THE RESULTS OF THE TESTS ARE THAT FEMALE PEDESTRIANS WERE WILLING TO WAIT LONGER AT CURBSIDE FOR A SUITABLE GAP THAN WERE MALE PEDESTRIANS; MALE PEDESTRIANS ACCEPTED SHORTER GAPS THAN DID FEMALE PEDESTRIANS; THE MINIMUM ACCEPTABLE GAP IN A SINGLE STREAM OF TRAFFIC WAS 3 SEC OR 75 FT; SHORTER GAPS WERE ACCEPTED BY GROUPS OF PEDESTRIANS RATHER THAN BY INDIVIDUALS; AND INDIVIDUAL PEDESTRIANS CROSSED THE ROADWAY AT GREATER WALKING SPEEDS THAN DID GROUPS OF PEDESTRIANS. /AUTHOR/
A MODEL FOR TRAFFIC SIMULATION

The impairment to man and environment by a steadily increasing traffic volume requires concrete solutions now more urgently than ever before. This problem can, however, only be coped with from a scientific point of view, when founded knowledge exists of the very complex interconnections of the system called 'traffic'. Regarding the enormous costs of experimental investigations undertaken to influence traffic purposefully, the significance of theoretical considerations prior to necessary field-tests can easily be seen. This paper will not only illustrate the development of such a model of traffic simulation, but also show first results thereof.
Conceptual-Intentional bootstrapping in the acquisition of the English verb

In the thesis I argue that intentionality, infant subjective knowledge and metacognitive growth, all interact to constrain and focus language acquisition to an inevitable and successful outcome. Neither innate UG, nor emergent usage based theories adequately address these elements and the literature review reveals that some or all them are either assumed, side-lined or left unconsidered by standard bootstrapping hypotheses. When foregrounded however, these elements can be demonstrated to provide a bridge between the conceptual and syntactic systems. I show that initially, infants’ utterances focus on the ‘here-and-now’ in joint attention, and they express infant subjective knowledge about how dynamic properties are attributive of substantive objects/entities. Uses of apparent nominal and verbal forms lack their typical grammatical function. Infants around 18months old, experience an inherent meta-cognitive development, which enables them to collate representations of Manifest Events, alongside a contrasting, constructed representation of a desired or intentional state of affairs. These Complex Events involve sub-events which are not currently in shared attention. Associated utterances involve intentions and desires, which require them to be understood by others. The acquisition of a conventional means of expression is therefore paramount. The research presents three sets of corpus studies based on 22,000 infant utterances, and includes exemplification from diary evidence, to show the inevitable bootstrapping effect of such intentional utterances. Complex Events require a predicate that describes an intentional state change and also a means to refer to a theme object that ‘measures out’ the change. In effect, it requires the use of Verbs and DPs. In contrast to other theories I show that it is only Complex Events that are the locus for the advent of grammatical categories [V] and [DP] and that a surprisingly simple, minimalist Merge process licensed by a selectional feature afforded by ‘it’, effectively bootstraps the syntactic system for English.
A comparison of concurrent programming and cooperative multithreading under load balancing applications

Two models of thread execution are the general concurrent programming execution model (CP) and the cooperative multithreading execution model (CM). CP provides nondeterministic thread execution where context switches occur arbitrarily. CM provides threads that execute one at a time until they explicitly choose to yield the processor. This paper focuses on a classic application to reveal the advantages and disadvantages of load balancing during thread execution under CP and CM styles; results from a second classic application were similar. These applications are programmed in two different languages (SR and Dynamic C) on different hardware (standard PCs and embedded system controllers). An SR‐like run‐time system, DesCaRTeS, was developed to provide interprocess communication for the Dynamic C implementations. This paper compares load balancing and non‐load balancing implementations; it also compares CP and CM style implementations. The results show that in cases of very high or very low workloads, load balancing slightly hindered performance; and in cases of moderate workload, both SR and Dynamic C implementations of load balancing generally performed well. Further, for these applications, CM style programs outperform CP style programs in some cases, but the opposite occurs in some other cases. This paper also discusses qualitative tradeoffs between CM style programming and CP style programming for these applications. Copyright © 2004 John Wiley & Sons, Ltd.
Large-scale Structural Reranking for Hierarchical Text Categorization

Current hierarchical text categorization (HTC) methods mainly fall into three directions: (1) Flat one-vs.-all approach, which flattens the hierarchy into independent nodes and trains a binary one-vs.-all classifier for each node. (2) Top-down method, which uses the hierarchical structure to decompose the entire problem into a set of smaller sub-problems, and deals with such sub-problems in top-down fashion along the hierarchy. (3) Big-bang approach, which learns a single (but generally complex) global model for the class hierarchy as a whole with a single run of the learning algorithm. These methods were shown to provide relatively high performance in previous evaluations. However, they still suffer from two main drawbacks: (1) relatively low accuracy as they disregard category dependencies, or (2) low computational efficiency when considering such dependencies. In order to build an accurate and efficient model we adopted the following strategy: first, we design advanced global reranking models (GR) that exploit structural dependencies in hierarchical multi-label text classification (TC). They are based on two algorithms: (1) to generate the k-best classification of hypotheses based on decision probabilities of the flat one-vs.-all and top-down methods; and (2) to encode dependencies in the reranker by: (i) modeling hypotheses as trees derived by the hierarchy itself and (ii) applying tree kernels (TK) to them. Such TK-based reranker selects the best hierarchical test hypothesis, which is naturally represented as a labeled tree. Additionally, to better investigate the role of category relationships, we consider two interesting cases: (i) traditional schemes in which node-fathers include all the documents of their child-categories; and (ii) more general schemes, in which children can include documents not belonging to their fathers. Second, we propose an efficient local incremental reranking model (LIR), which combines a top-down method with a local reranking model for each sub-problem. These local rerankers improve the accuracy by absorbing the local category dependencies of sub-problems, which alleviate the errors of top-down method in the higher levels of the hierarchy. The application of LIR recursively deals with the sub-problems by applying the corresponding local rerankers in top-down fashion, resulting in high efficiency. In addition, we further optimize LIR by (i) improving the top-down method by creating local dictionaries for each sub-problem; (ii) using LIBLINEAR instead of LIBSVM; and (iii) adopting the compact representation of hypotheses for learning the local reranking model. This makes LIR applicable for large-scale hierarchical text categorization. The experimentation on different hierarchical datasets has shown promising enhancements by exploiting the structural dependencies in large-scale hierarchical text categorization.
Usability of Wearable and Desktop Game-Based Simulations: A Heuristic Evaluation

Abstract : The use of simulators based on game software has the potential to deliver effective training. However, simulators with usability problems can interfere with training by presenting unwanted distractions. This report describes an assessment of the usability of a wearable computer system which has been designed to interface with a virtual environment and which can be used for simulator training. Usability of the wearable system was compared with that of a more common desktop interface in a game-based virtual environment. Eight evaluators conducted a heuristic usability evaluation of the wearable system and desktop interfaces. They identified 24 usability concerns with the wearable system and desktop interfaces, and the virtual environment. The majority of the concerns (46%) were with the virtual environment. Forty-two percent of the concerns were related to the wearable system, and the remaining 12% dealt with the desktop interface. However, when the frequency, impact, and persistence scores were aggregated into an overall score, the wearable system had the poorest usability. Eight of the ten greatest usability concerns were related to the wearable system. These data suggest that the virtual environment is more usable with the desktop interface than the wearable system.