Miracle-dz/UniFAR-FTUs huggingface dataset:
A 1.2 V 500 MHz 32-bit carry-lookahead adder

In this paper a 1.2 V 32-bit carry lookahead adder is proposed for high speed, low voltage applications. The proposed new 32-bit adder uses Non-full Voltage Swing True-Single-Phase-Clocking Logic (NSTSPC) to implement the proposed carry lookahead adder. Because the internal node of NSTSPC was non-full swing, its operation speed would be higher than the conventional TSPC. Moreover, the supply voltage for the new adder is 1.2 V, thus the power dissipation would also be reduced. The 32-bit CLA adder using 0.35 /spl mu/m 1P4M CMOS technology with 1.2 V power supply could be operated at a 500 MHz clock frequency.
What Kind of Information does an HCI expert want

Working with usability techniques, with focus on how a given technique enables data capture made us ask the question: What kind of information is it an HCI expert want from the user when conducting a usability test? We answer the question by discussing two techniques both relying on concurrent data. Think Aloud is one of the most frequently used techniques and almost an institution in itself. Eye-tracking is new in usability testing and still at an experimental level in HCI. We reflect critically upon the two obtrusive techniques. We discuss the usability of concurrent data capture, suggesting participatory analysis and retrospective verbalisation as a possible step in usability testing.
A connectionist approach to direct dynamic programming control

Direct dynamic programming controllers can be constructed with artificial neurons. Doing so facilitates the storage of content-addressable dynamic programming cost values only in regions of the state space that are actually passed through during control of the plant, thereby reducing total memory usage. Further, by connecting the neurons in different ways, neighboring states can be amalgamated together and treated uniformly. This gain reduces the overall memory requirement of the direct dynamic programming controller and can also reduce its learning time by facilitating generalization. A number of experiments with such neural networks designs are described, along with a particularly promising design that has emerged from this research. This new approach, transition point dynamic programming, operates by placing neurons only at states where a change in the control signals is required. <<ETX>>
Combining the Kohonen Self-Organizing Map and K-Means for On-Line Classification of Sensordata

Many devices, like mobile phones, use contextual profiles like in the car or in a meeting to quickly switch between behaviors. Achieving automatic context detection, usually by analysis of small hardware sensors, is a fundamental problem in human-computer interaction. However, mapping the sensor data to a context is a difficult problem involving near real-time classification and training of patterns out of noisy sensor signals. This paper proposes an adaptive approach that uses a Kohonen Self-Organizing Map, augmented with on-line k-means clustering for classification of the incoming sensor data. Overwriting of prototypes on the map, especially during the untangling phase of the Self-Organizing Map, is avoided by a refined k-means clustering of labeled input vectors.
Parallel k-Way Partitioning Approach for Large Graphs

With the emergence of large social networks, such as Facebook and Twitter, graphs with millions to billions vertices are common. Instead of processing the network within a single machine, all the applications related are intended to be done in a distributed way using a cluster of commodity machines. In this paper, we study the parallel graph partitioning problem, which is the fundamental operation for large graphs. With the help of Hadoop/MapReduce, we propose a parallel k-way partitioning approach. Unlike the previous ones, which require enough memory to keep the whole graph data within, our novel approach breaks such limitations. Also, due to the distributed nature, it is easy to integrate our partitioning approach into existed parallel platforms. We conduct extensive experiments on real graphs and synthetic graphs. All the experimental results prove the effectiveness and efficiency of our approach.
Statistical Analysis of The Most Popular Software Service Effort Estimation Datasets

Considering the complex nature of software projects, we have to use historical data and past experiences to execute them better. In previous years, a large number of software engineering datasets were introduced for different purpose. One of the important groups among these datasets is the use of software effort estimation repositories as a framework for analyzing diverse methods and models of estimation. In recent decades, researchers have worked on the different types of these datasets for various purposes and have tried to find the features of each one. DPS, ISBSG, Desharnais, Maxwell, and CF are among the most popular of these datasets. Insufficient or unstructured documentation causes problems for researchers in recognizing and working with datasets that are suitable for their purposes. This article intends to perform a thorough statistical analysis of the five the most popular datasets for software effort estimation to provide researchers with useful information and to help them select the appropriate repositories. In this paper, a thorough statistical analysis of software effort datasets is performed, and sufficient explanations are offered so that researchers have better options for their particular purposes. It is suggested that software engineering community should be aware of and account for the software effort dataset related issues when evaluating the validity of research outcomes
Hybrid Multicast and Segment‐Based Caching for VoD Services in LTE Networks

This paper proposes a novel video delivery scheme that reduces the bandwidth consumption cost from a video server to terminals in Long‐Term Evolution networks. This proposed scheme combines optimized hybrid multicast with a segment‐based caching strategy for use in environments where the maximum number of multicast channels is limited. The optimized hybrid multicast, allocation of multicast channels, and cache allocation are determined on the basis of a video's request rate, the related video's length, and the variable cost per unit size of a segment belonging to the related video. Performance evaluation results show that the proposed scheme reduces a video's delivery costs. This work is applicable to on‐demand TV services that feature asynchronous video content requests.
Conversations about absence and presence: Re-membering a loved partner in poetic form

iii Acknowledgements.v Preface: The Story bridges collection . vi Table of contents . lii List of tables . lviii List of figures . lix Chapter One: Locations . 1 1.1 Entry points.1 1.2 Rationale . 2 1.3 Locating the research . 3 1.4 Locating the researcher . 4 Therapist.5 Poet . 6 Researcher . 7 1.5 Outline of the thesis . 8 1.6 Reading the Story bridges collection . 9 Chapter Two: Conceptual frameworks.11 2.1 Research . 11 Qualitative research in a poststructuralist key . 11 Repositioning researcher power/knowledge . 13 Poststructuralist ideas as shaping the research processes . 14 Poststructuralist ideas as shaping the research concepts . 15 2.2 Practice . 19 A story of narrative therapy . 19 Deconstructing discourses . 20 Retellings . 21 Dialogism in retellings . 22 Narrative therapy as a three-act play . 27 Literary approaches in narrative therapy.29 Rescued speech poetry . 30
Tibidabo: a syntactically and semantically annotated corpus of Spanish

In this paper, I discuss the theoretical and practical issues raised in the development of Tibidabo, a syntactically and semantically annotated corpus of Spanish, which has been developed using the DELPH-IN corpus annotation environment and the HPSG-based grammar, SRG. I describe in detail the linguistic analysis that Tibidabo provides, focussing on various syntactic phenomena that are frequently discussed in the literature and consider alternative analyses proposed in the HPSG literature and in AnCora, another Spanish Treebank.22This work was funded by the Ramon y Cajal programme of the Spanish Ministerio de Ciencia e Innovacion.
A fast-acquisition demodulation scheme for 2.4 GHz wireless DSSS transceiver VLSI

In this paper, a CMOS cell based system VLSI design for Direct-Sequence Spread-Spectrum (DSSS) wireless LAN transceiver is presented. In addition, an efficient and fast-acquisition demodulation scheme is proposed to use in the receiver architecture. Implementation and testing results are also given. The proposed demodulation scheme can help to positively combine the received signal energy of multipaths so that the detection performance is improved by 3 dB in a typical frequency-selective indoor wireless communication environment. The proposed architecture can synchronize the PN code in 30 /spl mu/s and the chip size is 5600/spl times/4600 /spl mu/m/sup 2/. It can be operated from 3.3 V to 5 V and the power consumption ranges from 189 mW to 250 mW respectively.
French patterns for expressing concept relations

Researchers who are developing tools for extracting conceptual information automatically from corpora require inventories of linguistic patterns that can be incorporated into their toolsets. While several inventories of English patterns exist, almost none have been published for French. This paper provides an inventory of French linguistic patterns that commonly express generic-specific, part-whole and function relations in specialized texts. Our inventory is accompanied by a discussion of associated problematic issues.
Dual adaptive delta modulation for mobile voice channel and its DSP implementation

The objective of our work reported in this paper is to design a dual adaptive delta modulation (DADM) that can 1) transmit fairly good quality speech (as high as communications quality) at 16 kbps, 2) produce a graceful degradation in speech quality in the presence of channel bit errors of up to 1 percent, and 3) be implemented with a small-sized and economical digital hardware. Presented are: 1) basic characteristics of the algorithm proposed, including subjective assessment of voice quality, 2) optimization of system parameters using speech samples spoken by 4 males and 4 females, and 3) hardware realization of the DADM using a DSP and a PCM-Codec LSI chips for full-duplex operation.
Analysis of Online Behavior and Prediction of Learning Performance in Blended Learning Environments

A variety of studies to predict students’ performance have been conducted since educational data such as web-log files traced from Learning Management System (LMS) are increasingly used to analyze students’ learning behaviors. However, it is still challenging to predict students’ learning achievement in blended learning environment where online and offline learning are combined. In higher education, diverse cases of blended learning can be formed from simple use of LMS for administrative purposes to full usages of functions in LMS for online distance learning class. As a result, a generalized model to predict students’ academic success does not fulfill diverse cases of blended learning. This study compares two blended learning classes with each prediction model. The first blended class which involves online discussion-based learning revealed a linear regression model, which explained 70% of the variance in total score through six variables including total log-in time, log-in frequencies, log-in regularities, visits on boards, visits on repositories, and the number of postings. However, the second case, a lecture-based class providing regular basis online lecture notes in Moodle show weaker results from the same linear regression model mainly due to non-linearity of variables. To investigate the non-linear relations between online activities and total score, RF (Random Forest) was utilized. The results indicate that there are different set of important variables for the two distinctive types of blended learning cases. Results suggest that the prediction models and data-mining technique should be based on the considerations of diverse pedagogical characteristics of blended learning classes.
Behaviors of an enhanced transport protocol for multipeer multimedia communications

This paper proposes an enhanced transport protocol for multipeer communications. It is assumed that there exists a transport connection owner that takes charge of the establishment, management and termination of a multipeer transport connection. The proposed protocol classifies the type of multicast data transfer into simplex, duplex and N-plex and provides several transport services to support membership and reliability requirements in multiparty group communications. A shared control tree that is originated to avoid the ACK implosion problem carries out its general operations and reliability controls. The QoS negotiation is performed during the creation phase. The notification of negotiated values is followed by an acknowledgment for confirmation. The four-way handshake is introduced. This paper suggests a conceptual model of the transport layer and protocol behaviors. It is assumed that this transport protocol is operated over IPv6 multicasting or IP Multicast service with RSVP.
Adaptive algorithms for asynchronous DS-CDMA receivers

Issues relating to the choice of adaptive algorithms for use in single user minimum mean square error (MMSE) direct sequence (DS) code division multiple access (CDMA) receivers are discussed. Such receivers have the potential to dramatically increase capacity of CDMA systems compared to systems with conventional correlator receivers, without the high complexity associated with many proposed multi-user receivers. To be practical for many applications, the convergence rate of the adaptive algorithms must be improved, while maintaining low residual mean-squared error (MSE), robustness to noise and realisable complexity. The slow convergence of the least mean squares (LMS) algorithm is highlighted for this application. Recursive least squares (RLS) algorithms are shown to give much quicker convergence, but have much higher sensitivity to thermal noise. Algorithms normally termed "Fast-RLS", are shown to more complex than the conventional RLS algorithm when used in a CDMA receiver.
Singular Integral Formulations for Electrodynamic Analysis of Metamaterial-Inspired Antenna Array

In this letter, a set of singular integral formulations are derived to calculate the surface impedance matrix on the antenna array elements. The proposed mathematical model enables electrodynamic analysis of antenna arrays designed using metamaterial-inspired structures. The formulations allow the determination of the array's impedance, spatial, and polarization characteristics at significantly low computational cost compared to conventional electromagnetic (EM) solvers based on method-of-moments (MoM) numerical technique. The accuracy of the surface impedance results obtained from the theoretical formulations is verified using the full-wave EM software. It is shown that there is excellent agreement between the proposed formulations and EM software. The accuracy of the theoretical model presented is valid for single-layer structures.
Refinement and extension of the cloud decision support framework for application migration to the cloud

The maturity and dissemination of Cloud Computing across diverse business domains is leading to an increasing amount of migration projects with the goal to leverage the associated benefits for important legacy applications. However, the migration of applications to the cloud is a complex problem that entails various technical and organizational aspects. The existing Cloud Decision Support Framework has been a first step to provide decision makers with the means to find a suitable migration strategy. This master's thesis has refined the framework's underlying knowledge base by reviewing its decision points, decisions and their relations as well as outcomes. Based on this refinement, the framework has been extended by elaborating the relations between outcomes resulting in greater potential for decision support. In order to allow decision makers to derive migration strategies based on the framework in an interactive manner, a web application has been implemented. In a final step, an evaluation has been carried out comprising a validation of the knowledge base and, by means of a use case, a demonstration of the efficacy of the extended decision support framework.
Issues in the Design and Use of System-Dynamics-Based Interactive Learning Environments

The author presents an overview of the topics covered by the articles in this special issue on system-dynamics-based interactive learning environments (ILEs). The article shows how a system-dynamics-based ILE is being designed to portray the intimate relationship between structure and dynamic behavior in complex domains. The complexity and need for a structural foundation for the interpretation of behavior create the following challenges: to associate behavior to underlying structure; to explicitly represent the integration processes, including delays (lags), that drive dynamic behavior; to trace the various feedback structures so as to identify what determines their relative contribution to the overall behavior; to facilitate the strengthening and weakening of such loops as a basis for policy design; to represent any nonlinearity that might exist and map each operating point onto them so as to identify variations in dynamic sensitivity; to effectively portray the significance of uncertainty and vagueness; and last but not least, to put it all together.
Determining a Number of Training Data for Gesture Recognition Considering Decay in Gesture Movements

– Mobile phones and video game controllers using gesture recognition technologies enable easy and intuitive operations, such as those in drawing objects. Gesture recognition systems generally require several samples of training data before recognition takes place. However, recognition accuracy deteriorates as time passes since the trajectory of the gestures changes due to fatigue or forgetfulness. We investigated the change in gestures and found that the ﬁrst several samples of gestures were not suitable for training data. Therefore, we propose two methods of ﬁnding appropriate data for training for long-term use. We conﬁrmed that the proposed methods found better training data than the conventional method from the viewpoints of the number of data collected and recognition accuracy.
A Structure for Plans and Behavior

Abstract : This report describes progress to date in the ability of a computer system to understand and reason about actions. A new method of representing actions within a computer's memory has been developed, and this new representation, called the "procedural net," has been employed in developing new strategies for solving problems and monitoring the execution of the resulting solutions. A set of running computer programs, called the NOAH (Nets Of Action Hierarchies) system, embodies this representation. Its major goal is to provide a framework for storing expertise about the actions of a particular task domain, and to impart that expertise to a human in the cooperative achievement of nontrivial tasks. A problem is presented to NOAH as a statement that is to be made true by applying a sequence of actions in an initial state of the world. The actions are drawn from a set of actions previously defined to the system. NOAH first creates a one-step solution to the problem, then it progressively expands the level of detail of the solution, filling in ever more detailed actions. All the individual actions, composed into plans at differing levels of detail, are stored in the procedural net. The system avoids imposing unnecessary constraints on the order of the actions in a plan. Thus, plans are represented as partial orderings of actions, rather than as linear sequences. The same data structure is used to guide the human user through a task. Since the system has planned the task at varying levels of detail, it can issue requests for action to the user at varying levels of detail, depending on his/her competence and understanding of the higher level actions. If more detail is needed than was originally planned for, or if an unexpected event causes the plan to go awry, the system can continue to plan from any point during execution. In essence, the structure of a plan of actions is as important for problem solving and execution monitoring as the nature of the actions themselves.
On CMOS exclusive OR design

A collection of eight different CMOS EXOR (exclusive OR) gates is presented. The circuit implementations of these EXOR gates range from three to a dozen transistors. A circuit diagram, layout size, and simulation results from LSIM, SPICE, and IRSIM are given for each of the circuits. <<ETX>>
Design techniques for cascoded CMOS op amps with improved PSRR and common-mode input range

Internally compensated CMOS op amps have been widely used in sampled-analog signal processing applications over the past several years. However, the popular two-stage op amp suffers from poor AC power supply rejection to one of the power rails. Two circuits are presented that overcome the power-supply rejection ratio (PSRR) problems of the earlier amplifier: one for virtual ground applications such as switched-capacitor integrators, the other for buffer applications requiring wide common-mode input range. Small signal analysis is developed for the open-loop and PSRR responses of the two amplifiers. In addition, design guidelines are suggested and test results are presented.
Radio Channel Model of Wireless Sensor Networks Operating in 2.4 GHz ISM Band

This paper presents a novel signal propagation model of wireless sensor network (WSN) for outdoor open environments. This model can be used in simulators and also in WSN services as localization discovery. The model here proposed produces results with higher accuracy when compared to the models existing in the literature. It is based on the existing double path propagation model (tworay), but differently from the previous works, it takes into account the directivity of the antennas and the variable reﬂectivity index of the soil. Experiments conﬁrmed the outstanding results of our propagation model
Scalable, parallel poisson solvers for CFD problems

Het grootste deel van de rekencapaciteit nodig voor het berekenen van nietsamendrukbare turbulente stromingen wordt aangewend voor het oplossen van de Poissonvergelijking voor de druk. Daarom beschouwen we de parallelle prestaties van zeer efficiente Poissonsolvers binnen PETSc (Portable, Extensible Toolkit for Scientific Computation), met name Krylov Methoden and Algebra"{i}sche MultiGridmethoden. In drie dimensies zijn symmetrische Poissonproblemen opgelost op rekenroosters tot en met 1 miljard punten. De CG-methode met ML als preconditionering geeft de beste resultaten. Indien de randvoorwaarde de symmetrie van het Poissonprobleem verstoort, worden gepreconditioneerde GMRES-methoden gebruikt. Niet-symmetrische Poissonproblemen treden op na discretisatie van de Navier-Stokes vergelijkingen (behoud van massa en impuls) in de buurt van een vrij oppervlak. We beschouwen drie gevallen: een nietsamendrukbare eenfasestroming, een samendrukbare tweefasenstroming en een vrije oppervlakte stroming met in- en uitstroomrandvoorwaarden. Ook in deze gevallen geeft een AMG preconditionering goede resultaten. Verder zijn directe numerieke simulaties van turbulente kanaalstromingen beschouwd voor Reynoldsgetallen tot en met $Re_{tau}approx 1400$. Daarvoor zijn 1024 processoren gebruikt. De Poissonsolver voor de druk maakt wederom deel uit van PETSc, en de Message Passing Interface (MPI) standaard is toegepast om de overige delen van het computerprogramma om te zetten in een parallelle Fortrancode. De Poissonsolver vergt ongeveer 90% van de rekentijd. De berekeningen zijn uitgevoerd op Huygens, in Amsterdam. In deze toepassing blijkt de ML preconditionering ietsjes efficienter te zijn dan BoomerAMG.