Miracle-dz/UniFAR-FTUs huggingface dataset:
Contextualizing Experiences: Tracing the Relationships Between People and Technologies in the Social Web

This article uses both actor network theory (ANT) and activity theory to trace and analyze the ways in which both Twitter and third-party applications support the development and maintenance of meaningful contexts for Twitter participants. After situating context within the notion of a ‘‘fire space’’, the authors use ANT to trace the actors that support finding and moving information. Then they analyze the ‘‘prescriptions’’ of each application using the activity-theory distinction between actions and operations. Finally, they combine an activity-theory analysis with heuristics derived from the concept of ‘‘findability’’ in order to explore design implications for Social Web applications.
Stereo chemical and Statistical issues for evaluating the goodness of 30 different models generated by online freely protein 3D structure prediction servers

Proteins are known as the building blocks of the living body. For the correct diagnosis of any disease or malfunction of the living body, information about protein provides knowledge about the situation. Therefore protein structure and function plays an important role in assessing the condition of the organism. In silico analysis provides a faster way to detect the structure of proteins through three mechanisms namely homology modelling, Threading or fold recognition and Ab initio method. This can be done by using different server and software freely available online. An effort has been done to identify the ideal three dimensional structure of the protein among the thirty models generated by 30 different structure prediction servers. The evaluation was done taking into account several stereo chemical and statistical factors. The results have shown that the models generated by majority of the homology modelling servers are satisfying the evaluation factors when compared with the models generated by the other two mechanisms namely, Threading and Ab-initio.
Attentional focus training by boundary region data selection

An attempt is made to improve the classification performance of a trained multilayer perceptron. Using inversion to locate boundary points of the partially trained classification surfaces, the authors have defined boundary regions and selected those training data which fell within the boundary regions. Continuing the training with only the boundary region data, the authors improved classification performance by 6% in an automated cytological classification application. <<ETX>>
Remote sensing of soil moisture using EMAC/ESAR data

Presents the first results of surface soil moisture retrieval using data from the European Multisensor Airborne Campaign/Experimental Synthetic Aperture Radar (EMAC/ESAR) collected on April 9, 1994 in the Zwalm catchment, Belgium. The authors apply a theoretical backscattering model to investigate the sensitivity of EMAC/ESAR backscattering coefficients to surface parameters. By comparing the predicted backscattering coefficients to the observed ones, they conclude that current measurement techniques for surface roughness parameters in remote sensing campaigns are not accurate enough for retrieving soil moisture using theoretical models. A method based on simultaneous retrieval of surface roughness parameters and soil moisture using multiple ESAR measurements is hence proposed. Promising results on retrieved soil moisture confirm the validity of the proposed method.
Access control constrains what a user can do directly, as well as what programs executing on behalf of the users are allowed to do. In this way access control seeks to prevent activity that could lead to breach of security.

he purpose of access control is to limit the actionsoroperations that alegitimate user of a computer system can perform. Access controlconstrainswhat a user can do directly, as well as what programs executing on behalf of the users are allowed to do. In this way access control seeks to prevent activity that could lead to a breach of security. This article explains access control and its relationship to other security services such as authentication, auditing. and administration. It then reviews the access matrix model and describes different approaches to implementing the access matrix in practical systems, and follows with a discussion of access control policies commonly found in current systems, and a brief consideration of access control administration.
Sensorless rotor velocity tracking control of the permanent magnet stepper motor

We present a sensorless rotor velocity tracking controller for the full order, nonlinear dynamic model of the permanent magnet stepper motor actuating a mechanical subsystem. Specifically, the structure of the electrical subsystem dynamics is exploited to reconstruct the rotor position and velocity signals from measurements of stator current and stator voltage. This surrogate rotor position signal is then used to design a control strategy that achieves exponential rotor velocity tracking. Experimental results are included to demonstrate the efficacy of the proposed algorithm.
Increasing the Efficiency of IDS Systems by Hardware Implementation of Packet Capturing

Capturing is the first step in intrusion detection system (IDS). Having wire speed, omitting the OS fro m capturing process and no need for making a copy of packets from the system's environ ment to the user's environment are some o f the system characteristics. If these requirements are not met, packet capture system is considered as the main bottleneck of IDS and the overall efficiency of this system will be influenced. Presence of all these three characteristics calls for utilizat ion of hardware methods. In this paper, by using of FPGA, a line sniffing and load balancing system are designed in order to be applied in IDS systems. The main contribution of our work is the feasibility of attaching labels to the beginning part of each packet, aiming at quick easy access of other IDS modules to information of each packet and also reducing workload of these modules. Packet classification in the proposed system can be configured to 2, 3, and 5 tuple, wh ich can also be applied in IDS detection module in addition to load balancing part of this system. Load balancing module uses Hash table and its Hash function has the least flows collisions. This system is imp lemented on a set of virtex 6 and 7 families and is ab le to capture packets 100% and perform the above mentioned processes by speed of 12 Gbit/s.
Exponential Servers Sharing a Finite Storage: Comparison of Space Allocation Policies

Consider a finite waiting room shared by several servers. Such a system may approximate, for instance, a packet switch in a communications network. It is assumed that interarrival and service times have exponential distributions, and that a customer is lost if he cannot enter the waiting room. Different policies for sharing the finite waiting room are compared-the measure of performance being the probability that a customer is lost.
MODIS geolocation algorithm and error analysis tools

The Moderate Resolution Imaging Spectroradiometer (MODIS) contains 36 bands from the visible to the thermal infrared with the nominal ground field of views of 250 m, 500 m and 1 km. This paper summarizes the MODIS Earth location algorithm from the focal plane/detector system through the telescope system, rotating scan mirror system, spacecraft ephemeris/attitude processing system, and digital elevation model. It also describes how the geolocation of other bands can be derived from the ideal band ground coordinates. Some tools have been developed to check the model accuracy and validity of the geolocation. This paper describes these tools including a ground control point matching program, a trend and bias error analysis program, and a MODIS image simulation program using Landsat TM (Thematic Mapper) images. Some post launch findings on the model accuracy and necessary changes to the model are also described.
Semantic Knowledge-based Bayesian Refinement for Object Recognition

Even if some of previous approaches prove their effectiveness for tightly controlled environments such as industrial settings, dependable object recognition remains difficult in real environments. Thus, this paper proposes a method of robust object recognition effective in real environments. The basic idea is to recognize and predict objects via a combined use of ontology and Bayesian network. To demonstrate the benefits of the proposed approach, a case study is conducted in an actual working environment.
Incremental learning for Adaptive Visual Place Recognition in Dynamic Indoor Environments

Vision-based place recognition is a desirable feature for an autonomous mobile system. In order to work in realistic scenarios, a visual recognition algorithm should have two key properties: robustness and adaptability. This thesis focuses on the latter, and presents a discriminative incremental learning approach to place recognition. We propose a solution based on incremental extensions of support vector machine classifier. Computational and memory efficiency are crucial for mobile robot platforms aiming to continuously work in real-world settings; thus we put the emphasis on these properties. We use a recently introduced memory-controlled incremental technique, which allows to control the memory requirements as the system updates its internal representation. At the same time, it preserves the recognition performance of the batch algorithm and runs online. In order to assess the method, we acquired a database capturing the intrinsic variability of places over time. Extensive experiments show the power and the potential of the approach.
Word Sense Disambiguation With Sublexical Representations

This paper introduces a new representational scheme for word sense disambiguation. Drawing on work in information retrieval (Latent Semantic Indexing as proposed by [Deerwester et al. 1990]) an efficient method for learning sublezical representations is described: Words and contexts are represented as vectors in a multidimensional space which approximates similarity of collocational patterns. Closeness of words in the space is equivalent to occurrence in similar contexts, thus giving a rough approximation of semantic similarity. The Bayesian classification system AutoClass was then used to perform an unsupervised classification of sublexical representations of contexts of the three ambiguous words interest, suit and plant in a training text. In applying this classification to a test text, AutoClass disamhiguated 90% of all occurrences correctly. Unsupervised classification failed for tank, but a more sophisticated algorithm also achieved a disambiguation rate of 90%.
Irish in a 3D World: Engaging Primary School Children.

Gene Dalton, Trinity College Dublin Ann Devitt, Trinity College Dublin While the majority of people in Ireland speak English as a first language, the minority Irish language is spoken daily by approximately 3% of the population even though is a compulsory subject in Irish schools. Recent research has shown the language to be in crisis, with consistently declining standards of attainment in schools. This paper presents the first cycle of an Action Research project aiming to assess the potential of using a threedimensional virtual environment (3DVE) as a platform for task-based learning of Irish in the primary school. The action phase of the cycle consisted of an intensive pilot of a language learning intervention using a 3DVE (n=25 children aged 9-10 years). The reflection component was multiphase, involving analysis of pilot outputs, re-evaluation of the literature and an in-depth user consultation (n=15 children aged 10-11 years), inspired by Student Voice methodology. The user consultation findings indicated goal orientation as the primary driver for children learning in a 3DVE with social connectivity understood as a given in any such environment. This paper offers a novel classification of games and virtual worlds for language learning which serves to integrate the two research literatures in a meaningful way.
Behavioral analysis, user modeling, and protocol design based on large-scale wireless network traces

In this dissertation we describe the TRACE framework, which is a five-step procedure for the environment-aware approach towards wireless mobile computer networks. As mobile computer networks become ubiquitous and deeply integrated with the daily lives, it is crucial to understand the network and design its protocols and services with the environment-aware approach: We first collect extensive network Traces that reflect truthfully the detailed behaviors of its users, and Represent the rich data sets in concise representations. Then we Analyze these constructed representations to Characterize the users. While many observed characteristics are interesting in themselves and reveal important differences between the realistic environment and commonly made assumptions in the literature, we further add values to these findings by Employing them in various important tasks, including modeling the network users and designing routing protocols. The dissertation is centered around three major case studies, ranging from the microscopic, individual user behavior in the wireless networks to the macroscopic, global user encounter patterns. Specifically, in the case studies, we (1) observe the individual user mobility from the collected traces, identify skewed preferences and periodical re-appearance at the same location as prominent mobility characteristics, and propose the time-variant community (TVC) mobility model to capture such behaviors. The TVC model is flexible to match with many empirical traces while being mathematically tractable. (2) We construct an efficient way for mobile users to summarize their mobility preferences based on singular value decomposition (SVD) and calculate the distance metric between users. Based on this distance metric, we identify user groups in the population based on their mutual similarities, and design a profile-cast service to deliver messages to these behavioral groups without knowing their identities. (3) We further analyze the global encounter patterns between nodes, observe a fast-emerging Small World encounter pattern, and leverage such a network property to design an efficient message dissemination protocol named CSI, in which Communication relies on the Stable yet Implicit structures in mobile networks.
48.1: Distinguished Student Paper: A Depth‐Fused Multi‐Focal‐Plane Display Prototype Enabling Focus Cues in Stereoscopic Displays

Lack of focus cues in stereoscopic displays may have significant effects on depth perception accuracy and visual fatigue. In this paper, we present a depth‐fused six‐focal plane display prototype, capable of rendering nearly‐accurate focus cues for a depth range of 3 diopters with high image quality at flicker‐free speed.
A weighted competitive learning method extracting skeleton pattern from Japanese Kanji characters

A weighted competitive learning (WCL) method was proposed by authors for extracting skeleton patterns from digit and alphabet characters. The extracted pattern is essential in character recognition. It can satisfy the following important requirements. (a) Insensitive to irregular edge lines. (b) Nonstructure patterns are not extracted. (c) Insensitive to nonuniform line width. (d) Line information should be held even though the line width widely changes in a character. In this paper, the previous WCL method is improved for application to more complicated characters, such as Japanese Kanji characters. Furthermore, a PDP model, implements the WCL method, is provided. <<ETX>>
CIS: A Web-Based Course Information System

This report surveys the design and implementation of CIS, a web-based Course Information System. CIS has been developed for the Computer Science I/II courses held between 2000 and 2003 by Prof. Dr. R. Loos, which were attended by 300 to 450 students. It maintains and presents each student’s submissions and grades and holds related information such as worksheet texts, submission deadlines and the assignment of students to teaching assistents. In short, it covers most of the administrative data that comes up in regular university courses. CIS is designed to be used by first-year students conveniently. It aims at modelling real-world procedures, so that the system behaviour can be explained in well-known analogies. It is minimalistic, in the sense that it only takes on the routine work, while leaving the teacher free in any questions of structuring the contents of the course. Our problem statement and analysis focuses to two aspects: The requirements on the central data base and the interfaces for three groups of users: Students, teaching assistants, and teachers/administrators. The actual implementation is straightforward, and we only mention particular decisions taken herein. CIS has been in use at the Wilhelm-Schickard Institut for three years, in courses organized both by the authors and others. The experiences indicate that the system can be considered reliable and mature. As the effort of setting up CIS is small, it has become feasible to employ it for several advanced courses with fewer than 20 students.
Ensuring the successful adoption of discrete event simulation in a manufacturing environment

Discrete event simulation has long been recognized as a valuable tool for manufacturers, but converting the recognition of value into an embrace of the technology can be a challenge. Like most technologies with which an organization has little or no experience, timing and the manner in which simulation is introduced can significantly influence whether its adoption will succeed or fail. Without careful planning and adequate foresight, simulation technology will not prove its benefits in the workplace and will be viewed as an unnecessary expense. We examine the characteristics that signal the need for discrete event simulation, and we discuss the strategies and methods we have found to ensure its successful adoption.
PLC Based PID Speed Control System

In this paper, an intelligent controller of AC Motor drive designed using proportional-integral- derivative (PID) optimization for the optimal tuning of PID controller parameters. A PID controller control loop feedback mechanism controller widely used in Industrial control system. A optimization algorithm is employed in order to obtain the controller parameters assuring deadbeat response at each selected load. The AC-Motor PID-controller is modeled in SLC 500. The response of the developed controllers is compared to that of the controllers whose parameters are tuned using the Ziegler-Nichols method. The developed methodology is more proficient in improving the controller loop response stability, the steady state error, the rising time and overshoot and hence the disturbances do not affect the performances of AC-motor.
NESSR : a Neural Expert System for Speech Recognition

and key words Artificial neural networks (ANNs) have found applications in large spectrum of fields. Satisfactory results are obtained particularly in classification problems. In speech recognition context, the use of ANNs is hard, this is essentially due to the absence of the temporal aspect in their structure. On the other hand, assuming a speech recognition task, a word could be recognized and well categorized or recognized and badly categorized ; so the explanation of the decision is very important. In this paper, we address two limitations of ANNs : the lack of explicit knowledge and the absence of temporal aspect in their implementation. STN : is a model of a specialized temporal neuron, which includes both symbolic and temporal aspects. To illustrate the STN utility, we consider a system for speech recognition ; we underline in this paper the explanation aspect of the system. Artificial intelligence, machine learning, connectionism, speech recognition. traitement du signal 2007_volume 24_numéro 1 59
What’s trending in cloud computing from the internet cybersphere

Purpose – The purpose of this paper is to examine the following question: What is cloud computing? Design/methodology/approach – This paper surveys the current literature. Findings – Cloud computing is described in many ways. Originality/value – This paper is one of the first pieces to examine the nature of cloud computing.
An algorithm for linearly constrained adaptive array processing

A constrained least mean-squares algorithm has been derived which is capable of adjusting an array of sensors in real time to respond to a signal coming from a desired direction while discriminating against noises coming from other directions. Analysis and computer simulations confirm that the algorithm is able to iteratively adapt variable weights on the taps of the sensor array to minimize noise power in the array output. A set of linear equality constraints on the weights maintains a chosen frequency characteristic for the array in the direction of interest. The array problem would be a classical constrained least-mean-squares problem except that the signal and noise statistics are assumed unknown a priori. A geometrical presentation shows that the algorithm is able to maintain the constraints and prevent the accumulation of quantization errors in a digital implementation.
A Multipath Routing Protocol in Wireless Mesh Networks

Multipath routing protocols can effectively provide delay guarantees for delay-sensitive traffic such as live stream video over Wireless mesh networks (WMN). However, most existing multipath routing protocols rarely optimize the traffic over the multiple paths to promote network performance. In this paper, we propose a novel multipath routing protocol using convex optimization methods to formulate the problem and derive a multipath protocol through an optimization decomposition. Simulation results show that the proposed protocol dynamically and intelligently decomposes the contending traffic over multiple paths and hence efficiently supports delay-sensitive traffic.
Large deviations and overflow probabilities for the general single-server queue, with applications

Abstract We consider queueing systems where the workload process is assumed to have an associated large deviation principle with arbitrary scaling: there exist increasing scaling functions (at, vt, t∈R+) and a rate function I such that if (Wt, t∈R+) denotes the workload process, then on the continuity set of I. In the case that at = vt = t it has been argued heuristically, and recently proved in a fairly general context (for discrete time models) by Glynn and Whitt[8], that the queue-length distribution (that is, the distribution of supremum of the workload process Q = supt≥0Wt) decays exponentially: and the decay rate δ is directly related to the rate function I. We establish conditions for a more general result to hold, where the scaling functions are not necessarily linear in t: we find that the queue-length distribution has an exponential tail only if limt→∞at/vt is finite and strictly positive; otherwise, provided our conditions are satisfied, the tail probabilities decay like
Approaching Completeness

The aim of this article is to engage with problems of sampling and completeness currently discussed within data science through the specific example of conversations in Twitter. Some of the difficulties involved in Twitter concern restrictions laid out by platform owners, restrictions that make it difficult for researchers to collect complete conversations. A contribution is made through the development of a method for collecting and analyzing follow-on conversations around a set of hashtags. This was made possible through the simultaneous tracking of a set of hashtags and prominent participants in the conversation. The full set of tweets was compared to the subset of tweets including either of the selected hashtags. Including follow-on conversation increased the set of tweets by 56% and the set of tweeting users by 17%. It is also shown that different network analysis techniques and filtering options give different results with regard to prominent users.