Miracle-dz/UniFAR-FTUs huggingface dataset:
IMPROVING INSTRUCTOR RESPONSE TO STUDENT E-MAILS USING TEMPLATE AND REMINDER INTERVENTIONS

Student e-mails without the student’s name, message, file attachment, etc may impede a timely and thorough instructor response. To help resolve this issue, we apply template and reminder interventions to improve student e-mail format defined as the degree of agreement between a student’s e-mail format and an instructor provided template. A pilot study (Study 1) employing a sample of 36 online undergraduate marketing students concluded that instructor supplied e-mail format template significantly improved student e-mail format. Additional refinements were examined in Study 2 to test three instruction formats (verbal, separated graphic and verbal, and integrated graphic and verbal) and two levels of instruction reminders (once and three times) using a sample of 78 online undergraduate marketing students. Results show that integrated graphic and verbal instructions, and independently, reminder announcements improve student e-mail format. Results from the two studies are discussed in terms of pedagogical benefits for the marketing educator.
Using semantics to reveal knowledge divides in Dutch development cooperation: the case of the Millennium Development Goals

The paper is a first effort at examining the potential of scientometrics analysis to the field of development in the expectation that this type of analysis will make general patterns of knowledge within development more visible. In particular, we assume that it will reveal information on these patterns and in particular on knowledge divergences and divides within the sector. Semantic maps make it possible to compare semantics across the three domains under study, and reveal implicit frames within them. This methodology is tested using a pilot study comparing the semantics around Millennium Development Goals (MDGs) in three domains involved in development: policy, science and the mass media. In particular, it compares the semantics on MDGs in the website of the Dutch Ministry of Foreign Affairs, in scientific articles authored by Dutch scholars, and in Dutch newspaper articles. In conclusion, the semantic maps method provided fruitful insights into comparing the semantics of the debate around MDGs in the three separate knowledge domains involved in the debate.
Facing Architectural and Technological Variability of Rich Internet Applications

The advent of Rich Internet Applications has involved an authentic technological revolution providing Web users with advanced requirements similar to desktop applications. At the same time, RIAs have multiplied the possible architectural and technological alternatives complicating development and increasing risks. The real challenge is to select the right alternatives among the existing RIA variability, thus creating an optimal solution able to satisfy most user requirements. To face this challenge, for the RIA development process, we propose an extended OOH4RIA approach to introduce architectural and technological aspects at the design phase, to propagate these decisions to the rest of concerns and to provide a closer match between the modeled system and the final implementation.
Sentiment Analysis: A Perspective on its Past, Present and Future

The proliferation of Web-enabled devices, including desktops, laptops, tablets, and mobile phones, enables people to communicate, participate and collaborate with each other in various Web communities, viz., forums, social networks, blogs. Simultaneously, the enormous amount of heterogeneous data that is generated by the users of these communities, offers an unprecedented opportunity to create and employ theories & technologies that search and retrieve relevant data from the huge quantity of information available and mine for opinions thereafter. Consequently, Sentiment Analysis which automatically extracts and analyses the subjectivities and sentiments (or polarities) in written text has emerged as an active area of research. This paper previews and reviews the substantial research on the subject of sentiment analysis, expounding its basic terminology, tasks and granularity levels. It further gives an overview of the stateof – art depicting some previous attempts to study sentiment analysis. Its practical and potential applications are also discussed, followed by the issues and challenges that will keep the field dynamic and lively for years to come.
Thiopental Induces Contraction of Rat Aortic Smooth Muscle Through Ca2+ Release from the Sarcoplasmic Reticulum

Little is known about the mechanism of thiopental-induced contraction in vascular smooth muscle. This study aimed to clarify this question by conducting isometric tension experiments and 45Ca2+ flux measurements in endothelium-denuded rat aortic rings. Thiopental induced a concentration-dependent contraction under basal tension. This contraction was enhanced when rings were precontracted with phenylephrine in the presence of verapamil. In Ca2+-free solution, thiopental-induced contraction was reduced but not abolished with high concentrations. Ca2+ store depletion with a maximum dose of caffeine in Ca2+-free solution further reduced the contraction by subsequent thiopental. Ca2+ store depletion with thapsigargin completely abolished contraction by thiopental. 45Ca2+ influx experiment in the presence of verapamil showed that thiopental could not induce any Ca2+ influx with or without phenylephrine prestimulation. The 45Ca2+ efflux experiment showed more evidence of thiopental-induced Ca2+ release, which was abolished by thapsigargin. In conclusion, thiopental induces contraction in rat aortic smooth muscle by releasing Ca2+ from the sarcoplasmic reticulum without Ca2+ influx. Implications This is the first study providing evidence that thiopental-induced vascular contraction is caused by Ca2+ release from the sarcoplasmic reticulum of the smooth muscle.
Third-overtone resonator using thickness longitudinal mode of 36° Y-LiNbO3

The energy trapping characteristic of the thickness longitudinal mode propagating in a 36° rotation Y-cut LiNbO3 single crystal is theoretically analyzed. It is found that the fundamental wave has a high-frequency cutoff characteristic and the third overtone has a low-frequency cutoff characteristic. It is shown that a third-order overtone resonator with a small resonant level of the fundamental wave can be obtained. Further, a simulation analysis of the vibration displacement distribution is performed by the finite element method. The device dimensions for further improvement of the degree of suppression of the fundamental wave are experimentally derived. Based on these investigation results, a 34-MHz resonator was fabricated and a third-overtone resonator with a small fundamental response level with a resonance sharpness of 15,000, a capacitance ratio of 97, and a temperature characteristic of approximately –70 ppm/°C was obtained. The resonator is being mass produced as a clock resonator for a microprocessor operating between 25 and 100 MHz. © 1999 Scripta Technica, Electron Comm Jpn Pt 2, 82(7): 50–58, 1999
Selective visual attention in object detection processes

Object detection is an enabling technology that plays a key role in many application areas, such as content based media retrieval. Attentive cognitive vision systems are here proposed where the focus of attention is directed towards the most relevant target. The most promising information is interpreted in a sequential process that dynamically makes use of knowledge and that enables spatial reasoning on the local object information. The presented work proposes an innovative application of attention mechanisms for object detection which is most general in its understanding of information and action selection. The attentive detection system uses a cascade of increasingly complex classifiers for the stepwise identification of regions of interest (ROIs) and recursively refined object hypotheses. While the most coarse classifiers are used to determine first approximations on a region of interest in the input image, more complex classifiers are used for more refined ROIs to give more confident estimates. Objects are modelled by local appearance based representations and in terms of posterior distributions of the object samples in eigenspace. The discrimination function to discern between objects is modeled by a radial basis functions (RBF) network that has been compared with alternative networks and been proved consistent and superior to other artifical neural networks for appearance based object recognition. The experiments were led for the automatic detection of brand objects in Formula One broadcasts within the European Commission's cognitive vision project DETECT.
Control of Electro-Hydraulic Poppet Valves via Online Learning and Estimation

Online learning state trajectory control applied to Electro-Hydraulic Poppet Valves (EHPV) is considered herein. The control problem is to track a desired flow conductance coefficient KV for pressure or flow control applications. In general terms, the control methodology employed herein computes the input signal sent to the valve from the addition of three components. The first component comes from an experimentally approximated inverse input-output map of the system which gives a nominal input. The second component is computed through a neural network structure called the Nodal Link Perceptron Network that learns online the adjustment of this nominal map. The third component is an adaptive proportional feedback control input. This last component uses two system parameters known as the Jacobian and the Controllability parameter, which are estimated online via a recursive least squares algorithm with forgetting factor. The proposed controller is explored through experimental data on a pressure control application and the results are discussed. © 2005 ASME
Acronym extraction using SVM with Uneven Margins

Extracting acronyms and their expansions from plain text is an important problem in text mining. Previous research shows that the problem can be solved via machine learning approaches. That is, converting the problem of acronym extraction to binary classification. We investigate the classification problem and find that the classes are highly unbalanced (the positive instances are very rare compared to negative ones). So we try to tackle the problem using an uneven margin classifier - SVM with Uneven Margins. Experimental results showed that our approach can get better results than baseline methods of using heuristic rules and conventional SVM models. Experimental results also showed how uneven margins classifier made the tradeoff between the precision and recall of extraction.
Robust makespan minimisation in identical parallel machine scheduling problem with interval data

Parallel machine scheduling problems are commonly encountered in a wide variety of manufacturing environments and have been extensively studied. This paper addresses a makespan minimisation scheduling problem on identical parallel machines, in which the specific processing time of each job is uncertain, and its probability distribution is unknown because of limited information. In this case, the deterministic or stochastic scheduling model may be unsuitable. We propose a robust (min–max regret) scheduling model for identifying a robust schedule with minimal maximal deviation from the corresponding optimal schedule across all possible job-processing times (called scenarios). These scenarios are specified as closed intervals. To solve the robust scheduling problem, which is NP-hard, we first prove that a regret-maximising scenario for any schedule belongs to a finite set of extreme point scenarios. We then derive two exact algorithms to optimise this problem using a general iterative relaxation procedure. Moreover, a good initial solution (optimal schedule under a mid-point scenario) for the aforementioned algorithms is discussed. Several heuristics are developed to solve large-scale problems. Finally, computational experiments are conducted to evaluate the performance of the proposed methods.
Polarimetry in remote sensing: basic and applied concepts

One of the great challenges for modern radar is to classify, sort and identify targets of all kinds for military battlespace surveillance as well as for civilian geo-environmental stress change monitoring purposes. Whereas, in military radar utilization of complete polarization scattering matrix radars is not yet fully accepted, in remote sensing on the other hand, radar polarimetry seems to have been accepted as an indispensable tool, and convincing results have been obtained for geo-environmental applications in agriculture, forestry, hydrology, flood plain and rural infrastructure maintenance, volcanology and seismology, archeology, etc. However, there still exists a large void in standardization and proper handling of basic and applied polarimetric theory and concepts. In this paper a succinct assessment of the current state-of-the-art is presented summarizing the basic polarimetry concepts spelled out in Boerner et al. (1997). It is the purpose of this paper to draw attention of the IEEE Geoscience and Remote Sensing community to this recent compendium on 'Polarimetry in Remote Sensing'.
Efficiency of Network Structures: The Needle in the Haystack

The modelling of networks formation has recently became the object of an increasing interest in economics. One of the important issues raised in this literature is the one of networks efficiency. Nevertheless, for non trivial payoff functions, searching for efficient network structures turns out to be a very difficult analytical problem as well as a huge computational task, even for a relatively small number of agents. In this paper, we explore the possibility of using genetic algorithms (GA) techniques for identifying efficient network structures, because the GA have proved their power as a tool for solving complex optimization problems. The robustness of this method in predicting optimal network structures is tested on two simple stylized models introduced by Jackson and Wolinski (1996), for which the efficient networks are known over the whole state space of parameter values.
Effect of Multipath on Ranging Error for an Airplane-Satellite Link

An exact analysis is carried out on the effects of noise and surface scatter multipath on the one-way ranging errors of a singlesideband tone ranging modem used in an airplane-satellite link. With appropriate redefinition of parameters the results are shown to apply approximately to double-sideband tone ranging modems at high signal/ noise and signal/multipath ratios. The theoretical results are applied to obtain numerical results on ranging error for typical system geometries and sea states and for a representative hemispherical-coverage aircraft antenna. Multipath is shown to cause larger ranging errors than previously indicated. The need for additional channel measurements is pointed out.
Multiprocessor system on chip with shared memory using crossbar topology

Multiprocessor system on chip offers a set of processors, embedded in one single chip. A parallel application can, then, be scheduled to each processor, in order to accelerate its execution, using either shared memory or message passing for exchanging data. In this case, the use of a shared bus is no longer a viable solution, due to its high contention. In order to allow for non-blocking parallelism, we implemented the interconnection network based on the crossbar topology. In this kind of interconnection, processors have full access to their own memory module simultaneously, besides been able to address the whole memory. One processor accesses the memory module of another processor only when it needs to retrieve data generated by the latter. This paper presents the specification and modelling of an interconnection network based on the crossbar topology. The aim of this work is to investigate the performance characteristics of a parallel application running on this platform.
[Congenital toxoplasmosis: randomised comparison of strategies for retinochoroiditis prevention].

In France, children with confirmed congenital toxoplasmosis receive a treatment for a period of 12 to 24 months. Such prolonged treatment may generate potentially severe risks, in particular hematologic and cutaneous. Our objective is to compare the effectiveness of two therapeutic strategies on the prevention of retinochoroiditis by a randomized, non-inferiority, open-label, parallel study including 486 children, 3 to 6 months of age with a non-severe form of congenital toxoplasmosis. Following randomization, pyrimethamine-sulphonamide treatment is initiated for a period of three months, followed by a treatment with Fansidar(®) for 9 months, or therapeutic abstention. Follow-up visits during a two-year period will include an examination of the eye, a blood test, and questionnaires to evaluate the children's quality of life and their parents' anxiety. Confirming the non-inferiority of the effectiveness of a short-term treatment will improve the quality of life of parents and children.
A Digital Text Watermarking for Word Document

Text documents are the most dominant medium being used in the digital time and they require complete protection. A text watermarking algorithm based on Word Software (Microsoft Word or WPS Word) for document protection and copyright protection is proposed. The complete imperceptibility is achieved by the Font.Hidden attribute of Office Word. We implement this algorithm in C++ language and use a binary image as the watermark in the embedding algorithm. Experimental results demonstrate that this algorithm has completely imperceptibility, high robustness and can authenticate the copyright.
Modal Logic for Open Minds

In Modal Logic for Open Minds, Johan van Benthem provides an introduction to the field of modal logic, outlining its major ideas and exploring the numerous ways in which various academic fields have adopted it. Van Benthem begins with the basic theories of modal logic, examining its relationship to language, semantics, bisimulation, and axiomatics, and then covers more advanced topics, such as expressive power, computational complexity, and intelligent agency. Many of the chapters are followed by exercises.
Visual grammars and their neural networks

We exhibit a systematic way to derive neural nets for vision problems. It involves formulating a vision problem as Bayesian inference or decision on a comprehensive model of the visual domain given by a probabilistic grammar. A key feature of this grammar is the way in which it eliminates model information, such as object labels, as it produces an image; correspondence problems and other noise removal tasks result. The neural nets that arise most directly are generalized assignment networks. Also there are transformations which naturally yield improved algorithms such as correlation matching in scale space and the Frameville neural nets for high-level vision. Networks derived this way generally have objective functions with spurious local minima; such minima may commonly be avoided by dynamics that include deterministic annealing, for example recent improvements to Mean Field Theory dynamics. The grammatical method of neural net design allows domain knowledge to enter from all levels of the grammar, including `abstract' levels remote from the final image data, and may permit new kinds of learning as well.
Dynamic Spectrum Access Considering Channel Fading in Cognitive Networks

This paper investigated the method of Dynamic Spectrum Access (DSA) in cognitive networks, considering the PU channels both time-varying and fading. We used the Partially Observable Markov Decision Process (POMDP) framework to model this problem and designed a greedy strategy. The simulation results shows that the proposed strategy obtained better throughput performance than the existing works.
Lobular carcinoma in situ increases the risk of local recurrence in selected patients with stages I and II breast carcinoma treated with conservative surgery and radiation

Lobular carcinoma in situ (LCIS) is a known risk factor for the development of invasive breast carcinoma. However, little is known regarding the impact of LCIS in association with an invasive carcinoma on the risk of an ipsilateral breast tumor recurrence (IBTR) in patients who are treated with conservative surgery (CS) and radiation therapy (RT). The purpose of this study was to examine the influence of LCIS on the local recurrence rate in patients with early stage breast carcinoma after breast‐conserving therapy.
A stereo matching algorithm using line segment features

A binocular-stereo-matching algorithm, based on a line matching method, which does not require the horizontal epipolar line constraint is presented. The method makes use of the line searching window determined by the epipolar lines of the extreme pixels of a given line segment and two circles whose radius is equal to the maximum possible disparity. The proposed algorithm was implemented on the KAISION-I system, designed for real-time image processing, and has been tested with various types of real scenes. The experimental results show that the proposed algorithm can be a useful tool for solving the correspondence problem in 3D computer vision. <<ETX>>
Integrating multi-view transmission system into MPEG-21 stereoscopic and multi-view DIA (digital item adaptation)

As digital broadcasting technologies have been rapidly progressed, users' expectations for realistic and interactive broadcasting services also have been increased. As one of such services, 3D multi-view broadcasting has received much attention recently. In general, all the view sequences acquired at the server are transmitted to the client. Then, the user can select a part of views or all the views according to display capabilities. However, this kind of system requires high processing power of the server as well as the client, thus posing a difficulty in practical applications. To overcome this problem, a relatively simple method is to transmit only two view-sequences requested by the client in order to deliver a stereoscopic video. In this system, effective communication between the server and the client is one of important aspects. In this paper, we propose an efficient multi-view system that transmits two view-sequences and their depth maps according to user's request. The view selection process is integrated into MPEG-21 DIA (Digital Item Adaptation) so that our system is compatible to MPEG-21 multimedia framework. DIA is generally composed of resource adaptation and descriptor adaptation. It is one of merits that SVA (stereoscopic video adaptation) descriptors defined in DIA standard are used to deliver users' preferences and device capabilities. Furthermore, multi-view descriptions related to multi-view camera and system are newly introduced. The syntax of the descriptions and their elements is represented in XML (eXtensible Markup Language) schema. If the client requests an adapted descriptor (e.g., view numbers) to the server, then the server sends its associated view sequences. Finally, we present a method which can reduce user's visual discomfort that might occur while viewing stereoscopic video. This phenomenon happens when view changes as well as when a stereoscopic image produces excessive disparity caused by a large baseline between two cameras. To solve for the former, IVR (intermediate view reconstruction) is employed for smooth transition between two stereoscopic view sequences. As well, a disparity adjustment scheme is used for the latter. Finally, from the implementation of testbed and the experiments, we can show the valuables and possibilities of our system.
TCP/IP modeling and validation

We discuss the different issues to be considered when modeling the TCP protocol in a real environment. The discussion is based on measurements we made over the Internet. We show that the Internet is so heterogeneous that a simplistic assumption about TCP congestion control or the network may lead to erroneous results. We outline some of our results in this field, and we present a novel approach For a correct validation of a model for TCP.