Miracle-dz/UniFAR-FTUs huggingface dataset:
Diffusion approximation as a modelling tool in congestion control and performance evaluation

Diffusion theory is already a vast domain of modelling and performance evaluation. This tutorial does not cover all results but it presents in a coherent way an approach we have adopted and used in analysis of a series of models concerning evoluation of some traffic control mechanisms in computer and communication networks. Diffusion approximation is here presented from an engineer’s point of view, stressing its utility and commenting numerical problems of its implementation. Diffusion approximation is a method to model the behavior of a single queueing station or a network of stations. It allows us to include in a queueing model general sevice times, general (also self-similar) input streams and to investigate transient states, which are of interest in presence of bursty and constantly changing traffic.
Automatic Modelling and Forecasting with Artificial Neural Networks- A forecasting competition evaluation

During 2007 we conducted an empirical evaluation of the accuracy of artificial Neural Networks (NN) and other methods of Computational Intelligence (CI) in time series prediction through a dedicated forecasting competition: the NN3 (www.neural-forecasting-competition.com). The competition aimed to resolve two research questions: (a) what is the current performance of CI methods in comparison to established statistical forecasting methods, and (b) what are the current “best practices” regarding the methodologies to model CI such as NN for time series forecasting. The NN3 competition evaluated the ex ante accuracy of multiple step ahead predictions across multiple error metrics. The data sample contained two homogeneous sets of 111 or 11 time series of varying length (short and long) and different time series patterns (seasonal and non-seasonal) taken from the original M3-competition, in order to analyse the conditions under which a particular method would perform well and to compare the accuracy to the contenders in the earlier competition. The NN3 competition attracted 60 submissions of CI methods as well as novel statistical contenders, one of the largest forecasting competitions conducted to date. The final results suggest that for monthly time series of different length and seasonality a variety of different CI methods are capable of forecasting automatically using a consistent methodology and show a robust and comparative performance, but that statistical methods still outperform the majority of CI- methods.
Results of a prototype television bandwidth compression scheme

The transmitter/receiver system for bandwidth or data-rate compression of television signals, described herein, is a prototype model of the experimental system of Cherry et al. [1]. The system is suitable for both black-and-white or half-tone pictures, in realistic noise conditions. The system parameters my be adjusted so that an optimum run-length encoding may be found; the great advantages of run-length quantizing are shown, especially with regard to practical instrumentation, leading to the use of buffer stores of modest capacity. One particular cheap form of receiver operates on a quantized-variable-velocity principle and, being much more simple and cheap than the transmitter, is suitable for use in situations requiring many receivers.
The Roles of Nonlinguistic Statistical Learning and Memory in Language Skill

Prof. Dongsun Yim, PhD, Department of Communication Disorders, Ewha Womans University, 11-1, Daehyun-dong, Seodaemun-gu, Seoul, Korea e-mail: sunyim@ewha.ac. kr tel. : + 82 2 3277 6720 Background & Objectives: Statistical learning of transitional probabilities is a basic mechanism that may influence language performance. This study investigated whether nonlinguistic statistical learning can predict language performance as well as the role of memory as a potential mediating link between statistical learning and language performance. Methods: Participants included 20 typically achieving, school-aged children and 20 adults who completed auditory and visual statistical learning tasks and related memory tasks. Participants also completed tasks that assessed acquired language knowledge (grammatical judgment and a standardized language test) and language processing efficiency (rapid naming and non-word repetition). Results: Nonlinguistic statistical learning ability significantly contributed to language performance, illustrating the general learning mechanism underlying both linguistic and nonlinguistic domains. Statistical learning contributed no significant variance after memory to performance in the language processing tasks. Conversely, statistical learning but not memory performance was a significant predictor of performance in the language knowledge tasks. The results illustrate the important roles of both memory and statistical learning in language performance. Discussion & Conclusion: The results indicate that statistical learning appears to be more directly associated with language tasks that emphasize complex semantic and grammatical knowledge learned over time rather than language tasks that emphasize access and retrieval of less complex linguistic information. Additionally, statistical learning operates similarly across modalities, and memory is an important component of real time learning. (Korean Journal of Communication Disorders 2010;15;381-396)
Water quality mapping using digital camera images

The objective of this study was to implement a low-cost airborne remote sensing system to provide an alternative solution for remote sensing given the difficulty in obtaining cloud-free satellite scenes of the equatorial region. An inexpensive sensor, a Kodak DC 290 digital camera, was used, onboard a light aircraft, Cessna 172Q. The feasibility of using camera images for remote sensing applications was tested for quantifying total suspended solids (TSS) from three estuaries located in the northern region of Peninsular Malaysia. The aircraft was flown at altitudes of 914.4 to 2438.4 m for digital image acquisition of the study areas. Water samples were collected simultaneously with the aircraft overpasses and their locations were determined by using a hand-held Global Positioning System (GPS). Oblique images were corrected for brightness variation. A simple relative atmospheric correction was performed on the multidate images. The captured colour images were then separated into three bands (red, green and blue) for multispectral analysis. The digital numbers (DNs) were extracted corresponding to the sea data locations for each band. A multiband regression algorithm was developed based on a reflectance model, which is a function of the inherent optical properties of water, and this in turn can be related to the concentration of the TSS. Data from different scenes were combined and then divided into two sets, one for calibration of the algorithm and the other for a validation analysis. The calibrated algorithm had a correlation coefficient (R) of 0.96 and a root mean square error (RMSE) of approximately 17 mg l−1. The validation analysis showed that the algorithm could estimate the TSS concentration within an RMSE of about 23 mg l−1 and an R value of 0.95. The calibrated algorithm was used to generate water quality maps for all images. The maps were geometrically corrected and colour coded for visual interpretation.
A high-speed, low-power bipolar digital circuit for Gb/s LSI's: current mirror control logic

A novel low-power bipolar circuit for Gb/s LSIs, current mirror control logic (CMCL), is described. To reduce supply voltage and currents, the current sources of emitter-coupled-logic (ECL) series gate circuits are removed and the lower differential pairs are controlled by current mirror circuits. This enables circuits with the same function as two-stacked ECL circuits to operate at supply voltage of -2.0 V and reduces the current drawn through the driving circuits for the differential pairs to 50% of the conventional level shift circuits (emitter followers) in ECL. This CMCL circuit achieves 3.1-Gb/s (D-FF) and 4.3-GHz (T-FF) operation with a power supply voltage of -2.0 V and power dissipation of only 1.8 mW/(FF).
Analysis of Scheduling and Topology-Control Algorithms for Wireless Ad Hoc Networks

The ubiquity of wireless communication is one of the major innovations of the previous decades. In recent years especially wireless sensor networks evolved from theoretical consideration to practical application. In wireless sensor networks, energy conservation is crucial for the lifetime of the network. Since communication consumes most of the energy, research in recent years has focused on achieving more energy-efficient communication. One mechanism to improve the efficiency of communication is Time Division Multiple Access (TDMA) scheduling, which can be used to manage the medium access. TDMA schedules divide the time into time slots and assign those time slots to transmissions. In this thesis we study TDMA scheduling algorithms that enable efficient simultaneous transmission based on the Signal to Interference and Noise Ratio (SINR) model. In our simulations with the network simulator ns-3, we compare different SINR models and show that the throughput achieved with TDMA schedules is considerably higher than the throughput achieved with IEEE 802.11a CSMA/CA. Another mechanism that has been considered in this thesis is topology control. Topology control aims at achieving more efficient communication by selecting communication links and thus reducing the energy required for transmission and minimizing interference. However, many well-known topology control algorithms have only been analyzed theoretically. We use simulations in ns-3 to study the throughput performance and the energy-efficiency of several well-known topology control algorithms such as the Yao Graph and XTC among others. For wireless communication according to the IEEE 802.11a standard, we observe that the throughput performance depends primarily on the number of hops that are on average necessary to transmit packets from one node in the network to another node, and only secondly on further aspects such as the signal strength of the used communication links (given they are above some threshold). Regarding energy efficiency the results of our simulations show that for fixed transmission powers the consumed energy is strongly correlated to the time needed to finish the transmissions, and to the average length of the selected communication links for variable transmission powers.
The chemistry and kinetic behavior of Cu‐Cr‐As/B wood preservatives. II. Fixation of the Cu/Cr system on wood

The kinetic behavior of a Cr6+/Cu2+ system in its reaction with wood has been elucidated. The same reactions with carbohydrates and lignin of wood for CrVI alone are still present. Approximately 20% of the copper is fixed to the guaiacyl units of lignin in the form of copper chromate; the remaining copper forms complexes with cellulose and mainly with the guaiacyl units of lignin. The CrVI/lignin guaiacyl unit complexes already found for the treatment of wood with CrO3 are still the main CrVI complexes formed. Copper chromate is present as [Cu(H2O)2(guaiacol)]CrO4(guaiacol) complexes, and CuCrO4 bridges between different guaiacyl units of the lignin network appear to be likely. Substantial interference of the Cu2+ ions in the second-zone reactions of CrVI with wood occurs. The amount of CrVI and CrIII fixed onto lignin and cellulose compares well with experimental values. Rate constants, energies of activation, and Arrhenius equations of the various reactions have been obtained. The amount of Cu2+ interference in the reaction has also been calculated.
Assessing a Professional Development for Teaching Assistants in a Project-Based Guided Inquiry General Chemistry Lab

The purpose of this investigation was to explore changes in teaching assistants’ (TAs) content knowledge, perceptions of their role, and perceptions of the effectiveness of a professional development following professional development. The professional development was informed by the K-12 professional development and TA training literature bases as well as situated learning theory. It was designed for TAs implementing a project-based guided inquiry approach to General Chemistry laboratory instruction. The professional development was assessed using a sequential mixed methods approach. Participants included 8 graduate TAs and 5 undergraduate TAs. Data collection included TA pre-, post-, and delayed-post surveys and post- and delayed-post interviews. Data were analyzed using t-tests and systematic data analysis (Miles & Huberman, 1994). Results indicate TAs’ content knowledge significantly improved following the professional development (M=80.2%, t(11) = 2.20, p =. 025) and was maintained over the semester. By the end of the semester, the majority of TAs perceived their roles to include facilitating student learning (61.5%) and helping students act like scientists (53.4%). TAs cited modeling, performing experiments, and discussing logistics as the most helpful professional development components. TAs with no teaching experience and low content knowledge prior to the professional development had more malleable beliefs compared to TAs with previous teaching experience. The results of this investigation suggest situated learning theory may be an effective professional development model for TAs teaching reforms-based general chemistry lab courses. Further, TA previous experience, confidence, content knowledge, and self-efficacy may influence the extent to which professional development changes TAs beliefs. Future research will focus on examining TA self-efficacy, TA practice, and TA impact on student outcomes following implementation of professional development to support a project-based guided inquiry approach to general chemistry laboratory instruction.
CORRESPONDANCES ENTRE SAVOIRS LOCAUX ET SCIENTIFIQUES : PERCEPTIONS DES CHANGEMENTS CLIMATIQUES ET ADAPTATIONS ETUDE EN REGION COTONNIERE DU NORD DU BENIN

A survey carried out in four regions of Benin with different climatic profiles have shown producers' perceptions on climatic changes, their consequences and the different adapted measures taken by producers in order to deal with such consequences. Methodologies used comprise group discussions as well as individual interviews with open-ended, semi open and open questionnaires. The present paper is based on research results from 110 family farms of two villages in the northern region. Climate is Sudanese and the production system is cotton based. Recent climate trends perceived by producers are: irregular rainfalls, shortening of cultivation season, occurrence of violent winds and a increase of temperatures. Conventional analyses of climate series highlight significant increases of maxima and minima temperatures, although fail to show significant increases in violent winds as well as significant differences in rainfall distributions. Adaptive measures put to use by producers are many, but scarcely compensate negative effects of climate changes. Farms with little production means remain vulnerable. The study of producers' perceptions of climate changes traduces the need for a new approach in the analysis of climatic variables based on micro spatial and temporal scales.
Comparing the knowledge quality in rough classifier and decision tree classifier

This paper presents a comparative study of two rule based classifier; rough set (R c ) and decision tree (DT c ). Both techniques apply different approach to perform classification but produce same structure of output with comparable result. Theoretically, different classifiers will generate different sets of rules via knowledge even though they are implemented to the same classification problem. Hence, the aim of this paper is to investigate the quality of knowledge produced by R c and DT c when similar problems are presented to them. In this case, four important performance metrics are used as comparison, the accuracy of classification, rules quantity, rules length and rules coverage. Five dataset from UCI Machine Learning are chosen and then mined using R c toolkit namely ROSETTA while C4.5 algorithm in WEKA application is chosen as DT c rule generator. The experimental result shows that R c and DT c own capability to generate quality knowledge since most of the results are comparable. R c outperform as an accurate classifier, produce shorter and simpler rule with higher coverage. Meanwhile, DT c obviously generates fewer numbers of rules with significant difference.
Turkish Primary School Students' Strategies in Solving a Non-Routine Mathematical Problem and Some Implications for the Curriculum Design and Implementation.

Turkish primary mathematics curriculum emphasizes the role of problem solving for teaching mathematics and pays particular attention to problem solving strategies. Patterns as a subject and the use of patterns as a non-routine problem solving strategy are also emphasized in the curriculum. The primary purpose of this study was to determine how primary school students who learn mathematics in this context approached non-routine problems. The secondary purpose of this study was to discuss how effective this context could be for non-routine problem solving and to develop some perspectives for curriculum design and implementation. With these purposes, a rich problem in terms of problem solving strategies was employed and eight 6 grade students (12-13 years old) participated in the study. The problem solution attempts made by the students for 5 weeks indicated that their non-routine problem solving strategies were quite poor and inflexible. The results of the study also showed that the students used the pattern-seeking strategy as a simple search for regularity. These results were discussed in terms of both internal and external consistency problems to be taken into account when designing and implementing a curriculum.
Effect of Computer Assisted Instruction (CAI) on the Secondary School Students' Achievement in Science.

Computer-assisted instruction (CAI) is an interactive instructional technique whereby a computer is used to present the instructional material and monitor the learning that takes place. This study was designed to see the effect of computer-assisted instruction as a supplementing strategy on the academic achievement of secondary school students in the subject of science. The major objectives of the study were: (1) To find out the relative effects of computer-assisted instruction as a supplementing strategy on academic achievement in science; and (2) To investigate the difference between treatment effects on male and female students. To achieve the objectives of the study, the following null hypotheses were tested: (1) There is no significant difference between the mean scores of the students taught science with CAI as supplementing strategy and without CAI; and (2) There is no significant difference between the mean scores of male and female students of experimental and control groups.
Input estimation for uncertain linear singular systems and robust stabilization

In this paper, the problem of state and input estimation for linear singular systems with unknown inputs is concerned. An equivalent standard state spaces system is derived for the purpose of the observer design. The necessary and sufficient conditions for the existence of, the observer and the simple method to design the observer are given. The robust stability of the closed-loop obtained by dynamic output feedback is also discussed.
Walking Algorithm of Humanoid Robot on Uneven Terrain with Terrain Estimation

Humanoid robots are expected to achieve stable walking on uneven terrains. In this paper, a control algorithm for humanoid robots walking on previously unknown terrains with terrain estimation is proposed, which requires only minimum modification to the original walking gait. The swing foot trajectory is redesigned to ensure that the foot lands at the desired horizontal positions under various terrain height. A compliant terrain adaptation method is applied to the landing foot to achieve a firm contact with the ground. Then a terrain estimation method that takes into account the deformations of the linkages is applied, providing the target for the following correction and adjustment. The algorithm was validated through walking experiments on uneven terrains with the full-size humanoid robot Kong.
Unifying framework for development of message-passing applications

This thesis focuses on the development of applications for distributed memory systems in the area of scientific and engineering computations. The work addresses the problems inherent to rapid development of parallel applications and the complexity of tools used during their implementation. Herein, an abstract computation model for describing MPI (Message Passing Interface) applications is proposed. In the described topic of interest, MPI is the de facto API. The proposed approach is based on the usage of visual programming for expressing parallel aspects and communication in a developed application. The intention is not to create a complete program visually; rather, a user writes sequential parts of the application in C++ and puts them into the visual program. This allows simple modification of the communication structure and provides immediate visual feedback of the program's behavior through a visual debugger. An abstract model is also designed in a way that provides a unified view of activities that are used during development, including debugging, performance analyses, and verifications. While tools exist in all of these areas, they are usually single-purpose tools. In the proposed approach, all these activities are roofed by a single conceptual frame; everything from configurations to providing results of analyses uses one set of terms. The thesis makes the following contributions: It introduces the syntax and semantics of the visual language for describing parallel aspects and communication in applications for distributed memory systems. The semantics of the language is formalized and the usage of the language is demonstrated for various problems. These examples show that the sizes of diagrams describing the visual programs remain reasonably small for many practical parallel applications. Measurements show that the performance of the resulting programs is close to manually created C++ applications. Also, the features of the proposed approach may help in various ways in common activities that occur during development. The ideas presented in this thesis are implemented as a tool named Kaira (\url{http://verif.cs.vsb.cz/kaira/}); it is an open source tool released under GPL (GNU General Public License).
Growth and characterization of a new langasite‐type single crystal Sr3NbAl1.5Ga1.5Si2O14

Single crystals of Sr3NbAl1.5Ga1. 5Si2O14 (SNAGS) with langasite structure have been successfully grown by Czochralski method. The X‐ray diffraction (XRD) verified that the as‐grown crystal was isostructural with A3BC3D2O14 structure and the lattice parameters were calculated as follows: a = 8.242 Å, c = 5.041 Å, V = 296.6 Å3. The piezoelectric coefficient d11 was 5.7pC/N, which was 2.47 times of α‐quartz (d11=2.31pC/N). The electric resistivity was up to 3.04×106 Ωcm at 700 °C for X‐cut sample. In addition, the transmission spectrum of the SNAGS crystal showed that it had a high transmittance (>80%) in the range of 350‐800 nm and exceeded 90% above 520 nm. These results suggest that the SNAGS crystals have potential applications in high‐temperature piezoelectric sensors and optical techniques. (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)