Miracle-dz/UniFAR-FTUs huggingface dataset:
Planar visualization of vortical flows

Abstract This article presents two over-looked post-processing techniques which provide the investigator with additional tools for data analysis and visualization. Both techniques exploit the trend for planar experimental data collection and are implemented in two-dimensions. Critically, both techniques are suitable for use on computational and experimental datasets, require no a-priori knowledge of the flow-field, and minimal user interaction during processing. Firstly, line integral convolution will be introduced as an alternative to streamline or in-plane velocity vector visualization. Secondly, a feature identification procedure will be outlined that can be used to reduce datasets for clearer visualization and provide quantitative information about topological flow features.
A computational analysis of Turkish makam music based on a probabilistic characterization of segmented phrases

This study targets automatic analysis of Turkish makam music pieces on the phrase level. While makam is most simply defined as an organization of melodic phrases, there has been very little effort to computationally study melodic structure in makam music pieces. In this work, we propose an automatic analysis algorithm that takes as input symbolic data in the form of machine-readable scores that are segmented into phrases. Using a measure of makam membership for phrases, our method outputs for each phrase the most likely makam the phrase comes from. The proposed makam membership definition is based on Bayesian classification and the algorithm is specifically designed to process the data with overlapping classes. The proposed analysis system is trained and tested on a large data set of phrases obtained by transferring phrase boundaries manually written by experts of makam music on printed scores, to machine-readable data. For the task of classifying all phrases, or only the beginning phrases to come from the main makam of the piece, the corresponding F-measures are . 52 and . 60 respectively.
A Real Implementation of Dangerous Objects Capturing in Surveillance Web

The main focus of our research is capturing dangerous objects when they appear under the surveillance camera again, while have performed a dangerous activities in other places. Our solution is a two-phase method, including object learning and capturing under the classification framework. The samples of objects and non-objects are collected to train a classifier with libSVM in object learning phase. In object capturing phase, all moving objects are detected by background subtraction, then are classified into dangerous or non-dangerous. To obtain a robust objects representation to illumination, scale, rotation etc. we fuse HSV space based color feature and multiple scale texture feature. The experimental results with real surveillance data validated the proposed method.
An RF CMOS modified-cascode LNA with inductive source degeneration

An RF CMOS low-noise amplifier (LNA) is proposed using modified-cascode topology to reduce the voltage supply and consequently the power dissipation. The circuit was simulated and designed for 0.5 /spl mu/m CMOS MOSIS process. At 1 GHz, the LNA noise figure (NF) is 1.62 dB, forward gain is 18.6 dB and reverse isolation is -45.5 dB. The LNA consumes 12.5 mW from a 1 V power supply.
A medical microsensor for blood glucose monitoring

The fabrication and characterization of a microelectronic-based sensor for blood glucose are presented. This microsensor consists of a two-electrode electrochemical cell and a current-to-voltage amplifier. It is implemented by using the TSMC 0.6 u CMOS technology with the die size of 1.0 mm/spl times/1.0 mm. The enzymatic area of this two-electrode cell is 600 u/spl times/800 u that is enough to generate the dynamic range of the induced currents from 0 to 300 nA. According to the simulation results, a linear conversion of the current-to-voltage amplifier can be achieved with a rate of 12 mV per nano-ampere that can sense blood glucose concentration of 0.026 mM. The proposed microsensor can perform correct operations of amplification, calibration, and signal transformation from the chemical reactions. The prototype meter is also explored to provide rapid interpretation of blood glucose concentration at home or hospitals.
Improving Adolescent Students' Reading Comprehension with Istart

This study examines the benefits of reading strategy training on adolescent readers' comprehension of science text. Training was provided via an automated reading strategy trainer called the Interactive Strategy Trainer for Active Reading and Thinking (iSTART), which is an interactive reading strategy trainer that utilizes animated agents to provide reading strategy instruction. Half of the participants were provided with iSTART while the others (control) were given a brief demonstration of how to self-explain text. All of the students then self-explained a text about heart disease and answered text-based and bridging-inference questions. Both iSTART training and prior knowledge of reading strategies significantly contributed to the quality of self-explanations and comprehension. Adolescents with less prior knowledge about reading strategies performed significantly better on text-based questions if they received iSTART training. Conversely, for high-strategy knowledge students, iSTART improved comprehension for bridging–inference questions. Thus, students benefitted from training regardless of their prior knowledge of strategies, but these benefits translated into different comprehension gains.
Understanding of the Behaviour of Android Smartphone Users in Cameroon: Application of the Security

The popularity and adoption of smartphones has greatly attracted mobile attackers, especially for the popular platforms such as Android. In Sub-Saharan countries, the penetration of Android smartphones is considerable. Researchers tend to work mainly on technical aspects such as Android permissions to determine security risks that users face, ignoring other important aspects. This paper studies the behaviour of smartphone users in Cameroon towards security aspects on Android platform, particularly the basic practices for the security of Android recommended by Google. For this, a survey has been conducted through series of interviews with 2.500 Android Smartphones users across five regions of Cameroon: Centre, Adamawa, North, North-West, and Littoral. The research targeted different regions because of local diversity, and to cover a large area of the country to enrich the results. This research reveals that Cameroonian Android users are not aware of the security risks and therefore are directly exposed to attackers because they do not take measures. Alarmingly, it finds that users detain obsolete versions of Android or do not perform updates regularly. In sum, users are not currently (well) informed to apply basic privacy and security decisions on their devices. As it is not present in Cameroon, the present paper goes further on to propose a new web approach in Cameroon to inform and sensitise on security issues and practices in other to protect their information.
Recognition of hesitations in spontaneous speech

Both filled and unfilled (silent) hesitation types of pauses in a widely used speech database were examined for both unintended and intended pauses. A distinction is made between grammatical pauses (at major syntactic boundaries) and ungrammatical ones (within minor syntactic phrases). While unfilled pauses cannot be reliably thus separated based on silence duration alone, grammatical pauses tended to be longer. In the prepausal word before ungrammatical pauses, there were few continuation rises in fundamental frequency (F0), whereas 70% of the grammatical pauses were accompanied by a prior F0 rise. Identifying the syntactic function of such pauses could improve the performance of an automatic speech recognizer, by eliminating from consideration some hypotheses based on spectral analysis. Results are given which could allow simple identification of most filled and unfilled pauses and their syntactic function. <<ETX>>
Migration strategy and mathematical analysis of sub-population size adaptation in parallel genetic algorithm

Adaptive Parallel Genetic Algorithm adjusts the genetic parameters and operators dynamically during the iterations of evolution in order to accelerate the convergence and avoid the premature. By using the concept of coarse-grained parallelization, the population is divided into a few large subpopulations. These subpopulations evolve independently and concurrently on different processors. After a predefined period of time, some selected individuals are exchanged via a migration process. In this paper, a parallel multi-population adaptive genetic algorithm is proposed by adjusting the size of sub-population. The sub-population size is dynamically varied based on the fitness of the best individual of that sub-population compared with the mean fitness of the total population. The relevant migration strategy including synchronous and asynchronous migration is also put forward to avoid the work load imbalance in parallel genetic algorithm. Then, the convergence analysis based on schema theory is given to certify the efficiency of the Sub- Populations size adjustment in the algorithm.
Hyperspectral Image Classification via Discriminative Sparse Representation with Extended LBP Texture

Hyperspectral images (HSI) have rich texture information, so combining texture information and image spectral information can improve the recognition accuracy. Sparse representation has significant success in image classification. In this paper, we propose a new discriminative sparse-based classification framework using spectral data and extended Local Binary Patterns (LBP) texture. Firstly, we propose an extended LBP coding for HSI classification. Then we formulate an optimization problem that combines the objective function of classification with the representation error by sparsity. Furthermore, we use a procedure similar to K-SVD algorithm to learn the discriminative dictionary. The experimental results show that the proposed discriminative spasity-based classification of image including the extended LBP texture outperforms the classical HSI classification algorithms.
Modeling Internet topology

The topology of a network, or a group of networks such as the Internet, has a strong bearing on many management and performance issues. Good models of the topological structure of a network are essential for developing and analyzing internetworking technology. This article discusses how graph-based models can be used to represent the topology of large networks, particularly aspects of locality and hierarchy present in the Internet. Two implementations that generate networks whose topology resembles that of typical internetworks are described, together with publicly available source code.
Evaluating the Tourism — Environment Relationship: Central and East European Experiences

The relationship between environment and tourism in Central and Eastern Europe (CEE) can be portrayed as symbiotic, embedded within processes of postcommunist restructuring. With reference to specific CEE experience, I will evaluate briefly in this paper some of the components, problems, and outcomes of five dimensions of the tourism — environment relationship. These are: environment as a stimulus to tourism; environment as a constraint on tourism; tourism and sustainability; environment and place marketing; and tourism impacts on the environment. It is concluded that, although tourism should be viewed as just one element of postcommunist development, it has a multifaceted relationship with natural and cultural environments which demands that particular attention be paid to sustainable management.
Log-Structured B-Tree for NAND Flash Memory

Recently, NAND flash memory is becoming into the spotlight as a next-generation storage device because of its small size, fast speed, low power consumption, and etc. compared to the hard disk. However, due to the distinct characteristics such as erase-before-write architecture, asymmetric operation speed and unit, disk-based systems and applications may result in severe performance degradation when directly implementing them on NAND flash memory. Especially when a B-tree is implemented on NAND flash memory, intensive overwrite operations may be caused by record inserting, deleting, and reorganizing. These may result in severe performance degradation. Although μ -tree has been proposed in order to overcome this problem, it suffers from frequent node split and rapid increment of its height. In this paper, we propose Log-Structured B-Tree(LSB-Tree) where the corresponding log node to a leaf node is allocated for update operation and then the modified data in the log node is stored at only one write operation. LSB-tree reduces additional write operations by deferring the change of parent nodes. Also, it reduces the write operation by switching a log node to a new leaf node when inserting the data sequentially by the key order. Finally, we show that LSB-tree yields a better performance on NAND flash memory by comparing it to μ-tree through various experiments.
Feature evaluation by particle filter for adaptive object tracking

An online combined feature evaluation method for visual object tracking is put forward in this paper. Firstly, a feature set is built by combining color histogram (HC) bins with gradient orientation histogram (HOG) bins to emphasize the color representation and contour representation of an object respectively. Then a feature confidence evaluation approach in a Particle Filter framework is proposed to make that features of larger confidence can play more important roles in the instantaneous tracking, ensuring that the tracking can adapt to the appearance changes of either foreground or background. In this way, we extend the traditional filter framework from modeling motion states to modeling feature evaluation. The temporal consistency of particles can also ensure that the evolution of feature confidence is always gentle. Examples are presented to illustrate how the method adapts to changing appearances of both tracked object and background. Experiments and comparisons demonstrate that object tracking with evaluated combined features are highly reliable even when objects go across complex backgrounds.
Representing and remotivating musical processes: Modeling a recurrent musical ecology

Abstract This paper considers musical behavior in the context of an ecological dynamics, wherein the holistic experiencer adapts to the musical environment of which she/he is an active participant. As the result of this participation, a neural representation is developed which not only allows for recognition and representing ('making newly present') of previous musical situations, but also initiates remotivation, i.e. active anticipatory influence on music perception and action, based on the history of previous experiences. This system in which the experiencer influences the musical environment has a further recursive effect on the representation itself. The above dynamics is demonstrated by a connectionist, self‐organizing network model. Pilot experiments show that a dynamics of this type tends to move towards regular repetition of progressively shorter and more generalized musical sequences and an overall representational economy. This tendency may ultimately proceed to the point of ‘autistic’ behavior,.
A Study of the Effectiveness of the Louisiana Algebra I Online Course

Abstract Student enrollment in K–12 online learning programs showed a tenfold expansion in the years between 2002 and 2005. Despite increased implementation to fulfill critical local needs, there is very little evidence-based research available to inform education leaders’ decisions relating to these initiatives. To address the important question of whether online learning can be as effective as traditional face-to-face learning, this research presents the findings from a quasi-experimental design implemented to examine the effect of the Louisiana Algebra I Online initiative on student outcomes. The findings presented suggest that the Louisiana Algebra I Online model is a viable online model for providing effective Algebra I instruction.
DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS

Nowadays, corporations and a government agencies relay on computer-based information system to manage their information, this information may be classified, so it will be dangerous if it is disclosed by unauthorized persons. Therefore, there is urgent need for defense. In this research, defense has been categorized into four mechanisms technical defense, operation defense, management defense, and physical defense based on the logic of computer and network security. Also, each mechanism has been investigated and explained in the term of computer based information systems.
Methods for Answer Extraction in Textual Question Answering

In this thesis we present and evaluate two pattern matching based methods for answer extraction in textual question answering systems. A textual question answering system is a system that seeks answers to natural language questions from unstructured text. Textual question answering systems are an important research problem because as the amount of natural language text in digital format grows all the time, the need for novel methods for pinpointing important knowledge from the vast textual databases becomes more and more urgent. In addition to this, textual question answering systems form a well-defined framework with lots of existing evaluation data in which new methods can be developed and evaluated. The separate subproblem of developing answer extraction methods for extracting answers from unstructured text is an interesting problem not only by itself but also because it is quite similar to the problems of information extraction from text and of semantic annotation of text. Thus, answer extraction methods may be generalized for these problems also. In this thesis, we concentrate on developing methods for the automatic creation of answer extraction patterns. A new type of extraction patterns is developed as well. The pattern matching based approach chosen is interesting because of its language and application independence. The answer extraction methods are developed in the framework of our own question answering system. Publicly available datasets in English are used as training and evaluation data for the methods. The techniques developed
Artificial intelligence for medical knowledge representation/reasoning/acquisition

Time is central to medical reasoning in tasks such as diagnosis, prognosis, monitoring and therapy planning. However few computerized medical information systems make explicit use of time. Only in the last few years more attention has been given to the temporal aspects of medicine. The author attempts to provide a unified framework to capture diverse aspects of medical temporal reasoning such as knowledge representation, query processing, approximate reasoning and learning. <<ETX>>
Measuring stereoscopic image quality experience with interpretation based quality methodology

Stereoscopic technologies have developed significantly in recent years. These advances require also more understanding of the experiental dimensions of stereoscopic contents. In this article we describe experiments in which we explore the experiences that viewers have when they view stereoscopic contents. We used eight different contents that were shown to the participants in a paired comparison experiment where the task of the participants was to compare the same content in stereoscopic and non-stereoscopic form. The participants indicated their preference but were also interviewed about the arguments they used when making the decision. By conducting a qualitative analysis of the interview texts we categorized the significant experiental factors related to viewing stereoscopic material. Our results indicate that reality-likeness as well as artificiality were often used as arguments in comparing the stereoscopic materials. Also, there were more emotional terms in the descriptions of the stereoscopic films, which might indicate that the stereoscopic projection technique enhances the emotions conveyed by the film material. Finally, the participants indicated that the three-dimensional material required longer presentation time, as there were more interesting details to see.
A high-resolution rear projection TV for home-use

The typical characteristics of a newly developed 42-in compact PTV (projection TV) with high picture quality are shown. Descriptions are given of the optical system; the CRT and its accessories, comprising a dual focusing system, a focusing magnet, a six-pole convergence yoke, and a new green phosphor; and the digital convergence system. >
Continuous connected word recognition using whole word templates

Machines that recognize isolated words from a small, predefined vocabulary have been commercially available for many years. The whole word pattern-matching principles used in these machines are described, and it is shown how these principles can be extended to deal with continuously spoken sequences of words. Details are given of the resulting connected word recognition algorithm which has several novel features and potentially useful extensions. The algorithm has already been implemented in real-time hardware, which will be used to explore the full potential and limitations of the method in many different applications.
Interaction between hydrogen sulfide, nitric oxide, and carbon monoxide pathways in the bovine isolated retina

Purpose Nitric oxide (NO), carbon monoxide (CO) and hydrogen sulfide (H2S) are physiologically relevant gaseous neurotransmitters that are endogenously produced in mammalian tissues. In the present study, we investigated the possibility that NO and CO can regulate the endogenous levels of H2S in bovine isolated neural retina. Methods Isolated bovine neural retina were homogenized and tissue homogenates were treated with a NO synthase inhibitor, NO donor, heme oxygenase-1 inhibitor, and/donor. H2S concentrations in bovine retinal homogenates were measured using a well-established colorimetric assay. Results L-NAME (300 nM–500 µM) caused a concentration-dependent decrease in basal endogenous levels of H2S by 86.2%. On the other hand, SNP (10–300 µM) elicited a concentration-related increase in H2S levels from 18.3 nM/mg of protein to 65.7 nM/mg of protein. ZnPP-IX (300 nM–10 µM) caused a concentration-dependent increase in the endogenous production of H2S whereas hemin (300 nM–20 µM) attenuated the basal levels of H2S. Conclusion We conclude that changes in the biosynthesis and availability of both NO and CO can interfere with the pathway/s involved in the production of H2S in the retina. The demonstrated ability of NO, CO and H2S to interact in the mammalian retina affirms a physiological/pharmacological role for these gaseous mediators in the eye.
A Multi-Core Architecture for Video Streaming

In this paper, we focused on the architecture of video streaming based on multi-core processor. Compared with traditional video streaming server, multi-core architecture has a number of advantages: (1) according to system requirements, its flexible to add or remove executing core, (2) modules or units which consume much CPU resources can be configured to run concurrently on several cores, (3) multi-core architecture is fault-tolerant, and (4) the multi-core architecture fits well to future process technologies, more cores will be available in advanced process technologies, meanwhile the complexity per core does not increase. In order to improve the efficiency of video streaming and promote the concurrence number of tasks, we proposed a pipeline-parallel hybrid multi-core architecture on multi-core processor. We implemented the video streaming system with proposed architecture, and provided evidences of 48% outperformance based on Cavium OCTEON CN5860 multi-core processor than full parallel architecture.