Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Independent Component Analysis using Support Vector Machines for Multimodal Image fusion

The objective of this study is to combine multiple images of a scene acquired by different sensors to create a new image with all important information from the i nput images. Recent studies show that bases trained using Independent Component Analysis (ICA) is effective in multisensor fusion and has improved performance over traditional wavelet approaches. In the ICA based fusion, the coefficients of the inpu t images are combined simply by selecting the coeffic ients with maximum magnitude. But this method resulted in fused images with poor contrast, due to the distortion introduced in constant background a reas. The performance of ICA based fusion can be greatly improved by using a region based approach with intelligent decision making in order to choose the significant regions in the source images. Hence, a new region based image fusion algorithm for combining visible and Infrared (IR) images using Independent Component Analysis and Support Vector Machines (SVM) is proposed. Region based joint segmentation of the source images is carried out in the spatial dom ain and important features of each region are compu ted in spatial and transform domain. A Support Vector Machine is trained to select the regions from the sourc e images with significant features and the correspond ing ICA coefficients are combined to form the fused ICA representation. The proposed algorithm is appli ed to different sets of multimodal images to valida te the robustness of the algorithm and compared with some standard image fusion methods. The fusion results demonstrate that the proposed scheme performs better than the state-of-the-art image fusion methods an d show a significant improvement in Entropy, Petrovic and Piella evaluation metrics.
Web Interface for Habitat Monitoring using Wireless Sensor Network

In the near future, the wireless sensor networks (WSN) consisting of hundreds or thousands of small sensor devices are expected to become increasingly popular due to their low cost and easy use. As a distributed system, they are usually deployed in unattended environments and aim to collect useful information from the sensed area. In this paper, we present a web interface model for habitat monitoring using wireless sensor network, which can be used for wide range of applications. The interface we developed provides a userfriendly environment and a set of functionalities that easies the interaction between the end-users and the WSN. Our web interface is characterized with modularity, which makes applications easily extensible. Keywords-Wireless Sensor Networks, Web interface, Habitat Monitoring, Mica motes
Neural sliding mode control for magnetic levitation systems

Neural sliding mode control (NSMC) may decrease chattering of the sliding mode control (SMC) and improve control accuracy of the neural control (NC). There are some problems with the common parallel structure, such as the chattering is big at start stage. In order to overcome the above problem, we propose a new serial structure for NSMC, it is called two-stage neural sliding control. A dead-zone NC is used to make the tracking error bounded, then super-twisting second-order SMC is applied to guarantee finite time convergence. This new controllers has less chattering during its discrete realization, and ensures finite time convergence. Real-time experiments for a magnetic levitation system are presented to compare this new NSMC with regular controllers, such as PID, NC, SMC, and normal NSMC.
Development of active low-angle normal fault systems during orogenic collapse: Insight from Tibet

Active north-trending rifts in Tibet vary significantly in their character as a function of extension magnitude. Most rifts are characterized by internally drained basins bounded by high-angle normal faults with Paleogene or older rocks in the footwall. However, the central part of the Yadong-Gulu Rift (near Lhasa) and the newly documented Lunggar Rift in west-central Tibet are bounded by low-angle normal faults (detachments) with mylonitic rocks and Miocene granites in the footwall, and exhibit active basin incision and intrabasin topographic highs in areas of inferred maximum extension. We suggest that Tibetan rifts initiate as high-angle normal fault and half-graben or graben basin systems and evolve in response to increasing extension and footwall isostatic rebound into detachment systems that are active at uppermost crustal levels and above which rift basin fill is being uplifted and eroded.
Energy- and Heat-Aware HPC Benchmarks

To evaluate data centers is tough. Several metrics are available to provide insight into their behaviour, but usually they are tested using simple benchmarks like LINPACK for HPC oriented data centers. A good choice of benchmarks is necessary to evaluate all the impact of applications on those data centers. One point that is often overlooked is their energy- and thermal-quality. To evaluate these qualities, adequate benchmarks are required from several points of view: from the nodes to the whole building. Classical benchmarks selection mainly focuses on time and raw performance. This article aims at shifting the focus towards an energy- and power-point of view. To this end, we select benchmarks able to evaluate data centers not only from this performance perspective, but also from the energy and thermal standpoint. We also provide insight into several classical benchmarks and method to select an adequate and small number of benchmarks in order to provide a sensible and minimum set of energy- and thermal-aware benchmarks for HPC systems.
Image quality evaluation for CARE kV technique combined with iterative reconstruction for chest computed tomography scanning

Background: To investigate the radiation dose and image quality for iterative reconstruction combined with the CARE kV technique in chest computed tomography (CT) scanning for physical examination. Methods: A total of 130 patients who underwent chest CT scanning were randomly chosen and the quality reference value was set as 80 mAs. The scanning scheme was set and the patients were randomly divided into groups according to the scanning scheme. Sixty patients underwent a chest scan with 100 kV using the CARE kV technique and SAFIRE reconstruction (value=3) (experimental group) and the other 70 patients underwent chest scanning with 120 kV (control group). The mean CT value, image noise (SD), and signal-to-noise ratio (SNR) of the apex of the lung, the level of the descending aorta bifurcation of the trachea, and the middle area of the left atrium were measured. The image quality was assessed on a 5-point scale by two radiologists and results of the two groups were compared. The CT dose index of the volume (CTDIvol), dose length product (DLP), and effective dose (ED) were compared. Results: All the images for both groups satisfied the diagnosis requirement. There was no statistical difference in the image quality between the two methods (P > 0.05). The mean CT value of the apex of the lung, the level of the descending aorta bifurcation of the trachea, and the middle area of the left atrium were not significantly different for both groups (P > 0.05), while the image noise (SD) and the signal-to-noise ratio (SNR) of the apex of the lung, the level of the descending aorta bifurcation of the trachea, and the middle area of the left atrium were statistically different for both groups (P < 0.05). The CTDIvol was 3.29 ± 1.17 mGy for the experimental group and 5.30 ± 1.53 mGy for the control group. The DLP was 114.9 ± 43.73 mGy cm for the low-dose group and 167.6 ± 44.59 mGy cm for the control group. The ED was 1.61 ± 0.61 mSv for the low-dose group and 2.35 ± 0.62 mSv for the control group (P < 0.05). Conclusion: The CARE kV technique combined with iterative reconstruction for chest CT scanning for physical examination could reduce the radiation dosage and improve CT image quality, which has a potential clinical value for imaging the thorax.
A distributed scheme for lexicon-driven handwritten word recognition and its application to large vocabulary problems

Many offline handwritten word recognition systems have been proposed since the early nineties. Most systems reported high recognition rates, however, they overlooked a very important factor in the process: speed factor. The authors explore the potential for speeding up an offline handwritten word recognition system via concurrency. The goal of the system is to achieve both full accuracy and high speed when taking into account large vocabularies. This was accomplished by integrating the recognition process with multiprocessing and distributed computing concepts. Experimental results showed that the multiprocessing environment is very promising in enhancing a sequential offline handwritten word recognition system performance.
A genetic network programming model for portfolio optimization by generating risk-adjusted trading rules

Genetic network programming (GNP) as an evolutionary computation method has been used for stock trading recently. Former researches confirm the efficiency of trading rules which are created by GNP. In this paper, GNP has been applied for stock portfolio optimization by generating risk-adjusted trading rules. There are two main novelties in this paper: 1) we use conditional Sharp ratio as a risk-adjusted measure for generating trading rules, 2) in our GNP model, binary trading rules have been extended to more realistic rules which are called trinary rules using three signals of buy, sell and no trade. We applied our GNP model on ten stocks from Tehran Stock Exchange (TSE). The numerical results show that our proposed model with three signals outperformed the previous model with two signals of buy and sell in terms of excess return and excess risk adjusted return.
Cell cycle regulated transcription: from yeast to cancer

Recent studies have revealed exciting new functions for forkhead transcription factors in cell proliferation and development. Cell proliferation is a fundamental process controlled by multiple overlapping mechanisms, and the control of gene expression plays a major role in the orderly and timely division of cells. This occurs through transcription factors regulating the expression of groups of genes at particular phases of the cell division cycle. In this way, the encoded gene products are present when they are required. This review outlines recent advances in our understanding of this process in yeast model systems and describes how this knowledge has informed analysis in more developmentally complex eukaryotes, particularly where it is relevant to human disease.
Research on the Combustion Characteristics of a Free-Piston Gasoline Engine Linear Generator during the Stable Generating Process

The free-piston gasoline engine linear generator (FPGLG) is a new kind of power plant consisting of free-piston gasoline engines and a linear generator. Due to the elimination of the crankshaft mechanism, the piston motion process and the combustion heat release process affect each other significantly. In this paper, the combustion characteristics during the stable generating process of a FPGLG were presented using a numerical iteration method, which coupled a zero-dimensional piston dynamic model and a three-dimensional scavenging model with the combustion process simulation. The results indicated that, compared to the conventional engine (CE), the heat release process of the FPGLG lasted longer with a lower peak heat release rate. The indicated thermal efficiency of the engine was lower because less heat was released around the piston top dead centre (TDC). Very minimal difference was observed on the ignition delay duration between the FPGLG and the CE, while the post-combustion period of the FPGLG was significantly longer than that of the CE. Meanwhile, the FPGLG was found to operate more moderately due to lower peak in-cylinder gas pressure and a lower pressure rising rate. The potential advantage of the FPGLG in lower NO x emission was also proven with the simulation results presented in this paper.
Integrating models of diffusion of innovations: a Conceptual Framework.

▪ Abstract This chapter provides a conceptual framework for integrating the array of variables defined in diffusion research to explicate their influence on an actor's decision to adopt an innovation. The framework groups the variables into three major components. The first component includes characteristics of the innovation itself, within which two sets of variables are defined concerning public versus private consequences and benefits versus costs of adoption. A second component involves the characteristics of innovators (actors) that influence the probability of adoption of an innovation. Within this component six sets of variables concern societal entity of innovators (either people, organizations, states, etc.), familiarity with the innovation, status characteristics, socioeconomic characteristics, position in social networks, and personal qualities. The third component involves characteristics of the environmental context that modulate diffusion via structural characteristics of the modern world. T.
Differential Group Index Dispersion of a Holey Fiber Measured by White-Light Spectral Interferometry

We present a new white-light interferometric method to measure the differential group index dispersion of a pure-silica holey fiber. The method is based on the recording a series of the spectral interferograms in an unbalanced Mach-Zehnder interferometer with the fiber of known length placed in one of the interferometer arms and the other arm with adjustable path length. We measure the equalization wavelength as a function of the path length difference, or equivalently the group index dispersion. Subtracting the group dispersion of the optical components present in the interferometer along with the fiber, we measure the wavelength dependence of the differential group index of both the pure-silica fiber glass and fundamental mode supported by the holey fiber.
A linear control approach to distributed multi-agent formations in d-dimensional space

The paper presents a linear approach for formation control of multiple autonomous agents in d-dimensional space. The generalized notion of graph Laplacian, associated to a graph with possibly negative weights on the edges, is introduced aiming to solve the formation problem of controlling a network of point agents to form a given pattern (including rotation, translation, and scaling). By assuming the number of agents is larger than d + 1, we derive that a linear distributed control law exists for this purpose if and only if certain algebraic conditions hold (or equivalently, the graph is globally rigid). Next, it is shown that the generalized graph Laplacian used to stabilize the formations can be obtained by solving a convex optimization problem. Further results are also provided to reveal the conditions under which the attained formations are congruent to or just translations of the desired one.
Face recognition using mixtures of principal components

We introduce an efficient statistical modeling technique called mixture of principal components (MPC). This model is a linear extension to the traditional principal component analysis (PCA) and uses a mixture of eigenspaces to capture data variations. We use the model to capture face appearance variations due to pose and lighting changes. We show that this more efficient modeling leads to improved face recognition performance.
On the Floer homology of cotangent bundles

This paper concerns Floer homology for periodic orbits and for a Lagrangian intersection problem on the cotangent bundle T* M of a compact orientable manifold M. The first result is a new L∞ estimate for the solutions of the Floer equation, which allows us to deal with a larger—and more natural—class of Hamiltonians. The second and main result is a new construction of the isomorphism between the Floer homology and the singular homology of the free loop space of M in the periodic case, or of the based loop space of M in the Lagrangian intersection problem. The idea for the construction of such an isomorphism is to consider a Hamiltonian that is the Legendre transform of a Lagrangian on T M and to construct an isomorphism between the Floer complex and the Morse complex of the classical Lagrangian action functional on the space of W1,2 free or based loops on M. © 2005 Wiley Periodicals, Inc.
Mining burst topical keywords from microblog stream

Microblog is becoming more and more popular in daily life, through which people can exchange small elements of content, such as short sentences, individual images, or video links. Considering millions of data produced every day, a challenging issue is how to quickly know current burst topic from large volume of continuous microblog streams. This work proposed a method for mining burst topical keywords from microblog stream based on incremental calculation method and burst theory. Considering burst topic's immanent characters, such as burst phenomenon and uncommon, a method combining these characters was proposed to weight the words of microblog stream in a fixed time interval (Time Window). Eventually, those words whose weight is over a given threshold are selected as burst topical keywords of that period. The experimental results show that the proposed method can mine the burst topical keywords which can correctly reflects the trends of burst topics in microblog.
Predicting land-use change and its impact on the groundwater system of the Kleine Nete catchment, Belgium

Land-use changes are frequently indicated to be one of the main human-induced factors influencing the groundwater system. For land-use change, groundwater re- search has mainly focused on the change in water quality thereby neglecting changes in quantity. The objective of this paper is to assess the impact of land-use changes, from 2000 until 2020, on the hydrological balance and in partic- ular on groundwater quantity, as results from a case study in the Kleine Nete basin, Belgium. New is that this study tests a methodology, which couples a land-use change model with a water balance and a steady-state groundwater model. Four future land-use scenarios (A1, A2, B1 and B2) based on the Special Report on Emission Scenarios (SRES) are modelled with the CLUE-S model. Water balance com- ponents, groundwater level and baseflow are simulated us- ing the WetSpass model in conjunction with a steady-state MODFLOW groundwater flow model. Results show that the average recharge decreases with 2.9, 1.6, 1.8 and 0.8% for scenario A1, A2, B1 and B2, respectively, over the 20 cov- ered years. The predicted reduction in recharge results in a small decrease of the average groundwater level in the basin, ranging from 2.5 cm for scenario A1 to 0.9 cm for scenario B2, and a reduction of the baseflow with maximum 2.3% and minimum 0.7% for scenario A1 and B2, respectively. Al- though these averages appear to indicate small changes in the groundwater system, spatial analysis shows that much larger changes are located near the major cities in the study area. Hence, spatial planning should take better account of effects of land-use change on the groundwater system and define mitigating actions for reducing the negative impacts of land-use change.
The effects of articulatory gestures on L2 pronunciation learning: A classroom-based study

Research on second-language (L2) speech acquisition suggests that audio-visual aids could be effective in helping learners acquire difficult L2 speech sounds (Li, 2016a). However, most previous studies have been restricted to laboratory settings rather than the classroom environment. The present study, therefore, was designed to fill this knowledge gap by analysing the effectiveness of audio-visual aids, particularly articulatory gestures, in teaching L2 speech sounds in actual classrooms. The participants were students from two classes of non-English majors who had severe difficulties with the differentiation of /θ/–/s/ and /ð/–/z/. ‘Read-aloud’ tasks were employed for pronunciation tests. The baseline data of the students’ pronunciation of the two contrasts was collected with a pre-test, and the intuitive–imitative approach was adopted for teaching. Specifically, the students were exposed to seven audio- or audio-visually recorded poems (one poem per week over the course of seven weeks) containing the target contrasts. The students in Class 1 were taught with the audio-recordings without images of the speaker’s face being displayed; in contrast, students in Class 2 were taught using audio-visual recordings, which allowed them to observe the speakers’ articulatory gestures of /θ/–/s/ and /ð/–/z/. To detect the teaching effect, a post-test was carried out after the teaching programme was completed. A delayed post-test was conducted one month after the post-test. Comparisons with the respective pre-test results indicated that students in Class 2 had a significant improvement in the pronunciation of the target contrasts in the post-test, whereas those in Class 1 did not. In the delayed post-test, neither class showed any significant difference in the pronunciation performance in comparison with the post-test. The findings, therefore, confirmed the effectiveness of exposure to audio-visual aids in teaching L2 pronunciation.
Na+/Ca2+ Exchanger 3 is Downregulated in the Hippocampus and Cerebrocortex of Rats with Hyperthermia-induced Convulsion

Background:Na+/Ca2+ exchanger (NCX) plays a crucial role in pentylenetetrazol-induced convulsion. However, it is unclear whether NCX is critically involved in hyperthermia-induced convulsion. In this study, we examined the potential changes in NCX3 in the hippocampus and cerebrocortex of rats with hyperthermia-induced convulsion. Methods:Twenty-one Sprague Dawley rats were randomly assigned to control group, convulsion-prone group and convulsion-resistant group (n = 7 in each group). Whole-cell patch-clamp method was used to record NCX currents. Both the Western blotting analysis and immunofluorescence labeling techniques were used to examine the expression of NCX3. Results:NCX currents were decreased in rats after febrile convulsion. Compared to the control group, NCX3 expression was decreased by about 40% and 50% in the hippocampus and cerebrocortex of convulsion-prone rats, respectively. Furthermore, the extent of reduction in NCX3 expression seemed to correlate with the number of seizures. Conclusions:There is a significant reduction in NCX3 expression in rats with febrile convulsions. Our findings also indicate a potential link between NCX3 expression, febrile convulsion in early childhood, and adult onset of epilepsy.
Smart car care systems and its technology prospects with service robots function

Social and human demands promote the development of automobile technology. For general vehicles, the auxiliary driving or automated driving is from a safe and comfortable level to solve human driving requirements. As the growth of the social demand for cultural and health care, the demand is bound to be reflected during the vehicle driving or proposed by consumers. It is important to consider the driver who may be in fatigue, illness and disability. In this paper, the concept of service robots in the car environment is proposed from car security, cultural and health care. The characteristics of the intelligent service robot system and core technology are discussed and the design scheme is also proposed.