Miracle-dz/UniFAR-FTUs huggingface dataset:
Developing Fuzzy Inference System For Assessing Quality Of Distorted Images

Non existence of full proof method of feature extraction of images and lack of well defined relationship between image features and its visual quality, make quality assessment of distorted/decompressed image without reference to the original image extremely difficult task. Under such circumstances, human reasoning based on subjective information play vital role in assessing quality of image. The paper aims at assessing the quality of distorted/decompressed images without any reference to the original image by designing a fuzzy inference system. Five benchmark imagesLena, Mandril, Woman with Hat, Woman_Blond_Hair and Baby are decompressed using LBG (Linde, Beuzo, Gray) procedure with varying codebook sizes and divided into different connected regions. In our problem domain the input of the fuzzy inference system is comprised of four crisp measured data expressed using linguistic variables: area, extent, eccentricity and convex area obtained from the connected regions while output is made up of linguistic variable quality of images and measured using peak signal to noise ratio (PSNR) of the decompressed images with respect to the original images. The linguistic variables are represented by fuzzy sets whose degree of membership values obtained using Gaussian distribution functions with varied mean and standard deviation. In consultation with human observers various fuzzy if-then rules are constructed where the regional parameters and quality of the images are mapped as antecedents and consequents of the rules, respectively. Finally, by applying Mamdani inference rule, the quality of a new distorted/decompressed image is predicted. Different test images after decompression and inducting distortion by Gaussian and white noises are applied to the system for quality prediction without reference to the original image. Thus, we develop a robust fuzzy inference system producing output comparable with the two reported no reference techniques. Results are validated with the objective measure of image quality. Results are validated with the objective measure of image quality and compared with the existing no-reference techniques. ________________________________________ Indrajit De, Department of Information Technology, MCKV Institute of engineering, Liluah, Howrah, indrajitde2003@yahoo.co.in, Jaya Sil, Department of Computer science, BESUS, Howrah, js@cs.becs. ac.in.
Time-lapse changes of P- and S-wave velocities and shear wave splitting in the first year after the 2011 Tohoku earthquake, Japan: shallow subsurface

S U M M A R Y We detect time-lapse changes in Pand S-wave velocities (hereafter, VP and VS, respectively) and shear wave splitting parameters associated with the 2011 Tohoku earthquake, Japan, at depths between 0 and 504 m. We estimate not only medium parameters but also the 95 per cent confidence interval of the estimated velocity change by applying a new least squares inversion scheme to the deconvolution analysis of KiK-net vertical array records. Up to 6 per cent VS reduction is observed at more than half of the analysed KiK-net stations in northeastern Japan with over 95 per cent confidence in the first month after the main shock. There is a considerable correlation between the S-wave traveltime delay and the maximum horizontal dynamic strain (MDS) by the main shock motion when the strain exceeds 5 × 10−4 on the ground surface. This correlation is not clearly observed for MDS at the borehole bottom. On the contrary, VP and shear wave splitting parameters do not show systematic changes after the Tohoku earthquake. These results indicate that the time-lapse change is concentrated near the ground surface, especially in loosely packed soil layers. We conclude that the behaviour of VP, VS and shear wave splitting parameters are explained by the generation of omnidirectional cracks near the ground surface and by the diffusion of water in the porous subsurface. Recovery of VS should be related to healing of the crack which is proportional to the logarithm of the lapse time after the main shock and/or to decompaction after shaking.
Joint Global and Local Structure Discriminant Analysis

Linear discriminant analysis (LDA) only considers the global Euclidean geometrical structure of data for dimensionality reduction. However, previous works have demonstrated that the local geometrical structure is effective for dimensionality reduction. In this paper, a novel approach is proposed, namely Joint Global and Local-structure Discriminant Analysis (JGLDA), for linear dimensionality reduction. To be specific, we construct two adjacency graphs to represent the local intrinsic structure, which characterizes both the similarity and diversity of data, and integrate the local intrinsic structure into Fisher linear discriminant analysis to build a stable discriminant objective function for dimensionality reduction. Experiments on several standard image databases demonstrate the effectiveness of our algorithm.
Mobile SeoulSearch: Automatic Mobile Regional Information Retrieval System Based on Web

The convergence of multiple technologies, including the Internet, wireless communications, geographical information systems, location-based services and mobile devices, has given rise to new types of information utilities that may be referred as mobile location-based services(LBS). We proposed and developed a regional information retrieval system for the mobile environment, called "Mobile SeoulSearch" as mobile LBS. The proposed system has some representative advantages. First, as it utilizes Webbased regional information, we can easily get much usable regional information from the Internet. Second, through it uses location-based query, we can find closest usable location information from user's location automatically. Third, it serves improved user interface for mobile devices. Last, as it uses map & related keywords by Geo-searching then we can search some Geo-word intuitively.
Uplink power adjustment in wireless communication systems: a stochastic control analysis

This paper considers mobile to base station power control for lognormal fading channels in wireless communication systems within a centralized information stochastic optimal control framework. Under a bounded power rate of change constraint, the stochastic control problem and its associated Hamilton-Jacobi-Bellman (HJB) equation are analyzed by the viscosity solution method; then the degenerate HJB equation is perturbed to admit a classical solution and a suboptimal control law is designed based on the perturbed HJB equation. When a quadratic type cost is used without a bound constraint on the control, the value function is a classical solution to the degenerate HJB equation and the feedback control is affine in the system power. In addition, in this case we develop approximate, but highly scalable, solutions to the HJB equation in terms of a local polynomial expansion of the exact solution. When the channel parameters are not known a priori, one can obtain on-line estimates of the parameters and get adaptive versions of the control laws. In numerical experiments with both of the above cost functions, the following phenomenon is observed: whenever the users have different initial conditions, there is an initial convergence of the power levels to a common level and then subsequent approximately equal behavior which converges toward a stochastically varying optimum.
Interacting with virtual and augmented worlds

For more than three decades, the main focus was to be able to model realistic decors, lights and living beings, particularly humans that should look realistic. Actually, we are aiming for interacting with these worlds in a sensitive and meanful way. In this invited talk, I will present the research that we are developping on many aspects at MIRALab: interactive modelling of virtual humans, interactive clothes modelling and animation, touching textiles, haptic interaction with hair, gaze interaction with Virtual Humans in Augmented Reality, talking and being recognized by virtual humans with memory and personality models. In this short summary, we describe mainly the problematic of modelling any body size and shape and also dress it up, all in real-time.
Statistical texture characterization from discrete wavelet representations

We conjecture that texture can be characterized by the statistics of the wavelet detail coefficients and therefore introduce two feature sets: (1) the wavelet histogram signatures which capture all first order statistics using a model based approach and (2) the wavelet co-occurrence signatures, which reflect the coefficients' second-order statistics. The introduced feature sets outperform the traditionally used energy. Best performance is achieved by combining histogram and co-occurrence signatures.
Cache-Oblivious Sparse Matrix--Vector Multiplication by Using Sparse Matrix Partitioning Methods

In this article, we introduce a cache-oblivious method for sparse matrix-vector multiplication. Our method attempts to permute the rows and columns of the input matrix using a recursive hypergraph-based sparse matrix partitioning scheme so that the resulting matrix induces cache-friendly behavior during sparse matrix-vector multiplication. Matrices are assumed to be stored in row-major format, by means of the compressed row storage (CRS) or its variants incremental CRS and zig-zag CRS. The zig-zag CRS data structure is shown to fit well with the hypergraph metric used in partitioning sparse matrices for the purpose of parallel computation. The separated block-diagonal (SBD) form is shown to be the appropriate matrix structure for cache enhancement. We have implemented a run-time cache simulation library enabling us to analyze cache behavior for arbitrary matrices and arbitrary cache properties during matrix-vector multiplication within a $k$-way set-associative idealized cache model. The results of these simulations are then verified by actual experiments run on various cache architectures. In all these experiments, we use the Mondriaan sparse matrix partitioner in one-dimensional mode. The savings in computation time achieved by our matrix reorderings reach up to 50 percent, in the case of a large link matrix.
Bidirectional interpretation of XQuery

XQuery is a powerful functional language to query XML data. This paper gives a bidirectional interpretation of XQuery to address the problem of updating XML data through materialized XQuery views. We first design an expressive bidirectional transformation language, and then translate XQuery expressions into the code of this language. As a result, an XQuery expression can execute in two directions: in the forward direction, it generates a materialized view from the source XML data; while in the backward direction, it updates the source data by putting back the updates on the view. we have implemented our approach and applied it to some XQuery use cases from a W3C draft, which confirms the practicability of this approach.
The Choice of PCR Primers Has Great Impact on Assessments of Bacterial Community Diversity and Dynamics in a Wastewater Treatment Plant

Assessments of bacterial community diversity and dynamics are fundamental for the understanding of microbial ecology as well as biotechnological applications. We show that the choice of PCR primers has great impact on the results of analyses of diversity and dynamics using gene libraries and DNA fingerprinting. Two universal primer pairs targeting the 16S rRNA gene, 27F&1492R and 63F&M1387R, were compared and evaluated by analyzing the bacterial community in the activated sludge of a large-scale wastewater treatment plant. The two primer pairs targeted distinct parts of the bacterial community, none encompassing the other, both with similar richness. Had only one primer pair been used, very different conclusions had been drawn regarding dominant phylogenetic and putative functional groups. With 27F&1492R, Betaproteobacteria would have been determined to be the dominating taxa while 63F&M1387R would have described Alphaproteobacteria as the most common taxa. Microscopy and fluorescence in situ hybridization analysis showed that both Alphaproteobacteria and Betaproteobacteria were abundant in the activated sludge, confirming that the two primer pairs target two different fractions of the bacterial community. Furthermore, terminal restriction fragment polymorphism analyses of a series of four activated sludge samples showed that the two primer pairs would have resulted in different conclusions about community stability and the factors contributing to changes in community composition. In conclusion, different PCR primer pairs, although considered universal, target different ranges of bacteria and will thus show the diversity and dynamics of different fractions of the bacterial community in the analyzed sample. We also show that while a database search can serve as an indicator of how universal a primer pair is, an experimental assessment is necessary to evaluate the suitability for a specific environmental sample.
Galactosylated poly-L-lysine targeted microbubbles for ultrasound mediated antisense c-myc gene transfection in hepatocellular carcinoma cells

Introduction The aim of the study was to investigate the efficiency of delivery and targeted binding of c-myc antisense oligodeoxynucleotide (ASODN) and find a novel therapy for hepatic carcinoma. Material and methods A targeted ultrasound microbubble compound was synthesized to deliver the c-myc ASODN by ultrasound-targeted microbubble destruction (UTMD) and applied in hepatocellular carcinoma cells (HCC) and cancer bearing mice. Lipid microbubbles were conjugated with biotinylated galactosylated poly-L-lysine (G-PLL) and SonoVue to target the hepatocellular carcinoma SMMC7721 cells with asialoglycoprotein receptors. There were four groups in both in vitro and in vivo studies: control group (group A); c-myc ASODN + G-PLL (CG group, group B); c-myc ASODN + SonoVue (CUS group, group C); c-myc ASODN + G-PLL + SonoVue (CGUS group, group D). The expression of c-myc mRNA was detected by reverse transcription-polymerase chain reaction (RT-PCR), and proliferation investigations of the SMMC7721 cells were also performed. In addition, the tumor volume was calculated and compared among different groups. Results The level of c-myc mRNA in the three experimental groups was significantly lower than that in the control group in vitro (p < 0.05). Furthermore, c-myc gene expression was suppressed more strongly in the CGUS group compared with other groups in both in vitro and in vivo studies (p < 0.05). In addition, ultrasound mediation of targeted microbubbles yielded the highest inhibition of tumor growth and cell proliferation among the four groups. Conclusions The use of a G-PLL targeted microbubble contrast agent combined with ultrasound exposure could be a potential method for increasing gene delivery efficiency. This technique is a promising nonviral approach that can be used in liver cancer.
Seismic tomography of Taiwan: Improved constraints from a dense network of strong motion stations

In this study, a large collection of 41,141 S-P times from the untapped records of the Taiwan Strong Motion Instrumentation Program (TSMIP) network is combined with the P and S wave arrival times from the Taiwan Central Weather Bureau Seismic Network (CWBSN) to image the V_p and V_p /V_s structures beneath Taiwan. The records from the 680 TSMIP stations throughout Taiwan in the past 15 years enhance the path coverage and the resolution in the tomography inversions tremendously. Our result for the V_p structure largely confirms previous studies but brings better constraint on the V_p /V_s structure. The colliding Luzon volcanic arc is characterized by a belt of high V_p and high V_p /V_s with high seismicity that includes the offshore islands of Lutao and Lanyu and the Coastal Ranges in eastern Taiwan, at the depth between about 13 and 25 km. This high V_p /V_s belt can be traced to the subduction zone in the region between Hualian and Ilan in the deeper portion. The shallow portions of the southwestern coastal plain and the Pingtung region are also characterized by a belt of high V_p /V_s with lower seismicity. Most of the events occurred at the base of the high V_p /V_s zones. We suggest that material strength in those regions may be too low to accumulate stress, which may indicate water-saturated young sediments. Finally, the Central Range region is characterized by a low V_p /V_s belt.
A Preliminary Study of Functional Brain Activation among Marijuana Users during Performance of a Virtual Water Maze Task

Numerous studies have reported neurocognitive impairments associated with chronic marijuana use. Given that the hippocampus contains a high density of cannabinoid receptors, hippocampal-mediated cognitive functions, including visuospatial memory, may have increased vulnerability to chronic marijuana use. Thus, the current study examined brain activation during the performance of a virtual analogue of the classic Morris water maze task in 10 chronic marijuana (MJ) users compared to 18 nonusing (NU) comparison subjects. Imaging data were acquired using blood oxygen level-dependent (BOLD) functional MRI at 3.0 Tesla during retrieval (hidden platform) and motor control (visible platform) conditions. While task performance on learning trials was similar between groups, MJ users demonstrated a deficit in memory retrieval. For BOLD fMRI data, NU subjects exhibited greater activation in the right parahippocampal gyrus and cingulate gyrus compared to the MJ group for the Retrieval-Motor Control contrast (NU > MJ). These findings suggest that hypoactivation in MJ users may be due to differences in the efficient utilization of neuronal resources during the retrieval of memory. Given the paucity of data on visuospatial memory function in MJ users, these findings may help elucidate the neurobiological effects of marijuana on brain activation during memory retrieval.
The Cutting Edge in Brain Science and Sportology

Objective : We aimed to establish a novel approach that enables the prediction of behavioral effects of lesions using neuroimaging data, which is applicable to sportological analyses, particularly in identifying the links between brain activity and behavior related to sports. Materials and Methods : Experimental details are described in our previous reports (Miyamoto et al ., 2013; Osada et al ., 2015). Four monkeys ( M. mulatta and M. fuscata ) were used. All experimental protocols, animal welfare, and steps for minimizing suffering were in full compliance with the Guidelines for Proper Conduct of Animal Experiments by Science Council of Japan. Functional images were acquired using a 4.7-T MRI scanner (Biospec47/40, Bruker) during a recognition or temporal-order judgment task. Monkeys performed the tasks while sitting in an MRI-compatible chair. Group analyses of image data were conducted using SPM5. Results : A task-evoked connectivity network was identified based on data from the functional imaging conducted during recognition tasks (Miyamoto et al ., 2013) and temporal-order judgment tasks (Osada et al ., 2015). A significant positive correlation was observed between the predicted impact on performance and the betweenness centrality based on task-evoked connectivity network, whereas no correlation was observed between the predicted impact on performance and the betweenness centrality based on anatomical connectivity network. Conclusions : Severity of impairment arising from local brain damage was predicted by network “hubness” of the damaged area in the task-evoked connectivity network. These findings will form the basis for future research that aims to predict the functional brain center for watching or partaking in sports.
Preliminary investigation of Boltzmann machine classifiers for speaker recognition

We propose a novel generative approach to speaker recognition using Boltzmann machines, a fledgeling non-Gaussian probabilistic framework that is increasingly gaining attention in several machine learning fields. We show how a modified i-vector representation of speech utterances enables the development of several Boltzmann machine architectures for speaker verification and we report some preliminary speaker recognition results obtained with one of them, which we refer to as Siamese twins. The Siamese twin architecture is designed to capture correlations between utterances spoken by a single speaker and it can be regarded as probabilistic analogue of the well known cosine distance metric. A relative improvement of 27% is reported on NIST-2010 telephone female data.
A pr 2 00 5 Convex Separation From Optimization Using Analytic Centers

Let K be a convex subset of Rn containing a ball of finite radius centered at c0 and contained in a ball of finite radius R. We give an oracle-polynomial-time algorithm for the weak separation problem for K given an oracle for the weak optimization problem for K. This is done by reducing the weak separation problem for K to the convex feasibility (nonemptiness) problem for a set K ′, and then building a separation oracle for K ′ using the given oracle. The algorithm employs a slight modification of the cutting-plane algorithm for convex feasibility that uses analytic centers due to Atkinson and Vaidya; where they used a hyperbox to enclose K ′, we use a hypersphere. A polynomial-time reduction from separation to optimization is well known – even when c0 and R are unknown. The advantage of our algorithm is that, despite requiring knowledge of c0 and R, it is a direct reduction (i.e. does not use the polar of K) and it uses analytic centers (as opposed to the ellipsoid method), making it useful in practice. We end with an outline of the algorithm’s application to quantum information theory.
Asynchronous P300-Based Brain-Computer Interface to Control a Virtual Environment: Initial Tests on End Users

Motor disability and/or ageing can prevent individuals from fully enjoying home facilities, thus worsening their quality of life. Advance s in the field of accessible user interfaces for domotic appliances can represent a valuable way to improve the independence of these persons. An asynchronous P300-based Brain-Computer Interface (BCI) system was recently validated with the participation of healthy young volunteers for environmental control. In this study, the asynchronous P300-based BCI for the interaction with a virtual home environment was tested with the participation of potential end-users (clients of a Frisian home care organization) with limited autonomy due to ageing and/or motor disabilities. System testing revealed that the minimum number of stimulation sequences needed to achieve correct classification had a higher intra-subject variability in potential end-users with respect to what was previously observed in young controls. Here we show that the asynchronous modality performed significantly better as compared to the synchronous mode in continuously adapting its speed to the users' state. Furthermore, the asynchronous system modality confirmed its reliability in avoiding misclassifications and false positives, as previously shown in young healthy subjects. The asynchronous modality may contribute to filling the usability gap between BCI systems and traditional input devices, representing an important step towards their use in the activities of daily living.