Miracle-dz/UniFAR-FTUs huggingface dataset:
Fish Species Identification in Real-Life Underwater Images

Kernel descriptors consist in finite-dimensional vectors extracted from image patches and designed in such a way that the dot product approximates a nonlinear kernel, whose projection feature space would be high-dimensional. Recently, they have been successfully used for fine-gradined object recogntion, and in this work we study the application of two such descriptors, called EMK and KDES (respectively designed as a kernelized generalization of the common bag-of-words and histogram-of-gradient approaches) to the MAED 2014 Fish Classification task, consisting of about 50,000 underwater images from 10 fish species.
Spatialisation using Sounding Objects

A new approach to spatialisation, based on the idea of projecting sounds through virtual sounding objects, is proposed, and initial experiments are carried out using a modal synthesis model of a rectangular membrane. The effects of varying the dimensions and damping parameters of the model on the perception of spatial attributes are discussed, as well as the relevance to sound diffusion.
Application of Facial Feature Localization Using Constrained Local Models in Template-Based Caricature Synthesis

A three-step method for quasi-frontal face caricature generation is presented in the paper. First a CLM (constrained local models) and CQF (convex quadratic fitting) based face alignment approach is utilized to obtain initial locations of key facial features. Then facial components (eyebrow, eye, nose and mouth) are classified respectively into different categories defined by configuration and appearance in consistent with Chinese-Physiognomy. The mapping relationship between feature attributes and corresponding categories is learnt from a preclassified training set using the decision tree classification algorithm. Finally, separate facial feature cartoon templates are selected according to the classification results and then assembled to form an expressive caricature. Experimental results prove that the presented method is practical and robust for face caricature generation applications.
Advances in Retinal Tissue Engineering

Retinal degenerations cause permanent visual loss and affect millions world-wide. Current treatment strategies, such as gene therapy and anti-angiogenic drugs, merely delay disease progression. Research is underway which aims to regenerate the diseased retina by transplanting a variety of cell types, including embryonic stem cells, fetal cells, progenitor cells and induced pluripotent stem cells. Initial retinal transplantation studies injected stem and progenitor cells into the vitreous or subretinal space with the hope that these donor cells would migrate to the site of retinal degeneration, integrate within the host retina and restore functional vision. Despite promising outcomes, these studies showed that the bolus injection technique gave rise to poorly localized tissue grafts. Subsequently, retinal tissue engineers have drawn upon the success of bone, cartilage and vasculature tissue engineering by employing a polymeric tissue engineering approach. This review will describe the evolution of retinal tissue engineering to date, with particular emphasis on the types of polymers that have routinely been used in recent investigations. Further, this review will show that the field of retinal tissue engineering will require new types of materials and fabrication techniques that optimize the survival, differentiation and delivery of retinal transplant cells.
Optimization method for scheduling length and the number of processors on multiprocessor systems

A high performance algorithm for scheduling of tasks aims to optimize the overall execution time of the program by properly allocating and arranging the execution order of the tasks on the multiprocessor systems such that the precedence constraints among the tasks are preserved. In this paper, we propose an algorithm to get the optimality of scheduling for large problem sizes and optimize the target system. The algorithm uses geometrical analysis based on an Artificial Intelligence (AI) technique to produce the optimal solution for the allocation/scheduling problem, also it uses pruning techniques to reduce the size of the search space and to minimize the number of processors that used. The viability and potential of the proposed algorithm is demonstrated by extensive experimental results (more than 180 random task graphs) to conclude that the proposed algorithm is an efficient scheme to obtain the optimality with hard and large problem of task graphs.
Neurocognition, Insight and Medication Nonadherence in Schizophrenia: A Structural Equation Modeling Approach

Objective The aim of this study was to examine the complex relationships among neurocognition, insight and nonadherence in patients with schizophrenia. Methods Design: Cross-sectional study. Inclusion criteria: Diagnosis of schizophrenia according to the DSM-IV-TR criteria. Data collection: Neurocognition was assessed using a global approach that addressed memory, attention, and executive functions; insight was analyzed using the multidimensional ‘Scale to assess Unawareness of Mental Disorder;’ and nonadherence was measured using the multidimensional ‘Medication Adherence Rating Scale. ’ Analysis: Structural equation modeling (SEM) was applied to examine the non-straightforward relationships among the following latent variables: neurocognition, ‘awareness of positive symptoms’ and ‘negative symptoms’, ‘awareness of mental disorder’ and nonadherence. Results One hundred and sixty-nine patients were enrolled. The final testing model showed good fit, with normed χ2 = 1.67, RMSEA = 0.063, CFI = 0.94, and SRMR = 0.092. The SEM revealed significant associations between (1) neurocognition and ‘awareness of symptoms,’ (2) ‘awareness of symptoms’ and ‘awareness of mental disorder’ and (3) ‘awareness of mental disorder’ and nonadherence, mainly in the ‘attitude toward taking medication’ dimension. In contrast, there were no significant links between neurocognition and nonadherence, neurocognition and ‘awareness of mental disorder,’ and ‘awareness of symptoms’ and nonadherence. Conclusions Our findings support the hypothesis that neurocognition influences ‘awareness of symptoms,’ which must be integrated into a higher level of insight (i.e., the ‘awareness of mental disorder’) to have an impact on nonadherence. These findings have important implications for the development of effective strategies to enhance medication adherence.
Gait Based Human Recognition System using Single Triangle

Biometrics systems are becoming increasingly important, Since they provide more reliable and efficient mean of identity verification. Biometric gait recognition (i.e. recognizing people from the way their walk) is one of the recent attractive topic in biometric research. A lot of development has been done in this field. In this research work dynamic features of human body for gait recognition has been considered two features of human body that is hand and feet for gait recognition is considered. To be more specific centre point of base of both feet is taken as vertices of the triangle which will be found using hand as a third vertex. Angle formed at each vertex it the triangle is measured for each frame and after the completion of one cycle median of angles formed at each vertex is found out and stored. A cycle is formed one when a person whose walking posture is being captured reaches to the posture which is same as starting posture of the person . The gait system is designed using MAT LAB R2007b to accomplish this research work. Gray Level images are used for working.
Radio Frequency- Wireless Level Detection System by Using Spatial Field Attenuation

This paper introduces a new approach of a radio frequency (RF)-wireless fluid level detection system. The relative geometrical variation of the floating tag inside an automobile fluid container is identified. Significant fuel consumption of automobiles will be reduced by the substitution of RF-links as well as the complexity of engine carrier. To achieve the objective of this research, a sender circuit with dipole antenna and two passive ultrahigh frequency UHF)-tags with identical electrical rates are used. Considering the feasibility in automobile engine carriers, the sender circuit parameters and prototype model of automobile fluid level detection system are designed.
Chemical Antagonists of Plasminogen Activator Inhibitor-1: Mechanisms of Action and Therapeutic Potential in Vascular Disease

Plasminogen activator inhibitor-1 (PAI-1; SERPINE1) is a member of the serine protease inhibitor (SERPIN) superfamily and the predominant physiologic inhibitor of urokinase (uPA) and tissue-type (tPA) plasmingen activators. This system effectively restricts, both spatially and temporally, the conversion of plasminogen to plasmin, thereby regulating physiologic and pathophysiologic stromal remodeling. Dysregulation of this cascade frequently results in anomalies of the tissue repair response. Elevated PAI-1 levels are a causative factor in various forms of vascular disease and tissue fibrotic syndromes. Independent of its role in proteolysis, PAI-1 stimulates cell motility via interacting with low-density lipoprotein receptor-related protein-1 (LRP1) activating several cellular signaling pathwaays. PAI-1 also regulates the availability of cell-surface integrins by promoting their endocytosis in an LRP-1- dependent manner via PAI-1/uPA/uPAR (uPA receptor)/LRPI/integrin complexes. This process fine tunes the special control of pericellular proteolysis and the overall cadence of cell detachment/re-adhesion required for efficient cell migration. These data suggest that PAI-1 modulates cell motility under several contexts, both via by its established anti-proteolytic properties and as a signaling initiator.
Hand-Held Dynamometry Isometric Torque Reference Values for Children and Adolescents

Purpose: To establish hand-held dynamometry (HHD) maximal isometric muscle torque (MIT) reference values for children and adolescents who are developing typically. Methods: The MIT of 10 upper and lower limb muscle groups was assessed in 351 Caucasian youth (4 years 2 months to 17 years) using a standardized HHD protocol, previously shown to be feasible, valid, and reliable. Results: The mean MIT and 95% confidence interval of the mean for all muscle groups, for each of the 14 age groups (1 year age span for each group), and for each sex, were reported in both absolute (Nm) and normalized (Nm/kg) values. Conclusion: These HHD reference values may be helpful in the identification of muscle strength impairments in several pediatric populations, especially when bilateral impairments are present.
St Joint International Symposium on System-integrated Intelligence 2012: 69 New Challenges for Product and Production Engineering Resistivity Characteristics of Piezoresistive Based Transduction Tactile Sensing Using Pressure Sensitive Conductive Rubber Sheet

This paper presents the development of a tactile sensor based on pressure sensitive conductive rubber and outlines the resistance measurements performance. This sensor is specially designed for a robotic hand developed at UiTM Faculty of Mechanical Engineering. It exhibits piezoresistive like behaviour whose resistance change with force/pressure enables its applications as tactile sensor. The operating principle and hardware architecture of the sensor is explained. This study results in finding new alternative material selection for tactile sensor which needed more exploration and experimentation in order to discover their potential as tactile sensor for robotic hand as well as other field. In this paper, the working principle and sensor design concept are described. Further, experimental results and analysis of materials resistance characteristics are presented. The test results indicate significant drop of resistance with the increase of applied load.
AN EFFICIENT APPROACH FOR EXTRACTION OF LINEAR FEATURES FROM HIGH RESOLUTION INDIAN SATELLITE IMAGERIES

— This paper presents an Object oriented feature extraction approach in order to classify the linear features like drainage, roads etc. from high resolution Indian satellite imageries. It starts with the multiresolution segmentations of image objects for optimal separation and representation of image regions or objects. Fuzzy membership functions were defined for a selected set of image object parameters such as mean, ratio, shape index, area etc. for representation of required image objects. Experiment was carried out for both panchromatic (CARTOSAT-I) and multispectral (IRSP6 LISS IV) Indian satellite imageries. Experimental results show that the extraction of linear features can be achieved in a satisfactory level through proper segmentation and appropriate definition & representation of key parameters of image objects.
Impaired visual object recognition and dorsal/ventral stream interaction in schizophrenia.

BACKGROUND Schizophrenia is associated with well-documented deficits in high-order cognitive processes such as attention and executive functioning. The integrity of sensory-level processing, however, has been evaluated only to a limited degree. Our study evaluated the ability of patients with schizophrenia to recognize complete objects based on fragmentary information, a process termed perceptual closure. Perceptual closure processes are indexed by closure negativity (N(cl)), a recently defined event-related potential (ERP) component that is generated within the visual association cortex. This study assessed the neural integrity of perceptual closure processes in schizophrenia by examining N(cl) generation. Generation of the preceding positive (P1) and negative (N1) ERP components was also examined. METHODS We evaluated 16 patients with chronic schizophrenia and 16 healthy comparison subjects. Successively less fragmented images were presented during high-density ERP recording, which permitted the monitoring of brain activity during perceptual closure processes prior to object recognition. Analyses were performed at parieto-occipital and occipitotemporal sites consistent with dorsal and ventral stream generators of P1, N1, and N(cl). RESULTS Patients with schizophrenia showed significant impairment in the ability to recognize fragmented objects, along with impaired generation of N(cl). The amplitude of visual P1 was significantly reduced, particularly over dorsal stream sites. In contrast, the generation of visual N1 was intact. CONCLUSIONS Patients with schizophrenia are profoundly impaired in perceptual closure as indicated by both impaired performance and impaired N(cl) generation. The selective impairment in dorsal stream P1 is consistent with prior reports of impaired magnocellular processing in schizophrenia. By contrast, intact ventral N1 generation suggests that the initial stages of ventral stream processing are relatively preserved and that impaired magnocellular dorsal stream functioning in schizophrenia may lead to secondary dysregulation of ventral stream object recognition processing.
Electronic Tongue and Neural Networks, Biologically Inspired Systems Applied to Classifying Coffee Samples

In this paper, the possibility to use an electronic tongue based on a polypyrrole sensor array in classifying coffee samples has been studied. Each sensor shows a distinguished electrochemical response when exposed to the studied solutions, providing signals with a high degree of cross-selectivity. The sensor array electrochemical response is related to the interaction of the ionic and non-ionic solution compounds and to the surface of the sensors polymeric matrix. Furthermore, the electronic tongue was used to perform an analysis on coffee samples. In this case, each sensor showed a particular response to each coffee sample. Data obtained from the registered signals were used to perform a discrimination of the samples. The analysis with neural networks of the principal components (NNPC) done on the electronic tongue response to five types of commercial coffee, allows to achieve a clear differentiation of samples.
The INTEGRAL Galactic bulge monitoring program: the first 1.5 years

Aims.The Galactic bulge region is a rich host of variable high-energy point sources. Since 2005, February 17 we are monitoring the source activity in the Galactic bulge region regularly and frequently, i.e., about every three days, with the instruments onboard INTEGRAL. Thanks to the large field of view, the imaging capabilities and the sensitivity at hard X-rays, we are able to present for the first time a detailed homogeneous (hard) X-ray view of a sample of 76 sources in the Galactic bulge region. Methods: We describe the successful monitoring program and show the first results from the start of the monitoring up to 2006, April 21, i.e., for a period of about one and a half year, during three visibility seasons. We focus on the short (hour), medium (month) and long-term (year) variability in the hard X-ray bands, i.e., 20-60 keV and 60-150 keV. When available, we discuss the simultaneous observations in the soft X-ray, 3-10 keV and 10-25 keV, bands. Results: Almost all the sources in the Galactic bulge region we detect in the 20-60 keV and 60-150 keV bands are variable. During the last two and a half weeks of the third visibility season most of the known persistent (hard) X-ray sources in the Galactic Center region were not detected. Of our sample of sources, per visibility season we detect 32/33 sources in the 20-60 keV band and 8/9 sources in the 60-150 keV band above a signal to noise of 7. On average, we find per visibility season one active bright (âa†100 mCrab, 20-60 keV) black-hole candidate X-ray transient and three active weaker (âa‰25 mCrab, 20-60 keV) neutron star X-ray transients. Most of the time a clear anti-correlation can be seen between the soft and hard X-ray emission in some of the X-ray bursters. Hard X-ray flares or outbursts in X-ray bursters, which have a duration of the order of weeks are accompanied by soft X-ray drops. On the other hand, hard X-ray drops can be accompanied by soft X-ray flares/outbursts. During the course of our program we found a number of new sources, IGR J17354-3255, IGR 17453-2853, IGR J17454-2703, IGR J17456-2901b, IGR J17536-2339, and IGR J17541-2252. We report here on some of the high-energy properties of these sources. Conclusions: The high-energy light curves of all the sources in the field of view, and the high-energy images of the region, are made available through the WWW, as soon as possible after the observations have been performed, at http://isdc.unige. ch/Science/BULGE/. Appendices are only available in electronic form at http://www.aanda. org
Rev Variation during Persistent Lentivirus Infection

The ability of lentiviruses to continually evolve and escape immune control is the central impediment in developing an effective vaccine for HIV-1 and other lentiviruses. Equine infectious anemia virus (EIAV) is considered a useful model for immune control of lentivirus infection. Virus-specific cytotoxic T lymphocytes (CTL) and broadly neutralizing antibody effectively control EIAV replication during inapparent stages of disease, but after years of low-level replication, the virus is still able to produce evasion genotypes that lead to late re-emergence of disease. There is a high rate of genetic variation in the EIAV surface envelope glycoprotein (SU) and in the region of the transmembrane protein (TM) overlapped by the major exon of Rev. This review examines genetic and phenotypic variation in Rev during EIAV disease and a possible role for Rev in immune evasion and virus persistence.
Software-Based Cache Coherence with Hardware-Assisted Selective Self-Invalidations Using Bloom Filters

Implementing shared memory consistency models on top of hardware caches gives rise to the well-known cache coherence problem. The standard solution involves implementing coherence protocols in hardware, an approach with some design complexity, hardware costs, and restrictions on interconnect behavior. However, for some memory consistency models, an alternative is to enforce coherence in the software implementation of synchronization primitives, using software controlled invalidations and forced writebacks. This requires minimal hardware support but gives less selective enforcement, which affects performance. This paper proposes a novel hybrid software-hardware coherence mechanism. In this scheme, software is responsible for triggering the coherence actions-self-invalidations and writebacks-at appropriate times while hardware uses Bloom filters to perform more selective self-invalidations. We evaluate the proposed scheme on applications from two different domains: the SPLASH-2 scientific and ALP multimedia benchmarks. Experimental results show that while the software-only coherence scheme shows less performance degradation than expected, it still unacceptably degrades performance for some of the benchmarks. Filtering out unnecessary invalidations improves the worst-case performance by as much as 93 percent, and brings the performance of the hybrid scheme within five percent of full hardware coherence for 10 out of 13 benchmarks, on a 32-core CMP with a shared L2 cache.
Treatments to Optimize the Use of Artificial Insemination and Reproductive Efficiency in Beef Cattle under Tropical Environments

Bos indicus cattle, the preferred genetic group in tropical climates, are characterized by having a lower reproductive efficiency than Bos taurus. The reasons for the poorer reproductive efficiency of the Bos indicus cows include longer lengths of gestation and postpartum anestrus, a short length of estrous behavior with a high incidence of estrus occurring during the dark hours, and puberty at older age and at a higher percentage of body weight relative to mature body weight. Moreover, geography, environment, economics, and social traditions are factors contributing for a lower use of reproductive biotechnologies in tropical environments. Hormonal protocols have been developed to resolve some of the reproductive challenges of the Bos indicus cattle and allow artificial insemination, which is the main strategy to hasten genetic improvement in commercial beef ranches. Most of these treatments use exogenous sources of progesterone associated with strategies to improve the final maturation of the dominant follicle, such as temporary weaning and exogenous gonadotropins. These treatments have caused large impacts on reproductive performance of beef cattle reared under tropical areas.
A Hybrid Artificial Intelligence Approach to Monthly Forecasting of Crude Oil Price Time Series

Due to the important role of crude oil in the global economy, oil price is a key factor affecting economic plans and decisions of governments and commercial firms. Therefore, proactive knowledge of its future movements can lead to better decisions in various governmental and managerial levels. However, oil price forecasting with a satisfying accuracy has proved to be a difficult task because of the complex underlying mechanism governing oil price evolution. This paper proposes a hybrid artificial intelligence model for monthly crude oil price forecasting by means of feed-forward neural networks, genetic algorithm and k-means clustering. In order to evaluate the performance of the model, its forecasts are compared with those of the econometric model of Energy Information Administration as the best representative of econometric models, as well as three artificial intelligence models from the literature. Results show that our proposed model outperforms the above mentioned models.