Miracle-dz/UniFAR-FTUs huggingface dataset:
Directed Search In A 3D Objects Database Using SVM

3D objects, search in databases, moments, support vector machine, quadratic programming This paper introduces a content-based search algorithm for a database of 3D objects. The search is performed by giving an example object, and looking for similar ones in the database. The search system result is given as several nearest neighbor objects. The weighted Euclidean distance between a sequence of normalized moments is used to measure the similarity between objects. The moments are estimated based on uniformly distributed random generation of 3D points on the objects' surface.
Smartphone use can be addictive? A case report

Background and aims The use of mobile phones has become an integral part of everyday life. Young people in particular can be observed using their smartphones constantly, and they not only make or receive calls but also use different applications or just tap touch screens for several minutes at a time. The opportunities provided by smartphones are attractive, and the cumulative time of using smartphones per day is very high for many people, so the question arises whether we can really speak of a mobile phone addiction? In this study, our aim is to describe and analyze a possible case of smartphone addiction. Methods We present the case of Anette, an 18-year-old girl, who is characterized by excessive smartphone use. We compare Anette’s symptoms to Griffiths’s conception of technological addictions, Goodman’s criteria of behavioral addictions, and the DSM-5 criteria of gambling disorder. Results Anette fulfills almost all the criteria of Griffiths, Goodman, and the DSM-5, and she spends about 8 hr in a day using her smartphone. Discussion Anette’s excessive mobile phone usage includes different types of addictive behaviors: making selfies and editing them for hours, watching movies, surfing on the Internet, and, above all, visiting social sites. The cumulative time of these activities results in a very high level of smartphone use. The device in her case is a tool that provides these activities for her whole day. Most of Anette’s activities with a mobile phone are connected to community sites, so her main problem may be a community site addiction.
The Retrieval of Important News Stories by Influence Propagation among Communities and Categories

Nowadays, people receive information of the news stories not only from newspapers but also from online news websites. They search important news stories in order to know what happen today. However, it is hard to browse all the news stories published on a day. It is necessary to identify which news stories are more newsworthy on the specific day. In this paper, we investigate how to automatically identify the importance of news stories for different news categories on a specific day by utilizing the influence propagation among communities and news categories. In particular, we build an influence propagation model which consists of three features: category relevance, bloggers' attention and bursty influence. Based on this influence propagation model, we propose a Cross-Category Social Influence Propagation (C-SIP) approach for scoring the importance of news stories on a specific day. We evaluate our approach by using the judgment of Story Ranking Task in TREC 2010 Blog Track. The experiment shows our approach attains a prominent performance in the retrieval of important news stories and gets 9.94% improvement over the best performance of participating systems in TREC 2010 Blog Track.
Abstraction Databases in Theory and Model Checking Practice

ion Databases in Theory and Model Checking Practice Stefan Edelkamp Fachbereich Informatik Universitat Dortmund stefan.edelkamp@cs.uni-dortmund.de Alberto Lluch-Lafuente Dipartimento di Informatica Universita di Pisa lafuente@di.unipi. it
An Implementation of Digital Signature and Key Agreement on IEEE802.15.4 WSN Embedded Device

A wireless sensor network (WSN) now becomes popular in context awareness development to distribute critical information and provide knowledge services to everyone at anytime and anywhere. However, the data transfer in a WSN potentially encounters many threats and attacks. Hence, particular security schemes are required to prevent them. A WSN usually uses low power, low performance, and limited resources devices. One of the most promising alternatives to public key cryptosystems is Elliptic Curve Cryptography (ECC), due to it pledges smaller keys size. This implies the low cost consumption to calculate arithmetic operations in cryptographic schemes and protocols. Therefore, ECC would be strongly required to be implemented in WSN embedded devices with limited resources (i.e., processor speed, memory, and storage). In this paper, we present an implementation of security system on IEEE802.15. 4 WSN device with the employment of Elliptic Curve Digital Signature Algorithm (ECDSA) and Elliptic Curve Diffie-Hellman (ECDH) key exchange protocol. Our experimental results on Intel Mote2 showed that the total time for signature generation is 110 ms, signature verification is 134 ms, and ECDH shared key generation is 69 ms on the setting of 160bit security level.
AUTOMATIC TEXT CLASSIFICATION AND FOCUSED CRAWLING

Automatic classification of text documents has become an important research issue now days. We develop an automatic text categorization approach to text retrieval. Automatic text classification basically categories the text in bi-words using N-Gram approach. When it is categories the main objective is to crewel the document in particular area. Our experiments clearly indicate that automatic categorization improves the retrieval performance. Maintaining currency of search engine indices by exhaustive crawling is rapidly becoming impossible due to the increasing size and dynamic content of the web. So focused crawling is used to search the content in specific documents.
Real Time, Accurate, Multi‐Featured Rendering of Bump Mapped Surfaces

We present a new technique to render in real time objects which have part of their high frequency geometric detail encoded in bump maps. It is based on the quantization of normal‐maps, and achieves excellent result both in rendering time and rendering quality, with respect to other alternative methods. The method proposed also allows to add many interesting visual effects, even for object with large bumb maps, including non‐s rendering, chrome effects, shading under multiple lights, rendering of different materials within a single object, specular reflections and others. Moreover, the implementation of the method is not complex and can be eased by software reuse.
Time-frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions

The time-dependent shift in the spectral content of the surface myoelectric signal to lower frequencies has proven to be a useful tool for assessing localized muscle fatigue. Unfortunately, the technique has been restricted to constant-force, isometric contractions because of limitations in the processing methods used to obtain spectral estimates. A novel approach is proposed for calculating spectral parameters from the surface myoelectric signal during cyclic dynamic contractions. The procedure was developed using Cohen class time-frequency transforms to define the instantaneous median and mean frequency during cyclic dynamic contractions. Changes in muscle length, force, and electrode position contribute to the nonstationarity of the surface myoelectric signal. These factors, unrelated to localized fatigue, can be constrained and isolated for cyclic dynamic contractions, where they are assumed to be constant for identical phases of each cycle. Estimation errors for the instantaneous median and mean frequency are calculated from synthesized signals. It is shown that the instantaneous median frequency is affected by an error slightly lower than that related to the instantaneous mean frequency. In addition, the authors present a sample application to surface myoelectric signals recorded from the first dorsal interosseous muscle during repetitive abduction/adduction of the index finger against resistance. Results indicate that the variability of the instantaneous median frequency is related to the repeatability of the biomechanics of the exercise.
An Efficient Document Categorization Algorithm Based on LDA and SFL

With the explosive growth in the Web documents, classifying document from the large-scale document database has become one of the most active research fields in data mining communities. Thus, developing an efficient document categorization algorithm to automatically classify Web document is of great importance. In this paper, an efficient document classification algorithm with shuffled frog leaping (SFL) algorithm and linear discriminant analysis (LDA) is presented in this paper. The experimental results show that the proposed algorithm achieves much better performance than other conventional document classification algorithms.
Dealing with Hardware in Embedded Software: A General Framework Based on the Devil Language

Writing code that talks to hardware is a crucial part of any embedded project. Both productivity and quality are needed, but some flaws in the traditional development process make these requirements difficult to meet. We have recently introduced a new approach of dealing with hardware, based on the Devil language. Devil allows to write a high-level, formal definition of the programming interface of a peripheral circuit. A compiler automatically checks the consistency of a Devil specification, from which it generates the low-level, hardware-operating code. In our original framework, the generated code is dependent of the host architecture (CPU, buses, and bridges). Consequently, any variation in the hardware environment requires a specific tuning of the compiler. Considering the variability of embedded architectures, this is a serious drawback. In addition, this prevents from mixing different buses in the same circuit interface. In this paper, we remove those limitations by improving our framework in two ways. (i) We propose a better isolation between the Devil compiler and the host architecture. (ii) We introduce Trident, a language extension aimed at mapping one or several buses to each peripheral circuit.
Non-Stoichiometry and Calphad Modeling of Frank-Kasper Phases

One of the many singularities of Frank-Kasper phases is their ability to accommodate extremely large composition ranges by atom mixing on the different sites of the crystal structures. This phenomenon will be reviewed in the present paper with special emphasis on the experimental demonstration of this phenomenon, the theoretical calculation of disordered structures and the modeling of these phases.
UVI31+ Is a DNA Endonuclease That Dynamically Localizes to Chloroplast Pyrenoids in C. reinhardtii

UVI31+ is an evolutionarily conserved BolA family protein. In this study we examine the presence, localization and possible functions of this protein in the context of a unicellular alga, Chlamydomonas reinhardtii. UVI31+ in C. reinhardtii exhibits DNA endonuclease activity and is induced upon UV stress. Further, UVI31+ that normally localizes to the cell wall and pyrenoid regions gets redistributed into punctate foci within the whole chloroplast, away from the pyrenoid, upon UV stress. The observed induction upon UV-stress as well as the endonuclease activity suggests plausible role of this protein in DNA repair. We have also observed that UV31+ is induced in C. reinhardtii grown in dark conditions, whereby the protein localization is enhanced in the pyrenoid. Biomolecular interaction between the purified pyrenoids and UVI31+ studied by NMR demonstrates the involvement of the disordered loop domain of the protein in its interaction.
BATMAN : Maximizing Bandwidth Utilization of Hybrid Memory Systems

High bandwidth memory technologies such as HMC, HBM, and WideIO provide 4x-8x higher bandwidth than commodity DRAM while maintaining similar random access latency. The limited capacity of such high bandwidth memories require them to be architected in conjunction with traditional DRAM. Such a system would designate high bandwidth memory as Near Memory (NM) and commodity DRAM as Far Memory (FM), and rely on techniques that try to maximize NM hit rate. We show that the conventional approach of optimizing for NM hit rate is inefficient as it does not maximize the overall available system bandwidth. For example, when the application working set entirely fits in NM, all requests are serviced only by NM and the bandwidth of FM remains unutilized. We show that optimizing for overall system bandwidth, instead of hit rate of NM, can significantly improve system performance. We observe that performance can be maximized when the accesses to NM and FM are in proportion to the bandwidth of each memory. Our proposal, Bandwidth Aware Tiered-Memory Management (BATMAN), can achieve this access distribution at runtime, without relying on prior knowledge of application access pattern. For systems that do not perform data migration between NM and FM, BATMAN divides the working set randomly between NM and FM to guarantee the target access distribution. For systems that perform data migration between NM and FM (such as OS-based page migration or hardware-based cache line migration), BATMAN achieves the target access distribution by monitoring the distribution of accesses at runtime and uses this information to regulate the rate of data migration. Our evaluations on a system with 4GB of NM and 32GB of FM shows that BATMAN improves performance by as much as 40% (and on average, 10%, 10%, and 22% for systems with no data migration, OS-based page migration, and hardware cache, respectively), while requiring less than 12 bytes of storage overhead.
Study on the Relationship between Stair's Slope and Upward/Downward Gaits in Stairs

In this study, we try to find a method to investigate the relationship between stair's slope and ascent/descent gaits in stairs. With the method, we can speculate the stair slope of a particular stair from a subject's gait so that we can use it to be an initial parameter for estimating the vertical distance the subject has climbed. In this way, this study could provide a practical method to realize the calorie consumption of daily life for persons who are intended to increase calorie consumption through climbing stairs. To speculate the stair slope of a particular stair, we need to collect, analyze, and compare signals from ascent/descent gaits on stairs with normal gaits from flat ground. In our investigation, we develop a novel device called activity monitoring unit (AMU), which is equipped with a tri-axial accelerometer and includes some signal analytical and processing schemes, to identify an estimated stair slope. To assure the effectiveness of our study, we recruit 50 subjects and select three stairs in our campus to conduct a few experiments. From the results of the experiments, the accuracy of our study reaches to 92.67% in the experiments.
Classification of Multivariate Time Series Using Supervised Isomap

Multivariate time series (MTS) are used in very broad areas such as finance, medicine, multimedia and speech recognition. Most of existing approaches for MTS classification are not designed for preserving the within-class local structure of the MTS dataset. The within-class local structure is important when a classifier is used for classification. In this paper, a new feature extraction method for MTS classification based on supervised Isomap and generalized regression network is proposed. MTS samples in training dataset are projected into a low dimensional space by using the supervised Isomap, its mapping function can be learned by generalized regression network. Experimental results performed on six real-world datasets demonstrate the effectiveness of our proposed approach for MTS classification.
The Feasibility of Using Metacognitive Strategy Training to Improve Performance, Foster Participation, and Reduce Impairment Following Neurological Injury

Purpose. The purpose of this study was to estimate the effect of the Cognitive Orientation to daily Occupational Performance (CO-OP) approach compared with usual outpatient rehabilitation on activity and participation in people <3 months poststroke. Methods. An exploratory, single-blind, randomized controlled trial, with a usual-care control arm, was conducted. Participants referred to 2 stroke rehabilitation outpatient programs were randomized to receive either usual care or CO-OP. The primary outcome was actual performance of trained and untrained self-selected activities, measured using the Performance Quality Rating Scale (PQRS). Additional outcomes included the Canadian Occupational Performance Measure (COPM), the Stroke Impact Scale Participation Domain, the Community Participation Index, and the Self-Efficacy Gauge. Results. A total of 35 eligible participants were randomized; 26 completed the intervention. Post intervention, PQRS change scores demonstrated that CO-OP had a medium effect over usual care on trained self-selected activities (d = 0.5) and a large effect on untrained activities (d = 1.2). At a 3-month follow-up, PQRS change scores indicated a large effect of CO-OP on both trained (d = 1.6) and untrained activities (d = 1.1). CO-OP had a small effect on COPM and a medium effect on the Community Participation Index perceived control and on the Self-Efficacy Gauge. Conclusion. COOP was associated with a large treatment effect on follow-up performances of self-selected activities and demonstrated transfer to untrained activities. A larger trial is warranted.
Regulation of Episomal Gene Expression by KRAB/KAP1-Mediated Histone Modifications

ABSTRACT KAP1 is an essential cofactor of KRAB zinc finger proteins, a family of vertebrate-specific epigenetic repressors of largely unknown functions encoded in the hundreds by the mouse and human genomes. So far, KRAB/KAP1-mediated gene regulation has been studied within the environment of chromosomal DNA. Here we demonstrate that KRAB/KAP1 regulation is fully functional within the context of episomal DNA, such as adeno-associated viral and nonintegrated lentiviral vectors, and is correlated with histone modifications typically associated with this epigenetic regulator.
Structural and functional characterization of the human FMR1 promoter reveals similarities with the hnRNP-A2 promoter region.

Fragile X mental retardation syndrome is associated with an expansion of a CGG repeat within the 5'UTR of the first exon of the FMR1 gene, abnormal methylation of the CpG island in the promoter region, and a transcriptional silencing of this gene. We studied transcriptional regulation of the FMR1 gene using protein footprint analysis of the active and inactive gene in vivo . We identified four footprints within the FMR1 promoter region which correspond to consensus binding sites of known transcription factors, alpha-PAL/NRF1, Sp1, H4TF1/Sp1-like and c-myc. These footprints were present in normal cells with a transcriptionally active FMR1 gene. The same footprints were present in different cell types: primary fibroblasts, lymphoblastoid cells and peripheral lymphocytes. However, for the 1.1 kb region analyzed, no footprints were detected in a variety of cell types derived from patients with fragile X syndrome which have a transcriptionally inactive FMR1 gene. A BLAST nucleotide search identified sequence similarities between the region of the FMR1 gene containing the footprints and an analogous region within the promoter region of the gene for the heterogeneous nuclear ribonucleoprotein (hnRNP) A2, a member of a family of ribonucleoproteins implicated in mRNA processing and nuclear-cytoplasm transport. The nucleotide sequences identified in the hnRNP-A2 promoter region correspond to the same consensus binding sites showing DNA-protein interactions in the FMR1 gene. Our previous functional studies and the studies of others demonstrate that FMR proteins, like hnRNP-A2, are also ribonucleoproteins which appear to be involved in mRNA transport. The results from our footprint studies suggest that the expression of the FMR1 gene is regulated by the binding of specific transcription factors to sequence elements in the 5' region of the gene and that this expression may be regulated by elements in common with the hnRNP-A2 gene. Common regulation of these two genes might play an important role in the cooperative processing and transport of mRNA from the nucleus to the translation machinery.
Interspecies Knowledge Transfer for Facial Keypoint Detection

We present a method for localizing facial keypoints on animals by transferring knowledge gained from human faces. Instead of directly finetuning a network trained to detect keypoints on human faces to animal faces (which is sub-optimal since human and animal faces can look quite different), we propose to first adapt the animal images to the pre-trained human detection network by correcting for the differences in animal and human face shape. We first find the nearest human neighbors for each animal image using an unsupervised shape matching method. We use these matches to train a thin plate spline warping network to warp each animal face to look more human-like. The warping network is then jointly finetuned with a pre-trained human facial keypoint detection network using an animal dataset. We demonstrate state-of-the-art results on both horse and sheep facial keypoint detection, and significant improvement over simple finetuning, especially when training data is scarce. Additionally, we present a new dataset with 3717 images with horse face and facial keypoint annotations.
Cortical Thickness Abnormalities in Late Adolescence with Online Gaming Addiction

Online gaming addiction, as the most popular subtype of Internet addiction, had gained more and more attention from the whole world. However, the structural differences in cortical thickness of the brain between adolescents with online gaming addiction and healthy controls are not well unknown; neither was its association with the impaired cognitive control ability. High-resolution magnetic resonance imaging scans from late adolescence with online gaming addiction (n = 18) and age-, education- and gender-matched controls (n = 18) were acquired. The cortical thickness measurement method was employed to investigate alterations of cortical thickness in individuals with online gaming addiction. The color-word Stroop task was employed to investigate the functional implications of the cortical thickness abnormalities. Imaging data revealed increased cortical thickness in the left precentral cortex, precuneus, middle frontal cortex, inferior temporal and middle temporal cortices in late adolescence with online gaming addiction; meanwhile, the cortical thicknesses of the left lateral orbitofrontal cortex (OFC), insula, lingual gyrus, the right postcentral gyrus, entorhinal cortex and inferior parietal cortex were decreased. Correlation analysis demonstrated that the cortical thicknesses of the left precentral cortex, precuneus and lingual gyrus correlated with duration of online gaming addiction and the cortical thickness of the OFC correlated with the impaired task performance during the color-word Stroop task in adolescents with online gaming addiction. The findings in the current study suggested that the cortical thickness abnormalities of these regions may be implicated in the underlying pathophysiology of online gaming addiction.
Optimized APSK bit allocation for satellite communication

In this paper a novel optimal bit allocation for APSK modulation is proposed. Optimization is done by GA according to the satellite channel error sensitivity of the data. Furthermore, a new bit mapping is proposed for 16-APSK and 32-APSK. Results show the improvement of the proposed scheme with respect to the state of the art of the APSK modulation.