Miracle-dz/UniFAR-FTUs huggingface dataset:
CVP: an energy-efficient indirect branch prediction with compiler-guided value pattern

Indirect branch prediction is becoming increasingly important in modern high-performance processors. However, previous indirect branch predictors either require a significant amount of hardware storage and complexity, or heavily rely on the expensive manual profiling. In this paper, we propose the Compiler-Guided Value Pattern (CVP) prediction, an energy-efficient and accurate indirect branch prediction via compiler-microarchitecture cooperation. The key of CVP prediction is to use the compiler-guided value pattern as the correlated information to hint the dynamic predictor. The value pattern reflects the pattern regularity of the value correlation, and thus significantly improves the prediction accuracy even in the case of deep pipeline stage or long memory latency. CVP prediction relies on the compiler to automatically identify the primary value correlation based on three high-level program substructures: virtual function calls, switch-case statements and function pointer calls. The compiler-identified information is then fed back to the dynamic predictor and is further used to hint the indirect branch prediction at runtime. We show that CVP prediction can be implemented in modern processors with little extra hardware support. Evaluations show that CVP prediction can significantly improve the prediction accuracy by 46% over the traditional BTB-based prediction, leading to the performance improvement of 20%. Compared with the state-of-the-art aggressive ITTAGE and VBBI predictors, CVP prediction can improve the performance by 5.5% and 4.2% respectively.
Spam Filter for Short Messages Using Winnow

Unsolicited bulk short message (namely spam message) is a major problem for mobile phone users. In this paper, an updatable spam filter embedded in mobile phone will be presented. Based on the traditional balanced Winnow algorithm, the system has been improved in many aspects which help to get better performance. Our spam filter is designed to process the raw text materials without time-consuming word segmentation for Chinese, and most importantly, to be easily extended to multi-class pattern by extending the original Winnow algorithm to multiple classifier. Detailed evaluations discussed in this paper will provide a strong support to the further research on spam filter for short messages.
Amodal Completion of Moving Objects by Pigeons

In a series of four experiments, we explored whether pigeons complete partially occluded moving shapes. Four pigeons were trained to discriminate between a complete moving shape and an incomplete moving shape in a two-alternative forced-choice task. In testing, the birds were presented with a partially occluded moving shape. In experiment 1, none of the pigeons appeared to complete the testing stimulus; instead, they appeared to perceive the testing stimulus as incomplete fragments. However, in experiments 2, 3, and 4, three of the birds appeared to complete the partially occluded moving shapes. These rare positive results suggest that motion may facilitate amodal completion by pigeons, perhaps by enhancing the figure – ground segregation process.
Replication and Diversity in Machine-Tape Coevolutionary Systems

The origin and evolution of genetic system is studied by metaphor of machine-tape coevolutionary system. Mutation is taken as a rewriting process which machines act on tapes. A tape consists of a bit string, encoding a machine function. Tapes can be replicated only being read by adequate machines. It is reported in our previous studies that complex but stable autocatalytic structures evolve under effects of external noise. Ensembles of such autocatalytic networks are studied in this paper. Each network, embedded in a cell structure, can exchange machines with other networks. Each cell is assumed to be duplicated when a cell has a su cient amount of mutually catalyzing machines. A daughter cell has the same kinds and populations of machines and tapes as its parental cell. It is found that developed cells are classi ed into two di erent types. One cell type has unstable dynamics which generates cell di erentiation. The other cell type has stable dynamics which generates unlimitedly identical cell types. The former di erentiating cells form an ecology with essentially large degrees of freedom. On the other hand, the latter cell types are cancerlike cells, whose dynamics cannot be e ected by the other existing cells. Hence those cancer cells are characterized as those with independent small degrees of freedom.
Image guidance of breast cancer surgery using 3-D ultrasound images and augmented reality visualization

This paper describes augmented reality visualization for the guidance of breast-conservative cancer surgery using ultrasonic images acquired in the operating room just before surgical resection. By combining an optical three-dimensional (3-D) position sensor, the position and orientation of each ultrasonic cross section are precisely measured to reconstruct geometrically accurate 3-D tumor models from the acquired ultrasonic images. Similarly, the 3-D position and orientation of a video camera are obtained to integrate video and ultrasonic images in a geometrically accurate manner. Superimposing the 3-D tumor models onto live video images of the patient's breast enables the surgeon to perceive the exact 3-D position of the tumor, including irregular cancer invasions which cannot be perceived by touch, as if it were visible through the breast skin. Using the resultant visualization, the surgeon can determine the region for surgical resection in a more objective and accurate manner, thereby minimizing the risk of a relapse and maximizing breast conservation. The system was shown to be effective in experiments using phantom and clinical data.
Coarse scene geometry estimation from sparse approximations of multi-view omnidirectional images

This paper presents a framework for coarse scene geometry estimation, based on sparse representations of omnidirectional images with geometrical basis functions. We introduce a correlation model that relates sparse components in different views with local geometrical transforms, under epipolar constraints. By combining selected pairs of features represented by sparse components, we estimate the disparity map between images, evaluate coarse depth information, and recover the relative camera pose. The proposed framework allows to estimate the geometry of the scene, hence disparity between images, using only coarse approximations of multi-view images. The experimental results demonstrate that only a few components are sufficient to estimate the disparity map and the camera pose. This is certainly beneficial for predictive multi-view compression schemes, where the scene reconstruction relies on the disparity mapping from low-resolution images in order to progressively decode the higher image resolutions.
Color and Number Counts

We present near-IR (J and Ks) number counts and colors of galaxies detected in deep VLT-ISAAC images centered on the Chandra Deep Field and Hubble Deep Field-South for a total area of 13.6 arcmin. The limiting surface brightness obtained is Ks≃22.8 mag/arcsec and J≃24.5 (1σ) on both fields. A dlogN/dm relation with a slope of ∼ 0.34 in J and ∼ 0.28 in Ks is found in both fields with no evidence of decline near the magnitude limit. The median J-Ks color of galaxies becomes bluer at magnitudes fainter than Ks∼ 18, in agreement with the different number counts slope observed in the two bands. We find a fraction (≤ 5% of the total sample) of sources with color redder than J-Ks=2.3 at magnitudes Ks> 20. Most of them appear as isolated sources, possibly elliptical or dusty starburst galaxies at redshift z > 2. The comparison of the observed number counts with models shows that our J-band and Ks-band counts are consistent with the prediction of a model based on a small amount of merging in a Ω = 1 cosmology. On the other hand, we fail to reproduce the observed counts if we do not consider merging independently of the parameters defining the universe.
Automatic Coronary Artery Segmentation Using Active Search for Branches and Seemingly Disconnected Vessel Segments from Coronary CT Angiography

We propose a Bayesian tracking and segmentation method of coronary arteries on coronary computed tomographic angiography (CCTA). The geometry of coronary arteries including lumen boundary is estimated in Maximum A Posteriori (MAP) framework. Three consecutive sphere based filtering is combined with a stochastic process that is based on the similarity of the consecutive local neighborhood voxels and the geometric constraint of a vessel. It is also founded on the prior knowledge that an artery can be seen locally disconnected and consist of branches which may be seemingly disconnected due to plaque build up. For such problem, an active search method is proposed to find branches and seemingly disconnected but actually connected vessel segments. Several new measures have been developed for branch detection, disconnection check and planar vesselness measure. Using public domain Rotterdam CT dataset, the accuracy of extracted centerline is demonstrated and automatic reconstruction of coronary artery mesh is shown.
Introducing a Framework for the Evaluation of Music Detection Tools

The huge amount of multimedia information available nowadays makes its manual processing prohibitive, requiring tools for automatic labelling of these contents. This paper describes a framework for assessing a music detection tool; this framework consists of a database, composed of several hours of radio recordings that include different types of radio programmes, and a set of evaluation measures for evaluating the performance of a music detection tool in detail. A tool for automatically detecting music in audio streams, with application to music information retrieval tasks, is presented as well. The aim of this tool is to discard the audio excerpts that do not contain music in order to avoid their unnecessary processing. This tool applies fingerprinting to different acoustic features extracted from the audio signal in order to remove perceptual irrelevancies, and a support vector machine is trained for classifying these fingerprints in classes music and no-music. The validity of this tool is assessed in the proposed evaluation framework.
Patterns for Building Communities in Collaborative

Virtual communities offer a large potential for rich human interaction. While communication technology and the internet have become ubiquitous, a culture for social interaction in virtual communities is still evolving. This paper proposes a pattern language for helping newcomers to integrate and orient within a virtual community. It focusses on the process of getting to know each others and establishing interesting connections within the community.
RNAprotect saliva: An optimal room- temperature stabilization reagent for the salivary transcriptome.

Quantitative analysis can now be performed on a panel of human salivary mRNAs identified as potential markers for oral cancer (1)(2). Translational and clinical applications of salivary transcriptome diagnostics require RNA degradation in saliva to be stopped at the time of collection and until analysis, preferably with room-temperature–compliant stabilization reagents. We compared 3 RNA stabilizing reagents for their abilities to stabilize salivary RNA at room temperature: SUPERase·In™ RNase Inhibitor (SI), RNA Later ® (RL), and RNAprotect® Saliva Reagent (RPS). We incubated saliva samples with these reagents and control saliva samples with no stabilization reagent for up to 7 days at room temperature. We isolated RNA with the RNeasy Micro Kit (QIAGEN Inc.), and measured the amount of salivary β-actin mRNA with reverse-transcriptase quantitative PCR (RT-qPCR). The cycle threshold (CT) values increased rapidly after 1 h for control and SI samples (Fig. 1A⇓ ). The RL sample also exhibited an increase in CT value starting at day 1, and its CT value at day 7 was the highest of all the samples. RPS saliva samples, unlike the SI, RL, or control samples, did not show a …
On the Adaptability and Applicability of Multi-touch User Interfaces Addressing Behavioral Interventions for Children with Autism

Principles of human-computer interaction (HCI) are imperative when it comes to efficient user interface design. This becomes even more significant when the interface is for users with special needs and especially when there is a treatment methodology incorporated in a piece of software. This study investigates user interfaces that are specifically made for children with autism-spectrum disorders. We conducted a survey to evaluate the adaptability and applicability of various interfaces. For this, we selected four of the behavioral interventions for autism namely discrete trial training (DTT), cognitive-behavioral therapy (CBT), empathy enhancement and verbal behavior approach (VBA). User interfaces (UIs) of 16 software applications were assessed for the said features. Results of this assessment revealed that these Applications were adaptable to two behavioral interventions, on the average. Moreover, these Applications were simultaneously applicable for treatment of three levels of autism; namely high functioning, low functioning, and autistic adults. These interfaces were also applicable to the children with no autism (typically developing) who acted as a controlled group.
OpenEval: Web Information Query Evaluation

In this paper, we investigate information validation tasks that are initiated as queries from either automated agents or humans. We introduce OpenEval, a new online information validation technique, which uses information on the web to automatically evaluate the truth of queries that are stated as multi-argument predicate instances (e.g., DrugHasSideEffect(Aspirin,GI Bleeding)). OpenEval gets a small number of instances of a predicate as seed positive examples and automatically learns how to evaluate the truth of a new predicate instance by querying the web and processing the retrieved unstructured web pages. We show that OpenEval is able to respond to the queries within a limited amount of time while also achieving high F1 score. In addition, we show that the accuracy of responses provided by OpenEval is increased as more time is given for evaluation. We have extensively tested our model and shown empirical results that illustrate the effectiveness of our approach compared to related techniques.
Internal secular evolution in disk galaxies: the growth of pseudobulges

Abstract Observational and theoretical evidence that internal, slow (“secular”) evolution reshapes galaxy disks is reviewed in Kormendy & Kennicutt (2004). This update has three aims. First, I emphasize that this evolution is very general – it is as fundamental to the evolution of galaxy disks as (e. g.) core collapse is to globular clusters, as the production of hot Jupiters is to the evolution of protoplanetary disks, and as evolution to red giants containing proto-white-dwarfs is to stellar evolution. One consequence for disk galaxies is the buildup of dense central components that get mistaken for classical (i. e., merger-built) bulges but that were grown out of disk stars and gas. We call these pseudobulges. Second, I review new results on pseudobulge star formation and structure and on the distinction between boxy and disky pseudobulges. Finally, I highlight how these results make a galaxy formation problem more acute. How can hierarchical clustering produce so many pure disk galaxies with no evidence for merger-built bulges?
Fingerprint Authentication System: Toward Enhancing ATM Security

One of the major problems people face is the loss of the password and not remembering it again, these have cause a lot of damage to many people and organizations. ATM fraud has been very common in all banks and the problems has created fear in many costumers heart that they prefer going to the bank to collect their money than to use an ATM, also many people are illiterate that they don’t know how to use the ATM card. So, the main aim of introducing ATM machine has not been met because you still find long queues in almost all banks in Nigeria. The existing ATM machine uses PIN-Card as a security which is very weak and easy to contravene. This paper tries to find a solution to the above problems by introducing fingerprint authentication into the existing ATM machine. A program prototype was designed to imitate a typical ATM system that uses fingerprint identification to enhance the security of the ATMs. The proposed system demonstrated a three-tier architectural structure. The verification system which centered on the enrolment, enhancement, feature extraction and matching of fingerprints. The backend database system that serves as warehouse of the templates of all ATM account holders’ pre-registered fingerprints. The system’s platform creates related transactions such as withdrawals, bill payment, buying of credit cards and balance enquiries etc. The results obtained confirm that the current approach could significantly reduce ATM fraud if not totally eradicate it. Keyword and Phrases: ATM Machine, Verification, Authentication, Minutiae-Base, Account Holder
Attentional modulation of adaptation in V4

Adaptation and visual attention are two processes that alter neural responses to luminance contrast. Rapid contrast adaptation changes response size and dynamics at all stages of visual processing, while visual attention has been shown to modulate both contrast gain and response gain in macaque extrastriate visual cortex. Because attention aims to enhance behaviorally relevant sensory responses while adaptation acts to attenuate neural activity, the question we asked is, how does attention alter adaptation? We present here single‐unit recordings from V4 of two rhesus macaques performing a cued target detection task. The study was designed to characterize the effects of attention on the size and dynamics of a sequence of responses produced by a series of flashed oriented gratings parametric in luminance contrast. We found that the effect of attention on the response dynamics of V4 neurons is inconsistent with a mechanism that only alters the effective stimulus contrast, or only rescales the gain of the response. Instead, the action of attention modifies contrast gain early in the task, and modifies both response gain and contrast gain later in the task. We also show that responses to attended stimuli are more closely locked to the stimulus cycle than unattended responses, and that attended responses show less of the phase lag produced by adaptation than unattended responses. The phase advance generated by attention of the adapted responses suggests that the attentional gain control operates in some ways like a contrast gain control utilizing a neural measure of contrast to influence dynamics.
Positively supporting women faculty in the academy through a novel mentoring community model

Purpose The purpose of this paper is to explore the ways in which an innovative higher education women’s faculty mentoring community model fosters supportive networking and career-life balance. The secondary goal is to better understand the factors that both promote and limit retention of women faculty at a large, metropolitan university. Design/methodology/approach The paper examines data from the survey component of an applied research project on understanding and supporting the complex processes of women faculty’s pathways toward self-defined success. Adopting a mixed method research approach, this manuscript focuses on the survey questions related to four key issues related to retention: mentor experiences, gender-based obstacles, a sense of support and community, and goal attainment. In addition to quantitatively examining shifts in perceptions between pre- and post-survey Likert scale questions, the authors performed a qualitative analysis of the supplemental open-ended questions, utilizing a social constructionist lens to further understand perceived influences of the mentoring community on these issues. Findings The findings revealed qualitatively important shifts in increased awareness surrounding mentoring, gender-based obstacles, interpersonal support, and career-life choices, offering critical insight into the intangible, and thus often difficult to capture, forms of support a mentoring community model can offer women faculty. Findings also reveal how definitions of success can be integrated into community mentoring models to support retention and empowering women faculty. Research limitations/implications This study is limited by its exploratory nature with one mentoring community cohort. Ongoing implementations are in place to increase the participant size and further test the mentoring model, while future research is encouraged to implement and expand the research to additional higher education institutions. Practical implications This research offers a model that can be implemented across higher education institutions for all faculty, along with offering insight into particular points that can be emphasized to increase perceptions of support, offering concrete mentoring options. Originality/value This paper contributes to the advancement of mentoring models, helping to address concerns for better supporting and advancing women faculty, with implications for further supporting marginalized faculty. It offers insight into the ways in which a mentoring model can help to address key issues of retention. Additionally, analyzing quantitative and qualitative findings concurrently allowed for insight into areas that may otherwise be overlooked due to seemingly contradictory or non-significant statistical findings.
A Texture Synthesis Method Based on Multi-resolution Matching

Texture synthesis is the field of computer graphics and related basic core issues. Studies have shown that the MRF model-based two-dimensional image texture synthesis algorithm, the synthesis results are directly affected by the magnitude of the impact of random images; that is consistent with a high degree of MRF model is better than other texture synthesis texture. The same time, the quality of synthetic images and synthesis algorithms is proportional to time-consuming. In this paper, the synthesis of the texture image decomposition strategy is introduced and the concept of multi-resolution atlas. It can be used to guide the texture partition, to improve the quality of texture synthesis. Experiments show that the proposed algorithm is effective.