Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning to combine foveal glimpses with a third-order Boltzmann machine

We describe a model based on a Boltzmann machine with third-order connections that can learn how to accumulate information about a shape over several fixations. The model uses a retina that only has enough high resolution pixels to cover a small area of the image, so it must decide on a sequence of fixations and it must combine the "glimpse" at each fixation with the location of the fixation before integrating the information with information from other glimpses of the same object. We evaluate this model on a synthetic dataset and two image classification datasets, showing that it can perform at least as well as a model trained on whole images.
Managing Change: An Ontology Version Control System

In this paper we present the basic requirements and initial design of a system which manages and facilitates changes to an OWL ontology in a multi-editor environment. This system uses a centralized client-server architecture in which the server maintains the current state and full history of all managed ontologies. Clients can access the current ontology version, all historical revisions, and differences between arbitrary revisions, as well as metadata associated with revisions. This system will be used by many other ontology based services, such as incremental reasoning, collaborative ontology development, advanced ontology search, and ontology module extraction. Taken holistically, this network of services will provide a rich environment for the development and management of ontology based information systems. 1 Motivation and Requirements We need for a system that manages access to a changing ontology. This requirement is experienced by a variety applications with different stakeholders. An illustrative use case is presented below. A large distributed organization requires integration and alignment of many heterogeneous data sources and information artifacts. They facilitate such integration by employing one or more expressive OWL ontologies that exist in defined relations to data sources, information artifacts, and an enterprise conceptual model. These ontologies, as a critical infrastructure components, have stakeholders throughout the organization and outside its boundaries. Further, they are developed and maintained concurrently by many parties. Individual stakeholders participate in the ontology engineering process in different ways. Some are primarily consumers, but may make detailed edits to areas of the ontologies critical to them. Others are charged with maintaining high-level ontology coherence and use an integrated ontology development environment, such as Protege-OWL, to collaborate with similar editors in realtime, leveraging tools to maintain a dynamic view of the ontology. All stakeholders rely on the ontologies being available and consistent across the organization. This use case illustrates a set of requirements: Client Performance The network is a potential bottleneck of any distributed or client-server system, but the critical work of ontology development is
What about the White Women?: Racial Politics in a Women's Studies Classroom.

This paper is an analysis of racial politics in a women's studies course. As instructors of a course entitled Women of Color, we experienced much resistance from students about the de-centering of whiteness in the curriculum. In this article, we use Ruth Frankenberg's concepts of whiteness, power evasiveness, and race consciousness to theorize the origins of and solutions to this resistance. Further, we describe how ideologies of colorblindness frame the discourse on race for most students, and how this limits their ability to move from a racial discourse of diversity to one of difference. We also offer suggestions about addressing this type of student resistance in the future
Achievement, Parental Support and Gender Differences in Attitudes Toward Mathematics

AbstractThe purpose of this study was to investigate the relationships of attitudes toward mathematics with mathematics achievement, parental support, and gender. A secondary analysis was conducted using nationally representative samples of 13-year-old students in the United States (n = 3,846) and Thailand (n = 3,528), which were collected as a part of the Second International Mathematics Study (Garden, 1987). A multivariate general linear model was used to analyze the data within each country. Four attitude scales (Mathematics and Myself, Mathematics and Society, Mathematics as a Male Domain, and Mathematics Anxiety) were used as the criterion variables. Mathematics achievement, parental support, and gender were used as the predictor variables. In both countries, achievement, parental support, and gender were significant predictors of attitudes toward mathematics. The data suggest that there are gender differences in attitudes toward mathematics for 13-year-olds in the United States and Thailand. The lar.
Template Visible Map GT box Neg Proposal Training Patch Head ‐ Shoulder Part Detector ( ConvNet ) Part

Recent advances in pedestrian detection are attained by transferring the learned features of Convolutional Neural Network (ConvNet) to pedestrians. This ConvNet is typically pre-trained with massive general object categories (e.g. ImageNet). Although these features are able to handle variations such as poses, viewpoints, and lightings, they may fail when pedestrian images with complex occlusions are present. Occlusion handling is one of the most important problem in pedestrian detection. Unlike previous deep models that directly learned a single detector for pedestrian detection, we propose DeepParts, which consists of extensive part detectors. DeepParts has several appealing properties. First, DeepParts can be trained on weakly labeled data, i.e. only pedestrian bounding boxes without part annotations are provided. Second, DeepParts is able to handle low IoU positive proposals that shift away from ground truth. Third, each part detector in DeepParts is a strong detector that can detect pedestrian by observing only a part of a proposal. Extensive experiments in Caltech dataset demonstrate the effectiveness of DeepParts, which yields a new state-of-the-art miss rate of 11.89%, outperforming the second best method by 10%.
Chapter 4 RESOURCE RESERVATIONS IN SHARED-MEMORY MULTIPROCESSOR SOCS

Consumer electronics vendors increasingly deploy shared-memory multiprocessor SoCs, such as Philips Nexperia, to balance flexibility (late changes, software download, reuse) and cost (silicon area, power consumption) requirements. With the convergence of storage, digital television, and connectivity, these media-processing systems must support numerous operational modes. Within a mode, the system concurrently processes many streams, each imposing a potentially dynamic workload on the scarce system resources. The dynamic sharing of scarce resources is known to jeopardize robustness and predictability. Resource reservation is an accepted approach to tackle this problem. This chapter applies the resource reservation paradigm to interrelated SoC resources: processor cycles, cache space, and memory access cycles. The presented virtual platform approach aims to integrate the reservation mechanisms of each shared SoC resource as the first step towards robust, yet flexible and cost-effective consumer products.
Effect of rater race on conclusions regarding differential prediction in cognitive ability tests.

The possibility of predictive bias by race in employment tests is commonly examined by across-group comparisons of the slopes and intercepts of regression lines using test scores to predict performance measures. This research assumed that the criteria, primarily supervisory ratings, were unbiased. However, a concern is that the apparent lack of differential prediction in cognitive ability tests may be an artifact of the predominant use of performance ratings provided by supervisors who are members of the majority group; a criterion that is potentially biased against members of the minority group. We posited that ratings by a supervisor of the same race as the employee being rated would be less open to claims of bias. We compared ability-performance relationships in samples of Black and White employees that allowed for between-subjects and within-subjects comparisons under 2 conditions: when all employees were rated by a White supervisor and when each employee was rated by a supervisor of the same race. Neither analysis found evidence of predictive bias against Black employees.
The Implementation of a Mobile Java Debug Tool

As the handsets integrated the J2ME environment is increasing in recent time. After PhoneME which is one implementation of the J2ME had become an open project, transplanting it to many different platforms become a hotspot for some time. There are some implementations for the online debugging between the PC and specific embedded device. But there isn’t a well-designed architecture for the debugging processes between the PC and the mobile phone, there just some assistance tools for co-debug. As the mobile phone industry developing, there are many smart phones with affluent hardware resource. This makes the co-debug between PC and smart mobile phone become possible. In this paper, we present a debug framework for the JAVA application development platform across the PC and mobile phone. With this framework, we can develop the MIDlets for specific embedded device more convenient.
Visualization and functional assessment of proximal and middle left anterior descending coronary stenoses in humans with magnetic resonance imaging.

BACKGROUND Coronary artery bypass grafting improves survival in patients with >70% luminal diameter narrowing of the 3 major epicardial coronary arteries, particularly if there is involvement of the proximal portion of the left anterior descending (LAD) coronary artery. Measurement of coronary flow reserve can be used to identify functionally important luminal narrowing of the LAD artery. Although magnetic resonance imaging (MRI) has been used to visualize coronary arteries and to measure flow reserve noninvasively, the utility of MRI for detecting significant LAD stenoses is unknown. METHODS AND RESULTS Thirty subjects (23 men, 7 women, age 36 to 77 years) underwent MRI visualization of the left main and LAD coronary arteries as well as measurement of flow in the proximal, middle, or distal LAD both at rest and after intravenous adenosine (140 microgram/kg per minute). Immediately thereafter, contrast coronary angiography and when feasible, intracoronary Doppler assessments of coronary flow reserve, were performed. There was a statistically significant correlation between MRI assessments of coronary flow reserve and (a) assessments of coronary arterial stenosis severity by quantitative coronary angiography and (b) invasive measurements of coronary flow reserve (P<0.0001 for both). In comparison to computer-assisted quantitative coronary angiography, the sensitivity and specificity of MRI for identifying a stenosis >70% in the distal left main or proximal/middle LAD arteries was 100% and 83%, respectively. CONCLUSIONS Noninvasive MRI measures of coronary flow reserve correlated well with similar measures obtained with the use of intracoronary Doppler flow wires and predicted significant coronary stenoses (>70%) with a high degree of sensitivity and specificity. MRI-based measurement of coronary flow reserve may prove useful for identification of patients likely to obtain a survival benefit from coronary artery bypass grafting.
Natural Selection on Female Life-History Traits in Relation to Socio-Economic Class in Pre-Industrial Human Populations

Life-history theory predicts that resource scarcity constrains individual optimal reproductive strategies and shapes the evolution of life-history traits. In species where the inherited structure of social class may lead to consistent resource differences among family lines, between-class variation in resource availability should select for divergence in optimal reproductive strategies. Evaluating this prediction requires information on the phenotypic selection and quantitative genetics of life-history trait variation in relation to individual lifetime access to resources. Here, we show using path analysis how resource availability, measured as the wealth class of the family, affected the opportunity and intensity of phenotypic selection on the key life-history traits of women living in pre-industrial Finland during the 1800s and 1900s. We found the highest opportunity for total selection and the strongest selection on earlier age at first reproduction in women of the poorest wealth class, whereas selection favoured older age at reproductive cessation in mothers of the wealthier classes. We also found clear differences in female life-history traits across wealth classes: the poorest women had the lowest age-specific survival throughout their lives, they started reproduction later, delivered fewer offspring during their lifetime, ceased reproduction younger, had poorer offspring survival to adulthood and, hence, had lower fitness compared to the wealthier women. Our results show that the amount of wealth affected the selection pressure on female life-history in a pre-industrial human population.
A Systematic Approach to System State Restoration during Storage Controller Micro-Recovery

Micro-recovery, or failure recovery at a fine granularity, is a promising approach to improve the recovery time of software for modern storage systems. Instead of stalling the whole system during failure recovery, micro-recovery can facilitate recovery by a single thread while the system continues to run. A key challenge in performing micro-recovery is to be able to perform efficient and effective state restoration while accounting for dynamic dependencies between multiple threads in a highly concurrent environment. We present Log(Lock), a practical and flexible architecture for performing state restoration without re-architecting legacy code. We formally model thread dependencies based on accesses to both shared state and resources. The Log(Lock) execution model tracks dependencies at runtime and captures the failure context through the restoration level. We develop restoration protocols based on recovery points and restoration levels that identify when micro-recovery is possible and the recovery actions that need to be performed for a given failure context. We have implemented Log(Lock) in a real enterprise storage controller. Our experimental evaluation shows that Log(Lock)-enabled micro-recovery is efficient. It imposes < 10% overhead on normal performance and < 35% overhead during actual recovery. However, the 35% performance overhead observed during recovery lasts only six seconds and replaces the four seconds of downtime that would result from a system restart.
Feeding to Minimize Nitrogen Excretion by Dairy Cows 1

Dairy cows utilize feed crude protein (CP; N x 6.25) with much greater efficiency than other ruminant livestock but still excrete about 2-3 times more N in manure than in milk. This contributes to increased costs of milk production and to environmental N pollution. The function of dietary CP is to supply the cow with metabolizable protein (MP) as absorbed amino acids (AA) but any extra dietary CP that does not contribute absorbed AA that are used in production will be lost in the urine. Urinary N is the most polluting form of excretory N because much is lost as atmospheric ammonia or into surface and ground water. We conducted a number of trials testing various levels of CP in diets formulated from typical Midwest feeds. Generally, there were no increases in yields of milk, fat-corrected milk or protein with more than 16.5% dietary CP. In one trial, reducing CP to 15.6%, but adding rumen undegraded protein (RUP) as heated soybean meal (SBM), did not give production equal to 16.6% CP. However, fish meal, especially low soluble fish meal, and canola meal were found to be more effective sources of RUP than SBM or cottonseed meal. Supplementing rumen-protected methionine has also been shown to be effective for allowing some reduction in dietary CP without losing milk yield. Frequent sampling and analysis of feed ingredients is very important for tracking the CP contents of the actual diet fed. Monitoring milk urea can also be used to assess both dietary CP and urinary N 1 Mention of any trademark or proprietary product in this paper does not constitute a guarantee or warranty of the product by the USDA or the Agricultural Research Service and does not imply its approval to the exclusion of other products that also may be suitable. excretion in lactating cows. The NRC (2001) protein feeding model is useful for predicting production responses to alterations in dietary protein and should be used regularly. Hay-crop silages are the most degradable source of dietary CP. Where possible, replacing alfalfa silage with alfalfa hay will improve CP efficiency and reduce N excretion. Reducing grain particle size increases ruminal starch digestion and increases microbial protein formation, so long as ruminal pH is not depressed. The NRC (2001) model can also be used to match rumen-degraded protein with carbohydrate fermentation. Future research developments will allow even lower dietary CP levels to be fed, thus reducing N excretion, without loss of animal productivity.
CODA

To exploit parallelism and scalability of multiple GPUs in a system, it is critical to place compute and data together. However, two key techniques that have been used to hide memory latency and improve thread-level parallelism (TLP), memory interleaving, and thread block scheduling, in traditional GPU systems are at odds with efficient use of multiple GPUs. Distributing data across multiple GPUs to improve overall memory bandwidth utilization incurs high remote traffic when the data and compute are misaligned. Nondeterministic thread block scheduling to improve compute resource utilization impedes co-placement of compute and data. Our goal in this work is to enable co-placement of compute and data in the presence of fine-grained interleaved memory with a low-cost approach. To this end, we propose a mechanism that identifies exclusively accessed data and place the data along with the thread block that accesses it in the same GPU. The key ideas are (1) the amount of data exclusively used by a thread block can be estimated, and that exclusive data (of any size) can be localized to one GPU with coarse-grained interleaved pages; (2) using the affinity-based thread block scheduling policy, we can co-place compute and data together; and (3) by using dual address mode with lightweight changes to virtual to physical page mappings, we can selectively choose different interleaved memory pages for each data structure. Our evaluations across a wide range of workloads show that the proposed mechanism improves performance by 31% and reduces 38% remote traffic over a baseline system.
Pedestrian localization in moving platforms using dead reckoning, particle filtering and map matching

Localization in global navigation satellite system denied environments using inertial sensors alone, or radio sensors alone or a combination of both are the currently active research topics. The current research works are primarily focused on static environments with earth fixed coordinate frames, having nonmoving maps. In this research work, we use micro electromechanical sensors based inertial sensors, band pass filtering, particle filtering, maps and map matching techniques for pedestrian localization with respect to on ground moving platforms such as train or bus. Since these platforms are moving, the maps of such platforms are moving maps with respect to earth centered, earth fixed coordinate frames. The techniques of this research work could further be extended and adapted to other moving platforms such as airplanes, boats and submarines.
Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach

Evolutionary algorithms (EAs) are often well-suited for optimization problems involving several, often conflicting objectives. Since 1985, various evolutionary approaches to multiobjective optimization have been developed that are capable of searching for multiple solutions concurrently in a single run. However, the few comparative studies of different methods presented up to now remain mostly qualitative and are often restricted to a few approaches. In this paper, four multiobjective EAs are compared quantitatively where an extended 0/1 knapsack problem is taken as a basis. Furthermore, we introduce a new evolutionary approach to multicriteria optimization, the strength Pareto EA (SPEA), that combines several features of previous multiobjective EAs in a unique manner. It is characterized by (a) storing nondominated solutions externally in a second, continuously updated population, (b) evaluating an individual's fitness dependent on the number of external nondominated points that dominate it, (c) preserving population diversity using the Pareto dominance relationship, and (d) incorporating a clustering procedure in order to reduce the nondominated set without destroying its characteristics. The proof-of-principle results obtained on two artificial problems as well as a larger problem, the synthesis of a digital hardware-software multiprocessor system, suggest that SPEA can be very effective in sampling from along the entire Pareto-optimal front and distributing the generated solutions over the tradeoff surface. Moreover, SPEA clearly outperforms the other four multiobjective EAs on the 0/1 knapsack problem.
Primary Metastatic Breast Cancer: The Impact of Locoregional Therapy

The impact of treatment for the primary tumor on distant metastases and survival in primary metastatic breast cancer patients is controversial. Previous retrospective studies and meta-analyses suggested a survival benefit for the removal of the primary tumor. Early follow-up data from 2 prospectively randomized trials presented at San Antonio Breast Cancer Symposium 2013 could not confirm this. Only a very small subgroup of patients with solitary bone metastases seemed to profit from surgery, while patients with multiple visceral metastases showed a worse prognosis with initial surgery. There are no studies available with the primary aim to investigate the impact of axillary lymph node surgery or locoregional radiotherapy on the survival of stage IV breast cancer patients. Based on current data, locoregional treatment in primary metastatic breast cancer should not be recommended in patients with asymptomatic primary tumor as a matter of routine. More solid conclusion of the impact of primary tumor treatment in stage IV breast cancer patients on their prognosis will be reached with the completion of the ongoing prospectively randomized trials. Until these studies are completed, locoregional therapy, which can provoke additional morbidity in a metastatic setting with limited live expectancy, is exclusively indicated for palliative reasons.
Peer Victimization: The Case for Social Work Intervention

In this article, the author summarizes the research on bullying and discusses implications for practice. Children involved in peer victimization or bullying are at greater risk of having adjustment problems that may persist into adulthood. Because bullying unfolds in the context of the peer group, the school, and the community, a comprehensive framework is needed to address the factors influencing bullying and the interactions among them. This perspective is consistent with social work's mission and with the person-in-environment framework. Social workers are uniquely situated to help children, youth, and their families affected by bullying and to address peer victimization at all levels of intervention.