Miracle-dz/UniFAR-FTUs huggingface dataset:
Coordinated power-performance optimization in manycores

Optimizing the performance in multiprogrammed environments, especially for workloads composed of multi-threaded programs is a desired feature of runtime management system in future manycore processors. At the same time, power capping capability is required in order to improve the reliability of microprocessor chips while reducing the costs of power supply and thermal budgeting. This paper presents a sophisticated runtime coordinated power-performance management system called C-3PO, which optimizes the performance of manycore processors under a power constraint by controlling two software knobs: thread packing, and dynamic voltage and frequency scaling (DVFS). The proposed solution distributes the power budget to each program by controlling the workload threads to be executed with appropriate number of cores and operating frequency. The power budget is distributed carefully in different forms (number of allocated cores or operating frequency) depending on the power-performance characteristics of the workload so that each program can effectively convert the power into performance. The proposed system is based on a heuristic algorithm which relies on runtime prediction of power and performance via hardware performance monitoring units. Empirical results on a 64-core platform show that C-3PO well outperforms traditional counterparts across various PARSEC workload mixes.
Formal analysis of cross-validation for rule induction using probabilistic indices

This paper proposes a new framework for evaluation of cross-validation methods for rule induction based on statistical indices by using incremental sampling scheme. Although incremental sampling scheme is used for incremental rule induction, this paper shows that the same idea can be used for deletion of exampling, called decremental sampling scheme. Then, we applied this technique to the cross-validation method for rules define by the propositions whose constraints were define by inequalities of accuracy and coverage. The results show that the evaluation framework gives a powerful tool for evaluation of cross-validation.
Phase 1 Study of Aflibercept Administered Subcutaneously to Patients with Advanced Solid Tumors

Purpose: To determine the maximum tolerated dose or maximal administered dose and pharmacokinetic and safety profiles of s.c. administered vascular endothelial growth factor Trap (aflibercept), a novel antiangiogenic agent. Experimental Design: In this open-label, dose-escalation study, patients with advanced solid tumors were treated with subcutaneous doses of aflibercept at seven dose levels. Patients received a single dose of aflibercept and then underwent safety and pharmacokinetic assessments over the next 4 weeks. Patients then received weekly or biweekly treatment over the subsequent 6 weeks. Patients tolerating and benefiting could continue on aflibercept at the same dose and schedule until progression of disease. Results: Thirty-eight patients received at least one dose of aflibercept. Maximum tolerated dose was not reached. Due to solubility/dosing limits with the subcutaneous formulation, 1,600 μg/kg/week was the maximal administered dose. The most common toxicities were proteinuria (37%), fatigue (32%), injection site reactions (18%), nausea (17%), myalgia and anorexia (16% each), hypertension (13%), and voice hoarseness (11%). Drug-related grade 3 to 4 toxicity was uncommon (7%) and reversible: dehydration, cerebral ischemia, proteinuria, hypertension, leukopenia, and pulmonary embolism. We identified dose-proportional increases in plasma concentrations of aflibercept bound to vascular endothelial growth factor with a t1/2 of 18 days. No antiaflibercept antibodies were detected. Stable disease was maintained for at least 10 weeks in 18 patients (47%), and 2 patients maintained on study for >1 year. Conclusion: Subcutaneous aflibercept was well tolerated and had manageable side effects. Its favorable pharmacokinetic profile and potential antitumor activity warrants further evaluation. Clin Cancer Res; 16(1); 358–366
Graph parsing with s-graph grammars

A key problem in semantic parsing with graph-based semantic representations is graph parsing, i.e. computing all possible analyses of a given graph according to a grammar. This problem arises in training synchronous string-to-graph grammars, and when generating strings from them. We present two algorithms for graph parsing (bottom-up and top-down) with s-graph grammars. On the related problem of graph parsing with hyperedge replacement grammars, our implementations outperform the best previous system by several orders of magnitude.
Power control and channel access for physical-layer security of D2D underlay communication

Device-to-device (D2D) communication is a promising technology for 5G wireless communication system. Since D2D communication usually reuses the resource of cellular users, interference management and resource allocation of D2D are the mainly research directions in D2D communication underlay cellular networks. The physical-layer security problem of D2D link is rarely under studied. In this paper, we develop the Stackelberg game frame to model D2D underlay communication in cellular networks. We analyze the equilibrium solution and optimize the power control and channel access of D2D link to maximize the achievable rate of cellular users and the physical-layer secrecy rate of D2D link. We propose a power control and channel access algorithm of D2D link then. Finally, we perform numerical simulations to study the performance of the proposed algorithm.
On the feasibility of indoor broadband secondary access to 960–1215 MHz aeronautical spectrum

In this paper, we analyse the feasibility of indoor broadband service provisioning using secondary spectrum access to the 960–1215 MHz band, primarily allocated to the distance measuring equipment (DME) system for aeronautical navigation. We propose a practical secondary sharing scheme customised to the characteristics of the DME. Because the primary system performs a safety‐of‐life functionality, protection from harmful interference becomes extremely critical. The proposed scheme controls aggregate interference by imposing an individual interference threshold on the secondary users. We examine the feasibility of large scale secondary access in terms of the transmission probability of the secondary users that keeps the probability of harmful interference below a given limit. Uncertainties in the estimation of propagation loss and DME location affect the feasibility of the secondary access. Numerical results show that a large number of secondary users are able to operate in adjacent DME channels without harming the primary system even with limited accuracy on the estimation of the propagation loss. Copyright © 2013 John Wiley & Sons, Ltd.
Uncertainty visualization in the VisIt visualization environment

Visualization and analysis of very large datasets remains a significant challenge to the visualization community. Scientists have tried various techniques to deal with large data. Multiresolution data models reduce the size of the data using techniques such as mesh decimation, wavelet transformation, or data compression. The low resolution representation raises issues concerning the authenticity of the data at its resolution level. We address this issue by presenting our extensions to the VisIt visualization environment that enable the scientist to visualize both multiresolution data and the uncertainty information associated with the lower resolution representations of the data.
Machine Learning-Based Image Classification for Wireless Camera Sensor Networks

Wireless sensor networks, with their capability to capture physical phenomena at micro-scale, have changed how we collect and analyze data from the real world. Especially, using low-power cameras we can design interesting applications that provide us with previously difficult-to-capture information from the real-world. While cameras hold privacy threats in human-residing environments, they can be actively used in natural world analyzing applications. However, the disadvantage of using cameras is that the samples themselves (e.g., images) have large sizes, forcing the system to exchange more data, and in turn, decreasing energy efficiency. Given that camera-based sensor networks are usually deployed in remote locations, the lifetime of individual devices become a major concern. In this work, we target to utilize machine-learning algorithms to characterize the context of images captured from a real-world deployments. Specifically, using images from the James Reserve bird nest deployment [1], we utilize and optimize machine learning algorithms to operate on embedded low-power, resource-limited platforms. Using both a systematic and algorithmic approach, our proposed systems architecture and algorithms hold the potential to reduce the amount of data to be transmitted by as much a eight-fold.
SUPPORTING TRUSTED DATA EXCHANGES IN COOPERATIVE INFORMATION SYSTEMS

In cooperative processes and in e-services, an evaluation of the quality of exchanged data is essential for building mutual trust among cooperating organizations and correctly performing cooperative activities. Several quality dimensions, related to the intrinsic nature of data and to the context of the cooperative process where data are used, must be taken into consideration. In addition, in order to accomplish a trusted cooperative environment, data sensitivity parameters must be taken into account. A model for data quality in cooperative information systems and e-applications is proposed, together with an architecture for trusted exchanges of data and quality information associated to it. Strategic use of the model and of the architecture is discussed.
Reliability Assessment of Avalanche Mode Operating Power MOSFETs through Coffin Manson Law based Mathematical Models

A possible alternative to traditional, time crunching, endurance tests in accomplishing the reliability assessment of power devices are reliability models. Two possible approaches are compared in this paper to estimate the level of reliability of power MOSFETs working in avalanche mode. Although both the considered approaches exploit mathematical models carried out from the Coffin-Manson law, they differ in correlating the progressive degradation of the metal Source to different physical variables, the temperature variation and the total strain respectively. The consistence of the proposed techniques is evaluated by comparing estimations with endurance tests results. The described approaches can be usefully applied to assess the reliability of MOSFETs working in avalanche mode in a large set of applications in the automotive field.
Ring Signature Scheme from Multilinear Maps in the Standard Model

Ring signature is a group-oriented digital signature with anonymity. In 2006, Bencer et al. formalized stronger security definitions for ring signatures and proposed a concrete ring signature scheme based on Waters signature. However, their ring signature scheme can only support a two-user setting, and has relax security reduction. In this paper, we describe a ring signature scheme with multi users from multilinear maps. And then we prove that the proposed scheme is anonymous against full key exposure and unforgeable against chosen-subring attacks based on multilinear computational Diffie-Hellman assumption. Furthermore, the security reduction of our scheme is tighter than that of Bencer et al.'s scheme by using an optimal security reduction Waters signature.
Online matrix completion and online robust PCA

“To be considered for an 2015 IEEE Jack Keil Wolf ISIT Student Paper Award. ” This work studies two interrelated problems - online robust PCA (RPCA) and online matrix completion (MC). Both problems assume that an accurate estimate of the low-dimensional subspace from which the first true data vector is generated is available. We develop a practical modification of a recently proposed algorithm to solve both problems; and we obtain correctness results for the proposed algorithms under mild assumptions.
WD40 Domain Divergence Is Important for Functional Differences between the Fission Yeast Tup11 and Tup12 Co-Repressor Proteins

We have previously demonstrated that subsets of Ssn6/Tup target genes have distinct requirements for the Schizosaccharomyces pombe homologs of the Tup1/Groucho/TLE co-repressor proteins, Tup11 and Tup12. The very high level of divergence in the histone interacting repression domains of the two proteins suggested that determinants distinguishing Tup11 and Tup12 might be located in this domain. Here we have combined phylogenetic and structural analysis as well as phenotypic characterization, under stress conditions that specifically require Tup12, to identify and characterize the domains involved in Tup12-specific action. The results indicate that divergence in the repression domain is not generally relevant for Tup12-specific function. Instead, we show that the more highly conserved C-terminal WD40 repeat domain of Tup12 is important for Tup12-specific function. Surface amino acid residues specific for the WD40 repeat domain of Tup12 proteins in different fission yeasts are clustered in blade 3 of the propeller-like structure that is characteristic of WD40 repeat domains. The Tup11 and Tup12 proteins in fission yeasts thus provide an excellent model system for studying the functional divergence of WD40 repeat domains.
Addressing Asymmetric Link in Wireless Mesh Networks

In a mesh network, each node acts as a router/repeater for other nodes in the network. These nodes can be fixed pieces of network infrastructure and/or can be the mobile devices themselves. In such networks, because of the heterogeneous transmission range of the clients and routers, link asymmetry problem exists. Link asymmetry poses several challenges such as the unidirectional link problem, the heterogeneous hidden problem and the heterogeneous exposed problem. These challenges degrade the network performance. The proposed approach addresses these challenges and eliminates the unidirectional link in the network layer. Index Terms—heterogeneous hidden/ exposed problems, link asymmetry, unidirectional link, mesh networks.
Multiview camera-calibration framework for nonparametric distortions removal

This paper proposes a technique that uses a planar calibration object and projective constraints to calibrate parametric and nonparametric distortions. An iterative surface fitting is first used to constrain a B-spline distortion model by fusing the corrective distortion maps obtained from multiple views. The model is then refined within the whole camera-calibration process.
Efficient Block-Based Parameterized Timing Analysis Covering All Potentially Critical Paths

In order for the results of timing analysis to be useful, they must provide insight and guidance on how the circuit may be improved so as to fix any reported timing problems. A limitation of many recent variability-aware timing analysis techniques is that, while they report delay distributions, or verify multiple corners, they do not provide the required guidance for re-design. We propose an efficient block-based parameterized timing analysis technique that can accurately capture circuit delay at every point in the parameter space, by reporting all paths that can become critical. Using an efficient pruning algorithm, only those potentially critical paths are carried forward, while all other paths are discarded during propagation. This allows one to examine local robustness to parameters in different regions of the parameter space, not by considering differential sensitivity at a point (that would be useless in this context) but by knowledge of the paths that can become critical at nearby points in parameter space. We give a formal definition of this problem and propose a technique for solving it, which improves on the state of the art, both in terms of theoretical computational complexity and in terms of runtime on various test circuits.
Costimulatory Molecules on Immunogenic Versus Tolerogenic Human Dendritic Cells

Dendritic cells (DC) are sentinels of immunity, essential for homeostasis of T cell-dependent immune responses. Both functions of DC, initiation of antigen-specific T cell immunity and maintenance of tissue-specific tolerance originate from distinct stages of differentiation, immunogenic versus tolerogenic. Dependent on local micro milieu and inflammatory stimuli, tissue resident immature DC with functional plasticity differentiate into tolerogenic or immunogenic DC with stable phenotypes. They efficiently link innate and adaptive immunity and are ideally positioned to modify T cell-mediated immune responses. Since the T cell stimulatory properties of DC are significantly influenced by their expression of signal II ligands, it is critical to understand the impact of distinct costimulatory pathways on DC function. This review gives an overview of functional different human DC subsets with unique profiles of costimulatory molecules and outlines how different costimulatory pathways together with the immunosuppressive cytokine IL-10 bias immunogenic versus tolerogenic DC functions. Furthermore, we exemplarily describe protocols for the generation of two well-defined monocyte-derived DC subsets for their clinical use, immunogenic versus tolerogenic.
Making deterministic signatures quickly

We present a new technique of universe reduction. Primary applications are the dictionary problem and the predecessor problem. We give several new results on static dictionaries in different computational models: the word RAM, the Practical RAM, and for strings - the cache-oblivious model. All algorithms and data structures are deterministic and use linear space. Representative results are: a dictionary with a lookup time of O(log log n) and construction time of O(n log log n) on a word RAM, and a static predecessor structure for variable-length binary strings with a query performance of O(|s|/B + log |s| + log log n) I/Os, for query argument s, in the cache-oblivious model.
Object Recognition in 3D Point Clouds Using Web Data and Domain Adaptation

In recent years, object detection has become an increasingly active field of research in robotics. An important problem in object detection is the availability of a sufficient amount of labeled training data to learn good classifiers. In this paper we show how to significantly reduce the need for manually labeled training data by leveraging data sets available on the World Wide Web. Specifically, we show how to use objects from Google’s 3D Warehouse to train an object detection system for 3D point clouds collected by robots navigating through both urban and indoor environments. In order to deal with the different characteristics of the web data and the real robot data, we additionally use a small set of labeled point clouds and perform domain adaptation. Our experiments demonstrate that additional data taken from the 3D Warehouse along with our domain adaptation greatly improves the classification accuracy on real-world environments.
Denial of the Parental Alienation Syndrome Also Harms Women

Denying reality is obviously a maladaptive way of dealing with a situation. In fact, denial is generally considered to be one of the defense mechanisms, mechanisms that are inappropriate maladaptive, and pathological. In the field of medicine to deny the existence of a disease seriously compromises the physician's ability to help patients. If a physician does not believe that a particular disease exists, then it will not be given consideration when making a differential diagnosis, and the patient may then go untreated. This is in line with the ancient medical principle that proper diagnosis must precede proper treatment. Or, if for some external reason the physician recognizes the disorder, but feels obligated to use another name, other problems arise, for example, impaired communication with others regarding exactly what is going on with the patient, and hence improper treatment. This is what is occurring at this point with the parental alienation syndrome, a disorder whose existence has compelling verification. In this article I discuss the reasons for denial of the PAS and the ways in which such denial harms families. Particular emphasis will be given to the ways in which this denial harms women, although I will certainly comment on the ways in which the denial harms their husbands and children. In the past, denial of the PAS has caused men much grief. Such denial is now causing women similar grief.
Facilitating Physicians' Access to Information via Tailored Text Summarization

We have developed a summarization system, TAS (Technical Article Summarizer), which, when provided with a patient record and journal articles returned by a search, automatically generates a summary that is tailored to the patient characteristics. We hypothesize that a personalized summary will allow a physician to more quickly find information relevant to patient care. In this paper, we present a user study in which subjects carried out a task under three different conditions: using search results only, using a generic summary and search results, and using a personalized summary with search results. Our study demonstrates that subjects do a better job on task completion with the personalized summary, and show a higher level of satisfaction, than under other conditions.
Time-Series Analyses of Air Pollution and Mortality in the United States: A Subsampling Approach

Background: Hierarchical Bayesian methods have been used in previous papers to estimate national mean effects of air pollutants on daily deaths in time-series analyses. Objectives: We obtained maximum likelihood estimates of the common national effects of the criteria pollutants on mortality based on time-series data from ≤ 108 metropolitan areas in the United States. Methods: We used a subsampling bootstrap procedure to obtain the maximum likelihood estimates and confidence bounds for common national effects of the criteria pollutants, as measured by the percentage increase in daily mortality associated with a unit increase in daily 24-hr mean pollutant concentration on the previous day, while controlling for weather and temporal trends. We considered five pollutants [PM10, ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2)] in single- and multipollutant analyses. Flexible ambient concentration–response models for the pollutant effects were considered as well. We performed limited sensitivity analyses with different degrees of freedom for time trends. Results: In single-pollutant models, we observed significant associations of daily deaths with all pollutants. The O3 coefficient was highly sensitive to the degree of smoothing of time trends. Among the gases, SO2 and NO2 were most strongly associated with mortality. The flexible ambient concentration–response curve for O3 showed evidence of nonlinearity and a threshold at about 30 ppb. Conclusions: Differences between the results of our analyses and those reported from using the Bayesian approach suggest that estimates of the quantitative impact of pollutants depend on the choice of statistical approach, although results are not directly comparable because they are based on different data. In addition, the estimate of the O3-mortality coefficient depends on the amount of smoothing of time trends.