nils-herrmann/clean_scirepeval huggingface dataset:
Integrating Profile Caching into the HotSpot Multi-Tier Compilation System

The Java®HotSpot Virtual Machine includes a multi-tier compilation system that may invoke a compiler at any time. Lower tiers instrument the program to gather information for the highly optimizing compiler at the top tier, and this compiler bases its optimizations on these profiles. But if the assumptions made by the top-tier compiler are proven wrong (e.g., because the profile does not cover all execution paths), the method is deoptimized: the code generated for the method is discarded and the method is then executed at Tier 0 again. Eventually, after profile information has been gathered, the method is recompiled at the top tier again (this time with less-optimistic assumptions). Users of the system experience such deoptimization cycles (discard, profile, compile) as performance fluctuations and potentially as variations in the system's responsiveness. Unpredictable performance however is problematic in many time-critical environments even if the system is not a hard real-time system.
 A profile cache captures the profile of earlier executions. When the application is executed again, with a fresh VM, the top tier (highly optimizing) compiler can base its decisions on a profile that reflects prior executions and not just the recent history observed during this run. We report in this paper the design and effectiveness of a profile cache for Java applications which is implemented and evaluated as part of the multi-tier compilation system of the HotSpot Java Virtual Machine in OpenJDK version 9. For a set of benchmarks, profile caching reduces the number of (re)compilations by up to 23%, the number of deoptimizations by up to 90%, and thus improves performance predictability.
Exploring the Impact of IT Service Management Process Improvement Initiatives: A Case Study Approach

IT companies worldwide have started to improve their service management processes based on best practice frameworks, such as IT Infrastructure Library (ITIL). However, many of these companies face difficulties in demonstrating the positive outcomes of IT service management (ITSM) process improvement. This has led us to investigate the research problem: What positive impacts have resulted from IT service management process improvement? The main contributions of this paper are 1) to identify the ITSM process improvement outcomes in two IT service provider organizations and 2) provide advice as lessons learnt.
A Proactive Workflow Model for Healthcare Operation and Management

Advances in real-time location systems have enabled us to collect massive amounts of fine-grained semantically rich location traces, which provide unparalleled opportunities for understanding human activities and generating useful knowledge. This, in turn, delivers intelligence for real-time decision making in various fields, such as workflow management. Indeed, it is a new paradigm to model workflows through knowledge discovery in location traces. To that end, in this paper, we provide a focused study of workflow modeling by integrated analysis of indoor location traces in the hospital environment. In particular, we develop a workflow modeling framework that automatically constructs the workflow states and estimates the parameters describing the workflow transition patterns. More specifically, we propose effective and efficient regularizations for modeling the indoor location traces as stochastic processes. First, to improve the interpretability of the workflow states, we use the geography relationship between the indoor rooms to define a prior of the workflow state distribution. This prior encourages each workflow state to be a contiguous region in the building. Second, to further improve the modeling performance, we show how to use the correlation between related types of medical devices to reinforce the parameter estimation for multiple workflow models. In comparison with our preliminary work [11] , we not only develop an integrated workflow modeling framework applicable to general indoor environments, but also improve the modeling accuracy significantly. We reduce the average log-loss by up to 11 percent.
Deep convolutional encoder-decoder network with model uncertainty for semantic segmentation

We propose a new semantic segmentation method and the necessity of certainty for practical use of semantic segmentation in scene understanding. We implement a deep fully convolutional encoder-decoder neural network for semantic segmentation. This network architecture makes the segmentation accuracy improve by retaining boundary details in the extracted image representation. This accuracy means how much the segmentation results match to ground truth labels. However, the conventional evaluation method ignores unlabeled regions in ground truth labels. In other words, the segmentation results has not been evaluated in the regions of unknown objects. Toward practical use of the semantic segmentation, the evaluation should consider such regions. So it is necessary to recognize accurately whether the object is known or not. We call this factor certainty. Bayesian SegNet makes it possible to produce an uncertainty of the segmentation results with a measure of model uncertainty from the sampling of the posterior distribution of the model using Dropout. However, the uncertainty is not used for segmentation itself, and all pixels are classified into one of the predefined classes in this segmentation result. It means that the pixels within the regions of unknown objects are definitely misclassified as one of the predefined classes. Our study aims the improvement of certainty for semantic segmentation in road scene understanding with model uncertainty. Our method rejects the uncertain region and classifies it as an unknown object using the model uncertainty. We achieved improvement of certainty by our method as shown in the evaluation results. Furthermore, we indicated the possibility of the performance improvement on the deep convolutional encoder-decoder network architecture from the comparison of our network architecture with Bayesian SegNet architecture.
- 7232 RAPID MANUFACTURING IN MINUTES : THE DEVELOPMENT OF A MASK PROJECTION STEREOLITHOGRAPHY PROCESS FOR HIGH-SPEED FABRICATION

The purpose of this paper is to present a direct digital manufacturing (DDM) process that is an order of magnitude faster than other DDM processes currently available. The developed process is based on a mask-image-projection-based Stereolithography process (MIP-SL), during which a Digital Micromirror Device (DMD) controlled projection light cures and cross-links liquid photopolymer resin. In order to achieve high-speed fabrication, we investigated the bottom-up projection system in the MIP-SL process. A set of techniques including film coating and the combination of two-way linear motions have been developed for the quick spreading of liquid resin into uniform thin layers. The process parameters and related settings to achieve the fabrication speed of a few seconds per layer are presented. Additionally, the hardware, software, and material setups developed for fabricating given three-dimensional (3D) digital models are presented. Experimental studies using the developed testbed have been performed to verify the effectiveness and efficiency of the presented fast MIP-SL process. The test results illustrate that the newly developed process can build a moderately sized part within minutes instead of hours that are typically required.
Multi-Touch Attribution Based Budget Allocation in Online Advertising

Budget allocation in online advertising deals with distributing the campaign (insertion order) level budgets to different sub-campaigns which employ different targeting criteria and may perform differently in terms of return-on-investment (ROI). In this paper, we present the efforts at Turn on how to best allocate campaign budget so that the advertiser or campaign-level ROI is maximized. To do this, it is crucial to be able to correctly determine the performance of sub-campaigns. This determination is highly related to the action-attribution problem, i.e. to be able to find out the set of ads, and hence the sub-campaigns that provided them to a user, that an action should be attributed to. For this purpose, we employ both last-touch (last ad gets all credit) and multi-touch (many ads share the credit) attribution methodologies. We present the algorithms deployed at Turn for the attribution problem, as well as their parallel implementation on the large advertiser performance datasets. We conclude the paper with our empirical comparison of last-touch and multi-touch attribution-based budget allocation in a real online advertising setting.
Design of disaster management system using IoT based interconnected network with smart city monitoring

IoT deals with intricate systems that integrate multiple disperse components towards their synergetic use. In this paper a system of interconnected smart modules is developed as a way to enable centralized data acquisition as well as provide an interlinked network for transmission of data in absence of any existing infrastructure. Emphasis is given on how sensing and communication technologies of IoT can effectively be used in smart city monitoring as well as in case of disaster management. The hardware of the module used for this purpose is studied and elaborated in a detailed manner.
Ferrimagnetism in GdCo(12-x)Fe(x)B6.

The effects of iron substitution on the structural and magnetic properties of the GdCo(12-x)Fe(x)B6 (0 ≤ x ≤ 3) series of compounds have been studied. All of the compounds form in the rhombohedral SrNi12B6-type structure and exhibit ferrimagnetic behaviour below room temperature: T(C) decreases from 158 K for x = 0 to 93 K for x = 3. (155)Gd Mössbauer spectroscopy indicates that the easy magnetization axis changes from axial to basal-plane upon substitution of Fe for Co. This observation has been confirmed using neutron powder diffraction. The axial to basal-plane transition is remarkably sensitive to the Fe content and comparison with earlier (57)Fe-doping studies suggests that the boundary lies below x = 0.1.
The sparse data reduction engine: chopping sparse data one byte at a time

Sparse data and irregular data access patterns are hugely important to many applications, such as molecular dynamics and data analytics. Accelerating applications with these characteristics requires maximizing usable bandwidth at all levels of the memory hierarchy, reducing latency, maximizing reuse of moved data, and minimizing the amount the data is moved in the first place. Many specialized data structures have evolved to meet these requisites for specific applications, however, there are no general solutions for improving the performance of sparse applications. The structure of the memory hierarchy itself, conspires against general hardware for accelerating sparse applications, being designed for efficient bulk transport of data versus one byte at a time. This paper presents a general solution for a programmable data rearrangement/reduction engine near-memory to deliver bulk byte-addressable data access. The key technology presented in this paper is the Sparse Data Reduction Engine (SPDRE), which builds previous similar efforts to provide a practical near-memory reorganization engine. In addition to the primary contribution, this paper describes a programmer interface that enables all combinations of rearrangement, analysis of the methodology on a small series of applications, and finally a discussion of future work.
Intratester and Intertester Reliability of the Palpation Meter (PALM) in Measuring Pelvic Position

This study determined the intraand intertester reliability of the Palpation Meter (PALM) in measuring frontal and sagittal plane pelvic positions among asymptomatic adults during static standing. Four examiners measured 24 physical therapy students in two trials. The sagittal plane measurement was taken as the angle formed by a line connecting the ASIS and PSIS versus the horizontal. The frontal plane measurement was taken as the angle formed by a line connecting the superior border of the iliac crests versus the horizontal. Unlike previous studies, this study attempted to replicate the realities of clinical practice by using the PALM to perform measurements over clothing without applying adhesive markers for landmarks, and without controls for postural sway. Intraclass correlation coefficients suggest intratester reliability was high for both frontal (0.84) and sagittal plane measures (0.98), and intertester reliability was high for sagittal plane measures (0.89) but moderate for frontal plane measures (0.65). Standard error of the means for frontal and sagittal plane measures are presented, and clinicians are cautioned to observe the limitations of precision inherent in this device.
Leonhard Euler and the Theory of Ships

On April 15, 2007 the scientific world has commemorated Leonhard Euler's 300 th birthday. Euler's eminent work has become famous in many fields: Mathematics, mechanics, optics, acoustics, astronomy and geodesy, even in the theory of music. This article will recall his no less distinguished contributions to the founding of the modern theory of ships. These are not so widely known to the general professional public. In laying these foundations in ship theory like in other fields Euler was seeking " first principles, generality, order and above all clarity ". This article will highlight those achievements for which we owe him our gratitude. There is no doubt that Leonhard Euler was one of the founders of the modern theory of ships. He raised many fundamental questions for the first time and through all phases of his professional lifetime devoted himself to subjects of ship theory. Thereby he gave a unique profile to this still nascent scientific discipline. Many of his approaches have been of lasting, incisive influence on the structure of this field. Some of his ideas have become so much a matter of routine today that we have forgotten their descent from Euler. This article will synoptically review Euler's contributions to the foundation of this discipline, will correlate them with the stages of Euler's own scientific development, embedded in the rich environment of scientific enlightenment in the 18th c., and will appreciate the value of his lasting aftereffects until today. The same example will serve to recognize the fertile field of tension always existing between Euler's fundamental orientation and his desire to make contributions to practical applications, which has remained characteristic of ship theory to the present day. Without claiming completeness in detail this article aims at giving a coherent overview of Euler's approaches and objectives in this discipline. This synopsis will be presented primarily from the viewpoint of engineering science in its current stage of development.
A brief review of scheduling algorithms of Map Reduce model using Hadoop

Scheduling has been an active area of research in computing systems since their inception. Hadoop framework has become very much popular and most widely used in distributed data processing. Hadoop has become a central platform to store big data through its Hadoop Distributed File System (HDFS) as well as to run analytics on this stored big data using its MapReduce component. The main objective is to study MapReduce framework, MapReduce model, scheduling in hadoop, various scheduling algorithms and various optimization techniques in job scheduling. Scheduling algorithms of MapReduce model using hadoop vary with design and behaviour, and are used for handling many issues like data locality, awareness with resource, energy and time.
Recent advances in processing and applications of microwave ferrites

Next generation magnetic microwave devices will be planar, smaller, weigh less, and perform well beyond the present state-of-the-art. For this to become a reality advances in ferrite materials must first be realized. These advances include self-bias magnetization, tunability of the magnetic anisotropy, low microwave loss, and volumetric and weight reduction. To achieve these goals one must turn to novel materials processing methods. Here, we review recent advances in the processing of microwave ferrites. Attention is paid to the processing of ferrite films by pulsed laser deposition, liquid phase epitaxy, spin spray ferrite plating, screen printing, and compaction of quasi-single crystals. Conventional and novel applications of ferrite materials, including microwave non-reciprocal passive devices, microwave signal processing, negative index metamaterial-based electronics, and electromagnetic interference suppres-
A 22 to 26.5 Gb/s Optical Receiver With All-Digital Clock and Data Recovery in a 65 nm CMOS Process

This paper presents a 22 to 26.5 Gb/s optical receiver with an all-digital clock and data recovery (AD-CDR) fabricated in a 65 nm CMOS process. The receiver consists of an optical front-end and a half-rate bang-bang clock and data recovery circuit. The optical front-end achieves low power consumption by using inverter-based amplifiers and realizes sufficient bandwidth by applying several bandwidth extension techniques. In addition, in order to minimize additional jitter at the front-end, not only magnitude and bandwidth but also group-delay responses are considered. The AD-CDR employs an LC quadrature digitally controlled oscillator (LC-QDCO) to achieve a high phase noise figure-of-merit at tens of gigahertz. The recovered clock jitter is 1.28 ps rms and the measured jitter tolerance exceeds the tolerance mask specified in IEEE 802.3ba. The receiver sensitivity is 106 and 184 for a bit error rate of 10-12 at data rates of 25 and 26.5 Gb/s, respectively. The entire receiver chip occupies an active die area of 0.75 mm2 and consumes 254 mW at a data rate of 26.5 Gb/s. The energy efficiencies of the front-end and entire receiver at 26.5 Gb/s are 1.35 and 9.58 pJ/bit, respectively.
Zebrafish and Medaka: new model organisms for modern biomedical research

Although they are primitive vertebrates, zebrafish (Danio rerio) and medaka (Oryzias latipes) have surpassed other animals as the most used model organisms based on their many advantages. Studies on gene expression patterns, regulatory cis-elements identification, and gene functions can be facilitated by using zebrafish embryos via a number of techniques, including transgenesis, in vivo transient assay, overexpression by injection of mRNAs, knockdown by injection of morpholino oligonucleotides, knockout and gene editing by CRISPR/Cas9 system and mutagenesis. In addition, transgenic lines of model fish harboring a tissue-specific reporter have become a powerful tool for the study of biological sciences, since it is possible to visualize the dynamic expression of a specific gene in the transparent embryos. In particular, some transgenic fish lines and mutants display defective phenotypes similar to those of human diseases. Therefore, a wide variety of fish model not only sheds light on the molecular mechanisms underlying disease pathogenesis in vivo but also provides a living platform for high-throughput screening of drug candidates. Interestingly, transgenic model fish lines can also be applied as biosensors to detect environmental pollutants, and even as pet fish to display beautiful fluorescent colors. Therefore, transgenic model fish possess a broad spectrum of applications in modern biomedical research, as exampled in the following review.
Design of an X-band broad-band lumped-element quadrature hybrid

A method for synthesizing a two-section inductively-coupled lumped-element quadrature hybrid for broad-band applications is first proposed. Based on this analysis, a two-section inductively-coupled lumped-element quadrature hybrid operated at X-band is presented. The measured magnitude imbalance and phase difference are 2.4dB and 90°± 4° over the frequency band of 8–12GHz, respectively. Results show good agreement with the theoretical predictions.
The comparative morphology of pit organs in elasmobranchs.

The pit organs of elasmobranchs (sharks, skates and rays) are free neuromasts of the mechanosensory lateral line system. Pit organs, however, appear to have some structural differences from the free neuromasts of bony fishes and amphibians. In this study, the morphology of pit organs was investigated by scanning electron microscopy in six shark and three ray species. In each species, pit organs contained typical lateral line hair cells with apical stereovilli of different lengths arranged in an "organ-pipe" configuration. Supporting cells also bore numerous apical microvilli taller than those observed in other vertebrate lateral line organs. Pit organs were either covered by overlapping denticles, located in open grooves bordered by denticles, or in grooves without associated denticles. The possible functional implications of these morphological features, including modification of water flow and sensory filtering properties, are discussed.
A semantic feedback on student's performance with data mining techniques: State of the art survey

Feedback is assessing an individual's action in any endeavor. The judgment helps one to grow well in any field. By the feedback a student can understand and improve upon mistakes committed, teachers come to know about the student's capability and implement new teaching methods. New Technologies also come up for the enhancement of Student's Performance. A study of the assessment of student performance through various papers using data mining and also with ontology based applications makes one decide certain factors like confidence level, stress and time management, holistic approach towards an issue which may be useful in giving a prediction about the students' work performance level in organizations. The Survey encompasses the assessment of a student's performance in academics using Data mining Techniques and also with Ontology based Applications.
Methods in biomedical text mining

Methods in biomedical text mining Methods to improve text mining of molecular biology interactions are needed to capture a richer information space and qualify the quality of extraction. Simple interaction models fail to describe contextual and confidence information that would help with more fine-grained analyses. Herein a method is presented to streamline curation of text-mined data and a way to improve text mining of biomedical terms that can be adapted to other domains using different machine learning techniques. These advances can be integrated into more powerful text-mining systems to meet user demand and to further promote the adoption of text-mining tools. Additionally, three studies on the nature of biomedical publications are presented: their novelty hinges on the fact that each asks questions that had not been posed before. They cover the phenomena of retraction, ways to improve the impact of research, and the writing style used in biomedical literature. Retraction is a hot topic in recent times but it has not been heeded in an analytical fashion. Measuring the impact of scientific publications has brought heated debate on which are best at describing it. We propose a method not to measure impact, but to improve it. Finally, we analyze the influence of scientific writing style on the priming of its reader from a sensorial point of view.