Miracle-dz/UniFAR-FTUs huggingface dataset:
An information-theoretic look at branch-prediction

Accurate branch-prediction is necessary to utilize deeply pipelined and Very Long Instruction-Word (VLIW) architectures. For a set of program traces we show the upper limits on branch predictability, and hence machine utilization, for important classes of branch-predictors using static (compiletime) and dynamic (runtime) program information. A set of optimal superpredictors'' is derived from these program traces. These optimal predictors compare favorably with other proposed methods of branch-prediction. 11 refs., 5 figs., 11 tabs.
Photoacoustic image reconstruction via deep learning

Applying standard algorithms to sparse data problems in photoacoustic tomography (PAT) yields low-quality images containing severe under-sampling artifacts. To some extent, these artifacts can be reduced by iterative image reconstruction algorithms which allow to include prior knowledge such as smoothness, total variation (TV) or sparsity constraints. These algorithms tend to be time consuming as the forward and adjoint problems have to be solved repeatedly. Further, iterative algorithms have additional drawbacks. For example, the reconstruction quality strongly depends on a-priori model assumptions about the objects to be recovered, which are often not strictly satisfied in practical applications. To overcome these issues, in this paper, we develop direct and efficient reconstruction algorithms based on deep learning. As opposed to iterative algorithms, we apply a convolutional neural network, whose parameters are trained before the reconstruction process based on a set of training data. For actual image reconstruction, a single evaluation of the trained network yields the desired result. Our presented numerical results (using two different network architectures) demonstrate that the proposed deep learning approach reconstructs images with a quality comparable to state of the art iterative reconstruction methods.
Impact of optimization of ALS point cloud on classification

Airborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM and DSM generation it is necessary to apply filtration or classification algorithms. They allow to divide a point cloud into object groups (e.g.: terrain points, vegetation, etc.). In this study classification is conducted with one extra parameter–intensity. The obtained point groups were used for digital spatial model generation. Classification is a time and work consuming process, therefore there is a need to reduce the time of ALS point cloud processing. Optimization algorithm enables to decrease the number of points in a dataset. In this study the main goal was to test the impact of optimization on the results of a classification. Studies were conducted in two variants. Variant 1 includes classification of the original point cloud where points are divided in the groups: roofs, asphalt road, tree/bushes, grass. On variant 2 before classification, an optimization algorithm was performed in the original point cloud. Obtained from these two variants object groups were used to generate a spatial model, which was then statistically analyzed.
Visualising Volumetric Fourier Transforms of Asymmetric 3D Growth Models

Volumetric visualisation of Fourier spectral data is a powerful but computationally intensive tool for understanding growth models. Visualising frequency-domain spectral representations of simulation model variables that are normally defined on a spatial mesh can be a useful aid to understanding time evolutionary behaviour. While it is common to study the symmetric or spherically averaged FFT of models, we consider rendering the full 3D FFT representations in interactive time. We use volume rendering methods to study the FFT and also consider asymmetric model cases where spherical averaging would be misleading. We discuss visualisation of Fourier-transformed data fields and some techniques for analysing and interpreting them. We present some application examples and implementations of rendering iso surfaces in the spectral scattering representation of of the normal and small-world rewired Ising model using Graphical Processing Units(GPUs) that allow both simulation and rendering to be achieved in interactive time.
Performance enhancement by narrow-beam quad-sector cell and interleaved channel assignment in wireless networks

We propose an improved sectorization scheme for cellular networks, called narrow beam quad-sector cell (NBQC), in which each cell is divided into 4 sectors and each sector is covered by a 60/spl deg/ antenna. The NBQC architecture has a better coverage performance than the current 3-sector cellular architecture. More importantly, the NBQC architecture allows easy implementation of the powerful interleaved channel assignment (ICA) scheme. Because of taking full advantage of the antenna directivity, the NBQC architecture with the ICA scheme can improve the signal to interference ratio (SIR) performance, thereby increasing the system capacity significantly. Our results show that in a typical radio environment, the NBQC system with the ICA scheme can achieve a reuse factor N=2 with the 90 percentile of SIR as high as 11 dB, which represents 3 to 5 dB SIR improvement or about at least 40 percent system capacity improvement over current cellular networks.
Platform 2015: Intel ® Processor and Platform Evolution for the Next Decade

Summary This article and the accompanying paper has outlined an ambitious vision which, in some respects, is a wide departure from present-day processors and platforms. But in reality, this vision is based on a continued evolution of Intel’s drive for increased parallelism, and our proven investment, research, development, manufacturing and unparalleled ecosystem enabling capability that, when taken together, will continue to lead us into an era of more powerful, versatile and efficient processing engines and platforms containing those engines. Ultimately, this evolution is driven by usage—what people want from technology and what they do with it. And though no one can precisely predict the future course of technology, the developments now underway point to some likely outcomes. Based on current requirements and trends, we at Intel believe that processor and platform architecture needs to move toward a virtualized, reconfigurable CMP architecture with a large number of cores, a rich set of built-in processing capabilities, large on-chip memory subsystem and sophisticated microkernel. This architectural evolution, delivered with volume computing economics and an adherence to maintaining compatibility with thousands of already existing applications, will ensure that Intel processors and platforms will continue to power a breathtaking array of sophisticated new applications over the coming years, transforming business and daily life in ways we can only begin to imagine.
Role of micronutrients in HIV infection

More than 60% of the estimated 40 million persons with HIV/AIDS worldwide live in sub-Saharan Africa, where poverty, social insecurity, food shortages and malnutrition are major problems.1 In children under the age of 5 years, who live in developing countries, malnutrition has been associated with 50% of the 10.8 million deaths mainly caused by neonatal disorders, diarrhoea, pneumonia, malaria and HIV/AIDS.2 Likewise micronutrient deficiencies are widespread and are associated with increased morbidity and mortality particularly in relation to infectious diseases.3 This review focuss on the interaction between micronutrients and HIV/AIDS and discusses recent research findings that may have important public health implications in terms of the case management of persons with HIV/AIDS Southern African Journal of HIV Medicine Vol. 6 (2) 2005: pp. 18-22
Utility of an Emergency Department Chest Pain Protocol in Ruling Out Acute Coronary Syndrome

Objective: To assess the safety and efficacy of an Emergency Department Chest Pain Protocol in ruling out Acute Coronary Syndrome in a regional hospital in Singapore. Methodology: An audit was carried out of the cases admitted to our Short Stay Unit (SSU) under the Chest Pain Protocol from June to November 2014. Patients presenting with chest pain and possible acute coronary syndrome, but with normal initial electrocardiogram (ECG) and troponin level, could undergo this rule-out protocol, which comprised serial ECGs and troponin levels, followed by selective outpatient treadmill or Coronary Computed Tomographic Angiography (CCTA) if they were discharged. The list of patients was electronically generated from our database at fortnightly intervals. Their casenotes were then reviewed, and phone follow-up done for discharged patients at least 30 days after discharge. Primary outcome was missed Acute Coronary Syndrome (ACS) within 30 days, as determined by 2 independent cardiologists using pre-set criteria. Secondary outcomes were adverse events, and stable coronary artery disease (CAD) requiring Percutaneous Coronary Intervention (PCI). Results: During the period of audit, a total of 240 patients were admitted under the protocol, of which 3 were lost to follow-up. 4 patients were found to have ACS within 30 days, of which 3 were picked up by the protocol. There was 1 case of missed ACS, who had a negative treadmill after discharge from the SSU, but later had an ST-Elevation Myocardial Infarction (STEMI). 10 patients had stable CAD requiring PCI. Conclusion: Our results suggest that the protocol is safe and can rule out ACS in most patients.
An Intelligent Broker Architecture for Pervasive Context-Aware Systems

Context-aware systems exploit the use of situational information, or context, to provide relevant information and services to users. A great challenge remains in defining an architecture that supports context-aware systems. Critical research issues include modeling and reasoning (how to represent contextual information for machine processing and reasoning), knowledge sharing (how to enable agents to acquire consistent knowledge from unreliable sensors and agents), and user privacy protection (how to give users control of their private information that the system acquires). To address these issues, I developed a new agent architecture called the Context Broker Architecture (CoBrA). It uses the Web Ontology Language OWL to define ontologies for context representation and modeling, defines rule-based logical inference for context reasoning and knowledge maintenance, and provides a policy language for users to control the sharing of their private information. Central to CoBrA is a server agent called context broker. Its role is to maintain a consistent model of context that can be shared by all computing entities in the space and to enforce the user-defined policies for privacy protection. The major research contributions of this work include a broker-centric architecture for supporting context-aware systems, a standard pervasive computing ontology, a reasoning approach that integrates assumption-based reasoning and argumentation for resolving inconsistent contextual knowledge, and a privacy protection mechanism that exploits information granularity adjustment. To demonstrate the feasibility of CoBrA, I prototyped a context broker in the FIPA platform using the JADE API library. I showed its use in supporting EasyMeeting, a smart meeting room system that provides context-aware services for assisting speakers and audiences. Other contributions include the CoBrA Demo Toolkit (an open source software package for demonstrating various aspects of CoBrA) and the CoBrA Text Messaging Commands (a text messaging interface for mobile users to interact with a context broker via SMS messages). The lessons learned from this research are as the follows. (i) CoBrA's broker-centric design can help to reduce the time and effort to rapidly prototype context-aware applications. (ii) Ontologies expressed using the OWL language can provide a uniformed solution for context representation and reasoning, knowledge sharing, and meta-language definitions. (iii) Rule-based logical inference can help to develop flexible context-aware systems by separating high-level context reasoning from low-level system behaviors.
The Ballad of Sexual Dependency

The Ballad of Sexual Dependency is a visual diary chronicling the struggle for intimacy and understanding between friends, family, and lovers collectively described by Goldin as her tribe. Her work describes a world that is visceral, charged, and seething with life. First published in 1986, this reissue recognizes the persistent relevance and freshness of Nan Goldins cutting-edge photography. Her lush color photography and candid style demand that the viewer go beyond the surface to encounter a profound intensity. As Goldin writes: Real memory, which these pictures trigger, is an invocation of the color, smell, sound, and physical presence, the density and flavor of life. Through an accurate and detailed record of her life, Ballad reveals Goldins personal odyssey as well as a more universal understanding of the different languages men and women speak, and the struggle between autonomy and dependency. Over the past twenty-five years, the influence of Ballad on photography and other aesthetic realms has continually grown, making the work a contemporary classic. Nan Goldins story of urban life on the fringe was the swan song of an era that reached its peak in the early eighties. Yet it has captured an important element of humanity that is transcendent: a need to connect. This new paperback edition of The Ballad of Sexual Dependency has been printed using new scans and separations created by master-separator Robert Hennessey from Goldins original transparencies, rendering them with unparalleled sumptuousness and impact.
Design of traffic light identification scheme based on TensorFlow and HSV color space

This paper proposes an effective traffic light identification scheme based on TensorFlow API and HSV color space. The program uses a distortion-corrected wide-angle camera to collect the road images in real time and utilizes the RCNN target detection interface, which is provided by the Google TensorFlow framework, to track the precise bounding box of the traffic light in the image. The obtained corner information is recorded for cropping ROI image from the original. Then using Open CV to smooth the ROI image and enhance the contrast. After converting the ROI image from BGR to HSV color space, the result of the traffic light can be consulted on the H channel according to the area of the connected domain.
A Simple XML Producer-Consumer Protocol

There are many different projects from government, academia, and industry that provide services for delivering events in distributed environments. The problem with these event services is that they are not general enough to support all uses and they speak different protocols so that they cannot interoperate. We require such interoperability when we, for example, wish to analyze the performance of an application in a distributed environment. Such an analysis might require performance information from the application, computer systems, networks, and scientific instruments. In this work we propose and evaluate a standard XML-based protocol for the transmission of events in distributed systems. One recent trend in government and academic research is the development and deployment of computational grids. Computational grids are large-scale distributed systems that typically consist of high-performance compute, storage, and networking resources. Examples of such computational grids are the DOE Science Grid, the NASA Information Power Grid (IPG), and the NSF Partnerships for Advanced Computing Infrastructure (PACIs). The major effort to deploy these grids is in the area of developing the software services to allow users to execute applications on these large and diverse sets of resources. These services include security, execution of remote applications, managing remote data, access to information about resources and services, and so on. There are several toolkits for providing these services such as Globus, Legion, and Condor. As part of these efforts to develop computational grids, the Global Grid Forum is working to standardize the protocols and APIs used by various grid services. This standardization will allow interoperability between the client and server software of the toolkits that are providing the grid services. The goal of the Performance Working Group of the Grid Forum is to standardize protocols and representations related to the storage and distribution of performance data. These standard protocols and representations must support tasks such as profiling parallel applications, monitoring the status of computers and networks, and monitoring the performance of services provided by a computational grid. This paper describes a proposed protocol and data representation for the exchange of events in a distributed system. The protocol exchanges messages formatted in XML and it can be layered atop any low-level communication protocol such as TCP or UDP Further, we describe Java and C++ implementations of this protocol and discuss their performance. The next section will provide some further background information. Section 3 describes the main communication patterns of our protocol. Section 4 describes how we represent events and related information using XML. Section 5 describes our protocol and Section 6 discusses the performance of two implementations of the protocol. Finally, an appendix provides the XML Schema definition of our protocol and event information.
Les Modes de Rémunération comme Mécanismes Sélectifs de la Main d’oeuvre: Fondements Théoriques et Estimations Empiriques

Comme Saint-Paul (2001) montre que des travailleurs avec des niveaux de productivite proches ont tendance a se retrouver dans les memes firmes, on peut s’interroger sur le pouvoir selectif des mecanismes de remuneration. Le modele theorique de Lazear (2000) met en avant l’existence a la fois des effets d’incitation et de selection d’un mode de remuneration indexe sur la performance des employes. Ce modele a ete teste a l’aide de differentes methodes d’estimation et la majorite d’entre elles supportent les predictions theoriques. Ce modele a ete etendu a des travaux theoriques et empiriques supportant l’hypothese d’auto-selection des travailleurs en fonction de leurs caracteristiques intrinseques telles que l’aversion au risque, la motivation intrinseque ou encore les preferences sociales. Enfin, il est montre que l’heterogeneite de la main d’oeuvre contribue a l’efficience du marche si les travailleurs s’auto-selectionnent dans differentes organisations.
PENGARUH IMBANGAN MANGGA KWENI (Mangifera odorata Griff.) DENGAN WORTEL (Daucus carota L.) SERTA PENAMBAHAN GLISEROL TERHADAP BEBERAPA KARAKTERISTIK FRUIT LEATHER

Mangga kweni dan wortel dapat dibuat menjadi fruit leather. Keplastisan dari fruit leather dapat ditingkatkan dengan menambahkan gliserol. Tujuan penelitian ini untuk menetapkan imbangan mangga kweni dan wortel serta konsentrasi gliserol yang tepat, sehingga dihasilkan fruit leather dengan beberapa karakterisrik yang baik dan disukai panelis. Perlakuan terdiri dari dua faktor, yaitu imbangan bubur mangga kweni dengan bubur wortel (A) yang terdiri atas 3 taraf yaitu mangga 65 : wortel 35(a 1 ), mangga 55 : wortel 45 (a 2 ) dan mangga 45 : wortel 55 (a 3 ) dan faktor konsentrasi gliserol (B) yang terdiri dari tiga taraf yaitu 1,5% (b 1 ), 3% (b2) dan 4,5% (b 3 ). Penelitian telah dilakukan pada bulan Agustus 2007 di Laboratorium Kimia Pangan Universitas Padjadjaran. Hasil penelitian menunjukkan bahwa tidak terjadi interaksi antara imbangan dan konsentrasi gliserol pada kadar air, rendemen, kesukaan terhadap warna, rasa, tekstur dan aroma, kecuali pada antara imbangan dan konsentrasi gliserol pada uji plastisitas. Taraf imbangan mangga kweni dan wortel 65 : 35 menghasilkan fruit leather dengan karakteristik paling baik dengan kadar air 9,16%, rendemen 27,64%, nilai kesukaan warna 3,39, aroma 3,81, rasa 3,81 dan tekstur 3,54. Taraf konsentrasi gliserol 3% menghasilkan fruit leather dengan karakteristik paling baik dengan kadar air 9,26%, rendemen 27,69%, nilai kesukaan warna 3,72, aroma 3,72, rasa 3,69 dan tekstur 3,59 Kata kunci: Fruit leather, Konsentrasi gliserol
Music: A Very Short Introduction

Music: A Very Short Introduction is a study of music and thinking about music, focusing on its social, cultural, and historical dimensions. It draws on a wealth of accessible examples, ranging from Beethoven to Chinese zither music. This VSI also discusses the nature of music as a real-time performance practice; the role of music in social and political action; and the nature of musical thinking, including the roles played in it by instruments, notations, and creative imagination. It explores the impact of digital technology on the production and consumption of music, including how it has transformed participatory music-making and the music business. Finally it examines music’s position in a globalized world. In many ways music has changed out of all recognition over the last twenty years, and so the second edition of this VSI has been comprehensively rewritten.