Miracle-dz/UniFAR-FTUs huggingface dataset:
Clotho: Proactive wearout deceleration in Chip-Multiprocessor interconnects

With advancing process technology, Chip-Multiprocessors (CMPs) are experiencing ever worsening reliability due to prolonged operational stresses. The network-on-chip that interconnects the components of CMPs is especially vulnerable to such wearout-induced failure. To tackle this ominous threat we present Clotho, a novel, wearout-aware routing algorithm. Clotho continuously considers the stresses the on-chip interconnect experiences at runtime, along with temperature and fabrication process variation metrics, steering traffic away from locations that are most prone to Electromigration (EM)- and Hot-Carrier Injection (HCI)-induced wear. Under realistic workloads Clotho yields 66% and 8% average increases in mean time to failure for EM and HCI, respectively.
Modified Cramér-Rao Bounds for Continuous-Phase Modulated Signals

We consider the estimation of signal amplitude, time offset, and the parameters of a polynomial-phase signal from a continuous-phase modulated (CPM) signal that contains both unknown data symbols and known pilot symbols. Transformation of the polynomial-phase signal into an orthogonal basis allows us to derive the modified Cramér-Rao bounds (MCRB) for the problem of vector-parameter estimation in closed form. Numerical results demonstrate that the achievable estimation accuracy significantly depends on the burst structure and highlight the need for properly designed pilot sequences. Since our bounds are easy to evaluate, they can aid the design of pilot and burst configuration for CPM systems.
A Comparative Analysis of Nanoparticle Adsorption as Fire-Protection Approach for Fabrics

The present paper critically analyzes the potential for commercially available nanoparticles for enhancing the flame-retardant properties of synthetic and natural fabrics and their corresponding blends. Each nanoparticle has been applied to the fabric through a finishing-like process (namely impregnation/exhausting or, more simply, nanoparticle adsorption) in aqueous media and the resulting properties of these fabrics have been assessed in terms of combustion behavior by use of a cone calorimeter under a heat flux of 35 kW/m2. The influence of these nanoparticles on the main combustion parameters of polyester, cotton, and some of their blends has been thoroughly discussed. As a result of this discussion, a flame-retardant efficiency ranking of the nanoparticles under review has been established.
Implementation of dialogue system for intelligent service robots

This paper presents a dialogue system for intelligent service robot application. The dialogue system consists of an audio speech recognition module, a text-to-speech conversion module, and a dialogue manager for supervision of timely conversion of input command to output robotic service. The dialogue manager is implemented in the framework of task supervisor for HRI(Human-Robot-Interface) module and makes use of finite state machine module for each robotic service. Since the number of services generated grows larger as the complexity of robotic task increases, the set of finite state machine modules is designed in compact modular form in the dialogue manager enhancing the capability of intelligent service robot handling various missions. The effectiveness of proposed dialogue system is demonstrated by applying it to information delivery service of weather and news, scheduling service, and entertainment game service for robotic user.
Total Factor Productivity, Human Capital and Outward Orientation: Differences by Stage of Ddevelopment and Geographic Regions

Do openness and human capital accumulation promote economic growth? While intuition argues yes, the existing empirical evidence provides mixed support for such assertions. We examine Cobb-Douglas production function specifications for a 30-year panel of 83 countries representing all regions of the world and all income groups. We estimate and compare labor and capital elasticities of output per worker across each of several income and geographic groups, finding significant differences in production technology. Then we estimate the total factor productivity series for each classification. Using determinants of total factor productivity that include, among many others, human capital, openness, and distortion of domestic prices relative to world prices, we find significant differences in results between the overall sample and sub-samples of countries. In particular, a policy of outward orientation may or may not promote growth in specific country groups. even if geared to reducing price distortion and increasing openness. Human capital plays a smaller role in enhancing growth through total factor productivity.
Mesolevel simulation of reinforced concrete structures under impact loadings

Reinforced concrete structures are often subjected to extreme dynamic loading conditions due to direct impact. This paper deals with the numerical simulation of the effect of impact loadings on reinforced concrete structural members such as columns, beams and slabs. Concrete is modeled by a three-dimensional mesolevel lattice model, which can predict accurately concrete behavior in a wide range of loading conditions. The adopted constitutive law simulates fracture, friction and cohesion at the meso-level and takes into account the strain rate dependence of concrete behavior. A mesh of plastic beam elements simulates the effect of steel reinforcement. Since the nodes of the reinforcement do not coincide, in general, with the nodes of the lattice system ad hoc coupling algorithms are proposed. The mesolevel model for concrete and the concreterebar coupling algorithm are implemented in the framework of the object oriented dynamic finite element code MARS. Finally, numerical simulations of the behavior of reinforced concrete structural members subjected to impact loading are performed and the numerical results are compared with experimental data gathered from the literature.
Social Community Detection Based on Node Distance and Interest

Nowadays, social network sites, such as Facebook and Twitter, have tremendous number of users in their repositories. Having this huge amount of data requires analyzing them to get statistics about the users and their interests. In this paper, we propose a new algorithm that clusters the nodes in social networks into communities based on their geodesic location and the similarity between their interests. The algorithm is examined thoroughly to test its performance. The experiments show that the algorithm achieves a high community detection accuracy.
A Reliability Optimization Method Using Disk Reliability Degree and Data Heat Degree

The reliability of the traditional storage system can utilize data recovery and reconstruction operations to recover data in case of the disk failure; however it will result in longer data recovery time and increase the possibility of secondary failure. Hence, reliability optimization has become one of the key subjects of storage system research. In this paper we propose a novel reliability optimization method, which uses disk reliability degree to evaluate the reliability of disk based on SMART technology. And it uses data heat degree to compute the heat degree of data and the utilization degree of disk at the present time, so according to disk reliability degree and disk utilization degree we can protect current hotspots data. Data heat degree also predicts hotspots data in the future based on the current rank of data access frequency and Zipf-like distribution; we can also protect predicted new hotspots data according to disk reliability degree. Our experiment shows that disk reliability degree satisfies the actual usage and data heat degree achieves very high prediction accuracy. In order to evaluate the system performance's influence of our method, the experimental results of data migration based on RAID system demonstrate that reliability optimization method has little or no impact on the normal system performance, and outperforms the traditional reconstruct RAID system.
Hemoglobin A1c and Arterial and Ventricular Stiffness in Older Adults

Objective Arterial and ventricular stiffening are characteristics of diabetes and aging which confer significant morbidity and mortality; advanced glycation endproducts (AGE) are implicated in this stiffening pathophysiology. We examined the association between HbA1c, an AGE, with arterial and ventricular stiffness measures in older individuals without diabetes. Research Design & Methods Baseline HbA1c was measured in 830 participants free of diabetes defined by fasting glucose or medication use in the Cardiovascular Health Study, a population-based cohort study of adults aged ≥65 years. We performed cross-sectional analyses using baseline exam data including echocardiography, ankle and brachial blood pressure measurement, and carotid ultrasonography. We examined the adjusted associations between HbA1c and multiple arterial and ventricular stiffness measures by linear regression models and compared these results to the association of fasting glucose (FG) with like measures. Results HbA1c was correlated with fasting and 2-hour postload glucose levels (r = 0.21; p<0.001 for both) and positively associated with greater body-mass index and black race. In adjusted models, HbA1c was not associated with any measure of arterial or ventricular stiffness, including pulse pressure (PP), carotid intima-media thickness, ankle-brachial index, end-arterial elastance, or left ventricular mass (LVM). FG levels were positively associated with systolic, diastolic and PP and LVM. Conclusions In this sample of older adults without diabetes, HbA1c was not associated with arterial or ventricular stiffness measures, whereas FG levels were. The role of AGE in arterial and ventricular stiffness in older adults may be better assessed using alternate AGE markers.
Microbacterium sorbitolivorans sp. nov., a novel member of Microbacteriaceae isolated from fermentation bed in pigpen.

Two bacterial strains SZDIS-1-1T and GZDIS-1-1 were isolated from fermentation bed of a pigpen in Fujian Province, China. Cells were Gram-stain-positive, facultatively anaerobic, short rods without flagellum. Their nearest phylogenetic neighbours were Microbacterium amylolyticum N5T (16S rRNA gene sequence similarity 98.2 %), Microbacterium indicum BBH6T (97.9 %) and Microbacterium gubbeenense DPC 5286T (97.8 %) with the DNA-DNA hybridization values to strain SZDIS-1-1T as 20.0±1.2, 14.3±5.8 and 19.1±1.6 %, respectively. The DNA G+C content of the new isolates was 67.6-71.1 mol% and anteiso-C15 : 0, anteiso-C17 : 0 and iso-C16 : 0 were their predominant cellular fatty acids. These results were consistent with classification into the genus Microbacterium. However, cell-wall sugars and characteristic amino acid were rhamnose, glucose, galactose and ornithine. Major menaquinones were MK-11 and MK-10. The polar lipids consisted of diphosphatidylglycerol, phosphatidylglycerol, glycolipids, unknown phospholipid and unknown lipids. These characteristics constructed a distinct profile of the two isolates. Therefore, based on polyphasic taxonomic characteristics, strains SZDIS-1-1T and GZDIS-1-1 represented a novel species of genus Microbacterium, for which the name Microbacterium sorbitolivorans sp. nov. is proposed, with strain SZDIS-1-1T (=CGMCC 1.15228T=DSM 103422T) as the type strain.
FS-model predictive control of microgrid interface converters for reactive power and harmonic compensation

Microgrids can be controlled to optimize the generation and consumption of energy in a bounded geographical area which, in the global current scenario, facilitates the integration of distributed energy resources to the main grid. Additionally, some ancillary services, such as support of grid instabilities or power quality improvements, can be also obtained modifying the microgrid control scheme. In this paper, the compensation of reactive power and harmonic components in the main grid current using the microgrid interface converter is proposed. Using predictive current control for fast dynamical response and an energy-based model to avoid linear approximation the microgrid converter works as an active filter while the microgrid DC bus is regulated to the desired voltage. Simulations results for a 80 kW microgrid connected to the main grid is presented to support theoretical analysis.
G/sup en/oM: a tool for the specification and the implementation of operating modules in a distributed robot architecture

This paper presents a general methodology for the specification and the integration of functional modules in a distributed reactive robot architecture. The approach is based on a hybrid architecture basically composed of two levels: a lower distributed functional level controlled by a centralized decisional level. Due to this methodology, synchronous or asynchronous operating capabilities (servo-control, data processing, event monitoring) can be easily added to the functional level. They are encapsulated into modules, built according to a generic model, that are seen by the decisional level as homogeneous, programmable, reactive and robust communicant services. Each module is simply described with a specific language and is automatically produced by a generator of modules (G/sup en/oM) according to the generic model. G/sup en/oM also produces an interactive test program and interface libraries to control the module and to read the resulting data, which allow one to directly integrate the module into the architecture.
The Entropy Power Inequality and Mrs. Gerber's Lemma for groups of order 2n

Shannon's Entropy Power Inequality (EPI) can be viewed as characterizing the minimum differential entropy achievable by the sum of two independent random variables with fixed differential entropies. The EPI is a powerful tool and has been used to resolve a number of problems in information theory. In this paper we examine the existence of a similar entropy inequality for discrete random variables. We obtain an entropy power inequality for random variables taking values in any group of order 2n, i.e. for such a group G we explicitly characterize the function fG(x, y) giving the minimum entropy of the group product of two independent G-valued random variables with respective entropies x and y. Random variables achieving the extremum in this inequality are thus the analogs of Gaussians, and these are also determined. It turns out that fG(x, y) is convex in x for fixed y and, by symmetry, convex in y for fixed x. This is a generalization to groups of order 2n of the result known as Mrs. Gerber's Lemma.
Mind the Gap: Upgrading Genomes with Pacific Biosciences RS Long-Read Sequencing Technology

Many genomes have been sequenced to high-quality draft status using Sanger capillary electrophoresis and/or newer short-read sequence data and whole genome assembly techniques. However, even the best draft genomes contain gaps and other imperfections due to limitations in the input data and the techniques used to build draft assemblies. Sequencing biases, repetitive genomic features, genomic polymorphism, and other complicating factors all come together to make some regions difficult or impossible to assemble. Traditionally, draft genomes were upgraded to “phase 3 finished” status using time-consuming and expensive Sanger-based manual finishing processes. For more facile assembly and automated finishing of draft genomes, we present here an automated approach to finishing using long-reads from the Pacific Biosciences RS (PacBio) platform. Our algorithm and associated software tool, PBJelly, (publicly available at https://sourceforge.net/projects/pb-jelly/) automates the finishing process using long sequence reads in a reference-guided assembly process. PBJelly also provides “lift-over” co-ordinate tables to easily port existing annotations to the upgraded assembly. Using PBJelly and long PacBio reads, we upgraded the draft genome sequences of a simulated Drosophila melanogaster, the version 2 draft Drosophila pseudoobscura, an assembly of the Assemblathon 2.0 budgerigar dataset, and a preliminary assembly of the Sooty mangabey. With 24× mapped coverage of PacBio long-reads, we addressed 99% of gaps and were able to close 69% and improve 12% of all gaps in D. pseudoobscura. With 4× mapped coverage of PacBio long-reads we saw reads address 63% of gaps in our budgerigar assembly, of which 32% were closed and 63% improved. With 6.8× mapped coverage of mangabey PacBio long-reads we addressed 97% of gaps and closed 66% of addressed gaps and improved 19%. The accuracy of gap closure was validated by comparison to Sanger sequencing on gaps from the original D. pseudoobscura draft assembly and shown to be dependent on initial reference quality.
Automatically fixing real-world JavaScript performance bugs

Programs often suffer from poor performance that can be fixed by relatively simple changes. Currently, developers either manually identify and fix such performance problems, or they rely on compilers to optimize their code. Unfortunately, manually fixing performance bugs is non-trivial, and compilers are limited to a predefined set of optimizations. This paper presents an approach for automatically finding and fixing performance bugs in JavaScript programs. To focus our work on relevant problems, we study 37 real-world performance bug fixes from eleven popular JavaScript projects and identify several recurring fix patterns. Based on the results of the study, we present a static analysis that identifies occurrences of common fix patterns and a fix generation technique that proposes to transform a given program into a more efficient program. Applying the fix generation technique to three libraries with known performance bugs yields fixes that are equal or equivalent to those proposed by the developers, and that lead to speedups between 10% and 25%.
Cross-Layer Proactive Hybrid MAC to Prolong Lifetime of Wireless Sensor Networks

A fundamental design challenge in energy-constrained wireless sensor networks is to maximise the operational time. With increasing node density and multi-hop communications, disproportion on traffic intensity and congestion level among nodes leads to uneven battery consumption and thus the existence of failure-prone nodes. Common fault-tolerant schemes focus on routing strategies although the effectiveness of rerouting is limited by the congested medium where failure-prone nodes are located. We propose a localised proactive hybrid medium access control (MAC) approach (Pro-SSAS), where nodes that are expected to be failure-prone are enhanced with scheduling access from their senders to avoid being active during the energy-expensive contention periods. Cross-layer techniques are implemented to detect failure-prone nodes and to adapt the MAC operation. Realistic simulations have verified that Pro-SSAS significantly prolongs overall network lifetime compared with rerouting schemes.
Shear Strengthening of RC without Stirrups for Deep Beams with Near Surface Mounted CFRP Rods

The main objective of the work in this paper is to study Shear Strengthening of RC without stirrups Deep Beams with Near Surface Mounted CFRP Rods. The experimental work consists of fabrication and testing simply supported reinforced concrete deep beam with Near Surface Mounted CFRP Rods (NSM) beams , consists of five beams failed in shear and each beam had with dimensions (150 mm x400 mm x 1300 mm), with concrete compressive strength of about 30.54 MPa were casted and tested at 28 days. This research is devoted to investigate the behavior and load carrying capacity of reinforced concrete strengthened and repaired with carbon fiber reinforced polymer (CFRP) rods in shear. For NSM beams designed to fail in shear investigate how the orientation and spacing of CFRP rods affect the shear behavior and the load carrying capacity. The results, show that the beams strengthened externally by CFRP rods provided improvement in ultimate loads. The increase in ultimate loads reached (28.57 %) the behavior of strengthened and repaired NSM beams by CFRP rods increasing the ultimate strength and reducing the ultimate central deflection for increasing the load at the cracking stage and also the load capacity and reducing shear crack widths compared with the control beam. Keywords—Concrete; deep beam; CFRP rods
A Low Communication Sort Algorithm for a Parallel Database Machine

The paper considers the prcblem of sorting a file in a distributed system. The file is originally distributed on many sites, and the result of the sort is needed at another site called the “host”. The particular environment that we resume is a backend parallel database machine, but the work is applicable to distributed database systems as well. After discussing the drawbacks of several existing algorithms, we propose a novel algorithm that exhibits complete parallelism during the sort, merge, and return-tohost phases. In addition, this algorithm decreases the amou@ of inter-processor communication compared to existing parallel sort algorithms. We describe an implementation of the algorithm, present performance measurements, and use a validated model to demonstrate its scalability. We also discuss the effect of an uneven distribution of data among the various processors.
Cu pillar bump-on-trace (BoT) design for ultra low-k packaging

In this work, the design of a flip chip chip scale package (FCCSP) using 28 nm ultra low-k (ULK) die and copper (Cu) pillar BOT technology were presented and qualified by reliability test. Many tests and inspections were implemented to check the fabrication process quality such as bump shear test, die chipping/crack inspection after die saw, X-ray inspection after die bond reflow, and scanning acoustic microscopy (SAT) inspection after underfill dispersing and molding. In addition, the three-dimensional finite element analysis (FEA) was employed to compare the impact of molding compounds on the packaging stress before true experiment. All samples passed the open/short test and no underfill or ULK delamination was found by SAT and scanning electron microscopy (SEM) cross-section check after MSL-3 pre-condition, Thermal Cycling test (TCT), High Temperature Storage test (HTST) and Unbiased Highly Accelerated Stress Test (uHAST).
Energy-efficient acceleration of big data analytics applications using FPGAs

A recent trend for big data analytics is to provide heterogeneous architectures to allow support for hardware specialization. Considering the time dedicated to create such hardware implementations, an analysis that estimates how much benefit we gain in terms of speed and energy efficiency, through offloading various functions to hardware would be necessary. This work analyzes data mining and machine learning algorithms, which are utilized extensively in big data applications in a heterogeneous CPU+FPGA platform. We select and offload the computational intensive kernels to the hardware accelerator to achieve the highest speed-up and best energy-efficiency. We use the latest Xilinx Zynq boards for implementation and result analysis. We also perform a first order comprehensive analysis of communication and computation overheads to understand how the speedup of each application contributes to its overall execution in an end-to-end Hadoop MapReduce environment. Moreover, we study how other system parameters such as the choice of CPU (big vs little) and the number of mapper slots affect the performance and power-efficiency benefits of hardware acceleration. The results show that a kernel speedup of upto χ 321.5 with hardware+software co-design can be achieved. This results in χ2. 72 speedup, 2. 13χ power reduction, and 15. 21χ energy efficiency improvement (EDP) in an end-to-end Hadoop MapReduce environment.