Miracle-dz/UniFAR-FTUs huggingface dataset:
The Score Function

Many complex real world systems can be modeled as discrete-event systems (DES). Examples are computer-communication networks, exible manufacturing systems, probabilistic fracture mechanics models, PERT-project networks and ow networks. In view of the complex interaction of such DES they are typically studied via stochastic simulation. In designing and analyzing such complex DES we are often interested not only in performance evaluation but in sensitivity analysis and optimization as well. Consider for example: (1) Manufacturing system. Here (i) the performance measure may be the average waiting time of an item to be processed at several work stations (robots) according to a given schedule and route; (ii) the sensitivity and decision parameters may be the average rate at which the workstations (robots) process the item. In such a system we might be interested in minimizing the average make-span consisting of the processing time and delay time with allowance for some constraints (e.g. cost). (2) Failure probability models for mechanical passive components (pipes, vessels). Here (i) the performance measure may be cumulative failure or leakage probability of a passive component over some time; (ii) the sensitivity and decision parameters may be the geometry of the component (thickness of the walls), fracture toughness of the 0y
FPGA based Packet Classification using multi-Pipeline Architecture

This paper proposes a decision-tree-based linear multi-pipeline architecture on FPGA’s for packet sorting. We reflect on the next-generation packet classification problems where more than 5-tuple packet header fields has been classified. From traditional fixed 5-tuple matching, Multi-field packet classification has been evolved for flexible matching with arbitrary combination of numerous packet header fields. The recently proposed Open Flow switching requires classifying each packet using up to 12-tuple packet header fields. It become a great task to develop scalable solutions for next-generation packet classification that support larger rule sets, additional packet header fields and higher throughput. This paper proposes a 2-D multi-pipeline decision-tree-based architecture for next-generation packet classification which exploits the abundant parallelism and other desirable features such as current field-programmable gate arrays (FPGAs),. We propose several optimization techniques for the state-of-the-art decision-tree-based algorithm by examine the various traditional 5-tuple packet classification methods. By using set of 12-tuple rules, the framework has been developed to partition the rule set into multiple subsets each of which is built into an optimized decision tree. To maximize the memory utilization. a tree-to-pipeline mapping scheme is carefully designed while underneath high throughput. Our proposed architecture can store up to 1K synthetic 12-tuple rules or 10K real-life 5-tuple rules in on-chip memory of a single up to date FPGA, and maintain 80 or 40 Gbps throughput for least packets of size (40 bytes) respectively. To utilize the memory properly and to sustaining high throughput, a mapping scheme based on tree-to-pipeline is designed carefully. This paper deal with the profuse parallelism and other preferred features provided by present field-programmable gate arrays and propose a 2-D multi-pipeline decision tree based architecture for next-generation packet sorting. The Verilog Hardware description languages (VHDL) are used to design the proposed architecture and synthesized using Xilinx Software.
Location Inference from Tweets using Grid-based Classification

The impact of social media and its growing association with the sharing of ideas and propagation of messages remains vital in everyday communication. Twitter is one effective platform for the dissemination of news and stories about recent events happening around the world. It has a continually growing database currently adopted by over 300 million users. In this paper we propose a novel grid-based approach employing supervised Multinomial Naive Bayes while extracting geographic entities from relevant user descriptions metadata which gives a spatial indication of the user location. To the best of our knowledge our approach is the first to make location inference from tweets using geo-enriched grid-based classification. Our approach performs better than existing baselines achieving more than 57% accuracy at city-level granularity. In addition we present a novel framework for content-based estimation of user locations by specifying levels of granularity required in pre-defined location grids.
Scalable Relative Debugging

Detecting and isolating bugs that arise only at high processor counts is a challenging task. Over a number of years, we have implemented a special debugging method, called "relative debugging," that supports debugging applications as they evolve or are ported to larger machines. It allows a user to compare the state of a suspect program against another reference version even as the number of processors is increased. The innovative idea is the comparison of runtime data to reason about the state of the suspect program. While powerful, a naïve implementation of the comparison phase does not scale to large problems running on large machines. In this paper, we propose two different solutions including a hash-based scheme and a direct point-to-point scheme. We demonstrate the implementation, a case study, as well as the performance, of our techniques on 20K cores of a Cray XE6 system.
A full lifecycle performance verification methodology for multicore systems-on-chip

Multicore Systems-on-Chip (MCSoC) are comprised of a rich set of processor cores, specialized hardware accelerators, and I/O interfaces. Functional verification of these complex designs is a critical and demanding task, however, focusing only on functional verification is very risky because the motivation for building such systems in the first place is to achieve high levels of system throughput. Therefore a functionally correct MCSoC that does not exhibit sufficient performance will fail in the market. In addition, limiting performance verification efforts to analyzing individual system components in isolation is insufficient due to: (1) the degree of system-level resource contention that an application domain imposes on the MCSoC, and (2) the degree of configuration flexibility that is typically afforded by an MCSoC. These factors motivate system-level performance verification of MCSoC. This article presents an important industrial case study of MCSoC performance verification involving both pre- and postsilicon analysis, highlighting the methodology used, the lessons learned, and recommendations for improvement.
Ju n 20 01 Forecast and event control On what is and what cannot be possible Part I : Classical case

Consequences of the basic and most evident consistency requirement—that measured events cannot happen and not happen at the same time—are shortly reviewed. Particular emphasis is given to event forecast and event control. As a consequence, particular, very general bounds on the forecast and control of events within the known laws of physics result. These bounds are of a global, statistical nature and need not affect singular events or groups of events. Principle of self-consistency An irreducible, atomic physical phenomenon manifests itself as a click of some detector. There can either be a click or there can be no click. This yes-no scheme is experimental physics in-a-nutshell (at least according to a theoretician). From that kind of elementary observation, all of our physical evidence is accumulated.
The Strathclyde Complexity Measure

Corpus analysis has potential as a source of insight on language constituency. We describe a project whose objective is to employ such insights, drawn from statistical or frequency analyses, as a means of predicting the likely match between a readers’ reading comprehension level and one or more target texts. With this possibility, we provide a means of selecting reading materials that are suited to individual abilities. This has promising application both for native English speakers and for second language learners of English. Our approach to this aim is detailed in this paper.
Susceptibilidad a desinfectantes de Trichomonas vaginalis y Escherichia coli presentes en fómites experimentales

Las enfermedades infecciosas provocadas por microorganismos patogenos se pueden transmitir directa o indirectamente. El protozoario Trichomonas vaginalis y la bacteria Escherichia coli son patogenos para el ser humano que pueden ser trans- mitidos por fomites. Existe una gama de productos para desinfectar, pero no existe informacion sobre el efecto completo de su eficacia en forma comparativa sobre bacterias o tricomonas en interaccion con diferentes tipos de materiales. En este trabajo, se analizo el efecto de algunos desinfectantes sobre la viabilidad de Escherichia coli cepa 055 y Trichomonas vaginalis cepa GT-21, depositadas sobre diferentes tipos de materiales. Se diseno un sistema in vitro con fomites experi- mentales para estudiar el efecto sobre estos patogenos. Se encontro que las tricomonas permanecen viables hasta ocho horas, y las bacterias hasta 24 horas en madera, papel, tela y plastico. Sin embargo, ambos microorganismos sobreviven solamente entre 1 y 4 horas sobre vidrio o metal. Tanto las bacterias como las tricomonas son inhibidas por los desinfec- tantes probados, siendo los mas efectivos el etanol a 70% y el producto comercial Lysol.
A Review on HTTP Streaming Strategies in Media Streaming

- Streaming is mostly referred as a delivery system for media content or dynamic data. HTTP was not designed for data streaming. HTTP communications are stateless, and they take place over TCP/IP where there is no continuous connection between the ends. Usually, HTTP responses are buffered rather than streamed. HTTP 1.1 added supports for streaming through keep-alive header so data could be streamed. There are various HTTP streaming strategies-Progressive http streaming, HDS (HTTP dynamic streaming), HLS (HTTP live streaming), HSS (Http smooth streaming), DASH(Dynamic adaptive streaming over http and some others. HTTP streaming works by breaking the overall stream into a sequence of small HTTP-based file downloads, each down-load loading one short chunk of an overall potentially unbounded transport stream. My focus is on http streaming. In this paper, a review of various streaming strategies has been presented.
"Child as the measure of all things": the body as a referent in designing a museum exhibit to understand the nanoscale

The nanoscale, despite being something "present" in our everyday life, is actually an abstract concept given the impossibility of having a direct perception of it. This article presents the design process and analysis of an interactive exhibit called "NanoZoom" for a temporary exhibition for the science museum of Barcelona. The goal of the exhibit was to help users understand how small objects are in the nanoscale by designing a fullbody interactive experience. The hypothesis behind the design of the system was based on the idea that our body is our constant referent to allow us to understand issues of scale, proportions, distances, etc. Hence, taking the body of the user as a referent should help users better understand how small objects in the nanoscale are. The approach was based on a contemporary view on the Vitruvian Man in fullbody interaction; i.e. based on modern theories that claim that embodied interaction can foster a better learning of our environment. Experimental assessment was carried out with 64 children, comparing the fullbody interactive experience with a desktop adaptation of it. Results showed better performance on children's memorability and classification of objects (ranging from the size of centimeters to the nanoscale) for those who used the fullbody experience with respect to those in the desktop system.
Strong El Niño events and nonlinear dynamical heating

We present evidence showing that the nonlinear dynamic heating (NDH) in the tropical Pacific ocean heat budget is essential in the generation of intense El Niño events as well as the observed asymmetry between El Niño (warm) and La Niña (cold) events. The increase in NDH associated with the enhanced El Niño activity had an influence on the recent tropical Pacific warming trend and it might provide a positive feedback mechanism for climate change in the tropical Pacific.
Phoneme Recognition using Hidden Markov Models : Evaluation with signal parameterization techniques

HMM applications show that they are an effective and powerful tool for modelling especially stochastic signals. For this reason, we use HMM for Timit phoneme recognition. The main goal is to study the performance of an HMM phoneme recognizer to fix on an optimal signal parameters. So, we apply different techniques of speech parameterization such as MFCC, LPCC and PLP. Then, we compare the recognition rates obtained to check optimal features. We varied coefficient number of each sample from 12 to 39 for all features. Experimental results show that 39 PLP is the most appropriate parameters for our recognizer. Keywords— HMM, HTK, LPCC, MFCC, PLP, TIMIT
Comments-oriented blog summarization by sentence extraction

Much existing research on blogs focused on posts only, ignoring their comments. Our user study conducted on summarizing blog posts, however, showed that reading comments does change one's understanding about blog posts. In this research, we aim to extract representative sentences from a blog post that best represent the topics discussed among its comments. The proposed solution first derives representative words from comments and then selects sentences containing representative words. The representativeness of words is measured using ReQuT (i.e., Reader, Quotation, and Topic). Evaluated on human labeled sentences, ReQuT together with summation-based sentence selection showed promising results.
Docking to pallets with feedback from a sheet-of-light range camera

The problem studied is feedback for docking a mobile robot or AGV, to a pallet. The pallet is of known size but with an essentially unknown load. The pallet has an initial uncertainty in pose (position and orientation) of the order /spl plusmn/15 cm and /spl plusmn/20 degrees. The docking error is required to be within /spl plusmn/1 cm and /spl plusmn/1 degree with "very low" failure rate. For the docking a combination of a range camera and a video camera is used. In the paper the range camera is emphasized. Experimental results from this work in progress are presented. Successful docking has been made with typical /spl plusmn/5 mm as errors. Currently one weak part is the integration with the control system on board the robot. Our persistent experience from this and earlier tests is that the weak part when using non-contact sensing for feedback in robots is the association problem. It should be mentioned that the resolution of a range camera is strongly distance dependent. One finding in the paper is that this type of docking is feasible and can be made self-monitoring.
Bites of Lists - Mapping and Filtering Sublists

The idea of applying map and ﬁlter functions on consecutive sublists instead of on individual list elements is discussed and developed in this paper. A non-empty, consecutive sublist is called a bite. Both map and ﬁlter functions accept a function parameter - a bite function - which is responsible for returning a preﬁx bite of a list. We develop families of bite functions via a collection of higher-order bite generators. On top of the bite generators, a number of bite mapping and bite ﬁltering functions are introduced. We illustrate the usefulness of bite mapping and ﬁltering via examples drawn from a functional programming library that processes music, represented as Standard MIDI Files.
Multi-user MIMO CDMA systems using complete complementary sequences

The authors propose a novel use of complete complementary (CC) sequences for increased spectral efficiency in a multiple-input–multiple-output (MIMO) code division multiple access (CDMA) system. The new method overcomes many of the problems and limitations persistent in single-input–single-output (SISO) and proves that under the proposed MIMO CC-CDMA system, the capacity for the number of supported users increases linearly by the number of transmitters. The paper also shows that the MIMO CC-CDMA system demonstrates a superior performance over those using traditional Walsh spreading sequences (Walsh-CDMA). Results include the bit error rate comparison for CC-CDMA frequency selective fading channels and that of the Walsh-CDMA under flat fading channels.
Nerstrand: Fast Multi-Threaded Graph Clustering Extended Abstract

In this work we apply the multilevel paradigm to optimizing the modularity of a graph clustering on parallel shared memory architectures. We improve upon the state of the art by introducing new methods for eﬀectively and eﬃciently coarsening graphs with power-law degree distributions, detecting an unknown number of communities, and for performing greedy modularity reﬁnement in parallel. Finally, we present the culmination of this research, the graph clustering tool Nerstrand 1 . In serial mode, Nerstrand runs in a fraction of the time of current methods and produces re-sults of equal quality. When run with multiple threads, Nerstrand exhibits signiﬁcant speedup without decreasing quality. Nerstrand works well on large graphs, clustering a graph with over 18 million vertices and 261 million edges in 18 . 3 seconds.
Robust Simulation of Small-Scale Thin Features in SPH-based Free Surface Flows

Smoothed particle hydrodynamics (SPH) is efficient, mass preserving, and flexible in handling topological changes. However, small-scale thin features are difficult to simulate in SPH-based free surface flows, due to a number of robustness and stability issues. In this paper, we address this problem from two perspectives: the robustness of surface forces and the numerical instability of thin features. We present a new surface tension force scheme based on a free surface energy functional, under the diffuse interface model. We develop an efficient way to calculate the air pressure force for free surface flows, without using air particles. Compared with previous surface force formulae, our formulae are more robust against particle sparsity in thin feature cases. To avoid numerical instability on thin features, we propose to adjust the internal pressure force by estimating the internal pressure at two scales and filtering the force using a geometry-aware anisotropic kernel. Our result demonstrates the effectiveness of our algorithms in handling a variety of small-scale thin liquid features, including thin sheets, thin jets, and water splashes.
An Integrated De-noise and Enhancement Method for Ancient Chinese Tablet Images

Image noise can severely affect Chinese tablet image comprehension. In this paper, a novel integrated denoising and enhancement method for Chinese tablet image is proposed. The method consists of three stages de-noising operations. First, granular bright spots are smoothed by convoluting input Chinese tablet images with the bilateral filter. For obtaining more clear edge detail image, contrast enhancement between the foreground and background of the Chinese tablet image is followed by Top-Hat and Bottom-Hat transformations. Next, a mixture of run-length statistics and connected region techniques is employed to remove the random block noises in the images. Then, two mathematical morphological operators, erosion and dilation, are used to remove small holes and linear noises. Experimental results show that the proposed method can effectively remove most image noise (including block noise, and linear noise) and preserve characters better than existing methods.
Nrf2 Is a Direct PERK Substrate and Effector of PERK-Dependent Cell Survival

ABSTRACT Activation of PERK following the accumulation of unfolded proteins in the endoplasmic reticulum (ER) promotes translation inhibition and cell cycle arrest. PERK function is essential for cell survival following exposure of cells to ER stress, but the mechanisms whereby PERK signaling promotes cell survival are not thoroughly understood. We have identified the Nrf2 transcription factor as a novel PERK substrate. In unstressed cells, Nrf2 is maintained in the cytoplasm via association with Keap1. PERK-dependent phosphorylation triggers dissociation of Nrf2/Keap1 complexes and inhibits reassociation of Nrf2/Keap1 complexes in vitro. Activation of PERK via agents that trigger the unfolded protein response is both necessary and sufficient for dissociation of cytoplasmic Nrf2/Keap1 and subsequent Nrf2 nuclear import. Finally, we demonstrate that cells harboring a targeted deletion of Nrf2 exhibit increased cell death relative to wild-type counterparts following exposure to ER stress. Our data demonstrate that Nrf2 is a critical effector of PERK-mediated cell survival.
The Los Angeles Community Development Bank: The Possible Pitfalls of Public-Private Partnerships

In response to the 1992 Los Angeles riots, the federal government, city and county officials, commercial banks and community leaders established the nonprofit Los Angeles Community Development Bank (LACDB). This public-private partnership was a new development model, designed to spur economic growth in some of Los Angeles’ most disadvantaged areas. The LACDB was capitalized with $435 million from the U.S. Department of Housing and Urban Development and ranks as the federal government’s largest inner-city lending initiative. By January 2001, however, the bank had experienced unacceptably high losses and was seeking permission to continue operations, after reducing its staff by half and closing most of its offices. This article examines why this innovative public-private economic development partnership confronted such difficulties. Public-private partnerships continue to be an important vehicle for urban economic development. This case study provides a warning of potential pitfalls that can occur from such arrangements.
Motion planning of continuum tubular robots based on centerlines extracted from statistical atlas

Continuum tubular robots, which are constructed by telescoping pre-curved elastic tubes, are capable of balancing the force application and steerability during minimally invasive surgeries. These devices are able to reach the desired surgical sites in body cavities without colliding with critical blood vessels, nerves and tissues. However, the motion planning of continuum tubular robots is quite challenging because of their complicated kinematics as well as the high dimensional configuration space. In this paper, a sampling-based motion planning method is proposed based on the Rapidly-exploring Random Tree (RRT) algorithm for continuum tubular robots in 3D environments, such as medullary cavities. The proposed motion planner enables a continuum tubular robot to maneuver roughly along the central axis of the statistical humerus atlas in an approximate follow-the-leader manner. The experiment results have demonstrated the effectiveness and superiority of the proposed motion planning algorithm.