Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization environments and the NEOS server

The authors are interested in the development of problem-solving environments that simplify the formulation of optimization problems, and the access to computational resources. Once the problem has been formulated, the first step in solving an optimization problem in a typical computational environment is to identify and obtain the appropriate piece of optimization software. Once the software has been installed and tested in the local environment, the user must read the documentation and write code to define the optimization problem in the manner required by the software. Typically, Fortran or C code must be written to define the problem, compute function values and derivatives, and specify sparsity patterns. Finally, the user must debug, compile, link, and execute the code. The Network-Enabled Optimization System (NEOS) is an Internet-based service for optimization providing information, software, and problem-solving services for optimization. The main components of NEOS are the NEOS Guide and the NEOS Server. The current version of the NEOS Server is described in Section 2. The authors emphasize nonlinear optimization problems, but NEOS does handle linear and nonlinearly constrained optimization problems, and solvers for optimization problems subject to integer variables are being added. In Section 4 the authors begin to explore possible extensions to the NEOS Server by discussing the addition of solvers for global optimization problems. Section 5 discusses how a remote procedure call (RPC) interface to NEOS addresses some of the limitations of NEOS in the areas of security and usability. The detailed implementation of such an interface raises a number of questions, such as exactly how the RPC is implemented, what security or authentication approaches are used, and what techniques are used to improve the efficiency of the communication. They outline some of the issues in network computing that arise from the emerging style of computing used by NEOS.
Real-Time Cell Arrival Sequence Estimation and Simulation for IP-over-ATM Networks

We have developed a new traffic measuring tool and applied it to the real-time simulation of a network. It monitors IP traffic on an ATM link and continuously transfers the length and timestamp of each IP packet to a post-processing system. The post-processing system receives the data, estimates the cell’s arrival epoch at the transmission queue of the ATM link, and simulates the queueing behavior on-line if conditions differ from those of the actual system. The measuring tool and realtime simulation represent a new approach to traffic engineering. A new estimation problem, the arrival sequence estimation, is shown and some algorithms are proposed and evaluated. Also, a new dimensioning algorithm called the queue decay parameter method, which is expected to be robust and applicable to real-time control, is proposed and evaluated. key words: real-time simulation, traÆc engineering, ATM, IP
Robustness of digital artist authentication

In many cases it is possible to determine the authenticity of a painting from digital reproductions of the paintings; this has been demonstrated for a variety of artists and with diﬀerent approaches. Common to all these methods in digital artist authentication is that the potential of the method is in focus, while the robustness has not been considered, i.e. the degree to which the data collection process inﬂuences the decision of the method. However, in order for an authentication method to be successful in practice, it needs to be robust to plausible error sources from the data collection. In this paper we investigate the robustness of the newly proposed authenticity method introduced by the authors based on second generation multiresolution analysis. This is done by modelling a number of realistic factors that can occur in the data collection.
Synthetic Benchmark Digital Circuits: A Survey

Abstract Today’s VLSI CAD tools are to be designed to handle tomorrow’s designs. But, what are tomorrow’s designs? How large and complex will they be? are important questions, realistic answers for which are necessary for the tool architects. The scenario is similar in the case of hardware architects including those who design processors and FPGAs. For the VLSI CAD tool and FPGA architects, the synthetic benchmark circuits (SBCs) come to their rescue by providing representative designs of tomorrow. This paper elaborates on the various techniques reported in the literature for generation of SBCs. It also presents a case study of generating a SBC for accelerated life testing of an FPGA. The paper concludes posing interesting open issues in this field.
SMIL: Simple Morphological Image Library

SMIL est une bibliotheque de traitement d'images 2D/3D. Elle a ete developpee pour repondre a une demande de plus en plus forte (en particulier dans le cas de projets industriels) en termes de performances : taille d'images (2D ou 3D) et temps d'execution. Developpee en C++ et utilisant les templates, elle peut etre utilisee avec n'importe quel type standard de donnees. Un effort important a ete porte sur la factorisation du code (par le biais de functors), d'une part, pour faciliter l'integration de nouvelles fonctions, et d'autre part pour concentrer les parties du code permettant l'optimisation. Ces "briques" communes optimisees utilisent le code SIMD genere par l'auto-vectorisation de gcc et sont egalement parallelisees grâce a l'utilisation d'OpenMP.
GPU R‐Trie: Dictionary with ultra fast lookup

R‐Trie dictionary is a multi‐way retrieval tree for arbitrary length binary keys. It is designed taking into account utilization of thousands of parallel vector threads, a fundamental technique of programming GPU processors. Dictionary bulk creation algorithm automatically scales to use as many threads as elements in the input batch, without any synchronization or page locking, exceeding 20·106 key insertions per second on a consumer class device. Bulk search procedure achieves 600·106 lookups per second in case of a Longest Prefix Match algorithm and 3·109 lookups per second in case of exact key matching. In this paper, we describe details of implementation, present results of run‐time experiments, and enumerate several open problems for future.
Path-based compilation

Many compilers use profiles of programs to direct the focus and degree of performance optimizations. Profiles are statistics from program runs, usually collected at individual points in the program text, e.g., branches, call sites, or memory accesses. But optimizations based on individual sample points in the program miss an important detail of program behavior: how pieces of the program relate to each other dynamically. A path profile collects statistics over paths (sequences of points) in the program, linking the statistics to the dynamic behavior. By instrumenting and collecting path profiles through a program, we can exploit this dynamic behavior, improving performance more than point profiling techniques have allowed. This thesis shows how to collect path profiles efficiently, then applies the path profiles to two optimizations, static correlated branch prediction and path-based superblock scheduling. These two optimizations address different performance aspects of modern machines; many other optimizations can also benefit from path profile information. Path profiles can be collected with asymptotic efficiency comparable to point profiles. This thesis reports wall-clock times for a path profiler that performs within a factor of five of the overhead of point profilers. Path-based static correlated branch prediction (SCBP) exhibits better branch prediction accuracy than previously thought possible for static prediction techniques; cycle-level performance models show that SCBP improves performance on multiple-issue, deeply pipelined microprocessors like those being built today. In path-based superblock scheduling, path profiles guide the selection of blocks to build superblocks. Global instruction schedulers group instructions that are likely to execute together into scheduling regions and attempt to reduce program cycle counts by compacting regions. Path profiles improve on the former task over point profiles. This improvement translates to lower cycle counts to complete a program with code expansion and cache miss rates similar to or better than that of superblock selection using point profiles. Path profiling is practical and general; path profiles can be used to perform better optimizations. With tuning, path profiling overheads are similar to those of point profilers. This thesis demonstrates the generality of path statistics by exhibiting two optimizations that benefit from them, but many other optimizations can use the more detailed characterization of program behavior that path profiles provide.
Effects of mechanical and chemical treatments on the pore-size distribution in wood pulps examined by inverse size-exclusion chromatography

Nous avons adapte la technique de la chromatographie d'exclusion inverse a une methode de garnissage de colonne permettant l'analyse des pâtes de bois vierges et jamais sechees afin de determiner les effets des differents traitements mecaniques et chimiques sur le gonflement des fibres (volume des pores et distribution des grosseurs de pore). Nous avons observe que la reproductibilite etait elevee (±2-4%) pour les pâtes chimiques et plutot satisfaisante (±4-8%) pour les pâtes mecaniques. Par ailleurs, nous avons etudie les effets du raffinage, de la teneur en lignine, du recyclage et des contre-ions sur la distribution des grosseurs des pores. Cette nouvelle technique nous a permis d'avoir une comprehension a la fois meilleure et plus complete de la facon dont les grosseurs de pore sont affectees par les differents traitements. La distribution apparente des grosseurs des pores allait de pores petites dans la PTM non traitee a de grosses pores dans la pâte kraft ecrue. Cette tendance etait encore plus prononcee dans le cas de la pâte kraft blanchie. Le recyclage des pâtes engendre l'effondrement partiel irreversible des pores.
Retinal pigment epithelium transplantation in retinal diseases

Age-related macular degeneration (AMD) and inherited macular diseases (IMD) are retinal disorders that can cause blindness through atrophy of the retinal pigment epithelium (RPE) or choroidal neovascularisation (CNV). RPE transplantation in severe forms of neovascular AMD has been performed with promising short-term outcomes. However, this approach has not been evaluated in atrophic types of AMD or IMD. Furthermore, the long-term outcomes of photoreceptors cell function rescue by RPE reconstruction in neovascular AMD is unknown. Current surgical techniques are complex with associated high complication rates. Therefore, other treatment approaches to reconstruct the RPE are required. This thesis aims to examine whether long-term photoreceptor cell function rescue can be achieved through RPE reconstruction by investigating the outcomes of autologous RPE transplantation or full macular translocation in AMD and IMD. A further aim is to determine the feasibility of a new approach to reconstruct the RPE using human embryonic stem cell (hESC). A prospective study of autologous RPE-choroid grafts in 9 patients with atrophic macular disease secondary to AMD or IMD demonstrated that submacular RPE graft can support retinal function and fixation. However, there was a high surgical and post-operative complication rates and the overall visual acuity and reading ability declined. Long-term follow-up demonstrated that the graft can maintain retinal function for over 2 years in some patients. A retrospective review of long-term outcomes following autologous RPE-choroid grafts and full macular translocation in 12 and 40 patients with neovascular AMD, respectively, showed that rescue of retinal function beyond 2 years is possible. A visual acuity of 6/12 was achieved and maintained for over 2 years in 8% and 15% of patients who had patch graft and translocation, respectively. However, overall visual acuity outcomes were limited by delayed post-operative complications such as recurrent CNV and cystoid macular oedema. A prospective porcine experiment showed that subretinal implant of hESC derived-RPE was feasible and human donor cell can survive in vivo for up to 6 weeks. However, there was significant loss of the hESC-RPE which may have occurred intra-operatively or during the first 2 weeks post-operatively. Macrophages were noted at the site of the graft suggesting some inflammatory and immunological responses to the human cells, polyester substrate or surgical trauma. The work in this thesis has provided the proof of principle that reconstruction of the RPE can maintain retinal function in atrophic and neovascular macular diseases over the long-term. A novel approach using hESC-RPE on an artificial substrate may be a more feasible and safer alternative to current clinical techniques of RPE reconstruction.
Evaluating Predictive Models: Computing and Interpreting the c Statistic

Automation of predictive model selection has become the alchemy of today’s Business Intelligence (BI), with BI practitioners hoping to transform jargon and acronyms into gold. While statistical modeling experts disparage ‘black-box’ methods, business analysts tend to ignore theory and traditional model diagnostics, and rely on ‘lift’ or ‘gain’ charts; that is, evidence of improved accuracy of predictions of outcomes for groups, often represented graphically by Area Under Curve (AUC) of signal detection Receiver Operating Characteristic (ROC) plots. Even where interest in competitive advantage overrides concern for meaningful model parameter estimates, a concordance c statistic offers a simpler and more intuitive measure of accuracy of model predictions. SAS/Stat PROCs LOGISTIC and SURVEYLOGISTIC generate a c statistic. GENMOD and others do not, but a straightforward SAS/Base PROC SQL program computes c efficiently for at least a few thousand predictors and outcomes. A more robust hashing algorithm computes the c statistic efficiently for very large numbers of predictions and outcomes. A weighted or grouped c statistic, combined with other standard model diagnostics, effectively summarizes predictive model lift and gain. SAS Macros serve as templates for interesting c statistic algorithms, and examples from biomedical and administrative studies help analysts understand how to compute and interpret a important measure of predictive model accuracy.
Effective support of DSP by using MATLAB® in bachelor type of study

In the article an original way of teaching DSP is introduced. MATLAB system is used for direct support of DSP. An original form of MATLAB applications is developed. Students use a graphical interface and they can also work with a source code which is available in one of application windows. The source code of all applications can be modified by student and the application is immediately changed including computation results. This way of teaching is very effective because the students need not write many rows of source code.
Study of Association Rule Mining and Different Hiding Techniques

Data mining is the process of extracting hidden patterns from data. As more data is gathered,with the amount of data doubling every three years, data mining is becoming an increasingly important tool to transform this data into information. In this paper, we first focused on APRIORI algorithm, a popular data mining technique and compared the performances of a linked list based implementation as a basis and a tries-based implementation on it for mining frequent item sequences in a transactional database. We examined the data structure, implementation and algorithmic features mainly focusing on those that also arise in frequent item set mining. This algorithm has given us new capabilities to identify associations in large data sets. But a key problem, and still not sufficiently investigated, is the need to balance the confidentiality of the disclosed data with the legitimate needs of the data users. One rule is characterized as sensitive if its disclosure risk is above a certain privacy threshold. Sometimes, sensitive rules should not be disclosed to the public, since among other things, they may be used for inferring sensitive data, or they may provide business competitors with an advantage. So, next we worked with some association rule hiding algorithms and examined their performances in order to analyze their time complexity and the impact that they have in the original database. We worked on two different side effects – one was the number of new rules generated during the hiding process and the other one was the number of non-sensitive rules lost during the process.
USING IMPRECISE COMPUTATION FOR VIRTUAL AND CONSTRUCTIVE SIMULATIONS

In this work, we raise three critical questions that must be investigated to ameliorate composability of virtual simulation models and to enable adoption of systematic and stringent real-time techniques to enable more scalable simulation models for virtual and constructive simulation. The real-time techniques in question enable us to separate between policies and mechanisms and, thus, the simulation engine can decide dynamically how to run the simulation given the existing resources (e.g., processor) and the goals of the simulation (e.g., sufficient fidelity in terms of timing and accuracy). The three critical questions are: (i) how to design efficient and effective algorithms for making dynamic simulation model design decisions during simulation; (ii) how to map simulation entities (e.g., agents) into (real-time) tasks; and (iii) how to enable a divide and conquer approach to validating simulation models.
Color separation Algorithm and Rice identification

This article presents a method to identify good and bad grain and then they will be classified and processed. The algorithm mentioned here will determine the good and bad grain at high speed frame (18500 frames/s), and determine the speed of rice moving. The identification of better or worse than the threshold used in the algorithm are combination of light wavelengths and identify appropriate length of grain. This paper describes the experimental results: the influence of the light wavelength, the effect of imagecapturing speed, identity technique and threshold filtering.
Comparison of Scientific Literacy in Engine Tune-up Competencies through Guided Problem-Based Learning and Non-Integrated Problem-Based Learning in Vocational Education

This research is aimed to describe comparison of scientific literacy improvement of vocational school students in Banten, Indonesia in integrated scientific teaching using Guided model and non-integrated PBL. Research design uses quasi-experiment approach with pretest-posttest satis non randomaized group. Research instruments are essay test and performance test. Results reveal that there is no significant difference between students’ scientific literacy achievement improvement using integrated guided PBL and non-integrated PBL. Scientific literacy teaching using guided PBL can increase students achievement by 0.4243 (medium category) while the non-integrated PBL can give 0.3924 (medium category). It can be concluded that both PBL models increase student’s literacy comprehension. Improvement in scientific literacy is in the form of problem identification, problem investigation, and utilization of scientific facts. Efforts to improve scientific literacy must be conducted continually in vocational education, for problem solving in education environment.
Biological Solutions in Rotator Cuff Healing

One of the most common causes of shoulder pain and dysfunction is rotator cuff tears, and the extent of this problem is increasing with an aging population. High retear rates after rotator cuff repairs suggest that simple repairs lack the mechanical integrity to promote effective tendon healing. Greater insight into the biology underlying tendon healing processes have suggested a number of target pathways that could be modulated to encourage tendon healing after rotator cuff repairs. This review evaluates the evidence to support commonly used biological therapies and also novel and future therapeutics. The scope of this review encompasses biological therapies, modulation of systemic factors that contribute to tendinopathies and healing, as well as cellular and structural repair solutions. The role for mechanical modulation of tendon biology is also considered.
Reversing and Exploiting Wireless Sensors

Wireless sensors will soon be part of many industrial, military, and home networks. Of the various networking protocols, which include Zigbee, ISA100, Wireless HART, 6LowPAN, and others, none has yet become a definitive standard. Neither have vendors standardized upon a given operating system, compiler, or microcontroller. Users of these sensor networks are often given no command-line, no internal documentation, and no access to the internals of each device. This paper provides a thorough introduction to reverse engineering such devices, both in hardware and in software.
The injury severity score: Development and potential usefulness

A method for comparing death rates of groups of injured persons was developed, using hospital and medical examiner data for more than two thousand persons. The first step was determination of the extent to which injury severity as rated by the Abbreviated Injury Scale correlates with patient survival. Substantial correlation was demonstrated. Controlling for severity of the primary injury made it possible to measure the effect on mortality of additional injuries. Injuries that in themselves would not normally be life-threatening were shown to have a marked effect on mortality when they occurred in combination with other injuries. An Injury Severity Score was developed that correlates well with survival and provides a numerical description of the overall severity of injury for patients with multiple trauma.
An Efficient Three-phase Email Spam Filtering Technique

Email spam is one of the major problems of the today’s Internet, bringing financial damage to companies and annoying individual users. Many spam filtering techniques based on supervised machine learning algorithms have been proposed to automatically classify messages as spam or legitimate (ham). Naive Bayes spam filtering is a popular mechanism used to distinguish spam email from ham email. In this paper, we propose an efficient three-phase email spam filtering technique: Naive Bayes, Clonal Selection and Negative Selection. The experimental results applied on 10,000 email messages taken from the TREC 2007 corpus shows that when we apply the Clonal selection and Negative selection algorithms with the naive Bayes spam filtering technique the accuracy rate is increased than applying each technique alone.
Instrumental intentionality: an exploration of mediated intentionality in musical improvisation

ABSTRACT This paper examines the musician/instrument relationship through exploring notions of mediated intentionality. Ihde’s (1990) writings are taken as a starting point for examining these human–technology relationships with a particular focus on the intentionality of the human-instrument construction. Notions of instruments as mediators of intentionality are then examined from a variety of standpoints found in improvisational practice, with a focus on different conceptions of mediation, instrumental resistance and instrumental agency. Verbeek’s (2008, 387–395) conception of Cyborg Intentionality is explored as one way to extend these notions within a post-phenomenological posthuman framework. To help contextualise this discussion the author presents a performance system, the Feral Cello, whose design has been informed by the above discussion. Verbeek’s hybrid and composition notions of intentionality are used as a framework for reflection upon the performance system.