Miracle-dz/UniFAR-FTUs huggingface dataset:
Bi-objective optimization for integrating production and preventive maintenance scheduling in two-stage assembly flow shop problem

This paper presents a new bi-objective mixed integer programming model for the two-stage assembly flow shop scheduling problem with preventive maintenance (PM) activities, in which the reliability/availability approach is employed to model the maintenance concepts of a problem. PM activities carry out the operations on machines and tools before the breakdown takes place. Therefore, it helps to prevent failures before they happen. After developing a new bi-objective model, an Epsilon-constraint method is proposed to solve the problem. This problem has been known as Np-hard. Therefore, three multi-objective optimization methods, namely fast non-dominated sorting genetic algorithm, Multi-objective imperialist competitive algorithm, and non-dominated ranking genetic algorithm (NRGA) are employed to find the pareto-optimal front for large sized problems. The parameters of the proposed algorithms are calibrated using artificial neural network (ANN) and the performances of the proposed algorithms on the problems of various sizes are analyzed and the computational results reveal that NRGA outperform than two other proposed algorithms in quality of solutions and computational time.
Direct-sequence multi-carrier CDMA parallel acquisition in a multipath fading channel

This paper presents a matched filter acquisition scheme for a direct-sequence multi-carrier CDMA system using a small number of orthogonal overlapping carriers. The parallel structure of the multi-carrier system offers interesting possibilities to improve the acquisition time. The acquisition performance is discussed in a multipath fading channel and is compared to that of a single-carrier parallel acquisition scheme as well as a single-carrier serial acquisition scheme. A significant improvement of performance is shown.
Machine learning performance prediction model for heterogeneous systems

Recent advances in machine learning techniques and specialized hardware has enabled a resurgence in the interest and applicability of powerful artificial neural network based prediction systems. However, as of yet no significant leaps have been taken towards applying machine learning in heterogeneous scheduling in order to maximize system throughput. As heterogeneous systems become more ubiquitous, computer architects will need to develop new CPU scheduling approaches applying novel techniques capable of exploiting the diversity of computational resources. However, non-heterogeneous aware schedulers like the current Linux Completely Fair Scheduler (CFS) [3] cannot take advantage of diverse system resources. Heterogeneous scheduling approaches have been previously proposed by V. Craeynest et al. [6] and Markovic et al. [2] which intend to provide full and fair utilization of the different hardware resources for all threads. These approaches yielded significant performance benefits compared to the CFS on heterogeneous architectures. In this extended abstract, we describe a novel performance prediction model which is the first of its kind to utilize machine learning performance predictors at the granularity of scheduling quanta. We then highlight how a heterogeneous system scheduler may be improved by the addition of this model. The prediction model is composed of the following:
Advanced Electromagnetic Field Analysis and Its Application to Electrical Machines

The magnetic field analysis is widely used in order to design a miniature and highly efficient electrical machines. In order to analyze large (including huge mesh) and complicated problems, the development of new techniques, such as improved pre/post system, hysteresis, precise estimation method of iron loss, multigrid method, efficient optimization method, are required. In this article, recent developments of some of those techniques are discussed and a few examples are illustrated.
Effective Reading Programs for English Language Learners. A Best-Evidence Synthesis.

This article reviews experimental studies of reading programs for English language learners, focusing both on comparisons of bilingual and English-only programs and on specific, replicable models that have been evaluated with English language learners. The review method is best-evidence synthesis, which uses a systematic literature search, quantification of outcomes as effect sizes, and extensive discussion of individual studies that meet inclusion standards. The review concludes that while the number of highquality studies is small, existing evidence favors bilingual approaches, especially paired bilingual strategies that teach reading in the native language and English at the same time. Whether taught in their native language or English, English language learners have been found to benefit from instruction in comprehensive reform programs using systematic phonics, one-to-one or small group tutoring programs, cooperative learning programs, and programs emphasizing extensive reading. Research using longitudinal, randomized designs is needed to understand how best to ensure reading success for all English language learners.
PINK1 mediates spinal cord mitophagy in neuropathic pain

Background: Mitophagy is the selective engulfment of mitochondria by autophagosomes and the subsequent mitochondrial catabolism by lysosomes. Evidence has suggested an important role for mitochondrial dynamics and mitophagic flux in the development of many different neurodegenerative diseases. Objectives: The potential role of the mechanism underlying mitochondrial dynamics and mitophagic flux as it may relate to neuropathic pain is not well understood. This is a disease that largely remains an area of mechanistic uncertainty. PINK1 is a PTEN-induced mitochondrial kinase that can be selectively activated under mitochondrial stress conditions and lead to the induction of mitophagy. Materials and methods: A neuropathic pain rat model was established via spinal nerve ligation (SNL) and nociception was assayed via the von Frey filament method. Increased expression of PINK1 and the mechanism of mitophagy was detected in GABAergic interneurons of dorsal horn neurons of mice that underwent L5 SNL in comparison to control mice counterparts (n=8, P<0.001) by Western blotting, immunohistochemistry and double immunofluorescence staining. Results: Elevated expression of PINK1 appeared to localize selectively to GABAergic interneurons, particularly within autophagic mitochondria as evidenced by co-localization studies of PINK1 with BECN1, LC3II and COX IV on immunofluorescent microscopy. Furthermore, we also detected a significant increase in autophagosomes in dorsal horn neurons of SNL mice and this was consistent with increased autophagic activity as measured by the p62 autophagic substrate. Conclusion: These results demonstrate that neuropathic pain causes aberrant mitophagic flux selectively in GABAergic interneurons and provide evidence implicating mitophagy as an important area of future molecular studies to enhance our understanding of neuropathic pain.
High-level event detection in broadcast sports video

This thesis investigates semantic analysis of broadcast sports footage. A domain dependent sports video model is proposed. Under this model, the game semantics can be derived according to their relationship with the sequence of dynamic events that occur in the sport and the evolution of the spatio-temporal behaviour of a relevant object. Snooker and tennis are targeted as typical broadcast sports footage for the purpose of this research. The problem focus is to automatically extract semantically meaningful events and to convey a useful representation to the user. Access to semantics provides a more natural tool for a user to query a corpus of data than by low-level content based features alone. These semantics are however open to various interpretations by different viewers. Therefore, in order to create a successful semantic based retrieval system it is necessary to consider the user-context. Unconstrained sports footage is generally very complicated in structure, so restricting the domain being addressed enables a viewer model to be created. Domain specific features are extracted from the raw footage. These can then be exploited to develop algorithms which understand the characteristics of the data and the requirements of the user. These algorithms enable low-level domain features to be mapped to high-level semantics by learning the evolution of the features. Traditionally, low-level visual features have been used to summarise the content in view. Global colour, texture and motion have all been used for this purpose. In this thesis a novel algorithm is presented which captures the geometry of the scene without having to extract and reconstruct complicated 3D scene geometry. Hidden Markov models are then used in a novel fashion to model these observations for camera view classification. A new extension of the colour based Particle Filter is employed to track objects. It encourages better tracking in a constrained sports environment by exploiting prior scene geometry and playing surface colour information. The implementation of the tracker also allows for object collision and disappearance to be detected. The performance of the tracker is assessed using geometrical measures and by comparing it to the tracking produced using a gradient based motion estimator. Thus far, retrieval of semantic events from sports footage has relied on prior knowledge of the broadcast video syntax. Typically, the temporal interleaving of camera views has been used to infer these important events or highlights in the footage. In this research, the spatio-temporal behaviour of tennis players and snooker balls are considered as being the embodiment of a semantic event. This concept offers a new means of automatically extracting semantic episodes from sports footage. The scope of this thesis could easily be extended by further investigation into retrieval of semantic events from the vast quantities of other live and archived sports footage.
Secrecy Performance of Correlated $\alpha$ - $\mu$ Fading Channels

This letter investigates the secrecy performance of the classical Wyner’s wiretap model, where the main channel and eavesdropper channel experience correlated $\alpha $ - $\mu $ fading. Novel and exact expressions for the average secrecy capacity and secrecy outage probability are derived for the considered realistic scenario. The effect of correlation has been studied on the secrecy performance. Useful insights into the system performance are obtained through the asymptotic analysis.
Inspection en service des REP

L'inspection en service des reacteurs a eau pressurisee (REP) est une composante importante de la maintenance des reacteurs nucleaires electrogenes. Elle a pour but de prevenir, par des explorations in situ, dans la tres grande majorite des cas non destructives, l'apparition ou le developpement d'endommagements (dommage ou degradation) dont l'une des consequences est materialisee par une discontinuite appelee defaut. Cet (ces) endommagement(s) est (sont) susceptible(s) d'atteindre un degre tel que l'installation ne pourrait pas fonctionner sans un risque eleve vis-a-vis de la surete, et ce, pendant les phases de fonctionnement normal du reacteur et a fortiori en cas d'incident. On concoit donc que l'auscultation periodique des materiaux constitutifs des composants du reacteur soit essentielle tant pour: - verifier que la prise en compte des endommagements lors de la conception est pertinente ; - s'assurer, au cours du temps, que le vieillissement des composants des reacteurs ne risque pas de degrader les structures et les materiaux au-dela d'une limite qui ne serait pas acceptables pour la surete. Ainsi, l'inspection en service est une activite permanente qui doit etre geree tout le long de la vie de l'installation en exigeant un haut niveau de qualite vis-a-vis de la surete, mais aussi vis-a-vis de la competitivite.
Sensor-assisted ALOHA for wireless networks

A neural network-based system for stabilizing ALOHA random access networks is described. A grid of sensors is used to gather energy measurements for a neural network. The neural network has been trained to estimate the number of colliding users in a given slot, supporting an algorithm that tracks the number of backlogged users in the system.
Image Processing and Measurement

Images provide important information in scientific, technical, and forensic situations, in addition to their role in everyday life. Extracting information from images acquired by digital cameras involves image processing to correct colors, reduce noise, and correct for nonuniform illumination or nonplanar views. Enhancement of image details is generally accomplished by reducing the contrast of other information in the image, so that,for example, lines and edges that make measurements of structure are more accessible. The processing steps use a variety of computer algorithms and may be performed on the pixel array, or in a different space, for example, by using a Fourier transform. Some applications, especially forensic ones, require simple comparisons, but for object identification, classification, or correlations, quantitative measurements of color or density, position, size, and shape are needed. Several possible measurement quantities are available for each category, particularly shape, for which a variety of dimensionless ratios, Fourier or wavelet coefficients, and invariant moments may be used. Interpretation of the measurements depends on the nature of the image and of the specimen or scene, for instance, whether it consists of discrete objects on a surface, a section through a complex structure, or a projection through a three-dimensional space.
Epidemiology of cancer of the cervix

To the Editor:— I should like to congratulate you and your staff on the fine leading editorial, "Epidemiology of Cancer of the Cervix," inThe Journal, Dec. 3, 1960, page 1852. A former resident and friend of mine, now professor of surgery at the Christian Medical College in Ludhiana, Punjab, India, told me two years ago about not only the much lower incidence of carcinoma of the cervix in Moslems as compared with Hindus but also the similarly lower incidence of carcinoma of the penis among Moslems. The clinic and hospital there treat many patients from both groups. Might I suggest another step? I see no reason why we should not have preventive surgery as well as preventive medicine. During the war years when I was chief of surgery at the Ninth Evacuation Hospital and later surgical consultant of the Seventh Army, I always asked the various medical groups and
On the Noise Uncertainty for the Energy Detection of OFDM Signals

Orthogonal frequency-division multiplexing (OFDM) is a promising technology for communication systems. This paper investigates the impacts of unknown noise variance on the popular spectrum sensing scheme, i.e., energy detection, for OFDM cognitive radios over multipath fading channels. To study the effects of unknown parameters on the energy detector, a new maximum-likelihood estimation of noise and signal powers employing the cyclic prefix of OFDM is presented in this paper. The mean values and Cram$\acute{\text{e}}$r–Rao lower bounds of the estimation are obtained. Furthermore, the performances of the energy detector for both hypotheses, i.e., false-alarm rate and detection probability, under the influence of unknown noise variance are validated by both simulation and analytical results. The assessment on the required number of samples for the proposed energy detector is conducted, which indicates that an amount of 40–50% samples can be saved compared to the conventional energy detector.
A hybrid approach for selecting and optimizing graph traversal strategy for analyzing big code

Committee Members: Performance of program analysis expressed as traversals over graphs like control flow graph (CFG) heavily depends on the order of nodes visited during the traversals: {the traversal strategy}, more so in case of BigCode analysis that performs analysis over a large collection of input graphs. While, there exists several choices for traversal strategy, like depth-first, post-order, reverse post-order, etc., there exists no technique to choose the most time-efficient strategy for traversals. In this paper, we propose hybrid technique that utilizes the static properties of the analysis, and the dynamic properties of the input graphs to select a most time-efficient strategy for each traversal on a graph. Our contributions are: a system for expressing program analysis as traversals, a set of static and dynamic properties that influence the traversal strategy selection, a set of static analyses to compute the properties, and a decision tree that checks the properties to select and optimize the most time-efficient traversal strategy. Our evaluation shows that the hybrid technique successfully selected the most time-efficient traversal strategy for 99.99%--100% of the time and using the selected traversal strategy, the running times of the analyses on BigCode in our evaluation were considerably reduced by 23%--79%. The overhead imposed by collecting additional information for our hybrid approach is less than 0.2% of the total running time for a large dataset and less than 0.01% for an ultra-large dataset. A Hybrid Approach for Selecting and Optimizing Graph Traversal Strategy for Analyzing BigCode
Evaluation of sentence list equivalency for the TIMIT sentences by cochlear implant recipients

The equivalency of 34 TIMIT sentence lists was evaluated using adult cochlear implant recipients to determine if they should be recommended for future clinical or research use. Because these sentences incorporate gender, dialect and speaking rate variations, they have the potential to better represent speech recognition abilities in real-world communication situations. Copyright by: Sarah E. King May 2008
Topical Tacrolimus (FK506, Protopic) in the Treatment of Atopic Dermatitis

ABSTRACT Drugs are medications or substances that are used to modify physiologic responses and alleviate associated symptoms. In dermatology, medications and substances are utilized on a daily basis and include topical treatments to anesthetics in micrographic surgery to biologic-acting immunologic agents. The purposes of this section are to focus on drug, specifically how it works and how it is utilized, and to discuss routine alternatives (if available). In this column, we will focus on the uses, mechanism of action, adverse effects, and alternatives to topical tacrolimus (Protopic) in atopic dermatitis.
Effect of sildenafil on gastric emptying in healthy adults

Background and Aim: Phosphodiesterase type 5 hydrolyzes and inactivates cyclic guanosine monophosphate produced by the nitric oxide‐stimulated guanylate cyclase. Sildenafil is a potent, reversible, and highly selective inhibitor of this phosphodiesterase. It causes smooth muscle relaxation by increasing intracellular concentrations of cyclic guanosine monophosphate. The aim of this study was to test the hypothesis that sildenafil alters gastric emptying and the intragastric distribution of food in healthy adults.
Second language acquisition of intonation: the case of Dutch near-native speakers of Greek

This thesis focuses on the second language (L2) acquisition of intonation by Dutch near-native speakers of (Modern) Greek. Five experiments were carried out which can be divided into two main areas: one which was concerned with peak alignment (i.e. the timing of the intonational peaks with respect to the syllables), and another which focused on nucleus placement (the placement of the most prominent word in the utterance). The first three experiments were concerned with peak alignment in Greek prenuclear accents. A first experiment showed that there are crosslinguistic differences in the alignment of the peak in Greek and Dutch. In Greek prenuclear accents the peak is aligned just after the onset of the first postaccentual vowel. In Dutch, however, the peak is aligned earlier, and is influenced by the phonological length of the accented vowel of the word bearing the prenuclear accent. (Specifically, the peak is at the end of the accented vowel when that vowel is long, but at the end of the following consonant when it is short.) The next experiment showed that most non-native (Dutch) speakers of Greek failed to exhibit native-like peak alignment in the L2. The speakers aligned the peak in their Greek data as early as they would in Dutch when the test word has a long vowel in the accented syllable. It was also shown that speakers did not develop a 'merged' system, with values half-way between the monolingual norms for Dutch and Greek. Experiment 3 examined the effect of L2 learning on the peak alignment in prenuclear accents in the first language (LI). It was shown that even though most speakers did not master the alignment values in the L2, the alignment pattern in their LI was nevertheless affected. The last two experiments were concerned with another aspect of intonation, namely the realisation of nucleus placement in Greek yes/no questions. The yes/no questions were of two types: (i) nucleus-final (NF), in which the nucleus or main stress was located on the utterance-final word, and (ii) nucleus-non-final (NNF), in which the main stress was on an earlier word in the utterance. It was shown that the choice of nucleus placement was problematic for the group of non-native speakers. Only half of the non-native speakers produced the two different nucleus locations. Furthermore, non-native speakers' production of both types of yes/no questions differed from that of native speakers of Greek, specifically with respect to scaling (i.e. the fundamental frequency at which a certain pitch peak or valley occurs). However, their production of NF yes/no questions was closer to the native Greek norms than was their production of NNF yes/no questions. An attempt was made to interpret the results of the experiments in the light of Flege's Speech Learning Model (SLM), which was originally developed to account for segmental aspects of L2 learning. It was found that the ability of the model to account for intonational data was limited, and more specifically, that the notion of 'phonetic similarity' needs to be further refined.
A Recommendation Algorithm Based on Item Genres Preference and GBRT

The most mature and widely used collaborative filtering algorithm is facing the problem of data sparsity, which is not conducive to the acquisition of user preferences, thus affecting the recommendation effect. Introducing item genres into recommendation algorithm can reduce the impact of data sparsity on recommendation effect. The personalized preferences of users can be extracted more effectively from the preference information of item genres, and the recommendation accuracy can be further improved. On this basis, this paper proposes a recommendation algorithm based on item genres preference and GBRT, which divides similar users by K-means clustering algorithm, extracts user preferences of item genres and auxiliary features, and establishes a rating prediction model combined with GBRT algorithm. The experiments on the common datasets of Movie Lens 100K and Movie Lens 1M show that the proposed algorithm achieves 0.8%-7% optimization on the evaluation index MAE, which indicates that the impact of data sparsity is reduced to a certain extent and the recommendation efficiency is better than the existing recommendation algorithm.
Preface to Girard's Festschrift

This text is both meant as a preface to a volume of Theoretical Computer Science dedicated to Jean-Yves Girard, and as a short essay in French (with an English summary) on the relation between proof theory and programming languages -- a coming together in which Jean-Yves' works play a prominent role.
Causas de cegueira e visão subnormal no Centro Louis Braille-Porto Alegre

Etude de 235 patients, 136 masculins et 99 feminins, âges de 9 mois a 67 ans. Principales etiologies: chorio-retinite (38); glaucome congenital (37); cataracte congenitale (34); atrophie optique (24), retinopathie diabetique (10)