Miracle-dz/UniFAR-FTUs huggingface dataset:
Parameters of rank modulation codes: Examples

Rank modulation is a way of encoding information to correct errors in flash memory devices as well as impulse noise in transmission lines. Modeling rank modulation involves construction of packings of the space of permutations equipped with the Kendall tau distance. In a recent work we suggested several general constructions of codes in permutations that cover a broad range of code parameters. Here we compute examples of codes that can be obtained from these constructions.
2 Customer Familiarity and Its Effects on Post-purchase Evaluations

This paper examines the extent to which customer familiarity (i.e. the number of productrelated experiences accumulated by the customer) affects attribute-level performance and customer satisfaction. Literature on expectations and cognitive complexity suggests that the level of evaluations should be lower among high familiarity customers compared to low familiarity customers. This prediction was confirmed by the empirical study reported in this paper. The data were collected from a service setting with customers who were subject to a substantial variation in familiarity with respect to one major airline.
Bridging the gap: barriers and facilitators to research use among school principals from England and Israel

When a professional practitioner is faced with making a decision about what to do in a particular situation, do they base that decision on findings from research? This paper reports on qualitative and quantitative research which examined school principals’ perceptions of barriers to the use of research. To facilitate a comparison the study was conducted simultaneously in two countries: England and Israel using interviews, focus groups and the Barriers Scale survey instrument (Funk et al., 1991). The results of tests indicated that factors associated with the research itself, (e.g. relevance and access), were significant barriers to research use for principals from both countries (compared with factors associated with: the setting; the presentation of research; and the individual). The paper concludes that multiple strategies would be required to address a number of issues related to the dissemination of research and ways of addressing the gap between the aims of researchers, and the needs and expectations of practitioners.
Beyond linear sequence comparisons: the use of genome-level characters for phylogenetic reconstruction

The first whole genomes to be compared for phylogenetic inference were those of mitochondria, which provided the first sets of genome-level characters for phylogenetic reconstruction. Most powerful among these characters has been the comparisons of the relative arrangements of genes, which has convincingly resolved numerous branch points, including those that had remained recalcitrant even to very large molecular sequence comparisons. Now the world faces a tsunami of complete nuclear genome sequences. In addition to the tremendous amount of DNA sequence that is becoming available for comparison, there is also a potential for many more genome-level characters to be developed, including the relative positions of introns, the domain structures of proteins, gene family membership, the presence of particular biochemical pathways, aspects of DNA replication or transcription, and many others. These characters can be especially convincing owing to their low likelihood of reverting to a primitive condition or occurring independently in separate lineages, thereby reducing the occurrence of homoplasy. The comparisons of organelle genomes pioneered the way for using such features for phylogenetic reconstructions, and it is almost certainly true, as ever more genomic sequence becomes available, that further use of genome-level characters will play a big role in outlining the relationships among major animal groups.
Adaptive control of piecewise linear systems: The output tracking case

This paper studies the adaptive control problem of single-input, single-output (SISO) piecewise linear systems, a class of linear systems with switched parameters. A direct state feedback model reference adaptive control (MRAC) scheme is developed for such systems to achieve closed-loop signal boundedness and asymptotic output tracking performance. Simulation results on linearized NASA GTM models are presented to demonstrate the effectiveness of the proposed scheme.
SEMI-AUTOMATIC EXTRACTION OF DIFFERENT-SHAPED ROAD CENTERLINES FROM MS AND PAN-SHARPED IKONOS IMAGES

In this work we develop semi-automatic road extraction system for updating and storage road network data bases. Combination of some of the existing road extraction techniques such as spectral and spatial data clustering, morphological functions and graph theory is used in this proposed system. Input data of the proposed road extraction system are multi-spectral and pan-sharpened IKONOS images of Lavasan city in Iran (with respectively 4 and 1 meters spatial resolution). The proposed system investigates capability and amount of system success in extraction of different shaped roads such as straight, spiral, junction and square. In the proposed method, primarily the input image is spectrally classified by use of Fuzzy C-Means (FCM) clustering technique and road class binary image is obtained by definition of threshold value. Afterwards, quality of detected road features is improved using morphological operators like dilation, erosion, opening, closing, bridge and etc. Our approach proceeds by performing spatial cluster analysis using C-Means technique and hence, road centerline nodes are attained. Finally by use of graph theory and minimum spanning tree (MST) and defining an appropriate cost function, these key points are connected and vector road centerline is obtained. The only drawback of this system is limitation in completely extraction of road centerline in place of squares and closed loops. Attaining mean overall accuracy (OA) of 98.2% and Kappa coefficient of 86.26% in classification of image to road and non-road classes, and also mean RMS error of 0.64 pixel in comparing automatic extracted road centerline with manual extracted one, are a good criterion of proposed system success in semi-automatic extraction of roads.
Validation of Index of Well-being in a Sample of Chinese College Students

Objective:To evaluate psychometric properties of the Index of Well-being in a sample of Chinese college students. Methods: A total of 629 subjects were administered the Index of Well-being, State-Trait Anxiety Inventory, and Symptom Checklist-90. Results: Significant gender difference was found on the index of well-being. There was also significant correlation between index of well-being and negative emotionality. Index of Well-being was negatively correlated with factor scores of emotionality including state anxiety, trait anxiety, and SCl-90-depression. Conclusion:The "Index of Well-being”is psychometrically sound for application to Chinese college students.
Increased Cortical Grey Matter Lesion Detection in Multiple Sclerosis with 7 Tesla Mri: a Postmortem Verification Study 7t Postmortem Mri and Histopathology Study

The relevance of cortical grey matter pathology in multiple sclerosis has become increasingly recognised over the past decade. Unfortunately, a large part of cortical lesions remain undetected on MRI using standard field strength. In vivo studies have shown improved detection by using higher magnetic field strengths up to 7 T. So far, a systematic histopathological verification of ultrahigh-field MRI pulse sequences has been lacking. The aim of this study was to determine the sensitivity of 7T versus 3T MRI pulse sequences for the detection of cortical multiple sclerosis lesions by directly comparing them to histopathology. We obtained hemispheric coronally cut brain sections of 19 multiple sclerosis patients and 4 controls after rapid autopsy, formalin-fixed and scanned them on 3T and 7T MRI systems. Pulse sequences included T1 weighted, T2 weighted, fluid attenuated inversion recovery (FLAIR), double inversion recovery (DIR) and T2*. Cortical lesions (type I-IV) were scored on all sequences separately by an experienced rater blinded to histopathology and clinical data. Staining was performed with antibodies against proteolipid protein and scored by a second reader blinded to MRI and clinical data. Subsequently, MRI images were matched to histopathology and sensitivity of pulse sequences was calculated. Additionally, a second unblinded (retrospective) scoring of MR images was performed. Regardless of pulse sequence, 7T MRI detected more cortical lesions than 3 T. 7T FLAIR detected 225% more cortical lesions than 3T FLAIR (Z=2.22, p<0.05) and 7T T2* detected 200% more cortical lesions than 3T T2* (Z=2.05, p<0.05). Sensitivity of 7T MRI was influenced by cortical lesion type: 100% for type I (T2), 11% for type II (FLAIR/ T2), 32% for type III (T2*), and 68% for type IV (T2). We conclude that ultrahigh-field 7T MRI more than doubles detection of cortical multiple sclerosis lesions, compared to 3T MRI. Unfortunately (subpial) cortical pathology remains more extensive than what 7T MRI can reveal. 89 7T postmortem MRI and histopathology study
Nutrient losses in runoff from feedlot surfaces as affected by unconsolidated surface materials

Beef cattle feedlots contain unconsolidated surface materials (loose manure pack) that accumulate during a feeding cycle. The effects of varying amounts of unconsolidated surface materials on runoff nutrient losses are not well understood. The objectives of this study were to (1) compare runoff nutrient losses from feedlot surfaces containing varying amounts of unconsolidated surface materials, (2) determine if differences in runoff nutrient losses exist among rainfall simulation runs, (3) relate runoff nutrient losses to selected feedlot soil characteristics, and (4) identify the effects of varying runoff rate on nutrient loss rates from feedlot surfaces. This study was conducted on 0.75 m wide by 2 m long (2.47 ft wide by 6.58 ft long) plots containing 0, 6.7, 13.5, or 26.9 kg m−2 (0, 1.37, 2.77, or 5.51 lb ft−2) of unconsolidated surface materials. Simulated rainfall was applied during three 30-minute events that were separated by 24-hour intervals. Inflow was added at the top of all plots during selected tests to examine the effects of varying flow rate on nutrient loss rates. No significant differences in the measured water quality parameters were found among the surfaces containing varying amounts of unconsolidated surface materials. Measurements of dissolved phosphorus, particulate phosphorus, total phosphorus, ammonium nitrogen, chloride, total dissolved solids, electrical conductivity, and erosion consistently decreased during the three rainfall simulation runs. Runoff losses of ammonium nitrogen (NH4-N), total nitrogen, and nitrate nitrogen were all correlated to easily obtained soil EC measurements. All measured water quality parameters were significantly influenced by runoff rate. Thus, runoff rate, and not the amount of unconsolidated surface materials on the feedlot surface, significantly influenced nutrient losses in runoff.
Optimizing Planning Domains by Automatic Action Schema Splitting

As modeling details can have a large impact on planner perormance, domain transformation has been a traditional subject of interest in the planning community not only betweenlanguages, but also within languages. Herein, we automatean intra-language transformation method that has as yet beenapplied only manually, and that has never been formally described: action schema splitting, which transforms an actionschema with a big interface (many parameters) into severalschemas with smaller interfaces, exponentially reducing thenumber of ground actions. We spell out this method, characterizing exactly the choice of splits preserving equivalence tothe original schema. Making that choice involves a trade-off between interface size and plan length, which we explore bydesigning automatic domain optimization methods. Our experiments show that these methods can substantially improveperformance on domains with large interfaces.
The potential energy landscape of the ±J Ising spin glass

We calculate `inherent structures' (configurations corresponding to local potential energy minima) in the ±J Ising spin glass over a wide range of temperature T in two and three dimensions. We find that the T-dependence of the average value of the inherent-structure energy E is strikingly similar to that shown recently for a glass-forming liquids. E decreases with T only weakly at high T, but begins to decrease much more rapidly as the spin-glass transition temperature Tsg is approached. As in the liquid, we find that the rapid decrease of E with decreasing T occurs in the regime of T in which the relaxation of the spin autocorrelation function becomes increasingly non-exponential. In addition, we show that the inherent structures of the spin glass can be used to identify clusters of strongly correlated `frozen' spins, and that an incipient percolating cluster of these spins appears (within numerical error) at T = Tsg.
Iterative Universal Hash Function Generator for Minhashing

Minhashing is a technique used to estimate the Jaccard Index between two sets by exploiting the probability of collision in a random permutation. In order to speed up the computation, a random permutation can be approximated by using an universal hash function such as the $h_{a,b}$ function proposed by Carter and Wegman. A better estimate of the Jaccard Index can be achieved by using many of these hash functions, created at random. In this paper a new iterative procedure to generate a set of $h_{a,b}$ functions is devised that eliminates the need for a list of random values and avoid the multiplication operation during the calculation. The properties of the generated hash functions remains that of an universal hash function family. This is possible due to the random nature of features occurrence on sparse datasets. Results show that the uniformity of hashing the features is maintaned while obtaining a speed up of up to $1.38$ compared to the traditional approach.
Research in Agricultural Futures Markets : Past , Present and Future

In this paper we discuss how our insight into the grounds of existence of futures markets has changed. We discuss futures market research within agricultural marketing, on the one hand, and within finance, on the other hand. The research within these two disciplines may be considered complementary. Subsequently, a new research model is presented which integrates both strains of research. This model is a powerful instrument in the development of new commodity futures contracts. Finally, a future research agenda for agricultural economists is presented.
Repeated ordinal measurements: a generalised estimating equation approach

Cumulative logit and related regression models for ordered categorical data may be expressed as generalised linear models for correlated binary responses. These may be tted using the generalised estimated equation approach of Liang and Zeger (1986) and yields nearly identical results to maximum likelihood while offering further e xibility. The approach also generalises to deal with repeated ordinal measurements in the same subject, such as those commonly observed in medical cross-over experiments.
Polynomial Root Nding over Local Rings and Application to Error Correcting Codes *

This article is devoted to algorithms for computing all the roots of a univariate polynomial with coeecients in a complete commuta-tive Noetherian unramiied regular local domain, which are given to a xed common nite precision. We study the cost of our algorithms, dis-*. cuss their practical performances, and apply our results to the Guruswami and Sudan list decoding algorithm over Galois rings.
Building a Service-Oriented Ontology for Wireless Sensor Networks

Wireless sensor networks (WSNs) provide various environment data in the real-world, and also WSNss middleware is able to offer field data in real-time by user queries. For materialization of the future ubiquitous computing which enables networking with things at anytime, anywhere and any-devices, WSNs occupy the important position with RFID technologies, and it has evolved and advanced currently. This paper proposes a service-oriented sensor ontology which enables service-oriented services in future ubiquitous computing. Taking reuse of ontology into consideration, ServiceProperty, LocationProperty and PhysicalProperty classes were derived from Geography Markup Language (GML), Sensor Web Enablement(SWE), SensorML and Suggested Upper Merged Ontology(SUMO) and OntoSensor ontology, and its properties and constraints were also defined newly as service-oriented service. We presented the validation and consistency check of the proposed ontology using Protege 3.3. 1 and RACER 1.9. 0, respectively, and indicated the results of service query which used the SPARQL query language.
GOLDEN 2-LIKE Transcription Factors of Plants

Golden2-like (GLK) transcription factors are members of the GARP family of Myb transcription factors with an established relationship to chloroplast development in the plant kingdom. In the last century, Golden2 was proposed as a second golden producing factor and identified as controlling cellular differentiation in maize leaves. Then, GLKs were also found to play roles in disease defense and their function is conserved in regulating chloroplast development. Recently, research on GLKs has rapidly increased and shown that GLKs control chloroplast development in green and non-green tissues. Moreover, links between phytohormones and GLKs were verified. In this mini-review, we summarize the history, conservation, function, potential targets and degradation of GLKs.
Bistatic Sensing with Reflected GPS Signals Observed With a Digital Beam-Steered Antenna Array

Reflected GPS signals have applications for remote sensing including: earth mapping, ocean surface mapping, terrain modeling and digital mapping through application of bistatic signal processing techniques. Previous research in such uses of reflected GPS has been limited by the weak signal power of these bistatic GPS signal returns. This paper describes the design of a Digital Beam-Steered antenna array, which is used to increase the Signal/Noise ratio of the GPS bistatic signal returns to allow sensing of both specular and diffuse GPS signals. Flight test data is presented to demonstrate the performance improvements possible using Digital-BeamSteering for improved GPS bistatic signal processing and remote sensing.
Dynamic modules in higher-order languages

Providing programmers the ability to construct meaningful abstractions to help manage complexity is a serious language design issue. Many languages define a module system that can be used to specify distinct namespaces, and build user-defined data abstractions; however, few languages support dynamic modules, i.e., modules which are true first-class objects. We define a module semantics for a dialect of Scheme called Rascal. Modules are defined in terms of reified environments, and are first-class objects which may be dynamically created, freely assigned, used as arguments to procedures, etc. If defined naively, however, implementing modules using environments can entail the capture of unwanted bindings, leading to potentially severe violations of lexical abstraction and locality. We address these concerns by giving users great flexibility to manipulate environments, and to constrain the extent and scope of the environment reification process. We argue that the techniques and operators developed define a cohesive and semantically sound basis for building large-scale modular systems in dynamically-typed higher-order languages. <<ETX>>
Effect of Using Different Propagations on Performance of OLSR and DSDV Routing Protocols

The performance of Ad hoc routing protocol always has been measured by using free-space model and Two-ray ground model. But these two models are very simple and can't represent real world propagation, because they ignored the effect of obstacles in their environment representation. So the most real models is shadowing propagation model which has taken all these factors in account. This paper explains the effect of using two types of propagation models which are: Two Ray Ground model and shadowing model for two important protocols such as Destination Sequenced Distance Vector (DSDV) and Optimized Link Status Routing (OLSR), which are considered a proactive and Table Driven routing protocols and then different performance metrics has been measured. The simulations results have shown that the type of the propagation model has great impact on routing protocol, and it has effected severely on its performance.
A novel face recognition method based on Principal Component Analysis and Kernel Partial Least Squares

The automatic recognition of human face presents a significant challenge to the pattern recognition research community recently. As a traditional method for face recognition, principal component analysis (PCA) may neglect differentia. Since kernel partial least squares (KPLS) creates orthogonal score vectors by using the existing correlations and keeps most of the variance between different classes, it can compensate for the defects of PCA. This paper proposes a novel feature extraction method using PCA and KPLS and classification using support vector machine (SVM). The experimental results based on ORL and Yale face database prove that the proposed method has excellent classification performance.
Handling Missing Data Problems with Sampling Methods

Missing data cases are a problem in all types of statistical analyses and arise in almost all application domains. Several schemes have been studied in this paper to overcome the drawbacks produced by missing values in data mining tasks, one of the most well known is based on pre processing, formerly known as imputation. In this work, we propose a new multiple imputation approach based on sampling techniques to handle missing values problems, in order to improving the quality and efficiency of data mining process. The proposed method is favourably compared with some imputation techniques and outperforms the existing approaches using an experimental benchmark on a large scale, waveform dataset taken from machine learning repository and different rate of missing values (till 95%).