Miracle-dz/UniFAR-FTUs huggingface dataset:
Can language help in the characterization of user behavior? Feature engineering experiments with Word

Among the many signiﬁcant advances in the area of deep learning, the Natural Language Processing (NLP) space holds a special place. The availability of very large datasets along with the existence of powerful computing environments have created a fascinating environment for researchers. One of the algorithms recently developed is Word2Vec, which enables the creation of embeddings (low-dimensional, meaningful representations of language that can be used for machine learning tasks such as prediction or classiﬁcation). In this study, we experiment with Word2Vec and apply it to a different domain, i.e., representation of user behavior in information systems. We demonstrate how feature engineering tasks for user behavior characterization can be enriched by the use of NLP concepts.
Charles Darwin University Does the classification of intangibles matter? An equivalence testing Abeysekera, Indra

Many studies confirm that intangibles have future economic benefits included in them. This study examined whether analysts consider intangibles to be similar in economic value, regardless of the accounting treatment assigned to them. It conducted four experiments by providing 26 analysts with future earnings potentials, and asking them to forecast stock prices for three companies over three firms’ continuous years. One firm had an internally produced brand, the second company had a bought brand, and the third firm had an internally produced brand and bought brands. These three firms were used in four forecasting environments designed for this study. Each forecasting environment constituted an experiment. Each forecasting environment differed, with capital market information specific to each firm. Provided with this information, the analysts forecast stock prices for the three firms in each of the four experiments. Comparing the forecast stock prices, the study found that the two brand classes had similar influence on analysts’ stock pricing forecasts, to infer them as equivalent in economic value, in each of the four forecasting environments.
Attention mechanism for recommender systems

Sparseness of user item rating data affects the quality of recommender systems. To solve this problem, many approaches have been proposed. They added supplemental information to increase the accuracy. We propose a recommendation model namely attention matrix factorization (AMF) that integrates attention mechanism of the both item reviews document and item genre information into probabilistic matrix factorization (PMF). Consequently, AMF attends features which are mentioned in item reviews document and further increases the rating prediction accuracy by adding item genre information. Our experiments on the Movielens and Amazon instant video datasets show that AMF outperforms the previous traditional recommendation systems. This reveals that our model can capture subtle features of item reviews although the rating data is sparse.
Opleiding Informatica

An algorithm can only be computed as fast as the hardware will allow, but how do we make sure the hardware is used to the fullest possible extent? Matrix multiplication is a frequently used algorithm that can be improved by blocking. This thesis will try to identify the best blocking size for the matrix multiplication blocking algorithm on two different architectures and on various matrices. A number of blocking sizes will be tested, some derived from the cache size, which is determined at run-time by the program, others will be static values set from the start. The data collected from these tests will be used to determine the best blocking size for the local caches, and the best blocking size for the shared caches of both architectures. This outcome will be tested to see if it holds across different sizes and shapes of matrices. Lastly, it will be determined if a pattern can be found throughout the different architectures and the different matrices, so that a rule can be determined for calculating the best blocking size from the cache size.
Customer choice of reliability in spinning reserve procurement and cost allocation using well-being analysis

A novel pool-based market-clearing algorithm for spinning reserve (SR) procurement and the cost allocation associated with provision of spinning reserve among customers (DisCos) is developed in this paper. Rational buyer market model is used to clear energy and spinning reserve markets in the proposed algorithm. This market model gives DisCos the opportunity to declare their own energy requirement together with their desired reliability levels to the ISO and also they can participate in the SR market as a interruptible load. The DisCos’ desired reliability levels are selected from a hybrid deterministic/probabilistic framework designated as the system well-being model. Using the demand of each DisCo and its associated desired reliability level, the overall desired system reliability level is determined. The market operator then purchases spinning reserve commodity from the associated market such that the overall desired system reliability level is satisfied. A methodology is developed in this paper to fairly allocate the cost associated with providing spinning reserve among DisCos based on their demands and desired reliability levels. An algorithm is also presented in this paper for implementing the proposed approach. The effectiveness of the proposed technique is examined using the IEEE-RTS. © 2009 Elsevier B.V. All rights reserved.
Performance Evaluation of FPGA Soft Cores Configurations Case of Xilinx MicroBlaze

— Field Programmable Gate Array (FPGAs) present an attractive choice for implementing embedded systems due to their fast processing speed, their intrinsic parallelism, their rising integration scale and their lower cost solution. The increasing configurable logic capacities of FPGA have enabled designers to handle Microprocessors (MP) soft-cores onto FPGA products. Evaluating the performance of these cores presents the great dial of embedded designers to face up the various problems related to the selection of the efficient FPGA soft-core configuration, against a specific software application. The purpose of this paper was to evaluate the effect of the Xilinx MicroBlaze soft-core configuration on the execution time and the FPGA area consumption using two complementary benchmarks.
Daily Energy Expenditure in Free-ranging Gopher Tortoises (Gopherus Polyphemus)

Abstract Studies of ecological energetics in chelonians are rare. Here, we report the first measurements of daily energy expenditure (DEE) and water influx rates (WIRs) in free-ranging adult Gopher Tortoises (Gopherus polyphemus). We used the doubly labeled water (DLW) method to measure DEE in six adult tortoises during the non-breeding season in south-central Mississippi, USA. Tortoise DEE ranged from 76.7–187.5 kJ/day and WIR ranged from 30.6–93.1 ml H2O/day. Daily energy expenditure did not differ between the sexes, but DEE was positively related to body mass. Water influx rates varied with the interaction of sex and body mass. We used a log/log regression model to assess the allometric relationship between DEE and body mass for Gopher Tortoises, Desert Tortoises (Gopherus agassizii), and Box Turtles (Terrapene carolina), the only chelonians for which DEE has been measured. The slope of this allometric model (0.626) was less than that previously calculated for herbivorous reptiles (0.813), suggesting that chelonians may expend energy at a slower rate per unit of body mass compared to other herbivorous reptiles. We used retrospective power analyses and data from the DLW isotope analyses to develop guidelines for sample sizes and duration of measurement intervals, respectively, for larger-scale energetic studies in this species.
Web Page Segmentation for Non Visual Skimming

Web page segmentation aims to break a page into smaller blocks, in which contents with coherent semantics are kept together. Examples of tasks targeted by such a technique are ad-vertisement detection or main content extraction. In this paper, we study different segmentation strategies for the task of non visual skimming . For that purpose, we consider web page segmentation as a clustering problem of visual elements, where (1) all visual elements must be clustered, (2) a ﬁxed number of clusters must be discovered, and (3) the elements of a cluster should be visually connected. Therefore, we study three different algorithms that comply to these constraints: K -means, F-K -means, and Guided Expansion. Evaluation shows that Guided Expansion evidences statistically-relevant results in terms of compactness and separateness, and satisﬁes more logical constraints when compared to the other strategies.
Neospora caninum infection in cows: Effects on Reproductive Performance, Prevention and Control Methods

Backgraund/Aim:Fertility is the most important yield in livestock industry. However, abortion as an factor effecting the fertility and industrial economy is the most important reproductive problem. Abortions occurred due to infectious or non-infectious reasons in cows. Successful diagnosis, treatment and prevention have been provided of Brucella, Leptospira, IBR and BVD which accepted as important abortion factors in worlwide. N. caninum as a cause of abortion had a growing importance in recent years. Although there are some reports about diagnosis and prevention, efficient treatment of the disease are still unknown. This review aims to summarize the current literatures about the effects of N. caninum infection on fertility and prevention-control options in cows. Conclusion:The infection of N. caninum has been reported in different regions of Turkey bacause of the high population of definitive host (dogs) and high import rates of cows. Neospora caninum has negative effects on the reproductive and production performance as well. Approximately 95% of calves born from seropositive dams are clinically normal but congenitally infected. Therefore, it is considered that congenitally infected calves potentially resorvoir of infection are more hazardous than abortion problem. Because of the no effective treatment in cows, prevention against Neosporiosis is more significant.
Viabilidade econômica da utilização dos resíduos da bananicultura na alimentação de cordeiros confinados

Aimed to analyze the economic feasibility of replacing hay Cynodon spp by hay banana crop residues in diet of lambs. We used 25 Santa Ines lambs, with an average age of five months and an average initial weight of 26.5kg, distributed in a completely randomized design with five treatments (40% hay Cynodon spp. + 60% concentrate, 20% hay banana leaf and 20% of Cynodon spp. + 60% concentrate, 40% of banana leaf hay + 60% concentrate, 20% hay pseudostem of banana and 20% of Cynodon spp. + 60% concentrate, 40% hay pseudostem of banana + 60% concentrate). After 69 days of experiment the animals were slaughtered. Possession of the cost of each diet and consumption of animals was calculated economic feasibility. Treatment with 40% of banana leaf hay + 60% concentrate showed the best economic indicators, based on the highest net income, the higher rate of return to higher profitability and marketing of live animals or slaughtered. The inclusion of banana crop residues in the diet of growing lambs increases the economic viability of the activity.
Minimum Feedback for Collision-Free Scheduling in Massive Random Access

This paper considers a massive random access scenario where a small random set of k active users out of a larger number of n total potential users seek to transmit data to a base station. Specifically, we examine an approach in which the base station first determines the set of active users based on an uplink pilot phase, then broadcasts a common feedback message to all the active users for the scheduling of their subsequent data transmissions. Our main question is: What is the minimum amount of common feedback needed to schedule k users in k slots while completely avoiding collisions? Instead of a naive scheme of using k log(n) feedback bits, this paper presents upper and lower bounds to show that the minimum number of required common feedback bits scales linearly in k, plus an additive term that scales only as Θ(log log(n)). The achievability proof is based on a random coding argument. We further connect the problem of constructing a minimal length feedback code to that of finding a minimal set of complete k-partite subgraphs that form an edge covering of a k-uniform complete hypergraph with n vertices. Moreover, the problem is also equivalent to that of finding a minimal perfect hashing family, thus allowing leveraging the explicit perfect hashing code constructions for achieving collision-free massive random access.
3D Comic Rendering

: In this thesis a non-photorealistic rendering algorithm is devised for rendering a 3D scene. The algorithm follows the style of the illustrations in the La mémoire de l'eau (Water Memory) graphic novel. Implementation is carried out in Maya Non-Photorealistic Rendering Framework (MNPR), which is a framework for the 3D computer graphics software Autodesk Maya. The devised algorithm consists of edge detection using difference of Gaussians for stylized lines and color smudging. The output of the devised algorithm is compared to the source material and potential future improvements are offered.
RBF-based tensor decomposition with applications to oenology

As usually claimed, meshless methods work in any dimension and are easy to implement. However in practice, to preserve the convergence order when the dimension grows, they need a huge number of sampling points and both computational costs and memory turn out to be prohibitive. Moreover, when a large number of points is involved, the usual instability of the Radial Basis Function (RBF) approximants becomes evident. To partially overcome this drawback, we propose to apply tensor decomposition methods . This, together with rational RBFs, allows us to obtain efﬁcient interpolation schemes for high dimensions. The effectiveness of our approach is also veriﬁed by an application to oenology.
Is Terrorism an Effective Way to Attain Political Goals?

An oft-made claim is that terrorism is an effective strategy to achieve political objectives. The aim of this essay is to examine this claim and gauge whether terrorism is an effective way to achieve political goals. The essay proceeds in five sections. The first section defines terrorism and explains what measurement of effectiveness is used in this essay. Alternative definitions and measurements will be highlighted so as to underscore the appropriate and limited applicability of this essay’s findings. The second section presents prominent explanations for why terrorism is effective and the evidence to support this position. While the hypotheses are lucid and coherent, there is limited evidence to back them up. The third section explains how terrorism is ineffective and presents evidence to support this position. The hypotheses are robust and backed up by several quantitative studies. The fourth section, building on the previous two, presents possible explanations for why terrorists persist, even though terrorism is ineffective at accomplishing political goals. The concluding section summarizes the major findings and presents possible implications.
A Hyphomycete Fungus, Paecilomyces lilacinus, Associated with Wasting Disease in Two Species of Tilapia from Puerto Rico

Abstract The hyphomycete Paecilomyces lilacinus was isolated from internal tissue samples of a hatchery-raised blue tilapia Tilapia aurea and three of nine feral Mozambique tilapias T. mossambica suffering from tilapia wasting disease in Puerto Rico. Gross cultural and microscopical features of this fungus closely resemble those of P. farinosis and P. marquandii, both of which have been previously isolated from fish tissues. They also resemble features of P. fumoso-roseus, a species that has been isolated from a captive tortoise. However, the species from tilapia can be distinguished from these other species of Paecilomyces by its production of a brown exudate on Czapek yeast agar (CYA), its deep brown reverse coloration on CYA and Blakeskee malt extract agar (MEA), and its longer, more slender, solitary phialides. It can be further differentiated from these species by growth at 37°C, which is absent in the other three species. Externally, infected fish were emaciated and had sunken eyes and relatively la.
Thesis Report

As part of the ongoing research on balance assistance at the Delft Biorobotics Lab, the goal of this project was to analyse the relevance of optimising the control action to each individual user. In order to explore the feasibility of tuning balance assistance based on task performance as well as controller assistance, an experimental study was conducted on the optimisation of lateral balance assistance during slackline walking. The task performance was quantified as the distance walked on the slackline. The balance assistance was provided by the RYSEN– an active Bodyweight Support (BWS) system used in gait training– in the form of lateral damping. The damping value was tuned over successive trials to optimise the trade-off between maximising the distance walked by the participants before loss of balance and minimising the lateral impulses applied by the RYSEN during each trial. The Covariance Matrix Adaptation Evolution Strategy (CMAES) was used for the automated optimisation of the lateral damping assistance. The performance of the CMAES algorithm was compared to participant performance in optimising the damping based on the same cost measure. Using a final sample size of 15 healthy participants, comparisons were made between costs for trials conducted with Zero Damping (ZD), the optimal damping estimate returned by the algorithm (Da) and the optimal damping estimate selected by the participants (Dh), with the expectation that lower trial costs would be returned by the optimal damping estimates. No significant difference was found among the median cost measures of the three conditions (p = 0.24, Friedman’s ANOVA). Significant differences were found between the corresponding distance measures (p = 0.002, Friedman’s ANOVA), with significantly longer distances walked in Da and Dh trials compared to ZD trials (p = 0.003 and p = 0.005 respectively), but no significant differences between the measures for Da and Dh trials (p = 0.61). Analysis of the primary cost measures based on Grid Search (GS) trials indicated a shallow cost landscape with high variability. Post-hoc optimisation simulations were run using CMAES and Bayesian optimisation upon individual participant grid search data. Results indicated the possibility of better performance upon increasing the number of candidates sampled per generation and the initial step size used in the algorithm, using an alternative cost function with a quadratic distance cost component, or by using Bayesian optimisation for a comparable number of trial iterations.
Adaptive Multiscale Weighted Permutation Entropy for Rolling Bearing Fault Diagnosis

Fault diagnosis of rolling bearing is of great importance to ensure high reliability and safety in the industrial machinery system. Entropy measures are useful non-linear indicators for time series complexity analysis and have been widely applied in bearing fault diagnosis in the past decade. In this paper, an improved entropy measure is proposed, named Adaptive Multiscale Weighted Permutation Entropy (AMWPE). Then, a new rolling bearing fault diagnosis method is developed based on the AMWPE and multi-class SVM. For comparison, an experimental bearing dataset is analyzed using the AMWPE and conventional entropy measures, and then multi-class SVM is adopted for fault type classification. Further, the robustness of different entropy measures against noise is studied by analyzing noisy signals with various Signal-to-Noise Ratios (SNRs). The experimental results have demonstrated the effectiveness of the proposed method in bearing fault diagnosis under different fault types, severity degrees, and SNR levels.
Utilization of histories by country in question-answering system to solve world history essay type questions

We propose a query expansion method which uses the book of histories by country as a knowledge source for the question-answering system about world history complex essay type questions from the University of Tokyo ’ s entrance examination. As the result of the ex-periment, the recall increased distinctly but the precision decreased instead. Therefore, there was an improvement from the viewpoint of summarization’s preprocessing.
Multi-χ: Identifying Multiple Authors from Source Code Files

Abstract Most authorship identification schemes assume that code samples are written by a single author. However, real software projects are typically the result of a team effort, making it essential to consider a finegrained multi-author identification in a single code sample, which we address with Multi-χ. Multi-χ leverages a deep learning-based approach for multi-author identification in source code, is lightweight, uses a compact representation for efficiency, and does not require any code parsing, syntax tree extraction, nor feature selection. In Multi-χ, code samples are divided into small segments, which are then represented as a sequence of n-dimensional term representations. The sequence is fed into an RNN-based verification model to assist a segment integration process which integrates positively verified segments, i.e., integrates segments that have a high probability of being written by one author. Finally, the resulting segments from the integration process are represented using word2vec or TF-IDF and fed into the identification model. We evaluate Multi-χ with several Github projects (Caffe, Facebook’s Folly, Tensor-Flow, etc.) and show remarkable accuracy. For example, Multi-χ achieves an authorship example-based accuracy (A-EBA) of 86.41% and per-segment authorship identification of 93.18% for identifying 562 programmers. We examine the performance against multiple dimensions and design choices, and demonstrate its effectiveness.
A corpus-based investigation of collexemes for active-passive alternation in the English part of an English-Japanese parallel corpus

This study conducted a corpus-based investigation of collexemes for active-passive alternation found in the English part of an English-Japanese parallel corpus as an attempt to use them as metrics for distinguishing native English and non-native English. The results show that some verbs in the data are used more often in the active voice than the passive voice, and vice versa, and the differences are statistically significant. However, these verbs are not the same as those found in a previous study. This fact supports the claim that activepassive alternation constitutes a lexico-semantic phenomenon that is sensitive to various factors, such as differences in genres and type of the authors of the text.