Miracle-dz/UniFAR-FTUs huggingface dataset:
Your Opinions Let us Know: Mining Social Network Sites to Evolve Software Product Lines

Software product lines (SPLs) are complex software systems by nature due to their common reference architecture and interdependencies. Therefore, any form of evolution can lead to a more complex situation than a single system. On the other hand, software product lines are developed keeping long-term perspectives in mind, which are expected to have a considerable lifespan and a long-term investment. SPL development organizations need to consider software evolution in a systematic way due to their complexity and size. Addressing new user requirements over time is one of the most crucial factors in the successful implementation SPL. Thus, the addition of new requirements or the rapid context change is common in SPL products. To cope with rapid change several researchers have discussed the evolution of software product lines. However, for the evolution of an SPL, the literature did not present a systematic process that would define activities in such a way that would lead to the rapid evolution of software. Our study aims to provide a requirements-driven process that speeds up the requirements engineering process using social network sites in order to achieve rapid software evolution. We used classification, topic modeling, and sentiment extraction to elicit user requirements. Lastly, we conducted a case study on the smartwatch domain to validate our proposed approach. Our results show that users’ opinions can contain useful information which can be used by software SPL organizations to evolve their products. Furthermore, our investigation results demonstrate that machine learning algorithms have the capacity to identify relevant information automatically.
Model Driven Approach to design a Secure Routing Protocol for UAV Ad Hoc Networks

UAANET (UAV Ad Hoc Network) is a wireless network that is able to organize itself without a pre-existing infrastructure. It consists of forming an ad hoc network with multiple UAVs and the Ground Control Station (GCS). In order to route data packets between nodes, a routing protocol is required. This routing protocol must not only satisfy the UAANET network requirements but also the validation requirements with a formal method to verify the routing protocol conformance. This will eventually contribute to the certification of the UAANET communication network (e.g to be compatible with the specification document DO 178C). In this paper, we propose a validation model of a secure routing ad hoc protocol for UAANET based on the well known AODV algorithm. The MDD (Model Driven Development) approach is used and provides a formal specification capabilities to ensure reusability, modularity, and conformance of the AODV implementation.
An Overlapless Incident Management Maturity Model for Multi-Framework Assessment (ITIL, COBIT, CMMI-SVC)

Aim/Purpose This research aims to develop an information technology (IT) maturity model for incident management (IM) process that merges the most known IT frameworks’ practices. Our proposal intends to help organizations overcome the current limitations of multiframework implementation by informing organizations about frameworks’ overlap before their implementation. Background By previously identifying frameworks’ overlaps it will assist organizations during the multi-framework implementation in order to save resources (human and/or financial). Methodology The research methodology used is design science research (DSR). Plus, the authors applied semi-structured interviews in seven different organizations to demonstrate and evaluate the proposal. Contribution This research adds a new and innovative artefact to the body of knowledge. Findings The proposed maturity model is seen by the practitioners as complete and useful. Plus, this research also reinforces the frameworks’ overlap issue and concludes that some organizations are unaware of their actual IM maturity level; Overlapless Incident Management Maturity Model 138 some organizations are unaware that they have implemented practices of other frameworks besides the one that was officially adopted. Recommendations for Practitioners Practitioners may use this maturity model to assess their IM maturity level before multi-framework implementation. Moreover, practitioners are also incentivized to communicate further requirements to academics regarding multiframework assessment maturity models. Recommendations for Researchers Researchers may explore and develop multi-frameworks maturity models for the remaining processes of the main IT frameworks. Impact on Society This research findings and outcomes are a step forward in the development of a unique overlapless maturity model covering the most known IT frameworks in the market thus helping organizations dealing with the increasing frameworks’ complexity and overlap. Future Research Overlapless maturity models for the remaining IT framework processes should be explored.
Revectorization‐Based Soft Shadow Mapping

In this paper, we present revectorization‐based soft shadow mapping, an algorithm that enables the rendering of visually plausible anti‐aliased soft shadows in real time. In revectorization‐based shadow mapping, shadow silhouettes are anti‐aliased and filtered on the basis of a discontinuity space. By replacing the filtering step of the theoretical framework of the percentage‐closer soft shadow algorithm by a revectorization‐based filtering algorithm, we are able to provide anti‐aliasing mainly for near contact shadows or small penumbra sizes generated from low‐resolution shadow maps. Moreover, we present a screen‐space variant of our technique that generates visually plausible soft shadows with an overhead of only ∼23% in processing time, when compared to the fastest soft shadow algorithms proposed in the literature, but that introduces shadow overestimation artefacts in the final rendering.
TREE DROUGHT STRESS DETECTION BASED ON 3D MODELLING

Abstract. Precise and detailed reconstruction of 3D plant models is an important goal in computer vision. Based on these models, important parameters can be extracted, which would be very useful for monitoring the tree health situation. This paper has firstly constructed the 3D plant model based on MC-CNN using close-range photogrammetric imagery, and then applied a leaf index based segmentation to highlight the leaves region. In the end, the 3D model of each leaf can be represented and some geometric parameters of the leaf are designed and analyzed to predict the drought status. The experiments on real close-range stereo imagery justified the performance of the proposed approach to differentiate drought and healthy leaves.
Can Skeuomorphic Design Provide a Better Online Banking User Experience for Older Adults?

With the prevalence of digital technologies and internet connectivity, combined with the reduction in footfall on high streets, banks have taken steps to move most of their customer base online. This has left many older adults behind, trying to keep up with the changes and having to learn to use sometimes complex online banking interfaces. In this work we investigate whether skeuomorphic design can create a more usable online banking system for older adults, compared to the more commonplace flat design. This work took a user-centered approach, beginning with interviews with older adults that were conducted to gather data to be used in the production of prototype user interfaces. Two prototypes were then created: a flat user interface and a skeuomorphic one. We evaluated these interfaces with 15 older adults, gathering a combination of data, including data from the System Usability Scale, observations, and interviews. Results of the experiments showed that our older users preferred the flat prototype to the skeuomorphic one, but raised some potentially useful guidelines for the design of future skeuomorphic user interfaces for older adults. A validation experiment with 17 younger adults (aged 20–25) also showed that the skeuomorphic interface was more usable for older adults than younger ones.
Short-Term Water Demand Forecast Based on Deep Neural Network:

Short-time water demand forecasting is essential for optimal control in water distribution system (WDS). The current methods (e.g., conventional artificial neural network) have limited power in practice due to the nonlinear nature of changes in water demand. In particular, 15-min time step forecasting may not be accurate when using conventional models. To tackle this problem, this paper investigates the potential of deep learning in short-term water demand forecasting, developing a gated recurrent unit network (GRUN) model to forecast water demand 15 minutes into the future and 24 hours into the future with a 15-min time step. The performance of GRUN was compared with a conventional artificial neural network (ANN) model. The results show that the deep neural network model like GRUN outperforms the ANN model for both 15 minute and 24 hour forecasts. These findings can provide more flexible and effective solutions for water demand forecasting.
Execution and authentication of function queries

We introduce a new query primitive called Function Query (FQ). An FQ operates on a set of math functions and retrieves the functions whose output with a given input satisfies a query condition (e.g., being among top-k, within a given range). While FQ finds its natural uses in querying a database of math functions, it can also be applied on a database of discrete values. We show that by interpreting the database as a set of user-defined functions, FQ can retrieve the information like existing analytic queries such as top-k query and scalar product query and even more. Our research addresses the challenges of FQ execution and authentication. The former is how to minimize the computation and storage costs in processing an FQ, whereas the latter, how to verify that the result of an FQ returned by a potentially untrustworthy server is indeed correct. Our solutions are inspired from the observations that 1) the intersections of a set of continuous functions partition their domain into a number of subdomains, and 2) in each of these subdomains, the functions can be sorted based on their output. We prove the correctness of the proposed techniques and evaluate their performance through analysis, prototyping, and experiments using both synthetic and real-world data. In all settings, our techniques exhibit excellent performance. In addition to FQ, our research has developed another query primitive called Improvement Query, which we also include in this dissertation.
Métodos para estimar razón de prevalencia en estudios de cohorte transversal

OBJETIVO: Comparar empiricamente las regresiones de Cox, log-binomial, Poisson y logistica para estimar razones de prevalencia en estudios de cohorte transversal. METODOS: Fueron utilizados datos de un estudio epidemiologico transversal (n=2.072), de base poblacional, realizado con ancianos en la ciudad de Sao Paulo (Sureste de Brasil), entre mayo de 2003 y abril de 2005. Diagnosticos de demencia, posibles casos de trastorno mental comun y autopercepcion de salud pesima fueron escogidos como resultados con prevalencia baja, intermedia y alta, respectivamente. Fueron utilizadas variables de confusion con dos o mas categorias o valores continuos. Valores de referencia para estimaciones por punto y por intervalo para las razones de prevalencia (RP) fueron obtenidos por el metodo de estratificacion de Mantel-Haenszel. Estimaciones ajustadas fueron calculadas utilizando regresiones de Cox y Poisson con varianza robusta, y regresion log-binomial. Odds ratios (OR) brutos y ajustados fueron obtenidos por la regresion logistica. RESULTADOS: Las estimaciones por punto y por intervalo obtenidas por las regresiones de Cox y Poisson fueron semejantes a la obtenida por la estratificacion de Mantel-Haenszel, independientemente de la prevalencia del resultado y de las covariables del modelo. El modelo log-binomial presento dificultad de convergencia cuando el resultado tenia prevalencia alta y habia convariable continua en el modelo. La regresion logistica produjo estimaciones por punto y por intervalo mayores de las obtenidas por los otros metodos, principalmente para los resultados con mayores prevalencia iniciales. Si se interpretaban como estimaciones de RP, los OR superestimarian las asociaciones para los resultados con prevalencia inicial baja, intermedia y alta en 13%, casi 100% y cuatro veces mas, respectivamente. CONCLUSIONES: En analisis de datos de estudios de cohorte transversal, los modelos Cox y Poisson con varianza robusta son mejores alternativas que la regresion logistica. El modelo de regresion log-binomial produjo estimaciones sin sesgo de la RP, pero puede presentar dificultad de convergencia cuando el resultado es muy frecuente y la variable de confusion es continua.
A method for double series summation

The method of summation by diagonals is shown to be a practical method for the summation of double series which can give good results. Where problems arise an elementary analysis can often be used which enables the sum to be calculated to a high degree of accuracy. The method can be extended in an obvious manner to higher dimensional series.
Characterising polymer surfaces—nanoindentation, surface force data, calorimetric microscopy

Techniques now exist that allow near-surface mechanical and thermal properties of polymers to be measured at very high depth resolution. We review the use of: nanoindentation (hardness, modulus, flow properties, profilometry); force spectroscopy (adhesion, attractive forces and their variation with separation); and scanning calorimetric microscopy (image contrast determined by spatial variation of thermal conductivity, heat capacity, or reversing/non-reversing behaviour, as a function of temperature).
Performance analysis of large‐scale MIMO system for wireless backhaul network

In this paper, we present a performance analysis of large‐scale multi‐input multi‐output (MIMO) systems for wireless backhaul networks. We focus on fully connected N nodes in a wireless meshed and multi‐hop network topology. We also consider a large number of antennas at both the receiver and transmitter. We investigate the transmission schemes to support fully connected N nodes for half‐duplex and full‐duplex transmission, analyze the achievable ergodic sum rate among N nodes, and propose a closed‐form expression of the achievable ergodic sum rate for each scheme. Furthermore, we present numerical evaluation results and compare the resuts with closed‐form expressions.
Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting

Graph convolutional neural networks (GCNN) have become an increasingly active field of research. It models the spatial dependencies of nodes in a graph with a pre-defined Laplacian matrix based on node distances. However, in many application scenarios, spatial dependencies change over time, and the use of fixed Laplacian matrix cannot capture the change. To track the spatial dependencies among traffic data, we propose a dynamic spatio-temporal GCNN for accurate traffic forecasting. The core of our deep learning framework is the finding of the change of Laplacian matrix with a dynamic Laplacian matrix estimator. To enable timely learning with a low complexity, we creatively incorporate tensor decomposition into the deep learning framework, where real-time traffic data are decomposed into a global component that is stable and depends on long-term temporal-spatial traffic relationship and a local component that captures the traffic fluctuations. We propose a novel design to estimate the dynamic Laplacian matrix of the graph with above two components based on our theoretical derivation, and introduce our design basis. The forecasting performance is evaluated with two realtime traffic datasets. Experiment results demonstrate that our network can achieve up to 25% accuracy improvement.
Crosstalk and scatter correction in simultaneous dual isotope SPECT imaging using four energy windows method

One of the limitations of the simultaneous dual isotope SPECT with Tc-99m and I-123 is the crosstalk of the photons from one radionuclide to the other radionuclide's photopeak, which is serious since the difference between the photopeak of Tc-99m and I-123 is small (140 keV, 159 keV). We designed a method for correcting this crosstalk effect using four energy windows, by which we could reduce the effect of scatter as well as crosstalk. We also validated our method by comparing the corrected images to the single-isotope image acquired with phantom study. After defining the energy windows for each isotope, crosstalk fractions from the photopeak of one isotope to the photopeak/scatter windows of the other isotope were determined. Using these fractions, the effect of scatter and crosstalk was compensated. Relative errors were estimated between the single and the crosstalk/scatter corrected dual isotope images. Measured crosstalk fractions did not change regardless of the activity of each isotope. Contamination of activity was reduced as a result of crosstalk correction (CC), and image contrast was improved by scatter correction (SC). Relative errors decreased further after SC on CC images. Using four energy windows method, we could obtain a more accurate result in simultaneous dual isotope SPECT.
Procedural 3D urban content generation in simulation and games

As virtual urban environment generation becomes a widespread research topic, the need to create enriched urban worlds, which group both the geometric and semantic properties has become a necessity, the purpose being to obtain interactive, adaptive and consistent world entities. This paper suggests a representational model of urban environment generation based on both geometric and semantic knowledge, the future work being to create a modelling tool of a 3D urban environment, which stores the semantic information and allows the final non expert user to acquire information about the environment before and after its creation and to explore this information in an interactive way.
On the power handling of a high power combiner for industrial, scientific, and medical applications

In this paper a 2-way broadband power combiner that can handle up to 1 kW output power is designed and fabricated. The combiner covers the frequency range of 30 to 500 MHz, which is intended for industrial, scientific, and medical (ISM) applications. The power handling of the power combiner depends on the power handling of the components that constitute the combiner. The combiner is composed of some coaxial transmission lines and a transmission line transformer. The ferrite cores, which are used to suppress the common mode current, are one of the major limiting factors, regarding the power handling of the combiner. The power combiner is implemented with some binuclear and some stacked toroids of material 61, which is extensively used for common mode current suppression in this frequency range. As real ferrites have complex permeability, some of the input power dissipates as heat in the ferrite cores. The power dissipation due to the equivalent parallel resistance of each ferrite core is calculated. The proper operation of the high power combiner is verified by simulation of the temperature rise in the ferrite cores due to heat dissipation.
Measurement of substance use during pregnancy: methodologic issues.

This paper discusses some methodologic issues in the measurement of substance use, particularly the more complex issue of measuring substance use during pregnancy. Two specific questions are addressed in this presentation: (1) Whether the questions on use result in accurate assessment of use, and (2) Whether respondents report use accurately. Some of these methodological issues are illustrated with data from our ongoing research on substance use during pregnancy and its effect on outcome.
A Comparative Analysis of High School Students’ Perceptions of Classroom Quality in Traditional Pathway and Second Career Teachers’ Classrooms

A COMPARATIVE ANALYSIS OF HIGH SCHOOL STUDENTS’ PERCEPTIONS OF CLASSROOM QUALITY IN TRADITIONAL PATHWAY AND SECOND CAREER TEACHERS’ CLASSROOMS Eric G. Barna, Ph. D. George Mason University, 2008 Dissertation Director: Dr. Gary R. Galluzzo The purpose of this study was to determine if the students of teachers who are career switchers perceive a difference in classroom quality when compared to students taught by teachers who are from a traditional pathway. Additionally, this study investigated whether career switchers report that they plan instruction differently than traditional pathway teachers. A mixed methods design was used to compare students’ perceptions of teacher quality as defined by the Student Perception of Classroom Quality (SPOCQ) (Gentry and Owen, 2004) in the classes of four pairs of high school teachers in a small and diverse suburban school district who were matched on content. Four of the teachers gained entry into the classroom through a traditional academy-based pathway, and four came through a career-switcher program. Their students were surveyed using the SPOCQ while teachers completed the Teacher Experience Survey (TES) and were interviewed using the Teacher Interview Guide (TIG). Major findings of this study indicated that students of traditional pathway teachers perceived higher levels of appeal (p = .003), challenge (p < .001), choice (p =.015) and meaningfulness (p < .001) as measured by the SPOCQ. Additionally, traditional pathway teachers reported they were less reliant on the textbook and were more likely to rate their master’s program as relevant professional development. The results of the study suggest that future studies of teacher pathways need to explore the effects of the pathway on their graduates’ classroom quality in order to ensure that the teachers who are being placed in the classroom are perceived by their students as creating effective classroom environments.