Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Blockchain-Based Software-Defined Networking: Security Challenges and Solutions

SUMMARY Software-Deﬁned Networking (SDN) enables ﬂexible deployment and innovation of new networking applications by decoupling and abstracting the control and data planes. It has radically changed the concept and way of building and managing networked systems, and reduced the barriers to entry for new players in the service markets. It is considered to be a promising solution providing the scale and versatility necessary for IoT. However, SDN may also face many challenges, i.e., the centralized control plane would be a single point of failure. With the advent of blockchain technology, blockchain-based SDN has become an emerging architecture for securing a distributed network environment. Motivated by this, in this work, we summarize the generic framework of blockchain-based SDN, discuss security challenges and relevant solutions, and provide insights on the future development in this ﬁeld.
3D Unsteady Convection-Diffusion-Reaction via GFEM Solver

In this paper, an important study on the application of the α family of temporal discretization is presented. For spatial discretization the Galerkin Method (GFEM) was used. With the variation of the α coefficient in temporal discretization and through one numerical applications with exact solution, it will be possible to have an initial idea on how each one of the two suggested methods behaves. It is expected that this study can be able to advance several other studies within the domain of numerical simulation of physical problems. It is important to note that for all applications we will use a mesh that is considered gross, with the purpose of presenting a method that is robust, precise and mainly computationally economic.
Regeneration scanning method for M-WFRFT communication signals

Considering its simplicity and the uniform distribution of signal energy and interference after transformation, the weighted fractional Fourier transform (WFRFT) has been gradually applied to the field of communication. With in-depth study of WFRFT, the number of weighted terms can be extended from the original four terms to any number. This is called a multi-WFRFT ( M -WFRFT). As the number of weighted terms plays an important role in the receiving system, research into an M -WFRFT reception method compatible with different weighted terms is critical. In view of the high complexity of communication systems based on M -WFRFT, in order to solve the general receiving problems of the receiver when the parameters of the transmitter are not fixed or when multiple transmitters share the same receiving system, a regenerative transformation scan method for M -WFRFT signals is established. This is accomplished by adapting to dynamic processing conditions and avoiding the problem of high complexity. In this method, the 4-WFRFT mechanism is introduced, regeneration weighting coefficients are constructed, and the regeneration order is given by combining the inherent relationship between the weighting coefficients and the order. The new method can achieve the purpose of receiving M -WFRFT signals with different number of items and different orders.
Factors Affecting User's Intention to Adopt Smart Home in Malaysia

Nowadays, the advancement of technology makes the life easier and convenience. Smart home is one of the technology provide a better life environment for the residents. The purpose of this study is to make a systematic and empirical study on the factors and model that influencing the intention to adopt smart home in Malaysia. Clear interface, consistency, attractiveness, information accuracy, information completeness, perceived security and perceived privacy used as the variables to investigate the intention to adopt the smart home. The quantitative method was used in this research. The sample size of this research is 102 respondents. The questionnaire was used for data collection. From the statistical analysis, the result verify that clear interface, consistency, attractiveness, information accuracy, perceived security and perceived privacy have positive impact on the Malaysian householder’s intention to adopt smart home. Besides that, the result from clustering analysis shows that, the younger generation or higher education respondents have higher intention to adopt smart home system. By referring this, the practitioner can refer and focus on those variables to develop the smart home that suitable for Malaysian.
Self-Triggered Pinning Consensus Control for Multi-Agent Systems

SUMMARY Pinning control of multi-agent systems is a method that the external control input is added to some agents (pinning nodes), e.g., leaders. By the external control input, consensus to a certain target value and faster consensus are achieved. In this paper, we propose a new method of self-triggered predictive pinning control for the consensus problem. Self-triggered control is a method that both the control input and the next update time are calculated. Using self-triggered control, it is expected that the communication cost can be reduced. First, a new ﬁnite-time optimal control problem used in self-triggered control is formulated, and its solu-tion method is derived. Next, as an on-line algorithm, two methods, i.e., the multi-hop communication-based method and the observer-based method are proposed. Finally, numerical examples are presented.
Omnidirectional and omnifunctional connectivity analyses with a diverse species pool

Connectivity among habitat patches in both natural and disturbed landscapes needs to be accounted for in conservation planning for biodiversity maintenance. Yet methods to assess connectivity are often limited, because simulating the dispersal of many species is computationally prohibitive, and current simulations make simplifying assumptions about movement that are potentially erroneous. Here we show how these limits can be circumvented and propose a novel framework for the assessment of omnifunctional and omnidirectional connectivity in a 28000 km2 area in the Laurentian region of Québec, Canada. Our approach relies on (i) the use of Omniscape, an improved version of Circuitscape which allows omnidirectional simulations that better emulate animal movement and (ii) the synthesis of large volume of species-level dispersal simulations through a posteriori clustering of the current intensity. Our analysis reveals that the movement of 93 species evaluated can be clustered into three functional dispersal guilds, corresponding to mostly aquatic species, terrestrial species able to use aquatic environments, and strictly terrestrial species. These functional guilds do not share connectivity hotspots, suggesting that corridor planning would need to account for the multiplicity of dispersal strategies. Although this approach requires a large volume of computing resources, it provides richer information on which landscape features are critical to maintain or need to be regenerated for broader biodiversity maintenance goals.
Exploiting Semantic Relations for Fine-grained Entity Typing

Fine-grained entity typing results can serve as important information for entities while constructing knowledge bases. It is a challenging task due to the use of large tag sets and the requirement of understanding the context. We ﬁnd that, in some cases, existing neural ﬁne-grained entity typing models may ignore the semantic information in the context that is important for typing. To address this problem, we propose to exploit semantic relations extracted from the sentence to improve the use of context. The used semantic relations are mainly those that are between the mention and the other words or phrases in the sentence. We investigate the use of two types of semantic relations: hypernym relation, and verb-argument relation. Our approach combine the predictions made based on diﬀerent semantic relations and the predictions of a base neural model to produce the ﬁnal results. We conduct experiments on two commonly used datasets. The results show that our approach successfully improves ﬁne-grained typing performance.
A Release-Aware Bug Triaging Method Considering Developers' Bug-Fixing Loads

SUMMARY This paper proposes a release-aware bug triaging method that aims to increase the number of bugs that developers can ﬁx by the next release date during open-source software development. A variety of methods have been proposed for recommending appropriate developers for particular bug-ﬁxing tasks, but since these approaches only consider the developers’ ability to ﬁx the bug, they tend to assign many of the bugs to a small number of the project’s developers. Since projects generally have a release schedule, even excellent developers cannot ﬁx all the bugs that are assigned to them by the existing methods. The proposed method places an upper limit on the number of tasks which are assigned to each developer during a given period, in addition to considering the ability of developers. Our method regards the bug assignment problem as a multiple knapsack problem, ﬁnding the best combination of bugs and developers. The best combination is one that maximizes the e ﬃ ciency of the project, while meeting the constraint where it can only assign as many bugs as the developers can ﬁx during a given period. We conduct the case study, applying our method to bug reports from Mozilla Firefox, Eclipse Platform and GNU compiler collection (GCC). We ﬁnd that our method has the following properties: (1) it can prevent the bug-ﬁxing load from being concentrated on a small number of developers; (2) compared with the existing methods, the proposed method can assign a more appropriate amount of bugs that each developer can ﬁx by the next release date; (3) it can reduce the time taken to ﬁx bugs by 35%–41%, compared with manual bug triaging;
Energy supply per neuron is constrained by capillary density in the mouse brain

Neuronal densities vary enormously across sites within a brain. Does the density of the capillary bed accompany the presumably larger energy requirement of sites with more neurons, or with larger neurons, or is energy supply constrained by a mostly homogeneous capillary bed? Here we find evidence for the latter across various sites in the mouse brain and show that as a result, the ratio of capillary cells per neuron, and thus presumably blood and energy supply per neuron, decreases uniformly with increasing neuronal density and therefore smaller average neuronal size across sites. Additionally, we find that local capillary density is also not correlated with local synapse densities, although there is a small but significant correlation between lower neuronal density (and therefore larger neuronal size) and more synapses per neuron within the restricted range of 6,500-9,500 across cortical sites. Further, local variations in the glial/neuron ratio are also not correlated with local variations in number of synapses per neuron or local synaptic densities. These findings suggest that it is not that larger neurons, neurons with more synapses, or even sites with more synapses demand more energy, but simply that larger (and thus fewer) neurons have more energy available per cell, and to its synapses as a whole, than smaller (and thus more numerous) neurons due to competition for limited resources supplied by a capillary bed of fairly homogeneous density throughout the brain. Significance Statement The brain is an expensive organ and at rest already uses nearly as much energy as during sensory activation. To ultimately determine whether the high energy cost of the brain is driven by an unusually high energy demand by neurons or constrained by capillary density in the organ, we examine whether sites in the mouse brain with more neurons, larger neurons, or more synapses have more capillary supply, and find instead that capillary density is mostly homogeneous across brain structures. We propose that neurons are constrained to using what energy is available, with little evidence for adjustments according to local demand, which explains its high risk of ischemia and vulnerability to states of compromised metabolism, including normal aging.
Feature Vector Binarization: A Quantization-Based Approach to a Secure Biometric System

In this paper, a secure biometric template protection scheme using an error correcting code (ECC) is proposed. The usage of an ECC implies that a binary representation of the biometric template is required, thus the extraction of binary strings from real-valued templates is a fundamental issue in many biometric template protection schemes. The proposed Feature Vector Binarization (FVB) relies on a quantizer that is applied to each component of the real-valued biometric template, to convert into a binary representation. The bits extracted from every component are concatenated to form a fixed-length binary string that can be processed by an error correcting code and hashed to guarantee its privacy. A palmprint verification system is implemented for testing purposes, using the UST hand image database, with promising results.
Application of Metal Additive Manufacturing in the Aerospace Sector

Metal additive manufacturing (MAM) is a technology increasingly relevant in the aerospace industry due to its recognized advantages. The possibility to manufacture complex designs allows reducing assembly time and components weight, comparatively to conventional manufacturing methods. Overall, MAM enables a more efficient performance, allied to a reduction of costs. The introduction of a new technology in any industry requires not only an evaluation of the economic efficiency of that technology when compared with traditional manufacturing methods, but also an understanding of the most influential factors on production cost. In the scope of this research, an aerospace component was manufactured in a MAM machine, and the data concerning that production was analysed through to a cost model created to understand the costs involved in a MAM production. The results of this research show that direct costs influence decreases as production volumes increase. Furthermore, regardless of the production volume, indirect costs are responsible for the majority of production costs per part, mainly due to the initial investment on the MAM machine. Finally, the analysis carried out in this reasearch shows that the use of MAM is more appropriate to low and medium volumes since the design complexity possible to achieve with MAM is difficult (or even impossible) to match using traditional methods, such as injection moulding, which is reflected on the production cost.
CDASH: a cloud-enabled program for structure solution from powder diffraction data

Synopsis A cloud-computing approach to accelerating structure determination from powder diffraction data, based on the Amazon EC2 system and the DASH software, is presented. Abstract The simulated annealing approach to crystal structure determination from powder diffraction data, as implemented in the DASH program, is readily amenable to parallelisation at the individual run level. Very large scale increases in speed of execution can be achieved by distributing individual DASH runs over a network of computers. The CDASH program delivers this by using scalable, on-demand computing clusters built on the Amazon Elastic Compute Cloud service. By way of example, a 360 vCPU cluster returned the crystal structure of racemic ornidazole (Zʹ=3, 30 degrees of freedom) ca. 40 times faster than a typical modern quad-core desktop CPU. Whilst used here specifically for DASH , this approach is of general applicability to other packages that are amenable to coarse-grained parallelism strategies.
Understanding the Hip Joint: a Morphological Study of the Articular Surfaces in Asymptomatic and Pathologic Conditions

Understanding the morphological and functional features characterizing a normal hip joint is critical and necessary for a more comprehensive definition of pathological presentations, such as femoroacetabular impingement (FAI) and hip dysplasia, and improved designs of prosthetic devices. MacConaill introduced the notion, based on anatomical observations, that the articular surfaces of synovial joints are better represented by ovoidal shapes, in comparison with the spherical one, which is very well-established within the orthopaedic community. This work aims at testing MacConaill’s hypothesis by using a surface fitting framework to assess the goodness-of-fit of a set of implicitly represented sphere-like shapes to the articular surfaces of the femoral head and the acetabular cavity, whose anatomical and geometrical raw data were obtained from computed tomography (CT) and magnetic resonance imaging (MRI) data sets. The framework involved image segmentation with active contour methods, mesh smoothing and decimation, and surface fitting to point clouds performed with genetic algorithms. The study included two stages: (i) application of the surface fitting procedure on an asymptomatic population of 11 subjects, using 10 canonical shapes; and (ii) comparison of asymptomatic and pathological hips, by fitting a sphere, an ellipsoid, and a tapered ellipsoid to three populations (asymptomatic, FAI and dysplasia) of 20 subjects each. The statistical analysis of the surface fitting errors for both studies revealed the superior approximation of non-spherical shapes, namely ovoids and tapered ellipsoids, to both articular joint surfaces, especially in the pathological cases.
Cervix human papilloma virus positivity: Does it cause sexual dysfunction?

Objective: To investigate whether testing positive for human papilloma virus (HPV) in cervical screening has an impact on female sexual functioning. Materials and Methods: This study was designed as a single-center, prospective, descriptive-cross-sectional study and 300 women who received HPV testing in our hospital [HPV-positive (n=187) or HPV-negative (n=113)]. The Arizona Sexual Experiences (ASEX) scale and Female Sexual Functioning index (FSFI) were administered to study participants during face-to-face interviews. Results: No significant differences were found between women who were HPV-positive and HPV-negative in sexual functions as assessed using the ASEX and FSFI scales (p=0.343 and p=0.604, respectively). In addition, the analyses addressing whether sexual functioning was affected by a positive test result, at diagnosis or during the follow-up (before 2 weeks, 2 weeks-1 month, 1-3 months, 3-6 months, 6 months-1 year and over 1 year) revealed no significant differences between HPV-positive and HPV-negative women in sexual functioning (p>0.05). Sexual dysfunction was less common in married women than in the ASEX scale (p=0.03), and this difference was not detected when the FSFI scale was applied. The incidence of dysfunction was more frequent in working women than in retirees (p=0.006, p=0.01). Conclusion: Educational attainment, socioeconomic status, age, employment status, and marital status were found to have statistically significant effects on sexual functioning. Sexual functioning was affected by neither HPV test results (positive/negative) nor time from diagnosis.
Concepts and Implementation of Computer-Supported Structural Organizations

Computer-supported structural organizations are providing services for many applications, such as Human Ressource Management, Project Management, Workﬂow Management, and last but the least eCom-merce in the near future. A generic operator getAgent ( ) is speciﬁed and implemented to select an agent out of a structural organization with its application-speciﬁc rule systems.
Modeling and Control of a lumped parameter flexible beam with Port Hamiltonian approach ?

The purpose of this paper is to show how can be derived a simple finite dimension port Hamiltonian model for a flexible beam. The Port Hamiltonian approach to this problem gives the possibility of developing a control starting from energy considerations. On this purpose, a control law will be designed on the found model by using IDA-PBC method. This work has been done looking at the possible application on a endoscope actuated with multiple electroactive polymers attached directly in different places of the beam. The lumped parameters model offers the possibility of having input/output ports in every joint between two successive element in which the beam has been discretized. In such a way, the action of actuators is easily modeled as an input force in the joints where they are actually presented.
Structural Learning of Boltzmann Machine and its Application

This study proposed a way to solve problem efficiently which is through structural learning of Boltzmann machine. This method used mixed integer quadratic programming to solve the problem. An analysis is conducted by using the ideas of the reliability and risks of units assessed using a variance-covariance matrix and the effect and expanses of replacement are determined. In this study, the mean-variance analysis is formulated as a mathematical program with two objectives: (1) minimization of risk and (2) maximization of expected return. Lastly, the effectiveness of proposed method is illustrated by way of a life cycle management example. The result of this suggested method was demonstrated at the end. By using this method, more effective selection of results is gathered. Thus, this prove that the effectiveness of the decision making process can be reinforced.
Recalcitrant betas: Intraday variation in the cross‐sectional dispersion of systematic risk

We study the temporal behavior of the cross-sectional distribution of assets’ market exposure, or betas, using a large panel of high-frequency returns. The asymptotic setup has the sampling frequency of returns increasing to infinity, while the time span of the data remains fixed, and the cross-sectional dimension of the panel is either fixed or increasing. We derive functional limit results for the cross-sectional distribution of betas evolving over time. We demonstrate, for constituents of the S&P 500 market index, that the dispersion in betas is elevated at the market open and gradually declines over the trading day. This intraday pattern varies significantly over time and reacts to information shocks such as clustered earning announcements and releases of macroeconomic news. We find that earnings news increase beta dispersion while FOMC announcements have the opposite effect on market betas.
Autonomous system for track athletics guidance for the visual impaired

Currently, visually impaired people still suffer from the lack of adequate pedestrian guidance systems suited to their needs and without which they are not able to have a good quality of life, something that must be addressed urgently. Visually impaired athletes, more specifically, are not able to train and practise their runs due to increasing costs regarding guide athletes, infrastructures and needed equipment. In this work, available positioning/navigation techniques and guidance systems were evaluated regarding a set of requirements demanded for the specified target audience. Although the solutions mentioned have some key aspects developed, there is no system that gathers all the required functionalities. It is with that motive that it is proposed the TSAG system, a navigation guidance system for visually impaired athletes, that provides vibratory and audio feedback to an athlete during his competition, while using Pedestrian Dead Reckoning (PDR) techniques to track its position and correct it if it deviates from the course. Keywords— accelerometer, Android, Dead Reckoning (DR), gait, Global Positioning System (GPS), gyroscope, kinetic