Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Finite-State Model Predictive Current Control With Zero-Sequence Current Suppression for OEW-SPMSM Drives

In order to suppress zero-sequence current (ZSC) for open-end winding surfaced permanent magnet synchronous machine (OEW-SPMSM) drives with single dc voltage source, many methods have been employed. Actual solutions imply either proportional-integral-based control or direct torque control cannot present the characteristic of fast dynamic responses and low torque ripples at the same time. Hence, finite-state model predictive current control (FS-MPCC) based on a cost function with ZSC suppression was proposed. To suppress model parameter mismatch, many previous works have proposed related strategies but few work considered zero-sequence parameter disturbances such as zero-sequence inductance, resistance, and rotor flux linkage disturbances. This article improves the ZSC prediction model based on the previous ZSC errors and zero-sequence voltage deviations, and at the same time ZSC is reduced. A comparison between the conventional FS-MPCC and the improved one is carried out in simulation and experiment to verify the effectiveness of the proposed FS-MPCC scheme.
The Waves on a Rotating Liquid Spheroid of Finite Ellipticity. [Abstract]

1. The hydrodynamical problem of finding the waves or oscillations on a gravitating mass of liquid which, when undisturbed, is rotating as if rigid with finite angular velocity, in the form of an ellipsoid or spheroid, was first successfully attacked by M. Poincare in 1885. In his important memoir, “Sur l’Equilibre d’une Masse Fluide animee dun Mouvement de Rotation,” Poincare has (§ 13) obtained the differential equations for the oscillations of rotating liquid, and shown that, by a transformation of projection, the determination of the oscillations of any particular period is reducible to finding a suitable solution of Laplace’s equation. He then applies Lame’s functions to the case of the ellipsoid, showing that the differential equations are satisfied by a series of Lame’s functions referred to a certain auxiliary ellipsoid, the boundary-conditions, however, involving ellipsoidal harmonics, referred to both the auxiliary and actual fluid ellipsoid. At the same time, Poincare’s analysis does not appear to admit of any definite conclusions being formed as to the nature and frequencies of the various periodic free waves. The present paper contains an application of Poincare’s methods to the simpler case when the fluid ellipsoid is one of revolution (Maclaurin’s spheroid). The solution is effected by the use of the ordinary tesseral or zonal harmonics applicable to the fluid spheroid and to the auxiliary spheroid required in solving the differential equation. The problem is thus freed from the difficulties attending the use of Lame’s functions, and is further simplified by the fact that each independent solution contains harmonics of only one particular degree and rank.
Evaluating Code-Switched Malay-English Speech U sing Time Delay Neural Networks

This paper presents a new baseline for Malay-English code-switched speech corpus; which is constructed using a factored form of time delay neural networks (TDNN-F), which reflected a significant relative percentage reduction of 28.07% in the word-error rate (WER), as compared to the Gaussian Mixture Model-Hidden Markov Model (GMM-HMM). The presented results also confirm the effectiveness of time delay neural networks (TDNNs) for code-switched speech
Traditional vs. Modern Project Management Methods. Theory and Practice

The Purpose: The purpose of the article is to investigate the relationship between traditional project management (TPM) and modern project management (MPM), with a special focus on agile project management (APM). Moreover, the results of the studies on the application of APM in non-IT companies are presented. Methodology/methods: Based on the literature review, the descriptions of TPM and MPM methods are given. Furthermore, the questionnaire-based survey is applied to obtain relevant knowledge on the application of APM methods in the non-IT companies. Scientific aim: The scientific goal of the article is to ascertain the prerequisites for applying the TPM and MPM methods in the organisations, with a special focus on non-IT companies. Moreover, the conducted survey shed some light into the current state of application of APM methods in non-IT companies. Findings: The TPM methods have been developed since the sixties and are suitable for application in large, long-term projects in a stable environment. The prerequisite for their application is the ability to plan, in detail, the project ex-ante, while MPM methods seem to more accurately match the client’s needs, especially if the requirements have the tendency to change frequently over time. However, the result of the study showed that the application of APM methods is very limited, even if the companies reported that they mostly operate in turbulent environments. Conclusions: The MPM methods, with a special focus on APM, are a good alternative for non-IT companies seeking new ways of managing projects in a turbulent, client-oriented environment. However, the results of the studies revealed the limited application of APM methods in non-IT companies. They outlined directions for further research that should try to answer what hampers APM application in non-IT companies. Moreover, research dedicated to select industries should be performed.
A New Visual Analysis Approach to the High Dimensional Data

With the advent of cloud computing and big data era, high-dimensional data sets are widely available in real life. Because of the increase of data dimension and complexity, it is difficult to carry out comprehensive analysis and exploration for high-dimensional data. Therefore, we propose a new visual analysis approach to high-dimensional data. Firstly, we use the principal component analysis (PCA) to reduce the dimension of the high-dimensional data. Then, we use clustering algorithm to classify the reduced dimension data, and each class is rendered independently with different color. Finally, we use the edge binding algorithm to perform a visual clustering. The curves in the same classes are converged and in different classes are separated to alleviate visual confusion. In order to analyze the visualization results better, we also provide the visual interaction technology of "brush". The experimental result shows that our approach can help users to explore the implicit feature patterns quickly and is effective for visual analysis of large-scale high-dimensional data.
PENGENALAN WAJAH MENGGUNAKAN LOCAL BINARY PATTERN (LBP) DAN SUPPORT VECTOR MACHINE (SVM)

Terdapat banyak metode yang digunakan untuk mengenali identitas seseorang, misalkan nomor unik, kartu identitas dan sandi rahasia. Kekurangan metode-metode tersebut antara lain, kartu dapat hilang, nomor unik dan sandi rahasia dapat terlupakan. Salah satu solusi untuk masalah ini adalah sistem identifikasi seseorang berdasarkan metode biometrik jenis fisiologis. Penelitian ini merancang sebuah sistem untuk mengidentifikasi wajah. Citra wajah diambil menggunakan kamera web kemudian diekstraksi cirinya dengan metode local binary pattern (LBP). Ciri wajah yang diperoleh diklasifikasi menggunakan support vector machine (SVM). Model terbaik SVM dibangun berdasarkan validasi silang grid search . Kernel linier terbaik dibentuk dengan dan parameter . Kernel radial basis function (RBF) terbaik dicapai dengan dan parameter dan . Berdasarkan pengujian terhadap keseluruhan citra wajah, akurasi kedua kernel adalah 96,0%. Pada pengujian lima ekspresi wajah dengan SVM kernel linier, akurasi 100,0% diperoleh untuk ekspresi sedih, netral dan mata tertutup. Sedangkan SVM kernel RBF menghasilkan akurasi 100,0% untuk ekspresi terkejut, netral dan mata tertutup. Hasil pengujian tersebut menunjukkan sistem pengenalan wajah yang dirancang telah berfungsi baik.
Bio Inspired Modified Internal Model Control Approach for Improved Disturbance Rejection of Piezo Micro Manipulator

Classical Internal Model Control based approach for controller design has been used in different industrial control applications as it allows good set point tracking performance, especially for processes neglecting time delay. However, in many process control applications including nonlinear piezo electric actuation (PZA), disturbance rejection plays an important role compared to set point tracking. The present research firstly proposes an optimal filter design in series with a Modified Internal Model Control (M-IMC) based Proportional -Integral-Derivative (PID) controller for better set point tracking, improved disturbance rejection with reduced controller hardware resource requirement compared to classical IMC. Two efficient swarm intelligence based evolutionary soft computational techniques viz. Particle Swarm Optimization (PSO) and Bacterial Foraging Optimization (BFO) are then exploited towards optimizing a control evaluation index based fitness function to design the M-IMC control parameters, including filter time constant. The distillation of bio inspired principles in control is seen to exhibit exciting results when the optimized parameters are utilized in the piezo plant modeled using a Dahl based second order system. The performance of the controller has been evaluated by subjecting the plant to several perturbations as well as to external disturbances. The results illustrate the efficiency of the PSO based M-IMC over other controllers.
METHOD OF DETERMINING THE PARAMETERS OF AN EQUIVALENT ASYNCHRONOUS ELECTRIC MOTOR IN REAL TIME

A calculation of the parameters of the equivalent asynchronous electric machine allows introducing the automated calculation of the static and dynamic stability of an electrical supply system in an industrial enterprise for any combination of different electric motors. It also ensures the electromagnetic compatibility in a network by means of calculations of nonsinusoidal mode in the network with proposed sources of higher harmonics. The research purpose is a method for accurate determination of the equivalent asynchronous machine parameters for the load node consisting of several groups of asynchronous electric motors of the same type. An algorithm block diagram for calculating the initial data is developed. The input data is the number of groups of the same motor type, the number of machines in each group, and a vector of the engine power ratings. The polling of the counters of each engine in all groups is performed through the use of an embedded cycle. A fragment of a substation one-line scheme which feeds an electrical industrial enterprise water circuit is given: three 800 kW asynchronous machines for each pump, three 400 kW asynchronous machines and three 250 kW asynchronous machines. The calculation results for the given example of the scheme are executed and presented in the table. The data obtained show that the actual parameters of the equivalent machine in a 6 kV load node are significantly different from the averaged data. The typical difference between the results obtained by the proposed method and the available methods is 5%, and the maximum reaches 30%. Therefore, it is expedient to use accurate data when performing calculations.
Object classification and the determination of stellar parameters with Gaia

Gaia will observe more than one billion objects brighter than V=20, including stars, asteroids, galaxies and quasars. As Gaia performs real time detection (i.e. without an input catalogue) the intrinsic properties of most of these objects will not be known a priori. An integral part of the Gaia data processing is therefore to classify everything observed. This will be based primarily on multiband photometry provided by Gaia, but should also make optimal use of the high resolution spectroscopy (for brighter stars) and the parallaxes. In addition to a broad classification, we can also determine fundamental stellar parameters, in particular effective temperature, metallicity and the line-of-sight interstellar extinction. Such information will be essential for fully exploiting the astrometric part of the Gaia catalogue for stellar population studies. However, extracting this information is a significant challenge, and will need to make use of appropriate multidimensional data analysis techniques. I outline some of the problems and the strategies being developed to tackle them.
Determinants of Mobile Wallet Intentions to Use: The Mental Cost Perspective

ABSTRACT Mobile wallet has become the predominant form of electronic commerce in many countries, and India is no exception. It is imperative to understand the behavior of users of mobile wallets as it can help service providers to attract new users and retain their existing ones. For predicting intentions to use from a mental cost perspective, this empirical study focuses on evaluating different competing models using relevant, vital constructs rooted in theories of Diffusion of Innovation, Planned Behavior, and Technology Acceptance Model and Trust. Results point to the supremacy of the Perceived Behavioral Control construct over other constructs in predicting the intentions, to use mobile wallets. Among the competing models, the best predictive model explained 50.81% of the changes in intentions to use.
Visualisasi Sistem Tata Surya Menggunakan Teknologi Augmented Reality Berbasis Android

Seiring dengan pesatnya perkembangan teknologi membuat perkembangan pula pada bidang virtual reality menjadi augmented reality . Augmented reality secara cepat berkembang di berbagai bidang termasuk dalam bidang pendidikan. Salah satu kelebihan dari augmented reality yaitu dapat diimplementasikan secara luas dalam berbagai media sebagai aplikasi mobile dalam smartphone . Makalah ini mengembangkan aplikasi dengan menggunakan teknologi augmented reality untuk visualisasi sistem tata surya. Visualisasi terbagi menjadi 4 bagian yaitu visualisasi matahari dan planet-planet, pengelompokan planet-planet, gerhana, dan benda-benda langit. Software yang digunakan diantaranya Unity 3D, Vuforia, Cinema 4D, Android SDK. Hasil pengujian bahwa aplikasi berjalan baik pada perangkat smartphone dengan RAM minimal 278MB dan kecepatan prosesor minimal 800MHz. Hasil kuesioner pengguna menunjukkan aspek desain navigasi, kualitas, dan tingkat kepuasan lebih dari 50%.
Introduction to Geometric Probability

Introduction 1. The Buffon needle problem 2. Valuation and integral 3. A discrete lattice 4. The intrinsic volumes for parallelotopes 5. The lattice of polyconvex sets 6. Invariant measures on Grassmannians 7. The intrinsic volumes for polyconvex sets 8. A characterization theorem for volume 9. Hadwiger's characterization theorem 10. Kinematic formulas for polyconvex sets 11. Polyconvex sets in the sphere References Index of symbols Index.
Effect of the orbital-overlap dependence on Meta Generalized Gradient Approximation

The dimensionless inhomogeneity parameter, $\alpha$, characterizing the extent of orbital overlap, is disentangled for the first time, by the means of separability assumption, from the other dimensionless inhomogeneity parameter, s, the reduced density gradient,in the construction of a meta generalized gradient approximation (MGGA) for the exchange functional. We show that the formation of the intershell region between the outermost core and the valence of an atom within a solid is associated with an increase of $\alpha$ and a decrease of $s$. This observation leads to a simple MGGA exchange functional, which interpolates between the single-orbital regime, where $\alpha=0$, and the slowly varying density regime, where $\alpha \approx 1$, and then extrapolates to $\alpha \to \infty$. The exchange enhancement factor penalizes the formation of the intershell region by increasing monotonically with $s$ and decreasing monotonically with $\alpha$. When combined with a variant of the Perdew-Burke-Erzerhof (PBE) GGA correlation, the resulting MGGA performs equally well for atoms, molecules, surfaces, and solids, and respects a tight Lieb-Oxford bound.
Searching for an Optimal Partition of Incomplete Data with Application in Modeling Energy Efficiency of Public Buildings

In this paper, we consider the problem of searching for an optimal partition with the most appropriate number of clusters for an incomplete data set in which several outliers might occur. Special attention is given to the application of the Least Squares distance-like function. The procedure of preparing the incomplete data set and the outlier elimination procedure are proposed such that the clustering process gives acceptable solutions. Appropriate justifications with proof are provided for these procedures. An incremental algorithm for searching for optimal partitions with 2, 3, . clusters is applied on the prepared data set. After that, by using the Davies-Bouldin and the Calinski Harabasz index the most appropriate number of clusters is determined. The whole procedure is organized as an algorithm given in the paper. In order to illustrate its applicability, the above steps are applied on the real data set of public buildings and their energy efficiency data, providing clear clusters that could be used for further modeling procedures.
Throughput Efficient AODV for Improving QoS Routing in Energy Aware Mobile Adhoc Network

Mobile Ad hoc Networks (MANETs) is a type of wireless network that is made up of mobile nodes which coordinate themselves without the help of a central coordinator. The network topology changes as nodes are mobile. One of the major challenges of MANET is limited bandwidth which tends to mitigate the Quality of Service (QoS) of the network as users are not satisfied. A variety of routing protocols has been employed aiming at improving the throughput of the network in order to meet user demands. This paper proposes the development of a throughput efficient Ad-hoc On demand Distance Vector (TE-AODV) routing protocol targeted towards improving the QoS of MANET by mitigating network overhead. In this work, all nodes are assumed to be transmitting while calculating their Instant Processing State (IPS) using the concept of knapsack problem. A threshold value for node IPS is set and any node below the set threshold value is not considered during data transmission. An improved Location Aided Routing (iLAR) is used for route search process which helped in reducing network overhead. Results from simulation showed that TE-AODV has improved the throughput of energy aware Ad-hoc On demand Distance Vector (E-AODV) routing protocol. TE-AODV improved the network throughput by 2.9% as a function of simulation time and 3.7% as a function of mobility of node over the E-AODV routing protocol.
Cloud Computing: The Next Generation Computing Model to Accelerate Innovation in Kenya

The need for innovation is becoming more imperative today for Africa and Kenya as a nation. Countries in Africa have been unable to compete in the global market due to lack of innovation in various industry sectors. A major area of Innovation is in information technology, engineering and technology. The business world globally is witnessing rapid developments in information technology that is significantly changing the way business is being done. One such technology is Cloud Computing. This paper focuses on the Cloud Computing technology and seeks to enunciate it as a potential and significant platform that can drive and accelerate innovation in Kenya within various industry sectors. The paper reviews the Cloud computing technology and current impact on global innovation, discusses the need for innovation in Kenya and readiness for the adoption of the technology. The paper concludes with Cloud Computing utilization strategies as well as innovation opportunities within Kenya. Relevance to innovation. This paper addresses the innovative computing technology of Cloud Computing. As a pervasive technology that is presently changing business processes and businesses, Cloud computing is described in general and posited as an innovative technology necessary for adoption in Kenya and the African continent as a whole. The paper shows Cloud computing as a world class technology with the potential to change the whole discipline of computing and software engineering as we know it. Adopting Cloud computing in Kenya across various industry sectors is considered a major innovative strategy for educating a new workforce, creating economic growth and rapid product and service development. Keyword. Business, Cloud, Computing, Innovation, Software
Sub-session hijacking on the web: Root causes and prevention

Since cookies act as the only proof of a user identity, web sessions are particularly vulnerable to session hijacking attacks, where the browser run by a given user sends requests associated to the identity of another user. When n > 1 cookies are used to implement a session, there might actually be n sub-sessions running at the same website, where each cookie is used to retrieve part of the state information related to the session. Sub-session hijacking breaks the ideal view of the existence of a unique user session by selectively hijacking m sub-sessions, with m < n. This may reduce the security of the session to the security of its weakest sub-session. In this paper, we take a systematic look at the root causes of sub-session hijacking attacks and we introduce sub-session linking as a possible defense mechanism. Out of two flavors of sub-session linking desirable for security, which we call intra-scope and inter-scope sub-session linking respectively, only the former is relatively smooth to implement. Luckily, we also identify programming practices to void the need for inter-scope sub-session linking. We finally present Warden, a server-side proxy which automatically enforces intra-scope sub-session linking on incoming HTTP(S) requests, and we evaluate it in terms of protection, performances, backward compatibility and ease of deployment.
On the convergence analysis of the inexact linearly implicit Euler scheme for a class of SPDEs

This paper is concerned with the adaptive numerical treatment of stochastic partial differential equations. Our method of choice is Rothe's method. We use the implicit Euler scheme for the time discretization. Consequently, in each step, an elliptic equation with random right-hand side has to be solved. In practice, this cannot be performed exactly, so that efficient numerical methods are needed. Well-established adaptive wavelet or finite-element schemes, which are guaranteed to converge with optimal order, suggest themselves. We investigate how the errors corresponding to the adaptive spatial discretization propagate in time, and we show how in each time step the tolerances have to be chosen such that the resulting perturbed discretization scheme realizes the same order of convergence as the one with exact evaluations of the elliptic subproblems.
Entire functions of order l=1, with bounds on both axes

Results are proved on the existence of a not identically vanishing entire function f , of order ≤ 1, and satisfying log |f(x)| ≤ k(x), log |f(ix)| ≤ a|x|, x ∈ R, where k is a given odd function and a a positive constant. Existence is proved if k ∈ C 2 (R) with |xk '' (x)| ≤ 2aπ −1 , x ∈ R, or, for every a, if k is convex on R + , with kbounded. The second result is used to produce non-trivial translation invariant subspaces of the corresponding weighted l p (Z).