Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel clustering algorithm by deterministic annealing

Partition clustering and hierarchical clustering are two fundamental clustering methods. Partition clustering is often implemented as an optimization problem, but traditional partition clustering algorithms have difficulty achieving global optimization. This paper describes a parallel partition clustering algorithm that uses deterministic annealing to avoid the disadvantages of traditional methods and to improve performance. The algorithm was then implemented in parallel on cluster of workstations (COW). The optimal processor number and the speedup ratio were evaluated. Theoretical analysis and the simulation results show that COW is a good choice for the parallel clustering algorithm with deterministic annealing. High speedup ratios are achieved for clustering problems with large clusters with relatively low communication to computation ratios.
Stochastic modelling and prediction of call data from TrønderTaxi.

In this report we examine a data set from TrønderTaxi, which contains information about all phone calls their call center received from 1 March 2014 to 31 January 2016. We model the number of phone calls received per 30 minute time interval using two different models. The first model is a seasonal autoregressive integrated moving average model, or SARIMA model. The second model is a naive model, which treats all of the weeks of the data set as independent and identically distributed. We use both the SARIMA and naive models to make predictions of both one and two weeks into the future. The results show that the SARIMA model appears to make slightly better predictions for one week into the future, while the naive model is better for more distant predictions.
Density Functional Theory Study of the Energy Landscapes for the Channeling of Li in LiFePO4

By adopting the first-principles calculation based on density functional theory (DFT), the diffuse pattern and the energy landscape for Li transfer in the LiFePO4 are investigated for the three different directions. The results of relaxed structure are compared with those of the non-relaxed structure and the energy barriers are significantly reduced and the effect of structure relaxation is most obvious for Li displacement along [100] direction. Energy barrier for the Li diffusion along [010] direction is lower than the other two direction in both calculation which indicates that the Li diffusion in LiFePO4 is one dimensional.
Fusion de Données Multicapteurs pour un Système de Télésurveillance Médicale de Personnes à Domicile

Le developpement des systemes de telesurveillance medicale a domicile est fondamental face au vieillissement de la population et aux capacites limitees d admission dans les hopitaux et centres specialises. Ce travail de these concerne particulierement la conception d un assistant intelligent pour l analyse des donnees heterogenes collectees par des capteurs au domicile afin de detecter, voire prevenir, l occurrence de situations inquietantes. Il s agit de concevoir un systeme d apprentissage des habitudes de vie d une personne, tout ecart par rapport a ce profil comportemental etant considere comme critique. L etude proposee concerne d une part la conception d un processus de simulation pour la generation de grandes quantites de donnees appropriees au contexte experimental. D autre part, une methode generique pour l extraction non supervisee de motifs dans des sequences temporelles multidimensionnelles et heterogenes est proposee puis experimentee dans le contexte de l identification des comportements recurrents d une personne dans ses activites quotidiennes. On evalue en particulier les indices de sensibilite (tolerance aux modifications normales de comportement) et de specificite (rejet des modifications inquietantes) du systeme. L application du systeme d apprentissage aux sequences generees par la simulation permet egalement de verifier l extraction possible de comportements recurrents interpretes a posteriori en terme de la realisation d activites de la vie quotidienne.
Effects of thermal cycling on phenylethynyl-terminated PMDA-type asymmetric polyimide composites

The effects of thermal cycling on a polymerized monomeric reactant (PMR) type polyimide (TriA X) reinforced with carbon fibers were investigated. Composite specimens were subjected to 2000 thermal cycles between −54°C and 232°C. At 400-cycle intervals, laminates were inspected for microcracks, and glass transition temperature (T g) and short-beam shear (SBS) strength were measured. The composites did not exhibit microcracks after thermal cycling, although after 2000 thermal cycles, mechanical properties of the matrix declined slightly. The matrix degradation decreased the resistance to microcracking upon further loading. No effects of thermal oxidative aging were observed from thermal cycling, and thermally driven fatigue and creep were identified as the primary and secondary factors inducing mechanical degradation of the matrix. T g of the composites exhibited no change after 2000 cycles, while the SBS strength decreased slightly (3–9%). The results highlight the potential for use of TriA X composites as long-term structural components in high-temperature service environments.
Electromagnetic fault injection using transient pulse injections:a comparison of EM-FI and optical-FI on smart cards

An analysis of the effectiveness of fault injection attacks on smart cards using the transient pulse variety of electromagnetic fault injections. This thesis addresses the best testing method to use when using EM-FI technology and describes the types of effects that may be obtained. It also compares the effectiveness of EM-FI in contrast to other methods, such as laser-based optical fault injection, along with the advantages and disadvantages of both. It helps to distinguish in which situations EM-FI is a more viable or better option than optical FI techniques and gives insights into whether common fault injection protection mechanisms and countermeasures are effective against EM-FI or if additional security testing and new EM-FI specific countermeasures and certifications are required. Electromagnetic Fault Injection using Transient Pulse Injections iii
Physical design algorithms for asynchronous circuits

Asynchronous designs have been demonstrated to be able to achieve both higher performance and lower power compared with their synchronous counterparts [50] [51] [19]. It provides a very promising solution to the emerging challenges in advanced technology. However, due to the lack of proper EDA tool support, the design cycle for asynchronous circuits is much longer compared with the one for synchronous circuits. Thus, even with many advantages, asynchronous circuits are still not the mainstream in the industry. In this thesis, we provides several algorithms to resolve the emerging issues for the physical design of asynchronous circuits. Our proposed algorithms optimize asynchronous circuits using placement, gate sizing, repeater insertion and pipeline buffer insertion techniques. An incremental maximum cycle ratio algorithm is also proposed to speed up the timing analysis of asynchronous circuits.
Perovskite Solar Cells Yielding Reproducible Photovoltage of 1.20 V

High photovoltages and power conversion efficiencies of perovskite solar cells (PSCs) can be realized by controlling the undesired nonradiative charge carrier recombination. Here, we introduce a judicious amount of guanidinium iodide into mixed-cation and mixed-halide perovskite films to suppress the parasitic charge carrier recombination, which enabled the fabrication of >20% efficient and operationally stable PSCs yielding reproducible photovoltage as high as 1.20 V. By introducing guanidinium iodide into the perovskite precursor solution, the bandgap of the resulting absorber material changed minimally; however, the nonradiative recombination diminished considerably as revealed by time-resolved photoluminescence and electroluminescence studies. Furthermore, using capacitance-frequency measurements, we were able to correlate the hysteresis features exhibited by the PSCs with interfacial charge accumulation. This study opens up a path to realize new record efficiencies for PSCs based on guanidinium iodide doped perovskite films.
An Investigation of Selection Constraints on Non-coding RNAs and Reliability of Alignments

NcRNAs are transcripts which do not code for protein but rather function as RNA in catalytic, regulatory, or structural roles in the cell. NcRNAs are involved in several biological processes, including gene regulation and X-chromosome inactivation in eutherian mammals. Previous attempts at defining RNA selection compared rates of evolution between paired and unpaired bases. This proved mostly inconclusive and a broad trend valid for ncRNA families was not identified. I propose a robust approach focusing only on paired bases. By analogy to the different properties of codon positions, I use a well-developed energy model for RNA structure to classify stem positions into structural classes, and argue that they are under different selective constraints. The hypothesis is validated and confirmed on real and simulated data sets, except for miRNA where there exists plausible biological explanations. An important finding is that class labelling is a better model of ncRNA evolution than the tradition of treating stem positions equally. As well as providing a better understanding of RNA evolution, the evolutionary footprint identified can easily be incorporated into gene finders to improve their specificity. Underlying most if not all of comparative genomics, including the ncRNA work outlined in this thesis, is the quality of sequence alignment. Despite great efforts dating back to over three decades ago, alignments produced by existing algorithms still show considerable disagreement. Through this work, I argue that these differences do not result from inaccurate evolutionary modelling or sub-optimal choices of parameters, but instead that they simply reflect uncertainties resulting from the limited information available in extant sequences, from which different algorithms infer distinct but equally plausible homologies. To the extent that this is true, quantifying this unavoidable uncertainty, rather than optimising evolutionary models underpinning aligners, will certainly help experimentalists assess which regions in alignments are trustworthy.
Energy-Based Magnetic Hysteresis Models - Theoretical Development and Finite Element Formulations

This work focuses on the development of a highly accurate energy-based hysteresis model for the modeling of magnetic hysteresis phenomena. The model relies on an explicit representation of the magnetic pinning effect as a dry friction-like force acting on the magnetic polarization. Unlike Preisach and Jiles-Atherton models, this model is vectorial from the beginning and derives from thermodynamic ﬁrst principles. Three approaches are considered: the ﬁrst one, called vector play model, relies on a simpliﬁcation that allows an explicit, and thus fast, update rule, while the two oth-ers, called the variational and the differential approaches, avoid this simpliﬁcation, but require a non-linear equation to be solved iteratively. The vector play model and the variational approach were already used by other researchers, whereas the differential approach introduced in this thesis, is a new, more efﬁcient, exact implementation, which combines the efﬁciency of the vector play model with the accuracy of the variational approach. The three hysteresis implementations lead to the same result for purely unidirectional or rotational excitation cases, and give a rather good approximation in all situations in-between, at least in isotropic material conditions. These hysteresis modeling approaches are incorporated into a ﬁnite-element code as a local constitutive relation with memory effect. The inclusion is investigated in de-tail for two complementary ﬁnite-element formulations, magnetic ﬁeld h or ﬂux density b conforming, the latter requiring the inversion of the vector hysteresis model, naturally driven by h , for which the Newton-Raphson method is used. Then, at the ﬁnite-element level, once again, the Newton-Raphson technique is adopted to solve the nonlinear ﬁnite-element equations, leading to the emergence of discontinuous differential reluctivity and permeability tensors, requiring a relaxation technique in the Newton-Raphson scheme. To the best of the author’s knowledge, the inclusion of an energy-based hysteresis model has never been successfully achieved in a b -conform ﬁnite-element
Temperature Driven Transformation in Dextran-Graft-PNIPAM/Embedded Silver Nanoparticle Hybrid System

During the last decade, stimuli-responsible polymers based on poly(N-isopropylacrylamide) having conformational transition in the range of physiological temperature have been discussed as novel drug delivery nanosystems. A star-like copolymer with a dextran core and grafted poly(N-isopropylacrylamide) arms (D-g-PNIPAM) was synthesized, characterized, and used as a matrix for silver sol preparation. The comparative study of the behavior of individual D-g-PNIPAM and the nanohybrid system D-g-PNIPAM/silver nanoparticles has been done in the temperature range near the lower critical solution temperature (LCST). The methods of Dynamic Light Scattering, small angle X-ray scattering, and UV-VIS absorption spectroscopy have been used. The existence of single nanoparticles and aggregated nanoparticles located in a limited polymer macromolecular volume was established. The increase of the temperature leads to slight aggregation of the silver nanoparticles at the LCST transition. Single nanoparticles do not aggregate with the temperature increase. The thermally induced collapse of end-grafted poly(N-isopropylacrylamide) chains above the LCST do not affect significantly the size characteristics of silver nanoparticles incorporated into the polymer matrix.
A consumer-based textile quality scoring model using multi-criteria decision making

In the clothing industry, the understanding of the quality is a major issue to well meet the customer needs. The dilemma that faces manufacturers is to find the balance between good quality and “overquality,” what the quality criteria are, and how to target requirements specifications. The aim of this study was to propose a multi-attribute ranking method of products. Ranking is based on an overall quality score. The quality score, here called consumer-based quality, is computed via the combination of textile testing and consumer perception to deterioration. Such a perception has been surveyed, and damage that can lead to end of life has been investigated. Collected data have been translated into a consumer sensitivity using multi-criteria decision making and fuzzy techniques. The fuzzy analytic hierarchy process has been used. Five damage categories have been weighted. A selection of appropriate tests according to standards has been completed to test the product resistance to the damage. The tests results have been computed with the consumer sensitivity to obtain the consumer-based quality score. Finally, the ranking method is applied on T-shirts, and a single score ranking is made possible and objectively depict perceived quality.
Similarity Calculating-based Ontology Mapping Framework

Ontology mapping is an effective method to realize the interoperation and share of heterogeneous ontology.This paper presents a similarity calculation method,in accordance with the various relationships between concepts,and takes into account the impact of already established mapping experience on the unsolved concept similarity.It proposes a method based on the ontology axiom to verify the results of mapping methods,ensures the accuracy of the mapping under the premise of effectively improving the mapping speed.In addition to identify the equal and similar concepts,this paper considers the sub-class and super-class relationship between mapping concepts.
A NEW LANCZOS-TYPE ALGORITHM FOR SYSTEMS OF LINEAR EQUATIONS

Lanczos-type algorithms are efficient and easy to imple-ment. Unfortunately they breakdown frequently and well before con-vergence has been achieved. These algorithms are typically based on recurrence relations which involve formal orthogonal polynomials of low degree. In this paper, we consider a recurrence relation that has not been studied before and which involves a relatively higher degree polynomial. Interestingly, it leads to an algorithm that shows su-perior stability when compared to existing Lanczos-type algorithms. This new algorithm is derived and described. It is then compared to the best known algorithms of this type, namely A 5 /B 10 , A 8 /B 10 , as well as Arnoldi's algorithm, on a set of standard test problems. Numerical results are included.
Theoretical Investigation of NiI2 Based Bilayer Heterostructures

The electronic structure of nickel iodide monolayer in NiI2/ScX2 (X = S, Se and Te) and NiI2/NiTe2 heterostructures was investigated by density functional theory (DFT). The spin-asymmetric semiconducting behavior of NiI2 monolayer in these interfaces was observed. The width of the band gap of the NiI2 monolayer practically does not change in heterostructures and remains at the level of 1.7 and 3.0 eV for minor and major spin channels, respectively. The NiI2 layer can be p-doped by stacking with ScX2 dichalcogenides. On the contrary, charge transfer (~0.01 |e| per f.u.) from NiTe2 leads to n-doping of NiI2. As a result, the Fermi level shifts up to the area of NiI2 conduction band with spin down carriers only, which gives prospects of using this material in spin filter applications. The electronic structure of NiI2/ScTe2 under isotropic deformation in the plane remains the same under tension and compression within 5%, except for a small change in the band gap in the composite layers of NiI2 within 25%. This allows one to conclude about the stability of the electronic properties under deformations, which gives possibility to use the heterostructures in flexible electronics devices.
Chinese Word Segment Based on Character Representation Learning

Word segmentation is a fundamental technology of Chinese natural language processing.Using characterbased statistical machine learning methods to perform Chinese word segmentation is the main trendcurrently.However,conventional machine learning methods heavily rely on manually designed features,which require intensive labor to modify the features and verify their effectiveness.With the rapid develop of neural-network-based representation learning,it becomes realistic to learn featuresautomatically.This paper investigates a Chinese word segment method based on representation learning.We first learn embedding vectors for Chinese characters from a large corpus unsupervisedly,and then apply them to neural-network-based Chinese word segmentation supervisedly.Experimental results show that representation learning is an effective method for Chinese word segmentation.However,due to the limitation of corpus size,it still cannot replace conventional machine learning methods whichbased on manually designed features.
Simulation on the Two-phase Separation of Powder Injection Molding 316L Stainless Steel

By utilizing the FLUENT software, finite element simulation analysis was performed on the two-phase separation of powder injection molding, and the simulation results were verified through experiment. As indicated in the simulation results, the optimal process parameters for the injection molding of 316L stainless steel sample were to inject at 70 MPa and 140 °C, at an injection speed of 3.49 cm3/s. Under these conditions, the maximum average solid volume fraction in observation area of the sample was 57.68 %. Additionally, it was discovered that while preparing 316L stainless steel was prepared by powder injection molding, the smaller the average porosity of the sample, the greater the Vickers hardness. And then the higher the average solid volume fraction simulated the slighter the two-phase separation between the powder and the binder. DOI: http://dx.doi. org/10.5755/j01.ms.25.3. 19137
Energy Efficient Building Materials with Vermiculite Filler

The possibility of obtaining the vermiculite fire treatment at low temperature (burnt vermiculite) is considered in the article. The vermiculite structure features are investigated to reduce the subsequent burn temperature. By X-ray diffraction analysis it is established that the pre-treatment by a salt solution causes a change in the elementary cell of the vermiculite crystalline grid. It allows to receive the extended vermiculite under the lower burn temperature than in case of the ordinary non-treated vermiculite. To show the creation possibility of the building materials with burnt vermiculite the concrete unit weight and strength with gypsum and cement binder are studied. It is determined that the mentioned concrete strength is higher compared to concrete with ordinary vermiculite at the same density of these concretes. The thermal insulation properties are also significantly higher. The light concrete with vermiculite aggregate is used as the thermal-shield enclosing structures in building and structure constructions. The decrease of the vermiculite burn temperature will contribute to reducing the energy intensity of construction as a whole.
Investigations on Forming Ether Coated Iron Nanoparticle Materials by First-Principle Calculations and Molecular Dynamic Simulations

The mechanism of coating effects between ether molecules and iron (Fe) nanoparticles was generally estimated using first-principle calculations and molecular dynamic (MD) simulations coupling with Fe (110) crystal layers and sphere models. In the present work, the optimized adsorption site and its energy were confirmed. The single sphere model in MD simulations was studied for typical adsorption behaviors, and the double sphere model was built to be more focused on the gap impact between two particles. In those obtained results, it is demonstrated that ether molecules were prone to be adsorbed on the long bridge site of the Fe (110) crystal while comparing with other potential sites. Although the coating was not completely uniform at early stages, the formation of ether layer ended up being equilibrated finally. Accompanied with charge transfer, those coated ether molecules exerted much binding force on the shell Fe atoms. Additionally, when free ether molecules were close to the gap between two nanoparticles, they were found to come under double adsorption effects. Although this effect might not be sufficient to keep them adsorbed, the movement of these ether molecules were hindered to some extent.
Improved A1−A∞ and Related Estimates for Commutators of Rough Singular Integrals

Abstract An A1−A∞ estimate, improving on a previous result for [b, TΩ] with $\Omega \in L^{infty}({\open S}^{n - 1})$ and b∈BMO is obtained. A new result in terms of the A∞ constant and the one supremum Aq−A∞exp constant is also proved, providing a counterpart for commutators of the result obtained by Li. Both of the preceding results rely upon a sparse domination result in terms of bilinear forms, which is established using techniques from Lerner.
Blood image recognition system based on DSP

In order to reduce the human disturbance for blood analysis results,an automatic blood type image recognition system is established,and the system's hardware and software recognition algorithm is researched.The hardware of the system consists of a DSP chip,a SDRAM chip,a FLASH chip,an image coding chip,an image decoding chip,a U disk/SD card control chip,et al.The software recognition algorithm consists of gray-scale transformation,smoothing filtering,template matching,threshold processing,color component extraction,et al.Experimental results indicate that the software recognition algorithm can segment the micro-tubular from the blood card and recognize the red blood cell distribution effectively.In addition,the blood card's type can be differentiated through the color difference effectively.This system can meet the basic requirement of blood type image's automatic recognition.