Miracle-dz/UniFAR-FTUs huggingface dataset:
Formal Specification and Verification of Concepts in Information Language in ODP Systems

: Distributed systems can be very large and complex and the many different considerations which influence their design can result in a substantial body of specification, which needs a structuring framework if it is to be managed successfully. The purpose of the RM-ODP is to define such a framework. The Reference Model for Open Distributed Processing (RM-ODP) provides a framework within which support of distribution, inter-working and portability can be integrated. It defines: an object model, architectural concepts and architecture for the development of ODP systems in terms of five viewpoints. However, RM-ODP is a meta-norm, and several ODP standards have to be defined. Indeed, the viewpoint languages are abstract in sense that they define what concepts should be supported and not how these concepts should be represented using the UML/OCL meta-modeling approach. In this paper, we report on the definition and address of the syntax and semantics for a fragment of ODP object concepts defined in the RM-ODP foundations part and in the information language. These concepts are suitable for describing and constraining ODP information viewpoint specifications.
Electrodéposition de couches minces métalliques à partir de solutions de liquides ioniques pour des applications électroniques.

Les mecanismes d’electrodeposition realises a partir d'electrolytes a base de liquides ioniques ne sont pas tres bien compris en raison de l’organisation structurale complexe de ces electrolytes. Dans cette these, nous etudions les relations qui existent entre la morphologie des films, les proprietes electrochimiques ainsi que la structure de l'electrolyte liquide ionique. Plusieurs solutions ont ete etudiees: CuCl, CuCl2 et CuSO4 dans 1-ethyl-3-methylimidazolium ethyl-sulfate [EMIM] [EtSO4]; AgTFSI, CuTFSI2 et AlTFSI3 en 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide [EMIM] [TFSI]. Des mesures de cyclovoltammetrie montrent que les reductions de l’argent et du cuivre sont quasi-reversibles et se produisent par une reaction de transfert mono-electronique {(Ag (I) → Ag (0), (Cu (II) → Cu (I)) et (Cu (I) → Cu (0)}. La reduction de l'aluminium est irreversible. Les coefficients de diffusion augmentent avec la temperature de l'electrolyte et sont egalement influences par l'etat d'oxydation du metal et des anions en solution. Des films minces metalliques ont ete obtenus pour toutes les solutions, sauf pour AlTFSI3. L'analyse par XRD et EDX montrent que les films sont cristallins et sont principalement constitues de cuivre ou d'argent pur. Leur morphologie est controlee par la temperature, du temps et du potentiel d’electrodeposition. D'une maniere generale, l'elevation du temps de depot et de la temperature augmente la couverture du film et de la taille des particules, tandis que l'augmentation du potentiel de depot diminue la taille des particules. La structure des electrolytes a ete etudiee par Raman et IR spectroscopies et interpretee a l’aide de methodes theoriques de chimie quantique. Pour AgTFSI-[EMIM][TFSI], le cation d’argent est solvate par trois anions TFSI-. Pour CuCl2-[EMIM][EtSO4], le cation de cuivre est solvate par deux anions de chlore et deux anions EtSO4.
A Bergsonian Approach toward Phenomenal Externalism: Rendering Unity

Phenomenal Externalism (PE) is one proposed framework for resolving the problems associated with the intentional aspect of mental content. However, by privileging external objects over internal structure in identifying the characteristics of experience (qualia), PE is limited in its ability to explain the introspective (phenomenal) aspect of experience. This has become an Achilles’ heel for PE, to which many of its opponents have formulated significant objections. In this paper, we consider some possible ways of modifying and equipping PE to answer these objections. It will be shown that a degree of subjectivity can be returned to the qualia conception within a PE framework. This will be achieved by following Bergson, who claims that perception is made in things and that, though not identical, pure perception and objective reality are united. To explain this unity, we propose a computer rendering analogy, according to which qualia look like the products of mental rendering, which raises the possibility of locating some phenomenal properties in things. On this modified view, on the one hand qualia turn out to be objective, in the sense that they are unified with external entities, and on the other hand they are subjective, since they are unified with the mind. To be “in” the thing in the sense discussed means being “united with” and “inseparable from” both the thing and the mind.
Fluid Properties at Nano/Meso Scale: A Numerical Treatment

Biographies Series Preface Preface Symbols and Abbreviations 1 The Nature of Fluid Flow 1.1 Introduction 1.2 Basics of fluid motion 1.3 Molecular mechanics 1.4 Types of simulation 1.5 Effects at molecular scale 1.6 Summary 2 Fluid Physics at Meso Scales 2.1 Introduction 2.2 Top-down approach for meso scale computation 2.3 Bottom up approach for meso scale computation 2.4 Summary 3 Meso Scale Model Based on First Principles 3.1 Introduction 3.2 Fluid physics model 3.3 Extracting local bulk properties 3.4 Verification of proposed meso scale model 3.5 Summary 4 Enhancements to the Meso Scale Model 4.1 Introduction 4.2 Driving forces 4.3 Thermostats 4.4 Case studies 4.5 Summary 5 Modelling Fluid Regimes at Nano/Meso Scales 5.1 Introduction 5.2 Flow regimes 5.3 Fluid flow characterization from molecular simulation 5.4 Summary 6 Performance of Proposed Meso Scale Model 6.1 Introduction 6.2 Issues in using large numbers of molecules 6.3 Meso scale simulations 6.4 Summary 7 Experimental Aspects of Fluid Properties at the Nano/Meso Scale 7.1 Introduction 7.2 Colloidal interactions in nano-fluids 7.3 Osmotic phenomena and osmotic pressure 7.4 Gradient diffusion coefficient 7.5 Viscosity 7.6 Membrane separations 7.7 Membrane ultrafiltration models 7.8 Tensile and other rheological properties of liquids on the meso scale 7.9 Summary 8 Future Advancement 8.1 Future advancement References Index
Corporate Governance in Latin America: Towards Shareholder Democracy

Vol. 19, no. 2, 2019 How can Latin American majority shareholders keep their corporate control? Shareholder democracy, the idea that “oneshare equals one-vote” and that firms are controlled by shareholders who exercise their power with equal economic rights, has recently gained great attention in corporate governance debates. This is particularly because technology companies such as Ebay or Facebook have founders who control a lot more than they own via dual class shares, some companies such as social media Snap listed with shares with no voting rights, and stock exchanges such as Hong Kong Stock Exchange changed listing regulations to prevent losing future technology companies such as Alibaba.
PENINGKATAN HASIL BELAJAR MATEMATIKA MELALUI MODEL PEMBELAJARAN PROBLEM BASED LEARNING BERBANTUAN MEDIA VIDEO SISWA KELAS IV SD

Abstract . Tujuan dari penelitian ini adalah untuk meningkatan hasil belajar matematika melalui model Problem Based Learning (Pbl) Berbantuan Media Video pada siswa kelas 4 di SDN Batu 2 Kecamatan Karang Tengah Kabupaten Demak semester 2 tahun pelajaran 2018/2019. Rancangan penelitian ini adalah penelitian tindakan kelas (PTK). Teknik pengumpulan data dalam penelitian ini dengan tes dan non tes. Instrumen tes berupa butir soal dalam bentuk pilihan ganda, dan instrumen non tes berupa lembar observasi. Teknik analisis data yang digunakan adalah teknik statistik kuantitatif komparatif yaitu teknik persentase yaitu teknik statistik yang membandingkan hasil belajar tematik dari pra siklus, siklus I dan siklus II. Hasil penelitian menunjukkan bahwa terdapat peningkatan hasil belajar matematika siswa kelas 4 di SDN Batu 2 Kecamatan Karang Tengah Kabupaten Demak yang diupayakan melalui model Problem Based Learning (Pbl) Berbantuan Media Video. Hal ini ditunjukkan oleh peningkatan hasil belajar berdasarkan ketuntasan yakni banyaknya siswa yang tuntas sebelum tindakan sebanyak 9 siswa (43% dari seluruh siswa). Setelah diberikan tindakan pada siklus I, jumlah siswa yang tuntas belajar meningkat menjadi 15 siswa (71% dari seluruh siswa), dan pada siklus II, jumlah siswa yang tuntas menjadi 21 siswa (100% dari seluruh siswa).
Geometric Measurement Based on the Single Image with a Rectangular Structure

As characterized by its non-contact and universality, real-time and repeatability, image measuring gradually becomes one of the impor tant methods for geometric measurement. In binocular measure ment systems, precise matching between two images and camera cali bra tion have always been classic problems in photogrammetry. Geometric measurement based on a single image is getting more attention in photogrammetry owing to the avoidance of such problems.
ACOUSTIC SCENE CLASSIFICATION USING FULLY CONVOLUTIONAL NEURAL NETWORKS AND PER-CHANNEL ENERGY NORMALIZATION Technical

This technical report describes our approach to Task 1 ''Acoustic Scene Classification'' of the DCASE 2020 challenge. For subtask A, we introduce per-channel energy normalization (PCEN) as an additional preprocessing step along with log-Mel spectrograms. We also propose two residual network architectures utilizing “Shake-Shake” regularization and the “Squeeze-and-Excitation” block, respectively. Our best submission (ensemble of 8 classifiers) outperforms the corresponding baseline system by 16.2% in terms of macro-average accuracy. For subtask B, we mainly focus on a low complexity, fully convolutional neural network architecture, which leads to 5% relative improvement over base-line accuracy.
Final Report Deep Multi-Label Classiﬁcation for High Resolution Satellite Imagery of Rainforests

Satellite rainforest imagery is extremely helpful in tracking down deforestation and analyzing behaviors that contribute to wildlife destruction. Constant monitoring of this imagery however is completely infeasible for humans and so convolutional neural networks are the perfect candidate for detecting satellite image features. In this paper, we discuss our strategy for multi-label classiﬁcation of Amazon satellite imagery. Each image can have multiple tags activated like ”clear, slash and burn, habitation, water” and the classiﬁer must be able to detect these wide-scale and small-scale features simultaneously. We applied state-of-the-art image classiﬁcation architectures and developed an original CNN architecture for solving this problem. Using a binary cross-entropy loss function and our own architecture, we achieved an F 2 score of 0.9228 on the validation set. We showcase visualizations of the network on a variety of input images to validate that the network is generalizing to the speciﬁc land features for each label.
Application of Artificial Neural Network on Speech Signal Features for Parkinson’s Disease Classification

Since speech is affected in up to 90% of Parkinson’s Disease patients, it has drawn interest as a target symptom for diagnostic testing. Using a dataset of speech sample features, multilayer perceptron was trained to accurately classify between Parkinson’s Disease patients and healthy individuals. By optimizing the number of neurons in a single hidden layer network, a 0.937 accuracy model was identified. Using the single hidden layer results to inform a search for deep learning models with two hidden layers, accuracy improved to 0.952. Finding high accuracy and often 100% sensitivity, this method could be a very useful screening test for Parkinson’s Disease as it is also non-invasive, quick, and can be done remotely.
Liquidity or Convenience? Heterogeneous Impacts of Mobile Airtime Loans on Communication Expenditure

Credit market imperfections can decrease welfare by increasing vulnerability to shocks and destabilizing consumption. Meta data from individual cellphone users have enabled a proliferation of mobile financial services in markets where information asymmetries and high provision costs tend to deter formal financial institutions. As the first such financial product typically offered to new users, airtime loans provide prepaid customers small airtime advances for a fee as an alternative to recharges purchased from network agents. Relying on rich administrative data from a mobile network operator in Haiti, we study the impact of airtime loans on consumer cellphone expenditure and network usage. We find that access to loans increases total communication expenditure by 16% due to a crowding-in of additional network usage. This expenditure response to airtime loans is distinctly heterogeneous. Poorer customers in the lowest tercile of initial expenditure more than double their mobile communication spending when airtime loans become available, while access to loans leaves expenditure of the highest tercile unchanged. These differences in the expenditure impacts of airtime loans exist. We find suggestive evidence that these differences are driven by distinct motivations for requesting airtime loans: Poorer customers appear to use loans to relax short-term liquidity constraints at critical communication times whereas non-poor customers primarily use these loans for convenience, as it gives them more discretion in when to visit airtime vendors.
Is there a link between endowment inequality and deception? – an analysis of students and chess players

This paper investigates experimentally the relationship between inequality in endowment and deception. Our basic design is adopted from Gneezy (2005): two players interact in a deception game. It is common knowledge that player 1 has private information about the payoffs for both players of two alternative actions. Player 1 sends a message to player 2, indicating which alternative putatively will end up in a higher payoff for player 2. The message, which can either be true or false, does not affect the payoffs of the players. Player 2 has no information about the payoffs. However, player 2 selects one of the two alternatives A or B, which is payoff-relevant for both players. Our paper adds value to the literature by extending Gneezy (2005) in two ways. First, we systematically vary the initial endowment of players 1 and 2 (common knowledge to both of them). Second, we do not limit ourselves to the standard population of university students but also recruit chess players that are not enrolled in any degree program. Doing so, we want to find out if our results remain robust over a non-standard subject population which is known to be experienced to some extent in strategic interactions. Our main findings are: (i) non-students behave more honestly than students, (ii) students are more likely to trust the opponent’s message, and (iii) students and non-students behave differently to variation in initial endowment.
THE CAU-ET ACOUSTIC SCENERY CLASSIFICATION SYSTEM FOR DCASE 2020 CHALLENGE Technical Report

The acoustic scenery classiﬁcation problem is an interesting topic that has been studied for a long time through the DCASE competition. This technical report presents the CAU-ET’s submitted scenery detection system to the DCASE 2020 challenge, Task 1. In our method, we generated Mel-spectrogram from audio. From the log-mel spectrogram, we got Deltas, Delta-deltas, and Harmonic-percussive source separation(HPSS) features as inputs of our deep neural network models. The classiﬁcation result of the proposed system was 67.14% in subtask A and 95.27% in subtask B for each development set.
Segmentation and Classification of Brain Hemorrhage using U-net and CapsNet

— Stroke is the third largest cause of death and the biggest source of acquired disability worldwide. This condition is caused by a fatally low blood supply in a region of the brain. The use of Computed Tomography (CT) imaging for patients with stroke symptoms is an essential step for triaging and diagnosis in many hospitals. Human-centered diagnosis is typically error-prone and unreliable resulting in a recent surge of interest to automatize this process using convolutional neural networks (CNNs). A two-step approach to the brain intracranial hemorrhage classification system is proposed here. The implemented system consists of several stages that include image preprocessing, image segmentation and classification. Prior to entering neural nets, the brain CT image is subjected to noise removal and skull stripping. The preprocessed images are then given as input to U-net which segments the hemorrhage region. This segmented hemorrhage region will be classified using Capsule neural network into three types Intraparenchymal, Subdural, Epidural hemorrhages. The CapsNet model was able to achieve training accuracy of 97.3% and validation accuracy of 92.1% with learning rate of 0.02s.
Discovering Barriers to Opioid Addiction Treatment from Social Media: A Similarity Network-Based Deep Learning Approach

Opioid use disorder (OUD) costs the US healthcare systems $504 billion annually and poses significant mortality risk. Current studies attempt to understand barriers to OUD treatment using surveys to mitigate this opioid crisis. However, the response rate of these surveys is low because of social stigma. We explore user-generated content in social media as a new data source to study OUD. We design a novel IT system, SImilarity Network-based DEep Learning (SINDEL), to discover barriers to OUD treatment from patient narratives and address the challenge of morphs. SINDEL significantly outperforms state-of-the-art NLP models, reaching an F1 score of 76.79%. Thirteen types of OUD treatment barriers were identified and verified by domain experts. This work contributes to information systems with a novel deep-learning-based approach for social media analytics. We also provide a deeper understanding of the opioid epidemic and the hurdles that patients face.
Quantifying diffusion in biofilms : from model hydrogels to living biofilms

Biofilms are primarily communities of microorganisms embedded in a complex exopolymer matrix. They are thought to play an important role as diffusive barriers in environmental systems and human health, resulting in increased resistance to disinfectants and antibiotics. Since mass transport in a biofilm is primarily due to molecular diffusion, it is critical to understand the main parameters influencing diffusive fluxes in a biofilm. In this thesis, a Pseudomonas fluorescens biofilm and two model hydrogels, (agarose and calcium alginate), were investigated. Both self-diffusion (Brownian motion) and mutual diffusion coefficients were quantified. Fluorescence correlation spectroscopy was used to measure the self-diffusion coefficients in a ca. 1 m confocal volume in the gels or biofilms, whereas a diffusion cell setup was employed for mutual diffusion measurements. In addition, microelectrode voltammetry was used to evaluate Donnan potential of the gels in order to determine its impact on diffusion. For the agarose hydrogel, the combined observations of a decreasing self-diffusion coefficient coupled with increasing mutual diffusion as a function of a decreasing ionic strength have been attributed to the gel’s Donnan potential. Measurements of the Donnan effect (difference of -30 mV between ionic strengths of 10 and 10 M) and the corresponding accumulation of ions in the hydrogel (13x enhancement with respect to the bulk solution) indicated that electrostatic interactions can strongly influence the diffusive flux of cations, even in a weakly charged hydrogel, such as agarose. Somewhat surprisingly, for a more highly charged gel such as calcium alginate, varying ionic strength and pH resulted in only small changes to the diffusion of charged probes in the hydrogel. These results suggested that the direct effect of the cations on gel structure (due to an induced swelling or compression) was much more effective than the Donnan effect when influencing solute diffusion. Similarly, for a bacterial biofilm, self-diffusion coefficients were virtually constant across a range of examined ionic strengths (10-10 M) for both negatively and positively charged small solutes (Db/Dw≈85%) and nanoparticles (Db/Dw≈50%), suggesting that the obstruction effect of the biofilms again overwhelmed the charge effect.
Formation de capsules d'hydrogel à coeur aqueux par fragmentation d'un jet composé de fluides complexes

Cette these a pour objectif de comprendre les mecanismes physiques regissant la formation de capsules submillimetriques a coeur aqueux possedant une membrane fine d'hydrogel et ainsi de mieux maitriser ce procede. Des bigouttes sont d'abord formees dans l'air par fragmentation d'un jet cylindrique compose d'un coeur aqueux enveloppe par une solution d'alginate. La coque est ensuite gelifiee apres immersion dans une solution de calcium. L'etude du co-Ecoulement au sein de l'injecteur a montre l'existence d'une instabilite elastique qui est amplifiee en presence de cations, du fait du caractere polyelectrolyte de l'alginate. Nous avons montre que cette instabilite etait a l'origine d'un battement du jet compose en sortie d'extrusion. En provoquant un decentrage du coeur, l'instabilite induit une relaxation asymetrique du profil de vitesse, ce qui cree un couple qui courbe le jet. Nous avons mis en evidence cet effet en produisant des jets courbes a partir d'une pointe biseautee. La fragmentation du jet est ensuite controlee par une perturbation harmonique des debits d'injection. Nous observons une decroissance de la vitesse d'onde a la surface du jet pilotee par la tension de surface. La viscosite elevee des solutions d'alginate entraine une amplification de fluctuations de cette vitesse donnant lieu a des coalescences au sein du jet. L'ajout de tensioactifs peut exacerber cet effet en induisant une tension de surface dynamique a la surface du jet. Finalement, nous parvenons a produire des capsules submillimetriques de taille controlee, monodisperses, possedant une membrane fine, avec un taux d'encapsulation superieur a 99%. Ces capsules trouvent des applications dans le domaine des biotechnologies comme nouvel outil pour la culture cellulaire.
Symmetry group classification for generalized reaction-diffusion-convection equation

In this paper, the symmetry group classification is given for the non-linear generalized reaction-diffusion-convection equation admitting an extension by one of the principal Lie algebra of the equation under consideration using the preliminary group classification approach. Using the adjoint representation Gε of on its Lie algebra g6, the implementation of optimal systems to find its optimal one dimensional subalgebras is performed. The result of the work is a wide class of equations summarized in table 3. M.S.C. 2010: 53A55, 34C14, 76M60.
Summarization by Feature-Opinion Pairs from Web Opinion Sources

– With the rapidly growth Internet, web opinion sources is also dynamically developed. The valuable information useful for both customers and manufactures expressed over them. One of the important types of information on the Web are opinions expressed in the user generated content e.g., customer reviews of products, forum posts, and blogs. These are written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and opinions from each sentence. In this paper, we dedicate our work to the main subtask of summarization for the product. Therefore, product feature and opinion extraction is critical because its effectiveness significantly affects the identification of semantic relationships. The Probabilistic based model of supervised learning and dependency tree will improve the result that is more flexible and effective.