Miracle-dz/UniFAR-FTUs huggingface dataset:
Life cycle of a minimal protocell - a dissipative particle dynamics (DPD) study

Cross-reactions and other systematic issues generated by the coupling of functional chemical subsystems pose the largest challenge for assembling a viable protocell in the laboratory. Our current work seeks to identify and clarify such key issues as we represent and analyze in simulation a full implementation of a minimal protocell. Using a 3D dissipative particle dynamics (DPD) simulation method we are able to address the coupled diffusion, self-assembly, and chemical reaction processes, required to model a full life cycle of the protocell, the protocell being composed of coupled genetic, metabolic, and container subsystems. Utilizing this minimal structural and functional representation of the constituent molecules, their interactions, and their reactions, we identify and explore the nature of the many linked processes for the full protocellular system.
Bounded Perturbation Resilience and Superiorization of Proximal Scaled Gradient Algorithm with Multi-Parameters

In this paper, a multi-parameter proximal scaled gradient algorithm with outer perturbations is presented in real Hilbert space. The strong convergence of the generated sequence is proved. The bounded perturbation resilience and the superiorized version of the original algorithm are also discussed. The validity and the comparison with the use or not of superiorization of the proposed algorithms were illustrated by solving the l 1 − l 2 problem.
Learning Search Strategies from Human Demonstrations

Decision making and planning with partial state information is a problem faced by all forms of intelligent entities. The formulation of a problem under partial state information leads to an exorbitant set of choices with associated probabilistic outcomes making its resolution difficult when using traditional planning methods. Human beings have acquired the ability of acting under uncertainty through education and self-learning. Transferring our know-how to artificial agents and robots will make it faster for them to learn and even improve upon us in tasks in which incomplete knowledge is available, which is the objective of this thesis. We model how humans reason with respect to their beliefs and transfer this knowledge in the form of a parameterised policy, following a Programming by Demonstration framework, to a robot apprentice for two spatial navigation tasks: the first task consists of localising a wooden block on a table and for the second task a power socket must be found and connected. In both tasks the human teacher and robot apprentice only rely on haptic and tactile information. We model the human and robot's beliefs by a probability density function which we update through recursive Bayesian state space estimation. To model the reasoning processes of human subjects performing the search tasks we learn a generative joint distribution over beliefs and actions (end-effector velocities) which were recorded during the executions of the task. For the first search task the direct mapping from belief to actions is learned whilst for the second task we incorporate a cost function used to adapt the policy parameters in a Reinforcement Learning framework and show a considerable improvement over solely learning the behaviour with respect to the distance taken to accomplish the task. Both search tasks above can be considered as active localisation as the uncertainty originates only from the position of the agent in the world. We consider searches in which both the position of the robot and features of the environment are uncertain. Given the unstructured nature of the belief a histogram parametrisation of the joint distribution of the robots position and features is necessary. However, naively doing so becomes quickly intractable as the space and time complexity is exponential. We demonstrate that by only parametrising the marginals and by memorising the parameters of the measurement likelihood functions we can recover the exact same solution as the naive parametrisations at a cost which is linear in space and time complexity.
H-CFAR based rapid ship targets detection in SAR imagery

Rapid and accurate detection of SAR ship targets is an important aspect of the applications of SAR.A rapid detection method based on the histogram of constant false alarm rate(H-CFAR) is proposed.This method directly uses the SAR image histogram information,and integrates with CFAR algorithm to achieve the target detection of SAR ship.Under the same hardware conditions,compared with the existing K-CFAR,the experiments on real ASAR,TerraSAR and Radarsat-2 data demonstrate that the proposed method can detect SAR ship targets more rapidly and accurately.
A Literature Review: Cloud Computing Energy Aspects Research and Reports

With the rapid growth of Cloud services and applications, more and more researches have been focused on performance improvements of greater and larger Data Centers. What about their energy consumption? Have we reached the point where energy consumption is limiting further performance growth? The aim of this study is to give light to the answers for these questions by presenting an overview of the energy issue in cloud computing. This paper provides an overview of researches and reports published in the latest three years, 2010-2013, in the fields of Cloud Computing Energy Efficiency improvements and awareness.
Numerical Performance Of A Mixed Stabilized Finite Element Technology For Solid Mechanics. Parallel Implementation.

In this work, a mixed stabilized formulation based on the orthogonal sub-grid scale method, is evaluated. The approach considers linear interpolation for displacement and pressure variables. The numerical analysis is particularly addressed to test the formulation behavior under kinematical incompressibility constraints, such as incompressible elasticity problems, limit load determination or strain localization in standard isochoric plasticity models. The stabilized scheme is implemented in PETSc-FEM parallel finite element code. A novel preconditioner is used to solve the iterative linear system, comparing its convergence properties with other classical widely used preconditioner. J2 plasticity model is used as the constitutive law for the proposed examples. The numerical results are compared with standard Galerkin elements and with an alternative stabilized mixed formulation based on pressure stabilized Petrov-Galerkin method.
Reusing WordNet for Building Domain Ontology

Building ontology is an important process to develop the semantic-based information system. An approach for building a domain ontology reusing WordNet was proposed. The structure and semantic relations of WordNet were analyzed and WordNet was abstracted as a graph model. Regarding domain terms as the concepts of the ontology,a subgraph whose nodes were domain terms was abstracted and a domain sub-ontology was generated. The ontology was modified and complemented using an ontology editor. The experiment shows that WordNet’s structure can be reused and domain knowledge is acquired in this approach,and a domain ontology can be built semi-automatically and quickly.
Compact Endfire Coupled-Mode Patch Antenna With Vertical Polarization

Coupled-mode patch antenna (CMPA) is able to reform the beam by manipulating the phase of the fringing fields at the edges. In this paper, a method is proposed to realize endfire radiation with vertical polarization based on the concept of CMPA. Besides the phase controlled by the coupling, the asymmetric feeding introduces additional phase shift to one of the radiation slots, which makes the beam pointing to the forward endfire direction within the whole band. The ground of the antenna is truncated to be the same size of the top patch, which eliminates the undesired effect of the ground edge and ensures the symmetric patterns pointing around endfire direction. The size of the antenna itself is only <inline-formula> <tex-math notation="LaTeX">$0.26\lambda _{0} \times 0.44\lambda _{0}$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$\lambda _{0}$ </tex-math></inline-formula> is the free-space wavelength at the center operating frequency. In order to block the unwanted common mode current outside the feeding coaxial cable, a quarter-wavelength balun is applied in the implementation. The fabricated antenna sample has highly selective two-pole <inline-formula> <tex-math notation="LaTeX">$S_{11}$ </tex-math></inline-formula> response with center frequency of 2.41 GHz and 10 dB fractional bandwidth of 2.5%. The simulated and measured patterns confirm the endfire radiation of the proposed antenna. The measured 3 dB bandwidth of realized gain at forward endfire is 2.5% at center frequency of 2.41 GHz, where the realized gain is 2.8 dBi and the front-to-back (F/B) ratio is 17.1 dB. The proposed endfire antenna with vertical polarization has the advantages of its inexpensive and friendly fabrication, compact and simple configuration, and high selectivity.
Enhancement of RPC Positioning Accuracy Using Affine Transformation with Different Number of Ground Control Points

The spatial data of satellite image is determined by integration of geometry of imaging sensor and positioning sensors as GPS and star tracking systems. Sensor model is obtained using image geometry and system calibration parameters. Sensor model is not available but Rational Polynomial Function (RPC) model is provided as an alternative representation of sensor model. RPC model is used in determining spatial data for all features in the captured satellite image. The accuracy of geometric corrected image using RPC model may not be accepted for different applications. The availability of Ground Control Points (GCPs) is a motivation of this research paper in enhancing the accuracy of resultant RPC geometric correction image using GCPs. The available data is a high resolution satellite image which is captured by IKONOS2 senor. The RPC file with its parameters is available with seven GCPs from ground survey with high accuracy. The RPC model is used to get positioning information of the raw image pixels. The accuracy of the resultant image is tested against available GCPs. Some of available GCPs are added to RPC model with 1 st order polynomial mathematical model (affine transformation) in image geometric correction process using ERDAS imagine software. The accuracy for each case of the resultant corrected image using both RPC and GCPs is tested against all the seven available GCPs. The accuracy assessment of the accuracy of resultant image is applied to get not only the improvement quality but also the suitable number of GCPs for enhancing accuracy of RPC geometric correction. Adding GCPs enhanced the accuracy of RPC geometric correction from around (10.0:20.0) meter accuracy to (1.0:5.0) meter accuracy with 80% improvement factor.
Automatic 3-D Reconstruction of Indoor Environment With Mobile Laser Scanning Point Clouds

Three-dimensional (3-D) modeling of indoor environment plays an important role in various applications such as indoor navigation, Building Information Modeling (BIM), interactive visualization, etc. While automated reconstruction of 3-D models from point clouds is receiving more and more attention. Indoor modeling remains a challenging task in terms of dealing with the complexity of indoor environment, the level of automation and restrictions of input data. To address these issues, an automatic indoor reconstruction method that quickly and effectively reconstructs indoor environment of multi-floors and multi-rooms using both point clouds and trajectories from mobile laser scanning (MLS) is proposed. The proposed automatic method of parametric structure modeling comprises three steps. First, structural elements, such as doors, windows, walls, floors, and ceilings, are extracted based on the geometric and semantic features of point clouds. Then, the point clouds are automatically segmented into adjoining rooms through a combination of visibility analysis and physical constraints of the structural elements, which ensures the integrity of the room-space partitions and yields priors for the definition of point cloud label for reconstructed model. Finally, 3-D models of individual rooms are constructed by solving an energy optimization function via multi-label graph cuts. Three benchmark datasets collected by two handheld laser scanning (HLS) and a backpack laser scanning (BLS) system were used to evaluate the proposed method. Experiments demonstrate that the recall and precision of reconstructed surface models obtained by the proposed method are mostly larger than 60%, and the average F1-score of the model is close to 5 cm.
Influence of spatial power spectrum pattern gray-level distortion on coherent diffraction imaging reconstruction

With a piece of far-field diffraction image, the purpose of reconstruction an object can be achieved by the Coherent Diffraction Imaging (CDI) method under some certain conditions. Practically, the far-field diffraction images captured by the optical system are not always matched well with the phase retrieval algorithms, which frequently leads to lower resolution of the reconstructed object image. However, we find that the gray distortion of the power spectrum has a great impact on the object reconstruction, and even a good phase retrieve algorithm can not reconstruct the object. Based on experiment and simulation results, we find that the spatial power spectrum pattern gray-level distortion has much influence on the CDI reconstruction, and the acquired pattern distortion rate should be less than 0.1. When the gray-level distortion is less than 0.1, clear object can be reconstructed in fewer iterations. The reconstruction algorithm is fault-tolerant to the distortion of power spectrum. The convergence speed of the algorithm can be accelerated through giving an upper bound of gray-level distortion. This result provides a reference for other researches in CDI to avoid the convergence stagnation caused by the distortion of spatial power spectrum collected by experiments.
Instrument Transducers An Introduction To Their Performance And Design

Thank you for downloading instrument transducers an introduction to their performance and design. As you may know, people have look hundreds times for their chosen readings like this instrument transducers an introduction to their performance and design, but end up in harmful downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they are facing with some harmful bugs inside their desktop computer.
Sliding mode 
 H∞ control of time‐varying delay Markov jump with quantized output

This paper investigates the quantized sliding mode control of Markov jump systems with time‐varying delay. A dynamical adjustment law is explored to quantize the system output. By constructing an observer‐based integral sliding surface, a sliding mode controller is designed to take over the dynamical motion of state estimation and ensure the reachability of sliding surface. A new scaling manner is developed to build the bound between the system output and quantized error. With the help of separation strategies for controller synthesis and general transition probabilities and a lower bound theorem for nonlinear integral terms, a new synthesis method to ensure the required stability and meet the required H∞ performance is proposed in the form of linear matrix inequalities. The validity of the proposed control method is illustrated by a numerical example.
A SEARCH OF SIGNIFICANT PHRASES FOR BUILDING TOPIC MODELS IN TEXT DOCUMENTS

A huge amount of documents in the digitalized libraries requires efficient meth-ods for exploring contained there information. “Topic modeling” is considered as one of the most effective among them. In spite of commonly used approaches for finding occurrences of single words, in the paper building topic models based on phrases is pondered. We propose a methodology, which enables to create a set of significant word sequences and thus limiting the search area to phrases which contain them. The methodology is evaluated on experiments performed on real text datasets. Obtained results are compared with those received by using LDA algorithm
Non-linear effects in early Universe cosmology

In this thesis, we discuss several instances in which non-linear behaviour affects cosmological evolution in the early Universe. We begin by reviewing the standard cosmological model and the tools used to understand it theoretically and to compute its observational consequences. This includes a detailed exposition of cosmological perturbation theory and the theory of inflation. We then describe the results in this thesis, starting with the non-linear evolution of the curvature perturbation in the presence of vector and tensor fluctuations, in which we identify the version of that variable that is conserved in the most general situation. Next, we use second order perturbation theory to describe the most general initial conditions for the evolution of scalar perturbations at second order in the standard cosmological model. We compute approximate solutions valid in the initial stages of the evolution, which can be used to initialize second order Boltzmann codes, and to compute many observables taking isocurvature modes into account. We then move on to the study of the inflationary Universe. We start by analysing a new way to compute the consequences of a sudden transition in the evolution of a scalar during inflation. We use the formalism of quantum quenches to compute the effect of those transitions on the spectral index of perturbations. Finally, we detail the results of the exploration of a multi-field model of inflation with a non-minimal coupling to gravity. We study popular attractor models in this regime in both the metric and the Palatini formulations of gravity and find all results for both the power spectrum and bispectrum of fluctuations to closely resemble those of the single-field case. In all systems under study we discuss the effects of non-linear dynamics and their importance for the resolution of problems in cosmology.
KAJIAN PENGGUNAAN METODE IP, STORET, dan CCME WQI DALAM MENENTUKAN STATUS KUALITAS AIR

Pemantauan kualitas air perlu dilakukan pada air sungai, laut, danau, rawa dan tanah sehingga dapat dimanfaatkan sesuai dengan kegunaannya bagi makhluk hidup. Kajian ini bertujuan untuk membandingkan beberapa metode perhitungan indeks kualitas air yang paling efektif, sensitif dan obyektif dalam menentukan status kualitas air permukaan. Metode perhitungan Indeks Kualitas Air (IKA) diperlukan untuk menyederhanakan banyaknya nilai dari berbagai jenis parameter menjadi sebuah angka tunggal yang mampu mendeskripsikan kualitas air, sehingga lebih mudah dipahami oleh masyarakat. Perhitungan IKA dengan menggunakan metode Storet, IP, dan CCME WQI (Canadian Council of Ministers of The Environment) dilaksanakan di beberapa penelitian di berbagai negara. Kajian ini akan membandingkan hasil literatur dari penelitian IKA di beberapa negara. Metode tersebut akan dibandingkan dengan beberapa indikator. Hasil kajian menunjukkan Metode IP lebih unggul jika memakai data tunggal karena memiliki kelebihan dari segi biaya dan waktu, namun hanya mempresentasikan status mutu air pada saat itu saja, tidak dalam periode tertentu. Metode Storet dan CCME menggunakan data perulangan sepanjang waktu (time series data) sehingga menggambarkan status mutu air dalam periode tertentu. CCME WQI lebih unggul dari Metode Storet dan Metode IP karena memperhitungkan besarnya selisih hasil pengujian yang melebihi baku mutu melalui F3 (Amplitude). Dari kajian di atas disimpulkan, Metode CCME merupakan metode yang paling tepat untuk menganalisis kualitas air baik pada air permukaan maupun air tanah dengan tingkat efektivitas dan sensitivitas yang lebih tinggi dibandingkan dengan metode lainnya serta penggunaan jumlah dan jenis parameter yang fleksibel.
Cosmic Microwave Background from Effective Field Theory †

In this work, we study the key role of generic Effective Field Theory (EFT) framework to quantify the correlation functions in a quasi de Sitter background for an arbitrary initial choice of the quantum vacuum state. We perform the computation in unitary gauge, in which we apply the St u ¨ ckelberg trick in lowest dimensional EFT operators which are broken under time diffeomorphism. In particular, using this non-linear realization of broken time diffeomorphism and truncating the action by considering the contribution from two derivative terms in the metric, we compute the two-point and three-point correlations from scalar perturbations and two-point correlation from tensor perturbations to quantify the quantum fluctuations observed in the Cosmic Microwave Background (CMB) map. We also use equilateral limit and squeezed limit configurations for the scalar three-point correlations in Fourier space. To give future predictions from EFT setup and to check the consistency of our derived results for correlations, we use the results obtained from all classes of the canonical single-field and general single-field P ( X , ϕ ) model. This analysis helps us to fix the coefficients of the relevant operators in EFT in terms of the slow-roll parameters and effective sound speed. Finally, using CMB observations from Planck we constrain all these coefficients of EFT operators for the single-field slow-roll inflationary paradigm.
IMPROVING COLLABORATIVE FILTERING RECOMMENDER BY USING MULTI-CRITERIA RATING AND IMPLICIT SOCIAL NETWORKS TO RECOMMEND RESEARCH PAPERS

II ACKNOWLEDGMENT.IV DEDICATION.V CHAPTER 1: INTRODUCTION . 1 1.1 OBJECTIVES AND RESEARCH QUESTIONS . 4 1.1.1 Research Questions Related to Multi-Criteria Rating RSs . 4 1.1.2 Research Questions Related to Implicit Social Networks (ISNs) . 5 1.2 RESEARCH CONTRIBUTIONS . 6 1.3 DEFINITIONS OF TERMS . 7 1.4 DISSERTATION OUTLINE . 8 CHAPTER 2: RELATED WORK . 10 2.1 RECOMMENDER SYSTEMS . 10 2.1.1 Content-based Filtering . 2 2.1.2 Collaborative Filtering . 2 2.1.3 Hybrid Approach. 6 2.2 MULTI-CRITERIA RECOMMENDER SYSTEM (MCRS) . 8 2.2.1 Definition and Background . 8 2.2.2 Classification of MCRS . 8 2.2.3 Differences between the Single-rating Matrix and Multi-criteria Matrix . 9 2.2.4 Approaches of Incorporating Multi-criteria Information in the Recommendation Process . 11 2.3 SOCIAL NETWORK-BASED RECOMMENDER SYSTEMS (SNRSS) . 13 2.3.1 Explicit SNRSs . 19 2.3. 2 Implicit SNRSs . 22 2.3. 3 Considering Implicit and Explicit Social Relations . 26 2.3. 4 Summary . 27 2.4 RECOMMENDER SYSTEMS FOR RESEARCHERS . 29 2.4. 1 Recommending Research Papers using Content-based Filtering . 29 2.4. 2 Recommending Papers using Collaborative Filtering . 31 2.4. 3 Recommending Papers using Hybrid Approach . 35 2.4. 4 Social Bookmarking Tools . 37 2.4. 5 Summary of Recommending Research Papers . 39 CHAPTER 3: MULTI-CRITERIA RATINGS FOR RESEARCH PAPER RECOMMENDER SYSTEMS.42 3.1 QUALITATIVE STUDY . 42 3.1.1 Methodology . 44 3.1.2 Participants . 45
A Moment-Based Notion of Time Dependence for Functional Time Series

This paper addresses the fundamental topic of time dependence for time series when data points are given as functions. We construct a notion of time dependence through the scores of the principal components, which allows us to adapt various scalar time series techniques to the functional data context. In particular, we define dependence based on the autocovariances and cumulants of the scores, covering short and long memory scenarios. This notion naturally applies to linear processes. To justify this moment based approach we investigate the asymptotic properties of the estimator of the functional principal components and show its consistency under short and long memory. Finally, the applicability of our notion is illustrated through several statistical problems in functional time series: estimation of the functional autoregressive model, estimation of the long-run covariance function and testing for short memory against the long memory alternative.