Miracle-dz/UniFAR-FTUs huggingface dataset:
Compressive sensing using the log-barrier algorithm with complex-valued measurements

Compressive sensing constitutes a series of theories and algorithms that, under certain conditions, allow one to reconstruct a signal from limited linear measurements, based on knowledge about a domain where the signal is sparse. The ℓ0-minimization represents the ideal approach for reconstruction, as it searches for the sparsest representation that explains the measurements, but it is an NP-hard procedure. Fortunately, the ℓ1-minimization can frequently be used as an approximation to the ℓ0 approach, and the problem can be solved by some algorithms in polynomial time. One of the optimization problems formulated in this context corresponds to finding the sparsest solution subject to a quadratic constraint, such as in the log-barrier algorithm provided in the well- known ℓ1-Magic package. However, in this particular problem, real-valued signals are reconstructed from real- valued data. In this paper, we show how we can reconstruct sparse real-valued signals from noisy complex-valued measurements. The problem is still posed as a second-order cone program by means of the log barrier method. However, new modifications in the Newton’s step equations and in the ℓ1-Magic codes are necessary to fit the complex-valued data. In addition, in order to evaluate the reconstructions using complex data, we present the results of numerical experimentation and evaluate the performance of the signal reconstruction in terms of signal-to-error ratios. The provided method is well-suited for real applications involving the acquisition of complex-valued data, such as magnetic resonance imaging and computed tomography.
An Algorithmic Solution to Improve Command Centre Layout

A genetic algorithm was developed in this study to optimize the spatial layout of military command centres. The algorithm uses a textual string as the genetic encoding method, two genetic operations (i.e., selection and swap) for simulating an evolution process, a fitness function that reflects a human factors characterization of workplace layout requirements, and an elitist strategy for improving its search efficiency. To examine the effectiveness of the proposed algorithm, a simulation experiment was conducted using a hypothetical one dimensional layout problem. The results revealed that the algorithm identified the complete list of solutions that are theoretically optimal for the test problem. Compared to exhaustive search, the proposed algorithm increased search efficiency by more than 99%.
Power-law transform based spectral features for texture image retrieval

Searching specific digital images from large resources is an area of wide interest. Efficient access to digital images requires the development of techniques to search and organize the visual information. The traditional text based retrieval approach is not effective because it is not only expensive and time consuming process but also very subjective. Content based image retrieval (CBIR) is another image retrieval technique which is very effective. It automatically extracts image contents using low-level image features. Among the low-level image features, texture is the most important and prominent visual feature of an image. After extensive studying on existing texture feature descriptors, we find existing texture image retrieval systems are still incapable of providing retrieval result with high retrieval accuracy. To improve the CBIR performance, it is very important to find effective and efficient texture feature that can represent images more accurately. In this research, we propose two new texture features named Power-law transform based Gabor feature and Power-law transform based curvelet feature. These features are used to represent images and to measure the similarity among them. The retrieval outcome shows, the proposed Power-law based Gabor and curvelet texture features outperform the conventional Gabor and curvelet features in terms of retrieval precision. To obtain highest retrieval outcome, different level transform-power values are also investigated. To observe the retrieval performance of the proposed texture features, retrieval tests are performed using four different types of image databases. The experimental evaluation of the system is based on 2800, 11200, 5264 and 5600 texture images of original Brodatz database, scale distorted database, rotation distorted database and illumination distorted database, respectively. From the experimental results, we find that the Power-law based Gabor and curvelet texture features are robust to different types of distortion and significantly better than conventional Gabor and curvelet features.
Introductory Chapter: The Overview of Phosphorous Recovery

Phosphorus (P) is a finite, non-substitutable, non-renewable, and geographically restricted resource. Substantial interest in P availability was sparked [1]. Some researchers demonstrated sufficient availability to sustain production beyond the twenty-first century, or a maximum occurring late twenty-first century [2–4]. But there are no financial incentives to support mineral resource inspections worldwide without the exploitation of phosphate deposits. The anthropogenic influences on this critical resource are likely to bring about a number of challenges to P sustainability. Advances in technology, public health, and food production over the last couple of centuries have fundamentally interrupted the natural global P cycle. Phosphate deposits have been mined to supply human production, which generated a mostly one-way flow of P from mines to farms to surface waters, ultimately impairing freshwater and coastal waters environment and function [5]. Rapid increases in human population and the subsequent need for high agricultural productivity have led to substantial increases in fertilizer use [6]. The P used as fertilizer consumes more than 80% of the P resources [7]. P is simultaneously an important non-renewable agricultural nutrient and an environmental pollutant [8].
Towards and beyond the Pillars of Hercules: Integration and transformation of destructiveness in child psychosis (the case of Amine)

ABSTRACT Drawing on detailed clinical material taken from the first two years of the psychotherapy of Amine, a six-year-old psychotic child, the author shows how the destructiveness of the most extreme clinical realities can be transformed and integrated in the course of the treatment. During the first period of the treatment, the patient’s continuity of being was missing and he could not control his body and actions. In this situation, destructiveness was Amine’s only way to express and communicate the devastation of his inner world. Amine’s mind sought a container that might be able to receive, tolerate and symbolise his destructiveness. Thanks to the stability and reliability of the setting, together with a careful work of binding, a first border between inside and outside and between self and other could be developed. This led to the emergence of intrusion and persecutory anxieties and Amine’s original destructiveness was transformed into hate and rage. Separation was furthermore experienced as intolerable and ultimate abandonment. Only through a thorough process of working-through pertaining to the analyst’s countertransference could this impasse be overcome. Eventually, Amine could symbolise, through a dream, the possible acknowledgement, acceptance and integration of the borders that substantiate the existence of otherness.
A Review of 'Big Data' Variable Selection Procedures For Use in Predictive Modeling

A REVIEW OF ‘BIG DATA’ VARIABLE SELECTION PROCEDURES FOR USE IN PREDICTIVE MODELING By Sarah Papke August 2017 Thesis supervised by Dr. Frank D’Amico. Several problems arise when attempting to use traditional predictive modeling techniques on ‘big data. ’ For instance, multiple linear regression models cannot be used on datasets with hundreds of variables. However several techniques are becoming common tools for selective inference as the need for analyzing big data increases. Forward selection and penalized regression models (such as LASSO, Ridge Regression, and Elastic Net) are simple modifications of multiple linear regression that can provide some guidance on simplifying a model through variable selection. Dimension reducing techniques, such as Partial Least Squares and Principal Components Analysis, are more complex than regression but have the ability to handle highly correlated independent variables. Each of the aforeiv mentioned techniques are valuable in predictive modeling if used properly. This paper provides a mathematical introduction to these developments in selective inference. A sample dataset is used to demonstrate modeling and interpretation. Further, the applications to big data, as well as advantages and disadvantages of each procedure, are discussed.
3D Object Detection and Recognition for Robotic Grasping Based on RGB-D Images and Global Features

Abstract This paper describes the results of experiments on detection and recognition of 3D objects in RGB-D images provided by the Microsoft Kinect sensor. While the studies focus on single image use, sequences of frames are also considered and evaluated. Observed objects are categorized based on both geometrical and visual cues, but the emphasis is laid on the performance of the point cloud matching method. To this end, a rarely used approach consisting of independent VFH and CRH descriptors matching, followed by ICP and HV algorithms from the Point Cloud Library is applied. Successfully recognized objects are then subjected to a classical 2D analysis based on color histogram comparison exclusively with objects in the same geometrical category. The proposed two-stage approach allows to distinguish objects of similar geometry and different visual appearance, like soda cans of various brands. By separating geometry and color identification phases, the applied system is still able to categorize objects based on their geometry, even if there is no color match. The recognized objects are then localized in the three-dimensional space and autonomously grasped by a manipulator. To evaluate this approach, a special validation set was created, and additionally a selected scene from the Washington RGB-D Object Dataset was used.
La topología en el diseño de los centros asistenciales

Mathematical concepts applied to painting, as well as to architectural design, arise frequently from intuition. The important role they play in design processes is being currently vindicated, as it is evidenced by artists and mathematicians as Lucio Saffaro. Topology is concerned with the properties of spaces that are preserved under continuous deformations, and has proved to be particularly useful in the previous stages of the architectural projects, when the location of uses and itineraries is defined. On the other hand, topology brings lots of possibilities in those phases of design where no dimensional definition is needed, but just to satisfy some spatial properties. It becomes then a powerful easy tool to show and analyse different solutions by means of their spatial relationships. Concepts as adjacency, connectedness, intersection, or inclusion, can be directly applied to layout schemes, setting the basis to further dimensioning. These concepts are traditionally managed and implemented by Geographic Information Systems (GIS), and are now being applied to architecture by means of Building Information Models (BIM). As a particular use, the architectural design of hospitals and other health care facilities benefits directly from topology’s properties. It is due, firstly, to their high complexity derived from their particular technical, functional, and equipment constraints. Secondly, topology becomes helpful to design the inner and outer itineraries of both people and logistics, paying attention to the specific problems derived from transfer points, pollution risks, and intersections. And thirdly, it permits to take into account the various possible users: patients, visitors, accompanying persons, staff, logistics suppliers, etc. The case study is a result of the research project (BIA2016‒78893‒C3‒1‒R) funded by the Spanish Ministry of Economy, Industry and Competitiveness, and the EU.
The ghost in the machine: Don't let it haunt your software performance measurements

This paper describes pitfalls, issues, and methodology for measuring software performance. Ideally, measurement should be performed and reported in such a way that others will be able to reproduce the results in order to confirm their validity. We aim to motivate scientists to apply the necessary rigor to the design and execution of their software performance measurements to achieve reliable results. Repeatability of experiments, comparability of reported results, and verifiability of claims that are based on such results can be achieved only when measurements and reporting procedures can be trusted. In short, this paper urges the reader to measure the right performance and to measure the performance right.
Analysis of Human Cardiovascular System using Equivalent Electronic System

This paper describes simulation and analysis of the human cardiovascular system using a complex electronic circuit. In this study we have taken a slightly different approach to the modelling of the system and tried to advance existing electrical models by increasing more segments and parameters. Anatomical and physiological data for circuit parameters have been extracted from medical articles and textbooks. The frequency of heart is 1 Hz and the system operates in steady state condition. Each artery is modelled by one capacitor, resistor and inductor. The left and right ventricles are modelled using AC power suppliers and diodes. The results of the simulation including pressure graphs exhibit operation of the cardiovascular system under normal condition. From the electrical cardiovascular model we have analysed some cases which reflect the real time functioning of the human cardiovascular system. Hence we have changed the circuit parameters and observed the output responses which satisfy the actual human responses in different situations.
Children’s sensitivity to phonological and semantic cues during noun class learning: Evidence for a phonological bias

Abstract:Previous research on the acquisition of noun classification systems (e.g. grammatical gender) has found that child learners rely disproportionately on phonological cues to determine the class of a new noun, even when competing semantic cues are more reliable in their language. Culbertson, Gagliardi, and Smith (2017) use artificial language learning experiments with adults to argue that this likely results from the early availability of phonological information during acquisition. Learners base their initial representations on formal features of nouns, only later integrating semantic cues from noun meanings. Here, we use these same methods to show that early availability affects cue use in children (six- to seven-year-olds) as well. However, we also find evidence of developmental changes in sensitivity to semantics; when both cue types are simultaneously available, children are more likely to rely on phonology than adults are. Our results suggest that both early availability and a bias favoring phonological cues contribute to children’s overreliance on phonology in natural language acquisition.
Assessment of the Performance of Neural Networks Models for the Prediction of Surface Roughness After Grinding of Steels

Attaining acceptable levels of surface roughness is one of the primary goals of grinding. In order to achieve this goal, several approaches can be employed by varying the system parameters and attempting to find the conditions which ameliorate the outcome of the process. One way that can be rather assistive to the analysis of manufacturing processes is the use of soft computing methods such as artificial neural networks. In the current work, artificial neural network models of various categories, namely multi-layer perceptron and radial basis function neural networks, with various model parameters are developed and compared in order to determine the best performing model for the prediction of surface roughness during peripheral grinding of steel components. The results indicate that radial basis function networks outperform classical multi-layer perceptrons and constitute a promising alternative for the modeling of manufacturing processes.
Algorithms for ophthalmology image registration

II Resumo . III List of Figures . VI Acronyms and Abbreviations . VIII Chapter 1 . 1 Theoretical Background . 1 1.1. Motivation and Goals . 1 1.2. The Eye . 2 1.3. Retinography and Angiography . 4 1.4. Image Registration . 4 1.4. 1. Transformation . 5 1.4. 2. State of the art . 8 Chapter 2 . 13 Manual Registration . 13 2.1. Ocular Fundus Image Registration . 13 2.1.1. Implemented Algorithm . 13 2.1.2. Graphical User Interface . 18 2.2. Perimetry Exam Registration . 22 2.2.1. Implemented Algorithm . 24 2.2.2. Graphical User Interface . 26 Chapter 3 . 31 Automatic Registration . 31 3.1. Scale-space extrema detection . 32 3.2. Orientation . 35 3.3. Descriptor . 36 3.4. Matching . 38 3.4. 1. False Positive Elimination . 39 3.5. Registration algorithm . 41 Chapter 4 . 45 Conclusions . 45 Appendix A . 47 Mask Determination . 47 Appendix B . 48 -
Factor structure of problem-solving efficacy among college Algebra students

This paper discusses the development of the Problem – Solving Efficacy Scale on College Algebra. Through factor analytic research design, the scale underwent five development stages including assessment of factorability of the data, factor extraction, factor rotation and interpretation, rotation confirmation, and internal consistency analysis. In the 80 – item questionnaire administered to 80 randomly selected College Algebra students of Isabela State University, structural validity was attained with 34 scale items grouped into four components; namely, physiological/somatic responses, social persuasions, vicarious experiences, and mastery experiences. The developed instrument can explain 55.36% of the overall variance and has a high reliability coefficient ( .87), confirming that the four factors are integral to problem-solving efficacy in College Algebra. Physiological/Somatic responses and social persuasion explain greater amount of variance than mastery experience and vicarious which suggests that while teachers give importance on improving students’ mastery level and modelling them with successful others in problem-solving activities in College Algebra, they should also encourage students to like the subject and see themselves successful in it, and provide them with sincere and timely encouragements especially problem-solving is a challenging learning tasks. College Algebra teachers should then design attainable learning goals coupled with challenging teaching-learning activities and constructively aligned assessment, and de-emphasize drills, speed tests, and competitions in problem-solving lessons.
Scalable Telemonitoring Model in Cloud for Health Care Analysis

Telemonitoring model is health observations model that going to surveillance patients remotely. Telemonitoring model is suitable for patients to avoid high operating expense to get Emergency treatment. Telemonitoring gives the path for monitoring the medical device that generates a complete profile of patient’s health through assembling essential signs as well as additional health information. Telemonitoring model is relying on four differential modules which is capable to generate realistic synthetic electrocardiogram (ECG) signals. Telemonitoring model shows four categories of chronic disease: pulmonary state, diabetes, hypertension, as well as cardiovascular diseases. On the other hand, the results of this application model recommend facilitating despite of their nationality, socioeconomic grade, or age, patients observe amid tele-monitoring programs as well as the utilization of technologies. Patient’s multiple health status is shown in the result such as beat-to-beat variation in morphology and timing of the human ECG, including QT dispersion and R-peak amplitude modulation. This model will be utilized to evaluate biomedical signal processing methods that are utilized to calculate clinical information from the ECG.
The use of questions in a synchronous intercultural online exchange project

Abstract In this digital era, online intercultural exchange has gained increased popularity in language and culture education. However, concerns arise over its productiveness and efficacy in engaging participants cognitively. In addition, there is a paucity of research on out-of-classroom synchronous online exchange projects, let alone those involving Chinese English learners and English-speaking Chinese learners. Guided by the social constructivist theory, this study examined the productiveness of a small-scale intercultural online exchange project from its quality dimension measured by the participants’ use of questions. The purpose was to gain a better understanding of the dynamics and educational value of online synchronous text communication in language and culture learning. Participants were six English learners from China and six English-speaking Chinese learners from the U.S. Unlike many previous intercultural exchanges, this project was entirely independent from the curricula on both sides. Within a certain time frame, participants chose when and where exactly the synchronous text chat took place. Data analyses focused on the self-generated questions found in chat logs. Although participants seemed to self-generate more lower-order than higher-order thinking questions, the latter were frequently used in the process of online discussion to engage learners from both sides in critical thinking and self-reflection. Differences in the use of questions were found across dyads, languages, and groups of participants. Implications for future research and project design were discussed.
A Cross-Cultural Comparison of Lithuanian and Polish Adolescents’ Conflict Styles

Based on the assumption that cultural orientations affect interpersonal conflicts, the study examined conflict styles across two national cultures of neighboring European countries, i.e. Lithuania and Poland. Whereas Poland and Lithuania score relatively high in terms of individualism, they differ in terms of power distance, uncertainty avoidance, and masculinity-femininity. For the research purposes, a conflict resolving style questionnaire was applied, which was prepared by T. Wach according to the Thomas-Kilmann Conflict Mode Instrument. The questionnaire was administered to 520 participants aged 13–15. Conflict style comparisons demonstrated that the Lithuanians chose dominating and accommodating styles more often than the Polish did, and the Polish chose integrating more often than the Lithuanians. The research findings can be a valuable source in predicting conflict resolution patterns.
ASSESSING THE STOCK MARKET PERFORMANCES OF EU LOW-COST AIRLINES

The top seven Low-Cost Airlines in the EU, as ranked by 2018 passenger travel, are evaluated over a four year time frame using stock market performance in order to ascertain which airlines provide superior performance in relation to the others in the group and in relation to the European stock market. Several topics are discussed relating to this group of airlines including business models, operating strategies, airline networks, regional airports, and standardized fleets. Three airlines emerge with superior stock market performance: Jet2, WizzAir, and Ryanair.