Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Impact of Topology on Power System Transient and Frequency Stability

This paper presents a statistical study on the impact of topology of the transmission system on the transient and frequency stability of power systems. We consider four topologies: random graph; small-world graph; nested small-world graph; and lattice graph. These graphs are utilized to generate hundreds of synthetic networks with given topology and adequately generated static and dynamic data. Then, each network is simulated based on a Monte Carlo method and considering random contingencies and different levels of inertia. The case study allows drawing some remarkable conclusions on the correlation between power system stability and topology.
On Multichannel Neurons , with An Application to Template Search

The multichannel model is a complete reassessment of how neurons work at the biochemical level. Its results can be extended into an overarching theory of how vision, memory and cognition come to be in the living brain. This article documents a first attempt at testing the model’s validity, by applying its principles to the construction of an image templatematching framework, which is then used to solve a Graphical User Interface (GUI) automation problem. It was found that the template-matching function thus implemented can consistently locate required visual controls, even when template and match differ by color palette or (to a slighter degree) feature proportion. The article concludes by discussing the significance of these results and directions for further research.
Finding and understanding bugs in software model checkers

Software Model Checking (SMC) is a well-known automatic program verification technique and frequently adopted for checking safety-critical software. Thus, the reliability of SMC tools themselves (i.e., software model checkers) is critical. However, little work exists on validating software model checkers, an important problem that this paper tackles by introducing a practical, automated fuzzing technique. For its simplicity and generality, we focus on control-flow reachability (e.g., whether or how many times a branch is reached) and address two specific challenges for effective fuzzing: oracle and scalability. Given a deterministic program, we (1) leverage its concrete executions to synthesize valid branch reachability properties (thus solving the oracle problem) and (2) fuse such individual properties into a single safety property (thus improving the scalability of fuzzing and reducing manual inspection). We have realized our approach as the MCFuzz tool and applied it to extensively test three state-of-the-art C software model checkers, CPAchecker, CBMC, and SeaHorn. MCFuzz has found 62 unique bugs in all three model checkers -- 58 have been confirmed, and 20 have been fixed. We have further analyzed and categorized these bugs (which are diverse), and summarized several lessons for building reliable and robust model checkers. Our testing effort has been well-appreciated by the model checker developers, and also led to improved tool usability and documentation.
The Performance of Hedge Fund Strategies in Emerging Markets

In the past decades, emerging market hedge funds have been subject to significant capital inflow and today they constitute a $200 billion market. Previous research suggests that future investment opportunities exist in these regions. The objective of this study is to examine if emerging market hedge funds produce higher risk-adjusted returns than global hedge funds, focusing on how different hedge fund investment strategies perform. The research is based on the single factor Capital Asset Pricing Model (CAPM) to determine the strategies performance (alpha) net of fees. The study ranges from January 2002 to December 2016 and scrutinizes the strategies performance in seven different sub-periods. The research provides evidence that the magnitude of performance for hedge funds differ not only regarding the location of which fund managers choose to allocate the assets, but also on what kind of strategy they practice to generate return. On a risk-adjusted premise, the study finds that not all strategies in emerging markets manage to perform better than the global hedge fund market consistently over a longer period. These findings stress the importance of considering fund strategies rather than location, when comparing financial instruments. The conclusions provide helpful knowledge to both future research and financial authorities.
Adaptive MIMO Radar

We investigate several adaptive techniques for a multiple-input multiple-output (MIMO) radar system (that is, a radar with multiple transmitting and receiving antennas). By transmitting independent waveforms via different antennas, the echoes due to targets at different locations are linearly independent of each other, which allows the direct application of many adaptive techniques to achieve high resolution and excellent interference rejection capability. In the absence of array steering vector errors, we discuss the application of several existing adaptive algorithms including Capon, APES (amplitude and phase estimation) and CAPES (combined Capon and APES), and then propose an alternative estimation procedure, referred to as the combined Capon and approximate maximum likelihood (CAML) method. Via several numerical examples, we show that the proposed CAML method can provide excellent estimation accuracy of both target locations and target amplitudes. In the presence of array steering vector errors, we apply the robust Capon beamformer (RCB) and doubly constrained robust Capon beamformer (DCRCB) approaches to the MIMO radar system to achieve accurate parameter estimation and superior interference and jamming suppression performance. Index Terms – Adaptive arrays, MIMO Radar, direction of arrival (DOA), Capon, amplitude and phase estimation (APES), robust Capon beamformer (RCB), doubly constrained robust Capon beamformer (DCRCB). IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 3 Submitted in April 2006 Luzhou Xu and Jian Li are with the Department of Electrical and Computer Engineering, University of Florida, Gainesville, USA. Petre Stoica is with the Department of Information Technology, Uppsala University, Uppsala, Sweden. Please address all correspondences to: Dr. Jian Li, the Department of Electrical and Computer Engineering, P. O. Box 116130, University of Florida, Gainesville, USA. Phone: (352) 392-2642, Fax: (352) 392-0044, Email: li@dsp.ufl. edu.
Genetic Characterizations Among Drought Tolerant Wheat Genotypes by Biochemical and Molecular Markers

Wheat (Triticum aestivum L.) is the world’s most important cereal crop and due to its different uses and nutritive value it is the staple food for more than one third of the world’s population. Wheat production can be enchanced through the development of improved cultivars with wider genetic base capable of producing better yield under various agroclimatic conditions and stresses. This study aims to develop wheat genotypes, which have favorable response and tolerant for drought stress through in vitro culture and genetic polymorphism and genetic similarity of wheat genotypes by biochemical (SDS-PAGE) and RAPD-PCR as molecular marker. The genetic diversity of 25 wheat genotypes was estimated using germination characteristic under drought stress using two concentrations (-9 and -12 bar) from polyethylene glycol (PEG) in vitro and molecular analysis. The phenotypic data showed highly differences between genotypes for germination percentage. In addition, genotypes 2, 8, 13, 19, 22, 23 and 25 were more resistant for drought stress. Genetic similarity matrix was generated on the basis of Nei and Li’s coefficients. The coefficients were used to make clusters using unweighted pair group method of arithmetic means (UPGMA) which separated the studied genotypes into three main groups depending on results SDS-PAGE and RAPD-PCR combination. The first group A (similarity range 0.69 to 0.93) contains on genotypes (1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12 and 13), the second group B (similarity range 0.73 to 0.93) comprised of genotypes (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 and 25), while group C includes on genotype-4 (similarity range 0.53 to 0.72) which was distantly related to other two groups. The information generated here along with the use of most advanced DNA fingerprinting techniques like RAPDPCR would be helpful for future genome mapping programs, as well as for the application of intellectual breeder rights in Egypt. In addition, these tools could be used as complementary of traditional methods of identification of phenotypic traits for the control of registered cultivars in the trade market. This will help in collection and cataloguing of the germplasm in the form of a germplasm bank. Key wrods: Polyethylene glycol, SDS-PAGE, polyphenol oxidase, RAPD-PCR.
Semi-Supervised Machine Learning and Adaptive Data Clustering Approach for Software Defect Prediction

Software defect prediction is an important area of research due to its significant utilization in various real-time applications. The ever-increasing demand of software application has resulted in rapid development of software modules development that further has elevated the chances of faulty software production. In order to deal with this issue software testing solutions are recommended. As, manual testing require more human effort and time hence, automated testing has gained attention from industries and researchers. In this work, we present an automated software defect prediction strategy using semi-supervised machine learning approach. The complete process is divided into four main sections: pre-processing where we apply KNN based missing value imputation, feature selection where we apply PCA based optimal feature selection method, clustering where we apply SOM based clustering model and finally Naive Bayes classifier is implemented. Experimental study shows that proposed approach achieves promising performance when compared with the existing software defect prediction techniques.
Automatic Evaluation of Internal Combustion Engine Noise Based on an Auditory Model

To improve the accuracy and efficiency of the objective evaluation of noise quality from internal combustion engines, an automatic noise quality classification model was constructed by introducing an auditory model-based acoustic spectrum analysis method and a convolutional neural network (CNN) model. A band-pass filter was also designed in the model to automatically extract the features of the noise samples, which were later used as input data. The adaptive moment estimation (Adam) algorithm was used to optimize the weights of each layer in the network, and the model was used to evaluate sound quality. To evaluate the predictive performance of the CNN model based on the auditory input, a back propagation (BP) sound quality evaluation model based on psychoacoustic parameters was constructed and used as a control. When processing the label values of the samples, the correlation between the psychoacoustic parameters of the objective evaluation and evaluation scores was analyzed. Four psychoacoustic parameters with the greatest correlation with subjective evaluation results were selected as the input values of the BP model. The results showed that the sound quality evaluation model based on the CNN could predict the sound quality of internal combustion engines more accurately, and the input evaluation score based on the auditory spectrum in the CNN classification model was more accurate than the short-time average energy input evaluation score based on the time domain.
Compiler Design of a Policy Specification Language for Conditional Gradual Release

Securing the confidentiality and integrity of information manipulated by computer software is an old yet increasingly important problem. Current software permission systems present on Android or iOS provide inadequate support for developing applications with secure information flow policies. To be useful, information flow control policies need to specify declassifications and the conditions under which declassification must occur. Having these declassifications scattered all over the program makes policies hard to find, which makes auditing difficult. To overcome these challenges, a policy specification language, ‘Evidently’ is discussed that allows one to specify information flow control policies separately from the program and which supports conditional gradual releases that can be automatically enforced. I discuss the Evidently grammar and modular semantics in detail. Finally, I discuss the implementational details of Evidently compiler within the Xtext language development environment and the implementation’s enforcement of policies.
Effective Framework of Pedagogy Using the Plan-Do-Check-Act Improvement Cycle

Learning paths drive learners to proficiency by using a selected sequence of training activities under time constraints. Therefore, learners can regulate learning and give feedback for pedagogy improvements. Studying learning path evaluation provides a useful conceptual reference to enhance pedagogically. This paper proposes an approach based on the Plan-Do-Check-Act improvement cycle to systematically evaluate learning paths in learning management systems. The framework is a valuable resource that consolidates existing practices in learning management evaluation. Our approach integrates learning styles, learning profile, along with cognitive activities. The proposed framework was compared with current learning path methods. Results were competitive compared with related works. Keywords—Learning management system; learning styles; learning path; Plan-Do-Check-Act (PDCA)
Ionospheric scintillation monitoring and mitigation using a software GPS receiver

Scintillations are caused by ionospheric irregularities and affect the amplitude, phase, dispersion, and related parameters of GPS signals. Both L1 and L2 are affected in a somewhat uncorrelated fashion. Adequate understanding of the effects that ionospheric scintillation has on GPS signals is essential in order to produce a GPS receiver that is immune to the degradation of signal caused by these scintillation‐related effects. Access to the internal workings of commercial GPS receivers is not provided to users. However, in order to understand, control, and mitigate scintillation effects, it is necessary to have access to tracking loops and associated components such as local oscillator. The software GPS receiver developed by the Center for Remote Sensing, Inc. allows the user to access its internal workings; hence facilitating advanced development of GPS receivers under different conditions. In this paper we present the results of analysis of GPS signals under scintillating conditions. Raw signals under conditions of ionospheric scintillation at Ascension Island have been processed using our software GPS receiver in order to derive the scintillation parameters. The receiver has been configured to provide stable operation during scintillation. We describe the receiver architecture, particularly the portion involving the tracking filters and related components, and demonstrate their performances under scintillating conditions. The software‐based approach used by us allows receiver implementations which are suitable for ionospheric monitoring as well as for reliable operation during scintillating conditions. The improved architecture may be used for several other applications.
A STUDY ON MITOCHONDRIAL DNA HAPLOGROUPS AND CONTROL REGION SEQUENCES OF TURKISH NATIVE SHEEP BREEDS

In the present study, firstly the distribution of three mtDNA haplogroups (A, B, C) across 13 Turkish native sheep breeds was examined by RFLP and SSCP analyses. Haplogroup B, the most common type in Europe, is associated with the oldest domestication event and it is predominantly found in Turkey. The observed cline in the direction of West to EastSouth east Anatolia in an independent study is confirmed with the new data of the present study. In addition, the genetic barriers were determined by Delaunay analysis and the forth barrier lying in the middle of Anatolia (in north south direction) was noted.
Towards Unified Smart City Communication Platforms

Smart City solutions are gaining more momentum recently, motivated by the increase of population moving towards living in urban environments. The need to create a unified Smart Platform in order to overcome challenges in various domains has become an important research topic. In this paper we highlight our efforts in addressing requirements and challenges associated with building Smart City Communication platforms.
THE CONSTRUCTION OF THREE METROPOLISES A geographic , productive and configurational process

The explosive urban growth in developing countries has often resulted in social and territorial disparities, with zones well-provided with urban services, equipment and amenities for affluent groups and vast areas lacking infrastructure and services populated by the poor. This paper proposes that a configurational analysis of the urban process of metropolitan cities could shed light on the spatial mechanisms behind urban inequality. Specifically, we attempted to analyse (i) the historical urban tendencies related to changing economies and (ii) geographical constrains that determinate the suitable land for urban development. Three Chilean cities (Santiago, Valparaiso and Concepción) accommodate more than half of the national population. For each metropolitan area, a set of historical axial maps was drawn (1875, 1915, 1965 and 2015) that were analysed in relation to the geography and productive activities of the moment. With the global (HH) and local (r3) integrations, the main changes in the urban structures were identified, highlighting the migration of the centres and the characteristics of the most integrated/segregated areas. The trends of urban growth in the three cities evidence a process that starts with a geographic positioning of the city, very much in line with its economic vocation and viability, enhanced by a spatial configuration that potentiates both the geography and the economic potentials of the region. Nevertheless, when economic, social and cultural conditions vary the city adapts, centralities change and develop and in some cases the deep structure of the city changes. The configurational analysis allowed us to understand three very different cases which we believe can be compared and shed light in the development of other cities.
Posterior distributions with non explicit objective priors Distribuzioni a posteriori basate su distribuzioni a priori oggettive non esplicite

We introduce two methods useful to derive a posterior distribution for a parameter of interest, when only the first derivative of a log-prior is available. This is typically the situation when dealing with multidimensional parameters and objective priors. An example is illustrated using a predictive matching prior. Abstract In questo contributo vengono introdotti due metodi utili per derivare una distribuzione a posteriori per un parametro di interesse, quando è disponibile solo la derivata prima del logaritmo della distribuzioni a priori. Tale situazione si presenta tipicamente in presenza di parametri multidimensionali e distribuzioni a priori oggettive. Il metodo viene illustrato in un modello logistico con una matching prior predittiva.
Maximizing Spatial α-Fairness in Multi-Tier Multi-Rate Spatial Aloha Networks

We consider the maximization of α-fair utility in a generalized spatial Aloha network consisting of multiple tiers of transmitter-receiver (T-R) pairs each forming a Poisson bipolar process. The tiers are distinguished by transmission power and the T-R distance. Multi-rate communication between the T-R pairs is facilitated by multiple received signal-to-interference ratio (SIR) thresholds. We aim to optimize the transmission probability of each tier. This results in a complex non-convex optimization problem due to intra-tier and cross-tier interference. We propose a solution termed Minorize-Maximization with Tier Separation (MMTS), through designing an iterative sequence of lower bound problems that can be decomposed into tierseparable one-dimensional convex optimization problems and solved efficiently. Specific solutions are derived for the cases 0 ≤ α < 1, α = 1, and α > 1. We show the convergence of MMTS to the objective value of a Karush-Kuhn-Tucker (KKT) point of the original problem and further identify several conditions under which it finds the global optimum. Numerical results demonstrate the near optimality of MMTS and substantial performance advantage over existing alternatives.
Decoder Side Color Image Quality Enhancement using a Wavelet Transform based 3-stage Convolutional Neural Network

In this paper, we describe our submission to the work-shop and challenge on learned image compression (CLIC) hosted at CVPR 2019. Lossy compressed images usually suffer from unpleasant artifacts, especially when the bit-rate is low. In order to improve the image quality without spending extra bit-rate, decoder side quality enhancement becomes necessary. Most approaches focus on spatial information exploration and the quality enhancement is usually only performed on the luminance component, which leads to the neglect of inter-channel correlation. In addition, since compressed images mainly lose the high-frequency components, high-frequency and low-frequency components show different characteristics. Motivated by the characteristics of compressed images, a wavelet transform based 3-stage CNN is proposed in this paper. With the RGB image as input, the proposed network exploits the latent inter-channel correlations and enhances the low-frequency and high-frequency sub-band separately. Both objective and subjective evaluations show the noticeable quality improvements compared to Better Portable Graphics (BPG) and previous approaches.
Analyzing the oral speech of an Alzheimer affected person: A Case Study

This paper describes the case study of former British Prime Minister Harold Wilson’s oral interventions (19641970 and 1974-1976), potentially affected by Alzheimer disease (AD) at the time of resignation (Garrard, 2009). To pursue this research, the oral interventions of Harold Wilson are examined. One advantage of analyzing Harold Wilson is that all his Parliamentary interventions are available online (Hansard transcripts) and the context in which the speech is produced is held constant across the different years. The amount of data is divided into randomselected 25,000 words for each year of Wilson’s 10-years at office (1964-1970 and 1974-1976); totalling 250,000 tokens. To determine the extent of differences in the linguistic patterns before and after being AD affected, bigrams and trigrams are analysed in order to investigate whether different periods exhibit characteristic oral features. We are confident that this longitudinal study and pattern analysis might provide us with some new understanding of the evolution and progression of language deterioration in AD.