Miracle-dz/UniFAR-FTUs huggingface dataset:
Contour Segment Feature Weighting in Infrared Automatic Target Recognition

We study automatic target recognition (ATR) in infrared (IR) imagery by applying two recent computer vision techniques, Hierarchical description of contour and Bag-of-Words (BoW). We propose the idea of contour segment (CS) features which are extracted from the outer contour of IR target image and we developed a new weighted scalable vocabulary tree (SVT) that is learned from a set of training images to support efficient and scalable Bow-based ATR. We develop a weighted BoW model to improve the ATR performance by the feature weighting. Different from traditional BoW model, the saliency information is incorporated into feature weighting to enhance the voting confidance in Bow-based classification. The proposed CS features weighting ATR algorithm is evaluated against recent relevance grouping of vocabulary (RGV) approaches that reportedly outperform traditional methods. Experimental results on dedicated IR dataset demonstrate the advantages of the newly proposed algorithm outperform the baseline BoW method and the recent RGV approach.
A Parallel Programmer for Non-Volatile Analog Memory Arrays

A Parallel Programmer for Non-Volatile Analog Memory Arrays by Spencer L. Clites Master of Science in Electrical Engineering West Virginia University David W. Graham, Ph.D., Chair Since their introduction in 1967, floating-gate transistors have enjoyed widespread success as non-volatile digital memory elements in EEPROM and flash memory. In recent decades, however, a renewed interest in floating-gate transistors has focused on their viability as non-volatile analog memory, as well as programmable voltage and current sources. They have been used extensively in this capacity to solve traditional problems associated with analog circuit design, such as to correct for fabrication mismatch, to reduce comparator offset, and for amplifier auto-zeroing. They have also been used to implement adaptive circuits, learning systems, and reconfigurable systems. Despite these applications, their proliferation has been limited by complex programming procedures, which typically require high-precision test equipment and intimate knowledge of the programmer circuit to perform. This work strives to alleviate this limitation by presenting an improved method for fast and accurate programming of floating-gate transistors. This novel programming circuit uses a digitalto-analog converter and an array of sample-and-hold circuits to facilitate fast parallel programming of floating-gate memory arrays and eliminate the need for high accuracy voltage sources. Additionally, this circuit employs a serial peripheral interface which digitizes control of the programmer, simplifying the programming procedure and enabling the implementation of software applications that obscure programming complexity from the end user. The efficient and simple parallel programming system was fabricated in a 0. 5μm standard CMOS process and will be used to demonstrate the effectiveness of this new method. A Parallel Programmer for Non-Volatile Analog Memory Arrays
A BENCHMARK LOW VOLTAGE MICROGRID NETWORK

The increasing penetration of distributed generation resources to the low voltage (LV) grids, such as photovoltaics, CHP micro-turbines, small wind turbines in certain areas and possibly fuel cells in the near future, alters the traditional operating principle of the grids. A particularly promising aspect, related to the proliferation of small-scale decentralized generation, is the possibility for parts of the network comprising sufficient generating resources to operate in isolation from the main grid, in a deliberate and controlled way. These are called Microgrids and the study and development of technology to permit their efficient operation has recently started with a great momentum ([1,2]). Microgrids are foreseen within public distribution grids and therefore suitable study case networks are required to perform simulation and analysis tasks. Moreover, standardizing study case grids to provide “benchmark” networks suitable for Microgrid design would further enhance their merit and utility. The objective of this paper is to present and discuss a benchmark LV network developed within the EU project “Microgrids”, Contract ENK5-CT-2002-00610 and later adopted as a benchmark LV system by CIGRE TF C6.04. 02: “Computational Tools and Techniques for Analysis, Design and Validation of Distributed Generation Systems”. The network consists of an LV feeder, while a more extended multi-feeder version is also included in the Appendix. The emphasis is placed on the network itself, rather than on the microsources connected and the control concepts applied. The benchmark network maintains the important technical characteristic of real utility grids, whereas, at the same time, it dispenses with the complexity of actual networks, to permit efficient modeling and simulation of microgrid operation.
La reconnaissance des visages et de leurs expressions faciales au cours du vieillissement normal et dans les pathologies neurodegeneratives Processing facial identity and emotional expression in normal aging and neurodegenerative diseases

The ability to recognize facial identity and emotional facial expression is central to social relationships. This paper reviews studies concerning face recognition and emotio- nal facial expression during normal aging as well as in neurodegenerative diseases occur- ring in the elderly. It focuses on Alzheimer's disease, frontotemporal and semantic dementia, and also Parkinson's disease. The results of studies on healthy elderly indivi- duals show subtle alterations in the recognition of facial identity and emotional facial expression from the age of 50 years, and increasing after 70. Studies in neurodegenerative diseases show that - during their initial stages - face recognition and facial expression can be specifically affected. Little has been done to assess these difficulties in clinical practice. They could constitute a useful marker for differential diagnosis, especially for the clinical differentiation of Alzheimer's disease (AD) from frontotemporal dementia (FTD). Social dif- ficulties and some behavioural problems observed in these patients may, at least partly, result from these deficits in face processing. Thus, it is important to specify the possible underlying anatomofunctional substrates of these deficits as well as to plan suitable reme- diation programs.
Heterogeneous versus Homogeneous Machine Learning Ensembles

Abstract The research demonstrates efficiency of the heterogeneous model ensemble application for a cancer diagnostic procedure. Machine learning methods used for the ensemble model training are neural networks, random forest, support vector machine and offspring selection genetic algorithm. Training of models and the ensemble design is performed by means of HeuristicLab software. The data used in the research have been provided by the General Hospital of Linz, Austria.
What Makes Sound Patterns Expressive?: The Poetic Mode of Speech Perception

Poets, academics, and those who simply speak a language are subject to mysterious intuitions about the perceptual qualities and emotional symbolism of the sounds of speech. Such intuitions are Reuven Tsur’s point of departure in this investigation into the expressive effect of sound patterns, addressing questions of great concern for literary theorists and critics as well as for linguists and psychologists. Research in recent decades has established two distinct types of aural perception: a nonspeech mode, in which the acoustic signals are received in the manner of musical sounds or natural noises; and a speech mode, in which acoustic signals are excluded from awareness and only an abstract phonetic category is perceived. Here, Tsur proposes a third type of speech perception, a poetic mode in which some part of the acoustic signal becomes accessible, however faintly, to consciousness. Using Roman Jakobson’s model of childhood acquisition of the phonological system, Tsur shows how the nonreferential babbling sounds made by infants form a basis for aesthetic valuation of language. He tests the intersubjective and intercultural validity of various spatial and tactile metaphors for certain sounds. Illustrating his insights with reference to particular literary texts, Tsur considers the relative merits of cognitive and psychoanalytic approaches to the emotional symbolism of speech sounds.
Psihometrijska provera i validacija upitnika afektivnih stilova na srpskom uzorku

This paper presents the results of two validation studies of a Serbian translation of the Affective Styles Questionnaire (ASQ; Hofmann & Kashdan, 2010). The aim of the first study was to explore the internal consistency and predictive validity of the instrument. The sample consisted of 1633 students of the University of Novi Sad. The results confirmed the original factor structure i.e., the dimensions of Concealing (emotional regulation strategies aimed to conceal and suppress affect), Adjusting (strategies aimed to successfully adapt to the situation), and Tolerating (strategies of tolerance and acceptance of emotions). The Concealing and Adjusting subscales manifested highly acceptable coefficients of internal consistency, while the coefficient for Tolerance did not meet the criterion for acceptability. The highly acceptable predictive validity of the instrument was confirmed by correlations with depression, anxiety and stress scores of the DASS-21 questionnaire. The second study explored the correlations of the instrument's subscales with the concurrent measures of emotional regulation in order to test the instrument's concurrent validity. The sample consisted of 150 participants, including healthy people, people with psychosomatic complaints, and those suffering from hypertension and/or gastritis due to an organic disorder. Correlations with the Emotional Regulation Questionnaire (ERQ) scores, as well as with the Cognitive Emotional Regulation Questionnaire (CERQ) and the Toronto Alexithymia Scale (TAS) scores were consistent with the theoretical expectations, suggesting high validity of the instrument. Overall, results confirmed the applicability of the instrument, also suggesting a need for future research focused on exploration of the subtle cultural specificities in emotional regulation of the local population.
Navigation performances of a blind sailor using a haptic and auditory cartographic system on board

In this case study, we investigated the influence of two displays in a haptic and auditory navigation tool used on board by a blind sailor. The displays differed in their spatial frames of reference. We assessed the control and representation of his course after having used a force feed-back device as a maritime cane (i.e. egocentric) or as a mean to conventionally consult an updated geographic information system (i.e. allocentric). Results tended to show that the egocentric condition was better for precise course control and the allocentric one more efficient for building an accurate mental representation.
Unwinding the relative Tate diagonal

We show that a spectral sequence developed by Lipshitz and Treumann, for application to Heegaard Floer theory, converges to a localized form of topological Hochschild homology with coefficients. This allows us to show that the target of this spectral sequence can be identified with Hochschild homology when the topological Hochschild homology is torsion‐free as a module over THH∗(F2) , parallel to results of Mathew on degeneration of the Hodge‐to‐de Rham spectral sequence.
Multi-Ontology Refined Embeddings (MORE): A Hybrid Multi-Ontology and Corpus-based Semantic Representation for Biomedical Concepts

Objective: Currently, a major limitation for natural language processing (NLP) analyses in clinical applications is that a concept can be referenced in various forms across different texts. This paper introduces Multi-Ontology Refined Embeddings (MORE), a novel hybrid framework for incorporating domain knowledge from multiple ontologies into a distributional semantic model, learned from a corpus of clinical text. Materials and Methods: We use the RadCore and MIMIC-III free-text datasets for the corpus-based component of MORE. For the ontology-based part, we use the Medical Subject Headings (MeSH) ontology and three state-of-the-art ontology-based similarity measures. In our approach, we propose a new learning objective, modified from the Sigmoid cross-entropy objective function. Results and Discussion: We evaluate the quality of the generated word embeddings using two established datasets of semantic similarities among biomedical concept pairs. On the first dataset with 29 concept pairs, with the similarity scores established by physicians and medical coders, MORE's similarity scores have the highest combined correlation (0.633), which is 5.0% higher than that of the baseline model and 12.4% higher than that of the best ontology-based similarity measure.On the second dataset with 449 concept pairs, MORE's similarity scores have a correlation of 0.481, with the average of four medical residents' similarity ratings, and that outperforms the skip-gram model by 8.1% and the best ontology measure by 6.9%.
End-to-End Memory-Enhanced Neural Architectures for Automatic Speech Recognition

In this project, we seek to explore the integration of external memory into end-to-end neural architectures for Automatic Speech Recognition (ASR). Though memorybased networks have recently proven to be quite successful across a variety of tasks in other domains, to the best of our knowledge there have been no previous attempts to apply such models to the challenge of spoken language processing. We thus propose a novel neural system that explicitly incorporates external memory modules into an encoder-decoder framework, where we aim to predict character-level outputs from audio-level features over the Wall Street Journal (WSJ0), CHIME, and TIDIGITS corpora. Though our ultimate memory models do not quite surpass the performance of our pure attention-based models, our results are quite promising and perhaps indicate that with proper fine-tuning these networks could obtain superlative performance on ASR tasks. We believe there is much potential for future development and look forward to performing continued research in this area.
Evaluating a Coherence-Based Model of Pronoun Interpretation

We describe two pronoun interpretation experiments in which a Cohere nce Hypothesis is tested against preference-based accounts. The Coherence Hypothesis hold that apparent preferences in antecedent selection are actually byproducts of the infere ncing processes used to establish different types of coherence. In Experiment 1 we s how that preferences can be systematically disrupted through the manipulation of coherence and t h t when the relevant factors are balanced, preferences disappear. In Experiment 2 we s ho that the coherence effect is not disrupted by voice alternations (active/passiv e), providing evidence for a strong semantic model of coherence-driven interpretation. We speculate on he adequacy of this strong semantic model and propose additional online experiments to exa min the interaction between propositional content and information structure influence s on pronoun interpretation.
Computing path integrals using Lefschetz thimbles

Finding minima of functions S is of great physical importance. In particular, in quantum field theory calculating vacuum expectation values in spontaneously broken systems or finding classical equations of motions. For example if S : R→ R has a unique minimum xmin, then Laplace’s method (if applicable) gives xmin = lim λ→∞ ∫ R dx xe −λS ∫ R dx e −λS . We review a technique applicable to more general S by decomposing the integrals into ones over so called Lefschetz thimbles. This basically reduces to the previous situation with a unique minimum. As applications to the theory we choose the Airy function and a function motivated by the Gross-Neveu model. Zusammenfassung Das Finden von Minima von Funktionen S hat große physikalische Bedeutung. Insbesondere, wenn man Vakuum Erwartungswerte in der Quantenfeldtheorie für spontan gebrochene Systeme oder klassische Bewegungsgleichungen berechnet. Zum Beispiel, wenn S : R→ R genau ein Minimum bei xmin besitzt, dann liefert Laplace’s Methode (wenn anwendbar) xmin = lim λ→∞ ∫ R dx xe −λS ∫ R dx e −λS . Wir werden eine Methode lernen, die auf allgemeine S anwendbar ist. Dabei werden die Integrale in Summen einfacherer Integrale über sogenannte Lefschetz-Fingerhüte zerlegt. Damit reduziert man die Situation auf den Fall mit eindeutigem Minimum. Als Anwendung wählen wir die Airy-Funktion und eine Funktion, die vom GrossNeveu-Modell motiviert ist.
Coal sludge and their mixtures as prospective
energy resources

The new legislative provisions, regulating the solid fuel trade in Poland, and the resolutions of provincial assemblies assume, inter alia, a ban on the household use of lignite fuels and solid fuels produced with its use; this also applies to coal sludge, coal flotation concentrates, and mixtures produced with their use. These changes will force the producers of these materials to find new ways and methods of their development, including their modification (mixing with other products or waste) in order to increase their attractiveness for the commercial power industry. The presented paper focuses on the analysis of coal sludge, classified as waste (codes 01 04 12 and 01 04 81) or as a by-product in the production of coals of different types. A preliminary analysis aimed at presenting changes in quality parameters and based on the mixtures of hard coal sludge (PG SILESIA) with coal dusts from lignite (pulverized lignite) (LEAG) has been carried out. The analysis of quality parameters of the discussed mixtures included the determination of the calorific value, ash content, volatile matter content, moisture content, heavy metal content (Cd, Tl, Hg, Sb, As, Pb, Cr, Co, Cu, Mn, Ni, and W), and sulfur content. The preliminary analysis has shown that mixing coal sludge with coal dust from lignite and their granulation allows a product with the desired quality and physical parameters to be obtained, which is attractive to the commercial power industry. Compared to coal sludge, granulates made of coal sludge and coal dust from lignite with or without ground dolomite have a higher sulfur content (in the range of 1–1.4%). However, this is still an acceptable content for solid fuels in the commercial power industry. Compared to the basic coal sludge sample, the observed increase in the content of individual toxic components in the mixture samples is small and it therefore can be concluded that the addition of coal dust from lignite or carbonates has no significant effect on the total content of the individual elements. The calorific value is a key parameter determining the usefulness in the power industry. The size of this parameter for coal sludge in an as received basis is in the range of 9.4–10.6 MJ/kg. In the case of the examined mixtures of coal sludge with coal dust from lignite, the calorific value significantly increases to the range of 14.0–14.5 MJ/kg (as received). The obtained values increase the usefulness in the commercial power industry while, at the same time, the requirements for the combustion of solid fuels are met to a greater extent. A slight decrease in the calorific value is observed in the case of granulation with the addition of CaO or carbonates. Taking the analyzed parameters into account, it can be concluded that the prepared mixtures can be used in the combustion in units with flue gas desulfurization plants and a nominal thermal power not less than 1 MW. At this stage of work no cost analysis was carried out.
Brain-Controlled for Changing Modular Robot Configuration by Employing Neurosky’s Headset

Currently, the Brain Computer Interfaces (BCI) system was designed mostly to be implemented for control purpose or navigation which are mostly being employed for mobile robot, manipulator robot and humanoid robot by using Motor Imagery. This study presents an implementation of BCI system to Modular Self-Reconfigurable (MSR) Dtto robot so the robot able to propagate multiple configurations based on EEG-based brain signals. In this paper, a Neurosky’s Mindwave Mobile EEG headset is being used and a framework of controlling the Dtto robot by EEG signals, processed by OpenViBE software are built. The connection being established between Neurosky’s headsets to the OpenViBE, where a Motor Imagery BCI is created to receive and process the EEG data in real time. The main idea for system developed is to associate a direction (Left, Right, Up and Down) based on Hand and Feet Motor Imagery as a command for Dtto robot control. The Direction from OpenViBE were sent via Lab Streaming Layer (LSL) and transmitted via Python software to Arduino controller in the robots. To test the system performance, this study was conducted in Real time experiments. The results are being discussed in this paper.
Investigating the Manual View Specification and Visualization by Demonstration Paradigms for Visualization Construction

Interactivity plays an important role in data visualization. Therefore, understanding how people create visualizations given different interaction paradigms provides empirical evidence to inform interaction design. We present a two‐phase study comparing people's visualization construction processes using two visualization tools: one implementing the manual view specification paradigm (Polestar) and another implementing visualization by demonstration (VisExemplar). Findings of our study indicate that the choice of interaction paradigm influences the visualization construction in terms of: 1) the overall effectiveness, 2) how participants phrase their goals, and 3) their perceived control and engagement. Based on our findings, we discuss trade‐offs and open challenges with these interaction paradigms.
ATLAS ATLAS ATLAS ATLAS ATLAS ATLAS ATLAS Ripe Atlas Probe Medium AS 6 ATLAS AS 9 AS 7 AS 10 Medium AS 8 ATLASATLAS ATLAS

Spam messages are often used to propagate malware, to disseminate phishing exploits, and to advertise illegal products. Those messages generate costs for users and network operators, but it is hard to measure how much of their costs are associated with spam traffic, and who actually pays for it. In this work, we provide a method to quantify the transit costs of spam traffic. We identify the routes traversed by spam messages collected at five honeypots. Combining the volume of spam traffic with traceroute measurements and a database of inter-network business relationships, we show that stub networks are systematically subject to high spam traffic costs. Furthermore, we show that some networks profit from spam traffic and might not be interested in filtering spam. Finally, we present a simple but effective algorithm to identify the networks that would benefit in cooperating to filter spam traffic at the origin to reduce transit costs. Keywords-Electronic mail, Network topology, Measurement techniques.
First-Order Logic for Flow-Limited Authorization

We present the Flow-Limited Authorization First-Order Logic (FLAFOL), a logic for reasoning about authorization decisions in the presence of information-flow policies. We formalize the FLAFOL proof system, characterize its proof-theoretic properties, and develop its security guarantees. In particular, FLAFOL is the first logic to provide a non-interference guarantee while supporting all connectives of first-order logic. Furthermore, this guarantee is the first to combine the notions of non-interference from both authorization logic and information-flow systems. All the theorems in this paper are proven in Coq.