Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a scheduling application using fuzzy temporal constraints

The main objective of this research is the development of a temporal reasoning system able to manage qualitative and quantitative information also affected by vagueness and uncertainty; this is, in fact, the usual way in which temporal information about the external reality reaches us. A well-known method for modelling temporal reasoning problems is CSP. A limit of this method is its intractability, and there are two directions that can be considered in order to reduce the computational complexity: the first is the development of heuristic techniques that prune the search space, the second is the definition of tractable sub-algebras to work with. Classic CSPs are based on crisp constraints (i. e. constraints that are either completely satisfied or violated), for this reason over-constrained problems do not have solution while under-constrained problems have multiple solutions. Furthermore CSPs can not express uncertain or vague information. The above limits can be overcome using the FCSP theory (Dubois et al., 1996) that replaces the crisp constraints with fuzzy relations, that is constraints extended with possibility distributions; these distribution allow the auto-relaxation of the constraints in the over-constrained problems and add an order among multiple solutions of the under-constrained problems. Dealing with a real scheduling problem, two types of constraints may be present: qualitative and quantitative. As far as the qualitative constraints are concerned, the classic framework is the Allen’s algebra (Allen, 1983); here the temporal entities are intervals and there are 13 atomic disjunctive relations. As far as the quantitative constraints are concerned, the main classical model is that proposed by (Dechter et al., 1991). Real problems are usually affected by vagueness and uncertainty, because a problem can be known partially and/or in a imprecise manner. So it is important include in a scheduling system fuzzy information.
Big Data Analysis Model for MRO Business Using Artificial Intelligence System Concept

The rapidly changing environment of the shipbuilding industry has put Korea’s shipbuilding industry in a crisis. The purpose of this study was to develop a business model to maintain, maintain and operate Big Data-based MRO(Maintenance, Repair, and Operation) consumables, which is expected to be the new growth engine for the domestic shipbuilding industry. Although Korean shipbuilders have world-class technologies for ship dogma, the market for ship maintenance and repair is still in its infancy. For Korean shipbuilders, MRO business can be a growth engine that will provide food for the next 30 years, but to do so, we need to make sure that everything that happens in the entire process, from ship design to maintenance and maintenance. Therefore, by systematically establishing Big Data related to components and developing MRO business models based on data analysis capabilities using Artificial Intelligence system concept, we can develop new growth engines for related industries in Ship Industry.
0 PO INFORMATIK Weak E-nets for Points on a Hypersphere

A weak e-net for a set of points M, is a set of points W (not necessarily in M) where every convex set containing eiMI points in M must contain at least one point in W. Weak e-nets have applications in diverse areas such as computational geometry, learning theory, optimization and statistics. Here we show that, if M is a set of points quasi-uniformly distributed on a unit sphere sd-l, then there is a weak €-net w ~ JRd of size o((d 2 lo,d)k") log(kd/e)log(l/e)) for M, where kd is exponential in d. A set of points M is quasi-uniformly distributed on sd-l, if for any spherical cap C ~ sd-l with Vol(C) ~ c1/IMI, we have c2 Vol(C) ~ IC n Ml ~ c3 Vol(C) for three positive constants c1, c2, and c3. Further, we show that reducing our upper bound by asymptotically more than a log(l/e) factor directly implies the solution of a long unsolved problem of Danzer and Rogers.
Intelligent sensor fault detection and identification for temperature control

This paper addresses artificial intelligence and signal processing based online fault detection and identification. Fuzzy logic controller has been utilized for temperature control. Faults often cause undesired reactions, so to keep the system stable and to obtain an acceptable control performance is an important problem for control system design. In this paper, a multiplicative, an additive and a disturbance type of Termocouple sensor faults have been examined for temperature control. Feature vector of the sensor faults has been constructed using a statistical analysis. For classifier of the feature vector the Self Organizing Map (SOM) has been used. So sensor fault can be detected and identified using feature vector.
Decentralized College Admissions

We study decentralized college admissions with uncertain student preferences. Colleges strategically admit students likely to be overlooked by competitors. Highly ranked students may receive fewer admissions or have a higher chance of receiving no admissions than those ranked below. When students’ attributes are multidimensional, colleges avoid head-on competition by placing excessive weight on school-specific attributes such as essays. Restricting the number of applications or wait-listing alleviates enrollment uncertainty, but the outcomes are inefficient and unfair. A centralized matching via Gale and Shapley’s deferred acceptance algorithm attains efficiency and fairness but may make some colleges worse off than under decentralized matching.
IL-21 Receptor Expression in Human Tendinopathy

The pathogenetic mechanisms underlying tendinopathy remain unclear, with much debate as to whether inflammation or degradation has the prominent role. Increasing evidence points toward an early inflammatory infiltrate and associated inflammatory cytokine production in human and animal models of tendon disease. The IL-21/IL-21R axis is a proinflammatory cytokine complex that has been associated with chronic inflammatory diseases including rheumatoid arthritis and inflammatory bowel disease. This project aimed to investigate the role and expression of the cytokine/receptor pair IL-21/IL-21R in human tendinopathy. We found significantly elevated expression of IL-21 receptor message and protein in human tendon samples but found no convincing evidence of the presence of IL-21 at message or protein level. The level of expression of IL-21R message/protein in human tenocytes was significantly upregulated by proinflammatory cytokines (TNFα/IL-1β) in vitro. These findings demonstrate that IL-21R is present in early human tendinopathy mainly expressed by tenocytes and macrophages. Despite a lack of IL-21 expression, these data again suggest that early tendinopathy has an inflammatory/cytokine phenotype, which may provide novel translational targets in the treatment of tendinopathy.
Three-Point Functions in N=4 SYM Theory at One-Loop

We analyze the one-loop correction to the three-point function coefficient of scalar primary operators in N=4 SYM theory. By applying constraints from the superconformal symmetry, we demonstrate that the type of Feynman diagrams that contribute depends on the choice of renormalization scheme. In the planar limit, explicit expressions for the correction are interpreted in terms of the hamiltonians of the associated integrable closed and open spin chains. This suggests that at least at one-loop, the planar conformal field theory is integrable with the anomalous dimensions and OPE coefficients both obtainable from integrable spin chain calculations. We also connect the planar results with similar structures found in closed string field theory.
Effects of ship noise on the detectability of communication signals in the Lusitanian toadfish

SUMMARY Underwater noise pollution is an increasing environmental problem which might affect communication, behaviour, fitness and consequently species' survival. The most common anthropogenic noises in aquatic habitats derive from shipping. In the present study we investigated the implications of noise pollution from a ship on the sound detectability, namely of conspecific vocalizations in the Lusitanian toadfish, Halobatrachus didactylus. Ambient and ferry-boat noises were recorded in the Tagus River estuary (Portugal), as well as toadfish sounds, and their sound pressure levels determined. Hearing sensitivities were measured under quiet lab conditions and in the presence of these masking noises at levels encountered in the field, using the auditory evoked potentials (AEP) recording technique. The Lusitanian toadfish is a hearing generalist, with best hearing sensitivity at low frequencies between 50 and 200 Hz (below 100 dB re. 1 μPa). Under ambient noise conditions, hearing was only slightly masked at lower frequencies. In the presence of ship noise, auditory thresholds increased considerably, by up to 36 dB, at most frequencies tested. This is mainly because the main energies of ferry-boat noise were within the most sensitive hearing range of this species. Comparisons between masked audiograms and sound spectra of the toadfish's mating and agonistic vocalizations revealed that ship noise decreased the ability to detect conspecific acoustic signals. This study provides the first evidence that fishes' auditory sensitivity can be impaired by ship noise and that acoustic communication, which is essential during agonistic encounters and mate attraction, might be restricted in coastal environments altered by human activity.
Triangulation within and across HCI disciplines

How should we evaluate interactive software? Gray and Salzman (1998) examine five influential studies that compare methods of evaluating usability. In a carefully-argued critique, they identify numerous threats to validity and point out serious flaws in both the designs and claims made in each study. I think there will be various reactions to this article. Some people will react with alarm, concerned that if frequently-cited articles in respected publications are so full of errors, perhaps the field of human-computer interaction is in serious trouble. Others may attack the article, mis-interpreting it as the blind application of laboratory-style experiments to field studies. My own reaction is to commend Gray and Salzman for daring to critique some of the most influential work in the field, showing not only how to identify certain kinds of problems, but also how to address them. Their study helps to advance the field by raising the level of critical analysis in a graceful and constructive manner. This is how research disciplines make progress: through self-analysis and the creation of a solid research context.
THE PERFORMANCE OF SIR-BASED HYBRID LINK ADAPTATION ALGORITHMS IN MOBILE RADIO NETWORKS

SUMMARY In this article we have described and simulated new SIR-frame based link adaptation algorithms. Algorithms were designed to increase efficiency of data transmission among user equipment and base stations (uplink). Simulation results of hybrid adaptation (power and modulation BPSK, QPSK, 16-QAM, 64-QAM) are compared and expressed as data throughput and outage probability for different simulation environments (pedestrian channel with mobile subscriber speed 10 km/s and vehicular channel with speed 120 km/h).
Visual Control of Burst Priming in the Anesthetized Lateral Geniculate Nucleus

Thalamic relay cells fire bursts of action potentials. Once a long hyperpolarization “primes” (deinactivates) the T-type calcium channel, a depolarizing input will “trigger” a calcium spike with a burst of action potentials. During sleep, bursts are frequent, rhythmic, and nonvisual. Bursts have been observed in alert animals, and burst timing is known to carry visual information under light anesthesia. We extend this finding by showing that bursts without visual triggers are rare. Nevertheless, if the channel were primed at random with respect to the stimulus, then bursts would have the same visual significance as single spikes. We find, however, that visual signals influence when the channel is primed. First, natural time-varying stimuli evoke more bursts than white noise. Second, specific visual stimuli reproducibly elicit bursts, whereas others reliably elicit single spikes. Therefore, visual information is encoded by the selective tagging of some responses as bursts. The visual information attributable to visual priming (as distinct from the information attributable to visual triggering of the bursts) was two bits per burst on average. Although bursts are reportedly rare in alert animals, this must be investigated as a function of visual stimulus. Moreover, we propose methods to measure the extent of both visual triggering and visual priming of bursts. Whether or not bursts are rare, our methods could help determine whether bursts in alert animals carry a distinct visual signal.
Applying Internal Interface Diversification to IoT Operating Systems

Internet of Things (IoT) currently covers billions of devices with identical internal software interfaces. This software monoculture exposes the systems to the same security vulnerabilities. Internal interface diversification, by introducing diverse and unique interfaces on each device, is a solution for this problem. In this paper, we discuss interface diversification in the context of IoT operating system. We study internal interfaces of ten different operating systems to gauge the feasibility of diversification in IoT environment. This discussion brings us closer to practical diversification implementations for IoT operating systems.
A study of early career teachers’ practices related to language and language diversity during mathematics instruction

ABSTRACT The role of language in mathematics teaching and learning is increasingly highlighted by standards and reform movements in the US. However, little is known about teachers’, and especially early career teachers’ (ECTs) practices and understandings related to language in mathematics instruction. This multiple case study explored the language-related understandings and practices of six ECTs in diverse elementary classrooms. Using iterative cycles of analysis, we found that all ECTs regularly attended to students’ mathematical vocabulary use and development. Yet, there was variability in ECTs’ focus on how to teach mathematical vocabulary, expectations for students’ precise use of mathematical terminology, and the use of multiple languages during instruction. These findings indicate that ECTs need more targeted support during teacher preparation and early career teaching in order to better support all students’ language development in the mathematics classroom.
Multi-task GLOH feature selection for human age estimation

In this paper, we propose a novel age estimation method based on gradient location and orientation histogram (GLOH) descriptor and multi-task learning (MTL). The GLOH, one of the state-of-the-art local descriptor, is used to capture the age-related local and spatial information of face image. As the extracted GLOH features are often redundant, MTL is designed to select the most informative GLOH bins for age estimation problem, while the corresponding weights are determined by ridge regression. This approach largely reduces the dimensions of feature, which can not only improve performance but also decrease the computational burden. Experiments on the public available FG-NET database show that the proposed method can achieve comparable performance over previous approaches while using much fewer features.
Predictive Model of Insolvency Risk for Australian Corporations

This paper describes the development of a predictive model for corporate insolvency risk in Australia. The model building methodology is empirical with out-of-sample future year test sets. The regression method used is logistic regression after pre-processing by quantisation of interval (or numeric) attributes. We show that logistic regression matches the performance of ensemble methods, such as random forests and ada boost, provided that pre-processing and variable selection is performed. A distinctive feature of the insolvency risk model described in this paper is its breadth; since we are using income tax return data we are able to risk score one million companies across all industries, all corporation types (public, private) and all sizes, as measured either by assets or number of employees. This is an application paper that uses standard credit scoring methodology on a new data source. The contribution is to demonstrate that insolvency risk can be estimated using income tax return data. The corporate insolvency prediction model is still in development and so we welcome suggestions for improvements on the current methodology.
Cumulative-Separable Codes

q-ary cumulative-separable $\Gamma(L,G^{(j)})$-codes $L=\{ \alpha \in GF(q^{m}):G(\alpha )\neq 0 \}$ and $G^{(j)}(x)=G(x)^{j}, 1 \leq i\leq q$ are considered. The relation between different codes from this class is demonstrated. Improved boundaries of the minimum distance and dimension are obtained.
Section Ii‐ Exercise Physiology & Sports Medicine Left Atrial Enlargement in Young High‐level Endurance Athletes – Another Sign of Athlete's Heart?

Enlargement of the left atrium is perceived as a part of athlete's heart syndrome, despite the lack of evidence. So far, left atrial size has not been assessed in the context of exercise capacity. The hypothesis of the present study was that LA enlargement in athletes was physiological and fitness-related condition. In addition, we tried to assess the feasibility and normal values of left atrial strain parameters and their relationship with other signs of athlete's heart. The study group consisted of 114 international-level rowers (17.5 ± 1.5 years old; 46.5% women). All participants underwent a cardio-pulmonary exercise test and resting transthoracic echocardiography. Beside standard echocardiographic measurements, two dimensional speckle tracking echocardiography was used to assess average peak atrial longitudinal strain, peak atrial contraction strain and early left atrial diastolic longitudinal strain. Mild, moderate and severe left atrial enlargement was present in 27.2%, 11.4% and 4.4% athletes, respectively. There were no significant differences between subgroups with different range of left atrial enlargement in any of echocardiographic parameters of the left ventricle diastolic function, filling pressure or hypertrophy. A significant correlation was found between the left atrial volume index and maximal aerobic capacity (R > 0.3; p < 0.001). Left atrial strain parameters were independent of atrial size, left ventricle hypertrophy and left ventricle filling pressure. Decreased peak atrial longitudinal strain was observed in 4 individuals (3.5%). We concluded that LA enlargement was common in healthy, young athletes participating in endurance sport disciplines with a high level of static exertion and was strictly correlated with exercise capacity, therefore, could be perceived as another sign of athlete's heart.
The metabolic syndrome, cardiopulmonary fitness, and subcutaneous trunk fat as independent determinants of arterial stiffness: the Amsterdam Growth and Health Longitudinal Study.

BACKGROUND The mechanisms that link the metabolic syndrome to increased cardiovascular risk are incompletely understood, especially in young people. We therefore examined whether the metabolic syndrome was associated with arterial stiffness and whether any such associations were independent of cardiopulmonary fitness and subcutaneous trunk fat. METHODS Cross-sectional analyses of data on 364 men and women aged 36 years from the Amsterdam Growth and Health Longitudinal Study (ninth follow-up measurement, year 2000). The prevalence of the metabolic syndrome was defined by a slightly modified National Cholesterol Education Program (NCEP) definition. Arterial stiffness was ultrasonically estimated by distensibility and compliance of the carotid, femoral, and brachial arteries and by the carotid elastic modulus. RESULTS The prevalence of the metabolic syndrome in this young adult population was 18.3% in men and 3.2% in women. Individuals with the syndrome compared with individuals without risk factors had 11.2% and 17.0% less distensibility and 9.0% and 18.2% less compliance of the carotid and femoral arteries, respectively, and 15.9% higher carotid elastic modulus. After adjustment for cardiopulmonary fitness and subcutaneous trunk fat, the metabolic syndrome remained significantly associated with stiffness of the carotid but not the femoral artery. In addition, poor cardiopulmonary fitness and high subcutaneous trunk fat were associated with arterial stiffness, and this was independent of the metabolic syndrome. CONCLUSIONS A modified NCEP definition of the metabolic syndrome identified young individuals with increased arterial stiffness. The mechanisms that link the metabolic syndrome, poor cardiopulmonary fitness, and high subcutaneous trunk fat to greater arterial stiffness overlap but are partly independent of each other.
The ZeeRO Mobile RobotA Modular Architecture

This paper presents the general architecture of the ZeeRO mobile robot, with an emphasis on its main modules: navigation, sensors and data processing. The interface with the Player server that allows simulations in 2D (Stage) or 3D (Gazebo) is also presented. The last part of the paper presents some applications for this mobile robot, some of the performed tests and also some of the future plans for the extension of the current architecture.
Development of Nano-Carbon Biosensors Using Glycan for Host Range Detection of Influenza Virus

Nano-carbon materials are promising canidates for applications in high performance devices, including highly sensitive biosensors. We have developed a self-alignment process for nano-carbon field effect transistors (FETs), using a carbon nanowall (CNW)—a nano-carbon materials—to fabricate CNW-FETs. We measured the pH dependence of the device properties. The binding molecules are known to be key components for biosensors. We are concentrating on the development of an influenza virus sensor, because the influenza virus is a major public health problem and a highly sensitive sensor is urgently required. We estimated the size of detected molecules of glycan for influenza viruses using atomic force microscopy. The typical molecule size is around 1 nm, and this may be suitable for electronic detection using a FET structure.
Some E-optimal Designs for cDNA Microarray Experiments

In this paper, optimal incomplete block designs were determined for cDNA microarray experiments, where arrays are blocks, block size is always two, and the number of blocks or arrays available is approximately equal to the number of samples. A new class of designs, the mixed designs, which are a mixture of reference and loop designs, have been identified and their optimality has been proven in terms of Eoptimality.