Miracle-dz/UniFAR-FTUs huggingface dataset:
Traversable region detection with a learning framework

In this paper, we present a novel learning framework for traversable region detection. Firstly, we construct features from the super-pixel level which can reduce the computational cost compared to pixel level. Multi-scale super-pixels are extracted to give consideration to both outline and detail information. Then we classify the multiple-scale super-pixels and merge the labels in pixel level. Meanwhile, we use weighted ELM as our classifier which can deal with the imbalanced class distribution since we only assume that a small region in front of robot is traversable at the beginning of learning. Finally, we employ the online learning process so that our framework can be adaptive to varied scenes. Experimental results on three different style of image sequences, i.e. shadow road, rain sequence and variational sequence, demonstrate the adaptability, stability and parameter insensitivity of our method to the varied scenes and complex illumination.
ANN for prediction of Area and Production of Maize crop for Upper Brahmaputra Valley Zone of Assam

It is very important to have accurate, reliable and timely information on crop Area, crop Production and land use for making certain important decisions by the planners and policy makers for the development of agriculture. The present study is carried out to predict the crop Area and crop Production (Maize) of Upper Brahmaputra Valley Zone of Assam using Artificial Neural Networks (ANNs). Multilayer Perceptron (MLP) with single hidden layer and Radial Basis Function (RBF) network have been trained with the secondary data of the Area, Maize Production and meteorological data obtained from various sources. The appropriate model for each of the network is identified. The performance of the developed ANN models has been measured using Root Mean Squared Errors (RMSE) and Correlation Coefficients (CC). The accuracy of the developed ANN models has been compared with Multiple Linear Regression (MLR) Model. The experimental results show that MLP and RBF models outperform MLR model. Sensitivity analysis has been performed for Prediction of Maize Production and results show that temperature (maximum) is the most sensitive parameter for Maize Production followed by technology index for Upper Brahmaputra Valley Zone of Assam.
Reliability and validity of the Athens Insomnia Scale in chronic pain patients

Purpose To confirm the psychometric properties of the Athens Insomnia Scale (AIS) among Japanese chronic pain patients. Patients and methods In total, 144 outpatients were asked to complete questionnaires comprising the AIS and other study measures. According to the original article, the AIS has 2 versions: the AIS-8 (full version) and the AIS-5 (brief version). To validate the AIS-8 and AIS-5 among chronic pain patients, we confirmed: 1) factor structure by confirmatory factor analysis; 2) internal consistency by Cronbach’s a; 3) test–retest reliability using with interclass correlation coefficients; 4) known-group validity; 5) concurrent validity; and 6) cut-off values by receiver operating characteristic analysis. In addition, semi-structured interviews were conducted to assess the participants’ sleep disturbance. If the participants had any sleep complaints, including difficulty in initiating sleep, difficulty in maintaining sleep, and early morning awakening, they were defined as insomnia symptoms. Results A 2-factor model of the AIS-8 and 1-factor model of the AIS-5 demonstrated good fit. The AIS had adequate internal consistency and test–retest reliability. Patients with insomnia had a higher AIS score than those without insomnia. The sleep disturbance measured by the AIS was positively associated with pain intensity, disability, depression, anxiety, and pain catastrophizing, and negatively associated with pain-related self-efficacy. The cut-off values for detecting insomnia were estimated at 8 points in the AIS-8 and 4 points in the AIS-5. Conclusion The AIS-8 and AIS-5 had adequate reliability and validity in chronic pain patients.
HYBRID WEB ENGINEERING PROCESS MODEL FOR THE DEVELOPMENT OF LARGE SCALE WEB APPLICATIONS

Many web development models had been proposed in the literature and there are few studies related to proposing models for developing large web applications. It is important to construct a model that lead to large web applications development with minimum likelihood of failure. A Hybrid web engineering process model for large web development enterprises has been proposed in this research. This model focuses on overall development process phases and consists of many activities: division of large web application into many small sub applications; division of large number of developers into many sub teams; identify a management team to control the development process; Stakeholders’ and customers’ inclusion and feedback during development process; requirement analysis and management; adopting the Spiral model by management team; adopting the Throwaway Prototype, XP agile method, Web Engineering process model by each sub team; conducting CMMI levels key process areas; conducting web engineering practices and SQA activities; and training developers on CMMI and web engineering practices. An evaluation of this model according to CMMI process areas has been conducted in this research. This evaluation has been carried out by many professional developers currently working in many large web-development Jordanian enterprises. The evaluation results shows that the Hybrid model highly satisfied each of CMMI level2 and CMMI level3, medium satisfaction of CMMI level4, and finally low satisfaction of CMMI level5.
American Journal of Epidemiology Original Contribution Association of Prenatal Exposure to Polybrominated Diphenyl Ethers and Infant Birth Weight

Polybrominated diphenyl ethers (PBDEs) are a class of persistent compounds that have been used as flame retardants in vehicles, household furnishings, and consumer electronics. This study examined whether concentrations of PBDEs in maternal serum during pregnancy were associated with infant birth weight, length, head circumference, and length of gestation. Participants were pregnant women (n ¼ 286) enrolled in the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) Study, a longitudinal cohort study of low-income, predominantly Mexican families living in the Salinas Valley, California. Blood samples were collected were measured. Multiple linear regression models were used to investigate the association of lipid-adjusted, log 10-transformed PBDE concentrations and birth outcome. In adjusted analyses, negative associations with birth weight were seen with BDE-47 (b ¼ À115 g, 95% confidence interval (CI): À229, À2), BDE-99 (b ¼ À114 g, 95% CI: À225, À4), and BDE-100 (b ¼ À122 g, 95% CI: À235, À9). These findings were diminished slightly and were no longer statistically significant when maternal weight gain was included in the models. PBDE congeners were not associated with birth length, head circumference, or gestational duration. Polybrominated diphenyl ethers (PBDEs) are flame-retardant chemicals used in automobiles, airplanes, and homes. They have been used in polyurethane foam furniture and carpet padding, in textiles, and in plastic electronics housings (1). Because they are not chemically bound into products, PBDEs have the potential to leach into the home and the environment (2). PBDEs have been detected in wildlife , including fish, birds, and mammals (3), as well as in humans. Recent biomonitoring shows that 97% of Ameri-cans have detectable levels of PBDEs in their blood (4). Several concerns have been raised about the potential health effects of PBDEs. In animal studies, they have been shown to disrupt thyroid hormone balance (5–8); to alter behavior, memory, and learning (9–12); and to affect sex hormone levels and reproductive parameters (7, 13–16). Epidemiologic studies have similarly found PBDEs to be associated with changes in thyroid hormone levels (17–20), a lower intelligence quotient (21), and lower fecundability (22). Maternal exposure to chemical pollutants during pregnancy has been associated with low birth weight and preterm birth, major causes of infant mortality and morbidity (23). To date, 4 epidemiologic studies have examined whether PBDE exposure during pregnancy impacts birth weight. Wu et al. (24) examined 153 infants born in communities with e-waste (obsolete electrical and electronic devices) recycling facilities …
Automatic text-independent pronunciation scoring of foreign language student speech

SRI International is currently involved in the development of a new generation of software systems for automatic scoring of pronunciation as part of the Voice Interactive Language Training System (VILTS) project. This paper describes the goals of the VILTS system, the speech corpus and the algorithm development. The automatic grading system uses SRI's Decipher/sup TM/ continuous speech recognition system to generate phonetic segmentations that are used to produce pronunciation scores at the end of each lesson. The scores produced by the system are similar to those of expert human listeners. Unlike previous approaches, in which models were built for specific sentences or phrases, we present a new family of algorithms designed to perform well even when knowledge of the exact text to be used is not available.
Composition of monitoring components for on-demand construction of runtime model based on model synthesis

Monitoring functionality is implemented and provided as infrastructure of most software platforms and applications. However, the construction of system model cannot be achieved by directly composing runtime model of different applications. First, models which conform to different meta-models cannot be directly composed. Second, the abstract of a system may be different from different viewpoint. Finally, the relationships between systems are different from different abstract viewpoint. In this paper, we propose a DSL (Domain Specific Language) for composition of monitoring components. The DSL distinguish component definition and instance clearly in order to enables reuse of monitoring component. Based on the component composition, the meta-model of target runtime model is generated. We developed an algorithm to generate model transformation for synthesizing runtime models of its applications. In the case study, we choose four monitoring systems as monitoring component types in our DSL. We introduce how to compose monitoring components for on-demand construction of runtime model based on model synthesis.
Supersymmetry constraints on type IIB supergravity

Supersymmetry is used to derive conditions on higher derivative terms in the effective action of type IIB supergravity. Using these conditions, we are able to prove earlier conjectures that certain modular invariant interactions of order $({\ensuremath{\alpha}}^{\ensuremath{'}}{)}^{3}$ relative to the Einstein-Hilbert term are proportional to eigenfunctions of the Laplace operator on the fundamental domain of SL(2,Z). We also discuss how these arguments generalize to terms of higher order in ${\ensuremath{\alpha}}^{\ensuremath{'}},$ as well as to compactifications of supergravity.
System identification of a motor unit pool using a realistic neuromusculoskeletal model

The synaptic input to the motoneurons cannot be measured in humans due to ethical and technical difficulties. For these reasons realistic computational models of a motoneuron pool and the innervated muscle fibers (a “motor unit pool”) have an important role in the study of the human control of muscles. However such models are complex and their mathematical analysis is difficult. We present a system identification approach of a realistic motor unit pool model with the objective of obtaining a simpler model capable of representing the transduction of the motoneuron pool inputs into the force generated by the respective muscle. The system identification was based on an orthogonal least squares algorithm to find a NARMAX model, the input being the net dendritic excitatory synaptic conductance of the motoneurons and the output being the force produced by the muscle. The identified model output reproduced the mean behavior of the output from the realistic computational model even for input-output signals not used in the identification process, such as sinusoidally modulated output force signals.
Influencing Myself: Self-Reinforcement Through Online Political Expression

Over the past decade, various online communication platforms have empowered citizens to express themselves politically. Although the political impact of online citizen expression has drawn considerable attention, research has largely focused on whether and how citizen-generated messages influence the public as an information alternative to traditional news outlets. The present study aims to provide a new perspective on understanding citizen expression by examining its political implications for the expressers themselves rather than those exposed to the expressed ideas. Data from a national survey and an online discussion forum study suggest that expressing oneself about politics provides self-reinforcing feedback. Political expressions on social media and the online forum were found to (a) reinforce the expressers’ partisan thought process and (b) harden their pre-existing political preferences. Implications for the role the Internet plays in democracy will be discussed.
Angle-gathers by Fourier Transform

In this paper, we present a method for computing angle-domain common-image gathers from wave-equation depth-migrated seismic images. We show that the method amounts to a radial-trace transform in the Fourier domain and that it is equivalent to a slant stack in the space domain. We obtain the angle-gathers using a stretch technique that enables us to impose smoothness through regularization. Several examples show that our method is accurate, fast, robust, easy to implement and that it can be used for real 3-D prestack data in applications related to velocity analysis and amplitude-versus angle (AVA) analysis.
Refraction of Water Surface Intersecting Objects in Interactive Environments

This paper presents a rapid method to render dynamic water surfaces with penetrating obstacles in real-time. Taking the surface boundary into account, our method allows the rendering of single reflections and single refractions of objects even intersecting the water surface, including a physically approximative perspective refraction mapping. Thereby, water surfaces are represented as 2.5D height fields and obstacles as polygonal objects. In principle, we determine approximating virtual reflection and refraction eye coordinates. With respect to the water surface, the reflected and refracted objects and parts of objects are projected onto the surface from separate, virtual eye coordinates. Since we are using per-pixel reflection and refraction mapping, our multi-pass, image-based technique is suitable for GPU-based implementations. Moreover, we demonstrate the interactive application of the method for height field based data sets extracted from interactive 3D Smoothed Particle Hydrodynamics (SPH) simulations in real-time. Thereby, the presented approach achieves high frame rates and plausible results.
Oscillatory Cerebral Blood Flow Is Associated With Impaired Neurocognition and Functional Hyperemia in Postural Tachycardia Syndrome During Graded Tilt

We hypothesize that upright cognitive impairment in patients with postural tachycardia syndrome (POTS) is caused by reduced cerebral blood flow (CBF). The CBF velocity (CBFv) measured by transcranial Doppler ultrasound decreased excessively during 70° tilt in a minority of patients with intermittent hyperpnea/hypocapnia. Incremental tilt showed no difference in mean CBFv. But N-back memory tasking indicated progressive compromised memory, reduced functional hyperemia, and reduced neurovascular coupling. Orthostasis caused slow oscillations in CBFv linked to oscillations in arterial pressure in patients with POTS. We also hypothesize that oscillatory CBFv degrades neurovascular coupling. We performed 2-back testing when subjects were in supine position and during incremental tilts to 15°, 30°, 45°, and 60° in 11 patients with POTS and 9 controls. Oscillatory arterial pressure, oscillatory CBFv, and neurovascular coupling were similar in supine position. The oscillatory arterial pressure increased by 31%, 45%, 67%, and 93% in patients with POTS during tilt and remained unchanged in the controls. Oscillatory CBFv increased by 61%, 82%, 161%, and 264% in patients with POTS during tilt and remained unchanged in the controls. Functional hyperemia decreased from 4.1% to 3.0%, 1.1%, 0.2%, and to 0.04% in patients with POTS, but it was unchanged at 4% in the controls. Percent correct N-back responses decreased from 78% to 33% in patients with POTS, whereas they remained at 89% in the controls. In patients with POTS, oscillatory CBFv was linearly correlated with functional hyperemia (r2=0.76). Increased oscillatory CBF is associated with reduced neurovascular coupling and diminished cognitive perf ormance in patients with POTS.
Effects of mediated social touch on affective experiences and trust

This study investigated whether communication via mediated hand pressure during a remotely shared experience (watching an amusing video) can (1) enhance recovery from sadness, (2) enhance the affective quality of the experience, and (3) increase trust towards the communication partner. Thereto participants first watched a sad movie clip to elicit sadness, followed by a funny one to stimulate recovery from sadness. While watching the funny clip they signaled a hypothetical fellow participant every time they felt amused. In the experimental condition the participants responded by pressing a hand-held two-way mediated touch device (a Frebble), which also provided haptic feedback via simulated hand squeezes. In the control condition they responded by pressing a button and they received abstract visual feedback. Objective (heart rate, galvanic skin conductance, number and duration of joystick or Frebble presses) and subjective (questionnaires) data were collected to assess the emotional reactions of the participants. The subjective measurements confirmed that the sad movie successfully induced sadness while the funny movie indeed evoked more positive feelings. Although their ranking agreed with the subjective measurements, the physiological measurements confirmed this conclusion only for the funny movie. The results show that recovery from movie induced sadness, the affective experience of the amusing movie, and trust towards the communication partner did not differ between both experimental conditions. Hence, feedback via mediated hand touching did not enhance either of these factors compared to visual feedback. Further analysis of the data showed that participants scoring low on Extraversion (i.e., persons that are more introvert) or low on Touch Receptivity (i.e., persons who do not like to be touched by others) felt better understood by their communication partner when receiving mediated touch feedback instead of visual feedback, while the opposite was found for participants scoring high on these factors. The implications of these results for further research are discussed, and some suggestions for follow-up experiments are presented.
Fear of falling: measurement strategy, prevalence, risk factors and consequences among older persons.

BACKGROUND fear of falling (FOF) is a major health problem among the elderly living in communities, present in older people who have fallen but also in older people who have never experienced a fall. The aims of this study were 4-fold: first, to study methods to measure FOF; second, to study the prevalence of FOF among fallers and non-fallers; third, to identify factors related to FOF; and last, to investigate the relationship between FOF and possible consequences among community-dwelling older persons. METHODS several databases were systematically searched, and selected articles were cross-checked for other relevant publications. RESULTS a systematic review identified 28 relevant studies among the community-dwelling elderly. Due to the many different kinds of measurements used, the reported prevalence of FOF varied between 3 and 85%. The main risk factors for developing FOF are at least one fall, being female and being older. The main consequences were identified as a decline in physical and mental performance, an increased risk of falling and progressive loss of health-related quality of life. CONCLUSION this review shows that there is great variation in the reported prevalence of FOF in older people and that there are multiple associated factors. Knowledge of risk factors of FOF may be useful in developing multidimensional strategies to decrease FOF and improve quality of life. However, the only identified modifiable risk factor of FOF is a previous fall. In order to measure the impact of interventions, a uniform measurement strategy for FOF should be adopted, and follow-up studies should be conducted.
Adaptive resolution by matching pursuit algorithms

The family of matching pursuit algorithms are greedy heuristic methods for basis selection problem. In this paper, we propose an adaptive structure for matching pursuit algorithms that uses a progressive refinement structure. The proposed adaptive algorithm allows the detector to adjust the tradeoff between the computational complexity and the resolution performance. The novel algorithm is applied to direction of arrival detection problem and it is shown that the algorithm results in a lower computational complexity than the direct implementation of matching pursuit algorithms.
Community Detection in Complex Networks based on Multiobjective Honey Bee Mating Optimization

Detecting community structure is crucial for uncovering the links between structures and functions in complex networks. Most of contemporary community detection algorithms employ single optimization criteria (e.g., modularity), which may have fundamental disadvantages. This paper considers the community detection process as a Multi-Objective optimization Problem (MOP). To solve the community detection problem this study used improved honey bee mating optimization (HBMO) algorithm. In the proposed algorithm, an external repository is considered to save non-dominated (Pareto) solutions found during the search process. The efficiency of the proposed algorithm is studied by testing on several data sets. Numerical results show that the proposed evolutionary optimization algorithm is robust and suitable for community detection problem. Keywordscomplex network; community; multi-objective; honey bee mating optimization
Optimizing testing efficiency with error-prone path identification and genetic algorithms

We present a method for optimizing software testing efficiency by identifying the most error prone path clusters in a program. We do this by developing variable length genetic algorithms that optimize and select the software path clusters which are weighted with sources of error indexes. Although various methods have been applied to detecting and reducing errors in a whole system, there is little research into partitioning a system into smaller error prone domains for testing. Exhaustive software testing is rarely possible because it becomes intractable for even medium sized software. Typically only parts of a program can be tested, but these parts are not necessarily the most error prone. Therefore, we are developing a more selective approach to testing by focusing on those parts that are most likely to contain faults, so that the most error prone paths can be tested first. By identifying the most error prone paths, the testing efficiency can be increased.