Miracle-dz/UniFAR-FTUs huggingface dataset:
Data-Driven Dynamic Control Allocation for Uncertain Redundant Plants

This paper addresses the problem of achieving high-performance dynamic control allocation for uncertain plants by exploiting a data-driven design of the annihilator for the underlying plant. Previous work revealed that an output invisible control allocator can be decomposed as the cascade interconnection of a steady-state optimizer and an annihilator, where the latter unit modulates the allocator outputs in such a way to render such signals undetectable from the plant output. Clearly, the critical role and challenging requirements imposed on the annihilator make it the source of the fragility of control allocation schemes in the presence of uncertainty; nonetheless this critical aspect can be (almost) completely circumvented by tuning the annihilator to the actual plant parameters, namely by envisioning a data-driven control allocation scheme. Relations are also highlighted between the present results and the concepts of moments and orthogonal moments of a plant at frequencies of interest, whose use and estimation have recently been the subject of increasing interest.
Direct-to-Patient Survey for Diagnosis of Benign Paroxysmal Positional Vertigo

Given the high incidence of dizziness and its frequent misdiagnosis, we aim to create a clinical support system to classify the presence or absence of benign paroxysmal positional vertigo with high accuracy and specificity. This paper describes a three-phase study currently underway for classification of benign paroxysmal positional vertigo, which includes diagnosis by a specialist in a clinical setting. Patient background information is collected by a survey on an Android tablet and machine learning techniques are applied for classification. Decision trees and wrappers are employed for their ability to provide information about the question set. One goal of the study is to attain an optimal question set. Each phase of the study presents a unique set and style of questions. Results achieved in the first two phases of the survey indicate that our approach using decision trees with filters or wrappers does a good job of identifying benign paroxysmal positional vertigo.
An Exponentially Convergent Primal-Dual Algorithm for Nonsmooth Composite Minimization

We consider a class of nonsmooth convex composite optimization problems, where the objective function is given by the sum of a continuously differentiable convex term and a potentially non-differentiable convex regularizer. In [1], the authors introduced the proximal augmented Lagrangian method and derived the resulting continuous-time primal-dual dynamics that converge to the optimal solution. In this paper, we extend these dynamics from continuous to discrete time via the forward Euler discretization. We prove explicit bounds on the exponential convergence rates of our proposed algorithm with a sufficiently small step size. Since a larger step size can improve the convergence speed, we further develop a linear matrix inequality (LMI) condition which can be numerically solved to provide rate certificates with general step size choices. In addition, we prove that a large range of step size values can guarantee exponential convergence. We close the paper by demonstrating the performance of the proposed algorithm via computational experiments.
Behavioral Performance Evaluation and Emotion Analytics of a MOOC Course via Fuzzy Modeling

The main objective of this study is to compare and distinguish both behavioral differences and emotional changes of a group of students who "earned a certificate" after the end of a MOOC (Massive Open Online Course), versus another groups of students who "dropped out" the course unsuccessfully. To do this, a process mining process discovery technique so-called Fuzzy Miner, based on Frequency-Based and Time-Performance metrics, was applied on a set of event logs previously collected from an authentic learning environment. The resulting fuzzy graphs/models showed a significant dissimilarity between the two groups in terms of the behavioral structure and the sequence of the performed/executed tasks (and activities), the average (mean) duration of the waiting times (or inactive interval/time gaps) in addition to the emotional mood shifts and changes. The findings of the study can be beneficial to not only the MOOC course developers, but to lecturers and researchers as well, in such a way leading to higher attrition rate running online courses and syllabuses.
paper title : Perception and acceptance of health informatics learning among health-related students in Jordan and Palestine

This study used a tailored version of the Technology Acceptance Model (TAM) to assess Jordanian and Palestinian students’ attitudes and beliefs toward learning of health informatics (HI), determine their intention to learn, assess the needed HI skills, and determine reasons that could motivate students to study HI. A descriptive, cross-sectional study was conducted among undergraduate senior students in health – oriented disciplines in four universities in Jordan and Palestine. A sample of students was emailed the link to the web-based questionnaire and was voluntarily requested to fill the questionnaire. A total of 891 students responded to the study questionnaire. The majority (82.7%) of students were interested in learning HI. About 62.8% of students reported that they will take a set of HI courses as a pathway in their undergraduate degree if they are given such an opportunity. More than 70% of students perceived HI learning as useful. About three quarters of students had a behavioral intention to enter the HI program and about two thirds (75.4%) reported that they are enthusiastic about the use of health information technology in patient care in future medical practice. Higher ratings on perceived usefulness (r = 0 .73), perceived ease of learning and use of HI (r =0.76), attitude toward HI (r =0.83), enabling environment (r = 0.44) were significantly associated with higher behavioral intention to learn HI. In conclusion, students perceived HI learning as useful and easy, had a positive attitude toward HI, and had a high intention to learn HI. Keywords—health informatics, perceived usefulness, perceived ease of learning, Technology Acceptance Model
deimeq - A Deep Neural Network Based Hybrid No-reference Image Quality Model

Current no reference image quality assessment models are mostly based on hand-crafted features (signal, computer vision, …) or deep neural networks. Using DNNs for image quality prediction leads to several problems, e.g. the input size is restricted; higher resolutions will increase processing time and memory consumption. Large inputs are handled by image patching and aggregation a quality score. In a pure patching approach connections between the sub-images are getting lost. Also, a huge dataset is required for training a DNN from scratch, though only small datasets with annotations are available. We provide a hybrid solution (deimeq) to predict image quality using DNN feature extraction combined with random forest models. Firstly, deimeq uses a pre-trained DNN for feature extraction in a hierarchical sub-image approach, this avoids a huge training dataset. Further, our proposed sub-image approach circumvents a pure patching, because of hierarchical connections between the sub-images. Secondly, deimeq can be extended using signal-based features from state-of-the art models. To evaluate our approach, we choose a strict cross-dataset evaluation with the Live-2 and TID2013 datasets with several pre-trained DNNs. Finally, we show that deimeq and variants of it perform better or similar than other methods.
Encoding and Decoding of Music-Genre Representations in the Human Brain

Music-genre recognition (MGR) has been a central issue in understanding human preferences of music. Previous studies have used various acoustic features to achieve MGR, though it has been largely unknown how music genres and related features are represented in the brain. Here, we measured brain activity while subjects passively listened to naturalistic music of various genres. A voxel-wise encoding model showed different activation patterns for each music genre in the bilateral superior temporal gyrus. We further performed music-genre classification using both a feature-based approach and a brain activity-based approach. Both approaches provided above-chance classification accuracy. Among four feature models, a biologically plausible spectro-temporal modulation transfer function (MTF) model showed the highest performance. These results provide a new insight into biologically plausible models of music genre.
A Hybrid-Duplex System With Joint Detection for Interference-Limited UAV Communications

In this paper, the advantages of joint detection (JD) in a hybrid-duplex unmanned aerial vehicle (UAV) communication system (HBD-UCS) are investigated as a step toward addressing spectrum scarcity in UAV communications. Through extensive outage probability and finite signal-to-noise-ratio diversity gain analysis, we showed that the performance of JD is independent of the strength and the data rate of the inter-UAV interference signal. On the contrary, the successive interference cancellation (SIC) detector requires the data rate of the interfering UAV to be less than the ground station before meaningful performance can be seen. At the system level, it is observed that the half-duplex UAV communication system outperforms the HBD-UCS with JD at moderate and high SNR regimes, as the latter is constrained by self-interference at the full-duplex ground station. Finally, we investigated the multiplexing gain region and showed that the joint detector offers higher diversity gain over a wide range of multiplexing gains over the interference ignorant and the SIC detector.
Case Study of Target Localization Based on Hybrid and Traditional Ranging via RSS and TOA

This work addresses the problem of target localization in adverse non-line-of-sight (NLOS) environments by using received signal strength (RSS) and time of arrival (TOA) measurements. It is inspired by a recently published work in which authors discuss about a critical distance below and above which combined RSS-TOA measurements are inferior to RSS-only and TOA-only measurements. Here, we employ a state-of-the-art estimator for the considered target localization problem and study its performance against its counterparts that employ each individual measurement exclusively. It is shown that the hybrid approach is not the best one by default. Also, we propose a heuristic approach to choose the best measurement for each link in order to enhance the performance of the estimator. The new approach implicitly relies on the concept of critical distance, but does not assume certain link parameters as given. Our simulations show that the proposed approach works well, matching or even improving the performance of the best fixed choice in all considered scenarios.
Identifying Approaching Behavior of a Person During a Conversation: A Human Study for Improving Human-Robot Interaction

Development of intelligent service robots is a growing research area within the field of robotics. Users of these service robots expect human-like interaction abilities from the robots. These service robots must be capable of navigating in human populated environments by considering the comfort of the people for having smooth interaction with the users since many of the daily routine tasks involve the navigation. Therefore, a robot's way of approaching to users during interactions must be human-friendly in order to enhance the rapport between the human users and the robot. However, the natural approaching behavior of humans has to be studied in order to implement such human-like navigation abilities in service robots. Therefore, this paper contributes in a human study conducted for identifying the approaching behavior of a third person toward two persons who are having a conversation. The study has been conducted as three sub studies to identify the parameters that alter the approaching behavior. The key aspects of the approaching behavior of humans have been identified by analyzing the experimental scenarios. The capabilities required for a service robot for implementing a human-like approaching mechanism are discussed based on the outcomes of the human study. Furthermore, the directions for future investigation of human approaching behavior through human studies are also provided.
Barrier Function-Based Adaptive Integral Sliding Mode Control

In this paper, barrier function-based adaptive discontinuous and continuous integral sliding mode controls are proposed. The main advantage of the proposed algorithms is that they ensure that the solutions of the systems belong to a prescribed vicinity of the desired variables starting from the initial time moment despite of disturbance with unknown upper bound or disturbance with unknown upper bound of its derivative. The proposed algorithms do not require the knowledge of the upper bound of disturbance or its derivative, and, moreover, the control gains are not overestimated.
A Test-bed for Studies of Temporal Data Delivery Issues in a TPCAST Wireless Virtual Reality Set-up

Virtual Reality (VR) is becoming increasingly popular, and wireless cable replacements unleash the user of VR Head Mounted Displays (HMD) from the rendering desktop computer. However, the price to pay for additional freedom of movement is a higher sensitivity of the wireless solution to temporal disturbances of both video frame and input traffic delivery, as compared to its wired counterpart. This paper reports on the development of a test-bed to be used for studying temporal delivery issues of both video frames and input traffic in a wireless VR environment, here using TPCAST with a HTC Vive headset. We provide a solution for monitoring and recording of traces of (1) video frame freezes as observed on the wireless VR headset, and (2) input traffic from the headset and hand controls to the rendering computer. So far, the test-bed illustrates the resilience of the underlying WirelessHD technology and TCP connections that carry the input traffic, and will be used in future studies of Quality of Experience (QoE) in wireless desktop VR.
Null Subcarriers Assisted Impulsive Noise Mitigation for In-Vehicle Power Line Communication in the Presence of Narrowband Interference

Impulsive noise (IN) is one of the crucial affecting factors of in-vehicle power line communication (PLC) systems, and therefore an effective IN mitigation scheme is required to enhance the performance significantly. Narrowband interference (NBI) from various nearby radios often has great impact on the IN reconstruction and mitigation. In this paper, IN mitigation over uncoded orthogonal frequency division multiplexing (OFDM) PLC systems is investigated considering the impact of NBI. A null subcarriers assisted IN mitigation scheme is proposed to mitigate IN in the scenarios of NBI absence and NBI presence. The IN vector is reconstructed at the proposed receiver first, and then canceled out from the received signal. Theoretical analysis shows that the proposed scheme outperforms the blanking method. Also, the implementation of pre-joint NBI/IN mitigation with the aid of null subcarriers in the proposed scheme can combat the impact of intensive NBI, and achieve a near-optimal bit error rate performance with no iterations. The effectiveness of the proposed mitigation scheme is validated by simulation results, which is applicable to the vehicular environments under the disturbance of joint IN and NBI.
PLATELET AGGREGATION AND SERUM THROMBOXANE B2 LEVEL AFTER TAKING 60 MG/DAY OF ASPIRIN IN TYPE 2 DIABETIC THAI PATIENTS

This study is objected to determine whether 60 mg/day dose of aspirin inhibit platelet aggregation capacity adequately to be clinically effective in diabetic patients. Total 97 diabetic patients who were taking low doses of aspirin participated in the study; among these, 75 patients were taking 60 mg/day of aspirin. Besides, 32 diabetes patients who were not taking aspirin were recruited as the control group. Platelet function was assessed by optical platelet aggregation technique using arachidonic acid and ADP as agonists and serum thromboxane B2 level was determined by enzyme immunoassay (EIA) technique. Platelet functions as assessed by optical platelet aggregation after taking 60 mg/day of aspirin did not differ from those obtained after taking 300 mg/day of aspirin. The frequency of aspirin resistance after 60 mg/day of aspirin was similar the results previously reported for higher doses of aspirin. The serum thromboxane was more than 95% inhibited after taking 60 mg/day of aspirin. Aspirin 60 mg/day may be sufficient to be used in average type 2 diabetic patients for prevention of adverse cardiovascular events.
Serum Levels of Interleukins (IL)-4, IL-5, IL-13, and Interferon-γ in Acute Asthma

T-cell activation and alteration of cytokine levels are involved in the pathogenesis of bronchial asthma. However, the profile of circulating T-lymphocyte subsets and related cytokines during acute asthmatic attacks is still unclear. We hypothesized that serum levels of interleukin (IL)-4, IL-5, and IL-13 would be increased, whereas IFN-γ would be decreased in acute asthma. The subjects enrolled in this study included 58 acute asthmatics, 22 asymptomatic asthmatics, and 10 healthy controls. Serum levels of IL-4, IL-5, IL-13, and IFN-γ were measured using a sandwich enzyme-linked immunosorbent assay. We correlated serum levels of IL-4, IL-5, IL-13, and IFN-γ with initial forced expiratory volume in 1 sec (FEV1). Compared with control subjects, acute asthmatics had significantly increased levels of circulating IL-4 (p < 0.001), IL-5 (p < 0.001), and IL-13 (p < 0.001), although the differences were of borderline significance in serum IFN-γ (p = 0.069). There were also significant differences in the circulating levels of IL-4, IL-5, and IL-13 between acute asthmatics and asymptomatic asthmatics. There was no significant association between initial FEV1 and serum levels of IL-4 or IL-13, however, among acute asthmatics, a lower initial FEV1 was associated with higher IL-5 and/or lower IFN-γ levels. Our results suggest that serum levels of IL-4, IL-5, and IL-13 may be elevated in acute asthma, and that higher levels of IL-5 and/or lower levels of IFN-γ are associated with severe airway obstruction.
in The Metropolitan Museum of Art

B AC K G R O U N D The Metropolitan Museum of Art is one of the world’s largest encyclopedic art museums with artworks spanning more than 5,000 years from all corners of the globe. The multi-cultural richness of the collection positions the Met as a truly global museum; it is a must-see museum for tourists, and a source of enormous pride for New Yorkers. Now, the Met is spreading this message to tourists and locals alike through an institutional advertising campaign.
Case-Control Study of Vulvar Vestibulitis Syndrome

ABSTRACT This exploratory case-control study identified possible risk factors associated with vulvar vestibulitis, a problem of unknown etiology. Cases and controls were sampled from two outpatient facilities staffed by university faculty. The practice services a privately insured, self-referred population of patients. The participants were 95 vulvar vestibulitis patients and 188 controls. The main outcome measures were odds ratios (OR) with 95% confidence intervals (CI). As has been suggested by earlier studies, Caucasian women were found to be at significantly greater risk for vulvar vestibulitis than African American women (OR 15.73; 95% CI 2.47-65.2). The basis of this racial difference remains obscure. Nulliparous patients (OR 2.92; 95% CI 1.42-3.02) and patients reporting recurrent "yeast infections" (OR 1.83; 95% CI 1.06-3.16) were found to be at a higher risk of vulvar vestibulitis. Patients who reported prior oral contraceptive use were found to be at lower risk (OR 0.31; 95% CI 0.18-0.56). No di.
Jazz for the Ipod generation : digital media and jazz in the UK

The central aim of this thesis is to address the research question: In what ways are digital media affecting the dissemination of jazz in Britain? Within this are four sub-questions: 1. Has the changing position of jazz in British culture since 1980 affected its audience? 2. Has digital media had the same impact on the dissemination of jazz as it has on mainstream popular music? 3. How is digital technology affecting jazz scenes in the UK? 4. Is there an ‘online community’ of jazz enthusiasts in Britain? The term ‘digital media’ suggests that geographical boundaries are irrelevant, but basing this project in the UK provides a focus for the research, both in terms of jazz as an established cultural form in Britain and in order to investigate British jazz audiences. Theoretical approaches from several disciplines are drawn upon, including cultural studies, new media studies, ethnomusicology, popular music studies and jazz studies. Research methods include surveys of audiences at selected jazz festivals in Britain using questionnaires along with interviews with the festival directors, online surveys, and interviews with jazz enthusiasts. The broad findings indicate that while jazz is one of many types of music available to contemporary audiences who may also listen to other genres, there are fans of particular styles choosing to attend certain live events – increasingly making use of digital media to find information and facilitate their decisions. Sites such as YouTube are popular with jazz audiences, and there are independent jazz record labels that use digital media effectively, unlike, according to some respondents, certain jazz musicians. Audiences (which include a significant proportion of musicians) are now using social networking sites to create online groups with shared musical interests, but this activity has not prevented jazz being essentially a music of live performance – and indeed may be helping to keep it live.
Risk-Averse Transmission Path Selection for Secure State Estimation in Power Systems

The secure state estimation (SSE) problem is investigated for a kind of power systems where the smart meters’ measurements are transmitted to a remote estimator. In this paper, we mainly focus on the transmission via wireless networks. Taking consideration of the possible increase in transmission failure rate due to risk events, such as jamming attacks, a so-called risk-averse transmission path selection (RaTPS) method is proposed to improve SSE robustness. Based on the idea of reinforcement learning, the transmission acknowledgments are applied as the reinforcement signals to reward the source node (smart meter) for choosing more reliable paths. The multipath traffic allocation can adaptively performed according to the transmission failure rate of each path. The theoretical analysis about convergence of RaTPS and SSE is given with the technique of Markov chain, and it is illustrated in the simulation that the robustness of SSE can be improved by using RaTPS.