Miracle-dz/UniFAR-FTUs huggingface dataset:
Achievable Diversity Order of HARQ-Aided Downlink NOMA Systems

The combination between non-orthogonal multiple access (NOMA) and hybrid automatic repeat request (HARQ) is capable of realizing ultra-reliability, high throughput and many concurrent connections particularly for emerging communication systems. This paper focuses on characterizing the asymptotic scaling law of the outage probability of HARQ-aided NOMA systems with respect to the transmit power, i.e., diversity order. The analysis of diversity order is carried out for three basic types of HARQ-aided downlink NOMA systems, including Type I HARQ, HARQ with chase combining (HARQ-CC) and HARQ with incremental redundancy (HARQ-IR). The diversity orders of three HARQ-aided downlink NOMA systems are derived in closed-form, where an integration domain partition trick is developed to obtain the bounds of the outage probability specially for HARQ-CC and HARQ-IR-aided NOMA systems. The analytical results show that the diversity order is a decreasing step function of transmission rate, and full time diversity can only be achieved under a sufficiently low transmission rate. It is also revealed that HARQ-IR-aided NOMA systems have the largest diversity order, followed by HARQ-CC-aided and then Type I HARQ-aided NOMA systems. Additionally, the users’ diversity orders follow a descending order according to their respective average channel gains. Furthermore, we expand discussions on the cases of power-efficient transmissions and imperfect channel state information (CSI). Monte Carlo simulations finally confirm our analysis.
IoT network-based ANN for ventilation pattern prediction and actuation to optimize IAQ in educational spaces

Nowadays, in a user centered design approach, one of the main parameters for assessing the well-being of building spaces is Indoor Air Quality (IAQ), which can assure a crucial level of comfort and optimal conditions to preserve users’ productivity and cognitive performance. Research works in this direction mention that with 1000 ppm of CO2 concentration, a reduction of the users’ cognitive performance about 11-23% is reported and, for a concentration of 2500 ppm, the decrease reaches 44-94% compared to the performance at 600 ppm. Consequently, a correct buildings ventilation is crucial. The use of mechanical systems seems possibly to avoid the problem but indeed the existing buildings often have outdated and not flexible systems to face changing needs. Thereby, the ventilation rates are not related to people density and the static setup of HVAC systems might be an issue to maintain an acceptable level of CO2 concentration. Moreover, in school buildings, mechanical ventilation is not diffusely adopted and insufficient rates of fresh air supplied to the classrooms are connected with inappropriate IAQ, occurrence of SBS symptoms among pupils. Current technology provides easy measurement of CO2 through dedicated sensors networks. The present research uses the pilot educational building eLUX, located in the Smart Campus of the University of Brescia, to investigate the possibility to integrate IAQ data generated by IoT sensors to improve the estimation of occupancy rate in the educational spaces. The aim is to underline the relevance of the parameter to regulate properly the HVAC systems and to define opening/closing patterns for automated windows to enhance IAQ. The data collected during the monitoring phase are useful to train an Artificial Neural Network (ANN) that through an IoT communication protocol could actuate the ventilation rate control.
Do Illness Perceptions in Patients with Fibromyalgia Differ Across Countries? A Comparative Study

Abstract Objective: Illness perceptions, i.e. how patients think about their illness in terms of identity, cause and consequences, are important, as negative illness perceptions are associated with maladaptive illness behavior, more dysfunctioning, poor treatment adherence and treatment outcome. As illness perceptions are influenced by cultural background, former experiences and provided information, the aim of this study was to compare illness perceptions of patients with fibromyalgia syndrome [FMS] living in different countries. Methods: Dutch speaking participants from two countries were recruited in this international comparative study. In total, 114 Belgian [Flemish] and 283 Dutch FMS patients completed the Illness Perception Questionnaire for Fibromyalgia-Dutch Language version [IPQ-R FM-Dlv]. The Mann–Whitney U test for non-parametric data was used to compare data between the patient groups. Pearson’s chi-squared test was used to compare proportions. Results: Significant differences in illness perceptions were observed. Belgian patients reported a higher variety of symptoms and believed more strongly that these symptoms are related with their illness. They had more negative beliefs concerning the consequences of their illness and reported more external attributed factors to be the cause of their illness. Dutch patients demonstrated a better understanding and controllability. They indicated more internal attributed factors as a cause. Conclusions: These findings suggest that illness perceptions in patients with FMS are prone to local influences, including small differences in the health care system. Future studies are advised to measure mood, psychopathology, medical co-morbidity and socio-demographic factors and include them in a multivariate analysis.
Interactive faceted query suggestion for exploratory search: Whole‐session effectiveness and interaction engagement

The outcome of exploratory information retrieval is not only dependent on the effectiveness of individual responses to a set of queries, but also on relevant information retrieved during the entire exploratory search session. We study the effect of search assistance, operationalized as an interactive faceted query suggestion, for both whole‐session effectiveness and engagement through interactive faceted query suggestion. A user experiment is reported, where users performed exploratory search tasks, comparing interactive faceted query suggestion and a control condition with only conventional typed‐query interaction. Data comprised of interaction and search logs show that the availability of interactive faceted query suggestion substantially improves whole‐session effectiveness by increasing recall without sacrificing precision. The increased engagement with interactive faceted query suggestion is targeted to direct situated navigation around the initial query scope, but is not found to improve individual queries on average. The results imply that research in exploratory search should focus on measuring and designing tools that engage users with directed situated navigation support for improving whole‐session performance.
Sentiment Analysis of Mobile Product Reviews

: Reviews about products have started playing an important role in finding opinions about products that are available in the market [1]. Those reviews spread like rumours and help in decision making for the consumers to purchase the product or not and as well to the manufacturers to get feedback about their products. The reviews help in better selection of products for the customer and hence help them in selecting the best and the appropriate phone for their use. Several researches have been conducted on this problem using various techniques and have produced results of varied kinds. Many different kinds of approaches have been used to conduct the study of this problem and have shown the various desired results about a particular smartphone product. Some researches show comparative studies about various methodologies used for solving the problem while some make a combination of various approaches into one solution. All of these have been successful in their own ways and have helped the user in determining the best product according to their requirements. The growing number of opinions about a particular product make it ambiguous for a customer to take a decision of whether to buy that product or not [1]. The problem customers face while picking a mobile phone is that there is no mechanism which gives detailed reviews about a product. Taking the previous works into account we have tried to enhance the research about this topic by adding some contribution in our own way and helping the community. We make an effort here to build a system that efficiently tries to predict the sentiments regarding a mobile product based on the reviews that people have given to that product on a particular platform.
Unsupervised Temporospatial Neural Architecture for Sensorimotor Map Learning

The ability to learn the sensorimotor maps of unknown environments without supervision is a vital capability of any autonomous agent, be it biological or artificial. An accurate sensorimotor map should be able to encode the agent’s world and equip it with the capability to anticipate or predict the results of its actions. However, to design a robust autonomous learning technique for an unknown, dynamic, partially observable, or noisy environment remains a daunting task. This article proposes a temporospatial merge grow when required (TMGWR) network for continuous self-organization of an agent’s sensorimotor awareness in noisy environments. TMGWR is an adaptive neural algorithm that learns the sensorimotor map of an agent’s world using a time series self-organizing strategy and the grow when required (GWR) algorithm. The algorithm is compared with growing neural gas (GNG), GWR, and time GNG in terms of their disambiguation performance, sensorial representation accuracy, and sensorimotor-link error, a new metric that is developed in this article to evaluate how well a sensorimotor map represents causality in the agent’s world. The outcomes of the experiments show that TMGWR is more efficient and suitable for sensorimotor map learning in noisy environments than the competing algorithms.
Advancing Practical Specification Techniques for Modern Software Systems

The pervasive nature of software (and the tendency for it to contain errors) has long been a concern of theoretical computer scientists. Many investigators have endeavored to produce theories, tools, and techniques for verifying the behavior of software systems. One of the most promising lines of research is that of formal specification, which is a subset of the larger field of formal methods. In formal specification, one composes a precise mathematical description of a software system and uses tools and techniques to ensure that the software that has been written conforms to this specification. Examples of such systems are Z notation, the Java Modeling Language, and many others. However, a fundamental problem that plagues this line of research is that the specifications themselves are often costly to produce and difficult to reuse. If the field of formal specification is to advance, we must develop sound techniques for reducing the cost of producing and reusing software specifications. The work presented in this dissertation lays out a path to producing sophisticated, automated tools for inferring large, complex code bases, tools for allowing engineers to share and reuse specifications, and specification languages for specifying information flow policies that can be written separately from program code. This dissertation introduces three main lines of research. First, I discuss a system that facilitates the authoring, sharing, and reuse of software specifications. Next, I discuss a technique which aims to reduce the cost of producing specifications by automatically inferring them. Finally, I discuss a specification language called Evidently which aims to make information flow security policies easier to write, maintain, and enforce by untangling them from the code to which they are applied.
Care Allowances for the Frail Elderly and Their Impact on Women Care-Givers

This report discusses the impact of care allowances on women care-givers. These programmes, involving some payment for care in informal care settings, have recently been introduced in several OECD Member countries. While their primary goal has been to help older persons in need of care, their consequences for the persons providing care also deserve to be analysed. The bulk of informal care is provided by women care-givers. In this respect, long-term care systems involve a partnership between formal care systems, the state, and the family, in order to provide a continuum of care. This also renders the analysis very complex. The main objective of the paper is to answer the question: what is the impact for women care-givers of various models of care allowances for the frail elderly? These care allowances have been primarily instituted to address the needs of older persons for care, as well as to offer some compensation for caring responsibilities. Apart from these initial goals . Ce rapport discute de l'impact pour les aidants informels feminins des allocations de soins. Ces programmes qui impliquent des formes de paiement pour les soins dans un contexte de soins informels, ont ete recemment introduits dans plusieurs Pays Membres de l'OCDE. Tandis que leur but principal a ete d'aider des personnes âgees ayant besoin de soins, leurs consequences pour les personnes procurant les soins meritent aussi d'etre analysees. L'essentiel des soins informels est procure par des aidants feminins. Dans cette mesure, les systemes de soins dependance impliquent des partenariats entre les systemes de soins formels, l'Etat et la famille, afin d'offrir un continuum de soins. Ceci rend aussi l'analyse tres complexe. L'objectif principal de cette etude est de repondre a la question: quel est l'impact pour les aidants feminins de divers modeles d'allocation de soins pour les personnes âgees dependantes? Ces allocations de soins compensatrices ont ete principalement mises en .
GPS/GNSS spoofing and the real-time single-antenna-based spoofing detection system

Abstract The idea of C/A codes GPS/GNSS Spoofing (Substitution), or the ability to mislead a satellite navigation receiver into establishing a position or time fix which is incorrect, has been gaining attention as spoofing has become more sophisticated. Various techniques have been proposed to detect if a receiver is being spoofed – with varying degrees of success and computational complexity. If the jammer signals are sufficiently plausible then the GNSS receiver may not realize it has been duped. There are various means of detecting spoofing activity and hence providing effective mitigation methods. In this paper, a novel signal processing method applicable to a single antenna handset receiver for spoofing detection has been described. Mathematical models and algorithms have been developed to solve the problems of satellite navigation safety. What has been considered in the paper is a spoofing detection algorithm based on the analysis of a civil satellite signal generated by mobile C/A GPS/GNSS single-antenna receivers. The work has also served to refine the civilian spoofing threat assessment by demonstrating the challenges involved in mounting a spoofing attack.
Advanced functional materials for soft robotics: tuning physicochemical properties beyond rigidity control

Reversibility, a key property in materials science and soft matter, is extremely desirable to enable advanced functionality in soft robots. So far, tunable rigidity has attracted most of the attention, notably for its application in novel soft actuators, soft grippers, and its potential impact in locomotion of soft and hybrid robotic devices. Herein, we review recent progress on reversibility in other physicochemical properties which can also play important roles in the functionality of soft robots. We focus on the tunability of five key properties: electrical and thermal conductivities, surface wettability and adhesion, and optical properties. Materials and mechanisms are described, and performances are assessed, when possible, in terms of reversible tunability range, time response, cycling endurance, and power consumption. The potential integration of such solutions to soft robots is systematically discussed.
NELLY: Flow Detection Using Incremental Learning at the Server Side of SDN-Based Data Centers

The processing of big data generated by the Industrial Internet of Things (IIoT) calls for the support of processing at the edge of the network, as well as at the cloud data centers. The equal-cost multipath, which is the default routing technique in the cloud data centers, can degrade the network performance when handling mouse and elephant flows. Such degradation of performance can compromise the support of the strict quality of service requirements of the IIoT over 5G networks. Novel techniques for scheduling the elephant flows can alleviate this problem. Recently, several approaches have incorporated machine learning techniques at the controller-side in software-defined data center networks (SDDCNs) to detect elephant flows. However, these approaches can produce heavy traffic overhead, low scalability, low accuracy, and high detection time. This article introduces the Network Elephants Learner and anaLYzer (NELLY), a novel and efficient method for applying incremental learning at the server side of SDDCNs to accurately and timely identify elephant flows with low traffic overhead. Incremental learning enables NELLY to adapt to varying network traffic conditions and perform continuous learning with limited memory resources. NELLY has been extensively evaluated using real traces and various incremental learning algorithms. Results show that NELLY is accurate and supports low classification time when using adaptive decision trees algorithms.
Dynamic Programming algorithm for Computing Temporal Logic Robustness

i ABSTRACT In this thesis we deal with the problem of temporal logic robustness estimation. We present a dynamic programming algorithm for the robust estimation problem of Metric Temporal Logic (MTL) formulas regarding a finite trace of time stated sequence. This algorithm not only tests if the MTL specification is satisfied by the given input which is a finite system trajectory, but also quantifies to what extend does the sequence satisfies or violates the MTL specification. The implementation of the algorithm is the DP-TALIRO toolbox for MATLAB. Currently it is used as the temporal logic robust computing engine of S-TALIRO which is a tool for MATLAB searching for trajectories of minimal robustness in Simulink/ Stateflow. DP-TALIRO is expected to have near linear running time and constant memory requirement depending on the structure of the MTL formula. DP-TALIRO toolbox also integrates new features not supported in its ancestor FW-TALIRO such as parameter replacement, most related iteration and most related predicate. A derivative of DP-TALIRO which is DP-T-TALIRO is also addressed in this thesis which applies dynamic programming algorithm for time robustness computation. We test the running time of DP-TALIRO and compare it with FW-TALIRO. Finally, we present an application where DP-TALIRO is used as the robustness computation core of S-TALIRO for a parameter estimation problem. ii ACKNOWLEDGEMENTS I want to thank Dr. Georgios Fainekos for this wonderful opportunity to work on this interesting research topic and more importantly work along with him. I benefit greatly from his guidance, rigorous attitude and forward-looking spirit. I appreciate the financial support from Dr. Georgios Fainekos and Arizona State University in the past two years. I would also like to thank Dr. Hessam Sarjoughian and Dr. Aviral.Shrivastava for the support and feedback they gave me as part of my thesis committee. helped and inspired me during past few years. Also, I want to thank all the professors and staffs of Arizona State University who altogether create a great learning and working environment and atmosphere for me. findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Benchmarking input/output multiplexing facilities of the Linux kernel

In the last fewdecades, concurrent connectionprocessingneedshave increased, and will continue to do so – both server-side and client-side. There has been a big push in the industry towards solutions that improve the efficiency of all the pieces involved in this task. This Bachelor’s Thesis focuses in a foundational feature for many programs: how to handlemore than one connection at the same time. It is an apparently simple task –whether you ask a computer engineer or a computer user. However, it can be done in different ways, each of which has different efficiency consequences. This document will explore the main ways to be able to handle concurrent connections in Linux computer systems. In addition, we will be experimentally analysing the efficiency of themainmethods for accomplishingmultiple concurrent connections: using different threads or using one of the three I/O multiplexing tools (select, poll and epoll) provided by the Linux kernel.
Using Open-Source Software for Sign Language Learning and Assessment

This study reports on the use of an open-source software for sign language learning and (self-)assessment. A Yes/No vocabulary size test for Swiss German Sign Language (Deutschschweizerische Gebärdensprache, DSGS) was developed, targeting beginning adult learners. The Web-based test, which can be used for self-assessment or placement purposes, was administered to 20 DSGS adult learners of ages 24 to 55 (M = 39.3). The learners filled out a background questionnaire, took the Yes/No test tests, and filled out a feedback questionnaire. The comments provided by the learners about the suitability of the Web-based DSGS vocabulary self-assessment instrument provided concrete feedback towards improvement of the system.
Meta-Analysis of Public Acceptance of Unmanned Aircraft Systems in the United States

Automated and unmanned systems are rapidly revolutionizing every aspect of military, commercial, and public use operations in the United States. While this technology serves effectively in dull, dirty, and dangerous tasks, the rapid introduction of unmanned technologies into society has generated intense debate about their ethical, moral, and legal use. Specifically, the rise in the development and application of unmanned aircraft systems (UAS) has created significant public discord. As public acceptance of UAS plays a major role in the regulatory decisions that allow for expanded use in commercial and public use applications, it is critically important to understand the complexities involved in the public acceptance of UAS. A metaanalysis of archival data was conducted to identify a possible relationship between UAS intended missions and their acceptability within the public. Compiled survey research indicated that search and rescue (SAR) applications are the most publicly accepted intended missions. Additionally, a chi-square test of independence found evidence of a relationship between intended mission and public acceptance, with commercial and non-law enforcement public use having the highest levels of public acceptance. Recommendations include increasing the public’s knowledge and awareness of UAS through an iPhone Operating System (IOS) device application, and removing “drone” from future survey terminology.