Miracle-dz/UniFAR-FTUs huggingface dataset:
UWB radiolocation technology: Applications in relative positioning algorithms for autonomous aerial vehicles

This report presents methods and technologies used to investigate the use of commercially available Ultra-Wide Band (UWB) radiolocation technology in the positioning of autonomous vehicles. UWB radio has unique transmission characteristics which make pico-second resolution timing possible, a requirement for centimetre accuracy in positioning applications. Firstly, an investigation into the performance capabilities of UWB positioning infrastructure was undertaken, followed by the development of relative positioning algorithms utilising a relative and decentralised control approach. These algorithms are based on feedback provided by radiolocation data in combination with sensor fusion elements, including inertial (accelerometers), optical (optical flow sensors) and absolute ranging sensors such as Light Detection and Ranging (LIDAR). Performance of the UWB infrastructure was determined utilising static and dynamic measurement techniques to verify overall positioning accuracy and statistical characteristics, with respect to two different ranging algorithms, Time Difference of Arrival (TDOA) and Two Way Ranging (TWR). Data collected from an array of static collection points has shown, in the recommended infrastructure configuration, that commercially available UWB technology has a positional accuracy with an average offset from the real coordinate system of 7.30-15.28%. Logic-based tests using statistical inputs indicate the TDOA algorithm succeeds in more accurate positioning in 79.63%, 58.33% and 85.19% of test cases across twenty-seven points in three vertical planes respectively. Data collected from autonomous flight-path algorithms has provided practical insight into applications of the technology and its dynamic capabilities. Results demonstrate that in a high radio interference environment, performance of the UWB positioning system and drone achieve a 0.11% and 1.23% error on average from the programmed flight path gradient for TDOA and TWR respectively. The results of this investigation suggest that the technology is ready and capable of being implemented on real-world systems, with the recommendation that the technology be coupled with sensor fusion elements in relative positioning applications.
Graph Structure Fusion for Multiview Clustering

Most existing multiview clustering methods take graphs, which are usually predefined independently in each view, as input to uncover data distribution. These methods ignore the correlation of graph structure among multiple views and clustering results highly depend on the quality of predefined affinity graphs. We address the problem of multiview clustering by seamlessly integrating graph structures of different views to fully exploit the geometric property of underlying data structure. The proposed method is based on the assumption that the intrinsic underlying graph structure would assign corresponding connected component in each graph to the same cluster. Different graphs from multiple views are integrated by using the Hadamard product since different views usually together admit the same underlying structure across multiple views. Specifically, these graphs are integrated into a global one and the structure of the global graph is adaptively tuned by a well-designed objective function so that the number of components of the graph is exactly equal to the number of clusters. It is worth noting that we directly obtain cluster indicators from the graph itself without performing further graph-cut or $k$k-means clustering algorithms. Experiments show the proposed method obtains better clustering performance than the state-of-the-art methods.
APPLICATION OF SINGLE WIRELESS HOLTER TO SIMULTANEOUS EMG, MMG AND EIM MEASUREMENT OF HUMAN MUSCLES ACTIVITY

This paper describes application and design of wireless holter with innovative functionality, used it in field of human muscle monitoring. In our experiments we monitored EMG (electromyography), MMG (mechanomyography) and EIM (electrical impedance myography) all by single device. It is first time when these all parameters were monitored simultaneously taking advantage of the holter device data output in order to find the signals interconnection. Our data were compared with normally used medical device and signal quality was verified.
COGNITIVE ABILITIES QUESTIONNAIRE: DEVELOPMENT AND EVALUATION OF PSYCHOMETRIC PROPERTIES

فده تيلاعف : يياناوت دنمزاين هنازور ياه يياـناوت نـيا صـقن و تسا يتخانش ياه اـب اـه تيلاعف نيا يسررب فدـه . تـسا يياـسانش لـباق اه نوـمزآ كـي يـحارط ،هـعلاطم نـيا شسرپ همان يياناوت شجنس يارب يا يـسررب و يتخانش ياه ناور تايـصوصخ نآ يجنـس . تسا شور كي ،دش ارجا ازجم يعطقم ةعلاطم هس تروص هب هك شهوژپ نيا رد : و رازه 95 )رفن 444 و درم 651 شـسرپ ييادـتبا ةخسن ليمكت يارب (نز لـيلحت روـظنم هـب هـمان ،يفاشتكا يلماع 50 نومزآ ةعلاطم رد رفن هـب هاـم كـي اـت هـتفه هـس ةلصاف اب نومزآزاب اپ روـظنم شـسرپ يياـي و هـمان 181 و دنملاـس 224 زـيمت يـياور سررـب يارـب ناوـج شسرپ هداد ليلحت يارب .دندرك تكرش همان نومزآ زا ،اه فورگوـلوموك ،يلماع ليلحت ياه .دش هدافتسا يت نومزآ و نوسريپ نومزآ ،فنريمسا هتفاي اه ،يفاشتكا يلماع ليلحت : تـفه ختنا هجوت و يراهم لرتنك ،هظفاح لماع ميمصت ،يبا هـمانرب ،يرـيگ ،رادـياپ هـجوت ،يزـير فاطعنا و يعامتجا تخانش خاـبنورك ياـفلآ .درـك جارختـسا نومزآ زا ار يتخانش يريذپ شسرپ همان 834 / 0 حطـس رد نوـمزآ تـبون ود نوسريپ يگتسبمه و 01 / 0 .دوـب راداـنعم سايقم يمامت نومزآ ياه حطس رد (يعامتجا تخانش زج هب) 01 / 0 مه لدـعم اـب يگتـسب صخاـش يماـمت نيب يت نومزآ . دنتشاد نوـمزآ ياـه هـمانرب زـج هـب) تخانـش و يزـير انعم توافت (يعامتجا . داد ناشن يراد هجيتن يريگ شسرپ يياياپ و يياور : يحارط ةمان هدـش قـيقد يسررب اب دارفا يتخانش يياناوت . دوب بولطم يتخانش ياهدركراك يبايزرا روظنم هب تيلاعف . تسا يبايزرا لباق يتخانش يياناوت دنمزاين ةنازور ياه
Arousal, valence, and volume: how the influence of online review characteristics differs with respect to utilitarian and hedonic products

ABSTRACT Online reviews influence consumers’ purchase decisions. Product type – specifically, whether a product is utilitarian or hedonic – can help explain how consumers react to reviews. Characteristics of reviews – in particular, valence, measured by ratings, the arousal level of the language used in the text and the volume of the reviews – provide heuristics that consumers may use in making purchase decisions. Product type moderates the effect of these characteristics. Empirical evidence for this claim comes from multiple sources: a panel data analysis of 26,357 Amazon products and an online experiment with 541 participants. The findings of studies based on this evidence show that product type (hedonic or utilitarian) moderates the effect of the three heuristic attributes of online reviews (valence, volume, and arousal) on sales. The analysis uses OLS-fixed effects models and Granger causality tests. These findings explain why past studies have found that sometimes online review valence is more influential than volume and arousal with respect to sales and why sometimes this is reversed. Our findings have significant theoretical and practical implications for the design of choice architectures in online review systems.
Webpage Classification Using Naïve Bayes Classifier and Information Retrieval Method to Block the Pornography Contents

The need of information is such magnitude. It would trigger advances in information technology. Many things can be done by using the internet. The main objective that people use the Internet is to find the information. Unfortunately, not all the information available on the internet it is true and good consumed. There are plenty of information on the internet which is a hoax and contains elements that are contrary to morals and ethics such as terrorism, racism, and pornography. Thus, it required a strong faith and knowledge to be able to sort the incoming information. Due there are many children who also use the internet and conditions where the parents cannot supervise the activities of their children continuously, it would require an application that is embedded in the web browser so that bad content can be blocked automatically. This article focuses on the research of handling pornographic content on the text based webpages. It needed a smart application to be able to distinguish text that contains pornography. Thus, we are implementing artificial intelligence into our research by applying Naive Bayes and information retrieval method. As a result, the application is able to block 88.02% of the pornographic content. Keywords-pornography; web content filtering; smart system; information retrieval
Robust night target tracking via infrared and visible video fusion

Night target tracking usually fails due to various reasons such as insufficient light, appearance change, motion blur, illumination variation, and deformation. Because infrared (IR) and visible video data provides comple- mentary information that can be utilized suitably and efficiently, we explore a novel framework by combining correlation filter-based visible tracking and Markov chain Monte Carlo (MCMC)-based IR tracking to overcome these challenges. In this framework, the two types of videos are asynchronous, and the frame rate of visible video is several times faster than that of IR video. Visible video is first used for location and scale estimation by solving a ridge regression problem efficiently in the correlation filter domain. When recording IR data, we use a uniquely designed feature shape context descriptor for the best location and scale estimation of an IR video target by using the MCMC particle filter. Then, we use candidate region location-scale fusion rules for the final target tracking update. Meanwhile, we build an accurately labeled IR and visible target tracking dataset for experiments. The result shows that the performance of our proposed approach is better than the state-of-the-art trackers for night target tracking, and our approach can significantly improve re-tracking performance when there is the drift.
The Application of Modern Optimization Packages in Multisensor Data Assimilation [STUB]

This poster has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory (“Argonne”). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. This research was supported by the Climate Model Development and Validation activity funded by the Office of Biological and Environmental Research in the US Department of Energy Office of Science. Computing resources were provided by the Laboratory Computing Resource Center of Argonne National Laboratory. References
Trust Management Techniques for the Internet of Things: A Survey

A vision of the future Internet is introduced in such a fashion that various computing devices are connected together to form a network called Internet of Things (IoT). This network will generate massive data that may be leveraged for entertainment, security, and most importantly user trust. Yet, trust is an imperative obstruction that may hinder the IoT growth and even delay the substantial squeeze of a number of applications. In this survey, an extensive analysis of trust management techniques along with their pros and cons is presented in a different context. In comparison with other surveys, the goal is to provide a systematic description of the most relevant trust management techniques to help researchers understand that how various systems fit together to bring preferred functionalities without examining different standards. Besides, the lessons learned are presented, and the views are argued regarding the primary goal trust which is likely to play in the future Internet.
Millimeter-Wave for Unmanned Aerial Vehicles Networks: Enabling Multi-Beam Multi-Stream Communications

With the fifth-generation (5G) mobile networks being actively standardized and deployed, many new vehicular communications technologies are developed to support and enrich various application scenarios. Unmanned aerial vehicle (UAV) enabled communications emerges as one of many promising solutions of constructing the next-generation highly reconfigurable and mobile networks. In this article, we first investigate and envision the challenges of future UAV applications from the net-work, system, and hardware design perspectives, and then pre-sent a UAV aerial base station (ABS) prototype which works at millimeter-wave (mmWave) bands and enable multi-beam mul-ti-stream communications. In terms of the field trial tests of the first UAV-ABS of its kind in the world, multi-giga-bit-per-second data rate of uplink and downlink is verified with good stability and reliability against mildly challenging weather conditions.
An internet-based self-help intervention program application for traumatized persons

Objective:To examine the user dropouts at different stages of an internet-based intervention program application for traumatized persons and to investigate the influence of posttraumatic symptoms severity,perceived social acknowledgement and trauma disclosure attitudes on the usage of the program.Methods:A total of 428 traumatized persons were recruited via internet advertisements from 22 cities and provinces.Among them 103 gave consent to participation and were randomized into the treatment and waiting list groups.After completing pre-treatment test,the treatment group used the intervention program for one month.The waiting list group received one-month delayed treatment after they filled out post-waiting test.To examine the usage of the program,two new groups were used in data analyses,consisting of participants using or not using the intervention website.Participants' adherence to the program was examined with pre-treatment dropout,visiting days and pages visited at the website,and follow-up dropout.Measures used included the Posttraumatic Diagnostic Scale(PDS),Disclosure of Trauma Questionnaire(DTQ),and Social Acknowledgement Questionnaire(SAQ). Results:Among 103 participants,61(59.2%) used the website and 42(40.8%) dropped out before the treatment.Compared to using the website group,the participants who dropped out before intervention scored higher on the DTQ "urge to talk" [(2.1±1.2) vs.(1.5±1.0),P0.05] and consisted of more females(86% vs.69%,P=0.050). The number of users visiting the website decreased sharply from 61(10%) in the first week to 19(31%) in the second week.During one-month treatment period,51(84%) users visited the website for five days or less,and four(7%) users visited it more than 10 days with a maximum of 12;the mean of pages visited number was(81.3±77.1),and 18(30%) users visited(repeatedly) more than 100 pages,with a maximum of 295,at the website which contains 118 pages.Linear regression analyses showed that the users' visiting days at the website were positively correlated with the SAQ family disapproval scores(β=0.31,P0.05),and the number of pages visited was positively correlated with the SAQ general disapproval scores(β=0.31,P0.05). Conclusion:It suggests that individuals' urge to talk may influence their adoption of internet-based self-help interventions after trauma.Users might repeatedly read some contents of the self-help intervention programs.Perceived disapproval from family and social network may have influence on traumatized persons' adherence to the programs.
A Graduation Certificate Verification Model via Utilization of the Blockchain Technology

The graduation certificates issued by universities and other educational institutions are among the most important documents for graduates. A certificate is a proof of a graduate’s qualification and can be used to apply for a job or other related matters. The advance of information technology and the availability of low-cost and high-quality office equipment in the market have enabled forgery of important documents such as certificates, identity cards, and passports. However, verification of certificates using traditional methods is costly and very time-consuming. Therefore, the goal of this paper is to propose a theoretical model that can offer a potential solution for academic certificate issuing and verification using blockchain technology. The blockchain technology contains several functions including hash, public/private key cryptography, digital signatures, peer-to-peer networks and proof of work. The model uses various elements to formulate the block which is divided into two main processes, namely issuing a digitally signed academic certificate and verifying the academic certificate. The proposed model showed that academic certificate authentication could leverage the blockchain technology. It meets all the conditions necessary for a modern academic certificate verification system. In addition, it closes the gaps and challenges in the existing methods to verify academic certificate authenticity.
DEVELOPING A PREDICTIVE APPROACH TO KNOWLEDGE

Understanding how an artificial agent may represent, acquire, update, and use large amounts of knowledge has long been an important research challenge in artificial intelligence. The quantity of knowledge, or knowing a lot, may be nicely thought of as making and updating many predictions about many different courses of action. This predictive approach to knowledge ensures the knowledge is grounded in and learned from low-level data generated by an autonomous agent interacting with the world. Because predictive knowledge can be maintained without human intervention, its acquisition can potentially scale with available data and computing resources. The idea that knowledge might be expressed as prediction has been explored by Cunningham (1972), Becker (1973), Drescher (1990), Sutton and Tanner (2005), Rafols (2006), and Sutton (2009, 2012). Other uses of predictions include representing state with predictions (Littman, Sutton &, Singh 2002; Boots et al. 2010) and modeling partially observable domains (Talvitie & Singh 2011). Unfortunately, technical challenges related to numerical instability, divergence under off-policy sampling, and computational complexity have limited the applicability and scalability of predictive knowledge acquisition in practice. This thesis explores a new approach to representing and acquiring predictive knowledge on a robot. The key idea is that value functions, from reinforcement learning, can be used to represent policy-contingent declarative and goal-oriented predictive knowledge. We use recently developed gradient-TD methods that are compatible with off-policy learning and function approximation to explore the practicality of making and updating many predictions in parallel, while the agent interacts with the world from continuous inputs on a robot. The work described here includes both empirical demonstrations of the effectiveness of our new approach and new algorithmic contributions useful for scaling prediction learning. We demonstrate that our value functions are practically learnable and can encode a variety of knowledge with several experiments—including a demonstration of the psychological
Set Pair Social Network Analysis Model and its Application

Through the research of information mining of social networks,this paper finds that there exists uncertainty in the incidence relationship of individuals by the use of social networks,and social network is changing dynamically.Aims at the uncertainty and dynamic problems,this paper presents a set pair social network analysis model and related properties of set pair social network analysis model,gives a applications of model.
Perceptual and Memory Deficits in Unilateral Neglect

Unilateral neglect is a disorder in which patients behave as if the left half of space has ceased to exist. The disorder typically arises from right hemisphere brain damage involving the inferior parietal and superior temporal cortices. Classic models of neglect have suggested that the disorder represents impaired attentional functioning. More recently, research has suggested that the heterogeneous symptoms of neglect can not be fully explained by attentional deficits alone. This thesis first examined performance on both visual working memory and attention tasks in patients with right brain damage, some of whom presented with neglect. Results showed severe deficits in both domains. Next, prism adaptation, a treatment long understood to improve attention in neglect, was used to examine whether the technique could improve performance in domains not specifically related to attention. Results showed that prisms failed to meaningfully improve severe deficits in time perception and spatial working memory. Such deficits outside spatial attention may be the result of damage to perceptual systems. The final experimental chapter examined the potential for saccadic adaptation, an analogue of prism adaptation previously shown to induce some perceptual change, to influence both perception and action in ways relevant to neglect. Here, healthy individuals performed the classic saccadic adaptation paradigm, with performance on a line bisection and landmark task used as indices of action and perception respectively. The task was not found to measurably influence either domain. Overall, the thesis supports recent research that claims that neglect involves independent deficits, involving more than attention. Specifically, it provides evidence that working memory and perceptual deficits are not strongly coupled to spatial attention.
SEARCHSENSE: A SEMANTIC META SEARCH ENGINE

Despite the recent advancements in information retrieval research and in online search engines, satisfying the needs of search engines users remains largely challenging. This is due to many reasons including the size and richness of information available over the internet and the semantic gap between the intention of search engine user and how search engines understand that intention. This article highlights the main reasons for ineffective web searches and sheds the lights on the status of ongoing research stream, the SearchSense project, which focuses on improving the effectiveness of search engines in satisfying users’ needs. The research has been carried out through multiple projects that were implemented over several years with main overall focus on designing an effective semantic search engine. SearchSense employs the semantic technology to bridge the gap between search engines and their users and to provide a better presentation of web search results. SearchSense could be used as a Meta Semantic Search Engineontop of regular search engine or could easily be incorporated in any information retrieval system. The article describes the overall framework of the solution and outlines its main components. Details on the technicalities of the solution components are presented in relevant articles. The article also provided a summary of the results of the experiments that have been conducted to test the effectiveness of the solution.
Essays on Teaching Excellence Toward the Best in the Academy

Academic departments from physics to philosophy to physical therapy face new demands for “assessment of student learning. ” It’s hard to argue against the basic idea of assessment: when a department invests time and resources trying to nurture student learning, it should ask itself: Are they learning? Yet departments may also fear that assessment will require them to dumb-down their teaching; use standardized tests; teach alike; or compromise academic freedom. Every department wonders how it will find the time and resources for one more thing.