Miracle-dz/UniFAR-FTUs huggingface dataset:
Testing of parameters of proposed robotic wrist based on the precision modules

The use of precision actuators in robotic arm comes from the need to ensure the resulting accuracy of the robot at the maximum speed of movement. The replacement of actuators by means of electrical module allows the use of carrier body of the module for gripping flanges or other modules. Development of new modules is based on the requirement of providing a complete solution for the customer’s needs. After the development of new modules, the producer checks the parameters, receives feedback, and uses the authentication options in the independent workplaces, which can provide impartial results. Based on this data, manufacturers can optimize their solutions and deliver the products to market, complying with not only their vision but mainly the needs of customers. This article describes how to verify the characteristics of the modules used in the construction of robotic wrist. It primarily focuses on verification of the accuracy of results and repeatability of position of the wrist on output flange end module. In addition, it presents the design of the testing stand and selection methodologies of measurement. The declared values are compared with the values measured during verification.
Quantum Computing: A Gentle Introduction

The combination of two of the twentieth centurys most influential and revolutionary scientific theories, information theory and quantum mechanics, gave rise to a radically new view of computing and information. Quantum information processing explores the implications of using quantum mechanics instead of classical mechanics to model information and its processing. Quantum computing is not about changing the physical substrate on which computation is done from classical to quantum but about changing the notion of computation itself, at the most basic level. The fundamental unit of computation is no longer the bit but the quantum bit or qubit. This comprehensive introduction to the field offers a thorough exposition of quantum computing and the underlying concepts of quantum physics, explaining all the relevant mathematics and offering numerous examples. With its careful development of concepts and thorough explanations, the book makes quantum computing accessible to students and professionals in mathematics, computer science, and engineering. A reader with no prior knowledge of quantum physics (but with sufficient knowledge of linear algebra) will be able to gain a fluent understanding by working through the book. The text covers the basic building blocks of quantum information processing, quantum bits and quantum gates, showing their relationship to the key quantum concepts of quantum measurement, quantum state transformation, and entanglement between quantum subsystems; it treats quantum algorithms, discussing notions of complexity and describing a number of simple algorithms as well as the most significant algorithms to date; and it explores entanglement and robust quantum computation, investigating such topics as quantifying entanglement, decoherence, quantum error correction, and fault tolerance.
Scalable Modeling of Multivariate Longitudinal Data for Prediction of Chronic Kidney Disease Progression

Prediction of the future trajectory of a disease is an important challenge for personalized medicine and population health management. However, many complex chronic diseases exhibit large degrees of heterogeneity, and furthermore there is not always a single readily available biomarker to quantify disease severity. Even when such a clinical variable exists, there are often additional related biomarkers routinely measured for patients that may better inform the predictions of their future disease state. To this end, we propose a novel probabilistic generative model for multivariate longitudinal data that captures dependencies between multivariate trajectories. We use a Gaussian process based regression model for each individual trajectory, and build off ideas from latent class models to induce dependence between their mean functions. We fit our method using a scalable variational inference algorithm to a large dataset of longitudinal electronic patient health records, and find that it improves dynamic predictions compared to a recent state of the art method. Our local accountable care organization then uses the model predictions during chart reviews of high risk patients with chronic kidney disease.
Integrated mobility and third-party AAA management for 4GWW

In the near future it is expected that IPv6 will lie at the backbone of all networks. Networks will consist of more mobile devices than wired terminals. Mobile users will demand to be always best connected and served (ABC&S). Such a dynamic system will require seamless mobility and flexible authentication, authorization and accounting (AAA) scheme. Various emerging protocols may play a part in this fourth generation wireless world (4GWW), e.g. Mobile IPv6 (MIPv6), hierarchical MIPv6 (HMIPv6), fast MIPv6 (FMIPv6) and the Diameter protocol. Used alone each of these protocols have their own strengths and weaknesses, however, a hybrid of all these protocols may emphasize their various strengths and eliminate their individual weaknesses. This paper proposes a new third-party AAA architectural framework, employing a hybrid signaling protocol and integrating mobility and AAA functions for 4GWW orientated to a more consumer based business model (CBM).
Current Practices in Serious Game Research: A Review from a Learning Outcomes Perspective

Despite scant empirical substantiation, serious games are in widespread use. The authors review 28 studies with empirical data from a learning outcome perspective to outline the effectiveness of serious games (compared to other learning approaches and specific game features). They conclude that serious games potentially improve the acquisition of knowledge and cognitive skills. Moreover, they seem to be promising for the acquisition of fine-grid motor skills and to accomplish attitudinal change. However, not all game features increase the effectiveness of the game. To further advance game research the chapter proposes recommendations including the alignment of learning outcome(s) and game type, the alignment of the game complexity and human cognitive processes, attention for cognitive and motivational processes, research on specific mitigating factors like gender on game effectiveness and, finally, developing new ways of assessing game effectiveness. (http://www.cs.uu.nl/docs/vakken/b3elg/literatuur_files/Wouters.pdf)
Review on the achievements in simultaneous localization and mapping for mobile robot based on vision sensor

Simultaneous localization and mapping (SLAM) are necessary prerequisites to make mobile robot truly autonomous. The vision sensor attracts more and more attention in the SLAM research for its rich information of the environment. This paper summarizes the state of the art in the vision- based SLAM from the aspects such as the deployment of vision sensors, the extraction of visual features, the implementation mechanism of visual SLAM, the representation of the map and the effect of environ-ment on visual SLAM. Some classical visual SLAM methods are compared and analyzed. The research prospects are described.
An XMM-Newton Study of the 401 Hz Accreting Pulsar SAX J1808.4–3658 in Quiescence

SAX J1808.4-3658 is a unique source, being the first low-mass X-ray binary showing coherent pulsations at a spin period comparable to that of millisecond radio pulsars. Here we present an XMM-Newton observation of SAX J1808.4-3658 in quiescence, the first that assessed its quiescent luminosity and spectrum with a good signal-to-noise ratio. XMM-Newton did not reveal other sources in the vicinity of SAX J1808.4-3658, likely indicating that the source was also detected by previous BeppoSAX and ASCA observations, even with large positional and flux uncertainties. We derive a 0.5-10 keV unabsorbed luminosity of LX = 5 × 1031 ergs s-1, a relatively low value compared with other neutron star soft X-ray transient sources. At variance with other soft X-ray transients, the quiescent spectrum of SAX J1808.4-3658 was dominated by a hard (Γ ~ 1.5) power law with only a minor contribution (≲10%) from a soft blackbody component. If the power law originates in the shock between the wind of a turned-on radio pulsar and matter outflowing from the companion, then a spin-down to an X-ray luminosity conversion efficiency of η ~ 10-3 is derived; this is in line with the value estimated from the eclipsing radio pulsar PSR J1740-5340. Within the deep crustal heating model, the faintness of the blackbody-like component indicates that SAX J1808.4-3658 likely hosts a massive neutron star (M ≳ 1.7 M☉).
Arabic Treebank: from Phrase-Structure Trees to Dependency Trees

The aim here is to create a dependency treebank from a phrase-structure treebank for Arabic. Arabic has a number of characteristics,described below, which make it particularly challenging to any natural language processing (NLP) applications. We describe an encouraging semi-automatic technique for converting phrase-structure trees to dependency trees by using a head percolation table.One of the most signi? cant challenges here is the determination of the head of each subtree. We therefore examined different versionsof the head percolation table to ? nd the best priority list for each entry in the table. Given that there is no absolute measure of the? correctness? of a conversion of a phrase structure tree to dependency form, we tested the various transformations by seeing how well astate-of-the-art dependency parser learnt the generalisations that were embodied by the converted trees.
Near Duplicate Document Detection using Document Image

With development, access of Internet has allowed storage of huge documents containing information. Identifying near duplicate documents among those documents is a major problem in information retrieval due to their dimensionality which leads to high cost time. We propose an algorithm based on tf-idf method with importance and discriminative power of a term within a single document to speed up search process for detecting how documents are similar in collection. Using only 26.6% of original document size, our method performs well on efficiency and memory usage as we have reduced compare to the original one and that leads to a decreased time in searching process for similar documents in a collection.
Object recognition system by depth camera using k-nearest neighbors and naïve Bayes classification for robot

Today, the robot technology is used for many applications. The robot is expected to dwell in human society with the abilities such as perception, decision, and non-injury. The study aims to determine the efficiency of the robot object recognition using k-nearest neighbor (KNN) and naive Bayes classification. The red, green, and blue (RGB) camera of microsoft kinect sensor was use to classify the detail. The experimental showedthe accuracy rate of KNN was 77.0% while the naive Bayes classification was 60.4%.
The Research of Real-time Attitude Measurement Based on Theodolite by Using Auto collimation

Aerospace products have high-precision measurement requirements for attitude parameters, and cubic mirror-theodolite alignment measurement method is widely used. Based on the principle of theodolite auto collimation research, product attitude adjustment measurement proposed by real-time measurement, principle of the method, the scope and application experience have been introduced. This method can achieve real-time measurement of the product, adjustment of the operation is accuracy and immediate intervention, reduce the number of instrument station calibration and product attitude measurement frequency, improve measurement efficiency, and reduce operating strength.
A Workflow Model Based on Timed Petri Net

How to modeling a business process is discussed in this paper, in which the task stream and the resource stream are concurrently occurred. A Resource/Task net (R/T-net) based on the timed Petri net and the modeling process by using R/T-net for workflow is proposed. The resource dependence and expectancy set in task model can be used to control the task transition, while the fire-rule and the routing-rule can be used to control cooperation, synchronism, assignment and transition of resource, so that it is more powerful than the Petri net in the workflow modeling, such as the office automation, the product manufacturing, the material transaction, and so on.
Exploring Gamification Techniques for Classroom Management

A variety of gamification techniques from the literature are used in two college courses. Some techniques, such as an experience point-based system and leaderboards, proved confusing or frustrating, while other techniques, such as adding a meaningful narrative layer and allowing students to create their own learning paths, engaged students more deeply. In this article, the techniques used and the effects of each are explored and suggestions are provided for instructors considering adding game layers to the classroom.
Design and implementation of a Stroke Rehabilitation Registry for the systematic assessment of processes and outcomes and the development of data-driven prediction models: The STRATEGY study protocol

Background Stroke represents the second preventable cause of death after cardiovascular disease and the third global cause of disability. In countries where national registries of the clinical quality of stroke care have been established, the publication and sharing of the collected data have led to an improvement in the quality of care and survival of patients. However, information on rehabilitation processes and outcomes is often lacking, and predictors of functional outcomes remain poorly explored. This paper describes a multicenter study protocol to implement a Stroke rehabilitation Registry, mainly based on a multidimensional assessment proposed by the Italian Society of Physical and Rehabilitation Medicine (PMIC2020), in a pilot Italian cohort of stroke survivors undergoing post-acute inpatient rehabilitation, to provide a systematic assessment of processes and outcomes and develop data-driven prediction models of functional outcomes. Methods All patients with a diagnosis of ischemic or haemorrhagic stroke confirmed by clinical assessment, admitted to intensive rehabilitation units within 30 days from the acute event, aged 18+, and providing informed consent will be enrolled. Measures will be taken at admission (T0), at discharge (T1), and at follow-up, 3 months (T2) and 6 months (T3) after the stroke. Assessment variables include anamnestic data, clinical and nursing complexity information and measures of body structures and function, activity and participation (PMIC2020), rehabilitation interventions, adverse events and discharge data. The modified Barthel Index will be our primary outcome. In addition to classical biostatistical analysis, learning algorithms will be cross-validated to achieve data-driven prognosis prediction models. Conclusions This study will test the feasibility of a stroke rehabilitation registry in the Italian health context and provide a systematic assessment of processes and outcomes for quality assessment and benchmarking. By the development of data-driven prediction models in stroke rehabilitation, this study will pave the way for the development of decision support tools for patient-oriented therapy planning and rehabilitation outcomes maximization. Clinical tial registration The registration on ClinicalTrials.gov is ongoing and under review. The identification number will be provided when the review process will be completed.
Digitale Bildsignalverarbeitung : Grundlagen, Verfahren, Beispiele

Mit dem vorliegenden Buch soll eine Einfuhrung in die digitale Bildverarbeitung gegeben werden. Hierbei werden gemas der allgemeinen Themenstellung der vorliegenden Buchreihe insbesondere die signalorientierten Aspekte der Bildverarbeitung in den Vordergrund gestellt. Den besonderen Reiz der Bildverarbeitung sehe ich in dem interessanten Zusammenwirken von intuitiven und theoretischen Losungsansatzen, die jeweils durch ”anschauliche” Experimente evaluierbar sind. Entsprechend wird in der vorliegenden Darstellung versucht, insbesondere anhand von zahlreichen Simulationsbeispielen ein Verstandnis dieses jungen, an Bedeutung zunehmenden Gebietes beim Leser zu erreichen. Zum Verstandnis des Buches sind auser Kenntnissen der Mathematik, wie sie etwa in ingenieurswissenschaftlichen Studiengangen vermittelt werden, Grundkenntnisse der linearen Systemtheorie bzw. Signalverarbeitung und Grundkenntnisse der Wahrscheinlichkeitsrechnung vorteilhaft.
A preliminary investigation of amino acid and acylcarnitine levels in neonates from the Tibet autonomous

Background: The purpose of the study was to investigate the levels of amino acids and acylcarnitines in newborns of the Tibet Autonomous Region for the first time and to provide an experimental basis for the diagnosis of genetic metabolic diseases. Methods: We detected concentrations of 43 kinds of amino acids, acylcarnitines and succinylacetone in the dried blood spots of 18482 newborns using liquid chromatography tandem mass spectrometry and diagnose the case by gene sequencing. We compared the indexes between Tibet and our lab, where most data come from an inland area and Han Chinese people. Then we compared amino acid and acylcarnitine levels of seven regions in Tibet and explored their impact factors. Results: We described the levels of amino acids and acylcarnitines in Tibet newborns using 95% confidence intervals. The distribution of amino acid and acylcarnitines were different in Tibet. Conclusion: This study has contributed to filling in the blanks of Tibet newborn screening, which should be considered in the newborn metabolic disease screening in this area.
Genome-wide identi ﬁ cation and analysis of the cytokinin oxidase/ dehydrogenase ( ckx ) gene family in ﬁ nger millet ( Eleusine coracana )

Cytokinin dehydrogenase/oxidase (CKX) enzymes play a key role in regulating cytokinin (CK) levels in plants by degrading the excess of this phytohormone. CKX genes have proven an attractive target for genetic engineering, as their silencing boosts cytokinin accumulation in various tissues, thereby contributing to a rapid increase in biomass and overall plant productivity. We previously reported a similar effect in ﬁ nger millet ( Eleusine coracana ) somaclonal lines, caused by downregulation of EcCKX1 and EcCKX2 . However, the CKX gene family has numerous representatives, especially in allopolyploid crop species, such as E. coracana . To date, the entire CKX gene family of E. coracana and its related species has not been characterized. We offer here, for the ﬁ rst time, a comprehensive genome-wide identi ﬁ cation and analysis of a panel of CKX genes in ﬁ nger millet. The functional genes identi ﬁ ed in the E. coracana genome are compared with the previously-identi ﬁ ed genes, EcCKX1 and EcCKX2 . Exon-intron structural analysis and motif analysis of FAD- and CK-binding domains are performed. The phylogeny of the EcCKX genes suggests that CKX genes are divided into several distinct groups, corresponding to certain isotypes. Finally, the phenotypic effect of EcCKX1 and EcCKX2 in partially silencing the SE7 somaclonal line is investigated, showing that lines de ﬁ cient in CKX -expression demonstrate increased grain yield and greater bushiness, enhanced biomass accumulation, and a shorter vegetation cycle. structural CK-binding ﬁ ﬁ manipulation ﬁ nger CKX
An Efficient Human Authentication Using Multibiometric Approach for High Accuracy in Recognition Rate

In the development of recent technologies, a biometrics system has been the important affordable and more reliable system. A Biometrics identification system refers to the automatic recognition of individual person based on their characteristics. Biometrics system has two broad areas namely unimodal and multimodal biometric system. In Unimodal system it has some disadvantage due to its lack of non-universality and unacceptable error rate. To overcome the Unimodal challenging issues, Multimodal is the better system for its two or three level of identification and verification. In this paper, multimodal biometrics system characteristics are studied with various biometrics traits. The proposed system uses a multibiometric approach for authenticating a person. The multibiometric system comprises of multimodal (iris, fingerprint and face) and multi algorithm (Iterative Parallel Thinning Algorithm, Fuzzy Pattern Based with Laplacianfaces, Optimized Daugman Algorithm) biometrics whose recognition rate will be calculated separately using GAR, FAR and FRR scores. Finally, the matching scores of both the methods will be fused to find the final recognition rate, which will prove that multibiometric system provides high accuracy in recognizing a person, and highly secured against spoofing attacks.
Clustering short status messages: A topic model based approach

Recently, there has been an exponential rise in the use of online social media systems like Twitter and Facebook. Even more usage has been observed during events related to natural disasters, political turmoil or other such crises. Tweets or status messages are short and may not carry enough contextual clues. Hence, applying traditional natural language processing algorithms on such data is challenging. Topic model is a popular method for modeling term frequency occurrences for documents in a given corpus. A topic basically consists of set of words that co-occur frequently. Unsupervised nature allows topic models to be trained easily on datasets meant for specific domains. We use the topic modeling feature of MALLET - a machine learning tool kit, to generate topic models from unlabelled data. We propose a way to cluster tweets by using the topic distributions in each tweet. We address the problem of determining which topic model is optimal for clustering tweets based on its clustering performances. We also demonstrate a use case wherein we cluster Twitter users based on the content they tweet. We back our research with experimental results and evaluations.
Optical encryption device for software protection

An optical-based hardware encryption device for software protection is proposed. Software piracy and illegal usage require that software operation is secured through a form of hardware protection. Electronic-based hardware keys such as dongle keys may be vulnerable to attacks through reverse engineered technology. A simple optical device can be included as part of the hardware key where it can be used as an encryption device. Software users will require specific hardware key with built optical device in order to operate the software. The LED activated optical device can produce encrypted signals via generated optical codes solely based on the geometrical feature of the optical device. A suitable form of optical code generating device is presented in the form of 1xN asymmetric waveguide coupler.
New Concept for FES-Induced Movements

Functional Electrical Stimulation (FES) had become a viable option for movement restoration, therapy and rehabilitation in neurologically impaired subjects. Although the number of such subjects increase globally but only few orthosis devices combine with the technique are available and are costly. A factor resulting to this could be stringent requirement for such devices to have passed clinical acceptance. In that regard a new approach which utilize the patient wheelchair as support and also a novel control system to synchronize the stimulation such that the movement is accomplished safely was proposed. It is expected to improve well-being, social integration, independence, cost, and healthcare delivery.