Miracle-dz/UniFAR-FTUs huggingface dataset:
Admittance control of the intelligent assist robot manipulator for people with duchenne muscular dystrophy

ADMITTANCE CONTROL OF THE INTELLIGENT ASSIST ROBOT MANIPULATOR FOR PEOPLE WITH DUCHENNE MUSCULAR DYSTROPHY by Madeline Corrigan Duchenne muscular dystrophy (DMD), a neuromuscular disease with a prevalence of 1 in 3500 male births, results in characteristic muscle weakness which is progressive with age and leads to loss of independence. And, in this population, maintaining optimal quality of life depends on the preservation of self-sufficiency. Despite the loss of function, nonambulant people with DMD retain some muscle strength, just not sufficient strength to overcome the force of gravity. There are a number of upper-limb passive and active orthotic devices that attempt to augment the loss of upper limb function in people with DMD by taking advantage of this residual muscle strength by providing anti-gravity assistance. The majority of these devices, as well as currently available robotic manipulators, are considerably limited in the functionality that they provide, rendering them obtrusive and unaccommodating, resulting in lack of use by this population. This thesis presents the design of a novel upper limb assistive robotic device. This design involves the use of admittance control as the interface for the intelligent Assist Robot Manipulator (iARM). A thorough qualitative and quantitative analysis of the prototype is performed, the results of which are presented. The quantitative analysis focuses on the ideal delay that is required of human-machine interfaces to ensure comfort and passivity. Additionally, potential contributors to the delay of the iARM are investigated. ADMITTANCE CONTROL OF THE INTELLIGENT ASSIST ROBOT MANIPULATOR FOR PEOPLE WITH DUCHENNE MUSCULAR DYSTROPHY by Madeline Corrigan A Thesis Submitted to the Faculty of New Jersey Institute of Technology in Partial Fulfillment of the Requirements for the Degree of Master of Science in Biomedical Engineering Department of Biomedical Engineering
Bringing Computational Thinking Into High School Mathematics and Science Classrooms

Computation is reshaping modern science and mathematics practices, but relatively few students have access to, or take, courses that adequately prepare them for the increasingly technological nature of these fields. Further, students who do study computational topics tend to not reflect the greater student body, with female and minority students being disproportionately underrepresented. To address these issues, we investigate the approach of embedding computational thinking content into required high school mathematics and science coursework. Using data from a 3-year implementation, we present results showing differences in attitudes towards computing by gender, while also finding similar gaps do not correlate with aptitude. Using pre/post measures, we then show female participants expressed improved confidence with computational thinking and interest in STEM careers. Additionally, we report a dosage effect, where participating in more activities resulted in greater learning gains, providing evidence in support of embedding computational thinking enhanced activities across high school curriculum.
Individualized solidarity

A good definition of solidarity was provided by the critical theorist and ‘guru of the New Left’ Herbert Marcuse, who described it as a refusal to let one’s happiness coexist with the sufferings of others. [1] Solidarity is readiness to make sacrifices for and share with others. It differs from mere compassion since it typically rests on a presumption of potential mutuality, based in a feeling of community or togetherness, of being comrades. When used in the context of social movements, solidarity usually also implies joint struggle against the cause of suffering or against a common adversary.
Uncovering hidden block structure

We develop a multistage procedure for uncovering the block structure in a matrix. Our algorithm combines standard combinatorial techniques with a novel clustering approach that merges both numerical and structural analysis. A central part of our process is to use a doubly stochastic scaling. We illustrate the use of our algorithm in partitioning sparse matrices for constructing a preconditioner for iterative methods. We also show how we can use our approach in community detection in both undirected and directed networks.
Bi-Stability in an Improved Memristor-Based Third-Order Wien-Bridge Oscillator

ABSTRACT This paper reports the emergence of bi-stability in a third-order memristive Wien-bridge oscillator. By transforming the parallel RC feedback network into a series resistor and capacitor (RC) feedback network in the previous non-ideal voltage-controlled memristor emulator, an improved memristor emulator is proposed and its fingerprints are exhibited. And then through introducing the proposed emulator to replace the parallel resistor in the conventional Wien-bridge oscillator, an improved memristor-based third-order Wien-bridge oscillator is constructed. Based on its mathematical model, the initial condition-dependent dynamical behaviour is revealed by theoretical analyses and numerical simulations and further verified by hardware experiments, from which the emergence of bi-stability in the memristive oscillator is well demonstrated.
AUTOMATIC HEIGHT ATTRIBUTE ASSIGNMENT FOR BUILDING POLYGONS : CITY MODELING WITH LEVEL OF DETAIL ZERO

In recent years there has been a significant rise in interest in 3D city modeling and this is coupled with a need to quickly update 3D city models. It is essential to increase the speed and the level of automation of 3D data capture if costs are to be sufficiently low to make large scale production of 3D data viable. We assume that building footprints are available in advance. In our case, these are building polygons of the Ordnance Survey OS MasterMap Topography Layer. We propose an economically viable solution for extracting a basic roof description for city modeling based on a reliable estimation of a set of height attributes for each building roof. The height attributes can be estimated using a Digital Surface Model (DSM) that has been generated using photogrammetry or from aerial laser scanning. If a DSM is not available in advance, aerial images are used to extract a DSM of the building roof by image matching. Two steps are required in order to make the crude DSM more reliable for the height estimation. In the first step, blunders are eliminated using an efficient blunder detection method based on a local density function. In the second step, the points belonging only to the building roof are preserved. For this purpose, the local gradient is calculated and points falling on steep slopes, i.e. points on the building walls, are eliminated from the DSM. In this paper we present our design strategy and the results of automatically creating low level city models for a range of urban test sites. We also present first results of the quality assessment of the generated 2.5D city models.
To Study The Anti-ulcer Effect Of Azadirachta Indica Leaf Extract And Isolated Compound Of Neemnimolicine (nc) In Comparison With Ulcer Healing Drugs On Gastric Mucosa Of Albino Rats

The anti-ulcer effects of methanolic extract of neem leaf (NLE) and neem compound nimolicine (NC) have been studied and the effects were compared with the ulcer healing drugs Ranitidine and Omeperazole on stomach of albino rats (Wistar strain). A total of 90 rats of both sex weighing 150-200 gms were used in the study. The rats were divided into six groups. Per oral administration of ethanol (100%) was used for ulcer induction.This group served as a check group. The control group was given Peanut oil 1 ml/day for the treatment of ulcer.The test groups received NLE 1ml/day (0.88 gm) p/o for 5 days and NC 1% (0.01 gm in the healing effects of p/o Ranitidine 50 mg/kg and Omeperazole (2.5mg/kg). The ulcer induction and healing effects both were confirmed by histopathology of the gastric tissues. The calculaton of ulcer index and ulcer inhibition percentage was done. The gastric secretion of H mEq/100 Gms of rat was also calculated.The antioxidant activity of NLE and NC was also done. Finally the identification of NLE, NC, and drugs in tissue extracts were done by HPLC. The results were analysed by using a one way ANOVA by a SPSS version 18 computerized software programme.The P value (P<0.05) was considered significant.The results show that NLE is better than NC and the anti ulcer effect of NLE can be compared to the anti-ulcer drugs Ranitidine and Omeperazole. The high antioxidant activity of NLE compared to NC may explain the mechanism of action of NLE which needs further explorations.The effects of NLE and NC on gastric secretion of H mEq/100 gms when compared with PNO and Ranitidine and Omeperazole were insignificant. However there was a significant difference on comparison of gastric secretion between PNO control and Ranitidine.Further studies are required to confirm the present study by conducting clinical trials. Anti ulcer treatment by NLE will be of financial benefit to the community in developing countries specially in Pakistan. In conclusion NLE has a better ulcer healing effect compared to NC. The effect of NLE can be compared to the ulcer healing drugs Ranitidine and Omeperazole
Development and validation of control methods for an actuation system in a morphing wing and aileron system

Morphing wing technology is one of the most efficient approaches to reduce fuel consumption and air pollution. The project, called “CRIAQ MDO 505”, was created to explore and evaluate the morphing wing technology. A wing tip system composed of a wing and an aileron was designed and manufactured by the CRIAQ team at the LARCASE. In the context of this project, an optimization approach was studied to improve the aerodynamic performance by changing a wing’s shape. Different methodologies were applied to control four internal actuators attached inside the morphing wing. These actuators morph the upper skin of the wing so that the transition region moves from the wing leading edge to its trailing edge. The research presented here is a part of the MDO 505 project. The aim of this research is to model, simulate and validate the control methods for the wing-tip morphing control system. ANFIS (Adaptive Neuro-Fuzzy Inference System), an adaptive control algorithm, was selected for the morphing wing-tip control. A combination of neural networks and adaptive fuzzy control, ANFIS takes advantage of the fuzzy inference system (FIS) and of the selflearning abilities of the neural network, and thus offers a promising approach for the stability and accuracy of the proposed control system. The simulation and experimental results were acquired using National Instruments (NI) Veristand, Maxon drives and MATLAB/Simulink software. Experimental tests were carried out at the IAR-NRC Wind Tunnel in Ottawa to validate the simulation results. The results showed the potential for applying intelligent control methods to improve the performance of aircraft using morphing wing technology.
Rhetorical Sentence Classification for Automatic Title Generation in Scientific Article

In this paper, we proposed a work onrhetorical corpus construction andsentence classification model experiment that specifically could be incorporated in automatic paper title generation task for scientific article. Rhetorical classification is treated as sequence labeling. Rhetorical sentence classification model is useful in task which considers document’s discourse structure. We performed experiments using two domains of datasets: computer science (CS dataset), and chemistry (GaN dataset). We evaluated the models using 10-fold-cross validation (0.70-0.79 weighted average F-measure) as well as on-the-run (0.30-0.36 error rate at best). We argued that our models performed best when handled using SMOTE filter for imbalanced data
Investigating the relationship between customer emotions and sportsbike aesthetics

When designing a sportsbike, design engineers need to adopt a multidisciplinary approach to develop a product which is aesthetically pleasing as well as aerodynamically optimised as possible. The objective of this research is to investigate the emotions experienced by motorcycle enthusiasts when looking at sportsbike designs. For this study, a literature review was carried out and an online questionnaire was designed with the expert input of two psychologists. The main part of the questionnaire consisted of eight motorcycle images together with a set of Emocards. The results were analysed and verified by using statistical methods. The outcomes of this study can be used to formulate a set of guidelines which can be implemented in a Knowledge Intensive Computer Aided Design (KI-CAD) system.
Kazuyuki Tanaka's Work on AND-OR Trees and Subsequent Developments

Outline Background Tanaka’s work (1) (2) Extension (1) (2) (3) References Appendix: Graphs Kazuyuki Tanaka’s work on AND-OR trees and subsequent development Toshio Suzuki Department of Math. and Information Sciences, Tokyo Metropolitan University, CTFM 2015, Tokyo Institute of Technology September 7–11, 2015
A Neural Basis for the Implementation of Deep Learning and Arti cial Intelligence

One of the mathematical cornerstones of modern data ana-lytics is machine learning whereby we automatically learn subtle patterns which may be hidden in training data, we associate those patterns with outcomes and we apply these patterns to new and unseen data and make predictions about as yet unseen outcomes. This form of data analytics al-lows us to bring value to the huge volumes of data that is collected from people, from the environment, from commerce, from online activities, from scienti c experiments, from many other sources. The mathematical basis for this form of machine learning has led to tools like Support Vector Machines which have shown moderate e ectiveness and good e ciency in their implementation. Recently, however, these have been usurped by the emergence of deep learning based on convolutional neural networks. In this presentation we will examine the basis for why such deep net-works are remarkably successful and accurate, their similarity to ways in which the human brain is organised, and the challenges of implementing such deep networks on conventional computer architectures.
Improved CUDA 3D Medical Image Registration

A combination of manual and genetic improvement (GI) can optimise a critical component of NiftyReg healthcare industry software across a diverse range of six nVidia graphics processing units (GPUs). The improved K20c kernel gives a speed up >2000 fold compared to released code on a 3GHz CPU
Extracting Data from Tutorials for Android API Recommendation

Code recommendation is becoming more and more important for software development because increasing numbers of existing libraries are being utilized by developers and code recommendation tools offer great aids to developers in quickly finding suitable APIs to use. There have been many studies on recommending various libraries and APIs for developers according to their requirements for certain functionalities, but little effort is spent in Android API recommendation. This study aims at building a database which stores the mapping co-relationships from Android APIs and their descriptive texts which describe the functionalities that can be achieved using the APIs. The data of such mapping co-relationships are extracted from online tutorials, and the database can be further used for recommending APIs for Android development by comparing the similarity between users’ requirements and the descriptive texts in the database.
Dense 3D Point Cloud Representation of a Scene Using Uncalibrated Monocular Vision

iv DEDICATION . vi TABLE OF CONTENTS. vii LIST OF FIGURES . ix LIST OF TABLES . xviii CHAPTER I: INTRODUCTION . 1 I.1 Overview . 2 CHAPTER II: BACKGROUND AND RELATED WORK . 4 II.1 Data Type and Acquisition . 5 II.2 Monocular Vision . 8 II.3 Visual Structure from Motion . 10 II.4 Probabilistic Volumetric Representation . 14 CHAPTER III: SCENE RECONSTRUCTION FRAMEWORK . 22 III.1 SURF Extraction . 23 III.2 Feature Matching and Disparities . 25 III.3 Depth Triangulation . 29 III.4 Point Localization . 31 III.5 Point Cloud Model . 32 III.6 Evaluation . 35
A strategic approach to providing cloud services for research and education community

The emergence of cloud services and technologies is providing the education and research community with many new and innovative ways to help institutions meet their user’s requirements. Cloud services bring many opportunities and benefits but are complex and present many challenges and risks. A well-defined strategy is essential to define the right approach to navigate through the many options and decisions required to provide successful cloud services. In this paper we do not propose a strategy for adopting cloud services for research and education institutions. Instead, we propose a methodology to guideline policy makers in research and education institutions to define an effective strategy to help ensure success in adopting cloud services.
Performance Analysis of Secure Integrated Circuits using Blowfish Algorithm

Security is an essential feature of Information Communication Technology (ICT). Information has to be encrypted at the transmitter side to maintain secrecy and decrypted at the receiver side to retrieve the original information for secure data transmission over insecure computer data communication networks. This paper analyzes the performance metrics of blowfish algorithm with and without Wave Dynamic Differential Logic (WDDL) style to incorporate security against differential power analysis. It compares Encryption Time (Et), Decryption Time (Dt) and Total Time (Tt) of Blowfish, Modified Blowfish with and without WDDL logic for secure Integrated Circuits (SIC) [7, 8]. Modified Blowfish with and without WDDL logic yielded good results compared to Blowfish with and without WDDL logic implementation . This paper is implemented using Xilinx webpack9.2i with Verilog Hardware Description language (HDL).
Pattern Based Filtering Approach for Big Data Application

Now a day’s large Number of services are emerging on the Internet due to various social networking sites, services, cloud computing. Result of this is, service-relevant data become too big to be effectively processed by traditional approaches. Similarly growing technologies like Internet of Things is also responsible for generation of massive raw data and this is reason complexity and resource consumption increases. In this paper the system suggest the concept of pattern based filtering in which it automatically discovers new, hidden or unsuspected data from the large text collection. The propose model MPBTM consist of topic distribution describing topic preference of each collection of document and Pattern-based topic representation
Universal language extension for conducting laboratory experiments on analogue and digital circuit design

The article examines in a specialized language different variants of software provision in a specialized environment for conducting laboratory experiments on analogue and digital circuits. A universal language for ULLE laboratory experiments was developed as a resident driver. When declaring an I / O variable (to connect to lab model), it is transmitted to the driver, which is invoked similarly to the system interrupt dispatcher. This way, each time a call is invoked, the model’s output channels and input variables are refreshed. Such a conversion allows the driver to work with programs written in different programming languages.
Secure Server Login by Using Third Party and Chaotic System

Server is popular among all companies and it used by most of them but due to the security threat on the server make this companies are concerned when using it so that in this paper we will design a secure system based on one time password and third parity authentication (smart phone). The proposed system make security to the login process of server by using one time password to authenticate person how have permission to login and third parity device (smart phone) as other level of security.
Teaching vowels physically

Abstract This paper explores issues surrounding teaching vowels physically. First the inherent difficulty of describing vowels compared to consonants is examined. Next the traditional descriptions of vowel formation by early phoneticians are presented along with other early phonetic constructs, such as the Cardinal Vowels and the vowel quadrilateral. The author argues against a blanket acceptance of these ideas. Despite being well-known among the speech teaching community, many speech science researchers have long since discredited many of these established concepts. The relevant findings are evaluated and it is maintained that there can be no exact articulator positions for vowel sounds. Nevertheless, the author argues that speech teachers should teach physical positions for vowels, as students learn more effectively when a multi-modal (tactile, visual and auditory) approach is offered. To this end, the vowel quadrilateral is offered as a tool to not only show approximate tongue positions, but also for indicating auditory qualities. As long as students remain aware that physical descriptions of vowels are imperfect, they will benefit from such instruction. The concluding discussion examines how the author likes to coach vowels in his own teaching practice and provides guidance on how to teach vowels physically without misleading students.