The Classification of EMG Signals with Zero Retraining in the Influence of User and Rotation Independence

The surface electromyogram (EMG) contains information directly related to muscle contraction and modern classification techniques can obtain near-zero error when identifying various gestures over the forearm. However, good results come at a compromise over the ease of use. Once the EMG classifier trained on a user is changed, the accuracy rate will be greatly reduced. Furthermore, changing the position of the forearm also causes drop in accuracy rate. Acknowledging the limitations of EMG classification, this study aims to investigate the EMG signals based on the gestures, and evaluate if there are any gestures which are inherently robust to these variations. The EMG of forearm gestures have been classified in the combined influence user independence, rotation independence and hand exchange independence. Experiment results on 20 participants indicated that truly independent classification can be achieved for most forearm gestures (up to 100%) in some arm positions. Hand exchange is also not feasible as the study has shown that the data field for both hands are fairly different. Out of the nine gestures under study, only the wrist extension was found to be truly independent of all the influences

Review on EMG Acquisition and Classification Techniques: Towards Zero Retraining in the Influence of User and Arm Position Independence

The surface electromyogram (EMG) is widely studied and applied in machine control. Recent methods of classifying hand gestures reported classification rates of over 95%. However, the majority of the studies made were performed on a single user, focusing solely on the gesture classification. These studies are restrictive in practical sense: either focusing on just gestures, multi-user compatibility, or rotation independence. The variations in EMG signals due to these conditions present a challenge to the practical application of EMG devices, often requiring repetitious training per application. To the best of our knowledge, there is little comprehensive review of works done in EMG classification in the combined influence of user-independence, rotation and hand exchange. Therefore, in this paper we present a review of works related to the practical issues of EMG with a focus on the EMG placement, and recent acquisition and computing techniques to reduce training. First, we provided an overview of existing electrode placement schemes. Secondly, we compared the techniques and results of single-subject against multi-subject, multi-position settings. As a conclusion, the study of EMG classification in this direction is relatively new. However the results are encouraging and strongly indicate that EMG classification in a broad range of people and tolerance towards arm orientation is possible, and can pave way for more flexible EMG devices

Time Evolution and Deterministic Optimisation of Correlator Product States

We study a restricted class of correlator product states (CPS) for a spin-half chain in which each spin is contained in just two overlapping plaquettes. This class is also a restriction upon matrix product states (MPS) with local dimension $2^n$ ($n$ being the size of the overlapping regions of plaquettes) equal to the bond dimension. We investigate the trade-off between gains in efficiency due to this restriction against losses in fidelity. The time-dependent variational principle formulated for these states is numerically very stable. Moreover, it shows significant gains in efficiency compared to the naively related matrix product states - the evolution or optimisation scales as $2^{3n}$ for the correlator product states versus $2^{4n}$ for the unrestricted matrix product state. However, much of this advantage is offset by a significant reduction in fidelity. Correlator product states break the local Hilbert space symmetry by the explicit selection of a local basis. We investigate this dependence in detail and formulate the broad principles under which correlator product states may be a useful tool. In particular, we find that scaling with overlap/bond order may be more stable with correlator product states allowing a more efficient extraction of critical exponents - we present an example in which the use of correlator product states is several orders of magnitude quicker than matrix product states.Comment: 19 pages, 14 figure

Localization of a mobile autonomous robot based on image analysis

This paper introduces an innovative method to solve the problem of self localization of a mobile autonomous robot, and in particular a case study is carried out for robot localization in a RoboCup field environment. The approach here described is completely different from other methods currently used in RoboCup, since it is only based on the use of images and does not involve the use of techniques like Monte Carlo or other probabilistic approaches. This method is simple, acceptably efficient for the purpose it was created, and uses a relatively low computational time to calculate.Fundação para a Ciência e Tecnologia (FCT) - projecto POSI/ROBO/43892/200

Localization of a mobile autonomous robot based on image analysis

This paper introduces an innovative method to solve the problem of self localization of a mobile autonomous robot, and in particular a case study is carried out for robot localization in a RoboCup field environment. The approach here described is completely different from other methods currently used in RoboCup, since it is only based on the use of images and does not involve the use of techniques like Monte Carlo or other probabilistic approaches. This method is simple, acceptably efficient for the purpose it was created, and uses a relatively low computational time to calculate.Fundação para a Ciência e a Tecnologia (FCT) - POSI/ROBO/43892/200

IDENTIFYING MIXED ELEMENTS OF SPORT MARKETING IN PUBLIC AND PRIVATE SPORT PLACES FROM THE POINT OF VIEW OF SPORT CUSTOMERS

The goal of this research was identifying mixed elements of sport's marketing in public and private sport places from the point of view of female athletes. This research was descriptive in the case of method, in the sort of survey. In the term of time, it was sectional and in the term of aim, it was practical and in the term of data collecting, it was athletics. Population of this research was female athletes of Sanandaj city, in the sports of physical readiness, bodybuilding and swimming. Criteria of selecting of these trebles based on age, club's membership history, insurance history and gender, so that in the term of the age, only people over 18 years, in the term of membership, people who were registered for 6 months and in the term of insurance, only those who have insurance history in general administer of sport of Sanandaj city could participate and in the term of the age only female gender.            According on insurance history of females, in general administer of sport and youth, number of this people was over 3500 and based on it, for determine samples, we used Krejcle Mugger table. Research' sample size was 246 that were selected accessibly for replying to questionnaires. So first, a questionnaire had designed that checked out mixed marketing based on other template questionnaire. Freidman examine got choose for examining hypotheses. It should be noted that SPSS software ver. 22 and Larsel software ver. 8.80 were used for analysing data’s and, also, confidence level in this research was 95 percent Results showed that marketing mixes includes protection, promotion, distributing, production, people, process, price and physical evidence. Generally, if factors which have effect on decision of customers for choosing gyms get used by mixed marketing approaches, marketers will be able to design better strategies on gym's management. And also, bring more customers that has a lot of financial interests for club.  Article visualizations

Feature based face detection for unconstrained images

Face detection for unconstrained images often encounter issues like background variation, pose variation, facial expression, occlusion and noise. Face detection utilises two main methods; feature based and image based methods. The feature based method benefits from rotation independence, scale independence and quick execution time as compared to the image based method. Feature based method utilises skin colour, facial and blob features. Current research on feature based method often emphasises on Viola Jones (V-J) face detection and is only limited to the in-plane rotation of positive or negative forty-five degrees. However, the utilization of V-J face detection with the inclusion of noise is a challenge because the image of other objects will often be mistaken for faces thus resulting in false detections. This thesis focuses on pose variation and noise challenges of unconstrained images and will cover three techniques for V-J face detection for unconstrained images, namely the combination of V-J face detection with rotation enhancements, Bicubic interpolation and ratio Scale Invariant Feature Transform (SIFT). In this thesis, these three techniques play different roles in face detection. The first technique begins with the rotation of the image file at thirty degree steps until it reaches a total rotation of three hundred and sixty degrees. At each thirty degree step, V-J face detection is applied, which in turn covers more angles of a rotated face. The second technique, Bicubic interpolation, corrects distorted images. The third technique, ratio SIFT, is a proposed post-processing to eliminate false detection for unconstrained images. Robust feature detection in scaling and invariant rotation is utilised in the above techniques to aid in the detecting of faces in images. Different face detections have been recommended for the unconstrained grey images and unconstrained colour images respectively with in-plane rotations and some with multiple faces. The images utilised for testing and evaluation in this thesis originated from Carnegie Mellon University (CMU) unconstrained grey images with in-plane rotations and Face Detection Data Set and Benchmark (FDDB) unconstrained colour images with multiple faces datasets. Fifty CMU datasets with twelve rotations on each image and various permutations resulted in six hundred test pattern images have been performed. Furthermore, another six hundred test pattern images from FDDB were also evaluated. These images have been measured through correct detection rate, true positive and false positive. The results from these measurements indicate that the proposed feature based face detection technique, focused on the V-J face detection method, for unconstrained images has the ability to detect rotated faces with high detection accuracy which in turn reduces false detections. In conclusion, the proposed enhancements will improve the current V-J face detection technique and overcome future challenges for unconstrained images

A theoretical approach to auditor independence and audit quality

Auditor independence and the quality of audit report is of growing concern to regulators, institutional investors and stakeholders as a series of accounting scandals have undermined the professionalism of auditors. The findings from this study produced an insight of how auditor’s independence improve audit quality and that abnormal audit fees is as a result of additional effort for auditor to carry out rigorous audit engagement as a result of wider audit scope; that mandatory audit firm rotation will enhance auditor independence, and that audit committee with nonexecutive independence will promote audit quality. The study also finds that in terms of auditor size, smaller audit firms that belong to professional bodies will provide higher audit quality. The main conclusion of this research is that where an auditor is fully independent in carrying out audit engagement with strong resistance to fees pressure will enhance audit quality. This research provides insight into the impact of IFRS adoption on audit fees