High-temperature superconducting ring magnet

Many electrical engineering applications such as motors and generators use permanent magnets which approximately account for 45% of their electricity consumption. The conventional magnets in use have a maximum field of around 1.5-2 T. High performance superconducting materials such as REBCO have facilitated the development of superconducting magnets. Superconducting bulk magnets and stacks of tapes have already demonstrated the extraordinary potential to trap magnetic fields of very high order with very compact sizes. This has significantly increased the efficiency of rotating machines and improved power/torque density, while having low synchronous reactance with large overloading capacity, high transient stability with low noise and harmonic content with the additional cost of cooling. This thesis focuses on a new type of superconducting magnet which uses superconducting tape as the field source. The most significant limiting factor for superconducting magnets is their size.;This new superconducting magnet has made possible the development of HTS magnets with flexible sizes by splitting the 2G HTS tapes to form the persistent current rings. By stacking HTS closed loop rings into a compact magnet, our HTS ring magnet has been proven to generate a trapped magnetic field higher than 5 T. The main advantage of the new magnet compared to existing trapped field HTS magnets is that the magnetic field lies parallel to the ab plane of the HTS, leading to higher critical currents in the same magnetic field. This thesis reports our key findings so far. Two different stacking configuration magnet samples were tested using the field cooling magnetization at 25 K and 4.2 K, with magnet diameter 90 mm and 150 mm, respectively. Over 4.6 T of the trapped field has been reported by using Super Power tapes with a field cooling process at 25 K, which is the highest field trapped in the ring magnets for first configuration. A new stacking design was proposed to improve magnetic field distribution within the magnet and has the potential to trap more magnetic field with the estimated trap field of 9.4 T at 4.2 K. A three dimensional model was developed to simulate the performance of the ring magnets, and good agreements between experiment and simulation have been achieved. The new HTS permanent magnet with improved field homogenisation and large diameter is promising for medical imaging applications, as well as propulsion applications.Many electrical engineering applications such as motors and generators use permanent magnets which approximately account for 45% of their electricity consumption. The conventional magnets in use have a maximum field of around 1.5-2 T. High performance superconducting materials such as REBCO have facilitated the development of superconducting magnets. Superconducting bulk magnets and stacks of tapes have already demonstrated the extraordinary potential to trap magnetic fields of very high order with very compact sizes. This has significantly increased the efficiency of rotating machines and improved power/torque density, while having low synchronous reactance with large overloading capacity, high transient stability with low noise and harmonic content with the additional cost of cooling. This thesis focuses on a new type of superconducting magnet which uses superconducting tape as the field source. The most significant limiting factor for superconducting magnets is their size.;This new superconducting magnet has made possible the development of HTS magnets with flexible sizes by splitting the 2G HTS tapes to form the persistent current rings. By stacking HTS closed loop rings into a compact magnet, our HTS ring magnet has been proven to generate a trapped magnetic field higher than 5 T. The main advantage of the new magnet compared to existing trapped field HTS magnets is that the magnetic field lies parallel to the ab plane of the HTS, leading to higher critical currents in the same magnetic field. This thesis reports our key findings so far. Two different stacking configuration magnet samples were tested using the field cooling magnetization at 25 K and 4.2 K, with magnet diameter 90 mm and 150 mm, respectively. Over 4.6 T of the trapped field has been reported by using Super Power tapes with a field cooling process at 25 K, which is the highest field trapped in the ring magnets for first configuration. A new stacking design was proposed to improve magnetic field distribution within the magnet and has the potential to trap more magnetic field with the estimated trap field of 9.4 T at 4.2 K. A three dimensional model was developed to simulate the performance of the ring magnets, and good agreements between experiment and simulation have been achieved. The new HTS permanent magnet with improved field homogenisation and large diameter is promising for medical imaging applications, as well as propulsion applications

Innovative Method for Unsupervised Voice Activity Detection and Classification of Audio Segments

An accurate and noise-robust voice activity detection (VAD) system can be widely used for emerging speech technologies in the fields of audio forensics, wireless communication, and speech recognition. However, in real-life application, the sufficient amount of data or human-annotated data to train such a system may not be available. Therefore, a supervised system for VAD cannot be used in such situations. In this paper, an unsupervised method for VAD is proposed to label the segments of speech-presence and speech-absence in an audio. To make the proposed method efficient and computationally fast, it is implemented by using long-term features that are computed by using the Katz algorithm of fractal dimension estimation. Two databases of different languages are used to evaluate the performance of the proposed method. The first is Texas Instruments Massachusetts Institute of Technology (TIMIT) database, and the second is the King Saud University (KSU) Arabic speech database. The language of TIMIT is English, while the language of the KSU speech database is Arabic. TIMIT is recorded in only one environment, whereas the KSU speech database is recorded in distinct environments using various recording systems that contain sound cards of different qualities and models. The evaluation of the proposed method suggested that it labels voiced and unvoiced segments reliably in both clean and noisy audio

Access to Finance for African SMEs: Do Women Entrepreneurs face Discrimination.

This study examines the gender disparity in Africa‟s small and medium business (SME) credit market. It shows how capital market imperfections can lead to second best solutions, so this research is significant for emerging economies. The gender gap between men and women is still there in Africa, and unless particular efforts are made to address the underlying issues today, it will continue to increase. The fact that black women make up the majority of the self-employed population isn't reflected in present industry targets for company activity, which is a problem. Women-owned businesses in Africa face unique problems, and this study evaluates whether financial service providers in the country are adequately aware of these issues

An Automatic Digital Audio Authentication/Forensics System

With the continuous rise in ingenious forgery, a wide range of digital audio authentication applications are emerging as a preventive and detective control in real-world circumstances, such as forged evidence, breach of copyright protection, and unauthorized data access. To investigate and verify, this paper presents a novel automatic authentication system that differentiates between the forged and original audio. The design philosophy of the proposed system is primarily based on three psychoacoustic principles of hearing, which are implemented to simulate the human sound perception system. Moreover, the proposed system is able to classify between the audio of different environments recorded with the same microphone. To authenticate the audio and environment classification, the computed features based on the psychoacoustic principles of hearing are dangled to the Gaussian mixture model to make automatic decisions. It is worth mentioning that the proposed system authenticates an unknown speaker irrespective of the audio content i.e., independent of narrator and text. To evaluate the performance of the proposed system, audios in multi-environments are forged in such a way that a human cannot recognize them. Subjective evaluation by three human evaluators is performed to verify the quality of the generated forged audio. The proposed system provides a classification accuracy of 99.2% ± 2.6. Furthermore, the obtained accuracy for the other scenarios, such as text-dependent and text-independent audio authentication, is 100% by using the proposed system

A Practical Approach: Design and Implementation of a Healthcare Software for Screening of Dysphonic Patients

Risk management in the development of medical software and devices is one of the most crucial processes in ensuring accurate diagnoses and treatment of disease. The consequences of wrong decisions that happen in our daily life might be unembellished. However, wrong decisions in healthcare based on unreliable evidence due to erroneous software could result in loss of life. Dysphonic patients suffering from various vocal fold disorders might have a threat of life due to inaccurate diagnosis. Some voice disorders, such as keratosis, are precancerous, and can become cancerous in cases that involve inaccurate diagnosis due to software failure. The objective of this paper is to design and implement a healthcare software for the detection of voice disorders in nonperiodic speech signals. Occurrences of potential risks during the design and development of the proposed software are taken into account to avoid failure. The software is implemented by applying the local binary pattern (LBP) operator on the textures of nonperiodic signals. The textures are obtained through the recurrence plot. The LBP operator computes the histograms for normal persons and dysphonic patients, and these histograms are used with the support vector machine for the automatic classification of dysphonic patients. The software is evaluated and tested by using the Massachusetts Eye and Ear Infirmary voice disorder database. The success rate of the proposed healthcare system is 97.73% ± 1.2, and the area under the receiver operating characteristic curve is 0.98 ± 0. The performance of the proposed healthcare system is much better than the existing commercial software used for screening dysphonic patients

Does Improved Water Productivity Matter for the Farmers? A Case of Water-Efficient Rice Production from Pakistan

Rice is an important crop of Pakistan being the third most important export commodity in agriculture sector earning large revenues. This study was conducted with the rice farmers collaborating with Water Productivity project in Sheikhupura district in Pakistan. The study presents a comparison between the findings from a baseline study conducted in early 2017 and end 2018 based on 21 farmers selected from head, mid and tail of water channels. The objective of the analysis was to assess the economic impact of adopting improved irrigation practices and other related agronomic practices to increase water productivity. Two cropping seasons were compared between 2017 and 2018 based on economic returns from improved rice production practices. The data were collected through focus group discussions, individual interviews, and field evidences of use of technology and costs incurred and registered. The analysis is based on per acre inputs and output of paddy crop. The analysis shows that the net per acre revenue received by farmers significantly increased. The increase in revenue is mainly attributed to efficient irrigation practices and adoption of co-related better agronomic practices. The results prove economic viability of water efficient techniques and agronomic practices. The study also documents the effectiveness of public-private partnership aspects which served as a driving force for adoption of water productive approach. Keywords: Paddy; Rice; Water Productivity; Water Economics; Pakistan; Business Case DOI: 10.7176/DCS/9-9-07 Publication date:September 30th 201

A New Weighting Scheme in Weighted Markov Model for Predicting the Probability of Drought Episodes

Drought is a complex stochastic natural hazard caused by prolonged shortage of rainfall. Several environmental factors are involved in determining drought classes at the specific monitoring station. Therefore, efficient sequence processing techniques are required to explore and predict the periodic information about the various episodes of drought classes. In this study, we proposed a new weighting scheme to predict the probability of various drought classes under Weighted Markov Chain (WMC) model. We provide a standardized scheme of weights for ordinal sequences of drought classifications by normalizing squared weighted Cohen Kappa. Illustrations of the proposed scheme are given by including temporal ordinal data on drought classes determined by the standardized precipitation temperature index (SPTI). Experimental results show that the proposed weighting scheme for WMC model is sufficiently flexible to address actual changes in drought classifications by restructuring the transient behavior of a Markov chain. In summary, this paper proposes a new weighting scheme to improve the accuracy of the WMC, specifically in the field of hydrology

A zero-watermarking algorithm for privacy protection in biomedical signals

Confidentiality of health information is indispensable to protect privacy of an individual. However, recent advances in electronic healthcare systems allow transmission of sensitive information through the Internet, which is prone to various vulnerabilities, attacks and may leads to unauthorized disclosure. Such situations may not only create adverse effects for individuals but may also cause severe consequences such as hefty regulatory fines, bad publicity, legal fees, and forensics. To avoid such predicaments, a privacy protected healthcare system is proposed in this study that protects the identity of an individual as well as detects vocal fold disorders. The privacy of the developed healthcare system is based on the proposed zero-watermarking algorithm, which embeds a watermark in a secret key instead of the signals to avoid the distortion in an audio sample. The identity is protected by the generation of its secret shares through visual cryptography. The generated shares are embedded by finding the patterns into the audio with the application of one-dimensional local binary pattern. The proposed zero-watermarking algorithm is evaluated by using audio samples taken from the Massachusetts Eye and Ear Infirmary voice disorder database. Experimental results demonstrate that the proposed algorithm achieves imperceptibility and is reliable in its extraction of identity. In addition, the proposed algorithm does not affect the results of disorder detection and it is robust against noise attacks of various signal-to-noise ratios