Parametric classification in domains of characters, numerals, punctuation, typefaces and image qualities

This thesis contributes to the Optical Font Recognition problem (OFR), by developing a classifier system to differentiate ten typefaces using a single English character ‘e’. First, features which need to be used in the classifier system are carefully selected after a thorough typographical study of global font features and previous related experiments. These features have been modeled by multivariate normal laws in order to use parameter estimation in learning. Then, the classifier system is built up on six independent schemes, each performing typeface classification using a different method. The results have shown a remarkable performance in the field of font recognition. Finally, the classifiers have been implemented on Lowercase characters, Uppercase characters, Digits, Punctuation and also on Degraded Images

Revisiting Fine-Tuning Strategies for Self-supervised Medical Imaging Analysis

Despite the rapid progress in self-supervised learning (SSL), end-to-end fine-tuning still remains the dominant fine-tuning strategy for medical imaging analysis. However, it remains unclear whether this approach is truly optimal for effectively utilizing the pre-trained knowledge, especially considering the diverse categories of SSL that capture different types of features. In this paper, we first establish strong contrastive and restorative SSL baselines that outperform SOTA methods across four diverse downstream tasks. Building upon these strong baselines, we conduct an extensive fine-tuning analysis across multiple pre-training and fine-tuning datasets, as well as various fine-tuning dataset sizes. Contrary to the conventional wisdom of fine-tuning only the last few layers of a pre-trained network, we show that fine-tuning intermediate layers is more effective, with fine-tuning the second quarter (25-50%) of the network being optimal for contrastive SSL whereas fine-tuning the third quarter (50-75%) of the network being optimal for restorative SSL. Compared to the de-facto standard of end-to-end fine-tuning, our best fine-tuning strategy, which fine-tunes a shallower network consisting of the first three quarters (0-75%) of the pre-trained network, yields improvements of as much as 5.48%. Additionally, using these insights, we propose a simple yet effective method to leverage the complementary strengths of multiple SSL models, resulting in enhancements of up to 3.57% compared to using the best model alone. Hence, our fine-tuning strategies not only enhance the performance of individual SSL models, but also enable effective utilization of the complementary strengths offered by multiple SSL models, leading to significant improvements in self-supervised medical imaging analysis

Resource Efficient Authentication and Session Key Establishment Procedure for Low-Resource IoT Devices

open access journalThe Internet of Things (IoT) can includes many resource-constrained devices, with most usually needing to securely communicate with their network managers, which are more resource-rich devices in the IoT network. We propose a resource-efficient security scheme that includes authentication of devices with their network managers, authentication between devices on different networks, and an attack-resilient key establishment procedure. Using automated validation with internet security protocols and applications tool-set, we analyse several attack scenarios to determine the security soundness of the proposed solution, and then we evaluate its performance analytically and experimentally. The performance analysis shows that the proposed solution occupies little memory and consumes low energy during the authentication and key generation processes respectively. Moreover, it protects the network from well-known attacks (man-in-the-middle attacks, replay attacks, impersonation attacks, key compromission attacks and denial of service attacks)

Signal-Processing-Driven Integrated Circuits for Energy Constrained Microsystems.

The exponential growth in IC technology has enabled low-cost and increasingly capable wireless sensor nodes which provide a promising way forward to realize the vision of a trillion connected sensors in the next decade. However there are still many design challenges ahead to make these sensor nodes small,low-cost,secure,reliable and energy-efficient to name a few. Since the wireless nodes are expected to operate on a limited energy source or in some cases on harvested energy, the energy consumption of each building block is of prime importance to prolong the life of a sensor node. It has been found that the radio communication when active has been one of the highest power consuming modules on a sensor node. Low-energy protocols, e.g. processing the raw sensor data on-node, are more energy efficient for some applications as compared to transmitting the raw data over a wireless channel to a cloud server. In this thesis we explore signal processing techniques to realize a low power radio solution for wireless communication. Two prototype chips have been designed and their performance has been evaluated. The first prototype chip exploits compressed sensing for Ultra-Wide-Band (UWB) communication. UWB signals typically require a high ADC sampling rate in the receiver which results in high power consumption. Compressed sensing is demonstrated to relax the ADC sampling rate to save power. The second prototype chip exploits the sensitivity vs. power trade-off in a radio receiver to achieve iso-performance at lower power consumption and the time-varying wireless channel characteristics are used to adapt the sampling frequency of the receiver based on the SNR/Link quality of the communication channel, saving power, while maintaining the desired system performance. It is envisioned that embedded machine learning will play a key role in the integration of sensory data with prior knowledge for distributed intelligent sensing which might enable reduced wireless network traffic to a cloud server. A Near-Threshold hardware accelerator for arbitrary Bayesian network was designed for clique-tree message passing algorithm used for probabilistic inference. The hardware accelerator was benchmarked by the mid-size ALARM Bayesian network with total energy consumption of 76nJ for 250µS execution time.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107130/1/oukhan_1.pd

What do we know about business and economics research during COVID-19: a bibliometric review

The destructive COVID-19 has emerged as the most lethal disease and dented the global economies in every aspect. Consequently, a large amount of research emerged to understand the dynamics of COVID-19. Using meta-literature approach with combination of both bibliometric (quantitative) and content analysis (qualitative) approach, this study aims to present a comprehensive review of COVID-19 business-related research of 477 articles. The results reveal the most the most relevant and influential scientific aspects of the literature such as authors, articles, institutions, journals, and countries. We also identify intellectual structure within six streams: 1) COVID-19 and global economy, 2) Dynamics of COVID-19 in business and management research, 3) COVID-19 and financial markets, 4) COVID-19 and its implication for tourism & hospitality industry, 5) Dynamic of supply chain and COVID-19 and 6) COVID-19 and functionality of government. Lastly, the review of the literature helps us to identify the research gaps and present 62 future research directions

Experimental Clock Calibration\\on a Crystal-Free Mote-on-a-Chip

The elimination of the off-chip frequency reference, typically a crystal oscillator, would bring important benefits in terms of size, price and energy efficiency to IEEE802.15.4 compliant radios and systems-on-chip. The stability of on-chip oscillators is orders of magnitude worse than that of a crystal. It is known that as the temperature changes, they can drift more than 50 ppm/{\deg}C. This paper presents the result of an extensive experimental study. First, we propose mechanisms for crystal-free radios to be able to track an IEEE802.15.4 join proxy, calibrate the on-chip oscillators and maintain calibration against temperature changes. Then, we implement the resulting algorithms on a crystal-free platform and present the results of an experimental validation. We show that our approach is able to track a crystal-based IEEE802.15.4-compliant join proxy and maintain the requested radio frequency stability of +/-40 ppm, even when subject to temperature variation of 2{\deg}C/min.Comment: CNERT: Computer and Networking Experimental Research using Testbeds, in conjunction with IEEE INFOCOM 2019, April 29 - May 2, 2019, Paris, Franc

Non-Adherence to WHO recommendations regarding infant feeding practices results in dilemma of malnourishment: A community-based prospective cohort study conducted in Karachi, Pakistan

Background: The prevalence of chronic malnutrition and its associated morbid outcomes has been a significant cause of health loss globally, affecting millions of children hampering their mental, physical, social, and immune system development. World Health Organization\u27s (WHO) recommendations presenting infant feeding guidelines have largely controlled this burden. However, developing countries including Pakistan have failed to promote these guidelines and still succumb to a huge burden of morbidity and mortality secondary to malnourishment among infants.Methodology: Our study is a prospective cohort including 300 infants without predisposing congenital anomaly, followed from 6 months to 18 months of age. The primary outcome involved was classifying patients as malnourished based on anthropometric measurements, assessing the prevalence of co-morbidities and comparison of results in compliance with WHO guidelines.Results: A total of 276 infants were included and the rest were lost to follow-up. Stratification on socioeconomic status was done; 53% of infants were diagnosed as malnourished, either due to stunted growth, underweight, or both. The odds of development of malnourishment based on non-adherence to WHO guidelines on breastfeeding were 2.87 (p=0.001). The incidence of morbid complications was higher in the malnourished group, including gastrointestinal and respiratory tract infections.Conclusion: The implementation of WHO recommendations on infant feeding techniques can prove to be a pivotal instrument to control the soaring index of morbidities and mortalities associated with malnourishment. A strong focus on parental education and awareness among masses is required for its promulgation and controlling the infant health burden linked to this preventable condition

Hajdu cheney syndrome due to NOTCH2 defect - First case report from Pakistan and review of literature

Introduction and importance: Hajdu Cheney Syndrome (HCS) is a rare skeletal disease characterized by severe, progressive focal bone loss with osteoporosis, variable craniofacial, vertebral anomalies and distinctive facial features. It is inherited as an autosomal dominant disease although sporadic cases have been described in literature. Identifying these cases in clinical practice is important for proper diagnosis and management.Case presentation: We report a case of a 36-year-old male patient presented at metabolic bone disease clinic at the Aga Khan University Hospital with history of multiple fragility fractures and juvenile osteoporosis since childhood. DNA sequence analysis of the NOTCH2 coding sequence revealed a pathogenic variant in NOTCH 2, Exon 34, c.6426_6427insTT (p.Glu2143Leufs*5), consistent with a NOTCH2 related conditions including HCS.Clinical discussion: The multitude of presentations associated with HCS are linked to the NOTCH2 gene, as Notch signaling is one of the core signaling pathways that control embryonic development. Hence, mutations in the Notch signaling pathway cause developmental phenotypes that affect various organs including the liver, skeleton, heart, eye, face, kidney, and vasculature.Conclusion: To the best of our knowledge, nucleotide mutations of c.6933delT, c.6854delA, c.6787C.T, and c.6424-6427delTCTG were all determined to be novel, with c.6428T \u3e C being the most common mutation found in literature. The c.6426_6427insTT mutation our patient was found to have via gene sequencing too appears to be a novel mutation, which has not previously been reported in literature

Black Gold\u27s Price Plunge: Are Conventional and Islamic Banks Equally Vulnerable?

Regarding the vulnerability of the banking industry to oil price plunges, we investigate the effects of oil price declines on credit and insolvency risks for the banking industry within specific bank specializations (conventional, Islamic, and conventional banks with Islamic windows), from 2000 through 2016, at both the aggregate and country levels in the Gulf Cooperation Council (GCC). Our findings show that falling oil prices significantly increase the credit risk for the banking industry, particularly for banks operating in Kuwait, Qatar, Saudi Arabia and the United Arab Emirates. Commercial banks with Islamic windows are also prone to oil price shocks. However, falling oil prices do not affect the credit risk of Islamic banks. Utilizing accounting-based and marked-based proxies for the insolvency risk, our analysis shows that oil price plunges do not increase the insolvency risk of the banking industry or bank specializations. We argue that bailout packages given by the wealth funds to GCC banks is a probable cause for counter intuitive results with respect to solvency risk. Our research findings will be of interest to various stakeholders, particularly the regulators who look for empirical evidence to develop deeper insights to the sound functioning of the banking systems