Showing papers by "University of New Brunswick published in 2022"

Electromyography-Based Gesture Recognition: Is It Time to Change Focus From the Forearm to the Wrist?

Abstract: Despite a historical focus on prosthetics, the incorporation of electromyography (EMG) sensors into less obtrusive wearable designs has recently gained attention as a potential human–computer interaction scheme for general consumer use. Because consumers are more used to wrist-worn devices, this article presents a comprehensive and systematic investigation of the feasibility of hand gesture recognition using EMG signals recorded at the wrist. A direct comparison of signal and information quality is conducted between concurrently recorded wrist and forearm signals. Both signals were collected simultaneously from 21 subjects while they performed a selection of 17 different single-finger gestures, multifinger gestures, and wrist gestures. Wrist EMG signals yielded consistently higher ( $p ) signal quality metrics than forearm signals for gestures that involved fine finger movements, while maintaining comparable quality for wrist gestures. Similarly, the performance of both individual state-of-the-art EMG features and a standard feature set was found to be significantly better when using wrist signals for single and multifinger gestures, and comparable for wrist gestures. Classifiers trained and tested using wrist EMG signals achieved average accuracy levels of 92.1% for single-finger gestures, 91.2% for multifinger gestures, and 94.7% for the conventional wrist gestures. In conclusion, this article clearly demonstrates the feasibility of using wrist EMG signals for hand gesture recognition. Results highlight not only the promise of this approach, but also the viability of incorporating prior knowledge from the prosthetics field in the design of wrist-based EMG pattern recognition systems.

Effective and Efficient Hybrid Android Malware Classification Using Pseudo-Label Stacked Auto-Encoder

Abstract: Android has become the target of attackers because of its popularity. The detection of Android mobile malware has become increasingly important due to its significant threat. Supervised machine learning, which has been used to detect Android malware is far from perfect because it requires a significant amount of labeled data. Since labeled data is expensive and difficult to get while unlabeled data is abundant and cheap in this context, we resort to a semi-supervised learning technique, namely pseudo-label stacked auto-encoder (PLSAE), which involves training using a set of labeled and unlabeled instances. We use a hybrid approach of dynamic analysis and static analysis to craft feature vectors. We evaluate our proposed model on CICMalDroid2020, which includes 17,341 most recent samples of five different Android apps categories. After that, we compare the results with state-of-the-art techniques in terms of accuracy and efficiency. Experimental results show that our proposed framework outperforms other semi-supervised approaches and common machine learning algorithms.

Statistical Analysis of APXS‐Derived Chemistry of the Clay‐Bearing Glen Torridon Region and Mount Sharp Group, Gale Crater, Mars

Abstract: The Glen Torridon stratigraphic sequence marks the transition from the low energy lacustrine-dominated Murray formation (Mf) (Jura member: Jm) to the more diverse Carolyn Shoemaker formation (CSf) (Knockfarril Hill member: Knockfarril Hill; Glasgow member: Glasgow). This transition defines a change in depositional setting. Alpha Particle X-ray Spectrometer (APXS) results and statistical analysis reveal that the bulk primary geochemistry of Mf targets are broadly in family with CSf targets, but with subtle compositional and diagenetic trends with increasing elevation. APXS results reveal significant compositional differences between Jura_GT and the stratigraphically equivalent Jura on Vera Rubin ridge (Jura_VRR). The data define two geochemical facies (high-K or high-Mg), with a strong bimodal grain distribution in Jura_GT and Knockfarril Hill. The contact between Knockfarril Hill and Glasgow is marked by abrupt sedimentological changes but a similar composition for both. Away from the contact, the Knockfarril Hill and Glasgow plot discretely, suggesting a zone of common alteration at the transition and/or a gradual transition in provenance with increasing elevation in the Glasgow member. APXS results point to a complex history of diagenesis within Glen Torridon, with increasing diagenesis close to the Basal Siccar Point unconformity on the Greenheugh pediment, and with proximity to the beginning of the clay sulfate transition. Elemental mobility is evident in localized enrichments or depletions in Ca, S, Mn, P, Zn, Ni. The highly altered Hutton interval, in contact with the unconformity on Tower butte, is also identified on Western Butte, indicating that the “interval” was once laterally extensive.

AI and Robotics in the Fight Against COVID-19 Pandemic

Abstract: The outbreak of the novel coronavirus and its disease COVID-19 present an unprecedented challenge for humanity. Artificial Intelligence (AI) and robotics may help fighting COVID-19. Potential applications of AI in this accelerating pandemic include, but are not limited to, early detection and diagnosis, massive agent modeling and simulation, data analytics, assistive robots, disinfection robots, public awareness and patrolling, contactless delivery services, virtual healthcare assistants, drug repurposing and vaccination discovery. This chapter sheds light on the roles AI and robotics can play in fighting this disastrous pandemic, and possible future ones, and highlights several potential applications to transform this challenge into opportunities. This chapter also discusses the ethical implications of AI and robotics during the pandemic and in the post-pandemic world.

The architecture of Recent brachiopod shells: diversity of biocrystal and biopolymer assemblages in rhynchonellide, terebratulide, thecideide and craniide shells

Abstract: Biological hard tissues are a rich source of design concepts for the generation of advanced materials. They represent the most important library of information on the evolution of life and its environmental conditions. Organisms produce soft and hard tissues in a bottom-up process, a construction principle that is intrinsic to biologically secreted materials. This process emerged early on in the geological record, with the onset of biological mineralization. The phylum Brachiopoda is a marine animal group that has an excellent and continuous fossil record from the early Cambrian to the Recent. Throughout this time interval, the Brachiopoda secreted phosphate and carbonate shells and populated many and highly diverse marine habitats. This required great flexibility in the adaptation of soft and hard tissues to the different marine environments and living conditions. This review presents, juxtaposes and discusses the main modes of mineral and biopolymer organization in Recent, carbonate shell-producing, brachiopods. We describe shell tissue characteristics for taxa of the orders Rhynchonellida, Terebratulida, Thecideida and Craniida. We highlight modes of calcite and organic matrix assembly at the macro-, micro-, and nano-scales based on results obtained by Electron Backscatter Diffraction, Atomic Force Microscopy, Field Emission Scanning Electron Microscopy and Scanning Transmission Electron Microscopy. We show variation in composite hard tissue organization for taxa with different lifestyles, visualize nanometer-scale calcite assemblies for rhynchonellide and terebratulide fibers, highlight thecideide shell microstructure, texture and chemistry characteristics, and discuss the feasibility to use thecideide shells as archives of proxies for paleoenvironment and paleoclimate reconstructions.

Smartforests Canada: A Network of Monitoring Plots for Forest Management Under Environmental Change

Abstract: Monitoring of forest response to gradual environmental changes or abrupt disturbances provides insights into how forested ecosystems operate and allows for quantification of forest health. In this chapter, we provide an overview of Smartforests Canada, a national-scale research network consisting of regional investigators who support a wealth of existing and new monitoring sites. The objectives of Smartforests are threefold: (1) establish and coordinate a network of high-precision monitoring plots across a 4400 km gradient of environmental and forest conditions, (2) synthesize the collected multivariate observations to examine the effects of global changes on complex above- and belowground forest dynamics and resilience, and (3) analyze the collected data to guide the development of the next-generation forest growth models and inform policy-makers on best forest management and adaptation strategies. We present the methodological framework implemented in Smartforests to fulfill the aforementioned objectives. We then use an example from a temperate hardwood Smartforests site in Quebec to illustrate our approach for climate-smart forestry. We conclude by discussing how information from the Smartforests network can be integrated with existing data streams, from within Canada and abroad, guiding forest management and the development of climate change adaptation strategies.

Interweaving of reactive oxygen species and major neurological and psychiatric disorders

Abstract: Reactive oxygen species are found to be having a wide range of biological effects ranging from regulating functions in normal physiology to alteration and damaging various processes and cell components causing a number of diseases. Mitochondria are an important organelle responsible for energy production and in many signalling mechanisms. The electron transport chain in mitochondria, where oxidative phosphorylation takes place, is also coupled with the generation of reactive oxygen species (ROS). Changes in normal homeostasis and overproduction of reactive oxygen species by various sources are found to be involved in multiple neurological and major neurodegenerative diseases. This review summarises the role of reactive oxygen species and the mechanism of neuronal loss in major neuronal disorders such as Alzheimer's disease, Parkinson's disease, Huntington's disease, depression, and schizophrenia.

Personalized Privacy-Preserving Publication of Trajectory Data by Generalization and Distortion of Moving Points

Abstract: With the rising prevalence of location-aware devices such as mobile phones, Radio-Frequency Identification (RFID) tags, and Global Positioning Systems (GPSs), the amount of trajectory data is significantly increasing, resulting in various data mining applications. Improper publication of trajectory data may jeopardize the privacy of moving objects, so trajectories ought to be anonymized before making them accessible to the public. Many existing approaches for privacy-preserving publication of trajectory data provide only the same level of privacy protection for all moving objects, whereas different moving objects may require different amounts of privacy protection. In this paper, we address this issue by presenting WINR2D, a novel clustering-based approach for privacy-preserving publication of trajectory data. Being based on the concept of personalized privacy, the aim of WINR2D is to anonymize trajectories to some extent so that an adversary having some background knowledge cannot uniquely identify a specific trajectory, but with a maximum probability inversely proportional to the privacy protection requirement of the moving object that produced it. In doing so, we first assign a privacy level to each trajectory based on the privacy protection requirement of its moving object and then partition all the trajectories into a set of clusters based on a greedy strategy. Each cluster is created such that its size is proportional to the highest privacy level of trajectories within it. Eventually, we anonymize the trajectories of each cluster and generate a set of anonymized trajectories containing generalized and distorted moving points. Our experimental results show that WINR2D achieves a reasonable trade-off between the conflicting goals of data utility and data privacy according to the privacy protection requirements of moving objects.

Maternal incarceration in a provincial prison in Canada: A qualitative study

Abstract: To explore the experiences of provincially incarcerated mothers in Nova Scotia, Canada; and to make recommendations with respect to improving the experiences of mothers facing criminalization and their children.This qualitative study is rooted in feminist standpoint theory, community-based research methodologies and prison abolition.Mothers who were currently or previously incarcerated were recruited by community partners. Between Fall 2021 and Winter 2022, 14 individual interviews and one focus group were conducted, for a total of 18 study participants. Data were analysed collaboratively using thematic analysis.Three key themes were developed through the data analysis: Maintaining Connection, Broken Bonds and The Damage. Mothers shared experiences of trying to maintain connections with their children through numerous challenges, including emotional distress caused by the separation and significant logistical and financial barriers. Mothers felt their children unfairly bore the burden of their incarceration. They experienced a lack of or outright denial of services while incarcerated, and a lack of transitional support on release, making working towards parenting again difficult and discouraging.For participants in our study, separation from their children during incarceration caused severe emotional distress and had serious implications on their right to parent and their relationships with their children. Incarceration for even brief periods has detrimental social impacts, and release planning does not prepare people for the challenges of repairing that damage. Conditions of maternal incarceration are in violation of international human rights laws.Although we make some recommendations for reform (e.g. free phone calls), we focus on alternatives to incarceration for mothers experiencing criminalization. Findings will be shared with relevant institutional partners with the goal of impacting sentencing and incarceration practices.