QUILT: Effective Multi-Class Classification on Quantum Computers Using an Ensemble of Diverse Quantum Classifiers

Quantum computers can theoretically have significant acceleration over classical computers; but, the near-future era of quantum computing is limited due to small number of qubits that are also error prone. Quilt is a framework for performing multi-class classification task designed to work effectively on current error-prone quantum computers. Quilt is evaluated with real quantum machines as well as with projected noise levels as quantum machines become more noise-free. Quilt demonstrates up to 85% multi-class classification accuracy with the MNIST dataset on a five-qubit system

A Composite Trust Model for Secure Routing in Mobile Ad-Hoc Networks

It is imperative to address the issue of secure routing in mobile ad-hoc networks (MANETs) where the nodes seek for cooperative and trusted behaviour from the peer nodes in the absence of well-established infrastructure and centralized authority. Due to the inherent absence of security considerations in the traditional ad-hoc routing protocols, providing security and reliability in the routing of data packets is a major challenge. This work addresses this issue by proposing a composite trust metric based on the concept of social trust and quality-of-service (QoS) trust. Extended from the ad-hoc on-demand distance vector (AODV) routing protocol, we propose an enhanced trust-based model integrated with an attack-pattern discovery mechanism, which attempts to mitigate the adversaries craving to carry out distinct types of packet-forwarding misbehaviours. We present the detailed mode of operations of three distinct adversary models against which the proposed scheme is evaluated. Simulation results under different network conditions depict that the combination of social and QoS trust components provides significant improvement in packet delivery ratio, routing overhead, and energy consumption compared to an existing trust-based scheme

MISO: Exploiting Multi-Instance GPU Capability on Multi-Tenant Systems for Machine Learning

GPU technology has been improving at an expedited pace in terms of size and performance, empowering HPC and AI/ML researchers to advance the scientific discovery process. However, this also leads to inefficient resource usage, as most GPU workloads, including complicated AI/ML models, are not able to utilize the GPU resources to their fullest extent -- encouraging support for GPU multi-tenancy. We propose MISO, a technique to exploit the Multi-Instance GPU (MIG) capability on the latest NVIDIA datacenter GPUs (e.g., A100, H100) to dynamically partition GPU resources among co-located jobs. MISO's key insight is to use the lightweight, more flexible Multi-Process Service (MPS) capability to predict the best MIG partition allocation for different jobs, without incurring the overhead of implementing them during exploration. Due to its ability to utilize GPU resources more efficiently, MISO achieves 49% and 16% lower average job completion time than the unpartitioned and optimal static GPU partition schemes, respectively

Towards Quantum Dynamics Simulation of Physical Systems: A Survey

After the emergence of quantum mechanics and realising its need for an accurate understanding of physical systems, numerical methods were being used to undergo quantum mechanical treatment. With increasing system correlations and size, numerical methods fell rather inefficient, and there was a need to simulate quantum mechanical phenomena on actual quantum computing hardware. Now, with noisy quantum computing machines that have been built and made available to use, realising quantum simulations are edging towards a practical reality. In this paper, we talk about the progress that has been made in the field of quantum simulations by actual quantum computing hardware and talk about some very fascinating fields where it has expanded its branches, too. Not only that, but we also review different software tool-sets available to date, which are to lay the foundation for realising quantum simulations in a much more comprehensive manner.Comment: 37 Pages with 13 Figures and 3 Table

MosaiQ: Quantum Generative Adversarial Networks for Image Generation on NISQ Computers

Quantum machine learning and vision have come to the fore recently, with hardware advances enabling rapid advancement in the capabilities of quantum machines. Recently, quantum image generation has been explored with many potential advantages over non-quantum techniques; however, previous techniques have suffered from poor quality and robustness. To address these problems, we introduce, MosaiQ, a high-quality quantum image generation GAN framework that can be executed on today's Near-term Intermediate Scale Quantum (NISQ) computers.Comment: Accepted to appear at ICCV'2

AN OVERVIEW OF VISCOSUPPLEMENTS: THERAPEUTIC MODALITY FOR THE AILMENT OF OSTEOARTHRITIS

Osteoarthritis is a multifarious joint disease and is caused by inflammatory mediators, along with a procedure of wear and tear of cartilage. Osteoarthritis outcome in cartilage degradation, synovial inflammation, subchondral bone eburnation, degeneration of menisci, and capsular hypertrophy, which takes part in the pathogenesis of Osteoarthritis. Pain is the leading symptom of Osteoarthritis. However the precise mechanism causing pain is multifactorial and is still not well known. Viscosupplementation with intraarticular hylauronic acid promotes chondrocyte hyaluronic acid synthesis and prevents the additional cartilage degradation and may possible help to promote the cartilage regeneration. It is also postulated to diminish the production of inflammatory mediators and matrix metalloproteinase involved in Osteoarthritis. Viscosupplementation decline osteoarthritis symptoms in early to judicious Osteoarthritis, and improves functional outcome, if other conservative treatment modalities are ineffective. Hyaluronic acid (HA) is the major constituent of a 1-­â€2μm layer on the surface of articular cartilage; it is also a major constituent of synovial fluid. HA has many properties including exerting an anti-inflammatory effect, it acts as a lubricant when movements in the joint are slow and as a shock absorber when movements are fast effect. Viscosupplementation relieves the symptoms of osteoarthritis of the knee, and this therapeutic effect may last several weeks. However, it is apparently not much greater than that of placebo and, according to some studies, it barely reaches clinical significance. Its pain-relieving effect seems comparable to that of other non-surgical options. The modest clinical benefit of viscosupplementation may never be great enough to outweigh its disadvantages, which include slow onset of action, the need for several weekly injections, the low but present risk of adverse reactions and the relatively high cost of this treatment. It helps in improving the function in early osteoarthritis knee joint and might delay the need for future knee surgery Keywords: Joint disorders, intraarticular hylauronic acid, non-steroidal anti-inflammatory drugs, osteoarthritisÂ

FORMULATION DEVELOPMENT, OPTIMIZATION & IN VITRO CHARATERIZATION OF LIQUISOLID COMPACTS OF AN OXICAM DERIVATIVE

The rationale of the current research was to investigate the in vitro dissolution properties of poorly water soluble piroxicam by utilizing liquisolid technology. Dissimilar liquisoli compacts were formulated using a factorial design to estimate the required quantities of powder and liquid ingredients to fabricate adequately flowable and compressible admixture. About 16 different formulations were developed using factorial design with carriers Neusilin (Magnesium aluminometasilicate)  and Avicel PH 102, binder PVP K-30 and vehicle PEG-400 as independent variables and Aerosil 200 is used as coating material. The In-vitro drug release from the LSC has used a dependent variable. The empirical method by Spireas and Bolton was applied to calculate the amounts of carrier and coating materials and obtained the improved flow characteristics and hardness by changing the proportion of carrier and coating materials. Liquid solid compacts were fabricated and evaluated for their tabletting properties. Fourier transform infrared (FTIR) analysis, differential scanning calorimetry (DSC) and X- ray powder diffraction (XRPD) were performed. The FTIR spectra showed disappearance of the characteristic absorption band of piroxicam (3338.78 cm-1) in liquisolid formulations which might be attributed to the formation of hydrogen bonding between the drug and liquid vehicle; this resulted in drug dissolution enhancement. A 23 factorial design is used and developed liquid soild compacts using Neusilin LSCN1 to LSCN8 and Avicel PH 102 LSCA1 to LSCA8. The physicochemical characterization of all formulations exhibited well within the specification limits with respect to weight variation, hardness, friability and content uniformity.  The In-vitro drug release from these liquid soild compacts was evaluated in 0.1 N HCl and the optimized formulation LSCA8 was compared with pure drug (capsule) and physical mixture (tablet). The release studies suggested that the liquisolid tablets outcome in higher release profile than pure active pharmaceutical ingredient and physical mixture due to enhance in surface and wetting properties of the active pharmaceutical ingredient. Liquid solid compacts technique confirmed the enhanced dissolution rate of oxicam derivative, which in turn promotes in enhancing bioavailability. Keywords: Piroxicam, Factorial design, Solubility, Dissolution rate, Avicel PH 10