Architecting a One-to-many Traffic-Aware and Secure Millimeter-Wave Wireless Network-in-Package Interconnect for Multichip Systems

With the aggressive scaling of device geometries, the yield of complex Multi Core Single Chip(MCSC) systems with many cores will decrease due to the higher probability of manufacturing defects especially, in dies with a large area. Disintegration of large System-on-Chips(SoCs) into smaller chips called chiplets has shown to improve the yield and cost of complex systems. Therefore, platform-based computing modules such as embedded systems and micro-servers have already adopted Multi Core Multi Chip (MCMC) architectures overMCSC architectures. Due to the scaling of memory intensive parallel applications in such systems, data is more likely to be shared among various cores residing in different chips resulting in a significant increase in chip-to-chip traffic, especially one-to-many traffic. This one-to-many traffic is originated mainly to maintain cache-coherence between many cores residing in multiple chips. Besides, one-to-many traffics are also exploited by many parallel programming models, system-level synchronization mechanisms, and control signals. How-ever, state-of-the-art Network-on-Chip (NoC)-based wired interconnection architectures do not provide enough support as they handle such one-to-many traffic as multiple unicast trafficusing a multi-hop MCMC communication fabric. As a result, even a small portion of such one-to-many traffic can significantly reduce system performance as traditional NoC-basedinterconnect cannot mask the high latency and energy consumption caused by chip-to-chipwired I/Os. Moreover, with the increase in memory intensive applications and scaling of MCMC systems, traditional NoC-based wired interconnects fail to provide a scalable inter-connection solution required to support the increased cache-coherence and synchronization generated one-to-many traffic in future MCMC-based High-Performance Computing (HPC) nodes. Therefore, these computation and memory intensive MCMC systems need an energy-efficient, low latency, and scalable one-to-many (broadcast/multicast) traffic-aware interconnection infrastructure to ensure high-performance. Research in recent years has shown that Wireless Network-in-Package (WiNiP) architectures with CMOS compatible Millimeter-Wave (mm-wave) transceivers can provide a scalable, low latency, and energy-efficient interconnect solution for on and off-chip communication. In this dissertation, a one-to-many traffic-aware WiNiP interconnection architecture with a starvation-free hybrid Medium Access Control (MAC), an asymmetric topology, and a novel flow control has been proposed. The different components of the proposed architecture are individually one-to-many traffic-aware and as a system, they collaborate with each other to provide required support for one-to-many traffic communication in a MCMC environment. It has been shown that such interconnection architecture can reduce energy consumption and average packet latency by 46.96% and 47.08% respectively for MCMC systems. Despite providing performance enhancements, wireless channel, being an unguided medium, is vulnerable to various security attacks such as jamming induced Denial-of-Service (DoS), eavesdropping, and spoofing. Further, to minimize the time-to-market and design costs, modern SoCs often use Third Party IPs (3PIPs) from untrusted organizations. An adversary either at the foundry or at the 3PIP design house can introduce a malicious circuitry, to jeopardize an SoC. Such malicious circuitry is known as a Hardware Trojan (HT). An HTplanted in the WiNiP from a vulnerable design or manufacturing process can compromise a Wireless Interface (WI) to enable illegitimate transmission through the infected WI resulting in a potential DoS attack for other WIs in the MCMC system. Moreover, HTs can be used for various other malicious purposes, including battery exhaustion, functionality subversion, and information leakage. This information when leaked to a malicious external attackercan reveals important information regarding the application suites running on the system, thereby compromising the user profile. To address persistent jamming-based DoS attack in WiNiP, in this dissertation, a secure WiNiP interconnection architecture for MCMC systems has been proposed that re-uses the one-to-many traffic-aware MAC and existing Design for Testability (DFT) hardware along with Machine Learning (ML) approach. Furthermore, a novel Simulated Annealing (SA)-based routing obfuscation mechanism was also proposed toprotect against an HT-assisted novel traffic analysis attack. Simulation results show that,the ML classifiers can achieve an accuracy of 99.87% for DoS attack detection while SA-basedrouting obfuscation could reduce application detection accuracy to only 15% for HT-assistedtraffic analysis attack and hence, secure the WiNiP fabric from age-old and emerging attacks

Examining the linkage between class attendance at university and academic performance in an international branch campus setting

The relationship between class attendance and academic performance has been an important area of research, with a positive association being posited between the two. The setting for our study is an International Branch Campus (IBC) of a British university that needs to demonstrate the quality of its service delivery both to the parent institution and to the fee-paying students. We employ a dataset of over 900 students in an undergraduate degree programme and subject it to statistical techniques, namely quantile regression and two-stage quantile regression. Our results show that attendance has a beneficial influence on academic performance and this benefit persists at higher percentile of grades. We propose that IBCs could consider an attendance policy that encourages students to attend classes

Applying marketing mix constructs in higher education: the case of an MBA programme in the UAE

This exploratory study identifies significant choice factors for prospective students when selecting a Master of Business Administration (MBA) programme in the increasingly competitive higher education sector in the United Arab Emirates (UAE). Implications for Higher Education Institutions (HEIs) when they develop marketing communication strategies are addressed. Study participants included current MBA students, MBA graduates who have completed their degree at a British University’s campus in the UAE and prospective students who chose not to enrol on that MBA programme. Constructs were tested for reliability using the Cronbach Alpha test. The relative importance of specific choice factors were assessed via analysis of the means of the constructs. The difference between the most important (People) and least important (Promotion) factors were as much as 34%. Differences between three groups of study participants were analysed based on the results of Scheffé's post-hoc test. Marketing implications for HEIs include: improving the quality of the factors identified and communicating the quality of these factors; especially intangible ones, to potential MBA candidates more effectively

Robust Ensemble Morph Detection with Domain Generalization

Although a substantial amount of studies is dedicated to morph detection, most of them fail to generalize for morph faces outside of their training paradigm. Moreover, recent morph detection methods are highly vulnerable to adversarial attacks. In this paper, we intend to learn a morph detection model with high generalization to a wide range of morphing attacks and high robustness against different adversarial attacks. To this aim, we develop an ensemble of convolutional neural networks (CNNs) and Transformer models to benefit from their capabilities simultaneously. To improve the robust accuracy of the ensemble model, we employ multi-perturbation adversarial training and generate adversarial examples with high transferability for several single models. Our exhaustive evaluations demonstrate that the proposed robust ensemble model generalizes to several morphing attacks and face datasets. In addition, we validate that our robust ensemble model gain better robustness against several adversarial attacks while outperforming the state-of-the-art studies.Comment: Accepted in IJCB 202

Dredging induced changes in zooplankton community and water quality in Dal Lake, Kashmir, India

A study was conducted from July 2013 to June 2014 to assess the outcome of dredging activity on the water characteristics and zooplankton community structure in Dal Lake. An assessment was done with respect to alterations in physico-chemical  parameters and zooplankton community changes in predredged and post-dredging periods. The results showed a considerable  reduction in Secchi transparency while water depth, conductivity, total dissolved solids, nitrate and total phosphorous concentrations increased noticeably in post dredging scenario. Variations in the values of dissolved oxygen, pH and temperature as a result of dredging were not statistically significant. The environmental changes as a result of dredging activity affected the structure and distribution of zooplankton community; the abundance of rotifers decreased, while the crustaceans increased. The prominent taxa were Brachionus sp., Keratella cochlearis, Bosmina longirostris, Chydorus sphaericus and Diaptomus sp.Key words: Dredging, water quality, zooplankton, rotifer, crustacean