How to Reduce Information Silos While Blockchain-ifying Recycling Focused Supply Chain Solutions?

Blockchain has already found applications in the supply chain domain to ensure transparency. Recently, blockchain has further been extended to support the circular economy. Existing literature can broadly be divided into product tracing (or track-n-trace) and anti-counterfeiting. Unfortunately, the information generated in existing supply chain applications has stayed in silos. The existence of information silos reduces the value of “blockchain-ifying” the supply chain. Proper data curation via blockchain secures the information and eases the information flow in the supply chain ecosystem, which can accelerate the implementation of the circular economy. In this paper, a blockchain-IoT-based supply chain management framework has been proposed that offers two primary features. They are i) reducing data sitting in silos while opening doors to circular economy-focused services (particularly recycling), ii) documenting suppliers’ performances while delivering quality products focusing on sustainability. Thanks to such unification, relevant supply chain stakeholders will also have access to important events (ranging from the initial stage to the end of the product’s life cycle)

An Efficient NoC-based Framework To Improve Dataflow Thread Management At Runtime

This doctoral thesis focuses on how the application threads that are based on dataflow execution model can be managed at Network-on-Chip (NoC) level. The roots of the dataflow execution model date back to the early 1970’s. Applications adhering to such program execution model follow a simple producer-consumer communication scheme for synchronising parallel thread related activities. In dataflow execution environment, a thread can run if and only if all its required inputs are available. Applications running on a large and complex computing environment can significantly benefit from the adoption of dataflow model. In the first part of the thesis, the work is focused on the thread distribution mechanism. It has been shown that how a scalable hash-based thread distribution mechanism can be implemented at the router level with low overheads. To enhance the support further, a tool to monitor the dataflow threads’ status and a simple, functional model is also incorporated into the design. Next, a software defined NoC has been proposed to manage the distribution of dataflow threads by exploiting its reconfigurability. The second part of this work is focused more on NoC microarchitecture level. Traditional 2D-mesh topology is combined with a standard ring, to understand how such hybrid network topology can outperform the traditional topology (such as 2D-mesh). Finally, a mixed-integer linear programming based analytical model has been proposed to verify if the application threads mapped on to the free cores is optimal or not. The proposed mathematical model can be used as a yardstick to verify the solution quality of the newly developed mapping policy. It is not trivial to provide a complete low-level framework for dataflow thread execution for better resource and power management. However, this work could be considered as a primary framework to which improvements could be carried out

Quantifying the redshift space distortion of the bispectrum III : Detection prospects of the multipole moments

The redshift space anisotropy of the bispectrum is generally quantified using multipole moments. The possibility of measuring these multipoles in any survey depends on the level of statistical fluctuations. We present a formalism to compute the statistical fluctuations in the measurement of bispectrum multipoles for galaxy surveys. We consider specifications of a {\it Euclid} like galaxy survey and present two quantities: the signal-to-noise ratio (SNR) which quantifies the detectability of a multipole, and the rank correlation which quantifies the correlation in measurement errors between any two multipoles. Based on SNR values, we find that {\it Euclid} can potentially measure the bispectrum multipoles up to $\ell=4$ across various triangle shapes, formed by the three {\bf k} vectors in Fourier space. In general, SNR is maximum for the linear triangles. SNR values also depend on the scales and redshifts of observation. While, $\ell \leq 2$ multipoles can be measured with ${\rm SNR}>5$ even at linear/quasi-linear ($k \lesssim 0.1 \,{\rm Mpc}^{-1}$) scales, for $\ell>2$ multipoles, we require to go to small scales or need to increase bin sizes. For most multipole pairs, the errors are only weakly correlated across much of the triangle shapes barring a few in the vicinity of squeezed and stretched triangles. This makes it possible to combine the measurements of different multipoles to increase the effective SNR.Comment: Submitted to MNRAS main journal, 14 Pages, 8 Figure

Beyond Task-technology Fit: Exploring Network Value of Blockchain Technology Based on Two Supply Chain Cases

Despite the popularity of blockchain technology in the supply chain domain, cases with adoption beyond the pilot phase are limited. Even though technology fit is essential for blockchain adoption, we find network fit to be equally important for participating companies in a network. This research explores how the network affects value creation beyond a technology fit. Studying two cases, one from the gemstone industry and another from the shipping industry, we use the task technology fit model, network effects, and structural embeddedness as theoretical lenses to explore the fit that leads to the success of blockchain adoption. Our investigation reveals the task technology fit as a prerequisite and shows central organizations acting as initiators in the early phase, trying to extend the network in subsequent phases. Our investigation indicates that the network fit, autonomy, and equivalence of the organizations contributed to the successful adoption of blockchains