Minimising total cost with regular and emergency outsourcing sources: a neuro-dynamic programming approach

This study models and explains the business situation of an organisation which has regular and emergency outsourcing sources and where decisions have to be made at the beginning of every period regarding how much to order from these sources, so as to balance between different cost components of current and future periods. Previous works in this area have tried to attack this problem with dynamic programming. In this project, neuro-dynamic programming has been applied, and the reasons for doing so have been clearly stated. This model not only derives policies in order to minimise the expected total discounted cost over a period of time, but also enables the system to learn to make such decisions, and to improve its actions by using reinforcement learning. The performance of the present work has been measured quantitatively and has been compared with the models stated in literature. This study will be very useful for the organisations where such business problems exist or are likely to exist. This study will also be of great use to researchers, who are keen to understand and model the given business situation with distribution independent demand based models.     

Solar stills: A review

The availability of drinking water is reducing day by day; where as the requirement of drinking water is increasing rapidly. To overcome this problem there is a need for some sustainable source for the water distillation (purification). Solar still is a useful device that can be used for the distilling of brackish water for the drinking purposes. In this article a review has been done on different types of solar still.     

Efficient photodegradation of methylene blue (MB) under solar radiation by ZrC nanoparticles

Due to increase in water pollution, there is a need to dwindle this problem for a clean and green future. Photocatalysts like ZnO, CaO and TiO₂ have proved to be triumphant in removal of environmental contaminants. In this present work, ZrC nanopowder has been synthesized using a single-step reduction technique by heating zirconium oxide (ZrO₂) and hexane (C₆H₁₄) in metallic Mg powder and is used as a photocatalyst for the degradation of methylene blue (MB) dye under solar radiation. Optimization of synthesis parameters (temperature, holding time and carbon content) has been done to obtain single phase ZrC. Various characterization techniques like X-ray diffraction (XRD), transmission electron microscope (TEM), differential scanning calorimetry/thermal gravimetric analysis (DSC/TGA) and X-ray photoelectron spectroscopy (XPS) were studied for various structural, thermal and surface characteristics of as-synthesized samples. The effect of synthesis parameters on crystal distortion of ZrC particles was studied with the help of Double Voigt analysis. Further, the comparative catalytic activity as photodegradation of MB dye with the help of optimized sample was studied under UV and solar radiations. As an effect of illumination source with the same concentration of catalyst and dye, 80% degradation was observed under solar radiations which is quite higher than that observed under UV in 5?h.     

Additive Number Theory via Automata Theory

Theory of Computing Systems - We show how some problems in additive number theory can be attacked in a novel way, using techniques from the theory of finite automata. We start by recalling the...     

Liquid crystal order in colloidal suspensions of spheroidal particles by direct current electric field assembly

DC electric fields are used to produce colloidal assemblies with orientational and layered positional order from a dilute suspension of spheroidal particles. These 3D assemblies, which can be visualized in situ by confocal microscopy, are achieved in short time spans (t < 1 h) by the application of a constant voltage across the capacitor-like device. This method yields denser and more ordered assemblies than had been previously reported with other assembly methods. Structures with a high degree of orientational order as well as layered positional order normal to the electrode surface are observed. These colloidal structures are explained as a consequence of electrophoretic deposition and field-assisted assembly. The interplay between the deposition rate and the rotational Brownian motion is found to be critical for the optimal ordering, which occurs when these rates, as quantified by the Peclet number, are of order one. The results suggest that the mechanism leading to ordering is equilibrium self-assembly but with kinetics dramatically accelerated by the application of the DC electric field. Finally, the crystalline symmetry of the densest structure formed is determined and compared with previously studied spheroidal assemblies.     

Effects of Defects on Charge Transport in Armchair Nanoribbon WS2 Field Effect Transistors

We have studied the WS₂ armchair nanoribbon with various defects like vacancy, edge roughness, twist, turn and ripple and compared how the bandgap changes due to such defects with the bandgap of a nanoribbon with no defects. Materials like WS₂ and other transition metal dichalcogenides (MX₂) have a graphene like layered structure with hexagonal rings and have properties that have attracted a lot of interest. Hence it is essential to study the changes in the band structure of the nanoribbon of WS₂ due to the inclusion of defects like vacancy, rough edge, wrap, ripple and twist for making any device based on WS₂.     

Autonomous aerial cinematography in unstructured environments with learned artistic decision‐making

Aerial cinematography is revolutionizing industries that require live and dynamic camera viewpoints such as entertainment, sports, and security. However, safely piloting a drone while filming a moving target in the presence of obstacles is immensely taxing, often requiring multiple expert human operators. Hence, there is a demand for an autonomous cinematographer that can reason about both geometry and scene context in real‐time. Existing approaches do not address all aspects of this problem; they either require high‐precision motion‐capture systems or global positioning system tags to localize targets, rely on prior maps of the environment, plan for short time horizons, or only follow fixed artistic guidelines specified before the flight. In this study, we address the problem in its entirety and propose a complete system for real‐time aerial cinematography that for the first time combines: (a) vision‐based target estimation; (b) 3D signed‐distance mapping for occlusion estimation; (c) efficient trajectory optimization for long time‐horizon camera motion; and (d) learning‐based artistic shot selection. We extensively evaluate our system both in simulation and in field experiments by filming dynamic targets moving through unstructured environments. Our results indicate that our system can operate reliably in the real world without restrictive assumptions. We also provide in‐depth analysis and discussions for each module, with the hope that our design tradeoffs can generalize to other related applications. Videos of the complete system can be found at https://youtu.be/ookhHnqmlaU .     

A Temporal Locality-Aware Page-Mapped Flash Translation Layer

The poor performance of random writes has been a cause of major concern which needs to be addressed to better utilize the potential of flash in enterprise-scale environments. We examine one of the important causes of this poor performance： the design of the flash translation layer （FTL） which performs the virtual-to-physical address translations and hides the erase-before-write characteristics of flash. We propose a complete paradigm shift in the design of the core FTL engine from the existing techniques with our Demand-Based Flash Translation Layer （DFTL） which selectively caches page- level address mappings. Our experimental evaluation using FlashSim with realistic enterprise-scale workloads endorses the utility of DFTL in enterprise-scale storage systems by demonstrating： 1） improved performance, 2） reduced garbage collection overhead and 3） better overload behavior compared with hybrid FTL schemes which are the most popular implementation methods. For example, a predominantly random-write dominant I/O trace from an OLTP application running at a large financial institution shows a 78% improvement in average response time （due to a 3-fold reduction in operations of the garbage collector）, compared with the hybrid FTL scheme. Even for the well-known read-dominant TPC-H benchmark, for which DFTL introduces additional overheads, we improve system response time by 56%. Moreover, interestingly, when write-back cache on DFTL-based SSD is enabled, DFTL even outperforms the page-based FTL scheme, improving their response time by 72% in Financial trace.