Thermal transport and chemical conversion in single reacting sorbent particles

The effects of particle size and carbon dioxide concentration on chemical conversion in engineered spherical particles undergoing calcium oxide looping are investigated. Particles are thermochemically cycled in a furnace under different carbon dioxide concentrations. Changes in composition due to chemical reactions are measured using thermogravimetric analysis. Gas composition at the furnace exit is evaluated with mass spectroscopy. A numerical model of thermal transport phenomena developed previously is adapted to match the physical system investigated in the present study. The model is used to elucidate effects of reacting medium characteristics on particle temperature and reaction extent. Experimental and numerical results show that (1) an increase in particle size results in a decrease in carbonation extent, and (2) the carbonation step consists of fast and slow reaction regimes. The reaction rates in the fast and slow carbonation regimes increase with increasing carbon dioxide concentration. The effect of carbon dioxide concentration and the distinction between the fast and slow regimes become more pronounced with increasing particle size.     

Reducing web latency with coding-based fast multi-path loss recovery

Wireless Networks - TCP latency is critical to the performance of Web services. However, packet loss greatly impairs the TCP performance due to its poor loss recovery mechanisms. Recent work FUSO...     

Novel Collision Detection and Avoidance System for Midvehicle Using Offset-Based Curvilinear Motion

In recent days, the manufacture of automotive vehicles is dramatically enhanced worldwide. Most vehicle crashes are due to the drive distraction on the real highway roads and traffic-density. In this proposed method, a novel collision detection and avoidance algorithm are coined for Midvehicle Collision Detection and Avoidance System (MCDAS), addressing two scenarios, namely, (a) A rear-end collision avoidance with host vehicle under no front-end vehicle condition and (b) offset-based curvilinear motion under critical conditions, while, suitable parallel parking manoeuvring also addressed using offset-based curvilinear motion. The Monte Carlo analysis of the proposed MCDAS is demonstrated using the Constant Velocity (CV) manoeuvring strategy and simulated with real-time data using the NGSIM database.

     

An Adaptive Neuro-Fuzzy Inference System and Black Widow Optimization Approach for Optimal Resource Utilization and Task Scheduling in a Cloud Environment

Wireless Personal Communications - With the enhancing demand of the cloud computing products, task scheduling issue has become the hot study topic in this area. The task scheduling issue of the...     

The P-graph approach for systematic synthesis of wastewater treatment networks

Wastewater treatment consists of three or four sequential stages: preliminary, primary, secondary, and tertiary. Each stage can comprise multiple alternative technologies that can perform the same tasks with different efficiencies, operating times, and costs. Thus, we propose a systematic approach for designing wastewater treatment networks by utilizing principles of mathematical modeling and generating an exhaustive enumeration of all the possible technologies and their connections during the early stages of designing a treatment facility. Some of these structures are nonintuitive and include recycling, reprocessing, bypasses, and multiple technologies in parallel or series to remove the same contaminant. The nonintuitive structures with multiple technologies may provide a measure of resilience compared to typical heuristic designs. Thus, the combination of P-graph methodology and the sequence of treatment technologies predicted via the optimization algorithm from the maximal structure is based on holistic considerations and does not lead to suboptimal solutions.     

Optimized Path and Reduced Rule Caching Cost for Software Defined Network (SDN) Based Internet of Things (IOT)

Wireless Personal Communications - 2In Software Defined Network based Internet of Things (SDN-IoT), the path selected for forwarding the packets as per rules, should be Quality of Service (QoS)...     

Micro-expression recognition from local facial regions

MiE is a facial involuntary reaction that reflects the real emotion and thoughts of a human being. It is very difficult for a normal human to detect a Micro-Expression (MiE), since it is a very fast and local face reaction with low intensity. As a consequence, it is a challenging task for researchers to build an automatic system for MiE recognition. Previous works for MiE recognition have attempted to use the whole face, yet a facial MiE appears in a small region of the face, which makes the extraction of relevant features a hard task. In this paper, we propose a novel deep learning approach that leverages the locality aspect of MiEs by learning spatio-temporal features from local facial regions using a composite architecture of Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). The proposed solution succeeds to extract relevant local features for MiEs recognition. Experimental results on benchmark datasets demonstrate the highest recognition accuracy of our solution with respect to state-of-the-art methods.     

Optimizing Approach of Water Allocation to Off-Takes During Reduced Flows

Multi-objective optimization models with an index were developed based on farmers’ preferences, local requirements, supplies available at the head of the canal, system losses, crop demand about different growth stages, and field soil moisture balance. The models were applied using linear programming. The Model 1 determines the cropping pattern by maximizing net economic benefits using a monthly basis lumped volume available at the head of the canal and is set to the minimum and maximum area constraints along with the constraint of minimum main crop area. The areas for different crops given by the first model form input for the Model 2. The other inputs of Model 2 included periodic supply available at the head of the primary canal (7-day period in this study), root growth depth, demand, and soil moisture constants. The Model 2 optimizes the sum of relative yields of all the crops and provide the irrigation levels of various crops for specified periods. Finally, the distributed area and irrigation levels determined by Model 2 are used in conjunction with the losses to decide flow rates of off takes. The complete program was implemented in the West branch irrigated area of Mirpurkhas subdivision. The results showed that the resources were allocated to off-takes in a competitive and conflict-free manner.

     

5G-oriented Virtual Augmented Reality Scene Construction and Business Information Flow Demonstration

Mobile Networks and Applications - Aiming at the problems of large data volume, long calculation time, and information feedback speed in traditional virtual augmented reality-based scenes, this...