Characterisation of CO/NO/SO2 emission and ash-forming elements from the combustion and pyrolysis process

Bioenergy is considered as a sustainable energy which can play a significant role in the future’s energy scenarios to replace fossil fuels, not only in the heat production, but also in the electricity and transportation sectors. Emission formation and release of main ash-forming elements during thermal conversion of biomass fuels at different conditions have been the scope of this study. The experiments were conducted in a quartz glass reactor where the temperature and atmosphere could be controlled. The selected fuels represent a wide range of biomass compositions. They are torrefied softwood, spruce bark, waste wood, miscanthus, and wheat straw. The fuels were first grinded and then pressed with a pellet maker into pellets of the same size and weight. For each fuel, the experiments were carried out under both oxidation and pyrolysis condition, with atmosphere of 3 % O₂ + 97 % N₂ and 100 % N₂, respectively, at four residence times. The selected temperatures under which experiments were performed are 800, 900, and 1,050 °C. The concentration of SO₂, NO, CO, and CO₂ emissions and O₂ were monitored online by three analysers, simultaneously. The residue weight was measured after each process, and the comparison with the ash content of the fresh pellet is made. Additionally, the release of several ash-forming elements (K, Zn, Na, and Mn) from the fuels has been quantified as function of temperature and residence time by inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma atomic emission spectroscopy (ICP-AES). Time-dependent formation of NO and SO₂ and other emissions is presented and discussed with respect to different temperature and combustion conditions.     

Experimental investigation of adverse effect of frost formation on microchannel evaporators,part 1: Effect of fin geometry and environmental effects

This study experimentally investigated the frost growth on louvered folded fins in microchannel heat exchangers when used in outdoor air-source heat pump systems. The effects of surface temperature, fin geometries, and air environmental conditions were studied. The overall aim was to isolate and quantify the effect of geometry from surface temperature effects. Experimental data of frost weight, local frost thickness, air pressure drop across the coils, time of frost–defrost cycles and heat transfer rates were recorded. Data showed that the frosting time and the frost growth rates depended mainly on the local fin surface temperature. Lower fin density was beneficial because it delayed the blockage of the air flow. The fin length and fin depth had minor effects on frosting performance. The air humidity had a fairly significant effect on rate of frost formation while air velocity seemed to have a small effect on the frost growth rate.     

U-shaped energy loss curves utilization for distributed generation optimization in distribution networks

We propose novel techniques to find the optimal achieve the maximum loss reduction for distribution networks location, size, and power factor of distributed generation （DG） to Determining the optimal DG location and size is achieved simultaneously using the energy loss curves technique for a pre-selected power factor that gives the best DG operation. Based on the network＇s total load demand, four DG sizes are selected. They are used to form energy loss curves for each bus and then for determining the optimal DG options. The study shows that by defining the energy loss minimization as the objective function, the time-varying load demand significantly affects the sizing of DG resources in distribution networks, whereas consideration of power loss as the objective function leads to inconsistent interpretation of loss reduction and other calculations. The devised technique was tested on two test distribution systems of varying size and complexity and validated by comparison with the exhaustive iterative method （EIM） and recently published results. Results showed that the proposed technique can provide an optimal solution with less computation.     

Graph attention-based collaborative filtering for user-specific recommender system using knowledge graph and deep neural networks

Knowledge and Information Systems - Collaborative filtering suffers from the issues of data sparsity and cold start. Due to which recommendation models that only rely on the user–item...     

Attention control with reinforcement learning for face recognition under partial occlusion

In this paper a new method for handling occlusion in face recognition is presented. In this method the faces are partitioned into blocks and a sequential recognition structure is developed. Then, a spatial attention control strategy over the blocks is learned using reinforcement learning. The outcome of this learning is a sorted list of blocks according to their average importance in the face recognition task. In the recall mode, the sorted blocks are employed sequentially until a confident decision is made. Obtained results of various experiments on the AR face database demonstrate the superior performance of proposed method as compared with that of the holistic approach in the recognition of occluded faces.     

Model-based PI–fuzzy control of four-wheeled omni-directional mobile robots

The purpose of this study is to suggest and examine a PI–fuzzy path planner and associated low-level control system for a linear discrete dynamic model of omni-directional mobile robots to obtain optimal inputs for drivers. Velocity and acceleration filtering is also implemented in the path planner to satisfy planning prerequisites and prevent slippage. Regulated drivers’ rotational velocities and torques greatly affect the ability of these robots to perform trajectory planner tasks. These regulated values are examined in this research by setting up an optimal controller. Introducing optimal controllers such as linear quadratic tracking for multi-input–multi-output control systems in acceleration and deceleration is one of the essential subjects for motion control of omni-directional mobile robots. The main topics presented and discussed in this article are improvements in the presented discrete-time linear quadratic tracking approach such as the low-level controller and combined PI–fuzzy path planner with appropriate speed monitoring algorithm such as the high-level one in conditions both with and without external disturbance. The low-level tracking controller presented in this article provides an optimal solution to minimize the differences between the reference trajectory and the system output. The efficiency of this approach is also compared with that of previous PID controllers which employ kinematic modeling. Utilizing the new approach in trajectory-planning controller design results in more precise and appropriate outputs for the motion of four-wheeled omni-directional mobile robots, and the modeling and experimental results confirm this issue.     

Combination of data replication and scheduling algorithm for improving data availability in Data Grids

Data Grid is a geographically distributed environment that deals with large-scale data-intensive applications. Effective scheduling in Grid can reduce the amount of data transferred among nodes by submitting a job to a node, where most of the requested data files are available. Data replication is another key optimization technique for reducing access latency and managing large data by storing data in a wisely manner. In this paper two algorithms are proposed, first a novel job scheduling algorithm called Combined Scheduling Strategy (CSS) that uses hierarchical scheduling to reduce the search time for an appropriate computing node. It considers the number of jobs waiting in queue, the location of required data for the job and the computing capacity of sites. Second a dynamic data replication strategy, called the Modified Dynamic Hierarchical Replication Algorithm (MDHRA) that improves file access time. This strategy is an enhanced version of Dynamic Hierarchical Replication (DHR) strategy. Data replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement. MDHRA replaces replicas based on the last time the replica was requested, number of access, and size of replica. It selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. The simulation results demonstrate the proposed replication and scheduling strategies give better performance compared to the other algorithms.     

An enhanced cost-aware mapping algorithm based on improved shuffled frog leaping in network on chips

The Journal of Supercomputing - Network on chip (NoC) has been of great interest in recent years. However, according to the recent studies, high communication cost has been raised as the one most...     

VPR-Bench: An Open-Source Visual Place Recognition Evaluation Framework with Quantifiable Viewpoint and Appearance Change

International Journal of Computer Vision - Visual place recognition (VPR) is the process of recognising a previously visited place using visual information, often under varying appearance...