Study of the regenerator constituting material influence on a gamma type Stirling engine

A gamma Stirling engine with compressed air as working fluid was investigated. This engine operates at a maximum charge pressure of 10 bar, runs at a maximum rotation speed of 600 rpm and can provide 500 W of brake power on the shaft. The engine is equipped with several pressure sensors and thermocouples. This experimental study concentrates on the regenerator constituting material (porous medium). Four different materials were investigated: stainless steel, copper, aluminum and Monel 400. The obtained experimental results provide guidance to Stirling engine enhancement and selection of the appropriate regenerator material. As a conclusion, the regenerator has an important role to enhance the heat exchange and to improve Stirling engine performance, which closely depends on its constituting material.     

Highly-Directional,Highly-Efficient Solution-Processed Light-Emitting Diodes of All-Face-Down Oriented Colloidal Quantum Well Self-Assembly

Semiconductor colloidal quantum wells (CQWs) provide anisotropic emission behavior originating from their anisotropic optical transition dipole moments (TDMs). Here, solution-processed colloidal quantum well light-emitting diodes (CQW-LEDs) of a single all-face-down oriented self-assembled monolayer (SAM) film of CQWs that collectively enable a supreme level of IP TDMs at 92% in the ensemble emission are shown. This significantly enhances the outcoupling efficiency from 22% (of standard randomly-oriented emitters) to 34% (of face-down oriented emitters) in the LED. As a result, the external quantum efficiency reaches a record high level of 18.1% for the solution-processed type of CQW-LEDs, putting their efficiency performance on par with the hybrid organic-inorganic evaporation-based CQW-LEDs and all other best solution-processed LEDs. This SAM-CQW-LED architecture allows for a high maximum brightness of 19,800 cd m⁻² with a long operational lifetime of 247 h at 100 cd m⁻² as well as a stable saturated deep-red emission (651 nm) with a low turn-on voltage of 1.7 eV at a current density of 1 mA cm⁻² and a high J₉₀ of 99.58 mA cm⁻². These findings indicate the effectiveness of oriented self-assembly of CQWs as an electrically-driven emissive layer in improving outcoupling and external quantum efficiencies in the CQW-LEDs.     

An Efficient Internet Traffic Classification System Using Deep Learning for IoT

Internet of Things (IoT) defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central location. These IoT devices are connected to a network therefore prone to attacks. Various management tasks and network operations such as security, intrusion detection, Quality-of-Service provisioning, performance monitoring, resource provisioning, and traffic engineering require traffic classification. Due to the ineffectiveness of traditional classification schemes, such as port-based and payload-based methods, researchers proposed machine learning-based traffic classification systems based on shallow neural networks. Furthermore, machine learning-based models incline to misclassify internet traffic due to improper feature selection. In this research, an efficient multilayer deep learning based classification system is presented to overcome these challenges that can classify internet traffic. To examine the performance of the proposed technique, Moore-dataset is used for training the classifier. The proposed scheme takes the pre-processed data and extracts the flow features using a deep neural network (DNN). In particular, the maximum entropy classifier is used to classify the internet traffic. The experimental results show that the proposed hybrid deep learning algorithm is effective and achieved high accuracy for internet traffic classification, i.e., 99.23%. Furthermore, the proposed algorithm achieved the highest accuracy compared to the support vector machine (SVM) based classification technique and k-nearest neighbours (KNNs) based classification technique.     

First-Principle Investigation of Structural,Electronic and Magnetic Properties in Mn<Subscript>2</Subscript>RhZ (Z = Si,Ge, and Sn) Heusler Alloys

Mn ₂-based Heusler compounds exhibit different types of anti-site disorder. The electronic structure and magnetism of Heusler alloys Mn₂RhZ (Z = Si, Ge, and Sn) have been studied by first-principle calculations. Mn₂RhSi and Mn₂RhGe are ordinary half-metallic ferrimagnetic metals at equilibrium lattice constants, with a magnetic spin moments obeys to the Slater-Pauling rule and spin polarization of 100 % at the Fermi energy. The tetragonal phase transformation is studied for Mn₂RhSn. The total magnetic moment of Mn₂RhSn in the tetragonal structure is higher compared to the other materials, which results in a large ΔM between the saturation moments of tetragonal and a cubic. The tetragonal Mn₂RhSn predicted to a high spin polarization ratio of 93 %. These properties of these materials are particularly interesting due to their perpendicular magnetic anisotropy (PMA), which was realized in thin films opening the door for application in STT magnetic random access memories (STT-MRAMs)     

The effects of text structure and prior knowledge of the learner on computer-based learning

This study is an attempt to investigate the effects of document structure and knowledge level of the reader on reading comprehension, browsing, and perceived control. Four types of texts are distinguished, differing in structure (linear text, hierarchical hypertext, mixed hypertext, and generative text). All the materials were on a PC. In all conditions, participants were allowed 1 h to read through the document. After completing the reading part of the experiment, they were asked to fill out the perceived control questionnaire followed by the reading comprehension test. As far as reading comprehension was concerned, knowledgeable participants had higher reading comprehension scores than non-knowledgeable participants only in the linear text. In addition, there were no significant differences in terms of the reading comprehension scores of the knowledgeable participants among the four topologies. However, the performance of non-knowledgeable participants differed with respect to the type of the topology. In particular, non-knowledgeable participants in the hierarchical and generative conditions performed better than those in the other two conditions. With respect to perceived control, the performance of knowledgeable and non-knowledgeable participants was equivalent in all four conditions. The results are discussed in terms of their implications for the computer-based learning.     

Synthesis and electrochemical capacitance of binderless nanocomposite electrodes formed by dispersion of carbon nanotubes and carbon aerogels

Novel nanocomposite carbon aerogel (CAG)-multi-walled carbon nanotubes (MWNT) materials have been synthesized and studied in 5 M KOH for electrochemical capacitor applications. The amount of MWNT in the nanocomposite was varied from 3 to 10 wt%. High specific surface areas ranging between 670 and 710 m² g⁻¹ were obtained as measured by nitrogen gas adsorption method, whereas the average pore diameter ranged between 1 and 4 nm.     

Application of a Genetic Algorithm for the Optimization of a Complex Reservoir System in Tunisia

A genetic algorithm (GA) model is developed and used for optimizing the allocation of water resources within a complex multiple reservoir system located in Tunisia. The GA model considers two objectives: the water allocation to demand centers and the salinity level of the water supply to end users. These two objectives are combined into a single objective function using a weighting factor approach. Five different cases (representing five different weighting factor combinations) were analyzed by the GA model to produce the “optimum” allocation of water resources for each case. The generated solutions exhibited low variability. The results are then compared using a range of system performance indicators to measure reliability, resilience, and vulnerability. The evaluation of the system performance is an essential step to help system managers identify the preferred allocation strategy and it provides a comprehensive insight into system behavior.     

Reuse of urban wastewater treated by a combined stabilisation pond system in Benslimane (Morocco)

The aim of this paper is to study the performance of a combined waste stabilisation pond after three years of functioning and the reuse of treated wastewater for irrigating potatoes and lettuce culture. The combined ponds showed good functioning conditions and excellent performances either for organic load (90%), faecal coliform (6 log units) or helminth eggs (100%) and produced a high and perennial effluent quality. The effluent could be used for non-restrictive irrigation, with a clear improvement of culture production and hygienic quality for both fruits and soil.