Mepco Schlenk Engineering College

About: Mepco Schlenk Engineering College is a based out in . It is known for research contribution in the topics: Wavelet & Wavelet transform. The organization has 1307 authors who have published 1665 publications receiving 18690 citations.

Mechanical and Acoustic properties of Bagasse – Coconut Coir based Hybrid Reinforced Composites

Abstract: In this paper, a hybrid composite is developed from natural fibers of bagasse and coconut coir. The mechanical and acoustic properties of the hybrid composites are investigated. While preparing the...

Morphological Dependence of Field Emission Properties of Silicon Nanowire Arrays

Abstract: The electron field emission (EFE) properties of vertically aligned arrays of silicon nanowires (SiNWs) grown from silicon substrate at different gold sputtering periods of 0s, 8s, 15s and 25s at a rate of 10nm/min by electroless metal deposition process were investigated. It has been observed that the transformation of silicon tips from irregular to highly dense and uniform cylindrical morphological nanostructures with an increase in Au sputtering periods. A significant enhancement in EFE properties of as-prepared arrays of SiNWs with the increase in Au sputtering periods is observed. The threshold fields for attaining current density of 0.1mAcm−2 were decreased gradually as 32.38Vμm−1, 29.37Vμm−1 and 23.19Vμm−1 for the arrays of SiNWs synthesized from Si substrate by Au coating of 8s, 15s and 25s respectively. Moreover, from Fowler–Nordheim plot, the turn-on field is observed to decrease from 16.56V∕μm for as-prepared to 8.77V∕μm for 25s Au sputtered SiNW arrays. The effective work functions of the electron emitting array of SiNWs have been improved from 0.5meV to 0.1meV.

Design and Development of Closed Loop PI Controlled solar integrated modified A source dc to dc Boosting Topology for standalone battery charging system

Abstract: In this paper, the Electrical vehicle stimulating from renewable energy resources such as solar photovoltaic array using a highly effectual power converter is simulated. A source impedance network custom an autotransformer for comprehending converters for any application that demands a precise dc voltage improvement. Compared to other Magnetically Coupled Impedance Source (MCIS) networks, the network uses a minimum switch ratio to achieve a high voltage gain. Moreover, the improved boosting converter operates at continuous conduction mode and draws a constant current from the resource and is therefore apt for many types of renewable source application. The preferred MPP technique implemented for this propounds work is Incremental Conductance for tracking maximum power from the SPV for having improved solar adaptations.

Application of Differential Evolution Algorithm and Its Variants for Solving Energy Storage Technologies Integrated Generation Expansion Planning

Abstract: Generation expansion planning (GEP) should consider the integration of renewable energy sources (RES) and energy storage technologies (EST), along with conventional generating units so as to overcome the challenges such as uncertainties in future load growth forecasting, restrictions on investment for power generation, the type and availability of source for the generating units, environmental policy based on emission constraints and the reliability level to guarantee a continuous power. The proposed coordinated GEP-EST planning aims at minimizing the overall generation cost and environmental pollution, and at the same time, it considers large-scale ESTs. In this paper, the promising intelligent techniques such as differential evolution and self-adaptive differential evolution algorithms are applied to solve GEP-EST problem, where the power generating system of Tamil Nadu, an Indian state is taken as study system. Simulation results show that the integration of ESTs significantly reduces the overall cost and the pollutant emission.

An ontology enabled internet of things framework in intelligent agriculture for preventing post-harvest losses

Abstract: Constituting the agriculture solid substance manufacture, the post-harvest sector processing schema is direct to preventing reduce the losses in intelligent agriculture. Many processing schemata will be preventing post-harvest losses on the agriculture solid substance manufacture, especially sekai-ichi apple is the regularly used fruit also used to make active in human-related activities of the sensory and control function consisting of an agricultural industry. Sekai-ichi apple is being a definite number of diseases induce, but it is to the highest degree of wastage involving in the Post-Harvest process. Especially sekai-ichi apple count loss is an unsafe many time because it not critically post-harvest. Regardless of consideration, the existing hierarchical model specified post-harvest losses prevention research has deficiencies to precise and quick detection of wastage for ensuring healthy separation of agriculture surroundings. This paper suggests a “Hierarchical Model within Ontology Enabled IoT” for distinguishable healthy separation of sekai-ichi apple by using Boosted Continuous Non-spatial whole Attribute Extraction (BCNAE). Sekai-ichi apple count loss is always safe on critically post-harvest. Proposed Post-Harvest hierarchical model specified post-harvest losses prevention and deficiencies to precise and quick detection of wastage for ensuring healthy separation of agriculture surroundings. In these suggestions, the separation cognitive operation takes the three levels of processing schemes such as lower level, middle level, and higher level. Firstly, the lower level is express agreements with the dynamic functioning for maintaining the definite number of manual induces. This lower level showing an absorption with the activity of manual separation by the human reliability determination. Secondly, the middle level is an express arrangement with the dynamic functioning for reducing the overfitting and accommodate to fitting the right shape deliberation. Middle level is establishing being generalized by concentrating the time-varying features in the occurrence of a change for the worse identification. Finally, the upper level is express for features refining with the help of the function of sekai-ichi apple image segmentation connection. This interpretability process helps to make the proven position of a prominent classification in a particular fruit on the agriculture solid substance. These three processing flow constructs the ontology structure with manually collected sekai-ichi apple images from a 3D sensor. The observational consequences express that the proposed BCNAE framework recognizes a detection performance carrying out with an optimized—separation ratio for time-variant of the separation process.