The impact of daylight saving time on electricity consumption: Evidence from southern Norway and Sweden

This paper examines the impact of daylight saving time (DST) on electricity consumption in southern Norway and Sweden. As DST was implemented in both the countries in 1980, we do not have a clear counterfactual in the form of a control period to identify the impact of DST directly with before and after or with and without analysis. This problem in the study is resolved by using “equivalent day normalization technique” to identify the impact of DST. The difference-in-difference (DID) average treatment effects model suggests an annual reduction of at least 1.0 percent in electricity consumption for both Norway and Sweden due to DST. The average annual electricity consumption reduction corresponding to DST effects equals 519 and 882 GWh for southern Norway and Sweden, resulting in an annual financial saving of 16.1 million Euros and 30.1 million Euros, respectively. The distribution of treatment effects across different hours of the day indicates a small but significant reduction in electricity consumption during the morning and a steep decline during the evening hours in both countries.     

Synthesis and characterization of poppy seed oil methyl esters

Response surface methodology(RSM) was used to determine the optimum conditions of the methanolysis of crude poppy seed oil using Na OCH3 as catalyst. The experiments were run according to five levels, four variable central composite rotatable design(CCRD) using RSM. The reaction variables, i.e., molar ratio of methanol/oil(3:1–9:1), catalyst concentration(0.5 wt%–1.25 wt% Na OCH3), reaction temperature(25–65 °C), and reaction time(20–90 min) were studied. We demonstrated that the molar ratio of methanol/oil, catalyst concentration,and reaction temperature were the significant parameters affecting the yield of poppy seed oil methyl esters(PSOMEs). The optimum transesterification reaction conditions, established using the RSM, which offered a89.35% PSOME yield, were found to be 7.5:1 molar ratio of methanol/oil, 0.75% catalyst concentration, 45 °C reaction temperature, and 90 min reaction time. The proposed process provided an average biodiesel yield of more than 85%. A linear correlation was constructed between the observed and predicted values of the yield.The gas chromatography(GC) analyses have shown that PSOMEs contain linoleic-, oleic-, palmitic-, and stearic-acids as main fatty acids. The FTIR spectrum of the PSOMEs was also analyzed to confirm the completion of the transesterification reaction. The fuel properties of the PSOMEs were discussed in light of biodiesel standards(ASTM D 6751 and EN 14214).     

Optimization of Composite Material System and Lay-up to Achieve Minimum Weight Pressure Vessel

The use of composite pressure vessels particularly in the aerospace industry is escalating rapidly because of their superiority in directional strength and colossal weight advantage. The present work elucidates the procedure to optimize the lay-up for composite pressure vessel using finite element analysis and calculate the relative weight saving compared with the reference metallic pressure vessel. The determination of proper fiber orientation and laminate thickness is very important to decrease manufacturing difficulties and increase structural efficiency. In the present work different lay-up sequences for laminates including, cross-ply [0 _m /90 _n ] _s , angle-ply [±θ] _ns , [90/±θ] _ns and [0/±θ] _ns , are analyzed. The lay-up sequence, orientation and laminate thickness (number of layers) are optimized for three candidate composite materials S-glass/epoxy, Kevlar/epoxy and Carbon/epoxy. Finite element analysis of composite pressure vessel is performed by using commercial finite element code ANSYS and utilizing the capabilities of ANSYS Parametric Design Language and Design Optimization module to automate the process of optimization. For verification, a code is developed in MATLAB based on classical lamination theory; incorporating Tsai–Wu failure criterion for first-ply failure (FPF). The results of the MATLAB code shows its effectiveness in theoretical prediction of first-ply failure strengths of laminated composite pressure vessels and close agreement with the FEA results. The optimization results shows that for all the composite material systems considered, the angle-ply [±θ] _ns is the optimum lay-up. For given fixed ply thickness the total thickness of laminate is obtained resulting in factor of safety slightly higher than two. Both Carbon/epoxy and Kevlar/Epoxy resulted in approximately same laminate thickness and considerable percentage of weight saving, but S-glass/epoxy resulted in weight increment.     

Wireless distributed computing in cognitive radio networks

Individual cognitive radio nodes in an ad-hoc cognitive radio network (CRN) have to perform complex data processing operations for several purposes, such as situational awareness and cognitive engine (CE) decision making. In an implementation point of view, each cognitive radio (CR) may not have the computational and power resources to perform these tasks by itself. In this paper, wireless distributed computing (WDC) is presented as a technology that enables multiple resource-constrained nodes to collaborate in computing complex tasks in a distributed manner. This approach has several benefits over the traditional approach of local computing, such as reduced energy and power consumption, reduced burden on the resources of individual nodes, and improved robustness. However, the benefits are negated by the communication overhead involved in WDC. This paper demonstrates the application of WDC to CRNs with the help of an example CE processing task. In addition, the paper analyzes the impact of the wireless environment on WDC scalability in homogeneous and heterogeneous environments. The paper also proposes a workload allocation scheme that utilizes a combination of stochastic optimization and decision-tree search approaches. The results show limitations in the scalability of WDC networks, mainly due to the communication overhead involved in sharing raw data pertaining to delegated computational tasks.     

Task allocation and scheduling in wireless distributed computing networks

Wireless distributed computing (WDC) is an enabling technology that allows radio nodes to cooperate in processing complex computational tasks of an application in a distributed manner. WDC research is being driven by the fact that mobile portable computing devices have limitations in executing complex mobile applications, mainly attributed to their limited resource and functionality. This article focuses on resource allocation in WDC networks, specifically on scheduling and task allocation. In WDC, it is important to schedule communications between the nodes in addition to the allocation of computational tasks to nodes. Communication scheduling and heterogeneity in the operating environment make the WDC resource allocation problem challenging to address. This article presents a task allocation and scheduling algorithm that optimizes both energy consumption and makespan in a heuristic manner. The proposed algorithm uses a comprehensive model of the energy consumption for the execution of tasks and communication between tasks assigned to different radio nodes. The algorithm is tested for three objectives, namely, minimization of makespan, minimization of energy consumption, and minimization of both makespan and energy consumption.     

ACROSS MASS TRANSFER PHENOMENON IN A CHANNEL OF LOWER STRETCHING WALL

This study aims to investigate the effect of across mass transfer (AMT) phenomenon on a three-dimensional steady viscous flow in a channel of lower stretching wall. The phenomenon of AMT is established by imposing suction at one plate and injection at the other plate of the channel simultaneously. Both the walls are assumed to be porous so that suction/injection can take place. Interesting observations regarding viscous drag at the stretching plate have been recorded in the presence of AMT phenomenon at the twin walls. A highly accurate purely analytic solution has been obtained for the governing nonlinear equations. The issue of convergence and accuracy of the analytic solution has been discussed in detail. Results are discussed through graphs.     

Ion-induced secondary electron emission from MgO and Y2O3 thin films

We report a detailed study of the electron emission from MgO and Y₂O₃ induced by the impact of 0.1-1 keV Ar⁺ ions. The mechanisms of ion-induced secondary electron emission from oxides are far less understood because charging of the target surface during ion irradiation prohibits the precise measurement of electron yield. For this study, targets were prepared by depositing 20 nm thick films of MgO and Y₂O₃ on the semi-conducting SnO₂ substrate, which helps in charge neutralization. Additionally, a pulsed ion beam was used to further reduce the surface charging. It was found that the electron yield of both targets increases with energy of the ion. However, at a given ion energy the electron yield of Y₂O₃ was larger than MgO. Another important result of this study is that the electron emission from these large band gap insulators did not show any threshold effect, in contrast to the metal targets. It may be due to local reduction of the band gap through electron promotion processes. In addition, a Monte Carlo program was used to calculate the yield of secondary electrons excited by projectile ions, recoiling target atoms and electron cascades, and average escape depth of the secondary electrons emitted from the MgO and Y₂O₃ thin films.     

Energy RTD expenditures in the European union: Data gathering procedures and results towards a scientific reference system

Insights into the past Energy Research and Technology Development (ERTD) expenditures allows policy makers to better set priorities for current and future ERTD funding as well as to analyze the exact impact of ERTD investments to the development of energy technologies. However, despite numerous attempts in the past, there is currently no comprehensive, validated database that includes disaggregated data on public and private ERTD expenditures in the EU-27 for different technology groups. One of the main aims of the Scientific Reference System for New Energy Technologies and Energy End Use Efficiency (SRS NET & EEE) FP6 project is to enhance the availability, quality and completeness of data on public and private ERTD expenditures, disaggregated for energy technologies and energy end-use efficiency options in the EU-27. The aim of the paper is to outline the main data gathering procedures and results from the “SRS NET & EEE” project, as well as the related policy implication.     

Microscopic melanoma detection and classification: A framework of pixel‐based fusion and multilevel features reduction

The numbers of diagnosed patients by melanoma are drastic and contribute more deaths annually among young peoples. An approximately 192,310 new cases of skin cancer are diagnosed in 2019, which shows the importance of automated systems for the diagnosis process. Accordingly, this article presents an automated method for skin lesions detection and recognition using pixel‐based seed segmented images fusion and multilevel features reduction. The proposed method involves four key steps: (a) mean‐based function is implemented and fed input to top‐hat and bottom‐hat filters which later fused for contrast stretching, (b) seed region growing and graph‐cut method‐based lesion segmentation and fused both segmented lesions through pixel‐based fusion, (c) multilevel features such as histogram oriented gradient (HOG), speeded up robust features (SURF), and color are extracted and simple concatenation is performed, and (d) finally variance precise entropy‐based features reduction and classification through SVM via cubic kernel function. Two different experiments are performed for the evaluation of this method. The segmentation performance is evaluated on PH2, ISBI2016, and ISIC2017 with an accuracy of 95.86, 94.79, and 94.92%, respectively. The classification performance is evaluated on PH2 and ISBI2016 dataset with an accuracy of 98.20 and 95.42%, respectively. The results of the proposed automated systems are outstanding as compared to the current techniques reported in state of art, which demonstrate the validity of the proposed method.