scholarly journals Wielokryterialna optymalizacja zużycia energii w domu jednorodzinnym z modyfikacją preferencji entropią

2020 ◽  
pp. 51-64
Author(s):  
Marzena Łagoda ◽  
Keyword(s):  
Energy Consumption ◽  
Entropy Method ◽  
Weighted Sum ◽  
Single Family ◽  
Weighted Sum Method ◽  
Reduce Energy Consumption ◽  
Family Home ◽  
The Way

The article discusses examples of solutions that reduce energy consumption in a single-family home. 7 variants were selected to optimize energy consumption and 6 criteria, which describe the designated solutions. The validity value of the adopted criteria was chosen and four preference variants were subjectively determined for them. The data was then collected in a table and normalized to be able to use the weighted sum method to determine the best solution. In the next step, the entropy method was used and the subjective preferences adopted earlier, were used to determine the way to optimize electricity in a single-family home.

Naval Energy Management System

2020 ◽  
Vol 26 (3) ◽  
pp. 20-25
Author(s):  
Laurențiu Bogdan Asalomia ◽  
Gheorghe Samoilescu
Keyword(s):  
Energy Consumption ◽  
Power Systems ◽  
New Technologies ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Efficient Management ◽  
Reduce Energy Consumption ◽  
Energy Efficiency Design Index ◽  
Green Ship

AbstractThe paper analyses the role of control and monitoring of electro-energetic equipment in order to reduce operational costs, increase profits and reduce carbon emissions. The role of SCADA and EcoStruxure Power systems is presented and analysed taking into account the energy consumption and its savings. The paper presents practical and modern solutions to reduce energy consumption by up to 53%, mass by up to 47% and increase the life of the equipment by adjusting the electrical parameters. The Integrated Navigation System has allowed an automatic control and an efficient management. For ships, the implementation of an energy efficiency design index and new technologies was required for the GREEN SHIP project.

The Research of Measuring Approach and Energy Efficiency for Hadoop Periodic Jobs

2015 ◽  
Vol 8 (1) ◽  
pp. 206-210 ◽  
Author(s):  
Yu Junyang ◽  
Hu Zhigang ◽  
Han Yuanyuan
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Energy Saving ◽  
Energy Estimate ◽  
Cloud Platform ◽  
Periodic Tasks ◽  
Current Consumption ◽  
Reduce Energy Consumption

Current consumption of cloud computing has attracted more and more attention of scholars. The research on Hadoop as a cloud platform and its energy consumption has also received considerable attention from scholars. This paper presents a method to measure the energy consumption of jobs that run on Hadoop, and this method is used to measure the effectiveness of the implementation of periodic tasks on the platform of Hadoop. Combining with the current mainstream of energy estimate formula to conduct further analysis, this paper has reached a conclusion as how to reduce energy consumption of Hadoop by adjusting the split size or using appropriate size of workers (servers). Finally, experiments show the effectiveness of these methods as being energy-saving strategies and verify the feasibility of the methods for the measurement of periodic tasks at the same time.

Performance Analysis of Energy Efficient Opportunistic Routing Protocols in Wireless Sensor Network

2019 ◽  
Vol 09 ◽  
Author(s):  
Premkumar Chithaluru ◽  
Rajeev Tiwari ◽  
Kamal Kumar
Keyword(s):  
Energy Consumption ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Data Communication ◽  
Opportunistic Routing ◽  
Link Quality ◽  
Delivery Ratio ◽  
Performance Parameters ◽  
Wireless Medium ◽  
Reduce Energy Consumption

Background: Energy Efficient wireless routing has been an area of research particularly to mitigate challenges surrounding performance in category of Wireless Networks. Objectives: The Opportunistic Routing (OR) technique was explored in recent times and exhibits benefits over many existing protocols and can significantly reduce energy consumption during data communication with very limited compromise on performance. Methods : Using broadcasting nature of the wireless medium, OR practices to discourse two foremost issues of variable link quality and unpredictable node agility in constrained WSNs. OR has a potential to reduce delay in order to increase the consistency of data delivery in network. Results : Various OR based routing protocols have shown varying performances. In this paper, a detailed conceptual and experimental analysis is carried out on different protocols that uses OR technique for providing more clear and definitive view on performance parameters like Message Success Rate, Packet Delivery Ratio and Energy Consumption.

scholarly journals Graphene-based 3D XNOR-VRRAM with ternary precision for neuromorphic computing

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Batyrbek Alimkhanuly ◽  
Joon Sohn ◽  
Ik-Joon Chang ◽  
Seunghyun Lee
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Recognition Accuracy ◽  
Material Selection ◽  
Weighted Sum ◽  
Device Design ◽  
Key Factors ◽  
Neuromorphic Computing ◽  
Device Scaling ◽  
The Impact

AbstractRecent studies on neural network quantization have demonstrated a beneficial compromise between accuracy, computation rate, and architecture size. Implementing a 3D Vertical RRAM (VRRAM) array accompanied by device scaling may further improve such networks’ density and energy consumption. Individual device design, optimized interconnects, and careful material selection are key factors determining the overall computation performance. In this work, the impact of replacing conventional devices with microfabricated, graphene-based VRRAM is investigated for circuit and algorithmic levels. By exploiting a sub-nm thin 2D material, the VRRAM array demonstrates an improved read/write margins and read inaccuracy level for the weighted-sum procedure. Moreover, energy consumption is significantly reduced in array programming operations. Finally, an XNOR logic-inspired architecture designed to integrate 1-bit ternary precision synaptic weights into graphene-based VRRAM is introduced. Simulations on VRRAM with metal and graphene word-planes demonstrate 83.5 and 94.1% recognition accuracy, respectively, denoting the importance of material innovation in neuromorphic computing.

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