Improving the Technology of Reforestation in Cuttings with the Use of Energy-Efficient Tractors

Currently applied partial reforestation in cuttings and removal of stumps by uprooting have a number of significant technological, environmental and economic disadvantages. These are removal of the humus layer of soil outside the cleared strips, compaction and reduction of soil porosity; formation of understump holes and their local waterlogging; littering of noncleared belts of trees between strips with felling debris and uprooted stumps; low productivity of uprooting machines and high energy consumption of stump uprooting; termination of agrotechnical tending after 2–3 years after planting and impossibility of cleaning stands due to their obstruction for tractor units; low level of traction force of special forest tractors and their insufficient power for uprooting stumps. Technology, machines and tools for reforestation in cuttings become the subjects of the research. The aim of the research is to provide a comprehensive mechanization of the reforestation process in order to improve work productivity, reduce energy and material consumption of the technology and create conditions for the effective use of machines and tools in combination with energy-efficient tractors of the traction-energy concept, ensuring the elimination of harmful effects on soil and plants ecology. The results of achieving the set aim and objectives are substantiation of forestry and ecological, technical, and economic feasibility of using the technology based on the complete clearing of cuttings from felling residues, dead wood and coppice of shrub vegetation by their crushing using mobile mulchers; removal of stumps in cuttings through crushing them at a depth of 0.15–0.20 m by an upgraded MUP-4A machine with scattering chips over the planting area and subsequent continuous tillage with a disk harrow BDK-2.5. Harmful effects on the ecology of soil and plants are practically eliminated with an increase in productivity, and the grinded woody biomass mixed with the soil turns into an organic fertilizer. The elimination of mechanical obstacles such as felling residues, fallen trees and stumps makes it possible to effectively use energy-efficient tractors by combining technological operations and performing them in one pass of the unit, as well as increasing the working width and operating speeds. Conditions for efficient operation of forestry machines and tools on tractormotor traction to protect the forest from pests, diseases, and fires, and for mechanization of various types of thinning are being created. For citation: Bartenev I.M., Drapalyuk M.V. Improving the Technology of Reforestation in Cuttings with the Use of Energy-Efficient Tractors. Lesnoy Zhurnal [Russian Forestry Journal], 2021, no. 5, pp. 117–133. DOI: 10.37482/0536-1036-2021-5-117-133

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Energy efficient biomorphic pulse information coding in electronic neurons for the entrance unit of the neuroprocessor

Tyumen State University Herald Physical and Mathematical Modeling Oil Gas Energy ◽

10.21684/2411-7978-2019-5-3-186-212 ◽

2019 ◽

Vol 5 (3) ◽

pp. 186-212 ◽

Cited By ~ 1

Author(s):

Alexander D. Pisarev

Keyword(s):

Neural Networks ◽

Energy Efficiency ◽

Energy Efficient ◽

Information Transfer ◽

Biological Systems ◽

Technological Parameters ◽

Input Unit ◽

Efficient Operation ◽

Electric Circuits ◽

Electronic Neuron

This article studies the implementation of some well-known principles of information work of biological systems in the input unit of the neuroprocessor, including spike coding of information used in models of neural networks of the latest generation.<br> The development of modern neural network IT gives rise to a number of urgent tasks at the junction of several scientific disciplines. One of them is to create a hardware platform — a neuroprocessor for energy-efficient operation of neural networks. Recently, the development of nanotechnology of the main units of the neuroprocessor relies on combined memristor super-large logical and storage matrices. The matrix topology is built on the principle of maximum integration of programmable links between nodes. This article describes a method for implementing biomorphic neural functionality based on programmable links of a highly integrated 3D logic matrix.<br> This paper focuses on the problem of achieving energy efficiency of the hardware used to model neural networks. The main part analyzes the known facts of the principles of information transfer and processing in biological systems from the point of view of their implementation in the input unit of the neuroprocessor. The author deals with the scheme of an electronic neuron implemented based on elements of a 3D logical matrix. A pulsed method of encoding input information is presented, which most realistically reflects the principle of operation of a sensory biological neural system. The model of an electronic neuron for selecting ranges of technological parameters in a real 3D logic matrix scheme is analyzed. The implementation of disjunctively normal forms is shown, using the logic function in the input unit of a neuroprocessor as an example. The results of modeling fragments of electric circuits with memristors of a 3D logical matrix in programming mode are presented.<br> The author concludes that biomorphic pulse coding of standard digital signals allows achieving a high degree of energy efficiency of the logic elements of the neuroprocessor by reducing the number of valve operations. Energy efficiency makes it possible to overcome the thermal limitation of the scalable technology of three-dimensional layout of elements in memristor crossbars.

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Enhanced Adaptive Distributed Energy-Efficient Clustering (EADEEC) for Wireless Sensor Networks

Recent Advances in Computer Science and Communications ◽

10.2174/2213275912666190404162447 ◽

2020 ◽

Vol 13 (2) ◽

pp. 168-172

Author(s):

Ravi Kumar Poluru ◽

M. Praveen Kumar Reddy ◽

Syed Muzamil Basha ◽

Rizwan Patan ◽

Suresh Kallam

Keyword(s):

Network Lifetime ◽

Routing Protocols ◽

Energy Efficient ◽

High Energy ◽

Base Station ◽

Sensor Nodes ◽

Wireless Sensor ◽

Distributed Energy ◽

Stability Period ◽

Energy Efficient Clustering

Background:Recently Wireless Sensor Network (WSN) is a composed of a full number of arbitrarily dispensed energy-constrained sensor nodes. The sensor nodes help in sensing the data and then it will transmit it to sink. The Base station will produce a significant amount of energy while accessing the sensing data and transmitting data. High energy is required to move towards base station when sensing and transmitting data. WSN possesses significant challenges like saving energy and extending network lifetime. In WSN the most research goals in routing protocols such as robustness, energy efficiency, high reliability, network lifetime, fault tolerance, deployment of nodes and latency. Most of the routing protocols are based upon clustering has been proposed using heterogeneity. For optimizing energy consumption in WSN, a vital technique referred to as clustering.Methods:To improve the lifetime of network and stability we have proposed an Enhanced Adaptive Distributed Energy-Efficient Clustering (EADEEC).Results:In simulation results describes the protocol performs better regarding network lifetime and packet delivery capacity compared to EEDEC and DEEC algorithm. Stability period and network lifetime are improved in EADEEC compare to DEEC and EDEEC.Conclusion:The EADEEC is overall Lifetime of a cluster is improved to perform the network operation: Data transfer, Node Lifetime and stability period of the cluster. EADEEC protocol evidently tells that it improved the throughput, extended the lifetime of network, longevity, and stability compared with DEEC and EDEEC.

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Energy Efficient Operation of Massive MIMO in Industrial Internet of Things Networks

IEEE Internet of Things Journal ◽

10.1109/jiot.2020.3039236 ◽

2020 ◽

pp. 1-1

Author(s):

Byung Moo Lee

Keyword(s):

Internet Of Things ◽

Energy Efficient ◽

Massive Mimo ◽

Industrial Internet Of Things ◽

Efficient Operation ◽

Industrial Internet

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Enabling holistic design for high energy efficient office buildings through the use of subjective occupant feedback

Sustainable Cities and Society ◽

10.1016/j.scs.2021.102867 ◽

2021 ◽

pp. 102867

Author(s):

Niels Lassen ◽

Tine Hegli ◽

Tor Helge Dokka ◽

Terje Løvold ◽

Kristian Edwards ◽

...

Keyword(s):

Energy Efficient ◽

High Energy ◽

Office Buildings ◽

Occupant Feedback ◽

Holistic Design

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Processing Methodologies of Wet Microalga Biomass Toward Oil Separation: An Overview

Molecules ◽

10.3390/molecules26030641 ◽

2021 ◽

Vol 26 (3) ◽

pp. 641

Author(s):

Vânia Pôjo ◽

Tânia Tavares ◽

Francisco Xavier Malcata

Keyword(s):

Food System ◽

Lipid Extraction ◽

High Energy ◽

Economic Feasibility ◽

Alternative Source ◽

Microalgal Biomass ◽

Energy Demands ◽

Chemical Profiles ◽

System Sustainability ◽

Industrial Level

One of the main goals of Mankind is to ensure food system sustainability—including management of land, soil, water, and biodiversity. Microalgae accordingly appear as an innovative and scalable alternative source in view of the richness of their chemical profiles. In what concerns lipids in particular, microalgae can synthesize and accumulate significant amounts of fatty acids, a great fraction of which are polyunsaturated; this makes them excellent candidates within the framework of production and exploitation of lipids by various industrial and health sectors, either as bulk products or fine chemicals. Conventional lipid extraction methodologies require previous dehydration of microalgal biomass, which hampers economic feasibility due to the high energy demands thereof. Therefore, extraction of lipids directly from wet biomass would be a plus in this endeavor. Supporting processes and methodologies are still limited, and most approaches are empirical in nature—so a deeper mechanistic elucidation is a must, in order to facilitate rational optimization of the extraction processes. Besides circumventing the current high energy demands by dehydration, an ideal extraction method should be selective, sustainable, efficient, harmless, and feasible for upscale to industrial level. This review presents and discusses several pretreatments incurred in lipid extraction from wet microalga biomass, namely recent developments and integrated processes. Unfortunately, most such developments have been proven at bench-scale only—so demonstration in large facilities is still needed to confirm whether they can turn into competitive alternatives.

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Energy efficient fixed-cluster architecture for wireless sensor networks

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-192177 ◽

2021 ◽

Vol 40 (5) ◽

pp. 8727-8740

Author(s):

Rajvir Singh ◽

C. Rama Krishna ◽

Rajnish Sharma ◽

Renu Vig

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Data Aggregation ◽

Energy Efficient ◽

Search Algorithm ◽

Cluster Formation ◽

Wireless Sensor ◽

Efficient Operation ◽

Cluster Architecture ◽

Dynamic Cluster

Dynamic and frequent re-clustering of nodes along with data aggregation is used to achieve energy-efficient operation in wireless sensor networks. But dynamic cluster formation supports data aggregation only when clusters can be formed using any set of nodes that lie in close proximity to each other. Frequent re-clustering makes network management difficult and adversely affects the use of energy efficient TDMA-based scheduling for data collection within the clusters. To circumvent these issues, a centralized Fixed-Cluster Architecture (FCA) has been proposed in this paper. The proposed scheme leads to a simplified network implementation for smart spaces where it makes more sense to aggregate data that belongs to a cluster of sensors located within the confines of a designated area. A comparative study is done with dynamic clusters formed with a distributive Low Energy Adaptive Clustering Hierarchy (LEACH) and a centralized Harmonic Search Algorithm (HSA). Using uniform cluster size for FCA, the results show that it utilizes the available energy efficiently by providing stability period values that are 56% and 41% more as compared to LEACH and HSA respectively.

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