Percentage Of Energy Consumption Research Articles

Catalyzing sustainable development: Exploring the interplay between access to clean water, sanitation, renewable energy and electricity services in shaping China's energy, economic growth, and environmental landscape

The Sustainable Development Goals (SDGs) reflect the shift in global economic conversation toward inclusive growth. The growth can promote inclusivity and widespread sharing of its advancements by concentrating on four key dimensions. (a) Equality of opportunity, (b) sharing prosperity, (3) environmental sustainability/climate adaptation, and (4) macroeconomic stability. We used the Kao cointegration test to study how certain variables are connected over a long period. The relationship between CO2 and GDP per capita, renewable energy and tourism, improved water and sanitation, and access to power all have a positive feedback effect on each other. Based on FMOLS's findings, a 1 % increase in Inclusive growth leads to a 0.342 % (Model 1) and 0.258 % (Model 3) increase in CO2 emissions. An increase of 1 percent in energy consumption per person resulted in a rise of 1.343 % in CO2 emissions in Case 1, 0.524 % in Case 2, and 0.618 % in Case 3. Increasing the tourism sector's proportion of total exports by just one percent will reduce CO2 emissions by 0.221 % (case 1) and 0.234 % (case 3). Based on CCR findings, a 1 % improvement in inclusive growth leads to a 0.403 %

An efficient mechanism using IoT and wireless communication for smart farming

IoT sensors are able to aggregate data regarding their agriculture field in real time have given rise to the concept of smart farming. The agricultural sector is of great importance to fulfill food resources need of the country. Most industries, including “smart agriculture,” have been completely redone in light of new internet-of-things (IoT) technologies that brought in new quantitative approaches. Such revolutionary changes are upending traditional agricultural practices and presenting new opportunities in the face of a variety of challenges. Agricultural applications involving wireless sensors and IoT devices are analyzed in detail. For agriculture-specific use, such as soil grounding, harvest position, irrigation, bug & insect discovery, a list of available sensors is provided. In this article, we proposed a WSN framework based on the Internet of Things for use in smart agriculture, with different design levels to choose from. The first step is having sensors on the farm which are capable of collecting relevant data and determining the appropriate cluster heads. In addition, the signal strength on the communication link is calculated by means of the signal to noise ratio (SNR) in order to attain reliable and competent information diffusion over long distances. Second, the recurrence of the linear congruential generator is used to ensure the security of information spread as of agricultural sensors to base stations (BS) by means of the linear congruential producer. Comparing the proposed framework to other solutions, the simulation results showed that it significantly improved communiqué routine by standard of 16.3 percent in system throughput, 36.3 percent in packet drop ratio, 12.4 percent in network latency, 18 percent in energy consumption, and 19 percent in routing overheads.

Optimal selective floor cleaning using deep learning algorithms and reconfigurable robot hTetro

Floor cleaning robots are widely used in public places like food courts, hospitals, and malls to perform frequent cleaning tasks. However, frequent cleaning tasks adversely impact the robot’s performance and utilize more cleaning accessories (such as brush, scrubber, and mopping pad). This work proposes a novel selective area cleaning/spot cleaning framework for indoor floor cleaning robots using RGB-D vision sensor-based Closed Circuit Television (CCTV) network, deep learning algorithms, and an optimal complete waypoints path planning method. In this scheme, the robot will clean only dirty areas instead of the whole region. The selective area cleaning/spot cleaning region is identified based on the combination of two strategies: tracing the human traffic patterns and detecting stains and trash on the floor. Here, a deep Simple Online and Real-time Tracking (SORT) human tracking algorithm was used to trace the high human traffic region and Single Shot Detector (SSD) MobileNet object detection framework for detecting the dirty region. Further, optimal shortest waypoint coverage path planning using evolutionary-based optimization was incorporated to traverse the robot efficiently to the designated selective area cleaning/spot cleaning regions. The experimental results show that the SSD MobileNet algorithm scored 90% accuracy for stain and trash detection on the floor. Further, compared to conventional methods, the evolutionary-based optimization path planning scheme reduces 15% percent of navigation time and 10% percent of energy consumption.

Do energy efficiency building codes help minimize the efficiency gap in the U.S.? A dynamic panel data approach

This study estimates the effects of energy efficiency policy in the residential sector using panel data of 48 contiguous states starting from 1970 to 2017. To avoid any unobserved heterogeneity and facilitate efficiency in estimation, this study employs a Dynamic Panel Data model with a two-step Generalized Method of Moments technique. The results suggest that energy efficiency policy for the residential sector has saved about 8.6 percent in energy consumption, which is about 22 percent of the total stated saving, leaving an energy efficiency gap of 1.5771 quadrillion Btu. Consistent with previous estimations, this study finds that theoretical saving amounts overestimate energy efficiency output and overinflate the increase in potential energy efficiency by about 32 percent. Since energy efficiency policy has failed to achieve the stated amount of saving in the residential sector, households have no incentive to adopt the energy efficiency policy, which has created an unusual gap in energy efficiency.

An efficient termination control strategy of air-vented dryer for fabric drying

PurposeThe purpose of this paper is to develop an efficient termination control strategy of air-vented dryer in term of energy saving, improving smoothness and reducing microscopic damage of fiber.Design/methodology/approachA simple, low cost termination control strategy is developed by testing the instantaneous humidity of exhaust air and then deducing the drying degree of fabric in process. The practicability evaluation of this novel strategy was investigated by using both experimental and mathematical approaches. The effect of termination control strategy on drying efficiency and fabric apparent properties were also discussed.FindingsTermination control strategy significantly affects drying time, energy consumption, smoothness and microscopic of fiber. Specially, a novel termination control strategy that the combination of equilibrium moisture content of fabric in ambient environment and relative humidity of exhaust air in exhaust duct is workable and can save 25.2 percent of energy consumption, 26.7 percent of the drying time and improve 0.7 grade of the appearance smoothness, as well as significantly reduce the microscopic damage of fiber compare to the original control strategy of dryer. This indicates possible ways to minimize drying energy consumption and dryer damage by reducing unnecessary migrate out of the water from the clothes.Practical implicationsThe paper is helpful in not only the development of new drying product but also the optimization of appearance smoothness of fabric after drying and reduce the microscopic damage of fiber.Originality/valueA novel termination control strategy of dryer is applied to improve drying efficiency of dryer and reduce fabric damage.

Efficient Self-Invalidation/Self-Downgrade for Critical Sections with Relaxed Semantics

Cache coherence protocols based on self-invalidation allow simpler hardware implementation compared to traditional write-invalidation protocols, by relying on data-race-free semantics and applying self-invalidation on synchronization points. Their simplicity lies in the absence of invalidation traffic. This eliminates the need to track readers in a directory, and reduces the number of transient protocol states. Similarly, the use of self-downgrade on synchronization eliminates directory indirection, and hence the need to track writers in a directory. These protocols, effectively without a directory, have the potential to reduce area, energy consumption, and complexity, without sacrificing performance— provided , that self-invalidation and self-downgrade are performed prudently. In this work we examine how self-invalidation and self-downgrade are performed in relation to atomicity and ordering. We show that self-invalidation and self-downgrade do not need to be applied conservatively, as so far implemented. Our key observation is that, often, critical sections which are not ordered in time, are intended to provide only atomicity and not thread synchronization. We thus propose a new type of self-invalidation, forward self-invalidation (FSI), which invalidates solely data that are going to be accessed inside a critical section. Based on the same reasoning, we propose a new type of self-downgrade, forward self-downgrade (FSD), also restricted to writes in critical sections. Finally, we define the semantics of locks using FSI and FSD, which resemble the semantics of relaxed atomic operations in C++. Our evaluation for 64-core multiprocessors shows significant improvements using the proposed FSI and FSD—where applicable—in Splash-3 and PARSEC benchmarks, over a directory-based protocol (17.1 percent in execution time and 33.9 percent in energy consumption) and also over a state-of-the-art self-invalidation/self-downgrade protocol (7.6 percent in execution time and 9.1 percent in energy consumption), while still retaining the design simplicity of the protocol.

Green IT: A Key to a Better Future

Green IT is an effective approach to the practice and procedures of using computer resources in an environment friendly way while maintaining overall computing performance. The paper is going to describe the hazards causes by the computer and about the safety measures by which we can save our environment from those. Green IT is a well balanced and sustainable approach towards the achievement of a healthier, greener and safer environment. With Green IT we can build an energy efficient computer system and the other hand we can also reduce energy consumption by using IT. Green IT is comprised of initiatives and strategies that reduce the environmental footprints of technology. Green IT initiative also produces cost savings in energy use, purchase, management and support in addition to environmental benefits. Proper implementations of Green Computing or Green IT an individual and or a organization can reduce almost fifty percent of energy consumption per year, by which a organization not only save the energy but also produce more products with lower cost.

Power Consumption Optimization of a Building Using Multiobjective Particle Swarm Optimization

This paper discusses the development of a building energy optimization algorithm by using multiobjective Particle Swarm Optimization for a building. Particle Swarm Optimization is a well known algorithm that is proven to be effective in many complex optimization problems. Multiobjective PSO is developed by utilizing non-dominated sorting algorithm in tandem with majority-based selection algorithm. The optimizer is written by using MATLAB alongside its GUI interface. Results are then analyzed by using the Binh and Korn benchmark test and natural distance performance metrics. From the results, the optimizer is capable to minimize up to 42 percent of energy consumption and lowering the electricity bills up to 43 percent, while still maintaining comfort at more than 95 percent as well. With this, building owner can save energy with a low-cost and simple solution.

Performance analysis of Bayesian coalition game-based energy-aware virtual machine migration in vehicular mobile cloud

To provide computing and communication services to mobile clients, vehicular mobile cloud computing has gained lot of attention in recent times. However, one of the biggest challenges for the smooth execution of these services in this environment is the intelligent usage of VMs which may be overloaded due to numerous requests from mobile clients such as vehicles and mobile devices to access these services. However, poor utilization of VMs in this environment causes a lot of energy to be wasted. To address this issue, we propose Bayesian coalition game as-aservice for intelligent context-switching of VMs to support the above defined services in order to reduce the energy consumption, so that clients can execute their services without a performance degradation. In the proposed scheme, we have used the concepts of learning automata (LA) and game theory in which LA are assumed as the players such that each player has an individual payoff based upon the energy consumption and load on the VM. Players interact with the stochastic environment for taking action such as the selection of appropriate VMs and based upon the feedback received from the environment, they update their action probability vector. The performance of the proposed scheme is evaluated by using various performance evaluation metrics such as context-switching delay, overhead generated, execution time, and energy consumption. The results obtained show that the proposed scheme performs well with respect to the aforementioned performance metrics. Specifically, using the proposed scheme there is a reduction of 10 percent in energy consumption, 12 percent in network delay, 5 percent in overhead generation, and 10 percent in execution time.

Forecasting the Thermal Load for Implementing Solar Energy in a Model Poultry House

In this research, the possibility of a new hybrid method for implementing solar hot water systems in poultry houses is discussed. Iran is located in a sunny belt and most locations in Iran receive abundant solar energy. The poultry industry plays an important role in the economy of Iran because a huge consumption of chicken is demand. In Iran, the percent of energy consumption in poultry industry is high and the implementation of renewable energy is an important and valuable way to cover the energy demand. Solar hot water systems (SHWS) are used for producing hot water from solar energy. In this paper, the values of heat losses and heat gain were determined in a model poultry house. The collector area was considered as 5.1m 2 . According to the collector parameters, the quota of solar energy for warming process was calculated. Results indicated that the minimum value of solar power was 2000 W which is 20% required energy for December.

Socioeconomic Barriers to Biogas Development in Rural Southwest China: An Ethnographic Case Study

The household biogas system has a potential to offer significant health, economic, and environmental benefits to millions of households in rural China. In 1997, the Chinese legislature declared biogas as a national energy development agenda, and the Chinese government subsidies for biogas have been increasing since then. Nevertheless, only about 12 percent of rural households utilize biogas. In poor regions, the figure is much lower. At present, biogas counts for merely 1 percent of energy consumption in rural China. In this article, drawing on my ethnographic fieldwork, I examine the socioeconomic barriers to biogas development in rural Southwest China. My central question is: what are the factors that prevent farmers from utilizing biogas and how can development agencies help remove such barriers? Anchored in anthropological insights on technology adoption, this study first identifies main barriers to biogas adoption through a villagewide survey. Then, I examine such barriers in their socioeconomic cont...

Did fat intake in the United States really decline between 1989-1991 and 1994-1996?

The objectives of this study were to determine changes in fat and energy intakes in the United States between 1989-1991 and 1994-1996, and to examine the implications of expressing fat intake in grams vs as a percent of total energy intake. The source of data was the Continuing Survey of Food Intake by Individuals. The results suggest that intake of energy rose between the 2 time periods, primarily due to higher carbohydrate intake. There was also a modest increase in fat intake. However fat intake, as a percent of total energy, declined. The higher energy intakes were primarily from beverages, especially soft drinks, food mixtures, grain snacks, and pastries. The primary sources of higher fat intakes were meat mixtures, vegetables, and some categories of the grain group. Similar trends in the Food Supply Series suggested that the changes observed were not entirely due to changes in survey methodology. Because the increase in fat intake was masked by the increase in energy intake, we conclude that assessing trends in fat intake as a percent of energy consumption can be misleading, unless information on total energy and fat intake, in grams, is also provided. These preliminary findings should be interpreted cautiously until they are confirmed by formal secular trend analyses.

Reducing energy consumption through trajectory optimization for a metro network

The techniques of optimal control and optimization are applied to a practical problem of reducing energy consumed by the Montreal Metro (subway) system. The problem considered is the determination of tunnel trajectories in the equivalent vertical plane when trains traveling in both directions must follow the same trajectory. The problem is first formulated as a control problem with control and state constraints. Then, under certain simplifying assumptions, an heuristic method employing a direct search algorithm is presented and used in the trajectory optimization. The trajectories are optimized to reduce the sum of the energy consumed by the trains traveling in both directions on the trajectory. The results show an average reduction of 7.73 percent in energy consumption as compared with existing trajectories. The trajectories found using the method presented here will be followed in future tunnel construction.