Search results for: conscious consumption
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3675

Search results for: conscious consumption

3435 Green Wave Control Strategy for Optimal Energy Consumption by Model Predictive Control in Electric Vehicles

Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

Abstract:

Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

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3434 Experimental Analysis of the Plate-on-Tube Evaporator on a Domestic Refrigerator’s Performance

Authors: Mert Tosun, Tuğba Tosun

Abstract:

The evaporator is the utmost important component in the refrigeration system, since it enables the refrigerant to draw heat from the desired environment, i.e. the refrigerated space. Studies are being conducted on this component which generally affects the performance of the system, where energy efficient products are important. This study was designed to enhance the effectiveness of the evaporator in the refrigeration cycle of a domestic refrigerator by adjusting the capillary tube length, refrigerant amount, and the evaporator pipe diameter to reduce energy consumption. The experiments were conducted under identical thermal and ambient conditions. Experiment data were analysed using the Design of Experiment (DOE) technique which is a six-sigma method to determine effects of parameters. As a result, it has been determined that the most important parameters affecting the evaporator performance among the selected parameters are found to be the refrigerant amount and pipe diameter. It has been determined that the minimum energy consumption is 6-mm pipe diameter and 16-g refrigerant. It has also been noted that the overall consumption of the experiment sample decreased by 16.6% with respect to the reference system, which has 7-mm pipe diameter and 18-g refrigerant.

Keywords: heat exchanger, refrigerator, design of experiment, energy consumption

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3433 Applying Energy Consumption Schedule and Comparing It with Load Shifting Technique in Residential Load

Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasy

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Energy consumption schedule (ECS) technique shifts usage of loads from on peak hours and redistributes them throughout the day according to residents’ operating time preferences. This technique is used as form of indirect control from utility to improve the load curve and hence its load factor and reduce customer’s total electric bill as well. Similarly, load shifting technique achieves ECS purposes but as direct control form applied from utility. In this paper, ECS is simulated twice as optimal constrained mathematical formula, solved by using CVX program in MATLAB® R2013b. First, it is utilized for single residential building with ten apartments to determine max allowable energy consumption per hour for each residential apartment. Then, it is used for single apartment with number of shiftable domestic devices, where operating schedule is deduced using previous simulation output results as constraints. The paper ends by giving differences between ECS technique and load shifting technique via literature and simulation. Based on results assessment, it will be shown whether using ECS or load shifting is more beneficial to both customer and utility.

Keywords: energy consumption schedule, load shifting, comparison, demand side mangement

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3432 The Impact of Generative AI Illustrations on Aesthetic Symbol Consumption among Consumers: A Case Study of Japanese Anime Style

Authors: Han-Yu Cheng

Abstract:

This study aims to explore the impact of AI-generated illustration works on the aesthetic symbol consumption of consumers in Taiwan. The advancement of artificial intelligence drawing has lowered the barriers to entry, enabling more individuals to easily enter the field of illustration. Using Japanese anime style as an example, with the development of Generative Artificial Intelligence (Generative AI), an increasing number of illustration works are being generated by machines, sparking discussions about aesthetics and art consumption. Through surveys and the analysis of consumer perspectives, this research investigates how this influences consumers' aesthetic experiences and the resulting changes in the traditional art market and among creators. The study reveals that among consumers in Taiwan, particularly those interested in Japanese anime style, there is a pronounced interest and curiosity surrounding the emergence of Generative AI. This curiosity is particularly notable among individuals interested in this style but lacking the technical skills required for creating such artworks. These works, rooted in elements of Japanese anime style, find ready acceptance among enthusiasts of this style due to their stylistic alignment. Consequently, they have garnered a substantial following. Furthermore, with the reduction in entry barriers, more individuals interested in this style but lacking traditional drawing skills have been able to participate in producing such works. Against the backdrop of ongoing debates about artistic value since the advent of artificial intelligence (AI), Generative AI-generated illustration works, while not entirely displacing traditional art, to a certain extent, fulfill the aesthetic demands of this consumer group, providing a similar or analogous aesthetic consumption experience. Additionally, this research underscores the advantages and limitations of Generative AI-generated illustration works within this consumption environment.

Keywords: generative AI, anime aesthetics, Japanese anime illustration, art consumption

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3431 Energy Efficient Building Design in Nigeria: An Assessment of the Effect of the Sun on Energy Consumption in Residential Buildings

Authors: Ekele T. Ochedi, Ahmad H. Taki, Birgit Painter

Abstract:

The effect of the sun and its path on thermal comfort and energy consumption in residential buildings in tropical climates constitute a serious concern for designers, building owners, and users. Passive design approaches based on the sun and its path have been identified as a means of reducing energy consumption as well as enhancing thermal comfort in buildings worldwide. Hence, a thorough understanding regarding the sun path is key to achieving this. This is necessary due to energy need, poor energy supply, and distribution, energy poverty, and over-dependence on electric generators for power supply in Nigeria. These challenges call for a change in the approach to energy-related issues, especially in terms of buildings. The aim of this study is to explore the influence of building orientation, glazing and the use of shading devices on residential buildings in Nigeria. This is intended to provide data that will guide designers in the design of energy-efficient residential buildings. The paper used EnergyPlus to analyze a typical semi-detached residential building in Lokoja, Nigeria using hourly weather data for a period of 10 years. Building performance was studied as well as possible improvement regarding different orientations, glazing types and shading devices. The simulation results show some reductions in energy consumption in response to changes in building orientation, types of glazing and the use of shading devices. The results indicate 29.45% reduction in solar gains and 1.90% in annual operative temperature using natural ventilation only. This shows a huge potential to reduce energy consumption and improve people’s well-being through the use of proper building orientation, glazing and appropriate shading devices on building envelope. The study concludes that for a significant reduction in total energy consumption by residential buildings, the design should focus on multiple design options rather than concentrating on one or few building elements. Moreover, the investigation confirms that energy performance modeling can be used by building designers to take advantage of the sun and to evaluate various design options.

Keywords: energy consumption, energy-efficient buildings, glazing, thermal comfort, shading devices, solar gains

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3430 Cataract Surgery and Sustainability: Comparative Study of Single-Use Versus Reusable Cassettes in Phacoemulsification

Authors: Oscar Kallay

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Objective: This study compares the sustainability, financial implications, and surgical efficiency of two phacoemulsification cassette systems for cataract surgery: a machine with single-use cassettes and another with daily, reusable ones. Methods: The observational study involves retrospective cataract surgery data collection at the Centre Médical de l'Alliance, Braine-L’alleud, Belgium, a tertiary eye care center. Information on cassette weight, quantities, and transport volume was obtained from routine procedures and purchasing records. The costs for each machine were calculated by reviewing the invoices received from the accounting department. Results: We found significant differences across comparisons. The reusable cassette machine, when compared to the single-use machine, used 306.7 kg less plastic (75.3% reduction), required 2,494 cubic meters less storage per 1000 surgeries (67.7% decrease), and cost €54.16 less per 10 procedures (16.9% reduction). The machine with daily reusable cassettes also exhibited a 7-minute priming time advantage for 10 procedures, reducing downtime between cases. Conclusions: Our findings underscore the benefits of adopting reusable cassette systems: reduced plastic consumption, storage volume, and priming time, as well as enhanced efficiency and cost savings. Healthcare professionals and institutions are encouraged to embrace environmentally conscious initiatives. The use of reusable cassette systems for cataract surgeries offers a pathway to sustainable practices.

Keywords: cataract, epidemiolog, surgery treatment, lens and zonules, public health

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3429 Architectural Design, Low Energy, and Isolation Materials to Have Sustainable Buildings in Iran

Authors: Mohammadreza Azarnoush, Ali Bayati, Jamileh Azarnoush

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Nowadays according to increasing the population all around the world, consuming of fossil fuels increased dramatically. Many believe that most of the atmospheric pollution comes by using fossil fuels. The process of natural sources entering cities shows one of the large challenges in consumption sources management. Nowadays, everyone considers the consumption of fossil fuels and also reduction of consumption civil energy in megacities as playing a key role in solving serious problems such as air pollution, producing greenhouse gasses, global warming, and damage ozone layer. In the construction industry, we should use the materials with the lowest need to energy for making and carrying them, and also the materials which need the lowest energy and expenses to recycling. In this way, the kind of usage material, the way of processing, regional materials, and the adoption to the environment is critical. Otherwise, the isolation should be use and mention in the long term. Accordingly, in this article, we investigate the new ways in order to reduce environmental pollution and save more energy by using materials that are not harmful to the environment, fully insulated materials in buildings, sustainable and diversified buildings, suitable urban design and using solar energy more efficiently in order to reduce energy consumption.

Keywords: building design, construction masonry, insulation, sustainable construction

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3428 Meat Products Demand in Oyo West Local Government: An Application of Almost Ideal Demand System (LA/AIDS)

Authors: B. A. Adeniyi, S. A. Daud, O. Amao

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The study investigates consumer demand for meat products in Oyo West Local Government using linear approximate almost ideal demand system (LA/AIDS). Questions that were addressed by the study include: first, what is the type and quantity of meat products available to the household and their demand pattern? Second is the investigation of the factors that affect meat products demand pattern and proportion of income that is spent on them. For the above purpose cross-sectional data were collected from 156 households of the study area and analyzed to reveal the functional relationship between meat products consumption and some socio-economic variables of the household. Results indicated that per capita meat consumption increased as household income and education increased but decreased with age. It was also found that male tend to consume more meat products than their female counterparts and that increase in household size will first increased per caput meat consumption but later decreased it. Price also tends to greatly influence the demand pattern of meat products. The results of elasticity computed from the results of regression analysis revealed that own price elasticity for all meat products were negative which indicated that they were normal products while cross and expenditure elasticity were positive which further confirmed that meat products were normal and substitute products. This study therefore concludes that the relevance of these variables imposed a great challenge to the policy makers and the government, in the sense that more cost effective methods of meat production technology have to be devised in other to make consumption of meat products more affordable.

Keywords: meat products, consumption, animal production, technology

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3427 Green Fruit and Vegetables Have Favorable Effects on 3-Year Changes of Cardiometabolic Risk Factors: A Cohort Study

Authors: Parvin Mirmiran, Zahra Bahadoran, Nazanin Moslehi, Fereidoun Azizi

Abstract:

Background and aim: We aimed to investigate the effects of green fruits and vegetables (green FV) consumption on the 3-year changes of cardiometabolic risk factors. Methods: This longitudinal study was conducted in the framework of Tehran Lipid and Glucose Study, between 2006-2008 and 2009-2011, on 1272 adults. Dietary intake of green FV, including green cabbage, broccoli, lettuce, celery, green beans, green peas, cucumber, leafy vegetables, zucchini, green chili and bell pepper, and kiwi fruit, has been assessed by a validated semi-quantitative food frequency questionnaire at baseline and second examination. Demographics, anthropometrics and biochemical measures were evaluated at baseline and 3 years later. The associations of cardiometabolic risk changes with mean intake of green FV were estimated. Results: The mean age of men and women at baseline was 39.8±12.7 and 37.3±12.1 years, respectively. Mean intake of green FV was 152±77 g/d. More intake from green FV was accompanied to more intake of vitamin A, α and β-carotene, lutein, β-criptoxanthine, potassium, magnesium and fiber. Consumption of green FV was inversely associated with 3-year change of waist circumference (β= -0.07, P=0.01), total cholesterol (β= -0.11, P=0.01) and triglycerides (β= -0.13, P=0.01). Each 25 g/d increase in consumption of green FV decreased the incidence of hyper-triglyceridemia by 12% (OR:0.88, 95%CI:0.71-0.99) in men. In women, no significant association was observed between consumption of green FV with cardiometabolic risk factors. Conclusion: Higher consumption of green FV could have preventive effects against abdominal fat gain and lipid disorders.

Keywords: cardiometabolic risk factors, abdominal obesity, lipid disorders, fruits, vegetables

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3426 A Comparison of Neural Network and DOE-Regression Analysis for Predicting Resource Consumption of Manufacturing Processes

Authors: Frank Kuebler, Rolf Steinhilper

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Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords: artificial neural network, design of experiments, regression analysis, resource efficiency, manufacturing process

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3425 Optimizing Power in Sequential Circuits by Reducing Leakage Current Using Enhanced Multi Threshold CMOS

Authors: Patikineti Sreenivasulu, K. srinivasa Rao, A. Vinaya Babu

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The demand for portability, performance and high functional integration density of digital devices leads to the scaling of complementary metal oxide semiconductor (CMOS) devices inevitable. The increase in power consumption, coupled with the increasing demand for portable/hand-held electronics, has made power consumption a dominant concern in the design of VLSI circuits today. MTCMOS technology provides low leakage and high performance operation by utilizing high speed, low Vt (LVT) transistors for logic cells and low leakage, high Vt (HVT) devices as sleep transistors. Sleep transistors disconnect logic cells from the supply and/or ground to reduce the leakage in the sleep mode. In this technology, energy consumption while doing the mode transition and minimum time required to turn ON the circuit upon receiving the wake up signal are issues to be considered because these can adversely impact the performance of VLSI circuit. In this paper we are introducing an enhancing method of MTCMOS technology to optimize the power in MTCMOS sequential circuits.

Keywords: power consumption, ultra-low power, leakage, sub threshold, MTCMOS

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3424 Improve B-Tree Index’s Performance Using Lock-Free Hash Table

Authors: Zhanfeng Ma, Zhiping Xiong, Hu Yin, Zhengwei She, Aditya P. Gurajada, Tianlun Chen, Ying Li

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Many RDBMS vendors use B-tree index to achieve high performance for point queries and range queries, and some of them also employ hash index to further enhance the performance as hash table is more efficient for point queries. However, there are extra overheads to maintain a separate hash index, for example, hash mapping for all data records must always be maintained, which results in more memory space consumption; locking, logging and other mechanisms are needed to guarantee ACID, which affects the concurrency and scalability of the system. To relieve the overheads, Hash Cached B-tree (HCB) index is proposed in this paper, which consists of a standard disk-based B-tree index and an additional in-memory lock-free hash table. Initially, only the B-tree index is constructed for all data records, the hash table is built on the fly based on runtime workload, only data records accessed by point queries are indexed using hash table, this helps reduce the memory footprint. Changes to hash table are done using compare-and-swap (CAS) without performing locking and logging, this helps improve the concurrency and avoid contention. The hash table is also optimized to be cache conscious. HCB index is implemented in SAP ASE database, compared with the standard B-tree index, early experiments and customer adoptions show significant performance improvement. This paper provides an overview of the design of HCB index and reports the experimental results.

Keywords: B-tree, compare-and-swap, lock-free hash table, point queries, range queries, SAP ASE database

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3423 The Effectiveness of Environmental Policy Instruments for Promoting Renewable Energy Consumption: Command-and-Control Policies versus Market-Based Policies

Authors: Mahmoud Hassan

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Understanding the impact of market- and non-market-based environmental policy instruments on renewable energy consumption (REC) is crucial for the design and choice of policy packages. This study aims to empirically investigate the effect of environmental policy stringency index (EPS) and its components on REC in 27 OECD countries over the period from 1990 to 2015, and then use the results to identify what the appropriate environmental policy mix should look like. By relying on the two-step system GMM estimator, we provide evidence that increasing environmental policy stringency as a whole promotes renewable energy consumption in these 27 developed economies. Moreover, policymakers are able, through the market- and non-market-based environmental policy instruments, to increase the use of renewable energy. However, not all of these instruments are effective for achieving this goal. The results indicate that R&D subsidies and trading schemes have a positive and significant impact on REC, while taxes, feed-in tariff and emission standards have not a significant effect. Furthermore, R&D subsidies are more effective than trading schemes for stimulating the use of clean energy. These findings proved to be robust across the three alternative panel techniques used.

Keywords: environmental policy stringency, renewable energy consumption, two-step system-GMM estimation, linear dynamic panel data model

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3422 Comparing Machine Learning Estimation of Fuel Consumption of Heavy-Duty Vehicles

Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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3421 Decoupling Evaluation of Resource Consumption and Economic Development of Urban Industries under the View of Sustainable Development: The Case of Secondary and Tertiary Industries in Jiangsu Province, China

Authors: Jianghua Chen

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Sustainable urban development requires the coordination of economic growth and resource environment, and industrial transformation and upgrading is the key link. Based on the decoupling theory and the improved decoupling decomposition model, the quantitative evaluation and comprehensive analysis of the degree of decoupling between resource consumption and economic development in Jiangsu Province are conducted using the data related to the resource consumption and economic growth of the secondary and tertiary industries in Jiangsu Province from 2013 to 2018, as a way of exploring the sustainable development path of industrial transformation in Jiangsu Province. The results show that from the decoupling status, the degree of decoupling of economic development of the secondary industry to the required coke resources, water resources, and human resources is gradually deepening, and the decoupling index of economic development of the tertiary industry to the required water resources is fluctuating; from the perspective of the driving factors, the technological effect is the main driving factor to decouple the economic growth of Jiangsu Province to the resources, and the structural effect has a significant impact on the driving index of the decoupling of economic growth of the secondary and tertiary industries to the consumption of resources in Jiangsu Province. Finally, we discuss the difficulties of industrial transformation and layout faced by Jiangsu Province at present.

Keywords: resource consumption, economic growth, industrial transformation, decoupling theory

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3420 Applying ASHRAE Standards on the Hospital Buildings of UAE

Authors: Hanan M. Taleb

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Energy consumption associated with buildings has a significant impact on the environment. To that end, and as a transaction between the inside and outside and between the building and urban space, the building skin plays an especially important role. It provides protection from the elements; demarcates private property and creates privacy. More importantly, it controls the admission of solar radiation. Therefore, designing the building skin sustainably will help to achieve optimal performance in terms of both energy consumption and thermal comfort. Unfortunately, with accelerating construction expansion, many recent buildings do not pay attention to the importance of the envelope design. This piece of research will highlight the importance of this part of the creation of buildings by providing evidence of a significant reduction in energy consumption if the envelopes are redesigned. Consequently, the aim of this paper is to enhance the performance of the hospital envelope in order to achieve sustainable performance. A hospital building sited in Abu Dhabi, in the UAE, has been chosen to act as a case study. A detailed analysis of the annual energy performance of the case study will be performed with the use of a computerised simulation; this is in order to explore their energy performance shortcomings. The energy consumption of the base case will then be compared with that resulting from the new proposed building skin. The results will inform architects and designers of the savings potential from various strategies.

Keywords: ASHREA, building skin, building envelopes, hospitals, Abu Dhabi, UAE, IES software

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3419 Neural Synchronization - The Brain’s Transfer of Sensory Data

Authors: David Edgar

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To understand how the brain’s subconscious and conscious functions, we must conquer the physics of Unity, which leads to duality’s algorithm. Where the subconscious (bottom-up) and conscious (top-down) processes function together to produce and consume intelligence, we use terms like ‘time is relative,’ but we really do understand the meaning. In the brain, there are different processes and, therefore, different observers. These different processes experience time at different rates. A sensory system such as the eyes cycles measurement around 33 milliseconds, the conscious process of the frontal lobe cycles at 300 milliseconds, and the subconscious process of the thalamus cycle at 5 milliseconds. Three different observers experience time differently. To bridge observers, the thalamus, which is the fastest of the processes, maintains a synchronous state and entangles the different components of the brain’s physical process. The entanglements form a synchronous cohesion between the brain components allowing them to share the same state and execute in the same measurement cycle. The thalamus uses the shared state to control the firing sequence of the brain’s linear subconscious process. Sharing state also allows the brain to cheat on the amount of sensory data that must be exchanged between components. Only unpredictable motion is transferred through the synchronous state because predictable motion already exists in the shared framework. The brain’s synchronous subconscious process is entirely based on energy conservation, where prediction regulates energy usage. So, the eyes every 33 milliseconds dump their sensory data into the thalamus every day. The thalamus is going to perform a motion measurement to identify the unpredictable motion in the sensory data. Here is the trick. The thalamus conducts its measurement based on the original observation time of the sensory system (33 ms), not its own process time (5 ms). This creates a data payload of synchronous motion that preserves the original sensory observation. Basically, a frozen moment in time (Flat 4D). The single moment in time can then be processed through the single state maintained by the synchronous process. Other processes, such as consciousness (300 ms), can interface with the synchronous state to generate awareness of that moment. Now, synchronous data traveling through a separate faster synchronous process creates a theoretical time tunnel where observation time is tunneled through the synchronous process and is reproduced on the other side in the original time-relativity. The synchronous process eliminates time dilation by simply removing itself from the equation so that its own process time does not alter the experience. To the original observer, the measurement appears to be instantaneous, but in the thalamus, a linear subconscious process generating sensory perception and thought production is being executed. It is all just occurring in the time available because other observation times are slower than thalamic measurement time. For life to exist in the physical universe requires a linear measurement process, it just hides by operating at a faster time relativity. What’s interesting is time dilation is not the problem; it’s the solution. Einstein said there was no universal time.

Keywords: neural synchronization, natural intelligence, 99.95% IoT data transmission savings, artificial subconscious intelligence (ASI)

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3418 Highlighting of the Factors and Policies affecting CO2 Emissions level in Malaysian Transportation Sector

Authors: Siti Indati Mustapa, Hussain Ali Bekhet

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Global CO2 emission and increasing fuel consumption to meet energy demand requirement has become a threat in recent decades. Effort to reduce the CO2 emission is now a matter of priority in most countries of the world including Malaysia. Transportation has been identified as the most intensive sector of carbon-based fuels and achievement of the voluntary target to meet 40% carbon intensity reduction set at the 15th Conference of the Parties (COP15) means that the emission from the transport sector must be reduced accordingly. This posed a great challenge to Malaysia and effort has to be made to embrace suitable and appropriate energy policy for sustainable energy and emission reduction of this sector. The focus of this paper is to analyse the trends of Malaysia’s energy consumption and emission of four different transport sub-sectors (road, rail, aviation and maritime). Underlying factors influencing the growth of energy consumption and emission trends are discussed. Besides, technology status towards energy efficiency in transportation sub-sectors is presented. By reviewing the existing policies and trends of energy used, the paper highlights prospective policy options towards achieving emission reduction in the transportation sector.

Keywords: CO2 emissions, transportation sector, fuel consumption, energy policy, Malaysia

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3417 The Relationship Between Beauty Bloggers and the Consumption Patterns of Female Followers: A Case Study on Instagram Pages of Beauty Bloggers

Authors: Reyhane Abdollahi

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The beauty of appearance has been important in people's lives since the beginning of history. In every era, beauty has had a specific meaning, and individuals have represented the standards of beauty during each period. According to statistics, the beauty industry has experienced significant economic growth in recent decades, with projections indicating it will reach $583 billion by 2027. The emergence of social media, backed by technological advancements, has created a suitable platform for various beauty brands to engage in economic activities. It can be said that today, beauty bloggers represent the beauty standards of society, actively engaging on social media platforms such as Instagram. Beauty bloggers promote cosmetic and skin care products in front of the camera in their ideal state, utilizing their skills. Instagram, with its limited two-way communication between users and influencers, has also created a suitable environment for advertising. The aim of this research is to study the relationship between beauty bloggers and the consumption patterns of female followers. This research was conducted through interviews with Ten women over the age of 20 who have followed these pages for three years or more, and the findings were analyzed using qualitative content analysis. According to the findings, beauty bloggers encourage women to purchase cosmetic products by creating a sense of identification through sharing their experiences. Beauty bloggers generate a false sense of need for consumption among their audience by promoting beauty products. The feeling of inadequacy, stemming from women's comparisons with bloggers who are always beautiful, leads women to try to imitate the consumption habits and appearance of these bloggers.

Keywords: beauty blogger, instagram, beauty, consumption

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3416 Use and Health Effects of Caffeinated Beverages in Omani Students

Authors: Nasiruddin Khan

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The increased use of caffeinated beverages and energy drink is posing threat to all ages and gender especially, younger adults. There is a lack of scientific evidence in Oman regarding caffeine and energy drink consumption. Our study aims to demonstrate the prevalence, pattern, knowledge and awareness, and side effects of caffeine intake among university students. This cross-sectional study including (N=365) apparently healthy male and female Omani university students aged 18-30 years, was carried out from February 2018-June 2018. A self-administered questionnaire with various sections was used to obtain information. The prevalence of caffeinated beverage consumption was commonly high among participants (97%). The males preferred Nescafe, coffee (both p < 0.001), espresso (p < 0.022), and soda (p < 0.008) while females consumed more tea (p < 0.029). The awareness about negative health impact of caffeine intake was significantly higher in females rather than males (p < 0.002). The overall prevalence of energy drink consumption was 42.1% (n=149), and higher in males (75%, p < 0.001). More males consumed 3-5 and > 5 cans/day while females used 1-2 cans/day. The starting age of energy drink use was higher in females (16-20 years (51.1%)) as compared to males (11-15 years (33.3%)). Females were more aware of caffeine as energy drink ingredient (p < 0.036) than males. The major source of information about enery drink was family and friends (58.3%). Red Bull was the commonly used brand (55.5%) among participants. Common reasons for high energy drink consumption were energy boost (68.4 %), taste (62.9%), reduce fatigue (52.1%), and better performance (47.3%). Females reported breathing problem, and abnormal heart beat (p < 0.004, 0.054, respectively), while more males reported irritability than females (p < 0.052). The prevalence of caffeinated beverage and energy drink consumption is high among participants. The awareness, and knowledge among university student is not satisfactory and needs immediate action to avoid excess use of such consumption.

Keywords: energy drink, caffeinated beverages, awareness, Oman

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3415 Energy Consumption Estimation for Hybrid Marine Power Systems: Comparing Modeling Methodologies

Authors: Kamyar Maleki Bagherabadi, Torstein Aarseth Bø, Truls Flatberg, Olve Mo

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Hydrogen fuel cells and batteries are one of the promising solutions aligned with carbon emission reduction goals for the marine sector. However, the higher installation and operation costs of hydrogen-based systems compared to conventional diesel gensets raise questions about the appropriate hydrogen tank size, energy, and fuel consumption estimations. Ship designers need methodologies and tools to calculate energy and fuel consumption for different component sizes to facilitate decision-making regarding feasibility and performance for retrofits and design cases. The aim of this work is to compare three alternative modeling approaches for the estimation of energy and fuel consumption with various hydrogen tank sizes, battery capacities, and load-sharing strategies. A fishery vessel is selected as an example, using logged load demand data over a year of operations. The modeled power system consists of a PEM fuel cell, a diesel genset, and a battery. The methodologies used are: first, an energy-based model; second, considering load variations during the time domain with a rule-based Power Management System (PMS); and third, a load variations model and dynamic PMS strategy based on optimization with perfect foresight. The errors and potentials of the methods are discussed, and design sensitivity studies for this case are conducted. The results show that the energy-based method can estimate fuel and energy consumption with acceptable accuracy. However, models that consider time variation of the load provide more realistic estimations of energy and fuel consumption regarding hydrogen tank and battery size, still within low computational time.

Keywords: fuel cell, battery, hydrogen, hybrid power system, power management system

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3414 Coffee Consumption and Glucose Metabolism: a Systematic Review of Clinical Trials

Authors: Caio E. G. Reis, Jose G. Dórea, Teresa H. M. da Costa

Abstract:

Objective: Epidemiological data shows an inverse association of coffee consumption with risk of type 2 diabetes mellitus. However, the clinical effects of coffee consumption on the glucose metabolism biomarkers remain controversial. Thus, this paper reviews clinical trials that evaluated the effects of coffee consumption on glucose metabolism. Research Design and Methods: We identified studies published until December 2014 by searching electronic databases and reference lists. We included randomized clinical trials which the intervention group received caffeinated and/or decaffeinated coffee and the control group received water or placebo treatments and measured biomarkers of glucose metabolism. The Jadad Score was applied to evaluate the quality of the studies whereas studies that scored ≥ 3 points were considered for the analyses. Results: Seven clinical trials (total of 237 subjects) were analyzed involving adult healthy, overweight and diabetic subjects. The studies were divided in short-term (1 to 3h) and long-term (2 to 16 weeks) duration. The results for short-term studies showed that caffeinated coffee consumption may increase the area under the curve for glucose response, while for long-term studies caffeinated coffee may improve the glycemic metabolism by reducing the glucose curve and increasing insulin response. These results seem to show that the benefits of coffee consumption occur in the long-term as has been shown in the reduction of type 2 diabetes mellitus risk in epidemiological studies. Nevertheless, until the relationship between long-term coffee consumption and type 2 diabetes mellitus is better understood and any mechanism involved identified, it is premature to make claims about coffee preventing type 2 diabetes mellitus. Conclusion: The findings suggest that caffeinated coffee may impairs glucose metabolism in short-term but in the long-term the studies indicate reduction of type 2 diabetes mellitus risk. More clinical trials with comparable methodology are needed to unravel this paradox.

Keywords: coffee, diabetes mellitus type 2, glucose, insulin

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3413 Using Motives of Sports Consumption to Explain Team Identity: A Comparison between Football Fans across the Pond

Authors: G. Scremin, I. Y. Suh, S. Doukas

Abstract:

Spectators follow their favorite sports teams for different reasons. While some attend a sporting event simply for its entertainment value, others do so because of the personal sense of achievement and accomplishment their connection with a sports team creates. Moreover, the level of identity spectators feel toward their favorite sports team falls in a broad continuum. Some are mere spectators. For those spectators, their association to a sports team has little impact on their self-image. Others are die-hard fans who are proud of their association with their team and whose connection with that team is an important reflection of who they are. Several motives for sports consumption can be used to explain the level of spectator support in a variety of sports. Those motives can also be used to explain the variance in the identification, attachment, and loyalty spectators feel toward their favorite sports team. Motives for sports consumption can be used to discriminate the degree of identification spectators have with their favorite sports team. In this study, motives for sports consumption was used to discriminate the level of identity spectators feel toward their sports team. It was hypothesized that spectators with a strong level of team identity would report higher rates of interest in player, interest in sports, and interest in team than spectators with a low level of team identity. And spectators with a low level of team identity would report higher rates for entertainment value, bonding with friends or family, and wholesome environment. Football spectators in the United States and England were surveyed about their motives for football consumption and their level of identification with their favorite football team. To assess if the motives of sports fans differed by level of team identity and allegiance to an American or English football team, a Multivariate Analysis of Variance (MANOVA) under the General Linear Model (GLM) procedure found in SPSS was performed. The independent variables were level of team identity and allegiance to an American or English football team, and the dependent variables were the sport fan motives. A tripartite split (low, moderate, high) was used on a composite measure for team identity. Preliminary results show that effect of team identity is statistically significant (p < .001) for at least nine of the 17 motives for sports consumption assessed in this investigation. These results indicate that the motives of spectators with a strong level of team identity differ significantly from spectators with a low level of team identity. Those differences can be used to discriminate the degree of identification spectators have with their favorite sports team. Sports marketers can use these methods and results to develop identity profiles of spectators and create marketing strategies specifically designed to attract those spectators based on their unique motives for consumption and their level of team identification.

Keywords: fan identification, market segmentation of sports fans, motives for sports consumption, team identity

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3412 Customer Involvement in the Development of New Sustainable Products: A Review of the Literature

Authors: Natalia Moreira, Trevor Wood-Harper

Abstract:

The acceptance of sustainable products by the final consumer is still one of the challenges of the industry, which constantly seeks alternative approaches to successfully be accepted in the global market. A large set of methods and approaches have been discussed and analysed throughout the literature. Considering the current need for sustainable development and the current pace of consumption, the need for a combined solution towards the development of new products became clear, forcing researchers in product development to propose alternatives to the previous standard product development models. This paper presents, through a systemic analysis of the literature on product development, eco-design and consumer involvement, a set of alternatives regarding consumer involvement towards the development of sustainable products and how these approaches could help improve the sustainable industry’s establishment in the general market. The initial findings of the research show that the understanding of the benefits of sustainable behaviour lead to a more conscious acquisition and eventually to the implementation of sustainable change in the consumer. Thus this paper is the initial approach towards the development of new sustainable products using the fashion industry as an example of practical implementation and acceptance by the consumers. By comparing the existing literature and critically analysing it this paper concluded that the consumer involvement is strategic to improve the general understanding of sustainability and its features. The use of consumers and communities has been studied since the early 90s in order to exemplify uses and to guarantee a fast comprehension. The analysis done also includes the importance of this approach for the increase of innovation and ground breaking developments, thus requiring further research and practical implementation in order to better understand the implications and limitations of this methodology.

Keywords: consumer involvement, products development, sustainability, eco-design

Procedia PDF Downloads 593
3411 Multi-Objectives Genetic Algorithm for Optimizing Machining Process Parameters

Authors: Dylan Santos De Pinho, Nabil Ouerhani

Abstract:

Energy consumption of machine-tools is becoming critical for machine-tool builders and end-users because of economic, ecological and legislation-related reasons. Many machine-tool builders are seeking for solutions that allow the reduction of energy consumption of machine-tools while preserving the same productivity rate and the same quality of machined parts. In this paper, we present the first results of a project conducted jointly by academic and industrial partners to reduce the energy consumption of a Swiss-Type lathe. We employ genetic algorithms to find optimal machining parameters – the set of parameters that lead to the best trade-off between energy consumption, part quality and tool lifetime. Three main machining process parameters are considered in our optimization technique, namely depth of cut, spindle rotation speed and material feed rate. These machining process parameters have been identified as the most influential ones in the configuration of the Swiss-type machining process. A state-of-the-art multi-objective genetic algorithm has been used. The algorithm combines three fitness functions, which are objective functions that permit to evaluate a set of parameters against the three objectives: energy consumption, quality of the machined parts, and tool lifetime. In this paper, we focus on the investigation of the fitness function related to energy consumption. Four different energy consumption related fitness functions have been investigated and compared. The first fitness function refers to the Kienzle cutting force model. The second fitness function uses the Material Removal Rate (RMM) as an indicator of energy consumption. The two other fitness functions are non-deterministic, learning-based functions. One fitness function uses a simple Neural Network to learn the relation between the process parameters and the energy consumption from experimental data. Another fitness function uses Lasso regression to determine the same relation. The goal is, then, to find out which fitness functions predict best the energy consumption of a Swiss-Type machining process for the given set of machining process parameters. Once determined, these functions may be used for optimization purposes – determine the optimal machining process parameters leading to minimum energy consumption. The performance of the four fitness functions has been evaluated. The Tornos DT13 Swiss-Type Lathe has been used to carry out the experiments. A mechanical part including various Swiss-Type machining operations has been selected for the experiments. The evaluation process starts with generating a set of CNC (Computer Numerical Control) programs for machining the part at hand. Each CNC program considers a different set of machining process parameters. During the machining process, the power consumption of the spindle is measured. All collected data are assigned to the appropriate CNC program and thus to the set of machining process parameters. The evaluation approach consists in calculating the correlation between the normalized measured power consumption and the normalized power consumption prediction for each of the four fitness functions. The evaluation shows that the Lasso and Neural Network fitness functions have the highest correlation coefficient with 97%. The fitness function “Material Removal Rate” (MRR) has a correlation coefficient of 90%, whereas the Kienzle-based fitness function has a correlation coefficient of 80%.

Keywords: adaptive machining, genetic algorithms, smart manufacturing, parameters optimization

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3410 The Influence of Variable Geometrical Modifications of the Trailing Edge of Supercritical Airfoil on the Characteristics of Aerodynamics

Authors: P. Lauk, K. E. Seegel, T. Tähemaa

Abstract:

The fuel consumption of modern, high wing loading, commercial aircraft in the first stage of flight is high because the usable flight level is lower and the weather conditions (jet stream) have great impact on aircraft performance. To reduce the fuel consumption, it is necessary to raise during first stage of flight the L/D ratio value within Cl 0.55-0.65. Different variable geometrical wing trailing edge modifications of SC(2)-410 airfoil were compared at M 0.78 using the CFD software STAR-CCM+ simulation based Reynolds-averaged Navier-Stokes (RANS) equations. The numerical results obtained show that by increasing the width of the airfoil by 4% and by modifying the trailing edge airfoil, it is possible to decrease airfoil drag at Cl 0.70 for up to 26.6% and at the same time to increase commercial aircraft L/D ratio for up to 5.0%. Fuel consumption can be reduced in proportion to the increase in L/D ratio.

Keywords: L/D ratio, miniflaps, mini-TED, supercritical airfoil

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3409 Technical Analysis of Combined Solar Water Heating Systems for Cold Climate Regions

Authors: Hossein Lotfizadeh, André McDonald, Amit Kumar

Abstract:

Renewable energy resources, which can supplement space and water heating for residential buildings, can have a noticeable impact on natural gas consumption and air pollution. This study considers a technical analysis of a combined solar water heating system with evacuated tube solar collectors for different solar coverage, ranging from 20% to 100% of the total roof area of a typical residential building located in Edmonton, Alberta, Canada. The alternative heating systems were conventional (non-condensing) and condensing tankless water heaters and condensing boilers that were coupled to solar water heating systems. The performance of the alternative heating systems was compared to a traditional heating system, consisting of a conventional boiler, applied to houses of various gross floor areas. A comparison among the annual natural gas consumption, carbon dioxide (CO2) mitigation, and emissions for the various house sizes indicated that the combined solar heating system can reduce the natural gas consumption and CO2 emissions, and increase CO2 mitigation for all the systems that were studied. The results suggest that solar water heating systems are potentially beneficial for residential heating system applications in terms of energy savings and CO2 mitigation.

Keywords: CO2 emissions, CO2 mitigation, natural gas consumption, solar water heating system

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3408 Measuring Output Multipliers of Energy Consumption and Manufacturing Sectors in Malaysia during the Global Financial Crisis

Authors: Hussain Ali Bekhet, Tuan Ab. Rashid Bin Tuan Abdullah, Tahira Yasmin

Abstract:

The strong relationship between energy consumption and economic growth is widely recognised. Most countries’ energy demand declined during the economic depression known as the Global Financial Crisis (GFC) of 2008–2009. The objective of the current study is to investigate the energy consumption and performance of Malaysia’s manufacturing sectors during the GFC. We applied the output multiplier approach, which is based on the input-output model. Two input-output tables of Malaysia covering 2005 and 2010 were used. The results indicate significant changes in the output multipliers of the manufacturing sectors between 2005 and 2010. Moreover, the energy-to-manufacturing sectors’ output multipliers also decreased during the GFC due to a decline in export-oriented industries during the crisis. The increasing importance of the manufacturing sector to the development of Malaysian trade resulted in a noticeable decrease in the consumption of each energy sector’s output, especially the electricity and gas sector. Based on the research findings, the Malaysian government released several policy implementations in the form of stimulus packages to enhance these sectors’ performance and generally improve the Malaysian economy.

Keywords: global financial crisis, input-output model, manufacturing, output multipliers, energy, Malaysia

Procedia PDF Downloads 726
3407 Theorizing Income Inequality in the Face of Financial Globalization

Authors: Li Sheng

Abstract:

Based on an extended post-Keynesian model, we find that the association between the savings rate and income inequality is negative if savers’ funds are borrowed by spending households for consumption but positive if savings are channeled to investing firms for production. A negative association, such as the one that exists in the U.S., hinges on an income illusion created by an asset bubble and cheap credit. Thus, financial globalization leads consumption and income inequality to diverge, and the divergence is more extreme if lower-income groups have higher debt ratios. A positive association, such as the one that exists in China, relates to liquidity constraints faced by consumers such that consumption inequality closely follows income inequality. Our results imply that income inequality must be reduced in both types of countries to increase savings in deficit economies with negative associations and to reduce savings in surplus economies with positive associations.

Keywords: savings rate, income inequality, financial globalization, global imbalances

Procedia PDF Downloads 468
3406 Co-Alignment of Comfort and Energy Saving Objectives for U.S. Office Buildings and Restaurants

Authors: Lourdes Gutierrez, Eric Williams

Abstract:

Post-occupancy research shows that only 11% of commercial buildings met the ASHRAE thermal comfort standard. Many buildings are too warm in winter and/or too cool in summer, wasting energy and not providing comfort. In this paper, potential energy savings in U.S. offices and restaurants if thermostat settings are calculated according the updated ASHRAE 55-2013 comfort model that accounts for outdoor temperature and clothing choice for different climate zones. eQUEST building models are calibrated to reproduce aggregate energy consumption as reported in the U.S. Commercial Building Energy Consumption Survey. Changes in energy consumption due to the new settings are analyzed for 14 cities in different climate zones and then the results are extrapolated to estimate potential national savings. It is found that, depending on the climate zone, each degree increase in the summer saves 0.6 to 1.0% of total building electricity consumption. Each degree the winter setting is lowered saves 1.2% to 8.7% of total building natural gas consumption. With new thermostat settings, national savings are 2.5% of the total consumed in all office buildings and restaurants, summing up to national savings of 69.6 million GJ annually, comparable to all 2015 total solar PV generation in US. The goals of improved comfort and energy/economic savings are thus co-aligned, raising the importance of thermostat management as an energy efficiency strategy.

Keywords: energy savings quantifications, commercial building stocks, dynamic clothing insulation model, operation-focused interventions, energy management, thermal comfort, thermostat settings

Procedia PDF Downloads 302