Amount Of Savings Research Articles

기후대별 솔라사이니지 반투명 태양전지 창호 적용 사무용 건물의 에너지 성능분석

Purpose: This study analyzed building heating, cooling, and lighting energy performance and power generation performance under various climate zones in accordance with Solar Signage Semi-transparent window application. Method: American climate areas, them being tropical, desert, maritime, and microthermal, have been selected and 40%~80% window wall ratio (WWR) has been established in relation to five Solar Signage Semi-transparent windows. Designbuilder, building energy analyzation software, was used to model office building and simulate. Result: Total energy consumption presented Phoenix was highest, followed by Miami, Ann Arbor, with San Francisco being the lowest. The smaller the WWR the higher the heating energy consumption at San Francisco and Ann Arbor appeared with G1 window confirmed to be the highest. Cooling energy consumption in all four climate zones increased as WWR increased due to increase in amount of solar gain. Lighting energy consumption in all four climate zones decreased as WWR increased, with G5 showing smaller consumption than G1 due to VLT’s influence. Climate zone with the amount of energy savings on account of power generation being largest turned out to be San Francisco. Especially, possibility of zero energy building achievement in case of G1, G2 window being applied when WWR was 80% was confirmed. With the result of this particular research, to expand applicability as building exterior materials, products improved upon traits such as colour, insulation, and strength should be under continuous performance evaluation study across various foreign and domestic climate zones.

Why bears hibernate? Redefining the scaling energetics of hibernation.

Hibernation is a natural state of suspended animation that many mammals experience and has been interpreted as an adaptive strategy for saving energy. However, the actual amount of savings that hibernation represents, and particularly its dependence on body mass (the 'scaling') has not been calculated properly. Here, we estimated the scaling of daily energy expenditure of hibernation (DEEH), covering a range of five orders of magnitude in mass. We found that DEEH scales isometrically with mass, which means that a gram of hibernating bat has a similar metabolism to that of a gram of bear, 20 000 times larger. Given that metabolic rate of active animals scales allometrically, the point where these scaling curves intersect with DEEH represents the mass where energy savings by hibernation are zero. For BMR, these zero savings are attained for a relatively small bear (approx. 75 kg). Calculated on a per cell basis, the cellular metabolic power of hibernation was estimated to be 1.3 × 10-12 ± 2.6 × 10-13 W cell-1, which is lower than the minimum metabolism of isolated mammalian cells. This supports the idea of the existence of a minimum metabolism that permits cells to survive under a combination of cold and hypoxia.

Deteksi Peluang Gagal Bayar Calon Debitur Menggunakan Algoritma Particle Swarm Optimization (PSO) untuk Meningkatkan Kinerja Manajemen Risiko pada Koperasi Simpan Pinjam ABC

Savings and Loan Cooperatives (KSP) are financial institutions that have an important role in economic and trade activities, useful for channeling funds in the form of loans to members who need them for business or business. In this paper, we examine the detection of potential debtors' default opportunities using the Particle Swarm Optimization (PSO) algorithm in a logistic regression model. In the analysis method, there are several steps: (1) standardizing the data on the risk factor data of prospective debtors, (2) determining the assumptions of the logistic regression model, (3) estimating the parameters of the logistic regression model using the Particle Swarm Optimization (PSO) algorithm, and (4 ) to test the significance of each variable. The probability of default is determined using the eligibility parameters of the prospective debtor based on past data variables owned by KSP "ABC" in Bandung, Indonesia. The results show that of the eight factors analyzed, there are six factors that have a significant influence on the risk of default, namely the age of the debtor, the number of family dependents, the amount of savings, the amount of collateral, the amount of credit, the credit period with an accuracy of 99.1%. Based on these six factors, a logistic regression model estimator is obtained that can be used to determine the probability of default from prospective debtors. This probability of default is very useful for KSP "ABC" to make a decision on whether or not to give credit, so that the performance of problem loan risk management can be guaranteed.

VirtElect: A Peer-to-Peer Trading Platform for Local Energy Transactions

An average U.K. electricity bill is made up of at least 60&#x0025; service charge, with approximately 22&#x0025; related to network characteristics including distance charge. This makes distance and network constraints important factors in matching prosumers on any peer-to-peer energy trading platform as assessed in this article. To realize that, a platform&#x2014;<inline-formula> <tex-math notation="LaTeX">$VirtElect$ </tex-math></inline-formula>, based on a double auction market is developed to support the matching interaction between prosumers. Case studies based on real microgrid data are used to verify the performance of the platform in demonstrating the potential of local energy consumption. The results show that it is possible to balance local energy generation and consumption, with little or no interaction with the utility grid. We also show that local energy trading is not only beneficial to the environment but also leads to a significant amount of cost savings of up to 45&#x0025;, depending on the number of participants and their ratios on the platform.

Investigating the effect of varying block size on power and energy consumption of GPU kernels

Power consumption is likely to remain a significant concern for exascale performance in the foreseeable future. In addition, graphics processing units (GPUs) have become an accepted architectural feature for exascale computing due to their scalable performance and power efficiency. In a recent study, we found that we can achieve a reasonable amount of power and energy savings based on the selection of algorithms. In this research, we suggest that we can save more power and energy by varying the block size in the kernel configuration. We show that we may attain more savings by selecting the optimum block size while executing the workload. We investigated two kernels on NVIDIA Tesla K40 GPU, a Bitonic Mergesort and Vector Addition kernels, to study the effect of varying block sizes on GPU power and energy consumption. The study should offer insights for upcoming exascale systems in terms of power and energy efficiency.

Study on Properties of Bituminus Mix Using the Combination of Shredded Plastic combined with Chemical Additives

Abstract: The design of a satisfactory bituminous mix is a complex task due to the wide variation in properties of its constituents such as bitumen, coarse and fine aggregate, filler, etc. The design also depends on the shape and gradation of the aggregates. Flexible pavement with bituminous surfacing is commonly used in Indian highways. Distress symptoms, such as cracking, rutting, etc., are increasingly caused earlier by high traffic intensity, over loading of vehicles and significant variations in daily and seasonal temperature of the pavement. Investigations have revealed that Plastic and sulphur modifier can be used to improve properties of bitumen and bituminous mixes to make it more suitable for road construction. The present investigation comprises of determining the Marshall test properties of Dense Bitumen macadam Using VG-30 grade penetration grade bitumen modified with Sulphur as Modifier. The study helps to ascertain the suitability of Sulphur as modifier which could minimize the consumption of VG-30 grade bitumen. Also there is considerable amount of savings in bitumen cost. Keywords: Dense Bitumen macadam, combined index, Marshall Stability test, Sulfur, plastic.

Evaluating the Impact of Public Information and Training Campaigns to Improve Energy Efficiency: Findings from the Italian Industry

Energy efficiency is a pillar for the energy system transition and for reaching the Sustainable Development Goals. In the light of the “energy efficiency first!” principle, European member states enforce policies to spread energy saving throughout the whole energy chain involving both citizens and industries. In this context, information and training campaigns arise as valuable support tools to disseminate energy efficiency and, therefore, for reducing energy consumption. Although various studies have evaluated the impact of information campaigns targeted to citizens, there is a lack of investigations that assess the impact of campaigns dedicated to industry sectors. This study discusses the results of a survey targeted at energy-intensive Italian companies, with a sample of 300 responses. Starting from the analysis of drivers that trigger the implementation of energy efficiency measures, the paper proposes an approach to evaluate the amount of energy savings linked to the Italian information and training program targeted to industries carried out by the Italian Energy Efficiency Agency. Results show that although information campaigns are not a crucial driver for companies, they are recognized as a factor that contributes to the implementation of energy efficiency practices. Findings show that roughly 1.4% of energy savings noted by interviewed companies to the Italian Energy Efficiency Agency are a direct effect of the information and training program. This outcome has significant implications, especially for decision-makers, giving evidence of the efficacy of information campaigns on industries, which have great potential for the transition to low carbon production systems.

A Proposed Methodology for retrofit the Efficiency of Facades of High Educational Buildings in Egypt

A Proposed Methodology for retrofit the Efficiency of Facades of High Educational Buildings in Egypt

Adaptalight: An Inexpensive PAR Sensor System for Daylight Harvesting in a Micro Indoor Smart Hydroponic System

Environmental changes and the reduction in arable land have led to food security concerns around the world, particularly in urban settings. Hydroponic soilless growing methods deliver plant nutrients using water, conserving resources and can be constructed nearly anywhere. Hydroponic systems have several complex attributes that need to be managed, and this can be daunting for the layperson. Micro Indoor Smart Hydroponics (MISH) leverage Internet of Things (IoT) technology to manage the complexities of hydroponic techniques, for growing food at home for everyday citizens. Two prohibitive costs in the advancement of MISH systems are power consumption and equipment expense. Reducing cost through harvesting ambient light can potentially reduce power consumption but must be done accurately to sustain sufficient plant yields. Photosynthetic Active Radiation (PAR) meters are commercially used to measure only the light spectrum that plants use, but are expensive. This study presents Adaptalight, a MISH system that harvests ambient light using an inexpensive AS7265x IoT sensor to measure PAR. The system is built on commonly found IoT technology and a well-established architecture for MISH systems. Adpatalight was deployed in a real-world application in the living space of an apartment and experiments were carried out accordingly. A two-phase experiment was conducted over three months, each phase lasting 21 days. Phase one measured the IoT sensor’s capability to accurately measure PAR. Phase two measured the ability of the system to harvest ambient PAR light and produce sufficient yields, using the calibrated IoT sensor from phase one. The results showed that the Adaptalight system was successful in saving a significant amount of power, harvesting ambient PAR light and producing yields with no significant differences from the control. The amount of power savings would be potentially greater in a location with more ambient light. Additionally, the findings show that, when calibrated, the AS7265x sensor is well suited to accurately measure PAR light in MISH systems.

Старіння населення країн Європейського Союзу: особливості та соціально-економічні наслідки

The article is aimed at determining the characteristics and socioeconomic consequences of the population aging for the countries of the European Union. The article presents the proportion of the population over 65 years of age of the total population of the EU for the period 2011-2021, identifies the EU countries with the largest and smallest proportion of the elderly population in the total population, as well as changes in this indicator in 2021 compared to 2011. It is determined that the main reasons for the increase in the relative proportion of older people in the EU are an increase in life expectancy and a consistently low birth rate over the years. The data as to life expectancy at birth along with the dynamics of birth rate in the EU are provided. The coefficient of demographic load of the elderly population in the EU is considered. The correlation coefficient between the elderly population and GDP, as well as between the elderly population and household consumer spending, is computed. The result indicates a close relationship between these indicators. Among the main socioeconomic consequences of the population aging are the reduction of supply in the labor market, the impact on the rate of economic growth, changes in the amount of savings in the financial system, the budget deficit of pension systems, the growing burden on the bodies of health care system, etc. Three options for the influence of the EU Member States on the current situation are given: encourage marriages or cohabitation and the birth of children; carry out additional activities to attract immigrants of working age; develop new social policy measures aimed at mitigating the negative effects of the population aging. One of the main instruments to overcome the negative consequences of the aging process of the population be the effective realization of the resource potential of the older generation. Measures to increase the size of the workforce, such as lifelong learning and employment policies for the elderly, are also defined as important.

The Influence of Customer Demands and Marketing Mix on Total Customer Savings of Bank BJB Bandung City

Competition in the banking world today is very sharp, this is because people have many alternative choices in getting the most satisfying service. One of these options is in terms of saving the funds in the form of savings. This condition is exacerbated by economic conditions full of uncertainty, so that a bank is required to meet customer demands, if it does not have an advantage it will be difficult to defend itself. One strategy in winning today's competition is the strategy of implementing banking services marketing programs which are the elaboration of the service marketing mix and customer demands which are variables that can be controlled by the company in generating profits. Therefore, this research was conducted with the aim of knowing (1) the demands of savings customers at Bank BJB Bandung City; (2) the performance of the marketing mix of savings services implemented by Bank BJB Bandung City and ; (3) The influence of customer demands and the performance of the service marketing mix on the amount of customer savings at Bank BJB Bandung City. The research method used is a descriptive survey method and an explanatory survey using a sample of Simpeda savings customers and Tanda Mata Bank BJB Bandung as respondents, as many as 100 people. Based on the results of the study, it was found that customer demands include needs (quantity of bank services required), wants (quality of bank services desired) and demand (quality of bank services that customers can afford). The shift in consumer demands is relatively dynamic even though the level of flexibility and adaptability of companies to respond is relatively low, this is so that companies are better prepared to anticipate customer demands; The performance of the service marketing mix includes product, price, location/place, promotion, people, physical facilities and is quite good compared to other banks where the performance of the service marketing mix is one of the tools to determine choices in using banking services and customer demands and the performance of the service marketing mix has an effect on increasing the number of savings, but when viewed partially it turns out that the marketing mix of services dominantly affects the increase in the number of savings than customer demands.

Economic and Environmental Analysis of Solar Powered Desalination

In this paper the economics of a small-scale humidification dehumidification desalination (HDD) unit driven by a concentrating v-trough solar thermal collector is explained. A comparative analysis using the net present value method was carried out for when the system is operated using solar energy and electricity from fossil fuels. The system could provide different amount of fresh water depending on mode of operation. It was shown that by end of year six the investment for the solar system reaches breakeven when compared to the electric system. The analysis also considers the amount of carbon savings that could be achieved and final cost of water produced per cubic meter. The factors that influence the systems economic viability are the outputs and costs of the desalination unit and solar collector systems, the cost of alternative energy source, cost of operation and maintenance, and the geographic location of the system, i.e. solar intensity, environmental temperature and humidity.

ЭКОЛОГО-ЭКОНОМИЧЕСКОЕ ОБОСНОВАНИЕ ЭФФЕКТИВНОСТИ ОХРАНЫ ВОДНЫХ РЕСУРСОВ НА ОСНОВЕ РЕЦИКЛИНГА ДРЕНАЖНО-СБРОСНЫХ ВОД

The purpose is the development of a mathematical apparatus that makes it possible to calculate both the amount of possible increase in the irrigated area due to the recycling of drainage and waste water, and the amount of natural water savings provided that the irrigation area remains unchanged, as well as determining the possible annual additional profit from the recycling of drainage and waste water on irrigation systems. Materials and methods. The systematic analysis and, as a result, a balance method, the key factor of which is the observance of the annual soil salt balance during irrigation are used, together with various options for recycling drainage and waste water. Results. To achieve the research goal, the following was carried out: modeling the determination of the maximum allowable salinity of drainage and waste water suitable for irrigation; modeling of drainage and waste water recycling without dilution and with their successive dilution; modeling of drainage and waste waters recycling. As a result of the studies carried out for the option of drainage and waste water recycling with their successive dilution, the possibility of obtaining an annual additional profit from the recycling of such water in irrigation systems under conditions of insufficient water supply, which will be about 18 %, is revealed; the payback period for modernization of the irrigation system will be about 6 years. Conclusion. Recycling of drainage and waste water during irrigation is a promising direction for increasing water supply and improving the efficiency of water resources protection. With the help of the ratios obtained, the issues of optimal water distribution between irrigated plots and determination of their areas can be solved, taking into account the availability of natural waters and drainage and waste water recycling.

Residential Electricity Rate Plans and Their Selections Based on Statistical Learning

Demand response (DR) is one of the major benefits that utility companies can derive from the advanced metering infrastructure (AMI). In particular, the dynamic rate plan with DR is attracting attention as an electricity rate system suitable for the future power environment. In order for electricity consumers to select an appropriate electricity rate plan, it is necessary to provide information such as whether electricity bills are reduced by the plan and the estimated amount of electricity bill savings. In this paper, we first comparatively analyze the current progressive rate plan and a dynamic rate plan of the time-of-use (TOU). We next propose several prediction methods for households to provide information on whether the electricity bill amount can be reduced in advance when changing to the TOU rate plan from the progressive rate plan by using only the current monthly electricity usages and bills. In order to develop three different prediction methods based on statistical learning, we use the support vector machine, linear regression, and deep neural network techniques. As a ground truth training sequence, we use hourly electricity usages and bills obtained from ten apartment complexes through AMI, and an apartment complex is used for testing the designed methods. The decision accuracy for the test complex was more than 0.98 and the root mean square error of the saving prediction was 1.7%.

Структурний синтез кузова напівпричепа вантажного автомобіля з техніко-економічним обґрунтуванням

As a result of the synthesis of truck semi-trailer bodies by morphological analysis using hierarchical grouping and advanced engineering solutions for creating structures with improved technical and economic characteristics by analyzing the influence of various factors on design features. The data of the research are based on the stress - strain state (VAT) of the Simulation engineering analysis of the specialized software complex SolidWorks on the CAD model of the body of the truck semi - trailer. synthesis, brake disc, friction material. The synthesis of truck semi-trailer bodies was carried out by the method of morphological analysis using hierarchical grouping, and progressive engineering solutions were obtained for the creation of structures with improved technical and economic characteristics. As a result of the conducted research, it was established that the amount of cost savings due to the improvement of the construction of semi-trailer bodies of trucks with standard body dimensions of 2.5×8×1.8 (36 m3) will be approximately UAH 304.5 thousand.

Machine Learning-Based Pruning Technique for Low Power Approximate Computing

Approximate Computing is a low power achieving technique that offers an additional degree of freedom to design digital circuits. Pruning is one of the types of approximate circuit design technique which removes logic gates or wires in the circuit to reduce power consumption with minimal insertion of error. In this work, a novel machine learning (ML) -based pruning technique is introduced to design digital circuits. The machine-learning algorithm of the random forest decision tree is used to prune nodes selectively based on their input pattern. In addition, an error compensation value is added to the original output to reduce an error rate. Experimental results proved the efficiency of the proposed technique in terms of area, power and error rate. Compared to conventional pruning, proposed ML pruning achieves 32% and 26% of the area and delay reductions in 8*8 multiplier implementation. Low power image processing algorithms are essential in various applications like image compression and enhancement algorithms. For real-time evaluation, proposed ML optimized pruning is applied in discrete cosine transform (DCT). It is a basic element of image and video processing applications. Experimental results on benchmark images show that proposed pruning achieves a very good peak signal-to-noise ratio (PSNR) value with a considerable amount of energy savings compared to other methods.

A Novel Multi-Hierarchical Bidding Strategy for Peer-to-Peer Energy Trading Among Communities

Recently, several market types and regulations have been developed in an attempt to handle the increased carbon effect. End-users can also actively participate in the existing distribution system thanks to Peer-to-Peer (P2P) energy trading, which is one of the new emerging market types. In this paper, a novel dual bidding strategy for multi-hierarchical P2P energy trading that includes both intra community and inter communities is proposed considering uncertainties in solar irradiance and temperature. While the lower-level problem consists of both optimal bids of the households to the own Local Market Operators (LMO) for intra community trades and optimal bids of the LMOs to the Central Market Operator (CMO) for inter community trades, profit of both the LMOs and CMO is maximized by clearing the market prices at the upper-level problem. To prove the validity of the devised model, a set of case studies are created. Moreover, the results suggest that the proposed bi-level model is robust, and a remarkable amount of cost savings could be provided by integrating the model.

Does Personal Finance Impact on Financial Development? Evidence from Bangladesh

The purpose of the study is investigated the efficiency of personal finance in terms of financial gain and advancement. Despite the fact that there is an abundance of research on personal finance literacy in the literature, there is a scarcity of research on the effect of personal finance on financial growth in the literature, particularly in Bangladesh. With the passage of time, the amount of national income and savings in the country has been steadily increasing throughout time. Despite the fact that its frequency has fluctuated, there have been no official studies conducted on the usefulness of personal finance in

Nonintrusive Model Order Reduction for Cross-Diffusion Systems

In this paper, we investigate tensor based nonintrusive reduced-order models (ROMs) for parametric cross-diffusion equations. The full-order model (FOM) consists of ordinary differential equations (ODEs) in matrix or tensor form resulting from finite-difference discretization of the differential operators by taking the advantage of Kronecker structure. The matrix/tensor differential equations are integrated in time with the implicit-explicit (IMEX) Euler method. The reduced bases, relying on a finite sample set of parameter values, are constructed in form of a two-level approach by applying higher-order singular value decomposition (HOSVD) to the space-time snapshots in tensor form, which leads to a large amount of computational and memory savings. The nonintrusive reduced approximations for an arbitrary parameter value are obtained through tensor product of the reduced basis by the parameter dependent core tensor that contains the reduced coefficients. The reduced coefficients for new parameter values are computed using radial basis function (RBF) interpolation. The efficiency of the proposed method is illustrated through numerical experiments for two-dimensional Schnakenberg and three-dimensional Brusselator cross-diffusion equations. The spatiotemporal patterns are accurately predicted by the reduced-order models with speed-up factors of orders two and three over the full-order models.

Equity impact of minimum unit pricing of alcohol on household health and finances among rich and poor drinkers in South Africa

IntroductionSouth Africa experiences significant levels of alcohol-related harm. Recent research suggests minimum unit pricing (MUP) for alcohol would be an effective policy, but high levels of income inequality raise concerns...