INTRODUCTION. Although seldom a mainstream topic in social work, the financial functioning of individuals and families plays a central role in well-being. The time is right to better understand the workings of low-income families, especially in this uncertain economic climate. Matched savings program called Individual Development Accounts (IDAs) provide a context for investigating how low-income parents save and accumulate assets. IDAs offer a unique means for a systematic study of the saving strategies used by low-income individuals and how the decision to save may create hardships for themselves and their families. There is still a pressing need for more research that can help clarify parental saving strategies, the factors facilitating or impeding saving, and the potential hardships low-income savers face. Of critical importance to the field is research that helps to better understand what sacrifices low-income parents make when they have made the decision to secure a better future for their families. METHODS. The sample is 150 savers from a statewide matched savings program. This study is a secondary analysis of telephone survey and administrative data. Bivariate and multivariate statistical tests were conducted to test six hypotheses. The variables of interest are saving strategies, saving supports, and hardships. RESULTS. Parents who have a history of saving use significantly more helpful saving strategies than respondents without a saving history. Parents who have a history of saving experience less severe hardship than parents who do not have a history of saving. Also, married parents experience fewer hardships than non-married parents. Minority parents experience significantly less intense saving supports than non-minority parents. There was not a relationship between the number of helpful saving strategies and the age of the saver. A relationship was not found between the saver's age or number of children and the number of hardships experienced.

In this research paper, review of world geothermal energy production and their capacity is shown. Here, a research is conducted to know the potential and possibility of geothermal energy in India. All the geothermal province with their geographical locations are shown and a brief calculation is conducted in order to show the potential of the particular province. As India is having the low temperature geothermal fields, binary geothermal plants are used for this analysis and results are calculated by using R134a as a working fluid at different temperatures. The results are sufficient to prove the potential of geothermal energy in India.  Importance of Ground Source Heat Pump (GSHP) and power savings by its contribution over traditional heating and cooling methods is shown statistically. 9 different states of India are divided by their climatic condition, severe winter and moderate winter to calculate the heat demand in those states. Also, for the cold demands these states are considered to be same as per the climatic situation in summer. Then, comparison is done between GSHP and the traditional heating and cooling systems. The result shows the drastic power saving by using GSHP for space heating as well as cooling, over electric heater and air conditioner respectively.

The primary objective of this research is to model and optimize wastewater treatment process in a wastewater treatment plant (WWTP). As the treatment process is complex, its operations pose challenges. Traditional physics-based and mathematical- models have limitations in predicting the behavior of the wastewater process and optimization of its operations. Automated control and information technology enables continuous collection of data. The collected data contains process information allowing to predict and optimize the process. Although the data offered by the WWTP is plentiful, it has not been fully used to extract meaningful information to improve performance of the plant. A data-driven approach is promising in identifying useful patterns and models using algorithms versed in statistics and computational intelligence. Successful data-mining applications have been reported in business, manufacturing, science, and engineering. The focus of this research is to model and optimize the wastewater treatment process and ultimately improve efficiency of WWTPs. To maintain the effluent quality, the influent flow rate, the influent pollutants including the total suspended solids (TSS) and CBOD, are predicted in short-term and long-term to provide information to efficiently operate the treatment process. To reduce energy consumption and improve energy efficiency, the process of biogas production, activated sludge process and pumping station are modeled and optimized with evolutionary computation algorithms. Modeling and optimization of wastewater treatment processes faces three major challenges. The first one is related to the data. As wastewater treatment includes physical, chemical, and biological processes, and instruments collecting large volumes of data. Many variables in the dataset are strongly coupled. The data is noisy, uncertain, and incomplete. Therefore, several preprocessing algorithms should be used to preprocess the data, reduce its dimensionality, and determine import variables. The second challenge is in the temporal nature of the process. Different data-mining algorithms are used to obtain accurate models. The last challenge is the optimization of the process models. As the models are usually highly nonlinear and dynamic, novel evolutionary computational algorithms are used. This research addresses these three challenges. The major contribution of this research is in modeling and optimizing the wastewater treatment process with a data-driven approach. The process model built is then optimized with evolutionary computational algorithms to find the optimal solutions for improving process efficiency and reducing energy consumption.

A potable water distribution system (WDS) consists of pipes, pumps, valves, storage tanks, control and supporting components. Traditionally, it has two basic functions. First, provides end users with potable water at sufficient pressures and good water quality. Second, provides sufficient pressure and flow for fire fighting. Currently, potable water is still the least expensive material for fire fighting. To accomplish these two goals, water utilities have to consider the integrity and security of the water network. As a result, this research selected three research topics that are closely related to the daily operation of water utilities and water quality simulation. The first study is on optimal sampling design for chlorine decay model calibration. Three questions are investigated: (1) What is the minimum number of chlorine sample locations a water network needs? (2) How many combinations of sampling locations are available? (3) What is the optimal location combination? To answer the first two questions, the mathematical expressions of the chlorine concentrations between any two sampling locations are developed and sampling point relationship matrices are generated, then a mixed integer programming (MIP) algorithm is developed. Once obtained, the solutions to the first two questions are used to calculate the chlorine decay wall reaction coefficients and sensitivity matrix of chlorine concentration wall reaction coefficients; then, sampling location combinations achieved in the second question are sorted using a D-optimality algorithm. The model frame is demonstrated in a case study. The advantage of this method, compared to the traditional iterative sensitivity matrix method, is that a prior knowledge or estimation of wall reaction coefficients is not necessary. The second study is on optimizing the operation scheduling of automatic flushing device (AFD) in water distribution system. Discharging stagnant water from the pipeline through AFD is a feasible method to maintain water quality. This study presents a simulation-based optimization method to minimize total AFD discharge volume during a 24-hour horizon. EPANET 2.0 is used as hydraulics and water quality simulator. This is formulated as a single objective optimization problem. The decision variables are the AFD operation patterns. The methodology has three phases. In the first phase, AFD discharge capacities are calculated, whether existing AFDs are able to maintain chlorine residuals in the water network is also evaluated. In the second phase, the decision variables are converted to AFD discharge rates. A reduced gradient algorithm is used to quickly explore and narrow down the solution space. At the end of this phase, decision variables are switched back to the AFD operation patterns. In the third phase, simulated annealing is used to search intensively to exploit the global minimum. The method is demonstrated on the water system located at the south end of Pinellas County, Florida where AFD optimal operation patterns are achieved. The third study is on simulating contaminant intrusion in water distribution system. When contaminant matrix is introduced into water distribution system, it reacts with chlorine in bulk water rapidly and causes fast disinfectant depletion. Due to the difficulties in identifying contaminant types and chemical and biological properties, it is a challenging task to use EPANET-MSX to simulate chlorine decay under contaminant attack. EPANET 2.0 is used in the study to accomplish this goal. However, EPANET 2.0 cannot directly simulate chlorine depletion in the event of contamination attack because it assigns one time-independent bulk reaction coefficient to one specific pipe during the simulation. While under contaminant intrusion, chlorine decay bulk coefficient is not a constant. Instead, it is a temporal and spatial variable. This study presents an innovative approach for simulating contaminant intrusion in water distribution systems using EPANET multiple times. The methodology has six general steps. First, test bulk reaction coefficients of contaminant matrix in chemical lab. The uniqueness of this study is that the contaminant matrix is studied as a whole. The investigations of chemical, biological properties of individual aqueous constituents are not needed. Second, assume the contaminants as nonreactive, using EPANET 2.0 to identify where, when and at what concentrations of the inert contaminants will pass by in the water network. Third, determine the number of chlorine residual simulations based on the results in step two. Fourth, use EPANET to simulate the chlorine residual in the water network without the occurrence of contamination. Fifth, assign contaminated bulk coefficients to contaminated pipes; use EPANET to simulate the chlorine residual in the pipe network. Lastly, the chlorine concentrations of the impacted moments of impacted junctions are replaced with the results calculated in step five. This methodology is demonstrated in the south Pinellas County water distribution system.

There appears to be a growing recognition among economists and other social commentators that people attempt to enhance their relative position (which is commonly described as status) through consumption choices and other behaviour. It has been less common to consider whether attempts to enhance relative position impact on saving behaviour. This thesis makes a number of contributions relating to the impact of relative position on saving behaviour. In this thesis I: - consider why concern for relative position may impact on saving behaviour. I demonstrate, with a simple intertemporal model the surprising result that when people are concerned with relative position, income risk can lead to most people saving less and the rich saving more. - conduct an empirical study to test the importance of relative position on saving behaviour. I find a statistically and economically significant relationship between peer income and saving behaviour consistent with theories that people actively forgo saving to seek to enhance their relative position. I use the data to demonstrate that relative position can help to explain why prior research has consistently found that the rich have higher saving rates. - consider the policy implications of relative position to saving behaviour. I examine the policies, primarily corrective taxation, that have been advocated to address externalities of relative position in a static setting. I find that there are significant issues when these policies are considered in an intertemporal setting. I examine the policy of mandatory saving in addressing distortions caused by relative position and the possibility that concern for relative position improves the effectiveness of mandatory saving policy.

<p>Multiple causes of continuously occurring power outages in Yazd Province of Iran have been experienced in recent years. This research studies how key stakeholders have perceived the results of the strategic decisions taken by directors of HEPP to diminish the power shortages and to even increase power supply to a limit of exporting power to other neighboring provinces. How could HEPP emerge from an organization in the edge of bankruptcy to an organization that can surpass all expectations and won over their competitors? HEPP’s strategic decisions followed implications of several models and finally a strategic plan on the bases of the Bryson model was selected and practically applied to achieve their final expected results. The literature review in this study describes selected models as well as the Bryson model set up and structure. This study portrays a demonstration and an evaluation of various strategic plan management models used in Iranian organization in particular HEPP. The researcher designed several questionnaires and forwarded them to HEPP’s administrators, employees and other stakeholders in three groups. Additional phone interviews were conducted and the quantitative as well as qualitative data collected was evaluated and displayed in tables and figures in this study. Data analysis demonstrates a few shortcomings, weaknesses and strengths that are discussed in detail and conclusive proposals are presented through the conclusion section in enhancement of HEPP’s services to the advantages of stakeholders and employees of HEPP with a complete consideration for HEPP’s well being and awareness of its competitors. Although this study is limited in scope it highlights what needs to be done in HEPP or similar hydro electric organizations in Iran, and it can act as a stepping stone for further research and analysis of hydro electrical demand and supply issues in Yazd region of Iran.</p>

<p>This paper presents the energy saving curtains, in order to make the</p><p>consumers be more aware of the energy efficiency of the energy saving</p><p>curtains, the paper gave related analysis and conclusions.</p><p>The work was performed by using the Parasol Program, developed by Lunds University, Sweden. The Program is used for quantifying the influence of window size, glass type, textile type, wall thermal insulation and sun shading on annual energy use and indoor thermal comfort. The results which are obtained from the calculations are applicable to similar climatic and environment conditions. Calculations were performed to investigate the potential for using sunshade devices to reduce annual energy demand for cooling and heating. Different materials and dimensions of the energy saving</p><p>curtain are used as variables in the analysis. The results indicated that for the current climatic conditions and other related factors, the total reduction rate of the annual energy consumption of office used buildings in Stockholm is estimated generally 20% -30% lower comparing to those buildings without energy saving curtain system. That means at least 20% of energy cost can be saved by the energy saving curtain system.</p>

No description available.

Thesis (M.Ing. (Electrical Engineering))--North-West University, Potchefstroom Campus, 2007.

This work analyzes the saving and consumption behavior of agents faced with the possibility of unemployment in a dynamic and stochastic life cycle model. The intertemporal optimization is based on Dynamic Programming with a backward recursion algorithm. The implemented uncertainty is not based on income shocks as it is done in traditional life cycle models but uses Markov probabilities where the probability for the next employment status of the agent depends on the current status. The utility function used is a CRRA function (constant relative risk aversion), combined with a CES function (constant elasticity of substitution) and has several consumption goods, a subsistence level, money and a bequest function. / Diese Arbeit modelliert das Spar- und Konsumverhalten von Individuen in Deutschland mit einem Lebenszyklusmodell. Dabei hat das Modell zwei Besonderheiten, erstens trifft die Möglichkeit arbeitslos zu werden nicht jeden Agenten des Models mit der gleichen Wahrscheinlichkeit, sondern wird von Bildungsabschluss und dem Beschäftigungsstatus des Agenten beeinflußt und zweitens weicht die verwendete Nutzenfunktion von den Standardnutzenfunktionen ab und implementiert Vererbung, Geld, verschiedene Güter und Subsistenzlevel. Der Optimierungsalgorithmus basiert auf Dynamischer Programmierung.