Desalination of brackish water by a batch reverse osmosis desalink system for use with solar thermal energy

For remote, semi-arid areas, brackish groundwater (BW) desalination powered by solar energy may serve as the most technically and economically viable means to alleviate the water stresses. For such systems, high recovery ratio is desired because of the technical and economical difficulties of concentrate management. It has been demonstrated that the current, conventional solar reverse osmosis (RO) desalination can be improved by 40–200 times by eliminating unnecessary energy losses. In this work, a batch-RO system that can be powered by a thermal Rankine cycle has been developed. By directly recycling high pressure concentrates and by using a linkage connection to provide increasing feed pressures, the batch-RO has been shown to achieve a 70% saving in energy consumption compared to a continuous single-stage RO system. Theoretical investigations on the mass transfer phenomena, including dispersion and concentration polarization, have been carried out to complement and to guide experimental efforts. The performance evaluation of the batch-RO system, named DesaLink, has been based on extensive experimental tests performed upon it. Operating DesaLink using compressed air as power supply under laboratory conditions, a freshwater production of approximately 300 litres per day was recorded with a concentration of around 350 ppm, whilst the feed water had a concentration range of 2500–4500 ppm; the corresponding linkage efficiency was around 40%. In the computational aspect, simulation models have been developed and validated for each of the subsystems of DesaLink, upon which an integrated model has been realised for the whole system. The models, both the subsystem ones and the integrated one, have been demonstrated to predict accurately the system performance under specific operational conditions. A simulation case study has been performed using the developed model. Simulation results indicate that the system can be expected to achieve a water production of 200 m3 per year by using a widely available evacuated tube solar collector having an area of only 2 m2. This freshwater production would satisfy the drinking water needs of 163 habitants in the Rajasthan region, the area for which the case study was performed.

A New Charging and Billing Model and Architecture for the Ubiquitous Consumer Wireless World

In a Ubiquitous Consumer Wireless World (UCWW) environment the provision, administration and management of the authentication, authorization and accounting (AAA) policies and business services are provided by third-party AAA service providers (3P-AAA-SPs) who are independent of the wireless access network providers (ANPs). In this environment the consumer can freely choose any suitable ANP, based on his/her own preferences. This new AAA infrastructural arrangement necessitates assessing the impact and re-thinking the design, structure and location of ‘charging and billing’ (C&B) functions and services. This paper addresses C&B issues in UCWW, proposing potential architectural solutions for C&B realization. Implementation approaches of these novel solutions together with a software testbed for validation and performance evaluation are addressed.

Semantic representation for comparison of performance measurement indicators

Indicators are widely used by organizations as a way of evaluating, measuring and classifying organizational performance. As part of performance evaluation systems, indicators are often shared or compared across internal sectors or with other organizations. However, indicators can be vague and imprecise, and also can lack semantics, making comparisons with other indicators difficult. Thus, this paper presents a knowledge model based on an ontology that may be used to represent indicators semantically and generically, dealing with the imprecision and vagueness, and thus facilitating better comparison. Semantic technologies are shown to be suitable for this solution, so that it could be able to represent complex data involved in indicators comparison.

Ontology for performance measurement indicators’ comparison

Indicators are widely used by organizations as a way of evaluating, measuring and classifying organizational performance. As part of performance evaluation systems, indicators are often shared or compared across internal sectors or with other organizations. However, indicators can be vague and imprecise, and also can lack semantics, making comparisons with other indicators difficult. Thus, this paper presents a knowledge model based on an ontology that may be used to represent indicators semantically and generically, dealing with the imprecision and vagueness, and thus facilitating better comparison. Semantic technologies are shown to be suitable for this solution, so that it could be able to represent complex data involved in indicators comparison.

Carbon efficiency evaluation:an analytical framework using fuzzy DEA

Data Envelopment Analysis (DEA) is a powerful analytical technique for measuring the relative efficiency of alternatives based on their inputs and outputs. The alternatives can be in the form of countries who attempt to enhance their productivity and environmental efficiencies concurrently. However, when desirable outputs such as productivity increases, undesirable outputs increase as well (e.g. carbon emissions), thus making the performance evaluation questionable. In addition, traditional environmental efficiency has been typically measured by crisp input and output (desirable and undesirable). However, the input and output data, such as CO2 emissions, in real-world evaluation problems are often imprecise or ambiguous. This paper proposes a DEA-based framework where the input and output data are characterized by symmetrical and asymmetrical fuzzy numbers. The proposed method allows the environmental evaluation to be assessed at different levels of certainty. The validity of the proposed model has been tested and its usefulness is illustrated using two numerical examples. An application of energy efficiency among 23 European Union (EU) member countries is further presented to show the applicability and efficacy of the proposed approach under asymmetric fuzzy numbers.

Performance analysis of IEEE 802.11 cognitive radio ad hoc networks

IEEE 802.11 standard is the dominant technology for wireless local area networks (WLANs). In the last two decades, the Distributed coordination function (DCF) of IEEE 802.11 standard has become the one of the most important media access control (MAC) protocols for mobile ad hoc networks (MANETs). The DCF protocol can also be combined with cognitive radio, thus the IEEE 802.11 cognitive radio ad hoc networks (CRAHNs) come into being. There were several literatures which focus on the modeling of IEEE 802.11 CRAHNs, however, there is still no thorough and scalable analytical models for IEEE 802.11 CRAHNs whose cognitive node (i.e., secondary user, SU) has spectrum sensing and possible channel silence process before the MAC contention process. This paper develops a unified analytical model for IEEE 802.11 CRAHNs for comprehensive MAC layer queuing analysis. In the proposed model, the SUs are modeled by a hyper generalized 2D Markov chain model with an M/G/1/K model while the primary users (PUs) are modeled by a generalized 2D Markov chain and an M/G/1/K model. The performance evaluation results show that the quality-of-service (QoS) of both the PUs and SUs can be statistically guaranteed with the suitable settings of duration of channel sensing and silence phase in the case of under loading.

On the impossibility of fair risk allocation

Measuring and allocating risk properly are crucial for performance evaluation and internal capital allocation of portfolios held by banks, insurance companies, investment funds and other entities subject to financial risk. We show that by using a coherent measure of risk it is impossible to allocate risk satisfying the natural requirements of (Solution) Core Compatibility, Equal Treatment Property and Strong Monotonicity. To obtain the result we characterize the Shapley value on the class of totally balanced games and also on the class of exact games.

On the impossibility of fair risk allocation

Measuring and allocating risk properly are crucial for performance evaluation and internal capital allocation of portfolios held by banks, insurance companies, investment funds and other entities subject to financial risk. We show that by using coherent measures of risk it is impossible to allocate risk satisfying simultaneously the natural requirements of Core Compatibility, Equal Treatment Property and Strong Monotonicity. To obtain the result we characterize the Shapley value on the class of totally balanced games and also on the class of exact games.

Development of ``HealthServe'': A measure of customer service orientation in healthcare

An assessment tool designed to measure a customer service orientation among RN's and LPN's was developed using a content-oriented approach. Critical incidents were first developed by asking two samples of healthcare managers (n = 52 and 25) to identify various customer-contact situations. The critical incidents were then used to formulate a 121-item instrument. Patient-contact workers from 3 hospitals (n = 102) completed the instrument along with the NEO-FFI, a measure of the Big Five personality factors. Concurrently, managers completed a performance evaluation scale on the employees participating in the study in order to determine the predictive validity of the instrument.^ Through a criterion-keying approach, the instrument was scaled down to 38 items. The correlation between HealthServe and the supervisory ratings of performance evaluation data supported the instrument's criterion-related validity (r =.66, p $<$.0001). Incremental validity of HealthServe over the Big Five was found with HealthServe accounting for 46% of the variance.^ The NEO-FFI was used to assess the correlation between personality traits and HealthServe. A factor analysis of HealthServe suggested 4 factors which were correlated with the NEO-FFI scores. Results indicated that HealthServe was related to Extraversion, Openness to Experience, Agreeableness, Conscientiousness and negatively related to Neuroticism.^ The benefits of the test construction procedure used here over the use of broad-based measures of personality were discussed as well as the limitations of using a concurrent validation strategy. Recommendations for future studies were provided. ^

Development of prediction models for freeway incident durations using data mining techniques

The nation's freeway systems are becoming increasingly congested. A major contribution to traffic congestion on freeways is due to traffic incidents. Traffic incidents are non-recurring events such as accidents or stranded vehicles that cause a temporary roadway capacity reduction, and they can account for as much as 60 percent of all traffic congestion on freeways. One major freeway incident management strategy involves diverting traffic to avoid incident locations by relaying timely information through Intelligent Transportation Systems (ITS) devices such as dynamic message signs or real-time traveler information systems. The decision to divert traffic depends foremost on the expected duration of an incident, which is difficult to predict. In addition, the duration of an incident is affected by many contributing factors. Determining and understanding these factors can help the process of identifying and developing better strategies to reduce incident durations and alleviate traffic congestion. A number of research studies have attempted to develop models to predict incident durations, yet with limited success. ^ This dissertation research attempts to improve on this previous effort by applying data mining techniques to a comprehensive incident database maintained by the District 4 ITS Office of the Florida Department of Transportation (FDOT). Two categories of incident duration prediction models were developed: "offline" models designed for use in the performance evaluation of incident management programs, and "online" models for real-time prediction of incident duration to aid in the decision making of traffic diversion in the event of an ongoing incident. Multiple data mining analysis techniques were applied and evaluated in the research. The multiple linear regression analysis and decision tree based method were applied to develop the offline models, and the rule-based method and a tree algorithm called M5P were used to develop the online models. ^ The results show that the models in general can achieve high prediction accuracy within acceptable time intervals of the actual durations. The research also identifies some new contributing factors that have not been examined in past studies. As part of the research effort, software code was developed to implement the models in the existing software system of District 4 FDOT for actual applications. ^

Performance in Private Clubs: Criteria Utilized by Managers

As the first step toward developing performance benchmarks for non profit private clubs, the authors identify the criteria that club managers use to evaluate club performance. Responses from 254 club managers across the US. indicate that all 16 performance criteria included in the survey were utilized to some extent, but the top three were membership satisfaction, quality of services offered, and quality of staff.

Managing Quality in the Hospitality Industry:

In - Managing Quality In the Hospitality Industry – an observation by W. Gerald Glover, Associate Professor, Hospitality Management Program, Appalachian State University, initially Glover establishes: “Quality is a primary concern in the hospitality industry. The author sees problems in the nature of the way businesses are managed and discusses approaches to ensuring quality in corporate cultures.” As the title suggests, the author wants to point out certain discrepancies in hospitality quality control, as well as enlighten you as to how to address some of these concerns. “A discussion of quality presents some interesting dilemmas. Quality is something that almost everyone wants,” Assistant Professor Glover notes. “Service businesses will never admit that they don't provide it to their customers, and few people actually understand what it takes to make it happen,” he further maintains. Glover wants you to know that in a dynamic industry such as hospitality, quality is the common denominator. Whether it be hotel, restaurant, airline, et al., quality is the raison d’être of the industry. “Quality involves the consistent delivery of a product or service according to the expected standards,” Glover provides. Many, if not all quality deficiencies can be traced back to management, Glover declares. He bullet points some of the operational and guest service problems managers’ face on a daily basis. One important point of note is the measuring and managing of quality. “Standards management is another critical area in people and product management that is seldom effective in corporations,” says Glover. “Typically, this area involves performance documentation, performance evaluation and appraisal, coaching, discipline, and team-building.” “To be effective at managing standards, an organization must establish communication in realms where it is currently non-existent or ineffective,” Glover goes on to say. “Coaching, training, and performance appraisal are methods to manage individuals who are expected to do what's expected.” He alludes to the benefit quality circles supply as well. In addressing American organizational behavior, Glover postures, “…a realization must develop that people and product management are the primary influences on generating revenues and eventually influencing the bottom line in all American organizations.” Glover introduces the concept of pro-activity. “Most recently, quality assurance and quality management have become the means used to develop and maintain proactive corporate cultures. When prevention is the focus, quality is most consistent and expectations are usually met,” he offers. Much of the article is dedicated to, “Appendix A-Table 1-Characteristics of Corporate Cultures (Reactive and Proactive. In it, Glover measures the impact of proactive management as opposed to the reactive management intrinsic to many elements of corporate culture mentality.

Fuzzy Modeling and Control Based Virtual Machine Resource Management

Virtual machines (VMs) are powerful platforms for building agile datacenters and emerging cloud systems. However, resource management for a VM-based system is still a challenging task. First, the complexity of application workloads as well as the interference among competing workloads makes it difficult to understand their VMs’ resource demands for meeting their Quality of Service (QoS) targets; Second, the dynamics in the applications and system makes it also difficult to maintain the desired QoS target while the environment changes; Third, the transparency of virtualization presents a hurdle for guest-layer application and host-layer VM scheduler to cooperate and improve application QoS and system efficiency. This dissertation proposes to address the above challenges through fuzzy modeling and control theory based VM resource management. First, a fuzzy-logic-based nonlinear modeling approach is proposed to accurately capture a VM’s complex demands of multiple types of resources automatically online based on the observed workload and resource usages. Second, to enable fast adaption for resource management, the fuzzy modeling approach is integrated with a predictive-control-based controller to form a new Fuzzy Modeling Predictive Control (FMPC) approach which can quickly track the applications’ QoS targets and optimize the resource allocations under dynamic changes in the system. Finally, to address the limitations of black-box-based resource management solutions, a cross-layer optimization approach is proposed to enable cooperation between a VM’s host and guest layers and further improve the application QoS and resource usage efficiency. The above proposed approaches are prototyped and evaluated on a Xen-based virtualized system and evaluated with representative benchmarks including TPC-H, RUBiS, and TerraFly. The results demonstrate that the fuzzy-modeling-based approach improves the accuracy in resource prediction by up to 31.4% compared to conventional regression approaches. The FMPC approach substantially outperforms the traditional linear-model-based predictive control approach in meeting application QoS targets for an oversubscribed system. It is able to manage dynamic VM resource allocations and migrations for over 100 concurrent VMs across multiple hosts with good efficiency. Finally, the cross-layer optimization approach further improves the performance of a virtualized application by up to 40% when the resources are contended by dynamic workloads.

(Figure 2) Mean discharge per day (total and baseflow part) of the San Francisco River and daily precipitation at station ECPL (Planta), in 2007

We investigated controls on the water chemistry of a South Ecuadorian cloud forest catchment which is partly pristine, and partly converted to extensive pasture. From April 2007 to May 2008 water samples were taken weekly to biweekly at nine different subcatchments, and were screened for differences in electric conductivity, pH, anion, as well as element composition. A principal component analysis was conducted to reduce dimensionality of the data set and define major factors explaining variation in the data. Three main factors were isolated by a subset of 10 elements (Ca2+, Ce, Gd, K+, Mg2+, Na+, Nd, Rb, Sr, Y), explaining around 90% of the data variation. Land-use was the major factor controlling and changing water chemistry of the subcatchments. A second factor was associated with the concentration of rare earth elements in water, presumably highlighting other anthropogenic influences such as gravel excavation or road construction. Around 12% of the variation was explained by the third component, which was defined by the occurrence of Rb and K and represents the influence of vegetation dynamics on element accumulation and wash-out. Comparison of base- and fast flow concentrations led to the assumption that a significant portion of soil water from around 30 cm depth contributes to storm flow, as revealed by increased rare earth element concentrations in fast flow samples. Our findings demonstrate the utility of multi-tracer principal component analysis to study tropical headwater streams, and emphasize the need for effective land management in cloud forest catchments.

Benchmarking e regulação do setor de distribuição de energia elétrica nacional: proposta para avaliação dos custos operacionais eficientes

In Brazil, the National Agency of Electric Energy (ANEEL) represents the energy regulator. The rates review have been one of its main tasks, which establish a pricing practice at a level to cover the efficient operating costs and also the appropriate return of the distributors investments. The changes in the procedures to redefine the efficient costs and the several studies on the methodologies employed to regulate this segment denote the challenge faced by regulators about the best methodological strategy to be employed. In this context, this research aims to propose a benchmarking evaluation applied to the national regulation system in the establishment of efficient operating costs of electricity distribution utilities. The model is formulated to promote the electricity market development, partnering with government policies ant to society benefit. To conduct this research, an integration of Data Envelopment Analysis (DEA) with the Stochastic Frontier Analysis (SFA) is adopted in a three stages procedure to correct the efficiency in terms of environmental effects: (i) evaluation by means of DEA to measure operating costs slacks of the utilities, in which environmental variables are omitted; (ii) The slacks calculated in the first stage are regressed on a set of environmental variables by means of SFA and operating costs are adjusted to account the environmental impact and statistical noise effects; and, (iii) reassess the performance of the electric power distribution utilities by means of DEA. Based on this methodology it is possible to obtain a performance evaluation exclusively expressed in terms of management efficiency, in which the operating environment and statistical noise effects are controlled.