Personalizing Quantitative Homework Assignments to Facilate Student Learning

Electronic business tools, technology, and approaches have enabled organizations to reach new customers and markets more effectively and efficiently than ever before. A parallel process has occurred in the education industry. In many of these educational ventures, the desire to reach underserved populations is a primary motivation. In others, efficiencies and cost reductions are paramount. Still other e-learning and innovative teaching initiatives have been initiated by the sincere and direct desire to improve existing educational effectiveness. The project described in this paper is focused on educational effectiveness of teaching operations management to college students. The idea is to have a student-friendly approach to developing customized homework problems where each student has the same problem type but unique values, answers, and decisions. In this way, we seek to encourage student interaction and discussion of the problems while minimizing the risk of cheating through rote copying

Preface: CCWI 2013

Since 1991 "Computing and Control for the Water Industry – CCWI" is a well-established series of bi-annual meetings. On 2–4 September 2013, the 12th edition (CCWI2013) was held in Perugia (Italy) and was focused on Information for Water Systems and Smart Cities. CCWI2013 emphasized the integration between the more conventional themes of the analysis and planning of water systems and information technology. Such an integration offers opportunities for design solutions and innovative models for the challenging problems of water system management in an urban perspective, a key concept for smart cities (Brunone and Giustolisi, 2014). The large number of presentations – more than 200 with many young researchers from Europe and overseas – confirmed the interest for CCWI2013 themes and the increasing success of CCWI Conferences (Fig. 1). This CCWI2013 special issue contains a selection of extended CCWI2013 papers which give a taste of the Proceedings of the Conference published on Procedia Engineering Elsevier (www.sciencedirect.com/science/journal/ 18777058/70). In fact their topics range from sustainabilitybased indicators of the urban water systems (Behzadian et al., 2014), design and control parameters in water treatment (Ramphal and Sibiya, 2014), numerical simulation of the transition between surface and pressurized flow (Fernandez-Pato and Garcia-Navarro, 2014) to optimisation of pump and valve schedules in complex large-scale water distribution networks (Skworcow et al., 2014), and a real data-based model to simulate the behavior of a pumping station equipped with variable speed pumps (Capponi et al., 2014). Figure 1. Last nine editions of CCWI conferences: number of papers published in the proceedings (from Brunone and Giustolisi, 2014)

New modelling approach for the energy and steam consumption evaluation in a fresh pasta industry

The agri-food industry has a fundamental role in the Italian and European economy and is characterized by the need to reduce energy costs and emissions. Therefore, it is essential for food companies to give due consideration to the energy efficiency of the processes, to reduce production costs, without sacrificing the quality of primary production and maintaining adequate levels of competitiveness on the market. In this study, a theoretical and experimental mass and energy balance of the production process of fresh pasta was made, also considering the energy contributions of a cogeneration plant recently built in the company subject of the experimental study. The final aim was to determine scientific values of specific energy consumption for this type of production by mean a new modelling approach. The mass and energy balances were carried out for the production line of fresh semolina pasta, as well as for the cogeneration plant; monitoring the flows of raw materials and steam that characterize the production process. The results of this study can be generalized to all production processes of the same type and, in the specific case, constitute a decisive logical step for the definition of the energy recovery solutions to be adopted in the company studied, in relation to their economic-production needs

Hansenula polymorpha NMR2 and NMR4, two new loci involved in nitrogen metabolite repression

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A Detailed Procedure for Using Copulas to Classify E-Business Data

Decision support systems are widely implemented to effectively utilize the tremendous amount of data generated by information systems throughout an organization. In one common implementation, the goal is to correctly classify a customer so that appropriate action can take place. This may take the form of a customized purchase incentive given to increase the probability that a transaction is completed, while enhancing profitability. Intelligent agents employing neural network technology that function as Bayesian classifiers are one approach used here. Another approach that has been around for decades, called copulas, to our knowledge has yet to be utilized for classification in e-business applications. Copulas are functions that can describe the dependence among random variables. The very fact that copulas directly address co-dependence among variables may make them especially attractive in e-business applications where large numbers of correlated attributes may be present that could negatively affect the performance of other methods. In this paper, the basics of Bayesian decision making and posterior probabilities are reviewed. A detailed procedure for using copulas as Bayesian classifiers for e-business data is presented. The emphasis in describing the method is placed upon practitioner understanding to facilitate replication in real situations while maintaining technical rigor to ease computerized implementation

Optimal Design of District Metering Areas

Abstract The search for optimal segmentations aimed at defining district metering areas (DMAs) is a challenging and crucial issue in the analysis, planning and management of water distribution networks (WDNs). The need to select optimal segmentations relates to a number of important technical reasons. Today, the most relevant one is the leakage management by means of pressure-control zones. This contribution proposes a novel two-steps strategy for DMAs planning. The strategy is based on the segmentation design as first step, to achieve a scenario of optimal locations of "conceptual cuts"; during the second step, these are the candidate for the location of (closed) gate valves or flow measurement devices that gave rise to district monitoring areas (DMAs). The segmentation step is performed solving a multi-objective optimization problem (i.e. WDN-oriented modularity maximization versus the number of "conceptual cuts" minimization). The second step accomplishes the real DMAs design by solving a three-objective optimization, i.e. the minimization of the background leakages versus the unsupplied customers demand versus the flow observations. This means that the procedure will search for a set of scenarios having a number of closed gate valves installed at the "conceptual cuts" that do not decrease the WDN hydraulic capacity below that necessary for a sufficient service to customers, while contemporarily reducing the background leakages. A pressure-driven modelling approach is used to predict background leakage reduction and the unsupplied customers demand. The procedure is explained on a benchmark network from literature, the Apulian network

Experimental trials and dynamical simulation of the potential biogas production in a frozen food industry

Food industry determines the production of huge quantities of by-products, solid and waste. Identifying an ecological and economically viable solution for the management and disposal of horticultural wastes helps reducing the environmental impact of this kind of industries. In this paper a biogas production potential was obtained during one year of hourly data observation in a frozen food industry through dynamical simulation. This provides useful data for the correct management of an anaerobic digestion plant using the horticultural wastes coming from the production lines.The experimental analysis was carried out in an Italian cooperative firm, that process and market canned foods and frozen foods. Material flows were analysed especially considering the production of wastes. From the quantitative point of view, the hourly, daily, monthly, and annual flows of the single by-products of the studied processing cycle were determined. A dynamical simulation tool was developed to determine an optimized waste management procedure for biogas production. Design criteria was obtained for a biomass treatment to recover the organic substance for biogas production

Models of collaboration between general practice and mental health services in Italy.

Background and objectives: Anxiety and Depressive disorders represent an important public health problem, which involves not only the mental health services, but the General Practice as well. This paper examines models of Collaboration between General Practice and Community Mental Health Services developed in Italy. Methods: Different Consultation -Liaison activities are presented. For every Collaboration model advantages and disadvantage are discussed. Results: The structured Consultation Liaison Service is based on supplying diagnostic consultation and therapeutic interventions in support of General Practitioners (GPs). The service could be based in either a Community Mental Health Centre (CMHC) or externally. Diagnostic evaluation can be followed by brief and focal therapeutic interventions, in support of the GP's therapeutic plan. The spontaneous collaboration in small centres are frequent in rural areas where the contained dimensions of the services and the direct acquaintance between psychiatrists and GPs encourage the personalization of the collaboration. The model of Liaison and Group-Training focuses on direct contact between consultant and GPs. In the course of regular meetings, the consultant gives the GPs supervision and education, and they can discuss the therapeutic plans for patients requiring specialist intervention. Conclusion: The empiric classification presented should be considered an attempt to represent a complex reality. Every service, in fact, carries out activities that are necessarily wider than abstract typologies and that overlap with other models' activities

Ambient and personal noise exposure assessment in a pasta factory

Noise pollution is one of the most important risk factors in industrial settings. This study is assessing ambient and personal noise exposure among workers of a pasta factory. Two kinds of measurements were taken; at a fixed work point in three areas and personal ones for different employees; for 8h at different times. Results for the measurements carried out at fixed sample points show that exposure times of ≤ 8h are the same. The highest noise levels are in the press and packaging areas. Worker's activity is well planned as their movements avoid staying for a long time in areas where their continuous noise exposure can exceed the most critical values. Dosimeter data can be a source of concern for the workers' health and therefore for their employers. Operators are engaged to work very close to machines; so they are subjected to levels of noise exposure different from that measured in fixed sample points. This study has further confirmed that the risk evaluation is not an exact science; as it doesn't consist only of technical and mechanical factors, but needs also to consider the factors connected to workers' interaction with the workplace