Ranking efficient DMUs using cooperative game theory

The problem of ranking Decision Making Units (DMUs) in Data Envelopment Analysis (DEA) has been widely studied in the literature. Some of the proposed approaches use cooperative game theory as a tool to perform the ranking. In this paper, we use the Shapley value of two different cooperative games in which the players are the efficient DMUs and the characteristic function represents the increase in the discriminant power of DEA contributed by each efficient DMU. The idea is that if the efficient DMUs are not included in the modified reference sample then the efficiency score of some inefficient DMUs would be higher. The characteristic function represents, therefore, the change in the efficiency scores of the inefficient DMUs that occurs when a given coalition of efficient units is dropped from the sample. Alternatively, the characteristic function of the cooperative game can be defined as the change in the efficiency scores of the inefficient DMUs that occurs when a given coalition of efficient DMUs are the only efficient DMUs that are included in the sample. Since the two cooperative games proposed are dual games, their corresponding Shapley value coincide and thus lead to the same ranking. The more an ef- ficient DMU impacts the shape of the efficient frontier, the higher the increase in the efficiency scores of the inefficient DMUs its removal brings about and, hence, the higher its contribution to the overall discriminant power of the method. The proposed approach is illustrated on a number of datasets from the literature and compared with existing methods

Speaker-independent emotion recognition exploiting a psychologically-inspired binary cascade classification schema

In this paper, a psychologically-inspired binary cascade classification schema is proposed for speech emotion recognition. Performance is enhanced because commonly confused pairs of emotions are distinguishable from one another. Extracted features are related to statistics of pitch, formants, and energy contours, as well as spectrum, cepstrum, perceptual and temporal features, autocorrelation, MPEG-7 descriptors, Fujisakis model parameters, voice quality, jitter, and shimmer. Selected features are fed as input to K nearest neighborhood classifier and to support vector machines. Two kernels are tested for the latter: Linear and Gaussian radial basis function. The recently proposed speaker-independent experimental protocol is tested on the Berlin emotional speech database for each gender separately. The best emotion recognition accuracy, achieved by support vector machines with linear kernel, equals 87.7%, outperforming state-of-the-art approaches. Statistical analysis is first carried out with respect to the classifiers error rates and then to evaluate the information expressed by the classifiers confusion matrices. © Springer Science+Business Media, LLC 2011

A Survey on Economic-driven Evaluations of Information Technology

The economic-driven evaluation of information technology (IT) has become an important instrument in the management of IT projects. Numerous approaches have been developed to quantify the costs of an IT investment and its assumed profit, to evaluate its impact on business process performance, and to analyze the role of IT regarding the achievement of enterprise objectives. This paper discusses approaches for evaluating IT from an economic-driven perspective. Our comparison is based on a framework distinguishing between classification criteria and evaluation criteria. The former allow for the categorization of evaluation approaches based on their similarities and differences. The latter, by contrast, represent attributes that allow to evaluate the discussed approaches. Finally, we give an example of a typical economic-driven IT evaluation

Development of concepts for a zero-fossil-energy greenhouse

Dutch government and greenhouse horticultural practice aim for strongly reduced fossil energy use and of environmental loads in 2010 and energy neutral greenhouses in 2020. This research aims to design a greenhouse concept with minimal use of fossil energy and independent of nearby greenhouses. The concept is called the zero-fossil-energy-greenhouse. This paper presents a theoretical design study and analysis to assess the viability of a zero-fossil-energy-greenhouse concept. The greenhouse was designed for Dutch circumstances and relies on available state-of-art technologies. Nine concepts were generated and evaluated by a panel of experts. Although, none of the concepts was unanimously selected, one of the concepts received on-average highest votes. It uses an aquifer for long term heat and cold storage. Geothermal heat and a heat pump connected to the warm pit of the aquifer are used to heat of the greenhouse. Electricity need is covered by green-electricity. Cooling and dehumidification of the greenhouse is realised by a heat pump combined with the cold aquifer pit. This concept was more thoroughly evaluated in a simulation study that assessed design consistency and evaluated greenhouse performance in view of design requirements. From the simulations it was concluded that a combination of geothermal heat and a heat pump/aquifer can cover the heat demand of the greenhouse with help of heat buffers, but a fully closed greenhouse concept is not manageable in the summer season. With given technology the chosen concept was not able to cool and dehumidify greenhouse air to target temperature and humidity. A semi closed greenhouse solves this problem

Testing for Stochastic Dominance with Diversification Possibilities

We derive empirical tests for stochastic dominance that allow for diversification betweenchoice alternatives. The tests can be computed using straightforward linearprogramming. Bootstrapping techniques and asymptotic distribution theory canapproximate the sampling properties of the test results and allow for statistical inference.Our results could provide a stimulus to the further proliferation of stochastic dominancefor the problem of portfolio selection and evaluation (as well as other choice problemsunder uncertainty that involve diversification possibilities). An empirical application forUS stock market data illustrates our approach.stochastic dominance;portfolio selection;linear programming;portfolio diversification;portfolio evaluation

Concept paper on a curriculum initiative for energy, climate change, and sustainability at Boston University

[Summary] Boston University has made important contributions to the interconnected challenges of energy, climate change, and sustainability (ECS) through its research, teaching, and campus operations. This work reveals new opportunities to expand the scope of teaching and research and place the University at the forefront of ECS in higher education. This paper describes the framework for a University-wide curriculum initiative that moves us in that direction and that complements the University’s strategic plan. The central curricular objectives are to provide every undergraduate the opportunity be touched in some way in their educational program by exposure to some aspect of the ECS challenge, and to increase opportunities for every graduate student to achieve a focused competence in ECS. The initiative has six cornerstone initiatives. The first is the Campus as a Living Lab (CALL) program in which students, faculty and staff work together and use our urban campus and its community to study and implement ECS solutions. The second is a university-wide minor degree that helps students develop an integrated perspective of the economic, environmental, and social dimensions of sustainability. The third is one or more graduate certificate programs open to all graduate students. The fourth is an annual summer faculty workshop that develops new ECS curriculum and CALL opportunities. The fifth is web-based resource that underpins the construction of a vibrant knowledge network for the BU community and beyond. Finally, an enhanced sustainability alumni network will augment professional opportunities and generate other benefits. The learning outcomes of this initiative will be realized through the collaborative work of faculty, students, and staff from all 17 colleges and schools. The initiative will leverage existing BU student resources such as the Thurman Center, Build Lab, and Innovate@BU. Benefits of this initiative, beyond the curriculum, include acceleration towards the goals of our Climate Action Plan; improving the “sustainability brand” of BU; enhancing the ability to attract students and new faculty; strengthening our alumni and campus communities; deepening our ties with the city of Boston; and the potential to spin off new social and technological innovations.Published versio