The Effect of Media on Charitable Giving and Volunteering: Evidence from the `Give Five' Campaign

Fundraising campaigns advertised via mass media are common. To what extent such campaigns affect charitable behavior is mostly unknown, however. Using giving and volunteering surveys conducted biannually from 1988 to 1996, I investigate the e¡èect of a national fundraising campaign, "Give Five", on charitable giving and volunteering patterns. The widely advertised "Give Five" campaign was aimed to encourage people to give five percent of their income and volunteer five hours a week. After controlling for selection into being informed about the "Give Five", I find that people who were informed about the campaign increased their weekly volunteering activity on average by almost half an hour, but their giving behavior was not significantly affected. I discuss the policy implications associated with this result and argue that although the "Give Five" campaign did not achieve its goal, its economic impact was considerable.

Do Fundraisers Select Charitable Donors Based on Gender and Race? Evidence from Survey Data

Recent studies document that people are much more likely to donate to charity and volunteer their time when they are asked to. Using household surveys of giving and volunteering in the United States conducted from 1992 to 2001, which contain questions on whether the respondent was personally asked to give or volunteer, this paper investigates the factors associated with the probability of receiving a charitable solicitation and presents substantial evidence that race and gender differences play key roles in the selection of potential donors. In particular, males, blacks, and Hispanics are less likely to be solicited compared with females and whites. Using non-linear decomposition techniques, I find that differences in observable characteristics of individuals explain most of the racial gap in the probability of being solicited for charitable causes, but they fail to explain the gender gap in the probability of being asked to volunteer. Furthermore, these results are robust to alternative specifications. I also discuss related policy implications and argue that the economic impact of selecting potential donors based on gender and race can be considerable.

The Kuznets curve and the effect of international regulations on environmental efficiency

This paper extends the results of series of papers, i.e., Zaim (2004) and Yörük and Zaim (2005a, 2005b). We construct an environmental efficiency index for OECD countries and establish an environmental Kuznets curve relationship between environmental efficiency and income. We then investigate the effect of an international protocol on reducing global emissions on the environmental efficiency.

Assessment of an Underground Coal Mine Fire: A Case Study From Zonguldak, Turkey

This paper aims to evaluate an underground coal-mine fire detected on November, 11th 2007 in Gelik Mine of Karadon Colliery of Turkish Hardcoal Enterprise (TTK), Zonguldak, Turkey. Several techniques were employed by TTK to fight the fire including sealing, filling the mine with water and pumping nitrogen. The mine atmosphere was continuously monitored and gas samples were collected for analysis using a gas chromatograph. In this study, following a description of the fire fighting efforts, the interpretations of well-known fire indices applied to the different stages of the incident were given and attempts were made to compare and to test the reliability of these indices

Bit-wise Unequal Error Protection for Variable Length Block Codes with Feedback

The bit-wise unequal error protection problem, for the case when the number of groups of bits $\ell$ is fixed, is considered for variable length block codes with feedback. An encoding scheme based on fixed length block codes with erasures is used to establish inner bounds to the achievable performance for finite expected decoding time. A new technique for bounding the performance of variable length block codes is used to establish outer bounds to the performance for a given expected decoding time. The inner and the outer bounds match one another asymptotically and characterize the achievable region of rate-exponent vectors, completely. The single message message-wise unequal error protection problem for variable length block codes with feedback is also solved as a necessary step on the way.Comment: 41 pages, 3 figure

User centered neuro-fuzzy energy management through semantic-based optimization

This paper presents a cloud-based building energy management system, underpinned by semantic middleware, that integrates an enhanced sensor network with advanced analytics, accessible through an intuitive Web-based user interface. The proposed solution is described in terms of its three key layers: 1) user interface; 2) intelligence; and 3) interoperability. The system’s intelligence is derived from simulation-based optimized rules, historical sensor data mining, and a fuzzy reasoner. The solution enables interoperability through a semantic knowledge base, which also contributes intelligence through reasoning and inference abilities, and which are enhanced through intelligent rules. Finally, building energy performance monitoring is delivered alongside optimized rule suggestions and a negotiation process in a 3-D Web-based interface using WebGL. The solution has been validated in a real pilot building to illustrate the strength of the approach, where it has shown over 25% energy savings. The relevance of this paper in the field is discussed, and it is argued that the proposed solution is mature enough for testing across further buildings

Renewable energy policy in Turkey

Abstract: This study aims to explore the availability and potential of renewable energy sources in Turkey and discuss the government policies and economic aspects. Turkey is a country which has the highest hydropower and wind energy potential among European countries. Current energy policy of Turkey primarily aims to maximize geothermal, wind and hydropower potential of the country in next 15 years. In Several incentives were developed for electricity generation from renewable energy sources by the publication of Law No. 5346 in 2005. The most important ones are: ease of land acquisition and feed-in-tariffs which promises purchasing of electricity generated by legal entities with a price of 5-5.5 €c/kWh. Since Turkey is a European Union (EU) candidate its laws and regulations must be compatible with EU. As the legislation in EU member states is investigated it is apparent that Law No. 5346 should be restructured. This should include: (i) redetermination of feed-in-tariff amount according to type and capacity of renewable energy source, (ii) taking installed capacity into account instead of reservoir area for hydroelectric power plants as renewable energy source, (iii) making detailed Environmental Impact Assessment (EIA) report obligatory for renewable energy plants. The emphasis has been given on hydropower and wind energy. The renewable energy policy of Turkey has been compared with the advanced economies in Europe like Germany and Norwa

Beyond thresholding: analysis and improvements for deterministic parameter estimation

Hard-threshold estimators are popular in signal processing applications. We provide a detailed study of using hard-threshold estimators for estimating an unknown deterministic signal when additive white Gaussian noise corrupts observations. The analysis, depending heavily on Cramér-Rao bounds, motivates piecewise-linear estimation as a simple improvement to hard thresholding. We compare the performance of two piecewise-linear estimators to a hard-threshold estimator. When either piecewise-linear estimator is optimized for the decay rate of the basis coefficients, its performance is better than the best possible with hard thresholding.First author draf

Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model

We propose a novel end-to-end semi-supervised adversarial framework to generate photorealistic face images of new identities with wide ranges of expressions, poses, and illuminations conditioned by a 3D morphable model. Previous adversarial style-transfer methods either supervise their networks with large volume of paired data or use unpaired data with a highly under-constrained two-way generative framework in an unsupervised fashion. We introduce pairwise adversarial supervision to constrain two-way domain adaptation by a small number of paired real and synthetic images for training along with the large volume of unpaired data. Extensive qualitative and quantitative experiments are performed to validate our idea. Generated face images of new identities contain pose, lighting and expression diversity and qualitative results show that they are highly constraint by the synthetic input image while adding photorealism and retaining identity information. We combine face images generated by the proposed method with the real data set to train face recognition algorithms. We evaluated the model on two challenging data sets: LFW and IJB-A. We observe that the generated images from our framework consistently improves over the performance of deep face recognition network trained with Oxford VGG Face dataset and achieves comparable results to the state-of-the-art