The exercises in this workbook can be completed using print books in your library or using subscription-based online resources available through your law library. Because legal research is complex, we have tried to simplify the ideas in this coloring book. This
To be able to deal with the highly dimensional pose space, scene complexity, as well as other human appearances, nearly all existing works require computationally complex training and template matching processes. The positioning, dimensions, and color of the face area can be used for the localization of the body, construction of the models for that lower and upper body based on anthropometric constraints, and estimation of your skin color. We advise a bottom-up methodology for automatic extraction of human physiques from single images, within the situation of just about upright poses in cluttered environments. Segmentation of human physiques in images is really a challenging task that may facilitate numerous applications, like scene understanding and activity recognition. Different amounts of segmentation granularity are combined to extract the pose with greatest potential. Qualitative and quantitative experimental results show our methodology outperforms condition-of-the-art interactive and hybrid top-lower/bottom-
6. Refer to Figure 14.4 in your text to label the allele for both purple and white flower color, a homologous pair, and the locus of the flower color gene What is the difference between the nucleotide sequences of the purple flower allele compared to the white flower allele? Which allele does not produce a functional gene product?
“Bill may be the only one out there who, besides looking at what’s happening in each ZIP code, has the extra dimension that measures what the market potential is,” Blumberg told RIJ. “That allows him to be prescriptive on ZIP code by ZIP code basis. That kind of information can tell whether the area is producing up to potential or if it’s saturated.
Throughout the whole paper, for a meromorphic function f (z), we use standard notations of the Nevanlinna theory (see, e.g., [2, 8, 14]) such as T(r, f ), m(r, f ), and N(r, f ) and deﬁne respectively the order of growth of f (z), the exponent of convergence of the zeros of f (z), and the exponent of convergence of the poles of f (z) by ρ(f ), λ(f ), λ(1/f ) as follows:
The clearest implication for coeliac disease is that any drastic modification to the composition of the gluten protein fraction and/or to the sequences of the individual subunits are likely to have effects on functionality. Although these effects are not easy to predict, that fact that bread making wheats have been selected for functional properties for almost a century suggests that most modifications will be detrimental. Thus, although it may be possible to produce “acceptable” loaves from modified lines of wheat in the laboratory and in small scale systems [see, for example, (62, 63)], this is a much greater challenge for large scale commercial production where profit margins are narrow and small differences in parameters such as loaf height, crumb texture, color and shelf life will affect the quality of the product and hence acceptability by consumers.
Traditionally, doing all with the metric g is referred as the Jordan frame, while using g ˜ is called the Einstein frame. In the model we study in this paper, we do not use either the Jordan or the Einstein frame. We argue instead that one should not expect either of the metrics to be used for everything, as it happens in standard GR, and that is the essence of Weyl geometries. It is clear, for example by EPS kinematic analysis, that free fall and the causal structure are structures coming from dierent physical phenomena (free fall is associated to test particles, causality to light rays) and one has no reason to assume a priori a constraint between them. The choice of g ˜ for geodesics and g for causal and metric structures is precisely what makes this model dierent from the other analyses in which one frame is chosen to describe both structures. We shall eventually argue that this feature turns out to be in principle observable and important when one is going to compare the model with the solar system classical tests.
Look at all of your "to do’s to gauge the time requirement and whether additional resources will be needed to accomplish them (if yes, schedule time to obtain those resources). Don't postpone the small tasks (a sense of accomplishment is good and overlooked small tasks can become larger tasks.)
were assigned or gave themselves the following pseudonyms: Shambu, Carl, Jill, Bob, Bruce, Mac, and Elizabeth, all of who were of diverse races, ethnicities, ages, genders, and other identity statuses. All of the participants had or were working towards a doctorate in education and had taught or were currently teaching preschool to four-year- old children. They had a range of experience teaching young children and four-year-olds spanning a few years-to numerous decades. Many participants worried about their anonymity and the sensitive nature of some of the data, therefore a detailed biographical sketch of the participants is intentionally not provided in order to further ensure their anonymity within the research, nor is it integral to any of the research questions. Additionally, as educators committed to social justice who all expressed interest in teaching children about all forms of bigotry (racism, sexism, heterosexism, classism, etc.) the focus of these interviews was to learn how they carry out these practices and what obstacles they face while pushing the envelope with curriculum. However, a table is included that provides anonymous demographical data about the participants. TABLE 4.1: DEMOGRAPHICAL DATA OF INTERVIEW PARTICIPANTS Demographic Data # of Participants
name of the user as entered into their profile, obtaining 89% gender recognition (vs. 77% for screen names). Later, Liu and Ruths (2013) use the full first name from a user’s profile for gender detection, finding that for the names that are highly predictive of gender, performance improves by re- lying on this feature alone. However, more than half of the users have a name that has an unknown gender association. Manual inspection of these cases indicated that the majority includes strings formed like usernames, nicknames or other types of word concatenations. These examples are pre- cisely what the u-morph approach tries to address. Language identification is an active area of re- search (Bergsma et al., 2012; Zubiaga et al., 2014), but the username has not been used as a feature. Again, results are difficult to compare due to the lack of a common test set, but it is no- table that the average F1 score for the combination model approaches the scores obtained on a similar Twitter language identification task where the al- gorithm has access to the full text of the tweet (Lui and Baldwin, 2014): 73% vs. 77% .
class of extended gravities. PPK is a strong-ﬁeld analogue of the PPN formalism . It includes such eﬀects as the Einstein time delay, Römer time delay, Shapiro time delay and the eﬀects of aberration. The general form of these corrections is model-independent, therefore all possible manifestations of the extended gravity model can be expressed through the 8 PPK parameters ˙ ω, γ, ˙ P b , r, s, δ θ , ˙ e, ˙ x.
Let us shortly outline several relevant papers to our study. In  one of the most recent and consistent survey on evaluation of recommender systems can be found. Thus the authors discuss peculiarities of offline and online quality tests. They also review widely used quality metrics in the community (Precision, Re- call, MAE, Customer ROC, Diversity, Utility, Serendipity, Trust, etc.) noting trade-off between these set of properties. Similar trade-off effects for top-n rec- ommendations were noticed and studied earlier : “algorithms optimized for minimizing RMSE do not necessarily perform as expected in terms of top-N recommendation task”. In , importance of user-centric evaluation for recom- mender systems through a so called user experiment is stressed; in fact, this type of experiments suggests an interactive evaluation procedure that also ex- tends conventional A/B tests. In , the authors proposed a new concept of unexpectedness as recommending to users those items that different from what they would expect from the system; their method is based on the notions of util- ity theory of economics and outperforms baselines on real datasets in terms of such important measures as coverage, aggregate diversity and dispersion, while avoiding accuracy losses. However, the first approach which is close to our pro- posed metric is based on the usage of ROC curves for evaluation of customer behaviour and can be found in ; here, the authors modified conventional ROC curves by fixing the size of recommendation list for each user. Later, two more relevant papers that facilitated our findings appeared: 1)  continues studies with incorporation of quality measures (in the original paper, serendipity) into AUC-based quality evaluation framework and 2)  combines precision evalua- tion with a rather simple behavioral model of user’s interaction with the provided recommendation list. In the forthcoming sections, we extend and explain how these concrete ideas can be used for derivation of our user-centric evaluation measure to fulfill business needs of the company.
The instrument for the survey was a 26-item, self-admin- istered, structured questionnaire, designed in Chinese. The questionnaire was divided into five main sections to assess respondents’ personal information, their prenatal exami- nation utilization, delivery mode, and recovery status from the delivery, and the participation, implementation and effect of the prenatal education curriculum. A consistency test was used to evaluate the main section (prenatal edu- cation curriculum) of the questionnaire, the mean Cron- bach’s alpha coefficient was 0.825, indicating good consistency of the prenatal education curriculum section, and thus the questionnaire can be used in the investigation. To be specific, in Section A (personal information) mothers’ and their husband’s age, educational level, occu- pation, and monthly income were asked. In Section B (prenatal examination utilization), mothers were asked ‘‘did you attend the prenatal examination as required during your latest delivery?’’ (based on the requirements in the National Basic Public Health Service Specification 2011 issued by the Chinese NHFPC ). In Section C (delivery mode), mothers were asked ‘‘what was your latest delivery mode?’’ In Section D (recovery status), mothers were asked ‘‘what do you think about your recovery status from the latest deliv- ery?’’ In Section E (prenatal education curriculum), mothers were asked ‘‘did you participate in prenatal education cur- riculum during your latest pregnancy?’’, ‘‘what was the most important reason why you participated or did not participate in it?’’, ‘‘what information did the prenatal education cur- riculum provide for you?’’, ‘‘how was the prenatal education curriculum conducted?’’, and ‘‘what do you think about the effect of the prenatal education curriculum?’’