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At the beginning of the 1950s, an amateur cinema clubs network started developing in Yugoslavia. These cinema clubs soon became centres of experimental films production and development. In order to understand Yugoslav experimental film in a more comprehensive manner, the author of the paper analyses its institutional and production framework at the time and states a thesis about the organized cinema amateurism as an aspect of identity homogeniza- tion of the Yugoslav society. The paper also touches on the relationship between this branch of film making and professional cinema, the discourse presence of which formed the position and (self)awareness of amateur experimentalists to a large extent. The comparative model for the analysis of emancipation and market position of Yugoslav experimental film is the New York City based The Film-Maker’s Cooperative, serving as a model for the attempt to organize Yugoslav experimental film via the JUFIKO initiative (the Yugoslav Film Cooperative). Amateur experimental film is looked at through the optics of commercial activities in the socialist system, opening neo-avant-garde ideological questions and the questions about the discipline to which this film belongs – is it “art” or “film”. [ABSTRACT FROM AUTHOR]

• Estimate link travel time with large-scale incomplete vehicle trip data. • Propose a path-recovery-based method to iteratively estimate link travel time. • Conduct extensive experiments on two public large-scale vehicle trip datasets. The widespread use of positioning devices has generated large-scale trip data, boosting the study of traffic modeling. For instance, New York City Taxi & Limousine Commission regularly releases over 165 million taxi trip records containing the end-point information of each trip every year. Such big datasets provide us potential new perspectives to tackle traditional issues in traffic modeling. In this paper, we propose to use such vehicle trip data, which do not contain information on the intermediate vehicle positions other than the end points, to study the link (road segment) travel time estimation problem. A method named PR-LTTE is developed to estimate the mean travel time for interested links in a road network based on path recovery, jointly modeling trip distance and trip travel time. The key idea is to iteratively alternate between 1) inferring the most likely path for a given trip by minimizing a loss function that considers both trip distance and trip travel time, and 2) computing the link travel time via the least-squares estimation with the inferred path. Our experiments on two large-scale trip datasets (including New York City taxi trip data and Chengdu DiDi trip data) show very promising results. PR-LTTE improves the accuracy of travel time estimation by more than 50% in most cases over state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Exploiting deep learning techniques for traffic flow prediction has become increasingly widespread. Most existing studies combine CNN or GCN with recurrent neural network to extract the spatio-temporal features in traffic networks. The traffic networks can be naturally modeled as graphs which are effective to capture the topology and spatial correlations among road links. The issue is that the traffic network is dynamic due to the continuous changing of the traffic environment. Compared with the static graph, the dynamic graph can better reflect the spatio-temporal features of the traffic network. However, in practical applications, due to the limited accuracy and timeliness of data, it is hard to generate graph structures through frequent statistical data. Therefore, it is necessary to design a method to overcome data defects in traffic flow prediction. In this paper, we propose a long-term traffic flow prediction method based on dynamic graphs. The traffic network is modeled by dynamic traffic flow probability graphs, and graph convolution is performed on the dynamic graphs to learn spatial features, which are then combined with LSTM units to learn temporal features. In particular, we further propose to use graph convolutional policy network based on reinforcement learning to generate dynamic graphs when the dynamic graphs are incomplete due to the data sparsity i sue. By testing our method on city-bike data in New York City, it demonstrates that our model can achieve stable and effective long-term predictions of traffic flow, and can reduce the impact of data defects on prediction results. [ABSTRACT FROM AUTHOR]

The article discusses the acquisition and ownership of the newspaper the "Village Voice" by retail executive Peter Barbey and Barbey's move to New York City. Emphasis is given to topics such as hunting for an apartment, visiting New York City as a teenager, and the editorial focus of the publication.

The article reviews the exhibition Drawn to Greatness: Master Drawings from the Thaw Collection at the Morgan Library and Museum in New York.

The article previews and reviews theatrical performances in New York City as of July 2016, which include Richard Strand's play "Butler," directed by Joseph Discher at 59E59 beginning July 14, Elizabeth Swados' musical "Runaways," performed at the City Center from July 6-9, and the puppet play "The Paper Hat Game," directed by Torry Bend at #LD Art & Technology Center through July 17.

This paper presents an update to the MK model [M. Kabirnezhad, Phys. Rev. D 97, 013002 (2018)], which was developed to describe single pion production in neutrino-nucleon interactions. Originally, the MK model used the helicity amplitudes and the hadronic current form factors of the Rein and Sehgal model [Ann. Phys. (N.Y.) 50, 189 (1968)]. The update includes a new definition for the helicity amplitudes in the first and second resonance regions and new vector-current form factors. Fits to electron-proton scattering data were used to determine these vector-current form factors and to assign errors to the constrained free parameters of the model. [ABSTRACT FROM AUTHOR]

The article reviews the exhibition “Paintings and Works on Paper” at Skarstedt Gallery in New York City, New York from November11 to December 21, 2019.

The article offers the author's insights on street photography of New York. Topics discussed include the New York street photography by photographer Lee Friedlander, photography of visual environment, and photographs of New Yorkers talking to the cellphone in the street of the city. It also mentioned the use of black-and-white films.

The article reports on statistics regarding the granting of tenure in New York City in the aftermath of its 2009 changes to the city's education policies on the issue, taken from the 2014 working paper "Performance screens for school improvement: The case of teacher tenure reform in New York City," by S. Loeb and J. Wyckoff.