An Economic Analysis of Subscription Sharing of Digital Services

Subscription sharing, where one shares her premium digital services subscription with other users, has become common due to subscription-sharing platforms like Togetherprice, Gowd, and Sharesub. This raises a question: Does it still make economic sense to offer a menu of subscription plans (e.g., an individual plan as well as a discounted family plan)? In this study, we look at a monopolist service provider that offers both plans but faces the potential threat of subscription sharing. We analyze the optimal prices and the impact of sharing on profit, customer surplus, and overall society benefits. Our results indicate that even with subscription sharing, offering both plans is at least as profitable as only offering individual plans. Under certain conditions, subscription sharing can even boost profits. Furthermore, our numerical analysis suggests that subscription sharing can benefit society. These findings suggest that subscription sharing is not necessarily as troublesome as one would have expected

Structure-aware content creation : detection, retargeting and deformation

Nowadays, access to digital information has become ubiquitous, while three-dimensional visual representation is becoming indispensable to knowledge understanding and information retrieval. Three-dimensional digitization plays a natural role in bridging connections between the real and virtual world, which prompt the huge demand for massive three-dimensional digital content. But reducing the effort required for three-dimensional modeling has been a practical problem, and long standing challenge in compute graphics and related fields. In this thesis, we propose several techniques for lightening up the content creation process, which have the common theme of being structure-aware, ie maintaining global relations among the parts of shape. We are especially interested in formulating our algorithms such that they make use of symmetry structures, because of their concise yet highly abstract principles are universally applicable to most regular patterns. We introduce our work from three different aspects in this thesis. First, we characterized spaces of symmetry preserving deformations, and developed a method to explore this space in real-time, which significantly simplified the generation of symmetry preserving shape variants. Second, we empirically studied three-dimensional offset statistics, and developed a fully automatic retargeting application, which is based on verified sparsity. Finally, we made step forward in solving the approximate three-dimensional partial symmetry detection problem, using a novel co-occurrence analysis method, which could serve as the foundation to high-level applications.Jetzt hat die Zugang zu digitalen Informationen allgegenwärtig geworden. Dreidimensionale visuelle Darstellung wird immer zum Einsichtsverständnis und Informationswiedergewinnung unverzichtbar. Dreidimensionale Digitalisierung verbindet die reale und virtuelle Welt auf natürliche Weise, die prompt die große Nachfrage nach massiven dreidimensionale digitale Inhalte. Es ist immer noch ein praktisches Problem und langjährige Herausforderung in Computergrafik und verwandten Bereichen, die den Aufwand für die dreidimensionale Modellierung reduzieren. In dieser Dissertation schlagen wir verschiedene Techniken zur Aufhellung der Erstellung von Inhalten auf, im Rahmen der gemeinsamen Thema der struktur-bewusst zu sein, d.h. globalen Beziehungen zwischen den Teilen der Gestalt beibehalten wird. Besonders interessiert sind wir bei der Formulierung unserer Algorithmen, so dass sie den Einsatz von Symmetrische Strukturen machen, wegen ihrer knappen, aber sehr abstrakten Prinzipien für die meisten regelmäßigen Mustern universell einsetzbar sind. Wir stellen unsere Arbei aus drei verschiedenen Aspekte in dieser Dissertation. Erstens befinden wir Räume der Verformungen, die Symmetrien zu erhalten, und entwickelten wir eine Methode, diesen Raum in Echtzeit zu erkunden, die deutlich die Erzeugung von Gestalten vereinfacht, die Symmetrien zu bewahren. Zweitens haben wir empirisch untersucht dreidimensionale Offset Statistiken und entwickelten eine vollautomatische Applikation für Retargeting, die auf den verifizierte Seltenheit basiert. Schließlich treten wir uns auf die ungefähre dreidimensionalen Teilsymmetrie Erkennungsproblem zu lösen, auf der Grundlage unserer neuen Kookkurrenz Analyseverfahren, die viele hochrangige Anwendungen dienen verwendet werden könnten

Dual Long Short-Term Memory Networks for Sub-Character Representation Learning

Characters have commonly been regarded as the minimal processing unit in Natural Language Processing (NLP). But many non-latin languages have hieroglyphic writing systems, involving a big alphabet with thousands or millions of characters. Each character is composed of even smaller parts, which are often ignored by the previous work. In this paper, we propose a novel architecture employing two stacked Long Short-Term Memory Networks (LSTMs) to learn sub-character level representation and capture deeper level of semantic meanings. To build a concrete study and substantiate the efficiency of our neural architecture, we take Chinese Word Segmentation as a research case example. Among those languages, Chinese is a typical case, for which every character contains several components called radicals. Our networks employ a shared radical level embedding to solve both Simplified and Traditional Chinese Word Segmentation, without extra Traditional to Simplified Chinese conversion, in such a highly end-to-end way the word segmentation can be significantly simplified compared to the previous work. Radical level embeddings can also capture deeper semantic meaning below character level and improve the system performance of learning. By tying radical and character embeddings together, the parameter count is reduced whereas semantic knowledge is shared and transferred between two levels, boosting the performance largely. On 3 out of 4 Bakeoff 2005 datasets, our method surpassed state-of-the-art results by up to 0.4%. Our results are reproducible, source codes and corpora are available on GitHub.Comment: Accepted & forthcoming at ITNG-201

Research on the performance of a high pressure 5.3MPa twin screw compressor

High pressure twin screw compressors have been widely employed in fuel gas boosting and petrochemical industry. Recently, such compressors, whose maximum of discharging pressure is 5.3MPa, are also adopted in high temperature NH3 heat pumps and NH3/CO2 cascade refrigeration system. However, high pressure twin screw compressors are required to have large capacity, good performance and excellent stability at high operating pressure. In this paper, a semi-empirical model for open-type high pressure twin screw compressor is developed. Experimental research is conducted for identification of parameters, while validation is also made on the accuracy of the model. On the basis of theoretical and experimental research, the performance of the compressor, which includes volumetric efficiency, adiabatic efficiency, discharge temperature and lubricant oil flow rate/temperature, are illustrated. The change pattern of such features on the operating conditions, slide valve loadings and ambient features are then analyzed. Additionally, the stability test results of the high pressure twin screw compressor including the vibration and noise are also shown

Experimental Investigation on the Operating Characteristics of a Semi-hermetic Twin Screw Refrigeration Compressor by means of p-V Diagram

In this paper, a comprehensive experimental investigation is carried out to evaluate the operating characteristics of a semi-hermetic twin screw refrigeration compressor at different oil flow rates and slide valve positions under various conditions. The working volume pressure of the compressor is recorded by a serial of sensors arranged in consecutive positions in the housing. These measured pressure data are then transformed into an indicator diagram. Based on the p-V diagrams, the effect mechanism of some factors such as evaporation temperature, condensation temperature, slide valve positions, oil flow rates for the suction and discharge end bearings lubricating and oil flow rate returned from the suction pipe on the compressor performance and working process is analyzed. These results can be useful for optimum design of oil flow passage assembly and selection of optimal built-in volume ratio to improve the energy efficiency of refrigeration system with semi-hermetic twin screw compressor

Establishment and verification of solar radiation calculation model of glass daylighting roof in hot summer and warm winter zone in China

In this paper, solar heat gain through glass daylighting roof is deeply studied by theoretical calculation method, taking Guangzhou in the Hot Summer and Warm Winter (HSWW) zone as an example. The direct solar radiation is calculated by Bouguer formula whereas the diffuse solar radiation is calculated by Berlage formula, representing the basis for the calculation method of the solar radiation intensity through the glass daylighting roof. Through the establishment of solar radiation calculation model, the solar heat gain of the commonly used glass types has been calculated and analyzed, especially comparatively analyzing of Low-E cored-glass with double-coated silver and 6+12A+6 insulating glass. Then, comparison between solar heat gain as calculated and measured by field measurement tested the indoor solar radiation heat gain distribution by using adjacent rooms with different glass types in a hot summer area, with the aim of demonstrating the effectiveness of the model. The research in this paper is expected to further improve the calculation accuracy of both thermal load and indoor temperature

A Matlab Toolbox for Feature Importance Ranking

More attention is being paid for feature importance ranking (FIR), in particular when thousands of features can be extracted for intelligent diagnosis and personalized medicine. A large number of FIR approaches have been proposed, while few are integrated for comparison and real-life applications. In this study, a matlab toolbox is presented and a total of 30 algorithms are collected. Moreover, the toolbox is evaluated on a database of 163 ultrasound images. To each breast mass lesion, 15 features are extracted. To figure out the optimal subset of features for classification, all combinations of features are tested and linear support vector machine is used for the malignancy prediction of lesions annotated in ultrasound images. At last, the effectiveness of FIR is analyzed according to performance comparison. The toolbox is online (https://github.com/NicoYuCN/matFIR). In our future work, more FIR methods, feature selection methods and machine learning classifiers will be integrated

More Severe Manifestations and Poorer Short-Term Prognosis of Ganglioside-Associated Guillain-Barré Syndrome in Northeast China

Ganglioside as a neurotrophic drug has been hitherto widely used in China, although Guillain-Barré syndrome (GBS) following intravenous ganglioside treatment was reported in Europe several decades ago. We identified 7 patients who developed GBS after intravenous use of gangliosides (ganglioside+ group) and compared their clinical data with those of 77 non-ganglioside-associated GBS patients (ganglioside− group) in 2013, aiming at gaining the distinct features of ganglioside-associated GBS. Although the mean age, protein levels in cerebrospinal fluid (CSF) and frequency of cranial nerve involvement were similar between the two groups, the Hughes Functional Grading Scale (HFGS) score and the Medical Research Council (MRC) sum score at nadir significantly differed (4.9±0.4 vs 3.6±1.0; 7.7±5.5 vs 36.9±14.5, both p<0.001), indicating a higher disease severity of ganglioside-associated GBS. A higher ratio of patients with ganglioside-associated GBS required mechanical ventilation (85.7% vs 15.6%, p<0.01). The short-term prognosis of ganglioside-associated GBS, as measured by the HFGS score and the MRC sum score at discharge, was poorer (4.3±0.5 vs 2.8±1.1; 17.3±12.9 vs 46.0±13.9, both p<0.001). All the patients in the ganglioside+ group presented an axonal form of GBS, namely acute motor axonal neuropathy (AMAN). When compared with the AMAN patients in the ganglioside− group, more severe functional deficits at nadir and poorer recovery after standard treatment were still prominent in ganglioside-associated GBS. Anti-GM1 and anti-GT1a antibodies were detectable in patients with AMAN while not in patients with the demyelinating subtype of GBS. The concentrations of these antibodies in patients with AMAN were insignificantly different between the ganglioside+ and ganglioside− groups. In sum, ganglioside-associated GBS may be a devastating side effect of intravenous use of gangliosides, which usually manifests a more severe clinical course and poorer outcome