When Hashes Met Wedges: A Distributed Algorithm for Finding High Similarity Vectors

Finding similar user pairs is a fundamental task in social networks, with numerous applications in ranking and personalization tasks such as link prediction and tie strength detection. A common manifestation of user similarity is based upon network structure: each user is represented by a vector that represents the user's network connections, where pairwise cosine similarity among these vectors defines user similarity. The predominant task for user similarity applications is to discover all similar pairs that have a pairwise cosine similarity value larger than a given threshold $\tau$. In contrast to previous work where $\tau$ is assumed to be quite close to 1, we focus on recommendation applications where $\tau$ is small, but still meaningful. The all pairs cosine similarity problem is computationally challenging on networks with billions of edges, and especially so for settings with small $\tau$. To the best of our knowledge, there is no practical solution for computing all user pairs with, say $\tau = 0.2$ on large social networks, even using the power of distributed algorithms. Our work directly addresses this challenge by introducing a new algorithm --- WHIMP --- that solves this problem efficiently in the MapReduce model. The key insight in WHIMP is to combine the "wedge-sampling" approach of Cohen-Lewis for approximate matrix multiplication with the SimHash random projection techniques of Charikar. We provide a theoretical analysis of WHIMP, proving that it has near optimal communication costs while maintaining computation cost comparable with the state of the art. We also empirically demonstrate WHIMP's scalability by computing all highly similar pairs on four massive data sets, and show that it accurately finds high similarity pairs. In particular, we note that WHIMP successfully processes the entire Twitter network, which has tens of billions of edges

Morphologic and histological differentiation of gubernaculum in female fetus: a cadaveric study

Background: In both male and female fetuses inguinal canal development entails a complex sequence of anatomic events involving the gubernaculum and processus vaginalis. Much has been written about the embryological development of the genital system, particularly the male genital system and the descent of the testes from the abdominal cavity into the scrotum. In this process, the gubernaculum plays a relevant although still unclear role. Despite all the studies that have been performed, controversy still exists in this anatomical region.Methods: Twenty round ligaments of uterus were dissected from female fetuses and microscopic structure was studied under light microscope using haematoxylin and eosin stain. The specimens were collected from female fetuses (8wks-26wks). One male fetus was also dissected.Results: Gubernaculum plays a crucial role in the development of the inguinal region. The gubernaculum is directly associated with the migration of the testis through the inguinal canal and probably to the scrotum; but the inguinal canal is present before testicular descent and females have both an inguinal canal and gubernaculum, although the ovaries do not migrate through the abdominal wall.Conclusions: In this anatomical region, and despite all the studies that have been performed, controversy still exists. This article attempts to study the morphology and histology and the differentiation of the gubernaculum with age.

Video Object Detection with an Aligned Spatial-Temporal Memory

We introduce Spatial-Temporal Memory Networks for video object detection. At its core, a novel Spatial-Temporal Memory module (STMM) serves as the recurrent computation unit to model long-term temporal appearance and motion dynamics. The STMM's design enables full integration of pretrained backbone CNN weights, which we find to be critical for accurate detection. Furthermore, in order to tackle object motion in videos, we propose a novel MatchTrans module to align the spatial-temporal memory from frame to frame. Our method produces state-of-the-art results on the benchmark ImageNet VID dataset, and our ablative studies clearly demonstrate the contribution of our different design choices. We release our code and models at http://fanyix.cs.ucdavis.edu/project/stmn/project.html

Organisational synergies, dissonance and spinoffs

Spinoff firms are a distinct class of new entrants across industries. The causes for their emergence have been widely investigated in the literature. However, the role of team environments has received little attention. On the one hand, talented individuals may find it necessary to team up with others to utilise complementary knowledge and generate synergies. On the other hand, some types of team production environments may exhibit dissonance and motivate individuals to leave them. This study introduces environments of synergy and dissonance utilising team production functions and utilises them to analyse how team environments vary in their propensity to generate spinoffs. We show that the teams exhibiting synergy are not likely to spawn spinoffs but a new idea from a team member gets implemented only if it is of exceptional quality. The concepts of synergy and dissonance can also be utilised to analyse other phenomena such as mergers and alliances

A Hierarchical Recurrent Encoder-Decoder For Generative Context-Aware Query Suggestion

Users may strive to formulate an adequate textual query for their information need. Search engines assist the users by presenting query suggestions. To preserve the original search intent, suggestions should be context-aware and account for the previous queries issued by the user. Achieving context awareness is challenging due to data sparsity. We present a probabilistic suggestion model that is able to account for sequences of previous queries of arbitrary lengths. Our novel hierarchical recurrent encoder-decoder architecture allows the model to be sensitive to the order of queries in the context while avoiding data sparsity. Additionally, our model can suggest for rare, or long-tail, queries. The produced suggestions are synthetic and are sampled one word at a time, using computationally cheap decoding techniques. This is in contrast to current synthetic suggestion models relying upon machine learning pipelines and hand-engineered feature sets. Results show that it outperforms existing context-aware approaches in a next query prediction setting. In addition to query suggestion, our model is general enough to be used in a variety of other applications.Comment: To appear in Conference of Information Knowledge and Management (CIKM) 201

Comparison of measured and Monte Carlo-calculated electron depth dose distributions in aluminium

Depth dose profiles in aluminium have been measured using the cellulose triacetate dosimeter against different electron energies (4, 4.5 and 5 MeV) at a recently upgraded 15 kW industrial electron beam accelerator facility. The study also includes comparison of these profiles against Monte Carlo calculations. The measured and simulated depth dose profiles are similar in shape. For all electron energies, at initial depths, the measured doses are higher than the simulated ones. The simulated and measured normalized surface dose values are 0.58 and 0.66, respectively, independent of electron energy. The difference in the surface dose between Monte Carlo and experiment could be attributed to possible presence of low energy electrons in the measurements whereas the Monte Carlo calculations are based on monoenergetic electrons. Between the region of dose maximum and the tail portion of the depth dose curve, the measured dose is smaller than the simulated values (about 17% to 40% at 5 MeV). Using the depth dose profiles, electron beam parameters such as depth at which maximum dose occurs, dmax, practical range, Rp and half-value depth, R50 have been determined. Using the measured parameters Rp and R50, the incident kinetic energy of the electron beam has been determined. The estimated electron energies while using Rp are 4.02, 4.41 and 4.75 MeV. When using R50, the corresponding values are 3.83, 4.21 and 4.64 MeV. The measured RP/R50 ratios are slightly larger than the Monte Carlo-calculated values, which suggest that the electron beam may not be monoenergetic

Zen: Near-Optimal Sparse Tensor Synchronization for Distributed DNN Training

Distributed training is the de facto standard to scale up the training of Deep Neural Networks (DNNs) with multiple GPUs. The performance bottleneck of distributed training lies in communications for gradient synchronization. Recently, practitioners have observed sparsity in gradient tensors, suggesting the potential to reduce the traffic volume in communication and improve end-to-end training efficiency. Yet, the optimal communication scheme to fully leverage sparsity is still missing. This paper aims to address this gap. We first analyze the characteristics of sparse tensors in popular DNN models to understand the fundamentals of sparsity. We then systematically explore the design space of communication schemes for sparse tensors and find the optimal one. % We then find the optimal scheme based on the characteristics by systematically exploring the design space. We also develop a gradient synchronization system called Zen that approximately realizes it for sparse tensors. We demonstrate that Zen can achieve up to 5.09x speedup in communication time and up to 2.48x speedup in training throughput compared to the state-of-the-art methods

On Fixed Point theorems in Fuzzy Metric Spaces

Abstract: This paper presents some common fixed point theorems for occasionally weakly compatible mappings in fuzzy metric spaces. Keywords: Occasionally weakly compatible mappings,fuzzy metric space

Investigation of complete and incomplete fusion in 7^{7}Li+124^{124}Sn reaction around Coulomb barrier energies

The complete and incomplete fusion cross sections for $^{7}$Li+$^{124}$Sn reaction were measured using online and offline characteristic $\gamma$-ray detection techniques. The complete fusion (CF) cross sections at energies above the Coulomb barrier were found to be suppressed by $\sim$ 26 \% compared to the coupled channel calculations. This suppression observed in complete fusion cross sections is found to be commensurate with the measured total incomplete fusion (ICF) cross sections. There is a distinct feature observed in the ICF cross sections, i.e., $\textit{t}$-capture is found to be dominant than $\alpha$-capture at all the measured energies. A simultaneous explanation of complete, incomplete and total fusion (TF) data was also obtained from the calculations based on Continuum Discretized Coupled Channel method with short range imaginary potentials. The cross section ratios of CF/TF and ICF/TF obtained from the data as well as the calculations showed the dominance of ICF at below barrier energies and CF at above barrier energies.Comment: 9 pages, 8 figure

Stability Assessment of Pipeline Cathodic Protection Potentials under the Influence of AC Interference

Abstract: Metallic pipelines are protected from induced corrosion by the application of coating and Cathodic Protection (CP) systems. The latter is achieved by keeping the pipeline at a constant Direct Current (DC) voltage in relation to the surrounding soil. While this is conventionally meant to arrest corrosion, the Alternating Current (AC) interference from high voltage transmission lines has been a major problem to the CP potential systems of buried steel pipelines. Several research studies dealing with this problem have been published, and a lot of research work is still on going. This work focuses on assessing the stability of the CP potentials under the influence of AC interference. Seven different CP potentials varying from −800 mV to −1200 mV were applied on steel pipe specimen exposed to the AC interference with a varying AC voltage from 0–50 V. The results of the laboratory investigation revealed that CP potential of −1150 mV was more stable under the influence of AC interference, with just a minimal shift from the set value. The results from the corrosion morphology tests on the pipelines using Scanning Electron Microscope (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) reveal the need for optimising the CP potential to provide adequate or optimum protection to the pipelines. Thus, more research studies involving simulation and field studies may lead to a major breakthrough in improving protection potentials