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Alaska's Kenai fisheries are managed for maximum efficiency while ensuring fair allocation across multiple stakeholder groups and long term sustainability of the fishery. Managers must work to meet the fishery's goals while adapting their commercial and subsistence eco-service management practices to meet changing ecological conditions. Pre- and in-season fishery management practices are supported...
In this paper, a joint synchronization and Doppler scaling factor estimation algorithm has been proposed for underwater acoustic communications. The training sequence, which consists of two Zadoff-Chu (ZC) sequences being conjugate with each other, is utilized to synchronize and estimate Doppler scaling factor, time delay and carrier frequency offsets (CFOs). ZC sequences are well designed to show...
Harbor protection systems detect unauthorized harbor entry by intruders such as divers, mini-submarines, and small boats. These systems typically consists of a sensor network array to detect harbor entry, a messaging system to communicate status, and a response system to react to any perceived threat. This system falls under the general problem of detecting a moving target through an array of stationary...
Evaporation duct has strong impacts on the performance of marine radar and communication systems. Evaporation duct channel is a promising channel for marine high capacity data transmission. Wave propagation models and evaporation duct models are well studied, and statistical features of duct channel has been observed. However, the work on the physical model of small-scale characteristics of evaporation...
Underwater imaging is a crucial technology necessary for many ocean-related applications such as underwater navigation, surveying, mining and many others. Unfortunately, the optical attenuation produced by oceanic waters imposes severe limitations to traditional imaging devices. Thus, new technologies are needed to probe the underwater environment in a more efficient manner. Quantum imaging represents...
The increasing demand of global video traffic presents a grand challenge for Internet service providers. This is particularly important for Smart Cities, where the citizens will be surrounded by various multimedia services. The Information Centric Networking (ICN) paradigm has been proposed to handle the vast amount of data, mobility of users, and provide better scalability and efficiency in terms...
In this paper, we describe the LFM-1b User Genre Profile dataset. It provides detailed information on musical genre preferences for more than 120,000 listeners and links to the LFM-1b dataset. We created the dataset by exploiting social tags, indexing them using two genre term sets, and aggregating the resulting annotated listening events on the user level. We foresee several applications of the dataset...
Considering the cultural background of users is known to improve recommender systems for multimedia items. In this work, we focus on music and analyze user demographics and music listening events in a large corpus (120,000 users, 109 events) from Last.fm to investigate whether similarity between countries in terms of cultural and socio-economic factors is reflected in music taste. To this end, we...
With the rapid advances in digital technology, the multimedia documents have been growing ubiquitously. The analysis of this huge repository of multimedia documents requires efficient organization of documents. Multimedia document clustering organizes the multimedia documents with common multimedia topics. The important step of multimedia document clustering is computing the similarity between multimedia...
Venue photos, as a new type of multimedia contents, are exploding on the Internet because users like to take photos and share with their friends in which venue they spent time and what impressed them there. Discovering a venue by a social photo is very useful for supplementing venue retrieval and recommendation. However, little research focused on fine-grained venue discovery by leveraging multimodal...
Cloud applications run on numerous servers and network elements. Complexity and heterogeneity of these elements make evaluation of application performance very challenging without invasive application-specific probe. We propose an anomaly detection system for Cloud application servers. Our system only collects ingress and egress data packet counts. We observe that when an application server is operating...
Methods based on order statistics are often used in finance, quality control, data and signal processing, especially when signals of interest are immersed in impulsive noise. These allow to include rank information by increasing the dimension of the problem. In large dimension problems, we are usually required to know only the second order statistics. In this article we use a rank-one quadratic measurement...
The paper deals with the estimation method of a carrier and time of arrival by chirp-like phase-coded sequence. The developed estimation method of the carrier and time of arrival is suitable for primary synchronization upon signal detection in phase and frequency modulation modems. This method is of less computational complexity relative to the realization of matched filter assembly. To implement...
The quasi-likelihood algorithm detection of rectangle ultra-wideband quasi-radiosignal with unknown amplitude, initial phase and duration has been synthesized. The statistical characteristics of the efficiency synthesized detection algorithm — false alarm probability and probability of missing a signal, have been found.
Filter bank multicarrier (FBMC) has been taken as a candidate modulation for the 5th generation (5G) mobile network, because it exploits well-shaped prototype filters to reduce the inter-symbol-interference (ISI) and inter-carrier-interference (ICI) in OFDM system. To achieve more flexibility in filter performances, this paper designs nearly perfect reconstruction (NPR) filters by relaxing the Nyquist...
This paper addresses a specific example of nonperiodic translation symmetry and presents an algorithm to automatically detect multiple poles, or their shadows, in aerial imagery by looking for consistent and overlapping regions of self-similarity across a non-urban scene. The algorithm does not rely on having a pole template or knowing its exact size. For each image patch, similar regions (or blobs)...
Convolutional neural network (CNN) has drawn increasing interest in visual tracking, among which fully-convolutional Siamese network based method (SiamFC) is quite popular due to its competitive performance in both precision and efficiency. Generally, SiamFC captures robust semantics from high-level features in the last layer but ignores detailed spatial features in earlier layers, thus tending to...
Using spatio-temporal features is popular for action recognition. However, existing methods embed these local features into a global representation. Orders and correlations among local motions of each action are missing. This can make it difficult to distinguish closely related actions. This paper proposes a solution to address this challenge by encoding correlations of movements. Space-time interest...
A large number of long non-coding RNAs (lncRNAs) have been identified over the past decades. Accumulating evidence proves that lncRNAs play key roles in various biological processes. However, the majority of the lncRNAs have not been functionally characterized. The annotation of lncRNA functions has become an area of focus in the fields of biology and bioinformatics. In this paper, we develop a global...
Merging gene expression datasets is a simple way to increase the number of samples in an analysis. However experimental and data processing conditions, which are proper to each dataset or batch, generally influence the expression values and can hide the biological effect of interest. It is then important to normalize the bigger merged dataset, as failing to adjust for those batch effects may adversely...
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