Connection Discovery using Shared Images by Gaussian Relational Topic Model

Social graphs, representing online friendships among users, are one of the fundamental types of data for many applications, such as recommendation, virality prediction and marketing in social media. However, this data may be unavailable due to the privacy concerns of users, or kept private by social network operators, which makes such applications difficult. Inferring user interests and discovering user connections through their shared multimedia content has attracted more and more attention in recent years. This paper proposes a Gaussian relational topic model for connection discovery using user shared images in social media. The proposed model not only models user interests as latent variables through their shared images, but also considers the connections between users as a result of their shared images. It explicitly relates user shared images to user connections in a hierarchical, systematic and supervisory way and provides an end-to-end solution for the problem. This paper also derives efficient variational inference and learning algorithms for the posterior of the latent variables and model parameters. It is demonstrated through experiments with over 200k images from Flickr that the proposed method significantly outperforms the methods in previous works.Comment: IEEE International Conference on Big Data 201

On Evolution of the Pair-Electromagnetic Pulse of a Charge Black Hole

Using hydrodynamic computer codes, we study the possible patterns of relativistic expansion of an enormous pair-electromagnetic-pulse (P.E.M. pulse); a hot, high density plasma composed of photons, electron-positron pairs and baryons deposited near a charged black hole (EMBH). On the bases of baryon-loading and energy conservation, we study the bulk Lorentz factor of expansion of the P.E.M. pulse by both numerical and analytical methods.Comment: A&A macros, 2 pages, 1 figure and postscrit file. To appear in A&A Suppl. Series, Proceeding of Rome98 GRB workshop, ed. L. Pira and F. Fronter

Coded Wireless Video Broadcast/Multicast

Advancements in video coding, compact media display, and communication devices, particularly in emerging broadband wireless access networks, have created many foreseeable and exciting applications of video broadcast/multicast over the wireless meidum. For efficient and robust wireless video broadcast/multicast under fading, this thesis presents and examines a novel cross-layer framework that exploits the interplay between applying protections on a successively refinable video source and transmitting through a layered broadcast/multicast channel. The framework is realistically achieved and evaluated by using multiple description coding (MDC) on a scalable video source and using superposition coding (SPC) for layered broadcast/multicast transmissions. An analytical model using the total received/recovered video bitstreams from each coded wireless broadcast/multicast signal is developed, which serves as a metric of video quality for the system analysis and optimization. An efficient methodology has demonstrated that optimal power allocations and modulation selections can be practically determined to improve the broadcast/multicast video quality. From the information-theoretical perspective, a general closed-form formula is derived for the end-to-end distortion analysis of the proposed framework, which is applicable to any (n, k) protection code applied on a successive refinable source with a Gaussian distribution over layered Gaussian broadcast channels. The results reveal the scenarios for the proposed framework to lead to a lower distortion than a legacy system without any protection. By analyzing the characteristics of the closed-form formula, an efficient O(n log n) algorithm is developed to determine optimal k values in the (n, k) protection codes that minimize the distortion under the framework. Finally, a cross-layer design of logical SPC modulation is introduced to achieve layered broadcast/multicast for scalable video. It serves as an alternative for practically implementing the proposed framework of coded wireless video broadcast/multicast, if the hardware-based SPC component is not available in a wireless system. In summary, the thesis presents comprehensive analyses, simulations, and experiments to understand, investigate, and justify the effectiveness of the proposed cross-layer framework of coded wireless video broadcast/multicast. More importantly, this thesis contributes to the advancement in the related fields of communication engineering and information theory by introducing a new design dimension in terms of protection. This is unique when compared to previously-reported layered approaches that are often manipulating conventional parameters alone such as power and modulation scheme. The impact of this dimension was unapparent in the past, but is now proven as an effective means to enable high-quality, efficient, and robust wireless video broadcast/multicast for promising media applications

Evaluating the robustness of an active network management function in an operational environment

This paper presents the integration process of a distribution network Active Network Management (ANM) function within an operational environment in the form of a Micro-Grid Laboratory. This enables emulation of a real power network and enables investigation into the effects of data uncertainty on an online and automatic ANM algorithm's control decisions. The algorithm implemented within the operational environment is a Power Flow Management (PFM) approach based around the Constraint Satisfaction Problem (CSP). This paper show the impact of increasing uncertainty, in the input data available for an ANM scheme in terms of the variation in control actions. The inclusion of a State Estimator (SE), with known tolerances is shown to improve the ANM performance

What Sentiment and Fun Facts We Learnt Before FIFA World Cup Qatar 2022 Using Twitter and AI

Twitter is a social media platform bridging most countries and allows real-time news discovery. Since the tweets on Twitter are usually short and express public feelings, thus provide a source for opinion mining and sentiment analysis for global events. This paper proposed an effective solution, in providing a sentiment on tweets related to the FIFA World Cup. At least 130k tweets, as the first in the community, are collected and implemented as a dataset to evaluate the performance of the proposed machine learning solution. These tweets are collected with the related hashtags and keywords of the Qatar World Cup 2022. The Vader algorithm is used in this paper for sentiment analysis. Through the machine learning method and collected Twitter tweets, we discovered the sentiments and fun facts of several aspects important to the period before the World Cup. The result shows people are positive to the opening of the World Cup

A Model-Free Sampling Method for Estimating Basins of Attraction Using Hybrid Active Learning (HAL)

Understanding the basins of attraction (BoA) is often a paramount consideration for nonlinear systems. Most existing approaches to determining a high-resolution BoA require prior knowledge of the system's dynamical model (e.g., differential equation or point mapping for continuous systems, cell mapping for discrete systems, etc.), which allows derivation of approximate analytical solutions or parallel computing on a multi-core computer to find the BoA efficiently. However, these methods are typically impractical when the BoA must be determined experimentally or when the system's model is unknown. This paper introduces a model-free sampling method for BoA. The proposed method is based upon hybrid active learning (HAL) and is designed to find and label the "informative" samples, which efficiently determine the boundary of BoA. It consists of three primary parts: 1) additional sampling on trajectories (AST) to maximize the number of samples obtained from each simulation or experiment; 2) an active learning (AL) algorithm to exploit the local boundary of BoA; and 3) a density-based sampling (DBS) method to explore the global boundary of BoA. An example of estimating the BoA for a bistable nonlinear system is presented to show the high efficiency of our HAL sampling method.Comment: Update: 1) add the schematic of the magnet-induced bistable system, 2) emphasize that the proposed method can be implemented when the system's model is unknown. 6 pages, 5 figures, 2 table

Comparison between the Temperature Measurements by TIMED/SABER and Lidar in the Mid-Latitude

Comparisons of monthly-mean nighttime temperature profiles observed by the Sodium Lidar at Colorado State University and TIMED/SABER over passes are made. In the altitude range from 85 km to about 100 km, the two observations are in excellent agreement. Though within each other s error bars, important differences occur below 85 km in the entire year and above 100 km in the summer season. Possible reasons for these difference are high photon noise below 85 km in lidar observations, and less than accurate assumptions in the concentration of important chemical species like oxygen (and its quenching rate) in the SABER retrieval above 100 km. However, the two techniques both show the two-level mesopause thermal structure, with the times of change from one level to the other in excellent agreement. Comparison indicates that the high-level (winter) mesopause altitudes are also in excellent agreement between the two observations, though some difference may exist in the low-level (summer) mesopause altitudes between ground-based and satellite-borne data