Impact of imperfect angle estimation on spatial and directional modulation

In this paper, we investigate the impact of imperfect angle estimation (IAE) on spatial and directional modulation (SDM) systems, assuming that the signal experiences line of sight (LoS) propagation. In SDM systems with IAE, the variation is analyzed in detail, when there is a mismatch between the beamforming and precise channel matrices. Based on the union bound and statistics theory, the average bit error probabilities (ABEPs) for both the legitimate user and eavesdropper are derived. In addition, the ergodic rate is also quantified with IAE. Simulation results are presented to show that the achieved theoretical ABEPs are useful in quantifying the potential performance penalty. We also show that the mismatch between the beamforming and precise channel matrices will become greater with the increase in direction measurement error (DME), which affects the detection for both the legitimate user and eavesdropper. On the other hand, due to the effect of IAE, the SDM requires more signal-to-noise ratio (SNR) gain to achieve a stable ergodic secrecy rate

Structured Memetic Automation for Online Human-like Social Behavior Learning

Meme automaton is an adaptive entity that autonomously acquires an increasing level of capability and intelligence through embedded memes evolving independently or via social interactions. This paper begins a study on memetic multiagent system (MeMAS) toward human-like social agents with memetic automaton. We introduce a potentially rich meme-inspired design and operational model, with Darwin's theory of natural selection and Dawkins' notion of a meme as the principal driving forces behind interactions among agents, whereby memes form the fundamental building blocks of the agents' mind universe. To improve the efficiency and scalability of MeMAS, we propose memetic agents with structured memes in this paper. Particularly, we focus on meme selection design where the commonly used elitist strategy is further improved by assimilating the notion of like-attracts-like in the human learning. We conduct experimental study on multiple problem domains and show the performance of the proposed MeMAS on human-like social behavior

A study on like-attracts-like versus elitist selection criterion for human-like social behavior of memetic mulitagent systems

Memetic multi agent system emerges as an enhanced version of multiagent systems with the implementation of meme-inspired computational agents. It aims to evolve human-like behavior of multiple agents by exploiting the Dawkins' notion of a meme and Universal Darwinism. Previous research has developed a computational framework in which a series of memetic operations have been designed for implementing humanlike agents. This paper will focus on improving the human-like behavior of multiple agents when they are engaged in social interactions. The improvement is mainly on how an agent shall learn from others and adapt its behavior in a complex dynamic environment. In particular, we design a new mechanism that supervises how the agent shall select one of the other agents for the learning purpose. The selection is a trade-off between the elitist and like-attracts-like principles. We demonstrate the desirable interactions of multiple agents in two problem domains

On Information Coverage for Location Category Based Point-of-Interest Recommendation

Point-of-interest(POI) recommendation becomes a valuable service in location-based social networks. Based on the norm that similar users are likely to have similar preference of POIs, the current recommendation techniques mainly focus on users' preference to provide accurate recommendation results. This tends to generate a list of homogeneous POIs that are clustered into a narrow band of location categories(like food, museum, etc.) in a city. However, users are more interested to taste a wide range of flavors that are exposed in a global set of location categories in the city.In this paper, we formulate a new POI recommendation problem, namely top-K location category based POI recommendation, by introducing information coverage to encode the location categories of POIs in a city.The problem is NP-hard. We develop a greedy algorithm and further optimization to solve this challenging problem. The experimental results on two real-world datasets demonstrate the utility of new POI recommendations and the superior performance of the proposed algorithms

Influence Maximization with Novelty Decay in Social Networks

Influence maximization problem is to find a set of seed nodes in a social network such that their influence spread is maximized under certain propagation models. A few algorithms have been proposed for solving this problem. However, they have not considered the impact of novelty decay on influence propagation, i.e., repeated exposures will have diminishing influence on users. In this paper, we consider the problem of influence maximization with novelty decay (IMND). We investigate the effect of novelty decay on influence propagation on real-life datasets and formulate the IMND problem. We further analyze the problem properties and propose an influence estimation technique. We demonstrate the performance of our algorithms on four social networks

FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing

Text-to-video editing aims to edit the visual appearance of a source video conditional on textual prompts. A major challenge in this task is to ensure that all frames in the edited video are visually consistent. Most recent works apply advanced text-to-image diffusion models to this task by inflating 2D spatial attention in the U-Net into spatio-temporal attention. Although temporal context can be added through spatio-temporal attention, it may introduce some irrelevant information for each patch and therefore cause inconsistency in the edited video. In this paper, for the first time, we introduce optical flow into the attention module in the diffusion model's U-Net to address the inconsistency issue for text-to-video editing. Our method, FLATTEN, enforces the patches on the same flow path across different frames to attend to each other in the attention module, thus improving the visual consistency in the edited videos. Additionally, our method is training-free and can be seamlessly integrated into any diffusion-based text-to-video editing methods and improve their visual consistency. Experiment results on existing text-to-video editing benchmarks show that our proposed method achieves the new state-of-the-art performance. In particular, our method excels in maintaining the visual consistency in the edited videos.Comment: Project page: https://flatten-video-editing.github.io

A novel Fas ligand plays an important role in cell apoptosis of Crassostrea hongkongensis: molecular cloning, expression profiles and functional identification of ChFasL

BackgroundApoptosis regulates normal development, homeostasis, immune tolerance and response to environmental stress by eliminating unwanted or diseased cells, and plays a key role in non-specific immunity of invertebrates. The exogenous pathway mediated by death receptors and death ligands is a very important pathway for cell apoptosis. Death ligands are mainly members of the tumour necrosis factor (TNF) family, of which FasL is an important member. The deep involvement of FasL in vertebrates cell apoptosis and immunity has been reported many times, but there is limited research on the FasL gene in shellfish, and its functional importance in oyster cell apoptosis and immunity remains unclear.MethodsThe full length of ChFasL was identified and cloned based on the genome of Crassostrea hongkongensis. Quantitative PCR was used to detect the relative expression of ChFasL in different developmental stages and tissues, as well as the changes of relative expression in hemocytes after bacterial infection. The expression position of ChFasL in HEK293T cells was also located by subcellular localization, and the effect of increased recombinant protein content on the activity of reporter genes p53 and p21 was studied by dual-fluorescence reporter gene. Finally, the changes of apoptosis rate in hemocytes after ChFasL silencing was identified by RNA interference technology.ResultsWe identified a novel FasL gene from C. hongkongensis and named it ChFasL. We found that ChFasL has potential N-linked glycosylation site, a transmembrane domain and a TNF region, which was a typical characteristics of TNF family. ChFasL was expressed in all developmental stages of larvae and in all tissues of oysters. After stimulation by V. alginolyticus or S. haemolyticus, its relative expression in hemocytes increased significantly, suggesting that ChFasL was deeply engaged in the immune response process of C. hongkongensis to external microbial stimulation. The results of subcellular localization showed that ChFasL was mainly distributed in the cytoplasm of HEK293T cells. With the overexpression of the recombinant protein pcDNA3 1- ChFasL, the activity of p53 and p21 significantly increased, showing a positive regulatory effect. Moreover, after dsRNA successfully reduced the relative expression of ChFasL, the apoptosis rate of hemocytes was significantly lower than that the dsGFP group.ConclusionThese results comprehensively confirmed the important role of ChFasL in the apoptosis process of C. hongkongensis, which provided the basis and premise for the in-depth understanding of the immune function of apoptosis in molluscs, and also contributed to the research on the pathogenic death mechanism and disease resistance breeding of marine bivalves