SHRP - Secure Hybrid Routing Protocol over Hierarchical Wireless Sensor Networks

A data collection via secure routing in wireless sensor networks (WSNs) has given attention to one of security issues. WSNs pose unique security challenges due to their inherent limitations in communication and computing, which makes vulnerable to various attacks. Thus, how to gather data securely and efficiently based on routing protocol is an important issue of WSNs. In this paper, we propose a secure hybrid routing protocol, denoted by SHRP, which combines the geographic based scheme and hierarchical scheme. First of all, SHRP differentiates sensor nodes into two categories, nodes with GPS (NG) and nodes with antennas (NA), to put different roles. After proposing a new clustering scheme, which uses a new weight factor to select cluster head efficiently by using energy level, center weight and mobility after forming cluster, we propose routing scheme based on greedy forwarding. The packets in SHRP are protected based on symmetric and asymmetric cryptosystem, which provides confidentiality, integrity and authenticity. The performance analyses are done by using NS2 and show that SHRP could get better results of packet loss rate, delivery ratio, end to end delay and network lifetime compared to the well known previous schemes

6MapNet: Representing soccer players from tracking data by a triplet network

Although the values of individual soccer players have become astronomical, subjective judgments still play a big part in the player analysis. Recently, there have been new attempts to quantitatively grasp players' styles using video-based event stream data. However, they have some limitations in scalability due to high annotation costs and sparsity of event stream data. In this paper, we build a triplet network named 6MapNet that can effectively capture the movement styles of players using in-game GPS data. Without any annotation of soccer-specific actions, we use players' locations and velocities to generate two types of heatmaps. Our subnetworks then map these heatmap pairs into feature vectors whose similarity corresponds to the actual similarity of playing styles. The experimental results show that players can be accurately identified with only a small number of matches by our method.Comment: 12 pages, 4 figures, In 8th Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA21

Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM

As artificial intelligence spreads out to numerous fields, the application of AI to sports analytics is also in the spotlight. However, one of the major challenges is the difficulty of automated acquisition of continuous movement data during sports matches. In particular, it is a conundrum to reliably track a tiny ball on a wide soccer pitch with obstacles such as occlusion and imitations. Tackling the problem, this paper proposes an inference framework of ball trajectory from player trajectories as a cost-efficient alternative to ball tracking. We combine Set Transformers to get permutation-invariant and equivariant representations of the multi-agent contexts with a hierarchical architecture that intermediately predicts the player ball possession to support the final trajectory inference. Also, we introduce the reality loss term and postprocessing to secure the estimated trajectories to be physically realistic. The experimental results show that our model provides natural and accurate trajectories as well as admissible player ball possession at the same time. Lastly, we suggest several practical applications of our framework including missing trajectory imputation, semi-automated pass annotation, automated zoom-in for match broadcasting, and calculating possession-wise running performance metrics

NanoStriDE: normalization and differential expression analysis of NanoString nCounter data

<p>Abstract</p> <p>Background</p> <p>The nCounter analysis system (NanoString Technologies, Seattle, WA) is a technology that enables the digital quantification of multiplexed target RNA molecules using color-coded molecular barcodes and single-molecule imaging. This system gives discrete counts of RNA transcripts and is capable of providing a high level of precision and sensitivity at less than one transcript copy per cell.</p> <p>Results</p> <p>We have designed a web application compatible with any modern web browser that accepts the raw count data produced by the NanoString nCounter analysis system, normalizes it according to guidelines provided by NanoString Technologies, performs differential expression analysis on the normalized data, and provides a heatmap of the results from the differential expression analysis.</p> <p>Conclusion</p> <p>NanoStriDE allows biologists to take raw data produced by a NanoString nCounter analysis system and easily interpret differential expression analysis of this data represented through a heatmap. NanoStriDE is freely accessible to use on the NanoStriDE website and is available to use under the GPL v2 license.</p

Integrated In-vehicle Monitoring System Using 3D Human Pose Estimation and Seat Belt Segmentation

Recently, along with interest in autonomous vehicles, the importance of monitoring systems for both drivers and passengers inside vehicles has been increasing. This paper proposes a novel in-vehicle monitoring system the combines 3D pose estimation, seat-belt segmentation, and seat-belt status classification networks. Our system outputs various information necessary for monitoring by accurately considering the data characteristics of the in-vehicle environment. Specifically, the proposed 3D pose estimation directly estimates the absolute coordinates of keypoints for a driver and passengers, and the proposed seat-belt segmentation is implemented by applying a structure based on the feature pyramid. In addition, we propose a classification task to distinguish between normal and abnormal states of wearing a seat belt using results that combine 3D pose estimation with seat-belt segmentation. These tasks can be learned simultaneously and operate in real-time. Our method was evaluated on a private dataset we newly created and annotated. The experimental results show that our method has significantly high performance that can be applied directly to real in-vehicle monitoring systems.Comment: AAAI 2022 workshop AI for Transportation accepte

Normal modes of coupled vortex gyration in two spatially separated magnetic nanodisks

We found from analytical derivations and micromagnetic numerical simulations that there exist two distinct normal modes in apparently complex vortex gyrotropic motions in two dipolar-coupled magnetic nanodisks. The normal modes have characteristic higher and lower single angular eigenfrequencies with their own elliptical orbits elongated along the x (bonding axis) and y axes, respectively. The superposition of the two normal modes results in coupled vortex gyrations, which depend on the relative vortex-state configuration in a pair of dipolar-coupled disks. This normal-mode representation is a simple means of understanding the observed complex vortex gyrations in two or more dipolar-interacting disks of various vortex-state configurations.Comment: 18 pages, 3 figures, 1 tabl

Structure-Property Relationship of Amyloidogenic Prion Nanofibrils

The structure and its property for the prion nanofibrils, which exhibit self-assembled steric zipper, amyloid fibrils, are described in this chapter. There is the belief of origin for the infectiousness of the prion can be its molecular structure. It is due to the amyloid toxicity, which is related to its beta sheet rich molecular structure and self-aggregated long fibrils. There is evidence that the difference between PrPc and PrPsc is transitioned beta sheet from alpha helix to self-assemble and then to the amyloidogenic fibrils. Therefore, the scope of this chapter is the amyloidogenic structural characteristics of prion fibrils and its relationship to the property. The molecular structural characteristics can be changed by properties such as affinity, toxicity, infectivity, and so on, so this is a key factor to understand the origin of prion disease and develop the therapeutic strategy. One of the main properties of amyloid fibrils that we want to describe here is mechanical property such as dynamic property and material property for prion nanofibrils. This chapter can shed light on understanding the infectious characteristics of prion and the relationship of its molecular structures