scholarly journals ANALISIS PERBANDINGAN ARUS JENUH PADA PENDEKAT SIMPANG TERLINDUNG DAN TERLAWAN DENGAN METODE MKJI DAN METODE TIME SLICE (STUDI KASUS: SIMPANG SUBITA DAN SIMPANG WARIBANG)

2021 ◽  
Vol 10 (2) ◽  
pp. 385-397
Author(s):  
I Made Kariyana ◽  
Gede Sumarda ◽  
I Gede Aryanta Putra
Keyword(s):  
Time Slice

Sebanyak 33% kepemilikan kendaraan di Provinsi Bali pada tahun 2019 berada di Kota Denpasar, ditambah dengan melintasnya kendaraan dari luar kota untuk bekerja maupun berekreasi ikut membebani jaringan jalan di Kota Denpasar. Hal tersebut menimbulkan permasalahan pada sistem transportasi yaitu mempengaruhi kinerja jaringan jalan khususnya kinerja simpang bersinyal di Kota Denpasar. Kinerja simpang bersinyal dipengaruhi oleh kapasitas dari pendekatnya dimana salah satu faktor yang mempengaruhinya adalah arus jenuh. Penelitian ini bertujuan untuk mengetahui perbandingan arus jenuh pada pendekat terlindung dan terlawan antara Metode MKJI dengan Time Slice. Hasil arus jenuh pada pendekat terlindung di Simpang Subita berdasarkan MKJI adalah 3,629 smp/jam hijau lebih besar 71.18% dibandingkan dengan Metode Time Slice yaitu 2,120 smp/jam hijau, sedangkan hasil arus jenuh pada pendekat terlawan di Simpang Waribang berdasarkan MKJI adalah 1,857 smp/jam hijau lebih kecil 37.49% dibandingkan dengan Metode Time Slice yaitu 2,971 smp/jam hijau.

scholarly journals Community Detection Based on Graph Representation Learning in Evolutionary Networks

2021 ◽  
Vol 11 (10) ◽  
pp. 4497
Author(s):  
Dongming Chen ◽  
Mingshuo Nie ◽  
Jie Wang ◽  
Yun Kong ◽  
Dongqi Wang ◽  
...  
Keyword(s):  
Community Detection ◽  
Network Structure ◽  
Clustering Algorithm ◽  
Laplacian Matrix ◽  
Representation Learning ◽  
Detection Algorithm ◽  
Graph Representation ◽  
Time Slice ◽  
Current Time ◽  
Evolutionary Networks

Aiming at analyzing the temporal structures in evolutionary networks, we propose a community detection algorithm based on graph representation learning. The proposed algorithm employs a Laplacian matrix to obtain the node relationship information of the directly connected edges of the network structure at the previous time slice, the deep sparse autoencoder learns to represent the network structure under the current time slice, and the K-means clustering algorithm is used to partition the low-dimensional feature matrix of the network structure under the current time slice into communities. Experiments on three real datasets show that the proposed algorithm outperformed the baselines regarding effectiveness and feasibility.

scholarly journals Effective Data Transmission and Control Based on Social Communication in Social Opportunistic Complex Networks

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-20 ◽  
Author(s):  
Weiyu Yang ◽  
Jia Wu ◽  
Jingwen Luo
Keyword(s):  
Complex Networks ◽  
Information Transmission ◽  
Interference Cancellation ◽  
Propagation Delay ◽  
Transmission Efficiency ◽  
Successive Interference Cancellation ◽  
Time Slice ◽  
Signal Interference ◽  
Time Signal ◽  
Interference Avoidance

In opportunistic complex networks, information transmission between nodes is inevitable through broadcast. The purpose of broadcasting is to distribute data from source nodes to all nodes in the network. In opportunistic complex networks, it is mainly used for routing discovery and releasing important notifications. However, when a large number of nodes in the opportunistic complex networks are transmitting information at the same time, signal interference will inevitably occur. Therefore, we propose a low-latency broadcast algorithm for opportunistic complex networks based on successive interference cancellation techniques to improve propagation delay. With this kind of algorithm, when the social network is broadcasting, this algorithm analyzes whether the conditions for successive interference cancellation are satisfied between the broadcast links on the assigned transmission time slice. If the conditions are met, they are scheduled at the same time slice, and interference avoidance scheduling is performed when conditions are not met. Through comparison experiments with other classic algorithms of opportunistic complex networks, this method has outstanding performance in reducing energy consumption and improving information transmission efficiency.

Dynamic Time-slice Scaling for Addressing OS Problems Incurred by Main Memory DVFS in Intelligent System

2015 ◽  
Vol 20 (2) ◽  
pp. 157-168 ◽  
Author(s):  
Gangyong Jia ◽  
Guangjie Han ◽  
Jinfang Jiang ◽  
Aohan Li
Keyword(s):  
Intelligent System ◽  
Main Memory ◽  
Time Slice ◽  
Dynamic Time

scholarly journals Consistency of flashbulb memories of September 11 over long delays: Implications for consolidation and wrong time slice hypotheses

2009 ◽  
Vol 61 (4) ◽  
pp. 556-572 ◽  
Author(s):  
Lia Kvavilashvili ◽  
Jennifer Mirani ◽  
Simone Schlagman ◽  
Kerry Foley ◽  
Diana E. Kornbrot
Keyword(s):  
September 11 ◽  
Time Slice

Enabling Transmission-Aware Adaptive Optical Time Slice Switching in Time-Varying Optical Time Sliced Networks

2021 ◽  
Author(s):  
Chen Zhao ◽  
Nan Hua ◽  
Kangqi Zhu ◽  
Jipu Li ◽  
Bofan Yang ◽  
...  
Keyword(s):  
Time Slice ◽  
Time Varying ◽  
Optical Time

scholarly journals Tracking patients healthcare experiences during the COVID-19 outbreak: Topic modeling and sentiment analysis of doctor reviews

2021 ◽  
Vol 9 (3A) ◽  
Author(s):  
Adnan M. Shah ◽  
◽  
Xiangbin Yan ◽  
Samia tariq ◽  
Syed Asad A. Shah ◽  
...  
Keyword(s):  
Quality Of Care ◽  
Sentiment Analysis ◽  
Topic Modeling ◽  
Swot Analysis ◽  
Vaccine Development ◽  
Time Slice ◽  
Healthcare Organizations ◽  
Physician Rating ◽  
Physician Rating Website

Emerging voices of patients in the form of opinions and expectations about the quality of care can improve healthcare service quality. A large volume of patients’ opinions as online doctor reviews (ODRs) are available online to access, analyze, and improve patients’ perceptions. This paper aims to explore COVID-19-related conversations, complaints, and sentiments using ODRs posted by users of the physician rating website. We analyzed 96,234 ODRs of 5,621 physicians from a prominent health rating website in the United Kingdom (Iwantgreatcare.org) in threetime slices (i.e., from February 01 to October 31, 2020). We employed machine learning approach, dynamic topic modeling, to identify prominent bigrams, salient topics and labels, sentiments embedded in reviews and topics, and patient-perceived root cause and strengths, weaknesses, opportunities, and threats (SWOT) analyses to examine SWOT for healthcare organizations. This method finds a total of 30 latent topics with 10 topics across each time slice. The current study identified new discussion topics about COVID-19 occurring from time slice 1 to time slice 3, such as news about the COVID-19 pandemic, violence against the lockdown, quarantine process and quarantine centers at different locations, and vaccine development/treatment to stop virus spread. Sentiment analysis reveals that fear for novel pathogen prevails across all topics. Based on the SWOT analysis, our findings provide a clue for doctors, hospitals, and government officials to enhance patients’ satisfaction and minimize dissatisfaction by satisfying their needs and improve the quality of care during the COVID-19 crisis.

scholarly journals Branching Ratio Measurements of the Predissociation of 12C16O by Time-Slice Velocity-Map Ion Imaging in the Energy Region from 106 250 to 107 800 cm–1

2018 ◽  
Vol 122 (41) ◽  
pp. 8136-8142 ◽  
Author(s):  
Xiaoyu Shi ◽  
Hong Gao ◽  
Qing-Zhu Yin ◽  
Yih-Chung Chang ◽  
Roger C. Wiens ◽  
...  
Keyword(s):  
Energy Region ◽  
Branching Ratio ◽  
Time Slice ◽  
Ion Imaging
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