Dynamically Adjusting the Mining Capacity in Cryptocurrency with Binary Blockchain

Many cryptocurrencies rely on Blockchain for its operation. Blockchain serves as a public ledger where all the completed transactions can be looked up. To place transactions in the Blockchain, a mining operation must be performed. However, due to a limited mining capacity, the transaction confirmation time is increasing. To mitigate this problem many ideas have been proposed, but they all come with own challenges. We propose a novel parallel mining method that can adjust the mining capacity dynamically depending on the congestion level. It does not require an increase in the block size or a reduction of the block confirmation time. The proposed scheme can increase the number of parallel blockchains when the mining congestion is experienced, which is especially effective under DDoS attack situation. We describe how and when the Blockchain is split or merged, how to solve the imbalanced mining problem, and how to adjust the difficulty levels and rewards. We then show the simulation results comparing the performance of binary blockchain and the traditional single blockchain

Hadoop Performance Analysis Model with Deep Data Locality

Background: Hadoop has become the base framework on the big data system via the simple concept that moving computation is cheaper than moving data. Hadoop increases a data locality in the Hadoop Distributed File System (HDFS) to improve the performance of the system. The network traffic among nodes in the big data system is reduced by increasing a data-local on the machine. Traditional research increased the data-local on one of the MapReduce stages to increase the Hadoop performance. However, there is currently no mathematical performance model for the data locality on the Hadoop. Methods: This study made the Hadoop performance analysis model with data locality for analyzing the entire process of MapReduce. In this paper, the data locality concept on the map stage and shuffle stage was explained. Also, this research showed how to apply the Hadoop performance analysis model to increase the performance of the Hadoop system by making the deep data locality. Results: This research proved the deep data locality for increasing performance of Hadoop via three tests, such as, a simulation base test, a cloud test and a physical test. According to the test, the authors improved the Hadoop system by over 34% by using the deep data locality. Conclusions: The deep data locality improved the Hadoop performance by reducing the data movement in HDFS

sUTM System API at UNLV: Small UAS Traffic Management System API

This file contains the set of APIs for small unmanned aircraft systems (UAS) Traffic Management (sUTM). The sUTM server hosts a web service that allows any software or device that can use the Internet to utilize the server’s sUAS traffic management (sUTM) functions through these application programming interfaces (API). This library was developed as part of the MS thesis by Monetta Shaw in Spring 2016, A web based solution for small unmanned aircraft systems (sUAS) traffic management . The summary of the library and its usage instructions are described in the thesis

Evaluation of the high temperature solid Oxide cells using La0.1Sr0.9Co0.8Fe0.2O3-δ

The performance of the SOCs using La0.1Sr0.9Co0.8Fe0.2O3-δ (LSCF1982) was characterized by I-V measurement and electrochemical impedance spectroscopy (EIS). The distribution function of relaxation times of EIS was used to analyze the polarization resistance of the cells. The fitting was performed using the appropriate equivalent circuit through DRT analysis. Furthermore, we co-electrolyzed CO2 and H2O to obtain H2 / CO syngas as well as water splitting. The composition of syngas was investigated by gas chromatography and controlled by varying in-let gas composition

Development and Validation of a Postpartum Care Mobile Application for First-time Mothers

PURPOSE: The aims of the study were to develop mobile application for postpartum care of first-time mothers and to validate it's effect. METHODS: Using a nonequivalent control group pretest-posttest design, 52 first-time mothers were recruited (26 each in experimental and control) and the experimental group used the mobile application for 6 weeks after delivery. Postpartum self-care knowledge and confidence, infant care knowledge and confidence, and postpartum depressive mood (Edinburgh Postnatal Depression Scale) were measured before discharge from the hospital and 6 weeks later. RESULTS: Women who have used the postpartum care mobile application reported higher levels of postpartum self-care knowledge (p=.030) and confidence (p=.023) infant care knowledge (p=.001) and confidence (p=.004), while scores of postpartum depression (p=.021) were lower than those in the control group. CONCLUSION: The postpartum-care mobile application developed in this research may be effective in reinforcing knowledge and confidence for postpartum self-care and infant care and in reducing postpartum depressive mood

Comprehensive Genome Analysis on the Novel Species Sphingomonas panacis DCY99(T) Reveals Insights into Iron Tolerance of Ginseng

Plant growth-promoting rhizobacteria play vital roles not only in plant growth, but also in reducing biotic/abiotic stress. Sphingomonas panacis DCY99(T) is isolated from soil and root of Panax ginseng with rusty root disease, characterized by raised reddish-brown root and this is seriously affects ginseng cultivation. To investigate the relationship between 159 sequenced Sphingomonas strains, pan-genome analysis was carried out, which suggested genomic diversity of the Sphingomonas genus. Comparative analysis of S. panacis DCY99(T) with Sphingomonas sp. LK11 revealed plant growth-promoting potential of S. panacis DCY99(T) through indole acetic acid production, phosphate solubilizing, and antifungal abilities. Detailed genomic analysis has shown that S. panacis DCY99(T) contain various heavy metals resistance genes in its genome and the plasmid. Functional analysis with Sphingomonas paucimobilis EPA505 predicted that S. panacis DCY99(T) possess genes for degradation of polyaromatic hydrocarbon and phenolic compounds in rusty-ginseng root. Interestingly, when primed ginseng with S. panacis DCY99(T) during high concentration of iron exposure, iron stress of ginseng was suppressed. In order to detect S. panacis DCY99(T) in soil, biomarker was designed using spt gene. This study brings new insights into the role of S. panacis DCY99(T) as a microbial inoculant to protect ginseng plants against rusty root disease

Atomic Resolution Imaging of Rotated Bilayer Graphene Sheets Using a Low kV Aberration-corrected Transmission Electron Microscope

Modern aberration-corrected transmission electron microscope (TEM) with appropriate electron beam energy is able to achieve atomic resolution imaging of single and bilayer graphene sheets. Especially, atomic configuration of bilayer graphene with a rotation angle can be identified from the direct imaging and phase reconstructed imaging since atomic resolution Moir pattern can be obtained successfully at atomic scale using an aberration-corrected TEM. This study boosts a reliable stacking order analysis, which is required for synthesized or artificially prepared multilayer graphene, and lets graphene researchers utilize the information of atomic configuration of stacked graphene layers readily.ope

Risk and protective factors of depression in the general population during the COVID-19 epidemic in Korea

Background: The risk of depression has risen in the general population during the COVID-19 epidemic. This study was conducted to explore risk and protective factors associated with depression among the general population uninfected by COVID-19. Methods: A cross-sectional study was conducted with 1,500 representative South Korean citizens aged 19–65 years through an anonymous online survey. Depression was defined as a Patient Health Questionnaire-9 score of 10 or higher. Other questionnaires included one measuring psycho-behavioural and social changes, and stress, due to COVID-19, a six-item version of the Gratitude Questionnaire (GQ-6), and a three-item version of the UCLA loneliness scale. Results: Of the 1492 participants not infected by COVID-19, 312 (20.9%) exhibited depression. Multiple logistic regression analysis revealed that depression was positively associated with COVID-19-related stress and psycho-behavioural variables such as disturbances in eating and sleeping, younger age, smoking, underlying mental illness, and loneliness scale scores. In contrast, exercise three or more times per week and GQ-6 scale scores were inversely associated with depression. Conclusion: During the COVID-19 pandemic, maintaining daily routines including eating, sleeping, and regular exercise and focusing on gratitude may be important for the prevention of depression. In addition, more attention should be paid to vulnerable populations, including young people, those with mental illnesses, and smokers, who might be more susceptible to depression

Research poster: HTSMA: a hybrid temporal-spatial multi-channel assignment scheme in heterogeneous wireless mesh networks

Research poste