A Festival-Wide Social Network Using 2D Barcodes, Mobile Phones and Situated Displays

2011 ◽  
Vol 3 (3) ◽  
pp. 14-30 ◽  
Author(s):  
Jakob Eg Larsen ◽  
Arkadiusz Stopczynski
Keyword(s):  
Social Network ◽  
Mobile Phones ◽  
Low Cost ◽  
The Novel ◽  
Client Application ◽  
Mobile Client ◽  
Music Festival ◽  
Network Applications ◽  
Network Interaction ◽  
Novel Approach

This paper reports on the authors’ experiences with an exploratory prototype festival-wide social network. Unique 2D barcodes were applied to wristbands and mobile phones to uniquely identify the festival participants at the CO2PENHAGEN music festival in Denmark. The authors describe experiences from initial use of a set of social network applications involving participant profiles, a microblog and images shared on situated displays, and competitions created for the festival. The pilot study included 73 participants, each creating a unique profile. The novel approach had potential to enable anyone at the festival to participate in the festival-wide social network, as participants did not need any special hardware or mobile client application to be involved. The 2D barcodes was found to be a feasible low-cost approach for unique participant identification and social network interaction. Implications for the design of future systems of this nature are discussed.

scholarly journals A classification method for social information of sellers on social network

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Haoliang Cui ◽  
Shuai Shao ◽  
Shaozhang Niu ◽  
Chengjie Shi ◽  
Lingyu Zhou
Keyword(s):  
Deep Learning ◽  
Social Network ◽  
Mobile Phones ◽  
Classification Scheme ◽  
Social Information ◽  
Operating Environment ◽  
Network Applications ◽  
Text Information ◽  
Model Training ◽  
Deep Learning Model

AbstractSocial e-commerce has been a hot topic in recent years, with the number of users increasing year by year and the transaction money exploding. Unlike traditional e-commerce, the main activities of social e-commerce are on social network apps. To classify sellers by the merchandise, this article designs and implements a social network seller classification scheme. We develop an app, which runs on the mobile phones of the sellers and provides the operating environment and automated assistance capabilities of social network applications. The app can collect social information published by the sellers during the assistance process, uploads to the server to perform model training on the data. We collect 38,970 sellers’ information, extract the text information in the picture with the help of OCR, and establish a deep learning model based on BERT to classify the merchandise of sellers. In the final experiment, we achieve an accuracy of more than 90%, which shows that the model can accurately classify sellers on a social network.

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

Going digital on low-cost mobile phones in Bangladesh

2011 ◽  
Author(s):  
Christopher S. Walsh ◽  
Tom Power
Keyword(s):  
Mobile Phones ◽  
Low Cost

Exploring normative perceptions and misperceptions of private, environmentally impactful behaviours

2020 ◽  
Author(s):  
Elaine Gallagher ◽  
Bas Verplanken ◽  
Ian Walker
Keyword(s):  
Social Norms ◽  
Behaviour Change ◽  
Social Contexts ◽  
The Novel ◽  
Normative Influence ◽  
Change Mechanism ◽  
Novel Approach ◽  
Classical Studies ◽  
Referent Group

Social norms have been shown to be an effective behaviour change mechanism across diverse behaviours, demonstrated from classical studies to more recent behaviour change research. Much of this research has focused on environmentally impactful actions. Social norms are typically utilised for behaviour change in social contexts, which facilitates the important element of the behaviour being visible to the referent group. This ensures that behaviours can be learned through observation and that deviations from the acceptable behaviour can be easily sanctioned or approved by the referent group. There has been little focus on how effective social norms are in private or non-social contexts, despite a multitude of environmentally impactful behaviours occurring in the home, for example. The current study took the novel approach to explore if private behaviours are important in the context of normative influence, and if the lack of a referent groups results in inaccurate normative perceptions and misguided behaviours. Findings demonstrated variance in normative perceptions of private behaviours, and that these misperceptions may influence behaviour. These behaviours are deemed to be more environmentally harmful, and respondents are less comfortable with these behaviours being visible to others, than non-private behaviours. The research reveals the importance of focusing on private behaviours, which have been largely overlooked in the normative influence literature.

scholarly journals Pocket MUSE: an affordable, versatile and high-performance fluorescence microscope using a smartphone

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Yehe Liu ◽  
Andrew M. Rollins ◽  
Richard M. Levenson ◽  
Farzad Fereidouni ◽  
Michael W. Jenkins
Keyword(s):  
High Performance ◽  
Point Of Care ◽  
Low Cost ◽  
Consumer Electronics ◽  
Practical Implementation ◽  
The Novel ◽  
Point Of Care Diagnostics ◽  
Optical Module ◽  
Optical Configuration ◽  
User Friendly

AbstractSmartphone microscopes can be useful tools for a broad range of imaging applications. This manuscript demonstrates the first practical implementation of Microscopy with Ultraviolet Surface Excitation (MUSE) in a compact smartphone microscope called Pocket MUSE, resulting in a remarkably effective design. Fabricated with parts from consumer electronics that are readily available at low cost, the small optical module attaches directly over the rear lens in a smartphone. It enables high-quality multichannel fluorescence microscopy with submicron resolution over a 10× equivalent field of view. In addition to the novel optical configuration, Pocket MUSE is compatible with a series of simple, portable, and user-friendly sample preparation strategies that can be directly implemented for various microscopy applications for point-of-care diagnostics, at-home health monitoring, plant biology, STEM education, environmental studies, etc.

scholarly journals A Novel Approach to EEG Speech Activity Detection with Visual Stimuli and Mobile BCI

2021 ◽  
Vol 11 (2) ◽  
pp. 674
Author(s):  
Marianna Koctúrová ◽  
Jozef Juhár
Keyword(s):  
Visual Stimuli ◽  
Computer Interface ◽  
Single Subject ◽  
Detection Accuracy ◽  
The Novel ◽  
Activity Detection ◽  
Speech Activity ◽  
Novel Approach ◽  
Eeg Data ◽  
Speech Activity Detection

With the ever-progressing development in the field of computational and analytical science the last decade has seen a big improvement in the accuracy of electroencephalography (EEG) technology. Studies try to examine possibilities to use high dimensional EEG data as a source for Brain to Computer Interface. Applications of EEG Brain to computer interface vary from emotion recognition, simple computer/device control, speech recognition up to Intelligent Prosthesis. Our research presented in this paper was focused on the study of the problematic speech activity detection using EEG data. The novel approach used in this research involved the use visual stimuli, such as reading and colour naming, and signals of speech activity detectable by EEG technology. Our proposed solution is based on a shallow Feed-Forward Artificial Neural Network with only 100 hidden neurons. Standard features such as signal energy, standard deviation, RMS, skewness, kurtosis were calculated from the original signal from 16 EEG electrodes. The novel approach in the field of Brain to computer interface applications was utilised to calculated additional set of features from the minimum phase signal. Our experimental results demonstrated F1 score of 86.80% and 83.69% speech detection accuracy based on the analysis of EEG signal from single subject and cross-subject models respectively. The importance of these results lies in the novel utilisation of the mobile device to record the nerve signals which can serve as the stepping stone for the transfer of Brain to computer interface technology from technology from a controlled environment to the real-life conditions.

ChemInform Abstract: The Novel Approach to Indole Alkaloids by Using Pd(II)-Catalyzed Cyclization.

ChemInform ◽  
2015 ◽  
Vol 46 (17) ◽  
pp. no-no
Author(s):  
Hajime Yokoyama ◽  
Takayoshi Kubo ◽  
Yosuke Matsumura ◽  
Junichi Hosokawa ◽  
Masahiro Miyazawa ◽  
...  
Keyword(s):  
Indole Alkaloids ◽  
The Novel ◽  
Novel Approach

scholarly journals Caffeine-Induced Effects on Human Skeletal Muscle Contraction Time and Maximal Displacement Measured by Tensiomyography

Nutrients ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 815
Author(s):  
Przemysław Domaszewski ◽  
Paweł Pakosz ◽  
Mariusz Konieczny ◽  
Dawid Bączkowicz ◽  
Ewa Sadowska-Krępa
Keyword(s):  
Skeletal Muscle ◽  
Muscle Activation ◽  
Electric Pulse ◽  
Professional Athletes ◽  
Mechanical Activity ◽  
The Novel ◽  
Contraction Time ◽  
Novel Approach ◽  
Skeletal Muscle Contraction ◽  
Maximal Displacement

Studies on muscle activation time in sport after caffeine supplementation confirmed the effectiveness of caffeine. The novel approach was to determine whether a dose of 9 mg/kg/ body mass (b.m.) of caffeine affects the changes of contraction time and the displacement of electrically stimulated muscle (gastrocnemius medialis) in professional athletes who regularly consume products rich in caffeine and do not comply with the caffeine discontinuation period requirements. The study included 40 professional male handball players (age = 23.13 ± 3.51, b.m. = 93.51 ± 15.70 kg, height 191 ± 7.72, BMI = 25.89 ± 3.10). The analysis showed that in the experimental group the values of examined parameters were significantly reduced (p ≤ 0.001) (contraction time: before = 20.60 ± 2.58 ms/ after = 18.43 ± 3.05 ms; maximal displacement: before = 2.32 ± 0.80 mm/after = 1.69 ± 0.51 mm). No significant changes were found in the placebo group. The main achievement of this research was to demonstrate that caffeine at a dose of 9 mg/kg in professional athletes who regularly consume products rich in caffeine has a direct positive effect on the mechanical activity of skeletal muscle stimulated by an electric pulse.

Core–Shell Chain-Like Cu@Ni Composite with Dual Absorption Peaks to Improve Microwave Absorption Properties

NANO ◽  
2018 ◽  
Vol 13 (05) ◽  
pp. 1850052
Author(s):  
Yuanyuan Zhou ◽  
Jianying Deng ◽  
Shimei Li ◽  
Zefeng Li
Keyword(s):  
Hydrothermal Reaction ◽  
Low Cost ◽  
Electromagnetic Properties ◽  
Formation Mechanisms ◽  
Core Shell ◽  
The Novel ◽  
Redox Potentials ◽  
X Ray Diffraction ◽  
Ni Alloy ◽  
Absorbing Material

Core–shell Cu@Ni chains were successfully synthesized through a mild hydrothermal reaction. The morphology, structure and microwave electromagnetic properties of the composite were then characterized by X-ray diffraction, energy-dispersive spectroscopy, scanning electron microscopy and vector network analysis. The formation mechanisms of the core–shell structure and one-dimensional chains were ascribed to the varying redox potentials of Cu and Ni ions and the magnetic dipole–dipole attraction. Furthermore, a minimal reflection loss (RL) of [Formula: see text]20.7[Formula: see text]dB was observed at 9.6[Formula: see text]GHz with a thickness of 2.0[Formula: see text]mm and the effective absorption ([Formula: see text]10[Formula: see text]dB, 90% microwave attenuation) bandwidth can be adjusted between 5.2[Formula: see text]GHz and 16.6[Formula: see text]GHz for the thin absorber thickness of 2.0–4.0[Formula: see text]mm. The novel core–shell chain-like Cu@Ni alloy can be used as a promising absorbing material because it shows numerous features such as thin thickness, strong absorption, low cost and lightweight.

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