Understanding the Employment Status of Gig-Workers in China’s Sharing Economy Era–An Empirical Legal Study

2019 ◽  
Vol 10 (3) ◽  
Author(s):  
Shanyun Xiao
Keyword(s):  
Mobile Applications ◽  
Employment Status ◽  
Sharing Economy ◽  
The Internet ◽  
Court Cases ◽  
Legal Study ◽  
Empirical Results ◽  
Domestic Practices ◽  
Employment Legislation

Abstract The prevalence of the Internet Plus model and mobile applications have brought people into the era of sharing economy, thus accelerating the generation of the “gig-worker.” Foreign experiences have tended to classify gig-workers as employees or as an additional employment category. However, reviewing China’s domestic practices, employment legislation is not enough to keep up with this innovative working style because the work classification and supporting mechanisms for gig-workers have not yet been explicated. This paper identifies the major types of gig-workers that have arisen and investigates 110 court cases to better understand the employment status of gig-workers in China. The empirical results indicate that the judgements of similar facts are diverse in the absence of a unified employment standard. Therefore, it is recommended that the work classification of gig-workers be clarified, lawful access to benefit plans and work protection system be safeguarded, and burden of accident liabilities be fairly distributed.

ASPECTS IN BUILDING A COMPANY WEB-SITE AND ITS ROLE FOR THE DEVELOPMENT OF BUSINESS

2018 ◽  
pp. 117-124
Author(s):  
Petar Halachev ◽  
Victoria Radeva ◽  
Albena Nikiforova ◽  
Miglena Veneva
Keyword(s):  
Life Cycle ◽  
Web Site ◽  
The Internet ◽  
A Company ◽  
The Web ◽  
Design Construction ◽  
Made In ◽  
Site Types

This report is dedicated to the role of the web site as an important tool for presenting business on the Internet. Classification of site types has been made in terms of their application in the business and the types of structures in their construction. The Models of the Life Cycle for designing business websites are analyzed and are outlined their strengths and weaknesses. The stages in the design, construction, commissioning, and maintenance of a business website are distinguished and the activities and requirements of each stage are specified.

Effectiveness of Supervised Classification Models for Hate Speech on Twitter

2020 ◽  
Author(s):  
Kunal Srivastava ◽  
Ryan Tabrizi ◽  
Ayaan Rahim ◽  
Lauryn Nakamitsu
Keyword(s):  
Supervised Classification ◽  
Hate Speech ◽  
The Internet ◽  
Classification Models ◽  
Personal Attack ◽  
Political Beliefs ◽  
The Many ◽  
Primary Medium ◽  
Offensive Speech

<div> <div> <div> <p>Abstract </p> <p>The ceaseless connectivity imposed by the internet has made many vulnerable to offensive comments, be it their physical appearance, political beliefs, or religion. Some define hate speech as any kind of personal attack on one’s identity or beliefs. Of the many sites that grant the ability to spread such offensive speech, Twitter has arguably become the primary medium for individuals and groups to spread these hurtful comments. Such comments typically fail to be detected by Twitter’s anti-hate system and can linger online for hours before finally being taken down. Through sentiment analysis, this algorithm is able to distinguish hate speech effectively through the classification of sentiment. </p> </div> </div> </div>

Update of the last 2 years on the impact of the internet and social networks on the management of type 2 diabetes mellitus: simple review. (Preprint)

2020 ◽  
Author(s):  
Mayli Lañas-Navarro ◽  
Jose Ipanaque-Calderon Sr ◽  
Fiorela E Solano
Keyword(s):  
Social Networks ◽  
Mobile Applications ◽  
Health Personnel ◽  
Online Courses ◽  
The Internet ◽  
Diabetic Patients ◽  
Bibliographic Search ◽  
Use Of The Internet ◽  
And Control ◽  
The Impact

BACKGROUND Research on the use of the Internet in the medical field is experiencing many advances, including mobile applications, social networks, telemedicine. Its implementation in medical care and comprehensive patient management is a much discussed topic at present. OBJECTIVE This narrative review aims to understand the impact of the internet and social networks on the management of diabetes, both for patients and medical staff. METHODS The bibliographic search was carried out in the databases Pubmed, Virtual Health Library (VHL) and Lilacs between 2018 to 2020. RESULTS Multiple mobile applications have been created for the help and control of diabetic patients, as well as the implementation of online courses, improving the knowledge of health personnel applying them in the field of telemedicine. CONCLUSIONS The use of the Internet and social networks brings many benefits for both the diabetic patient and the health personnel, offering advantages for both.

Design and development of an intelligent system based on the Internet of Things for the early detection of forest fires

2022 ◽  
Vol 12 (2) ◽  
pp. 0-0
Keyword(s):  
Neural Network ◽  
Early Detection ◽  
Forest Fires ◽  
Mobile Applications ◽  
Intelligent System ◽  
The Internet ◽  
Scientific Practices ◽  
Depth Analysis ◽  
Neural Network Algorithm ◽  
The Internet Of Things

Automatic environmental monitoring is a field that encompasses several scientific practices for the assessment of risks that may negatively impact a given environment, such as the forest. A forest is a natural environment that hosts various forms of plant and animal life, so preserving the forest is a top priority. To this end, the authors of this paper will focus on the development of an intelligent system for the early detection of forest fires, based on an IoT solution. This latter will thus facilitate the exploitation of the functionalities offered by the Cloud and mobile applications. Detecting and predicting forest fires with accuracy is a difficult task that requires machine learning and an in-depth analysis of environmental conditions. This leads the authors to adopt the forward neural network algorithm by highlighting its contribution through real experiments, performed on the prototype developed in this paper.

Classification of soils of Russia: Discussion on the internet site

2010 ◽  
Vol 43 (12) ◽  
pp. 1344-1350 ◽  
Author(s):  
M. I. Gerasimova ◽  
S. F. Khokhlov
Keyword(s):  
The Internet ◽  
Internet Site

scholarly journals SEMANTIC CLASSIFICATION OF METAPHORS IN UKRAINIAN AND ENGLISH INSCRIPTIONS ON CLOTHING

2021 ◽  
pp. 23-33
Author(s):  
Natalia STRIUK
Keyword(s):  
The Internet ◽  
Semantic Classification ◽  
Comparative Aspect ◽  
Figure Of Speech ◽  
Similar Images

The present research is an attempt to analyse metaphors in English and Ukrainian clothing inscriptions in a comparative aspect. The study focuses on providing a sufficient semantic classification of this versatile figure of speech in the discourse that has never been analysed in terms of metaphors. It deals with English and Ukrainian metaphorical inscriptions on clothing harvested on the Internet over a two-year period (2017-2019). The paper shows that metaphorisation is unevenly typical of English and Ukrainian linguocultural environments. The peculiarities of the source from which the units under analysis were collected allows us to identify seven main vehicle-driven categories of metaphors employed in clothing inscriptions: anthropic, zoomorphic, botanomorphic, creaturemorphic, artefactomorphic, ecomorphic and sensory. The research proves that both English and Ukrainian metaphorical clothing inscriptions have their peculiar sources; moreover, even if metaphors are built on the same or similar images, the focus is usually quite different. This study argues that metaphors on clothing inscriptions can serve as an applicable source to study social priorities, values and tendencies of two different European linguocultural environments. The outcome of the research can be used as an interesting material for sociolinguistics and linguocultural studies.

scholarly journals Machine learning: Enhancing the Perception of the Computer

2020 ◽  
Vol 9 (4) ◽  
pp. 758-761
Keyword(s):  
Machine Learning ◽  
Computer Training ◽  
Internet Traffic ◽  
The Internet ◽  
Popular Method ◽  
Exponential Increase ◽  
Computer Teaching ◽  
Traffic Detection ◽  
The Web

The advancement of technology and networking allows the use of the Web incredibly important. There is thus an exponential increase in data and information via the Internet. This flow thus is a beneficial field of study which can be defined accurately. Internet traffic detection is a very popular method of identifying information. Although so many methods have been successfully developed for classifying internet traffic, computer training technology among them is most popular. A short study of the classification of Internet traffic on various managed and non-regulated computer teaching systems was undertaken by many researchers. This paper will give various ideas to the other researcher’s and help them to learn a lot about machine learning

scholarly journals CRESS: Framework for Vulnerability Assessment of Attack Scenarios in Hardware Reverse Engineering

2021 ◽  
Author(s):  
Matthias Ludwig ◽  
Alexander Hepp ◽  
Michaela Brunner ◽  
Johanna Baehr
Keyword(s):  
Reverse Engineering ◽  
Autonomous Driving ◽  
The Internet ◽  
Changing Trends ◽  
Remediation Strategies ◽  
The Common ◽  
The One ◽  
Soft And Hardware ◽  
The Internet Of Things

Trust and security of microelectronic systems are a major driver for game-changing trends like autonomous driving or the internet of things. These trends are endangered by threats like soft- and hardware attacks or IP tampering -- wherein often hardware reverse engineering (RE) is involved for efficient attack planning. The constant publication of new RE-related scenarios and countermeasures renders a profound rating of these extremely difficult. Researchers and practitioners have no tools or framework which aid a common, consistent classification of these scenarios. In this work, this rating framework is introduced: the common reverse engineering scoring system (CRESS). The framework allows a general classification of published settings and renders them comparable. We introduce three metrics: exploitability, impact, and a timestamp. For these metrics, attributes are defined which allow a granular assessment of RE on the one hand, and attack requirements, consequences, and potential remediation strategies on the other. The system is demonstrated in detail via five case studies and common implications are discussed. We anticipate CRESS to evaluate possible vulnerabilities and to safeguard targets more proactively.

scholarly journals The ‘gig economy’: employee, self-employed or the need for a special employment regulation?

2017 ◽  
Vol 23 (2) ◽  
pp. 193-205 ◽  
Author(s):  
Adrián Todolí-Signes
Keyword(s):  
Service Providers ◽  
Sharing Economy ◽  
Business Organisation ◽  
Digital Era ◽  
Gig Economy ◽  
New Type ◽  
The One ◽  
Individual Service ◽  
Labour Regulation

The digital era has changed employment relationships dramatically, causing a considerable degree of legal uncertainty as to which rules apply in cyberspace. Technology is transforming business organisation in a way that makes employees – as subordinate workers – less necessary. New types of companies, based on the ‘on-demand economy’ or so-called ‘sharing economy’ and dedicated to connecting customers directly with individual service providers, are emerging. These companies conduct their entire core business through workers that they classify as self-employed. In this context, employment law is facing its greatest challenge, as it has to deal with a very different reality to the one existing when it was created. This article analyses the literature available about the classification of this new type of worker as an employee or as self-employed, concluding that there is a need for a new special labour regulation. It also describes and justifies the bases for this new special labour regulation.

Classifying Mobile Applications Using Word Embeddings

2022 ◽  
Vol 31 (2) ◽  
pp. 1-30
Author(s):  
Fahimeh Ebrahimi ◽  
Miroslav Tushev ◽  
Anas Mahmoud
Keyword(s):  
Mobile Applications ◽  
Empirical Investigation ◽  
Mobile Apps ◽  
Human Subjects ◽  
Sharing Economy ◽  
Support Vector ◽  
Word Embeddings ◽  
Mobile Software ◽  
Vector Machines ◽  
Modern Application

Modern application stores enable developers to classify their apps by choosing from a set of generic categories, or genres, such as health, games, and music. These categories are typically static—new categories do not necessarily emerge over time to reflect innovations in the mobile software landscape. With thousands of apps classified under each category, locating apps that match a specific consumer interest can be a challenging task. To overcome this challenge, in this article, we propose an automated approach for classifying mobile apps into more focused categories of functionally related application domains. Our aim is to enhance apps visibility and discoverability. Specifically, we employ word embeddings to generate numeric semantic representations of app descriptions. These representations are then classified to generate more cohesive categories of apps. Our empirical investigation is conducted using a dataset of 600 apps, sampled from the Education, Health&Fitness, and Medical categories of the Apple App Store. The results show that our classification algorithms achieve their best performance when app descriptions are vectorized using GloVe, a count-based model of word embeddings. Our findings are further validated using a dataset of Sharing Economy apps and the results are evaluated by 12 human subjects. The results show that GloVe combined with Support Vector Machines can produce app classifications that are aligned to a large extent with human-generated classifications.

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