Patrilocality and Child Sex Ratios in India

In multi-level and multi-layered foundations of gendered approaches for understanding the kinship system, son preferences, and male-skewed child sex ratios in India; patriarchy, and patrilineality have received greater attention than patrilocality. To fill this gap, in this study, we construct a measure of patrilocality and examine its association with skewed child sex ratios. We hypothesize that households practice sex selection and daughter discrimination because of patrilocal norms that dictate the later life co-residence between parents and sons. Our findings reveal that the child sex ratio, the sex ratio at birth, and the sex ratio at last birth are positively correlated with the patrilocality rates across states and districts of India. The relationship holds across the multiple robustness checks. Findings, although not surprising, emerge from the robust empirical analyses at a time when child sex ratios continue to worsen in India, notwithstanding the country’s socio-economic progress. We conclude that in the absence of strong social security measures and lack of preference for old-age homes amidst the accepted practice of patrilocality coupled with increasing lower fertility norms, the dependency on sons will continue and further lead to the continuation of sex selection in India.

A Comprehensive Survey on Radio Frequency (RF) Fingerprinting: Traditional Approaches, Deep Learning, and Open Challenges

Fifth generation (5G) networks and beyond envisions massive Internet of Things (IoT) rollout to support disruptive applications such as extended reality (XR), augmented/virtual reality (AR/VR), industrial automation, autonomous driving, and smart everything which brings together massive and diverse IoT devices occupying the radio frequency (RF) spectrum. Along with spectrum crunch and throughput challenges, such a massive scale of wireless devices exposes unprecedented threat surfaces. RF fingerprinting is heralded as a candidate technology that can be combined with cryptographic and zero-trust security measures to ensure data privacy, confidentiality, and integrity in wireless networks. Motivated by the relevance of this subject in the future communication networks, in this work, we present a comprehensive survey of RF fingerprinting approaches ranging from a traditional view to the most recent deep learning (DL) based algorithms. Existing surveys have mostly focused on a constrained presentation of the wireless fingerprinting approaches, however, many aspects remain untold. In this work, however, we mitigate this by addressing every aspect - background on signal intelligence (SIGINT), applications, relevant DL algorithms, systematic literature review of RF fingerprinting techniques spanning the past two decades, discussion on datasets, and potential research avenues - necessary to elucidate this topic to the reader in an encyclopedic manner.

Legal problems of use of compulsory psychiatric treatment in Russia and Belarus

The subject of the research is the problems of legislative regulation of compulsory psychiatric measures in the criminal legislation of the Republic of Belarus and the Russian Federation.The purpose of the article is to confirm or refute the hypothesis that there are defects in legislative regulation that prevent the effective use of compulsory psychiatric treatment. They are not eliminated in the Criminal Codes of the Russian Federation and the Republic of Belarus. Research methodology. On the basis of a system-integrated approach on an interdisciplinary basis, a scientific analysis of special legal and forensic psychiatric scientific literature and interpretation of the criminal legislation of the Republic of Belarus and the Russian Federation were carried out.Main results. An analysis of the Criminal Codes of the Republic of Belarus and the Russian Federation showed that compulsory psychiatric treatment is an independent institution of criminal law, which is regulated in sufficient detail in the national criminal legislation. The article includes a comparative legal analysis of the norms of the criminal legislation of both states (Chapter 14 of the Criminal Code of the Republic of Belarus and Chapter 15 of the Criminal Code of the Russian Federation) that regulate psychiatric coercive measures applied to persons with mental disorders who have committed illegal acts. Based on the results of the study, a number of problems were identified in the legislative regulation of psychiatric compulsory measures in the criminal codes of both states, the authors propose directions for further improvement of the current criminal legislation.Conclusions. The Criminal Codes of the Republic of Belarus and the Russian Federation contain only general criteria for choosing the type of psychiatric measures of a coercive nature, in the most general form, the procedure for their change and termination is provided, they need editorial clarification of their purpose. There is no legislative definition of the concepts of “coercive security measures and treatment” (Chapter 14 of the Criminal Code of the Republic of Belarus) and “compulsory measures of a medical nature” (Chapter 15 of the Criminal Code of the Russian Federation), etc., which causes serious difficulties in law enforcement practice and indicates the need to continue work to improve the current criminal legislation.The terminology used “coercive and security measures and treatment” (Chapter 14 of the Criminal Code of the Republic of Belarus) and “coercive measures of a medical nature” (Chapter 15 of the Criminal Code of the Russian Federation) does not reflect the specifics of these measures, which in their essence and content are exclusively psychiatric measures. The identified problems of legislative regulation of psychiatric compulsory measures in the criminal legislation of both states require their further resolution, and based on the interdisciplinary medico-legal nature of the problems involved, with the obligatory involvement of forensic psychiatrists in their solution.

A Comprehensive Survey on Radio Frequency (RF) Fingerprinting: Traditional Approaches, Deep Learning, and Open Challenges

Fifth generation (5G) networks and beyond envisions massive Internet of Things (IoT) rollout to support disruptive applications such as extended reality (XR), augmented/virtual reality (AR/VR), industrial automation, autonomous driving, and smart everything which brings together massive and diverse IoT devices occupying the radio frequency (RF) spectrum. Along with spectrum crunch and throughput challenges, such a massive scale of wireless devices exposes unprecedented threat surfaces. RF fingerprinting is heralded as a candidate technology that can be combined with cryptographic and zero-trust security measures to ensure data privacy, confidentiality, and integrity in wireless networks. Motivated by the relevance of this subject in the future communication networks, in this work, we present a comprehensive survey of RF fingerprinting approaches ranging from a traditional view to the most recent deep learning (DL) based algorithms. Existing surveys have mostly focused on a constrained presentation of the wireless fingerprinting approaches, however, many aspects remain untold. In this work, however, we mitigate this by addressing every aspect - background on signal intelligence (SIGINT), applications, relevant DL algorithms, systematic literature review of RF fingerprinting techniques spanning the past two decades, discussion on datasets, and potential research avenues - necessary to elucidate this topic to the reader in an encyclopedic manner.

A Comprehensive Survey on Radio Frequency (RF) Fingerprinting: Traditional Approaches, Deep Learning, and Open Challenges

Fifth generation (5G) networks and beyond envisions massive Internet of Things (IoT) rollout to support disruptive applications such as extended reality (XR), augmented/virtual reality (AR/VR), industrial automation, autonomous driving, and smart everything which brings together massive and diverse IoT devices occupying the radio frequency (RF) spectrum. Along with spectrum crunch and throughput challenges, such a massive scale of wireless devices exposes unprecedented threat surfaces. RF fingerprinting is heralded as a candidate technology that can be combined with cryptographic and zero-trust security measures to ensure data privacy, confidentiality, and integrity in wireless networks. Motivated by the relevance of this subject in the future communication networks, in this work, we present a comprehensive survey of RF fingerprinting approaches ranging from a traditional view to the most recent deep learning (DL) based algorithms. Existing surveys have mostly focused on a constrained presentation of the wireless fingerprinting approaches, however, many aspects remain untold. In this work, however, we mitigate this by addressing every aspect - background on signal intelligence (SIGINT), applications, relevant DL algorithms, systematic literature review of RF fingerprinting techniques spanning the past two decades, discussion on datasets, and potential research avenues - necessary to elucidate this topic to the reader in an encyclopedic manner.

Impacts of a health crisis on music festivals: a qualitative approach

PurposeThis research explores the consequences of a health crisis provoked by a pandemic scenario on music festival impacts considered by the stakeholders involved. The purpose of this paper is to identify the perceptions from the stakeholders' point of view (host community, public and private sector) and to identify the impacts generated before and after a health crisis regarding the celebration of a festival.Design/methodology/approachThe study offers a holistic insight into impact research by music festivals. The methodology implemented is based on qualitative techniques. By conducting 20 in-depth interviews with essential stakeholders, it is possible to determine their perceptions of the impact of the event and the effects of a health crisis.FindingsThe results allow detecting a gap between internal and external stakeholders due to poor communication and planning of the event. The results show that a health crisis provokes negative impacts on the economic benefits of events' organisation. However, the cultural city's identity suffers an important damage that it is difficult to overcome. The community and visitors are the stakeholders that suffer a detrimental impact on their experience when attending the festival, considering the security measures. Moreover, results allow us to identify practical implications for event management and planning in a health crisis scenario.Originality/valueThe most important contribution of this research is the theoretical model proposed to analyse stakeholders' perception of the event celebration in a context of a health crisis. The model also considers different moments of the social exchange. The theoretical approaches considered theory of social exchange (SET) and Visitor, Industry, Community and Environment (VICE) models allow analysing the stakeholder's perception of a case study of a music festival (Viña Rock Festival, Spain). The emerging and central role of the cooperation between stakeholders constitutes another notable contribution to the literature.

Design and Development of an Internet of Things (IoT)-Based Anti-Theft System in Museum Cultural Relics Using RFID

Art colonnades and museums all over the world are the first option for individuals to visit for the enhancement of the cultural life of people. To ensure their safety, museums have established numerous cultural security measures. Traditional strategies do not obstruct their pace entirely. They only use a computer in the museum to check individuals at the entrance and exit. Therefore, the authors proposed a gallery anti-stealing device created on the internet-of-things (IoT) technology that ensures security through passive readers/writers of RFID. Radio frequency identification (RFID) remains a system that practices isolated data storing and recovery and offers object tracking with a unique identity code. The system then sends sound and light warning information, while the photographic camera structure is triggered to capture a picture at the same time. The recognition of the accuracy in the hardware component of the device can be additionally enhanced by the use of this technology to increase the safety of museum equipment.

COVID-19 and the Hospitality Industry

The ongoing coronavirus (COVID-19) pandemic and the ensuing public health policy measures to contain its spread have inevitably had profound effects on businesses throughout the world. While the pandemic has impacted every industry in all countries, hospitality is clearly the worst hit. This chapter explores the impact of the pandemic on the hospitality industry by focusing on accommodation and food service businesses in Turkey. By looking at government policies and changes in business activities in these sectors in response to the crisis, the authors discuss the measures policymakers and firms can take to mitigate the devastating impacts of the pandemic. Findings suggest that focusing on creating novel products and processes, collaboration and open innovation, informational and corporate advertising, as well as investment in quality and health security measures and trust building via communication are effective in moving forward with the new normal.

Crafting Strategies of Security Breaches

In recent years, the number of financial technology players and users have increased at a significant rate due to the rapid technological advancement in financial technology. While smart devices are providing more useful features to users, they have also made it possible for cyber threats to migrate from desktops to smart devices. Thus, it is important for smart device users to be aware that their device could be exposed to cyber threats and that users could protect their devices by employing data-centric cyber security measures. This study reveals how financial technology business model responded to the breach phenomenon by employing data-centric protection approaches. The result is very interesting. Data-centric security is very needed as it is capable of protecting data as a whole. It provides a gapless protection, meaning to say, the data are encrypted and classified wherever it moves. With persistent protection and cross-platform operability, data-centric security will eliminate gaps and keep data protected.

IoT Big Data Security, Privacy and Challenges Related to Smart Grid

The highly interconnected network of heterogeneous devices which enables all kinds of communications to take place in an efficient manner is referred to as “IOT.” In the current situation, the data are increasing day by day in size as well as in terms of complexities. These are the big data which are in huge demand in the industrial sectors. Various IT sectors are adopting big data present on IOT for the growth of their companies and fulfilling their requirements. But organizations are facing a lot of security issues and challenges while protecting their confidential data. IOT type systems require security while communications which is required currently by configuration levels of security algorithms, but these algorithms give more priority to functionalities of the applications over security. Smart grids have become one of the major subjects of discussions when the demands for IOT devices increases. The requirements arise related to the generation and transmission of electricity, consumption of electricity being monitored, etc. The system which is responsible to collect heterogeneous data are a complicated structure and some of its major subsystems which they require for smooth communications include log servers, smart meters, appliances which are intelligent, different sensors chosen based on their requirements, actuators with proper and efficient infrastructure. Security measures like collection, storage, manipulations and a massive amount of data retention are required as the system is highly diverse in its architecture and even the heterogeneous IOT devices are interacting with each other. In this article, security challenges and concerns of IOT big data associated with smart grid are discussed along with the new security enhancements for identification and authentications of things in IOT big data environments.