Differentiating criminal networks in the illegal wildlife trade: organized, corporate and disorganized crime

Historically, the poaching of wildlife was portrayed as a small-scale local activity in which only small numbers of wildlife would be smuggled illegally by collectors or opportunists. Nowadays, this image has changed: criminal networks are believed to be highly involved in wildlife trafficking, which has become a significant area of illicit activity. Even though wildlife trafficking has become accepted as a major area of crime and an important topic and criminologists have examined a variety of illegal wildlife markets, research that specifically focusses on the involvement of different criminal networks and their specific nature is lacking. The concept of a ‘criminal network’ or ‘serious organized crime’ is amorphous – getting used interchangeably and describes all crime that is structured rather than solely reflecting crime that fits within normative definitions of ‘organized’ crime. In reality, criminal networks are diverse. As such, we propose categories of criminal networks that are evidenced in the literature and within our own fieldwork: (1) organized crime groups (2) corporate crime groups and (3) disorganized criminal networks. Whereas there are instances when these groups act alone, this article will (also) discuss the overlap and interaction that occurs between our proposed categories and discuss the complicated nature of the involved criminal networks as well as predictions as to the future of these networks

Differentiating criminal networks in the illegal wildlife trade: organized, corporate and disorganized crime

Historically, the poaching of wildlife was portrayed as a small-scale local activity in which only small numbers of wildlife would be smuggled illegally by collectors or opportunists. Nowadays, this image has changed: criminal networks are believed to be highly involved in wildlife trafficking, which has become a significant area of illicit activity. Even though wildlife trafficking has become accepted as a major area of crime and an important topic and criminologists have examined a variety of illegal wildlife markets, research that specifically focusses on the involvement of different criminal networks and their specific nature is lacking. The concept of a ‘criminal network’ or ‘serious organized crime’ is amorphous – getting used interchangeably and describes all crime that is structured rather than solely reflecting crime that fits within normative definitions of ‘organized’ crime. In reality, criminal networks are diverse. As such, we propose categories of criminal networks that are evidenced in the literature and within our own fieldwork: (1) organized crime groups (2) corporate crime groups and (3) disorganized criminal networks. Whereas there are instances when these groups act alone, this article will (also) discuss the overlap and interaction that occurs between our proposed categories and discuss the complicated nature of the involved criminal networks as well as predictions as to the future of these networks

Principles of Neuromorphic Photonics

In an age overrun with information, the ability to process reams of data has become crucial. The demand for data will continue to grow as smart gadgets multiply and become increasingly integrated into our daily lives. Next-generation industries in artificial intelligence services and high-performance computing are so far supported by microelectronic platforms. These data-intensive enterprises rely on continual improvements in hardware. Their prospects are running up against a stark reality: conventional one-size-fits-all solutions offered by digital electronics can no longer satisfy this need, as Moore's law (exponential hardware scaling), interconnection density, and the von Neumann architecture reach their limits. With its superior speed and reconfigurability, analog photonics can provide some relief to these problems; however, complex applications of analog photonics have remained largely unexplored due to the absence of a robust photonic integration industry. Recently, the landscape for commercially-manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. The scientific community has set out to build bridges between the domains of photonic device physics and neural networks, giving rise to the field of \emph{neuromorphic photonics}. This article reviews the recent progress in integrated neuromorphic photonics. We provide an overview of neuromorphic computing, discuss the associated technology (microelectronic and photonic) platforms and compare their metric performance. We discuss photonic neural network approaches and challenges for integrated neuromorphic photonic processors while providing an in-depth description of photonic neurons and a candidate interconnection architecture. We conclude with a future outlook of neuro-inspired photonic processing.Comment: 28 pages, 19 figure

MPR+SP: Towards a Unified MPR-based MANET Extension for OSPF

International audienceHeterogeneous networks and wireless components - fixed routers as well as mobile routers - emerge as wireless mesh networks are being deployed. Such heterogeneity is bound to become more and more present in the near future as mobile ad hoc networking becomes a reality. While it is possible to cope with heterogeneity by employing different routing protocols for the fixed / wired part and for the wireless / ad hoc part of the network, this may lead to sub-optimal performance, e.g. by way of longer routing paths due to these routing protocols sharing prefixes and "connecting" the network only at distinct gateways between the two routing domains. Thus, the establishment of a single unified routing domain, and the use of a single routing protocol, for such heterogeneous networks is desired. OSPF is a natural candidate for this task, due to its wide deployment, its modularity and its similarity with the popular ad hoc routing protocol OLSR. Multiple OSPF extensions for MANETs have therefore been specified by the IETF. This paper introduces a novel OSPF extension for operation on ad hoc networks, MPR+SP, and compares it with the existing OSPF extensions via simulations, which show that MPR+SP outperforms prior art

Toward the distributed implementation of immersive augmented reality architectures on 5G networks

Augmented reality (AR) has been presented lately as one of the key technology fields in which 5G networks can become a disruptive tool, raising interest from both industry and academia. The main goal of this article is to extend the current state of the art of distributed AR studies and implementations by extracting the main AR algorithms' offloading requirements individually. This extension is further achieved by depicting the data flow between these algorithms and their hardware requirements. From the obtained results, we estimate a preliminary set of network key performance indicators (KPIs) for a subset of three examples of distributed AR implementations highlighting the necessity of 5G technologies and their ecosystem to unveil the full potential of AR. Finally, based on these KPls, we propose a set of 5G configuration parameters for a successful distributed AR implementation. As most of the described algorithms are also used in virtual reality (VR) applications, our contributions can facilitate future distributed implementations of both AR and VR applications.This work has received funding from the European Union (EU) Horizon 2020 research and innovation programme under the Marie Skodowska-Curie ETN TeamUp5G, grant agreement no. 813391

Experimental Validation for Distributed Control of Energy Hubs

As future energy systems become more decentralised due to the integration of renewable energy resources and storage technologies, several autonomous energy management and peer-to-peer trading mechanisms have been recently proposed for the operation of energy hub networks based on optimization and game theory. However, most of these strategies have been tested either only in simulated environments or small prosumer units as opposed to larger energy hubs. This simulation reality gap has hindered large-scale implementation and practical application of these method. In this paper, we aim to experimentally validate the performance of a novel multi-horizon distributed model predictive controller for an energy hub network by implementing the controller on a complete network of hubs comprising of a real energy hub inter-faced with multiple virtual hubs. The experiments are done using two different network topologies and the controller shows promising results in both setups.Comment: 6 pages, 2 figures, CISBAT conference 202

The Future of the Internet III

Presents survey results on technology experts' predictions on the Internet's social, political, and economic impact as of 2020, including its effects on integrity and tolerance, intellectual property law, and the division between personal and work lives

Guest Editorial Special Issue on Integrated Sensing and Communication-Part I

Driving a gradual integration of the physical and digital worlds is perceived to become a reality in the 6G era, from vehicles to drones, from surveillance facilities in cities to agricultural tools in the countryside. Jointly motivated by recent advances in communication and signal processing, radio sensing functionality can be integrated into a 6G radio access network (RAN) in a low-cost and fast manner. That is, future networks have the ability to “see” the physical world through imaging and measuring the surrounding environment, which enables advanced location-aware services, ranging from the physical to application layers. In essence, a radio emission could simultaneously convey communication data from the transmitter to the receiver and deliver environmental information from the scattered echoes. Therefore, sensing and communication (S&C) functionalities are possible to be co-designed to utilize resources efficiently and to assist each other for mutual benefits. This type of research is typically referred to as integrated sensing and communication (ISAC)

Contextual Beamforming: Exploiting Location and AI for Enhanced Wireless Telecommunication Performance

The pervasive nature of wireless telecommunication has made it the foundation for mainstream technologies like automation, smart vehicles, virtual reality, and unmanned aerial vehicles. As these technologies experience widespread adoption in our daily lives, ensuring the reliable performance of cellular networks in mobile scenarios has become a paramount challenge. Beamforming, an integral component of modern mobile networks, enables spatial selectivity and improves network quality. However, many beamforming techniques are iterative, introducing unwanted latency to the system. In recent times, there has been a growing interest in leveraging mobile users' location information to expedite beamforming processes. This paper explores the concept of contextual beamforming, discussing its advantages, disadvantages and implications. Notably, the study presents an impressive 53% improvement in signal-to-noise ratio (SNR) by implementing the adaptive beamforming (MRT) algorithm compared to scenarios without beamforming. It further elucidates how MRT contributes to contextual beamforming. The importance of localization in implementing contextual beamforming is also examined. Additionally, the paper delves into the use of artificial intelligence schemes, including machine learning and deep learning, in implementing contextual beamforming techniques that leverage user location information. Based on the comprehensive review, the results suggest that the combination of MRT and Zero forcing (ZF) techniques, alongside deep neural networks (DNN) employing Bayesian Optimization (BO), represents the most promising approach for contextual beamforming. Furthermore, the study discusses the future potential of programmable switches, such as Tofino, in enabling location-aware beamforming