Colour Relations in Form

The orthodox monadic determination thesis holds that we represent colour relations by virtue of representing colours. Against this orthodoxy, I argue that it is possible to represent colour relations without representing any colours. I present a model of iconic perceptual content that allows for such primitive relational colour representation, and provide four empirical arguments in its support. I close by surveying alternative views of the relationship between monadic and relational colour representation

The Security of Elliptic Curve Cryptosystems - A Survey

Elliptic curve cryptography or ECC is a public-key cryptosystem. This paper introduces ECC and describes its present applications. A mathematical background is given initially. Then its2019; major cryptographic uses are given. These include its2019; use in encryption, key sharing and digital signatures. The security of these ECC-based cryptosystems are discussed. It was found that ECC was well suited for low-power and resource constrained devices because of its2019; small key size

The Media Layers of the OSI (Open Systems Interconnection) Reference Model: A Tutorial

The Media Layers of the open systems interconnection (OSI) reference model convert bits to packets. It is a very important aspect of network communication and consists of various networking protocols. At the lowest level the physical layer deals with Media, Signal and Binary Transmission of Bits. Then there is the Data Link layer which deals with media access control (MAC) and logical link control (LLC) Physical Addressing of Frames, for example Ethernet. Finally, there is the Network layer which deals with Path Determination and IP Logical addressing of Packets. This article gives a review of these Media Layers and will contribute to adding knowledge for a networking novice while consolidating concepts for an experienced professional or academic

Optimizing Adaptive Video Streaming: A Fuzzy Logic Approach to Resource Allocation

The demand for high-quality video streaming has propelled the evolution of adaptive streaming systems. Efficient resource allocation is paramount to ensuring optimal viewer experience, considering dynamic factors such as server load, network bandwidth, and viewer demand. This review paper investigates the application of fuzzy logic to enhance resource allocation in adaptive video streaming. Fuzzy logic, known for its adaptability in uncertain environments, offers a promising approach to address the complexities of resource optimization. We delve into the integration of fuzzy logic in resource allocation models, considering key parameters like server load, network bandwidth, and viewer demand. The paper provides a comprehensive examination of the benefits, challenges, and limitations associated with fuzzy logic-based resource allocation, supported by case studies illustrating successful implementations. Evaluation metrics are discussed to gauge the performance of this approach in comparison to traditional methods. The review concludes with insights into future directions, offering a roadmap for further advancements in the field of adaptive video streaming. "Optimizing Adaptive Video Streaming: A Fuzzy Logic Approach to Resource Allocation" aims to contribute to the ongoing discourse on intelligent resource management for enhanced video streaming quality and user satisfaction

Enhancing Adaptive Video Streaming through Fuzzy Logic-Based Content Recommendation Systems: A Comprehensive Review and Future Directions

As the demand for high-quality video content continues to rise, adaptive video streaming plays a pivotal role in delivering an optimal viewing experience. However, traditional content recommendation systems face challenges in dynamically adapting to users' preferences, content features, and contextual information. This review paper explores the integration of fuzzy logic into content recommendation systems for adaptive video streaming. Fuzzy logic, known for handling uncertainty and imprecision, provides a promising framework for modeling and accommodating the dynamic nature of user preferences and contextual factors. The paper discusses the evolution of adaptive video streaming, reviews traditional content recommendation algorithms, and introduces fuzzy logic as a solution to enhance the adaptability of these systems. Through a comprehensive exploration of case studies and applications, the effectiveness of fuzzy logic in improving user satisfaction and system performance is highlighted. The review also addresses challenges associated with the integration of fuzzy logic and suggests future research directions to further advance this approach. The proposed framework offers insights into a dynamic and context-aware content recommendation system, contributing to the evolution of adaptive video streaming technologies.Comment: 7 page

Interaction of perceptual grouping and crossmodal temporal capture in tactile apparent-motion

Previous studies have shown that in tasks requiring participants to report the direction of apparent motion, task-irrelevant mono-beeps can "capture'' visual motion perception when the beeps occur temporally close to the visual stimuli. However, the contributions of the relative timing of multimodal events and the event structure, modulating uni- and/or crossmodal perceptual grouping, remain unclear. To examine this question and extend the investigation to the tactile modality, the current experiments presented tactile two-tap apparent-motion streams, with an SOA of 400 ms between successive, left-/right-hand middle-finger taps, accompanied by task-irrelevant, non-spatial auditory stimuli. The streams were shown for 90 seconds, and participants' task was to continuously report the perceived (left-or rightward) direction of tactile motion. In Experiment 1, each tactile stimulus was paired with an auditory beep, though odd-numbered taps were paired with an asynchronous beep, with audiotactile SOAs ranging from -75 ms to 75 ms. Perceived direction of tactile motion varied systematically with audiotactile SOA, indicative of a temporal-capture effect. In Experiment 2, two audiotactile SOAs-one short (75 ms), one long (325 ms)-were compared. The long-SOA condition preserved the crossmodal event structure (so the temporal-capture dynamics should have been similar to that in Experiment 1), but both beeps now occurred temporally close to the taps on one side (even-numbered taps). The two SOAs were found to produce opposite modulations of apparent motion, indicative of an influence of crossmodal grouping. In Experiment 3, only odd-numbered, but not even-numbered, taps were paired with auditory beeps. This abolished the temporal-capture effect and, instead, a dominant percept of apparent motion from the audiotactile side to the tactile-only side was observed independently of the SOA variation. These findings suggest that asymmetric crossmodal grouping leads to an attentional modulation of apparent motion, which inhibits crossmodal temporal-capture effects

A fuzzy c-means bi-sonar-based Metaheuristic Optimization Algorithm

Fuzzy clustering is an important problem which is the subject of active research in several real world applications. Fuzzy c-means (FCM) algorithm is one of the most popular fuzzy clustering techniques because it is efficient, straightforward, and easy to implement. Fuzzy clustering methods allow the objects to belong to several clusters simultaneously, with different degrees of membership. Objects on the boundaries between several classes are not forced to fully belong to one of the classes, but rather are assigned membership degrees between 0 and 1 indicating their partial membership. However FCM is sensitive to initialization and is easily trapped in local optima. Bi-sonar optimization (BSO) is a stochastic global Metaheuristic optimization tool and is a relatively new algorithm. In this paper a hybrid fuzzy clustering method FCB based on FCM and BSO is proposed which makes use of the merits of both algorithms. Experimental results show that this proposed method is efficient and reveals encouraging results

Security in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) pose a new challenge to network designers in the area of developing better and secure routing protocols. Many sensor networks have mission-critical tasks, so it is clear that security needs to be taken into account at design time. However, sensor networks are not traditional computing devices, and as a result, existing security models and methods are ill suited. The security issues posed by sensor networks represent a rich field of research problems. Improving network hardware and software may address many of the issues, but others will require new supporting technologies. With the recent surge in the use of sensor networks, for example, in ubiquitous computing and body sensor networks (BSNs) the need for security mechanisms has a more important role. Recently proposed solutions address but a small subset of current sensor network attacks. Also because of the special battery requirements for such networks, normal cryptographic network solutions are irrelevant. New mechanisms need to be developed to address this type of network

The State-of-the-Art of Set Visualization

Sets comprise a generic data model that has been used in a variety of data analysis problems. Such problems involve analysing and visualizing set relations between multiple sets defined over the same collection of elements. However, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations. We classify these techniques into six main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address these challenges. Further resources on set visualization are available at http://www.setviz.net

What's in a Name? The Multiple Meanings of "Chunk" and "Chunking"

© 2016 Gobet, Lloyd-Kelly and Lane. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.The term chunk, denoting a unit, and the related term chunking, denoting a mechanism to construct that unit, are familiar terms within psychology and cognitive science. The Oxford English Dictionary provides several definitions for “chunk.” First, “a thick, more or less cuboidal, lump, cut off anything,” or, colloquially, “a large or substantial amount.” The Merriam-Webster dictionary provides similar definitions. OUP's Oxford Dictionary alone gives a computer-related meaning: “a section of information or data.” It is in this context, a chunk as a section of information, that the word is used within psychology and cognitive science. In these fields, a chunk typically refers to a single unit built from several smaller elements, and chunking to the process of creating a chunk. Gobet et al. (2001, p. 236) define a chunk as “a collection of elements having strong associations with one another, but weak associations with elements within other chunks.” However, in different contexts and with different authors, these two terms are used with a variety of meanings, which are very often conflated, leading to considerable confusion. Table 1 provides a taxonomy of the main meanings of “chunk” and “chunking,” which will be used to structure this article.Peer reviewedFinal Published versio