Effects of Triangular Core Rotation of a Hybrid Porous Core Terahertz Waveguide

In this paper, we investigate the effects for rotating the triangular core air hole arrangements of a hybrid design porous core fiber. The triangular core has been rotated in anti-clockwise direction to evaluate the impact on different waveguide properties. Effective Material Loss (EML), confinement loss, bending loss, dispersion characteristics and fraction of power flow are calculated to determine the impacts for rotating the triangular core. The porous fiber represented here has a hybrid design in the core area which includes circular rings with central triangular air hole arrangement. The cladding of the investigated fiber has a hexagonal array of air hole distribution. For optimum parameters the reported hybrid porous core fiber shows a flat EML of ±0.000416 cm-1 from 1.5 to 5 terahertz (THz) range and a near zero dispersion of 0.4±0.042 ps/THz/cm from 1.25 to 5.0 THz. Negligible confinement and bending losses are reported for this new type of hybrid porous core design. With improved concept of air hole distribution and exceptional waveguide properties, the reported porous core fiber can be considered as a vital forwarding step in this field of research

Application of Computer Vision and Mobile Systems in Education: A Systematic Review

The computer vision industry has experienced a significant surge in growth, resulting in numerous promising breakthroughs in computer intelligence. The present review paper outlines the advantages and potential future implications of utilizing this technology in education. A total of 84 research publications have been thoroughly scrutinized and analyzed. The study revealed that computer vision technology integrated with a mobile application is exceptionally useful in monitoring students’ perceptions and mitigating academic dishonesty. Additionally, it facilitates the digitization of handwritten scripts for plagiarism detection and automates attendance tracking to optimize valuable classroom time. Furthermore, several potential applications of computer vision technology for educational institutions have been proposed to enhance students’ learning processes in various faculties, such as engineering, medical science, and others. Moreover, the technology can also aid in creating a safer campus environment by automatically detecting abnormal activities such as ragging, bullying, and harassment

A survey on the relationship between trust and interest similarity in online social networks

A remarkable growth in quantity and popularity of online social networks has been observed in recent years. There is a good number of online social networks exists which have over 100 million registered users. Many of these popular social networks offer automated recommendations to their users. This automated recommendations are normally generated using collaborative filtering systems based on the past ratings or opinions of the similar users. Alternatively, trust among the users in the network also can be used to find the neighbors while making recommendations. To obtain the optimum result, there must be a positive correlation exists between trust and interest similarity. Though the positive relations between trust and interest similarity are assumed and adopted by many researchers; no survey work on real life people’s opinion to support this hypothesis is found. In this paper, we have reviewed the state-of-the-art research work on trust in online social networks and have presented the result of the survey on the relationship between trust and interest similarity. Our result supports the assumed hypothesis of positive relationship between the trust and interest similarity of the users

Optimal trust network analysis with subjective logic

Trust network analysis with subjective logic (TNA-SL) simplifies complex trust graphs into series-parallel graphs by removing the most uncertain paths to obtain a canonical graph. This simplification could in theory cause loss of information and thereby lead to sub-optimal results. This paper describes a new method for trust network analysis which is considered optimal because it does not require trust graph simplification, but instead uses edge splitting to obtain a canonical graph. The new method is compared with TNA-SL, and our simulation shows that both methods produce equal results. This indicates that TNA-SL in fact also represents an optimal method for trust network analysis and that the trust graph simplification does not affect the result

Trust and reputation management in web-based social network

know personally. They also communicate with other members of the network who are the friends of their friends and may be friends of their friend’s network. They share their experiences and opinions within the social network about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Opinions, reputations and ecommendations will influence users' choice and usage of online resources. Recommendations may be received through a chain of friends of friends, so the problem for the user is to be able to evaluate various types of trust recommendations and reputations. This opinion or ecommendation has a great influence to choose to use or enjoy the item by the other user of the community. Users share information on the level of trust they explicitly assign to other users. This trust can be used to determine while taking decision based on any recommendation. In case of the absence of direct connection of the recommender user, propagated trust could be useful

Integrating trust with public reputation in location-based social networks for recommendation making

The recent emergence of location-based social networking services is revolutionizing web-based social networking allowing users to share real-life experiences via geo-tagged user-generated multimedia content. One of the key challenges of the web-based social networks as an information sharing and exchanging channel is how to manage healthy relationships among community users and ensure the quality of the information shared and exchanged within the community, which holds a very significant importance to user satisfaction. Deciding whom and what information to trust is very difficult in environment where the users are unknown to each other. This paper investigates the possibilities of managing trust between the users of a web-based social network while recommending items to the members of the network. A novel framework is proposed to integrate trust among community members and public reputation of items to recommend the most appropriate items to a user of the network