Kinematic Self-Similar Plane Symmetric Solutions

This paper is devoted to classify the most general plane symmetric spacetimes according to kinematic self-similar perfect fluid and dust solutions. We provide a classification of the kinematic self-similarity of the first, second, zeroth and infinite kinds with different equations of state, where the self-similar vector is not only tilted but also orthogonal and parallel to the fluid flow. This scheme of classification yields twenty four plane symmetric kinematic self-similar solutions. Some of these solutions turn out to be vacuum. These solutions can be matched with the already classified plane symmetric solutions under particular coordinate transformations. As a result, these reduce to sixteen independent plane symmetric kinematic self-similar solutions.Comment: 29 pages, accepted for publication in Classical Quantum Gravit

Performance of a multi-stack microchannel heat sink

The usage of a very large scale integrated circuits generate high heat fluxes and require an effective cooling system. A microchannel heat sink (MCHS) is one of the reliable cooling systems that had been applied. In terms of performance, a MCHS can be appraised by obtaining low total thermal resistance and pumping power. However, as the total thermal resistance decreases, the pumping power will increase. A few studies have been focused on the minimization of the thermal resistance and pumping power of a multi-stack MCHS. Optimization of two objective functions which are the total thermal resistance and pumping power has been done by using genetic algorithm. It is demonstrated that both objective functions can be minimized by optimizing two design variables which are the channel aspect ratio, α, and wall width ratio,β. It was found that the usage of a stacked configuration for the MCHS is able to reduce the total thermal resistance. From the optimization, it was found that the optimum number of stacks that can be implemented is three. With the three-stack configuration, the total thermal resistance found is 0.1180 K/W which is 21.8% less compared to the single-stack MCHS. However, the pumping power needed for the three-stack MCHS is increased by 0.17 % compared to single-stack which is 0.7535 W

Real-Time Customer Emotion Analysis in E-Commerce based on Social Media Data: Insights and Opportunities

In this era of social media, it's essential for businesses to monitor their customers options and feelings regarding their services and products in a timely manner. Due to the ease of sharing opinions and feedback on social media, the customers can share their reviews about the business or a product instantly. This feedback can have a significant impact on the business's reputation and in turn on its revenue. In this regard, sentiment analysis has developed into a vital tool that companies can use to comprehend the emotional factors that influence client behavior and to aid them in making decisions that will increase customer pleasure. This work presents the use of social media data for real-time consumer emotion analysis in e-commerce. The study aims to identify the most expressed emotions and provide businesses with the ability to tailor their product and services accordingly. The employed dataset consists of 58,000 English comments that have been labelled for 27 different emotion categories. The study uses machine learning methods to categorize the emotions expressed in the comments, including convolutional neural networks and Bidirectional Encoder Representations from Transformers (BERT). The practical result of this research shows the importance of machine learning model coupled with a user interface that can provide stakeholders, such as e-commerce companies, with insights into consumer emotion as well as realtime customer sentiment about their goods and services

Energy and Momentum of a Class of Rotating Gravitational Waves

We calculate energy and momentum for a class of cylindrical rotating gravitational waves using Einstein and Papapetrou's prescriptions. It is shown that the results obtained are reduced to the special case of the cylindrical gravitational waves already available in the literature.Comment: 11 pages, no figure, Late

Social media and orthodontics – are our patients scrolling?

OBJECTIVE: To assess patients’ awareness of the availability of information related to orthodontics on social media, and to explore patients’ willingness to engage with social media to aid with orthodontic treatment. DESIGN: Prospective cross-sectional survey. SETTING: This survey was conducted at Croydon University Hospital orthodontic department. PARTICIPANTS: A total of 125 orthodontic patients, both new and in treatment. There were no exclusion criteria. METHODS: All participants completed a questionnaire designed to explore their awareness, access to and utilisation of social media as well as their willingness to engage with social media to support orthodontic treatment. There were no age restrictions or exclusion criteria. RESULTS: Of the patients, 99% had access to social media. Of these patients, 64% were aware that social media platforms were available to help with orthodontic treatment, 30% had utilised social media related to orthodontics, with the most popular platforms being Instagram (n = 17) and Snapchat (n = 12). Of the patients, 73% stated that they would be willing to use social media in the future to support orthodontic treatment. CONCLUSION: Social media can be engaging, accessible and versatile, and has been shown to be effective at improving patients’ knowledge regarding orthodontic treatment. As such, it may be used as a valuable tool for information provision to engage orthodontic patients. Awareness of the availability of orthodontics content on social media is increasing; however, only one-third of participants had previously used it to aid with orthodontic treatment. Given the availability of information on social media targeted at orthodontic patients there is a need to assess the quality of this information and if appropriate navigate patients towards high-quality, effective resources

Teleparallel Energy-Momentum Distribution of Spatially Homogeneous Rotating Spacetimes

The energy-momentum distribution of spatially homogeneous rotating spacetimes in the context of teleparallel theory of gravity is investigated. For this purpose, we use the teleparallel version of Moller prescription. It is found that the components of energy-momentum density are finite and well-defined but are different from General Relativity. However, the energy-momentum density components become the same in both theories under certain assumptions. We also analyse these quantities for some special solutions of the spatially homogeneous rotating spacetimes.Comment: 12 pages, accepted for publication in Int. J. Theor. Phy

Prioritizing the Relative Dominance of Drivers for Intellectual Entrepreneuring Through the Tertiary Knowledge Industry.

The knowledge industry is becoming the dominant contributor to sustainable growth. It is causing a paradigm drift towards knowledge capitalization for improvement of productivity-driven competition to attain better economic performance, wealth generation, and development. Research has identified an “intellectual entrepreneurial capacity gap” as the constraint to attaining equity between developed and developing economies. The gap is fuelling the growing technological innovation divide – the widening boundary between developed and developing economies. As a contribution to reducing the gap, this paper presents a conceptual framework of drivers for intellectual entrepreneurial capacity in knowledge capitalization for technological and economic leapfrogging in development.The knowledge industry is becoming the dominant contributor to sustainable growth. It is causing a paradigm drift towards knowledge capitalization for improvement of productivity-driven competition to attain better economic performance, wealth generation, and development. Research has identified an “intellectual entrepreneurial capacity gap” as the constraint to attaining equity between developed and developing economies. The gap is fuelling the growing technological innovation divide – the widening boundary between developed and developing economies. As a contribution to reducing the gap, this paper presents a conceptual framework of drivers for intellectual entrepreneurial capacity in knowledge capitalization for technological and economic leapfrogging in development.The knowledge industry is becoming the dominant contributor to sustainable growth. It is causing a paradigm drift towards knowledge capitalization for improvement of productivity-driven competition to attain better economic performance, wealth generation, and development. Research has identified an “intellectual entrepreneurial capacity gap” as the constraint to attaining equity between developed and developing economies. The gap is fuelling the growing technological innovation divide – the widening boundary between developed and developing economies. As a contribution to reducing the gap, this paper presents a conceptual framework of drivers for intellectual entrepreneurial capacity in knowledge capitalization for technological and economic leapfrogging in development

Orthodontic apps: An assessment of quality (using the Mobile App Rating Scale (MARS)) and Behaviour Change Techniques (BCTs)

BACKGROUND: Apps have been shown to be an effective tool in changing patients’ behaviours in orthodontics and can be used to improve their compliance with treatment. The Behaviour Change Techniques (BCTs) and quality (using MARS) within these apps have previously not been published. OBJECTIVES: 1. To evaluate the quality of these apps aiming to change behaviour. 2. To assess BCTs used in patient focused orthodontic apps. METHODS: The UK Google Play and Apple App Stores were searched to identify all orthodontic apps and 305 apps were identified. All 305 apps were assessed for the presence of BCTs using an accepted taxonomy of BCTs (Behaviour Change Wheel (BCW)), widely utilised in healthcare. Of those containing BCTs, the quality was assessed using the Mobile App Rating Scale (MARS), a validated and multi-dimensional tool which rates apps according to 19 objective criteria. Data collection was carried out by two calibrated, independent assessors and repeated after 6 weeks for 25% of the apps by both assessors. RESULTS: BCTs were found in 31 apps, although only 18 of them were analysed for quality and 13 apps were excluded. Six different BCTs were identified: these were most commonly ‘prompts/cues’, and ‘information about health consequences’. All apps were shown to be of moderate quality (range 3.1–3.7/5). Inter-rater and intra-rater reliability for BCT and quality assessment were excellent. CONCLUSIONS: The current availability of orthodontic apps of sufficient quality to recommend to patients is very limited. There is therefore a need for high-quality orthodontic apps with appropriate BCTs to be created, which may be utilised to improve patients’ compliance with treatment

Energy Distribution associated with Static Axisymmetric Solutions

This paper has been addressed to a very old but burning problem of energy in General Relativity. We evaluate energy and momentum densities for the static and axisymmetric solutions. This specializes to two metrics, i.e., Erez-Rosen and the gamma metrics, belonging to the Weyl class. We apply four well-known prescriptions of Einstein, Landau-Lifshitz, Papaterou and M$\ddot{o}$ller to compute energy-momentum density components. We obtain that these prescriptions do not provide similar energy density, however momentum becomes constant in each case. The results can be matched under particular boundary conditions.Comment: 18 pages, accepted for publication in Astrophysics and SpaceScienc

Fault Sneaking Attack: a Stealthy Framework for Misleading Deep Neural Networks

Despite the great achievements of deep neural networks (DNNs), the vulnerability of state-of-the-art DNNs raises security concerns of DNNs in many application domains requiring high reliability.We propose the fault sneaking attack on DNNs, where the adversary aims to misclassify certain input images into any target labels by modifying the DNN parameters. We apply ADMM (alternating direction method of multipliers) for solving the optimization problem of the fault sneaking attack with two constraints: 1) the classification of the other images should be unchanged and 2) the parameter modifications should be minimized. Specifically, the first constraint requires us not only to inject designated faults (misclassifications), but also to hide the faults for stealthy or sneaking considerations by maintaining model accuracy. The second constraint requires us to minimize the parameter modifications (using L0 norm to measure the number of modifications and L2 norm to measure the magnitude of modifications). Comprehensive experimental evaluation demonstrates that the proposed framework can inject multiple sneaking faults without losing the overall test accuracy performance.Comment: Accepted by the 56th Design Automation Conference (DAC 2019