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Abstract
Facial recognition technology is transformative in security and human-machine interaction, reshaping societal interactions. Robust descriptors, essential for high precision in machine learning tasks like recognition and recall, are integral to this transformation. This paper presents a hybrid model enhancing local binary pattern descriptors for facial representation. By integrating rotation-invariant local binary pattern with uniform rotation-invariant grey-level co-occurrence, employing linear discriminant analysis for feature space optimization, and utilizing an artificial neural network for classification, the model achieves exceptional accuracy rates of 100% for Olivetti Research Laboratory, 99.98% for Maastricht University Computer Vision Test, and 99.17% for Extended Yale B, surpassing traditional methods significantly.
Abstract
The study aims to investigate and find natural fiber as concrete reinforcement using the self-compacting concrete method. Methods of adding fiber and self-compacting concrete methods are exciting because these two methods have different characteristics and advantages. Therefore, the performance of the fresh-state flow capability of the self-compacting concrete method, which contains various fibers, was observed. Coconut fiber, pineapple leaf fiber, ijuk sugar palm fiber, and artificial polypropylene fiber were used with varying compositions of 0.3, 0.5, and 0.7% by mass of binder. The results show that coconut and pineapple fiber concrete met the European Guidelines for Self-Compacting Concrete standards. The coconut and pineapple fiber concrete performed admirably in all tests.
Abstract
With the rise of the digital era, digital reading and learning have become widespread. University libraries, as core locations for study and communication, face challenges in fully meeting the demands of modern teaching and learning. This paper takes the library at the Changqing campus of Shandong University of Arts as a case study to explore the environmental space design of constructed libraries in the digital era. By reviewing relevant concepts and theoretical frameworks, analyzing the existing environment, and researching intervention design methods, the paper discusses the positive role of adapting to the digital future in renovating established library spaces.
Abstract
Streaming services spread rapidly. Among these services there are the linear TV, video library or program review system, while the online platform offering these contents is called mobile TV. A recommendation system may not only keep existing clients, but may also generate further turnover, should it introduce new content to the users. In this paper a recommendation system based on the Élő point calculation method is addressed. It is detailed how the programs should be grouped into different dimensions and what type of categories should be considered. Further, the idea of punch cards is introduced. Besides, the user profiles are set. The match system introduced by Élő is applied to the present situation. The system is introduced at a local mobile TV provider with 20,000 users.
Abstract
A computational model is developed to investigate the convective heat transfer properties and the fluid flow characteristics of cupric oxide - water nano-fluid in a horizontal circular pipe aiming to provide insights into optimizing heat transfer in such systems. A twisted tape with varied twist ratios is inserted. This quantitative investigation used five Reynolds number from 4,000 to 12,000 under a uniform heat flux scenario of 25,000 W m−2. All experiments were performed as a single-phase fluid with cupric oxide values of 0, 0.4, 1, and 2% by volume. By reducing the twist ratio and increasing volume concentration, the average heat transfer coefficient of cupric oxide-water nano-fluid was improved. For a twist ratio of 4D, the maximum heat transfer improvement was 228% greater than the plain pipe. The presence of twisted tape with modest step ratios causes the friction factor to grow.
Abstract
This research aims to study the pullout resistance of a helical pile using three methods of machine learning techniques, which are: random forest regression, support vector regression, and adaptive neuro-fuzzy inference system, based on experimental results of a helical pile. The performance of these three techniques has been d compared and the results show that random forest algorithm has best performance than neuro-fuzzy inference system and support vector technique. The results show that machine learning considered a good tool in terms of estimating the pullout resistance of helical piles in the soil.
Abstract
Fused deposition modeling (FDM) 3D printing is widely utilized for producing thermoplastic components with functional purposes. However, the inherent mechanical limitations of pure thermoplastic materials necessitate enhancements in their mechanical characteristics when employed in certain applications. One strategy for addressing this challenge involves the incorporation of reinforcement materials, such as carbon fiber (CF), within the thermoplastic matrix. This approach leads to the creation of carbon fiber-reinforced polymer composites (CFRPs) suitable for engineering applications. The utilization of CFRPs in 3D printing amalgamates the benefits of additive manufacturing, including customization, cost-effectiveness, reduced waste, swift prototyping, and accelerated production, with the remarkable specific strength of carbon fiber. This study encompasses tensile and compressive testing of distinct material compositions: recycled polylactic acid (rPLA), PLA enriched with 10 wt.% carbon fiber, pristine polyethylene terephthalate glycol (PETG), and PETG bolstered with 10 wt.% carbon fiber. Tensile tests adhere to the ASTM D3039 standard for specimens of rectangular shape, while the ASTM D695 standard governs the compressive testing procedures. Additionally, an inquiry into the influence of the primary 3D printing build orientation parameter on the tensile and compressive strengths of diverse materials was conducted. The outcomes reveal that rPLA exhibits superior mechanical properties in both tensile and compressive tests, irrespective of flat or on-edge build orientations. In the context of tensile strength analysis, it is noteworthy that rPLA demonstrated a superior performance, surpassing CFPLA by 30% in flat orientation and exhibiting a remarkable 39.2% advantage in on-edge orientation. Moreover, PLA reinforced with carbon fiber exhibits superior tensile and compressive properties compared to its PETG counterpart. A comparative analysis between CFPLA and CF-PETG indicates that CF-PLA demonstrates higher tensile strengths, with increases of 26.6 and 27.6% for flat and on-edge orientations, respectively. In the context of compressive strength analysis, rPLA surpassed CFPLA, PETG, and CF-PETG by 23.7, 53, and 67%, respectively. Intriguingly, the findings indicate that the incorporation of 10 wt.% carbon fiber diminishes the tensile and compressive properties in comparison to pure PETG.
