Application of Cascade Forward Backpropagation Neural Networks for Selecting Mining Methods

Decision-making is very important in many fields, such as mining engineering. In addition, there has been a growth of computer applications in all fields, especially mining operations. One of these application fields is mine design and the selection of suitable mining methods, and computer applications can help mine engineers to decide upon and choose more satisfactory methods. The selection of mining methods depends on the rock-layer specification. All rock characteristics should be classified in terms of technical and economic concerns related to mining rock specifications, such as mechanical and physical properties, and evaluated according to their weights and ratings. Methodologically, in this study, the criteria considered in the University of British Columbia (UBC) method were used as references to establish general criteria. These criteria consist of general shape, ore thickness, ore plunge, and grade distribution, in addition to the rock quality designation (ore zone, hanging wall, and foot wall) and rock substance strength (ore zone, hanging wall, and foot wall). The technique for order of preference by similarity to ideal solution (TOPSIS) was adopted, and an improved TOPSIS method was developed based on experimental testing and checked by means of the application of cascade forward backpropagation neural networks in mining method selection. The results provide indicators that decision makers can use to choose between different mining methods based on the total points given to all ore properties. The best mining method is cut and fill stopping, with a rank of 0.70, and the second is top slicing, with a rank of 0.67.

METHODOLOGY OF CONVERTING OF THE COORDINATES OF THE BASIS ATOMS IN A UNIT CELL OF CRYSTALLINE Β-GA2O3, SPECIFIED IN A MONOCLINIC CRYSTALLOGRAPHIC SYSTEM, IN THE LABORATORY CARTESIAN COORDINATES FOR COMPUTER APPLICATIONS

One of the most important areas of modern technology is the creation of new structural materials with predetermined properties. Along with industrial methods for their preparation and technologies associated with the artificial growth of crystalline structures, various methods of computer modeling of new materials have recently become increasingly important. Such approaches can significantly reduce the number of full-scale experiments. Many applications of the computational materials science are related to the need to establish a relationship between structure and electronic characteristics, and other physical properties of crystals. This article on the example of crystalline β-Ga2O3 presents the algorithms used in the converting of the coordinates of the basis atoms in a unit cell of crystal, specified in a crystallographic system, in the Cartesian coordinates for the computational experiment.

Hand Pose Recognition Using Parallel Multi Stream CNN

Recently, several computer applications provided operating mode through pointing fingers, waving hands, and with body movement instead of a mouse, keyboard, audio, or touch input such as sign language recognition, robot control, games, appliances control, and smart surveillance. With the increase of hand-pose-based applications, new challenges in this domain have also emerged. Support vector machines and neural networks have been extensively used in this domain using conventional RGB data, which are not very effective for adequate performance. Recently, depth data have become popular due to better understating of posture attributes. In this study, a multiple parallel stream 2D CNN (two-dimensional convolution neural network) model is proposed to recognize the hand postures. The proposed model comprises multiple steps and layers to detect hand poses from image maps obtained from depth data. The hyper parameters of the proposed model are tuned through experimental analysis. Three publicly available benchmark datasets: Kaggle, First Person, and Dexter, are used independently to train and test the proposed approach. The accuracy of the proposed method is 99.99%, 99.48%, and 98% using the Kaggle hand posture dataset, First Person hand posture dataset, and Dexter dataset, respectively. Further, the results obtained for F1 and AUC scores are also near-optimal. Comparative analysis with state-of-the-art shows that the proposed model outperforms the previous methods.

Author Profiling in Informal and Formal Language Scenarios Via Transfer Learning

The interest in author profiling tasks has increased in the research community because computer applications have shown success in different sectors such as security, marketing, healthcare, and others. Recognition and identification of traits such as gender, age or location based on text data can help to improve different marketing strategies. This type of technology has been widely discussed regarding documents taken from social media. However, its methods have been poorly studied using data with a more formal structure, where there is no access to emoticons, mentions, and other linguistic phenomena that are only present in social media. This paper proposes the use of recurrent and convolutional neural networks and a transfer learning strategy to recognize two demographic traits, i.e., gender and language variety, in documents written in informal and formal language. The models were tested in two different databases consisting of tweets (informal) and call-center conversations (formal). Accuracies of up to 75 % and 68 % were achieved in the recognition of gender in documents with informal and formal language, respectively. Moreover, regarding language variety recognition, accuracies of 92 % and 72 % were obtained in informal and formal text scenarios, respectively. The results indicate that, in relation to the traits considered in this paper, it is possible to transfer the knowledge from a system trained on a specific type of expressions to another one where the structure is completely different and data are scarcer.

Codings for rhythm generation

In this work, we present a brief review of strategies to code rhythms and point to their possibilities and limitations in a unified way. We start by giving an overview of the representation (coding) of rhythms and their possible uses. Then we present different methods to analyse and generate rhythm patterns, which can be easily read by humans, through a simple algorithm. We also aim to provide a general evaluation of their pros and cons regarding their use in composition and analysis. In a more abstract approach, we define Rhythm Spaces as sets of strings of symbols endowed with suitable operations and algorithms that can be applied to generate new and complex rhythm patterns. Our approach can be useful in order to provide suitable code/notation to be used in computer applications in rhythm analysis and composition.

Natural language query formalization to SPARQL for querying knowledge bases using Rasa

The idea of data to be semantically linked and the subsequent usage of this linked data with modern computer applications has been one of the most important aspects of Web 3.0. However, the actualization of this aspect has been challenging due to the difficulties associated with building knowledge bases and using formal languages to query them. In this regard, SPARQL, a recursive acronym for standard query language and protocol for Linked Open Data and Resource Description Framework databases, is a most popular formal querying language. Nonetheless, writing SPARQL queries is known to be difficult, even for experts. Natural language query formalization, which involves semantically parsing natural language queries to their formal language equivalents, has been an essential step in overcoming this steep learning curve. Recent work in the field has seen the usage of artificial intelligence (AI) techniques for language modelling with adequate accuracy. This paper discusses a design for creating a closed domain ontology, which is then used by an AI-powered chat-bot that incorporates natural language query formalization for querying linked data using Rasa for entity extraction after intent recognition. A precision–recall analysis is performed using in-built Rasa tools in conjunction with our own testing parameters, and it is found that our system achieves a precision of 0.78, recall of 0.79 and F1-score of 0.79, which are better than the current state of the art.

A graph-based computerized optimal conceptual design synthesis within the distributed multi-disciplinary resource environment

The trend of inter-disciplinary conceptual design synthesis requires designers to involve more and more distributed multi-disciplinary design resources. Therefore, this paper proposes a graph-based computerized optimal conceptual design synthesis to help designers explore novel design schemes within the distributed multi-disciplinary resource environment. The design resources tightly related to the design goal can be extracted from the huge resource environment by a proposed searching engine. The optimal design scheme can be generated from these related design resources by a proposed graph-based algorithm. A set of computer applications called Automatic Conceptual Design System (ACDS) is established to verify the feasibility of this proposed conceptual design synthesis, and a garbage power system’s conceptual design is completed by this software prototype.

THE IMPACT OF PALESTINIAN TEACHER’S ACCEPTANCE OF USING TECHNOLOGY ON THEIR TEACHING PRACTICES IN LIGHT OF THE CORONA PANDEMIC

This paper studied the impact of Palestinian teacher’s acceptance of using technology on their teaching practices in light of the corona pandemic, twelves teachers are from different education directories in West- Bank. Qualitative methodology was employed in-depth semi- structured interviews to explain how their acceptance of using technology according to a model of technology acceptance (TAM); impact their teaching practices in light of the corona pandemic. Findings shows that Teacher’s perception that employing technology is useful in education. These perceptions of usefulness of using technology have been reflected in their practices in all aspect of the educational process: content, communication with students, teaching strategies, assessment methods, and the variety of applications they used. Also employing technology in education is easy, if the teacher possesses the technological skills. They worked to develop themselves in the field of technology and computer applications through self-learning and enrollment in the online workshops and courses, then applying what they had learned during in their practice, continuing to develop themselves, and employing technology after the pandemic. Finally, teacher’s acceptance of employing technology in education has been affected by physical and human factors. It is recommended that establishing an integrated plan by the Ministry of Education to include human and physical resources in order to achieve readiness for education in emergencies‎.

Influence of Numerical Control Cutting Parameters on Performance of Numerical Control Tool

As China has stepped into a new era of development, the popularity of computer applications is becoming more and more profound. Especially in the machinery manufacturing industry, the current market has put forward a higher requirement for the accuracy and toughness of machinery manufacturing, and the traditional artificial manufacturing has not been adapted to the development of the industry. Through numerical control technology, numerical control tool manufacturing process can become very standardized, its accuracy and toughness is also guaranteed. This paper will from the numerical control this point of view, to explore the influence of numerical control cutting parameters on the numerical control tool.

Reducing the Dimensionality of Grid Approximations

Предложен общий подход к развитию методов математического моделирования сложных систем. Центральной проблемой, связанной с использованием вычислительной техники, являются сеточные аппроксимации большой размерности и суперЭВМ высокой производительности с большим числом параллельно работающих микропроцессоров. В качестве возможных альтернатив сеточным аппроксимациям большой размерности разрабатываются кинетические методы решения дифференциальных уравнений и методы «склейки» точных решений на грубых сетках. A general approach to the development of complex systems simulation is proposed. The key computer applications problem is the high-dimensional grid approximations and high-performance supercomputers with a large number of parallel CPUs. Kinetic methods for solving differential equations and methods for ”gluing” exact solutions produced with coarse meshes are developed as possible alternatives to high-dimensional grid approximations.