scholarly journals Sensoring a Generative System to Create User-Controlled Melodies

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3201
Author(s):  
María Navarro-Cáceres ◽  
Wataru Hashimoto ◽  
Sara Rodríguez-González ◽  
Belén Pérez-Lancho ◽  
Juan Corchado
Keyword(s):  
Intelligent System ◽  
State Of The Art ◽  
Automatic Generation ◽  
Case Based Reasoning ◽  
Mechanical Device ◽  
Specific Context ◽  
Partial Control ◽  
Art Research ◽  
Generative System

The automatic generation of music is an emergent field of research that has attracted the attention of countless researchers. As a result, there is a broad spectrum of state of the art research in this field. Many systems have been designed to facilitate collaboration between humans and machines in the generation of valuable music. This research proposes an intelligent system that generates melodies under the supervision of a user, who guides the process through a mechanical device. The mechanical device is able to capture the movements of the user and translate them into a melody. The system is based on a Case-Based Reasoning (CBR) architecture, enabling it to learn from previous compositions and to improve its performance over time. The user uses a device that allows them to adapt the composition to their preferences by adjusting the pace of a melody to a specific context or generating more serious or acute notes. Additionally, the device can automatically resist some of the user’s movements, this way the user learns how they can create a good melody. Several experiments were conducted to analyze the quality of the system and the melodies it generates. According to the users’ validation, the proposed system can generate music that follows a concrete style. Most of them also believed that the partial control of the device was essential for the quality of the generated music.

On transferability and contexts when using simulated grasp databases

Robotica ◽  
2014 ◽  
Vol 33 (5) ◽  
pp. 1131-1146
Author(s):  
Jimmy A. Rytz ◽  
Lars-Peter Ellekilde ◽  
Dirk Kraft ◽  
Henrik G. Petersen ◽  
Norbert Krüger
Keyword(s):  
Real World ◽  
State Of The Art ◽  
Specific Context ◽  
Grasp Planning ◽  
Large Databases ◽  
Outcome Space ◽  
Bin Picking ◽  
Use Context ◽  
Context Specific

SUMMARYIt has become a common practice to use simulation to generate large databases of good grasps for grasp planning in robotics research. However, the existence of a generic simulation context that enables the generation of high quality grasps that can be used in several different contexts such as bin-picking or picking objects from a table, has to our knowledge not yet been discussed in the literature.In this paper, we investigate how well the quality of grasps simulated in a commonly used “generic” context transfers to a specific context, both, in simulation and in the real world.We generate a large database of grasp hypotheses for several objects and grippers, which we then evaluate in different dynamic simulation contexts e.g., free floating (no gravity, no obstacles), standing on a table and lying on a table.We present a comparison on the intersection of the grasp outcome space across the different contexts and quantitatively show that to generate reliable grasp databases, it is important to use context specific simulation.We furthermore evaluate how well a state of the art grasp database transfers from two simulated contexts to a real world context of picking an object from a table and discuss how to evaluate transferability into non-deterministic real world contexts.

scholarly journals Semi-Supervised Text Simplification with Back-Translation and Asymmetric Denoising Autoencoders

2020 ◽  
Vol 34 (05) ◽  
pp. 9668-9675
Author(s):  
Yanbin Zhao ◽  
Lu Chen ◽  
Zhi Chen ◽  
Kai Yu
Keyword(s):  
State Of The Art ◽  
Automatic Generation ◽  
Complex Sentences ◽  
Text Simplification ◽  
Parallel Data ◽  
Different Types ◽  
Back Translation ◽  
Multiple State ◽  
Simple Pair

Text simplification (TS) rephrases long sentences into simplified variants while preserving inherent semantics. Traditional sequence-to-sequence models heavily rely on the quantity and quality of parallel sentences, which limits their applicability in different languages and domains. This work investigates how to leverage large amounts of unpaired corpora in TS task. We adopt the back-translation architecture in unsupervised machine translation (NMT), including denoising autoencoders for language modeling and automatic generation of parallel data by iterative back-translation. However, it is non-trivial to generate appropriate complex-simple pair if we directly treat the set of simple and complex corpora as two different languages, since the two types of sentences are quite similar and it is hard for the model to capture the characteristics in different types of sentences. To tackle this problem, we propose asymmetric denoising methods for sentences with separate complexity. When modeling simple and complex sentences with autoencoders, we introduce different types of noise into the training process. Such a method can significantly improve the simplification performance. Our model can be trained in both unsupervised and semi-supervised manner. Automatic and human evaluations show that our unsupervised model outperforms the previous systems, and with limited supervision, our model can perform competitively with multiple state-of-the-art simplification systems.

Intelligent Tool for the Design of Electrical Connectors

2013 ◽  
Vol 336-338 ◽  
pp. 1344-1348
Author(s):  
S.C. Fok ◽  
Fock Lai Tan
Keyword(s):  
Intelligent System ◽  
Automatic Generation ◽  
Case Based Reasoning ◽  
Electrical Connector ◽  
Conceptual Designs ◽  
Fixed Topology ◽  
Case Based ◽  
Electrical Connectors

The paper describes an intelligent system for the automatic generation of electrical connector designs. A framework for the system is proposed based on the case-based reasoning approach. The work aims to improve the productivity through automatic exploration of the electronic CAD drawings and reuse successful past solutions for the generation of new conceptual designs. Although this paper focuses on the connector designs, the fundamentals could be applicable to other products that contain distinct sub-components confined within a fixed topology.

scholarly journals A Study of eHealth from the Perspective of Social Sciences

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 108
Author(s):  
Juan Uribe-Toril ◽  
José Luis Ruiz-Real ◽  
Bruno José Nievas-Soriano
Keyword(s):  
Social Sciences ◽  
Technology Acceptance ◽  
Professional Training ◽  
State Of The Art ◽  
The State ◽  
Budget Management ◽  
Efficient Integration ◽  
Art Research ◽  
Acceptance Model

The field of social sciences has become increasingly important in eHealth. Patients currently engage more proactively with health services. This means that eHealth is linked to many different areas of Social Sciences. The main purpose of this research is to analyze the state-of-the-art research on eHealth from the perspective of social sciences. To this end, a bibliometric analysis was conducted using the Web of Science database. The main findings show the evolution of publications, the most influential countries, the most relevant journals and papers, and the importance of the different areas of knowledge. Although there are some studies on eHealth within social sciences, most of them focus on very specific aspects and do not develop a holistic analysis. Thus, this paper contributes to academia by analyzing the state-of-the-art of research, as well as identifying the most relevant trends and proposing future lines of research such as the potential of eHealth as a professional training instrument, development of predictive models in eHealth, analysis of the eHealth technology acceptance model (TAM), efficient integration of eHealth within public systems, efficient budget management, or improvement in the quality of service for patients.

Automatic generation of a large dictionary with concreteness/abstractness ratings based on a small human dictionary

2021 ◽  
pp. 1-9
Author(s):  
Vladimir Ivanov ◽  
Valery Solovyev
Keyword(s):  
State Of The Art ◽  
Research Question ◽  
Automatic Generation ◽  
Expert Assessment ◽  
High Quality ◽  
Test Set ◽  
Expert Assessments ◽  
Abstract Words ◽  
Expert Ratings

Concrete/abstract words are used in a growing number of psychological and neurophysiological research. For a few languages, large dictionaries have been created manually. This is a very time-consuming and costly process. To generate large high-quality dictionaries of concrete/abstract words automatically one needs extrapolating the expert assessments obtained on smaller samples. The research question that arises is how small such samples should be to do a good enough extrapolation. In this paper, we present a method for automatic ranking concreteness of words and propose an approach to significantly decrease amount of expert assessment. The method has been evaluated on a large test set for English. The quality of the constructed dictionaries is comparable to the expert ones. The correlation between predicted and expert ratings is higher comparing to the state-of-the-art methods.

An Intelligent System of Semi-Automatic Design of Cylindrical Gear Reducers with a Choice of Best Solutions

2020 ◽  
pp. 3-14
Author(s):  
G.B. Eugenev
Keyword(s):  
Intelligent Systems ◽  
Intelligent System ◽  
Good Reason ◽  
Automatic Generation ◽  
Generation Process ◽  
Automatic Design ◽  
Cylindrical Gear ◽  
Engineering Activity ◽  
Technical Specifications

The complexity and cost of design, as well as the quality of its results, are determined by the volume and depth of engineering knowledge embedded in a computer. The intellectual technology of computerization of engineering activity enables specialists who does not possess deep knowledge of computer science to create specialized workstations for themselves and their colleagues. At the same time, the engineering activity undergoes qualitative changes: the specialist enters technical specifications into a computer and oversees the project generation process, making fundamental creative decisions by selecting one of the options offered by the computer. Such systems with good reason can be attributed to a fundamentally new category of semi-automatic design systems. This paper examines the technology of creating semi-automatic systems for designing cylindrical gear reducers with an option of searching for the best solutions using genetic algorithms. The relevance of this topic is related to the fact that creation of intelligent systems for product design is an important direction in improving the engineering development of machine-building production. Such systems can increase the productivity and quality of designers’ work due to the semi-automatic generation of 3D models of products in typical variant design.

Sign in / Sign up

Export Citation Format

Share Document