Bionic design and analysis of a multi-posture wheelchair

Posture transformation is an essential function for multi-posture wheelchairs. To improve the natural motion in posture transformation that is a popular problem in the design of multi-posture wheelchairs because the current wheelchair's posture transformation mechanism cannot remain consistent between the rotation center of the wheelchair and the rotation center of the human body joints. This paper proposes a sitting–standing–lying three-posture bionic transformation mechanism for a smart wheelchair. A human–wheelchair coupling model is described and analyzed according to the biomechanical characteristics of the posture transformation of human beings and their functional requirements. The configuration of the transformation mechanism is chosen by comparing the trails of the wheelchair rotation centers and the corresponding human joint rotation centers. The kinematics of the optimized configuration are discussed in detail to obtain the most bionic motion performance using the multivariable nonlinear constraint optimization algorithm. Finally, the mechanism is designed, and its posture transformation performance is simulated and verified using Adams (Automatic Dynamic Analysis of Mechanical Systems) software.

Multilayer Architecture for Fault Diagnosis of Embedded Systems

This work presents a multilayer architecture for fault diagnosis in embedded systems based on formal modeling of Discrete Event Systems (DES). Most works on diagnosis of DES focus in faults of actuators, which are the devices subject to intensive wear in industry. However, embedded systems are commonly subject to cost reduction, which may increase the probability of faults in the electronic hardware. Further, software faults are hard to track and fix, and the common solution is to replace the whole electronic board. We propose a modeling approach which includes the isolation of the source of the fault in the model, regarding three layers of embedded systems: software, hardware, and sensors & actuators. The proposed method is applied to a home appliance refrigerator and after exhaustive practical tests with forced fault occurrences, all faults were diagnosed, precisely identifying the layer and the faulty component. The solution was then incorporated into the product manufactured in industrial scale.

Dynamic Control of Computation Consistency in the Parallel Dataflow Computing System

When developing high-performance multiprocessor computing systems, much attention is paid to ensuring uninterrupted operation, both in terms of hardware and software. In traditional computing systems, software is the main focus in address­ing these issues. The article discusses the solution to the issue of ensuring uninterrupted operation for the parallel dataflow computing system (PDCS), which implements the dataflow computational model with a dynamically formed context. Due to the features of the PDCS, it is proposed to implement this type of control in hardware, which will increase its efficiency, since the computational process will be controlled in dynamics, and not only in statics.

Searching Deterministic Chaotic Properties in System-Wide Vulnerability Datasets

Cybersecurity is a never-ending battle against attackers, who try to identify and exploit misconfigurations and software vulnerabilities before being patched. In this ongoing conflict, it is important to analyse the properties of the vulnerability time series to understand when information systems are more vulnerable. We study computer systems’ software vulnerabilities and probe the relevant National Vulnerability Database (NVD) time-series properties. More specifically, we show through an extensive experimental study based on the National Institute of Standards and Technology (NIST) database that the relevant systems software time series present significant chaotic properties. Moreover, by defining some systems based on open and closed source software, we compare their chaotic properties resulting in statistical conclusions. The contribution of this novel study is focused on the prepossessing stage of vulnerabilities time series forecasting. The strong evidence of their chaotic properties as derived by this research effort could lead to a deeper analysis to provide additional tools to their forecasting process.

Data-Driven Facial Expression Analysis from Live Video

<p>Emotion analytics is the study of human behavior by analyzing the responses when humans experience different emotions. In this thesis, we research into emotion analytics solutions using computer vision to detect emotions from facial expressions automatically using live video. Considering anxiety is an emotion that can lead to more serious conditions like anxiety disorders and depression, we propose 2 hypotheses to detect anxiety from facial expressions. One hypothesis is that the complex emotion “anxiety” is a subset of the basic emotion “fear”. The other hypothesis is that anxiety can be distinguished from fear by differences in head and eye motion. We test the first hypothesis by implementing a basic emotions detector based on facial action coding system (FACS) to detect fear from videos of anxious faces. When we discover that this is not as accurate as we would like, an alternative solution based on Gabor filters is implemented. A comparison is done between the solutions and the Gabor-based solution is found to be inferior. The second hypothesis is tested by using scatter graphs and statistical analysis of the head and eye motions of videos for fear and anxiety expressions. It is found that head pitch has significant differences between fear and anxiety. As a conclusion to the thesis, we implement a systems software using the basic emotions detector based on FACS and evaluate the software by comparing commercials using emotions detected from facial expressions of viewers.</p>

Data-Driven Facial Expression Analysis from Live Video

<p>Emotion analytics is the study of human behavior by analyzing the responses when humans experience different emotions. In this thesis, we research into emotion analytics solutions using computer vision to detect emotions from facial expressions automatically using live video. Considering anxiety is an emotion that can lead to more serious conditions like anxiety disorders and depression, we propose 2 hypotheses to detect anxiety from facial expressions. One hypothesis is that the complex emotion “anxiety” is a subset of the basic emotion “fear”. The other hypothesis is that anxiety can be distinguished from fear by differences in head and eye motion. We test the first hypothesis by implementing a basic emotions detector based on facial action coding system (FACS) to detect fear from videos of anxious faces. When we discover that this is not as accurate as we would like, an alternative solution based on Gabor filters is implemented. A comparison is done between the solutions and the Gabor-based solution is found to be inferior. The second hypothesis is tested by using scatter graphs and statistical analysis of the head and eye motions of videos for fear and anxiety expressions. It is found that head pitch has significant differences between fear and anxiety. As a conclusion to the thesis, we implement a systems software using the basic emotions detector based on FACS and evaluate the software by comparing commercials using emotions detected from facial expressions of viewers.</p>

Modelling and Optimisation of the Business Process of Documentary Support of Cargo Transportation for Building a Digital Document Management System

The objective of the work is to analyse the examples of optimisation of documentary support system regarding rail cargo transportation based on the transition to the electronic form of documents.The theoretical concept of modelling the business process of documentary support of cargo transportation is developed using the ARIS (Architecture of Integrated information Systems) software, which is used for development of an integrated process model of the activities of many manufacturing and transportation companies in Russia and in the world [1].The subject of the research is modelling of the document circulation system supporting cargo transportation to eliminate losses in a significant part of the processes of interaction with customers. The objective of business process modelling is to use all the advantages and functionality of case tools to eliminate duplication of actions and operations that do not add value to the customers of the transport company but reduce their loyalty to the products and services of railway transportation. The studied business processes ensure formation of an application for transportation and its transformation during the transportation process.The study reflects the results of modelling business processes for documentary support of transportation in digital form. A comparative analysis of these models is followed by description of the advantages of the electronic documents in comparison with their paper form considering a possibility of using a digital signature.

Automated Prediction of the Liquid Paraffins Viscosity

The article deals with an approach to the construction of self-adjusting automatic control systems, in which parametric adaptation occurs when the properties of technological raw materials change during its processing due to changes in the parameters of state. A new algorithm for predicting the viscosity of hydrocarbon liquids is proposed, which can be used as part of the control systems software. The main dependences are obtained on the basis of reliable experimental data on the viscosity of normal C8–C20 alkanes, which are similar in properties to commodity petroleum products. The data of physicochemical analysis are used as the initial data for the computation. Based on the theory of corresponding states, a new approach to scaling the viscosity using a set of characteristic parameters is developed and technique for their determination is proposed. The method is tested in the temperature range (0.4 – 0.7)TC at pressures up to 10 MPa. It is shown that the deviation of the predicted values from the experimental data is comparable to the error of the viscosity measurement.

Invariant-Based Safety Assessment of FPGA Projects: Conception and Technique

This paper describes a proposed method and technology of safety assessment of projects based on field programmable gate arrays (FPGA). Safety assessment is based on special invariants, e.g., properties which remain unchanged when a specified transformation is applied. A classification and examples of FPGA project invariants are provided. In the paper, two types of invariants are described. The first type of invariants used for such assessment are those which are versatile since they reflect the unchanged properties of FPGA projects, hardware description languages, etc. These invariants can be replenished as experience gained in project implementation accumulates. The second type of invariants is formed based on an analysis of the specifics of a particular FPGA project and reflects the features of the tasks to be solved, the algorithms that are implemented, the hardware FPGA chips used, and the computer-aided design tools, etc. The paper contains a description of the overall conception and particular stages of FPGA projects invariant-based safety assessment. As examples for solving some tasks (using of invariants and defect injections), the paper contains several algorithms written in the VHSIC hardware description language (VHDL). The paper summarizes the results obtained during several years of practical and theoretical research. It can be of practical use for engineers and researchers in the field of quality, reliability, and security of embedded systems, software and information management systems for critical and business applications.