Markov chains

Call number: LD2668 .R4 1964 H63

Deep Learning Obstacle Detection and Avoidance for Powered Wheelchair

Depth sensors like RGB-D cameras, LiDARs and laser scanners are widely investigated in research for Smart Wheelchair (SW) to carry out navigation, localization and ob-stacle detection and avoidance tasks. These sensors are costly compared to monocular camera sensor. A single off-the-shelf camera can be an economically efficient sensor to achieve obstacle detection and avoidance. We present in this paper a single camera based obstacle detection and avoidance method without using any 3D information. It is a novel vision-only system for wheelchair obstacle detection and avoidance that uses a Raspberry Pi along with Raspberry Pi camera. The obstacles are detected using a deep learning model built on MobileNetV2 SSD. The model is retrained using a dedicated dataset that was built for this purpose. Bounding boxes are used to mark detected obstacles; and feed them as features to the image space obstacle avoidance module. Figure 1 depicts internal view of what does the system see and an abstract description of our system's functionality. © 2022 IEEE

Leadership Qualities of School Principals and Their Role in Decision-Making from the Point of View of the Principals Themselves

The current study aimed to reveal the leadership qualities of school principals and their role in decision-making from the point of view of the principals themselves. The study used the descriptive survey method, and to achieve this, the researcher designed a questionnaire consisting of (25) items, and it was applied to the study sample that was selected in an accessible manner, which included (44) principals. From the point of view of the managers themselves in the field of creativity and excellence, development and a medium degree in the field of decision-making, influence and inspiration. The results also showed that there were no statistically significant differences in the decline in the leadership qualities of school principals and their role in decision-making from the point of view of the principals themselves, according to gender, and there were differences in favor of those who were more than five courses for the variable of training courses. Keywords: leadership qualities, school principal, decision-making DOI: 10.7176/JEP/13-19-03 Publication date:June 30th 202

Visual system for punched card reading in textile industry

In this paper we present a novel design and implementation of a vision-based system for reading punched cards. The new system is designed to visually retrieve information stored in punched cards and store them in digital format. The system is dedicated to types of cards used in mechanical Jacquard looms widely spread in different textile industries. Image processing techniques like searching for edges using gradient, normalized cross correlation, and image registration are efficiently utilized to face several challenges. The existence of different types of disturbances makes gradient-based search for the pattern holes insufficient to obtain zero error ratio. As expected image registration can cope with such a problem after efficiently solving the feature extraction and matching problem resulted from the fact that the card image does not contain any kind of information except the pattern holes which are not discriminating features. Experiments have been carried out using the built real system. Experiments show results with 0.041% error ratio. This ratio is highly satisfying the textile industry

Dynamic Time Warping of Deep Features for Place Recognition in Visually Varying Conditions

This paper presents a new visual place recognition (VPR) method based on dynamic time warping (DTW) and deep convolutional neural network. The proposal considers visual place recognition in environments that exhibit changes in several visual conditions like appearance and viewpoint changes. The proposed VPR method belongs to the sequence matching category, i.e., it utilizes the sequence-to-sequence image matching to recognize the best matching to the current test image. This approach extracts the image’s features from a deep CNN, where different layers of a two selected CNNs are investigated and the best performing layer along with the DTW is identified. Also, the performance of the deep features is compared to the one of classical features (handcrafted features like SIFT, HOG and LDB). Our experiments also compare the performance with other state-of-the-art visual place recognition algorithms, Holistic, Only look once, NetVLAD and SeqSLAM in particular. © 2021, King Fahd University of Petroleum & Minerals

Real-time GP-based wheelchair corridor following

In this paper, we present a novel GP-based visual controller. The HOG features are used as a global representation of the observed image. The Gaussian Processes (GP) algorithm is trained to learn the mapping from the HOG feature vector onto the velocity variables. The GP training is achieved using corridor images collected from different places, these images are labeled using velocity values generated by a geometric-based control law and robust features. A hand-based verification of the features is done to ensure the accuracy of the ground truth labels. Experiments were conducted to explore the capabilities of the developed approach. Results have shown R Squared metric with more than ninety percent on the trained GP model in noisy conditions. © 2021 IEEE

COLCONF: Collaborative ConvNet Features-based Robust Visual Place Recognition for Varying Environments

Several deep learning features were recently proposed for visual place recognition (VPR) purpose. Some of them use the information laid in the image sequences, while others utilize the regions of interest (ROIs) that reside in the feature maps produced by the CNN models. It was shown in the literature that features produced from a single layer cannot meet multiple visual challenges. In this work, we present a new collaborative VPR approach, taking the advantage of ROIs feature maps gathered and combined from two different layers in order to improve the recognition performance. An extensive analysis is made on extracting ROIs and the way the performance can differ from one layer to another. Our approach was evaluated over several benchmark datasets including those with viewpoint and appearance challenges. Results have confirmed the robustness of the proposed method compared to the state-of-the-art methods. The area under curve (AUC) and the mean average precision (mAP) measures achieve an average of 91% in comparison with 86% for Max Flow and 72% for CAMAL

A Proposed Model for Assessing Organisational Culture Towards Achieving Business Objectives

Most of the traditional business performances measures are based on productivity and process criteria, which mainly focus on method of investment appraisal such as payback method, return on investment (ROI), cost-benefits analysis (CBA), net present value (NPV), internal rate of return (IRR). However, the measurement scales of business performance are not limited to those measures. One element that has strong correlation to the business performances is ‘organisational culture’. Many studies proved that one of the significant criteria for achieving desired business objectives is the right organisational culture within workplace. Basically, the measurement of organisational culture is reflecting on two distinct elements: organisational culture and business objectives. In broader perspective, an organisation is considered effective if it meets its business objectives. This paper aims to present and discuss the preliminary culture model to indicate the culture performance within organisational. The model has been developed through literature review, expert opinion and experience which is anticipated of being able to potentially measure the culture capability of organisations across industries to “successfully achieve business objectives”. The model is composed of six progressive stages of maturity that an organisation can achieve its culture performance. For each maturity stage, the model describes a set of characteristics that must be in place for the company to achieve each stage. The validity of the proposed model will be tested by a few case studies. The idea is to provide managers with a qualitative measurement tools to enable them to identify where culture improvements are required within their organisations and to indicate their readiness for achieving business objectives

Angiotensinogen Gene Transcription in Pulmonary Fibrosis

An established body of literature supports the hypothesis that activation of a local tissue angiotensin (ANG) system in the extravascular tissue compartment of the lungs is required for lung fibrogenesis. Transcriptional activation of the angiotensinogen (AGT) gene is believed to be a critical and necessary step in this activation. This paper summarizes the data in support of this theory and discusses transcriptional regulation of AGT, with an emphasis on lung AGT synthesis as a determinant of fibrosis severity. Genetic data linking AGT polymorphisms to the severity of disease in Idiopathic Pulmonary Fibrosis are also discussed