Characterization of optical communication in a leader-follower unmanned underwater vehicle formation

As part of the research to development an optical communication design of a leader-follower formation between unmanned underwater vehicles (UUVs), this paper presents light field characterization and design configuration of the hardware required to allow the use of distance detection between UUVs. The study specifically is targeting communication between remotely operated vehicles (ROVs). As an initial step in this study, the light field produced from a light source mounted on the leader UUV was empirically characterized and modeled. Based on the light field measurements, a photo-detector array for the follower UUV was designed. Evaluation of the communication algorithms to monitor the UUV’s motion was conducted through underwater experiments in the Ocean Engineering Laboratory at the University of New Hampshire. The optimal spectral range was determined based on the calculation of the diffuse attenuation coefficients by using two different light sources and a spectrometer. The range between the leader and the follower vehicles for a specific water type was determined. In addition, the array design and the communication algorithms were modified according to the results from the light field

Pose Detection and control of multiple unmanned underwater vehicles using optical feedback

This paper proposes pose detection and control algorithms in order to control the relative pose between two Unmanned Underwater Vehicles (UUVs) using optical feedback. The leader UUV is configured to have a light source at its crest which acts as a guiding beacon for the follower UUV which has a detector array at its bow. Pose detection algorithms are developed based on a classifier, such as the Spectral Angle Mapper (SAM), and chosen image parameters. An archive look-up table is constructed for varying combinations of 5-degree-of-freedom (DOF) motion (i.e., translation along all three coordinate axes as well as pitch and yaw rotations). Leader and follower vehicles are simulated for a case in which the leader is directed to specific waypoints in horizontal plane and the follower is required to maintain a fixed distance from the leader UUV. Proportional-Derivative (PD) control (without loss of generality) is applied to maintain stability of the UUVs to show proof of concept. Preliminary results indicate that the follower UUV is able to maintain its fixed distance relative to the leader UUV to within a reasonable accuracy

Determinants of Youth Educational Attainment in Myanmar (Win May Khaing, 2024)

This study explores the primary factors affecting educational attainment among youth in Myanmar. Data for individuals aged 15-24 were sourced from the 2019 Myanmar Inter-censal Survey. The research utilized descriptive analysis, Chisquare tests, and multinomial logistic regression. The sample comprised 85,851 youths. The results show that 12.5% of the youth have reached higher education or above, 65% have completed secondary education, and 18% have achieved primary education or less. According to the multinomial logistic regression analysis, the key factors influencing the attainment of higher education and above include age, gender, marital status, occupation, place of residence, the states and regions of residence, household size, and type of housing. The study underscores the need for establishment of policies to address the issues, including region-specific education strategies, improvements in rural educational infrastructure, gender equality initiatives, support systems for balancing work and education, financial aid for low-income students, and better housing conditions, so that it is able to create a more inclusive and equitable education system in Myanmar, promoting broader socio-economic development

Simple guide to starting a research group

Conducting cutting-edge research and scholarship becomes more complicated with each passing year; forming a collaborative research group offers a way to navigate this increasing complexity. Yet many individuals whose work might benefit from the formation of a collaborative team may feel overwhelmed by the prospect of attempting to build and maintain a research group. We propose this simple guide for starting and maintaining such an enterprise

Transparent Object Detection Using Faster R-CNN

"Recently, object detection has become a popular area in computer vision and object recognition. In many robotic researches, the most basic step is to perform object detection so that the reaction can be taken after detecting object location and its category. One of the main tasks for domestic robots is household object detection. In this paper, we intend to detect transparent objects such as glass in images. Compared with other kinds of objects, the detection of transparent object is very difficult to be performed using classical computer vision algorithms. Most of the classical computer vision algorithms implement the object detection based on their appearance such as colour or texture of the objects. However, the appearance of transparent objects changes according to different backgrounds and illumination conditions. With the popularity of object detection researches, deep learning algorithms now offer a high performance in detection of objects. Therefore, we apply one of the deep learning models called Faster R-CNN (Regions with Convolutional Neural Network) to perform detection of transparent objects and evaluate the performance of the system. According to experimental results, the system achieves 89.8% mAP in the detection of transparent objects. Keywords – Computer vision and object recognition, Deep learning, Domestic robots, Faster R-CNN, Transparent object detection

QoS-aware Traffic Management in Software Defined Networking

Software defined networking (SDN) provides effective traffic management solution by separating control and data planes, global centralization control, and being programmable. And, the traditional shortest path routing cannot provide effective traffic engineering because it only aware shortest path. The constraint-aware routing is more efficient than the traditional shortest path routing, however, it needed to estimate constraints such as link capacity, delay, jitter, and so on and it cannot guarantee the future traffic demands. This paper proposed QoS-aware traffic management method in SDN to guarantee the QoS-aware traffic by selecting the optimal path based on the estimated constraints. First, the proposed traffic management method categorized traffic classes: QoS-aware traffic and non QoS-aware traffic classes. Then, the proposed method estimated the QoS parameters and calculated the optimal path based on the estimated parameters. Finally, the QoS-aware traffic routed with the optimal path and non QoS-aware traffic simply routed through the shortest path. The proposed method is validated by using network emulator, Mininet and SDN controller, ONOS. The experiment results of throughput and packet loss show that our proposed method outperformed the other two traffic management methods

Comparison of Data Mining Classification Algorithms, C5.0 and CART for Car Evaluation and Credit Card Information Datasets

Data mining is the use of algorithm to discoverenormous amount of data automatically by searchinghidden information from large data sets usingmultiple algorithms and techniques. Differentmethods and algorithms are available in data miningsystem. Classification and prediction are the mostcommon method used to make out models and predictprobable data patterns and can be solving severalproblems in different domains like education,medicine, business, and science. In the presentscenario, as almost everything is becomingcomputerized, various classifications algorithms havebeen developed to make the automatic decisionprocess. The Decision Tree is an imperativeclassification method in data mining classification.This paper provides a comparison between two datamining classification algorithms: C5.0 and CART(classification and regression tree) applied on twodifferent UCI datasets: car evaluation dataset andcredit card dataset