Dr. Qamar Ul Islam D.Engg. B.Tech. M.Tech. Ph.D. FHEA

We aimed to improve the performance of ship detection methods in synthetic aperture radar (SAR) images by utilizing machine learning (ML) and artificial intelligence (AI) techniques. The maritime industry faces challenges in collecting precise data due to constantly changing sea conditions and weather, which can affect various maritime operations, such as maritime security, rescue missions, and real-time monitoring of water boundaries. To overcome these challenges, we present a survey of AI-… Show more

We aimed to improve the performance of ship detection methods in synthetic aperture radar (SAR) images by utilizing machine learning (ML) and artificial intelligence (AI) techniques. The maritime industry faces challenges in collecting precise data due to constantly changing sea conditions and weather, which can affect various maritime operations, such as maritime security, rescue missions, and real-time monitoring of water boundaries. To overcome these challenges, we present a survey of AI- and ML-based techniques for ship detection in SAR images that provide a more effective and reliable way to detect and classify ships in a variety of weather conditions, both onshore and offshore. We identified key features frequently used in the existing literature and applied the graph theory matrix approach (GTMA) to rank the available methods. This study’s findings can help users select a quick and efficient ship detection and classification method, improving the accuracy and efficiency of maritime operations. Moreover, the results of this study will contribute to advancing AI- and ML-based techniques for ship detection in SAR images, providing a valuable resource for the maritime industry. Show less

Simultaneous Localization and Mapping (SLAM) is a crucial technology for intelligent mobile robots to operate successfully in unknown environments. While many excellent SLAM systems have been developed in recent years, most assume that the environment is static, resulting in poor performance in dynamic environments. To address this limitation, we propose multiview stereo (MVS)-SLAM (MVS-SLAM), a real-time semantic RGBD SLAM system with improved-multiview geometry, built on the RGBD mode of… Show more

Simultaneous Localization and Mapping (SLAM) is a crucial technology for intelligent mobile robots to operate successfully in unknown environments. While many excellent SLAM systems have been developed in recent years, most assume that the environment is static, resulting in poor performance in dynamic environments. To address this limitation, we propose multiview stereo (MVS)-SLAM (MVS-SLAM), a real-time semantic RGBD SLAM system with improved-multiview geometry, built on the RGBD mode of ORB-SLAM3. MVS-SLAM tightly integrates semantic and geometric information to tackle the challenges posed by dynamic scenes. To meet the real-time requirements, the semantic module leverages the latest and fastest object detection network, YOLOv7, to provide semantic prior knowledge for the geometric module. We introduce a novel geometric constraint method that capitalizes on depth images and semantic information to recover three-dimensional (3D) feature points and initial camera pose. We use a 3D coordinate error threshold to identify dynamic points and remove them using the K-means clustering algorithm. This approach effectively reduces the impact of dynamic points. We validate MVS-SLAM using challenging dynamic sequences from the TUM data set, demonstrating that it significantly improves localization accuracy and system robustness in all types of dynamic environments. Show less

Purpose

Many popular simultaneous localization and mapping (SLAM) techniques have low accuracy, especially when localizing environments containing dynamically moving objects since their presence can potentially cause inaccurate data associations. To address this issue, the proposed FADM-SLAM system aims to improve the accuracy of SLAM techniques in environments containing dynamically moving objects. It uses a pipeline of feature-based approaches accompanied by sparse optical flow and… Show more

Purpose

Many popular simultaneous localization and mapping (SLAM) techniques have low accuracy, especially when localizing environments containing dynamically moving objects since their presence can potentially cause inaccurate data associations. To address this issue, the proposed FADM-SLAM system aims to improve the accuracy of SLAM techniques in environments containing dynamically moving objects. It uses a pipeline of feature-based approaches accompanied by sparse optical flow and multi-view geometry as constraints to achieve this goal.

Design/methodology/approach

FADM-SLAM, which works with monocular, stereo and RGB-D sensors, combines an instance segmentation network incorporating an intelligent motion detection strategy (iM) with an optical flow technique to improve location accuracy. The proposed AS-SLAM system comprises four principal modules, which are the optical flow mask and iM, the ego motion estimation, dynamic point detection and the feature-based extraction framework.

Findings

Experiment results using the publicly available RGBD-Bonn data set indicate that FADM-SLAM outperforms established visual SLAM systems in highly dynamic conditions.

Originality/value

In summary, the first module generates the indication of dynamic objects by using the optical flow and iM with geometric-wise segmentation, which is then used by the second module to compute the starting point of a posture. The third module, meanwhile, first searches for the dynamic feature points in the environment, and second, eliminates them from further processing. An algorithm based on epipolar constraints is implemented to do this. In this way, only the static feature points are retained, which are then fed to the fourth module for extracting important features Show less

It is significant for port ship scheduling and traffic management to be able to obtain more precise location and shape information from ship instance segmentation in SAR pictures. Instance segmentation is more challenging than object identification and semantic segmentation in high-resolution RS images. Predicting class labels and pixel-wise instance masks is the goal of this technique, which is used to locate instances in images. Despite this, there are now just a few methods available for… Show more

It is significant for port ship scheduling and traffic management to be able to obtain more precise location and shape information from ship instance segmentation in SAR pictures. Instance segmentation is more challenging than object identification and semantic segmentation in high-resolution RS images. Predicting class labels and pixel-wise instance masks is the goal of this technique, which is used to locate instances in images. Despite this, there are now just a few methods available for instance segmentation in high-resolution RS data, where a remote-sensing image’s complex background makes the task more difficult. This research proposes a unique method for YOLOv7 to improve HR-RS image segmentation one-stage detection. First, we redesigned the structure of the one-stage fast detection network to adapt to the task of ship target segmentation and effectively improve the efficiency of instance segmentation. Secondly, we improve the backbone network structure by adding two feature optimization modules, so that the network can learn more features and have stronger robustness. In addition, we further modify the network feature fusion structure, improve the module acceptance domain to increase the prediction ability of multi-scale targets, and effectively reduce the amount of model calculation. Finally, we carried out extensive validation experiments on the sample segmentation datasets HRSID and SSDD. The experimental comparisons and analyses on the HRSID and SSDD datasets show that our model enhances the predicted instance mask accuracy, enhancing the instance segmentation efficiency of HR-RS images, and encouraging further enhancements in the projected instance mask accuracy. The suggested model is a more precise and efficient segmentation in HR-RS imaging as compared to existing approaches. Show less

Land use is a process that turns a piece of land’s natural ecosystem into an artificial one. The mix of plant and man-made covers on the Earth’s surface is known as land cover. Land use is the primary external force behind change in land cover, and land cover has an impact on how land use is carried out, resulting in a synergistic interaction between the two at the Earth’s surface. In China’s Shandong Peninsula city cluster, Dongying is a significant coastal port city. It serves as the… Show more

Land use is a process that turns a piece of land’s natural ecosystem into an artificial one. The mix of plant and man-made covers on the Earth’s surface is known as land cover. Land use is the primary external force behind change in land cover, and land cover has an impact on how land use is carried out, resulting in a synergistic interaction between the two at the Earth’s surface. In China’s Shandong Peninsula city cluster, Dongying is a significant coastal port city. It serves as the administrative hub for the Yellow River Delta and is situated in Shandong Province, China’s northeast. The changes in its urban land use and land cover in the future are crucial to understanding. This research suggests a prediction approach that combines a patch-generation land use simulation (PLUS) model and long-term short-term memory (LSTM) deep learning algorithm to increase the accuracy of predictions of future land use and land cover. The effectiveness of the new method is demonstrated by the fact that the average inaccuracy of simulating any sort of land use in 2020 is around 5.34%. From 2020 to 2030, 361.41 km2 of construction land is converted to cropland, and 424.11 km2 of cropland is converted to water. The conversion areas between water and unused land and cropland are 211.47 km2 and 148.42 km2, respectively. The area of construction land and cropland will decrease by 8.38% and 3.64%, respectively, while the area of unused land, water, and grassland will increase by 5.53%, 2.44%, and 0.78%, respectively. Show less

Purpose
Developing graduate students' academic writing has been a major concern for many scholars over the past few years. Existing literature on the challenges of thesis writing has not focused on master's students in English language teaching (ELT). Data on the challenges have been mainly gathered from the theses and focused on the structure and genre requirements. Few available studies have investigated such challenges through the lens of supervisors in an international context. Knowledge… Show more

Purpose
Developing graduate students' academic writing has been a major concern for many scholars over the past few years. Existing literature on the challenges of thesis writing has not focused on master's students in English language teaching (ELT). Data on the challenges have been mainly gathered from the theses and focused on the structure and genre requirements. Few available studies have investigated such challenges through the lens of supervisors in an international context. Knowledge about the factors hindering the thesis writing process of non-native MA students in English from the supervisors' perspectives is scarce. This study attempts to fill these gaps by answering this question: From supervisors' perspectives, what factors hinder the thesis writing process of non-native MA students?

Design/methodology/approach
Thirty supervisors from state and private universities across Iran voluntarily participated in this qualitative study. Drawing upon teachers' diaries and semi-structured interviews, the authors identified major factors negatively influencing the thesis work of master's students. Data were transferred into NVivo 10 and analyzed thematically following Colaizzi's method.

Findings
The study found that factors constraining students' writing were (1) students' lack of effort, (2) students' lack of a strategy for writing, (3) students' lack of autonomy and (4) students' absence of voice.

Originality/value
The authors discuss the practical implications of these factors for different stakeholders. There is a growing interest in postgraduate students' thesis writing processes. Surprisingly, no research exists on supervisors' perceptions of factors that constrain the thesis writing process of non-native English master's students. Show less

As a source of green energy, solar energy provides a clean way for the production of heat and electricity. PV solar panels, in particular, have been extensively applied for the production of electricity with reasonable operating costs and fewer environmental in comparison to fossil fuels. Previous studies suggest that the PV panel’s temperature decreases its power generation. The current study compares the productivity of photovoltaic panels in the capital city of Kuala Lumpur with the coolest… Show more

As a source of green energy, solar energy provides a clean way for the production of heat and electricity. PV solar panels, in particular, have been extensively applied for the production of electricity with reasonable operating costs and fewer environmental in comparison to fossil fuels. Previous studies suggest that the PV panel’s temperature decreases its power generation. The current study compares the productivity of photovoltaic panels in the capital city of Kuala Lumpur with the coolest city of Malaysia namely Cameron Highlands. Typical KC200GT Photovoltaic Panel was used as a common PV model, and the analysis was performed in MATLAB Editor. When giving information on solar irradiation and panel temperature, the model output illustrated the I-V, P-V, and P-I characteristics. The result of the study confirms that the photovoltaic panel power output is significantly higher in the coolest city of Malaysia (Cameron Highlands) comparing the capital city (Kuala Lumpur). Show less

Scheffler solar reflector has been used internationally more than two decades. invented by Wolfgang Scheffler. This collector harvests the solar energy and has a fixed focal point and sun tracking system. the current study aims to conduct a exhaustive review on Scheffler solar collectors and its implications. Scheffler fixed focus concentrators, Parabolic Scheffler reflectors, Techniques used in Scheffler, Applications, Concentrated Solar Power (CSP), Concentrated Solar Technologies (CST), and… Show more

Scheffler solar reflector has been used internationally more than two decades. invented by Wolfgang Scheffler. This collector harvests the solar energy and has a fixed focal point and sun tracking system. the current study aims to conduct a exhaustive review on Scheffler solar collectors and its implications. Scheffler fixed focus concentrators, Parabolic Scheffler reflectors, Techniques used in Scheffler, Applications, Concentrated Solar Power (CSP), Concentrated Solar Technologies (CST), and Design Factors of Scheffler are areas this study focus. Show less

Phase angle control method is applied to ac circuits (a triac based ac regulator). The power device used in phase angle controllers is a thyristor – mostly triacs or SCR. The power flow to the load is controlled by delaying the triggering angle in each half-cycle of the power device [5].

When the thyristor is turned on by a gating signal and the current is higher than the holding current, the thyristor stays on. This is the natural line commutation. In this case (grid tied) inverter, two… Show more

Phase angle control method is applied to ac circuits (a triac based ac regulator). The power device used in phase angle controllers is a thyristor – mostly triacs or SCR. The power flow to the load is controlled by delaying the triggering angle in each half-cycle of the power device [5].

When the thyristor is turned on by a gating signal and the current is higher than the holding current, the thyristor stays on. This is the natural line commutation. In this case (grid tied) inverter, two phase controlled converters (half-wave) are used. In this case two gate signal (pulse) is required in both the half cycles.

The circuit, code and simulation of an example are discussed later. For the sake of simulation, an ac regulator is studied. First this is triggered by two gate signals. Therefore, in phase angle control, a gate pulse is sent to the triac. When the triac turn on, it stays on until the current through it becomes zero (natural line commutation).

The voltage is supplied to the load for a fraction of the cycle, determined by how long the triac is on, which is determined by the delay time between the zero-crossing and the applying of the triac gating signal.

Here the zero-crossing is first checked. After zero-crossing occurs, a small delay is present before the triac is triggered. (Here, it is 2ms) So, the triac is triggered after 2ms when the zero-crossing occurs. Then the gate signal is generated for 250μs. It is enough time to ensure that the triac has turned on. Even though the gating signal is removed, the triac stays on until the next zero-crossing as it is a latching device.
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As wireless control is widely used nowadays because of their wide range of control. The wireless controlled robots use RF circuits, which were run-over by wireless control using mobile network, but both have the drawbacks of limited range & operation. The operation of control using mobile network is limited with the availability of cellular network. This drawback can be removed by replacing cellular signal with satellite signal. This enables the user to control the robot in remote areas… Show more

As wireless control is widely used nowadays because of their wide range of control. The wireless controlled robots use RF circuits, which were run-over by wireless control using mobile network, but both have the drawbacks of limited range & operation. The operation of control using mobile network is limited with the availability of cellular network. This drawback can be removed by replacing cellular signal with satellite signal. This enables the user to control the robot in remote areas too.

The operation of control using RF circuits have a limited range, limited frequency, whereas cellular network has a broad range but cannot be used in remote areas. So to overcome these drawbacks, satellite network can be used. As using a satellite phone would sharply increase the cost of the project, so by converting a GSM Phone to a satellite phone is an easy way to reduce the cost of the project. This can be done by using the Thuyara Sat Sleeve gadget, which will convert a simple GSM Phone to a satellite phone. It has robust control, a wide range (where satellite signals are present i.e. in 154 countries) and we can have up to 12 controls. Show less