arXiv subjects

Waseem Akram

Publications and source records attributed to Waseem Akram.

25 records · Page 2Linked to original sources

arXiv2023

Sorted Range Reporting and Range Minima Queries

Given an array A[1: n] of n elements drawn from an ordered set, the sorted range selection problem is to build a data structure that can be used to answer the following type of queries efficiently: Given a pair of indices i, j $ (1\le i\le j \le n)$, and a positive integer k, report the k smallest elements from the sub-array A[i: j] in order. Brodal et al. (Brodal, G.S., Fagerberg, R., Greve, M., and L{ó}pez-Ortiz, A., Online sorted range reporting. Algorithms and Computation (2009) pp. 173--182) introduced the problem and gave an optimal solution. After O(n log n) time for preprocessing, the query time is O(k). The space used is O(n). In this paper, we propose the only other possible optimal trade-off for the problem. We present a linear space solution to the problem that takes O(k log k) time to answer a range selection query. The preprocessing time is O(n). Moreover, the proposed algorithm reports the output elements one by one in non-decreasing order. Our solution is simple and practical. We also describe an extremely simple method for range minima queries (most of whose parts are known) which takes al most (but not exactly) linear time. We believe that this method may be, in practice, faster and easier to implement in most cases.

cs.DS↗

arXiv2023

Evaluating Deep Learning Assisted Automated Aquaculture Net Pens Inspection Using ROV

In marine aquaculture, inspecting sea cages is an essential activity for managing both the facilities' environmental impact and the quality of the fish development process. Fish escape from fish farms into the open sea due to net damage, which can result in significant financial losses and compromise the nearby marine ecosystem. The traditional inspection system in use relies on visual inspection by expert divers or ROVs, which is not only laborious, time-consuming, and inaccurate but also largely dependent on the level of knowledge of the operator and has a poor degree of verifiability. This article presents a robotic-based automatic net defect detection system for aquaculture net pens oriented to on-ROV processing and real-time detection. The proposed system takes a video stream from an onboard camera of the ROV, employs a deep learning detector, and segments the defective part of the image from the background under different underwater conditions. The system was first tested using a set of collected images for comparison with the state-of-the-art approaches and then using the ROV inspection sequences to evaluate its effectiveness in real-world scenarios. Results show that our approach presents high levels of accuracy even for adverse scenarios and is adequate for real-time processing on embedded platforms.

cs.CV↗

arXiv2023

Vision-Based Autonomous Navigation for Unmanned Surface Vessel in Extreme Marine Conditions

Visual perception is an important component for autonomous navigation of unmanned surface vessels (USV), particularly for the tasks related to autonomous inspection and tracking. These tasks involve vision-based navigation techniques to identify the target for navigation. Reduced visibility under extreme weather conditions in marine environments makes it difficult for vision-based approaches to work properly. To overcome these issues, this paper presents an autonomous vision-based navigation framework for tracking target objects in extreme marine conditions. The proposed framework consists of an integrated perception pipeline that uses a generative adversarial network (GAN) to remove noise and highlight the object features before passing them to the object detector (i.e., YOLOv5). The detected visual features are then used by the USV to track the target. The proposed framework has been thoroughly tested in simulation under extremely reduced visibility due to sandstorms and fog. The results are compared with state-of-the-art de-hazing methods across the benchmarked MBZIRC simulation dataset, on which the proposed scheme has outperformed the existing methods across various metrics.

cs.CV↗

arXiv2022

Dominance for Containment Problems

In a containment problem, the goal is to preprocess a set of geometric objects so that, given a geometric query object, we can report all the objects containing the query object. We consider the containment problem where input objects are homothetic triangles and the query objects considered are line segments, circles, and trapezoids with bases parallel to either axis. We show that this problem can be solved using the 3-d query dominance problem. The solutions presented can also be extended for higher dimensions.

cs.DS↗

arXiv2021

Point Enclosure Problem for Homothetic Polygons

In this paper, we investigate the homothetic point enclosure problem: given a set $S$ of $n$ triangles with sides parallel to three fixed directions, find a data structure for $S$ that can report all the triangles of $S$ that contain a query point efficiently. The problem is "inverse" of the homothetic range search problem. We present an $O(n\log n)$ space solution that supports the queries in $O(\log n + k)$ time, where $k$ is the output size. The preprocessing time is $O(n\log n)$. The same results also hold for homothetic polygons.

cs.CG↗

arXiv2017

A Formal Specification Framework for Smart Grid Components

Smart grid can be considered as the next step in the evolution of power systems. It comprises of different entities and objects ranging from smart appliances, smart meters, generators, smart storages, and more. One key problem in modeling smart grid is that while currently there is a considerable focus on the practical aspects of smart grid, there are very few modeling attempts and even lesser attempts at formalization. To the best of our knowledge, among other formal methods, formal specification has previously not been applied in the domain of smart grid. In this paper, we attempt to bridge this gap by presenting a novel approach to modeling smart grid components using a formal specification approach. We use a state-based formal specification language namely Z (pronounced as `Zed') since we believe Z is particularly suited for modeling smart grid components.We demonstrate the application of Z on key smart grid components. The presented formal specification can be considered as first steps towards modeling of smart grid using a Software Engineering formalism. It also demonstrates how complex systems, such as the smart grid, can be modeled elegantly using formal specification.

cs.LO↗

arXiv2017

Towards Agent-Based Model Specification in Smart Grid: A Cognitive Agent-based Computing Approach

A smart grid can be considered as a complex network where each node represents a generation unit or a consumer. Whereas links can be used to represent transmission lines. One way to study complex systems is by using the agent-based modeling (ABM) paradigm. An ABM is a way of representing a complex system of autonomous agents interacting with each other. Previously, a number of studies have been presented in the smart grid domain making use of the ABM paradigm. However, to the best of our knowledge, none of these studies have focused on the specification aspect of ABM. An ABM specification is important not only for understanding but also for replication of the model. In this study, we focus on development as well as specification of ABM for smart grid. We propose an ABM by using a combination of agent-based and complex network-based approaches. For ABM specification, we use ODD and DREAM specification approaches. We analyze these two specification approaches qualitatively as well as quantitatively. Extensive experiments demonstrate that DREAM is a most useful approach as compared with ODD for modeling as well as for replication of models for smart grid.

cs.MA↗