Volume 1, Issue 1
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This issue presents five papers exploring diverse technological applications. The first paper examines the use of UAVs and deep learning for real-time disaster mapping and object detection. The second explores the intersection of machine learning and digital art, raising questions about authenticity. The third conducts a literature review on peer-to-peer networks, highlighting security and privacy challenges. The fourth focuses on optimizing telemedicine over satellite networks to improve remote healthcare. The fifth compares the use of natural and synthetic indicators in acid-base titration, advocating for environmentally-friendly green indicators. Together, these studies demonstrate the interdisciplinary nature of modern technological research and its societal impact across multiple domains.
Front Cover
Publication Month: January 2022, Page(s): i – iÂ
Editorial Board
Publication Month: January 2022, Page(s): ii – ii
Editorial
Publication Month: January 2022, Page(s): iii – iv
Table of Contents
Publication Month: January 2022, Page(s): v – v
Visual Slam-Based Mapping and Localization for Aerial Images
Onur Eker, Hakan Cevikalp, Hasan Saribas
J. Engg. Res. & Sci. 1(1), 1-9 (2022);
Fast and accurate observation of an area in disaster scenarios such as earthquake, flood and avalanche is crucial for first aid teams. Digital surface models, orthomosaics and object detection algorithms can play an important role for rapid decision making and response in such scenarios. In recent years, Unmanned Aerial Vehicles (UAVs) have become increasingly popular because of their ability to perform different tasks at lower costs. A real-time orthomosaic generated by using UAVs can be helpful for various tasks where both speed and efficiency are required. An orthomosaic provides an overview of the area to be observed, and helps the operator to find the regions of interest. Then, object detection algorithms help to identify the desired objects in those regions. In this study, a monocular SLAM based system, which combines the camera and GPS data of the UAV, has been developed for mapping the observed environment in real-time. A deep learning based state-of-the-art object detection method is adapted to the system in order to detect objects in real time and acquire their global positions. The performance of the developed method is evaluated in both single and multiple UAVs scenarios.
Neural Networks and Digital Arts: Some Reflections
Rômulo Augusto Vieira Costa, Flávio Luiz Schiavoni
J. Engg. Res. & Sci. 1(1), 10-18 (2022);
The Constant advancement in the area of machine learning has unified some areas that until then di a of computing with the arts in general. With the emergence of digital art, people have become increasingly interested in the development of expressive techniques and algorithms for creating works of art, whether in the form of music, image, aesthetic artifacts, or even combinations of these forms, usually being applied in an interactive technology installation. Due to their high diversity of creation and complexity during processing, neural networks have been used to create these digital works, which present results that are difficult to reproduce by human hand and are usually presented in museums, conferences, or even at auctions, being sold at high prices. The fact that these works are gaining more and more recognition in the art scene, ended up raising some questions about authenticity and art. In this way, this work aims to address the historical context regarding the advancement of the area of machine learning, addressing the evolution of neural networks in this field, about what art would be and who would be the artist responsible for digital work, given that despite After performing a good part of the creation process, the computer does not perform the entire process, becoming dependent on the programmer, who in turn is responsible for defining parameters, techniques and, above all, concepts that will attribute all the aesthetic value to the work. From this point of view and the growing interest in the generation of art via computers, the present work presents applied research around neural network techniques and how they can be applied in artistic practice, either generating visual elements or generating visual elements or generating sound elements. Finally, perspectives for the future are presented and how this area can evolve even further.
A State-of-the-Art Survey of Peer-to-Peer Networks: Research Directions, Applications and Challenges
Frederick Ojiemhende Ehiagwina, Nurudeen Ajibola Iromini, Ikeola Suhurat Olatinwo, Kabirat Raheem, Khadijat Mustapha
J. Engg. Res. & Sci. 1(1), 19-38 (2022);
Centralized file-sharing networks have low reliability, scalability issues, and possess a single point of failure, thus making peer-to-peer (P2P) networks an attractive alternative since they are mostly anonymous, autonomous, cooperative, and decentralized. Although, there are review articles on P2P overlay networks and technologies, however, other aspects such as hybrid P2P networks, modelling of P2P, trust and reputation management issues, coexistence with other existing networks, and so on have not been comprehensively reviewed. In addition, existing reviews were limited to articles published in or before 2012. This paper performs a state-of-the-art literature survey on the emerging research areas of P2P networks, applications and ensuing challenges along with proposed solutions by scholars. The literature search for this survey was limited to the top-rated publisher of scholarly articles. This research shows that issues with security, privacy, the confidentiality of information and trust management will need greater attention, especially in sensitive applications like health services and vehicle to vehicle communication ad hoc networks. In addition, more work is needed in developing solutions to effectively investigate and curb deviant behaviours among some P2P networks.
Analytical Framework to Minimize the Latency in Tele-herbal Healthcare Service
Ogirima Sanni Abubakar Omuya, Arulogun Oladiran Tayo
J. Engg. Res. & Sci. 1(1), 39-50 (2022);
Telemedicine is using telecommunications and IT and other ICT tools to widen healthcare services to remote rural areas. ICT global coverage, multicasting ability, and the high capacity of satellites in GEO can be served as an instrument to widen and enhance the high quality of healthcare service to remote rural areas. Long end-to-end latency could be attributed to the GEO satellites that demean the performance of data communications that can lead to underutilization of the high available capacity due to high link errors and the long latency. The real latency of GEO satellites could be 200ms or above, which can leads to capacity utilization as lower as 37% with a maximum of 458kbps obtainable capacity of the test from LAUTECH Ogbomoso (service provider). The TCP performance can be enhanced through the adoption of other necessary transmission protocols for testing and investigating any possible modifications to improve the performance over the satellite and hybrid channels network. TCP performances largely depend on its loss recovery. To minimize latency, the network must have the necessary resources to provide quality communication within the shortest latency times to perform its required real-time transmission. To transmit from node to node it needs a minimum of 3123.2 1KB and a maximum of 5683.2 1KB packets to go from each connection.
Comparative Analysis of Curcuma longa Rhizome and Tectona grandis Leaves Extracts as Green Indicators versus some Synthetic Indictors in Acid-Base Titration
Kaana Asemave, Agube Solomon Shiebee
J. Engg. Res. & Sci. 1(1), 51-55 (2022);
The work considered comparative analysis of CRI (Curcuma longa rhizome extract indicator) and TLI (Tectona grandis leaves extract indicator) as green indicators versus some synthetic indicators in acid – base titration involving HCl-NaOH, CH3COOH-NaOH, CH3COOH -NH4OH, and HCl-NH4OH. The codes used were SA (strong acid), SB (strong base), WA (weak acid) and WB (weak base). 10 mL of the base with three drops of the CRI, TLI, MO (methyl orange), and PL (phenolphthalein) were used. Prior to the titrations, the extracts of Curcuma longa rhizome and Tectona grandis leaves were tested for their colours in acidic and basic media. Also, the UV-visible absorptions of the extracts were determined. There were sharp colours of yellow (for CRI) and red (for TLI) in acid and brown (for CRI) and black (for TLI) in base media. Meanwhile, CRI absorbed (absorbance of 0.83-0.85) substantially at 400-450 nm, but gave lesser absorption at 500-800 nm with absorbance of 0.55-0.24. On the other hand, TLI was found with higher absorbance (0.09) at 400 nm and lesser absorption (absorbance ~0.04) at 720 nm. The titre values of 10.95±0.95 mL (SA-SB), 13.75±0.15 mL (WA-SB), 2.15±0.15 mL (WA-WB), 1.85±0.05 mL (SA-WB) and 11.70±0.3 mL (SA-SB), 13.45±0.45 mL (WA-SB), 2.15±0.05 mL (WA-WB), 2.20±0 mL (SA-WB) were obtained for CRI and TLI, respectively. The results matched with the values 12.25±0.15 mL (SA-SB), 13.90±0.7 mL (WA-SB), 2.10±0.2 mL (WA-WB), and 3.00±0.6 mL (SA-WB) of PL and MO, respectively. It will be beneficial to us to replace the use of MO and PL as indicators with CRI and TLI, because these green indicators are more benign and also effective. This will facilitate the eradication of toxicity accruing from synthetic indicators, MO and PL. In the future, we are looking out to determining the pKa and stability of these natural indicators.
