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For the past decade, the main problem that has attracted researchers’ attention in aerial robotics is the position estimation or Simultaneous Localization and Mapping (SLAM) of Unmanned Aerial Vehicles (UAVs) where the GPS signal is poor or denied. This article reviews the strengths and weaknesses of existing methods in the field of aerial robotics. There are many different techniques and algorithms that are used to overcome the localization and mapping problem of these UAVs. These techniques and algorithms use different sensors, such as Red Green Blue-Depth (RGB_D), Light Detecting and Ranging (LIDAR), and Ultra-wideband (UWB). The most common technique is used, i.e., probability-based SLAM, which uses two algorithms: Linear Kalman Filter (LKF) and Extended Kalman Filter (EKF). LKF consists of five phases and this algorithm is just used for linear system problems. However, the EKF algorithm is used for non-linear systems. Aerial robots are used to perform many tasks, such as rescue, transportation, search, control, monitoring, and different military operations because of their vast top view. These properties are increasing their demand as compared to human service. In this paper, different techniques for the localization of aerial vehicles are discussed in terms of advantages and disadvantages, practicality and efficiency. This paper enables future researchers to find the suitable SLAM solution based on their problems; either the researcher is dealing with a linear problem or a non-linear problem.

Power augmentation in a small-scale horizontal axis wind turbine, with its rotor encased in a flanged diffuser is explored. The power output of the wind turbine varies with changes in the diffuser design and the resulting back pressure. Reduction in this back pressure also results in early flow separation at the diffuser surface, which hinders turbine performance. The main aim of this study is to numerically investigate the local configuration of the wind turbine location inside the diffuser by varying diffuser angles and wind speeds. Therefore, shroud and flange were modeled and analyzed using the computational fluid dynamic (CFD) analyses and experiments were performed at two wind speeds 6 m/s and 8 m/s with and without the diffuser for model validation. The divergence angle of 4° was found to have no flow separation, thus maximizing flow rate. The proposed design shows wind speed improvement of up to 1.68 times compared to the baseline configuration. The corresponding optimum flange height was found to be 250 mm. However, increasing the divergence angle had a similar output. The dimensionless location of wind turbine was found to be between 0.45 and 0.5 for 2° and 4° divergence angle respectively. Furthermore, the maximum augmentation location varies with wind speed and diffuser's divergence angle as described by dimensionless location of wind turbine, thus presenting a noteworthy contribution to the horizontal axis wind turbine area with the flanged diffuser. [ABSTRACT FROM AUTHOR]

Cloud computing is a technology that provides secure storage space for the customer’s massive data and gives them the facility to retrieve and transmit their data efficiently through a secure network in which encryption and decryption algorithms are being deployed. In cloud computation, data processing, storage, and transmission can be done through laptops and mobile devices. Data Storing in cloud facilities is expanding each day and data is the most significant asset of clients. The important concern with the transmission of information to the cloud is security because there is no perceivability of the client’s data. They have to be dependent on cloud service providers for assurance of the platform’s security. Data security and privacy issues reduce the progression of cloud computing and add complexity. Nowadays; most of the data that is stored on cloud servers is in the form of images and photographs, which is a very confidential form of data that requires secured transmission. In this research work, a public key cryptosystem is being implemented to store, retrieve and transmit information in cloud computation through a modified Rivest-Shamir-Adleman (RSA) algorithm for the encryption and decryption of data. The implementation of a modified RSA algorithm results guaranteed the security of data in the cloud environment. To enhance the user data security level, a neural network is used for user authentication and recognition. Moreover; the proposed technique develops the performance of detection as a loss function of the bounding box. The Faster Region-Based Convolutional Neural Network (Faster R-CNN) gets trained on images to identify authorized users with an accuracy of 99.9% on training. [ABSTRACT FROM AUTHOR]

The photovoltaic energy generation system is one of the most promising technology to meet our future electricity demand as well as mitigate climate change. This study aims to design, simulate and evaluate the performance of hybrid photovoltaic (PV) system using PVsyst software to supply electricity for energy efficient streetlights in educational institute. Meteonorm database of daily and monthly irradiation, temperatures, precipitation and sunlight hours are utilized while performing the analysis. The photovoltaic system consists of 56 bifacial-polycrystalline 360-watt PV modules having 17.9% efficiency. The photovoltaic modules were installed at 0° azimuth angle and 15° tilt angle. Two hybrid inverters with rated capacity of 10 kW are used. The energy storage system consists of 16 batteries (2 in series x 8 in parallel) with a nominal capacity of 1600 ampere-hours and discharging minimum SOC is 20 %. A total of 100 streetlight poles with 8 working-hours/day are installed to cover both sides of the road, with monthly energy consumption of 672 kilowatt-hours. The average annual ambient temperature is 23.66℃, and the annual GH irradiation is 1693 kilowatt-hour/m² . The annual production of the hybrid PV system is 25.96 MWh/year, the specific energy production of the system is 1288 kWh/kWp/year with 70.38% performance ratio. By means of proposed photovoltaic system for energy efficient street lightning structure, 157.9t CO2 is reduced. The project can save 0.004737 million tonnes of CO2 emissions over its lifetime of 30 years. The proposed system is a viable solution for public lighting with the right selection of system components. [ABSTRACT FROM AUTHOR]

Renewable energy resources are promising in power generation due to their sustainability aspect and environment friendliness as they are means of pollution free power production. Wind energy.y is utilized for power production with the help of wind turbines. The offshore and onshore windfarms consisting of horizontal axis wind turbines are major contributors in the wind energy. However, this type of turbine is not domestically viable mainly due to limitations of directionality and noise. Vertical axis wind turbines do not have these constraints and may blend in the urban environments. In built environments, the wind flow is quite complex due to large scale effects and turbulence. In this paper, the academic building of a university is studied as a possible platform for harnessing the wind energy resources. This case study is performed on academic blocks of University of Gujrat. These building environments were modeled and analyzed with computational fluid dynamic software to model the wind behavior on the building roof top. These results show that there is potential in setting up micro windfarms for the academic environments. The simulation for single building showed a potential for 61.8kW whereas this potential decreased substantially when terrain effects are considered using the circular arrangement for the simulation. [ABSTRACT FROM AUTHOR]

Purpose – Ontologies are used to formally describe the concepts within a domain in a machine-understandable way. Matching of heterogeneous ontologies is often essential for many applications like semantic annotation, query answering or ontology integration. Some ontologies may include a large number of entities which make the ontology matching process very complex in terms of the search space and execution time requirements. The purpose of this paper is to present a technique for finding degree of similarity between ontologies that trims down the search space by eliminating the ontology concepts that have less likelihood of being matched. Design/methodology/approach – Algorithms are written for finding key concepts, concept matching and relationship matching. WordNet is used for solving synonym problems during the matching process. The technique is evaluated using the reference alignments between ontologies from ontology alignment evaluation initiative benchmark in terms of degree of similarity, Pearson’s correlation coefficient and IR measures precision, recall and F-measure. Findings – Positive correlation between the degree of similarity and degree of similarity (reference alignment) and computed values of precision, recall and F-measure showed that if only key concepts of ontologies are compared, a time and search space efficient ontology matching system can be developed. Originality/value – On the basis of the present novel approach for ontology matching, it is concluded that using key concepts for ontology matching gives comparable results in reduced time and space. [ABSTRACT FROM AUTHOR]