A comprehensive review of vehicle detection using computer vision

A crucial step in designing intelligent transport systems (ITS) is vehicle detection. The challenges of vehicle detection in urban roads arise because of camera position, background variations, occlusion, multiple foreground objects as well as vehicle pose. The current study provides a synopsis of state-of-the-art vehicle detection techniques, which are categorized according to motion and appearance-based techniques starting with frame differencing and background subtraction until feature extraction, a more complicated model in comparison. The advantages and disadvantages among the techniques are also highlighted with a conclusion as to the most accurate one for vehicle detection

Utilization of waste as a constituent ingredient for enhancing thermal performance of bricks – a review paper

In view of the environmental regulations, practitioners have been inclined to use bricks with higher insulation capability, however with minimal attention to sustainable material composition, let alone waste material. From a research perspective, in the wake of the growing concerns for the environment, the use of waste material to develop bricks which can exhibit suitable characteristics attributed to the material composition has been on the rise. However, the extant literature on utilization of waste materials for brick mix design has neglected to provide detailed literature review on the influence of waste materials on the thermal performance of bricks. Methods: This paper provides detailed review of research conducted on thermal properties of bricks produced from various types of waste. Influence of the method of manufacturing and type of waste on thermal performance of bricks is discussed. A sustainability selection criteria format is provided to assist optimal decision making in considering alternative sustainable waste material. Findings: A sustainability selection criteria format is provided to assist optimal decision making in considering alternative sustainable waste material. Applications: The outcome of this paper can serve as a common reference for practitioners and researchers attempting to seek out solutions for further improving overall quality of thermally insulated waste-incorporated bricks, paving the way for more focused research on waste utilization in the development of more sustainable wall material based on the current brick production process

Breast cancer diagnosis using the fast learning network algorithm

The use of machine learning (ML) and data mining algorithms in the diagnosis of breast cancer (BC) has recently received a lot of attention. The majority of these efforts, however, still require improvement since either they were not statistically evaluated or they were evaluated using insufficient assessment metrics, or both. One of the most recent and effective ML algorithms, fast learning network (FLN), may be seen as a reputable and efficient approach for classifying data; however, it has not been applied to the problem of BC diagnosis. Therefore, this study proposes the FLN algorithm in order to improve the accuracy of the BC diagnosis. The FLN algorithm has the capability to a) eliminate overfitting, b) solve the issues of both binary and multiclass classification, and c) perform like a kernel-based support vector machine with a structure of the neural network. In this study, two BC databases (Wisconsin Breast Cancer Database (WBCD) and Wisconsin Diagnostic Breast Cancer (WDBC)) were used to assess the performance of the FLN algorithm. The results of the experiment demonstrated the great performance of the suggested FLN method, which achieved an average of accuracy 98.37%, precision 95.94%, recall 99.40%, F-measure 97.64%, G-mean 97.65%, MCC 96.44%, and specificity 97.85% using the WBCD, as well as achieved an average of accuracy 96.88%, precision 94.84%, recall 96.81%, F-measure 95.80%, G-mean 95.81%, MCC 93.35%, and specificity 96.96% using the WDBC database. This suggests that the FLN algorithm is a reliable classifier for diagnosing BC and may be useful for resolving other application-related problems in the healthcare sector

A review of forest fire surveillance technologies: Mobile ad-hoc network routing protocols perspective

Mobile Ad-Hoc Network (MANET) is a type of structure-less wireless mobile network, in which each node plays the role of the router and host at the same time. MANET has gained increased interest from researchers and developers for various applications such as forest fire detection. Forest fires require continuous monitoring and effective communication, technology, due to the big losses are brought about by this event. As such, disaster response and rescue applications are considered to be a key application of the MANET. This paper gives an extensive review of the modern techniques used in the forest fire detection based on recent MANET routing protocols such as reactive Location-Aided Routing (LAR), proactive Optimized Link State Routing (OLSR) and LAR-Based Reliable Routing Protocol (LARRR)

Smartphone’s off grid communication network by using Arduino microcontroller and microstrip antenna

After a major disaster, the present communication system fails in providing the services in the affected area. No means of communication proves to be more dangerous as the rescue and relief operations become more difficult. Our current research is about establishing a network in such a disaster-prone area, which would facilitate to communicate and carry out the rescue missions. This research project used Java to create a fire-chat application and used it with the smartphone android system. It used Bluetooth model HC-05 linked with Arduino UNO by the SPI interface to connect Arduino with the smartphone. The FR-model HCW69 connected with Arduino by using UART to transceiver the message. The microstrip antenna 915 MHz connected with the FR-model HCW69 to give us more distance. The maximum effective range of the transceiver was 1 kilometer, to communicate by forming a mesh network. This application is helpful in the case when the smartphone is out of service; it (smartphone) can be communicated connected to the other nearby users with a message

Implantable slot antenna with substrate integrated waveguide for biomedical applications

This work presents a new design of capsule slot antenna with substrate integrated waveguide (SIW) for wireless body area networks (WBANs) operating at the range of (2.5-4 GHz) which is located in the body area networks (BAN) standard in IEEE802.15.6. The proposed antenna was designed for WBANs. The substrate is assumed to be from Rogers 5880 with relative permittivity of 2.2, and thickness of 0.787 mm. The ground and the patch are created from annealed copper while the capsule is assumed to be a plastic material of medical grade polycarbonate. The antenna designed and summited using computer simulation technology (CST) software. A CST voxel model was used to study the performance of SIW capsule antenna and the ability of the band (2.5-4 GHz). Results indicated a wide bandwidth of 1.5 GHz between the range of (2.5-4) GHz at 3.3 GHz as center frequency, with return loss with more than -24.52 dB, a gain of -18.2 dB, voltage standing wave ratio (VSWR) of 1.17, and front-to-back ratio (FBR) of 10.07 dB. Through simulation, all considerable parameters associated with the proposed antenna including return loss, bandwidth, operating frequency, VSWR less than 2, radiation pattern were examined. Regarding size, gain, and frequency band, the proposed antenna is located with the standards of implantable medical devices (IMDs)

Smartphone’s off grid communication network by using Arduino microcontroller and microstrip antenna

After a major disaster, the present communication system fails in providing the services in the affected area. No means of communication proves to be more dangerous as the rescue and relief operations become more difficult. Our current research is about establishing a network in such a disaster-prone area, which would facilitate to communicate and carry out the rescue missions. This research project used Java to create a fire-chat application and used it with the smartphone android system. It used Bluetooth model HC-05 linked with Arduino UNO by the SPI interface to connect Arduino with the smartphone. The FR-model HCW69 connected with Arduino by using UART to transceiver the message. The microstrip antenna 915 MHz connected with the FR-model HCW69 to give us more distance. The maximum effective range of the transceiver was 1 kilometer, to communicate by forming a mesh network. This application is helpful in the case when the smartphone is out of service; it (smartphone) can be communicated connected to the other nearby users with a message

Detection and Classification of Conflict Flows in SDN Using Machine Learning Algorithms

Software-Defined Networking (SDN) is a new type of technology that embraces high flexibility and adaptability. The applications in SDN have the ability to manage and control networks while ensuring load balancing, access control, and routing. These are considered the most significant benefits of SDN. However, SDN can be influenced by several types of conflicting flows which may lead to deterioration in network performance in terms of efficiency and optimisation. Besides, SDN conflicts occur due to the impact and adjustment of certain features such as priority and action. Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. As a result, this paper presents several machine learning algorithms that include Decision Tree (DT), Support Vector Machine (SVM), Extremely Fast Decision Tree (EFDT) and Hybrid (DT-SVM) for detecting and classifying conflicting flows in SDNs. The EFDT and hybrid DT-SVM algorithms were designed and deployed based on DT and SVM algorithms to achieve improved performance. Using a range flows from 1000 to 100000 with an increment of 10000 flows per step in two network topologies namely, Fat Tree and Simple Tree Topologies, that were created using the Mininet simulator and connected to the Ryu controller, the performance of the proposed algorithms was evaluated for efficiency and effectiveness across a variety of evaluation metrics. The experimental results of the detection of conflict flows show that the DT and SVM algorithms achieve accuracies of 99.27% and 98.53% respectively while the EFDT and hybrid DT-SVM algorithms achieve respective accuracies of 99.49% and 99.27%. In addition, the proposed EFDT algorithm achieves 95.73% accuracy on the task of classification between conflict flow types. The proposed EFDT and hybrid DT-SVM algorithms show a high capability of SDN applications to offer fast detection and classification of conflict flows

Forest Fire Detection Using New Routing Protocol

The Mobile Ad-Hoc Network (MANET) has received significant interest from researchers for several applications. In spite of developing and proposing numerous routing protocols for MANET, there are still routing protocols that are too inefficient in terms of sending data and energy consumption, which limits the lifetime of the network for forest fire monitoring. Therefore, this paper presents the development of a Location Aided Routing (LAR) protocol in forest fire detection. The new routing protocol is named the LAR-Based Reliable Routing Protocol (LARRR), which is used to detect a forest fire based on three criteria: the route length between nodes, the temperature sensing, and the number of packets within node buffers (i.e., route busyness). The performance of the LARRR protocol is evaluated by using widely known evaluation measurements, which are the Packet Delivery Ratio (PDR), Energy Consumption (EC), End-to-End Delay (E2E Delay), and Routing Overhead (RO). The simulation results show that the proposed LARRR protocol achieves 70% PDR, 403 joules of EC, 2.733 s of E2E delay, and 43.04 RO. In addition, the performance of the proposed LARRR protocol outperforms its competitors and is able to detect forest fires efficiently

MANET Routing Protocols Evaluation: AODV, DSR and DSDV Perspective

Mobile Ad Hoc Network (MANET) is a set of mobile nodes that communicate with each other to configure an immediate network without utilizing any of infrastructure, the centralized access point or centralized administration in multiple hop manner. There are a lot of routing protocols have been proposed in MANET which are different from each other in the performance and the mechanism. Therefore, the performance study of those protocols in different scenarios is needed. This paper presents the performance comparison between Dynamic Source Routing (DSR), Ad hoc on demand distance Vector Routing (AODV) as reactive routing protocols and Destination Sequenced Distance Vector (DSDV) as a proactive routing protocol to precisely determine which protocol is more effective. Network Simulator (NS) version 2.35 has used to simulate and evaluate the performance of these protocols in terms of the packet delivery ratio, average throughput, average end-to-end delay, and packet loss ratio with respect to the variable number of nodes