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In vital energy applications especially the agricultural environments, the service of adaptive power utilization plays an essential role in facilitating the usage of Internet of Things systems. Such environments are distinguished by the large range of lands where most of the region lacks the commercial power lines. Reaching some high or deep sensing points is…

Soil moisture is one of the most important variables to monitor in agriculture. Its analysis gives insights about strategies to utilize better a particular area regarding its use, i.e., pasture for cows (or similar), production forests, or even to answer what crops should be planted. The vertical structure of the soil moisture plays an important…

Rescuers escorted search dogs into the disaster area, using their unique sense of smell to find the injured. First, researchers summarize the design requirements in the search process from interviews with rescuers, and construct a conceptual prototype to confirm the interaction mode between the user and the dog. User central design invited people melt into…

Environmental monitoring has gained significant importance in outdoor air quality measurement and assessment for fundamental survival as well as ambient assisted living. In real-time outdoor urban scale, instantaneous air quality index estimation, the electrochemical sensors warm-up time, cross-sensitivity computation-error, geo-location typography, instantaneous capacity or back up time; and energy efficiency are the six major challenges.…

Forest mapping by remote sensing is a hot topics in forestry. At present, many researchers focus on the research of forest type classification or tree species identification using different machine learning methods and try to improve the accuracy of classification of satellite image. However, forest type classification using deep belief network (DBN) is still limited…

The fast-paced development of smart technologies and the prevalence of vehicles, created an urgent demands to study and improve safety issues related to driving. In order to reduce traffic accidents, driving behavior was found to be very important issues to study and investigate. Recently, the advent and widespread of smartphone platforms with advanced computing competence…

In this paper we propose the application of supervised learning techniques to recognize stress situations in drivers by analyzing their Skin Potential Response (SPR) and the Electrocardiogram (ECG). A sensing device is used to acquire the SPR from both hands of the drivers, and the ECG from their chest. We also consider a motion artifact…

The large and ever-increasing variety of remote sensing sensors used in satellite imagery today explains why detecting changes between identical locations in images that are captured, at two separate times, from heterogeneous capturing systems is a major and challenging recent research problem in the field of satellite imaging for fast and accurate determination of temporal…

This paper addresses essential features/issues and proposes solutions that would improve the overall performance of a multi-phase buck converter. Low efficiency at light load is addressed with phase shedding, load fast transient and regulated output voltage spiking/dipping is addressed with novel helper technique at the point of load (output node). An Integrated current sensing is…

Age and growth are two essential rice biophysics parameters used to determine the health parameters and production rate. The spatial data of both parameters can utilize remote sensing technology, which in turn makes use of several vegetation indices to achieve accurate estimation. However, due to the rapid changes in rice plants’ characteristics, it is essential…

With the advent of the Internet of Things Technologies (IOT), smart homes, and smart city applications, E-Nose was created. Almost of gas sensors consisting the electronic nose system suffer from cross sensitivity and lack of selectivity. Coupling smart gas sensors with artificial intelligence algorithms can thus empower conventional gas sensing technologies and increase accuracy in…

In this paper, we present an experimental approach that allows a humanoid robot to effectively plan and execute whole body motions, like climbing obstacles and straight stairs up or down, besides jumping over obstacles using only on-board sensing. Re- liable and accurate motion sequence for humanoid employed in complex indoor en- vironments is a necessity…

Here the work approaches the detection of fruit maturity level. In addition, a gas sensor is proposed to obtain better sensitivity to know the level of ethylene gas released from matured fruit. Better sensitivity can be achieved by obtaining an enhanced active area, changing the intermediate layer thickness and the pitch value of the electrode.…

Content Based Image Retrieval (CBIR) for remote sensing image data is a tedious process due to high resolution and complexity of image interpretation. Development of feature extraction technique is a major portion to represent the image content in an optimal way. In this paper, we propose a feature descriptor which combines the color coherent pixel…

Person recognition using thermal imaging, multi-biometric traits, with groups of feature filters and classifiers, is the subject of this paper. These were used to tackle the problems of biometric systems, such as a change in illumination and spoof attacks. Using a combination of, hard and soft-biometric, attributes in thermal facial images. The hard-biometric trait, of…

Wireless sensor networks (WSNs) are considered to be the currently flourishing scientific domain, thereby found to be applicable in numerous industrial and domestic applications. As per the mathematical results in Pulse-coupled oscillator (PCO), it has been predicted that, numerous iterations are needed for convergence, leading to increased power consumption. Biologically inspired solutions are greatly applicable…

This work extends the development of the nonuniform Parallel Digital Ramp Pulse Position Modulation Analog-to-Digital Converter (PDRADC) architecture. The continuous to discrete transform of the PDRADC is achieved by partitioning the signal amplitude axis into P nonoverlapping partitions that sample the analog input at input signal driven instances. Each partition contains L uniform levels with…

Proportional navigation (PN) is a widely-used guidance law for missiletarget engagement. The goal of the missile intercept problem is to reduce the closest distance between the missile and target by diminishing the line-of-sight rate (LOS rate). In general, PN guidance law necessitates information of the LOS rate and missile velocity. The closing velocity (relative approaching…

This work introduces the design and prototype development of a novel optical-based fingertip force sensor, which is integrated in a bio-mimetic finger for robotic and prosthetic manipulation. Given the optical nature of the sensor, the proposed device is free of any electrical and metal components. Accordingly, the design improves manipulation of objects with high electromagnetic…

Recent standards, legislation, and best practices point to data center infrastructure management systems to control and monitor data center performance. This work presents an innovative approach to address some of the challenges that currently hinder data center management. It explains how monitoring and management systems should be envisioned and implemented. Key parameters associated with data…

One of the most important roles of the wireless sensor networks (WSN) is to avoid wiring costs, be self-sustainable and be able to function for several years. However, due to the slow progress in battery technology, power continues to be a limited resource in wireless sensor communication and electric energy storage remains to be an…

In the aim to manage and retrieve the organizational knowledge, in the last years numerous proposals of models and tools for knowledge management and knowledge representation have arisen. However, most of them store knowledge in a non-structured or semi-structured way, hindering the semantic and automatic processing of this knowledge. In this paper we present a…

Extreme Learning Machine (ELM) is a high effective learning algorithm for the single hidden layer feed forward neural networks. Compared with the existing neural network learning algorithm it solves the slow training speed and over-fitting problems. It has been used in different fields and applications such as biomedical engineering, computer vision, remote sensing, chemical process…