Energy-Efficient Transmission Range Optimization Model for WSN-Based Internet of Things

With the explosive advancements in wireless communications and digital electronics, some tiny devices, sensors, became a part of our daily life in numerous fields. Wireless sensor networks (WSNs) is composed of tiny sensor devices. WSNs have emerged as a key technology enabling the realization of the Internet of Things (IoT). In particular, the sensor-based revolution of WSN-based IoT has led to considerable technological growth in nearly all circles of our life such as smart cities, smart homes, smart healthcare, security applications, environmental monitoring, etc. However, the limitations of energy, communication range, and computational resources are bottlenecks to the widespread applications of this technology. In order to tackle these issues, in this paper, we propose an Energy-efficient Transmission Range Optimized Model for IoT (ETROMI), which can optimize the transmission range of the sensor nodes to curb the hot-spot problem occurring in multi-hop communication. In particular, we maximize the transmission range by employing linear programming to alleviate the sensor nodes’ energy consumption and considerably enhance the network longevity compared to that achievable using state-of-the-art algorithms. Through extensive simulation results, we demonstrate the superiority of the proposed model. ETROMI is expected to be extensively used for various smart city, smart home, and smart healthcare applications in which the transmission range of the sensor nodes is a key concern.     

Interrelationship between uncompacted void content of aggregates and asphalt concrete properties

It is a well known fact that morphological characteristics of aggregates influence the mechanical response of asphalt concrete (AC). Uncompacted void content (UVC) of aggregate is often related to their morphological characteristics. A detailed experimental study was performed to explore relationship between UVC and mechanical response of AC. Initially, aggregates were artificially smoothened using Los Angles abrasion testing machine. UVC was then evaluated using blended aggregates at five levels of smoothness/texture. Increasing aggregate smoothness resulted in decreased UVC values. Higher UVC was obtained with a finer gradation compared to coarse gradation. Three AC mixtures prepared using these smoothened aggregates were tested for their strength and flow properties. A linear, strong positive correlation was found between UVC and Marshall parameters (stability, Marshall quotient). This can be attributed to interparticle resistance developed during mechanical loading. Parabolic relations were found between UVC and retained Marshall parameters. The retained Marshall parameters was found to be a function of UVC. It is concluded that UVC can be effectively used to capture changes in aggregate morphology and AC response.     

Reliable agnostic learning

It is well known that in many applications erroneous predictions of one type or another must be avoided. In some applications, like spam detection, false positive errors are serious problems. In other applications, like medical diagnosis, abstaining from making a prediction may be more desirable than making an incorrect prediction. In this paper we consider different types of reliable classifiers suited for such situations. We formalize the notion and study properties of reliable classifiers in the spirit of agnostic learning (Haussler, 1992; Kearns, Schapire, and Sellie, 1994), a PAC-like model where no assumption is made on the function being learned. We then give two algorithms for reliable agnostic learning under natural distributions. The first reliably learns DNFs with no false positives using membership queries. The second reliably learns halfspaces from random examples with no false positives or false negatives, but the classifier sometimes abstains from making predictions.     

Collective-reward based approach for detection of semi-transparent objects in single images

Most computer and robot vision algorithms, be it for object detection, recognition, or reconstruction, are designed for opaque objects. Non-opaque objects have received less attention, although various special cases have been the subject of research efforts, especially the case of specular objects. The main objective of this paper is to provide a research work in the case of semi-transparent objects, i.e. objects that are transparent but also reflect light, typically objects made of glass. They are rather omnipresent in man-made environments (especially, windows and doors). Detection of these objects provides important information that can be used in a robot’s navigational strategies such as obstacle avoidance, detection of oil/water spills on the floor, localization, etc. In order to achieve the detection of semi-transparent objects we developed a novel approach using a collective-reward based technique on an image captured by an uncalibrated camera. Several experiments were conducted over different scenarios to test the efficacy of the algorithm.     

Resolving uncertainty and creating value from the exercise of e‐commerce investment options

This study examines the effect of the resolution of uncertainty on real options exercise decisions with respect to three e‐commerce investment options: scale‐up, stage and joint investment, and the relationship between exercise of these options and firm performance. The results of a study of 172 public e‐commerce investment announcements show that resolution of external (exogenous) and internal (endogenous) uncertainty has a significant effect on option exercise decisions. However, the results also imply that simply waiting without investment in active learning does not create significant value from real options. The key differentiator is how a firm resolves endogenous uncertainty as this endows it with the ability to successfully undertake the information technology investment and exploit the economic opportunity implied by the resolution of exogenous uncertainty. Furthermore, our results imply that different options should be used to manage situations involving certainty of loss on one hand and severity of loss on the other hand. Thus, it is important for firms to make the right choices when using options‐based investing to manage risk. We suggest that, perhaps, managers need to maintain a portfolio of options to manage the two dimensions of risk simultaneously.     

Analog/RF and Linearity Distortion Analysis of MgZnO/CdZnO Quadruple-Gate Field Effect Transistor (QG-FET)

Silicon - In this study, the authors propose a novel MgZnO/CdZnO Quadruple-Gate Field Effect Transistor (QG-FET). The analog/RF and linearity distortion performance of the proposed QG-FET has been...     

Strategic orientation and performance of internet-based businesses

Abstract. Many of the pure internet‐based businesses that proliferated over the past 5 years have encountered serious problems as their lofty valuations have plunged. Industry observers have attributed this phenomenon to a variety of factors, generally framed in terms of poor conceptualization or implementation of the ‘business model’. This study explores an often‐used concept in strategic management called ‘strategic orientation’ and applies it to internet‐based businesses. Based on an analysis of over 100 public businesses, firms that cluster together with similar strategic orientation are observed. These strategic groups are then analysed for performance differences. The results are discussed with the intent of learning from the dot‐burn effects as we evolve to the next generation of internet‐based business.     

Minimum component SRCO and VFO using a single DVCCC

Two oscillator topologies each employing a single differential voltage complementary current conveyor (DVCCC) are presented. The first oscillator uses a single active element, five passive components, grounded capacitors, has independent control of frequency and condition of oscillation. It has a current mode output and can be extended to provide a voltage mode output. It combines all the features of the current state-of-art oscillators. The second oscillator uses a single DVCCC, four passive elements, grounded capacitors and provides independent control of frequency. This oscillator not only has all the desired oscillator features, but requires lesser passive components. Theoretical analysis of these oscillators was verified with SPICE simulations.     

Some further microstructural characteristics of face-centered cubic polycrystalline metal thin films

We have made detailed observations of gold thin films and commercial aluminum-copper alloy films, using transmission electron microscopy. All of the films embody a strong <111> fiber texture. We have measured the misorientation distributions for the grain boundaries in these films, and also determined the “grain boundary character distribution” in terms of the coincident site lattice model. We show that in spite of their apparent similarity, these films embody significant differences in terms of these measures.     

Two phase micromixing and analysis using electrohydrodynamic instabilities

Organic–aqueous liquid (phenol) extraction is one of many standard techniques to efficiently purify DNA directly from cells. Effective mixing of the two fluid phases increases the surface area over which biological component partitioning may occur. In this work, two phase mixing has been demonstrated in a three inlet microfluidic device geometry. Mixing between the two phases has been achieved by producing an electrohydrodynamic instability at the liquid–liquid interface between the two phases. The initial instability is modeled by considering the small signal linearized analysis for interfacial stresses from both fluid and electrical stress tensors for both inviscid and viscous models. These models predict the onset of instability and the stability criteria over a range of unstable wavenumbers of the mixing process. These models may be applied to relevant microscale geometries, where the unstable wavenumbers and fastest growth wavenumber are determined. At an applied electric field of ∼8.0×10⁵ V/m an instability is experimentally observed by labeling the organic phase with a fluorescent dye and visualizing interfacial perturbations by microscopy. Increasing the electric field increases the instability growth rate and results in an increase of the level of mixing. These results show an increase in conductive fluid entrainment into the nonconducting fluid core measured as a percentage of area of entrainment into the fluorescently labeled organic phase. The entrainment area is seen to increase from 1.9 to 28.6% as the applied field is increased from 8.0×10⁵ to 9.0×10⁵ V/m. The mixing images are converted into a power spectrum using a fast Hartley transform and the band of unstable wavenumbers of the mixing process are determined. From these results, the theoretical field strengths required to produce these unstable wavenumbers are calculated using the theoretical model, determining the maximum field strength required to excite the largest measured unstable wavenumber. At lower field strengths tested, the theoretically predicted maximum electric field and fastest growth wavenumber compare favorably with the initially applied field and measured fastest growth wavenumber whereas at higher field strengths the theoretical field is much larger than the initially applied field. This is attributed to the larger level of mixing and the ability of the instability to grow beyond the linear range and the field increases as the mixing process occurs due to entrainment of highly conductive fluid decreasing the effective dielectric spacing so that the linearized models underpredict the instability growth rates and interfacial perturbations.