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Isolation Forest (or iForest) is a well-known technique for anomaly detection. It is, however, a bulky approach that assumes the luxury of large storage space and is also ineffective with dynamic streaming data so common nowadays in varied application domains. In this work, we present the Preprocessed Isolation Forest (PiForest) approach for anomaly detection that works well in resource constrained environments and is also effective on streaming data. PiForest is largely based on the iForest algorithm and to effectively handle the streaming data includes a pre-processing stage. In the pre-processing stage, Principal Component Analysis (PCA) is first harnessed to significantly reduce the dimension and bulk of the data. Subsequently, the streaming characteristic of the data is handled through a sliding window mechanism that creates sequential blocks of data for systematic processing. PiForest is able to identify anomalies as effectively as iForest and other state-of-the-art anomaly detection techniques but has substantially low storage and prediction complexity. We conduct empirical evaluation of the proposed approach with standard data sets and show that it performs comparably with standard techniques in terms of Area Under the Receiver Operating Characteristic Curve (AUC-ROC) and is able to work with high-dimensional, streaming data. Subsequently, we do a real-world hardware implementation of PiForest and demonstrate that the approach is realistic and practicable in resource-constrained environments.

In this article, we investigate a spectral and energy-efficient wireless body area network (WBAN) for smart healthcare applications. Herein, we primarily focus on improving the spectrum utilization by intelligently sharing spectrum resources through cognitive radio (CR) technology, allowing various sensor nodes in the underlying network to co-exist without compromising on their quality-of-service (QoS). We prioritize the sensor nodes based on their applications (medical/non-medical) and thereby categorize them into primary and secondary users to implement an on-body CR-WBAN. Furthermore, two energy harvesting (EH) protocols namely time-switching cooperation (TSC) and power-splitting cooperation (PSC) are employed to facilitate the secondary node cooperation with the primary network in return for spectrum access. For both the primary and secondary networks, we derive useful expressions for the outage probability. To provide more insights into the proposed CR-WBAN, the throughput and energy efficiency performances assuming a delay-limited scenario are investigated. The impact of key parameters are demonstrated to provide guidelines for the practical design of spectral and energy-efficient WBANs. The accuracy of our proposed analytical framework is verified through Monte Carlo simulations.

Recently, quantum dots (QD) and quantum rods (QRs) have become extremely popular in displays and lighting applications. Liquid crystal displays (LCDs) equipped with quantum dot enhancement films (QDEFs) offer extended color saturation, increasing said saturation from 60 to 70% to more than 100% of the NTSC color gamut. A plethora of research dealing with EL/PL properties and the device-based performance of these materials has been published. The tunable emission wavelength and the narrow emission bandwidth are the key features of quantum dots and perovskite nanoparticles that primarily depend on the nanoparticle size and material composition. QRs, in contrast, have a core–shell structure and emit polarized light that can roughly double the efficiency of modern displays. However, blue emission for QRs, because of the large bathochromic redshift during shell growth, is a serious problem. Besides photoluminescence, electroluminescence is also important for display applications. These QD-LEDs show a lower turn ON voltage in comparison to organic LEDs, which is very important for high-resolution displays. The solution-processed narrower emission QD-LEDs have already achieved efficiency and a brightness comparable to vacuum-deposited phosphorescent organic LEDs (OLEDs). However, the blue-emitting nanoparticles and their short operational lifetime are the key obstacles in the progression of these devices. Furthermore, recently the display and lighting industry are trying to reduce the short-wavelength emissions, particularly in the spectral region below 455 nm, which has a much greater impact on human ocular health and circadian rhythm. Thus, industries are aiming at blue light in the spectral range of 460–475 nm. This spectral range is very challenging for nanomaterials because of the limited choice of materials. In this review, we summarize the recent progress made in the blue-emitting nanomaterials with a different morphology and composition. This includes recent developments in low Cd materials. Both the PL and EL properties of these materials have been discussed depending on the NP’s shape and material composition. This review also aims to discuss the various device architectures employing blue-emitting NPs, any recent achievements and future challenges.

This article reveals a ferroelectric liquid crystal Dammann grating (FLCDG) based polarisation-modulation system for three-dimensional imaging (3D-imaging) device, which seriously increases the det...

Today, the de-facto standard mechanism for data service providers to share their services is through web-service interfaces; clients invoke the service through request messages and receive the data as payloads in the corresponding response messages. Typically, clients need information beyond what any single provider offers; in such cases, multiple data services must be composed to provide a complete solution meeting the client needs. The term “data-service composition” refers to a unified interface that delivers to the client the data it needs in response to a single request message, as if it were available withing a single source. Data-service composition is useful and convenient for the requesting client, but raises privacy concerns since a participating data-service provider potentially can infer information about the data held by other providers. In this paper, we propose a data-service composition method that relies on a mediator for the communication between any two service providers, ensures that the mediator is strictly following the data-composition plan, and maintains privacy between the mediator and service providers. The data service provider first authenticates that the input data is coming from the correct source as per the composition plan, and this is done whilst ensuring complete privacy between the mediator and other service providers. Similarly, data service providers also authenticate the destination of their output data. The approach is validated and its performance evaluated using a real world online retail dataset.

The fringe field effect (FFE) is one of the biggest bottlenecks for the display, and the photonic industry limiting the pixel per inch (PPI) to ~450. The modern applications such as AR/VR headsets and photonic elements such as wavelength selective switches required significantly higher PPI panel. Despite the rigorous research efforts, conventional LCs still show serious FFE, and therefore, hinder the progress of high PPI display and photonic elements. In this article, we studied FFE in the deformed helix ferroelectric liquid crystals (DHFLCs) and found that the subwavelength pitch of the DHFLCs is critically important to suppress the FFE. These DHFLCs show no FFE, for the electric field parallel to the FLC helix, however, we have observed some FFE for the electric field perpendicular to the FLC helix. Additionally, we have found that the high-frequency driving further suppresses the FFE. Later, we deployed DHFLCs to diffraction grating and display to confirm our findings. The proposed DHFLCs with subwavelength pitch can support pixel density up to 4233 PPI for displays, and up to 12,700 PPI for monochromatic photonic devices. Thus, the fast switchable DHFLCs with subwavelength pitch pave the way for the high-pixel density display and photonic devices.

In this paper, the possibility of quantifying a person's interest using data-driven algorithms is investigated. In doing so, interest estimation problem is formulated as a latent state estimation problem, and an answer is deduced via Bayesian Inference. First, a Subjective-Objective approach is used to measure activity. Through this calculated activity, the method indirectly infers human latent state values. A formulation of interest is then presented by drawing inspiration from the Ornstein-Uhlenbeck (OU) process in Physics. Moreover, concepts of stochastic volatility are employed to vary the instantaneous volatility of the OU process. This is done to further improve the performance. Subsequently, the convergence speed of the OU process is varied with time. A novel statistical framework is discussed that dynamically transforms interest into activity. Each of these individual contributions is combined to present a solution via Monte Carlo Simulations. To demonstrate the efficacy of the proposed method, numerical simulations are performed on real datasets. Lastly, a prototype is engineered and the method is implemented as a RESTful Web service. The prototype is hosted as a Web service on several Virtual Machines to demonstrate the practical feasibility of the framework in cloud-based deployment scenarios.

In this article, we disclose low voltage tunable liquid crystal Fibonacci gratings (FbG). Photoalignment technique has been used to create two domains of Fibonacci structure using a photomask. Swit...

This study presents a kind of healthy lighting which provides $\boldsymbol{Ra=97}$ with extremely high R9 up to 99 with least efficiency tradeoff due to the narrow band emission from CdSe/Zn x Cd 1 -xS/ZnS nanorods with high solid-state QY, as well as low blue portion for the whole spectrum.

We propose a simple method of improving the hole injection in the quantum rod light-emitting diode (QRLED) device by doping hydroquinone (HQ) into the PEDOT:PSS HIL. The turn-on voltage and the EQE of QRLEDs improved from 2.8 to 2.3 V and from 6.5 to 9.5%.

This paper aims to propose and analyze an energy-and spectrum-efficient wireless body area network (WBAN) for smart healthcare applications. On one hand, we focus on improving the spectrum utilization in WBANs by incorporating an overlay cognitive radio (CR) paradigm that allows the co-existence of various sensor nodes as primary and secondary users based on their applications i.e., medical or non-medical. On the other hand, we employ an energy harvesting (EH) based time-switching cooperation protocol through the secondary device to improve energy efficiency. We evaluate the performance of the proposed overlay CR WBAN in terms of outage probability, throughput and energy efficiency, and thereby provide practical design guidelines in IoT-based e-healthcare framework. Above all, we assess the correctness of the proposed analytical framework when compared to Monte Carlo simulations.

Low-voltage fast switchable 1D and 2D Fibonacci grating (FbG), using an electrically suppressed helix ferroelectric liquid crystal (ESHFLC), with high diffraction efficiency for a super-resolution imaging system in far-field are disclosed in this paper. Specifically, the polarization-independent two-domain (0, π) structure is well designed based on photoalignment technology to maximize the total diffraction efficiency that can reach 97.4% (1st order:8.5%, 2nd order: 30%). Apart from that, the FLC gratings offer two tunable states: non-diffractive and diffractive states. Derived from the fast-response property of ferroelectric liquid crystal material, the switching speed of the 1D and 2D ESHFLC-FbG is 103µs at 4 V of the driving voltage. Furthermore, this system achieves the high-resolving power of (λ/2.25) for object detection based upon the intensity map received behind 1D ESHFLC-FbG at far-field. Contribution from the quasi-periodic FbG’s special ability to translate the super-resolution information (including at evanescent wave) into the detectable far-field region. Concisely, the proposed ESHFLC-FbG can be a promising candidate for a super-resolution imaging system, superstructure fibre sensor, and other photonic applications.

This paper proposes a method to quantify interest. In common terminology, when we engage with an object, e.g. Online Games, Social Networking Websites, Mobile Apps, etc., there is a degree of interest between us and the object. But, owing to the lack of a procedure that can quantify interest, we are unable to tell by how ‘much’ of a factor are we interested in the object. In other words, can we find a number for someone’s interest? In this article, we propose a method that uses the principle of Bayesian Inference to tackle this issue. We formulate the “interest estimation problem” as a state estimation problem to deduce interest (in any object) indirectly from user activity. Activity caused by interest is computed through a subjective–objectiveweighted approach, then using indirect inference rules, we provide numerical estimates of interest. To do that, we model the dynamics of interest through the Ornstein–Uhlenbeck process. To further enhance the base performance, we draw inspiration from Stochastic Volatility models from Finance. Subsequently, drawing upon a self-adapting transfer function, we provide an avant-garde statistical procedure to model the transformation of interest into activity. The individual contributions are then combined and a solution is provided via Particle filters. Validation of the method is done in two ways. (1) Experimentation is performed on real datasets. Through numerical investigation we have found that the method shows good performance. (2) We implement the framework as a Web application and deploy it on an Enterprise Service Bus. The framework has been successfully hosted on a Cloud based Virtualized testbed consisting of several Virtual Machines constructed over XENServer as the underlying hypervisor. Through this experimental setup, we show the efficacy of the proposed algorithm in estimating interest, at much the same time, we demonstrate the viability of the method in practical cloud based deployment scenarios.

Design and studying of high-performance ferroelectric liquid crystal (FLC) materials targeted on high demand applications in display and photonic devices is described. Combination of high twisting ability with large spontaneous polarization (PS > 100 nC/cm2) resulted in promising FLC mixtures: almost defect-free alignment in electro-optical cells, the optical quality of the cells becomes comparable to that based on nematic liquid crystals, but switching is at least in order faster. The most important parameter is responsible for the remarkable performance of the materials is their ultra-short helix pitch as low as 65 nm. The key components of new mixtures provided the advanced properties are high-twisting diesters of terphenyldicarboxylic acid and chiral 1,1,1-trifluoroalkan-2-ols (FOTDA-n, n = 4–8). Analysis of origin of twisting power in SmC* phase, main difference with N* LC, relationship with chemical structure of chiral components are given. Thus, remarkable increase (up to 2.8-fold) of helical twisting power in the smectic C* (SmC*) phase upon lengthening of terminal alkyl chains from 4th to 8th homologues is observed for FOTDA-n. New chiral compounds, FOTDA-n, where n is 5 and higher, at concentrations as low as 25–33 mol.% in non-chiral BPP based SmC* host induce the helix pitch considerably below 100 nm.

Semiconductor quantum rods (QRs) show a polarized emission, which opens up the possibility of the enhancement of both brightness and color for liquid crystal displays (LCD) in the form of quantum rod enhancement films (QREFs) for LCD backlights. However, the QR alignment over a large area, suitable for displays, is a challenge. Inkjet printing of QREFs, introduced here, allows fabrication of well-aligned, uniform QREFs on photoaligned substrates using optimized QR inks. We observed that the ink composition and printing conditions affect the QR alignment quality significantly. A relative humidity of 50% with an exposure energy of 1 J cm−2 for the photoalignment process provided optimal conditions for QREFs. We have successfully shown a good QR alignment for 2.5-inch films and were able to align QRs in multiple layers. Thus, fabricated QREFs show a polarization ratio of 7.2 : 1 for the emitted light. These QREFs were combined with a blue LED and deployed as a backlight unit for an LCD which shows a brightness of ∼250 nits with an optical efficiency of ∼8%, reaching an NTSC of 109% in a CIE1976 color space. Thus, these printed QREFs, over a large area, provide an unprecedented increase of 77% in the optical efficiency of the LCDs and simultaneously offer better color performance.

Optical devices like virtual reality (VR) headsets present challenges in terms of vergence-accommodation conflict that leads to visual fatigue for the user over time. Lenses available to meet these challenges include liquid crystal (LC) lenses, which possess a response time in the millisecond range. This response time is slow, while accessing multiple focal lengths. A ferroelectric liquid crystal (FLC) has a response time in the microsecond range. In this article, we disclose a switchable lens device having a combination of the fast FLC-based polarization rotation unit and a passive polarization-dependent LC lens. A cascaded combination of three such lens units allows access to eight different focal points quite rapidly and can be a convenient device for VR applications.