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Recently, a number of two-dimensional van der Waals (vdW) ferroelectrics have been reported, showing the potential to develop various ultra-thin smart devices down to the atomic monolayer limit. In particular, they have been demonstrated to exhibit intriguing polar domain structures. However, phenomenological thermodynamic models of vdW ferroelectrics, which can capture their ferroic domain structure evolution, are still lacking, limiting our further exploration of domain-structure-related applications. In this work, combining first-principles calculations, we construct a phenomenological phase field model for monolayer ferroelectrics, FEβ-In2Se3. Based on the model, one can calculate the phase stability, ferroelectric hysteresis curves, and domain structures of FEβ-In2Se3 under different loading conditions, showing the feasibility of electromechanically driving the rotation of in-plane polarization and manipulation of the domain structures. By including the second-order partial derivative gradient energy term, the model further captures well the antiferroelectric–ferroelastic domain structures of β′-In2Se3 observed in previous experiments. The developed phase field model should help better understand the domain structure evolution behavior in low-dimensional materials and promote further exploration of domain-structure-related applications. [ABSTRACT FROM AUTHOR]

Artiklis keskendume tehnoloogia arengule kui mõjutegurile, mis kujundab keelekeskkonda ning toetab mitme keele arengut väikelapse- ja koolieelses eas. Uurimuse ajendiks on juhtum, kus telerit mittevaatavast eestikeelsest perest pärit kaks last hakkasid end mängusituatsioonides väljendama inglise keeles, olles sellega varem kokku puutunud vaid YouTube’i vahendusel meelelahutuse eesmärgil. YouTube’i kui digitaalse õpiruumi fenomeni paremaks mõistmiseks viisime lapsevanematega läbi poolstruktureeritud standardiseerimata paariintervjuud, et uurida, kuidas on võimalik kodus enne kooliiga toetada L1-st erineva keele omandamist nutiseadmete ja YouTube’i abil. Intervjuude analüüsimisel kasutasime kvalitatiivse sisuanalüüsi meetodit. Uurimistulemusena selgus, et vanemate rollid on dünaamilised ning need muutuvad lapse kognitiivse, sotsiaalse ja keelelise arengu käigus koosvaatamisest mentorluseni. *** "A smart device as a magic wand? Parents’ perspective on the impact of YouTube on young children’s second language acquisition" The present article explores the role of technology in shaping language environments and supporting the acquisition of multiple languages among young children and preschoolers. The study focuses on a case where children from an Estonian-speaking family, pseudonymised as Karola and Oskar, began expressing themselves in English in gaming situations, having previously encountered the language primarily through entertainment content on YouTube. Karola started emulating English-speaking YouTubers at the age of five and even created her own videos, while Oskar mainly used English when playing with his toys. The study aims to answer three research questions: when and how the children started using smart devices; how their choices in online content evolved as the children grew; and what roles the parents played in this process. To better understand the phenomenon of YouTube as a digital learning space, a semi-structured non-standardized paired interview was conducted with the children's parents. The goal was to investigate how it is possible to support the acquisition of a language different from L1 at home using smart devices and YouTube. The analysis of the interviews employed qualitative content analysis methods. The results reveal that children started watching short cartoons and animated songs in L1 at the age of one or two. However, as the number of appropriate resources in Estonian on YouTube was limited, they soon opted for cartoons and videos in English. As children grew, they selected the content to watch on the basis of the characters they could relate to. The language in the videos also progressed from simple clearly pronounced words and phrases to fluent authentic use of English. The analysis indicated that parental roles are dynamic and evolve alongside the child's cognitive, social, and linguistic development, ranging from supervision during media consumption to active mentorship.

Summary: Unmanned aerial vehicles (UAVs) can serve as aerial mobile edge computing (MEC) servers to provide computing services to Internet of Things smart devices (ISDs) with insufficient computing capacity on the ground. However, how to provide energy‐efficient computing services by designing appropriate resource optimization strategy is still a challenge issue in UAV‐enabled MEC networks. To this end, this paper proposes a computation efficiency (CE)‐oriented partial offloading framework for UAV‐enabled MEC networks, where the ISDs' computation bits and energy consumption are taken into account simultaneously. Specifically, we firstly divide the ISDs into multiple clusters and determine the deployment of UAVs by k‐means method. Meanwhile, ISDs occupying the same subchannel in the same cluster can offload data through non‐orthogonal multiple access (NOMA) technology. Then, the problem of maximizing the CE of the system is formulated by optimizing subchannel allocation, transmit power and computation resources of ISDs. To solve it, we propose a staged optimization approach by using matching theory, Dinkelbach and sequential convex programming (SCP) methods. Numerical results demonstrate the proposed scheme can achieve higher CE compared with other baseline schemes. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has emerged as an inevitable part of human life, that includes online learning, smart homes, smart cars, smart grids, smart cities, agriculture, and e-healthcare. It allows us to operate them 24/7 from anywhere. These smart IoT devices streamline our daily lives by automating everything around us. Several security issues have arisen with the continuous growth of non-secure IoT devices. Distributed Denial of Service (DDoS) attack is one of the most prominent security threats to Internet-based services and IoT platforms. It has the potential to break down the victim's server or network by transferring an immense amount of irrelevant traffic from the pool of compromised IoT devices. In this article, we present: (i) A comprehensive cyberattacks taxonomy for IoT platforms, (ii) Systematically demonstrate IoT technology: evolution, applications, and challenges, (iv) Systematic review of existing machine learning (ML) and deep learning (DL)-based detection approaches for large-scale IoT traffic-based DDoS attacks, (v) Characterize publicly available IoT-traffic-specific datasets, and (vi) Discuss various open research issues with possible solutions for detecting IoT traffic-based DDoS attacks, including future directions. [ABSTRACT FROM AUTHOR]

The development of the Internet of Things has increased the anticipation for wearable smart devices in personalized healthcare. Carbon aerogel films, characterized by multifunctional and lightweight porous properties, are emerging as promising components for lightweight smart devices. In this study, we adopt a straightforward, cost-effective approach to fabricate carbon aerogels using cellulose nanofibers (CNF) and graphene (GO) co-stabilized Pickering emulsion, followed by vacuum filtration, freeze-drying, and carbonization treatment. The carbonization process involves the pyrolysis of paraffin wax and the reduction of graphene oxide, resulting in a uniquely porous structure, low density, and remarkable properties related to Joule heating, photothermal conversion, and conductivity sensitivity across a wide range of stresses. Incorporating CRP-30 into a piezoresistive sensor enables real-time monitoring of subtle human activities such as carotid pulse beats, swallowing, and facial expressions. This multifunctional carbon aerogel film holds great promise in the domains of wearable personal thermal management and personal health monitoring. [ABSTRACT FROM AUTHOR]

Organic ultrathin nanofilms are increasingly favored in a wide range of applications, including flexible photonics and electronics, smart skin devices, sensing, and bioinspired designs, due to their high flexibility, chemical activity, and stimuli‐responsiveness. To create large‐area, robust, and freestanding nanofilms efficiently, a protein interfacial cooperative assembly technique that utilizes silk fibroin and lysozyme as building blocks is developed. The strong intermolecular interaction between these two proteins, coupled with the abundant intra‐ and intermolecular β‐sheets, confers remarkable mechanical robustness to the nanofilms with thicknesses as low as 50 nm. Consequently, these nanofilms exhibit the unique ability to stand freely in the air and can be conformally transferred to substrates of different types and topographies, forming stable, and versatile nanocoatings. The advantageous attributes of their ultrathinness, large‐scale homogeneity, robustness, and rapid and tunable responsiveness facilitate the construction of ultrasensitive photonic architectures and organic–inorganic hybrid multilayers with outstanding optical and mechanical properties. It is envisioned that these all‐protein‐based robust nanofilms with unique nanoscale effects can be easily integrated into various advanced technological platforms to enable adaptive, multifunctional, and intelligent systems with exceptional mechanical strength. [ABSTRACT FROM AUTHOR]

Smart windows that incorporate photothermal modulators (PMs) can independently regulate solar transmittance and infrared (IR) emissivity to improve building comfort and reduce energy consumption. Herein, a novel all‐solid‐state variable IR emissivity device (VED) is first designed and fabricated with a high visible irradiation transmittance (T′vis = 0.79) and solar irradiation transmittance (T′sol = 0.75) using an ITO/SiO2/ITO Fabry–Perot cavity structure. The VED exhibits different IR emissivity (ɛ) values at positive (ɛP = 0.80) and negative (ɛN = 0.38) bias, allowing for dynamic regulation of radiation by controlling the electrical conductivity of the indium tin oxide (ITO) layer. Furthermore, an all‐solid‐state PM with a structure of ITO/SiO2/ITO/Glass/ITO/NiO/ZrO2/Li/WO3/ITO, which is capable of independently regulating solar transmittance (ΔT'sol = 0.31) and IR emissivity (Δɛ2.5–25 µm = 0.42), is fabricated. The multi‐mode smart window incorporating PMs can achieve "bright," "dark," "warm," and "cool" modes, making them suitable for deployment in diverse climate zones. The innovative smart window holds a massive potential for use in reducing building energy consumption. [ABSTRACT FROM AUTHOR]

Smart hydrogels responsive to external stimuli are promising for various applications such as soft robotics and smart devices. High mechanical strength and fast response rate are particularly important for the construction of hydrogel actuators. Herein, tough hydrogels with rapid response rates are synthesized using vinyl‐functionalized poly(N‐isopropylacrylamide) (PNIPAM) microgels as macro‐crosslinkers and N‐isopropylacrylamide as monomers. The compression strength of the obtained PNIPAM hydrogels is up to 7.13 MPa. The response rate of the microgel‐crosslinked hydrogels is significantly enhanced compared with conventional chemically crosslinked PNIPAM hydrogels. The mechanical strength and response rate of hydrogels can be adjusted by varying the proportion of monomers and crosslinkers. The lower critical solution temperature (LCST) of the PNIPAM hydrogels could be tuned by copolymerizing with ionic monomer sodium methacrylate. Thermo‐responsive bilayer hydrogels are fabricated using PINPAM hydrogels with different LCSTs via a layer‐by‐layer method. The thermo‐responsive fast swelling and shrinking properties of the two layers endow the bilayer hydrogel with anisotropic structures and asymmetric response characteristics, allowing the hydrogel to respond rapidly. The bilayer hydrogels are fabricated into clamps to grab small objects and flowers that mimicked the closure of petals, and it shows great application prospects in the field of actuators. [ABSTRACT FROM AUTHOR]

Electrochromic batteries as emerging smart energy devices are highly sought after owing to their real‐time energy monitoring through visual color conversion. However, their large‐scale applicability is hindered by insufficient capacity, inadequate cycling stability, and limited color variation. Herein, a flexible Zn‐ion electrochromic battery (ZIEB) was assembled with sodium vanadate (VONa+) cathode, ion‐redistributing hydrogel electrolyte, and Zn anode to address these challenges. The electrolyte contains anchored −SO3− and ‐NH3+, which facilitates ionic transportation and prevents Zn dendrite formation by promoting orientated Zn2+ deposition on the Zn (002) surface. The ZIEB exhibits a continuous reversible color transition, ranging from fully charged orange to mid‐charged brown and drained green. It also demonstrates a high specific capacity of 302.4 mAh ⋅ g−1 at 0.05 A ⋅ g−1 with a capacity retention of 96.3 % after 500 cycles at 3 A ⋅ g−1. Additionally, the ZIEB maintains stable energy output even under bending, rolling, knotting, and twisting. This work paves a new strategy for the design of smart energy devices in wearable electronics. [ABSTRACT FROM AUTHOR]

Mobile Crowdsensing (MCS) has shown the greatest potential that allows smart devices to collect and share different sensing data. Mobile users (or participants) send the desired sensing data to the service providers and collect rewards. However, the reward needs to be given such as, it does not increase platform costs. On the other hand, the unsatisfactory reward may reduce the interest of the participant which may degrade the quality data. Therefore, increasing sensing data quality with a constrained budget is a crucial challenge. There has been extensive research on the reward mechanism for MCS, but, most of the work is on the basic assumption that participant will complete their assigned task positively. In this paper, we propose an efficient user selection mechanism for Mobile Crowdsensing System (MCS) by considering the Probability of Success (PoS) of users (i.e. participant may fail to complete the assigned task with some probability). For the selection of an efficient user, the proposed mechanism also accounts the parameters like data quality and platform cost. We also propose a reward calculation model for the selected users. Minimizing the platform cost with a constrained budget is an NP-hard problem. To provide a sub-optimal solution to this problem Chaotic Krill-Herd optimization algorithm is used. The extensive simulation results reveal that the proposed method outperforms the existing work by considerable margins. [ABSTRACT FROM AUTHOR]

Currently, wearable technology is an emerging trend that offers remarkable access to our data through smart devices like smartphones, watches, fitness trackers and textiles. As such, wearable devices can enable health monitoring without disrupting our daily routines. In clinical settings, electrocardiograms (ECGs) and photoplethysmographies (PPGs) are used to monitor heart and respiratory behaviors. In more practical settings, accelerometers can be used to estimate the heart rate when they are attached to the chest. They can also help filter out some noise in ECG signals from movement. In this work, we compare the heart rate data extracted from the built-in accelerometer of a commercial smart pen equipped with sensors (STABILO's DigiPen) to standard ECG monitor readouts. We demonstrate that it is possible to accurately predict the heart rate from the smart pencil. The data collection is carried out with eight volunteers writing the alphabet continuously for five minutes. The signal is processed with a Butterworth filter to cut off noise. We achieve a mean-squared error (MSE) better than 6.685 × 10 − 3 comparing the DigiPen's computed Δ t (time between pulses) with the reference ECG data. The peaks' timestamps for both signals all maintain a correlation higher than 0.99. All computed heart rates (HR = 60 Δ t ) from the pen accurately correlate with the reference ECG signals. [ABSTRACT FROM AUTHOR]

With the wide applications of the Internet of Things (IoT) in smart home systems, IEEE 802.11n Wireless Local Area Networks (WLANs) have become a frequently chosen communication technology due to their adaptability and affordability. In a high-density network of devices such as the smart home scenerio, a host often meets interferences from other devices and unequal Received Signal Strength (RSS) from Access Points (APs). This results in throughput unfairness/insufficiency problems between hosts communicating concurrently in WLAN. Previously, we have studied the throughput request satisfaction method to address this problem. It calculates the target throughput from measured single and concurrent throughputs of hosts and controls the actual throughput at this target one by applying traffic shaping at the AP. However, the insufficiency problem of maximizing the throughput is not solved due to interferences from other hosts. In this paper, we present an extension of the throughput request satisfaction method to maximize the throughput of a high-priority host under concurrent communications. It recalculates the target throughput to increase the actual throughput as much as possible while the other hosts satisfy the least throughput. For evaluations, we conduct experiments using the test-bed system with Raspberry Pi as the AP devices in several topologies in indoor environments. The results confirm the effectiveness of our proposal. [ABSTRACT FROM AUTHOR]

Smart dust devices are tiny systems-on-a-chip platforms capable of sensing, storing and transmitting data wirelessly as part of a large network with distributed capabilities. Previous works investigated the long-term orbital evolution of smart dust in space by studying the combined effect of gravitational perturbations, solar radiation pressure (SRP) and atmospheric drag. In the current work, the problem of finding long-term orbital equilibria conditions for smart dust is recast and extended to include Poynting–Robertson and Solar Wind (PRSW) drag. By including the PRSW effects and defining new equilibrium conditions on the orbital orientation, some additional partial equilibrium solutions are found. Moreover, it is shown that even though PRSW is not dominant compared to SRP or J 2 , it still influences the evolution of the relative Sun-orbit orientation. For orbits with higher initial perigee altitudes, where drag and J 2 effects subside, it is shown that PRSW influences long-term orbital behavior, and should be considered in the orbit design scheme of smart dust devices. [ABSTRACT FROM AUTHOR]

Sensor data that is often collected in the Internet of Things (IoT) or any smart city environment should be protected against security and privacy concerns. Often, sensor data that is shared by devices in smart cities contains sensitive or private information that can often be shared over different networks and by different smart applications. In the last decade, the area of Privacy-Preserving Data Mining (PPDM) has received a lot of attention as the amount of data received and collected daily is huge. Unfortunately, PPDM mostly applies to binary data. To improve the usefulness of PPDM, we present a more usable version for smart cities called Privacy-Preserving Utility Mining (PPUM), in the form of a Maximal Sensitive Utility-Maximal Sensitive ConflIct (MSU-MSI) algorithm. MSU-MSI finds any conflicting items that may contain sensitive itemsets with high-utility and sanitizes them, stripping them of sensitive and private information while maintaining utility. Any transactions encountered that contain sensitive itemsets are first fed through sanitization processes. This is followed by calculating the total number of items that conflict, and then removing them so sanitization processes can operate more efficiently so as to not redo known sanitization processes. We conduct an in-depth experimental analysis, where our detailed methodology is compared directly with state-of-the-art frameworks such as MSU-MIU, MSU-MAU, HHUIF and MSCIF. Our proposed MSU-MSI shows a higher performance in missing cost, in particular when dealing with highly dense or highly sparse datasets. Moreover, our novel framework is shown to achieve an excellent performance with regards to similarity in database structure and database utility. [ABSTRACT FROM AUTHOR]

[Display omitted] • This review provides a systematic summary of FDA-approved biologic-device combination products regarding their device configurations, routes of administration, formulations, instructions for use, etc. • While prefilled syringes, autoinjectors and pen injectors remain as the mainstay of medical devices, innovative modifications like dual-chamber design and novel devices like on-body injector also emerged as promising presentations. • Insulin related combination products are all delivered by pen injectors with multi-dose cartridges subcutaneously. Vaccine-device combination products are presented with PFS and administered through the intramuscular route. • Around 40 % of products employ high-concentration formulations (≥ 100 mg/mL), and 78 % of mAb products are at high concentrations. With the remarkably strong growth of the biopharmaceutical market, an increasing demand for self-administration and rising competitions attract substantial interest to the biologic-device combination products. The ease-of-use of biologic-device combination products can minimize dosing error, improve patient compliance and add value to the life-cycle management of biological products. As listed in the purple book issued by the U.S. Food and Drug Administration (FDA), a total of 98 brand biologic-device combination products have been approved with Biologic License Application from January 2000 to August 2023, where this review mainly focused on 63 products containing neither insulin nor vaccine. Prefilled syringes (PFS) and autoinjectors are the most widely adopted devices, whereas innovative modifications like needle safety guard and dual-chamber design and novel devices like on-body injector also emerged as promising presentations. All 16 insulin products employ pen injectors, while all 19 vaccine products are delivered by a PFS. This review provides a systematic summary of FDA-approved biologic-device combination products regarding their device configurations, routes of administration, formulations, instructions for use, etc. In addition, challenges and opportunities associated with biologic-device compatibility, regulatory complexity, and smart connected devices are also discussed. It is believed that evolving technologies will definitely move the boundaries of biologic-device combination product development even further. [ABSTRACT FROM AUTHOR]

The advent of the Internet of Things brought a new age of interconnected device functionality, ranging from personal devices and smart houses to industrial control systems. However, increased security risks have emerged in its wake, in particular self-replicating malware that exploits weak device security. Studies modeling malware epidemics aim to predict malware behavior in essential ways, usually assuming a number of simplifications, but they invariably simplify the single most important subdynamics of malware: random propagation. In our previous work, we derived and presented the first exact mathematical model of random propagation, defined as the subdynamics of propagation of a malware model. The propagation dynamics were derived for the SIS model in discrete form. In this work, we generalize the methodology of derivation and extend it to any Markov chain model of malware based on random propagation. We also propose a second method of derivation based on modifying the simplest form of the model and adjusting it for more complex models. We validated the two methodologies on three malware models, using simulations to confirm the exactness of the propagation dynamics. Stochastic errors of less than 0.2% were found in all simulations. In comparison, the standard nonlinear model of propagation (present in ∼95% of studies) has an average error of 5% and a maximum of 9.88% against simulations. Moreover, our model has a low mathematical trade-off of only two additional operations, being a proper substitute to the standard literature model whenever the dynamical equations are solved numerically. [ABSTRACT FROM AUTHOR]

Controllable devices in a classical centralized grid work independently, providing desired functionalities for the owner only, making grid stability and efficient energy management challenging. Therefore, the dynamically developing communication infrastructure has been crucial in improving local energy management and stability, introducing the Internet of Things and, finally, creating micro- or smart grids. Communication technology already allows for exchanging data and information with high bandwidth in practical industrial and grid applications. However, considering the increasing number of electrical devices with different purposes, parameters, and possibilities to work as an energy source or storage, the challenge is device profile standardization, especially for power electronics devices. As many devices as possible should be able to exchange information with the grid operator or local area/home energy management device, like industrial agents, energy routers, or smart transformers. The number and types of parameters, outputs, and input signals available in the devices from the communication point of view are significantly different, making it extremely difficult to apply the advanced energy management algorithm. Therefore, the unified data profile for modern loads was developed and discussed. The proposed device model was standardized, including mandatory information about the device's work and parameters, with the possibility of reading the control commands from the supervisor device. The proposed unified model was studied in simulation research, integrating self-balanced and self-control areas. [ABSTRACT FROM AUTHOR]

A mechanism of fog computing environment is employed in order to enhance the cloud computing services toward the edge devices in a range of locations with low latency. A fog computing environment is effective when compared to cloud computing for providing communication between various edge devices such as smart devices and mobile devices used by users in the same location. Even though fog servicing extends the best services of cloud computing, it also suffers from a set of security threats like authentication, key management, data privacy and trust management. Authentication with effective key management between edge devices is the most pressing security issue in fog computing. This paper proposes an effective two-way authentication between edge devices with key management in fog computing environments (TAKM-FC). The edge nodes are the user's mobile devices and set of smart devices controlled by the fog server. To improve the proposed authentication system, we have made use of techniques like fuzzy extractor and one-way hash with cryptographic primitives. The proposed TAKM-FC scheme is validated mathematically based on the ROR model and then verified using the ProVerif tool. The TAKM-FC scheme has been evaluated using iFogSim to measure the performance parameters like throughput, end-to-end delay, packet loss, energy consumption and network usage. The overhead analysis of the proposed scheme is carried out and shows that the computation cost, communication cost and storage cost are improved by 11–21%, 8–19% and 6–13%, respectively, compared to existing schemes. [ABSTRACT FROM AUTHOR]

Mobile smart devices, such as mobile phones, wearable devices, and in-vehicle navigation systems, bring us convenience and have become necessities in modern daily life. The built-in global positioning system (GPS) of these mobile devices collects the users' mobility data to support path planning, navigation and other location-related applications, which also inevitably causes privacy issues. Previous research has shown that employing count-min sketch (CMS) to aggregate mobility datasets is a valid privacy-preserving method for resisting the reconstruction attack on population distributions. However, as the utility/accessibility of the protected datasets is excessively correlated with the size of CMS, decreasing the data transmission cost has become an unsolved issue of that approach. In this paper, we propose an efficient scheme with differential privacy to protect mobility datasets, which releases the privacy-preserving population distributions and achieves better utility as well as a much smaller data transmission cost compared to the CMS-based method. Our proposed scheme is comprised of two collaborative components, global sketch and temporal sketch. The global sketch is responsible for aggregating the raw mobility data and decreasing the data transmission cost, while the temporal sketch is in charge of guaranteeing the utility of the population distributions aggregated by the global sketch. Besides, to enhance the privacy preservation, we employ the Laplace mechanism to make the transmitted data satisfy ϵ -differential privacy. Through our analysis and empirical experiments, compared to the other three state-of-the-art privacy-preserving methods on mobility datasets, our scheme could preserve the privacy of the mobility datasets with much less data transmission cost under the same utility loss. [ABSTRACT FROM AUTHOR]

In the sixth-generation (6G) wireless networks, the use of unmanned aerial vehicles (UAVs) and tethered balloons (TBs) to assist cellular networks has attracted considerable attentions due to their dynamic and quick deployment with their relative low cost. In this article, we propose a new task offloading scheme for smart devices in the modern battlefield area. By the integrative platform of TBs, UAVs and smart devices, the main challenges are (i) providing a task splitting algorithm for the partial offloading service, and (ii) develop a TB resource sharing algorithm to handle the offloading requests. For convenient wireless communications, UAVs work as relay nodes between TBs and individual devices. To achieve a mutually desirable solution, our proposed scheme is formulated as cooperative game models. First, the sequential Raiffa bargaining solution is applied to split the computation-intensive task of each smart device in the battlefield area. Second, the average-surplus value is adopted to effectively share the TB computing resource. Based on the reciprocal combination of two cooperative game solutions, we explore the sequential interaction of TBs, UAVs and battlefield devices, and jointly design our integrated control scheme for offloading services. According to the synergy effect, our hybrid approach can provide a fair-efficient solution in the UAV-TB-assisted battlefield network infrastructure. Finally, extensive simulations are conducted, and the results demonstrate the superiority of our proposed scheme over the existing baseline protocols. [ABSTRACT FROM AUTHOR]

Bottom-up nanofabrication, organizing colloidal nanoparticles into ordered clusters with structural and functional complexity, provides an alternative to yield nanometric smart structures unachievable in traditional top-down approaches. Those remarkable structures assembled of colloidal nanoparticles possessing optical properties feature exotic optical responses under the illumination of incident light, showing highly dependent on the particle separation, composition, and arrangement. Here, the nanoscale electromagnetic coupling in magnetic–plasmonic nanoparticle clusters is analyzed by using a 3D full-wave computational model, and the mechanism of the resonances in a split-ring resonator out of magnetic–plasmonic nanoparticle building blocks is also illustrated. In particular, once assembling those artificial molecules (split-ring resonator) into secondary metamaterial superstructures, such as split-ring resonator dimer and Y-shaped structures, a series of exotic optical responses are presented due to the greatly enhanced near-field coupling of nanoparticles and the generation of antiparallel ring currents in the asymmetrical superstructure, exhibiting flexible sensitivity to the changes of the surrounding environment. Besides, the H-shaped arrangement exhibits high sensitivity with Q = 50.5 at λ = 2.02 μ m. Our finding provides a platform for yielding complex structures with flexible tunability of the optical response through arranging those assembled artificial molecules into complex secondary structures, allowing for the development of smart sensing devices. [ABSTRACT FROM AUTHOR]

No matter how good a smart device may be, it remains useless outside the context of a digital ecosystem. Internet of Things (IoT) environments are possible as long as services and products can interconnect smoothly and exchange data in real time. Therefore, interoperability ranks high in global policy agendas, with the promise of bringing an end to network effects slanted in favour of ecosystem orchestrators. However, recent regulatory initiatives introducing interoperability obligations risk falling short of their intent or even risk generating unintended consequences in the absence of a coherent approach to standardisation. Against this backdrop, focusing on the UK Open Banking experience, this article makes a proposal for workable interoperability in IoT ecosystems aimed at ensuring market contestability without undermining incentives to innovate. [ABSTRACT FROM AUTHOR]

Edge computing is an emerging computing paradigm representing decentralized and distributed information technology architecture. The demand for edge computing is primarily driven by the increased number of smart devices and the Internet of Things (IoT) that generate and transmit a substantial amount of data, that would otherwise be stored on cloud computing services. The edge architecture enables data and computation to be performed in close proximity to users and data sources and acts as the pathway toward upstream data centers. Rather than sending data to the cloud for processing, the analysis and work is done closer to where the source of the data is generated (). Edge services leverage local infrastructure resources allowing for reduced network latency, improved bandwidth utilization, and better energy efficiency compared to cloud computing. [ABSTRACT FROM AUTHOR]

Looking at the weakness of students in learning geometry, a study was conducted on using modules with augmented reality technology for primary school students. This study aims to identify the effectiveness of using such modules on students' conceptual and procedural knowledge in geometry, particularly for Year 4. A random sampling of students was conducted to determine the experimental group of students who studied using modules with augmented reality. In contrast, the control group studied with traditional module methods. Fifty-nine students were involved in this study, with 29 in the experimental group and 30 in the control group. The study results analyzed by ANCOVA showed that the conceptual and procedural scores of the experimental group students were significantly better than the control group students in the post-test and the delayed post-test. Using modules with augmented reality benefits students' conceptual and procedural knowledge in learning geometry. This study indirectly allows students to learn geometry concepts through an augmented reality technology approach with smart devices. Students also have the opportunity to learn through a student-centered approach and collaborative learning strategies while using augmented reality applications in learning. Simultaneously, using this technology is an innovation that also benefits teachers and stakeholders. [ABSTRACT FROM AUTHOR]

Now, the Cyber security is facing unprecedented difficulties as a result of the proliferation of smart devices in the Internet of Things (IoT) environment. The rapid growth in the number of Internet users over the past two decades has increased the need for cyber security. Users have provided new opportunities for attackers to do harm. Limited security budgets leave IoT devices vulnerable and easily hacked to launch distributed denial-of-service (DDoS) attacks, with disastrous results. Unfortunately, due to the unique nature of the Internet of Things environment, most security solutions and intrusion detection systems (IDS) cannot be directly adapted to the IoT with acceptable security performance and are vulnerable to various attacks that do not benefit. In this paper we propose an optimal secure defense mechanism for DDoS in IoT network using feature optimization and intrusion detection system (OSD-IDS). In OSD-IDS mechanism, first we introduce an enhanced ResNet architecture for feature extraction which extracts more deep features from given traffic traces. An improved quantum query optimization (IQQO) algorithm for is used feature selection to selects optimal best among multiple features which reduces the data dimensionality issues. The selected features have given to the detection and classification module to classify the traffic traces are affected by intrusion or not. For this, we design a fast and accurate intrusion detection mechanism, named as hybrid deep learning technique which combines convolutional neural network (CNN) and diagonal XG boosting (CNN-DigXG) for the fast and accurate intrusion detection in IoT network. Finally, we validate the performance of proposed technique by using different benchmark datasets are BoNeSi-SlowHTTPtest and CIC-DDoS2019. The simulation results of proposed IDS mechanism are compared with the existing state-of-art IDS mechanism and analyze the performance with respects to different statistical measures. The results show that the DDoS detection accuracy of proposed OSD-IDS mechanism is high as 99.476% and 99.078% for BoNeSi-SlowHTTPtest, CICDDoS2019, respectively. [ABSTRACT FROM AUTHOR]

High bit-error rates and high transmission rates are required for the Multimedia Wireless Sensor Networks (MWSN) to transmit high-quality pictures through smart devices. To fully utilize the advantages of the technology known as Multiple-Input Multiple-Output, MWSN heavily relies on cooperative communication. Large-scale wireless networks use multi-radio-multi-channel to improve performance by simultaneous broadcasts across symmetrical channels to reduce interference. Expanding cooperative communication in vast networks is subject to severe interference. And, as each node in the network is mobile, routing and transmission delay pose significant problems for cooperative multimedia wireless sensor networks. Mobility increases the MWSNs' dynamic nature, which reflects in the overhead control traffic. To address above issues, a Cluster-based Delay Aware Cooperative Relay Selection (CDACRS) was proposed by employing mobility and distance metrics and channel assignment (CA) using dynamic Global Table (GT). To minimize the end-to-end transmission latency without compromising aggregate throughput, our approach chooses a relay-node depending on the mobility and the maximum available channel capacity. Further, to improve the end-to-end energy consumption, Power Aware Transmission (PAT) protocol is developed by calculating maximum transmission power required to meet target bit error rate (BER). The proposed method's performance is evaluated against the Cluster-based Cooperative Multi-Hop Optimal Relay Selection (CCORS); energy efficient and quality aware multi-hop cooperative image transmission; and Energy Aware Cooperative Image Transmission (EACIT) algorithms and observed that our approach improves the transmission delay by 37.5% (approx.) and end-to-end energy consumption by 48.8%. [ABSTRACT FROM AUTHOR]

Within the expansive domain of maritime safety, optimizing evacuation procedures stands as a critical endeavour. After all, evacuation is literally the last and fundamental safety level afforded to mariners and passengers. Recent incidents have rekindled interest in assessing the performance of this ultimate safety barrier. However, addressing evacuability requires a holistic approach. The authors present herein the setup, simulation, and ultimately evaluation of a novel approach and its ability to rigorously assess multiple innovative risk-control options in a challenging, realistic setting. Moreover, its benchmarking against conventional regulation-dictated evacuation processes is captured distinctively along with the relative effectiveness of each proposed measure. Such measures include smart technologies and procedural changes that can result in substantial improvements to the current procedures. These will impact the ongoing discourse on maritime safety by providing insights for policymakers, vessel operators, emergency planners, etc., and emphasize the need for further research and development efforts to fortify the industry against evolving safety challenges. [ABSTRACT FROM AUTHOR]

Biological species can walk, swim, fly, jump, and climb with fast response speeds and motion complexity. These remarkable functions are accomplished by means of soft actuation organisms, which are commonly composed of muscle tissue systems. To achieve the creation of their biomimetic artificial counterparts, various biomimetic stimuli-responsive materials have been synthesized and developed in recent decades. They can respond to various external stimuli in the form of structural or morphological transformations by actively or passively converting input energy into mechanical energy. They are the core element of soft actuators for typical smart devices like soft robots, artificial muscles, intelligent sensors and nanogenerators. Significant progress has been made in the development of bioinspired stimuli-responsive materials. However, these materials have not been comprehensively summarized with specific actuation mechanisms in the literature. In this review, we will discuss recent advances in biomimetic stimuli-responsive materials that are instrumental for soft actuators. Firstly, different stimuli-responsive principles for soft actuators are discussed, including fluidic, electrical, thermal, magnetic, light, and chemical stimuli. We further summarize the state-of-the-art stimuli-responsive materials for soft actuators and explore the advantages and disadvantages of using electroactive polymers, magnetic soft composites, photo-thermal responsive polymers, shape memory alloys and other responsive soft materials. Finally, we provide a critical outlook on the field of stimuli-responsive soft actuators and emphasize the challenges in the process of their implementation to various industries. [ABSTRACT FROM AUTHOR]

Thermosets have been crucial in modern engineering for decades, finding applications in various industries. Welding cross-linked components are essential in the processing of thermosets for repairing damaged areas or fabricating complex structures. However, the inherent insolubility and infusibility of thermoset materials, attributed to their three-dimensional network structure, pose challenges to welding development. Incorporating dynamic chemical bonds into highly cross-linked networks bridges the gap between thermosets and thermoplastics presenting a promising avenue for innovative welding techniques. External stimuli, including thermal, light, solvent, pH, electric, and magnetic fields, induce dynamic bonds' breakage and reformation, rendering the cross-linked network malleable. This plasticity facilitates the seamless linkage of two parts to an integral whole, attracting significant attention for potential applications in soft actuators, smart devices, solid batteries, and more. This review provides a comprehensive overview of dynamic bonds employed in welding dynamic cross-linked networks (DCNs). It extensively discusses the classification and fabrication of common epoxy DCNs and acrylate DCNs. Notably, recent advancements in welding processes based on DCNs under external stimuli are detailed, focusing on the welding dynamics among covalent adaptable networks (CANs). [ABSTRACT FROM AUTHOR]

Crowdsourcing Internet of Things (IoT) applications have resulted in the widespread use of smart mobile devices, such as wearable devices and smartphones. E-healthcare is a significant application of crowdsourcing IoT that enables authorized users (for instance, patients, doctors, and nurses) to access and store medical server data via the public Internet or openly available wireless channels. The public Internet and wireless channel are exposed to eclectic hazards and attacks. Thus, user authentication is paramount for the streamlined usage of these services. The article proposes a new authentication protocol called CMAP-IoT for crowdsourcing IoT, which utilizes chaotic maps and authenticated encryption. This protocol allows for mutual authentication between the user and server and establishes a session key for encrypted transmission. Unlike other protocols, CMAP-IoT effectively prevents attacks that compromise user authentication. The security of CMAP-IoT was validated through ROM-based validation and informal security analysis, which demonstrated its resilience against various malicious security vulnerabilities. Additionally, Scyther-tool-based validation confirmed that CMAP-IoT is secure. Lastly, performance evaluation showed that CMAP-IoT requires [2.63–32.73%] and [66.92–94.85%] lower communication and computational costs compared to other authentication protocols making it suitable for e-healthcare applications. [ABSTRACT FROM AUTHOR]

The Internet of Things is an ecosystem that connects billions of smart devices, meters, and sensors. These devices and sensors collect and share data for use and evaluation by organizations in different industry sectors. Humans may use the IoT to live and work more intelligently and gain total control over their lives. Consequently, IoT can be used to connect devices and integrate them with new digital technologies for customers. On the other hand, smart utility companies in the electric, gas, and water sectors need to deliver services more efficiently and analyze their operations in a way that can help optimize performance, detect growing problems in real time, and initiate fixes to avoid unplanned service interruptions. Building actual smart metering networks is costly and time-consuming. Therefore, in this paper, a new Smart Utilities Traffic Scheduling Algorithm (SUTSA) is proposed. To minimize the system complexity, the model is based on narrowband power line communication, in which a wired hidden network sends data across power lines. A simulation is performed using OPNET Modeler 14.5 to evaluate the proposed model. The results proved that the proposed model is highly scalable and achieves full network-bandwidth utilization in different situations based on different application requirements. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) facilitates the delivery of intelligent services by sensing, gathering, processing, and exchanging data from millions of linked smart devices. The Internet of Things (IoT), which is based on communication infrastructure, provides real-time cyber-physical device monitoring, control, and sensing, such as electric autos. Traditional communication infrastructure's vulnerability to cyberattacks hampered IoT's capacity to investigate these potential applications. This study proposes an algorithm for monitoring and controlling electric vehicles through the Internet of Things communication network to prevent fake data injection attacks. A state-space model depicts a fully autonomous electric car equipped with a vision system. Intelligent sensors and actuators from the Internet of Things are utilized to monitor and change system conditions, compensating for the large distance between the electric car and the control center. Sensing data is delivered from the vehicle to the central command center via an insecure, attack-prone communication path. The mean square error approach is used to derive states in the most effective state estimation system for comprehending and showing autos. A semi-definite programming approach is used to create an optimal control algorithm to manage the vehicle states. The simulation results show how precisely and successfully the proposed algorithms can foresee and regulate a vehicle's state. [ABSTRACT FROM AUTHOR]

Storage temperature fluctuation is a major problem faced in food and pharmaceutical industry, apart from prevailing fraud in marketing frozen products as fresh. The present work aimed to study the effect of intrinsic properties of chitosan on synthesis and performance of gold nanoparticles as smart packaging devices. Different types of Chitosan from shrimp waste were used as reducing and capping agent in the synthesis of metal nanoparticle. Time is taken to reduce gold atom to gold nanoparticles varied with the type of reducing agent, between 6 min 40 s to 15 min 02 s. The maximum absorbance (λ max) for AuNPs was observed between 517 and 530 nm. An increase in the concentration of chitosan resulted in smaller and uniform size AuNPs with size ranging from 8.09 to 9.95 nm compared with 14.44 to 19.88 nm for lower concentration of chitosan. Visible ruby red colour of AuNPs synthesised using trisodium citrate (TSC) and lower concentration of chitosan (0.1%) changed to colourless and grey to blue, respectively upon exposure to frozen condition (−18 °C ± 1 °C). UV Visible spectra indicated distinctly different (broader) spectrum with reduced peak intensity. A visible change in colour from ruby red to bluish and colourless state indicates that irrespective of the properties of available chitosan, it can be used for synthesis of gold nanoparticles as smart packaging to distinguish packed fresh/chilled/refrigerated products from frozen ones. [ABSTRACT FROM AUTHOR]

Home area network (HAN) devices send the electricity consumption and other important data to the smart meter that must remain confidential from other devices. This paper proposes a novel one-dimensional hybrid chaotic map. The proposed map shows excellent chaotic properties when analyzed by bifurcation diagram, Lyapunov exponent & Shannon entropy. We further design an encryption strategy for data transfers between the smart meter and HAN devices. The proposed encryption scheme uses the existing lightweight key management in advanced metering infrastructure (LKM-AMI) architecture for data transfers, in which the encrypted data is transferred through an insecure channel and private keys are provided by trusted third party (TTP) through secure channels. The 2-way communication between HAN devices and the smart meter sends messages that are encrypted by using the proposed novel hybrid one-dimensional chaotic map. The encryption strategy mainly consists of three steps. In the first step, the seed and the control parameters are initialized. The second phase generates two intermediate keys using the proposed hybrid chaotic map. In the last phase, we encrypt the message by applying permutation followed by diffusion using intermediate keys. The proposed encryption strategy is resistant to various attacks. [ABSTRACT FROM AUTHOR]