Memory Storage Research Articles

An Assessment of the Role of the Timex Sampling Strategy on the Precision of Shoreline Detection Analysis

Remote video imagery using shoreline edge detection is widely used in coastal monitoring in order to acquire measurements of nearshore and swash features. Some of these systems are constrained by their long setup time, positioning requirements and considerable hardware costs. As such, there is a need for an autonomous low-cost system (~EUR 500), such as Timex cameras, that can be rapidly deployed in the field, while still producing the outcomes required for coastal monitoring. This research presents an assessment of the effect of the sampling strategy (time-lapse intervals) on the precision of shoreline detection for two low-cost cameras located in a remote coastal area in western Ireland, overlooking a dissipative beach–dune system. The analysis shows that RMSD in the detected shoreline is similar to other studies for sampling intervals ranging between 1 s and 30 s (i.e., RMSDmean for Camera 1 = 1.4 m and Camera 2 = 0.9 m), and an increase in the sampling interval from 1 s to 30 s had no significant adverse effect on the precision of shoreline detection. The research shows that depending on the intended use of the detected shorelines, the current standard of 1 s image sampling interval when using Timex cameras can be increased up to 30 s without any significant loss of accuracy. This positively impacts battery life and memory storage, making the systems more autonomous; for example, the battery life increased from ~10 days to ~100 days when the sampling interval was increased from 1 to 5 s.

Cycle equivalence classes, orthogonal Weingarten calculus, and the mean field theory of memristive systems

It has been recently noted that for a class of dynamical systems with explicit conservation laws represented via projector operators, the dynamics can be understood in terms of lower dimensional equations. This is the case, for instance, of memristive circuits. Memristive systems are important classes of devices with wide-ranging applications in electronic circuits, artificial neural networks, and memory storage. We show that such mean-field theories can emerge from averages over the group of orthogonal matrices, interpreted as cycle-preserving transformations applied to the projector operator describing Kirchhoff’s laws. Our results provide insights into the fundamental principles underlying the behavior of resistive and memristive circuits and highlight the importance of conservation laws for their mean-field theories. In addition, we argue that our results shed light on the nature of the critical avalanches observed in quasi-two-dimensional nanowires as boundary phenomena.

Tuneable quantised conductance memory states in TiO2 based resistive switching devices in crossbar geometry for high density memory applications

The tunability and controllability of conductance quantization mediated multilevel resistive switching (RS) memory devices, fabricated in crossbar geometry can be a promising alternative for boosting storage density. Here, we report fabrication of Cu/TiO2/Pt based RS devices in 8 × 8 crossbar geometry, which showed reliable bipolar RS operations. The crossbar devices showed excellent spatial and temporal variability, time retention and low switching voltage (<1 V) and current (∼100 μA). Furthermore, during the reset switching, highly repeatable and reliable integral and half-integral quantized conductance (QC) was observed. The observed QC phenomenon was attributed to the two dimensional confinement of electrons as lateral width of the conducting filament (CF) matches the fermi wavelength. The magnitude and number of the QC steps were found to increase from ∼2.5 to 12.5 and from 5 to 18, respectively by increasing the compliance current (I C) from 50 to 800 μA which also increased the diameter of the CF from ∼1.2 to 3.3 nm. The enhancement in both number and magnitude of QC states was explained using electrochemical dissolution mechanism of CF of varying diameter. A thicker CF, formed at higher I C, undergoes a gradual rupture during reset process yielding a greater number of QC steps compared to a thinner CF. The realisation of QC states in the crossbar Cu/TiO2/Pt device as well as I C mediated tunability of their magnitude and number may find applications in high-density resistive memory storage devices and neuromorphic computing.

Complete Stability of Delayed Recurrent Neural Networks With New Wave-Type Activation Functions.

Activation functions have a significant effect on the dynamics of neural networks (NNs). This study proposes new nonmonotonic wave-type activation functions and examines the complete stability of delayed recurrent NNs (DRNNs) with these activation functions. Using the geometrical properties of the wave-type activation function and subsequent iteration scheme, sufficient conditions are provided to ensure that a DRNN with n neurons has exactly (2m + 3)n equilibria, where (m + 2)n equilibria are locally exponentially stable, the remainder (2m + 3)n - (m + 2)n equilibria are unstable, and a positive integer m is related to wave-type activation functions. Furthermore, the DRNN with the proposed activation function is completely stable. Compared with the previous literature, the total number of equilibria and the stable equilibria significantly increase, thereby enhancing the memory storage capacity of DRNN. Finally, several examples are presented to demonstrate our proposed results.

A numerical method for two-dimensional transient nonlinear convection-diffusion equations

In this research, we have developed the half-boundary method (HBM) for nonlinear convection-diffusion equations (CDEs), which hold significant importance in nuclear power engineering. The HBM employs a variable relationship between the nodes within the computational domain and the nodes located on half of the boundaries. This approach offers notable benefits, includingthe reduction ofthe maximum matrix order and the optimization the maximum memory storage for calculations. Moreover, the HBM is an efficient and streamlined approach to directly handle Neumann boundary conditions, thanks to the utilization of mixed variables. We primarily investigate the memory usage and accuracy of the proposed algorithm in the unsteady-state CDEs, in context of material nonlinear CDEs, the Burgers’ equation and the system of Burgers' equations. The numerical results obtained demonstrate the method’s potential in simulating flow and heat transfer phenomena, particularly in situations where convection is dominant.

Self-powered photodetector based on 1D TiO2-3D CdS mixed dimensional heterostructure fabricated at low temperature

Solution processed photodetectors have garnered great attention in applications such as, machine vision perception, neuromorphic computing and opto-electronic memory storage. Though, such photodetectors offer several advantages such as ease of fabrication, high scalability, low thermal budget and low-cost processing, multi-modal functionality etc. however, they suffer from the major drawback of inferior device performance −as low responsivity and slow rise time, particularly due to the intrinsic poor crystallinity of the photoactive material. In this work, we demonstrate a solution processed photodetector with impressive performance at comparatively low processing temperatures (<150 °C) based on the mixed dimensional heterostructure configuration of 1D TiO2 nanorods and 3D CdS nanoflowers. TiO2 nanorods have been synthesized by hydrothermal technique, whereas their CdS sensitization is done by chemical bath deposition. Low cost carbon paste is used as electrode instead of conventional non-economic noble metal electrodes. X-ray diffraction studies validated excellent crystallinity of the photoactive material even under low temperature processing condition. The type-II Heterojunction (TiO2 and CdS) configuration photodetector shows efficient response at zero bias, thus yielding a self-powered device. The detector shows response in UV and visible region, with excellent responsivity of 110 mA/W (5 V), 563 µA/W (0 V) and a quicker rise time of 81 ms. Albeit the simple fabrication scheme and low processing temperatures, the detector exhibited promising figures-of-merit, which aids in fabrication of novel solution processed photodetectors.

Synthesis and multifunctional characterizations of Gd2 O3 and Sm2 O3 modified ZnO nanoparticles

In the present communication multifunctional characterizations suitable for spintronics and memory storage devices are described. Double doped (Gd3+, Sm3+) ZnO nanoparticles are prepared from Sol-Gel method using poly vinyl alcohol (PVA) as chelating agent. The as prepared powders are annealed at 500 °C–1000 °C with a step size of 100 °C. The genesis of single phase hexagonal wurtzite structure, morphological and topographical changes, optical, magnetic and mechanical properties were studied with XRD (X-ray diffraction), SEM (scanning electron microscopy), TEM (transmission electron microscopy), EDS (energy dispersive spectroscopy), UV- DRS (ultraviolet diffuse reflective spectroscopy), PL (photoluminescence), VSM (vibrating sample magnetometer) and pin on disc tribometer. XRD study untangled the crystallite size and found to be in the range23-50nm. Polycrystalline nanoparticles of spherical geometry with induced porosity is observed from SEM study. The particle size associated with the samples annealed at 500 °C and 900 °C is 24 nm and 27 nm respectively from TEM study. Analyzed the proximity of functional groups, molecular vibrations in the range of 400-4000 cm−1 employing FTIR (Fourier transform infrared spectroscopy). EDS results revealed the stoichiometry of the produced samples. The pronounced optoelectronic applications of Zn1-x Gdx Smx O (ZGS) can be attributed to the large band gap (3.50–3.02 eV) associated with the materials with rise in annealing temperature. The room temperature ferromagnetism was evidenced with double doped ZnO nanomaterials. The wear coefficient, and friction coefficient were evaluated using pin-on-disc tribometer. The utility of materials as solid state lubricants was confiscated from the range of frictional coefficient values (0.067–0.893).

Processing wh-filler-gap dependencies.

We present experimental evidence showing that different wh-filler-gap dependencies are processed differently, depending on their syntactic licensors. Our studies compared the active storage profiles for why, how, and who (serving as subject or object of the verb). The results of offline and online experiments revealed that these wh-fillers are stored in memory for different durations, and predictably so based on the hypothesised structural distance between each wh-filler and the licensor which determines its grammatical and interpretive functions. Furthermore, the results showed that once the wh-filler is licenced, it is integrated to the current structure, and no longer engenders additional memory costs. Based on these findings, we argue that the mechanism of online sentence processing may employ both storage and integration components in memory.

Beyond the Pump: A Narrative Study Exploring Heart Memory.

The field of organ transplantation, particularly heart transplantation, has brought to light interesting phenomena challenging traditional understandings of memory, identity, and consciousness. Studies indicate that heart transplant recipients may exhibit preferences, emotions, and memories resembling those of the donors, suggesting a form of memory storage within the transplanted organ. Mechanisms proposed for this memory transfer include cellular memory, epigenetic modifications, and energetic interactions. Moreover, the heart's intricate neural network, often referred to as the "heart brain," communicates bidirectionally with the brain and other organs, supporting the concept of heart-brain connection and its role in memory and personality. Additionally, observations from hemispherectomy procedures highlight the brain's remarkable plasticity and functional preservation beyond expectations, further underscoring the complex interplay between the brain, body, and identity. However, ethical and philosophical questions regarding the implications of these findings, including the definition of death and the nature of personal identity, remain unresolved. Further interdisciplinary research is needed to unravel the intricacies of memory transfer, neuroplasticity, and organ integration, offering insights into both organ transplantation and broader aspects of neuroscience and human identity. Understanding these complexities holds promise for enhancing patient care in organ transplantation and deepens our understanding of fundamental aspects of human experience and existence.

Versatile polyamides with new triphenylamine monomer based on dinaphtho furan as core for electrochromic/electrofluorochromic device, TNP detection and memory storage

In order to obtain a versatile electrochromic (EC) and electrofluorochromic (EFC) material with good processability, stable redox properties, high optical contrast and fast response, a novel diamine monomer, N1, N1'-(dinaphtho[2,1-b:1',2'-d] furan-5,9-diyl) bis(N1-(4-methoxyphenyl) benzene- 1,4-diamine) (DNFTPA-NH2), which introducing an oxa[5]helicene core into two electron-rich triphenylamine (TPA) blocks is designed and synthesized. Subsequently, four polyamides (PAs) were obtained via polycondensation of diamine with dicarboxylic acids, denoted as DNFTPA-CA, DNFTPA-OA, DNFTPA-NA and DNFTPA-SA, respectively. The four PAs show excellent solution processability and thermal stability, and cyclic voltammograms (CV) with excellent redox reversibility. Among them, DNFTPA-SA shows marked optical contrast of 34 % at 831 nm and rapid switching time (color/bleach, 3.23s/0.39s) between 0 V and 1.0 V, with no significant decay after 5000 s cycle. DNFTPA-CA exhibits high fluorescence (PL) quantum efficiency of 27 %, which is sensitive to explosive trinitrophenol (TNP) with a low detection limit of 7.24 × 10−2 μM. Given the practical application, it is deemed necessary to prepare EC/EFC device. The findings demonstrate the value of PAs for practical applications in EC/EFC device. Moreover, PAs used in memory devices with sandwich structure of ITO/PAs/Al demonstrate non-volatile flash-type behavior with excellent stability within 10000 s and current switching ratios up to 103. Thus, it provides a facile strategy for the design of polymers in the devices of EC/EFC, PL sensing detection and memristor.

A post-quantum secure PUF based cross-domain authentication mechanism for Internet of drones

With the increasing prevalence of drones, guaranteeing their authentication and secure communication has become paramount in drone networks to mitigate unauthorized access and malicious attacks. Cross-domain authentication is crucial in the context of the Internet of Drones (IoD) for safely verifying and establishing trust between diverse drones and their respective control stations, which may belong to different regions or organizations. Effectively accessing resources or services in another domain while maintaining security and efficiency poses a significant challenge. Conventional authentication mechanisms relying on challenging problems like discrete logarithm and integer factorization might not be sufficient to guarantee the security and effectiveness of drone-based systems in the post-quantum era. To address this, we propose a distributed post-quantum cryptography and Physical Unclonable Function (PUF) based cross-domain authentication protocol for IoD. Key contributions of this work include the elimination of secret key storage on drones, mutual authentication, emphasis on hardware security, incorporation of post-quantum security measures, efficient cross-domain authentication and resilience against cyber attacks such as eavesdropping, impersonation, replay attack, untraceability, and PUF-modeling attack. The performance of the proposed protocol is assessed utilizing metrics like processing time, communication cost and storage utilization. In operations associated to the blockchain ledger, variables such as latency, throughput, CPU utilization, and memory utilization are also examined. The protocol shows a reduced computation time and zero sensitive data storage in drone memory, despite a slightly higher communication cost that is manageable with 5G-enabled drones. Comparative analysis against existing solutions in the domain highlights the superior security of the proposed protocol, positioning it as a promising solution for the evolving quantum landscape.

Confining single Er3+ ions in sub-3 nm NaYF4 nanoparticles to induce slow relaxation of the magnetisation

Molecular systems known as single-molecule magnets (SMMs) exhibit magnet-like behaviour of slow relaxation of the magnetisation and magnetic hysteresis and have potential application in high-density memory storage or quantum computing. Often, their intrinsic magnetic properties are plagued by low-energy molecular vibrations that lead to phonon-induced relaxation processes, however, there is no straightforward synthetic approach for molecular systems that would lead to a small amount of low-energy vibrations and low phonon density of states at the spin-resonance energies. In this work, we apply knowledge accumulated over the last decade in molecular magnetism to nanoparticles, incorporating Er3+ ions in an ultrasmall sub-3 nm diamagnetic NaYF4 nanoparticle (NP) and probing the slow relaxation dynamics intrinsic to the Er3+ ion. Furthermore, by increasing the doping concentration, we also investigate the role of intraparticle interactions within the NP. The knowledge gained from this study is anticipated to enable better design of magnetically high-performance molecular and bulk magnets for a wide variety of applications, such as molecular electronics.

Reconciling the PSBG and CBM Models of Musical Processing: A Response to Schubert and Pearce

Schubert and Pearce (2016) contrast two modes of musical memory (more broadly, musical perception and cognition): the schematic and the veridical, which they formalise in terms of the Problem-Solving by Generalisation (PSBG) and Case-Based Memory (CBM) models, respectively. The former hypothesises the ab- straction of schematic categories as solutions to the processing of unfamiliar music, the latter the invocation of (sequentially concatenated segments of) a vast memory store of previously heard pieces as locally stored “keys” engaging with the relevant incoming “locks”. This article explores how these two models might be implemented neuronally, in terms of Calvin’s Hexagonal Cloning Theory (HCT), arguing that they can be explained as two related, indeed complementary, functions of the same un- derpinning mechanism. It also explores the cultural-evolutionary implications of the two models through the lens of memetics.

Internet of Things assisted Unmanned Aerial Vehicle for Pest Detection with Optimized Deep Learning Model

IoT technologies &amp; UAVs are frequently utilized in ecological monitoring areas. Unmanned Aerial Vehicles (UAVs) &amp; IoT in farming technology can evaluate crop disease &amp; pest incidence from the ground’s micro &amp; macro aspects, correspondingly. UAVs could capture images of farms using a spectral camera system, and these images are been used to examine the presence of agricultural pests and diseases. In this research work, a novel IoT- assisted UAV- based pest detection with Arithmetic Crossover based Black Widow Optimization-Convolutional Neural Network (ACBWO-CNN) model is developed in the field of agriculture. Cloud computing mechanism is used for monitoring and discovering the pest during crop production by using UAVs. The need for this method is to provide data centers, so there is a necessary amount of memory storage in addition to the processing of several images. Initially, the collected input image by the UAV is assumed on handling the via-IoT-cloud server, from which the pest identification takes place. The pest detection unit will be designed with three major phases: (a) background &amp;foreground Segmentation, (b) Feature Extraction &amp; (c) Classification. In the foreground and background Segmentation phase, the K-means clustering will be utilized for segmenting the pest images. From the segmented images, it extracts the features including Local Binary Pattern (LBP) &amp;improved Local Vector Pattern (LVP) features. With these features, the optimized CNN classifier in the classification phase will be trained for the identification of pests in crops. Since the final detection outcome is from the Convolutional Neural Network (CNN); its weights are fine-tuned through the ACBWO approach. Thus, the output from optimized CNN will portray the type of pest identified in the field. This method’s performance is compared to other existing methods concerning a few measures.

Control of working memory by phase–amplitude coupling of human hippocampal neurons

Retaining information in working memory is a demanding process that relies on cognitive control to protect memoranda-specific persistent activity from interference1,2. However, how cognitive control regulates working memory storage is unclear. Here we show that interactions of frontal control and hippocampal persistent activity are coordinated by theta–gamma phase–amplitude coupling (TG-PAC). We recorded single neurons in the human medial temporal and frontal lobe while patients maintained multiple items in their working memory. In the hippocampus, TG-PAC was indicative of working memory load and quality. We identified cells that selectively spiked during nonlinear interactions of theta phase and gamma amplitude. The spike timing of these PAC neurons was coordinated with frontal theta activity when cognitive control demand was high. By introducing noise correlations with persistently active neurons in the hippocampus, PAC neurons shaped the geometry of the population code. This led to higher-fidelity representations of working memory content that were associated with improved behaviour. Our results support a multicomponent architecture of working memory1,2, with frontal control managing maintenance of working memory content in storage-related areas3–5. Within this framework, hippocampal TG-PAC integrates cognitive control and working memory storage across brain areas, thereby suggesting a potential mechanism for top-down control over sensory-driven processes.

CONSTRUCTING BATANG BATIK MOTIFS USING TURTLE GRAPHICS ALGORITHMS

During the COVID–19 pandemic, many activities were carried out digitally, including storing batik motifs to maintain the cloth pattern's sustainability. The samples were Batang Batik motifs of grapes, Jamblang Papat and Kawung Jenggot. The study aimed to store batik motifs in the form of computer programs with turtle graphics algorithms to ease the batik motif delivery because of the smaller memory storage. Computer programmers are needed to create batik patterns similar to Batang Batik patterns. Python programming uses turtle graphics to paint curves and generate graphics. The results of this study indicated that Batang Batik motifs can be made using turtle graphics without losing the characteristics of the batik itself. This finding can be used for more efficient storage of memory. The quality was also good when it was scaled up and down. This study has successfully created Grape, Jambang Prapat, and Kawung Jenggot motifs using turtle graphics algorithms in Python. The picture quality of the turtle graphics-scaled reconstructed image was equivalent to that of a photo image.

Briefing: Temporary works legacy archive: a pensieve to store memories

The recent release of the Temporary Works Forum’s (TWf) e-learning courses has revolutionised awareness. These courses have shown the importance of being reminded of the past, of lessons learned and other experiences, some of which would be lost without this initiative. The TWf legacy project is to make available an online searchable folder, or a ‘pensieve’. Primarily, this is focused on capturing TW memories, stories and events for archive, partially by retiring members who would like some of their career photos and experiences recorded. The project also aims to interview leading TW practitioners on their current thoughts on achieving best practice.

Bifunctionalized polyamides based on quinoxaline structure for durable electrochromic display and memory storage

With the aim to obtain multifunctional durable electrochromic (EC) devices, we propose an effective strategy by introducing weak electron acceptor segment with suitable bandgap and oxidation potential. A series of quinoxaline-based units polyamides (PAs) (denoted as T2BPA-CA, T2BPA-OA, T2BPA-TP, and T2BPA-SA) were prepared from a novel donor–acceptor-donor (D-A-D) type diamine with weak electron acceptor quinoxaline and connected with two methoxyl-substituted donor triphenylamine, 10,13-bis[4-aminophenyl (4-methoxyphenyl) amino]-dibenzo[a,c]phenazine, and four dicarboxylic acids, which are high soluble in various organic solvents and exhibit excellent thermostability. Furthermore, the T2BPA-SA thin film exhibits excellent EC performance with outstanding optical contrast (50 %), high coloration efficiency (230 cm2 C−1) and impressive cycle stability (optical contrast remains 80 % over 1400 cycles) in the NIR range. Meanwhile, all of these PAs are served as memristors and exhibit typical nonvolatile ternary memory, realizing an accessible threshold voltage of −0.65 V, a retention time of more than104 s and high current switch ratio (103.52:102.43:1). Overall, this work implies the great potential of these PAs in EC displays and memory storage devices.

A new class of single-phase multiferroics: Bismuth-based layered supercell oxide thin films—Current progress and future perspectives

Multiferroic materials, where ferroelectric and magnetic orders coexist, have ignited substantial research interest due to the achievable manipulation of magnetic orders using external electric fields, a feature that has garnered serious interest for memory storage applications. Nonetheless, naturally occurring single-phase multiferroic materials are scarce, thus constraining options for practical use. Over the last decade, bismuth-based layered supercell (LSC) oxides have emerged as novel candidates for multiferroics, catalyzing extensive investigations in this domain. Additionally, these LSC systems are known for their anisotropic structures and optical properties, making them promising for application in optics such as polarizers, beam splitters, and modulators. This thorough review explores the development and current advancements in multiferroic bismuth-based LSC materials. It covers the diverse nature of LSCs, detailing their microstructure, properties, and the mechanics of self-assembly formation. It also highlights the remarkable multifunctional characteristics of LSC-based nanocomposites, with a particular focus on their applications in electronics and optics. Moreover, this review examines the significant potential of LSCs in practical applications, particularly through their integration onto silicon and flexible substrates via heteroepitaxy and film transfer techniques. Finally, it offers insights into potential future research avenues and the broader implications of these versatile LSC materials.

Cognitive style of field dependence-independence modulates the working memory storage of biological motion.

The biological motion refers to the continuous configuration movement of live agents in space. The perceptual processing of biological motion has the specificity of the dissociation between body form and body motion. However, there is limited evidence for whether such specificity continues when holding biological motion in working memory. We explored this question from the perspective of field dependence (FD) and field independence (FI) cognitive styles in the current study. Three categories of biological motion have been developed: intact movement, motion feature, and form feature. We examined the working memory capacity of motion features, form features, intact movements (Experiments 1-3), and the recognition of three categories of biological motion when remembering intact movements (Experiment 4). The results showed that for the motion features, FI individuals had better memory performance when remembering five items and showed greater working memory capacity and recognition compared with FD individuals, whereas the opposite pattern was observed between FI and FD individuals for the form features. The cognitive style could modulate the working memory storage of biological motion when the task becomes demanding, suggesting that body form and body motion are dissociable in working memory. Our study provided additional evidence for the specificity of biological motion processing in working memory, extending the hierarchical neural model. (PsycInfo Database Record (c) 2024 APA, all rights reserved).