Memory Structure Research Articles

A Method for Identifying the Wear State of Grinding Wheels Based on VMD Denoising and AO-CNN-LSTM

Monitoring the condition of the grinding wheel in real-time during the grinding process is crucial as it directly impacts the precision and quality of the workpiece. Deep learning technology plays a vital role in analyzing the changes in sensor signals and identifying grinding wheel wear during the grinding process. Therefore, this paper innovatively proposes a grinding wheel wear recognition method based on Variational Mode Decomposition (VMD) denoising and Aquila Optimizer—Convolutional Neural Network—Long Short-Term Memory (AO-CNN-LSTM). The paper utilizes Acoustic Emission (AE) signals generated during grinding to identify the condition of the grinding wheel. To address noise interference, the study introduces the VMD algorithm for denoising the sample dataset, enhancing the effectiveness of neural network training. Subsequently, the dataset is fed into the designed Convolutional Neural Network—Long Short-Term Memory (CNN-LSTM) structure with AO-optimized parameters. Experimental results demonstrate that this method achieves high accuracy and performance.

Iterative image rain removal network using consecutive residual long short-term memory

Image rain removal is designed to effectively separate rain streaks from the background image layer. However, rain streaks in real-world scenarios vary in density, shape, and direction, making it difficult to decompose rainy images into clean backgrounds and rain layers. In this study, we introduce an iterative framework for image deraining to progressively enhance rainy images using a residual long short-term memory structure. The overall network comprises a multidomain residue channel, a fusion module, and a consecutive residual long short-term memory. We introduce multidomain residue channels by computing them in both the image and wavelet low-frequency domains. We propose a fusion module to combine the residue channel for guidance with wavelet domain features for rain removal. We also propose a feature extraction module based on successive residual long short-term memory to extract the main features in the wavelet domain. An iterative image restoration framework comprising three primary modules is introduced to progressively enhance rainy images. To evaluate the performance of the proposed approach, we conduct experiments using widely used benchmarks. The results demonstrate that our method outperforms state-of-the-art methods in image rain removal https://github.com/workofsu/.

Spontaneous eye movements reflect the representational geometries of conceptual spaces

Functional neuroimaging studies indicate that the human brain can represent concepts and their relational structure in memory using coding schemes typical of spatial navigation. However, whether we can read out the internal representational geometries of conceptual spaces solely from human behavior remains unclear. Here, we report that the relational structure between concepts in memory might be reflected in spontaneous eye movements during verbal fluency tasks: When we asked participants to randomly generate numbers, their eye movements correlated with distances along the left-to-right one-dimensional geometry of the number space (mental number line), while they scaled with distance along the ring-like two-dimensional geometry of the color space (color wheel) when they randomly generated color names. Moreover, when participants randomly produced animal names, eye movements correlated with low-dimensional similarity in word frequencies. These results suggest that the representational geometries used to internally organize conceptual spaces might be read out from gaze behavior.

Temporal memory for threatening events encoded in a haunted house

ABSTRACT Despite the salient experience of encoding threatening events, these memories are prone to distortions and often non-veridical from encoding to recall. Further, threat has been shown to preferentially disrupt the binding of event details and enhance goal-relevant information. While extensive work has characterised distinctive features of emotional memory, research has not fully explored the influence threat has on temporal memory, a process putatively supported by the binding of event details into a temporal context. Two primary competing hypotheses have been proposed; that threat can impair or enhance temporal memory. We analysed two datasets to assess temporal memory for an in-person haunted house experience. In study 1, we examined the temporal structure of memory by characterising memory contiguity in free recall as a function of individual levels of heart rate as a proxy of threat. In study 2, we replicated marginal findings of threat-related increases in memory contiguity found in study 1. We extended these findings by showing threat-related increases in recency discriminations, an explicit test of temporal memory. Together, these findings demonstrate that threat enhances temporal memory regarding free recall structure and during explicit memory judgments.

Space-efficient and high-performance inline deduplication for emerging hybrid storage system with Libra＋

In the face of the ever-increasing data volume of data-intensive applications, deduplication, as a promising solution to reduce space consumption, has attracted increasing attention in modern storage systems. Specifically, in modern SSD caching-based hybrid storage systems, inline deduplication achieves data reduction on the fly before storing data in the SSDs, thereby enhancing performance and extending their lifespan. However, with the emergence of new storage media featuring fast access speed and high endurance, hybrid storage systems have evolved by incorporating these new storage devices in place of SSDs at the front end of the primary storage. In this work, we revisit the concept of inline deduplication in the context of emerging hybrid storage and propose a new inline deduplication system designed for emerging hybrid storage, named Libra＋. Libra＋ contains three components: First, we propose two cooperative index structures for memory and cache. Second, we design a selective deduplication approach to perform targeted deduplication. Third, we introduce a lightweight dirty list that replaces the conventional dirty list in inline deduplication, reducing time overhead and space costs. Experimental results show that Libra＋ can achieve simultaneous performance improvement and space cost reduction.

Testing nanometer memories: a review of architectures, applications, and challenges

Newer defects in memories arising from shrinking manufacturing technologies demand improved memory testing methodologies. The percentage of memories on chips continues to rise. With shrinking technologies (10 nm up to 1.8 nm), the structure of memories is becoming denser. Due to the dense structure and significant portion of a chip, the nanometer memories are highly susceptible to defects. High-frequency specifications, the complexity of internal connections, and the process variation due to newer manufacturing technology further increased the probability of the physical failure of memories to a great extent. Memories need to be defect-free for the chip to operate successfully. Therefore, testing embedded memories has become crucial and is taking significant test costs. Researchers have proposed multiple approaches considering these factors to test the nanometer memories. They include using new fault models, march algorithms, memory built-in self-test (MBIST) architectures, and validation strategies. This paper surveys the methodologies presented in recent times. It discusses the core principles used in them, along with benefits. Finally, it discusses key opens in each and offers the scope for future research.

Distinguishing the rehabilitation of Nazism from related crimes: theory and practice

The subject of this study is the criminal law prohibition on the rehabilitation of Nazism, established by the criminal legislation of the Russian Federation. The author emphasizes the importance of considering aspects of the qualification of this act in the presence of a large number of related crimes, which in all their elements are very close to the one under consideration. The article examines in detail such crimes that are classified as extremist, as well as vandalism, slander, destruction or damage to military graves, monuments, obelisks, other memorial structures or objects perpetuating the memory of those who died defending the Fatherland or its interests, or dedicated to the days of military glory of Russia. The author draws attention to the presence of similar features of the corpus delicti aimed at prohibiting the rehabilitation of Nazism with administrative offenses, in particular, with article 20.3 of the Administrative Code of the Russian Federation. The methodology of the research consists of such methods as formal legal, logical, systematic, as well as the method of analysis. The novelty of this study lies in the complexity and comprehensiveness of the consideration of the stated issues. The author argues that the difficulty of qualification lies in the fact that actions can simultaneously fall under both "extremist" crimes and directly under the corpus delicti, which enshrines the prohibition of rehabilitation of Nazism. The author concludes that the identification of extremism and the prohibition on the rehabilitation of Nazism is incorrect, and Article 354.1 of the Criminal Code of the Russian Federation is special in relation to Article 282 of the Criminal Code of the Russian Federation. The author's special contribution is manifested in a large number of analyzed sources of judicial practice from different years, on the basis of which the author drew his conclusions and justified the terminology used by the legislator in constructing various provisions of Article 354.1 of the Criminal Code of the Russian Federation.

ARCHITECTURAL AND STRUCTURAL AND FUNCTIONAL FEATURES OF THE ORGANIZATION OF PARALLEL-HIERARCHICAL MEMORY

Parallel hierarchical memory (PI memory) is a new type of memory that is designed to improve the performance of parallel computing systems. PI memory is composed of two blocks: a mask RAM and a tail element RAM. The mask RAM stores the masks that are used to encode the information, while the tail element RAM stores the actual information. The address block of the PI memory is responsible for generating the physical addresses of the cells where the tail elements and their masks are stored. The address block also stores the field of addresses where the array was written and associates this field of addresses with the corresponding external address used to write the array. The proposed address block structure is able to efficiently generate the physical addresses of the cells where the tail elements and their masks are stored. The address block is also able to store the field of addresses where the array was written and associate this field of addresses with the corresponding external address used to write the array. The proposed address block structure has been implemented in a prototype PI memory. The prototype PI memory has been shown to be able to achieve significant performance improvements over traditional memory architectures. The paper will present a detailed description of the PI transformation algorithm, a description of the different modes of addressing organization that can be used in PI memory, an analysis of the efficiency of parallel-hierarchical memory structures, and a discussion of the challenges and future research directions in the field of PI memory.

Методы сетевого моделирования структуры семантической памяти: теоретический обзор

The article is aimed at considering the network modeling methods for human semantic memory structure. The work provides an analytical review of existing approaches to modeling the structure of human semantic memory, as a result of which the most methodologically optimal way of modeling semantic memory is estab-lished – based on the construction and analysis of semantic networks. The authors study various methods of network modeling of semantic memory structure: verbal fluency problem, snowball problem, semantic connec-tivity problem. In addition, examples of using these methods in psychological research are given, and their methodological advantages and disadvantages are highlighted. The results of the present work can be useful in the formation of new methods for network modeling of the structure of human semantic memory, as well as in the creation of intelligent systems that process graph data.

4D-printing of high-temperature shape-memory polymers based on polyimide, N,N-dimethylacrylamide and photoactive cross-linkers

Thermally responsive shape memory polyimides (PIs) have attracted significant attention in the high-tech fields like aerospace industry. At the same time creating of materials and approaches to the formation of three-dimensional (3D) shape memory structures containing PIs remains an urgent task. In this work we have developed new photopolymeric compositions (PPCs) based on high-performance readily soluble PI, reactive solvent (N,N-dimethylacrylamide) and photoactive cross-linker (bisphenol A ethoxylate diacrylate (BAEDA) or tris[2-(acryloyloxy)ethyl] isocyanurate (TAI)). The resulting PPCs were used to form 3D-structures using LCD 3D-printing. It has been found that the nature of the cross-linker and post-processing temperature have a significant impact on the thermal and mechanical properties of the materials. The tensile strength has the maximum value after the thermal post-curing at 250°С for 1 h (83.3 ± 7.4 MPa and 60.8 ± 4.8 MPa for PPCs with TAI and BAEDA, respectively). Moreover, 4D-printed PI-containing materials exhibit an excellent shape memory performance at recovery temperatures >150 °C, with shape fixity ratio >99% and shape recovery ratio up to 95.6%.

Color blindness and semantic knowledge: Cognition of color terms from elicited lists in dichromats and normal observers

AbstractColor blindness (color vision deficiency) affects ~8% of males and ~ 0.4% females worldwide. Here we use the elicited lists method to investigate their semantic knowledge regarding “basic color terms” and their relationships. Lists were obtained from color vision deficient and normal observers. 32 dichromats (15 protanopes, 17 deuteranopes) and 32 normal trichromats (17 females, 15 males) diagnosed by a battery of color tests (Ishihara, City University Test, anomaloscope) wrote monolexemic lists of colors. Psychological salience of terms (ln(CSI)), adjacency between pairs of terms (ADJ; MDS) and the presence of clusters of terms defined on the basis of the Universals and evolution hypothesis were analyzed. All four groups of participants showed the same semantic memory structure: lists started with the cardinal primaries cluster (blue, red, yellow, green), followed by the achromatic primaries cluster (black and white), or the derived cluster (brown, orange, violet, pink, purple, and gray). After the clusters (cardinals, achromatics, and derived), a highly variable number of non‐basic terms appeared. This number was higher in normal trichromats. Non‐basic terms were not part of any cognitive cluster. The similarity in the lists of trichromats and dichromats suggest that both may acquire similar semantic knowledge about color terms. Several potential explanations are considered.

High thermal stability effect of vanadium on the binary CuAl base alloy for a novel CuAlV high-temperature shape memory alloy

Abstract In this study, two high-temperature shape memory alloys (HTSMAs) of CuAlV with unprecedented chemical compositions were fabricated using the arc melting technique, followed by traditional ice-brine water quenching after the melting process. To characterize the shape memory properties and structure of the alloys, a series of tests including differential calorimetry (DSC and DTA), EDS, optical microscopy, and XRD were conducted. The DSC tests, performed at different heating and cooling rates, demonstrated highly stable reversible martensitic phase transformation peaks at high temperatures, which were also confirmed by the results of DTA tests. Microstructural XRD and optical microscopy tests were conducted at room temperature, revealing the martensitic structure of the alloys in both cases. Based on all the results, the effects of different minor amounts of vanadium additives directly on the CuAlV alloy were discussed.

IMPROVING WORKING CONDITIONS FOR WORKERS INSTALLING MONUMENTS IN RITUAL ECONOMY

The ritual industry in everyday life is emotionally associated with mourning. Оccupational safety issues in this industry are not discussed as widely in society as in other industries. The ritual industry does not have its own sectoral labor protection rules, therefore, labor protection issues are regulated only by intersectoral labor protection rules.
 Memorial structures in terms of weight, as a rule, exceed the maximum permissible norms for single lifting and moving weights for men. Therefore, when lifting and moving memorial structures, means of small mechanization are required.
 In large cities, burial in cemeteries is very dense and the passages between the graves are getting narrower and narrower. Therefore, at present, an essential requirement for the means of mechanization for the transportation
 of monuments is the requirement that the dimensions of transport mechanisms correspond to the dimensions of narrow passages. Various types of mechanization equipment (trolleys) for transporting monuments are presented on the Russian market, but most of them are wider in size than necessary.
 This article examines the working conditions and risks of a worker installing monuments in a ritual household. The article presents technical solutions for moving memorial structures around the cemetery using small-scale mechanization tools to reduce the severity of workers» labor. Reducing the severity of workers» work will reduce the number of.

Nonvolatile memory cells from hafnium zirconium oxide ferroelectric tunnel junctions using Nb and NbN electrodes

Ferroelectric tunnel junctions (FTJs) utilizing hafnium zirconium oxide (HZO) have attracted interest as non-volatile memory for microelectronics due to ease of integration into back-end-of-line (BEOL) complementary metal oxide semiconductor fabrication. This work examines asymmetric electrode NbN/HZO/Nb devices with 7 nm thick HZO as FTJs in a memory structure, with an output resistance that can be controlled by read and write voltages. The individual FTJs are measured to have a tunneling electroresistance of 10 during the read state without significant filament conduction formation and reasonable ferroelectric performance. Endurance and remanent polarizations of up to 105 cycles and 20 μC/cm2, respectively, are measured and are shown to be dependent on the cycling voltage. Electrical measurements demonstrate how magnitude of the write pulse can modulate the high state resistance and the read pulse influences both resistance values as well as separation of resistance states. Then, by using two opposite switching FTJ devices in series, a programmable nonvolatile resistor divider is demonstrated. Measurements of these two FTJ unit memory cells show wide applicability to a BEOL microfabrication process for a re-readable, rewritable, and nonvolatile memory cell.

A phase-field simulation of easily switchable vortex structure for multilevel low-power ferroelectric memory

Ferroelectric materials with multi-directional polarization orders can form a variety of special domain structures, which have a wide range of applications. In this work, lead-free potassium sodium niobate ferroelectric thin films were simulated by solving the Time-Dependent-Landau-Ginzburg (TDLG) equation. Based on vortex topological structure characteristic of perovskite-type ferroelectric, domain types are simplified from 26 to 9 through virtual polarization vectors. By temperature selection, we accomplished a large easily switchable vortex structure with 20% side length. Based on this, as low as 0.04V/nm electric-field pulse was applied to explore vortex domain structures change. Under different low external electric-field pulses, conductance states change in vortex have been calculated and discussed systematically. Free energy computation results reveal that the domain wall (DW) conductance states primarily originate from the competition between electrostatic energy, gradient energy, and elastic energy. Finally, we propose the multilevel data ferroelectric memory through easily switchable vortex topological structures for the first time. Under electric-field pulses, diverse storage states were presented through 0/1 measurement of 8 positions. By achieving an easy-to-distinguish and robust-to-switch data map at the vortex structure, this work might provide a significant idea of vortex structure on low-power ferroelectric memory applications.

TLN-LSTM: an automatic modulation recognition classifier based on a two-layer nested structure of LSTM network for extremely long signal sequences

Purpose Automatic modulation recognition (AMR) is a challenging problem in intelligent communication systems and has wide application prospects. At present, although many AMR methods based on deep learning have been proposed, the methods proposed by these works cannot be directly applied to the actual wireless communication scenario, because there are usually two kinds of dilemmas when recognizing the real modulated signal, namely, long sequence and noise. This paper aims to effectively process in-phase quadrature (IQ) sequences of very long signals interfered by noise. Design/methodology/approach This paper proposes a general model for a modulation classifier based on a two-layer nested structure of long short-term memory (LSTM) networks, called a two-layer nested structure (TLN)-LSTM, which exploits the time sensitivity of LSTM and the ability of the nested network structure to extract more features, and can achieve effective processing of ultra-long signal IQ sequences collected from real wireless communication scenarios that are interfered by noise. Findings Experimental results show that our proposed model has higher recognition accuracy for five types of modulation signals, including amplitude modulation, frequency modulation, gaussian minimum shift keying, quadrature phase shift keying and differential quadrature phase shift keying, collected from real wireless communication scenarios. The overall classification accuracy of the proposed model for these signals can reach 73.11%, compared with 40.84% for the baseline model. Moreover, this model can also achieve high classification performance for analog signals with the same modulation method in the public data set HKDD_AMC36. Originality/value At present, although many AMR methods based on deep learning have been proposed, these works are based on the model’s classification results of various modulated signals in the AMR public data set to evaluate the signal recognition performance of the proposed method rather than collecting real modulated signals for identification in actual wireless communication scenarios. The methods proposed in these works cannot be directly applied to actual wireless communication scenarios. Therefore, this paper proposes a new AMR method, dedicated to the effective processing of the collected ultra-long signal IQ sequences that are interfered by noise.

The reach of reactivation: Effects of consciously triggered versus unconsciously triggered reactivation of associative memory

Consolidating memories for long-term storage depends on reactivation. Reactivation occurs both consciously, during wakefulness, and unconsciously, during wakefulness and sleep. While considerable work has examined conscious awake and unconscious sleep reactivation, in this study, we directly compare the consequences of conscious and unconscious reactivation during wakefulness. Forty-one participants learned associations consisting of adjective-object-position triads. Objects were clustered into distinct semantic groups (e.g., fruits, vehicles) such that we could examine consequences of reactivation on semantically related memories. After an intensive learning protocol, we systematically reactivated some of the triads by presenting the adjective as a cue. Reactivation was done so that it was consciously experienced for some triads, and only unconsciously processed for others. Memory for spatial positions, the most distal part of the association, was affected by reactivation in a consciousness-dependent and memory-strength-dependent manner. Conscious reactivation resulted in weakening of semantically related memories that were strong initially, resonating with prior findings of retrieval-induced forgetting. Unconscious reactivation, on the other hand, selectively benefited weak reactivated memories, as previously shown for reactivation during sleep. Semantically linked memories were not impaired, but rather were integrated with the reactivated memory. These results taken together demonstrate that conscious and unconscious reactivation have qualitatively different consequences. Results support a consciousness-dependent inhibition account, whereby unconscious reactivation entails less inhibition than conscious reactivation, thus allowing more liberal spread of activation. Findings set the stage for additional exploration into the role of conscious experience in memory storage and structuring.

An Optimized Device Structure with a Highly Stable Process Using Ferroelectric Memory in 3D NAND Flash Memory Applications

In this paper, we propose an optimized device structure with a highly stable process that addresses threshold voltage shift issues in the String-Select-Line (SSL) and Ground-Select-Line (GSL) gates using ferroelectric memory in 3D NAND flash memory applications. The proposed device utilizes nickel (Ni) instead of tungsten (W) for the GSL and SSL gates, enabling optimized polarization properties during the annealing process and leveraging the disparity in thermal expansion coefficients. Notably, the difference in thermal expansion coefficient from tungsten (W), employed in other Word Line (WL) gates, allows effective control over polarization properties. To validate the proposed structure, we fabricated and measured a Metal–Ferroelectric–Insulator–Silicon (MFIS) capacitor utilizing Hafnium–Zirconium Oxide (HZO) material. The measurement results indicate that a change in the upper metal layer results in a more than fivefold increase in the variance of polarization characteristics between the WL gates (responsible for the memory function) and the SSL and GSL gates dedicated to channel control. In addition, process simulation was conducted using the same device structure, confirming the application of tensile stress to the HZO thin film in the case of a W electrode and compressive stress in the case of a Ni electrode. Furthermore, applying this controlled polarization characteristic parameter to the 3D NAND flash memory structure revealed a reduction in the threshold voltage shift of the control gate from a previous change of 2.6 V or more to 0.05 V, facilitating stable control.

Effects of Dy on structural, morphology, optical, and resistive switching properties of HfO2 thin films

This paper studies the effect of Dy on the structure, morphology, and optical properties of HfO2 thin films deposited on fused silica substrates and the optical transparency and resistive switching (RS) behavior of the thin films as an active insulator layer in Ag/active insulator layer/ITO/glass memories. Thin films were deposited by spin-coating using a precursor solution obtained by the Pechini-type sol-gel method. The structural analysis revealed that the insertion of Dy ions into the HfO2 lattice caused the phase transformation from the monoclinic to the cubic phase. Morphological analysis revealed that the thin films had thicknesses between 98 and 101 nm, and their surfaces were composed of 3D islands formed by aggregates of spherical particles ranging from 8 to 5 nm. The active insulator layers had thicknesses ranging from 235 to 218 nm, with no cavities or cracks between them. The optical transparency of the active insulator layer/ITO/glass memory structures was between 70 and 87 %. Optical transmittance, optical bandgap, and optical constants were modified incorporating Dy ions into HfO2 thin films compared to the undoped HfO2 thin films. Incorporating Dy ions into HfO2 increased oxygen vacancies in the active insulator layers. The memory with 10 w% of Dy had the highest resistance off/on ratio of 9.04 compared with undoped HfO2 memory. Also, the conduction mechanism in the high resistive state (HRS) of the memory with 10 w% of Dy was related to ohmic conduction and space charge limited conduction (SCLC).

Hyperbranched polyimide with triazole core structure for nonvolatile resistive switching memory

AbstractHyperbranched polyimides (HBPIs) possess a unique branched structure, which can make the lowest unoccupied molecular orbitals (LUMOs) degenerate and reduce the bandgap between the highest occupied molecular orbital (HOMO) and LUMO energy levels. The triazole group can facilitate the charge transfer process. Thus, a novel hyperbranched polyimide (HBPI‐TZA‐6FDA) has been prepared from new triazole derivative triamine monomer (TZA) and 4,4′‐(hexafluoroisopropylidene)diphthalic anhydride (6FDA) for memory device. The memory device with the structure ITO/HBPI‐TZA‐6FDA/Al exhibits a low‐threshold voltage of −2.2 V and a high ON/OFF current ratio of about 105. Meanwhile, the memory device shows nonvolatile write once read many times (WORM) type memory behavior and excellent stability with an operation time of 104 at a continuous applied voltage of −1 V. Optical, electrochemical experiments, and molecular simulation have been carried out to illustrate the memory performance. The memory performance is governed by the charge transfer between TZA and 6FDA units. The branched structure and triazole unit can reduce the band gap between HOMO and LUMO energy levels effectively, which is favorable for improving charge transfer and reducing threshold voltage. The HBPI‐TZA‐6FDA‐based memory device is favorable for memory device applications due to its relatively low‐power consumption and high‐operation stability.