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There is growing interest in voxelated matter that is designed and fabricated voxel by voxel 1 – 4 . Currently, inkjet-based three-dimensional (3D) printing is the only widely adopted method that is capable of creating 3D voxelated materials with high precision 1 – 4 , but the physics of droplet formation requires the use of low-viscosity inks to ensure successful printing 5 . By contrast, direct ink writing, an extrusion-based 3D printing method, is capable of patterning a much broader range of materials 6 – 13 . However, it is difficult to generate multimaterial voxelated matter by extruding monolithic cylindrical filaments in a layer-by-layer manner. Here we report the design and fabrication of voxelated soft matter using multimaterial multinozzle 3D (MM3D) printing, in which the composition, function and structure of the materials are programmed at the voxel scale. Our MM3D printheads exploit the diode-like behaviour that arises when multiple viscoelastic materials converge at a junction to enable seamless, high-frequency switching between up to eight different materials to create voxels with a volume approaching that of the nozzle diameter cubed. As exemplars, we fabricate a Miura origami pattern 14 and a millipede-like soft robot that locomotes by co-printing multiple epoxy and silicone elastomer inks of stiffness varying by several orders of magnitude. Our method substantially broadens the palette of voxelated materials that can be designed and manufactured in complex motifs. Voxelated soft matter is designed and fabricated using multimaterial multinozzle three-dimensional printing, which switches between different viscoelastic inks along the same print filament to print multiple materials simultaneously.

An Aggregation-Aware Energy-Efficient Bit-Mapping Medium Access Control Protocol (AABMP) is proposed for efficient data transmission in Wireless Sensor Networks and the Internet of Things. The main objective of the proposed method is to effectively manage the data transmission from sensor nodes to cluster heads in an energy-efficient manner. AABMP aggregates the data by estimating the mean value of a sliding window of the previous few samples and calculates the deviation of the current reading with respect to mean value. The deviation aware method is proposed for the transmission decision from sensor node to cluster head node. The deviation is predicted for real-time dataset using various machine learning methods. Based on performance evaluations, the most effective ML method is integrated with the bit-mapping MAC protocol in an energy-efficient manner. The aggregation-aware ML approach reduces the number of transmitted packets by efficiently identifying redundant data. The proposed approach is evaluated using the Intel LAB dataset ( https://db.csail.mit.edu/labdata/labdata.html ) of 55 real sensor nodes. The proposed method demonstrates practical applicability for energy-efficient data transmission in IoT-oriented WSN deployments. For the efficient analysis, the precise number of transmitted packet is estimated based on transmission probability. The algorithm is proposed for the estimation of transmission probability. For performance analysis, we have compared multiple ML methods to determine the most suitable one. This optimal method is then integrated with the bit-mapping-based energy-efficient piggybacking scheme. AABMP is also compared with existing MAC protocols. The results demonstrate its superiority in terms of energy savings across both worst-case and best-case scenarios.

Reliable and efficient medium access control (MAC) protocols are crucial for energy-efficient data communication and effective resource utilization in Wireless Sensor Networks (WSNs). In this work, we propose an Energy-Efficient UAV-assisted Two-Layer Hierarchical (EE-UAV-TLH) MAC protocol, designed for mission-critical applications with energy constraints and limited bandwidth. The protocol employs a two-level hierarchical clustering structure, where sensor nodes communicate with their Cluster Head (CH), and the CH coordinates with an Unmanned Aerial Vehicle (UAV) for data collection and transmission scheduling. By adopting a bit-mapping access scheme, EE-UAV-TLH significantly reduces idle listening and control overheads, while the UAV acts as a mobile sink and synchronization controller, enhancing scalability and minimizing energy usage. Simulation results across diverse scenarios demonstrate that the TLH-ETDMA variant consistently outperforms its counterparts (TLH-TDMA and TLH-BMA), yielding average energy savings of about 20% over TLH-TDMA and 34% over TLH-BMA. In peak cases, EE-UAV-TLH achieves up to 31% improvement against TLH-TDMA and up to 52% against TLH-BMA. Even under large-scale deployment with 110 nodes, it sustains 17% and 39% savings, respectively, highlighting its superior efficiency and scalability for UAV-assisted WSNs.

This paper proposes a low-floor bit-mapping (LFBM) scheme for bit-interleaved coded modulation (BICM) systems to meet more stringent quality of service requirements of 5G and beyond. For high-efficiency transmissions, we consider the 5G low-density parity-check codes with high-order 2 m -quadrature amplitude modulations (QAMs). The proposed LFBM scheme overcomes plenty of trapping sets induced by the bit interleaver, which focuses on the waterfall performance too aggressively. When the high-order QAM is used, the row-column interleaver specified by the 5G standard is such a bit interleaver. The LFBM scheme only optimizes the rule of mapping an m -bit tuple output by the row-column interleaver to a modulation symbol, rather than the entire bit interleaver. Therefore, the optimized bit mapper is actually an m -bit permutation module concatenated with the original bit interleaver employed in the current 5G BICM systems. The simulation results confirm that the LFBM scheme can lower the error floor of the 5G BICM system by approximately two orders of magnitude, while with negligible performance loss in the waterfall region.

The article is devoted to the introduction of digital watermarks, which formthe basis for copyright protection systems. Methods in this area are aimed at embedding hidden markers that are resistant to various container transformations. This paper proposes a method for embedding a digital watermark into bitmap images using Lagrange interpolation and the Bezier curve formula for five points, called Lagrange interpolation along the Bezier curve 5 (LIBC5). As a means of steganalysis, the RS method was used, which uses a sensitive method of double statistics obtained on the basis of spatial correlations in images. The output value of the RS analysis is the estimated length of the message in the image under study. The stability of the developed LIBC5 method to the detection of message transmission by the RS method has been experimentally determined. The developed method proved to be resistant to RS analysis. A study of the LIBC5 method showed an improvement in quilting resistance compared to that of the INMI image embedding method, which also uses Lagrange interpolation. Thus, the LIBC5 stegosystem can be successfully used to protect confidential data and copyrights.

Mining high utility itemsets is one of the most important research issues in data mining owing to its ability to consider nonbinary frequency values of items in transactions and different profit values for each item. Although a number of relevant approaches have been proposed in recent years, they incur the problem of producing a large number of candidate itemsets for high utility itemsets. In this paper, the authors propose an efficient algorithm, namely BAHUI (Bitmap-based Algorithm for High Utility Itemsets), for mining high utility itemsets with bitmap database representation. In BAHUI, bitmap is used vertically and horizontally. On the one hand, BAHUI exploits a divide-and-conquer approach to visit itemset lattice by using bitmap vertically. On the other hand, BAHUI horizontally uses bitmap to calculate the real utilities of candidates. Using bitmap compression scheme, BAHUI reduces the memory usage and makes use of the efficient bitwise operation. Furthermore, BAHUI only records candidate high utility itemsets with maximal length, and inherits the pruning and searching strategies from maximal itemset mining problem. Extensive experimental results show that the BAHUI algorithm is both efficient and scalable.

With the wide application of 3D STL model in 3D printing, much attention has been paid to its content security and copyright protection. Based on entity rearrangement and bit mapping, a lossless and high capacity watermarking scheme is proposed for 3D STL model. Experimental results and analysis show that the average capacity is improved 0.71bits/facet compared with the original entity rearrangement method, and the capacity is 0.247 bits/entity larger than that of the optimal capacity of the standard entity rearrangement method. It can achieve good efficiency and it is robust against translation, rotation and even scaling. It has potential application in secret communication and copyright protection of 3D STL model.

Compute-in-memory (CIM) is a key focus in chip design, with mapping strategies gaining attention. However, many studies overlook the arrangement of significant bits in weights and the influence of the input order of activation bits, which are key aspects of bit-level mapping strategies. While the three existing bit-level mapping strategies have their respective application scenarios and can address the majority of cases through combined use, a major challenge remains: their lack of support for signed computations, which limits their applicability in many practical scenarios. This work improves three existing mapping strategies to support signed weights and activations, optimizing CIM peripheral circuits with minimal overhead. The experimental results show a 68.4% improvement in energy efficiency and 56.2% in speed with a less than 1% area increase on Yolov3-tiny, and a 4× and 3.59× boost in energy efficiency using input-side parallel mapping strategy (ISP) and input- and output-side parallel mapping strategy (IOSP) on a single layer. The proposed work has the potential to significantly advance the field of CIM-based neural network accelerators by enabling efficient signed computations and enhancing flexibility, paving the way for broader adoption in real-time and energy-constrained applications.

Bite force is an important indicator of masticatory performance. However, existing methods for measuring bite force are either ineffective or expensive. Hence, we developed a novel capacitive-type pressure-mapping sensor that converts mechanical forces into changes in capacitance and calculates bite force. A portable device was fabricated based on this sensor sheet, and the accuracy of the bite-force measurements provided by the device was evaluated. The sensor has a thickness of 1.6 mm and has 63 measurement points. It was inserted into a dental model, where the output value was measured and compared with that of a universal testing machine (AG-IS 100 kN). A regression equation to estimate the bite force was obtained based on the relationship between the output of the capacitive-type pressure-mapping sensor and that of the load cell of the universal testing machine. The estimated bite force from the sensor and the quadratic regression equation closely resembled the known load applied by the compression tester (R2 = 0.992). We therefore conclude that the developed sensor can measure bite force accurately and effectively. A device with a built-in capacitive-type pressure-mapping sensor can potentially be a user-friendly tool for bite-force measurements in both clinical and epidemiological settings.

Recently, an occlusal force-measuring device with a capacitive-type pressure-mapping sensor (OFMD-CPS) was developed. We aimed to establish age- and sex-specific standard values for OFMD-CPS-measured occlusal force (OF) and to assess the concurrent validity of the OFMD against another OF measuring system with a pressure-sensitive sheet (Dental Prescale II). Using data from a population-based study, we calculated the OFMD-CPS-measured OF means and deciles in 5-year age groups for each sex. The OFMD-CPS-measured OF was validated against the Dental Prescale II-measured OF with Spearman correlation coefficients. Furthermore, we calculated the area under the receiver operating characteristic curve (AUC) against the preexisting Dental Prescale II-measured OF cutoff value of 350 N. In total, 596 individuals (236 men and 360 women) with a mean (standard deviation (SD)) age of 73.7 (6.7) years were included in the analyses. The mean (SD) OFMD-CPS-measured OFs were 581.6 (284.6) N in men and 446.9 (209.9) N in women. There was a strong positive correlation (Spearman’s Rho = 0.73) between OFMD-CPS-measured and Dental Prescale II-measured OF. The diagnostic accuracy of the OFMD-CPS-measured OF for the Dental Prescale II-measured OF cutoff value was high (AUC = 0.88). In conclusion, we demonstrated standard values and concurrent validity of OFMD-CPS-measured OF in community-dwelling older adults.