Telemetry Data Compression Algorithm Using Balanced Recurrent Neural Network and Deep Learning

Telemetric information is great in size, requiring extra room and transmission time. There is a significant obstruction of storing or sending telemetric information. Lossless data compression (LDC) algorithms have evolved to process telemetric data effectively and efficiently with a high compression ratio and a short processing time. Telemetric information can be packed to control the extra room and association data transmission. In spite of the fact that different examinations on the pressure of telemetric information have been conducted, the idea of telemetric information makes pressure incredibly troublesome. The purpose of this study is to offer a subsampled and balanced recurrent neural lossless data compression (SB-RNLDC) approach for increasing the compression rate while decreasing the compression time. This is accomplished through the development of two models: one for subsampled averaged telemetry data preprocessing and another for BRN-LDC. Subsampling and averaging are conducted at the preprocessing stage using an adjustable sampling factor. A balanced compression interval (BCI) is used to encode the data depending on the probability measurement during the LDC stage. The aim of this research work is to compare differential compression techniques directly. The final output demonstrates that the balancing-based LDC can reduce compression time and finally improve dependability. The final experimental results show that the model proposed can enhance the computing capabilities in data compression compared to the existing methodologies.

Biomechanical Characteristics of Vertical Jumping of Preschool Children in China Based on Motion Capture and Simulation Modeling

Vertical jumping is one of the basic motor skills, and it is an essential part of many sports. The main purpose of this paper is to investigate characteristics of vertical jumping of children. This paper uses a motion capture system, three-dimensional platforms, and a simulation modeling system to analyze the kinematics and dynamics performance of children’s vertical jumping. The compression time increases from 3 to 4 years old, and flight height and time increases with age and stage gradually. In the compression phase and pushing phase, the hip and knee joint play a major role; in the landing phase, the knee and ankle joint play a major role. Muscle forces are mainly affected by age, and the three types of muscle force had two different trends. The muscle force of the shank and thigh increased with age, and the pelvic girdle muscles showed an “low–high–low” trend. The regression model suggests that the force of GMiP and the hip angular velocity have a great influence on jumping ability. Therefore, if we want to improve the jumping ability of preschool children, we should pay more attention to hip exercises. We should integrate the hip exercises into interesting games, which are more in line with their physical and mental health.

ALTERNATIVE IMPROVEMENT OF SUBGRADE AND REINFORCEMENT OF EMBANKMENT ON PELABUHAN KUALA TANJUNG TOLL ROAD, INDERAPURA - KUALA TANJUNG SECTION IN NORTH SUMATRA (STA 0+000 S/D STA 3+500)

Planning the Kuala Tanjung Ruas Port of Inderapura - Kuala Tanjung Toll Road is one of the efforts to support economic growth in North Sumatra. The toll road will be built on a pile with a height of 2 ms / 9 m at STA 0 + 000 to STA 3 + 500. Due to limited land, the toll road section must be built on the poor subgrade. Based on the N-SPT test results, it is known that the subsoil consists of a clay layer with a thickness reaching 36 meters and a layer of sand at the top and bottom with a low N-SPT value. If the soft subgrade is burdened with a high heap, it is estimated that the subgrade will experience landslides, so it is necessary to plan the improvement of the subgrade and reinforcement of the pile.The soil improvement method chosen is the pre-loading method with a combination of the prefabricated vertical drain (PVD). Pre-loading method aims to spend the compression that occurs on the subgrade so that there is no compression during the service life of the road. The combination with PVD is intended to speed up the compression time in thick clay layers. The stability of the embankment will be calculated using a computer-assisted program, and geotextile reinforcement planning will be carried out if the value of the safety factor does not meet the requirements.Based on the analysis of compression computation will be divided into five zones. The amount of compression obtained under various piles of 2 ms / d 9 m was 2.25 m, 1.49 m, 1.75 m, 2.57 m, 3.65 m, 4.3 m, 4.69 m, and 5.06 m with an initial heap height of 5.02 m, 5.26 m, 6.51 m, 8.34 m, 10.41 m, 12.07 m, 13.46 m, and 14.83 m. Compression time required for subgrade is relatively long with a period of more than five years so that the planned acceleration with PVD. To accelerate the compression time to 5-6 weeks, a triangular PVD installation pattern is used with a spacing between PVD of 1.5 m and a depth of PVD installation as thick as a soft soil layer. From the results of the pile stability control, it is predicted that the pile will experience slides so that the reinforcement is installed with geotextile.Rp1.598,213,522,582.08.

No Fine-Tuning, No Cry: Robust SVD for Compressing Deep Networks

A common technique for compressing a neural network is to compute the k-rank ℓ2 approximation Ak of the matrix A∈Rn×d via SVD that corresponds to a fully connected layer (or embedding layer). Here, d is the number of input neurons in the layer, n is the number in the next one, and Ak is stored in O((n+d)k) memory instead of O(nd). Then, a fine-tuning step is used to improve this initial compression. However, end users may not have the required computation resources, time, or budget to run this fine-tuning stage. Furthermore, the original training set may not be available. In this paper, we provide an algorithm for compressing neural networks using a similar initial compression time (to common techniques) but without the fine-tuning step. The main idea is replacing the k-rank ℓ2 approximation with ℓp, for p∈[1,2], which is known to be less sensitive to outliers but much harder to compute. Our main technical result is a practical and provable approximation algorithm to compute it for any p≥1, based on modern techniques in computational geometry. Extensive experimental results on the GLUE benchmark for compressing the networks BERT, DistilBERT, XLNet, and RoBERTa confirm this theoretical advantage.

A New and Ecological Method to Quantify Vancomycin in Pharmaceutical Product by Infrared Spectrometry

Vancomycin, an antimicrobial, does not present quantitative method by infrared spectrometry in the literature for the evaluation of a pharmaceutical product. This technique is considered a clean alternative because in the main, there is no solvent involved and the generation of waste is reduced. So, the aim of this study was to develop and validate a new, ecological, low cost and fast method by infrared spectrometry using KBr and band between 1450–1375 cm–1. It was linear in the range of 1.0–2.0 mg/150 mg, with a correlation coefficient of 0.9994. Selective when the spectra of vancomycin reference and sample were compared. Precise by repeatability (2.29%) and intermediate precision (3.12%). Accurate with average recovery of 99.37% and robust when strength and compression time of the pellets and KBr brand were varied. Considering all the methods found in literature, there is not one using infrared spectrometry for quantitative purpose, so the method developed and validated could be considered an innovation and clean alternative. This is due to the fact that it is fast, easy to handle, low cost, and non-toxic as well as generating minimal waste. The method can be applied in the routine analysis of vancomycin dosage form and is an important option for the current and sustainable pharmaceutical analysis.

HEVC Fast Intra-Mode Selection Using World War II Technique

High-Efficiency Video Coding (HEVC) applies 35 intra modes to every block of a frame and selects the mode that gives the best prediction. This brute-force nature of HEVC makes it complex and unfit for real-time applications. Therefore, a fast intra-mode estimation algorithm is presented here based on the classic World War II (WW2) technique known as the ‘German Tanks Problem’ (GTP). This not only is the first article to use GTP for early estimation of intra mode, but also expedites the estimation process of GTP. Secondly, the various elements of the intra process are efficiently mapped to the elements of GTP estimation. Finally, the two variations of GPT are modeled and are also minimum-variance estimates. These experimental results indicate that proposed GTP-based fast estimation reduced the compression time of HEVC from 23.88% to 31.44%.

Efficient Low Power Region Enhanced Architectures For DWT And AES For Protected Coding Image

In this article presents an HDL template on the ASIC platform. For quicker and safer image data transmission stable encoding of pictures via image compression and AES through encryption, the DWT was facilitated. The DWT calculation algorithm based on a lifting scheme and a multi-level sub-bands on the ASIC platform are created. 2D-DWTwas built using it. The related sub-bands were chosen to minimize the compression time of the AES encryption, based on compression ratio and data recovery. To ensure high efficiency and latency, the DWT architecture was developedHDL model and AES algorithm for the area, timing and power performance of the ASIC platform have been developed and validated for the DWT architecture. Using 56 nm CMOS technology, the ASIC implementation was carried out.

A compression method for DNA

The development of high-throughput sequencing technology has generated huge amounts DNA data. Many general compression algorithms are not ideal for compressing DNA data, such as the LZ77 algorithm. On the basis of Nour and Sharawi’s method,we propose a new, lossless and reference-free method to increase the compression performance. The original sequences are converted into eight intermediate files and six final files. Then, the LZ77 algorithm is used to compress the six final files. The results show that the compression time is decreased by 83% and the decompression time is decreased by 54% on average.The compression rate is almost the same as Nour and Sharawi’s method which is the fastest method so far. What’s more, our method has a wider range of application than Nour and Sharawi’s method. Compared to some very advanced compression tools at present, such as XM and FCM-Mx, the time for compression in our method is much smaller, on average decreasing the time by more than 90%.