洁净室内AMC治理方法研究

气态分子级污染物(Airborne Molecular Continent,AMC)是影响洁净室生产环境的主要因素之一,因此控制洁净室内AMC浓度成了半导体行业发展的关键问题之一。分别从“防”与“治”两个方面阐述了有效控制室内AMC浓度的方法,提供了室外新风的不同处理方式及应用场景,提供了洁净室内装修材料选用的标准及依据,研究了面板行业敏感度较高的VOCs(Volatile Organic Compounds)的相关处理方式及应用场景,为后续相关洁净室设计提供了参考及工程实际意义。

Intrusion Detection Model Using Chaotic MAP for Network Coding Enabled Mobile Small Cells

Wireless Network security management is difficult because of the ever-increasing number of wireless network malfunctions,vulnerabilities,and assaults.Complex security systems,such as Intrusion Detection Systems(IDS),are essential due to the limitations of simpler security measures,such as cryptography and firewalls.Due to their compact nature and low energy reserves,wireless networks present a significant challenge for security procedures.The features of small cells can cause threats to the network.Network Coding(NC)enabled small cells are vulnerable to various types of attacks.Avoiding attacks and performing secure“peer”to“peer”data transmission is a challenging task in small cells.Due to the low power and memory requirements of the proposed model,it is well suited to use with constrained small cells.An attacker cannot change the contents of data and generate a new Hashed Homomorphic Message Authentication Code(HHMAC)hash between transmissions since the HMAC function is generated using the shared secret.In this research,a chaotic sequence mapping based low overhead 1D Improved Logistic Map is used to secure“peer”to“peer”data transmission model using lightweight H-MAC(1D-LM-P2P-LHHMAC)is proposed with accurate intrusion detection.The proposed model is evaluated with the traditional models by considering various evaluation metrics like Vector Set Generation Accuracy Levels,Key Pair Generation Time Levels,Chaotic Map Accuracy Levels,Intrusion Detection Accuracy Levels,and the results represent that the proposed model performance in chaotic map accuracy level is 98%and intrusion detection is 98.2%.The proposed model is compared with the traditional models and the results represent that the proposed model secure data transmission levels are high.

The Application of Nicotiana benthamiana as a Transient Expression Host to Clone the Coding Sequences of Plant Genes

Coding sequences (CDS) are commonly used for transient gene expression, in yeast two-hybrid screening, to verify protein interactions and in prokaryotic gene expression studies. CDS are most commonly obtained using complementary DNA (cDNA) derived from messenger RNA (mRNA) extracted from plant tissues and generated by reverse transcription. However, some CDS are difficult to acquire through this process as they are expressed at extremely low levels or have specific spatial and/or temporal expression patterns in vivo. These challenges require the development of alternative CDS cloning technologies. In this study, we found that the genomic intron-containing gene coding sequences (gDNA) from Arabidopsis thaliana, Oryza sativa, Brassica napus, and Glycine max can be correctly transcribed and spliced into mRNA in Nicotiana benthamiana. In contrast, gDNAs from Triticum aestivum and Sorghum bicolor did not function correctly. In transient expression experiments, the target DNA sequence is driven by a constitutive promoter. Theoretically, a sufficient amount of mRNA can be extracted from the N. benthamiana leaves, making it conducive to the cloning of CDS target genes. Our data demonstrate that N. benthamiana can be used as an effective host for the cloning CDS of plant genes.

A quantum blind signature scheme based on dense coding for non-entangled states

In some schemes, quantum blind signatures require the use of difficult-to-prepare multiparticle entangled states. By considering the communication overhead, quantum operation complexity, verification efficiency and other relevant factors in practical situations, this article proposes a non-entangled quantum blind signature scheme based on dense encoding. The information owner utilizes dense encoding and hash functions to blind the information while reducing the use of quantum resources. After receiving particles, the signer encrypts the message using a one-way function and performs a Hadamard gate operation on the selected single photon to generate the signature. Then the verifier performs a Hadamard gate inverse operation on the signature and combines it with the encoding rules to restore the message and complete the verification.Compared with some typical quantum blind signature protocols, this protocol has strong blindness in privacy protection,and higher flexibility in scalability and application. The signer can adjust the signature operation according to the actual situation, which greatly simplifies the complexity of the signature. By simultaneously utilizing the secondary distribution and rearrangement of non-entangled quantum states, a non-entangled quantum state representation of three bits of classical information is achieved, reducing the use of a large amount of quantum resources and lowering implementation costs. This improves both signature verification efficiency and communication efficiency while, at the same time, this scheme meets the requirements of unforgeability, non-repudiation, and prevention of information leakage.

Decoding topological XYZ^(2) codes with reinforcement learning based on attention mechanisms

Quantum error correction, a technique that relies on the principle of redundancy to encode logical information into additional qubits to better protect the system from noise, is necessary to design a viable quantum computer. For this new topological stabilizer code-XYZ^(2) code defined on the cellular lattice, it is implemented on a hexagonal lattice of qubits and it encodes the logical qubits with the help of stabilizer measurements of weight six and weight two. However topological stabilizer codes in cellular lattice quantum systems suffer from the detrimental effects of noise due to interaction with the environment. Several decoding approaches have been proposed to address this problem. Here, we propose the use of a state-attention based reinforcement learning decoder to decode XYZ^(2) codes, which enables the decoder to more accurately focus on the information related to the current decoding position, and the error correction accuracy of our reinforcement learning decoder model under the optimisation conditions can reach 83.27% under the depolarizing noise model, and we have measured thresholds of 0.18856 and 0.19043 for XYZ^(2) codes at code spacing of 3–7 and 7–11, respectively. our study provides directions and ideas for applications of decoding schemes combining reinforcement learning attention mechanisms to other topological quantum error-correcting codes.

Recurrent neural network decoding of rotated surface codes based on distributed strategy

Quantum error correction is a crucial technology for realizing quantum computers.These computers achieve faulttolerant quantum computing by detecting and correcting errors using decoding algorithms.Quantum error correction using neural network-based machine learning methods is a promising approach that is adapted to physical systems without the need to build noise models.In this paper,we use a distributed decoding strategy,which effectively alleviates the problem of exponential growth of the training set required for neural networks as the code distance of quantum error-correcting codes increases.Our decoding algorithm is based on renormalization group decoding and recurrent neural network decoder.The recurrent neural network is trained through the ResNet architecture to improve its decoding accuracy.Then we test the decoding performance of our distributed strategy decoder,recurrent neural network decoder,and the classic minimum weight perfect matching(MWPM)decoder for rotated surface codes with different code distances under the circuit noise model,the thresholds of these three decoders are about 0.0052,0.0051,and 0.0049,respectively.Our results demonstrate that the distributed strategy decoder outperforms the other two decoders,achieving approximately a 5%improvement in decoding efficiency compared to the MWPM decoder and approximately a 2%improvement compared to the recurrent neural network decoder.

Single Photon Detection Technology in Underwater Wireless Optical Communication:Modulation Modes and Error Correction Coding Analysis

This study explores the application of single photon detection(SPD)technology in underwater wireless optical communication(UWOC)and analyzes the influence of different modulation modes and error correction coding types on communication performance.The study investigates the impact of on-off keying(OOK)and 2-pulse-position modulation(2-PPM)on the bit error rate(BER)in single-channel intensity and polarization multiplexing.Furthermore,it compares the error correction performance of low-density parity check(LDPC)and Reed-Solomon(RS)codes across different error correction coding types.The effects of unscattered photon ratio and depolarization ratio on BER are also verified.Finally,a UWOC system based on SPD is constructed,achieving 14.58 Mbps with polarization OOK multiplexing modulation and 4.37 Mbps with polarization 2-PPM multiplexing modulation using LDPC code error correction.

Improved Segmented Belief Propagation List Decoding for Polar Codes with Bit-Flipping

Belief propagation list(BPL) decoding for polar codes has attracted more attention due to its inherent parallel nature. However, a large gap still exists with CRC-aided SCL(CA-SCL) decoding.In this work, an improved segmented belief propagation list decoding based on bit flipping(SBPL-BF) is proposed. On the one hand, the proposed algorithm makes use of the cooperative characteristic in BPL decoding such that the codeword is decoded in different BP decoders. Based on this characteristic, the unreliable bits for flipping could be split into multiple subblocks and could be flipped in different decoders simultaneously. On the other hand, a more flexible and effective processing strategy for the priori information of the unfrozen bits that do not need to be flipped is designed to improve the decoding convergence. In addition, this is the first proposal in BPL decoding which jointly optimizes the bit flipping of the information bits and the code bits. In particular, for bit flipping of the code bits, a H-matrix aided bit-flipping algorithm is designed to enhance the accuracy in identifying erroneous code bits. The simulation results show that the proposed algorithm significantly improves the errorcorrection performance of BPL decoding for medium and long codes. It is more than 0.25 d B better than the state-of-the-art BPL decoding at a block error rate(BLER) of 10^(-5), and outperforms CA-SCL decoding in the low signal-to-noise(SNR) region for(1024, 0.5)polar codes.

添加AMC复相材料的刚玉质浇注料的性能改善及应用效果

在刚玉质浇注料中添加AMC复相材料,利用AMC复相材料的CA6和MA抗渣性好、热震稳定性好的特点来改善刚玉质浇注料的使用性能,同时AMC复相材料作为资源再利用的新产品,在价格方面具有明显的优势,它能够降低耐材的生产成本。试验表明,在刚玉质浇注料中加入30%的AMC复相材料取得了较为理想的实验数据,其应用在钢包座砖上取得了良好的效果,既降低了生产成本,又有效地提高了钢包座砖的使用寿命。

Recent Advances in Video Coding for Machines Standard and Technologies

To improve the performance of video compression for machine vision analysis tasks,a video coding for machines(VCM)standard working group was established to promote standardization procedures.In this paper,recent advances in video coding for machine standards are presented and comprehensive introductions to the use cases,requirements,evaluation frameworks and corresponding metrics of the VCM standard are given.Then the existing methods are presented,introducing the existing proposals by category and the research progress of the latest VCM conference.Finally,we give conclusions.

Performance Analysis of an AMC System with an Iterative V-BLAST Decoding Algorithm

In this paper, the iterative Vertical-Bell-lab Layered Space-Time (V-BLAST) decoding algorithm of an Adaptive Modulation and Coding (AMC) system is proposed, and the corresponding MIMO scheme is analyzed. The proposed decoding algorithm adopts iteratively extrinsic information from a Maximum A Posteriori (MAP) decoder as an a priori probability in the two decoding procedures of the V-BLAST scheme of ordering and slicing in an AMC system. Furthermore, the performance of the proposed decoding algorithm is compared with that of a conventional V-BLAST decoding algorithm and a Maximum Likelihood (ML) decoding algorithm in the combined system of an AMC scheme and a V-BLAST scheme. In this analysis, each MIMO schemes are assumed to be parts of the system for performance improvement.

A Study on Scalable Video Coding for AMC with Mobile Media-Based Multicast over WiMAX 802.16e

Adaptive Modulation and Coding (AMC), which is a technology used when channel condition changes, is adapted in Mobile Worldwide Interoperability for Microwave Access (WiMAX). Scalable Video Coding (SVC) is a video coding scheme used for different users with bandwidth level. SVC encodes a video into a number of layers. Users receive different number of encoded layers based on their channel condition. In this paper, Intermediate Control Server (ICS) is proposed to deal with the signaling between multimedia server and BS. Both AMC and SVC are employed to enhance the user perceived video quality in the system.

Deep Learning Aided SCL Decoding of Polar Codes with Shifted-Pruning

Recently,a generalized successive cancellation list(SCL)decoder implemented with shiftedpruning(SP)scheme,namely the SCL-SP-ωdecoder,is presented for polar codes,which is able to shift the pruning window at mostωtimes during each SCL re-decoding attempt to prevent the correct path from being eliminated.The candidate positions for applying the SP scheme are selected by a shifting metric based on the probability that the elimination occurs.However,the number of exponential/logarithm operations involved in the SCL-SP-ωdecoder grows linearly with the number of information bits and list size,which leads to high computational complexity.In this paper,we present a detailed analysis of the SCL-SP-ωdecoder in terms of the decoding performance and complexity,which unveils that the choice of the shifting metric is essential for improving the decoding performance and reducing the re-decoding attempts simultaneously.Then,we introduce a simplified metric derived from the path metric(PM)domain,and a custom-tailored deep learning(DL)network is further designed to enhance the efficiency of the proposed simplified metric.The proposed metrics are both free of transcendental functions and hence,are more hardware-friendly than the existing metrics.Simulation results show that the proposed DL-aided metric provides the best error correction performance as comparison with the state of the art.

来那度胺联合R-CHOP治疗DLBCL改善ALC/AMC比值的研究进展

弥漫大B细胞淋巴瘤(diffuse large B-cell lymphomas,DLBCL)是非霍奇金淋巴瘤的主要亚型。DLBCL在临床表现、基因表达、治疗反应及预后方面均存在差异,外周血绝对淋巴细胞(ALC)/单核细胞(AMC)比值(ALC/AMC)作为宿主免疫和肿瘤微环境的替代指标,是预测DLBCL患者临床疗效的生物标志物。来那度胺是一种免疫调节药物,对DLBCL患者有效,对肿瘤微环境及宿主免疫反应有多种作用机制。来那度胺联合标准R-CHOP治疗以前未经治疗的DLBCL患者,似乎克服了单用R-CHOP治疗患者ALC/AMC比值的不良预后价值,本文对这一观点进行综述。

地方AMC行业数字化转型问题研究

我国地方AMC行业成立时间较短,发展方式较为传统,数字化转型理论和实践工作较为落后,本文通过对地方AMC行业数字化转型现状的深入调查和研究,明确了地方AMC数字化转型的内涵和特征,理清了地方AMC数字化转型的模式,找出了地方AMC在数字化转型过程中存在的问题,并提出了相关对策建议。研究发现,我国地方AMC普遍存在对数字化转型认知和统筹规划不足、数字化转型组织保障缺乏、数字化转型模式落后、数字化建设人才、技术、储备不足等问题,为推动地方数字化转型进程,地方AMC需要完善数字化顶层设计、强化数字化转型组织保障、推动数字化转型模式的创新和应用,同时要注重增加技术、人才和数据储备,夯实数字化转型安全建设。

Belief Propagation List Decoding for Polar Codes:Performance Analysis and Software Implementation on GPU

Belief propagation(BP)decoding outputs soft information and can be naturally used in iterative receivers.BP list(BPL)decoding provides comparable error-correction performance to the successive cancellation list(SCL)decoding.In this paper,we firstly introduce an enhanced code construction scheme for BPL decoding to improve its errorcorrection capability.Then,a GPU-based BPL decoder with adoption of the new code construction is presented.Finally,the proposed BPL decoder is tested on NVIDIA RTX3070 and GTX1060.Experimental results show that the presented BPL decoder with early termination criterion achieves above 1 Gbps throughput on RTX3070 for the code(1024,512)with 32 lists under good channel conditions.

The Effect of Coding Method on Cause-of-Death Rankings

Background: Cause-of-death rankings are often used for planning or evaluating health policy measures. In the European Union, some countries produce cause-of-death statistics by a manual coding of death certificates, while other countries use an automated coding system. The outcome of these two different methods in terms of the selected underlying cause of death for statistics may vary considerably. Therefore, this study explores the effect of coding method on the ranking of countries by major causes of death. Method: Age and sex standardized rates were extracted for 33 European (related) countries from the cause-of-death registry of the European Statistical Office (Eurostat). Wilcoxon’s rank sum test was applied to the ranking of countries by major causes of death. Results: Statistically significant differences due to coding method were identified for dementia, stroke and pneumonia. These differences could be explained by a different selection of dementia or pneumonia as underlying cause of death and by a different certification practice for stroke. Conclusion: Coding method should be taken into account when constructing or interpreting rankings of countries by cause of death.

Forward stagewise regression with multilevel memristor for sparse coding

Sparse coding is a prevalent method for image inpainting and feature extraction,which can repair corrupted images or improve data processing efficiency,and has numerous applications in computer vision and signal processing.Recently,sev-eral memristor-based in-memory computing systems have been proposed to enhance the efficiency of sparse coding remark-ably.However,the variations and low precision of the devices will deteriorate the dictionary,causing inevitable degradation in the accuracy and reliability of the application.In this work,a digital-analog hybrid memristive sparse coding system is pro-posed utilizing a multilevel Pt/Al_(2)O_(3)/AlO_(x)/W memristor,which employs the forward stagewise regression algorithm:The approxi-mate cosine distance calculation is conducted in the analog part to speed up the computation,followed by high-precision coeffi-cient updates performed in the digital portion.We determine that four states of the aforementioned memristor are sufficient for the processing of natural images.Furthermore,through dynamic adjustment of the mapping ratio,the precision require-ment for the digit-to-analog converters can be reduced to 4 bits.Compared to the previous system,our system achieves higher image reconstruction quality of the 38 dB peak-signal-to-noise ratio.Moreover,in the context of image inpainting,images containing 50%missing pixels can be restored with a reconstruction error of 0.0424 root-mean-squared error.

The Confidentiality of Coding Video Games with Cheat Code and Bots for Cheating in a Virtual World

Video games have been around for several decades and have had many advancements from the original start of video games. Video games started as virtual games that were advertised towards children, and these virtual games created a virtual reality of a variety of genres. These genres included sports games, such as tennis, football, baseball, war games, fantasy, puzzles, etc. The start of these games was derived from a sports genre and now has a popularity in multiplayer-online-shooting games. The purpose of this paper is to investigate different types of tools available for cheating in virtual world making players have undue advantage over other players in a competition. With the advancement in technology, these video games have become more expanded in the development aspects of gaming. Video game developers have created long lines of codes to create a new look of video games. As video games have progressed, the coding, bugs, bots, and errors of video games have changed throughout the years. The coding of video games has branched out from the original video games, which have given many benefits to this virtual world, while simultaneously creating more problems such as bots. Analysis of tools available for cheating in a game has disadvantaged normal gamer in a fair contest.

List-Serial Pipelined Hardware Architecture for SCL Decoding of Polar Codes

For polar codes,the performance of successive cancellation list(SCL)decoding is capable of approaching that of maximum likelihood decoding.However,the existing hardware architectures for the SCL decoding suffer from high hardware complexity due to calculating L decoding paths simultaneously,which are unfriendly to the devices with limited logical resources,such as field programmable gate arrays(FPGAs).In this paper,we propose a list-serial pipelined hardware architecture with low complexity for the SCL decoding,where the serial calculation and the pipelined operation are elegantly combined to strike a balance between the complexity and the latency.Moreover,we employ only one successive cancellation(SC)decoder core without L×L crossbars,and reduce the number of inputs of the metric sorter from 2L to L+2.Finally,the FPGA implementations show that the hardware resource consumption is significantly reduced with negligible decoding performance loss.