Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Althoug...Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.展开更多
In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shippi...In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shipping is characterized by a vast array of document types, filled with complex, large-scale, and often chaotic knowledge and relationships. Effectively managing these documents is crucial for developing a Large Language Model (LLM) in the maritime domain, enabling practitioners to access and leverage valuable information. A Knowledge Graph (KG) offers a state-of-the-art solution for enhancing knowledge retrieval, providing more accurate responses and enabling context-aware reasoning. This paper presents a framework for utilizing maritime and shipping documents to construct a knowledge graph using GraphRAG, a hybrid tool combining graph-based retrieval and generation capabilities. The extraction of entities and relationships from these documents and the KG construction process are detailed. Furthermore, the KG is integrated with an LLM to develop a Q&A system, demonstrating that the system significantly improves answer accuracy compared to traditional LLMs. Additionally, the KG construction process is up to 50% faster than conventional LLM-based approaches, underscoring the efficiency of our method. This study provides a promising approach to digital intelligence in shipping, advancing knowledge accessibility and decision-making.展开更多
National Fire codes,mandated by government authorities to tackle technical challenges in fire prevention and control,establish fundamental standards for construction practices.International collaboration in fire prote...National Fire codes,mandated by government authorities to tackle technical challenges in fire prevention and control,establish fundamental standards for construction practices.International collaboration in fire protection technologies has opened avenues for China to access a wealth of documents and codes,which are crucial in crafting regulations and developing a robust,scientific framework for fire code formulation.However,the translation of these codes into Chinese has been inadequate,thereby diminishing the benefits of technological exchange and collaborative learning.This underscores the necessity for comprehensive research into code translation,striving for higher-quality translations guided by established translation theories.In this study,we translated the initial segment of the NFPA 1 Fire Code into Chinese and examined both the source text and target text through the lens of Translation Shift Theory,a concept introduced by Catford.The conclusion culminated in identifying four key shifts across various linguistic levels:lexis,sentences,and groups,to ensure an accurate and precise translation of fire codes.This study offers a through and lucid explanation of how the translator integrates Catford’s theories to solve technical challenges in NFPA 1 Fire Code translation,and establish essential standards for construction translation practices.展开更多
In the article“Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space”by Mudassir Khalil,Muhammad Imran Sharif,Ahmed Naeem,Muhammad Umar Chaudhry,Hafiz Tayyab Rauf,Adham E.Ragab C...In the article“Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space”by Mudassir Khalil,Muhammad Imran Sharif,Ahmed Naeem,Muhammad Umar Chaudhry,Hafiz Tayyab Rauf,Adham E.Ragab Computers,Materials&Continua,2023,Vol.77,No.2,pp.2031–2047.DOI:10.32604/cmc.2023.043687,URL:https://www.techscience.com/cmc/v77n2/54831,there was an error regarding the affiliation for the author Hafiz Tayyab Rauf.Instead of“Centre for Smart Systems,AI and Cybersecurity,Staffordshire University,Stoke-on-Trent,ST42DE,UK”,the affiliation should be“Independent Researcher,Bradford,BD80HS,UK”.展开更多
With the development of anti-virus technology,malicious documents have gradually become the main pathway of Advanced Persistent Threat(APT)attacks,therefore,the development of effective malicious document classifiers ...With the development of anti-virus technology,malicious documents have gradually become the main pathway of Advanced Persistent Threat(APT)attacks,therefore,the development of effective malicious document classifiers has become particularly urgent.Currently,detection methods based on document structure and behavioral features encounter challenges in feature engineering,these methods not only have limited accuracy,but also consume large resources,and usually can only detect documents in specific formats,which lacks versatility and adaptability.To address such problems,this paper proposes a novel malicious document detection method-visualizing documents as GGE images(Grayscale,Grayscale matrix,Entropy).The GGE method visualizes the original byte sequence of the malicious document as a grayscale image,the information entropy sequence of the document as an entropy image,and at the same time,the grayscale level co-occurrence matrix and the texture and spatial information stored in it are converted into grayscale matrix image,and fuses the three types of images to get the GGE color image.The Convolutional Block Attention Module-EfficientNet-B0(CBAM-EfficientNet-B0)model is then used for classification,combining transfer learning and applying the pre-trained model on the ImageNet dataset to the feature extraction process of GGE images.As shown in the experimental results,the GGE method has superior performance compared with other methods,which is suitable for detecting malicious documents in different formats,and achieves an accuracy of 99.44%and 97.39%on Portable Document Format(PDF)and office datasets,respectively,and consumes less time during the detection process,which can be effectively applied to the task of detecting malicious documents in real-time.展开更多
This video series is the first experimental psychology documentary made in China.It focuses on analyzing professional theories to raise people’s general understanding of basic psychology.By combining innovative audio...This video series is the first experimental psychology documentary made in China.It focuses on analyzing professional theories to raise people’s general understanding of basic psychology.By combining innovative audiovisual narrative with psychological experiments,it zooms in on real human nature through discussing social hotspots from the perspectives of social psychology,cognitive psychology,and personality psychology,in order to help people find answers for their current psychological difficulties.展开更多
A two-stage algorithm based on deep learning for the detection and recognition of can bottom spray codes and numbers is proposed to address the problems of small character areas and fast production line speeds in can ...A two-stage algorithm based on deep learning for the detection and recognition of can bottom spray codes and numbers is proposed to address the problems of small character areas and fast production line speeds in can bottom spray code number recognition.In the coding number detection stage,Differentiable Binarization Network is used as the backbone network,combined with the Attention and Dilation Convolutions Path Aggregation Network feature fusion structure to enhance the model detection effect.In terms of text recognition,using the Scene Visual Text Recognition coding number recognition network for end-to-end training can alleviate the problem of coding recognition errors caused by image color distortion due to variations in lighting and background noise.In addition,model pruning and quantization are used to reduce the number ofmodel parameters to meet deployment requirements in resource-constrained environments.A comparative experiment was conducted using the dataset of tank bottom spray code numbers collected on-site,and a transfer experiment was conducted using the dataset of packaging box production date.The experimental results show that the algorithm proposed in this study can effectively locate the coding of cans at different positions on the roller conveyor,and can accurately identify the coding numbers at high production line speeds.The Hmean value of the coding number detection is 97.32%,and the accuracy of the coding number recognition is 98.21%.This verifies that the algorithm proposed in this paper has high accuracy in coding number detection and recognition.展开更多
This critical review looks at the assessment of the application of artificial intelligence in handling legal documents with specific reference to medical negligence cases with a view of identifying its transformative ...This critical review looks at the assessment of the application of artificial intelligence in handling legal documents with specific reference to medical negligence cases with a view of identifying its transformative potentialities, issues and ethical concerns. The review consolidates findings that show the impact of AI in improving the efficiency, accuracy and justice delivery in the legal profession. The studies show increased efficiency in speed of document review and enhancement of the accuracy of the reviewed documents, with time efficiency estimates of 60% reduction of time. However, the review also outlines some of the problems that continue to characterize AI, such as data quality problems, biased algorithms and the problem of the opaque decision-making system. This paper assesses ethical issues related to patient autonomy, justice and non-malignant suffering, with particular focus on patient privacy and fair process, and on potential unfairness to patients. This paper’s review of AI innovations finds that regulations lag behind AI developments, leading to unsettled issues regarding legal responsibility for AI and user control over AI-generated results and findings in legal proceedings. Some of the future avenues that are presented in the study are the future of XAI for legal purposes, utilizing federated learning for resolving privacy issues, and the need to foster adaptive regulation. Finally, the review advocates for Legal Subject Matter Experts to collaborate with legal informatics experts, ethicists, and policy makers to develop the best solutions to implement AI in medical negligence claims. It reasons that there is great potential for AI to have a deep impact on the practice of law but when done, it must do so in a way that respects justice and on the Rights of Individuals.展开更多
The care of a patient involved in major trauma with exsanguinating haemorrhage is time-critical to achieve definitive haemorrhage control,and it requires coordinated multidisciplinary care.During initial resuscitation...The care of a patient involved in major trauma with exsanguinating haemorrhage is time-critical to achieve definitive haemorrhage control,and it requires coordinated multidisciplinary care.During initial resuscitation of a patient in the emergency department(ED),Code Crimson activation facilitates rapid decisionmaking by multi-disciplinary specialists for definitive haemorrhage control in operating theatre(OT)and/or interventional radiology(IR)suite.Once this decision has been made,there may still be various factors that lead to delay in transporting the patient from ED to OT/IR.Red Blanket protocol identifies and addresses these factors and processes which cause delay,and aims to facilitate rapid and safe transport of the haemodynamically unstable patient from ED to OT,while minimizing delay in resuscitation during the transfer.The two processes,Code Crimson and Red Blanket,complement each other.It would be ideal to merge the two processes into a single protocol rather than having two separate workflows.Introducing these quality improvement strategies and coor-dinated processes within the trauma framework of the hospitals/healthcare systems will help in further improving the multi-disciplinary care for the complex trauma patients requiring rapid and definitive haemorrhage control.展开更多
Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition d...Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition degree can easily be adjusted simultaneously.This paper introduces a new type of pliable FR codes,called absolute balanced pliable FR(ABPFR)codes,in which the access balancing in DSS is considered.Additionally,the equivalence between pliable FR codes and resolvable transversal packings in combinatorial design theory is presented.Then constructions of pliable FR codes and ABPFR codes based on resolvable transversal packings are presented.展开更多
Multilevel coding(MLC)is a commonly used polar coded modulation scheme,but challenging to implement in engineering due to its high complexity and long decoding delay for high-order modulations.To address these limitat...Multilevel coding(MLC)is a commonly used polar coded modulation scheme,but challenging to implement in engineering due to its high complexity and long decoding delay for high-order modulations.To address these limitations,a novel two-level serially concatenated MLC scheme,in which the bitlevels with similar reliability are bundled and transmitted together,is proposed.The proposed scheme hierarchically protects the two bit-level sets:the bitlevel sets at the higher level are sufficiently reliable and do not require excessive resources for protection,whereas only the bit-level sets at the lower level are encoded by polar codes.The proposed scheme has the advantages of low power consumption,low delay and high reliability.Moreover,an optimized constellation signal labeling rule that can enhance the performance is proposed.Finally,the superiority of the proposed scheme is validated through the theoretical analysis and simulation results.Compared with the bit interleaving coding modulation(BICM)scheme,under 256-quadrature amplitude modulation(QAM),the proposed scheme attains a performance gain of 1.0 dB while reducing the decoding complexity by 54.55%.展开更多
What Are You Up To Today?Chief Director:Wu Zijuan Length:12 Episodes Producer:bilibili Broadcasting Platform:bilibili Produced by China’s YouTube-like video sharing platform bilibili,the film is a series of short doc...What Are You Up To Today?Chief Director:Wu Zijuan Length:12 Episodes Producer:bilibili Broadcasting Platform:bilibili Produced by China’s YouTube-like video sharing platform bilibili,the film is a series of short documentaries presenting people's daily life in different jobs.It follows 12 individuals in their respective jobs and trades that keep society functioning.By focusing on their daily lives,the documentary films capture the hustle and bustle of the days that make up a hopeful life.展开更多
In this paper,we first generalize the constant dimension and orbit codes over finite fields to the constant rank and orbit codes over finite chain rings.Then we provide a relationship between constant rank codes over ...In this paper,we first generalize the constant dimension and orbit codes over finite fields to the constant rank and orbit codes over finite chain rings.Then we provide a relationship between constant rank codes over finite chain rings and constant dimension codes over the residue fields.In particular,we prove that an orbit submodule code over a finite chain ring is a constant rank code.Finally,for special finite chain ring F_(q)+γF_(q),we define a Gray mapφfrom(F_(q)+γF_(q))^(n)to F^(2n)_(q),and by using cyclic codes over F_(q)+γF_(q),we obtain a method of constructing an optimum distance constant dimension code over F_(q).展开更多
基金supported by Key Laboratory of Cyberspace Security,Ministry of Education,China。
文摘Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.
文摘In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shipping is characterized by a vast array of document types, filled with complex, large-scale, and often chaotic knowledge and relationships. Effectively managing these documents is crucial for developing a Large Language Model (LLM) in the maritime domain, enabling practitioners to access and leverage valuable information. A Knowledge Graph (KG) offers a state-of-the-art solution for enhancing knowledge retrieval, providing more accurate responses and enabling context-aware reasoning. This paper presents a framework for utilizing maritime and shipping documents to construct a knowledge graph using GraphRAG, a hybrid tool combining graph-based retrieval and generation capabilities. The extraction of entities and relationships from these documents and the KG construction process are detailed. Furthermore, the KG is integrated with an LLM to develop a Q&A system, demonstrating that the system significantly improves answer accuracy compared to traditional LLMs. Additionally, the KG construction process is up to 50% faster than conventional LLM-based approaches, underscoring the efficiency of our method. This study provides a promising approach to digital intelligence in shipping, advancing knowledge accessibility and decision-making.
基金Hangzhou Philosophy and Social Science Planning Program(24JD15)。
文摘National Fire codes,mandated by government authorities to tackle technical challenges in fire prevention and control,establish fundamental standards for construction practices.International collaboration in fire protection technologies has opened avenues for China to access a wealth of documents and codes,which are crucial in crafting regulations and developing a robust,scientific framework for fire code formulation.However,the translation of these codes into Chinese has been inadequate,thereby diminishing the benefits of technological exchange and collaborative learning.This underscores the necessity for comprehensive research into code translation,striving for higher-quality translations guided by established translation theories.In this study,we translated the initial segment of the NFPA 1 Fire Code into Chinese and examined both the source text and target text through the lens of Translation Shift Theory,a concept introduced by Catford.The conclusion culminated in identifying four key shifts across various linguistic levels:lexis,sentences,and groups,to ensure an accurate and precise translation of fire codes.This study offers a through and lucid explanation of how the translator integrates Catford’s theories to solve technical challenges in NFPA 1 Fire Code translation,and establish essential standards for construction translation practices.
文摘In the article“Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space”by Mudassir Khalil,Muhammad Imran Sharif,Ahmed Naeem,Muhammad Umar Chaudhry,Hafiz Tayyab Rauf,Adham E.Ragab Computers,Materials&Continua,2023,Vol.77,No.2,pp.2031–2047.DOI:10.32604/cmc.2023.043687,URL:https://www.techscience.com/cmc/v77n2/54831,there was an error regarding the affiliation for the author Hafiz Tayyab Rauf.Instead of“Centre for Smart Systems,AI and Cybersecurity,Staffordshire University,Stoke-on-Trent,ST42DE,UK”,the affiliation should be“Independent Researcher,Bradford,BD80HS,UK”.
基金supported by the Natural Science Foundation of Henan Province(Grant No.242300420297)awarded to Yi Sun.
文摘With the development of anti-virus technology,malicious documents have gradually become the main pathway of Advanced Persistent Threat(APT)attacks,therefore,the development of effective malicious document classifiers has become particularly urgent.Currently,detection methods based on document structure and behavioral features encounter challenges in feature engineering,these methods not only have limited accuracy,but also consume large resources,and usually can only detect documents in specific formats,which lacks versatility and adaptability.To address such problems,this paper proposes a novel malicious document detection method-visualizing documents as GGE images(Grayscale,Grayscale matrix,Entropy).The GGE method visualizes the original byte sequence of the malicious document as a grayscale image,the information entropy sequence of the document as an entropy image,and at the same time,the grayscale level co-occurrence matrix and the texture and spatial information stored in it are converted into grayscale matrix image,and fuses the three types of images to get the GGE color image.The Convolutional Block Attention Module-EfficientNet-B0(CBAM-EfficientNet-B0)model is then used for classification,combining transfer learning and applying the pre-trained model on the ImageNet dataset to the feature extraction process of GGE images.As shown in the experimental results,the GGE method has superior performance compared with other methods,which is suitable for detecting malicious documents in different formats,and achieves an accuracy of 99.44%and 97.39%on Portable Document Format(PDF)and office datasets,respectively,and consumes less time during the detection process,which can be effectively applied to the task of detecting malicious documents in real-time.
文摘This video series is the first experimental psychology documentary made in China.It focuses on analyzing professional theories to raise people’s general understanding of basic psychology.By combining innovative audiovisual narrative with psychological experiments,it zooms in on real human nature through discussing social hotspots from the perspectives of social psychology,cognitive psychology,and personality psychology,in order to help people find answers for their current psychological difficulties.
文摘A two-stage algorithm based on deep learning for the detection and recognition of can bottom spray codes and numbers is proposed to address the problems of small character areas and fast production line speeds in can bottom spray code number recognition.In the coding number detection stage,Differentiable Binarization Network is used as the backbone network,combined with the Attention and Dilation Convolutions Path Aggregation Network feature fusion structure to enhance the model detection effect.In terms of text recognition,using the Scene Visual Text Recognition coding number recognition network for end-to-end training can alleviate the problem of coding recognition errors caused by image color distortion due to variations in lighting and background noise.In addition,model pruning and quantization are used to reduce the number ofmodel parameters to meet deployment requirements in resource-constrained environments.A comparative experiment was conducted using the dataset of tank bottom spray code numbers collected on-site,and a transfer experiment was conducted using the dataset of packaging box production date.The experimental results show that the algorithm proposed in this study can effectively locate the coding of cans at different positions on the roller conveyor,and can accurately identify the coding numbers at high production line speeds.The Hmean value of the coding number detection is 97.32%,and the accuracy of the coding number recognition is 98.21%.This verifies that the algorithm proposed in this paper has high accuracy in coding number detection and recognition.
文摘This critical review looks at the assessment of the application of artificial intelligence in handling legal documents with specific reference to medical negligence cases with a view of identifying its transformative potentialities, issues and ethical concerns. The review consolidates findings that show the impact of AI in improving the efficiency, accuracy and justice delivery in the legal profession. The studies show increased efficiency in speed of document review and enhancement of the accuracy of the reviewed documents, with time efficiency estimates of 60% reduction of time. However, the review also outlines some of the problems that continue to characterize AI, such as data quality problems, biased algorithms and the problem of the opaque decision-making system. This paper assesses ethical issues related to patient autonomy, justice and non-malignant suffering, with particular focus on patient privacy and fair process, and on potential unfairness to patients. This paper’s review of AI innovations finds that regulations lag behind AI developments, leading to unsettled issues regarding legal responsibility for AI and user control over AI-generated results and findings in legal proceedings. Some of the future avenues that are presented in the study are the future of XAI for legal purposes, utilizing federated learning for resolving privacy issues, and the need to foster adaptive regulation. Finally, the review advocates for Legal Subject Matter Experts to collaborate with legal informatics experts, ethicists, and policy makers to develop the best solutions to implement AI in medical negligence claims. It reasons that there is great potential for AI to have a deep impact on the practice of law but when done, it must do so in a way that respects justice and on the Rights of Individuals.
文摘The care of a patient involved in major trauma with exsanguinating haemorrhage is time-critical to achieve definitive haemorrhage control,and it requires coordinated multidisciplinary care.During initial resuscitation of a patient in the emergency department(ED),Code Crimson activation facilitates rapid decisionmaking by multi-disciplinary specialists for definitive haemorrhage control in operating theatre(OT)and/or interventional radiology(IR)suite.Once this decision has been made,there may still be various factors that lead to delay in transporting the patient from ED to OT/IR.Red Blanket protocol identifies and addresses these factors and processes which cause delay,and aims to facilitate rapid and safe transport of the haemodynamically unstable patient from ED to OT,while minimizing delay in resuscitation during the transfer.The two processes,Code Crimson and Red Blanket,complement each other.It would be ideal to merge the two processes into a single protocol rather than having two separate workflows.Introducing these quality improvement strategies and coor-dinated processes within the trauma framework of the hospitals/healthcare systems will help in further improving the multi-disciplinary care for the complex trauma patients requiring rapid and definitive haemorrhage control.
基金Supported in part by the National Key R&D Program of China(No.2020YFA0712300)NSFC(No.61872353)。
文摘Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition degree can easily be adjusted simultaneously.This paper introduces a new type of pliable FR codes,called absolute balanced pliable FR(ABPFR)codes,in which the access balancing in DSS is considered.Additionally,the equivalence between pliable FR codes and resolvable transversal packings in combinatorial design theory is presented.Then constructions of pliable FR codes and ABPFR codes based on resolvable transversal packings are presented.
基金supported by the External Cooperation Program of Science and Technology of Fujian Province,China(2024I0016)the Fundamental Research Funds for the Central Universities(ZQN-1005).
文摘Multilevel coding(MLC)is a commonly used polar coded modulation scheme,but challenging to implement in engineering due to its high complexity and long decoding delay for high-order modulations.To address these limitations,a novel two-level serially concatenated MLC scheme,in which the bitlevels with similar reliability are bundled and transmitted together,is proposed.The proposed scheme hierarchically protects the two bit-level sets:the bitlevel sets at the higher level are sufficiently reliable and do not require excessive resources for protection,whereas only the bit-level sets at the lower level are encoded by polar codes.The proposed scheme has the advantages of low power consumption,low delay and high reliability.Moreover,an optimized constellation signal labeling rule that can enhance the performance is proposed.Finally,the superiority of the proposed scheme is validated through the theoretical analysis and simulation results.Compared with the bit interleaving coding modulation(BICM)scheme,under 256-quadrature amplitude modulation(QAM),the proposed scheme attains a performance gain of 1.0 dB while reducing the decoding complexity by 54.55%.
文摘What Are You Up To Today?Chief Director:Wu Zijuan Length:12 Episodes Producer:bilibili Broadcasting Platform:bilibili Produced by China’s YouTube-like video sharing platform bilibili,the film is a series of short documentaries presenting people's daily life in different jobs.It follows 12 individuals in their respective jobs and trades that keep society functioning.By focusing on their daily lives,the documentary films capture the hustle and bustle of the days that make up a hopeful life.
基金Supported by Research Funds of Hubei Province(D20144401,Q20174503)。
文摘In this paper,we first generalize the constant dimension and orbit codes over finite fields to the constant rank and orbit codes over finite chain rings.Then we provide a relationship between constant rank codes over finite chain rings and constant dimension codes over the residue fields.In particular,we prove that an orbit submodule code over a finite chain ring is a constant rank code.Finally,for special finite chain ring F_(q)+γF_(q),we define a Gray mapφfrom(F_(q)+γF_(q))^(n)to F^(2n)_(q),and by using cyclic codes over F_(q)+γF_(q),we obtain a method of constructing an optimum distance constant dimension code over F_(q).
