Along with the proliferating research interest in semantic communication(Sem Com),joint source channel coding(JSCC)has dominated the attention due to the widely assumed existence in efficiently delivering information ...Along with the proliferating research interest in semantic communication(Sem Com),joint source channel coding(JSCC)has dominated the attention due to the widely assumed existence in efficiently delivering information semantics.Nevertheless,this paper challenges the conventional JSCC paradigm and advocates for adopting separate source channel coding(SSCC)to enjoy a more underlying degree of freedom for optimization.We demonstrate that SSCC,after leveraging the strengths of the Large Language Model(LLM)for source coding and Error Correction Code Transformer(ECCT)complemented for channel coding,offers superior performance over JSCC.Our proposed framework also effectively highlights the compatibility challenges between Sem Com approaches and digital communication systems,particularly concerning the resource costs associated with the transmission of high-precision floating point numbers.Through comprehensive evaluations,we establish that assisted by LLM-based compression and ECCT-enhanced error correction,SSCC remains a viable and effective solution for modern communication systems.In other words,separate source channel coding is still what we need.展开更多
Topic models such as Latent Dirichlet Allocation(LDA) have been successfully applied to many text mining tasks for extracting topics embedded in corpora. However, existing topic models generally cannot discover bursty...Topic models such as Latent Dirichlet Allocation(LDA) have been successfully applied to many text mining tasks for extracting topics embedded in corpora. However, existing topic models generally cannot discover bursty topics that experience a sudden increase during a period of time. In this paper, we propose a new topic model named Burst-LDA, which simultaneously discovers topics and reveals their burstiness through explicitly modeling each topic's burst states with a first order Markov chain and using the chain to generate the topic proportion of documents in a Logistic Normal fashion. A Gibbs sampling algorithm is developed for the posterior inference of the proposed model. Experimental results on a news data set show our model can efficiently discover bursty topics, outperforming the state-of-the-art method.展开更多
The challenge faced by the visually impaired persons in their day-today lives is to interpret text from documents.In this context,to help these people,the objective of this work is to develop an efficient text recogni...The challenge faced by the visually impaired persons in their day-today lives is to interpret text from documents.In this context,to help these people,the objective of this work is to develop an efficient text recognition system that allows the isolation,the extraction,and the recognition of text in the case of documents having a textured background,a degraded aspect of colors,and of poor quality,and to synthesize it into speech.This system basically consists of three algorithms:a text localization and detection algorithm based on mathematical morphology method(MMM);a text extraction algorithm based on the gamma correction method(GCM);and an optical character recognition(OCR)algorithm for text recognition.A detailed complexity study of the different blocks of this text recognition system has been realized.Following this study,an acceleration of the GCM algorithm(AGCM)is proposed.The AGCM algorithm has reduced the complexity in the text recognition system by 70%and kept the same quality of text recognition as that of the original method.To assist visually impaired persons,a graphical interface of the entire text recognition chain has been developed,allowing the capture of images from a camera,rapid and intuitive visualization of the recognized text from this image,and text-to-speech synthesis.Our text recognition system provides an improvement of 6.8%for the recognition rate and 7.6%for the F-measure relative to GCM and AGCM algorithms.展开更多
The present study investigated the impact from GOs （Graphic Organizers） upon reading comprehension ability. To this end, an OPT （Oxford Placement Test） was administered to a research population （N = 354） in orde...The present study investigated the impact from GOs （Graphic Organizers） upon reading comprehension ability. To this end, an OPT （Oxford Placement Test） was administered to a research population （N = 354） in order to homogenize it. On the basis of the test results, the population was sorted into three groups of reading-low, reading-mid, and reading-high students. Sixty participants with the lowest level of reading comprehension proficiency were randomly selected and assigned to an EG （Experimental Group） （N = 30） and a CG （Control Group） （N = 30）. Afterwards, a TOEFL （Test of English as a Foreign Language） reading comprehension pretest was administered to both groups in order to determine their current level of reading proficiency. Then, the EG received 10 successive 90-minute sessions on GOs as post-reading strategies for expository text comprehension, while the CG received the same amount of treatment on other post-reading strategies. In the end, another TOEFL reading comprehension posttest was administered to the research groups to measure their reading comprehension performance level after the treatment. The results revealed that GOs were statistically more significant and effective for the low-skilled readers than other post-reading strategies.展开更多
Alphanumerical usernames and passwords are the most used computer authentication technique.This approach has been found to have a number of disadvantages.Users,for example,frequently choose passwords that are simple t...Alphanumerical usernames and passwords are the most used computer authentication technique.This approach has been found to have a number of disadvantages.Users,for example,frequently choose passwords that are simple to guess.On the other side,if a password is difficult to guess,it is also difficult to remember.Graphical passwords have been proposed in the literature as a potential alternative to alphanumerical passwords,based on the fact that people remember pictures better than text.Existing graphical passwords,on the other hand,are vulnerable to a shoulder surfing assault.To address this shoulder surfing vulnerability,this study proposes an authentication system for web-applications based on visual cryptography and cued click point recall-based graphical password.The efficiency of the proposed system was validated using unit,system and usability testing measures.The results of the system and unit testing showed that the proposed system accomplished its objectives and requirements.The results of the usability test showed that the proposed system is easy to use,friendly and highly secured.展开更多
基金supported in part by the National Key Research and Development Program of China under Grant No.2024YFE0200600the Zhejiang Provincial Natural Science Foundation of China under Grant No.LR23F010005the Huawei Cooperation Project under Grant No.TC20240829036。
文摘Along with the proliferating research interest in semantic communication(Sem Com),joint source channel coding(JSCC)has dominated the attention due to the widely assumed existence in efficiently delivering information semantics.Nevertheless,this paper challenges the conventional JSCC paradigm and advocates for adopting separate source channel coding(SSCC)to enjoy a more underlying degree of freedom for optimization.We demonstrate that SSCC,after leveraging the strengths of the Large Language Model(LLM)for source coding and Error Correction Code Transformer(ECCT)complemented for channel coding,offers superior performance over JSCC.Our proposed framework also effectively highlights the compatibility challenges between Sem Com approaches and digital communication systems,particularly concerning the resource costs associated with the transmission of high-precision floating point numbers.Through comprehensive evaluations,we establish that assisted by LLM-based compression and ECCT-enhanced error correction,SSCC remains a viable and effective solution for modern communication systems.In other words,separate source channel coding is still what we need.
基金Supported by the National High Technology Research and Development Program of China(No.2012AA011005)
文摘Topic models such as Latent Dirichlet Allocation(LDA) have been successfully applied to many text mining tasks for extracting topics embedded in corpora. However, existing topic models generally cannot discover bursty topics that experience a sudden increase during a period of time. In this paper, we propose a new topic model named Burst-LDA, which simultaneously discovers topics and reveals their burstiness through explicitly modeling each topic's burst states with a first order Markov chain and using the chain to generate the topic proportion of documents in a Logistic Normal fashion. A Gibbs sampling algorithm is developed for the posterior inference of the proposed model. Experimental results on a news data set show our model can efficiently discover bursty topics, outperforming the state-of-the-art method.
基金This work was funded by the Deanship of Scientific Research at Jouf University under Grant Number(DSR2022-RG-0114).
文摘The challenge faced by the visually impaired persons in their day-today lives is to interpret text from documents.In this context,to help these people,the objective of this work is to develop an efficient text recognition system that allows the isolation,the extraction,and the recognition of text in the case of documents having a textured background,a degraded aspect of colors,and of poor quality,and to synthesize it into speech.This system basically consists of three algorithms:a text localization and detection algorithm based on mathematical morphology method(MMM);a text extraction algorithm based on the gamma correction method(GCM);and an optical character recognition(OCR)algorithm for text recognition.A detailed complexity study of the different blocks of this text recognition system has been realized.Following this study,an acceleration of the GCM algorithm(AGCM)is proposed.The AGCM algorithm has reduced the complexity in the text recognition system by 70%and kept the same quality of text recognition as that of the original method.To assist visually impaired persons,a graphical interface of the entire text recognition chain has been developed,allowing the capture of images from a camera,rapid and intuitive visualization of the recognized text from this image,and text-to-speech synthesis.Our text recognition system provides an improvement of 6.8%for the recognition rate and 7.6%for the F-measure relative to GCM and AGCM algorithms.
文摘The present study investigated the impact from GOs （Graphic Organizers） upon reading comprehension ability. To this end, an OPT （Oxford Placement Test） was administered to a research population （N = 354） in order to homogenize it. On the basis of the test results, the population was sorted into three groups of reading-low, reading-mid, and reading-high students. Sixty participants with the lowest level of reading comprehension proficiency were randomly selected and assigned to an EG （Experimental Group） （N = 30） and a CG （Control Group） （N = 30）. Afterwards, a TOEFL （Test of English as a Foreign Language） reading comprehension pretest was administered to both groups in order to determine their current level of reading proficiency. Then, the EG received 10 successive 90-minute sessions on GOs as post-reading strategies for expository text comprehension, while the CG received the same amount of treatment on other post-reading strategies. In the end, another TOEFL reading comprehension posttest was administered to the research groups to measure their reading comprehension performance level after the treatment. The results revealed that GOs were statistically more significant and effective for the low-skilled readers than other post-reading strategies.
文摘Alphanumerical usernames and passwords are the most used computer authentication technique.This approach has been found to have a number of disadvantages.Users,for example,frequently choose passwords that are simple to guess.On the other side,if a password is difficult to guess,it is also difficult to remember.Graphical passwords have been proposed in the literature as a potential alternative to alphanumerical passwords,based on the fact that people remember pictures better than text.Existing graphical passwords,on the other hand,are vulnerable to a shoulder surfing assault.To address this shoulder surfing vulnerability,this study proposes an authentication system for web-applications based on visual cryptography and cued click point recall-based graphical password.The efficiency of the proposed system was validated using unit,system and usability testing measures.The results of the system and unit testing showed that the proposed system accomplished its objectives and requirements.The results of the usability test showed that the proposed system is easy to use,friendly and highly secured.
