Individuals with special needs learn more slowly than their peers and they need repetitions to be permanent.However,in crowded classrooms,it is dif-ficult for a teacher to deal with each student individually.This probl...Individuals with special needs learn more slowly than their peers and they need repetitions to be permanent.However,in crowded classrooms,it is dif-ficult for a teacher to deal with each student individually.This problem can be overcome by using supportive education applications.However,the majority of such applications are not designed for special education and therefore they are not efficient as expected.Special education students differ from their peers in terms of their development,characteristics,and educational qualifications.The handwriting skills of individuals with special needs are lower than their peers.This makes the task of Handwriting Recognition(HWR)more difficult.To over-come this problem,we propose a new personalized handwriting verification sys-tem that validates digits from the handwriting of special education students.The system uses a Convolutional Neural Network(CNN)created and trained from scratch.The data set used is obtained by collecting the handwriting of the students with the help of a tablet.A special education center is visited and the handwrittenfigures of the students are collected under the supervision of special education tea-chers.The system is designed as a person-dependent system as every student has their writing style.Overall,the system achieves promising results,reaching a recognition accuracy of about 94%.Overall,the system can verify special educa-tion students’handwriting digits with high accuracy and is ready to integrate with a mobile application that is designed to teach digits to special education students.展开更多
In the data communication system,the real-time information interaction of communication device increases the risk of privacy sensitive data being tam-pered with.Therefore,maintaining data security is one of the most i...In the data communication system,the real-time information interaction of communication device increases the risk of privacy sensitive data being tam-pered with.Therefore,maintaining data security is one of the most important issues in network data communication.Because the timestamp is the most impor-tant way to authenticate data in information interaction,it is very necessary to pro-vide timestamp service in the data communication system.However,the existing centralized timestamp mechanism is difficult to provide credible timestamp ser-vice,and users can conspire with timestamping servers to forge timestamps.Therefore,this paper designs a distributed timestamp mechanism based on contin-uous verifiable delay functions.It utilizes multiple independent timestamp servers to provide timestamp services in a distributed model and appends the timestamp to the data once the data is generated.Thus,it can prove that the data already exists at a certain time and ensure the accuracy of the timestamp.Moreover,a digital blind signature based on elliptic curve cryptography is utilized to solve the problem of timestamp forgery in timestamp service.Finally,the security ana-lysis of the scheme ensures the data security of data communication system and the concurrency rate of timestamp.The experimental results also show that the scheme greatly improves the efficiency of digital signatures.展开更多
文摘Individuals with special needs learn more slowly than their peers and they need repetitions to be permanent.However,in crowded classrooms,it is dif-ficult for a teacher to deal with each student individually.This problem can be overcome by using supportive education applications.However,the majority of such applications are not designed for special education and therefore they are not efficient as expected.Special education students differ from their peers in terms of their development,characteristics,and educational qualifications.The handwriting skills of individuals with special needs are lower than their peers.This makes the task of Handwriting Recognition(HWR)more difficult.To over-come this problem,we propose a new personalized handwriting verification sys-tem that validates digits from the handwriting of special education students.The system uses a Convolutional Neural Network(CNN)created and trained from scratch.The data set used is obtained by collecting the handwriting of the students with the help of a tablet.A special education center is visited and the handwrittenfigures of the students are collected under the supervision of special education tea-chers.The system is designed as a person-dependent system as every student has their writing style.Overall,the system achieves promising results,reaching a recognition accuracy of about 94%.Overall,the system can verify special educa-tion students’handwriting digits with high accuracy and is ready to integrate with a mobile application that is designed to teach digits to special education students.
基金supported by National Key R&D Program of China(Grant Nos.2021YF B2700503,2020YF B1005900)supported by the National Natural Science Foundation of China(No.62072249)。
文摘In the data communication system,the real-time information interaction of communication device increases the risk of privacy sensitive data being tam-pered with.Therefore,maintaining data security is one of the most important issues in network data communication.Because the timestamp is the most impor-tant way to authenticate data in information interaction,it is very necessary to pro-vide timestamp service in the data communication system.However,the existing centralized timestamp mechanism is difficult to provide credible timestamp ser-vice,and users can conspire with timestamping servers to forge timestamps.Therefore,this paper designs a distributed timestamp mechanism based on contin-uous verifiable delay functions.It utilizes multiple independent timestamp servers to provide timestamp services in a distributed model and appends the timestamp to the data once the data is generated.Thus,it can prove that the data already exists at a certain time and ensure the accuracy of the timestamp.Moreover,a digital blind signature based on elliptic curve cryptography is utilized to solve the problem of timestamp forgery in timestamp service.Finally,the security ana-lysis of the scheme ensures the data security of data communication system and the concurrency rate of timestamp.The experimental results also show that the scheme greatly improves the efficiency of digital signatures.
文摘背景支气管肺发育不良(bronchopulmonary dysplasia,BPD)是早产儿常见的并发症,也是导致早产儿不良神经发育结局的重要原因之一。目前国内外关于BPD早产儿不良神经发育结局高危因素的研究较少。目的研究BPD早产儿(出生胎龄≤32周)早期神经发育不良的危险因素。设计病例对照研究。方法以2017年1月1日至2018年12月31日复旦大学附属儿科医院收治的符合纳入和排除标准的新生儿为研究对象,根据Peabody运动发育量表(Peabody Developmental Motor Scales,PDMS)评估结果分为运动发育迟缓组与运动发育正常组,比较两组间一般情况、呼吸支持、实验室检查、治疗措施、共患病和神经系统检查的差异,分析BPD早产儿早期不良神经发育结局的危险因素。主要结局指标BPD早产儿不良神经发育结局的危险因素。结果共纳入85例在校正胎龄12月龄内完成PDMS评估的BPD早产儿,其中82例(96.5%)在校正胎龄6月龄时首次完成PDMS评估,运动发育迟缓组12例,运动发育正常组73例。单因素分析提示运动发育迟缓组有创机械通气时长[7.5(2,15.7)d]长于运动发育正常组[3(0,9)d],差异有统计学意义(P=0.038)。运动发育迟缓组Ⅲ级及以上脑室内出血的发病率(33.3%)高于运动发育正常组(6.8%),差异有统计学意义(P=0.020)。头颅MRI提示运动发育迟缓组脑白质损伤的发生率高于运动发育正常组,差异有统计学意义(P=0.022)。多因素Logistic回归分析显示脑白质损伤为BPD早产儿早期运动发育迟缓的独立危险因素(OR=3.549,95%CI:1.317~9.804,P=0.012)。结论头颅MRI提示的脑白质损伤为BPD早产儿早期运动发育落后的独立危险因素,对于这部分患儿应加强随访,尽早干预改善预后。
