Designing a Secure and Scalable Data Sharing Mechanism Using Decentralized Identifiers(DID)

Centralized storage and identity identification methods pose many risks,including hacker attacks,data misuse,and single points of failure.Additionally,existing centralized identity management methods face interoperability issues and rely on a single identity provider,leaving users without control over their identities.Therefore,this paper proposes a mechanism for identity identification and data sharing based on decentralized identifiers.The scheme utilizes blockchain technology to store the identifiers and data hashed on the chain to ensure permanent identity recognition and data integrity.Data is stored on InterPlanetary File System(IPFS)to avoid the risk of single points of failure and to enhance data persistence and availability.At the same time,compliance with World Wide Web Consortium(W3C)standards for decentralized identifiers and verifiable credentials increases the mechanism’s scalability and interoperability.

Analysis of identifiers in IoT platforms

The Internet of Things(IoT)provides new opportunities for different IoT platforms connecting various devices together.The need to identify those devices is the foremost important to perform any kind of operation.Many organizations and standard bodies that provide specifications and frameworks for the IoT currently have their own identification mechanisms.Some existing industrial identification mechanisms can also be used in the IoT.There is no common Identification Scheme(IS)for the IoT as yet,because of the political and commercial differences amongst the standard bodies.The unavailability of a unified IS method makes the inter-working among IoT platforms challenging.This paper analyses and compares ISs used by several selected IoT platforms.This work will help in understanding the need for a common identification mechanism to provide inter-working among different IoT platforms.

Conditions of Non-Unique Identifiers in Record Linkage Using Japanese Cohort Dataset

The applications of unique identifiers such as name, home address and social security number to link different datasets have been commonly used and well-published. Also, the theoretical concepts of probabilistic algorithm in record linkage have been well-defined in the literature. However, few studies have reported the applications of its probabilistic algorithm using non-unique identifiers. In this paper, we investigate several variables (weight, height, waist, age, sex, smoking and alcohol habit) as non-unique identifiers using Japanese cohort dataset with three-year baseline of 1989-1991 to observe how effectively these identifiers can be used and what influence those may have on record linkage. Moreover, we modify the conditions of these identifiers and estimate the sensitivity, specificity and accuracy for comparison. We further investigate this by using extended ten-year baseline of 1989-1999 as well. As a result, we conclude that the combination of age, sex, weight and height predicts better estimation with regards to the sensitivity, specificity and accuracy than other combinations in both men and women in case of using three-year baseline, whereas the combination of age, sex and height predicts better in both men and women in case of using ten-year baseline.

Ai2NU: A Cytoscape plugin for uniformization of biomolecular accession identifiers

Cytoscape is one of the most popular platforms for biomolecular networks research. However Cytoscape cannot display biomolecular names according to their accession identifiers in different databases. A plugin named Ai2NU is designed and implemented in this paper. It can make biomolecular names displayed automatically in biomolecular networks graphs in Cytoscape by constructing a local dictionary. It is convenient for researchers to recognize biomolecules and enhance the research efficiency.

Utilizing Geospatial Tools to Assign Unique Identifiers to Water Bodies in a Low-Income Country

Inland waters support the growth of several sectors including mining, agriculture, and health. This makes it crucial to have sustainable quantity and quality through conservation practices. Achieving sustainability requires information on the spatial distribution of water bodies. This requirement is particularly critical in low-income nations where dependence on natural resources is a key driver to economic growth. Unfortunately, these nations lack the resources to promote costly waterbody characterization. This study pre-sents a cost-effective approach in assigning Unique Identifiers (UIDs) that define locations and characteristics of rivers and streams. Our objective is to develop a scheme that can be used to identify and characterize rivers and streams in a nation. We utilized an open-source Digital Elevation Model (DEM) of NASA’s ASTER satellite and the hydrology tool in ArcGIS 10.7.1. The DEM was imported to ArcGIS followed by delineation of hydrologic regions, subregions, and stream orders. Each stream segment was given a UID based on its region and Strahler’s stream order system. We present a case study analysis for two regions within Sierra Leone using water quality data of selected rivers and streams. These will lay the foundation for a nationwide coding exercise and provide a useful reference for water resource practitioners.

Unique,Persistent,Resolvable:Identifiers as the Foundation of FAIR

The FAIR principles describe characteristics intended to support access to and reuse of digital artifacts in the scientific research ecosystem.Persistent,globally unique identifiers,resolvable on the Web,and associated with a set of additional descriptive metadata,are foundational to FAIR data.Here we describe some basic principles and exemplars for their design,use and orchestration with other system elements to achieve FAIRness for digital research objects.

From Persistent Identifiers to Digital Objects to Make Data Science More Efficient

Data-intensive science is reality in large scientific organizations such as the Max Planck Society,but due to the inefficiency of our data practices when it comes to integrating data from different sources,many projects cannot be carried out and many researchers are excluded.Since about 80%of the time in data-intensive projects is wasted according to surveys we need to conclude that we are not fit for the challenges that will come with the billions of smart devices producing continuous streams of data-our methods do not scale.Therefore experts worldwide are looking for strategies and methods that have a potential for the future.The first steps have been made since there is now a wide agreement from the Research Data Alliance to the FAIR principles that data should be associated with persistent identifiers(PID)and metadata(MD).In fact after 20 years of experience we can claim that there are trustworthy PID systems already in broad use.It is argued,however,that assigning PIDs is just the first step.If we agree to assign PIDs and also use the PID to store important relationships such as pointing to locations where the bit sequences or different metadata can be accessed,we are close to defining Digital Objects(DOs)which could indeed indicate a solution to solve some of the basic problems in data management and processing.In addition to standardizing the way we assign PIDs,metadata and other state information we could also define a Digital Object Access Protocol as a universal exchange protocol for DOs stored in repositories using different data models and data organizations.We could also associate a type with each DO and a set of operations allowed working on its content which would facilitate the way to automatic processing which has been identified as the major step for scalability in data science and data industry.A globally connected group of experts is now working on establishing testbeds for a DO-based data infrastructure.

Re-identifying beef cattle using improved AlignedReID++

Accurate and continuous identification of individual cattle is crucial to precision farming in recent years.It is also the prerequisite to monitor the individual feed intake and feeding time of beef cattle at medium to long distances over different cameras.However,beef cattle can tend to frequently move and change their feeding position during feeding.Furthermore,the great variations in their head direction and complex environments(light,occlusion,and background)can also lead to some difficulties in the recognition,particularly for the bio-similarities among individual cattle.Among them,AlignedReID++model is characterized by both global and local information for image matching.In particular,the dynamically matching local information(DMLI)algorithm has been introduced into the local branch to automatically align the horizontal local information.In this research,the AlignedReID++model was utilized and improved to achieve the better performance in cattle re-identification(ReID).Initially,triplet attention(TA)modules were integrated into the BottleNecks of ResNet50 Backbone.The feature extraction was then enhanced through cross-dimensional interactions with the minimal computational overhead.Since the TA modules in AlignedReID++baseline model increased the model size and floating point operations(FLOPs)by 0.005 M and 0.05 G,the rank-1 accuracy and mean average precision(mAP)were improved by 1.0 percentage points and 2.94 percentage points,respectively.Specifically,the rank-1 accuracies were outperformed by 0.86 percentage points and 0.12 percentage points,respectively,compared with the convolution block attention module(CBAM)and efficient channel attention(ECA)modules,although 0.94 percentage points were lower than that of squeeze-and-excitation(SE)modules.The mAP metric values were exceeded by 0.22,0.86 and 0.12 percentage points,respectively,compared with the SE,CBAM,and ECA modules.Additionally,the Cross-Entropy Loss function was replaced with the CosFace Loss function in the global branch of baseline model.CosFace Loss and Hard Triplet Loss were jointly employed to train the baseline model for the better identification on the similar individuals.AlignedReID++with CosFace Loss was outperformed the baseline model by 0.24 and 0.92 percentage points in the rank-1 accuracy and mAP,respectively,whereas,AlignedReID++with ArcFace Loss was exceeded by 0.36 and 0.56 percentage points,respectively.The improved model with the TA modules and CosFace Loss was achieved in a rank-1 accuracy of 94.42%,rank-5 accuracy of 98.78%,rank-10 accuracy of 99.34%,mAP of 63.90%,FLOPs of 5.45 G,frames per second(FPS)of 5.64,and model size of 23.78 M.The rank-1 accuracies were exceeded by 1.84,4.72,0.76 and 5.36 percentage points,respectively,compared with the baseline model,part-based convolutional baseline(PCB),multiple granularity network(MGN),and relation-aware global attention(RGA),while the mAP metrics were surpassed 6.42,5.86,4.30 and 7.38 percentage points,respectively.Meanwhile,the rank-1 accuracy was 0.98 percentage points lower than TransReID,but the mAP metric was exceeded by 3.90 percentage points.Moreover,the FLOPs of improved model were only 0.05 G larger than that of baseline model,while smaller than those of PCB,MGN,RGA,and TransReID by 0.68,6.51,25.4,and 16.55 G,respectively.The model size of improved model was 23.78 M,which was smaller than those of the baseline model,PCB,MGN,RGA,and TransReID by 0.03,2.33,45.06,14.53 and 62.85 M,respectively.The inference speed of improved model on a CPU was lower than those of PCB,MGN,and baseline model,but higher than TransReID and RGA.The t-SNE feature embedding visualization demonstrated that the global and local features were achieve in the better intra-class compactness and inter-class variability.Therefore,the improved model can be expected to effectively re-identify the beef cattle in natural environments of breeding farm,in order to monitor the individual feed intake and feeding time.

Analysis on Genetic Diversity of 40 Flowering Cherry Cultivars and Construction of Molecular ID Based on SSR Markers

Studying on the genetic diversity and genetic relationship of flowering cherry cultivars is extremely important for germplasm conservation, cultivar identification and breeding. Flowering cherry is widely cultivated as an important woody ornamental plant in worldwide, especially Japan, China. However, owning to the morphological similarity, many cultivars are distinguished hardly in non-flowering season. Here, we evaluated the genetic diversity and genetic relationship of 40 flowering cherry cultivars, which are mainly cultivated in China. We selected 13 polymorphicprimers to amplify to allele fragments with fluorescent-labeled capillary electrophoresis technology. The population structure analysis results show that these cultivars could be divided into 4 subpopulations. At the population level, Na and Ne were 6.062, 4.326, respectively. Ho and He were 0.458 and 0.670, respectively. The Shannon’s information index (I) was 1.417. The Pop3, which originated from P. serrulata, had the highest Ho, He, and I among the 4 subpopulations. AMOVA showed that only 4% of genetic variation came from populations, the 39% variation came from individuals and 57% (p < 0.05) came from intra-individuals. 5 polymorphic SSR primers were selected to construct molecular ID code system of these cultivars. This analysis on the genetic diversity and relationship of the 40 flowering cherry cultivars will help to insight into the genetic background, relationship of these flowering cherry cultivars and promote to identify similar cultivars.

Ad Blockers & Online Privacy: A Comparative Analysis of Privacy Enhancing Technologies (PET)

Online tracking mechanisms employed by internet companies for user profiling and targeted advertising raise major privacy concerns. Despite efforts to defend against these mechanisms, they continue to evolve, rendering many existing defences ineffective. This study performs a large-scale measurement of online tracking mechanisms across a large pool of websites using the OpenWPM (Open Web Privacy Measurement) platform. It systematically evaluates the effectiveness of several ad blockers and underlying Privacy Enhancing Technologies (PET) that are primarily used to mitigate different tracking techniques. By quantifying the strengths and limitations of these tools against modern tracking methods, the findings highlight gaps in existing privacy protections. Actionable recommendations are provided to enhance user privacy defences, guide tool developers and inform policymakers on addressing invasive online tracking practices.

IDentifier DNA分型盒(炎黄34)的法医学验证及应用评估

目的 测试IDentifier DNA分型盒(炎黄34)的技术性能指标,评估其法医学应用价值。方法 根据《法庭科学人类荧光标记STR复合扩增检测试剂质量基本要求》(GB/T 37226—2018),从种属特异性、分型准确性、灵敏度、适应性、耐受性、一致性、均衡性、反应条件验证、混合样本、稳定性、批间差11个方面对IDentifier DNA分型盒(炎黄34)进行测试。比较IDentifier DNA分型盒(炎黄34)与Power Plex~?Fusion 6C系统、Versa Plex~?27PY系统、Veri Filer~(TM) Plus PCR扩增试剂盒的系统效能。使用IDentifier DNA分型盒(炎黄34)检测日常案件中的拭子类生物检材,观察其STR检验结果 。结果 IDentifier DNA分型盒(炎黄34)具有良好的种属特异性、分型准确性、适应性、耐受性和均衡性,灵敏度可达0.062 5 ng,能检测案件中不同类型的检材、降解检材及混有抑制剂的检材,对混合比例为4∶1以内的样本均能获得完整分型。该试剂盒的系统效能非常高,TDP可达1-1.08×10~(-37),CPE_(trio)和CPE_(duo)分别可达1-5.47×10~(-14)和1-6.43×10~(-9)。针对案件中的接触类生物检材,其有效检出率可达21.05%。针对亲缘关系鉴定,单亲鉴定和全同胞鉴定的系统效能均得到了有效提高。结论 IDentifier DNA分型盒(炎黄34)的上述性能指标符合要求,可用于个体识别及亲权鉴定,适合在法庭科学领域应用。

A Novel Method in Wood Identification Based on Anatomical Image Using Hybrid Model

Nowadays,wood identification is made by experts using hand lenses,wood atlases,and field manuals which take a lot of cost and time for the training process.The quantity and species must be strictly set up,and accurate identification of the wood species must be made during exploitation to monitor trade and enforce regulations to stop illegal logging.With the development of science,wood identification should be supported with technology to enhance the perception of fairness of trade.An automatic wood identification system and a dataset of 50 commercial wood species from Asia are established,namely,wood anatomical images collected and used to train for the proposed model.In the convolutional neural network(CNN),the last layers are usually soft-max functions with dense layers.These layers contain the most parameters that affect the speed model.To reduce the number of parameters in the last layers of the CNN model and enhance the accuracy,the structure of the model should be optimized and developed.Therefore,a hybrid of convolutional neural network and random forest model(CNN-RF model)is introduced to wood identification.The accuracy’s hybrid model is more than 98%,and the processing speed is 3 times higher than the CNN model.The highest accuracy is 1.00 in some species,and the lowest is 0.92.These results show the excellent adaptability of the hybrid model in wood identification based on anatomical images.It also facilitates further investigations of wood cells and has implications for wood science.

Improved Euler method for the interpretation of potential data based on the ratio of the vertical fi rst derivative to analytic signal

We propose a new automatic method for the interpretation of potential fi eld data, called the RDAS–Euler method, which is based on Euler＇s deconvolution and analytic signal methods. The proposed method can estimate the horizontal and vertical extent of geophysical anomalies without prior information of the nature of the anomalies（structural index）. It also avoids inversion errors because of the erroneous choice of the structural index N in the conventional Euler deconvolution method. The method was tested using model gravity anomalies. In all cases, the misfi t between theoretical values and inversion results is less than 10%. Relative to the conventional Euler deconvolution method, the RDAS–Euler method produces inversion results that are more stable and accurate. Finally, we demonstrate the practicability of the method by applying it to Hulin Basin in Heilongjiang province, where the proposed method produced more accurate data regarding the distribution of faults.

乙嘧酚磺酸酯中杂质的GC-MS分析

The structure of bupirimate was identified by using MS and NMR.The structures of 10 impurities were identified by using GC-MS.The method provides a powerful tool for structure analysis special in complex samples.

蓝牙服务搜索的设计与实现

本文介绍蓝牙技术中服务搜索基本功能及其实现 .通过对蓝牙硬拷贝电缆替代课题研究中服务搜索的设计和实现 ,提供了一个在蓝牙环境下的服务搜索的方法和思路 .

数字版权保护中DCI编码方案及数字证书研究

数字版权标志符为数字内容在互联网上提供唯一的版权身份标志,为确保在网络环境中能够精准定位和检索数字作品、确认版权主体提供了技术基础。建立数字版权标志符体系是我国数字版权管理发展的迫切要求。通过研究DCI(数字版权标志符)的概念、设计原则,分析了国外相关研究的现状,提出了适合我国版权保护的DCI编码方案,并给出了应用于移动互联网的加密机制、数字证书及DCI嵌入方案。研究结果表明,采用上述方法,兼容性好,易于与国际上的DOI(digital object identifier)接轨,加密机制及数字证书的设计适合在移动互联网上应用。

The Research about A Regional Drought Identifying System Based on Dynamic Drought Index

With the data of daily precipitation and daily evaporation,dynamic drought index was calculated and compared with the identification standard of drought grade to qualify the severity of drought.According to the dynamic drought index,a regional drought identifying system was developed for the watershed between the reach of the Yangtze River and Huaihe River in Anhui Province by using VC++ working platform and Access database.This drought identifying system would be very useful to forecast and early warn the happening of drought in this area.

贵州汉族人群15个STR基因座遗传多态性研究

目的对贵州汉族人群在Identifiler体系中的15个短串连重复序列(STR)基因座进行遗传多态性调查。方法采用荧光标记STR-PCR复合扩增、毛细管电泳基因分型技术,对1 000名贵州汉族人群无关个体进行15个STR基因座的基因分型,计算其等位基因频率、杂合度(H)、匹配概率(PM)、个人识别力(DP)、非父排除率(PE)、多态信息总量(PIC)、父权指数(PI)等多态性参数,并进行统计学分析。结果在贵州汉族人群1 000名无关个体中共检出178个等位基因,其频率分布为0.000 5~0.531 5。15个STR基因座的基因型分布进行χ~2检验符合Hardy-Weinberg平衡定律(P>0.05)。杂合度为0.603 0~0.880 0;个人识别力为0.786 1~0.966 6,累积DP>0.999 999 999;匹配概率为0.033 4~0.213 9,累积PM=1.198×10^(-17);三联体非父排除率为0.294 5~0.754 8,累积CPE=0.999 998 925;二联体非父排除率为0.195 9~0.571 6,累积CPE=0.999 760 600;多态信息含量为0.545 1~0.849 2,累积PIC=0.999 999 999;亲权指数为1.2 594~4.1 667。结论贵州汉族人群检测的15个STR基因座具有高度多态性,是较理想的遗传标记,统计的等位基因频率等基础数据可为本地区的个人识别、三联体亲子鉴定及群体遗传学研究提供依据,但在二联体亲子鉴定中运用存在一定风险。

Office Word文档溯源方法研究

基于最广泛使用的Microsoft Office Word文件结构格式分析,集中关注编辑过程还原主题,立足document.xml与core.xml文件内容,挖掘OOXML格式中独特的RI值变化规则,进而完成文件来源的取证分析,并通过自主研发的软件使得分析工作智能化工具化。电子数据取证实践证明,所述方法准确高效。

教师绩效评估中的评估者目标对评估结果的影响研究

目前,在绩效评估研究中缺乏评估者目标理论的实证研究。本研究在"假设对象"(Paper People)的实验情境下,通过509名大学生被试对教师绩效的评估,探讨了评估者目标对评估结果的影响,并验证了Murphy等人开发的评估者目标问卷的信效度。研究表明:绩效评估中确定不足目标对总体评估结果有负向影响,确定优势目标对总体评估结果有正向影响;确定优势目标越高,总体准确度越低;确定不足目标对区分被评个体有正向影响。