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对比文件列表
2002-11-29_发明专利_JP2002342185A Remote maintenance system_+++A_B_C_D_E_F_G_M_Q_R_S_V_o+++.docx
2026-02-23 17:41
2004-05-27_发明申请_US20040103144A1 Systems and methods for communicating with devices as Web Services_+++B_C_Q_R_S_d_f_g_i_j_k_l_m_n_o+++.docx
2026-02-23 17:41
2007-09-20_发明专利_JP2007526992A System for electrical fault detection apparatus and method_+++A_B_C_D_E_F_G_Q_R_S_i_j_k_o_u+++.docx
2026-02-23 17:41
2008-06-12_发明申请_US20080136581A1 SMART CURRENT ATTENUATOR FOR ENERGY CONSERVATION IN APPLIANCES_+++O_Q_a_b_c_d_e_f_g_j_k_r_s_t_u+++.docx
2026-02-23 17:41
2009-08-06_发明申请_US20090199296A1 DETECTING UNAUTHORIZED USE OF COMPUTING DEVICES BASED ON BEHAVIORAL PATTERNS_+++D_E_H_P_Q_R_V_a_b_c_f_g_o_s+++.docx
2026-02-23 17:41
2009-11-12_发明申请_US20090281676A1 Systems, Apparatus, and Methods for the Management and Control of Remotely Controlled Devices_+++c_d_f_g_j_k_o_p_q_r_s_t_u+++.docx
2026-02-23 17:41
2010-02-18_发明专利_DE10353861B4 Discharge lamp of the short arc type_+++Q+++.docx
2026-02-23 17:41
2010-04-30_发明专利_JP2010098198A Substrate storage container and positioning structure thereof_+++q+++.docx
2026-02-23 17:41
2010-07-22_发明专利_JP2010161488A Network monitoring system and method therefor_+++b_c_d_e_f_k_o_p_q_r_s+++.docx
2026-02-23 17:41
2010-11-18_发明申请_WO2010131259A2 A MONITORING SYSTEM FOR CAPTURING INFORMATION RELATING TO THE WIRELESS SMART DEVICE FOR BEHAVIORAL ANALYTICS_+++C_D_R_S_b_k_q+++.docx
2026-02-23 17:41
2012-10-02_发明授权_US08280009B2 Consumer electronic registration, control and support concierge device and method_+++c_g_q_r_s+++.docx
2026-02-23 17:41
2013-01-09_发明专利_JP5115325B2 Lens barrel and imaging device_+++d_e_f_g_q_r+++.docx
2026-02-23 17:41
2014-02-13_发明申请_US20140047544A1 Server-Side Malware Detection and Classification_+++B_C_D_E_F_G_H_K_P_R_S_T_V_a_i_j_l_m_n_o_q_u+++.docx
2026-02-23 17:41
2014-08-28_发明申请_US20140244768A1 AUTOMATIC IOT DEVICE SOCIAL NETWORK EXPANSION_+++C_G_K_Q_R_S_a_b_d_f_i_j_l_o+++.docx
2026-02-23 17:41
2014-11-05_发明授权_CN102802158B 基于信任评估的无线传感器网络异常检测方法_+++B_C_D_E_P_T_a_f_g_h_o_q_r_s+++.docx
2026-02-23 17:41
2015-01-07_发明公开_CN104272788A 在移动计算装置中传达行为信息_+++C_D_E_F_H_O_P_Q_R_a_b_g_m_s_v+++.docx
2026-02-23 17:41
2015-03-05_发明申请_WO2015031676A2 INTEGRITY TESTING OF HAIR SAMPLES_+++D_E_a_b_c_f_g_o_q_r+++.docx
2026-02-23 17:41
2015-04-01_发明授权_CN102227691B 检测航空发动机的异常_+++D_E_Q_a_b_c_h_j_r_s_u+++.docx
2026-02-23 17:41
2015-06-11_发明申请_US20150163121A1 DISTRIBUTED MONITORING, EVALUATION, AND RESPONSE FOR MULTIPLE DEVICES_+++A_C_D_E_F_G_P_Q_R_V_b_i_k_o_s_t_u+++.docx
2026-02-23 17:41
2015-03-05_发明申请_WO2015031676A2 INTEGRITY TESTING OF HAIR SAMPLES_+++D_E_a_b_c_f_g_o_q_r+++.docx

对比文件名称:2015-03-05_发明申请_WO2015031676A2 INTEGRITY TESTING OF HAIR SAMPLES

目标专利名称:监视物联网设备健康状况的方法、装置、设备和存储介质CN107409073B

本次调用的模型名称:gpt-4o

特征比对表格如下:

技术特征描述以及公开性判断结果对比文件原文引用公开性论述
技术特征A《隐含公开》[p0071] “The sample is then subjected to proteolytic or non-proteolytic digestion methods...”, [p0018] “comparing the condition of the hair in the test sample to a control sample; and identifying the hair sample as damaged... or identifying the hair sample as suitable for further processing if the condition of the hair in the test solution is commensurate with the condition of the control sample.”对比文件公开了将头发样本与“对照样本”进行比较以判断其是否损伤或适合进一步处理(即是否“正常”)。本领域技术人员能够理解,在测试前,需将代表“正常/健康”头发(如未处理过的头发)的“对照样本”作为基准或模型,用于后续比较。该过程隐含了为目标样本(类比为“第二节点”)的正常行为(即健康头发的状态)建立一个参考模型。因此,技术特征A被对比文件隐含公开。
技术特征B《隐含公开》[p0018] “comparing the condition of the hair in the test sample to a control sample”, [p0058] “Accordingly, provided herein are methods for determining the presence of an analyte in a keratinized structure of a subject, the methods comprising: assessing the condition of a keratinized structure sample; and determining if the analyte is present in the keratinized structure sample.”对比文件描述了评估测试样本(Test sample)状况并将其与对照样本(Control sample)进行比较的方法。本领域技术人员可以合理地推断,执行该比较和分析功能的实体(例如,实验室技术人员或自动化分析设备)充当了“分析者节点”的角色,而被评估的头发样本本身则充当了提供行为(即物理/化学状态)信息的“观察者节点”的角色。这两者是不同的物理实体。因此,技术特征B被对比文件隐含公开。
技术特征C《隐含公开》[p0071] “The sample is then subjected to proteolytic or non-proteolytic digestion methods...”, [p0081] “Once the hair sample has been treated with a solution of a non-proteolytic reducing agent for a time sufficient to release entrapped analytes... the condition of the hair sample for analyte analysis is assessed.”对比文件描述了获取头发样本并对其进行处理,然后评估其状况。本领域技术人员能够理解,在处理和评估过程中,关于头发样本状况的信息(例如,溶解速度、柔软度、吸光度值)必然会被收集并传达给进行分析的实体。这相当于“第一节点”(分析者)通过实验操作流程“接收”来自“第二节点”(头发样本)的“行为信息”(即样本的状态变化)。因此,技术特征C被对比文件隐含公开。
技术特征D《直接公开》[p0018] “assessing the condition of a hair sample”, [p0023] “estimating the degree of damage to hair by absorption spectrophotometry...”, [p0082] “Hair samples that exhibit disintegration after non-proteolytic reduction as compared to the control sample... can be identified as damaged for analyte analysis.”对比文件明确公开了“评估头发样本的状况”,具体方法包括视觉检查、测量吸光度等,以分析样本的行为(即损伤程度)。例如,通过分光光度法测量吸光度(A380)来估计损伤程度,这直接对应于对观察到的行为(样本状态)进行分析。因此,技术特征D被对比文件直接公开。
技术特征E《直接公开》[p0018] “comparing the condition of the hair in the test sample to a control sample; and identifying the hair sample as damaged when the hair sample has dissolved in the test solution more rapidly than the control sample, or the hair sample appears soft and less rigid as compared to the control sample, or identifying the hair sample as suitable for further processing if the condition of the hair in the test solution is commensurate with the condition of the control sample.”对比文件明确描述了将测试样本的状况与对照样本(代表正常/健康状态)进行比较,并根据比较结果判断样本是“损伤的”(异常)还是“适合进一步处理”(正常)。这直接对应于将分析的行为信息与建模的正常行为进行比较,以确定行为是正常还是异常。因此,技术特征E被对比文件直接公开。
技术特征F《隐含公开》[p0082] “Hair samples identified as extremely damaged may not be suitable for use in subsequent analyte detection methods. In some embodiments, methods disclosed herein include requesting an additional hair sample from an individual when their hair sample has been identified as invalid for hair analyte analysis.”, [p0083] “Alternatively, the hair samples identified as damaged may be labeled or flagged as damaged and still analyzed in downstream analyte testing procedures.”对比文件指出,当识别出样本损伤(异常状况)时,可以采取相应措施,例如:将样本标记为无效、请求新的样本、或在后续分析程序中特别标记。本领域技术人员可以合理地推断,这些措施(如请求新样本、应用特殊清洗程序)是为了“矫正”因样本损伤可能导致的分析问题(如假阴性或假阳性),相当于触发了“执行者”(如采样人员、采用特定分析流程)来应对异常。因此,技术特征F被对比文件隐含公开。
技术特征G《隐含公开》[p0122] “...the hair sample can be washed with a non-swelling solvent (e.g., ethanol) prior to the assessing and/or determining steps.”, [p0155] “The ethanolic wash method presented herein... consists of three 30-min and two 60-min washes in 90% ethanol...”对比文件公开了对于被识别为损伤的头发样本,可以采用特定的清洗程序(如乙醇清洗法)来进行处理。这提供了用于辅助矫正因样本损伤(行为异常)所导致问题的具体技术。虽然对比文件未明确称之为“执行者”,但本领域技术人员能够理解,执行这些特定清洗方法的过程或实体,就是被“提供有技术”以辅助矫正异常的执行者。因此,技术特征G被对比文件隐含公开。
技术特征H《未公开》无相应内容。对比文件通过测量吸光度(如A380)等单一或少数指标来评估损伤,这是一种标量测量。虽然这可以视为一个“行为特征”,但对比文件没有公开将多个行为特征组合并“映射到n维空间中”以形成“行为向量”的概念。本领域技术人员无法从对比文件中毫无疑义地得出或合理推断出这种多维向量提取和映射的技术方案。因此,技术特征H未被对比文件公开。
技术特征I《未公开》无相应内容。对比文件仅涉及对单个头发样本(或与对照样本比较)的评估,未涉及对包含多个互连设备(如IoT设备)的整个“网络”进行建模。本领域技术人员无法从对比文件中得出为包含多个节点的“本地IoT网络”建模的技术启示。因此,技术特征I未被对比文件公开。
技术特征J《未公开》无相应内容。由于对比文件未公开为“本地IoT网络”建模(技术特征I),因此也就不存在基于节点行为信息“更新与所述本地IoT网络相关联的当前状态”的技术方案。因此,技术特征J未被对比文件公开。
技术特征K《未公开》无相应内容。对比文件仅处理头发样本本身,未涉及聚集与多个“IoT设备”相关联的属性(如设备类型、能力、状态等)。因此,技术特征K未被对比文件公开。
技术特征L《未公开》无相应内容。对比文件未涉及任何与设备间连接关系相关的“拓扑”构造。因此,技术特征L未被对比文件公开。
技术特征M《未公开》无相应内容。对比文件未涉及从“制造商”或“仓储库”获取与设备相关的“行为模型”。用于比较的“正常行为”基准是对照样本,而非从外部仓储库获取的模型。因此,技术特征M未被对比文件公开。
技术特征N《未公开》无相应内容。由于技术特征K、L、M均未被公开,因此对比文件不可能公开将这些元素组合以为网络建模的技术方案。因此,技术特征N未被对比文件公开。
技术特征O《隐含公开》[p0082] “Hair samples identified as extremely damaged may not be suitable for use in subsequent analyte detection methods. In some embodiments, methods disclosed herein include requesting an additional hair sample from an individual when their hair sample has been identified as invalid for hair analyte analysis.”, [p0115] “In some embodiments, the methods disclosed herein further comprise indicating the hair sample as unsuitable for determining if the analyte is present in the test solution when the hair sample has been identified as damaged.”对比文件指出,当样本被识别为损伤(异常)时,可以将其标记为“无效”或“不适合”进行分析,或者请求新的样本。本领域技术人员可以合理地推断,这种“标记”或“请求”行为相当于向负责后续处理或决策的实体(可以类比为“客户服务实体”)报告了异常情况。因此,技术特征O被对比文件隐含公开。
技术特征P《未公开》无相应内容。对比文件中识别的“异常”是头发样本的物理/化学损伤,这种损伤源于美容处理、环境因素等,与物联网环境中“潜在恶意攻击”的概念完全不同。本领域技术人员无法从对比文件中得出检测恶意攻击的技术启示。因此,技术特征P未被对比文件公开。
技术特征Q《隐含公开》[p0007] “However, hair damage occurs mostly in the form of physical and chemical changes as a result of bleaching, oxidative dyeing...”, [p0018] “identifying the hair sample as damaged...”对比文件公开的头发“损伤”状态,可以合理地理解为样本的一种“故障或异常工作状况”。在物联网设备健康监测的语境下,设备故障或异常工作状况是常见的监测目标。虽然领域不同,但“检测异常状况”这一抽象功能是相通的。因此,本领域技术人员有可能通过推理,将头发样本的损伤检测类比为物联网设备的故障检测。因此,技术特征Q被对比文件隐含公开。
技术特征R《隐含公开》[p0058] “assessing the condition of a keratinized structure sample”, [p0071] “The sample is then subjected to proteolytic or non-proteolytic digestion methods...”对比文件中的“头发样本”本身是提供其状态信息的来源。在测试过程中,样本的物理化学变化(如溶解、变软)被观察和测量。这可以隐含地理解为,样本自身包含了能展现其状态(行为)的“组件”(即其化学构成和物理结构)。虽然未明确描述为“被配置成观察”,但其作为信息源的功能是存在的。因此,技术特征R被对比文件隐含公开。
技术特征S《未公开》无相应内容。对比文件中的信息传递是通过人工操作或实验室仪器直接测量样本实现的,未描述样本(第二节点)包含一个“发射机”组件,主动将表示其行为特征的数据发送给另一个节点。因此,技术特征S未被对比文件公开。
技术特征T《未公开》无相应内容。对比文件未涉及任何形式的“网络”,也没有描述通过监视网络上传送的消息来获取行为信息。所有信息均直接来源于对样本本身的处理和分析。因此,技术特征T未被对比文件公开。
技术特征U《未公开》无相应内容。对比文件的判断基于测试样本与单一对照样本的比较,或与预设阈值(如A380>0.35)的比较。未公开涉及整个系统或网络“总状态模型”的概念,也未将个体行为与这种总体模型进行比较以辅助判断。因此,技术特征U未被对比文件公开。
技术特征V《未公开》无相应内容。对比文件未提及在确定行为正常(非异常)后,应用“机器学习”来更新用于未来比较的“设备行为模型”。其正常行为的基准(对照样本或阈值)是静态或预设的。因此,技术特征V未被对比文件公开。

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