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摘要： In the original publication of the article, Algorithm1 titled "Iterative Principal Component Analysis method for Breast Cancer Prediction" was missed and Figure 1 was duplicated. The Algorithm1 was inserted prior to Algorithm 2. The duplicate figure was removed. The original article has been corrected. © 2021, International Federation for Medical and Biological Engineering.

关键词： PLS-DA   LDA   SIMCA   Authentication   Food control   Breed purity   Feeding regime   FATTY-ACIDS   MEAT   IDENTIFICATION   QUALITY   SYSTEM   COLOR   HAM  

摘要： The potential of Near Infrared Spectroscopy combining different spectral treatments and classification models was assessed for the classification of individual pre-sliced Iberian dry-cured loin packaged under modified atmosphere packaging (MAP) into three official commercial categories (which involve the breed purity and production system) according to the current Iberian Quality Standard (Black, Red and White) and for the assignment to the shelf-life time (0, 4, 8 and 12 months). External validation results provided acceptable results, with up to 100% of samples correctly assigned to Black and White official commercial category and into all storage times. Actually the 100% assignments were obtained using more than one approach (SIMCA and LDA for commercial categories and PLS-DA, SIMCA and LDA for storage times). These results might contribute to support the on-line control of authenticity of official commercial category and to facilitate the monitoring of the quality of pre-package dry-cured products throughout the shelf-life prediction.

关键词： 免疫检验   质量控制   检验结果   重要性  

摘要： 目的探讨临床免疫检验中质量控制的作用。方法选取2018年7月至2020年2月恩施市中心医院检验科收治的需要接受免疫检验患者94例,根据检验方式的不同将其分为两组,常规免疫检验方法作为对照组(47例),研究组(47例)应用免疫检验质量控制。比较两组检验结果、临床指标效果。结果研究组血清C肽(C-P指数)、血清胰岛素(INS)、癌胚抗原(CEA)、糖类抗原CA125(CA125)、糖类抗原CA199(CA199)、胃癌抗原(CA724)、血清胰岛素抗体(IAb)、甲胎球蛋白(AFP)低于对照组,差异有统计学意义(P<0.05);研究组总有效率高于对照组,差异有统计学意义(P<0.05)。结论临床免疫检验中,质量控制可以体现出其总有效率,临床上应当进一步推广应用。

关键词： ICP OES   Machine learning   Sample digestion   SHAP   Used engine oil   XGBoost   TRACE-ELEMENTS   LUBRICATING OILS   INFRARED-SPECTROSCOPY   WEAR METALS   EXTRACTION   DEGRADATION   PERFORMANCE   OXIDATION   SULFUR   SIZE  

摘要： The analysis of used engine oils from industrial engines enables the study of engine wear and oil degradation in order to evaluate the necessity of oil changes. As the matrix composition of an engine oil strongly depends on its intended application, meaningful diagnostic oil analyses bear considerable challenges. Owing to the broad spectrum of available oil matrices, we have evaluated the applicability of using an internal standard and/or preceding sample digestion for elemental analysis of used engine oils via inductively coupled plasma optical emission spectroscopy (ICP OES). Elements originating from both wear particles and additives as well as particle size influence could be clearly recognized by their distinct digestion behaviour. While a precise determination of most wear elements can be achieved in oily matrix, the measurement of additives is performed preferably after sample digestion. Considering a dataset of physicochemical parameters and elemental composition for several hundred used engine oils, we have further investigated the feasibility of predicting the identity and overall condition of an unknown combustion engine using the machine learning system XGBoost. A maximum accuracy of 89.6% in predicting the engine type was achieved, a mean error of less than 10% of the observed timeframe in predicting the oil running time and even less than 4% for the total engine running time, based purely on common oil check data. Furthermore, obstacles and possibilities to improve the performance of the machine learning models were analysed and the factors that enabled the prediction were explored with SHapley Additive exPlanation (SHAP). Our results demonstrate that both the identification of an unknown engine as well as a lifetime assessment can be performed for a first estimation of the actual sample without requiring meticulous documentation.

关键词： Detection   Edge devices   Interference   Jamming   Machine learning   Security   WSNs and ZigBee   INTRUSION DETECTION SYSTEMS   ALGORITHMS   ATTACKS  

摘要： Despite Wireless Sensor Networks (WSNs) significantly developing over the past decade, these networks, like most wireless networks, remain susceptible to malicious interference and spectrum coexistence. Other vulnerabilities arise as WSN applications adopt open standards and typically resource and energy-constrained commercial-off-the-shelf equipment. Deployments include safety-critical applications such as the internet of things, medical, aerospace and space and deep-sea exploration. To manage safety and privacy requirements across such a diverse wireless landscape, security on wireless edge devices needs improvement while maintaining low complexity. This paper improves wireless edge device security by developing a novel intelligent interference diagnostic framework. Received in-phase (I) and quadrature-phase (Q) samples are exclusively utilized to detect modern, subtle and traditional crude jamming attacks. This I/Q sample utilization inherently enables decentralized decision-making, where the low-order features were extracted in a previous study focused on classifying typical 2.4-2.5 GHz wireless signals. The associated optimal intelligent models are leveraged as the foundation for this paper's work. Initially, Matlab Monte Carlo simulations investigate the ideal case, which incorporates no hardware limitations, identifies the required data type of signal interactions and motivates a hardware investigation. Software-defined radios (SDRs) collect the required live over-the air I/Q data and transmit matched signal (ZigBee) and continuous-wave interference in developed ZigBee wireless testbeds. Low complexity supervised machine learning models are developed based exclusively on the low-order features and achieve an average accuracy among the developed models above 98%. The designed methodology involves examining ZigBee over-the-air data for artificial jamming and SDR jamming of ZigBee signals transmitted from SDR and commercial (XBee) sources. This approach expands

关键词： 临床妇科   常规检验   重要作用  

摘要： 使用临床妇科常规检验方式来进行妇科病症检测,并对检测效果和准确程度进行深入的研究与探讨。方法:选择符合要求的观察研究对象100例进行研究。所有加入到本次调查当中来的病例都应当符合相关的妇科疾病检查标准,医学研究者将对这100例患者的阴道分泌物进行详细的检查,并对检查结果进行细致的分析,所有参与本次调查研究的观察对象,均选自2018年7月至2019年7月这一时间段内。结果:通过临床妇科常规检验后,有关医护人员发现这些患者均患有妇科类疾病,且病症类型有所不同。结论:使用临床常规检测方式来给患者进行病情诊断,这对及时发现相应病症,让医护人员按照诊断结果进行进一步的治疗和病情控制是能够起到正面引导的。这种病症检查手段有利于医护人员采取必要措施让患者进行身体康复,因此临床妇科常规检验值得进行进一步的推广与使用。

关键词： 质量控制   临床检验   免疫检验   检验作用  

摘要： 分析质量控制用于临床免疫检验中的作用。方法:从2019年1月-2020年12月期间前往本院接受诊治的乙肝患者中选择120例研究,根据数字简表法将其随机分为实验组与对照组,每组分别60例。对照组实施常规的免疫检查,实验组则在此基础上实施免疫检测,最终对比干预效果。结果:实验组检测假阳性的人数为2例,假阴性人数为1例。对照组检测假阳性人数为10例,假阴性人数为9例。对比两组数据结果显示,P<0.05。实验组免疫球蛋白检查结果显著优于对照组,P<0.05。结论:对临床免疫实施质量控制措施,可以显著改善检测准确率,具有较高的应用价值。

关键词： 质量监督   纺织品   连续   控制  

摘要： 从质量监督的范围、质量监督内容和质量监督员任命等方面阐述了质量监督在纺织品检验检测中的作用。作为检验检测机构确保质量的一种行为,需要从“人、机、料、法、环、测”等六个要素对纺织品检验检测进行监督,保证实验室长期连续稳定地符合检验检测认定评审准则要求,确保结果数据真实、客观、准确、有效。

关键词： 药品检验过程   质量控制   作用  

摘要： 探讨药品检验过程中质量控制的必要性和有效措施。方法:从被测药物中随机选择240种药物,并根据药物检测时间分为对照组和研究组,每组120份。对照组药物采用常规检查方法,研究组采用质量控制方法观察和比较两组药物的测定结果(原料和制剂的含量均在相关标准范围内)并合格。结果:经统计学分析,两组药物的测定结果无统计学差异(P>0.05)。与对照组相比,研究组的考试通过率明显更高。两组数据的比较表明,差异具有统计学意义(P<0.05)。结论:药品检验过程中必须进行质量控制,质量控制不仅可以有效地保证药品质量,还可以在一定程度上提高药品合格率。

关键词： 动物   检验检疫   食品安全  

摘要： 近年来,人们对肉类食品的需求不断提高,这也对肉类食品的品质提出了更高的要求,在动物饲养、屠宰、加工、运输到进入市场的各个环节,都需要进行更高水平的要求,以此来确保进入市场的肉类食品能够安全,能够健康,保障消费者的身体健康,因此加强动物的检验检疫工作是至关重要的,本文就针对动物检验检疫在食品安全中的作用展开了一定的讨论研究。