Tele health utilizes information and communication mechanisms to convey medical information for providing clinical and educational assistances. It makes an effort to get the better of issues of health service delivery involving time factor, space and laborious terrains, validating cost-efficiency and finer ingress in both developed and developing countries. Tele health has been categorized into either real-time electronic communication, or store-and-forward communication. In recent years, a third-class has been perceived as remote healthcare monitoring or tele health, presuming data obtained via Internet of Things (IOT). Although, tele health data analytics and machine learning have been researched in great depth, there is a dearth of studies that entirely concentrate on the progress of ML-based techniques for tele health data analytics in the IoT healthcare sector. Motivated by this fact, in this work a method called, Weighted Bayesian and Polynomial Taylor Deep Network (WB-PTDN) is proposed to improve health prediction in a computationally efficient and accurate manner. First, the Independent Component Data Arrangement model is designed with the objective of normalizing the data obtained from the Physionet dataset. Next, with the normalized data as input, Weighted Bayesian Feature Extraction is applied to minimize the dimensionality involved and therefore extracting the relevant features for further health risk analysis. Finally, to obtain reliable predictions concerning tele health data analytics, First Order Polynomial Taylor DNN-based Feature Homogenization is proposed that with the aid of First Order Polynomial Taylor function updates the new results based on the result analysis of old values and therefore provides increased transparency in decision making. The comparison of proposed and existing methods indicates that the WB-PTDN method achieves higher accuracy, true positive rate and lesser response time for IoT based tele health data analytics than the traditional methods.
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在企业的经营活动过程中,存在着一项非常重要的组织功能——采购。随着全球经济一体化的不断发展,各生产企业均面临着日益剧烈的市场竞争压力。如何降低企业成本从而提高产品市场竞争力是各企业不得不面对的一个关键问题,而产品成本最主要构成就是原材料或外购零部件,企业需要对采购进行有效的管理以提高企业竞争力。 相似文献
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以灰色GM(1,1)和马尔柯夫理论为基础,提出基于灰色马尔柯夫模型的采购预测方法。首先利用灰色模型进行短期预测,再利用马尔可夫理论进行波动状态预测,最后得到采购量期望值。实例结果表明,灰色马尔柯夫模型预测精度较高,具有较好的应用价值,能为采购预测工作提供有用依据。 相似文献
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本文以集中供应链管理（EC_ISCM）软件开发项目为背景,通过分析工作流管理系统的设计思想和基本理论,重点研究了工作流技术与物流采购业务融合支持业务重组（BRP）,建立基于工作流的采购物流管理通用业务模型,对于具体采购物流管理系统的开发具有很好的实用价值． 相似文献
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异常事件可能导致供应链中断或订单延迟,由此形成的异常采购提前期(procurement lead time,PLT)往往比正常的PLT要长。为了应对异常状态,企业需要权衡成本和服务水平以制定最优的订货策略。较高水平的订货批量会降低订货次数,形成稳健的订货策略;较低水平的订货批量可以形成灵活的订货策略。本研究将PLTs相关性定义为异常与正常PLTs差异乘数项的均值,基于两个相关PLTs构建零售商库存决策的成本服务均衡模型,研究订货批量决策。研究结果表明,当周期服务水平较高时,PLTs相关性变化并不会影响企业的订货策略;当周期服务水平小于某一值时,PLTs相关性增大,企业倾向于较高的订货批量,从而形成稳健的订货策略。同时,PLT波动对订货批量影响存在多个服务水平阈值,在不同的服务水平范围内,企业可采取的最佳订货策略不同。这个发现与独立PLTs假设中,PLT波动对订货批量影响只有一个服务水平阈值有明显区别。随着PLT波动增大,企业会采取与独立PLTs条件下不同的对策。 相似文献
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降低成本是作为企业生存的关键因素之一,在企业发展中占据至关重要的位置。随着我国经济的快速发展,企业的生存成本越来越高,企业的管理者从任何可能的角度来降低各种成本。本文从采购设备的角度出发,引入动态规划模型来确定采购价格,从而提出设备采购策略,为相关企业在采购设备时提供参考。 相似文献
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考虑单产品多供应商和多运输业务采购决策问题.引入抵扣价值概念来处理采购量高于实际需求量的情况,分整运和零运两种情况研究了运输业务的选择对总成本、延期交货率、到货缺陷率等采购要素的影响,基于此提出了考虑运输的多供应商采购模型,并特别设计了编码和算子以便应用NSGA-Ⅱ遗传算法,最后利用算例分析了模型和算法的有效性. 相似文献
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研究了柔性契约机制下,中国外向型制造商在全球采购环节中的多阶段策略,以期能应对后危机时代更大的不确定性风险。提出了模糊随机动态规划这一新的研究模型,通过二叉树模型模拟汇率、蒙特卡罗技术模拟模糊随机变量,构建了求解此类规划的算法。对理论模型进行了算例仿真,仿真结果验证了算法的可行性,为中国外向型制造企业制定全球采购计划提供了更加科学的方法和依据。 相似文献
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The collaboration of vendor and buyer is one of the key factors for successful supply chain management. The most common strategy for a cooperative system is to propose an integrated replenishment plan. Almost all inventory models assume that setup cost is deterministic and is not subject to control. However, in many practical situations, setup cost can be reduced at an added investment. The paper assumes that setup cost can be reduced at an added investment and shortage is permitted during the lead time. This article relaxes the assumption that the demand of lead time is deterministic and is assumed to be a compound Poisson process. A model is derived to determine an optimal integrated inventory policy with controllable setup cost. The expected annual integrated total cost function is derived and a solution procedure is established to find out the optimal solution. Finally, a numerical example is provided to illustrate the solution procedure. 相似文献
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Kamalrulnizam Bin Abu Bakar Fatima Tul Zuhra Babangida Isyaku Fuad A. Ghaleb 《计算机、材料和连续体（英文）》2023,75(1):785-798
The Internet of Medical Things (IoMT) emerges with the vision of the Wireless Body Sensor Network (WBSN) to improve the health monitoring systems and has an enormous impact on the healthcare system for recognizing the levels of risk/severity factors (premature diagnosis, treatment, and supervision of chronic disease i.e., cancer) via wearable/electronic health sensor i.e., wireless endoscopic capsule. However, AI-assisted endoscopy plays a very significant role in the detection of gastric cancer. Convolutional Neural Network (CNN) has been widely used to diagnose gastric cancer based on various feature extraction models, consequently, limiting the identification and categorization performance in terms of cancerous stages and grades associated with each type of gastric cancer. This paper proposed an optimized AI-based approach to diagnose and assess the risk factor of gastric cancer based on its type, stage, and grade in the endoscopic images for smart healthcare applications. The proposed method is categorized into five phases such as image pre-processing, Four-Dimensional (4D) image conversion, image segmentation, K-Nearest Neighbour (K-NN) classification, and multi-grading and staging of image intensities. Moreover, the performance of the proposed method has experimented on two different datasets consisting of color and black and white endoscopic images. The simulation results verified that the proposed approach is capable of perceiving gastric cancer with 88.09% sensitivity, 95.77% specificity, and 96.55% overall accuracy respectively. 相似文献
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检测设备是产品质量优劣的判断工具,而检测设备的量值是由相应的计量装置来保证的。该文探讨将物联网概念应用在自行车检测设备的计量模式中,可将传统的周期计量模式转变为动态按需计量模式,又为检测设备动态计量提供了解决的思路。 相似文献
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泛在电力物联网的建设主要是将信息化和人工智能等新技术、新理念应用于企业发展进程中,以提高电力企业的技术水平,同时这也是服务于国家战略需要,符合推动互联网、大数据、人工智能和制造业深度融合的战略要求,其对推动我国的科技进步、产业升级和提高人民生活水平具有重要意义。对泛在电力物联网的提出背景、建设目标和意义等进行介绍;讨论各界对泛在电力物联网的态度和相应措施;对泛在电力物联网建设的技术支持进行分析;举例说明泛在电力物联网在当下的典型应用;最后指出泛在电力物联网发展过程中可能遇到的问题。 相似文献
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物联网时代的智慧型物品探析 总被引：3，自引：13，他引：3
阐述了以物与物之间交流为标志的物联网将是一种无处不在的泛在网络,其目的是使地球上的"物"变得更加智慧。针对物联网中的物是具有感知和交流功能的智慧物之特点,分析了用智慧型物品的术语来表述物联网中的人造物可以体现与传统智能产品的差异和物联网特征,提出了智慧型物品的智慧主要来自于网络系统各类智慧解决方案以及智慧型物品的设计策略和理念。 相似文献
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Sohail Abbas Zahid Raza Nida Siddiqui Faheem Khan Taegkeun Whangbo 《计算机、材料和连续体（英文）》2022,71(2):2683-2696
Wireless Sensor Network (WSN) is considered to be one of the fundamental technologies employed in the Internet of things (IoT); hence, enabling diverse applications for carrying out real-time observations. Robot navigation in such networks was the main motivation for the introduction of the concept of landmarks. A robot can identify its own location by sending signals to obtain the distances between itself and the landmarks. Considering networks to be a type of graph, this concept was redefined as metric dimension of a graph which is the minimum number of nodes needed to identify all the nodes of the graph. This idea was extended to the concept of edge metric dimension of a graph G, which is the minimum number of nodes needed in a graph to uniquely identify each edge of the network. Regular plane networks can be easily constructed by repeating regular polygons. This design is of extreme importance as it yields high overall performance; hence, it can be used in various networking and IoT domains. The honeycomb and the hexagonal networks are two such popular mesh-derived parallel networks. In this paper, it is proved that the minimum landmarks required for the honeycomb network HC(n), and the hexagonal network HX(n) are 3 and 6 respectively. The bounds for the landmarks required for the hex-derived network HDN1(n) are also proposed. 相似文献
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