Diseño de un sistema de monitoreo del comportamiento de vacas en tiempo real basado en redes de sensores inalámbricos y algoritmo de clustering de K-Means

Introduction: The present article is the product of the research whose code CS20.04, carried out during 2020. This work was supported by the Institute of Information Technology (IOIT), Vietnam Academy of Science and Technology (VAST). Problem: Animal monitoring is a significant problem in the agricultural sector. The primary purpose is to monitor the health of animals regularly. Consequently, animal welfare and product quality could be improved, leading to an improvement in profit. Cow behavior recognition system was considered as the right solution for cow monitoring. The requirements for this kind of system are economical, high performance, and real-time. Objective: The research objective is to design a real-time cow monitoring system based on wireless sensor networks and the K-means clustering algorithm. Methodology: A wireless sensor node was designed to measure the collar-mounted acceleration data using an accelerometer. Firstly, the collected data were classified into three classes based on the VeDBA (Vector of Dynamic Body Acceleration) feature using the K-means algorithm. Then, the thresholds for VeDBA in the previous step were used to classify new data. Results: Three behaviors (including feeding, lying, and standing) were classified in real-time with the accuracy of classification about 89%.   Conclusion: The proposed system could be adapted in monitoring cow in real-time, the behavior classification could be implemented on the microcontroller. The results confirmed the reliability of the proposed system. Originality: The behavior classification could be implemented on the microcontroller for the first time in monitoring cow. Limitations: Only three behaviors were classified in the experiment

Information Management in the Concurrent Design Process

Former achievements for integrated information management have concentrated on interoperability of applications like e.g. CAD, structural analysis or facility management, based on product models introducing additional application independent model layers (core models). In the last years it has become clear, that besides interoperability of autonomous applications, the concurrent processes of model instantiation and evolution have to be modeled, including the relationship to available project resources, persons, legal requirements and communication infrastructure. This paper discusses some basic concepts for an emerging methodology relating the fields of product modeling, project management and workflow systems by elaborating the concept of a process model, which gives a decomposition of the project goals into executable activities. Integrated information management systems should be related to process models to detect pending activities, deadlocks and alternatives of execution. According to the heterogeneous nature of project communication processes, a method for dynamic classification of ad-hoc activities is suggested, that complements predefined highlevel process definitions. In a brief outline of the system architecture, we show how sophisticated information management systems can be broadly made available by using conventional Internet technologies

Correct and Control Complex IoT Systems: Evaluation of a Classification for System Anomalies

In practice there are deficiencies in precise interteam communications about system anomalies to perform troubleshooting and postmortem analysis along different teams operating complex IoT systems. We evaluate the quality in use of an adaptation of IEEE Std. 1044-2009 with the objective to differentiate the handling of fault detection and fault reaction from handling of defect and its options for defect correction. We extended the scope of IEEE Std. 1044-2009 from anomalies related to software only to anomalies related to complex IoT systems. To evaluate the quality in use of our classification a study was conducted at Robert Bosch GmbH. We applied our adaptation to a postmortem analysis of an IoT solution and evaluated the quality in use by conducting interviews with three stakeholders. Our adaptation was effectively applied and interteam communications as well as iterative and inductive learning for product improvement were enhanced. Further training and practice are required.Comment: Submitted to QRS 2020 (IEEE Conference on Software Quality, Reliability and Security

What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective

Managing knowledge management tools: a systematic classification and comparison

Knowledge management (KM) is playing an important role in commercial and academic activities, and people are usually armed with effective KM tools for implementation. On one hand, KM tools can facilitate KM activities; however, on the other hand, with the “explosion” of KM tools development, people may feel confused about which to choose or which is more suitable. As a result, KM tools should be managed, so this paper aims at making a systematic classification and comparison research and proposes a KM tools selection strategy based on a point of view on knowledge lifecycle