bluuebunny/crossref_metadata_2025 huggingface dataset:
THE OPPORTUNITY OF DEVELOPING RURAL WELLBEING TOURISM IN PUGLIA REGION, ITALY IN THE TIME OF COVID-19 PANDEMIC
Authors: Aluculesei Alina-Cerasela , Avram Daniel
Published: February 2021

The tourism industry is facing nowadays a wide range of issues caused by the COVID-19 pandemic or accentuated by it. The dramatic decline in tourist flows in every destination forced stakeholders to rethink the actual model of business and to adapt to the new reality. The need for social distancing and the fear of tourists to visit crowded places prepared the field for more sustainable tourist activity, based on green products and services. In this context, new and innovative products like rural wellness tourism can take momentum and offer the visitors the opportunity of spending the free time in nature, in less polluted areas and with a higher impact of health.

Italy is one of the most representative tourist destinations worldwide, with a wide range of attractions that make both urban and rural spots to be visited annually by millions of tourists. Tourism also supports the local economy and helps local communities from less developed regions to diversify their sources of income, as is the case of Puglia region, known for its agricultural potential. Puglia is one of the Italian regions where local authorities encourage the development of tourist activities, especially those specific to the ecotourism niche, as a real alternative to agriculture. In the current context of the COVID-19 pandemic, ecotourism can represent the solution for a faster economic recovery of the southern region of the country that was dramatically affected by the lockdown imposed by the authorities in the first part of 2020. Based on the wellness tradition from the region and the international reputation of the Termes from this area, Puglia region can develop the concept of rural wellbeing tourism and promote a more sustainable tourist model.

The present paper analyses the potential of Puglia region to introduce in its offer rural wellbeing tourism packages taking into account the profile of a spa and thermal center in the area in terms of structure and business model. The results were obtained by applying a structured questionnaire in one of the most representative thermal units in the region and the answers were interpreted using Qualitative Content Analysis. The results show that Puglia region could thrive the concept of rural wellbeing tourism and adapt it to the particularities of the area. Adopting such an innovative tourist concept that is based on a sustainable way to explore natural resources would have a significant impact on Italian tourism by creating a new trend among tourists. In this regard, the guests will have another opportunity to spend their holidays more sustainably, with a considerably lower impact on the environment.
política do esporte e a construção do estádio Mineirão
Authors: Lott Wanessa Pires
Published: February 2021

O presente trabalho tem o objetivo de apresentar a construção do Estádio Magalhães Pinto, popularmente conhecido como Mineirão, localizado em Belo Horizonte, Minas Gerais, Brasil. Destaca-se neste estudo o contexto da política do esporte nacional como fator relevante no processo de edificação do estádio. Assim, como uma partida de futebol, o artigo será apresentado em dois tempos, além da ‘concentração’, com intuito de uma breve apresentação sobre o tema e do ‘apito final’ para as últimas considerações. Primeiramente, será feito um panorama das políticas públicas nacionais de esporte, com destaque para a valorização do futebol no estado de Minas Gerais e em seguida o processo de construção e inauguração do Mineirão. A pesquisa, para além da bibliografia acadêmica pertinente, utilizou jornais e revistas de relevância nacional.
Quando se mistura futebol e política
Authors: Tobar Felipe Bertazzo , Coelho Ilanil , Gusso Luana de Carvalho Silva
Published: February 2021

O artigo tem por objetivo discutir a relação entre futebol e política a partir do estudo do processo de tombamento da sede social do America Football Club (RJ). Mediante pesquisa sobre a história do clube, análise de reportagens da imprensa e do estudo da legislação, discutem-se os atos de tombamento da sede social, realizados no início da década de 2010, pela lavra discricionária do poder executivo municipal. Com base na teoria geral dos campos sociais de Bourdieu, buscou-se responder como e por que agentes políticos, provocados por dirigentes futebolísticos, apropriaram-se deste instrumento jurídico para, num primeiro momento proteger a edificação e, posteriormente, por outro decreto regulamentador, determinar o seu destombamento.  Deste modo, possibilitou-se inferir ser o presente caso um inequívoco exemplo sobre os usos e abusos políticos do instituto do tombamento que, desvirtuado, não respondeu ao seu primordial interesse público, mas a interesses particulares.
ON SOME POLITICAL SCIENCE ASPECTS OF THE 2020 CONSTITUTIONAL REFORM IN THE RUSSIAN FEDERATION
Authors: РУМЯНЦЕВ О.Г.
Published: February 2021

До реформы-2020 Конституция, при известных изъянах содержания и процедуры принятия, воспринималась многими как основа консенсуса и дальнейшего развития. Конституционная реформа изменила текст Конституции на треть, а дух ее и общественное восприятие – почти полностью. Требуется анализ состояния и перспектив переформатирования отношений государства и общества, как и соответствия предпринятого замаха нарастающим вызовам и явно усиливающемуся общественному запросу социально-политического развития России как обновленной передовой нации. С принятием новой редакции Конституции вряд ли исчезнут причины объективного обострения противоречий, острой политической дифференциации в обществе и субъективные трудности в управлении процессом нарастающего размежевания. Потенциал консенсуса середины десятилетия подходит к концу. Нужны глубинные стимулы к новой и долгосрочной консолидации общества и государства.
EUROPEAN UNION ENERGY SECURITY: BETWEEN RUSSIA AND THE USA
Authors: ХЛОПОВ О.А.
Published: February 2021

В статье рассматриваются проблемы энергетической политики Европейского Союза в контексте усиления энергетического диалога с США и противоречивых отношений с Россией. Несмотря на разногласия – ЕС и США имеют сильные стимулы для совместной работы, которые позволяют расширять энергетическое сотрудничество в реализации программ возобновляемых источников энергии. Расширение диверсификации поставок, экспорт сжиженного газа в Европу, энергоэффективность стали главным компонентами американской внешней политики и энергетической безопасности ЕС. Реализация этих проектов ведет к столкновениям интересов России на европейских рынках, которая в ближайшее время будет иметь сильную конкуренцию со стороны экспортного газа из США и увеличения объемов энергии из возобновляемых источников энергии в странах ЕС.
The Function and Perception of Urban Ecosystem Services in the Society
Authors: Edlund Fredrik
Published: February 2021

The urban development that is now taking place globally has led to the most extensive permanent land use that has caused ecosystems to be destroyed and the depletion of natural resources. Today, about 50% of the world’s population lives in urbanized cities and by 2030 it is estimated to be about 70%. The fact that we gather in larger numbers in cities means that we transport large volumes of resources to these areas, which gives rise to waste and emissions, which places a burden on the neighboring environment to the it’s limits. This leads to problems for both human health and society’s economy, which is because the ecosystems that help us, collapse. To counter this, a better urban planning is required which includes the environment in society as ecosystem services. The problem with ecosystem services is that they do not have a commercial value, which makes it difficult to implement since they do not indicate any economic gain. Therefore, it is necessary to increase knowledge about how they contribute so that they can be correlated to how they contribute to society from three aspects: economic, social, environmental.
Immigration and Social Aspects of Sustainable Development. The Case of Germany
Authors: Rydzewski Paweł
Published: February 2021

The aim of the article is to show the relationship between immigration and the social aspect of sustainable development. Data from the German General Social Survey (ALLBUS) study conducted in 2016 on a sample of 3490 respondents (residents of Germany) was used. Research suggests that this relationship is negative: mass immigration from culturally foreign countries and social environments can significantly reduce the quality of life of residents in developed societies. This manifests in opinions about the need to limit or stop immigration. The case of Germany can probably be generalized to other developed countries, especially from the European Union.
Achieving Sustainable Competitive Advantage Through Intellectual Capital and Corporate Character: The Mediating Role of Innovation
Authors: Xiao Huan , Yu Dengke
Published: February 2021

This study aims to discuss the impacts of intellectual capital and corporate character on sustainable competitive advantage.
The structural equation model is used to analyze the relationships between intellectual capital, corporate character and sustainable competitive advantage, which are mediated by technological innovation and business model innovation, based on a survey of 377 observations in China.
The empirical results indicate that the intellectual capital and corporate character are as the doors that enterprises can open to acquire technological innovation and business model innovation, which are beneficial to achieving and maintaining sustainable competitive advantage. The findings provide some implications for entrepreneurs that their enterprises should focus on the coordination and balance of intellectual capital and corporate character for better achieving the perfect integration of cost leading strategy and differentiation strategy on the basis of mixing technological innovation and business model innovation together. Such strategy helps enterprises to realize sustained growth.
This study provides scholars a new binary perspective to explore the source of sustainable competitive advantage.
Ethics of Sustainable Development from the View of A. Badiou’s Critique of Contemporary Ethics
Authors: Papuziński Andrzej
Published: February 2021

The main problem of that article is effectiveness / ineffectiveness of an axiological system of the sustainable development as the base of a program of activities taken in individual and social-political scale. The problem was presented from the view of Alain Badiou’s ethics, which is a trial of overcoming weaknesses of the contemporary ethics of the mainstream, especially very low effectiveness of the ethics in the sphere of social practice. For developing the title problem there was applied the critique of contemporary ethics as the ethics of consensus, conducted by Badiou. Established research prospect has a limited application. It allows exclusively and only for drawing a conclusions in the matter of possible usability of the ethics of sustainable development in the activities leading to the change of dominant stereotypes of thinking and standards of conduct nowadays. From the point of view of Badiou’s ethics this is the first, but necessary step on the way to answer a following question – does the ethic of sustainable development have actual causative power and is it effective in initiating and performing social changes?
Does Appearance of the Migrants Change Citizens Perception of the Public Space? Case Study of Disturbed Sustainability, Belgrade, Serbia
Authors: Hristić Nataša Danilović , Stefanović Nebojša
Published: February 2021

The migrant crisis that hit Europe in 2015 established Belgrade as one of transit cities on the route along which they travel to the final destination. A large number of migrants, no matter of reason for leaving homeland (war, economy, climate change consequences), mostly men travelling alone, prefer to stay in the central urban parks or squares. The result was change of personal feeling of safety of citizens and intensive monitoring by local police, but some other examples gave us a different focus, when the spontaneously formed refugee camp, with tents set up in parks, became a temporary assistance centre and meeting point for citizens and refugees.
Consumption and Sustainable Development: Ethical Aspects
Authors: Miczyńska-Kowalska Maria
Published: February 2021

Economic growth, excessive consumption and the consequent growing exploitation of natural resources pose the risk of a global ecological disaster. Therefore, it is vital to create a new consumer awareness concerned about the natural environment. This paper describes the issue of sustainable consumption in the context of sustainable development. It has been assumed that the increasing popularity of ecological awareness, plays the key role in the implementation of the objectives of sustainable consumption and sustainable development. The aim of this paper is to explain mechanisms responsible for the increasing role of consumption in the modern world and to draw attention to the need to raise the ecological awareness of consumers. The paper uses the analytic-synthetic method.
Sustainable Habitat as the Main Factor of Urbanization Development: 19th-20th Centuries
Authors: Aghasalim Azizov
Published: February 2021

The goals set in this article are to reveal the state of urbanized systems resulting from accelerated globalization, to analyze the facts of deteriorating environmental conditions and depletion of natural resources and tendencies of formation of residential territories with the condition for the organization of sustainable habitat.
Moreover, for the first time, discusses the development of residential and industrial zones in terms of the formation of the urban planning framework of the residential and industrial environment. The novelty of the problems considered in the article consists of the differentiated approach to the policy of forming a sustainable habitat based on the town planning framework. The characteristics, directions and design of urban planning frameworks in the architectural and planning structure of various cities, as well as regions consider. The result of the study was a thorough analysis of the master plans of the of various European and American cities, including Azerbaijan.
A Comprehensive Approach: Inclusive, Smart and Green Urban Development
Authors: Przywojska Justyna , Podgórniak-Krzykacz Aldona
Published: February 2021

The subject literature provides knowledge about various contemporary concepts of urban development, emphasizing a variety of goals and priorities of this process. Although sustainability should be a key objective of development policy, the methods of achieving it seem to be diverse. As a result, there are many theories describing development processes on a local scale, but there are no scientific attempts to summarise them or to comprehensively evaluate them. In the presented article such an attempt was initiated – the evolution of the concept of sustainable development in the context of transformation of the role of man in socio-economic and political processes from homo-oeconomicus to homo cooperativus was outlined and the assumptions of contemporary concepts of urban development (smart city, eco city and compact city) were identified and evaluated in terms of their cohesion and implementation of sustainable development principles. On this basis, a conceptual framework for an inclusive urban development model was defined, considering their key values in a synergic way.
Reconsidering Land System Changes in Borderlands: Insights from the China-ASEAN Borderland
Authors: Hua Xiaobo , Kono Yasuyuki
Published: February 2021

This study contributes to the literature on how to explicitly describe, track, and interpret the structure and dynamics of land systems in borderlands. The shift in land system science analytics from place-based toward larger-scale analysis of interactions and connections in a globalized context provides an opportunity to synthesize the knowledge about borderlands. This paper argues that studies on land system changes in borderlands need to thoroughly link the features of borderland regions with multiple interactions – on either or both sides of a border – rather than simply focusing on shifts within closed national boundaries. Furthermore, this paper provides important insights that can advance existing approaches to track and interpret changes in the land systems of borderlands.
Optimalisasi Bhabinkamtibmas Dalam Rangka Harkamtibmas Di Wilayah Hukum Polres Palu
Authors: Maisa Maisa , Ambo Irmawati
Published: February 2021

Penelitian ini membahas, pertama menganalisa optimalisasi kinerja Bhabinkamtibmas dalam Harkamtibmas di Kota Palu. Kedua, mengetahui dan menganalisa faktor pendukung dan penghambat apa saja yang mempengaruhi optimalisasi kinerja Bhabinkamtibmas dalam Harkamtibmas di kota palu. Penelitian ini menggunakan tipe penelitian hukum normatif dan Penelitian hukum empiris. Hasil penelitian, pertama kebedaraaan bhabinkamtibmas di kelurahan sudah dirasakan manfaatnya oleh masyarakat dan  program-program yang telah dilaksanakan oleh bhabinkamtibmas mendapat dukungan dari masyarakat tetapi masih ada beberapa tindak pidana yang terjadi, hal ini menunjukkan perlu   pelaksanakan tugas bhabinkamtibmas belum dioptimalkan, kedua faktor pendukung yaitu adanya dukungan dari pemerintah kota Palu dan partisipasi masyarakat menjaga lingkungannya, faktor penghambat yaitu tingkat pendidikan rata-rata SMA, sarana dan prasarana yang masih sangat minim, kurangnya pelatihan bagi bhabinkamtibmas, penempatan yang jauh dari tempat tinggal, serta belum adanya rumah Bhabin di kelurahan. Rekomendasi Penelitian mengoptimalkan kinerja Bhabinkamtibmas dalam hal perekrutannya berpendidikan S1, dilaksanakan pelatihan IHT/pendidikan khususnya di bidang bhabinkamtibmas dan Pemenuhan Sarana dan prasana untuk menunjang tugas Bhabin seperti rumah kantor bhabinkamtibmas di kelurahan, alat komputer/laptop serta camera, serta penugasan Bhabinkamtibmas seusi kedekatan tempat dinggalnya dan Bhabin melaksanakan tugas rangkap
Efektivitas Proses Pendaftaran Tanah Hak Milik
Authors: Nurmiati Nurmiati , Rahman Sufirman , Yunus Ahyuni
Published: February 2021

Penelitian ini bertujuan untuk mengetahui efektivitas proses pendaftaran tanah hak milik dan faktor-faktor yang mempengaruhi efektivitas pendaftaran tanah hak milik di Kantor Pertanahan Kota Makassar. Populasi penelitian ini adalah semua pegawai Kantor Pertanahan Kota Makassar yang akan diwawancarai dan masyarakat sebagai responden pada Kantor Pertanahan Kota Makassar. Hasil penelitian menunjukkan bahwa pelaksanaan peraturan pemerintah Nomor 24 tahun 1997 belum sepenuhnya efektif akibat dari pengaruh substansi hukum, struktur hukum, budaya hukum, kesadaran hukum masyarakat dan sarana/prasarana. Untuk itu diperlukan adanya penyuluhansubstansi hukum guna meningkatkan kesadaran hukum masyarakat tentang pendaftaran tanah, pembentukan budaya hukum, serta pembenahan secara prioritas sarana/prasarana sesuai dengan kemampuan anggaran yang tersedia pada Kantor Pertanahan Kota Makassar. Dalam rangka keefektifan pelaksanaan Peraturan Pemerintah Nomor 24 Tahun 1997 tentang Pendafatran Tanah, diharapkan kantor pertanahan untuk lebih sering mengadakan penyuluhan ke desa/kelurahan secara menyeluruh guna meningkatkan kesadaran hukum masyarakat tentang pendafatran tanah, agar masyarakat lebih memahami akan pentingnya pendaftaran tanah. Bagi kantor pertanahan, perlu meningkatkan sumber daya manusia dan komputer, jaringan internet serta perangkat lainnya dilakukan secara teliti dan cermat dimasa depan agar lebih meningkatkan pelayanan dan keahlian.

This research aims to know the effectiveness of land registration process of proprietary rights and factors that affect the effectiveness of land registration of property rights in the land Office of Makassar. The population of this research is all employees of the land office of Makassar that will be interviewed and the community as respondents in the land office of Makassar.The results showed that the implementation of government Regulation number 24 year 1997 has not been fully effective as a result of the influence of legal substance, legal structure, legal culture, public law awareness and facilities/infrastructure. Therefore, there is a need for legal counseling to increase public law awareness about land registration, the establishment of legal culture, and the prioritization of facilities/infrastructure in accordance with the budget capability available in the Land Office of Makassar. In the framework of the effectiveness of government Regulation number 24 year 1997 on the implementation of the land, it is expected that land office to more often conduct counseling to the village/Kelurahan thoroughly to increase public awareness about the implementation of the land, so that the community better understand the importance of land registration. For land offices, need to improve human resources and computers, Internet network and other devices are done carefully and carefully in the future to further improve service and expertise.
Coronavirus (COVID-19) Pandemic in Indonesia: Cases Overview and Daily Data Time Series using Naïve Forecast Method
Authors: Kirana Annisa Puspa , Bhawiyuga Adhitya
Published: February 2021

At the end of December 2019, the virus emerges from Wuhan, China, and resulted in a severe outbreak in many cities in China and expanding globally, including Indonesia. Indonesia is the fourth most populated country globally. As of February 2021, Indonesia in the first rank of positive cases of COVID-19 in Southeast Asia, number 4 in Asia, and number 19 in the world. Our paper aims to provide detailed reporting and analysis of the COVID-19 case overview and forecasting that have hit Indonesia. Our time-series dataset from March 2020 to January 2021. Summary of cases studied included the number of positive cases and deaths due to COVID-19 on a daily or monthly basis. We use time series and forecasting analysis using the Naïve Forecast method.  The prediction is daily case prediction for six months starting from February 1, 2021, to June 30, 2021, using active cases daily COVID-19 data in all provinces in Indonesia. The highest monthly average case prediction is in June, which is 35,662 cases. Our COVID-19 prediction study has a mean absolute percentage error (MAPE) score of 15.85%.
Development of a Low-Cost and Effisient ECG devices with IIR Digital Filter Design
Authors: Rachman Rizki Aulia , Wisana I Dewa Gede Hari , Nugraha Priyambada Cahya
Published: February 2021

Measurement of biosignals such as electrocardiograph has the interpretation of noise from other signals. The noise can interfere with the measurement of the heart signal and make the measurement inaccurate, so the purpose of this study is to make a 6-Lead Electrocardiogram module with an Arduino-Based Digital Filter. By using a digital filter. The contribution of this research is the use of digital filters to eliminate noise in electrocardiograph signals. This research uses Infinite Impulse Filter digital filters such as Butterworth, Chebyshev I, Chebyshev II, and Elliptic in order 2, 4, 6, 8, and 10. The study was conducted by providing input from the Function Generator on Arduino which has been applied digital filters with Frequency with 0.5Hz – 100Hz cut-off. The instrument is compared with a factory electrocardiograph. Filter measurements using 460 input data. Butterworth filter with the greatest emphasis on order 8 frequency 0.5Hz produces an emphasis of -5.74298158 dB and a frequency of 100Hz produces an emphasis of -5.93529424 dB. The Chebyshev I filter has the greatest emphasis on order 6 frequency 0.5Hz producing an emphasis of -3.27104076 dB and on order 8 frequency 100Hz producing an emphasis of -5.08730424 dB. Chebyshev II filter the biggest emphasis on the order of frequency 0.5Hz produces a suppression of -44,66011104 dB and 80Hz frequency produces a suppression of -37,3653957 dB. Elliptic filters the greatest emphasis on order 6 frequency 0.5Hz produces an emphasis on -1.55429354 dB and 100Hz frequency on order 8 produces an emphasis on -2.2849115 dB. The results showed that what was appropriate with the cut-off frequency was the Butterworth order 8 filter which was suitable for the application of the Electrocardiograph signal filter because it had bandwidth that suppressed the signal outside the cut-off frequency. The results of this study can be implemented on a 6-Lead ECG module to eliminate noise or interference when tapping ECG signals.
Design of Vital Sign Monitor with ECG, BPM, and Respiration Rate Parameters
Authors: Aditya Mahendra Oka Gede , Pudji Andjar
Published: February 2021

Vital sign monitor is a device used to monitor a patient's vital sign, in the form of a heartbeat, pulse, blood pressure, temperature of the heart's pulse form continuously. Condition monitoring in patients is needed so that paramedics know the development of the condition of inpatients who are experiencing a critical period. Electrocardiogram (ECG) is a physiological signal produced by the electrical activity of the heart. Recording heart activity can be used to analyze how the characteristics of the heart. By obtaining respiration from outpatient electrocardiography, which is increasingly being used clinically to practice to detect and characterize the abnormal occurrence of heart electrical behavior during normal daily activities. The purpose of this study is to determine that the value of the Repiration Rate is taken from ECG signals because of its solidity. At the peak of the R ECG it has several respiratory signals such as signals in fluctuations. An ECG can be used to determine breathing numbers. This module utilizes leads ECG signals to 1 lead, namely lead 2, respiration rate taken from the ECG, BPM in humans displayed on a TFT LCD. This research module utilizes the use of filters to obtain ECG signals, and respiration rates to display the results on a TFT LCD. This module has the highest error value of 0.01% compared to the Phantom EKG tool. So this module can be used for the diagnosis process.ECG, Respiration Rate, Filter
Central Monitor Based on Personal Computer Design with SpO2 and Body Temperature Parameters Using Wireless Xbee Pro
Authors: I KOMANG YOGI MAHARDIKA  , Bambang Guruh Irianto  , Torib Hamzah  , Misra Shubhrojit
Published: February 2021

Central patient monitor that is not real-time and continues will cause inaccuracies monitoring results and also sending data that is still using cable will cause limited distance. The purpose of this research is to design a central monitoring based personal computer via Xbee Pro. The contribution of this research is,  the system works in real-time and continues, more parameters, using wireless, longer transmission distances. So that monitoring can be done in real-time and continue via wireless with more distance, then the wireless system uses the Xbee Pro module which has larger output power and uses the same number of wireless modules between transmitter and receiver. Body temperature was measured using the LM35 sensor and oxygen saturation in the blood was measured using the MAX30100 sensor. Data is sent using Xbee Pro and displayed on a personal computer. At the distance of receiving data approximately 25 meters with a wall divider, obtained results of smooth monitoring without any loss of data. The results showed that the average SpO2 error value was 0.34% in module 1 and 0.68% in module 2. The average value of body temperature error was 0.46% in module 1 and 0.72% in module 2. The results of this research can be implemented in a centralized patient monitoring system at the hospital, making it easier for health workers to monitor multiple patients, with the results of monitoring in real-time and continue, more parameters, via wireless with greater distance.
Optimization of Targeting Rocket Launchers with Wheeled Robots
Authors: Anggara Trisna Nugraha  , Ravi Alwy Muhammad , Priyambodo Dadang
Published: February 2021

The quick launch weapon system is unique. This rocket launcher has a high launch rate, but the rocket launched is one stage lower than the launcher normally launched by ships of this size. For example, a (medium) cruiser would use a fast light rocket launcher to launch a light (small) rocket. Currently rocket launchers are still controlled by humans, using PCs and servo motors as control tools to determine the accuracy of the shooting angle, so complete components are needed when designing the robot so that the robot can work automatically as needed. For the input given, Automatically control the rocket launcher robot and communicate via PC, then use a USB TTL cable to forward commands to the microcontroller, then send it to the Xbee-pro transmitter circuit, then send and receive by the Xbee-pro receiver, and then send the Microcontroller for transmitter control sent to servo and rocket motors in the transmitter control system in the form of a relay. Based on the test results, the robot can guide the rocket launcher at a predetermined angle, and can launch manual rockets, multiple rockets, triple rockets and all rockets, with a success rate of up to 80%.
Classification-based Diagnosis Using Synthetic Data from Uncertain Models
Authors: Matei Ion , Zhenirovskyy Maksym , De Kleer Johan , Feldman Alexander
Published: February 2021

Machine learning based diagnosis engines require large data sets for training. When experimental data is insucient, system models can be used to supplement the data. Such models are typically simplified and imprecise, hence with some degree of uncertainty. In this paper we show how to deal with uncertainty in synthetic training data. The data is produced using a model with uncertainties. The uncertainties originate from inaccurate parameter values or parameters that take dierent values based on the mode of operation. We demonstrate how techniques from the uncertainty quantification field can be used to reduce the numerical complexity of the training algorithm. In particular, we use generalize polynomial chaos to eciently approximate the loss function. In addition, we present a neural network architecture specifically designed to deal with uncertainties in the training data. As an illustrative example, we show how our approach can be used to detect faults in an elevator system.
Rotating Machinery Prognostics and Application of Machine Learning Algorithms
Authors: Techane Asheber Wagshum , Wang Yu-Fu , Weldegiorgis Bereket Haile
Published: February 2021

The internet of things (IOT) enabled presence of abundant sensors on smart machineries and the recent advance in deep learning is accelerating the development of predictive maintenance in production systems with less time and fair amount of effort. In this work a Deep learning Neural Networks (DNN) based bearing health monitoring system with index of similarity check is developed and tested for its effectiveness. The assessment procedure followed in here trains a DNN model on a time series data segmented to a vector size equal to number of data points per cycle as training and test data sets. Moreover the model measures the similarity of the test signal to an anchor signal selected from each fault class. The classification performance comparison done proves that DNN with fair depth and large data perform better and can be extended to other problems in intelligent maintenance systems development efforts. The proposed system is intuitive and has minimal complexity with uncompromised fault detection accuracy.
Development of Robust Fault Signatures for Battery and Starter Failure Prognosis
Authors: Du Xinyu , Zhang Yilu
Published: February 2021

Battery and starter are crucial vehicle components, whose failures may cause customers to be stranded. To enhance customer satisfaction and improve dealership serviceability, the failure prognosis and fault isolation for battery or starter are very important. In order to develop a robust diagnostic and prognostic solution, in this work, the feature extraction algorithms are developed to extract two fault signatures, namely battery charging resistance equivalent and battery cranking resistance ratio. The algorithms are based on the equivalent circuit model for the battery and starter system, the battery empirical model, and the field knowledge about the driver’s behavior and battery management system. The proposed solution is a passive approach, and does not require any additional sensors for GM vehicles, or expensive computing hardware. Therefore, it is suitable for both onboard and off-board implementation. The solution has been validated with large fleet of vehicles under different scenarios, and implemented for selected GM vehicles through the OnStar™ Proactive Alerts service.
Data Analytics for Performance Monitoring of Gas Turbine Engine
Authors: Liu Yuan , Banerjee Avisekh , Ravichandran Thambirajah , Kumar Amar , Heppler Glenn
Published: February 2021

Performance analysis of a low power rating and partially loaded industrial gas turbine engine (GTE) was carried out by using a model-free data analytic approach. By adopting an efficient input selection method, several performance indices (PI) are proposed to quantify the performance of the GTE. These indices are extracted using engine operating data related to power output and parameters related to fuel consumption, and validated with engine performance monitoring measurements for a three year period corresponding to one time between overhaul intervals. The dependency of the PIs on ambient temperature has been studied by using linear and polynomial fitting curves. Then novel methods are introduced for analysis of short-term and long-term performance deterioration arising from compressor fouling and structural degradation respectively. The results have clearly shown the ability of the proposed PIs to detect short-term compressor fouling as well as long-term performance deterioration, which is directly relevant to the Prognostics and Health Management of gas turbine engine.
Operational Anomaly Detection in Flight Data Using a Multivariate Gaussian Mixture Model
Authors: Li Guoyi , Rai Ashwin , Lee Hyunseong , Chattopadhyay Aditi
Published: February 2021

This paper presents a robust real-time aircraft health monitoring framework using a machine learning based approach, specifically the multivariate Gaussian mixture model (mGMM), for the detection of in-air operational anomalies of an aircraft system. Sensor fusion and noise filtering algorithms have also been adopted to reduce dimensionality of the feature space while avoiding the elimination of useful information from the original flight data. Random noise in each feature, induced by the aircraft sensors and data acquisition system, is filtered out using a weighted averaging window while maintaining inherent variances. The filtered dataset is then fused according to the underlying physics of each sensed feature to reduce redundant features and subsequently trained using the mGMM. The methodology allows monitoring the behavior of each feature as well as correlations between features, significantly improving detection sensitivity. The high computational efficiency of this approach permits real-time monitoring of an aircraft system.
Extensible System for Optical Character Recognition of Maintenance Documents
Authors: Labarga John Anthony , Singh Amardeep , Moffitt Vera Zaychik
Published: February 2021

In the course of maintenance and operations, equipment operators and manufacturers frequently generate large volumes of paper documents. This is particularly the case in maintaining legacy systems, and when external factors (e.g. security concerns, environment, training procedures) make it infeasible to record data in a computer system in real time. To implement analytics or automated monitoring, these documents must later be converted to digital copies, which can be ingested into a database. This paper describes a flexible system for converting paper forms into digital documents through Optical Character Recognition (OCR), utilizing open source tools and packages. This system allows for the incorporation of business rules and processes that deliver high fidelity digital copies.
Modeling the Effects of Uncertainty on the National Airspace System
Authors: DeCarlo Erin C. , Bichon Barron J.
Published: February 2021

This paper presents the first steps toward managing uncertainty and assessing risk within the national airspace system (NAS) by investigating the impact of uncertainty on “flight plan flexibility” (FPF) – a proposed quantitative measure of an aircraft’s ability to adapt its flight plan due to improbable events. First, an air traffic scenario derived from national flight plan data is simulated with an open source BlueSky air traffic control analysis centered on a busy airport. Next, state-space diagrams derived from the aircraft state parameters (i.e., speeds, altitudes, headings), spatial proximities, and surveillance signals are used to construct the FPF metric. Finally, a probabilistic analysis is used to propagate uncertainty in the aircraft positions through BlueSky to observe the resulting uncertainty in FPF through time. Future work will aggregate individual aircraft safety measures and additional metrics into a single system-wide indicator, transitioning from BlueSky to a gate-to-gate simulation for prognostics, and deriving probabilistic models of epistemic and aleatory sources of uncertainty in the NAS from available data.
Ensemble Learning Based Surrogate Modeling for Gas Turbine Blisk Temperature Predictions
Authors: Ravichandran Thambirajah , Heppler Glenn , Banerjee Avisekh
Published: February 2021

Temperature prediction in complex systems like gas turbines provides insights to temperature dependent damage accumulation but usually involves a huge computational cost. For simulation-based prognostics, the computational cost is a major hindrance to a real time implementation. In this work an ensemble learning based multistage surrogate modeling approach is investigated as a possible solution for reducing the computational cost. First the nodal temperature of a turbine blisk is predicted using computational fluid dynamic (CFD) simulations for a limited number of engine operating points. Next the proposed ensemble learning based surrogate modeling approach is implemented to train surrogate models for every node defining the blisk. To achieve computational efficiency, the proposed surrogate modeling framework implements in sequence, clustering techniques for data analysis, multistage polynomial regression modeling, and ensemble learning based model combination. Finally the prediction errors are quantified using the leave-one-out cross-validation method. The result suggests that the computational time could be significantly reduced using the proposed ensemble learning based multistage surrogate modeling technique. The threshold value used to tune the polynomial regression model complexity is also shown to influence the time for surrogate model training.
Data-driven Modeling for Aviation Safety Diagnosis and Prognosis
Authors: Zhang Xiaoge , Kong Yingxiao , Subramanian Abhinav , Mahadevan Sankaran
Published: February 2021

The safety of the air transportation system is affected by a variety of uncertainties arising from multiple sources. This paper investigates a diagnosis and prognosis approach to detect anomalies in the flight trajectory, diagnose root causes, and then perform prognosis regarding the risk of occurrence of adverse events, in the presence of various sources of uncertainty. The proposed method is illustrated using a three-step procedure. First, using flight trajectory data, we evaluate the probabilities of system states corresponding to each failure case, from which we formulate a state-space model. Next, we perform anomaly detection for a specific flight trajectory by developing a Bayesian state estimation-based method, and subsequently identify the cause of the detected anomaly. Once the root cause is identified, prognosis is performed to predict the future state in a probabilistic manner. The proposed method is illustrated using near-ground landing data synthetically generated from an open source air traffic simulator – BlueSky. The simulation data mimicking the nearground landing process with different initial states (e.g., aircraft altitude and speed, response delay, and brake performance) and other factors (such as wind direction) are used to demonstrate the procedures of diagnosis and prognosis.
Procedure for Selecting a Transmission Mode Dependent on the State-of-charge and State-of-health of a Lithium-ion Battery in Wireless Sensor Networks with Energy Harvesting Devices
Authors: Quintero Vanessa , Perez Aramis , Jaramillo Francisco , Estevez Claudio , Orchard Marcos
Published: February 2021

Diverse methods and considerations have been proposed to manage the available energy in an efficient manner in Wireless Sensor Networks. By incorporating Energy Harvesting Devices in these type of networks it is possible to reduce the dependency of the availability of the Energy Storage Devices, particularly the lithium-ion battery. Recently, the State-of-Charge and State-of-Health of the battery have been considered as inputs for the design of the Medium- Access-Control protocols for Wireless Sensor Networks. In this article, different guidelines are proposed for the design of Medium-Access-Control protocols used in Wireless Sensor Networks with Energy Harvesting Devices considering the State-of-Charge and State-of-Health as indicators for the estimation of the transmission time of the sensor node. The proposed guidelines consider different currents used during the transmission to estimate the State-of-Charge and Stateof- Health of the battery. The incorporation of these indicators aim to improve the decision-making process of the sensor node when transmitting.
Fault Diagnosis and Prognosis Based on Deep Belief Network and Particle Filtering
Authors: Niu Guangxing , Tang Shije , Liu Zhichao , Zhao Guangquan , Zhang Bin
Published: February 2021

Fault diagnosis and prognosis (FDP) plays more and more important role in industries FDP aims to estimate current fault condition and then predict the remaining useful life (RUL). Based on the estimation of health state and RUL, essential decisions on maintenance, control, and planning can be conducted optimally in terms of economy, efficiency, and availability. With the increase of system complexity, it becomes more and more difficult to model the fault dynamics, especially for multiple interacting fault modes and for fault modes that are affected by many internal and external factors. With the development of machine learning and big data, deep learning algorithms become important tools in FDP due to their excellent performance in data processing, information extraction, and automatic modeling. In the past a few years, deep learning algorithms demonstrate outstanding performance in feature extraction and learning fault dynamics. As emerging techniques, their powerful learning capabilities attract more and more attentions and have been extended to various applications. This work presents a novel diagnosis and prognosis methodology which combined deep belief networks (DBNs) and Bayesian estimation. In the proposed work, the DBNs are trained offline using available historical data. The fault dynamic model is then represented by the trained DBNs and modeling uncertainty is described by noise. The integration of DBNs with particle filtering is then developed to provide an estimation of the current fault state and predict the remaining useful life, which is very suitable and efficient for most nonlinear fault models. Experimental studies of lithium-ion batteries are presented to verify the effectiveness of the proposed solution.
Automated Contingency Management for Water Recycling System
Authors: Tang Shijie , Niu Guangxing , Zhang Bin , Thakker Ash , Vivanco Santiago , Martin Rodney , Moore Craig
Published: February 2021

To enable effective management, planning, and operations for future missions that involve a crewed space habitat, operational support must be migrated from Earth to the habitat. Intelligent System Health Management technologies (ISHM) promise to enable the future space habitats to increase the safety and mission success while minimizing operational risks. In this paper, Water Recycling System (WRS) deployed at NASA Ames Research Center's Sustainability Base is used for verification and validation of the proposed solution. Our work includes the development of the WRS simulation model based on its dynamic physical characteristics and the design of Automatic Contingency Management (ACM) framework that integrates fault diagnosis and optimization. In WRS modeling, a nominal model with fault injectors is developed. Fault detection and isolation techniques are then developed for isolating causes and identifying the severity of the faults. Dynamic Programming (DP) based fault mitigation strategies are designed to accommodate the faults in the system. A series of simulations are presented with different fault modes and the results indicate that the proposed ACM system can alleviate the fault in the WRS optimally regarding energy consumption and effects of the fault.
Information Fusion for National Airspace System Prognostics
Authors: Liu Yongming , Goebel Kai
Published: February 2021

Expanding Prognostics and Health Management (PHM) from an equipment-centric view to complex large-scale engineering systems is a challenging problem. One example for a large engineering system is the next generation national airspace system (NAS), which is a fully coupled cyberphysical- human system. This paper presents an overview of a NASA University Leadership Initiative (ULI) project which aims to address the safety needs and their technology solutions for future NAS. The ULI is a 5-year collaborative project in which researchers from several universities and commercial entities work together to advance real-time airspace safety concepts. The underlying premise is that it is imperative to be able to assess and predict the evolution of the airspace’s safety state. Towards that end the work envisions to address the following issues: modeling of the airspace using both data-driven and physics based approaches; quantifying and managing uncertainty; advancing prognostics and information fusion algorithms; and understanding and modeling human computer interface. A comprehensive simulation environment is being built that allows for assessment of performance and verification and validation. The paper discusses the various activities and places them into the context of overall NAS safety.
Machine Learning Based Prognostics of Fatigue Crack Growth in Notch Pre-cracked Aluminum 7075-T6 Rivet Hole
Authors: Haynes Robert , Joshi Ghanashyam , Bradley Natasha
Published: February 2021

Constant stress amplitude fatigue tests were conducted on the notch pre-cracked Aluminum 7075-T6 rivet hole dog-bone coupons. Monitoring of visible surface crack length by special surface engraving using digital microscope images and by ultrasonic sensors signals was carried out to yield fatigue crack length measurements in relation to number of fatigue cycles applied. The experimental results provide ultrasonic sensor validation for fatigue crack length measurements. Fracto-graphic examination of failed fatigue surfaces has provided further confirmation of notch pre-crack length, crack initiation process, and crack growth marker bands. These experimental inputs were used in NASGRO and AFGROW software fatigue crack growth simulations. The simulation results did not match the crack initiation fatigue life measured by experiments. However, there was good agreement with crack growth simulations of larger cracks. Hence, we plan to develop a machine learning application that will learn the fatigue crack initiation and crack growth processes from data obtained from our own experiments and other fatigue data available from AFGROW databases. Nonlinear AutoRegressive models with eXogenous input (NARX) artificial neural network were used to predict crack growth longer than 5.0-mm. Particle filtering modeling with Bayesian updating was applied to these experimental data for prognostics of fatigue crack growth. A concept design and preliminary implementation results will be presented.