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Preparing future entrepreneurs: reflections about the COVID-19 impacts on the entrepreneurial potential of Brazilian students

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Journal of Work-Applied management 2021年第2期13卷 277-283页

作者： Cazeri, Gustavo T. Anholon, Rosley Rampasso, Izabela Simon Quelhas, Osvaldo L.G. Leal Filho, Walter School of Mechanical Engineering State University of Campinas Campinas Brazil PNPD/CAPES Program Doctoral Program in Sustainable Management Systems Federal Fluminense University Niterói Brazil Master Program in Management Systems Doctoral Program in Sustainable Management Systems Federal Fluminense University Niterói Brazil Faculty of Life Sciences Hamburg University of Applied Sciences Hamburg Germany

Purpose: This viewpoint aims to present reflections on the coronavirus disease 2019 (COVID-19) pandemic scenario and the entrepreneurial potential of Brazilian students. Guidelines are proposed to support debates in the academic environment and better prepare future entrepreneurs to the labour market. Design/methodology/approach: Since this is a viewpoint article, some statements presented here are characterised by the authors' opinions. However, for a better foundation, bibliographic research related to the theme was carried out. Findings: In the authors' point of view, the COVID-19 pandemic scenario may negatively influence the decisions of Brazilian students that are characterised as potential future entrepreneurs. Educators can use the guidelines presented here to conduct debates with students in order to clarify aspects related to profile, behaviour and other issues. Originality/value: By understanding better entrepreneurial aspects in the COVID-19 pandemic scenario, Brazilian students can make better decisions. This initiative will contribute to future success in the Brazilian entrepreneurial activity and national economy. © 2021, Gustavo T. Cazeri, Rosley Anholon, Izabela Simon Rampasso, Osvaldo L.G. Quelhas and Walter Leal Filho.

关键词： Brazilian higher education institutions COVID-19 pandemic Entrepreneurial activity Labour market

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Joint green dynamic order batching and picker routing problem using PSO with global worst experience

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Applied Soft Computing 2024年 154卷

作者： Lin, Chun-Cheng Peng, Yi-Chun Kang, Jia-Rong Department of Industrial Engineering and Management National Yang Ming Chiao Tung University Hsinchu300 Taiwan International Master Program of Smart Manufacturing and Applied Information Science National Chin-Yi University of Technology Taichung411 Taiwan Department of Information Management Tatung University Taipei104 Taiwan

With the increasing importance of various countries’ initiatives on reducing carbon emissions (e.g., carbon border adjustment mechanism, CBAM), intelligent order picking systems have assisted electronic retailers in realizing a green supply chain. Previous studies on picker routing operations focused on adopting offline static customer order information to carry out operational decisions. However, in practice, the customer order information is updated dynamically;and high-efficiency warehouse layouts have been increasingly concerned. Therefore, this study creates a mixed-integer programming model for minimizing both the total carbon footprint and the total penalty cost for delayed orders in the joint order batching and picker routing problem with dynamic arriving orders and shipping time constraints in a high-efficiency fishbone warehouse layout. To solve this complex problem, a particle swarm optimization algorithm that integrates the swarm's previous global and local worst experiences and a migration mechanism is further proposed to increase solution quality and computing efficiency. In addition, a three-dimensional space for the warehouse floorplan and shipping time constraints is designed to divide orders into batches to address the constraints. Theoretical analysis of this algorithm is conducted, and experimental analysis shows that this algorithm finds superior solutions than current practical strategies, to offer a valuable reference for carbon emission reduction in greening warehousing. © 2024 Elsevier B.V.

关键词： Carbon footprint

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Real Time Monitoring System of Drinking Water Quality Using Internet of Things 24

Real Time Monitoring System of Drinking Water Quality Using ...

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24th International Electronics Symposium, IES 2022

作者： Abidin, Zainul Maulana, Eka Nurrohman, Muhammad Yogi Wardana, Fitri Candra Warsito Universitas Brawijaya Faculty of Computer Science Department of Computer Engineering Malang Indonesia Universitas Brawijaya Faculty of Engineering Department of Electrical Engineering Malang Indonesia Universitas Brawijaya Master Program in Environmental Resources and Development Management Postgraduate School Malang Indonesia Universitas Brawijaya Faculty of Mathematics and Natural Sciences Department of Chemistry Malang Indonesia

ISBN: (数字)9781665489713

ISBN: (纸本)9781665489713

In order to reduce Polyethylene Terephthalate (PET) bottle plastic waste, Universitas Brawijaya (UB) provided reverse osmosis drinking water in some buildings. Water monitoring is needed to keep the water quality. Therefore, a water monitoring system based on Total Dissolved Solids (TDS), pH, and water flow was proposed. Since the UB buildings have good internet connection (WiFi), Internet of Things (IoT) was employed to the system to support real time monitoring. So, data of TDS, pH, and water flow can be periodically sent to cloud and displayed to a specific website. The system worked very well and the data can be summarized and used by operator as indicators of performance of the reverse osmosis machine. When water quality and performance decrease, operator must check filters membrane or water pump for further maintenance to support long life use. Although the sensors have been calibrated properly, some measurement errors occur. The measurement error percentages of TDS and pH are 0.62% and 0.94%, respectively. © 2022 IEEE.

关键词： Internet of things

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An Architecture of Real-World Data Database 1

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5th International Conference on Innovative Computing, IC 2022

作者： Lee, Hsiu-An Hsu, Chien-Yeh Department of Computer Science and Information Engineering Tamkang University New Taipei City Taiwan Department of Information Management National Taipei University of Nursing and Health Sciences Taipei Taiwan Master Program in Global Health and Development Taipei Medical University Taipei Taiwan

ISBN: (数字)9789811941320

ISBN: (纸本)9789811941313

In the analysis of medical data, it is now important to use "Real-World Data (RWD)". In the past, clinical research in the medical field was often completed by clinical trials. Clinical trials are a kind of use of listed drugs and comfort according to research objectives. The process of comparing drugs or other medical treatments on subjects as a control group. The Real-world data research database is essential to precision health. In order to develop the value of clinical data, improve the medical care service, and promote precision medicine, the goal of this research is to design a Real-World Data Research Database, aiming at the wide range and standardization of data, the detail component including: *** standard Health Level 7-Fast Health Interoperability Resources (HL-7 FHIR).*** sorting and cleaning ***-based database research ***-based technology for identity verification and database authorization recognition mechanism. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Clinical research

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Using AI Algorithm to Establish the CVD Risk Assessment Model 1

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5th International Conference on Innovative Computing, IC 2022

作者： Chen, Yin-Chen Lee, Hsiu-An Hsu, Chien-Yeh Department of Information Management National Taipei University of Nursing and Health Sciences Taipei Taiwan Department of Computer Science and Information Engineering Tamkang University New Taipei City Taiwan Master Program in Global Health and Development Taipei Medical University Taipei Taiwan

ISBN: (数字)9789811941320

ISBN: (纸本)9789811941313

In Taiwan, diseases with cardiovascular include heart disease and cerebrovascular disease among the top ten causes of death. With the development of data mining in the medical field, it can be used to establish the risk prediction models of disease as a tool to assist physicians in decision-making in diagnosis. The purpose of this study is taking Taiwanese health examination data as an example, to identify the significant risk factors of cardiovascular disease and to establish the risk assessment model of cardiovascular disease using data mining. Using Chi-square test and Information Gain identify the correlation between various factors and cardiovascular diseases. Using eight algorithms such as decision tree, random forest, XGBoost, neural network, logistic regression, support vector machine, K nearest neighbor algorithm and voting algorithm to establish the risk assessment model of cardiovascular disease and using confusion matrix and AUC as model evaluation. Compare model performance with different factor combinations. Experiment result shows that it finds 22 questionnaires and biochemical variable risk factors affecting cardiovascular disease and 10 questionnaire factors. ANN and VOTE with 22 factors of Information Gain (threshold > 0.01) are the best models. Both models have the same accuracy (0.88) and AUC (0.90). The best model of questionnaire variable is ANN with the accuracy rate is 0.89, and the AUC is 0.91. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Data mining

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An Integer Linear programming for Hospital Bed Scheduling and Capacity management 22

An Integer Linear Programming for Hospital Bed Scheduling an...

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4th International Conference on management Science and Industrial engineering, MSIE 2022

作者： Jewpanya, Parida Acla, Arni Ellorin-Igros, Clarinda Joanne Santos, Aira Ronalie P. Rachmandika, Pino Prasetyo, Dimas Redi, Anak Agung Ngurah Perwira Department of Industrial Engineering Rajamangala University of Technology Lanna Tak Tak Thailand School of Industrial Engineering and Engineering Management Mapúa University 658 Muralla St. Intramuros Manila1002 Philippines Industrial Engineering Department Binus Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Binus University Banten Tangerang15325 Indonesia

ISBN: (纸本)9781450395816

COVID-19 has struck the Philippines in December 2019 and has brought great panic to the country's healthcare system. In a short period of time, the number of infected increased exponentially. Hospitals are suddenly filled with patients infected by the virus to the extent that patients wait for hours to days to be admitted. Others die on the road even before finding hospitals that can accommodate them. The hospitals and the country's healthcare system must consider this increasing demand to serve patients fully. Patient planning is commonly used in other countries to maximize bed allocation. A recent study using Bernoulli Distributed Random Variable represents the binary integer program. The approach combines the queuing model and simulation to reduce the patient dismissal rate and increase hospital output. On the other hand, this paper deals with strategic hospital bed capacity optimization using linear integer programming by considering the diverse resources, such as doctors, nurses, beds, and hospital rooms. © 2022 ACM.

关键词： Hospitals

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Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains

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Computational and Structural Biotechnology Journal 2024年 23卷 1864-1876页

作者： Do, Duyen Thi Yang, Ming-Ren Vo, Tran Nam Son Le, Nguyen Quoc Khanh Wu, Yu-Wei Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Business Administration College of Management Lunghwa University of Science and Technology Taoyuan City Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan TMU Research Center for Digestive Medicine Taipei Medical University Taipei Taiwan

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR. © 2024 The Authors

关键词： Genes

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A Mixed Integer Linear programming for COVID-19 Related Medical Waste Reverse Logistics Network Design 22

A Mixed Integer Linear Programming for COVID-19 Related Medi...

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4th International Conference on management Science and Industrial engineering, MSIE 2022

作者： Santos, Aira Ronalie P. Maghfiroh, Meilinda Fitriani Nur Sapiter, John Rayam Prasetyo, Yogi Tri Redi, Anak Agung Ngurah Perwira Persada, Satria Fadil Young, Michael Nayat Nadlifatin, Reny Ardiansyahmiraja, Bobby School of Industrial Engineering and Engineering Management Mapua University Manila Philippines Department of Industrial Engineering Universitas Islam Indonesia Yogyakarta Indonesia Industrial Engineering Department Binus Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia Faculty of Business and Economics Universitas Surabaya Surabaya Indonesia

ISBN: (纸本)9781450395816

Medical wastes bring probable hazards and public risks if not handled correctly, especially during the covid-19 pandemic. Waste management costs are rising due to continues devastation of covid-19 virus. Increased care and handling processes have been implemented to avoid further spreading the infection while ensuring the proper disposal. Given this, medical waste related to covid-19, including other wastes generated by medical facilities, requires delicate integration into the waste management process thru a reverse logistics network for cost-efficient collection, processing, and transport style. Using AMPL software as solving tool, this paper was designed to utilize a mixed-integer linear programming model of a reverse logistics network to improve medical waste management by identifying the total minimum cost of the waste disposal cycle from Waste generating facilities, treatment facilities, and to the disposal factory. © 2022 ACM.

关键词： COVID-19

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Leveraging ROTI map derived from Indonesian GNSS receiver network for advancing study of Equatorial Plasma Bubble in Southeast/East Asia

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Earth and Planetary Physics 2025年第1期9卷 101-116页

作者： Prayitno Abadi Ihsan N.Muafiry Teguh N.Pratama Angga Y.Putra Suraina Gatot H.Pramono Sidik T.Wibowo Febrylian F.Chabibi Umar A.Ahmad Wildan P.Tresna Asnawi Research Center for Climate and Atmosphere Indonesian National Research and Innovation Agency(BRIN)BandungIndonesia School of Electrical Engineering Telkom UniversityBandungIndonesia Directorate of Laboratory Management Facilities and Science and Technology Park Indonesian National Research and Innovation Agency(BRIN)PontianakIndonesia Geophysics Laboratory Master Program in PhysicsUniversitas Gadjah Mada(UGM)YogyakartaIndonesia Research Center for Space Indonesian National Research and Innovation Agency(BRIN)BandungIndonesia Indonesian Geospatial Information Agency(BIG) JakartaIndonesia Research Center for Photonics Indonesian National Research and Innovation Agency(BRIN)Tangerang SelatanIndonesia Department of Earth and Planetary Sciences Hokkaido UniversitySapporoJapan

This paper highlights the crucial role of Indonesia’s GNSS receiver network in advancing Equatorial Plasma Bubble(EPB)studies in Southeast and East Asia,as ionospheric irregularities within EPB can disrupt GNSS signals and degrade positioning *** by the Indonesian Geospatial Information Agency(BIG),the Indonesia Continuously Operating Reference Station(Ina-CORS)network comprises over 300 GNSS receivers spanning equatorial to southern low-latitude ***-CORS is uniquely situated to monitor EPB generation,zonal drift,and dissipation across Southeast *** provide a practical tool for EPB research,by sharing two-dimensional rate of Total Electron Content(TEC)change index(ROTI)derived from this *** generate ROTI maps with a 10-minute resolution,and samples from May 2024 are publicly available for further scientific *** preliminary findings from the ROTI maps of Ina-CORS are ***,the Ina-CORS ROTI maps reveal that the irregularities within a broader EPB structure persist longer,increasing the potential for these irregularities to migrate farther ***,we demonstrate that combined ROTI maps from Ina-CORS and GNSS receivers in East Asia and Australia can be used to monitor the development of ionospheric irregularities in Southeast and East *** have demonstrated the combined ROTI maps to capture the development of ionospheric irregularities in the Southeast/East Asian sector during the G5 Geomagnetic Storm on May 11,*** observed simultaneous ionospheric irregularities in Japan and Australia,respectively propagating northwestward and southwestward,before midnight,whereas Southeast Asia’s equatorial and low-latitude regions exhibited irregularities *** sharing ROTI maps from Indonesia and integrating them with regional GNSS networks,researchers can conduct comprehensive EPB studies,enhancing the understanding of EPB behavior across Southeast and East Asia and contributing significantly to ionosphe

关键词： Equatorial Plasma Bubble(EPB) GNSS receivers’network Indonesia Continuously Operating Reference Station(Ina-CORS) ionospheric map Rate of TEC change index(ROTI)map

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A Soft System Approach for Smart Agriculture: The Use of Digital Marketing in Organic Farm Business

A Soft System Approach for Smart Agriculture: The Use of Dig...

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International Conference on ICT For Smart Society (ICISS)

作者： Lim Sanny Pantri Heriyati Chairani Putri Pratiwi Diana Lo Glory Aguzman Sekar Wulan Prasetyaningtyas Management Department Binus Business School Master-Program Bina Nusantara University Jakarta Indonesia Department of Management Doctor of Research in Management Bina Nusantara University Jakarta Indonesia Binus Entrepreneurship Center & Management Department Bina Nusantara University Jakarta Indonesia Food Technology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia Binus Business SchoolMaster-Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

One of the main problems in the organic farm industry is the marketing channel to find its customers. This problem might lead to a loss of possibility of gaining economic value from them. Implementation of digital marketing technologies could prevent economic value loss since digitalization utilizes tools to create strategies to reach its customers. However, the digital marketing application in organic farm has obstacles and a lack of discussion in the literature, particularly in the case of Indonesia. This research develops a conceptual model of the application for digital marketing in an organic farming through the soft systems methodology approach. The results shed light on the ongoing literature by identifying the overall system and relevant components. The lack of engagement between producers and consumers, which reduces consumers' desire to buy organic foods, is one of the other difficulties that this study also brings to light. It is advised that producers improve contact with their stakeholders and customers to better understand their requirements and desires to implement digitalization in this business.

关键词： Economics Smart agriculture Information and communication technology Stakeholders Farming Business

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