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Journal articles on the topic 'Green Software'

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Author: Grafiati

Published: 14 March 2023

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1

Verdecchia, Roberto, Patricia Lago, Christof Ebert, Carol de Vries, and Christof Ebert. "Green IT and Green Software." IEEE Software 38, no. 6 (November 2021): 7–15. http://dx.doi.org/10.1109/ms.2021.3102254.

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2

Haron, Haryani, Ibraheem Y. Y. Ahmaro, Syed Ahmad Aljunid, and M. Bakri. "Software Reusability in Green Computing." Advanced Science Letters 21, no. 10 (October 1, 2015): 3283–87. http://dx.doi.org/10.1166/asl.2015.6454.

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3

Sambhanthan, Arunasalam, and Vidyasagar Potdar. "Green Business Practices for Software Development Companies." International Journal of Enterprise Information Systems 11, no. 3 (July 2015): 13–26. http://dx.doi.org/10.4018/ijeis.2015070102.

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This paper reports the findings of a text analysis of the corporate sustainability reports of eleven large scale Indian Software Development Businesses for the period of 2012 to 2014. The results shows that there are twenty two reported components of software development sustainability namely green buildings, green energy, green factory, green data centres, green infrastructure, green initiatives, green innovation, green packaging, green portfolio, green power, green practices, green procurement, green products, green program, green rating, green solutions, green space, green team, green tech and green supply chain which are addressed in the published reports of Indian software development businesses. The reports were further analysed to infer some knowledge on how the software development companies could contribute to green environment and the possible environmental impacts of these contributions. Finally a number of generalised conclusions were derived and followed by a set of implications for best practices in green software development as the outcome of the research reported in this paper.

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Thilmany, Jean. "Green Decisions." Mechanical Engineering 132, no. 03 (March 1, 2010): 40–42. http://dx.doi.org/10.1115/1.2010-mar-4.

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This article discusses the introduction and implementation of environmental regulations in manufacturing industry. Manufacturers are responding to customer demand for environmentally friendly products. Several vendors such as PTC and Siemens PLM Software make products that track environmental performance of products, parts, materials, and suppliers. Many products are integrated with a company’s supply chain and product development systems. IBM offers Environmental Product Lifecycle Management, which includes software and consulting services, and assists clients in analyzing every phase their product passes through to ensure environmental compliance. A number of lifecycle assessment software packages have been released in recent years to help designers. Sustainable Minds develops software, for example, that is intended to give engineers pertinent supplier and material information, which allows them to weigh each design decision from an environmental standpoint. Engineers call upon lifecycle analysis software to ensure their products comply with environmental regulations. Meanwhile, the number of manufacturers who will need to meet those regulations represents a growing market for software makers.

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Calero, Coral, Javier Mancebo, Felix Garcia, Maria Angeles Moraga, Jose Alberto Garcia Berna, Jose Luis Fernandez-Aleman, and Ambrosio Toval. "5Ws of green and sustainable software." Tsinghua Science and Technology 25, no. 3 (June 2020): 401–14. http://dx.doi.org/10.26599/tst.2019.9010006.

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6

Turkmanovic, Haris, Ivan Popovic, Dejan Drajic, and Zoran Cica. "Green computing for iot - software approach." Facta universitatis - series: Electronics and Energetics 35, no. 4 (2022): 541–55. http://dx.doi.org/10.2298/fuee2204541t.

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More efficient usage of limited energy resources on embedded platforms, found in various IoT applications, is identified as a universal challenge in designing such devices and systems. Although many power management techniques for control and optimization of device power consumption have been introduced at the hardware and software level, only few of them are addressing device operation at the application level. In this paper, a software engineering approach for managing the operation of IoT edge devices is presented. This approach involves a set of the application-level software parameters that affect consumption of the IoT device and its real-time behavior. To investigate and illustrate the impact of the introduced parameters on the device performance and its energy footprint, we utilize a custom-built simulation environment. The simulation results obtained from analyzing simplified data producer-consumer configuration of IoT edge tier, under push-based communication model, confirm that careful tuning of the identified set of parameters can lead to more energy efficient IoT end-device operation.

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Et.al, SitiRohana Ahmad Ibrahim. "Green Software Process Assessment: The Theoretical Framework." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (April 10, 2021): 2011–16. http://dx.doi.org/10.17762/turcomat.v12i3.1039.

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Many differentdomains such as engineering, education and health apply green development through sustainability concept.The aim is to ensure the product and services are still relevance and applicable for the next generation. Previously, they were three common pillars of sustainability elements which were economic, social, and environmental. The technical and individual elements were added later to evaluate the software system. Yet, effortsare made to achieve green development process by reducing wastes and to preserve the environment.Most studies targeted on greenness of software products and less consideration on green in software processes. In this study, focus is given to ensure and guarantee green in software process activities. This paper presents the background works on existing studies in green software process and related. Further, it presents the theoretical framework that is based on literature findings and will be the groundwork of this study. The theoretical frameworkdefined consists of software process, green context, and assessment method. The elements of sustainability and waste reduction will be identified further.

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8

Ahmad Ibrahim, Siti Rohana, Jamaiah Yahaya, and Hasimi Sallehudin. "Green Software Process Factors: A Qualitative Study." Sustainability 14, no. 18 (September 7, 2022): 11180. http://dx.doi.org/10.3390/su141811180.

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In the twenty-first century, the use of software is growing due to many applications requiring large and complex software. Many people do not realise that the use of software has influenced the operation of computer hardware to move indirectly as it affects the hardware’s energy consumption and carbon emissions. Previous studies focused more on models and tools to measure the impact of power consumption and energy efficiency from hardware than on software development studies. Energy consumption can be optimised by the greening software process throughout all phases of development activity. Besides, the current green software process models are more focused on environmental and economic elements and do not integrate with the waste elements in the development phase. Integrating sustainability and waste elements is essential to ensure that the development process complies with green process standards. A qualitative method is used through interviews involving eight informants from Malaysia’s public and private sectors. The objectives of the empirical study are to reveal the current practices of the green software process in industry, identify software process waste and determine green factors associated with the software process. The analysis is guided by a thematic approach using Atlas.ti 8 software. This paper describes the results from the qualitative study that consists of three main themes: best practices of a software process, nine software wastes (building the wrong feature, rework, unnecessarily complex solutions, extraneous cognitive load, psychological distress, waiting, knowledge loss, ineffective communication, delay), and six green factors (resources, people, organisational, technical, environmental, technology). The analysis findings indicate that the software industry needs elements of best practices, green practices, and software technologies in each development phase to produce a green and sustainable software process. The advancement of computing today presents technology as an essential factor in green elements to ensure that the software process is constantly updated and always green.

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9

Lago, Patricia, Rick Kazman, Niklaus Meyer, Maurizio Morisio, Hausi A. Müller, and Frances Paulisch. "Exploring initial challenges for green software engineering." ACM SIGSOFT Software Engineering Notes 38, no. 1 (January 23, 2013): 31–33. http://dx.doi.org/10.1145/2413038.2413062.

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10

Sierszecki, Krzysztof, Tommi Mikkonen, Michaela Steffens, Thomas Fogdal, and Juha Savolainen. "Green Software: Greening What and How Much?" IEEE Software 31, no. 3 (May 2014): 64–68. http://dx.doi.org/10.1109/ms.2014.63.

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11

Li, Dong, Ming-Tuo Zhou, Peng Zeng, Ming Yang, Yan Zhang, and Haibin Yu. "Green and reliable software-defined industrial networks." IEEE Communications Magazine 54, no. 10 (October 2016): 30–37. http://dx.doi.org/10.1109/mcom.2016.7588226.

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12

Naumann, Stefan, Eva Kern, and Markus Dick. "Classifying Green Software Engineering - The GREENSOFT Model." Softwaretechnik-Trends 33, no. 2 (May 2013): 18–19. http://dx.doi.org/10.1007/s40568-013-0027-z.

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13

Sabharwal, Manuj, Abhishek Agrawal, and Grace Metri. "Enabling Green IT through Energy-Aware Software." IT Professional 15, no. 1 (January 2013): 19–27. http://dx.doi.org/10.1109/mitp.2012.104.

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14

Ardito, Luca, Giuseppe Procaccianti, Marco Torchiano, and Antonio Vetro. "Understanding Green Software Development: A Conceptual Framework." IT Professional 17, no. 1 (January 2015): 44–50. http://dx.doi.org/10.1109/mitp.2015.16.

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15

Godboley, Sangharatna, Arpita Dutta, and Durga Prasad Mohapatra. "Green DRCT." International Journal of Knowledge Discovery in Bioinformatics 7, no. 1 (January 2017): 14–29. http://dx.doi.org/10.4018/ijkdb.2017010102.

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Being a good software testing engineer, one should have the responsibility towards environment sustainability. By using green principles and regulations, we can perform Green Software Testing. In this paper, we present a new approach to enhance Branch Coverage and Modified Condition/Decision Coverage uses concolic testing. We have proposed a novel transformation technique to improve these code coverage metrics. We have named this new transformation method Double Refined Code Transformer (DRCT). Then, using JoulMeter, we compute the power consumption and energy consumption in this testing process. We have developed a tool named Green-DRCT to measure energy consumption while performing the testing process.

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16

Bhattacharya, Suparna, K. Gopinath, Karthick Rajamani, and Manish Gupta. "Software Bloat and Wasted Joules: Is Modularity a Hurdle to Green Software?" Computer 44, no. 9 (September 2011): 97–101. http://dx.doi.org/10.1109/mc.2011.293.

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17

Verma, Neeta. "Green Based Software Engineering Approach for Sustainable Protocol." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (July 31, 2022): 3612–20. http://dx.doi.org/10.22214/ijraset.2022.45731.

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Abstract: A sturdy green software model is the prominent necessity for various governments fields and banking areas for Energy utilization processing. The model should give all the Energy consumption aspects namely power consumption, utilization of Memory, (Co2) Carbon dioxide release which is related to development of software and make it energy efficient. For Software Development Life Cycle phases this research paper proposes a new green software model for the virtual host machine, which is the base for all the Green based Software Development process.

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18

Hu, Ying, Tao Luo, Norman Beaulieu, and Wenjie Wang. "An Initial Load-Based Green Software Defined Network." Applied Sciences 7, no. 5 (May 2, 2017): 459. http://dx.doi.org/10.3390/app7050459.

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19

Płotka-Wasylka, Justyna, and Wojciech Wojnowski. "Complementary green analytical procedure index (ComplexGAPI) and software." Green Chemistry 23, no. 21 (2021): 8657–65. http://dx.doi.org/10.1039/d1gc02318g.

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It is not easy to find appropriate tools for the evaluation of the “green” nature of analytical methodologies which involve the use of compounds, materials, or chemicals manufactured prior to the analytical step.

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20

LIU, Chen, Jia-Liang LU, Ling-He KONG, Feng-Gang WU, Qiang WU, and Min-You WU. "Software-Based Green Proxy System for Wireless Networks." Journal of Software 23, no. 2 (March 6, 2012): 215–29. http://dx.doi.org/10.3724/sp.j.1001.2012.04142.

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21

Paul, P. K., A. Bhuimali, S. L. Mewada, and J. L. Dey. "Is Green Computing a Social Software Engineering Domain?" International Journal of Applied Science and Engineering 4, no. 2 (2016): 67. http://dx.doi.org/10.5958/2322-0465.2016.00008.3.

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22

Ganesan, Madhubala, Ah-Lian Kor, Colin Pattinson, and Eric Rondeau. "Green Cloud Software Engineering for Big Data Processing." Sustainability 12, no. 21 (November 7, 2020): 9255. http://dx.doi.org/10.3390/su12219255.

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Internet of Things (IoT) coupled with big data analytics is emerging as the core of smart and sustainable systems which bolsters economic, environmental and social sustainability. Cloud-based data centers provide high performance computing power to analyze voluminous IoT data to provide invaluable insights to support decision making. However, multifarious servers in data centers appear to be the black hole of superfluous energy consumption that contributes to 23% of the global carbon dioxide (CO2) emissions in ICT (Information and Communication Technology) industry. IoT-related energy research focuses on low-power sensors and enhanced machine-to-machine communication performance. To date, cloud-based data centers still face energy–related challenges which are detrimental to the environment. Virtual machine (VM) consolidation is a well-known approach to affect energy-efficient cloud infrastructures. Although several research works demonstrate positive results for VM consolidation in simulated environments, there is a gap for investigations on real, physical cloud infrastructure for big data workloads. This research work addresses the gap of conducting real physical cloud infrastructure-based experiments. The primary goal of setting up a real physical cloud infrastructure is for the evaluation of dynamic VM consolidation approaches which include integrated algorithms from existing relevant research. An open source VM consolidation framework, Openstack NEAT is adopted and experiments are conducted on a Multi-node Openstack Cloud with Apache Spark as the big data platform. Open sourced Openstack has been deployed because it enables rapid innovation, and boosts scalability as well as resource utilization. Additionally, this research work investigates the performance based on service level agreement (SLA) metrics and energy usage of compute hosts. Relevant results concerning the best performing combination of algorithms are presented and discussed.

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23

Huang, Huawei, Song Guo, Jinsong Wu, and Jie Li. "Green DataPath for TCAM-Based Software-Defined Networks." IEEE Communications Magazine 54, no. 11 (November 2016): 194–201. http://dx.doi.org/10.1109/mcom.2016.1600067cm.

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24

Mi, Jun, Kun Wang, Peng Li, Song Guo, and Yanfei Sun. "Software-Defined Green 5G System for Big Data." IEEE Communications Magazine 56, no. 11 (November 2018): 116–23. http://dx.doi.org/10.1109/mcom.2017.1700048.

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25

Sun, Yuzhong, Yiqiang Zhao, Ying Song, Yajun Yang, Haifeng Fang, Hongyong Zang, Yaqiong Li, and Yunwei Gao. "Green challenges to system software in data centers." Frontiers of Computer Science in China 5, no. 3 (May 20, 2011): 353–68. http://dx.doi.org/10.1007/s11704-011-0369-3.

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26

Fakhar, Faiza, Barkha Javed, Raihan ur Rasool, Owais Malik, and Khurram Zulfiqar. "Software level green computing for large scale systems." Journal of Cloud Computing: Advances, Systems and Applications 1, no. 1 (2012): 4. http://dx.doi.org/10.1186/2192-113x-1-4.

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27

Saraiva, João, Rui Abreu, Jácome Cunha, and João Paulo Fernandes. "GreenSoftwareLab: Towards an Engineering Discipline for Green Software." Impact 2018, no. 1 (March 20, 2018): 9–11. http://dx.doi.org/10.21820/23987073.2018.9.

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28

Raisian, Komeil, Jamaiah Yahaya, and Aziz Deraman. "Exploring Potential Factors in Green and Sustainable Software Product." JOIV : International Journal on Informatics Visualization 2, no. 1 (January 5, 2018): 23. http://dx.doi.org/10.30630/joiv.2.1.100.

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software engineering is a principle role of our activity in social and economic life. Software engineers are starting to comprehend the significance of designing sustainability regarding software processes. The field of sustainable and green software and green software engineering is still young. Thus, in modern society, researches effort is mainly focused on green and sustainable software engineering itself. In other words, the aim of this study at hand aims an in-depth understanding of the related potential factors for the purpose of improving the recently reluctant trend of sustainability dimension in green software based on life cycle of green software product process. To reach this purpose, this study is reviewed latest research and used conceptual model. A conceptual model is rendered demonstrating the consolidated life cycles of sustainable product and principle sustainable measurement dimensions, for example, energy or information efficiency, low cost, Resource efficiency, Waste reduction, Equality support and human health.

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29

Ansari, Mohammed Afzal, and Kiran Bhimrao Ingle. "Software Testing." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 979–84. http://dx.doi.org/10.22214/ijraset.2022.43914.

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Abstract— With the developing complexity of today’s software program applications injunction with the increasing competitive pressure has driven the excellent assurance of developed software towards new heights. software program trying out is an inevitable part of the software program development Lifecycle and retaining in keeping with its criticality in the pre and submit development process makes it something that have to be catered with stronger and green methodologies and strategies. This paper objectives to speak about the prevailing in addition to advanced trying out techniques for the betterquality warranty functions. Keywords— Testing Methodologies, Software Testing Life Cycle, Testing Frameworks, Automation Testing, Test Driven Development, Test optimization, Quality Metrics

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30

Beghoura, Mohamed Amine, Abdelhak Boubetra, and Abdallah Boukerram. "Green software requirements and measurement: random decision forests-based software energy consumption profiling." Requirements Engineering 22, no. 1 (July 26, 2015): 27–40. http://dx.doi.org/10.1007/s00766-015-0234-2.

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31

Bochare, Rewa, and Poonam Bagora. "Comparative Analysis of Green Building Rating Systems for Residential House: A Case Study." ECS Transactions 107, no. 1 (April 24, 2022): 7091–101. http://dx.doi.org/10.1149/10701.7091ecst.

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Rating a building for its ecological sustainability and energy efficient is the new black in the construction industry. In this study, we assessed a small house for green building optimization and energy efficient rating with the help of two softwares, namely EDGE (Excellence in Design for Greater Efficiencies) for green building rating and IGBC Green New Building Rating SystemVersion 3.0. The former is cost effective software, furnishing detailed results about optimal design aspects for the green buildings like energy efficiency, water efficiency, and material efficiency. The latter, however, is a certified rating system assessing the drawings on similar criteria as EDGE but delivering overall points for the building (out of 100), thereby providing the performance level in terms of certified levels namely Certified, Silver, Gold, Platinum, and Super Platinum. After performing analysis for the case plan, using EDGE software, the energy efficiency measured 57.93%, water efficiency was 66.24%, and material efficiency was 81%. Upon using the IGBC green house rating system software, 65 points were matched out of 100 for our case plan. Thus, the certification level was Silver and recognition achieved was Best Practices.

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32

Cheng, Yu Han, Shao Bai Zhang, and Jian Bin Cheng. "Green Experiment and Green Network." Applied Mechanics and Materials 291-294 (February 2013): 3056–59. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.3056.

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In the "sustainable development" under the influence of ethics, professional colleges and universities Electricity experiments and the campus network are facing new opportunities and challenges. This paper that presents experimental and universities should carry out green building green campus, discusses in detail the power class of "green experiment" and college "green network" of the specific content of the power class that should focus on the development of laboratory simulation experiments, virtual experiments, the network test and saving experiment, so we can build an energy-based, health-based, harmony-based network software and hardware environment in the "green network"; green experiments and the specific implementation method about green network had been launched a more in-depth discussion and analysis which are a kinds of colleges and universities and networking power quasi-experimental values of the new goals and explore.

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33

Want, Roy. "How Green Is Green?" IEEE Pervasive Computing 8, no. 1 (January 2009): 2–4. http://dx.doi.org/10.1109/mprv.2009.8.

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34

Lanatri Danirmala. "THE MEDIATING ROLE OF GREEN TRAINING TO THE INFLUENCE OF GREEN ORGANIZATIONAL CULTURE TO GREEN ORGANIZATIONAL CITIZENSHIP BEHAVIOR AND GREEN EMPLOYEE INVOLVEMENT." IJHCM (International Journal of Human Capital Management) 6, no. 1 (June 30, 2022): 66–75. http://dx.doi.org/10.21009/ijhcm.06.01.6.

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At present, concern for the environment is being intensified by companies around the world. Employees in the organization are taught and provided with knowledge, learning, and real practice to care for the environment. Companies must have a competitive advantage to differentiate them from other companies. One way is to apply environmental care. In order to implement these goals, the company applies various ways to achieve them. Green Human Resource Management (GHRM) is an environmental management practice that is supported by human resources, because it can stimulate organizational success. This research used online survey on 211 respondents. Validity and reliability were tested by factor analysis using SPSS 15.0 software which stated that all items were valid and reliable. The hypothesis was tested using WarpPLS 7.0 software. All hypotheses are supported, green organizational culture has a positive and significant effect on green training, green training has a positive and significant effect on organizational citizenship behavior environment, green training has a positive and significant effect on green employee involvement, there is an indirect effect on organizational citizenship behavior environment and green employee involvement mediated by green training.

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35

Román-Augusto, Jose Antonio, Camila Garrido-Lecca-Vera, Manuel Luis Lodeiros-Zubiria, and Martin Mauricio-Andia. "How to Reach Green Word of Mouth through Green Trust, Green Perceived Value and Green Satisfaction." Data 8, no. 2 (January 19, 2023): 25. http://dx.doi.org/10.3390/data8020025.

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The production and consumption of green food products have become hot topics in marketing. Companies are implementing marketing strategies such as green perceived value, green trust, and green satisfaction to guarantee green word of mouth. An online questionnaire distributed through social media was used to collect the data. The sample consists of 297 people. The 297 responses were coded and analysed with the Software Smart-PLS. The data described include the sample sociodemographic profile, the descriptive analysis of all items, the reliability and validity of the measures of the reflective model and the evaluation of the results of the structural model. Four hypotheses included in the PLS-SEM proposed were validated for a p-value of 0.001. The results confirmed the influence of green perceived value on green trust and green satisfaction. Moreover, the results highlight that green satisfaction and green trust influence green word of mouth.

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36

Raisian, Komeil, Jamaiah Yahaya, and Aziz Deraman. "Green Measurements for Software Product Based on Sustainability Dimensions." Computer Systems Science and Engineering 41, no. 1 (2022): 271–88. http://dx.doi.org/10.32604/csse.2022.020496.

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37

El-Ahwal, Mostafa, ashraf elmokadem, and Dalia EL-Gheznawy. "Green Roof Analysis and Design Software Calculator in Egypt." Port-Said Engineering Research Journal 20, no. 1 (March 1, 2016): 12–20. http://dx.doi.org/10.21608/pserj.2016.33626.

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38

Huang, Xumin, Rong Yu, Jiawen Kang, Yue Gao, Sabita Maharjan, Stein Gjessing, and Yan Zhang. "Software Defined Energy Harvesting Networking for 5G Green Communications." IEEE Wireless Communications 24, no. 4 (August 2017): 38–45. http://dx.doi.org/10.1109/mwc.2017.1600360.

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39

Zhong, Weifeng, Rong Yu, Shengli Xie, Yan Zhang, and Danny H. K. Tsang. "Software Defined Networking for Flexible and Green Energy Internet." IEEE Communications Magazine 54, no. 12 (December 2016): 68–75. http://dx.doi.org/10.1109/mcom.2016.1600352cm.

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40

Maevsky, Dmitry, Elena Maevskaya, Ludmila Shapa, and Dmitry Stetsyuk. "Program Tools for Estimation of the Green Software Reliability." ITM Web of Conferences 9 (2017): 03008. http://dx.doi.org/10.1051/itmconf/20170903008.

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41

Zhou, Zhang Bing, Wendong Xiao, Jucheng Yang, and Faming Gong. "Special issue on green networking, computing, and software systems." Journal of Network and Computer Applications 59 (January 2016): 1–3. http://dx.doi.org/10.1016/j.jnca.2015.11.008.

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42

Tarantino, Matteo, and Basile Zimmermann. "Database Green: Software, Environmentalism and Data Flows in China." China Quarterly 229 (January 31, 2017): 205–17. http://dx.doi.org/10.1017/s0305741016001600.

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AbstractSignificant efforts towards environmental transparency have been made by the Chinese government since 2008. This paper focuses on the technical decisions shaping a database of official pollution information built and operated by a Chinese NGO known as the Institute of Public and Environmental Affairs (IPE). Issues of standardization, power distribution and institutional fragmentation are discussed. The paper illustrates a case of NGOs integrating enforcement capabilities as data centres amidst the growing reliance on processes of informational governance of environmental issues.

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43

Hou, Gang, Kuanjiu Zhou, Tie Qiu, Xun Cao, Mingchu Li, and Jie Wang. "A novel green software evaluation model for cloud robotics." Computers & Electrical Engineering 63 (October 2017): 139–56. http://dx.doi.org/10.1016/j.compeleceng.2017.08.021.

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44

Kumar, Pradeep, Shailendra Narayan Singh, and Sudhir Dawra. "Green factors of referential value-based software component repository." International Journal of Cloud Computing 9, no. 2/3 (2020): 178. http://dx.doi.org/10.1504/ijcc.2020.10031534.

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45

Kumar, Pradeep, Shailendra Narayan Singh, and Sudhir Dawra. "Green factors of referential value-based software component repository." International Journal of Cloud Computing 9, no. 2/3 (2020): 178. http://dx.doi.org/10.1504/ijcc.2020.109369.

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46

Chauhan, Nitin Singh, and Ashutosh Saxena. "A Green Software Development Life Cycle for Cloud Computing." IT Professional 15, no. 1 (January 2013): 28–34. http://dx.doi.org/10.1109/mitp.2013.6.

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47

Su, Bo. "Research on Green Hotels Based on Green Materials." Applied Mechanics and Materials 340 (July 2013): 325–28. http://dx.doi.org/10.4028/www.scientific.net/amm.340.325.

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While the hardware of the domestic hotel has reached the international first-class, there is still much room left in software and benefit level at present. According to the outlook on scientific development and the requirement of sustainable development, we have to face up to the problem of the lack of environmental protection in the course of hotel construction in the tide of global competition. The author puts forward some problems in the transition process from the traditional hotel to green hotel. The author also gives corresponding countermeasures to solve the problems in the hotel industry through the explanation of the green hotels.

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48

Baek, Woongki, and Trishul M. Chilimbi. "Green." ACM SIGPLAN Notices 45, no. 6 (June 12, 2010): 198–209. http://dx.doi.org/10.1145/1809028.1806620.

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Román-Augusto, Jose Antonio, Camila Garrido-Lecca-Vera, Manuel Luis Lodeiros-Zubiria, and Martin Mauricio-Andia. "Green Marketing: Drivers in the Process of Buying Green Products—The Role of Green Satisfaction, Green Trust, Green WOM and Green Perceived Value." Sustainability 14, no. 17 (August 25, 2022): 10580. http://dx.doi.org/10.3390/su141710580.

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Green marketing is currently one of the most powerful strategies in the corporate world as it responds to a growing demand for green products. Therefore, this study aims to analyse the influence of green perceived value on green trust and green satisfaction, study how both variables impact green word of mouth in turn and, at the same time, how the three variables influence green purchase intention. Data collection was carried out through a digital survey of buyers of green products. The hypotheses posed were solved with a PLS-SEM model through the Smart-PLS software. The results showed that green perceived value positively affects green trust and green satisfaction. Furthermore, green satisfaction was found to influence green trust and green WOM. Green trust also influences green WOM. Regarding the antecedents of green purchase intention, only green satisfaction and green trust showed a positive relationship. In contrast, green WOM did not show a relationship with green purchase intention. The article shows the importance of green satisfaction for green companies in achieving green purchase intention, green WOM and green trust. Green perceived value is also an important variable, as it is the trigger for the process that leads to green purchase intention.

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Gil, David, Jose Fernández-Alemán, Juan Trujillo, Ginés García-Mateos, Sergio Luján-Mora, and Ambrosio Toval. "The Effect of Green Software: A Study of Impact Factors on the Correctness of Software." Sustainability 10, no. 10 (September 28, 2018): 3471. http://dx.doi.org/10.3390/su10103471.

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Unfortunately, sustainability is an issue very poorly used when developing software and hardware systems. Lately, and in order to contribute to the earth sustainability, a new concept emerged named Green software which is computer software that can be developed and used efficiently and effectively with minimal or no impact to the environment. Currently, new teaching methods based on students’ learning process are being developed in the European Higher Education Area. Most of them are oriented to promote students’ interest in the course’s contents and offer personalized feedback. Online judging is a promising method for encouraging students’ participation in the e-learning process, although it still has to be researched and developed to be widely used and in a more efficient way. The great amount of data available in an online judging tool provides the possibility of exploring some of the most indicative attributes (e.g., running time, memory) for learning programming concepts, techniques and languages. So far, the most applied methods for automatically gathering information from the judging systems are based on statistical methods and, although providing reasonable correlations, these methods have not been proven to provide enough information for predicting grades when dealing with a huge amount of data. Therefore, the great novelty of this paper is to develop a data mining approach to predict program correctness as well as the grades of the students’ practices. For this purpose, powerful data mining technologies taken from the artificial intelligence domain have been used. In particular, in this study, we have used logistic regression, decision trees, artificial neural network and support vector machines; which have been properly identified as the most suitable ones for predicting activities in the e-learning domains. The results have achieved an accuracy of around 74%, both in the prediction of the program correctness as well as in the practice grades’ prediction. Another relevant issue provided in this paper is a comparison among these four techniques to obtain the best accuracy in predicting grades based on the availability of data as well as their taxonomy. The Decision Trees classifier has obtained the best confusion matrix, and time and memory efficiency were identified as the most important predictor variables. In view of these results, we can conclude that the development of green software leads programmers to implement correct software.

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