Refine your search
Collections
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Corchado, Juan M.
- Blockchain for Democratic Voting:How Blockchain Could Cast of Voter Fraud
Abstract Views :166 |
PDF Views:0
Authors
Affiliations
1 BISITE Digital Innovation Hub, University of Salamanca. Edificio Multiusos I+D+i, 37007, Salamanca, ES
2 Osaka Institute of Technology, Osaka, JP
1 BISITE Digital Innovation Hub, University of Salamanca. Edificio Multiusos I+D+i, 37007, Salamanca, ES
2 Osaka Institute of Technology, Osaka, JP
Source
Oriental Journal of Computer Science and Technology, Vol 11, No 1 (2018), Pagination: 1-3Abstract
During a political elections campaign, citizens learn about candidates and decide who they support. Once this period is over, they go to vote for the candidate of their choice. However, we must question the reliability of our voting procedures and look at how technology can be used to make these procedures more secure. The application of Blockchain technology could prevent electoral fraud as it provides a clear record of the votes cast and avoids any risk of a rigged election. Furthermore, if Blockchain is incorporated into the electoral system, the State would no longer be an intermediary. Blockchain allows people to authenticate themselves with their personal data provided on the blockchain. Therefore, the incorporation of Blockchain into the election process would prevent electoral fraud and interference of external agents, such as the state attempting to manipulate the election results.Full Text
References
- Satoshi Nakamoto. (2008) Bitcoin: A Peer-to-Peer Electronic Cash System. Retrieved from https://bitcoin.org/bitcoin.pdf
- A pplication of Blockchain Technology in online voting University of Maryland University Col-lege (UMUC) (2017). Online available: https://www.rsaconference.com/writable/files/About/application_ of_blockchain_technology_in_online_voting.pdf
- Li, T., Corchado, J. M., & Sun, S. (2017). Partial consensus and conservative fusion of gaussian mixtures for distributed PHD fusion. arXiv preprint arXiv:1711.10783.
- Bajo M and Corchado Juan M., 2018. Neural networks in distributed computing and artificial intelligence. Neurocomput. 272, C (January 2018), 1-2.
- Gazafroudi, A. S., & Corchado, J. M. Multi Agent-based Smart Home Electricity System Considering Electric Vehicle (2018).
- Virtual Agent Organizations to Optimize Energy Consumption in Households
Abstract Views :176 |
PDF Views:0
Authors
Affiliations
1 BISITE Digital Innovation Hub, University of Salamanca. Edificio Multiusos I+D+i, 37007, Salamanca, ES
2 Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, 535-8585 Osaka, JP
1 BISITE Digital Innovation Hub, University of Salamanca. Edificio Multiusos I+D+i, 37007, Salamanca, ES
2 Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, 535-8585 Osaka, JP
Source
Oriental Journal of Computer Science and Technology, Vol 11, No 2 (2018), Pagination: 72-74Abstract
Sadly, not everyone agrees with this scientifically proven fact; there are many sceptics around the world who deny the very existence of global warming or the idea of humans being able to positively or negatively influence these changes. However, it has been proven that this undoubtedly complex problem can be resolved to a large degree if we individually take measures in the correct direction. Simple solutions, such as saving and using our energy in a more efficient way at home will have a positive impact on reducing the adverse effects of climate change on our planet. Some proposals were aimed at using energy in buildings more efficiently. This solution makes it possible to reduce electricity bills, accounting for around 70% of the annual bill payment. On the basis of these factors temperature can be adjusted to reduce unnecessary energy consumption while maintaining the residents’ comfort.Full Text
References
- Mozer, M. C. (1998). The neural network house: An environment hat adapts to its inhabit-ants. In Proc. AAAI Spring Symp. Intelligent Environments (Vol. 58)
- Hoes, P., Hensen, J. L. M., Loomans, M. G. L. C., De Vries, B., & Bourgeois, D. (2009). User behavior in whole building simulation. Energy and buildings, 41(3), 295-302.
- Gonzalez-Briones, A., Prieto, J., De La Prieta, F., Herrera-Viedma, E., & Corchado, J. M. (2018). Energy Optimization Using a Case-Based Reasoning Strategy. Sensors, 18(3), 865.
- Gonzalez-Briones, A., Chamoso, P., Yoe, H., & Corchado, J. M. (2018). GreenVMAS: Virtual Organization Based Platform for Heating Greenhouses Using Waste Energy from Power Plants. Sensors, 18(3), 861.
- Machine Learning in Music Generation
Abstract Views :171 |
PDF Views:0
Authors
Affiliations
1 BISITE Digital Innovation Hub, University of Salamanca. Edificio Multiusos I+D+i, Salamanca, ES
2 Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, Osaka, JP
1 BISITE Digital Innovation Hub, University of Salamanca. Edificio Multiusos I+D+i, Salamanca, ES
2 Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, Osaka, JP
Source
Oriental Journal of Computer Science and Technology, Vol 11, No 2 (2018), Pagination: 75-77Abstract
The different computational advances in the field of Artificial Intelligence (AI) have attracted the attention of researchers with all kinds of origins, background and motivations. From an interdisciplinary research that sits at the intersection of the fields of AI, psychology, cognitive science, linguistics, anthropology and other human-centered sciences born the area of Computational Creativity (CC). CC can be defined as a “philosophy, science and engineering of computational systems which, by taking on particular responsibilities, exhibit behaviours that unbiased observers would deem to be creative”.Full Text
References
- M. Navarro-Caceres, J. Bajo, and J. M. Corchado, “Applying social computing to generate sound clouds,” Eng. Appl. Artif. Intell., vol. 57, pp. 171–183, 2017.
- J. M. Corchado and R. Laza, “Constructing deliberative agents with case-based reasoning technology,” Int. J. Intell. Syst., vol. 18, no. 12, pp. 1227–1241, 2003.
- S. Rodriguez, V. Julian, J. Bajo, C. Carrascosa, V. Botti, and J. M. Corchado, “Agent-based virtual organization architecture,” Eng. Appl. Artif. Intell., vol. 24, no. 5, pp. 895–910, 2011.
- M. Delgado, W. Fajardo, and M. Molina-Solana, “Inmamusys: Intelligent multiagent music system,” Expert Syst. Appl., vol. 36, no. 3, pp. 4574–4580, 2009.
- A. Moroni, J. Manzolli, F. Von Zuben, and R. Gudwin, “Vox populi: An Interactive Evolutionary System for Algorithmic Music Composition,” Leonardo Music J., vol. 10, pp. 49–54, 2000.
- M. Navarro, M. Caetano, G. Bernardes, L. N. de Castro, and J. M. Corchado, “Automatic generation of chord progressions with an artifificial immune system,” in International Conference on Evolutionary and Biologically Inspired Music and Art, 2015, pp. 175–186.
- Towards Financial Valuation in Data-Driven Companies
Abstract Views :235 |
PDF Views:1
Authors
Affiliations
1 BISITE Research Group, University of Salamanca. Edificio I+D+i, Calle Espejo2, 37007, Salamanca, ES
2 Air Institute, IoT Digital Innovation Hub, Carbajosa de la Sagrada, 37188, Salamanca, ES
1 BISITE Research Group, University of Salamanca. Edificio I+D+i, Calle Espejo2, 37007, Salamanca, ES
2 Air Institute, IoT Digital Innovation Hub, Carbajosa de la Sagrada, 37188, Salamanca, ES
Source
Oriental Journal of Computer Science and Technology, Vol 12, No 2 (2019), Pagination: 28-33Abstract
The following work presents a methodology of determining the economic value of the data owned by a company in a given time period. The ability to determine the value of data at any point of its lifecycle, would make it possible to study the added value that data gives to a company in the long term. Not only external data should be considered but also the impact that the internal data can have on company revenues. The project focuses on data-driven companies, which are different to the data-oriented ones, as explained below. Since some studies affirm that data-driven companies are more profitable, the indirect costs of using those data must be allocated somewhere to understand their financial value14 and to present a possible alternative for measuring the financial impact of data on the revenue of companies.Keywords
Case-Based Reasoning, Data-Driven Companies, Financial Valuation, Recommendation Systems.Full Text
References
- Terje Aven. A conceptual framework for linking risk and the elements of the data– information–knowledge–wisdom (dikw) hierarchy. Reliability Engineering & System Safety, 111:30–36, 2013.
- Amos Azaria, Avinatan Hassidim, Sarit Kraus, Adi Eshkol, Ofer Weintraub, and Irit Netanely. Movie recommender system for profit maximization. In Proceedings of the 7th ACM conference on Recommender systems, pages 121–128. ACM, 2013.
- Aniello Castiglione, Marco Gribaudo, Mauro Iacono, and Francesco Palmieri. Exploiting mean field analysis to model performances of big data architectures. Future Generation Computer Systems, 37:203–211, 2014.
- Pablo Chamoso, Alfonso González-Briones, and Francisco José García-Peñalvo. Data analysis platform for the optimization of employability in technological profiles. In Inter-national Conference on Practical Applications of Agents and Multi-Agent Systems, pages 322–325. Springer, 2019.
- Hsinchun Chen, Roger HL Chiang, and Veda C Storey. Business intelligence and analytics: From big data to big impact. MIS quarterly, 36(4), 2012.
- Yuri Demchenko, Cees De Laat, and Peter Membrey. Defining architecture components of the big data ecosystem. In 2014 International Conference on Collaboration Technologies and Systems (CTS), pages 104–112. IEEE, 2014.
- Daniel M Fleder and Kartik Hosanagar. Recommender systems and their impact on sales diversity. In Proceedings of the 8th ACM conference on Electronic commerce, pages 192–199. ACM, 2007.
- David García-Retuerta, Álvaro Bartolomé, Pablo Chamoso, Juan M Corchado, and Al-fonso González-Briones. Original content verification using hash-based video analysis. In International Symposium on Ambient Intelligence, pages 120–127. Springer, 2019.
- Rashi Glazer. Measuring the value of information: The information-intensive organiza-tion. IBM Systems Journal, 32(1):99–110, 1993.
- Alfonso González-Briones, Pablo Chamoso, Roberto Casado-Vara, Alberto Rivas, Sigeru Omatu, and Juan M Corchado. Internet of things platform to encourage recycling in a smart city. 2019.
- A l fonso González-Briones, Javier Prieto, Fernando De La Prieta, Enrique Herrera-Viedma, and Juan Corchado. Energy optimization using a case-based reasoning strategy. Sensors, 18(3):865, 2018.
- Alfonso González-Briones, Alber to Rivas, Pablo Chamoso, Roberto CasadoVara, and Juan Manuel Corchado. Case-based reasoning and agent based job offer recommender system. In The 13th International Conference on Soft Computing Models in Industrial and Environmental Applications, pages 21–33. Springer, 2018.
- Jo Yong Ju, Il Young Choi, Hyun Sil Moon, and Jae Kyeong Kim. Reinforcement learning for profit maximization of recommender systems. 2017.
- Steve Lohr. The age of big data. New York Times, 11(2012), 2012.
- Daniel L Moody and Peter Walsh. Measuring the value of information-an asset valuation approach. In ECIS, pages 496–512, 1999.
- Paul Resnick and Hal R Varian. Recommender systems. Communications of the ACM, 40(3):56–59, 1997.
- Alberto Rivas, Pablo Chamoso, Alfonso González-Briones, Roberto Casado-Vara, and Juan Manuel Corchado. Hybrid job offer recommender system in a social network. Expert Systems, page e12416.
- Alberto Rivas, Jesús M Fraile, Pablo Chamoso, Alfonso González-Briones, Sara Ro-dríguez, and Juan M Corchado. Students performance analysis based on machine learning techniques. In International Workshop on Learning Technology for Education in Cloud, pages 428–438. Springer, 2019.
- Alberto Rivas, Jesús M Fraile, Pablo Chamoso, Alfonso González-Briones, Inés Sittón, and Juan M Corchado. A predictive maintenance model using recurrent neural networks. In International Workshop on Soft Computing Models in Industrial and Environmental Applications, pages 261–270. Springer, 2019.