Emotionally-Related Song Playing System for Users that Makes Use of Force Sensor
Keywords:
software requirement specification, robust transactional property graph database, Cypher, graph query language, class-based, object-oriented, computer programming language, graphical user interface eclipseAbstract
A user's mood is just as important as their past tastes or the type of music they listen to when deciding what to play. In order to discover a user's emotional state from signals collected by wearable physiological sensors, this research suggests a framework for music recommendations based on emotions. Specifically, a wearable computer that incorporates a Force sensor may identify the user's emotional state. Any recommendation engine that relies on collaboration or content can use this emotional data as supplemental information. You can use this data to make the recommendation engines that are already out there even better. In our suggested system, we want to detect the user's emotions and play music automatically based on those feelings. The sensors we've supplied act as the user's biological mental signal, which it then converts into an equivalent electrical signal. The music player then plays the songs based on this electrical signal. In the future, wearable gear can be used to improve this system even further. The bracelet has a built-in force sensor that can detect an emotional signal and provide music recommendations based on that reading.
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R. Rai and J. H. Kim, “Effect Of Storage Temperature And Cultivars On Seed Germination OF Lilium×formolongi HORT.,” Journal of Experimental Biology and Agricultural Sciences, vol. 8, no. 5, pp. 621–627, Oct. 2020.
R Rai, &J.H. Kim ,Estimation of combining ability and gene action for growth and flowering traits in Lilium longiflorum.International Journal of Advanced Science and Technology,Vol.29 No.8S pp 1356-1363,2020
R. Rai, A. Badarch, and J.-H. Kim, “Identification Of Superior Three Way-Cross F1s, Its Line×Tester Hybrids And Donors For Major Quantitative Traits In Lilium×formolongi,” Journal of Experimental Biology and Agricultural Sciences, vol. 8, no. 2, pp. 157–165, Apr. 2020.
R. Rai, J. Shrestha, and J. Kim, “Line×tester analysis in lilium×formolongi: identification of superior parents for growth and flowering traits,” SAARC Journal of Agriculture, vol. 17, no. 1, pp. 175–187, Aug. 2019.
R. Rai,J.Shrestha and J.H.Kim “Combining Ability and Gene Action Analysis of Quantitative Traits in Lilium × formolongi,” vol. 30, no. 3, pp. 131–143, Dec. 2018.
T. X. Nguyen, S.-I. Lee, R. Rai, N. Kim, and Jong Hwa Kim, “Ribosomal DNA locus variation and REMAP analysis of the diploid and triploid complexes ofLilium lancifolium,” Genome, vol. 59, no. 8, pp. 551–564, Aug. 2016.
N. X. Truong, J. Y. Kim, R. Rai, J. H. Kim, N. S. Kim, and A. Wakana, “Karyotype Analysis of Korean Lilium maximowiczii Regal Populations,” Journal of The Faculty of Agriculture Kyushu University, vol. 60, no. 2, pp. 315–322, Sep. 2015.
Tak, A. (2021). Multi-Modal Fusion for Enhanced Image and Speech Recognition in AI Systems. International Journal of Science and Research, 10(6), 1780-1788.
Tak, A. (2021). The Data Mining Techniques for Analyzing Employee Performance and Productivity. International Journal of Science and Research, 10(10), 1575-1578.
Tak, A. (2022). The Impact of Electronic Health Records on Patient Care in the US Healthcare System. Journal of Health Statistics Reports, 1(2), 1–7.
Tak, A. (2022). Big Data Analytics in Healthcare: Transforming Information into Actionable Insights. Journal of Health Statistics Reports, 1(3), 1-6.
Tak, A. (2023). The Role of Cloud Computing in Modernizing Healthcare IT Infrastructure. Journal of Artificial Intelligence & Cloud Computing, 2(2), 1–7.
Tak, A., & Sundararajan, V. (2023, December 2). Pervasive Technologies and Social Inclusion in Modern Healthcare: Bridging the Digital Divide. FMDB Transactions on Sustainable Health Science Letters, 1(3), 118-129.
Gaurav Kumawat, Santosh Kumar Viswakarma, Prasun Chakrabarti , Pankaj Chittora, Tulika Chakrabarti , Jerry Chun-Wei Lin, “Prognosis of Cervical Cancer Disease by Applying Machine Learning Techniques”, Journal of Circuits, Systems, and Computers, 2022.
Akhilesh Kumar Sharma, Gaurav Aggarwal, Sachit Bhardwaj, Prasun Chakrabarti, Tulika Chakrabarti, Jemal Hussain, Siddhartha Bhattarcharyya, Richa Mishra, Anirban Das, Hairulnizam Mahdin, “Classification of Indian Classical Music with Time-Series Matching using Deep Learning”, IEEE Access , 9 : 102041-102052 , 2021.
Akhilesh Kumar Sharma, Shamik Tiwari, Gaurav Aggarwal, Nitika Goenka, Anil Kumar, Prasun Chakrabarti, Tulika Chakrabarti, Radomir Gono, Zbigniew Leonowicz, Michal Jasiński , “Dermatologist-Level Classification of Skin Cancer Using Cascaded Ensembling of Convolutional Neural Network and Handcrafted Features Based Deep Neural Network”, IEEE Access , 10 : 17920-17932, 2022.
Abrar Ahmed Chhipa , Vinod Kumar, R. R. Joshi, Prasun Chakrabarti, Michal Jaisinski, Alessandro Burgio, Zbigniew Leonowicz, Elzbieta Jasinska, Rajkumar Soni, Tulika Chakrabarti, “Adaptive Neuro-fuzzy Inference System Based Maximum Power Tracking Controller for Variable Speed WECS”, Energies ,14(19) :6275, 2021.
Chakrabarti P. , Goswami P.S., “Approach towards realizing resource mining and secured information transfer”, International Journal of Computer Science and Network Security, 8(7), pp.345-350, 2008.
Chakrabarti P., Choudhury A., Naik N. , Bhunia C.T., “Key generation in the light of mining and fuzzy rule”, International Journal of Computer Science and Network Security, 8(9), pp.332-337, 2008.
Chakrabarti P., De S.K., Sikdar S.C., “Statistical Quantification of Gain Analysis in Strategic Management” , International Journal of Computer Science and Network Security,9(11), pp.315-318, 2009.
Chakrabarti P. , Basu J.K. , Kim T.H., “Business Planning in the light of Neuro-fuzzy and Predictive Forecasting”, Communications in Computer and Information Science , 123, pp.283-290, 2010.
Prasad A. , Chakrabarti P., “Extending Access Management to maintain audit logs in cloud computing", International Journal of Advanced Computer Science and Applications ,5(3),pp.144-147, 2014.
Sharma A.K., Panwar A., Chakrabarti P. ,Viswakarma S., “Categorization of ICMR Using Feature Extraction Strategy and MIR with Ensemble Learning”, Procedia Computer Science, 57,pp.686-694,2015.
Patidar H. , Chakrabarti P., “A Novel Edge Cover based Graph Coloring Algorithm”, International Journal of Advanced Computer Science and Applications , 8(5),pp.279-286,2017.
Patidar H., Chakrabarti P., Ghosh A., “Parallel Computing Aspects in Improved Edge Cover based Graph Coloring Algorithm”, Indian Journal of Science and Technology ,10(25),pp.1-9,2017.
Tiwari M., Chakrabarti P, Chakrabarti T., “Novel work of diagnosis in liver cancer using Tree classifier on liver cancer dataset ( BUPA liver disorder )” , Communications in Computer and Information Science , 837, pp.155-160, 2018.
Verma K., Srivastava P. , Chakrabarti P., “Exploring structure oriented feature tag weighting algorithm for web documents identification”, Communications in Computer and Information Science ,837, pp.169-180, 2018.
Chakrabarti P. ,Chakrabarti T., Sharma M . , Atre D, Pai K.B., “Quantification of Thought Analysis of Alcohol-addicted persons and memory loss of patients suffering from stage-4 liver cancer”, Advances in Intelligent Systems and Computing, 1053, pp.1099-1105, 2020.
Chakrabarti P., Bane S.,Satpathy B.,Goh M, Datta B N , Chakrabarti T., “Compound Poisson Process and its Applications in Business”, Lecture Notes in Electrical Engineering, 601, pp.678-685,2020.
Chakrabarti P., Bhuyan B., Chaudhuri A. and Bhunia C.T., “A novel approach towards realizing optimum data transfer and Automatic Variable Key(AVK)” , International Journal of Computer Science and Network Security, 8(5), pp.241-250, 2008.
Chakrabarti P., Chakrabarti T., Satpathy B., SenGupta I . Ware J A., “Analysis of strategic market management in the light of stochastic processes, recurrence relation, Abelian group and expectation”, Advances in Artificial Intelligence and Data Engineering, 1133 , pp.701-710, 2020.
Chakrabarti P., Satpathy B., Bane S., Chakrabarti T., Chaudhuri N.S. , Siano P., “Business forecasting in the light of statistical approaches and machine learning classifiers”, Communications in Computer and Information Science , 1045, pp.13-21, 2019.
Kothi N., Laxkar P. Jain A. , Chakrabarti P., “Ledger based sorting algorithm”, Advances in Intelligent Systems and Computing, 989, pp. 37-46, 2020.
Magare A., Lamin M., Chakrabarti P., “Inherent Mapping Analysis of Agile Development Methodology through Design Thinking”, Lecture Notes on Data Engineering and Communications Engineering, 52, pp.527-534,2020.
Patidar H. , Chakrabarti P., “A Tree-based Graphs Coloring Algorithm Using Independent Set”, Advances in Intelligent Systems and Computing, 714, pp. 537-546, 2019.
Prince, Ananda Shankar Hati , Prasun Chakrabarti , Jemal Hussein , Ng Wee Keong , "Development of Energy Efficient Drive for Ventilation System using Recurrent Neural Network" , Neural Computing and Applications , 33 : 8659 , 2021.
Priyadarshi N., Bhoi A.K., Sahana S.K., Mallick P.K. , Chakrabarti P., Performance enhancement using novel soft computing AFLC approach for PV power system”, Advances in Intelligent Systems and Computing, 1040, pp.439-448,2020.
Priyadarshi N., Bhoi A.K., Sharma A.K., Mallick P.K. , Chakrabarti P., “An efficient fuzzy logic control-based soft computing technique for grid-tied photovoltaic system”, Advances in Intelligent Systems and Computing, 1040,pp.131-140,2020.
R, Steffi., S. Suman Rajest, R. Regin, and Shynu T. 2023. “Detection Of Prominent Objects by The Use of Deep Learning”. Central Asian Journal of Mathematical Theory and Computer Sciences 4 (5), 62-82.
R. Regin, S. Suman Rajest, Shynu T, & Steffi. R. (2023). Planning the Most Effective Itinerary for Tourists through the use of Data Analysis. International Journal of Human Computing Studies, 5(12), 77-92.
Rajest, S. S., Regin, R., T, Shynu., & R, Steffi. (2023). Treatment Method for Sewage Water Used in Horticulture. European Journal of Life Safety and Stability, 36(12), 11-27.
S. Silvia Priscila, S. Suman Rajest, R. Regin, Shynu T, & Steffi. R. (2023). Classification of Satellite Photographs Utilizing the K-Nearest Neighbor Algorithm. Central Asian Journal of Mathematical Theory and Computer Sciences, 4(6), 53-71.
S. Suman Rajest, R. Regin, Shynu T, & Steffi. R. (2023). An Approach Based on Machine Learning for Conducting Sentiment Analysis on Twitter Data. International Journal of Human Computing Studies, 5(12), 57-76.
S. Suman Rajest, R. Regin, Shynu T, & Steffi. R. (2023). Using Voice Guidance, an Intelligent Walking Assistance Mechanism for the Blind. Central Asian Journal of Theoretical and Applied Science, 4(11), 41-63. Retrieved from https://cajotas.centralasianstudies.org/index.php/CAJOTAS/article/view/1335
S. Suman Rajest, R. Regin, Shynu T, & Steffi. R. (2024). Analysis of Sentimental Bias the Implementation of Supervised Machine Learning Algorithms. International Journal of Innovative Analyses and Emerging Technology, 4(1), 8–33.
S. Suman Rajest, S. Silvia Priscila, R. Regin, Shynu T, & Steffi. R. (2023). Application of Machine Learning to the Process of Crop Selection Based on Land Dataset. International Journal on Orange Technologies, 5(6), 91-112.
Shah K., Laxkar P. , Chakrabarti P., “A hypothesis on ideal Artificial Intelligence and associated wrong implications”, Advances in Intelligent Systems and Computing, 989, pp.283-294, 2020.
Shynu T, S. Suman Rajest, R. Regin, & Steffi. R. (2023). Android Application for Remote Control of Personal Computers. International Journal on Orange Technologies, 5(12), 44-58.
Shynu T, S. Suman Rajest, R. Regin, & Steffi. R. (2023). Region Segmentation and Support Vector Machine for Brain Tumour Stage Analysis, Detection, and Automatic Classification. Central Asian Journal of Medical and Natural Science, 25-43.
Steffi. R, S. S. Rajest, R. Regin, Shynu T, & S. S. Priscila. (2023). Analysis of an Interview Based on Emotion Detection Using Convolutional Neural Networks. Central Asian Journal of Theoretical and Applied Science, 4(6), 78-102.
Steffi. R, Shynu T, S. Suman Rajest, & R. Regin. (2023). A Convolutional Neural Network with a U-Net for Brain Tumor Segmentation and Classification. Central Asian Journal of Medical and Natural Science, 4(6), 1326-1343.
Suman Rajest, S., Regin, R., Y, A., Paramasivan, P., Christabel, G. J. A., & T, Shynu. (2023). The Analysis of How Artificial Intelligence Has an Effect on Teachers and The Education System. EAI Endorsed Transactions on E-Learning, 9(4), 1-10.
Sundararajan, V., Steffi, R., & Shynu, T. (2023). Data Fusion Strategies for Collaborative Multi-Sensor Systems: Achieving Enhanced Observational Accuracy and Resilience. FMDB Transactions on Sustainable Computing Systems, 1(3), 112–123.
Tiwari M., Chakrabarti P , Chakrabarti T., “Performance analysis and error evaluation towards the liver cancer diagnosis using lazy classifiers for ILPD”, Communications in Computer and Information Science , 837, pp.161-168,2018.
V. K. Nomula, R. Steffi, and T. Shynu, “Examining the Far-Reaching Consequences of Advancing Trends in Electrical, Electronics, and Communications Technologies in Diverse Sectors,” FMDB Transactions on Sustainable Energy Sequence, vol. 1, no. 1, pp. 27–37, 2023.
Priscila, S. S., Rajest, S. S., T, S. and G, G. (2022) “An Improvised Virtual Queue Algorithm to Manipulate the Congestion in High-Speed Network”, Central Asian Journal of Medical and Natural Science, 3(6), pp. 343-360.
