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1

Sawlikar, Mr Akash, Mr Vrushant Jawlekar, SawlikarMiss Kanchan Uike, Miss Shweta Ingle, and Asst Prof Prachiti Deshpande. "Intelligent Medicine Suggestion System." International Journal of Research Publication and Reviews 6, no. 4 (2025): 5379–83. https://doi.org/10.55248/gengpi.6.0425.1498.

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Kashyap, Vipul, Dhruv Darji, Yash Mistry, and Prof Chhaya Dhavale. "Smart Agriculture Suggestion System." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (2022): 2121–27. http://dx.doi.org/10.22214/ijraset.2022.41717.

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Abstract: Agriculture is a career that has been performed for many years. However, as time passes, people's confidence in this profession is eroding. One of the reasons for this is that agriculture is practiced in an unscientific manner. Traditional approaches are getting less successful as time passes. To address this, the method described here analyses the current environmental and soil parameters and predicts the best crop for the scenario. This technology is intended to assist farmers by serving as a gateway between them and all accessible information. The project's main goal is to gather information from many sources on the internet and display it to the user in a user-friendly and understandable manner. This site will serve as a resource for farmers around the country, as 3well as a platform for them to connect and share their important resources and expertise with one another. We also want to dedicate a part of this programme solely to crop, equipment, and labour management. We want to make resource collection and farm management considerably more efficient. Keywords: Agriculture, Management, Sustainable Web, Android
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3

Kashyap, Vipul, Dhruv Darji, Yash Mistry, and Prof Chhaya Dhavale. "Smart Agriculture Suggestion System." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (2022): 2121–27. http://dx.doi.org/10.22214/ijraset.2022.41717.

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Abstract: Agriculture is a career that has been performed for many years. However, as time passes, people's confidence in this profession is eroding. One of the reasons for this is that agriculture is practiced in an unscientific manner. Traditional approaches are getting less successful as time passes. To address this, the method described here analyses the current environmental and soil parameters and predicts the best crop for the scenario. This technology is intended to assist farmers by serving as a gateway between them and all accessible information. The project's main goal is to gather information from many sources on the internet and display it to the user in a user-friendly and understandable manner. This site will serve as a resource for farmers around the country, as 3well as a platform for them to connect and share their important resources and expertise with one another. We also want to dedicate a part of this programme solely to crop, equipment, and labour management. We want to make resource collection and farm management considerably more efficient. Keywords: Agriculture, Management, Sustainable Web, Android
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4

Valarmathi.E, Valarmathi E., Aswin Gladsingh.R, Balajee V. Balajee.V, and Pratheep S. Pratheep.S. "AI-Chronic Disease Suggestion System." International Journal of Advanced Engineering, Management and Science 9, no. 2 (2023): 01–06. http://dx.doi.org/10.22161/ijaems.92.1.

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The core of artificial intelligence is certification. It demonstrates a productive method for resolving urgent issues, and it denotes how to approach a dataset. For speedier access and seamless client service, we integrate artificial intelligence into our concept. Tensor-flow is used in its development to accelerate activities and automate data collection. Our module is standardised using a standard scaler. Cross-validation is done using the grid-search CV approach. The random-forest algorithm is the algorithm that we defined here. We reduce processing time while increasing usability adaptability. We criticise the strong emphasis on current solutions when it comes to attribution as a process for knowledge development since this focus influences the knowledge structure. Like chronic illness, which takes a lengthy time to diagnose because it is a long-lasting sickness, everywhere on the globe, chronic diseases are dangerous illnesses that are more expensive to detect and force the patient to endure their effects for the rest of their lives. There is a wealth of information about these diseases in the medical field; thus, data mining techniques are used to simplify the healthcare system.
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5

Ferreira, Diogo, Mário Antunes, Diogo Gomes, and Rui L. Aguiar. "CLASSY: A Conversational Aware Suggestion System." Proceedings 31, no. 1 (2019): 40. http://dx.doi.org/10.3390/proceedings2019031040.

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Over the last few years, pervasive systems have seen some interesting development. Nevertheless, human–human interaction can also take advantage of those systems by using their ability to perceive the surrounding environment. In this work, we have developed a pervasive system – named CLASSY – that is aware of the conversational context and suggests documents potentially useful to the users based on an Information Retrieval system, and proposed a new scoring approach that uses semantics and distance based on proximity data in order to classify the relationship between tokens.
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6

Hadi, Mohammad, Haniye Sajjadi, Sara Baratpour, and Ali Toghiani. "Performance Evaluation of the Suggestion System." Medical Archives 67, no. 2 (2013): 131. http://dx.doi.org/10.5455/medarh.2013.67.131-133.

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7

Lasrado, Flevy, Mohammed Arif, and Aftab Rizvi. "The determinants for sustainability of an employee suggestion system." International Journal of Quality & Reliability Management 32, no. 2 (2015): 182–210. http://dx.doi.org/10.1108/ijqrm-02-2013-0035.

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Purpose – Although the corporations widely use the suggestion schemes to elicit the creative ideas of their employee, sustaining a suggestion scheme is still a challenge. Employee suggestion schemes have been studied from many perspectives to illustrate its objectives, nature, content, process, significance and the benefits. Arguments have also been made with respect to the success and failures of the suggestion schemes. The purpose of this paper is to explore the factors to assess the sustainability of a suggestion system. Design/methodology/approach – This paper thus explores the critical success factors of suggestion scheme through a literature review and filters the critical determinants for sustainability of suggestion using factor analysis. The data collection was done using a survey technique. Findings – The results identity the five major factors as determinants to sustainability of a suggestion system as reported in the paper. Originality/value – This paper has made an attempt to explore the determinants to assess the sustainability of a suggestion system and has contributed toward the new knowledge in terms of sustainability of a suggestion system.
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8

Et.al, Foo Yoke Ling. "Bus Ticketing System with Multiple Routes Suggestion." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 1816–24. http://dx.doi.org/10.17762/turcomat.v12i3.1010.

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An important part of the bus ticket booking system is the route. Online bus tickets are systems that integrate all the different bus organization routes. However, the existing online system only provides direct transportation to destinations. In many cases, customers will need to take some connecting buses before reaching their desired destination. Therefore, a multiple routes suggestion for bus ticketing system is introduced using an advance route generation algorithm. In addition to the basic features of the existing online system, the developed system offers recommended routes if the desired destination does not have a direct bus. The recommended route will be at several different bus operators and waiting time for the next route. The development of this system is expected to provide convenience for the customer to find multiple routes suggestion.
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9

Sharma, Ankit, and Ekta . "Review on Machine Learning Based Suggestion System." International Journal of Computer Sciences and Engineering 6, no. 4 (2018): 242–44. http://dx.doi.org/10.26438/ijcse/v6i4.242244.

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10

Podobina, V. M. "Suggestion to Create a New Foraminiferal System." Open Journal of Geology 07, no. 04 (2017): 577–87. http://dx.doi.org/10.4236/ojg.2017.74039.

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11

Versari, P. P., G. D'Aliberti, G. Talamonti, and M. Collice. "Foraminal syringomyelia: Suggestion for a grading system." Acta Neurochirurgica 125, no. 1-4 (1993): 97–104. http://dx.doi.org/10.1007/bf01401835.

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12

Aydar, Mehmet, and Serkan Ayvaz. "A Suggestion-Based RDF Instance Matching System." International Journal of Computer Theory and Engineering 9, no. 5 (2017): 380–84. http://dx.doi.org/10.7763/ijcte.2017.v9.1170.

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13

Yadav, Akash. "PassionPulse: Personalized Hobby Exploration and Suggestion System." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem44375.

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Abstract— In today’s fast-paced world, individuals often struggle to explore and pursue their personal interests and hobbies due to busy schedules and a lack of self-awareness regarding their preferences. PassionPulse: Personalized Hobby Exploration and Suggestion System aims to bridge this gap by leveraging a data-driven approach to recommend hobbies based on user responses. The system collects user inputs through a structured questionnaire, applies an internal mapping mechanism to analyze responses, and suggests personalized hobby recommendations. By integrating web technologies such as HTML, CSS, JavaScript, Bootstrap, and Spring Boot, along with MySQL for data management, the system ensures seamless functionality and user experience. Unlike conventional recommendation models, PassionPulse prioritizes a personalized and interactive approach, enabling users to discover hobbies aligned with their interests. The study explores the effectiveness of PassionPulse through user engagement and recommendation accuracy, highlighting its potential in self-discovery, mental well-being, and skill development. Additionally, the system presents future scalability options, including a hobby purchase feature to provide users with structured guidance for pursuing their interests. With a growing need for personalized recommendation systems in various domains, this research contributes to enhancing hobby exploration through intelligent, user-centric methodologies. Keywords— Data-Driven Recommendation, Hobby Exploration, Interest Mapping, Machine Learning, MySQL, Personalized Recommendation, Questionnaire-Based Analysis, Spring Boot, User Engagement, Web Technologies
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Olcay, Ayhan, Gamze Guler, and Ekrem Guler. "An alternative malpractice system suggestion for Turkey: Patient compensation system." Anatolian Journal of Cardiology 15, no. 9 (2015): 775–76. http://dx.doi.org/10.5152/anatoljcardiol.2015.6543.

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15

Patk, Jungyoon, and Hyunsun Choi. "How a Public Suggestion System can Increase Social Value?: A Case Study of the National Suggestion System in Korea." Korean Association of Governance Studies 30, no. 2 (2020): 59–88. http://dx.doi.org/10.26847/mspa.2020.30.2.59.

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16

UYAR, OKAN. "Preparing Diet List Suggestion with Fuzzy Expert System." International Journal of Intelligent Systems and Applications in Engineering 4, Special Issue-1 (2016): 58–62. http://dx.doi.org/10.18201/ijisae.266528.

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17

Kim, Taw-Wan, Il-Hyung Lim, Myeon-Song Choi, Seung-Jae Lee, and Sung-Chul Kwon. "IEC 61968/61970 based Distribution Management System Suggestion." Transactions of The Korean Institute of Electrical Engineers 60, no. 2 (2011): 231–38. http://dx.doi.org/10.5370/kiee.2011.60.2.231.

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18

C R, Nirmala. "A Coordinated Yield Suggestion System for Effective Cultivation." International Journal for Research in Applied Science and Engineering Technology 8, no. 9 (2020): 105–14. http://dx.doi.org/10.22214/ijraset.2020.31288.

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19

Kye, Min-Seok, Hyeon-Suk Jang, and Hoe-Kyung Jung. "Personal Training Suggestion System based on Hybrid App." Journal of the Korea Institute of Information and Communication Engineering 18, no. 6 (2014): 1475–80. http://dx.doi.org/10.6109/jkiice.2014.18.6.1475.

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20

Bonache, Jaime. "The International Transfer of an Idea Suggestion System." International Studies of Management & Organization 29, no. 4 (1999): 24–44. http://dx.doi.org/10.1080/00208825.1999.11656774.

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21

Wells, Jeffery P., Horacio R. Roman, and Ramona Houmanfar. "A Suggestion System for Youth for Juvenile Offenders." Journal of Organizational Behavior Management 26, no. 4 (2006): 19–40. http://dx.doi.org/10.1300/j075v26n04_02.

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22

Wi, Hansaem, Chan-Kuk Jang, Jae-Hoon Lee, and Okyeon Yi. "Suggestion SSL-VPN for Traffic Signal Control System." Advanced Science Letters 23, no. 12 (2017): 12725–28. http://dx.doi.org/10.1166/asl.2017.10887.

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23

Venkatesh, S. "Implementation of Low Cost Automatic Gear Suggestion System." International Journal on Recent and Innovation Trends in Computing and Communication 3, no. 4 (2015): 2034–36. http://dx.doi.org/10.17762/ijritcc2321-8169.150458.

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24

B M, Asst Prof Spoorthi. "IoT and Machine Learning Based Crop Suggestion System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem29821.

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The practise of analysing and extracting meaningful information from enormous amounts of data is referred to as data mining. Data mining is used in a wide range of industries, including banking, retail, medicine, agriculture, and so on. In agriculture, data mining is utilised to investigate the various biotic and abiotic factors that influence crops. Agriculture is India's most important industry, providing the majority of work possibilities. One of the most common issues that Indian farmers confront is choosing the right crop for their soil. As a result, they are experiencing a major drop in output. Precision agriculture has provided farmers with a solution to this problem. Agriculture with pinpoint accuracy Precision agriculture is a modern agricultural strategy that uses research data on soil features, soil types, and crop yield data to recommend the best crop to produce based on site-specific parameters to farmers. Precision agriculture is gaining popularity.
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25

Gohary, Ali, Hamid Alizadeh, and Kambiz Heidarzadeh Hanzaee. "How co-creation uplift suggestion systems’ performance." Asia-Pacific Journal of Business Administration 8, no. 2 (2016): 197–222. http://dx.doi.org/10.1108/apjba-11-2015-0095.

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Purpose – Suggestion systems have always been used as the means of continuous development and co-creating values among the employees of organizations. On the other hand, the co-creation has been introduced as a solution to co-create values between companies and customers. Since a simultaneous study on setting up suggestion systems and co-creation among employees and customers have been ignored so far, the purpose of this paper, focussing on the combination of two strategies of suggestion systems (generally more effective among the employees of organizations) and co-creation (studied so far merely the scope of customers), is to evaluate variables leading to intention to use, improvement in understanding the concept of justice, and positive word-of-mouth. Design/methodology/approach – Two between-subjects experiments were carried out to explore the interactional role of co-creation, reward, and time in efficiency of suggestion systems. The first study which was carried out among customers analyzed the effect of setting up suggestion systems along with co-creation on the amount of their intention to use this system in the future and positive word-of-mouth. The second study discussed the effect of setting up suggestion systems along with co-creation on the level of understanding organizational justice and commitment. Findings – The results indicate that the effectiveness of co-creation and tangible factors, such as offered reward, on improving the evaluation of suggestion system. In the other word, when firm’s encourage customers to participate in value co-creation program in suggestion system, they perceive more justice and intend to participate more in such program in future. Originality/value – Most of the previous studies carried out on co-creation considered its effectiveness on occasions when a service failure occurs to consumers and the service provider urgently needs service recovery, but this paper aimed to provide a collaborative perspective toward co-creation through suggestion system that puts emphasis on service experience, innovation, and intention to future participation in such programs.
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Mehdi, Tajpour, hajian Fatemeh, and Nabaei Amirmohammad. "The Impact of Suggestions to Entrepreneurial opportunity recognition Case study: Bank Tejart of Iran." International Journal of Management Sciences and Business Research 6, no. 12 (2017): 45–53. https://doi.org/10.5281/zenodo.3473872.

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this article was written with the aim of investigating the effect of the principled establishment of proposals on identification of entrepreneurial opportunities. In this paper, Bank Tejart of Iran has been selected as one of the organizations active in the field of suggestion system as the study organization. The suggestion system is known as a management tool that is used to establish participatory management in the organization. The institutionalization of this system in the organization, in addition to increasing creativity, motivation and morale of the personnel in the organization and spiritual effects, can lead to increased profitability and positive material effects. In this article, after reviewing the literature of the suggestion system and Entrepreneurial opportunity recognition, we first outline the effect of the Suggestion system on the organization on the personality characteristics of individuals, including creativity and risk-taking, and then the effect of these personality feature on Entrepreneurial opportunity recognition in the Bank Tejart of Iran Review. The findings of this qualitative research were carried out through the Focus Group method, whose members were experts in the suggestion system at the management consulting centers and the operators of this system at the Bank Tejart of Iran. These findings show the positive effect of the suggestion system on the creativity of the staff and managers of the bank. The positive effect of the suggestion system on the managers' risk-taking, the positive effect of creativity of the staff and managers on the identification of entrepreneurial opportunities, and ultimately the positive impact of personnel and managers risk-taking on the recognition of entrepreneurial opportunities at the Bank Tejart of Iran is The results of this research do not confirm the positive impact of the Suggestion system on personnel risk.
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Raushan, Ritik, Sangam Kumari, Sanskriti Singh, Pawan Mishra, Dr Vikas Singhal, and Dr Ajay Sahu. "AI Based Course Suggestion Portfolio." International Journal of Innovative Research in Advanced Engineering 11, no. 12 (2024): 847–53. https://doi.org/10.26562/ijirae.2024.v1112.03.

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The rapid expansion of online education platforms has fundamentally changed the way students engage with learning opportunities. Students now have access to a vast array of courses, offered by different institutions, in various fields of study, and at different levels. [1] However, with such an overwhelming selection, choosing the right courses that align with a student's academic path, interests, and career aspirations can be a daunting task. Traditional course recommendation systems, which have relied on simple rule-based or manual methods, often fall short of addressing the diverse and evolving needs of modern learners. [5] To solve these challenges, this paper proposes the development of an AI-powered course suggestion system that adapts to the individual needs of each student by using advanced machine learning techniques. Unlike traditional systems, which are confined to static rules or rigid structures, the AI-based system is designed to learn from each student's behaviour, interactions, and academic profile to offer personalized course recommendations that evolve over time.
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Guttiganur, Nagappa, Shivanand Aspalli, MuktaV Sanikop, Anupama Desai, Reetika Gaddale, and Archana Devanoorkar. "Classification systems for gingival recession and suggestion of a new classification system." Indian Journal of Dental Research 29, no. 2 (2018): 233. http://dx.doi.org/10.4103/ijdr.ijdr_207_17.

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Verma, Shraddha, Rutvik Kshirsagar, Khushboo Kulkarni, Sanyukta Deshmukh, and Shubhangi Bhagat. "Opinion and Suggestion Mining on Customer Reviews." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 2524–35. http://dx.doi.org/10.22214/ijraset.2023.52148.

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Abstract: Opinion and suggestion mining on customer reviews is a system providing both organizations and customers with valuable insights into the quality of products and services. The system operates on two perspectives, the customer, and the organization. For new customers, the system analyses reviews from previous customers to help them determine whether the product or service offered by the organization is worth purchasing. For organizations, the system performs suggestion mining on negative reviews to provide actionable feedback for improvements. Additionally, the system provides organizations with the percentage of customers who have liked or disliked their products or services, offering valuable insights into customer satisfaction. Overall, this project offers a valuable tool for organizations looking to improve their offerings and for customers seeking reliable information to inform their purchasing decisions
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30

Lasrado, Flevy. "Assessing sustainability of employee suggestion schemes: a framework." International Journal of Quality and Service Sciences 7, no. 4 (2015): 350–72. http://dx.doi.org/10.1108/ijqss-12-2014-0056.

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Purpose – The purpose of this paper is to assess the employee suggestion scheme of three organizations based in the United Arab Emirates. A framework that consists of five sustainability factors identified based on an empirical study has been applied. The sustainability factors identified through this study include leadership and organizational environment, system capability, system effectiveness, organizational encouragement and system barrier. The paper draws conclusions about the key practices necessary to foster sustainability of the employee suggestion system. The paper then presents a final framework that the organizations can apply to assess their suggestion schemes and to develop potential change strategies. The study findings reveal the importance of five factors, and with more cases, future research can be conducted to identify further practices relevant to specific industry. More levels of maturity for sustainability suggestion system could also be defined with future research. Design/methodology/approach – The assessment framework was developed drawing on a thorough review of the literature and data collected and analyzed using various statistical tools. The developed assessment framework was validated using case study method. Semi-structured interviews were used to elicit relevant information during the case study. Findings – An assessment framework comprising five major factors for sustainability of suggestion scheme of has been presented. The five factors include: leadership and work environment, system capability, system effectiveness, organizational encouragement and system barriers. Sustainability of a suggestion system can be understood as a three-stage model comprising three stages: the initial stage, the developmental stage and the advanced stage. The key practices associated for each of these stages are discussed in detail. Research limitations/implications – The framework has taken into consideration the critical success factors, and critical success factors emerged from the literature review conducted for this study. The framework therefore could be further refined by conducting more case studies and can propose maturity levels. Originality/value – The paper has developed a framework that can be used to assess the sustainability of the suggestion scheme in an organization. This model has been applied to assess the individual schemes and draw upon potential change strategies.
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Kim, Jung Ha. "The Suggestion for National Archival Management System in Korea." Journal of international area studies 11, no. 3 (2007): 187. http://dx.doi.org/10.18327/jias.2007.10.11.3.187.

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32

Lee, Michael Byungnam, and Yuzo Yasuda. "40 Years, 20 Million Ideas: The Toyota Suggestion System." Industrial and Labor Relations Review 45, no. 3 (1992): 620. http://dx.doi.org/10.2307/2524297.

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Mrs.S.Vijayarani, Mrs S. Vijayarani. "Motivating Employees Creativity through Suggestion System – An Empirical Study." IOSR Journal of Business and Management 9, no. 2 (2013): 22–27. http://dx.doi.org/10.9790/487x-0922227.

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Yi, Kyong-Hwa, and Hye-Soo Kim. "A Suggestion of Sizing System for Developing Taekwondo Protectors." Journal of the Korean Society of Clothing and Textiles 32, no. 9 (2008): 1397–406. http://dx.doi.org/10.5850/jksct.2008.32.9.1397.

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Sandeep, R. "CropsIT- A Portable Soil Analysis and Crop Suggestion System." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (2022): 1448–52. http://dx.doi.org/10.22214/ijraset.2022.39655.

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Abstract: Many farmers, especially ones from underdeveloped and developing countries, rely on agriculture for their family's livelihood. Agriculture is the most useful and noble employment of man. Yet on the contrary agriculture industry holds a record for the highest death rate by profession. Thisfatality is a result of many reasons. One such reason is when the farmer does not get the proper yield due to a lack of knowledge regarding the soil quality and fertilizers to be used. The solution to this is an easily operable device that senses the soil nutrient components and analyses the values obtained to provide a detailed report, along with crop suggestions suitable for the soil, instantaneously through a message or web service. The device will collect information regarding the NPK percentages present in the soil on a regular basis. The Technologies involved in the device are Colorimetry, Python, Deep Learning, Flask, and Heroku. The analysis made by the device will suggest the farmer with a variety of crops that are suitable for their land. The farmer can then get the required seeds and fertilizers to get a greater yield. Keywords: fatality, colorimetry, reagents
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Kwon, Tae-Geon. "Prerequisites for international article: suggestion for our publication system." Journal of the Korean Association of Oral and Maxillofacial Surgeons 38, no. 3 (2012): 184. http://dx.doi.org/10.5125/jkaoms.2012.38.3.184.

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Efraimidis, Pavlos, George Drosatos, Avi Arampatzis, Giorgos Stamatelatos, and Ioannis Athanasiadis. "A Privacy-by-Design Contextual Suggestion System for Tourism." Journal of Sensor and Actuator Networks 5, no. 2 (2016): 10. http://dx.doi.org/10.3390/jsan5020010.

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38

White, Jessica, and Gregor Reid. "A suggestion for evolution of Canada’s health regulatory system." FACETS 3, no. 1 (2018): 45–60. http://dx.doi.org/10.1139/facets-2017-0049.

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Aspects of Canada’s health regulatory system are currently being reviewed. This is timely, as the regulation and definition of drugs, foods, and natural health products (NHPs) is in need of revision to facilitate greater transparency and less ambiguity. A number of studies have illustrated the importance of a nutritious diet to prevent and manage chronic disease. Therefore, legislation surrounding food health claims needs to be adjusted so that it is more informative for disease prevention and, in some cases, treatment. Canada is modernizing the regulation of self-care products, under which NHPs, including probiotic products, are listed. With the growing appreciation for the role that microbes play in human health and the recognition that many foods, including those containing probiotic organisms, can prevent or mitigate disease, this provides an opportunity to reassess regulatory categories.
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Hayes, Lauren, and Christos Michalakos. "Imposing a Networked Vibrotactile Communication System for Improvisational Suggestion." Organised Sound 17, no. 1 (2012): 36–44. http://dx.doi.org/10.1017/s1355771811000495.

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This paper describes the implementation ofNeVIS, a local network system that establishes communication between individual performers, as well as between laptop and performers. Specifically, this is achieved by making use of vibrotactile feedback as a signalling tool within an improvisational setting. A discussion of the current developments regarding the use of networks within improvisation is presented, followed by an outline of the benefits of utilising the haptic feedback channel as a further sensory information pathway when performing digital music. We describe a case study of the system within the context of our computer-mediated improvisational duo Můstek, involving piano, percussion and live electronics. Here, a cueing system or framework is imposed over the improvisation and is transmitted directly to the skin of the performers via tiny vibrations. Additionally, performers may make use of simple vibrotactile signals to enhance traditional visual cues that are often employed within performance. A new work,Socks and Ammo, was created using NeVIS, and was presented at various international conferences and festivals. We also tested the system itself within a group of postgraduate researchers and composers. Qualitative evaluation of the musical outcomes as experienced both by the performers and by the listeners at these events is offered, as well as implications about the nature of collaborative music-making.
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Baz, Fatih Çağatay, and Hilmi Cihan Meral. "Semantic web oriented personalized electronic commerce product suggestion system." European Mechanical Science 7, no. 2 (2023): 82–88. http://dx.doi.org/10.26701/ems.1261229.

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With the studies on semantic web technology, the interest in this technology has increased over time. Today, the importance of data has increased to be used for purposes such as optimization, increasing user experience and improving. This increase has brought with it the need for readability of data. At this point, the semantic web has increased the readability of information by putting large data sets in a format that machines can interpret like humans. In this study, an electronic commerce system has been developed that can suggest related products to users by making use of the literature review in which semantic web technology is used. In the system development phase, firstly accepted ontology creation methods were examined, and a method was selected to create the needed ontology. Within the scope of the study, first, the capabilities of the semantic web to meet the technological needs are introduced. Then the semantic web and the technologies used in it are explained. In addition, the tools needed to develop applications with the semantic web are explained. Application development steps are explained in the study. Information about the successfully developed system is given and thus the use of semantic web is exemplified. Finally, suggestions were shared to improve the designed system. Due to the rapid developments in electronic commerce in recent years, it can be stated that this study is important.
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Tan, KianLam, Haseeb Ur Rehman Khan, and Chen Kim Lim. "Current Challenges and Approaches in Recommending Venues by Using Contextual Suggestion Track from TREC." International Journal of Engineering & Technology 7, no. 4.19 (2018): 207–11. http://dx.doi.org/10.14419/ijet.v7i4.19.22049.

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Contextual suggestion systems have been emerging as an entrance region of research, attributable to the innovative advances in smart connecting things and rapid growth of Big Data. In this regard, the primary purpose of contextual suggestion systems is to propose things that assist users to settle on choices from countless activities, for example, according to their specific context, the system may predict what place users would find interesting to visit or in what restaurant they would prefer to eat. In a smart environment using big data, users’ current activity and past behavior could be incorporated into the suggestion process with an end goal that provides right suggestion at the right time with appropriate location on users personal preferences. The objective of this paper is to provide an overview of contextual suggestion system and a review of TREC’s contextual suggestion track to investigate the approaches have been used in order to develop a model for contextual suggestion. Â
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T., Nithya Lakshmi, and G. Nallavan Dr. "PLAYER'S HEALTH MONITORING AND SUGGESTION THROUGH IOT." International Journal of Computational Research and Development 3, no. 1 (2018): 152–56. https://doi.org/10.5281/zenodo.1226615.

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This paper aims at monitoring the players health and informing the players injury condition. These entire detail can be monitored through IOT. The players injury details is uploaded through IOT and we monitor the details. This system is implemented in Paralympic games. As the System contains a variety of sensor types like ECG sensor and EMG sensor. The data transmission protocols will lead to a large amount of heterogeneous data of different sensors current and voltage values and the data is difficult to integrate with applications in upper layer.                 A data processing framework is introduced into the system to deal with such problems and data processing framework is introduced into the online monitoring system, which acts as a bridge between physical layer and application layer. In flow we fix smart sensor in the Players body and monitor body condition instantly. The data we get from ECG and EMG sensor are finally confirmed. The condition of the Injury and the details are finally uploaded. The medical suggestion will be sent through IOT
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43

Lasrado, Flevy, and Boštjan Gomišček. "A Tool to Measure Maturity of an Employee Suggestion Scheme." Management and Production Engineering Review 6, no. 2 (2015): 4–13. http://dx.doi.org/10.1515/mper-2015-0011.

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Abstract Employee Suggestion Schemes have been used in organizations for a long time due to the fact that they enable fostering of creative ability of employees. However, they must be used effectively and in a sustainable manner to better the creativity and innovation capacity of organizations in order to improve competitive advantage. Therefore there is a need to understand the maturity of Employee Suggestion Schemes. This paper proposes a new, structured evaluation tool for assessing an organizational Employee Suggestion Scheme maturity. It suggests five building blocks: Leadership and Work Environment, System Capability, System Effectiveness, Organizational Encouragement and System Barriers, each of them characterized by several relevant indicators and an assessment/grading scale in order for an organization to be able to determine the maturity level of their Employee Suggestion Scheme as: Initial stage, Development stage or Advanced stage. Organizations should apply this tool to assess the maturity level of their Employee Suggestion Scheme and draw a roadmap for its improvements.
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44

Ghanwat, Sakshi. "Book Recommendation System Using Machine Learning Algorithms." International Journal for Research in Applied Science and Engineering Technology 13, no. 2 (2025): 1009–13. https://doi.org/10.22214/ijraset.2025.66996.

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The book suggestion system has become a useful tool in today's extensive digital landscape, assisting consumers in finding books that suit their individual tastes. User profiles, which contain personal information like reading preferences, genres of interest, ratings and reviews are analyzed by this system using algorithms. By seeing trends and patterns in user behavior, user profile data improves the system's capacity to offer tailored recommendations. In these systems, recommendation algorithms are based on collaborative filtering, content- based filtering and hybrid techniques. While content- based filtering examines book attributes to recommend related books, collaborative filtering depends on user preference similarities. By integrating both methods, hybrid systems provide a more sophisticated strategy that raises user satisfaction and suggestion accuracy [1][2]. User profiling in which a structured profile gathers and updates data over time as user interactions continue, is a crucial component of book recommendation systems. Because of this dynamic process, systems can adjust to changing preferences and make sure that recommendations are still applicable. Research indicates that adding contextual, behavioral and demographic information to user profiles improves suggestion accuracy even further [3]. Modern book recommendation systems use advanced machine learning to analyze user profiles based on reading history, preferences and behaviors, creating personalized suggestions that cater closely to individual tastes. By combining hybrid filtering and deep learning algorithm such as CNN and RNN, these systems make book discovery more intuitive, helping readers find books they’re likely to enjoy.
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Lee, Jae Sung, Young Soon Oh, Sang Hee Han, and Young Sung Lee. "A Korean MeSH Keyword Suggestion System for Medical Paper Indexing." Journal of Korean Society of Medical Informatics 11, no. 4 (2005): 337. http://dx.doi.org/10.4258/jksmi.2005.11.4.337.

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Kim, Kwnag Lae, and Won Sik Lee. "A Study and Suggestion for Japanese Community Total Care System." Academy of Social Welfare and Law 10, no. 2 (2019): 141–68. http://dx.doi.org/10.35589/swlj.2019.10.2.141.

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Ковалевська, Т. Ю. "NEUROLINGUISTIC MILTON-MODEL IN THE COMMUNICATIVE SUGGESTION RESEARCH METHODS SYSTEM." Opera in linguistica ukrainiana 2, no. 24 (2017): 116–23. http://dx.doi.org/10.18524/2414-0627.2017.24.131412.

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Sujino, Tetsuo, and Noboru SUGIMOTO. "GS-1 Suggestion of hierarchical evacuation system for Tsunami prevention." Proceedings of the Industrial, Chemical Machinery & Safety Division Conference 2014.Summer (2014): 3–4. http://dx.doi.org/10.1299/jsmeicm.2014.summer.3.

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Fairbank, James F., and Scott David Williams. "Motivating Creativity and Enhancing Innovation through Employee Suggestion System Technology." Creativity and Innovation Management 10, no. 2 (2001): 68–74. http://dx.doi.org/10.1111/1467-8691.00204.

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Lee, Yu-Been, and Hae-Young Rieh. "A Suggestion of Interface for Ontology-Based Record Retrieval System." Journal of Records Management & Archives Society of Korea 17, no. 1 (2017): 217–44. http://dx.doi.org/10.14404/jksarm.2017.17.1.217.

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