Journal articles: 'Fitness applications'

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Ariff, Mohamed Imran Mohamed, Nabil Farhan Roslan, Khairulliza Ahmad Salleh, and Masurah Mohamad. "Mobile fitness application for beginners." Indonesian Journal of Electrical Engineering and Computer Science 24, no. 1 (October 1, 2021): 500. http://dx.doi.org/10.11591/ijeecs.v24.i1.pp500-506.

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<p>The present project is motivated by the recognition that the use of mobile fitness application is increasingly popular among sports and exercise participants in recent years. However, an extensive research on mobile fitness application indicates that most of them are not suitable for beginners. Thus, this project paper describes the development process of a mobile fitness application for beginners, who are looking at enhancing their physical fitness level. This mobile fitness application is developed using android studio and java language. Upon the development of this mobile fitness application, a user testing was conducted and analyzed. The result shows that users were satisfied with the applications as most test scores were above average. Based on these results, the usage of this newly developed mobile fitness application can be suggested to be used by beginner exercisers.</p>

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Khaghani-Far, Iman, Svetlana Nikitina, Marcos Baez, Ekaterina A. Taran, and Fabio Casati. "Fitness Applications for Home-Based Training." IEEE Pervasive Computing 15, no. 4 (October 2016): 56–65. http://dx.doi.org/10.1109/mprv.2016.76.

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Bayu, Wahyu Indra, Herri Yusfi, Syafaruddin Syafaruddin, Al Ikhsan Al Ikhsan, Lusiana Lusiana, and Kevin Waldo. "Needs Analysis of Development Digital-Based Physical Fitness Test Application." Kinestetik : Jurnal Ilmiah Pendidikan Jasmani 5, no. 3 (September 30, 2021): 597–603. http://dx.doi.org/10.33369/jk.v5i3.17763.

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This article aims to describe a needs analysis related to the development of a digital-based physical fitness test application. This physical fitness test application will later help physical education teachers to be able to evaluate the physical fitness of students. The target respondents in this study were students and physical education teachers in South Sumatra. The results showed that, from 115 respondents who filled out questionnaires distributed online via google form, it showed that 105 (91.30%) respondents had done physical fitness tests to students, 3 (2.61%) respondents had never, and 7 (6.09%) respondents answered maybe. And 103 (89.57%) respondents want the development of test and measurement applications related to physical fitness, 2 (1.74%) respondents think “no”, and 10 (8.70%) respondents think "maybe". The conclusion of this study is the need for a digital-based physical fitness test and measurement application, either in the form of a website or mobile application.

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Higgins, John P. "Smartphone Applications for Patients' Health and Fitness." American Journal of Medicine 129, no. 1 (January 2016): 11–19. http://dx.doi.org/10.1016/j.amjmed.2015.05.038.

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IONIŢE, Cătălin, Dragoş AROTĂRIŢEI, Marius TURNEA, Mihai ILEA, and Mariana ROTARIU. "Applications of fitness function in Pubalgia affliction." Balneo and PRM Research Journal 12, Vol.12, no.1 (March 20, 2021): 77–81. http://dx.doi.org/10.12680/balneo.2021.423.

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Introduction. The relationships among variables are important in medicine and sport, and the most common approaches use linear correlation for optimization and prediction. Material and method. We propose to o novel usage of a known method (the genetic programming algorithm) to construct a nonlinear model in a practical case for rehabilitation find out the mathematical formula for a relationship among many variables . This study seeks to find a mathematical function to estimate the current state of the patient: healthy, affected by Pubalgia. Results and discussions. In the proposed application, a mathematical relationship is sought for five variables that express a state of health for patients, plantar footprint, plantar footprint – right, plantar pressure, plantar pressure – right and the surface of the body weight center. Conclusions. In this article, genetic programming has been proposed to construct a mathematical function to estimate the patient's condition possibly affected by Pubalgia. Keywords: e-health, rehabilitation, genetic algorithm,fitness function,

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Editorial Submission, Haworth. "Physical Fitness:." Technical Services Quarterly 3, no. 3-4 (August 29, 1985): 211–16. http://dx.doi.org/10.1300/j124v03n03_19.

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Harvianto, Yudo, Andi Tenri Abeng, Garry William Dony, Abdullah, and Muharfa. "Pelatihan Penggunaan Aplikasi SIPGAR Bagi Pemuda DAS di Kota Palangka Raya." Jurnal Pengabdian Magister Pendidikan IPA 4, no. 4 (November 16, 2021): 254–59. http://dx.doi.org/10.29303/jpmpi.v4i4.1056.

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During the Covid-19 pandemic, health factors in the form of maintaining physical fitness are very important. There are many ways to keep your body in shape. The most effective way to maintain physical fitness during the current covid-19 pandemic is to comply with health protocols and get used to exercising so that the body is always in a fit condition. Exercise can be used as an alternative to keep the body fit. Another important thing besides exercising during the current pandemic is checking physical fitness regularly and independently. One way that can be used is the SIPGAR application. An application published by the Ministry of Health of the Republic of Indonesia to check a person's physical fitness independently via Android. The purpose of this activity is that participants get education about physical fitness and can do tests independently through the operation of the SIPGAR application. The method used in this activity is training. The training was conducted for 5 times, with different participants and places. The total number of participants who attended the training was 42 people. Based on the results of the training, there were several problems experienced by the participants including not all participants were able to download applications on the play store and register an account. This is because each participant's cellphone has different specifications. The solution is that participants who successfully register help their friends to register, while still using the identity of the participant who cannot register. After successful registration, then login using their respective cellphones. After the implementation of this activity the youth felt happy, this was because they already had new skills in operating the SIPGAR application. According to the participants, SIPGAR is an application that is easy and accurate to measure a person's physical fitness, besides that the test can also be carried out anywhere and does not require a special place, the most important thing is that the distance reached is 1600 meters. So that the participants will be able to check their physical fitness regularly and independently easily. Another hope that the participants want is training on other applications to support their skills in operating applications regarding self-health checks independently

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Aziz, Nian, Justin Champion, and Ibrahim Hamarash. "Evaluation of Smartphone’s Embedded Sensors Through Applications: A Case Study of Gyroscope and Accelerometer." UKH Journal of Science and Engineering 5, no. 2 (December 28, 2021): 10–17. http://dx.doi.org/10.25079/ukhjse.v5n2y2021.pp10-17.

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Smartphones are used for many daily activities like tele-communication, gaming, web browsing, fitness and health monitoring and traditional office working. Smartphones are equipped with built-in sensors to be able to perform these activities. It is well known that the sensors affect the resolution of the smartphone applications which is very vital in life critical applications (LCA). In this paper, two main sensors, the gyroscope and accelerometer have been studied. All commercial smartphones contain these two sensors and support functions related to them. These two sensors have direct link with the physical measurements which feed the fitness and health applications. A fitness application has been selected and ran under Android and iOS operating systems in two different popular smartphones: Samsung Note5 and iPhone7s smartphones. Statistical methodology has been applied to analysis the data and evaluate the performance of the sensors. The results show that commercial smartphones are not reliable devices for motion-related measurements and they can only be used for general purpose monitoring but not in life critical applications.

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Bates, Michael, Terri Wrin, Wei Huang, Christos Petropoulos, and Nicholas Hellmann. "Practical applications of viral fitness in clinical practice." Current Opinion in Infectious Diseases 16, no. 1 (February 2003): 11–18. http://dx.doi.org/10.1097/00001432-200302000-00003.

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HIRSEKORN, LINDA, and SUE TAYLAR. "VR Technology Applications in Determining Fitness to Drive." CyberPsychology & Behavior 1, no. 4 (January 1998): 385–89. http://dx.doi.org/10.1089/cpb.1998.1.385.

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Bhuiyan, Mohammad A., Melissa C. Smith, and Vivek K. Pallipuram. "Performance, optimization, and fitness: Connecting applications to architectures." Concurrency and Computation: Practice and Experience 23, no. 10 (December 28, 2010): 1066–100. http://dx.doi.org/10.1002/cpe.1688.

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Kim, Hyo-Jung. "Intention of Information Sharing: Fitness Applications with Smartwatch." Journal of Consumer Studies 32, no. 6 (December 30, 2021): 101–20. http://dx.doi.org/10.35736/jcs.32.6.5.

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XU, XIN-JIAN, LIU-MING ZHANG, and LI-JIE ZHANG. "MUTUAL SELECTION IN NETWORK EVOLUTION: THE ROLE OF THE INTRINSIC FITNESS." International Journal of Modern Physics C 21, no. 01 (January 2010): 129–35. http://dx.doi.org/10.1142/s0129183110015014.

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We propose a new mechanism leading to scale-free networks which is based on the presence of an intrinsic character of a vertex called fitness. In our model, a vertex i is assigned a fitness xi, drawn from a given probability distribution function f(x). During network evolution, with rate p we add a vertex j of fitness xj and connect to an existing vertex i of fitness xi selected preferentially to a linking probability function g(xi, xj) which depends on the fitnesses of the two vertices involved and, with rate 1 - p we create an edge between two already existed vertices with fitnesses xi and xj, with a probability also preferential to the connection function g(xi, xj). For the proper choice of g, the resulting networks have generalized power-laws, irrespective of the fitness distribution of vertices.

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Moey, Cheah C. J., and Jonathan E. Rowe. "Population aggregation based on fitness." Natural Computing 3, no. 1 (2004): 5–19. http://dx.doi.org/10.1023/b:naco.0000023414.30362.8a.

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Yu, Jo-Hung, Gordon Chih-Ming Ku, Yu-Chih Lo, Che-Hsiu Chen, and Chin-Hsien Hsu. "Identifying the Antecedents of University Students’ Usage Behaviour of Fitness Apps." Sustainability 13, no. 16 (August 12, 2021): 9043. http://dx.doi.org/10.3390/su13169043.

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The purpose of the study is to explore the antecedents of university students’ fitness application usage behaviours by combining the theory of planned behaviour and the technology acceptance model. An anonymous questionnaire survey was adopted to address the objectives of the study. Purposive and snowball sampling was used to select eligible students from six universities in Zhanjiang City. An online survey was used to collect data from 634 eligible subjects, and partial least squares structural equation modelling was used to analyse the collected data. The results indicated that the students’ perceived usefulness (β = 0.17, p < 0.05) and perceived ease of use (β = 0.32, p < 0.05) concerning the application and their attitude (β = 0.31, p < 0.05) toward it significantly influenced their usage intentions. Furthermore, perceived usefulness (β = 0.11, p < 0.05) and perceived ease of use (β = 0.38, p < 0.05) fully mediated the relationship between subjective norms and usage intentions. However, subjective norms and perceived behavioural control did not enhance the students’ intentions to use fitness applications. That is, students’ attitudes and fitness application design are the determinants of usage intention. Accordingly, improving students’ fitness applications usage intention requires strategies that involve customised services, social networking, and collaboration with schools; this would further increase students’ engagement in physical exercise.

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Chevin, Luis-Miguel. "On measuring selection in experimental evolution." Biology Letters 7, no. 2 (September 2010): 210–13. http://dx.doi.org/10.1098/rsbl.2010.0580.

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Distributions of mutation fitness effects from evolution experiments are available in an increasing number of species, opening the way for a vast array of applications in evolutionary biology. However, comparison of estimated distributions among studies is hampered by inconsistencies in the definitions of fitness effects and selection coefficients. In particular, the use of ratios of Malthusian growth rates as ‘relative fitnesses’ leads to wrong inference of the strength of selection. Scaling Malthusian fitness by the generation time may help overcome this shortcoming, and allow accurate comparison of selection coefficients across species. For species reproducing by binary fission (neglecting cellular death), ln2 can be used as a correction factor, but in general, the growth rate and generation time of the wild-type should be provided in studies reporting distribution of mutation fitness effects. I also discuss how density and frequency dependence of population growth affect selection and its measurement in evolution experiments.

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Li, Liangming, and Aihua Yang. "A Recommendation Method of National Fitness Items Based on Neural Network Algorithm." Scientific Programming 2022 (January 18, 2022): 1–10. http://dx.doi.org/10.1155/2022/1544767.

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In order to improve the effectiveness of national fitness programs, this article analyzes the method of national fitness items recommendation based on a neural network algorithm. By using the time and space characteristics of fitness users’ sign-in, a novel POI recommendation model is proposed, and a novel fusion method is proposed to combine similarity and spatial similarity to achieve the final similarity calculation based on fitness users’ temporal and spatial preferences. In addition, in order to model the spatial similarity of fitness users, the Voronoi diagram is constructed by using the geographic locations of all POIs. Finally, this paper constructs a recommendation system for national fitness items based on a neural network algorithm. The experimental research results show that the national fitness program recommendation system proposed in this article basically meets the expected demand.

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Zeng, Qingfeng, Artem R. Oganov, Andriy O. Lyakhov, Congwei Xie, Xiaodong Zhang, Jin Zhang, Qiang Zhu, et al. "Evolutionary search for new high-kdielectric materials: methodology and applications to hafnia-based oxides." Acta Crystallographica Section C Structural Chemistry 70, no. 2 (January 9, 2014): 76–84. http://dx.doi.org/10.1107/s2053229613027861.

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High-kdielectric materials are important as gate oxides in microelectronics and as potential dielectrics for capacitors. In order to enable computational discovery of novel high-kdielectric materials, we propose a fitness model (energy storage density) that includes the dielectric constant, bandgap, and intrinsic breakdown field. This model, used as a fitness function in conjunction with first-principles calculations and the global optimization evolutionary algorithm USPEX, efficiently leads to practically important results. We found a number of high-fitness structures of SiO2and HfO2, some of which correspond to known phases and some of which are new. The results allow us to propose characteristics (genes) common to high-fitness structures – these are the coordination polyhedra and their degree of distortion. Our variable-composition searches in the HfO2–SiO2system uncovered several high-fitness states. This hybrid algorithm opens up a new avenue for discovering novel high-kdielectrics with both fixed and variable compositions, and will speed up the process of materials discovery.

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Bt Wan Mohamed Radzi, Che Wan Jasimah, Hashem Salarzadeh Jenatabadi, and Nadia Samsudin. "mHealth Apps Assessment among Postpartum Women with Obesity and Depression." Healthcare 8, no. 2 (March 26, 2020): 72. http://dx.doi.org/10.3390/healthcare8020072.

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Background: Pregnancy has become the main constituent for women to become overweight or obese during the postpartum phase. This could lead women to suffer from postpartum depression as well. Information technology (IT) has become more prevalent in the healthcare industry. It offers patients the opportunity to manage their health conditions via the use of several applications, one being the mHealth applications. Objective: The main purpose of this study is to experiment and understand the effects the mHealth applications (i.e., fitness and nutrition applications) have on the body mass index (BMI) and depression levels amongst postpartum women. Methods: Online questionnaires were sent to postpartum women within one year after their pregnancy, of which 819 completed questionnaires were returned. The frequency of the mHealth applications usage was categorized into daily, weekly, rarely and never streams. Therefore, the frequency of use of the mHealth applications for BMI and depression levels was analyzed based on the available statistical data. Descriptive statistics, ANOVA, and Dunnet tests were applied to analyze the experimental data. Results: Out of 819 respondents, 37.9% and 42.1% of them were overweight and obese, respectively. Almost 32.9% of the respondents were likely depressed, and 45.6% were at an increased risk. This study reports that only 23.4% and 28.6% of respondents never used the fitness and nutrition applications. The impact of the frequency of using the fitness applications on BMI and depression levels was obvious. This means that with the increased use of the fitness applications, there was also a significant effect in maintaining and decreasing the BMI and depression levels amongst Malaysians postpartum women. However, from the data of weekly and daily use of fitness applications, we found that the contribution toward the BMI and depression levels was high (p = 0.000). However, nutrition applications amongst the users were not significant within the main variables (p > 0.05). From the Dunnet test, the significance of using the fitness applications within the depression levels started from daily usage, whereas for BMI, it started from weekly usage. Conclusion: The efficiency of the fitness applications toward the BMI and depression levels has been proven in this research work. While nutrition applications did not affect the BMI and depression levels, some of the respondents were still categorized as weekly and daily users. Thus, the improvements in BMI and depression levels are associated with the types of mHealth app that had been used.

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Gerstung, Moritz, Hani Nakhoul, and Niko Beerenwinkel. "Evolutionary Games with Affine Fitness Functions: Applications to Cancer." Dynamic Games and Applications 1, no. 3 (August 23, 2011): 370–85. http://dx.doi.org/10.1007/s13235-011-0029-0.

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Schoenfeld, Brad, and Jay Dawes. "High-Intensity Interval Training: Applications for General Fitness Training." Strength and Conditioning Journal 31, no. 6 (December 2009): 44–46. http://dx.doi.org/10.1519/ssc.0b013e3181c2a844.

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Li, Xinwen, Xiaowei Chen, Lihui Guo, and Christine A. Rochester. "Application of Big Data Analysis Techniques in Sports Training and Physical Fitness Analysis." Wireless Communications and Mobile Computing 2022 (March 25, 2022): 1–7. http://dx.doi.org/10.1155/2022/3741087.

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With the development of sports and information technology, people use mathematical tools and computer technology to study sports data and mine the intrinsic value of sports data. Statistical methods are the most widely used to achieve this goal. The research purpose of sports effect evaluation research is to understand the impact of sports on physical fitness through mining and analysis of sports data and to provide theoretical guidance for the public to participate in fitness activities scientifically and effectively. At present, in the study of combining individual performance test data, the research on the standardization of physical fitness monitoring data for sports training is relatively scarce. Therefore, based on the background of big data, this paper integrates the existing data standardization work and designs a plan for the standardization of physical fitness monitoring data for sports training. Combined with machine learning, data preprocessing is performed to obtain the data required by the machine model. The comprehensive physical fitness rating model and the recommendation model are established to realize the development of physical fitness monitoring service applications. In the experiment, compared with the three classical methods, the results show that the classification accuracy of this paper is 4% higher than that of other algorithms, which can more intuitively reflect the characteristic samples of sports training. In this paper, the data mining and analysis technology based on feature indicators in the mining and application of sports data has great application value for human fitness guidance and has certain research value and market application prospects.

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Oyibo, Kiemute, and Julita Vassileva. "Gender Preference and Difference in Behavior Modeling in Fitness Applications: A Mixed-Method Approach." Multimodal Technologies and Interaction 4, no. 2 (May 22, 2020): 21. http://dx.doi.org/10.3390/mti4020021.

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In recent years, the employment of behavior models to motivate behavior change has become a global trend in fitness application design. However, there is hardly any large-scale study of these applications to understand users’ exercise-type preferences, their drivers and barriers, and the potential of employing them for gender-based tailoring. To bridge this gap, we conducted a mixed-method study among 669 participants to investigate users’ exercise-type preferences (their drivers and barriers) and how they and gender can impact users’ social-cognitive beliefs and projected performance of bodyweight exercises. Firstly, we presented to the study participants a behavior model performing push-up or squat bodyweight exercise in a fitness application and asked them to rate their perceived self-efficacy, self-regulation, outcome expectation, and projected (exercise) performance level as observers of the behavior model. Secondly, we presented the study participants with a preselected list of commonly employed exercise types in fitness applications and requested them to identify their most/least preferred, and the reasons behind their choices. Our results showed that there were differences between both genders in their exercise-type preferences, perceived self-efficacy and projected exercise performance level. Males prefer push-up, squat, crunch, plank, and chair dip the most, with effectiveness being the most important driver, followed by ease of performance and improvement of the physique, look, and appearance. On the other hand, females prefer squat, crunch, jumping jack, step up, and plank the most, with ease of performance being the most important driver, followed by improvement of the physique, look, appearance, and effectiveness. Moreover, males prefer running in place the least, while females prefer push-up the least, with perceived difficulty being the greatest barrier for both genders. Moreover, our analysis of variance supported the female’s least preference for a push-up. Females have a lower perceived self-efficacy and projected performance level for push-up than males. We discussed the implications of our findings and provided guidelines for tailoring fitness applications on the market to users’ preferences and gender.

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House, Amanda, and Arvin Agah. "Autonomous Evolution of Digital Art Using Genetic Algorithms." Journal of Intelligent Systems 25, no. 3 (July 1, 2016): 319–33. http://dx.doi.org/10.1515/jisys-2014-0173.

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AbstractThis paper applies a genetic algorithm (GA) to the autonomous evolution of digital art, eliminating the need for a human in the loop. Creative applications of GAs face the challenge of producing art or music to fit a wide range of human tastes. One approach is to use a human in the loop to determine the fitness function in order to direct the selection and evolution. Another approach, which this paper explores, is to define an objective fitness function to automate evolution without the need for human input. In this paper, several features of digital art are identified and used as the basis for fitness functions. The resulting images are recognizable for the intended evolution of the fitness function used. This indicates the potential of an approach to create more robust algorithmic fitness functions capable of evolving creative applications autonomously.

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Angosto, Salvador, Jerónimo García-Fernández, Irena Valantine, and Moisés Grimaldi-Puyana. "The Intention to Use Fitness and Physical Activity Apps: A Systematic Review." Sustainability 12, no. 16 (August 17, 2020): 6641. http://dx.doi.org/10.3390/su12166641.

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Recently the development of new technologies has produced an increase in the number of studies that try to evaluate consumer behavior towards the use of sports applications. The aim of this study is to perform a systematic review of the literature on the intention to use mobile applications (Apps) related to fitness and physical activity by consumers. This systematic review is a critical evaluation of the evidence from quantitative studies in the field of assessment of consumer behavior towards sport applications. A total of 13 studies are analyzed that propose models for evaluating the intentions to use fitness applications by sport consumers. The results revealed several key conclusions: (a) Technology Acceptance Model is the most widely used model; (b) the relationship between perceived utility and future intentions is the most analyzed; and (c) the most evaluated applications are diet/fitness. These findings could help technology managers to know the most important key elements to take into account in the development of future applications in sport organizations.

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Li, Lu, Yanchun Liang, Tingting Li, Chunguo Wu, Guozhong Zhao, and Xiaosong Han. "Boost particle swarm optimization with fitness estimation." Natural Computing 18, no. 2 (July 25, 2018): 229–47. http://dx.doi.org/10.1007/s11047-018-9699-5.

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Gabor, Thomas, Thomy Phan, and Claudia Linnhoff-Popien. "Productive fitness in diversity-aware evolutionary algorithms." Natural Computing 20, no. 3 (April 29, 2021): 363–76. http://dx.doi.org/10.1007/s11047-021-09853-3.

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AbstractIn evolutionary algorithms, the notion of diversity has been adopted from biology and is used to describe the distribution of a population of solution candidates. While it has been known that maintaining a reasonable amount of diversity often benefits the overall result of the evolutionary optimization process by adjusting the exploration/exploitation trade-off, little has been known about what diversity is optimal. We introduce the notion of productive fitness based on the effect that a specific solution candidate has some generations down the evolutionary path. We derive the notion of final productive fitness, which is the ideal target fitness for any evolutionary process. Although it is inefficient to compute, we show empirically that it allows for an a posteriori analysis of how well a given evolutionary optimization process hit the ideal exploration/exploitation trade-off, providing insight into why diversity-aware evolutionary optimization often performs better.

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Li, Chengzhao. "Research on Contactless Identification and Evaluation of Unarmed Fitness Activity." Scientific Programming 2022 (March 11, 2022): 1–10. http://dx.doi.org/10.1155/2022/4282569.

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For low accuracy in the recognition and evaluation of unarmed fitness activities, analyzing the impact of the diversity of the execution speed of unarmed fitness activities on the recognition and evaluation results, a contactless recognition and evaluation method of unarmed fitness activities has been proposed by using the normalization to improve dynamic time warping (DTW) algorithm. As can be seen, the proposed method can reduce the influence of activity execution speed change on activity recognition and evaluation, so as to improve the contactless recognition accuracy of unarmed fitness activities. Meanwhile, the overall recognition accuracy can reach 0.91, and the positive rate can be more than 0.84, which has strong robustness.

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Akçay, Erol, and Jeremy Van Cleve. "There is no fitness but fitness, and the lineage is its bearer." Philosophical Transactions of the Royal Society B: Biological Sciences 371, no. 1687 (February 5, 2016): 20150085. http://dx.doi.org/10.1098/rstb.2015.0085.

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Inclusive fitness has been the cornerstone of social evolution theory for more than a half-century and has matured as a mathematical theory in the past 20 years. Yet surprisingly for a theory so central to an entire field, some of its connections to evolutionary theory more broadly remain contentious or underappreciated. In this paper, we aim to emphasize the connection between inclusive fitness and modern evolutionary theory through the following fact: inclusive fitness is simply classical Darwinian fitness, averaged over social, environmental and demographic states that members of a gene lineage experience. Therefore, inclusive fitness is neither a generalization of classical fitness, nor does it belong exclusively to the individual. Rather, the lineage perspective emphasizes that evolutionary success is determined by the effect of selection on all biological and environmental contexts that a lineage may experience. We argue that this understanding of inclusive fitness based on gene lineages provides the most illuminating and accurate picture and avoids pitfalls in interpretation and empirical applications of inclusive fitness theory.

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Luhanga, Edith Talina, Akpa Akpro Elder Hippocrate, Hirohiko Suwa, Yutaka Arakawa, and Keiichi Yasumoto. "Identifying and Evaluating User Requirements for Smartphone Group Fitness Applications." IEEE Access 6 (2018): 3256–69. http://dx.doi.org/10.1109/access.2018.2793844.

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Lierman, Ali M., Mike A. Slack, Dale D. Brown, and Kelly R. Laurson. "Accuracy of Cellular Phone Fitness Applications to Assess Physical Activity." Medicine & Science in Sports & Exercise 43, Suppl 1 (May 2011): 700. http://dx.doi.org/10.1249/01.mss.0000401940.58192.f8.

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Kita, Hajime. "Genetic Algorithms for Noisy Fitness Functions ― Applications, Requirements and Algorithms." Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 2001 (May 5, 2001): 137–42. http://dx.doi.org/10.5687/sss.2001.137.

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Bernadó-Mansilla, Ester, and Josep M. Garrell-Guiu. "Accuracy-Based Learning Classifier Systems: Models, Analysis and Applications to Classification Tasks." Evolutionary Computation 11, no. 3 (September 2003): 209–38. http://dx.doi.org/10.1162/106365603322365289.

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Recently, Learning Classifier Systems (LCS) and particularly XCS have arisen as promising methods for classification tasks and data mining. This paper investigates two models of accuracy-based learning classifier systems on different types of classification problems. Departing from XCS, we analyze the evolution of a complete action map as a knowledge representation. We propose an alternative, UCS, which evolves a best action map more efficiently. We also investigate how the fitness pressure guides the search towards accurate classifiers. While XCS bases fitness on a reinforcement learning scheme, UCS defines fitness from a supervised learning scheme. We find significant differences in how the fitness pressure leads towards accuracy, and suggest the use of a supervised approach specially for multi-class problems and problems with unbalanced classes. We also investigate the complexity factors which arise in each type of accuracy-based LCS. We provide a model on the learning complexity of LCS which is based on the representative examples given to the system. The results and observations are also extended to a set of real world classification problems, where accuracy-based LCS are shown to perform competitively with respect to other learning algorithms. The work presents an extended analysis of accuracy-based LCS, gives insight into the understanding of the LCS dynamics, and suggests open issues for further improvement of LCS on classification tasks.

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Vinnikova, Anna, Liangdong Lu, Jiuchang Wei, Guangbao Fang, and Jing Yan. "The Use of Smartphone Fitness Applications: The Role of Self-Efficacy and Self-Regulation." International Journal of Environmental Research and Public Health 17, no. 20 (October 20, 2020): 7639. http://dx.doi.org/10.3390/ijerph17207639.

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With the popularity of the health and wellness trend in recent years, smartphone fitness applications have become more and more popular. Thus, this study explored factors affecting the behavioral intention to use and the actual usage behavior of smartphone fitness apps from technical, health, and social perspectives by integrating the Social Cognitive Theory (SCT) and Unified Theory of Acceptance and Use of Technology (UTAUT). We examined whether perceived usefulness, perceived ease-of-use, social influence, self-efficacy, goal-setting, and self-monitoring predict usage behavior. Based on the survey responses of 1066 smartphone fitness apps users, we revealed that all of the variables, except for self-monitoring, significantly influence usage behavior, while behavioral intention acts as a total mediator between perceived usefulness, perceived ease-of-use and usage behavior. Drawing on the research findings, we suggest that influencing behavioral intention to use a fitness app can be an effective method to increase its adoption. Therefore, app developers need to pay attention to interventions that seek to enhance the usefulness of the app, provide professional counseling, as well as an opportunity for effortless goal setting features.

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Eid, Ahmed M., Amr Fouda, Mohamed Ali Abdel-Rahman, Salem S. Salem, Albaraa Elsaied, Ralf Oelmüller, Mohamed Hijri, Arnab Bhowmik, Amr Elkelish, and Saad El-Din Hassan. "Harnessing Bacterial Endophytes for Promotion of Plant Growth and Biotechnological Applications: An Overview." Plants 10, no. 5 (May 7, 2021): 935. http://dx.doi.org/10.3390/plants10050935.

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Endophytic bacteria colonize plants and live inside them for part of or throughout their life without causing any harm or disease to their hosts. The symbiotic relationship improves the physiology, fitness, and metabolite profile of the plants, while the plants provide food and shelter for the bacteria. The bacteria-induced alterations of the plants offer many possibilities for biotechnological, medicinal, and agricultural applications. The endophytes promote plant growth and fitness through the production of phytohormones or biofertilizers, or by alleviating abiotic and biotic stress tolerance. Strengthening of the plant immune system and suppression of disease are associated with the production of novel antibiotics, secondary metabolites, siderophores, and fertilizers such as nitrogenous or other industrially interesting chemical compounds. Endophytic bacteria can be used for phytoremediation of environmental pollutants or the control of fungal diseases by the production of lytic enzymes such as chitinases and cellulases, and their huge host range allows a broad spectrum of applications to agriculturally and pharmaceutically interesting plant species. More recently, endophytic bacteria have also been used to produce nanoparticles for medical and industrial applications. This review highlights the biotechnological possibilities for bacterial endophyte applications and proposes future goals for their application.

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Cotton, Victor, and Mitesh S. Patel. "Gamification Use and Design in Popular Health and Fitness Mobile Applications." American Journal of Health Promotion 33, no. 3 (July 26, 2018): 448–51. http://dx.doi.org/10.1177/0890117118790394.

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Purpose: To evaluate the presence of gamification in popular mobile applications and whether principles from behavioral economics were incorporated in the design. Design: The top 50 ranked free health and fitness applications were downloaded. Gamification elements were predetermined through literature review, and applications were evaluated for their presence. Setting: App Store by Apple Inc. Measures: Presence of gamification, type of game element, and use of behavioral economic principles. Analysis: We classified the types and frequencies of targeted behaviors and features of gamification. Use of behavioral economic principles focused on designing rewards or points using loss aversion (allocated upfront and could be lost), variable reinforcement (not allocated constantly), and probability inflation (using drawings or lottery designs). Results: Gamification was used by 64% of mobile applications. Most applications that included gamification (97%) targeted behaviors related to physical activity and weight loss. Applications focused on other areas such as reproductive health, meditation, and sleep used gamification less often (11%). Game elements used most commonly included goal setting (78%), social influences (78%), and challenges (63%), while less common elements included points (6%) and levels (3%). No applications incorporated behavioral economics principles specified in the study. Conclusions: Gamification was commonly used by popular health and fitness mobile applications, but none used the specified behavioral economic principles to design rewards or points. Mobile applications could potentially improve their use if their design better leveraged principles from behavioral economics.

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Kari, Tuomas. "Can Exergaming Promote Physical Fitness and Physical Activity?" International Journal of Gaming and Computer-Mediated Simulations 6, no. 4 (October 2014): 59–77. http://dx.doi.org/10.4018/ijgcms.2014100105.

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This systematic review of systematic reviews evaluates the effectiveness of exergaming on physical fitness and physical activity. A systematic literature search was conducted on 10 databases, and 1040 articles were identified. Sixty-eight articles were found potentially relevant and were selected for closer screening. Cross-referencing was conducted to find other potentially relevant articles. The quality of all relevant articles was evaluated using the AMSTAR tool. After all the duplicates were removed and inclusion, exclusion, and quality criteria were implemented, six articles remained for review. The results indicate that exergaming is generally enjoyed and can evoke some benefits for physical fitness and physical activity, but the current evidence does not support the ability of exergaming to increase physical fitness or physical activity levels sufficiently for significant health benefits. This systematic review also revealed several gaps in previous research. Additional high-quality research and systematic reviews concerning exergaming are needed.

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Zhang, Hang, and Jonathan E. Rowe. "Best approximations of fitness functions of binary strings." Natural Computing 3, no. 1 (2004): 113–24. http://dx.doi.org/10.1023/b:naco.0000023418.20610.4d.

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Menczer, Filippo, Melania Degeratu, and W. Nick Street. "Efficient and Scalable Pareto Optimization by Evolutionary Local Selection Algorithms." Evolutionary Computation 8, no. 2 (June 2000): 223–47. http://dx.doi.org/10.1162/106365600568185.

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Local selection is a simple selection scheme in evolutionary computation. Individual fitnesses are accumulated over time and compared to a fixed threshold, rather than to each other, to decide who gets to reproduce. Local selection, coupled with fitness functions stemming from the consumption of finite shared environmental resources, maintains diversity in a way similar to fitness sharing. However, it is more efficient than fitness sharing and lends itself to parallel implementations for distributed tasks. While local selection is not prone to premature convergence, it applies minimal selection pressure to the population. Local selection is, therefore, particularly suited to Pareto optimization or problem classes where diverse solutions must be covered. This paper introduces ELSA, an evolutionary algorithm employing local selection and outlines three experiments in which ELSA is applied to multiobjective problems: a multimodal graph search problem, and two Pareto optimization problems. In all these experiments, ELSA significantly outperforms other well-known evolutionary algorithms. The paper also discusses scalability, parameter dependence, and the potential distributed applications of the algorithm.

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Xiao, Yingtai, Zeyu Ding, Yuxin Wang, Danfeng Zhang, and Daniel Kifer. "Optimizing fitness-for-use of differentially private linear queries." Proceedings of the VLDB Endowment 14, no. 10 (June 2021): 1730–42. http://dx.doi.org/10.14778/3467861.3467864.

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In practice, differentially private data releases are designed to support a variety of applications. A data release is fit for use if it meets target accuracy requirements for each application. In this paper, we consider the problem of answering linear queries under differential privacy subject to per-query accuracy constraints. Existing practical frameworks like the matrix mechanism do not provide such fine-grained control (they optimize total error, which allows some query answers to be more accurate than necessary, at the expense of other queries that become no longer useful). Thus, we design a fitness-for-use strategy that adds privacy-preserving Gaussian noise to query answers. The covariance structure of the noise is optimized to meet the fine-grained accuracy requirements while minimizing the cost to privacy.

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Shrestha, Govinda, Shabeg S. Briar, and Gadi V. P. Reddy. "Plant defense elicitors: plant fitness versus wheat stem sawfly." PeerJ 6 (November 1, 2018): e5892. http://dx.doi.org/10.7717/peerj.5892.

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The wheat stem sawfly (WSS), Cephus cinctus Norton, is an important wheat pest in the Northern Great Plains of the USA. No single control measure effectively suppresses WSS damage. This study provides information on the effects on the WSS adult settling preference behavior on wheat plants under laboratory conditions from treatment with both synthetic plant defense elicitors (Actigard® and cis-jasmone) and a botanical insecticide (Azadirachtin®). In addition, field experiments were performed to determine whether these chemicals impact the WSS fitness (larval mortality and larval body weight), winter wheat plant fitness (infestation, stem lodging, yield, and quality), adult population of WSS and Bracon spp., and larval parasitism levels. Our lab results showed that there were no significant differences in adult settling behavior on plants exposed separately to each chemical and control. In contrast, when adults were exposed simultaneously to treated and untreated plants, there was a significant reduction in the percentage of adults settling on Actigard® and Azadirachtin® treated plants compared to plants sprayed with water in the same cage. However, in field situations, regardless of application timing and field location, none of the chemicals significantly reduced adult population or stems damage. The exception was two times applications of Actigard® had significantly lower WSS infested stem damage levels at 30 days after initial treatment applications at Knees and 50 days at Choteau locations compared to control, but without effect at the Conrad location. The field study indicated that two times applications of Actigard® significantly increased diapausing larval mortality percentages and lowered stem lodging levels compared to untreated controls at Knees and Choteau locations, while no effects at Conrad location. Larval body weight was significantly lower in plots treated with Actigard® at Knees and Conrad, but no effects at Choteau. No significant differences were found in wheat yield and quality in plots treated with chemicals and controls at any location. Bracon spp. adult population and parasitism levels were not negatively affected by the use of chemicals. In conclusion, this study offers insights on what treatments should be emphasized in more detail despite variable findings.

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Somerville, Jasmine, Liqin Zhou, and Ben Raymond. "Aseptic Rearing and Infection with Gut Bacteria Improve the Fitness of Transgenic Diamondback Moth, Plutella xylostella." Insects 10, no. 4 (March 28, 2019): 89. http://dx.doi.org/10.3390/insects10040089.

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Mass insect rearing can have a range of applications, for example in biological control of pests. The competitive fitness of released insects is extremely important in a number of applications. Here, we investigated how to improve the fitness of a transgenic diamondback moth, which has shown variation in mating ability when reared in different insectaries. Specifically we tested whether infection with a gut bacteria, Enterobacter cloacae, and aseptic rearing of larvae could improve insect growth and male performance. All larvae were readily infected with E. cloacae. Under aseptic rearing, pupal weights were reduced and there was a marginal reduction in larval survival. However, aseptic rearing substantially improved the fitness of transgenic males. In addition, under aseptic rearing, inoculation with E. cloacae increased pupal weights and male fitness, increasing the proportion of transgenic progeny from 20% to 30% relative to uninfected insects. Aseptic conditions may improve the fitness of transgenic males by excluding microbial contaminants, while symbiont inoculation could further improve fitness by providing additional protection against infection, or by normalizing insect physiology. The simple innovation of incorporating antibiotic into diet, and inoculating insects with symbiotic bacteria that are resistant to that antibiotic, could provide a readily transferable tool for other insect rearing systems.

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Veldhuizen, David A. Van, and Gary B. Lamont. "Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art." Evolutionary Computation 8, no. 2 (June 2000): 125–47. http://dx.doi.org/10.1162/106365600568158.

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Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied during the mid-eighties in an attempt to stochastically solve problems of this generic class. During the past decade, a variety of multiobjective EA (MOEA) techniques have been proposed and applied to many scientific and engineering applications. Our discussion's intent is to rigorously define multiobjective optimization problems and certain related concepts, present an MOEA classification scheme, and evaluate the variety of contemporary MOEAs. Current MOEA theoretical developments are evaluated; specific topics addressed include fitness functions, Pareto ranking, niching, fitness sharing, mating restriction, and secondary populations. Since the development and application of MOEAs is a dynamic and rapidly growing activity, we focus on key analytical insights based upon critical MOEA evaluation of current research and applications. Recommended MOEA designs are presented, along with conclusions and recommendations for future work.

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Lin, I.-I., You-Lin Chen, and Li-Ling Chuang. "Test-Retest Reliability of Home-Based Fitness Assessments Using a Mobile App (R Plus Health) in Healthy Adults: Prospective Quantitative Study." JMIR Formative Research 5, no. 12 (December 8, 2021): e28040. http://dx.doi.org/10.2196/28040.

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Background Poor physical fitness has a negative impact on overall health status. An increasing number of health-related mobile apps have emerged to reduce the burden of medical care and the inconvenience of long-distance travel. However, few studies have been conducted on home-based fitness tests using apps. Insufficient monitoring of physiological signals during fitness assessments have been noted. Therefore, we developed R Plus Health, a digital health app that incorporates all the components of a fitness assessment with concomitant physiological signal monitoring. Objective The aim of this study is to investigate the test-retest reliability of home-based fitness assessments using the R Plus Health app in healthy adults. Methods A total of 31 healthy young adults self-executed 2 fitness assessments using the R Plus Health app, with a 2- to 3-day interval between assessments. The fitness assessments included cardiorespiratory endurance, strength, flexibility, mobility, and balance tests. The intraclass correlation coefficient was computed as a measure of the relative reliability of the fitness assessments and determined their consistency. The SE of measurement, smallest real difference at a 90% CI, and Bland–Altman analyses were used to assess agreement, sensitivity to real change, and systematic bias detection, respectively. Results The relative reliability of the fitness assessments using R Plus Health was moderate to good (intraclass correlation coefficient 0.8-0.99 for raw scores, 0.69-0.99 for converted scores). The SE of measurement and smallest real difference at a 90% CI were 1.44-6.91 and 3.36-16.11, respectively, in all fitness assessments. The 95% CI of the mean difference indicated no significant systematic error between the assessments for the strength and balance tests. The Bland–Altman analyses revealed no significant systematic bias between the assessments for all tests, with a few outliers. The Bland–Altman plots illustrated narrow limits of agreement for upper extremity strength, abdominal strength, and right leg stance tests, indicating good agreement between the 2 assessments. Conclusions Home-based fitness assessments using the R Plus Health app were reliable and feasible in young, healthy adults. The results of the fitness assessments can offer a comprehensive understanding of general health status and help prescribe safe and suitable exercise training regimens. In future work, the app will be tested in different populations (eg, patients with chronic diseases or users with poor fitness), and the results will be compared with clinical test results. Trial Registration Chinese Clinical Trial Registry ChiCTR2000030905; http://www.chictr.org.cn/showproj.aspx?proj=50229

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LEE, MAL-REY. "GENERATING FUZZY RULES BY GENETIC METHOD AND ITS APPLICATIONS." International Journal on Artificial Intelligence Tools 07, no. 04 (December 1998): 399–413. http://dx.doi.org/10.1142/s0218213098000184.

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This paper proposes a GA method for choosing an appropriate set of fuzzy rules for classification problems. The aim of the proposed method is to find a minimum set of fuzzy rules that can correctly classify all training patterns. The number of inference rules and the shapes of the membership functions in the antecedent part of the fuzzy rules are determined by the genetic algorithms. The real numbers in the consequent parts of the fuzzy rules are obtained through the use of the descent method. A fitness function is used to maximize the number of correctly classified patterns, and to minimize the number of fuzzy rules. A solution obtained by the genetic algorithm is a set of fuzzy rules, and its fitness is determined by the two objectives, in a combinatorial optimization problem. In order to demonstrate the effectiveness of the proposed method, computer simulation results are shown.

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Sas-Nowosielski, Krzysztof, Sylwia Szopa, and Agnieszka Kowalczyk. "Use of Mobile Fitness-Related Applications and Active Video Games in High-School Youth." Polish Journal of Sport and Tourism 23, no. 3 (September 1, 2016): 167–70. http://dx.doi.org/10.1515/pjst-2016-0022.

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Abstract Introduction. Not many studies have been performed in Poland on using mobile applications from the sport and fitness category and exergames. The main purpose of this study was to investigate to what extent such technologies are used by youth. Material and methods. A total of 435 pupils (including 263 females) aged 17.78 ± 1.19 years took part in the study. A diagnostic survey was carried out; the data were collected using a questionnaire developed by the authors and a scale assessing the stage of exercise change developed by Marcus, Rakowski, and Rossi (1992). Descriptive statistics (means and standard deviations) were used to describe the data and to test differences between groups; a chi2 test was used with Cramér’s V statistic as a measure of effect size in contingency tables larger than 2 × 2. Results. Of the 435 participants, approximately a third (30.8%) had used some type of fitness application. The most frequently downloaded applications were exercise plans, such as Weider’s Aerobic Six and applications for physical activity monitoring (steps, distance), such as Endomondo. Exergames were less popular. Only 5.29% of the respondents claimed they used exergames regularly, although about every third person used them regularly, especially males. Conclusions. Eight of ten respondents held the view that such applications are useful but are something that they could do without; only one in ten could not imagine exercising without such applications. Most of the latter category of users were persons at the action stage, next - persons at the preparation stage, but - what is interesting - none at the maintenance stage. It seems, then, that such applications may be - and in the light of the data obtained really are - an indispensable aid for people at the early stages of developing a habit of regular physical activity.

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Oyibo, Kiemute, and Julita Vassileva. "Investigation of persuasive system design predictors of competitive behavior in fitness application: A mixed-method approach." DIGITAL HEALTH 5 (January 2019): 205520761987860. http://dx.doi.org/10.1177/2055207619878601.

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Fitness applications aimed at behavior change are becoming increasingly popular due to the global prevalence of sedentary lifestyles and physical inactivity, causing countless non-communicable diseases. Competition is one of the most common persuasive strategies employed in such applications to motivate users to engage in physical activity in a social context. However, there is limited research on the persuasive system design predictors of users’ susceptibility to competition as a persuasive strategy for motivating behavior change in a social context. To bridge this gap, we designed storyboards illustrating four of the commonly employed persuasive strategies (reward, social learning, social comparison, and competition) in fitness applications and asked potential users to evaluate their perceived persuasiveness. The result of our path analysis showed that, overall, users’ susceptibilities to social comparison (βT = 0.48, p < 0.001), reward (βT = 0.42, p < 0.001), and social learning (βT = 0.29, p < 0.01) predicted their susceptibility to competition, with our model accounting for 41% of its variance. Social comparison partially mediated the relationship between reward and competition, while social learning partially mediated the relationship between social comparison and competition. Comparatively, the relationship between reward and social learning was stronger for females than for males, whereas the relationship between reward and competition was stronger for males than for females. Overall, our findings underscore the compatibility of all four persuasive strategies in a one-size-fits-all fitness application. We discuss our findings, drawing insight from the comments provided by participants.

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Lattanzio, Veronica M. T. "Toward Harmonization of Performance Criteria for Mycotoxin Screening Methods: The EU Perspective." Journal of AOAC INTERNATIONAL 99, no. 4 (July 1, 2016): 906–13. http://dx.doi.org/10.5740/jaoacint.16-0118.

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Abstract Screening methods are defined as methods that are used to detect the presence of a substance or class of substances at the level of interest. These methods must have the capability of high sample throughput when being used to screen large numbers of samples for potential noncompliant results. Before using a screening method for practical applications, its fitness for the intended purpose needs to be demonstrated. This is normally achieved by conducting a validation study, comparing method performance against predefined criteria. Official guidelines recently established by the European Union for the evaluation of fitness-for-purpose performance parameters of screening methods to be used for the detection of mycotoxins in foods are presented and discussed herein. Practical applications of this evaluation scheme for single- and interlaboratory validation studies, as well as relevant information on screening method performances are reviewed, with emphasis on the impact of mycotoxin contamination in real samples on the fitness-for-purpose of the screening test. Lastly, validation follow-up is discussed in terms of extension of the scope of the method (increasing the range of application in terms of mycotoxin/matrix combinations), method implementation and verification, and evaluation of the method's applicability to modified mycotoxins.

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Gusev, A. V., A. A. Ivshin, and A. V. Vladzymyrskyy. "Healthcare in the smartphone: the situation in Russia." Russian Journal of Telemedicine and E-Health 7, no. 3 (September 6, 2021): 21–31. http://dx.doi.org/10.29188/2712-9217-2021-7-3-21-31.

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The purpose of the study was to analyze the popularity of mobile applications for health care in Russia. Material and methods. The app stores «App Store» of Apple and «Google Play Store» of Google were studied for comparative analysis. In case of The App Store we analyzed the categories «Medicine and Health and Fitness», in the Google Play Store – the categories «Medicine», «Motherhood and Childhood» and «Health and Fitness». The total amount of applications was 231. The reviewed applications were grouped into several groups and ranked in descending order of popularity. Results. The most popular applications by the number of downloads were applications from the group «Fitness and healthy lifestyle»: by individual positions – more than 1,2 billion. installations. On the second place was the group «Women's Health» with more than 285 million installations. The highest ratings of applications in the context of groups were received by services related to pregnancy control, evaluation of fetal and child development, as well as services for determining the symptoms of diseases. Conclusions. Thus, the most popular content for health care is the analysis of physical activity, regular diagnostics of the state of the body, monitoring of women's health indicators and monitoring the course of pregnancy, children's health.

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Rowan, Mark, and Josh Dehlinger. "A Privacy Policy Comparison of Health and Fitness Related Mobile Applications." Procedia Computer Science 37 (2014): 348–55. http://dx.doi.org/10.1016/j.procs.2014.08.051.

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Journal articles on the topic 'Fitness applications'

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