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Relevant bibliographies by topics / Weight training

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Academic literature on the topic 'Weight training'

Author: Grafiati

Published: 4 June 2021

Last updated: 31 July 2024

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Journal articles on the topic "Weight training"

1

Van Kley, Emily. "Weight Training." Iowa Review 41, no. 3 (December 2011): 55–56. http://dx.doi.org/10.17077/0021-065x.7076.

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Bahrke, Michael S., and Charles E. Yesalis. "Weight Training." Sports Medicine 18, no. 5 (November 1994): 309–18. http://dx.doi.org/10.2165/00007256-199418050-00003.

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Bartels, Robert L. "Weight Training." Physician and Sportsmedicine 20, no. 3 (March 1992): 233–34. http://dx.doi.org/10.1080/00913847.1992.11710261.

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Yang, Jum Hong, Chi Wook Park, and Jae Hyun Choi. "Effects of 24-Week Weight Training and Plyometric Training on the Physique, Body Composition and Fitness of Male High School Students." Journal of Sport and Leisure Studies 30 (September 30, 2007): 583–93. http://dx.doi.org/10.51979/kssls.2007.09.30.583.

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Stamford, Bryant. "Weight Training Basics." Physician and Sportsmedicine 26, no. 2 (February 1998): 115–16. http://dx.doi.org/10.3810/psm.1998.02.1585.

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Reeves, Ronald K., Edward R. Laskowski, and Jay Smith. "Weight Training Injuries." Physician and Sportsmedicine 26, no. 2 (February 1998): 67–96. http://dx.doi.org/10.3810/psm.1998.02.939.

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Kelemen, Michael H., and Kerry J. Stewart. "Circuit Weight Training." Sports Medicine 2, no. 6 (1985): 385–88. http://dx.doi.org/10.2165/00007256-198502060-00001.

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Mazur, Lynnette J., Robert J. Yetman, and William L. Risser. "Weight-Training Injuries." Sports Medicine 16, no. 1 (July 1993): 57–63. http://dx.doi.org/10.2165/00007256-199316010-00005.

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STEWART, KERRY J., and MICHAEL H. KELEMEN. "Resistive Weight Training." Medicine & Science in Sports & Exercise 21, no. 6 (December 1989): 667. http://dx.doi.org/10.1249/00005768-198912000-00007.

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McNamara, John M., Ricky L. Swalm, David J. Stearne, and Tracey M. Covassin. "Online Weight Training." Journal of Strength and Conditioning Research 22, no. 4 (July 2008): 1164–68. http://dx.doi.org/10.1519/jsc.0b013e31816eb4e0.

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Dissertations / Theses on the topic "Weight training"

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Lee, Andrew George. "The effect of endurance training, weight training and a combination of endurance and weight training on blood lipid profiles." Virtual Press, 1987. http://liblink.bsu.edu/uhtbin/catkey/546117.

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Etten, Ludovicus Maria Leonardus Anna van. "Weight training: implications for energy metabolism." Maastricht : Maastricht : Universiteit Maastricht ; University Library, Maastricht University [Host], 1997. http://arno.unimaas.nl/show.cgi?fid=6819.

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Tanaka, Hirofumi. "Dry-land strength training for competitive swimming : interaction between strength training and swim training." Virtual Press, 1992. http://liblink.bsu.edu/uhtbin/catkey/834620.

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In an attempt to determine the value of dry-land weight training on swimming performance, two groups of twenty four intercollegiate male swimmers were equated based upon pre-swimming performance, swim power values, stroke specialities, and collegiate swimming experience. At the start of a swimming season there were no significant differences (p>0.05) between the swim training group (SWIM, N=12) and the combined weight and swim training group (COMBO, N=12). Throughout the 13 weeks of their competitive swimming season, both SWIM and COMBO swam together six days a week. In addition, the COMBO engaged in a weight training program three days a week between the third and eleventh weeks (for eight weeks) of the season. The weight training program, using free weights, was intended to simulate arm actions and muscle actions similar to those used during front crawl swimming. Both COMBO and SWIM groups had significant but similar power gains (p<0.05) as measured on the biokinetic swim bench and during a tethered swim. Swimmers in both groups experienced a significant (p<0.05) increase in competitive swim performance from 1991 to 1992 (0.89 ± 0.60% in COMBO and 0.87 ± 0.4Q% in SWIM) whereas no change in distance per stroke (p>0.05) was observed throughout the course of this investigation. Mean total testosterone levels were not altered during the weight training period in either group. No significant (p>0.05) differences were found between the groups in any of the swim power and swimming performance tests. In this investigation, dry-land weight training did not improve swimming performance despite the fact that the COMBO was able to increase the weights used during strength training by 25 to 35%. The lack of positive transfer between dry-land strength gains and swimming propulsive force may be due to the specificity of training.
Human Performance Laboratory

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Johnston, Cutting Smart. "Menstrual dysfunction and eating behaviors in weight training women." Thesis, Virginia Polytechnic Institute and State University, 1986. http://hdl.handle.net/10919/90950.

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To obtain descriptive information concerning female bodybuilders and women who weight train, a questionnaire concerning training regimes, menstrual history and dieting strategies was developed and administered with the EDI included as part of the questionnaire. Factors assessed included: incidence of menstrual irregularity, scores on the Eating Disorder Inventory (EDI), prevalence of behaviors associated with eating disorders, and mean body fat. Subjects were between the ages of 18 and 35 and included individuals from Personal Health Classes at Virginia Tech, the Virginia Tech Weight Lifting Club, and Goad's Gym in Blacksburg, Virginia. Subjects were classified by activity (weight lifters versus controls), involvement (high, moderate and low) and competition (noncompetitive and competitive). Chi-square analysis indicated that there was no difference in incidence rates of menstrual irregularity between weight lifters (WLs) and controls (Cs); however, the rates of both groups were higher than the general population. Although there was no difference in menstrual function of involvement groups, 50% of the competitors, significantly more than non-competitors, were classified as oligomenorrheic or amenorrheic. All subject groups had mean scores approaching anorexic patient norms on the EDI Bulimia and Maturity Fears subscales. WLs were significantly higher on Drive for Thinness than Cs and more WLs had subscale scores higher than the mean scores presented for anorexics. Additionally, significantly more WLs reported uncontrollable urges to eat, fear of fat, and history of anorexia. Mean %BF of the WLs was 20.18% with competitors being significantly leaner than non-competitors. The high degree of menstrual dysfunction in both WLs and Cs is confusing; yet, the 27% incidence of oligomenorrhea and amenorrhea in WLs is much higher than the rates documented for the general population. The high Drive for Thinness and incidence of negative eating behaviors indicate that the prevalence of eating disorders in this population may progress as this relatively new sport evolves and competitive participation increases.
M.S.

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Adams, Lisa G. Suh Suhyun. "Weight bias amongst counselors-In-training a qualitative inquiry /." Auburn, Ala, 2008. http://hdl.handle.net/10415/1438.

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Greer, Micah D. "Exercise training improves premenopausal women's ability to estimate energy expediture after weight loss." Birmingham, Ala. : University of Alabama at Birmingham, 2008. https://www.mhsl.uab.edu/dt/2008m/greer.pdf.

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Frost, David M. "A biomechanical comparison of pneumatic and free weight resistance." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2008. https://ro.ecu.edu.au/theses/215.

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蒲志強 and Chi-keung Philip Po. "The effect of massage and weight training on muscular performance." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B31257318.

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Po, Chi-keung Philip. "The effect of massage and weight training on muscular performance /." Hong Kong : University of Hong Kong, 2002. http://sunzi.lib.hku.hk/hkuto/record.jsp?B25336253.

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Sipe, Marie Elizabeth. "Weight training in older adults : an intervention for psychological empowerment /." Electronic thesis, 2004. http://etd.wfu.edu/theses/available/etd-05132004-142300/.

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Books on the topic "Weight training"

1

British Amateur Weight Lifters' Association., ed. Weight training. London: Black, 1986.

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1958-, Roberts Scott, ed. Weight training. Boston: WCB/McGraw-Hill, 1999.

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1967-, Earle Roger W., ed. Fitness weight training. Champaign, IL: Human Kinetics, 1995.

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1967-, Earle Roger W., ed. Fitness weight training. 2nd ed. Champaign, IL: Human Kinetics, 2005.

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F, Signorile Joseph, and Tuten Rich, eds. Weight training everyone. 4th ed. Winston-Salem, N.C: Hunter Textbooks, 1993.

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D, Fahey Thomas. Basic weight training. Mountain View, Calif: Mayfield Pub. Co., 1989.

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Harfield, David. Safe weight training. Oxford: British Amateur Weightlifter's Association (BAWLA) Coaching Publication, 1993.

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Signorile, Joseph F. Weight training everyone. 5th ed. Winston-Salem, N.C: Hunter Textbooks, 2007.

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Sandler, David. Fundamental weight training. Champaign, IL: Human Kinetics, 2010.

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Sandler, David. Fundamental weight training. Champaign, IL: Human Kinetics, 2010.

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Book chapters on the topic "Weight training"

1

Harrison, Layci. "Nutrition and Weight Management." In Clinical Nutrition in Athletic Training, 73–87. New York: Routledge, 2024. http://dx.doi.org/10.4324/9781003523079-7.

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Ho, Kevin, Chi-sing Leung, and John Sum. "On Weight-Noise-Injection Training." In Advances in Neuro-Information Processing, 919–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03040-6_112.

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Schmidt, Alexandria M., and Paula M. Brochu. "Incorporating fat pedagogy into health care training." In Weight Bias in Health Education, 148–58. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003057000-15.

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Phillips, Stuart M., Keith Baar, and Nathan Lewis. "Nutrition for Weight and Resistance Training." In Sport and Exercise Nutrition, 120–33. Oxford, UK: Wiley-Blackwell, 2011. http://dx.doi.org/10.1002/9781444344905.ch10.

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Manore, Melinda M. "Weight Management in the Performance Athlete." In Nutritional Coaching Strategy to Modulate Training Efficiency, 123–33. Basel: S. KARGER AG, 2013. http://dx.doi.org/10.1159/000345831.

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Gorse, Keith M., Francis Feld, and Robert O. Blanc. "Hip Injury in a College Swimmer in a Weight Room." In Athletic Training Case Scenarios, 67–68. New York: Routledge, 2024. http://dx.doi.org/10.4324/9781003522676-34.

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Sum, John, and Kevin Ho. "SNIWD: Simultaneous Weight Noise Injection with Weight Decay for MLP Training." In Neural Information Processing, 494–501. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10677-4_56.

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Zhang, Daiyuan. "Training Neural Networks by Rational Weight Functions." In Artificial Intelligence and Computational Intelligence, 346–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23896-3_42.

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Fuengfusin, Ninnart, and Hakaru Tamukoh. "Mixed Precision Weight Networks: Training Neural Networks with Varied Precision Weights." In Neural Information Processing, 614–23. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04179-3_54.

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Hu, Qinghao, Gang Li, Peisong Wang, Yifan Zhang, and Jian Cheng. "Training Binary Weight Networks via Semi-Binary Decomposition." In Computer Vision – ECCV 2018, 657–73. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01261-8_39.

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Conference papers on the topic "Weight training"

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Toor, Karanbir S., Ameet S. Toor, Charlton M. Smith, and Alexander G. Orozco. "Oli, Your Weight-Training Assistant." In CHI '17: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3027063.3048429.

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Wang, Xiaohuan Corina, and Cary Phillips. "Body building through weight training." In ACM SIGGRAPH 2002 conference abstracts and applications. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/1242073.1242165.

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Niehaus, Lukas, Ulf Krumnack, and Gunther Heidemann. "Weight Rescaling: Applying Initialization Strategies During Training." In 14th Scandinavian Conference on Artificial Intelligence SCAI 2024, June 10-11, 2024, Jönköping, Sweden. Linköping University Electronic Press, 2024. http://dx.doi.org/10.3384/ecp208010.

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The training success of deep learning is known to depend on the initial statistics of neural network parameters. Various strategies have been developed to determine suitable mean and standard deviation for weight distributions based on network architecture. However, during training, weights often diverge from their initial scale. This paper introduces the novel concept of weight rescaling, which enforces weights to remain within their initial regime throughout the training process. It is demonstrated that weight rescaling serves as an effective regularization method, reducing overfitting and stabilizing training while improving neural network performance. The approach rescales weight vector magnitudes to match the initialization methods’ conditions without altering their direction. It exhibits minimal memory usage, is lightweight on computational resources and demonstrates comparable results to weight decay, but without introducing additional hyperparameters as it leverages architectural information. Empirical testing shows improved performance across various architectures, even when combined with additional regularization methods like dropout in AlexNet and batch normalization in ResNet-50. The effectiveness of weight rescaling is further supported by a thorough statistical evaluation.

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Kim, Jung-Jae, Min-woo Ryu, Si-Ho Cha, and Kuk-Hyun Cho. "Weight Initialization-based Partial Training Algorithm." In Smart Information Technology 2016. Science & Engineering Research Support soCiety, 2016. http://dx.doi.org/10.14257/astl.2016.142.14.

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Hwang, Joong-won, Youngwan Lee, Sungchan Oh, and Yuseok Bae. "Adversarial Training With Stochastic Weight Average." In 2021 IEEE International Conference on Image Processing (ICIP). IEEE, 2021. http://dx.doi.org/10.1109/icip42928.2021.9506548.

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Yu, Chaojian, Bo Han, Mingming Gong, Li Shen, Shiming Ge, Du Bo, and Tongliang Liu. "Robust Weight Perturbation for Adversarial Training." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/512.

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Overfitting widely exists in adversarial robust training of deep networks. An effective remedy is adversarial weight perturbation, which injects the worst-case weight perturbation during network training by maximizing the classification loss on adversarial examples. Adversarial weight perturbation helps reduce the robust generalization gap; however, it also undermines the robustness improvement. A criterion that regulates the weight perturbation is therefore crucial for adversarial training. In this paper, we propose such a criterion, namely Loss Stationary Condition (LSC) for constrained perturbation. With LSC, we find that it is essential to conduct weight perturbation on adversarial data with small classification loss to eliminate robust overfitting. Weight perturbation on adversarial data with large classification loss is not necessary and may even lead to poor robustness. Based on these observations, we propose a robust perturbation strategy to constrain the extent of weight perturbation. The perturbation strategy prevents deep networks from overfitting while avoiding the side effect of excessive weight perturbation, significantly improving the robustness of adversarial training. Extensive experiments demonstrate the superiority of the proposed method over the state-of-the-art adversarial training methods.

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Seibert, K. E., M. J. Bailey, D. L. Pruitt, M. S. Dejesus, P. A. Toste, and T. C. Hammond. "Spontaneous Tension Hemopneumothorax After Weight Training." In American Thoracic Society 2024 International Conference, May 17-22, 2024 - San Diego, CA. American Thoracic Society, 2024. http://dx.doi.org/10.1164/ajrccm-conference.2024.209.1_meetingabstracts.a4825.

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Kowsar, Yousef, Masud Moshtaghi, Eduardo Velloso, Lars Kulik, and Christopher Leckie. "Detecting unseen anomalies in weight training exercises." In the 28th Australian Conference. New York, New York, USA: ACM Press, 2016. http://dx.doi.org/10.1145/3010915.3010941.

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Meron, Yoram, and Keikichi Hirose. "Efficient weight training for selection based synthesis." In 6th European Conference on Speech Communication and Technology (Eurospeech 1999). ISCA: ISCA, 1999. http://dx.doi.org/10.21437/eurospeech.1999-506.

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Masood, Sarfaraz, and Pravin Chandra. "Training neural network with zero weight initialization." In the CUBE International Information Technology Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2381716.2381761.

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Reports on the topic "Weight training"

1

McDonnell, John R. Training Neural Networks with Weight Constraints. Fort Belvoir, VA: Defense Technical Information Center, March 1993. http://dx.doi.org/10.21236/ada264665.

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Buckmaster, Lisa. Effects of cognition training on locus of control, weight reduction, and problem solving ability. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2850.

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Brittany Hollerbach, Brittany Hollerbach. A Comparison of Muscular Strength, Power, and Endurance Between CrossFit and Traditional Weight Training Classes. Experiment, August 2017. http://dx.doi.org/10.18258/9745.

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Hesslink, Robert. The effects of a combined weight training and running program on body composition in college males. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.3299.

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Gorman, Peter, Paula Geigle, and Keith Tansey. A Comparison of Robotic, Body Weight-Supported Locomotor Training and Aquatic Therapy in Chronic Motor Incomplete Spinal Cord Injury Subject. Fort Belvoir, VA: Defense Technical Information Center, October 2012. http://dx.doi.org/10.21236/ada570537.

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Gorman, Peter, and Paula Geigle. A Comparison of Robotic, Body Weight-Supported Locomotor Training and Aquatic Therapy in Chronic Motor Incomplete Spinal Cord Injury Subject. Fort Belvoir, VA: Defense Technical Information Center, October 2013. http://dx.doi.org/10.21236/ada594822.

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Regan, Jack, and Robin Zevotek. Evaluation of the Thermal Conditions and Smoke Obscuration of Live Fire Training Fuel Packages. UL Firefighter Safety Research Institute, March 2019. http://dx.doi.org/10.54206/102376/karu4002.

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Firefighters routinely conduct live fire training in an effort to prepare themselves for the challenges of the fire ground. While conducting realistic live fire training is important, it also carries inherent risks. This is highlighted by several live fire training incidents in which an inappropriate fuel load contributed to the death of participants. NFPA 1403: Standard on Live Fire Training Evolutions was first established in response to a live fire training incident in which several firefighters died. Among the stipulations in NFPA 1403 is that the fuel load shall be composed of wood-based fuels. The challenge of balancing safety with fidelity has led instructors to explore a variety of different methods to create more realistic training conditions. A series of experiments was conducted in order to characterize common training fuels, compare these training fuels to furnishings, and examine the performance of these training fuels in a metal container prop. Heat release rate (HRR) characterization of training fuels indicated that wood-based training fuels had a constant effective heat of combustion. Depending on the method used, this value was between 13.6 and 13.9 MJ/kg. This indicates that, even in engineered wood products, wood is the primary material responsible for combustion. In order to further explore the conclusions from the HRR testing, additional experiments were conducted in an L-shaped metal training prop. The results of these experiments highlighted a number of considerations for firefighter training. Thermal conditions consistent with “realistic fires” could be produced using NFPA 1403 compliant fuels, and in fact the thermal conditions produced by larger wood-based fuel packages were more severe than those produced by fuel packages with a small amount of synthetic fuel. The fuel package used in training evolutions should reflect the training prop or building being used, the available ventilation, and the intended lesson. Fuel load weight and orientation are both important considerations when designing a fuel package. The training considerations drawn from this report will help to increase firefighters’ understanding of fire dynamics, and help instructors better understand fuel packages and the fire dynamics that they produce.

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liu, cong, xing wang, rao chen, and jie zhang. Meta-analyses of the Effects of Virtual Reality Training on Balance, Gross Motor Function and Daily Living Ability in Children with Cerebral Palsy. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, April 2022. http://dx.doi.org/10.37766/inplasy2022.4.0137.

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Review question / Objective: Cerebral palsy (CP) is a non-progressive, persistent syndrome occurring in the brain of the fetus or infant[1]. The prevalence of CP is 0.2% worldwide, and the prevalence can increase to 20-30 times in preterm or low birth weight newborns. There are about 6 million children with CP in China, and the number is increasing at a rate of 45,000 per year. Virtual reality (VR) refers to a virtual environment that is generated by a computer and can be interacted with.VR can mobilize the visual, auditory, tactile and kinesthetic organs of CP, so that they can actively participate in the rehabilitation exercise. Information sources: Two researchers searched 5 databases, including Pubmed (N=82), Embase (N=191), The Cochrane Library (N=147), Web of Science (N=359) and CNKI (N=11).

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Medina, Carlos, Jairo Núñez, and Jorge Andrés Tamayo. The Unemployment Subsidy Program in Colombia: An Assessment. Inter-American Development Bank, May 2013. http://dx.doi.org/10.18235/0011497.

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This paper assesses the effects of the Colombian Unemployment Subsidy (US), which includes benefits as well as training for some recipients. Using regression discontinuity and matching differences-in-differences estimators, the study finds that participation in the labor market, earnings of beneficiaries, and household income do not increase, and for some populations decrease during the 18 months after leaving the US program. Enrollment in formal health insurance falls. Effects on male heads of household include reductions in their earnings, decreases in their labor participation, and increases in their unemployment rates. The study also finds a small though statistically significant positive effect on beneficiaries¿ school attendance, but none on their children¿s weight or height at birth. The results are sensitive to the type of training that beneficiaries receive. Overall, the program serves more as a mechanism for smoothing consumption and providing social assistance than for increasing labor market efficiency.

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Rinaudo, Christina, William Leonard, Jaylen Hopson, Christopher Morey, Robert Hilborn, and Theresa Coumbe. Enabling understanding of artificial intelligence (AI) agent wargaming decisions through visualizations. Engineer Research and Development Center (U.S.), April 2024. http://dx.doi.org/10.21079/11681/48418.

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The process to develop options for military planning course of action (COA) development and analysis relies on human subject matter expertise. Analyzing COAs requires examining several factors and understanding complex interactions and dependencies associated with actions, reactions, proposed counteractions, and multiple reasonable outcomes. In Fiscal Year 2021, the Institute for Systems Engineering Research team completed efforts resulting in a wargaming maritime framework capable of training an artificial intelligence (AI) agent with deep reinforcement learning (DRL) techniques within a maritime scenario where the AI agent credibly competes against blue agents in gameplay. However, a limitation of using DRL for agent training relates to the transparency of how the AI agent makes decisions. If leaders were to rely on AI agents for COA development or analysis, they would want to understand those decisions. In or-der to support increased understanding, researchers engaged with stakeholders to determine visualization requirements and developed initial prototypes for stakeholder feedback in order to support increased understanding of AI-generated decisions and recommendations. This report describes the prototype visualizations developed to support the use case of a mission planner and an AI agent trainer. The prototypes include training results charts, heat map visualizations of agent paths, weight matrix visualizations, and ablation testing graphs.

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