Relevant bibliographies by topics / Interval FL type 2

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Interval FL type 2'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Interval FL type 2"

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Hayder, Yousif Abed, Thiab Humod Abdulrahim, and J. Humaidi Amjad. "Type 1 versus type 2 fuzzy logic speed controllers for brushless DC motors." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 1 (2020): 265–74. https://doi.org/10.11591/ijece.v10i1.pp265-274.

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This work presented two fuzzy logic (FL) schemes for speed-controlled brushless DC motors. The first controller is a Type 1 FL controller (T1FLC), whereas the second controller is an interval Type 2 FL controller (IT2FLC). The two proposed controllers were compared in terms of system dynamics and performance. For a fair comparison, the same type and number of membership functions were used for both controllers. The effectiveness of the structures of the two FL controllers was verified through simulation in MATLAB/SIMULINK environment. Simulation result showed that IT2FLC exhibited better perfo
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Abed, Hayder Yousif, Abdulrahim Thiab Humod, and Amjad J. Humaidi. "Type 1 versus type 2 fuzzy logic speed controllers for brushless dc motors." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 1 (2020): 265. http://dx.doi.org/10.11591/ijece.v10i1.pp265-274.

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<span lang="EN-US">This work presented two fuzzy logic (FL) schemes for speed-controlled brushless DC motors. The first controller is a Type 1 FL controller (T1FLC), whereas the second controller is an interval Type 2 FL controller (IT2FLC). The two proposed controllers were compared in terms of system dynamics and performance. For a fair comparison, the same type and number of membership functions were used for both controllers. The effectiveness of the structures of the two FL controllers was verified through simulation in MATLAB/SIMULINK environment. Simulation result showed that IT2F
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Hwang, Ji-Hwan, Young-Chang Kang, Jong-Wook Park, and Dong W. Kim. "Advanced Interval Type-2 Fuzzy Sliding Mode Control for Robot Manipulator." Computational Intelligence and Neuroscience 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/9640849.

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In this paper, advanced interval type-2 fuzzy sliding mode control (AIT2FSMC) for robot manipulator is proposed. The proposed AIT2FSMC is a combination of interval type-2 fuzzy system and sliding mode control. For resembling a feedback linearization (FL) control law, interval type-2 fuzzy system is designed. For compensating the approximation error between the FL control law and interval type-2 fuzzy system, sliding mode controller is designed, respectively. The tuning algorithms are derived in the sense of Lyapunov stability theorem. Two-link rigid robot manipulator with nonlinearity is used
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Mashhadany (SMIEEE), Yousif Al, Sameh Jassam, and Elaf Hamzah Yahia. "Design and Simulation of Modified Type-2 Fuzzy Logic Controller for Power System." International Journal of Electrical and Electronics Research 10, no. 3 (2022): 731–36. http://dx.doi.org/10.37391/ijeer.100352.

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This Article exhibits the structure of a Modified Type-2 (MT2) Fuzzy Logic (FL) Controller (MT2FLC), direction line programming of development, also performance optimization for different power systems. The implementation of the MT2FLC for control of a power system. New participation capacities were considered in adjusting a domain for an Interval Type-2 (IT2) Fuzzy Logic (FL) System (IT2FLS). Another structure in graphic user interface (GUI) mimicked four controllers: an optimal PID controller, FLC, a Type-1(TIFLC), an Interval Type-2 ((IT2FLC), and the MIT2FLC. Their yields were analysed, di
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Kasmi, B., and A. Hassam. "Comparative Study between Fuzzy Logic and Interval Type-2 Fuzzy Logic Controllers for the Trajectory Planning of a Mobile Robot." Engineering, Technology & Applied Science Research 11, no. 2 (2021): 7011–17. http://dx.doi.org/10.48084/etasr.4031.

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In this study, Fuzzy Logic (FL) and Interval Type-2 FL (IT-2FL) controllers were applied to a mobile robot in order to determine which method facilitates navigation and enables the robot to overcome real-world uncertainties and track an optimal trajectory in a very short time. The robot under consideration is a non-holonomic unicycle mobile robot, represented by a kinematic model, evolving in two different environments. The first environment is barrier-free, and moving the robot from an initial to a target position requires the introduction of a single action module. Subsequently, the same pro
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Atacak, İsmail, Oğuzhan Çıtlak, and İbrahim Alper Doğru. "Application of interval type-2 fuzzy logic and type-1 fuzzy logic-based approaches to social networks for spam detection with combined feature capabilities." PeerJ Computer Science 9 (April 21, 2023): e1316. http://dx.doi.org/10.7717/peerj-cs.1316.

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Background Social networks are large platforms that allow their users to interact with each other on the Internet. Today, the widespread use of social networks has made them vulnerable to malicious use through different methods such as fake accounts and spam. As a result, many social network users are exposed to the harmful effects of spam accounts created by malicious people. Although Twitter, one of the most popular social networking platforms, uses spam filters to protect its users from the harmful effects of spam, these filters are insufficient to detect spam accounts that exhibit new meth
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Arai, Hiroyuki, Eisuke Inoue, Kensei Yamaguchi, et al. "Clinical implication of using up both fluoropyrimidine (FU) and paclitaxel (PTX) in patients with severe peritoneal metastases (SPM) of gastric cancer (GC)." Journal of Clinical Oncology 39, no. 3_suppl (2021): 221. http://dx.doi.org/10.1200/jco.2021.39.3_suppl.221.

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221 Background: JCOG1108/WJOG7312G trial showed favorable but not significantly better outcomes of 5-FU/ l-leucovorin ( l-LV) /PTX combination (FLTAX) compared to 5-FU/ l-LV (FL) in untreated patients with SPM of GC. However, a half of patients treated with FL could not sequentially use PTX which is a key drug for peritoneal metastasis. We conducted a post hoc analysis to investigate the clinical implication of using up both FU and PTX in either combination or sequential strategy for GC patients with SPM. Methods: Among 101 patients enrolled in the trial (FL: N = 51; FLTAX: N = 50), overall su
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Freckmann, Guido, Stephan Arndt, Albrecht Fießelmann, et al. "Randomized Cross-Over Study Comparing Two Infusion Sets for CSII in Daily Life." Journal of Diabetes Science and Technology 11, no. 2 (2016): 253–59. http://dx.doi.org/10.1177/1932296816667510.

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Background: Continuous subcutaneous insulin infusion (CSII) therapy is a valuable option especially for people with type 1 diabetes. Although insulin infusion sets (IIS) are essential components of most insulin pump systems, only few studies have been conducted on their performance and safety. In this study 2 IIS with soft cannulas were compared. Methods: In an open-label, randomized, crossover, multicenter 8-week study 80 type 1 diabetic subjects on CSII (20-74 years, mean 46.5 ± 12.9 years, 58.8% male) were enrolled to evaluate the use of 2 IIS. The Accu-Chek® FlexLink Plus (FL Plus) and the
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Heller, Nicola, Xiulan Qi, Franck Gesbert, and Achsah Keegan. "The region in the common gamma chain between amino acids (aa) 314-323 dictates efficient activation of the insulin receptor substrate (IRS)-2 pathway by interleukin (IL)-4. (134.4)." Journal of Immunology 184, no. 1_Supplement (2010): 134.4. http://dx.doi.org/10.4049/jimmunol.184.supp.134.4.

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Abstract Previously, we demonstrated that the γC subunit of type I IL-4 receptor was required for robust tyrosine phosphorylation of the downstream adapter protein, IRS-2, and the robust expression of mRNA and protein of a subset of genes characteristic of alternatively-activated macrophages. The type II IL-4 receptor did not have this robust activity. In addition to the unique ability to bind Jak3, the cytoplasmic domain of human γC contains a putative IRS-2 docking motif and other γC-utilizing cytokines also activate IRS-2. Thus, we hypothesized that the γC cytoplasmic domain provides a dock
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Kurniawan, Dinar Hananto, Sarju Winardi, and Ferian Anggara. "Rock Typing Pada Reservoar Gas Upper Eastern View Coal-Measures (EVCM), Cekungan Bass, Australia." Lembaran publikasi minyak dan gas bumi 56, no. 3 (2023): 149–58. http://dx.doi.org/10.29017/lpmgb.56.3.1100.

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Kesulitan terkadang muncul ketka menentukan permeabilitas, terutama pada interval yang tidak memiliki data batuan inti (core). Pada penelitian ini, digunakan teknik sedimentary rock type (SRT) dan petrophysical rock type (PRT) dengan tujuan untuk mengurai permasalahan tersebut. SRT terdapat 4 rock type, yaitu thoroughly bioturbated sandstone and mudstone, fl aser bedded sandstone, laminated sandstone and mudstone, dan thoroughly bioturbated mudstone. Teknik PRT dilakukan dengan mengkomparasikan metode Hydraulic Flow Unit, Global Hydraulic Element, Winland R35, dan Pore Geometry Structure untuk
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Dissertations / Theses on the topic "Interval FL type 2"

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Aladi, Jabran. "Handling uncertainty : from type-1 to interval type-2 fuzzy sets and systems." Thesis, University of Nottingham, 2016. http://eprints.nottingham.ac.uk/31281/.

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Fuzzy logic systems (FLSs) are widely accepted for their ability to model and handle uncertainty. Type-2 fuzzy sets (T2 FSs) were introduced as an extension of type-1 fuzzy sets (T1 FSs). They are characterised by membership functions (MFs) that are themselves fuzzy for which the membership degrees are expressed as FSs on [0,1], and have been widely accepted as capable of modelling uncertainty with more detail than T1 FSs. Interval type-2 fuzzy sets (IT2 FSs) are a special type of (general) T2 FSs and currently the most widely used, due to their reduction in computational cost. The study of T2
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Eyoh, Imo. "Interval type-2 Atanassov-intuitionistic fuzzy logic for uncertainty modelling." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/51441/.

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This thesis investigates a new paradigm for uncertainty modelling by employing a new class of type-2 fuzzy logic system that utilises fuzzy sets with membership and non-membership functions that are intervals. Fuzzy logic systems, employing type-1 fuzzy sets, that mark a shift from computing with numbers towards computing with words have made remarkable impacts in the field of artificial intelligence. Fuzzy logic systems of type-2, a generalisation of type-1 fuzzy logic systems that utilise type-2 fuzzy sets, have created tremendous advances in uncertainty modelling. The key feature of the typ
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Gu, Ling. "Web Shopping Expert Systems Using New Interval Type-2 Fuzzy Reasoning." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/cs_theses/15.

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Finding a product with high quality and reasonable price online is a difficult task due to the fuzzy nature of data and queries. In order to handle the fuzzy problem, a new type-2 fuzzy reasoning based decision support system, the Web Shopping Expert for online users is proposed. In the Web Shopping Expert, an interval type-2 fuzzy logic system is used and a fuzzy output can be obtained using the up-low limit technique, which offers an opportunity to directly employ all the rules and methods of the type-1 fuzzy sets onto the type-2 fuzzy sets. To achieve the best performance the fuzzy inferenc
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Qiu, Yu. "Statistical Genetic Interval-Valued Type-2 Fuzzy System and its Application." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/cs_theses/22.

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In recent years, the type-2 fuzzy sets theory has been used to model and minimize the effects of uncertainties in rule-base fuzzy logic system. In order to make the type-2 fuzzy logic system reasonable and reliable, a new simple and novel statistical method to decide interval-valued fuzzy membership functions and a new probability type reduced reasoning method for the interval-valued fuzzy logic system are proposed in this thesis. In order to optimize this particle system’s performance, we adopt genetic algorithm (GA) to adjust parameters. The applications for the new system are performed and
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Hamrawi, Hussam. "Type-2 fuzzy alpha-cuts." Thesis, De Montfort University, 2011. http://hdl.handle.net/2086/5137.

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Systems that utilise type-2 fuzzy sets to handle uncertainty have not been implemented in real world applications unlike the astonishing number of applications involving standard fuzzy sets. The main reason behind this is the complex mathematical nature of type-2 fuzzy sets which is the source of two major problems. On one hand, it is difficult to mathematically manipulate type-2 fuzzy sets, and on the other, the computational cost of processing and performing operations using these sets is very high. Most of the current research carried out on type-2 fuzzy logic concentrates on finding mathem
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Chen, Chao. "A novel framework for the implementation and evaluation of type-1 and interval type-2 ANFIS." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/49442/.

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This thesis explores a novel framework for implementing and evaluating type-1 (T1) and interval type-2 (IT2) models of Adaptive Network Fuzzy Inference Systems (ANFIS). A fundamental requirement for this research is the capability to reliably and efficiently implement ANFIS models. In the last ten years, many studies have been devoted to creating IT2 ANFIS models. However, a clear architecture for IT2 ANFIS has not yet been presented. This somehow has been an obstacle to the research of IT2 ANFIS and its application to real-world problems. In this thesis, we introduce an extended ANFIS archite
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Francois, Monique Emily. "Metabolic and cardiovascular benefits of high-intensity interval training in type 2 diabetes." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/62164.

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Gu, Yu. "Early-onset type 2 diabetes: nerve function, impacts of high-intensity interval training, and exercise program acceptability." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/25024.

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Diabetes is recognised as the world’s fastest growing chronic condition. The prevalence of early-onset type 2 diabetes (diagnosed with type 2 diabetes before the age of 45 years) has risen sharply over the past decades, with lack of physical activity and excessive sedentary behaviour being important contributing factors. Early-onset type 2 diabetes is associated with earlier onset of diabetes-related complications, including diabetic peripheral neuropathy and brachial arterial stiffness. Exercise is a well-established, first-line management strategy for type 2 diabetes, but there is limited hi
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Cheng, Martin Chun-Sheng, and pjcheng@ozemail com au. "Dynamical Near Optimal Training for Interval Type-2 Fuzzy Neural Network (T2FNN) with Genetic Algorithm." Griffith University. School of Microelectronic Engineering, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030722.172812.

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Type-2 fuzzy logic system (FLS) cascaded with neural network, called type-2 fuzzy neural network (T2FNN), is presented in this paper to handle uncertainty with dynamical optimal learning. A T2FNN consists of type-2 fuzzy linguistic process as the antecedent part and the two-layer interval neural network as the consequent part. A general T2FNN is computational intensive due to the complexity of type 2 to type 1 reduction. Therefore the interval T2FNN is adopted in this paper to simplify the computational process. The dynamical optimal training algorithm for the two-layer consequent part of inte
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Cheng, Martin Chun-Sheng. "Dynamical Near Optimal Training for Interval Type-2 Fuzzy Neural Network (T2FNN) with Genetic Algorithm." Thesis, Griffith University, 2003. http://hdl.handle.net/10072/366350.

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Type-2 fuzzy logic system (FLS) cascaded with neural network, called type-2 fuzzy neural network (T2FNN), is presented in this paper to handle uncertainty with dynamical optimal learning. A T2FNN consists of type-2 fuzzy linguistic process as the antecedent part and the two-layer interval neural network as the consequent part. A general T2FNN is computational intensive due to the complexity of type 2 to type 1 reduction. Therefore the interval T2FNN is adopted in this paper to simplify the computational process. The dynamical optimal training algorithm for the two-layer consequent part of inte
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Books on the topic "Interval FL type 2"

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Castillo, Oscar, and Patricia Melin. Recent Advances in Interval Type-2 Fuzzy Systems. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28956-9.

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Jafelice, Rosana Sueli da Motta, and Ana Maria Amarillo Bertone. Biological Models via Interval Type-2 Fuzzy Sets. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-64530-4.

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Castillo, Oscar. Recent advances in interval type-2 fuzzy systems. Springer, 2012.

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Li, Hongyi, Ligang Wu, Hak-Keung Lam, and Yabin Gao. Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0593-0.

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Jafelice, Rosana Motta, and Ana Maria Amarillo Bertone. Biological Models Via Interval Type-2 Fuzzy Sets. Springer International Publishing AG, 2021.

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Wu, Ligang, Hongyi Li, Hak-Keung Lam, and Yabin Gao. Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems. Springer London, Limited, 2016.

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Wu, Ligang, Hongyi Li, Hak-Keung Lam, and Yabin Gao. Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems. Springer, 2018.

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Wu, Ligang, Hongyi Li, Hak-Keung Lam, and Yabin Gao. Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems. Springer, 2016.

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Walker, Carol L., Elbert A. Walker, and Harding John. Truth Value Algebra of Type-2 Fuzzy Sets: Order Convolutions of Functions on the Unit Interval. Taylor & Francis Group, 2016.

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Walker, Carol L., Elbert A. Walker, and Harding John. Truth Value Algebra of Type-2 Fuzzy Sets: Order Convolutions of Functions on the Unit Interval. Taylor & Francis Group, 2016.

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Book chapters on the topic "Interval FL type 2"

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Mendez, Gerardo M., and Ma Angeles Hernandez. "Interval Type-2 ANFIS." In Advances in Soft Computing. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74972-1_10.

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Mendel, Jerry M. "Interval Type-2 Fuzzy Systems." In Uncertain Rule-Based Fuzzy Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51370-6_9.

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Mendel, Jerry M. "Interval Type-2 Fuzzy Systems." In Explainable Uncertain Rule-Based Fuzzy Systems. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-35378-9_9.

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Figueroa-García, Juan C., Dusko Kalenatic, and Cesar Amilcar Lopez. "Interval Type-2 Fuzzy Markov Chains: Type Reduction." In Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25944-9_28.

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Kumbasar, Tufan, and Hani Hagras. "Interval Type-2 Fuzzy PID Controllers." In Springer Handbook of Computational Intelligence. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-43505-2_18.

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Figueroa-García, Juan Carlos. "Interval Type-2 Fuzzy Markov Chains." In Advances in Type-2 Fuzzy Sets and Systems. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6666-6_4.

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Wu, Tong, and Xinwang Liu. "Interval Type-2 Fuzzy Decision-Making." In Large-Scale Group Decision-Making with Uncertain and Behavioral Considerations. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8167-8_3.

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Bai, Ying, and Zvi S. Roth. "Interval Type-2 Fuzzy Logic Controllers." In Classical and Modern Controls with Microcontrollers. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01382-0_9.

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Scherer, Rafał, and Janusz T. Starczewski. "Relational Type-2 Interval Fuzzy Systems." In Parallel Processing and Applied Mathematics. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14390-8_37.

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Sharma, Teena, and Nishchal K. Verma. "Adaptive Interval Type-2 Fuzzy Filter." In Artificial Intelligent Algorithms for Image Dehazing and Non-Uniform Illumination Enhancement. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2011-8_6.

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Conference papers on the topic "Interval FL type 2"

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Amartya, Prodipta S., Shaily Kabir, Sagar C. K. Babu, and Mosarrat Jahan. "An Interval Creation Approach to Construct Interval Type-2 Fuzzy Sets." In 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2024. http://dx.doi.org/10.1109/fuzz-ieee60900.2024.10611950.

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Meng, Aiwen, Zuokuang Song, Zhaoyan Zhang, and Peiguang Wang. "Finite Time Stability Analysis of Interval Type-2 Fuzzy Polynomial Positive Systems Based on Interval Type-2 Fuzzy Lyapunov Function." In 2024 China Automation Congress (CAC). IEEE, 2024. https://doi.org/10.1109/cac63892.2024.10865113.

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Azad, Farheen, and Parveen Kumar Shukla. "Optimizing Rainfall Prediction: A Comparative Study of General Type-2 and Interval Type-2 Fuzzy Systems." In 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES). IEEE, 2024. https://doi.org/10.1109/ic3tes62412.2024.10877643.

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Zamri, Nurnadiah, and Lazim Abdullah. "Flood control project selection using an interval type-2 entropy weight with interval type-2 fuzzy TOPSIS." In PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES. AIP Publishing LLC, 2014. http://dx.doi.org/10.1063/1.4882467.

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Chen, Chao, Robert John, Jamie Twycross, and Jonathan M. Garibaldi. "Type-1 and interval type-2 ANFIS: A comparison." In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2017. http://dx.doi.org/10.1109/fuzz-ieee.2017.8015555.

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Khosravi, Abbas, Saeid Nahavandi, Doug Creighton, and Reihaneh Naghavizadeh. "Prediction interval construction using interval type-2 Fuzzy Logic systems." In 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2012. http://dx.doi.org/10.1109/fuzz-ieee.2012.6251272.

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Runkler, Thomas A., Simon Coupland, and Robert John. "Properties of interval type-2 defuzzification operators." In 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2015. http://dx.doi.org/10.1109/fuzz-ieee.2015.7337817.

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Van Nha Pham and Long Thanh Ngo. "Interval type-2 fuzzy co-clustering algorithm." In 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2015. http://dx.doi.org/10.1109/fuzz-ieee.2015.7337960.

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Li, Jie, Longzhi Yang, Xin Fu, Fei Chao, and Yanpeng Qu. "Interval Type-2 TSK+ Fuzzy Inference System." In 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2018. http://dx.doi.org/10.1109/fuzz-ieee.2018.8491448.

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Chang, Chia-Wen, Wen-Rong Xiao, Chih-Ching Hsiao, Song-Shyong Chen, and Chin-Wang Tao. "A simplified interval type-2 fuzzy CMAC." In 2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS). IEEE, 2017. http://dx.doi.org/10.1109/ifsa-scis.2017.8023236.

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Reports on the topic "Interval FL type 2"

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Liang, Qilian, and Haining Shu. Wireless Sensor Network Lifetime Analysis Using Interval Type-2 Fuzzy Logic Systems. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada428428.

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Suksom, Daroonwan, Chaicharn Deerochanawong, Tanaka, Hirofumi, and Witid Mitranun. The comparison effects of aerobic continuous training and aerobic interval training on glycemic control and endothelial function in type 2 diabetes mellitus. Chulalongkorn University, 2013. https://doi.org/10.58837/chula.res.2013.71.

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The objective of this study was to compare the effects of continuous aerobic exercise training (CON) and interval aerobic exercise training (INT) on glycemic control and endothelium-dependent vasodilatation in patients with type 2 diabetes. A total of 43 participants with type 2 diabetes aged 50-70 years were stratified in parallel-group study and randomly allocated to the sedentary control, continuous aerobic training (CON), and interval aerobic training ( INT) groups. Exercise training programs were designed to yield the same energy expenditure/exercise session and included walking on treadm
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Skow, Jason. PR-719-223803-R01 API 1163 Performance Validation Guidelines. Pipeline Research Council International, Inc. (PRCI), 2023. http://dx.doi.org/10.55274/r0000021.

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The main purpose of this project is to provide technical guidance for the practical implementation of the measurement performance validation methodologies outlined in the API RP 1163 2021 Edi- tion (API 1163-2021), which include three levels of validation: Level 1: The vendor specification is used to define measurement performance with little or no field validation. This level typically applies to ILI systems that have been proven in the past on pipelines that have previous ILI baselines for comparison. Level 2: The vendor specification is tested against field-measured anomalies by calculating
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Peterson, Bian, J. Hutchinson, Bijan Gurung, et al. Exploring spatial patterns of overflights at Grand Canyon National Park. National Park Service, 2023. http://dx.doi.org/10.36967/2299660.

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This study explored spatial patterns of overflights at Grand Canyon National Park (GRCA). Overflights were analyzed from February 5th, 2020 to January 9th, 2023 (975 days of data; 95 days of missing data) using Automatic Dependent Surveillance-Broadcast (ADS-B) data. The first phase of analysis focused on all overflights and found a high concentration of overflights above GRCA and definitive travel patterns across the park. The second phase of analysis focused on low-level overflights that fly below 10,000 ft mean sea level (MSL) and fly within 10-miles of the GRCA boundary. Phase 2 figures di
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5

Chou, Roger, Azrah Y. Ahmed, Benjamin J. Morasco, et al. Living Systematic Review on Cannabis and Other Plant-Based Treatments for Chronic Pain: 2023 Update. Agency for Healthcare Research and Quality, 2023. http://dx.doi.org/10.23970/ahrqepccer250update2023.

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Objectives. To update the evidence on benefits and harms of cannabinoids and other plant-based compounds to treat sub-acute and chronic pain in adults and adolescents using a living systematic review approach. Data sources. Ovid® MEDLINE®, PsycINFO®, Embase®, the Cochrane Library, and SCOPUS® databases; and reference lists of included studies were searched to April 23, 2023. Review methods. An updated protocol with expanded inclusion criteria (addition of sub-acute [4 to 12 weeks’ duration] pain and adolescents) was posted on the PROSPERO registry. We grouped studies based on their THC to CBD
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Chou, Roger, Azrah Y. Ahmed, Tracy Dana, et al. Living Systematic Review on Cannabis and Other Plant-Based Treatments for Chronic Pain: 2024 Update. Agency for Healthcare Research and Quality (AHRQ), 2024. https://doi.org/10.23970/ahrqepccer250.2024update.

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Abstract:
Objectives. To update the evidence on benefits and harms of cannabinoids and other plant-based compounds to treat subacute and chronic pain in adults and adolescents using a living systematic review approach. Data sources. Ovid® MEDLINE®, PsycINFO®, Embase®, the Cochrane Library, and SCOPUS® databases, and reference lists of included studies were searched to June 30, 2024. Review methods. We grouped studies based on their tetrahydrocannabinol (THC) to cannabidiol (CBD) ratio and by product type: synthetic, purified (plant-derived product consisting of a single cannabinoid, e.g., dronabinol or
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