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Journal articles on the topic 'Admission control'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 June 2025

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1

Breslau, Lee, Edward W. Knightly, Scott Shenker, Ion Stoica, and Hui Zhang. "Endpoint admission control." ACM SIGCOMM Computer Communication Review 30, no. 4 (October 2000): 57–69. http://dx.doi.org/10.1145/347057.347400.

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2

Kelly, F. P., P. B. Key, and S. Zachary. "Distributed admission control." IEEE Journal on Selected Areas in Communications 18, no. 12 (December 2000): 2617–28. http://dx.doi.org/10.1109/49.898741.

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3

Mortier, R., I. Pratt, C. Clark, and S. Crosby. "Implicit admission control." IEEE Journal on Selected Areas in Communications 18, no. 12 (December 2000): 2629–39. http://dx.doi.org/10.1109/49.898743.

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4

Yang, Jui-Pin. "Stateless Fair Admission Control." SIMULATION 87, no. 3 (September 14, 2010): 253–61. http://dx.doi.org/10.1177/0037549710383610.

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5

Haas, Zygmunt. "Adaptive admission congestion control." ACM SIGCOMM Computer Communication Review 21, no. 5 (October 1991): 58–76. http://dx.doi.org/10.1145/122431.122436.

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6

Salles, R. M., and J. A. Barria. "Proportional Differentiated Admission Control." IEEE Communications Letters 8, no. 5 (May 2004): 320–22. http://dx.doi.org/10.1109/lcomm.2004.827384.

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7

Menth, Michael, Stefan Kopf, Joachim Charzinski, and Karl Schrodi. "Resilient network admission control." Computer Networks 52, no. 14 (October 2008): 2805–15. http://dx.doi.org/10.1016/j.comnet.2008.05.016.

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8

Misic, J., K. L. Chan, and V. B. Misic. "Admission Control in Bluetooth Piconets." IEEE Transactions on Vehicular Technology 53, no. 3 (May 2004): 890–911. http://dx.doi.org/10.1109/tvt.2004.827154.

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9

Örmeci, E. Lerzan, and Apostolos Burnetas. "Admission control with batch arrivals." Operations Research Letters 32, no. 5 (September 2004): 448–54. http://dx.doi.org/10.1016/j.orl.2004.01.001.

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10

Blum, Avrim, Adam Kalai, and Jon Kleinberg. "Admission Control to Minimize Rejections." Internet Mathematics 1, no. 2 (January 2004): 165–76. http://dx.doi.org/10.1080/15427951.2004.10129085.

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J. Tostes, Anna Izabel, Fatima Duarte Figueiredo, and Luis E. Zarate. "Dynamic Fuzzy Cellular Admission Control." IEEE Latin America Transactions 13, no. 2 (February 2015): 510–15. http://dx.doi.org/10.1109/tla.2015.7055572.

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12

Borin, Juliana Freitag, and Nelson Luis Saldanha da Fonseca. "Admission control for WiMAX networks." Wireless Communications and Mobile Computing 14, no. 14 (August 29, 2012): 1409–19. http://dx.doi.org/10.1002/wcm.2272.

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13

Himsworth, Catherine, Priyamvada Paudyal, and Christopher Sargeant. "Risk factors for unplanned hospital admission in a specialist homeless general practice population: case–control study to investigate the relationship with tri-morbidity." British Journal of General Practice 70, no. 695 (May 18, 2020): e406-e411. http://dx.doi.org/10.3399/bjgp20x710141.

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Background‘Tri-morbidity’ describes the complex comorbidity of chronic physical illness, mental illness, and alcohol and/or drug misuse within the homeless population. Poor health outcomes of homeless people are reflected by the higher rate of unplanned hospital admissions compared with the non-homeless population.AimTo identify whether tri-morbidity is a risk factor for unplanned hospital admissions in the homeless population.Design and settingA case–control study of patients who were registered with a specialist homeless GP surgery in Brighton (72 cases and 72 controls).MethodCases were defined as those who had ≥1 overnight hospital admission within a 12-month period. Controls were matched for demographics but with no hospital admission. The primary care record was analysed, and tri-morbidity entered into binomial logistic regression with admission as the dichotomous dependent variable.ResultsThe logistic regression analysis demonstrated that other enduring mental health disorders and/or personality disorder (odds ratio [OR] 3.84, 95% confidence interval [CI] = 1.56 to 9.44), alcohol use (OR 2.92, 95% CI = 1.42 to 5.98), and gastrointestinal disorder (OR 2.90, 95% CI = 1.06 to 7.98) were independent risk factors for admission. Tri-morbidity increased odds of admission by more than four-fold (OR 4.19, 95% CI = 1.90 to 9.27).ConclusionThis study shows that tri-morbidity is an important risk factor for unplanned hospital admissions among the homeless population, and provides an interesting starting point for the development of a risk stratification tool to identify those at risk of unplanned admission in this population.

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Jiang, Ying. "Enforcing Admission Control Using Admission-Time-Ratio and PI Controller." Journal of Computer Research and Development 44, no. 1 (2007): 65. http://dx.doi.org/10.1360/crad20070109.

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15

Frankel, S., A. Farrow, and R. West. "Non-admission or non-invitation? A case-control study of failed admissions." BMJ 299, no. 6699 (September 2, 1989): 598–600. http://dx.doi.org/10.1136/bmj.299.6699.598.

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16

Daabiss, Mohamed, Ahmed H. Mahran, Nezar Al Zughaibi, Abdulhameed F. Basaleem, Khaled AlManea, Mohamed I. Emam, and Ahmed H. Mahmoud. "Pediatric Unplanned Admission in Specialized Tertiary Children Hospital; Case-control study." Saudi Medical Horizons Journal 5, no. 1 (January 4, 2025): 1–8. https://doi.org/10.54293/smhj.v5i1.109.

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Background: Unplanned hospital admissions following surgical procedures are an important quality performance indicator, as they can reflect complications from anesthesia or surgery, in addition to communication issues within the healthcare team. Any patient who undergoes a surgical procedure under general anesthesia but has an unexpected hospital disposition, differing from the pre-operative plan, is considered to have an unplanned admission. These unanticipated admissions can have negative social, economic, and physical consequences for these patients. This study aimed to determine the proportion of unplanned post-operative admissions and to investigate the risk factors that contributed to these unplanned admissions. Methods: The data on unplanned admissions was collected retrospectively by analyzing the medical records of children aged 14 and younger who underwent non-cardiac surgical procedures under general anesthesia at the King Abdullah Specialized Children's Hospital (KASCH) facility from January 2021 to October 2022. Results: Out of 15,178 non-cardiac procedures performed, 119 patients (0.78%) experienced unplanned admission. The leading contributing factors were anesthesia-related in 49 patients (41.2%), surgical-related factors in 35 patients (29.4%), and communication failure between the anesthesia, surgical teams, and bed management in 19 cases (16%). Conclusion: The unplanned admission rate of 0.78% in this facility was lower than the rates reported in the literature. However, these rates may not represent the national practice, and more multi-center studies are needed to gain a more comprehensive understanding of the extent of this problem within the country.

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17

Belenki, Stanislav. "An enforced inter-admission delay performance-driven connection admission control algorithm." ACM SIGCOMM Computer Communication Review 32, no. 2 (April 2002): 31–41. http://dx.doi.org/10.1145/568567.568569.

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18

Chromy, Erik, Matej Kavacky, and Lubomir Dresto. "Admission Control Methods in IMS Networks." International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems 5, no. 3 (September 27, 2016): 142. http://dx.doi.org/10.11601/ijates.v5i3.175.

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In this paper we present admission control methods for IMS network. The task of RACS block is to accept or reject new connection into the network. The main goal of the admission control method is to ensure the Quality of Service not only for new connection but also for already accepted connections. We discuss and compare three admission control algorithms in the paper from the qualitative parameters point of view.

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19

Elayoubi, Salah-Eddine, Tijani Chahed, Mazen Tlais, and Abed-Ellatif Samhat. "Measurement-based admission control in UMTS." Annales des Télécommunications 59, no. 11-12 (November 2004): 1433–45. http://dx.doi.org/10.1007/bf03179729.

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20

Ali, Z., W. Sheikh, E. K. P. Chong, and A. Ghafoor. "A Scalable Call Admission Control Algorithm." IEEE/ACM Transactions on Networking 16, no. 2 (April 2008): 424–34. http://dx.doi.org/10.1109/tnet.2007.900414.

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21

Cetinkaya, C., V. Kanodia, and E. W. Knightly. "Scalable services via egress admission control." IEEE Transactions on Multimedia 3, no. 1 (March 2001): 69–81. http://dx.doi.org/10.1109/6046.909595.

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22

Katoh, Naoki, Toshihide Ibaraki, and Tiko Kameda. "Cautious transaction schedulers with admission control." ACM Transactions on Database Systems 10, no. 2 (June 1985): 205–29. http://dx.doi.org/10.1145/3857.3860.

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23

Weijia Jia, D. Xuan, Wanqing Tu, Lidong Lin, and Wei Zhao. "Distributed admission control for anycast flows." IEEE Transactions on Parallel and Distributed Systems 15, no. 8 (August 2004): 673–86. http://dx.doi.org/10.1109/tpds.2004.34.

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24

Eugster, Patrick, Alex Kesselman, Kirill Kogan, Sergey Nikolenko, and Alexander Sirotkin. "Admission control in shared memory switches." Journal of Scheduling 21, no. 5 (April 13, 2018): 533–43. http://dx.doi.org/10.1007/s10951-018-0564-2.

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25

Altman, E., B. Gaujal, and A. Hordijk. "Admission control in stochastic event graphs." IEEE Transactions on Automatic Control 45, no. 5 (May 2000): 854–67. http://dx.doi.org/10.1109/9.855547.

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26

Perros, H. G., and K. M. Elsayed. "Call admission control schemes: a review." IEEE Communications Magazine 34, no. 11 (1996): 82–91. http://dx.doi.org/10.1109/35.544197.

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27

Chromy, Erik, Marcel Jadron, and Tomas Behul. "Admission Control Methods in IP Networks." Advances in Multimedia 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/918930.

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Telecommunications operators and research institutions pay close attention to the issue of quality of service. The paper deals with methods of admission control in IP networks, which is only one of the subsets of quality of service. There are two large groups of AC methods: parameter-based admission control and measurement-based admission control. The core of the paper is simulation of AC methods and algorithms for topology model in MATLAB. Our simulations are mainly focused on required bandwidth and loss rates. At the end of the paper there are compared results of simulations.

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28

Ooghe, Sven, Adrianus Van Ewijk, and Ramesh Nagarajan. "Resource admission control in access networks." Bell Labs Technical Journal 13, no. 1 (May 15, 2008): 87–104. http://dx.doi.org/10.1002/bltj.20284.

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29

Mi?i?, Jelena, Yat-Kwan Tang, and Vojislav B. Mi?i? "Admission control in TD-CDMA networks." Wireless Communications and Mobile Computing 3, no. 2 (2003): 209–23. http://dx.doi.org/10.1002/wcm.112.

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30

Narendran, K., R. M. Karthik, and Krishna M. Sivalingam. "Iterative power control based admission control for wireless networks." Wireless Networks 22, no. 2 (June 13, 2015): 619–33. http://dx.doi.org/10.1007/s11276-015-0985-1.

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31

Langford, John, Lihong Li, Preston McAfee, and Kishore Papineni. "Cloud control: voluntary admission control for intranet traffic management." Information Systems and e-Business Management 10, no. 3 (January 15, 2011): 295–308. http://dx.doi.org/10.1007/s10257-011-0166-4.

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32

Bruer, Robert A., Marissa Rodway-Norman, and Matthew Large. "Closer to the Truth: Admission to Multiple Psychiatric Facilities and an Inaccurate History of Hospitalization Are Strongly Associated with Inpatient Suicide." Canadian Journal of Psychiatry 63, no. 11 (April 23, 2018): 748–56. http://dx.doi.org/10.1177/0706743718772519.

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Objective: To investigate clinical associations within Canadian psychiatric inpatient suicides. Method: We conducted a case-control study comparing 98 patients who died by suicide while in hospital and 196 similarly admitted living inpatient controls. All were admitted to an Ontario psychiatric bed between 2008 and 2015 inclusive and had data collected at admission using the Resident Assessment Instrument for Mental Health (RAI-MH). The data were analyzed with bivariate tests and logistic regression modeling. Results: The strongest associations with inpatient suicide were prior admission to any Ontario psychiatric bed within the previous 30 days (odds ratio [OR] = 6.13), self-harm assessed at prior admission to a psychiatric hospital other than the hospital of suicide (OR = 6.07), and prior admission to a psychiatric hospital other than the hospital of suicide in the previous year (OR = 5.38). A multivariate model using risk factors assessed at admission had an area under the curve (AUC) of 0.77. The model improved to (AUC) 0.81 using a retrospective search of all Ontario admissions to more accurately detect prior admissions. The risk model was optimized to (AUC) 0.83 when the model also included a “discrepancy” variable to denote records in which admission assessment data and retrospective search data did not agree regarding past month admissions. Conclusions: In addition to the well-known risks of suicide associated with previous suicide attempts and depressive conditions, our data suggest a particular risk of inpatient suicide associated with inpatient care in more than one hospital, particularly when the treating clinicians were unaware of recent previous admissions.

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33

Ursum, Jennie, Mark M. J. Nielen, Jos W. R. Twisk, Mike J. L. Peters, François G. Schellevis, Michael T. Nurmohamed, and Joke C. Korevaar. "Cardiovascular Disease-related Hospital Admissions of Patients with Inflammatory Arthritis." Journal of Rheumatology 42, no. 2 (December 15, 2014): 188–92. http://dx.doi.org/10.3899/jrheum.140476.

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Objective.Patients with inflammatory arthritis (IA) have an increased risk of cardiovascular diseases (CVD), suggesting a high rate of CVD-related hospitalizations, but data on this topic are limited. Our study addressed hospital admissions for CVD in a primary care–based population of patients with IA and controls.Methods.All newly diagnosed patients with IA between 2001 and 2010 were selected from electronic medical records of the Netherlands Institute for Health Services Research Primary Care database, representing a national network of general practices. Two control patients matched for age, sex, and practice were selected for each patient with IA. Hospital admission data for all patients was retrieved from the Dutch Hospital Data.Results.There were 2615 patients with IA and 5555 controls included in our study. CVD-related hospital admissions were observed more frequently among patients with IA as compared with control patients: 48% versus 36% (p < 0.001) in a followup period of 4 years. Patients with IA were more often hospitalized because of ischemic heart disease (OR 1.7, 95% CI 1.2–2.2) and for day-care admission because of cerebrovascular disease (OR 2.2, 95% CI 1.0–4.9).Conclusion.Increased hospital admission rates confirm the higher CVD burden among patients with IA compared with controls, and underscore the need for proper CVD risk management in patients with IA.

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Castells-Aulet, Laura, Miguel Hernández-Viadel, Jesús Jiménez-Martos, Carlos Cañete-Nicolás, Carmen Bellido-Rodríguez, Roman Calabuig-Crespo, Pedro Asensio-Pascual, and Guillem Lera-Calatayud. "Impact of involuntary out-patient commitment on reducing hospital services: 2-year follow-up." BJPsych Bulletin 39, no. 4 (August 2015): 196–99. http://dx.doi.org/10.1192/pb.bp.114.047464.

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Aims and methodTo evaluate whether involuntary out-patient commitment (OPC) in patients with severe mental disorder reduces their use of hospital services. This is a retrospective case-control study comparing a group of patients on OPC (n = 75) and a control group (n = 75) which was composed of patients whose sociodemographic variables and clinical characteristics were similar to those of the OPC group. Each control case is paired with an OPC case, so the control case must have an involuntary admission in the month that the index OPC case admission occurred. Emergency room visits, admissions and average length of hospital stay over a 2-year follow-up after the initiation of OPC were compared.ResultsNo statistically significant evidence was found in the use of mental healthcare services between the two groups. Different reasons for admission found between the groups limit similarity when comparing the two.Clinical implicationsThe findings cast doubt over the effectiveness of this legal measure to reduce emergency visits, the number of admissions and the length of stay in the hospital.

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GIBSON, J. S., J. M. MORTON, R. N. COBBOLD, L. J. FILIPPICH, and D. J. TROTT. "Risk factors for multidrug-resistant Escherichia coli rectal colonization of dogs on admission to a veterinary hospital." Epidemiology and Infection 139, no. 2 (April 15, 2010): 197–205. http://dx.doi.org/10.1017/s0950268810000798.

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SUMMARYThis study aimed to identify risk factors for intestinal colonization with multidrug-resistant (MDR) E. coli in dogs on admission to a veterinary teaching hospital. Exposures to potential risk factors, including prior treatments, hospitalizations and interventions during the 42 days prior to admission were assessed for 82 case admissions and 82 time-matched controls in a retrospective prevalence-based case-control study of 20 months duration. On multivariable analyses, risk of MDR E. coli colonization on admission was increased with prior hospitalization for 4–7 days and >7 days relative to shorter periods, and in dogs that had prior diagnostic imaging techniques. Univariable analyses indicated that risk was increased following prior treatment with several antimicrobial agents. However, on multivariable analysis, administration of fluoroquinolones was associated with increased risk but risk did not appear to increase following administration of other antimicrobials. These results can inform management of canine patients and infection control procedures to mitigate the risk of clinical disease due to MDR bacteria in hospitalized dogs.

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36

Zimmermann, Judith, Alina von Davier, and Hans Rudolf Heinimann. "Adaptive admissions process for effective and fair graduate admission." International Journal of Educational Management 31, no. 4 (May 8, 2017): 540–58. http://dx.doi.org/10.1108/ijem-06-2015-0080.

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Purpose Graduate admission has become a critical process for quality assurance in tertiary education. Hitherto, most research has investigated the validity of admissions instruments. However, surprisingly little work has been conducted on the overall organization of admission, which often remains “informal, ad hoc, and lacking in continuity.” The purpose of this paper is to investigate how to systematically design an admissions process for effectiveness, fairness, and the ability to continually improve, and determine how to condense and analyze the massive amount of data available from student records to obtain high-value feedback for admissions decision making. Design/methodology/approach An admissions process was systematically designed based on results from process management theory. Tenets of decision theory were applied to the organization of decision making and validity theory was utilized for validating admissions instruments. Performance of the implemented process was evaluated via student records covering a seven-year period. Findings The authors have designed a four-phase admissions process that ensures high quality through screening, scoping, selection, and evaluation/feedback. The last phase introduces closed-loop control and facilitates stabilization and continual improvement. Additionally, the authors have established a three-stage decision-making hierarchy that promotes consistency and equal treatment in admissions. The evaluations of undergraduate achievements and GRE® General Test scores indicate that both are valid admissions instruments in the European context. Finally, the evaluation of the implemented process provides evidence that decision making has effectively improved over the years and has become more consistent. Originality/value The systematic design of the admissions process presented generalizes well and is a significant contribution to the organization of decentralized graduate admission.

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37

Carter, Gregory L., Kerrie Clover, Ian M. Whyte, Andrew H. Dawson, and Catherine D'Este. "Postcards from the EDge: 5-year outcomes of a randomised controlled trial for hospital-treated self-poisoning." British Journal of Psychiatry 202, no. 5 (May 2013): 372–80. http://dx.doi.org/10.1192/bjp.bp.112.112664.

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BackgroundRepetition of hospital-treated self-poisoning and admission to psychiatric hospital are both common in individuals who self-poison.AimsTo evaluate efficacy of postcard intervention after 5 years.MethodA randomised controlled trial of individuals who have self-poisoned: postcard intervention (eight in 12 months) plus treatment as usualv.treatment as usual. Our primary outcomes were self-poisoning admissions and psychiatric admissions (proportions and event rates).ResultsThere was no difference between groups for any repeat-episode self-poisoning admission (intervention group: 24.9%, 95% CI 20.6-29.5; control group: 27.2%, 95% CI 22.8-31.8) but there was a significant reduction in event rates (incidence risk ratio (IRR)=0.54, 95% CI 0.37-0.81), saving 306 bed days. There was no difference for any psychiatric admission (intervention group: 38.1%, 95% CI 33.1-43.2; control group: 35.5%, 95% CI 30.8-40.5) but there was a significant reduction in event rates (IRR=0.66, 95% CI 0.47-0.91), saving 2565 bed days.ConclusionsA postcard intervention halved self-poisoning events and reduced psychiatric admissions by a third after 5 years. Substantial savings occurred in general hospital and psychiatric hospital bed days.

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38

Park, Sang-Min, and Marty Humphrey. "Predictable High-Performance Computing Using Feedback Control and Admission Control." IEEE Transactions on Parallel and Distributed Systems 22, no. 3 (March 2011): 396–411. http://dx.doi.org/10.1109/tpds.2010.100.

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39

Moore, Andrew W. "An implementation‐based comparison of Measurement‐Based Admission Control algorithms." Journal of High Speed Networks 13, no. 2 (January 2004): 87–102. https://doi.org/10.3233/hsn-2004-237.

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In this paper we present an implementation‐based comparison of Measurement‐based Admission Control algorithms. Through the use of a special purpose environment, a performance and behaviour comparison is made. The results of this paper illustrate the independence of traffic from admission control behaviour in the homogeneous traffic environment. While illustrating the impact the admission decision will make upon heterogenous traffic systems. These results highlight the importance of estimators being robust to statistical variation in measurements and offering calibrated controls. While based upon a comparison of measurement‐based admission control algorithms — these conclusions are applicable to any application of measurement‐based estimation.

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40

Bajracharya, Rojeena, Rakesh Shrestha, and Sung Kim. "An Admission Control Mechanism for 5G LWA." Sustainability 10, no. 6 (June 13, 2018): 1999. http://dx.doi.org/10.3390/su10061999.

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41

S., Ahmed, Nawal A., and Nada M. "Admission Control Algorithm for MPLS-TE Networks." International Journal of Computer Applications 160, no. 5 (February 15, 2017): 11–16. http://dx.doi.org/10.5120/ijca2017913049.

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42

Sudvarg, Marion, Chris Gill, and Sanjoy Baruah. "Linear-time admission control for elastic scheduling." Real-Time Systems 57, no. 4 (August 2, 2021): 485–90. http://dx.doi.org/10.1007/s11241-021-09373-4.

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MURILLO-P^|^Eacute;REZ, Rub^ ^eacute;n Pavel, Carmen Beatriz RODR^|^Iacute;GUEZ-ESTRELLO, and Felipe CRUZ-P^|^Eacute;REZ. "Call Admission Control with Fractional Buffer Size." IEICE Transactions on Communications E95.B, no. 9 (2012): 2972–75. http://dx.doi.org/10.1587/transcom.e95.b.2972.

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44

MENG, Man, and Yan-bing LIU. "Mixed-mode-based admission control in WLAN." Journal of Computer Applications 30, no. 6 (June 22, 2010): 1451–54. http://dx.doi.org/10.3724/sp.j.1087.2010.01451.

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45

Seung Yeob Nam, Sunggon Kim, and Dan Keun Sung. "Measurement-Based Admission Control at Edge Routers." IEEE/ACM Transactions on Networking 16, no. 2 (April 2008): 410–23. http://dx.doi.org/10.1109/tnet.2007.900403.

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46

Deyun Gao and Jianfei Cai. "Admission control in IEEE 802.11e wireless LANs." IEEE Network 19, no. 4 (July 2005): 6–13. http://dx.doi.org/10.1109/mnet.2005.1470677.

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47

Hordijk, Arie, and Flos Spieksma. "Constrained admission control to a queueing system." Advances in Applied Probability 21, no. 2 (June 1989): 409–31. http://dx.doi.org/10.2307/1427167.

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We consider an exponential queue with arrival and service rates depending on the number of jobs present in the queue. The queueing system is controlled by restricting arrivals. Typically, a good policy should provide a proper balance between throughput and congestion. A mathematical model for computing such a policy is a Markov decision chain with rewards and a constrained cost function. We give general conditions on the reward and cost function which guarantee the existence of an optimal threshold or thinning policy. An efficient algorithm for computing an optimal policy is constructed.

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48

Han, Bin, Di Feng, and Hans D. Schotten. "A Markov Model of Slice Admission Control." IEEE Networking Letters 1, no. 1 (March 2019): 2–5. http://dx.doi.org/10.1109/lnet.2018.2873978.

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49

Saito, H., and K. Shiomoto. "Dynamic call admission control in ATM networks." IEEE Journal on Selected Areas in Communications 9, no. 7 (1991): 982–89. http://dx.doi.org/10.1109/49.103546.

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50

Widjaja, I. "Performance analysis of burst admission-control protocols." IEE Proceedings - Communications 142, no. 1 (1995): 7. http://dx.doi.org/10.1049/ip-com:19951551.

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