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Relevant bibliographies by topics / Combination

Academic literature on the topic 'Combination'

Author: Grafiati

Published: 4 June 2021

Last updated: 30 July 2024

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Dissertations / Theses
Books
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Journal articles on the topic "Combination"

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Kotovskaya, Yu V., N. К. Runikhina, and V. S. Ostapenko. "COMBINATION ANTIHYPERTENSION THERAPY: THE “UNDERRESEARCHED” COMBINATIONS." Russian Journal of Cardiology, no. 5 (January 1, 2017): 132–39. http://dx.doi.org/10.15829/1560-4071-2017-5-132-139.

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Cheng, Lan, and Xuguang Simon Sheng. "Combination of “combinations of p values”." Empirical Economics 53, no. 1 (February 11, 2017): 329–50. http://dx.doi.org/10.1007/s00181-017-1230-9.

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Ali, Naseem, Arzoo Shamoon, Neelesh Yadav, and Tanuj Sharma. "Peptide Combination Generator: a Tool for Generating Peptide Combinations." ACS Omega 5, no. 11 (March 16, 2020): 5781–83. http://dx.doi.org/10.1021/acsomega.9b03848.

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TANOUE, Masahiro. "Good Combination and Bad Combination." JOURNAL OF JAPAN SOCIETY OF HYDROLOGY AND WATER RESOURCES 33, no. 4 (July 5, 2020): 176–77. http://dx.doi.org/10.3178/jjshwr.33.176.

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Burgess, Darren J. "Combination screens for combination therapies." Nature Reviews Genetics 17, no. 6 (April 12, 2016): 313. http://dx.doi.org/10.1038/nrg.2016.52.

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Gilad, Yosi, Gary Gellerman, David M. Lonard, and Bert W. O’Malley. "Drug Combination in Cancer Treatment—From Cocktails to Conjugated Combinations." Cancers 13, no. 4 (February 7, 2021): 669. http://dx.doi.org/10.3390/cancers13040669.

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It is well recognized today that anticancer drugs often are most effective when used in combination. However, the establishment of chemotherapy as key modality in clinical oncology began with sporadic discoveries of chemicals that showed antiproliferative properties and which as a first attempt were used as single agents. In this review we describe the development of chemotherapy from its origins as a single drug treatment with cytotoxic agents to polydrug therapy that includes targeted drugs. We discuss the limitations of the first chemotherapeutic drugs as a motivation for the establishment of combined drug treatment as standard practice in spite of concerns about frequent severe, dose limiting toxicities. Next, we introduce the development of targeted treatment as a concept for advancement within the broader field of small-molecule drug combination therapy in cancer and its accelerating progress that was boosted by recent scientific and technological progresses. Finally, we describe an alternative strategy of drug combinations using drug-conjugates for selective delivery of cytotoxic drugs to tumor cells that potentiates future improvement of drug combinations in cancer treatment. Overall, in this review we outline the development of chemotherapy from a pharmacological perspective, from its early stages to modern concepts of using targeted therapies for combinational treatment.

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Souček, Miroslav, Hana Nechutová, Jan Novák, and Ivan Řiháček. "Combination therapy for hypertension with a focus on fixed combinations." Interní medicína pro praxi 19, no. 2 (April 1, 2017): 58–65. http://dx.doi.org/10.36290/int.2017.011.

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Park, Kinam. "True combination therapy using synergistic drug combination." Journal of Controlled Release 187 (August 2014): 198. http://dx.doi.org/10.1016/j.jconrel.2014.06.034.

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Mahammatov, Abdumannon, Azam Abdurakhimov, and Mingjigit Kholbekov. "Combination Of Music And Physical Education." American Journal of Social Science and Education Innovations 03, no. 03 (March 6, 2021): 6–15. http://dx.doi.org/10.37547/volume03issue03-02.

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S.Shantha, S. Shantha. "Dhana Yoga- The Combination For Prosperity." International Journal of Scientific Research 3, no. 4 (June 1, 2012): 12–14. http://dx.doi.org/10.15373/22778179/apr2014/6.

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Dissertations / Theses on the topic "Combination"

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Hutchings, Claire L. "Combination vaccines." Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.437038.

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Braña, García Irene. "Anticancer targeted agent combination." Doctoral thesis, Universitat Autònoma de Barcelona, 2017. http://hdl.handle.net/10803/457506.

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Las toxicidades limitantes de dosis fuero una neutropenia febril grado 4 (en el brazo de docetaxel) y una neutropenia grado 3 en el brazo de gemcitabina. La combinación de carlumab no tuvo un impacto El cáncer es una enfermedad altamente frecuente y con alta mortalidad. El desarrollo de fármacos contra el cáncer se ha caracterizado por su ineficiencia, con una de las tasas de aprobación de fármacos más baja entre las diferentes especialidades médicas. El principal motivo de esta baja tasa de éxito es la falta de eficacia de los nuevos fármacos que entran al desarrollo clínico. Se han planteado diferentes estrategias para mejorar la eficiencia del desarrollo de fármacos, incluyendo la combinación de fármacos antitumorales, el desarrollo en paralelo de biomarcadores y la optimización del diseño de los ensayos clínicos usando modelización basada en farmacocinética y farmacodinamia Esta tesis es un compendio de dos artículos que evalúan estrategias para optimizar el desarrollo de fármacos mediante la combinación de agentes antitumorales. El primer proyecto es la evaluación preclínica en xenoinjertos derivados de pacientes (PDX) la combinación de inhibidores de PI3K-mTOR con diferentes agentes antitumorales y el segundo es el ensayo clínico fase I evaluando carlumab, un anticuerpo anti CCL2, en combinación con diferentes quimioterapias en pacientes con tumores sólidos avanzados. Proyecto 1: se seleccionaron tres modelos de PDX con deficiencia en PTEN: un PDX de cáncer de mama triple negativo (TNBC), otro de carcinoma de ovario de bajo grado KRAS G12R mutado y otro de adenocarcinoma de pulmón con mutaciones en KRAS G12C y TP53 R181P. En estos modelos se evaluaron dos inhibidores de PI3K-mTOR—PF-04691502 and PF-05212384— en combinación con cisplatino, paclitaxel o dacomitinib. La adición de los inhibidores de PI3K-mTOR a cisplatino o paclitaxel aumentó la actividad de la quimioterapia en los modelos de TNBC y LGSOC; sin embargo, no se objetivó este efecto en modelo de adenocarcinoma de pulmón con mutación de KRAS y TP53. Se objetivó modulación farmacodinámica de pAKT y pS6 en los grupos tratados con inhibidores de PI3K-mTOR. Nuestra investigación sugiere que añadir un inhibidor de PI3K-mTOR puede aumentar el efecto inhibitorio sobre el crecimiento de la quimioterapia en modelos PDX con deficiencia en PTEN. Sin embargo, este beneficio no se observó en el modelo de adenocarcinoma KRAS y TP53 mutado. En el futuro se deberá ahondar en el papel de la pérdida de PTEN en la actividad de estas combinaciones. Proyecto 2: se trata de un ensayo clínico fase Ib evaluando carlumab, un anticuerpo monoclonal contra CCL-2, en combinación con cuatro regímenes de quimioterapia (docetaxel, gemcitabina, carboplatino + paclitaxel y doxorrubicina liposomal pegilda (PLD). En este estudio participaron 53 pacientes en los que o bien los agentes quimioterápicos eran parte del tratamiento convencional o no tenían otras opciones de tratamiento convencional: docetaxel (n=15), gemcitabina (n=12), carboplatino + paclitaxel (n=12) y PLD (n=14). Las toxicidades limitantes de dosis incluyeron una neutropenia febril grado 4 (en el brazo de docetaxel) y una neutropenia grado 3 (en el brazo de gemcitabina). De acuerdo a los brazos de tratamiento, las toxicidades grado 3 o mayores más frecuentes fueron: neutropenia (6/15) y neutropenia febril (4/15) en el brazo de docetaxel, neutropenia (2/12) en el brazo de gemcitabina, neutropenia (4/12), trombocitopenia (4/12) y anemia (2/12) en el brazo de carboplatino-paclitaxel y anemia (3/14) y mucositis (2/14) en el brazo de PLD. Se objetivo una respuesta parcial y 18 estabilizaciones de la enfermedad (38%). La adición de carlumab no tuvo cambios relevantes en el perfil farmacocinético de ninguna de las quimioterapias evaluadas. Los niveles de CCL2 libres descendieron inmediatamente tras el tratamiento con carlumab, pero aumentaron con las administraciones posteriores, sugiriendo que carlumab secuestraba CCL2 de manera temporal. No se objetivaron anticuerpos anti-droga que justificasen dicho efecto. No se objetivaron cambios en las células tumorales circulantes ni en las células circulantes endoteliales. En 3 de 19 pacientes evaluables se objetivó una reducción del 30% en los niveles de N-telopeptido de colágeno tipo I en orina (uNTx). Carlumab es seguro administrado a dosis de 10 o 15 mg/kg en combinación con quimioterapia convencional y tiene buena tolerancia. Sin embargo, no se alcanza una inhibición sostenida de CCL2, ni se han objetivado un número de respuestas significativas.
Cancer is a highly frequent disease associated to high mortality. Drug development in Oncology has shown to be inefficient, having one of the lowest success rate of drugs entering in phase I trials that finally achieves marketed authorization. The main reason for this high failure rate is lack of efficacy. Different strategies have been adopted to improved anti-cancer drug development with the aim of improving patient care. This strategies include the combinatorial use of agents, biomarker co-development, and optimization of clinical trial design with the use of pharmacokinetic-pharmacodynamic modeling. This thesis is presented as compendium of work integrating two projects; the first project preclinically evaluates the combination of two PI3K-mTOR inhibitors and chemotherapy or the pan-HER inhibitor dacomitinib in patient derived xenografts. The second project evaluates de monoclonal antibody anti-CCL2 carlumab in patient derived xenografts. Project 1: Three PDXs were selected for their lack of PTEN expression by immunohistochemistry: a triple-negative breast cancer (TNBC), a KRAS G12R low-grade serous ovarian cancer (LGSOC), and KRAS G12C and TP53 R181P lung adenocarcinoma (LADC). Two dual PI3K-mTOR inhibitors were evaluated—PF-04691502 and PF-05212384—in combination with cisplatin, paclitaxel, or dacomitinib. The addition of PI3K-mTOR inhibitors to cisplatin or paclitaxel increased the activity of chemotherapy in the TNBC and LGSOC models; whereas no added activity was observed in the LADC model. Pharmacodynamic modulation of pS6 and pAKT was observed in the group treated with PI3K-mTOR inhibitor. Our research suggests that the addition of a PI3K-mTOR inhibitor may enhance tumor growth inhibition when compared to chemotherapy alone in PTEN-deficient PDXs. However, this benefit was absent in the KRAS and TP53 mutant LADC model. The role of PTEN deficiency in the antitumor activity of these combinations should be further investigated in the clinic. Project 2 is a first-in-human phase 1b study of carlumab with one of four chemotherapy regimens (docetaxel, gemcitabine, paclitaxel+carboplatin, and pegylated liposomal doxorubicin HCl [PLD]). Fifty-three patients with advanced solid tumors for which ≥1 of these regimens was considered standard of care or for whom no other treatment options existed participated in the study: docetaxel (n=15), gemcitabine (n=12), paclitaxel or carboplatin (n=12), or PLD (n=14). Dose-limiting toxicities included one grade 4 febrile neutropenia (docetaxel arm) and one grade 3 neutropenia (gemcitabine arm). The most common drug-related grade ≥3 adverse events were docetaxel arm—neutropenia (6/15) and febrile neutropenia (4/15); gemcitabine arm—neutropenia (2/12); paclitaxel+carboplatin arm—neutropenia, thrombocytopenia (4/12 each), and anemia (2/12); and PLD arm—anemia (3/14) and stomatitis (2/14). One partial response and 18 (38 %) stable disease responses were observed. Combination treatment with carlumab had no clinically relevant pharmacokinetic effect on any of the chemotherapeutic agents tested. Free CCL2 declined immediately post-treatment with carlumab but increased with further chemotherapy administrations in all arms, suggesting that carlumab could sequester CCL2 for only a short time. Neither antibodies against carlumab nor consistent changes in circulating tumor cells (CTCs) or circulating endothelial cells (CECs) enumeration were observed. Three of 19 evaluable patients showed a 30 % decrease from baseline urinary cross-linked N-telopeptide of type I collagen (uNTx). Carlumab could be safely administered at 10 or 15 mg/kg in combination with standard-of-care chemotherapy and was well-tolerated, although no long-term suppression of serumCCL2 or significant tumor responses were observed.

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Soule, David P. "Forecast Combination with Multiple Models and Expert Correlations." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5809.

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Combining multiple forecasts in order to generate a single, more accurate one is a well-known approach. A simple average of forecasts has been found to be robust despite theoretically better approaches, increasing availability in the number of expert forecasts, and improved computational capabilities. The dominance of a simple average is related to the small sample sizes and to the estimation errors associated with more complex methods. We study the role that expert correlation, multiple experts, and their relative forecasting accuracy have on the weight estimation error distribution. The distributions we find are used to identify the conditions when a decision maker can confidently estimate weights versus using a simple average. We also propose an improved expert weighting approach that is less sensitive to covariance estimation error while providing much of the benefit from a covariance optimal weight. These two improvements create a new heuristic for better forecast aggregation that is simple to use. This heuristic appears new to the literature and is shown to perform better than a simple average in a simulation study and by application to economic forecast data.

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McDonald, Ross Alistair. "Combination in supervised classification problems." Thesis, Imperial College London, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.413670.

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Maktabi, Siavash. "Combination methods for microbial decontamination." Thesis, University of Glasgow, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433618.

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Wilkie, Ormond L. "Modification models of conceptual combination." Thesis, Massachusetts Institute of Technology, 1992. http://hdl.handle.net/1721.1/13100.

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Opel, Cary F. (Cary Francis). "T cell mediated combination immunotherapy." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/107075.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, February 2016.
Cataloged from PDF version of thesis. "September 2015."
Includes bibliographical references (pages 128-131).
Immunotherapy is a broad treatment strategy that harnesses the immune system to fight off a particular condition or disease. Cancer immunotherapy is the specific application of agents designed to interact or stimulate the immune system to fight off tumors. Treatments as diverse as passive antibody therapy, cytokine support, and comprehensive adoptive T cell transfer make up the broad field of immunotherapeutics. Due to the naturally complex interactions inherent in the immune system, there are many options for therapeutic intervention, however, this same complexity makes it extremely difficult to optimize treatment strategies. Because of this, research into developing new immunotherapies, optimizing existing immunotherapies, and designing new combinations of immunotherapies is still critical in the fight against cancer. Although there have been ongoing successes of individual immunotherapies in the clinic, the complexity and interdependence of the immune system suggests that any single therapeutic intervention will be insufficient to reject established malignancies. Increased interest in applying combinations of immunotherapies in the clinic requires more thorough preclinical work to guide the designs of these studies. The work presented in this thesis focuses on developing combinations of immunotherapies to treat preclinical models of cancer, as well as studying the underlying mechanism of tumor control. T cells are potent mediators of cytotoxicity and when properly used in adoptive cell transfer (ACT) protocols, can be highly effective in the treatment of cancer. ACT consists of three steps: 1) harvesting and purifying T cells from the patient, 2) enriching or modifying the T cells to become tumor specific, and 3) reinfusing the T cells along with supporting therapies. Therapies given alongside ACT are often adjuvants designed to enhance T cell response. However, focusing therapies only on enhancing the activity of the transferred T cells may miss out on synergistic effects when other parts of the immune system are simultaneously engaged. To study the effect of adjuvant therapy on ACT, a preclinical murine model was analyzed. Large, established B16F10 tumors were controlled when pmel-1 T cells were given with a course of supportive MSA-IL2 cytokine therapy, however, no cures were observed. When a course of TA99 antibody therapy was added alongside ACT, a high rate of cures was observed. Flow cytometry of both circulating and tumor infiltrating pmel-1 cells showed massive expansion and activation. Additionally, tumor infiltration of neutrophils, NK cells, and DCs were greatly enhanced by adjuvant therapy. DCs in the tumor draining lymph nodes were largely unchanged by the therapies. Engagement of the humoral immune response was also observed in both treatment cases. Surprisingly, antibody therapy did not substantially alter any of the mechanistic observations made in this study, despite its critical role in achieving cures of tumors. While ACT is a highly effective therapy, its clinical applicability is hindered by the complexity of performing T cell transplants and manipulations. A more optimal solution would involve purely injectable treatments that could elicit the same level of tumor specific T cell response in conjunction with potent recruitment of the adaptive immune system against tumors. To achieve this, working in collaboration with the Irvine Lab, combinations of immunotherapy using up to four different components were tested to identify critical factors in the successful rejection of established tumors in preclinical models. The four components of tumor targeting antibody, cytokine support, checkpoint blockade, and cancer vaccine acted synergistically to reject tumors from B16F10, TC-1, and DD-Her2/neu cell lines. The cancer vaccine elicited large numbers of tumor-specific T cells, and acted as a replacement for ACT. By analyzing subset combinations of this full treatment, the roles of each therapeutic component were identified. CD8 T cells and cross-presenting DCs were critical to curing subcutaneous tumors. Cytokine therapy was indispensable for effective tumor control, promoted immune cell infiltration into the tumor, and led to an increase in DCs. In combination with the other therapies, vaccination against a tumor antigen elicited a strong immunological memory response that was able to reject subsequent tumor rechallenge, as well as promote antigen spreading to new epitopes. Successful combinations were demonstrated to be dependent on the recruitment of both the adaptive and innate branches of the immune system. Finally, the efficacy of this combination of treatments was demonstrated by controlling the growth of induced tumors in a BRaf/Pten model. Combination immunotherapy promises a future where synergistic treatments are specifically tailored to individual cancers leading to highly effective responses. However, determining the optimal combination of therapies, the complexity of dosing strategies, and the availability of targeted treatments are all barriers that must be overcome. The analysis presented here will make a significant contribution to the body of knowledge on immunotherapy as it has shown the importance of combining orthogonal immunotherapies in order to get durable cures to established tumors. These results will hopefully encourage combinations of orthogonally acting therapies based on T cells to achieve stronger clinical responses. By determining the necessary requirements for a strong, synergistic response to tumorous growths, more effective combination immunotherapy protocols may be designed in the future.
by Cary F. Opel.
Ph. D.

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Kao, Lie-Jane. "Designs for drug combination experiments /." The Ohio State University, 1994. http://rave.ohiolink.edu/etdc/view?acc_num=osu14878493772931.

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Kiesgen, Alexander [Verfasser]. "Business Combination Agreements. / Alexander Kiesgen." Berlin : Duncker & Humblot, 2021. http://d-nb.info/1238493661/34.

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Sternhell, Robert. "The Combination Problem for Panpsychism." Thesis, The University of Sydney, 2020. https://hdl.handle.net/2123/25041.

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This thesis examines the combination problem for panpsychism and its responses. Panpsychism is the view that fundamental physical entities instantiate phenomenal properties and that our consciousness, in some way, comes from those phenomenal properties. Proponents of panpsychism have argued that it is able to retain key benefits of physicalism over dualism whilst responding to objections to physicalism. However, the view is exposed to one notable problem called the combination problem. Roughly, this problem concerns how the microphenomenal properties of the physical combine to form our consciousness. In this thesis, I examine the combination problem and argue against proposed solutions. In assessing the problem, I separate it into two types of combination problems: subject combination, and quality combination. I identify several strategies available to the panpsychist in response to these issues. I then assess those strategies at length and argue they fail to save constitutive panpsychism. I then address an argument that combination problems exist in all theories of the mind and argue that panpsychism is uniquely disposed to it. I conclude that many of the virtues of panpsychism dispose it to combination problems.

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Books on the topic "Combination"

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MacGregor, David Hutchinson. Industrial combination. London: Routledge, 1997.

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Ellis, Ronald W., ed. Combination Vaccines. Totowa, NJ: Humana Press, 1999. http://dx.doi.org/10.1007/978-1-59259-265-4.

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Goldstein, Allan L., and Enrico Garaci, eds. Combination Therapies. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3340-5.

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Carr, Elias. The combination. Minneapolis: Darby Creek, 2011.

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Boelter, Ashaki. Perfect Combination. S.l: iUniverse, 2007.

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Kitt, Sandra. Perfect combination. London: Harlequin, 1986.

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Vicki, Blizzard, and House of White Birches, eds. Combination crafts. Berne, Ind: House of White Birches, 2004.

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Beecham, Jahnna. The right combination. Toronto: Bantam, 1988.

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Schwartz, Gary K., ed. Combination Cancer Therapy. Totowa, NJ: Humana Press, 2005. http://dx.doi.org/10.1385/1592598641.

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Urish, Kenneth L., and William M. Mihalko, eds. Antimicrobial Combination Devices. 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959: ASTM International, 2020. http://dx.doi.org/10.1520/stp1630-eb.

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Book chapters on the topic "Combination"

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Vose, John R. "Combination Vaccines." In Combination Vaccines, 213–31. Totowa, NJ: Humana Press, 1999. http://dx.doi.org/10.1007/978-1-59259-265-4_10.

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Gooch, Jan W. "Combination." In Encyclopedic Dictionary of Polymers, 158. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_2687.

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Peck, Jamie. "Combination." In Keywords in Radical Geography: Antipode at 50, 50–55. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2019. http://dx.doi.org/10.1002/9781119558071.ch9.

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Saville, John. "Combination." In The New Palgrave Dictionary of Economics, 1823–26. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-349-95189-5_617.

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Saville, John. "Combination." In The New Palgrave Dictionary of Economics, 1–4. London: Palgrave Macmillan UK, 1987. http://dx.doi.org/10.1057/978-1-349-95121-5_617-1.

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Del Giacco, G. S., G. Mantovani, V. Arangino, F. Locci, A. C. Scanu, and G. Pusceddu. "Combination Chemotherapy and Cytokines in the Treatment of Advanced Primary Lung Cancer: Controlled Clinical Trial Three Year Results." In Combination Therapies, 79–85. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3340-5_10.

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Jemma, Cristina, Stefania Vai, Tiziana Musso, Massimo Geuna, Guido Valente, and Guido Forni. "Tumor Immunotherapy with Combined Interleukins Injected Perilymphatically: Experimental and Clinical Findings." In Combination Therapies, 87–96. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3340-5_11.

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Romani, Luigina, Simonetta Mocci, Franca Campanile, Paolo Puccetti, and Francesco Bistoni. "Combination Therapies with Cytokines and Anti-Cytokines in Murine Opportunistic Infections." In Combination Therapies, 97–104. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3340-5_12.

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Lopez-Berestein, Gabriel, and Michael G. Rosenblum. "Treatment and Pharmacokinetics of Liposomal-Amphotericin B Patients with Systemic Fungal Infections." In Combination Therapies, 105–12. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3340-5_13.

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Hersh, Evan M., Carole Y. Funk, and Eskild A. Petersen. "The Potential Role of Immunomodulation in the Treatment of HIV-Infection and Malignant Diseases." In Combination Therapies, 113–22. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3340-5_14.

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Conference papers on the topic "Combination"

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Schwan, Aaron, Josh Willhite, Ladia Jakubec, and Joe Pygott. "Guide Shoe Cart Combination." In Guide Shoe Cart Combination. US DOE, 2021. http://dx.doi.org/10.2172/1825320.

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Jefferson, Christopher, Wendy Moncur, and Karen E. Petrie. "Combination." In the 2011 ACM Symposium. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/1982185.1982383.

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De Smedt, Floris, Kristof Van Beeck, Tinne Tuytelaars, and Toon Goedeme. "The Combinator: Optimal Combination of Multiple Pedestrian Detectors." In 2014 22nd International Conference on Pattern Recognition (ICPR). IEEE, 2014. http://dx.doi.org/10.1109/icpr.2014.606.

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Sen, Mehmet Umut, and Hakan Erdogan. "Nonlinear classifier combination for simple combination types." In 2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU). IEEE, 2011. http://dx.doi.org/10.1109/siu.2011.5929830.

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Staub, Rene, Wayne R. Tompkin, and Jean-Frederic Moser. "Combination gratings." In Photonics West '96, edited by Ivan Cindrich and Sing H. Lee. SPIE, 1996. http://dx.doi.org/10.1117/12.239633.

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Holland, Simon, and Daniel Oppenheim. "Direct combination." In the SIGCHI conference. New York, New York, USA: ACM Press, 1999. http://dx.doi.org/10.1145/302979.303057.

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Feng, Shaokun, and Yanan Zhao. "Feature Combination Tracking." In 2017 10th International Symposium on Computational Intelligence and Design (ISCID). IEEE, 2017. http://dx.doi.org/10.1109/iscid.2017.101.

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8

Lewis, Darrin P., Tony Jebara, and William Stafford Noble. "Nonstationary kernel combination." In the 23rd international conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1143844.1143914.

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Frigó, Erzsébet, and Levente Kocsis. "Online ranking combination." In RecSys '19: Thirteenth ACM Conference on Recommender Systems. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3298689.3346993.

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Delamare, William, Chaklam Silpasuwanchai, Sayan Sarcar, Toshiaki Shiraki, and Xiangshi Ren. "On Gesture Combination." In ISS '19: Interactive Surfaces and Spaces. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3343055.3359706.

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Reports on the topic "Combination"

1

Kuhn, D. R., M. S. Raunak, and R. N. Kacker. Combination Frequency Differencing. National Institute of Standards and Technology, December 2021. http://dx.doi.org/10.6028/nist.cswp.12062021-draft.

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Diebold, Francis, and Jose Lopez. Forecast Evaluation and Combination. Cambridge, MA: National Bureau of Economic Research, March 1996. http://dx.doi.org/10.3386/t0192.

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Socol, Allison Socol, Ary Amerikaner Amerikaner, Betty Chang Chang, Bryon Nichols Nichols, Caitlin Richards Richards, Danielle Adams Adams, Daven McQueen McQueen, et al. The Education Combination Toolkit. Washington, District of Columbia United States: Education Trust, February 2020. http://dx.doi.org/10.15868/socialsector.40738.

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Xiang, Rong. Novel Combination Therapy for Prostate Carcinoma. Fort Belvoir, VA: Defense Technical Information Center, February 2005. http://dx.doi.org/10.21236/ada435053.

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Rennie, Michael W. Mixing Combination and the Acceptance test. Fort Belvoir, VA: Defense Technical Information Center, September 1986. http://dx.doi.org/10.21236/ada196499.

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Xiang, Rong. Novel Combination Therapy for Prostate Carcinoma. Fort Belvoir, VA: Defense Technical Information Center, February 2003. http://dx.doi.org/10.21236/ada417972.

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Xiang, Rong. Novel Combination Therapy for Prostate Carcinoma. Fort Belvoir, VA: Defense Technical Information Center, February 2004. http://dx.doi.org/10.21236/ada423719.

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Ullman, Shimon, and Ronen Basri. Recognition by Linear Combination of Models. Fort Belvoir, VA: Defense Technical Information Center, August 1989. http://dx.doi.org/10.21236/ada224268.

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D'Haultfoeuille, Xavier, Christophe Gaillac, and Arnaud Maurel. Partially Linear Models under Data Combination. Cambridge, MA: National Bureau of Economic Research, April 2022. http://dx.doi.org/10.3386/w29953.

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SENTZ, KARI, and SCOTT FERSON. Combination of Evidence in Dempster-Shafer Theory. Office of Scientific and Technical Information (OSTI), April 2002. http://dx.doi.org/10.2172/800792.

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