Constrained Robust Control by a Novel Dynamic Sliding Mode Surface

Kazem Zare,Mokhtar Shasadeghi,Taher Niknam,Mohammad Hassan Asemani,Saleh Mobayen 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.3

In this paper, a sliding mode control (SMC) using a novel dynamic sliding surface is proposed for multi-input multi-output (MIMO) nonlinear systems. The proposed control design provides a robust approach with additional degrees of freedom to satisfy the control input constraint. By decomposing the original system into subsystems, the coupling dynamic terms are modelled in the form of system uncertainties. The dynamic sliding surface is established from inspiring state-space representation of an LTI system with error as input, internal states, and the surface as output. Moreover, the adaptive law is designed to estimate the upper bounds of uncertainties. The performance of the proposed controller is evaluated through a benchmark quadruple-tank process (QTP).

Comparison between Parametric and Semi-parametric Cox Models in Modeling Transition Rates of a Multi-state Model: Application in Patients with Gastric Cancer Undergoing Surgery at the Iran Cancer Institute

Zare, Ali,Mahmoodi, Mahmood,Mohammad, Kazem,Zeraati, Hojjat,Hosseini, Mostafa,Naieni, Kourosh Holakouie Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.11

Background: Research on cancers with a high rate of mortality such as those occurring in the stomach requires using models which can provide a closer examination of disease processes and provide researchers with more accurate data. Various models have been designed based on this issue and the present study aimed at evaluating such models. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at Iran Cancer Institute from 1995 to 1999 were analyzed. Cox-Snell Residuals and Akaike Information Criterion were used to compare parametric and semi-parametric Cox models in modeling transition rates among different states of a multi-state model. R 2.15.1 software was used for all data analyses. Results: Analysis of Cox-Snell Residuals and Akaike Information Criterion for all probable transitions among different states revealed that parametric models represented a better fitness. Log-logistic, Gompertz and Log-normal models were good choices for modeling transition rate for relapse hazard (state $1{\rightarrow}state$ 2), death hazard without a relapse (state $1{\rightarrow}state$ 3) and death hazard with a relapse (state $2{\rightarrow}state$ 3), respectively. Conclusions: Although the semi-parametric Cox model is often used by most cancer researchers in modeling transition rates of multistate models, parametric models in similar situations- as they do not need proportional hazards assumption and consider a specific statistical distribution for time to occurrence of next state in case this assumption is not made - are more credible alternatives.

Assessing Markov and Time Homogeneity Assumptions in Multi-state Models: Application in Patients with Gastric Cancer Undergoing Surgery in the Iran Cancer Institute

Zare, Ali,Mahmoodi, Mahmood,Mohammad, Kazem,Zeraati, Hojjat,Hosseini, Mostafa,Naieni, Kourosh Holakouie Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.1

Background: Multi-state models are appropriate for cancer studies such as gastrectomy which have high mortality statistics. These models can be used to better describe the natural disease process. But reaching that goal requires making assumptions like Markov and homogeneity with time. The present study aims to investigate these hypotheses. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at Iran Cancer Institute from 1995 to 1999 were analyzed. To assess Markov assumption and time homogeneity in modeling transition rates among states of multi-state model, Cox-Snell residuals, Akaikie information criteria and Schoenfeld residuals were used, respectively. Results: The assessment of Markov assumption based on Cox-Snell residuals and Akaikie information criterion showed that Markov assumption was not held just for transition rate of relapse (state 1 ${\rightarrow}$ state 2) and for other transition rates - death hazard without relapse (state 1 ${\rightarrow}$ state 3) and death hazard with relapse (state 2 ${\rightarrow}$ state 3) - this assumption could also be made. Moreover, the assessment of time homogeneity assumption based on Schoenfeld residuals revealed that this assumption - regarding the general test and each of the variables in the model- was held just for relapse (state 1 ${\rightarrow}$ state 2) and death hazard with a relapse (state 2 ${\rightarrow}$ state 3). Conclusions: Most researchers take account of assumptions such as Markov and time homogeneity in modeling transition rates. These assumptions can make the multi-state model simpler but if these assumptions are not made, they will lead to incorrect inferences and improper fitting.

Assessing Misdiagnosis of Relapse in Patients with Gastric Cancer in Iran Cancer Institute Based on a Hidden Markov Multi-state Model

Zare, Ali,Mahmoodi, Mahmood,Mohammad, Kazem,Zeraati, Hojjat,Hosseini, Mostafa,Naieni, Kourosh Holakouie Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.9

Background: Accurate assessment of disease progression requires proper understanding of natural disease process which is often hidden and unobservable. For this purpose, disease status should be clearly detected. But in most diseases it is not possible to detect such status. This study, therefore, aims to present a model which both investigates the unobservable disease process and considers the error probability in diagnosis of disease states. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at the Iran Cancer Institute from 1995 to 1999 were analyzed. Moreover, to estimate and assess the effect of demographic, diagnostic and clinical factors as well as medical and post-surgical variables on transition rates and the probability of misdiagnosis of relapse, a hidden Markov multi-state model was employed. Results: Classification errors of patients in alive state without a relapse ($e_{21}$) and with a relapse ($e_{12}$) were 0.22 (95% CI: 0.04-0.63) and 0.02 (95% CI: 0.00-0.09), respectively. Only variables of age and number of renewed treatments affected misdiagnosis of relapse. In addition, patient age and distant metastasis were among factors affecting the occurrence of relapse (state1${\rightarrow}$state2) while the number of renewed treatments and the type and extent of surgery had a significant effect on death hazard without relapse (state2${\rightarrow}$state3)and death hazard with relapse (state2${\rightarrow}$state3). Conclusions: A hidden Markov multi-state model provides the possibility of estimating classification error between different states of disease. Moreover, based on this model, factors affecting the probability of this error can be identified and researchers can be helped with understanding the mechanisms of classification error.

Survival Analysis of Patients with Gastric Cancer Undergoing Surgery at the Iran Cancer Institute: A Method Based on Multi-State Models

Zare, Ali,Mahmoodi, Mahmood,Mohammad, Kazem,Zeraati, Hojjat,Hosseini, Mostafa,Naieni, Kourosh Holakouie Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.11

Background: Gastric cancer is one of the most common causes of cancer deaths all over the world and the most important reason for its high rate of death is its belated diagnosis at advanced stages of the disease. Events occur in patients which are regarded not only as themselves factors affecting patients' survival but also which can be affected by other factors. This study was designed and implemented aiming to identify these events and to investigate factors affecting their occurrence. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at the Iran Cancer Institute from 1995-1999 were analyzed. The survival time of these patients was determined after surgery and the effects of various factors including demographic, diagnostic and clinical as well as medical, and post-surgical varuiables on the occurrence of death hazard without relapse, hazard of relapse, and death hazard with a relapse were assessed. Results: The median survival time for these patients was 16.3 months and the 5-year survival rate was 21.6%. Based on the results of multi-state model, age and distant metastases affected relapse whereas disease stage, type and extent of surgery, lymph nodes metastases, and number of renewed treatments affected death hazard without relapse. Moreover, age, type and extent of surgery, number of renewed treatments, and liver metastases were identified as factors affecting death hazard in patients with relapse. Conclusions: Most cancer studies pay heed to factors which have effect on death occurrence, but some events occur which should be taken into consideration to better describe the natural process of the disease and provide researchers with more accurate data.

Lack of Altered BECN1 Gene Expression in Iranian Patients with Acute Myeloid Leukemia

Keyvan, Ladan,Bidoki, Seyed Kazem,Abdollahi, Davood Zare,Mansouri, Neda,Hashemi, Mehrdad,Tabatabaei, SA Mortazavi,Fardmanesh, Hediyeh,Meimandi, Mansour,Ayatollahi, Seyed Majid,Movafagh, Abolfazl Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.12

Acute myeloid leukemia (AML), one of the most prevalent leukemia types in adults, demonstrates great heterogeneity in molecular and clinical terms. Hence, there is a necessity to the mechanisms involved in AML generation in order to determine optimal treatment. This cross sectional study aimed to assess changes in BECN1 gene expression in with blood samples from 30 AML patients, compared with samples from 15 healthy persons. RNA was extracted and cDNA was synthesized and Real Time PCR applied to determine BECN1 gene expression. The results showed no significant differences in BECN1 gene expression between patients with AML and normal controls (P > 0.05). It appears that expression of BECN1 does not play a significant role in genesis of AML leukemia.

Relative Survival of Breast Cancer Patients in Iran

Kasaeian, Amir,Mosavi-Jarrahi, Alireza,Abadi, Alireza,Mahmoodi, Mahmood,Mehrabi, Yadollah,Mohammad, Kazem,Eshraghian, Mohammad Reza,Zare, Ali Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.14

Background: The survival rate reflecting prognosis of breast cancer patients is usually estimated based on crude survival methods such as observed and cause-specific. In situations where data are based on population-cancer registries, this method may produce biased estimations. This study therefore aimed to estimate the net survival of breast cancer based on relative survival. Materials and Methods: Data for 622 breast cancer patients diagnosed at the Iran Cancer Institute during 1990-95 and tracked till the end of 2000 were analyzed. For estimation of relative survival, Ederer's second method and SAS (9.1) and STATA (11) software were used. Results: Threeyear relative survivals of 85%, 90%, 80% and 67% were observed for age groups 15-44, 55-59, 60-74, and 75+years-old, respectively. A relative survival of approximately one was observed for two subsequent years for age-group 45-59 years-old. A value greater than one for two subsequent years of follow-up was observed in the age-group 60-74 years-old. Conclusions: Tracking the diagnosis of breast cancer, the relative survival decreases as we go to higher age-groups. It is also perceived that through follow-up, relative survival first decreased and then increased a little. The statistical cure point is acceptable for age group 45-59 years-old while for age-groups 15-44 and 60-74 years old is a sign of low quality data for some follow-up intervals.