Mohammad Rezaeian - Academia.edu (original) (raw)
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Papers by Mohammad Rezaeian
Computing Research Repository, 2006
We consider a pair of correlated processes {Zn} ∞ n=−∞ and {Sn} ∞ n=−∞ , where the former is obse... more We consider a pair of correlated processes {Zn} ∞ n=−∞ and {Sn} ∞ n=−∞ , where the former is observable and the later is hidden. The uncertainty in the estimation of Zn upon its finite past history Z n−1 0 is H(Zn|Z n−1 0 ), and for estimation of Sn upon this observation is H(Sn|Z n−1 0
Archives of Disease in Childhood, 1985
A controlled, randomised trial comparing the results of oral rehydration therapy with those of in... more A controlled, randomised trial comparing the results of oral rehydration therapy with those of intravenous fluid treatment in 470 children with severe gastroenteritis was undertaken. The oral rehydration therapy was divided into two phases--a rehydration phase that used high sodium isotonic fluid at 40 ml/kg per hour and a maintenance phase using low sodium isotonic fluid (sodium 40, potassium 30, bicarbonate 25, chloride 45, and dextrose 130 mmol/l). The results indicate that oral rehydration treatment, used according to this protocol, is successful in treating severe diarrhoea and dehydration, and has considerable advantages over intravenous fluid therapy in reducing complications associated with the treatment of hypernatraemia, in promoting rapid correction of hypokalaemia and acidosis, in decreasing the duration of diarrhoea, and in promoting a greater weight gain at hospital discharge.
Computing Research Repository, 2006
We consider sensor scheduling as the optimal observability problem for partially observable Marko... more We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process is observed by a single sensor which needs to be dynamically adjusted or by a set of sensors which are selected one at a time in a way that maximizes the information acquisition from the process. Similar to conventional POMDP problems, in this model the control action is based on all past measurements; however here this action is not for the control of state process, which is autonomous, but it is for influencing the measurement of that process. This POMDP is a controlled version of the hidden Markov process, and we show that its optimal observability problem can be formulated as an average cost Markov decision process (MDP) scheduling problem. In this problem, a policy is a rule for selecting sensors or adjusting the measuring device based on the measurement history. Given a policy, we can evaluate the estimation entropy for the joint state-measurement processes which inversely measures the observability of state process for that policy. Considering estimation entropy as the cost of a policy, we show that the problem of finding optimal policy is equivalent to an average cost MDP scheduling problem where the cost function is the entropy function over the belief space. This allows the application of the policy iteration algorithm for finding the policy achieving minimum estimation entropy, thus optimum observability.
We consider sensor scheduling as the optimal observability problem for partially observable Marko... more We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process is observed by a single sensor which needs to be dynamically adjusted or by a set of sensors which are selected one at a time in a way that maximizes the information acquisition from the process. Similar to conventional POMDP problems, in this model the control action is based on all past measurements; however here this action is not for the control of state process, which is autonomous, but it is for influencing the measurement of that process. This POMDP is a controlled version of the hidden Markov process, and we show that its optimal observability problem can be formulated as an average cost Markov decision process (MDP) scheduling problem. In this problem, a policy is a rule for selecting sensors or adjusting the measuring device based on the measurement history. Given a policy, we can evaluate the estimation entropy for the joint state-measurement processes which inversely measures the observability of state process for that policy. Considering estimation entropy as the cost of a policy, we show that the problem of finding optimal policy is equivalent to an average cost MDP scheduling problem where the cost function is the entropy function over the belief space. This allows the application of the policy iteration algorithm for finding the policy achieving minimum estimation entropy, thus optimum observability.
International Journal of Engineering Science
In this paper, the performances of two wavelet based damage detection approaches to find the loca... more In this paper, the performances of two wavelet based damage detection approaches to find the location and the size of a crack in a beam subjected to a moving load are compared. In the first approach, designated as 'Fixed Sensor Approach', a sensor is assumed to be located at the mid span of the beam. Thus in this approach, Continuous Wavelet Transform (CWT) coefficient of the time varying deflection attributed to the beam at mid span is used. In the second approach, the sensor is attached to the moving load and CWT coefficient of moving sensor is analyzed. The crack is modeled as a rotational spring which its stiffness is obtained from fracture mechanics, and modal expansion theory is used to find the deflection of cracked beam. The two approaches are compared for several cases of moving load speeds, crack sizes and crack locations, and also several scales of CWT. In the both approaches, wavelet Gaussian 4 is employed. It is shown that, the highest magnitude of CWT coefficient occurs at the exact location of crack and its value depends on damage size. As a result, it can be considered as a damage index. It is found that the moving sensor approach is more effective than the fixed sensor. Thereafter, the effect of beam parameters such as length, width, modulus of elasticity and density and also, crack size and location on the damage index were investigated based on the moving sensor approach. The obtained damage index has two significant features: (a) it has an explicit expression and shows the effects of all parameters clearly, (b) it is not dependent upon the response of the undamaged beam. From the obtained explicit relation for damage index, it is illustrated that the damage index does not depend on material properties of a homogeneous beam. Moreover in a rectangular cross section beam, the damage index is independent of width and has a linear relationship with the height to length ratio. It is shown that using this damage index, small cracks with a depth more than 10% of the beam height can be detected.
Multiprocessors Systems-on-Chip (MPSoCs) are a trend in VLSI design, since they minimize the desi... more Multiprocessors Systems-on-Chip (MPSoCs) are a trend in VLSI design, since they minimize the design crisis represented by the gap between the silicon technology and the actual SoC design capacity. MPSoCs may employ NoCs to integrate several programmable processors, specialized memories, and other specific IPs in a scalable way. Besides communication infrastructure, another important issue in MPSoCs is task mapping. Dynamic task mapping is needed, since the number of tasks running in the MPSoC may exceed the available resources. Most works in literature present static mapping solutions, not appropriate for this scenario. This paper investigates the performance of mapping algorithms in NoC-based heterogeneous MPSoCs, targeting NoC congestion minimization. The use of the proposed congestion-aware heuristics reduces the NoC channel load, congestion, and packet latency.
Computing Research Repository, 2006
We consider a pair of correlated processes {Zn} ∞ n=−∞ and {Sn} ∞ n=−∞ , where the former is obse... more We consider a pair of correlated processes {Zn} ∞ n=−∞ and {Sn} ∞ n=−∞ , where the former is observable and the later is hidden. The uncertainty in the estimation of Zn upon its finite past history Z n−1 0 is H(Zn|Z n−1 0 ), and for estimation of Sn upon this observation is H(Sn|Z n−1 0
Archives of Disease in Childhood, 1985
A controlled, randomised trial comparing the results of oral rehydration therapy with those of in... more A controlled, randomised trial comparing the results of oral rehydration therapy with those of intravenous fluid treatment in 470 children with severe gastroenteritis was undertaken. The oral rehydration therapy was divided into two phases--a rehydration phase that used high sodium isotonic fluid at 40 ml/kg per hour and a maintenance phase using low sodium isotonic fluid (sodium 40, potassium 30, bicarbonate 25, chloride 45, and dextrose 130 mmol/l). The results indicate that oral rehydration treatment, used according to this protocol, is successful in treating severe diarrhoea and dehydration, and has considerable advantages over intravenous fluid therapy in reducing complications associated with the treatment of hypernatraemia, in promoting rapid correction of hypokalaemia and acidosis, in decreasing the duration of diarrhoea, and in promoting a greater weight gain at hospital discharge.
Computing Research Repository, 2006
We consider sensor scheduling as the optimal observability problem for partially observable Marko... more We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process is observed by a single sensor which needs to be dynamically adjusted or by a set of sensors which are selected one at a time in a way that maximizes the information acquisition from the process. Similar to conventional POMDP problems, in this model the control action is based on all past measurements; however here this action is not for the control of state process, which is autonomous, but it is for influencing the measurement of that process. This POMDP is a controlled version of the hidden Markov process, and we show that its optimal observability problem can be formulated as an average cost Markov decision process (MDP) scheduling problem. In this problem, a policy is a rule for selecting sensors or adjusting the measuring device based on the measurement history. Given a policy, we can evaluate the estimation entropy for the joint state-measurement processes which inversely measures the observability of state process for that policy. Considering estimation entropy as the cost of a policy, we show that the problem of finding optimal policy is equivalent to an average cost MDP scheduling problem where the cost function is the entropy function over the belief space. This allows the application of the policy iteration algorithm for finding the policy achieving minimum estimation entropy, thus optimum observability.
We consider sensor scheduling as the optimal observability problem for partially observable Marko... more We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process is observed by a single sensor which needs to be dynamically adjusted or by a set of sensors which are selected one at a time in a way that maximizes the information acquisition from the process. Similar to conventional POMDP problems, in this model the control action is based on all past measurements; however here this action is not for the control of state process, which is autonomous, but it is for influencing the measurement of that process. This POMDP is a controlled version of the hidden Markov process, and we show that its optimal observability problem can be formulated as an average cost Markov decision process (MDP) scheduling problem. In this problem, a policy is a rule for selecting sensors or adjusting the measuring device based on the measurement history. Given a policy, we can evaluate the estimation entropy for the joint state-measurement processes which inversely measures the observability of state process for that policy. Considering estimation entropy as the cost of a policy, we show that the problem of finding optimal policy is equivalent to an average cost MDP scheduling problem where the cost function is the entropy function over the belief space. This allows the application of the policy iteration algorithm for finding the policy achieving minimum estimation entropy, thus optimum observability.
International Journal of Engineering Science
In this paper, the performances of two wavelet based damage detection approaches to find the loca... more In this paper, the performances of two wavelet based damage detection approaches to find the location and the size of a crack in a beam subjected to a moving load are compared. In the first approach, designated as 'Fixed Sensor Approach', a sensor is assumed to be located at the mid span of the beam. Thus in this approach, Continuous Wavelet Transform (CWT) coefficient of the time varying deflection attributed to the beam at mid span is used. In the second approach, the sensor is attached to the moving load and CWT coefficient of moving sensor is analyzed. The crack is modeled as a rotational spring which its stiffness is obtained from fracture mechanics, and modal expansion theory is used to find the deflection of cracked beam. The two approaches are compared for several cases of moving load speeds, crack sizes and crack locations, and also several scales of CWT. In the both approaches, wavelet Gaussian 4 is employed. It is shown that, the highest magnitude of CWT coefficient occurs at the exact location of crack and its value depends on damage size. As a result, it can be considered as a damage index. It is found that the moving sensor approach is more effective than the fixed sensor. Thereafter, the effect of beam parameters such as length, width, modulus of elasticity and density and also, crack size and location on the damage index were investigated based on the moving sensor approach. The obtained damage index has two significant features: (a) it has an explicit expression and shows the effects of all parameters clearly, (b) it is not dependent upon the response of the undamaged beam. From the obtained explicit relation for damage index, it is illustrated that the damage index does not depend on material properties of a homogeneous beam. Moreover in a rectangular cross section beam, the damage index is independent of width and has a linear relationship with the height to length ratio. It is shown that using this damage index, small cracks with a depth more than 10% of the beam height can be detected.
Multiprocessors Systems-on-Chip (MPSoCs) are a trend in VLSI design, since they minimize the desi... more Multiprocessors Systems-on-Chip (MPSoCs) are a trend in VLSI design, since they minimize the design crisis represented by the gap between the silicon technology and the actual SoC design capacity. MPSoCs may employ NoCs to integrate several programmable processors, specialized memories, and other specific IPs in a scalable way. Besides communication infrastructure, another important issue in MPSoCs is task mapping. Dynamic task mapping is needed, since the number of tasks running in the MPSoC may exceed the available resources. Most works in literature present static mapping solutions, not appropriate for this scenario. This paper investigates the performance of mapping algorithms in NoC-based heterogeneous MPSoCs, targeting NoC congestion minimization. The use of the proposed congestion-aware heuristics reduces the NoC channel load, congestion, and packet latency.