This study was conducted during summer and winter of 2018- 2019 in the agricultural research field of Shahid Chamran University. Experimental design was split- plot based on RCBD with three replications. The main plot was the type of agricultural system in three levels including conventional (Conv), organic (Org) and sustainable (Sust) (integrated between Conv and Org) and sup- plot was the type of pre- cultivated crop in sequence with wheat including cultivation of mung bean (M- W), corn (C- W), sesame (S- W) and fallow (F- W). Yield quantity (yield and its component) and quality (grain protein), an estimate of photosynthesis matter transfer index of wheat and soil organic carbon (SOC) after one double-cropping were measured. The result showed that the highest (545.04 g/m2) and the lowest (409.28 g/m2) seed yields were obtained in Conv and Org respectively. In contract, with the changing type of system from Conv to Org, grain protein was increased significantly (from 8.3 to 9.6 %). In addition, the highest (535.47 g/m2) yield of wheat was obtained from M- W double cropping. On the other hands the highest remobilization and current photosynthesis matter were obtained in the organic agricultural system with M- W and conventional with M- W double cropping. The situation of SOC showed that the highest (33.18 mg/g) SOC was obtained in the organic agricultural system with C- W double cropping. The reason for improving SOC in the organic and sustainable agricultural system was application of organic matter (compost and vermicompost) and crop residue management. Totally, from the crop ecology point of view, sustainable agricultural method with a sequence of M- W was the most desirable system.

The aim of this paper is to analyze the undamped second order descriptor systems to show the possibility of transform an undamped second order descriptor system to a pure first order descriptor system, on different ways, while stating some of its benefits. Meanwhile we will introduce pure first order systems and undamped second order systems and indicate that under some assumptions every undamped second order descriptor system can be changed to a pure first order one.

This paper proposes a new hierarchical identification method for fractional-order systems. In this method, a SISO (single input, single output) state space model has been considered in which parameters and also state variables should be estimated. By using a linear transformation and a shift operator, the system will be transformed into a form appropriate for identification of a fractional order system. Then, the unknown parameters will be identified through a recursive least squares method and the states will be estimated using a fractional order Kalman filter. This identification method is based on the hierarchical identification principle that reduces the computational burden and is easy to implement on computer. The promising performance of the proposed method is verified using two stable fractional-order systems.

This paper describes a preliminary investigation into the use of normal form theory for modelling large non-linear dynamic systems. Limit cycle oscillations are determined for simple two-degree-of-freedom double pendulum systems. Such a system is reduced into its centre manifold before computation of normal forms, which are obtained using a period averaging method applicable to non-autonomous systems and more advantageous than the classical methods. A good agreement was observed between the predicted results from the normal form theory and the numerical simulations of the original system.

In this paper, an appropriate fractional-integer integral sliding mode method for the control of fractional-order chaotic systems with perturbations such as uncertainties and external disturbances is addressed. When the upper bound of the perturbations is determined, a sliding mode controller is presented. Also, when the upper bound of the perturbations is unknown, an adaptive sliding mode control is designed. Analysis of the stability of the sliding mode surface is presented using the Lyapunov stability theory. Eventually, the results were carried out for the control of the complex fractional order chaotic T system.

In this paper, a novel conformable fractional order (FO) sliding mode control technique is studied for a class of FO chaotic systems in the presence of uncertainties and disturbances. First, a novel FO nonlinear surface based on conformable FO calculus is proposed to design the FO sliding mode controller. Then, asymptotic stability of the controller is derived by means of the Lyapunov direct method via conformable FO operators. The stability analysis is performed in the sliding and reaching phase. In addition, the realization of reaching phase is guaranteed in finite time and the reaching time is calculated analytically. The proposed control approach has some superiorities. Reduction of the chattering phenomenon, high robustness against the uncertainty and external disturbance, and fast convergence speed are the main advantages of the proposed control scheme. Moreover, it has simple calculations because of using conformable FO operators in the control design. The numerical simulations verify the efficiency of the proposed controller.

This paper presents a fractional-order adaptive controller based on sliding mode control for synchronization of commensurate fractional-order chaotic systems. The adaptive controller is a fractional PID controller, which the coefficients will be tuned according to a proper adaptation mechanism. Fractional PID coefficients are updated using the gradient method when a proper sliding surface is chosen. To illustrate the effectiveness and performance of the controller, the proposed controller is implemented on chaotic fractional-order Genesio Tessi and Coullet systems. Performance of fractional-order PID adaptive controller (PaIlDm) based on synchronization error, and control signal is compared with the conventional adaptive controller (PID) and sliding mode controller (SMC). The simulation results show the efficiency of the proposed controller.

Intelligent agents are considered as significant means towards realizing the semantic web vision. On the Semantic Web, integrating ontologies and rules enables software agents to interoperate between them, however, this leads to a problem, that no studies have focused on effective distributed reasoning for integrating ontologies and rules in multiple knowledge-bases. The methods that have been presented for distributed reasoning not only get a lot of times and memory, but also do not lead to a complete and sound reasoning. In this paper, to solve this problem, we present a distributed reasoning system that deals with the representation of the knowledge-base of order sorted logic. This logic is able to describe the hierarchy of predicates and inheritance of expressions that there are in our natural language. To have a distributed reasoning, our proposed method uses the expansion of rigid and valid-non-rigid properties between knowledge-bases. Furthermore, with considering time and the situation of properties for reasoning, the non-rigid properties have not been ignored, in fact, in their valid time and situation, they are used. With this method, we achieve a complete reasoning and, moreover, the extracted knowledge is completely considered in the knowledge-bases and we have a distributed reasoning with high efficiency and sound without missing any information.

In this paper we have developed a framework for hierarchical production planning in make to order systems. This framework consists of three levels. In the first level we consider minimizing the cost of overtime and tardy jobs and in the second level minimizing major setup costs are considered. In the modeling of third level the objective function is minimizing the cost of minor setups. For this level we have developed a heuristic algorithm to obtain the sequencing and lot sizes of items. Using real data from a cable manufacturing company during a four months period we have evaluated our models. The results show the efficiency of proposed framework.