Experimental Measurement of Asymmetric Fluctuations of Poloidal Magnetic Field in Damavand Tokomak at Different Plasma Currents

Toroidal and Poloidal magnetic fields have an important effect on the tokomak topology. Damavand Tokomak is a small size tokomak characterized with k?=?1.2, B _t?=?1T, R ₀?=?36?cm, maximum plasma current is about 35?KA with a discharge time of 21?ms. In this experimental work, the variation of poloidal magnetic field on the torodial cross section is measured and analyzed. In order to measure the polodial magnetic field, 18 probes were installed on the edge of tokomak plasma with ?θ?=?18°, while a limiter was installed inside the torus. Plasma current, I _p, induces a polodial magnetic field, B _p, smaller than the torodial magnetic field B _t. Magnetic lines B produced as a combination of B _t and B _p, are localized on the nested toroidal magnetic surfaces. The presence of polodial magnetic field is necessary for particles confinement. Mirnov oscillations are the fluctuations of polodial magnetic field, detected by magnetic probes. Disrupted instability in Tokomak typically starts with mirnov oscillations which appear as fluctuations of polodial magnetic field and is detected by magnetic probes. Minor disruptions inside the plasma can contain principal magnetic islands and their satellites can cause the annihilation of plasma confinement. Production of thin layer of turbulent magnetic field lines cause minor disruption. Magnetic limiter may cause the deformation of symmetric equilibrium configuration and chaotic magnetic islands reveal in plasma occurring in thin region of chaotic field lines close to their separatrix. The width of this chaotic layer in the right side of poloidal profile of Damavand Tokomak is smaller than the width in the left side profile because of Shafranov displacement. Ergodic region in the left side of profile develops a perturbation on the magnetic polodial field lines, B _p, that are greater in magnitude than that in the right side, although the values of B _p on the left side are smaller than that on the right side of the profile. The Left side of profile is close to the principal magnetic axis and the right side is away from Z axis of Tokamak.     

Incorporation of a Regularization Term to Control Negative Correlation in Mixture of Experts

Combining accurate neural networks (NN) in the ensemble with negative error correlation greatly improves the generalization ability. Mixture of experts (ME) is a popular combining method which employs special error function for the simultaneous training of NN experts to produce negatively correlated NN experts. Although ME can produce negatively correlated experts, it does not include a control parameter like negative correlation learning (NCL) method to adjust this parameter explicitly. In this study, an approach is proposed to introduce this advantage of NCL into the training algorithm of ME, i.e., mixture of negatively correlated experts (MNCE). In this proposed method, the capability of a control parameter for NCL is incorporated in the error function of ME, which enables its training algorithm to establish better balance in bias-variance-covariance trade-off and thus improves the generalization ability. The proposed hybrid ensemble method, MNCE, is compared with their constituent methods, ME and NCL, in solving several benchmark problems. The experimental results show that our proposed ensemble method significantly improves the performance over the original ensemble methods.     

New approaches for determining a common set of weights for a voting system

Data Envelopment Analysis (DEA) is one of the methods that have been proposed to determine the weights in a ranked voting system. DEA solves one model corresponding to each candidate and evaluates candidates with their own weights. However, sometimes solving only one model, and evaluating the candidates based on a common set of weights, is preferred. In this paper, some drawbacks of existing models are explained and new approaches for determining a common set of weights are proposed. Numerical examples are utilized to illustrate the content of the paper.     

Role of situational method engineering to improve visual information systems in agile distributed environment

Software product prone to continuous evolution due to increase in the use of technology. Therefore, more stakeholders are involved in software evolution increases the cost and complexity. This required optimization of resources and cost to handle evolution with Global Software Development (GSD) to utilize time zones efficiently. The significance challenge of GSD reports: time zone difference, geographical location, communication delays, knowledge sharing, control among stakeholders and development team. Because of these challenges, the requirements for development in GSD environment are also challenge as compared to on site development. Different requirement engineering methods have been used to improve the requirements analysis to deal with ambiguities and inconsistency in large set of requirements. The customization and tailoring of requirements according to changing project’s situations required to improve project development with reusing existing agile methods during requirement engineering phase. Moreover, complex information systems where heterogeneity is inevitable that implies the involvement of divergent stakeholders and necessitate a comprehensive framework to capture multidimensional viewpoints and fulfill aforementioned issues. Therefore, a situational multi-dimensional agile requirement engineering method has been proposed to support team and stakeholders’ viewpoints. The schema of the proposed method is based on challenges recognized by performing Literature Review. Then proposed method has been evaluated via experimental approach and statistical analysis conducted to validated reliability of data collected. This result is significant approved both practically and statistically that the proposed approach ease to use, implement, trained and increased productivity and performance. Hence, the experimental study for the evaluation of the proposed approach results concluded that, proposed approach is the important multimedia tool for supporting organization and distributed development team for information sharing, collaboration, product development.

     

ACTNET: End-to-End Learning of Feature Activations and Multi-stream Aggregation for Effective Instance Image Retrieval

International Journal of Computer Vision - We propose a novel CNN architecture called ACTNET for robust instance image retrieval from large-scale datasets. Our key innovation is a learnable...     

Identification of pole-like structures from mobile lidar data of complex road environment

Pole-like structures (PLSs) located in road environment are important roadway assets. They play a vital role in road safety inspection and road planning. The use of light detection and ranging (lidar) based mobile mapping technology for mapping of PLSs is an important area of research as it holds the potential for automation. Point cloud data of rural, peri-urban, and urban road environment are used in this study, which pose special challenge in view of the complexity of terrain, unlike well-planned roads, which have been the subject of interest in existing literature for identification of PLSs. A new five-step method is proposed in this article. The first two steps, i.e. ground filtering and voxelization of filtered non-ground points, are used for data size reduction. Next three steps are used to extract PLSs from reduced data. The proposed method was tested on point cloud data of three test sites having different levels of complexities. PLSs including partially occluded pole, tilted pole, pole situated very close to other objects, and vertical pole attached to tilted pole were accurately identified. Average correctness and completeness, respectively of 92.6% and 94.9%, were achieved in three different complex test sites, i.e. urban, peri-urban, and rural sites, respectively. Computation complexity shows that our proposed method delivers fast and computationally efficient solution for identifying the PLSs from volumetric mobile lidar point cloud. Impact of PLSs on road safety and road planning is also addressed for these selected test sites.     

Miniaturized on‐body antenna for small and wearable brain microwave imaging systems

A miniaturized inset‐fed on‐body meandered bowtie antenna designed for brain microwave imaging systems is presented in this article. The proposed on‐body antenna can contribute to the realization of a wearable and portable brain microwave imaging system. The size of 18 × 18 mm² is achieved at a frequency range of 0.75 to 4 GHz by the simultaneous use of self‐complementary structures and meandered lines. The frequency band is a trade‐off between penetration depth and spatial resolution. The proposed antenna performance was studied at different positions on the human head voxel model in terms of several parameters such as reflection coefficient, near‐field directivity, and fidelity factor. In addition, the antenna bandwidth was surveyed on several volunteers using a wearable measurement setup. It has been found that the averages of measured reflection coefficients in different scenarios are in good agreement with the corresponding simulation results, and the antenna shows stable performance under different practical situations. The proposed antenna takes advantage of a small footprint and body matching, which make it an eligible choice for compact, portable, and wearable head microwave imaging systems.     

Computations of Explosive Boiling in Microgravity

Dynamics of the explosive growth of a vapor bubble in microgravity is investigated by direct numerical simulation. A front tracking/finite difference technique is used to solve for the velocity and the temperature field in both phases and to account for inertia, viscosity, and surface deformation. The method is validated by comparison of the numerical results with the available analytical formulations such as the evaporation of a one-dimensional liquid/vapor interface, frequency of oscillations of capillary waves, and other numerical results. Evolution of a three-dimensional vapor nucleus during explosive boiling is followed and a fine scale structure similar to experimental results is observed. Two-dimensional simulations yield a similar qualitative instability growth.     

The Double Edge Sword Based Distributed Executor Service

Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate TPS optimization strategy at backend servers or improper load balancing scheme that cannot quickly recover an overload. Consequently, the performance of software-intensive system is suffered. Thus, in this paper, we propose a new DTPS that follows the collaborative round robin load balancing that has the effect of a double-edge sword. On the one hand, it effectively performs the load balancing (in case of overload situation) among available TPSs by a fast overload recovery procedure that decelerates the load on the overloaded TPSs up to their capacities and shifts the remaining load towards other gracefully running TPSs. And on the other hand, its robust load deceleration technique which is applied to an overloaded TPS sets an appropriate upper bound of thread pool size, because the pool size in each TPS is kept equal to the request rate on it, hence dynamically optimizes TPS. We evaluated the results of the proposed system against state of the art DTPSs by a client-server based simulator and found that our system outperformed by sustaining smaller response times.