scholarly journals Optimization of PSWAN in terms of cost and bandwidth

2018 ◽  
Vol 1 (1) ◽  
pp. 42-47
Author(s):  
Aadil Gani Ganie
Keyword(s):  
Cost Effective ◽  
Simulation Software ◽  
Bandwidth Utilization ◽  
Network Cost ◽  
Proposed Model ◽  
Broadband Network ◽  
Bottle Neck ◽  
Access Policies ◽  
Positive Results ◽  
Vast Area

PSWAN is an internetworking project undertaken by Govt. of India at Pondicherry. It covers a vast area, under it there are various state headquarters and district headquarters. Approximately 3000 systems are using its internet services. Since the number of systems are more and the bandwidth required is less so optimization was needed. Optimization was required without hardware modifications, so we defined some of the parameters through which we can achieve the optimization of this network, these parameters are 1. Type of protocol 2. Type of Topology 3. Access policies 4. Load balancing 5. Traffic bottle neck 6. Bandwidth utilization. To make the network cost effective, some small networks were moved to broadband network so that bandwidth usage can be mitigated and consequently network will get optimized. Since this project (PSWAN) is using the CISCO devices only so it was easy to simulate the network, we used OPNET simulator as it is precise than other simulators. First the operational network was simulated and then the proposed one, proposed model showed evident positive results. The simulation tool used is Opnet. OPNET is extensive and powerful simulation software with wide variety of capabilities. It enables the possibility to simulate entire heterogeneous networks with various protocols

scholarly journals Improved Modeling of a Multi-Level Inverter for TACS to Reduce Computational Time and Improve Accuracy

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 849
Author(s):  
Sung-An Kim
Keyword(s):  
Mechanical Model ◽  
Simulation Software ◽  
Computational Time ◽  
Electrical Model ◽  
Conventional Model ◽  
Switching Operation ◽  
Air Compressor ◽  
Power Semiconductors ◽  
Proposed Model ◽  
Multi Level

A modeling of a turbo air compressor system (TACS), with a multi-level inverter for driving variable speed, combining an electrical model of an electric motor drive system (EMDS) and a mechanical model of a turbo air compressor, is essential to accurately analyze dynamics characteristics. Compared to the mechanical model, the electrical model has a short sampling time due to the high frequency switching operation of the numerous power semiconductors inside the multi-level inverter. This causes the problem of increased computational time for dynamic characteristics analysis of TACS. To solve this problem, the conventional model of the multi-level inverter has been proposed to simplify the switching operation of the power semiconductors, however it has low accuracy because it does not consider pulse width modulation (PWM) operation. Therefore, this paper proposes an improved modeling of the multi-level inverter for TACS to reduce computational time and improve the accuracy of electrical and mechanical responses. In order to verify the reduced computational time of the proposed model, the conventional model using the simplified model is compared and analyzed using an electronic circuit simulation software PSIM. Then, the improved accuracy of the proposed model is verified by comparison with the experimental results.

scholarly journals Graph contextualized attention network for predicting synthetic lethality in human cancers

2021 ◽  
Author(s):  
Yahui Long ◽  
Min Wu ◽  
Yong Liu ◽  
Jie Zheng ◽  
Chee Keong Kwoh ◽  
...  
Keyword(s):  
Synthetic Lethality ◽  
Critical Role ◽  
Design Feature ◽  
Cost Effective ◽  
Attention Network ◽  
New Genes ◽  
Lab Experiments ◽  
Proposed Model ◽  
Multiple Feature ◽  
Wet Lab

Abstract Motivation Synthetic Lethality (SL) plays an increasingly critical role in the targeted anticancer therapeutics. In addition, identifying SL interactions can create opportunities to selectively kill cancer cells without harming normal cells. Given the high cost of wet-lab experiments, in silico prediction of SL interactions as an alternative can be a rapid and cost-effective way to guide the experimental screening of candidate SL pairs. Several matrix factorization-based methods have recently been proposed for human SL prediction. However, they are limited in capturing the dependencies of neighbors. In addition, it is also highly challenging to make accurate predictions for new genes without any known SL partners. Results In this work, we propose a novel graph contextualized attention network named GCATSL to learn gene representations for SL prediction. First, we leverage different data sources to construct multiple feature graphs for genes, which serve as the feature inputs for our GCATSL method. Second, for each feature graph, we design node-level attention mechanism to effectively capture the importance of local and global neighbors and learn local and global representations for the nodes, respectively. We further exploit multi-layer perceptron (MLP) to aggregate the original features with the local and global representations and then derive the feature-specific representations. Third, to derive the final representations, we design feature-level attention to integrate feature-specific representations by taking the importance of different feature graphs into account. Extensive experimental results on three datasets under different settings demonstrated that our GCATSL model outperforms 14 state-of-the-art methods consistently. In addition, case studies further validated the effectiveness of our proposed model in identifying novel SL pairs. Availability Python codes and dataset are freely available on GitHub (https://github.com/longyahui/GCATSL) and Zenodo (https://zenodo.org/record/4522679) under the MIT license.

scholarly journals Cost-Effectiveness of Investigations for Invasive Bladder Cancer

1987 ◽  
Vol 80 (3) ◽  
pp. 143-144 ◽  
Author(s):  
M T Hunt ◽  
C R J Woodhouse
Keyword(s):  
Transitional Cell ◽  
Clinical Signs ◽  
Cost Effective ◽  
Intravenous Urography ◽  
Liver Scan ◽  
Chest X Ray ◽  
Carcinoma Of The Bladder ◽  
Disseminated Disease ◽  
Positive Results ◽  
Diagnostic Investigations

The results of diagnostic and staging investigations in consecutive cases of invasive transitional cell carcinoma of the bladder are reviewed. Urine culture, urine cytology and intravenous urography had positive results in a high percentage of cases. As diagnostic investigations they are cost-effective but certainly do not remove the obligation to perform cystoscopy and examination under anaesthetic. Isotopic bone scan and liver scan showed metastases in 4 and one cases respectively and only when there were clinical signs of disseminated disease. Chest X-ray showed metastases in one case. These investigations are not cost-effective. Lymphangiography was positive in 12 of the 94 cases and, although expensive (£70), is still a staging investigation of value in planning treatment.

An E2GPGP-GASA-Based Multi-Agent Job Shop Scheduling System

2012 ◽  
Vol 505 ◽  
pp. 65-74
Author(s):  
Lin Lin Lu ◽  
Xin Ma ◽  
Ya Xuan Wang
Keyword(s):  
Large Scale ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Simulation Software ◽  
Prototype System ◽  
Shop Scheduling ◽  
Model Combining ◽  
Proposed Model ◽  
Multi Agent ◽  
Global Planning

In this paper, a job shop scheduling model combining MAS (Multi-Agent System) with GASA (Simulated Annealing-Genetic Algorithm) is presented. The proposed model is based on the E2GPGP (extended extended generalized partial global planning) mechanism and utilizes the advantages of static intelligence algorithms with dynamic MAS. A scheduling process from ‘initialized macro-scheduling’ to ‘repeated micro-scheduling’ is designed for large-scale complex problems to enable to implement an effective and widely applicable prototype system for the job shop scheduling problem (JSSP). Under a set of theoretic strategies in the GPGP which is summarized in detail, E2GPGP is also proposed further. The GPGP-cooperation-mechanism is simulated by using simulation software DECAF for the JSSP. The results show that the proposed model based on the E2GPGP-GASA not only improves the effectiveness, but also reduces the resource cost.

scholarly journals SIMULATING THE SENSITIVITY OF UNDERGROUND VENTILATION NETWORKS TO FLUCTUATING AMBIENT CONDITIONS

2021 ◽  
Vol 32 (2) ◽  
pp. 45-51
Author(s):  
Ryan Fair ◽  
Jean van Laar ◽  
Kristy Nell ◽  
Diaan Nell ◽  
Edward Mathews
Keyword(s):  
Cost Effective ◽  
Mine Ventilation ◽  
Simulation Software ◽  
Underground Mines ◽  
Ambient Conditions ◽  
Mining Operations ◽  
Industrial Systems ◽  
Effective Ventilation ◽  
Cost Implications ◽  
Ventilation Systems

The weather directly impacts ventilation systems, especially large industrial systems found in underground mines. Underground mine ventilation systems have high cost implications that add to the financial strains and uncertainties of future mining operations. In addition, the dynamic nature of underground ventilation systems makes the accurate prediction of underground conditions extremely difficult using traditional steady-state methods. Therefore, improved prediction methods of dynamic underground environmental conditions are needed to ensure cost-effective ventilation systems. This paper investigates simulating the sensitivity that underground ventilation systems have to fluctuating ambient conditions. Simulation software was applied to a case study on a gold mine in South Africa. The results showed that transient software can now be applied to entire mine ventilation systems, and can improve predicting the underground environment because of fluctuating ambient conditions.

scholarly journals METHODOLOGICAL APPROACH TO CREATING A MODEL OF COST-EFFECTIVE MECHANISM FOR MANAGING INNOVATIVE ACTIVITY OF HOTEL ORGANIZATIONS

2021 ◽  
pp. 68-76
Author(s):  
T. P. Levchenko ◽  
M. B. Moldazhanov ◽  
V. V. Purichi ◽  
I. V. Strishkina
Keyword(s):  
Innovation Management ◽  
Methodological Approach ◽  
Cost Effective ◽  
Innovative Activity ◽  
Effective Management ◽  
Management Mechanism ◽  
Effective Mechanism ◽  
Scenario Modeling ◽  
Proposed Model ◽  
Activity Management

The transition of hotel organizations to a qualitatively new level of development can be ensured by the formation and use of a cost-effective innovation management mechanism. The article attempts to create a model of a cost-effective management mechanism that could take into account the multifaceted relationships of indicators and indicators of innovative activity. The operation of this mechanism implies the use of indicative control tools, as well as factor and scenario modeling. The author considers the mechanism from the perspective of implementing five interconnected blocks: subjects, goals and tasks, objects, processes and resulting effects. The content of the resulting effects of the implementation of innovative processes based on the calculation of integral indicators of innovative activity and its elements. Based on the proposed model of a cost-effective mechanism for managing the innovative activity of hotel organizations, an analysis of trends in the level of innovative activity was carried out at using the example of three hotel in Sochi, their graphical interpretation is presented. As part of the presented model, scenario modeling of innovative activity management was carried out as one of its tools, a graph of the ratio of indicators of innovative activity of hotel organizations in Sochi was built.

Modeling of a Wind Turbine Rotor Blade System

2017 ◽  
Vol 139 (5) ◽  
Author(s):  
Dayuan Ju ◽  
Qiao Sun
Keyword(s):  
Wind Turbine ◽  
Rotor Blade ◽  
Simulation Software ◽  
Wind Flow ◽  
Coupling Effects ◽  
Horizontal Axis Wind Turbine ◽  
Blade Vibration ◽  
Proposed Model ◽  
Blade System ◽  
Coupling Terms

In wind turbine blade modeling, the coupling between rotor rotational motion and blade vibration has not been thoroughly investigated. The inclusion of the coupling terms in the wind turbine dynamics equations helps us understand the phenomenon of rotor oscillation due to blade vibration and possibly diagnose faults. In this study, a dynamics model of a rotor-blade system for a horizontal axis wind turbine (HAWT), which describes the coupling terms between the blade elastic movement and rotor gross rotation, is developed. The model is developed by using Lagrange's approach and the finite-element method has been adopted to discretize the blade. This model captures two-way interactions between aerodynamic wind flow and structural response. On the aerodynamic side, both steady and unsteady wind flow conditions are considered. On the structural side, blades are considered to deflect in both flap and edge directions while the rotor is treated as a rigid body. The proposed model is cross-validated against a model developed in the simulation software fatigue, aerodynamics, structure, and turbulence (fast). The coupling effects are excluded during the comparison since fast does not include these terms. Once verified, we added coupling terms to our model to investigate the effects of blade vibration on rotor movement, which has direct influence on the generator behavior. It is illustrated that the inclusion of coupling effects can increase the sensitivity of blade fault detection methods. The proposed model can be used to investigate the effects of different terms as well as analyze fluid–structure interaction.

An analytical model for predicting noise radiated by switch reluctance electric motors

2021 ◽  
Vol 263 (2) ◽  
pp. 4100-4110
Author(s):  
Murat Inalpolat ◽  
Bahadir Sarikaya ◽  
Enes Timur Ozdemir ◽  
Hyun Ku Lee
Keyword(s):  
Magnetic Energy ◽  
Cost Effective ◽  
Torque Ripple ◽  
Air Gap ◽  
Sound Power ◽  
Electromagnetic Forces ◽  
Phase Switching ◽  
Proposed Model ◽  
Torque Ripples

Switch reluctance motors (SRM) have become a prominent alternative for electric vehicles in recent years due to their simple, high power density architecture and cost-effective manufacturability. Despite its potential, NVH problems have been one of the biggest challenges for SRM's implementation. Vibration and noise generated by the SRM are mainly caused by phase switching related torque ripple, unbalanced electromagnetic forces from air gap variations and lamination problems. Our proposed model is an analytical noise radiation prediction model which relates geometrical, material and electrical design inputs to radiated sound power. The electromagnetic part of the model is nonlinear with saturation and provides back-emf and flux linkage by receiving design inputs. The computed magnetic energy, radial and tangential rotor forces are utilized as excitation sources to a continuous shell dynamic model to obtain the steady-state vibration response. Finally, surface velocities obtained from the shell model are used to calculate sound power. Utilizing a shell structure provides axial, radial and tangential information on the casing by considering the effect of magneto-restrictive forces of laminations, torque ripples and unbalanced electromagnetic forces. The effect of air gap, lamination error, and stator and rotor geometry on sound radiation are studied through an example case study.

scholarly journals Coupling Quasi-Two-Dimensional Friction Model and Discrete Vapor Cavity Model for Simulation of Transient Cavitating Flows in Pipeline Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Qiang Sun ◽  
Yuebin Wu ◽  
Ying Xu ◽  
Liang Chen ◽  
Tae Uk Jang
Keyword(s):  
Cost Effective ◽  
Friction Model ◽  
Experimental Results ◽  
Complex Nature ◽  
Two Dimensional ◽  
Cavity Model ◽  
Cavitating Flows ◽  
Vapor Cavity ◽  
Proposed Model ◽  
Pipeline Systems

Accurate simulation of cavitating flows in pipeline systems is important for cost-effective surge protection. However, this is still a challenge due to the complex nature of the problem. This paper presents a numerical model that combines the discrete vapor cavity model (DVCM) with the quasi-two-dimensional (quasi-2D) friction model to simulate transient cavitating flows in pipeline systems. The proposed model is solved by the method of characteristics (MOC), and the performance is investigated through a numerical case study formulated based on a laboratory pipeline reported in the literature. The results obtained by the proposed model are compared with those calculated by the classic one-dimensional (1D) friction model with the DVCM and the corresponding experimental results provided by the literature, respectively. The comparison shows that the pressure peak, waveform, and phase of pressure pulsations predicted by the proposed model are closer to the experimental results than those obtained by the classic 1D model. This demonstrates that the proposed model that combines the quasi-2D friction model with the DVCM has provided a solution to more accurately simulate transient cavitating flows in pipeline systems.

Clustering-Based Transductive Semi-Supervised Learning for Learning-to-Rank

2019 ◽  
Vol 33 (12) ◽  
pp. 1951007 ◽  
Author(s):  
Ashwini Rahangdale ◽  
Shital Raut
Keyword(s):  
Supervised Learning ◽  
Learning To Rank ◽  
Cost Effective ◽  
Unlabeled Data ◽  
Training Data ◽  
Density Region ◽  
The Arts ◽  
Proposed Model ◽  
Supervised Learning Algorithms ◽  
Multiple Loss

Learning-to-rank (LTR) is a very hot topic of research for information retrieval (IR). LTR framework usually learns the ranking function using available training data that are very cost-effective, time-consuming and biased. When sufficient amount of training data is not available, semi-supervised learning is one of the machine learning paradigms that can be applied to get pseudo label from unlabeled data. Cluster and label is a basic approach for semi-supervised learning to identify the high-density region in data space which is mainly used to support the supervised learning. However, clustering with conventional method may lead to prediction performance which is worse than supervised learning algorithms for application of LTR. Thus, we propose rank preserving clustering (RPC) with PLocalSearch and get pseudo label for unlabeled data. We present semi-supervised learning that adopts clustering-based transductive method and combine it with nonmeasure specific listwise approach to learn the LTR model. Moreover, each cluster follows the multi-task learning to avoid optimization of multiple loss functions. It reduces the training complexity of adopted listwise approach from an exponential order to a polynomial order. Empirical analysis on the standard datasets (LETOR) shows that the proposed model gives better results as compared to other state-of-the-arts.

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