Optimal Energy-Delay Routing Protocol with Trust Levels for Wireless Ad Hoc Networks

This paper presents the Trust Level Routing (TLR) pro- tocol, an extension of the optimized energy-delay rout- ing (OEDR) protocol, focusing on the integrity, reliability and survivability of the wireless network. TLR is similar to OEDR in that they both are link state routing proto- cols that run in a proactive mode and adopt the concept of multi-point relay (MPR) nodes. However, TLR aims at incorporating trust levels into routing by frequently changing the MPR nodes as well as authenticating the source node and contents of control packets. TLR calcu- lates the link costs based on a composite metric (delay incurred, energy available at the neighbor node, energy spent during transmission and the number of packets sent on each link) for the selection ofMPR nodes. We highlight the vulnerabilities in OEDR and show ways to counter the possible attacks by using authentication and traffic par- tition as a basis for mitigating the effects of malicious activity. Network simulator NS2 results show that TLR delivers the packets with a noticeable decrease in the av- erage end-to-end delay with a small increase in the power consumed due to the additional computational overhead attributed to the security extension

Dynamic disorder in receptor-ligand forced dissociation experiments

Recently experiments showed that some biological noncovalent bonds increase their lifetimes when they are stretched by an external force, and their lifetimes will decrease when the force increases further. Several specific quantitative models have been proposed to explain the intriguing transitions from the "catch-bond" to the "slip-bond". Different from the previous efforts, in this work we propose that the dynamic disorder of the force-dependent dissociation rate can account for the counterintuitive behaviors of the bonds. A Gaussian stochastic rate model is used to quantitatively describe the transitions observed recently in the single bond P-selctin glycoprotein ligand 1(PSGL-1)$-$P-selectin force rupture experiment [Marshall, {\it et al.}, (2003) Nature {\bf 423}, 190-193]. Our model agrees well to the experimental data. We conclude that the catch bonds could arise from the stronger positive correlation between the height of the intrinsic energy barrier and the distance from the bound state to the barrier; classical pathway scenario or {\it a priori} catch bond assumption is not essential.Comment: 4 pages, 2 figure

Feedback Linearization Based Power System Stabilizer Design with Control Limits

In power system controls, simplified analytical models are used to represent the dynamics of power system and controller designs are not rigorous with no stability analysis. One reason is because the power systems are complex nonlinear systems which pose difficulty for analysis. This paper presents a feedback linearization based power system stabilizer design for a single machine infinite bus power system. Since practical operating conditions require the magnitude of control signal to be within certain limits, the stability of the control system under control limits is also analyzed. Simulation results under different kinds of operating conditions show that the controller design not only can damp the power system oscillations very well but can also minimize the impact on the terminal voltage. In addition, the Brunovsky Canonical form of the power system model presented in this paper can be used for other forms of controller design

Neural Network Stabilizing Control of Single Machine Power System with Control Limits

Power system stabilizers are widely used to generate supplementary control signals for the excitation system in order to damp out the low frequency oscillations. This paper proposes a stable neural network (NN) controller for the stabilization of a single machine infinite bus power system. In the power system control literature, simplified analytical models are used to represent the power system and the controller designs are not based on rigorous stability analysis. This work overcomes the two major problems by using an accurate analytical model for controller development and presents the closed-loop stability analysis. The NN is used to approximate the complex nonlinear power system online and the weights of which can be set to zero to avoid the time consuming offline training process. Magnitude constraint of the activators is modeled as saturation nonlinearities and is included in the Lyapunov stability analysis. Simulation results demonstrate that the proposed design can successfully damp out oscillations. The control algorithms of this work can also be applied to other similar control problems

Two Neural Network Based Decentralized Controller Designs for Large Scale Power Systems

This paper presents two neural network (NN) based decentralized controller designs for large scale power systems\u27 generators, one is for the excitation control and the other is for the steam valve control. Though the control signals are calculated using local signals only, the transient and overall system stabilities can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system and the interconnection terms, thus the requirements for exact system parameters are released. Simulation studies with a three machine power system demonstrate the effectiveness of the proposed controller designs

Adaptive Neural Network Based Stabilizing Controller Design for Single Machine Infinite Bus Power Systems

Power system stabilizers are widely used to generate supplementary control signals for the excitation system in order to damp out the low frequency oscillations. In power system control literature, the performances of the proposed controllers were mostly demonstrated using simulation results without any rigorous stability analysis. This paper proposes a stabilizing neural network (NN) controller based on a sixth order single machine infinite bus power system model. The NN is used to approximate the complex nonlinear dynamics of power system. Unlike the other indirect adaptive NN control schemes, there is no offline training process and the NN can be directly used online and learn through time. Magnitude constraint of the activators is modeled as saturation nonlinearities and is included in the Lyapunov stability analysis. The new NN controller design is compared with conventional power system stabilizers (CPSS) whose parameters are fine tuned by particle swarm optimization (PSO). Simulation results demonstrate that the proposed NN controller design can successfully damp out power system oscillations. The control algorithms of this paper can also be applied to other similar nonlinear control problems

Neural Network Based Decentralized Controls of Large Scale Power Systems

This paper presents a suite of neural network (NN) based decentralized controller designs for large scale power systems\u27 generators, one is for the excitation control and the other is for the steam valve control. Though the control inputs are calculated using local signals, the transient and overall system stability can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system dynamics and the inter-connection terms, thus the requirements for exact system parameters are relaxed. Simulation studies with a three-machine power system demonstrate the effectiveness of the proposed controller designs

The Realities of Evaluating Educational Technology in School Settings

\ua9 2024 Copyright held by the owner/author(s).HCI researchers are increasingly interested in the evaluation of educational technologies in context, yet acknowledge that challenges remain regarding the logistical, material and methodological constraints of this approach to research [18, 53].Through the analysis of the authors\u27 contributed thematic research vignettes, the following article exposes the practical realities of evaluating educational technologies in school settings. This includes insights into the planning stages of evaluation, the relationship between the researcher and the school environment, and the impact of the school context on the data collection process.We conclude by providing an orientation for the design of HCI educational technology research undertaken in school contexts, providing guidance such as considering the role of modular research design, clarifying goals and expectations with school partners, and reporting researcher positionality

Comparisons of an Adaptive Neural Network Based Controller and an Optimized Conventional Power System Stabilizer

Power system stabilizers are widely used to damp out the low frequency oscillations in power systems. In power system control literature, there is a lack of stability analysis for proposed controller designs. This paper proposes a Neural Network (NN) based stabilizing controller design based on a sixth order single machine infinite bus power system model. The NN is used to compensate the complex nonlinear dynamics of power system. To speed up the learning process, an adaptive signal is introduced to the NN\u27s weights updating rule. The NN can be directly used online without offline training process. Magnitude constraint of the activators is modeled as saturation nonlinearities and is included in the stability analysis. The proposed controller design is compared with Conventional Power System Stabilizers whose parameters are optimized by Particle Swarm Optimization. Simulation results demonstrate the effectiveness of the proposed controller design

ANALIZA FINANCIJSKIH IZVJEŠĆA SA POSEBNIM OSVRTOM NA ANALIZU PUTEM FINANCIJSKIH POKAZATELJA NA PRIMJERU Jadranske banke d.d.

Tema rada je „Analiza financijskih izvještaja s posebnim osvrtom na analizu putem financijskih pokazatelja na primjeru poduzeća Jadranske banke D.D. Šibenik“. Ovu temu sam odabrao iz razloga što smatram da je razumijevanje financijske dimenzije poslovanja i upoznavanje njenih pravilnosti neophodno i iznimno važno da bi se uspješno upravljalo poduzećem te financijskim i kreditnim institucijama. Istraživanjem i izradom ovog rada smatram da ću produbiti razumijevanje i obogatiti svoje znanje o upravljanju financijama. Predmet rada su financijski izvještaji. Bilanca kao prikaz imovine i obveza poduzeća na određeni dan, račun dobiti i gubitka kao prikaz prihoda, rashoda i njihove razlike za određeno razdoblje. Bilanca i račun dobiti i gubitka za 2012.g., 2013.g. i 2014.g. Svrha rada je analizom financijskih izvještaja, bilance stanja i RDG-a za trogodišnje razdoblje provesti mjerenja i ustanoviti međusobne odnose brojčanih vrijednosti te izvesti značajne i korisne informacije za donošenje financijskih odluka. Cilj rada je otkriti uzroke neuspješnog poslovanja Jadranske banke D.D. Šibenik