Coupling of pinned magnetic moments in an antiferromagnet to a ferromagnet and its role for exchange bias

The interaction between uncompensated pinned magnetic moments within an antiferromagnetic (AFM) layer and an adjacent ferromagnetic (FM) layer responsible for the existence of exchange bias is explored in epitaxially grown trilayers of the form FM2/AFM/FM1 on Cu3Au(0 0 1) where FM1 is ~12 atomic monolayers (ML) Ni, FM2 is 21–25 ML Ni, and AFM is 27 ML or 50 ML Ni~25Mn~75. Field cooling for parallel or antiparallel alignment of the out-of-plane magnetizations of the two FM layers does not make a difference for the temperature-dependent coercivity (H C), magnitude of exchange bias field (H eb), AFM ordering temperature (T AFM), and blocking temperature for exchange bias (T b). We explain this by a model in which the uncompensated pinned magnetic moments distributed within the volume of the AFM layer interact with both of the FM layers, albeit with different strength. Parallel and antiparallel coupling between the magnetization of the pinned moments and the FM layers equally exists. This leads to the experimentally observed independence of H C, H eb, as well as of T AFM and T b on the magnetization direction of the FM layers during field cooling. These results provide new and detailed insight into revealing the subtle and complex nature of the exchange bias effect

Simulation Analysis of Medium Access Techniques

This paper presents comparison of Access Techniques used in Medium Access Control (MAC) protocol for Wireless Body Area Networks (WBANs). Comparison is performed between Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA), Pure ALOHA and Slotted ALOHA (S-ALOHA). Performance metrics used for comparison are throughput (T), delay (D) and offered load (G). The main goal for comparison is to show which technique gives highest Throughput and lowest Delay with increase in Load. Energy efficiency is major issue in WBAN that is why there is need to know which technique performs best for energy conservation and also gives minimum delay.Comment: NGWMN with 7th IEEE International Conference on Broadband and Wireless Computing, Com- munication and Applications (BWCCA 2012), Victoria, Canada, 201

Data-driven network performance prediction for B5G networks: a graph neural network approach

Extreme connectivity, dynamic resource provision-ing and demand of quality assurance in 5G and Beyond 5G (B5G) networks calls for advance network modeling solutions. We need functional network models that are able to produce accurate prediction of Key Performance Indicators (KPI) such as latency, overall delay, jitter or packet loss at low cost. Graph Neural Networks (GNN) have already shown great potential for network performance prediction, because of their ability to understand the network configurations. In this paper, we focus on improving the generalization capabilities of GNN in relatively complex IP transport network scenarios of future generation networks. We take RouteNet GNN as a reference model and present an alternative GNN. We train both models with relatively smaller network scenarios while for evaluation we use complex and large network configurations. After hyper-parameter tuning for RouteNet and proposed GNN, the results show that our model outperforms baseline architecture in evaluation phase. The validation losses for scenarios not seen during training phase, are significantly lower than the RouteNet

Transmission Delay of Multi-hop Heterogeneous Networks for Medical Applications

Nowadays, with increase in ageing population, Health care market keeps growing. There is a need for monitoring of Health issues. Body Area Network consists of wireless sensors attached on or inside human body for monitoring vital Health related problems e.g, Electro Cardiogram (ECG), ElectroEncephalogram (EEG), ElectronyStagmography(ENG) etc. Data is recorded by sensors and is sent towards Health care center. Due to life threatening situations, timely sending of data is essential. For data to reach Health care center, there must be a proper way of sending data through reliable connection and with minimum delay. In this paper transmission delay of different paths, through which data is sent from sensor to Health care center over heterogeneous multi-hop wireless channel is analyzed. Data of medical related diseases is sent through three different paths. In all three paths, data from sensors first reaches ZigBee, which is the common link in all three paths. After ZigBee there are three available networks, through which data is sent. Wireless Local Area Network (WLAN), Worldwide Interoperability for Microwave Access (WiMAX), Universal Mobile Telecommunication System (UMTS) are connected with ZigBee. Each network (WLAN, WiMAX, UMTS) is setup according to environmental conditions, suitability of device and availability of structure for that device. Data from these networks is sent to IP-Cloud, which is further connected to Health care center. Main aim of this paper is to calculate delay of each link in each path over multihop wireless channel.Comment: BioSPAN with 7th IEEE International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA 2012), Victoria, Canada, 201

Analyzing Delay in Wireless Multi-hop Heterogeneous Body Area Networks

With increase in ageing population, health care market keeps growing. There is a need for monitoring of health issues. Wireless Body Area Network (WBAN) consists of wireless sensors attached on or inside human body for monitoring vital health related problems e.g, Electro Cardiogram (ECG), Electro Encephalogram (EEG), ElectronyStagmography (ENG) etc. Due to life threatening situations, timely sending of data is essential. For data to reach health care center, there must be a proper way of sending data through reliable connection and with minimum delay. In this paper transmission delay of different paths, through which data is sent from sensor to health care center over heterogeneous multi-hop wireless channel is analyzed. Data of medical related diseases is sent through three different paths. In all three paths, data from sensors first reaches ZigBee, which is the common link in all three paths. Wireless Local Area Network (WLAN), Worldwide Interoperability for Microwave Access (WiMAX), Universal Mobile Telecommunication System (UMTS) are connected with ZigBee. Each network (WLAN, WiMAX, UMTS) is setup according to environmental conditions, suitability of device and availability of structure for that device. Data from these networks is sent to IP-Cloud, which is further connected to health care center. Delay of data reaching each device is calculated and represented graphically. Main aim of this paper is to calculate delay of each link in each path over multi-hop wireless channel.Comment: arXiv admin note: substantial text overlap with arXiv:1208.240

The X-Ray Spectral Variability of Mrk 766

Analysis results from ASCA and ROSAT observations of the narrow-line Seyfert 1 galaxy Mrk 766 are reported. In the ASCA observation we observed rapid variability with a doubling time scale of 1000 seconds. A spectral variability event was observed in which the spectrum softened and hardened above and below ~1 keV, respectively, as the flux increased. The spectra could be modeled with 5 components: a power law, warm absorber, iron K(alpha) line and soft excess component flux. The spectral variability resulted from a highly significant change in the intrinsic photon law index from Gamma ~1.6 to ~2.0, an increase in the warm absorber ionization, and a marginally significant decrease in the soft component normalization. A ~100 eV equivalent width narrow iron K(alpha) line was detected in the high state spectrum. Spectral hardening during flux increases was observed in three ROSAT observations. The change in intrinsic photon index and disappearance of the soft excess component in the ASCA spectra can be explained as a transition from a first order pair reprocessed spectrum to a pair cascade brought about by a sudden increase in the injected electron Lorentz factor. The change in the ionization of the warm absorber, though model dependent, could correspond to the increase in flux at the oxygen edges resulting from the spectral index change. The ROSAT spectral variability can be interpreted by variable intensity hard power law and a relatively nonvarying soft component, possibly primary disk emission. These results are compared with those reported from other narrow-line Seyfert 1 galaxies.Comment: 29 pages using (AASTeX) aaspp4.sty and 18 Postscript figures. To appear in the September 1, 1996, issue of The Astrophysical Journa