EVM as generic QoS trigger for heterogeneous wieless overlay network

Fourth Generation (4G) Wireless System will integrate heterogeneous wireless overlay systems i.e. interworking of WLAN/ GSM/ CDMA/ WiMAX/ LTE/ etc with guaranteed Quality of Service (QoS) and Experience (QoE).QoS(E) vary from network to network and is application sensitive. User needs an optimal mobility solution while roaming in Overlaid wireless environment i.e. user could seamlessly transfer his session/ call to a best available network bearing guaranteed Quality of Experience. And If this Seamless transfer of session is executed between two networks having different access standards then it is called Vertical Handover (VHO). Contemporary VHO decision algorithms are based on generic QoS metrics viz. SNR, bandwidth, jitter, BER and delay. In this paper, Error Vector Magnitude (EVM) is proposed to be a generic QoS trigger for VHO execution. EVM is defined as the deviation of inphase/ quadrature (I/Q) values from ideal signal states and thus provides a measure of signal quality. In 4G Interoperable environment, OFDM is the leading Modulation scheme (more prone to multi-path fading). EVM (modulation error) properly characterises the wireless link/ channel for accurate VHO decision. EVM depends on the inherent transmission impairments viz. frequency offset, phase noise, non-linear-impairment, skewness etc. for a given wireless link. Paper provides an insight to the analytical aspect of EVM & measures EVM (%) for key management subframes like association/re-association/disassociation/ probe request/response frames. EVM relation is explored for different possible NAV-Network Allocation Vectors (frame duration). Finally EVM is compared with SNR, BER and investigation concludes EVM as a promising QoS trigger for OFDM based emerging wireless standards.Comment: 12 pages, 7 figures, IJWMN 2010 august issue vol. 2, no.

Identification and validation of genomic regions associated with pre-harvest sprouting resistance in white-grained wheat (triticum aestivum L.)

Pre-harvest sprouting (PHS) in bread wheat (Triticum aestivum L.) is one of the major abiotic constraints influencing the production of high quality grain. The flour milled from sprouted wheat grains has increased Ą-amylase activity as compared to non-sprouted grain. PHS negatively affects the properties of flour with deleterious effects on bread and noodle quality. White-grained wheat is generally more susceptible to PHS damage than red-grained wheat. The objectives of this study were to identify a suitable method for phenotyping PHS resistance and to identify PHS resistance genomic regions and markers that could be used for marker-assisted selection in wheat improvement programs. A doubled haploid (DH) mapping population from a cross between two white-grained spring wheat genotypes, Argent (non-dormant) and W98616 (dormant) was used in this study. Forty DH lines (20 dormant and 20 non-dormant) were evaluated for germination frequency, Falling Number, and Ą-amylase activity in dry and water-imbibed seeds and spikes. The germination test was the most reliable method for measurement of PHS resistance, whereas the Falling Number and Ą-amylase activity in dry harvested seeds could not be correlated to dormancy levels. However, a positive association (r = 0.60***) was detected between germination frequency and Ą-amylase activity in imbibed seeds. To identify the genomic regions associated with PHS resistance, a genetic linkage map with a total genome coverage of 2,577 cM was developed. The map was constructed from 913 scored markers (356 SSR, 290 AFLP, 258 DArT and 9 EST) with an average marker density of 3.7 cM/marker. Five genomic regions on chromosomes 1A, 3A, 4A, 7A and 7D were associated with PHS resistance by interval mapping and all regions were contributed by the dormant parent W98616. A total of 60 Canadian wheat cultivars and experimental lines were screened with three SSR markers, DuPw004, barc170 and wmc650, located under the major quantitative trait locus (QTL) on chromosome 4A. The SSR markers explained 60-75% of the total variation in germination frequency among different wheat genotypes. By using the DuPw004 marker in marker-assisted back crossing, the population size in the BC1F1 and BC2F1 generations were reduced by 41% and 59%, respectively. Thus, the 4A QTL markers have been proven useful for marker-assisted selection of PHS resistance for wheat improvement

Long term outcomes in patients with heart failure The Darlington Retrospective Out Patient Study (DROPSY)

The Darlington Retrospective Outpatient Study (DROPSY) was carried out at the Darlington Memorial Hospital Darlington. From Jan 2002 to Dec 2007, 1041 patients were seen in the heart failure (HF) clinic. Of these 270 (26%) were diagnosed as having left ventricular systolic dysfunction (LVSD). Of the 771 patients who did not have systolic dysfunction, we identified 243 patients who fulfilled the study criteria for heart failure with preserved ejection fraction (HFpEF). The remaining 528 patients formed the non heart failure (Other) group. Patients with HFpEF were older and more likely to have hypertension and diabetes than the other two groups. The LVSD group had more men plus ischemic heart disease patients while the third group of non HF also had more females and a high number with COPD. Over the mean follow up of 7 years, the number of admissions to hospital per patient was similar in both the LVSD and HFpEF groups, but HFpEF patients had a significantly longer length of stay. In the HFpEF group, the use of beta blockers, ACE inhibitors, and a lower median resting HR of < 78 / min predicted better survival. All cause mortality was high in both LVSD and HFpEF groups, with strikingly different cause of death. Patients with LVSD had more cardiovascular deaths whereas HFpEF patients were more likely to die of non cardiovascular causes. Patients in the third group diagnosed as not having HF (Other group) also had high five year mortality. Conclusion Patients with LVSD and HFpEF have high mortality but different causes of death. The use of beta blockers, ACE inhibitors, and a lower resting heart rate in the HFpEF group was associated with better survival. Patients who were reassured as not having HF do badly as well

Internet banking : Hyderabad scenario a banking and non-banking group perspective

Salah satu bentuk perbankan yang baru pada masa kini ialah e-perbankan atau perbankan internet. Teknologi perbankan ini menawarkan pelbagai kaedah pengurusan dan perkhidmatan bank yang mudah dan ekonomikal kepada pengguna. Tujuan kajian ini, "Internet Banking: Hyderabad Scenario - A Banking and Non-Banking Group Perspective,", adalah untuk mengkaji faktor di sebalik penerimaan teknologi perbankan internet di kalangan rakyat India. Tidak banyak kajian yang pemah dijalankan dalam bidang ini, di mana penganalisaan data dilakukan untuk mengenalpasti perbezaan yang wujud dalam persepsi perbankan internet di antara kumpulan perbankan dan kumpulan kerja bukan-perbankan. One of the forms of banking is e-banking or internet banking. This technology offers a non-traditional way through which banking products and services can be delivered to customers more conveniently and economically. The aim of this thesis "Internet Banking: Hyderabad Scenario- A Banking and Non-Banking Group Perspective" is to look in to the factors that are effecting the acceptance in the Indian market. This is among the very few researches which will try to analyze the data and find out the differences exists in the perception of internet banking between the banking and nonbanking working groups

Manganese-Zinc Spinel Ferrite Nanoparticles and Ferrofluids

The nanoparticles and ferrofluids of spinel ferrites are useful in bio-sensors, transducers, storage devices, optical devices, and so on. The Mn-Zn ferrite (MZF) is generalized soft spinel ferrite having high saturation magnetization at low applied magnetic field. This chapter covers the synthesis of nanoparticles of various sizes and compositions of Mn1-xZnx Fe2O4 with x = 0–1 by co-precipitation method. The structural and magnetic properties of the nanoparticles are discussed. The ferrofluids of superparamagnetic and ferromagnetic MZF nanoparticles were synthesized. The magneto-viscosity of ferrofluids with the dispersion of nanoparticles in different colloidal was studied. The Herschel-Bulkley model is applied to analyse the data for low viscosity ferrofluids

L859F mutation in androgen receptor gene results in complete loss of androgen binding to the receptor

Androgens drive male secondary sexual differentiation and maturation. Mutations in the androgen receptor (AR) gene cause an array of abnormal sex differentiation phenotypes in humans, ranging from mild through partial to complete androgen insensitivity. Earlier, we reported a C3693T missense mutation in the AR gene in a familial case of complete androgen insensitivity syndrome (CAIS), resulting in the replacement of a highly conserved leucine residue with phenylalanine (L859F) in ligand-binding domain (LBD) of the receptor. In silico analysis and the information from the crystal structure of AR-LBD indicated that the residue L859, located in helix 10 of AR protein, plays a significant role in overall architecture of the ligand-binding pocket. From this information we anticipated that the mutation might have resulted in the loss of the ligand binding to the receptor. In the present study, we have conducted the in vitro functional assays for this mutation. The mutation resulted in highly significant loss of the ligand binding to the receptor. The loss of ligand binding and subsequent AR function was confirmed by the transactivation assay, in which we observed very little activation of the reporter gene expressed under the control of the ligand-AR complex

ESR and Magnetization Studies of Bi-manganites

The electron spin resonance (ESR) and magnetization (M) studies of Bi-manganites were undertaken to understand the coexistence of various magnetic phases and their effect on charge ordering as a function of composition and temperature. The studies on several compositions of Bi-manganites reveal that the electronic phase separation (PS) is an intrinsic phenomenon in this system

RESDEN: A Novel Deep Unified Model for Face Recognition System

The Face Recognition technology plays a significant role in the field of Computer Vision in contemporary times. The research article is centered on a Facial attendance system that utilizes a deep learning technique to recognize face photos. To execute face identification and classification via the use of deep learning processes, many Convolutional Neural Network (CNN) models are taken into account. Previous studies have mostly focused on either the ResNet or DenseNet-based convolutional neural network model. The present research utilizes the merging of ResNet and DenseNet to propose a hybrid model. The proposed work is expected to provide enhanced efficiency and accuracy. In the training and testing stages of the simulation, considerations are made for both binary and category classifications. The current research focuses on the use of the LFW dataset. The pictures undergo an initial step of the noise reduction process. The evaluation of picture quality is conducted by taking into account metrics such as Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM). After the proposed model has undergone training, it generates photographs of superior quality. Finally, the proposed system incorporates the RESDEN framework, which integrates DenseNet with a noise reduction technique, a segmentation mechanism, and a CNN based on ResNet. A comparative analysis has been conducted to evaluate the accuracy of several filtered picture sets across different convolutional neural network (CNN) models. The simulation results indicate that the suggested model exhibited a good level of performance and accuracy

Correlates of Professional Obsolescence among Researchers

Obsolescence setting in the employees of the organisations significantly hampers the organisational productivity. An empirical investigation of the associated factors and the efforts to minimise them help in designing strategies to deal with obsolescence and maintain optimum effectiveness of the organisation. As an attempt in this direction, the present study aimed at exploring the role of literature-suggested correlates of obsolescence in case of researchers in an Indian government organisation. The sample included 200 participants (146 males and 54 females) working as researchers in government scientific institutions with service experience ranging from two to 30 years. The participants were administered with standardised measures of obsolescence, work engagement, work motivation, resistance to change, organisational climate, human resource management (HRM) Policies and Practices, and Self Esteem. The obtained data were analysed with correlation and regression analyses. The findings revealed that in the target population obsolescence due to both organisational and individual level factors was found significantly and positively correlated with amotivation and resistance to change; whereas, negatively correlated with work engagement, organisational climate, HRM policies and practices, intrinsic motivation, and self-esteem. Regression analyses indicated that adequate recognition of efforts, better training and development, qualitative work availability (pressure), and enhanced concern to optimally maintain the intrinsic motivation and dedication of employees are significant factors for keeping check on obsolescence. The findings are explained and discussed in details

Securing IoT Networks for Detection of Cyber Attacks using Automated Machine Learning

Cybercriminals are always developing innovative strategies to confound and frustrate their victims. Therefore, maintaining constant vigilance is essential if one wishes to protect the availability, confidentiality, and integrity of digital systems. Machine learning (ML) is becoming an increasingly powerful technique for doing intelligent cyber analysis, which enables proactive defenses. Machine learning (ML) has the potential to thwart future assaults by studying the recurring patterns that have already been successful. Nevertheless, there are two significant drawbacks associated with the utilization of ML in security analysis. To begin, the most advanced machine learning systems have significant problems with their computing overheads. Because of this constraint, firms are unable to completely embrace ML-based cyber strategies. Second, in order for security analysts to make advantage of ML for a wide variety of applications, they will need to develop specialized frameworks. In this study, we aim to put a numerical value on the degree to which a hub can improve the safety of an ecosystem. Typical cyberattacks were carried out on an Internet of Things (IoT) network located within a smart house in order to validate the hub. Further investigation of the intrusion detection system's (IDS) resistance to adversarial machine learning (AML) assaults was carried out. In this method, models can be attacked by supplying adversarial samples that attempt to take advantage of the defects in the detector that are present in the pre-trained model