Secured Transmission of a compressed image by using ECC

Security is the main issue concerned with protecting the digital images that are transmitted over the network. By providing the high security, the digital images on the network can be protected from various types of attacks. A Cryptographic technique plays a major role in providing the security goals such as confidentiality and integrity for digital images. Elliptical curve cryptography (ECC) is the asymmetric encryption which is used to apply to the images that result from DWT Compression. Discrete Wavelet Transform (DWT) is an important compression technique which is used to compress the image effectively. It represents the input data in the form of the low pass (approximate) and high pass (detailed) coefficients. These coefficients are entered into the filters. The outputs from these filters are down-sampled for compression. In this paper, the transmitted images via wireless network were secured by encryption using the public key. The sender will generate the private key from the compressed image based on elliptical curve cryptography. The Sender will send the compressed image and private key separately to the receiver. DWT provides high compression ratio and robustness for protecting the digital image integrity. This experiment result provides some performance measures such as Peak Signal to Noise Ratio (PSNR), Bit Error Rate (BER) and Mean Squared Error (MSE). It also provides high integrity for transmitted digital images

Secured Transmission of a compressed image by using ECC

Security is the main issue concerned with protecting the digital images that are transmitted over the network. By providing the high security, the digital images on the network can be protected from various types of attacks. A Cryptographic technique plays a major role in providing the security goals such as confidentiality and integrity for digital images. Elliptical curve cryptography (ECC) is the asymmetric encryption which is used to apply to the images that result from DWT Compression. Discrete Wavelet Transform (DWT) is an important compression technique which is used to compress the image effectively. It represents the input data in the form of the low pass (approximate) and high pass (detailed) coefficients. These coefficients are entered into the filters. The outputs from these filters are down-sampled for compression. In this paper, the transmitted images via wireless network were secured by encryption using the public key. The sender will generate the private key from the compressed image based on elliptical curve cryptography. The Sender will send the compressed image and private key separately to the receiver. DWT provides high compression ratio and robustness for protecting the digital image integrity. This experiment result provides some performance measures such as Peak Signal to Noise Ratio (PSNR), Bit Error Rate (BER) and Mean Squared Error (MSE). It also provides high integrity for transmitted digital images

Global patterns in monthly activity of influenza virus, respiratory syncytial virus, parainfluenza virus, and metapneumovirus: a systematic analysis

Background: Influenza virus, respiratory syncytial virus, parainfluenza virus, and metapneumovirus are the most common viruses associated with acute lower respiratory infections in young children (<5 years) and older people (≥65 years). A global report of the monthly activity of these viruses is needed to inform public health strategies and programmes for their control. Methods: In this systematic analysis, we compiled data from a systematic literature review of studies published between Jan 1, 2000, and Dec 31, 2017; online datasets; and unpublished research data. Studies were eligible for inclusion if they reported laboratory-confirmed incidence data of human infection of influenza virus, respiratory syncytial virus, parainfluenza virus, or metapneumovirus, or a combination of these, for at least 12 consecutive months (or 52 weeks equivalent); stable testing practice throughout all years reported; virus results among residents in well-defined geographical locations; and aggregated virus results at least on a monthly basis. Data were extracted through a three-stage process, from which we calculated monthly annual average percentage (AAP) as the relative strength of virus activity. We defined duration of epidemics as the minimum number of months to account for 75% of annual positive samples, with each component month defined as an epidemic month. Furthermore, we modelled monthly AAP of influenza virus and respiratory syncytial virus using site-specific temperature and relative humidity for the prediction of local average epidemic months. We also predicted global epidemic months of influenza virus and respiratory syncytial virus on a 5° by 5° grid. The systematic review in this study is registered with PROSPERO, number CRD42018091628. Findings: We initally identified 37 335 eligible studies. Of 21 065 studies remaining after exclusion of duplicates, 1081 full-text articles were assessed for eligibility, of which 185 were identified as eligible. We included 246 sites for influenza virus, 183 sites for respiratory syncytial virus, 83 sites for parainfluenza virus, and 65 sites for metapneumovirus. Influenza virus had clear seasonal epidemics in winter months in most temperate sites but timing of epidemics was more variable and less seasonal with decreasing distance from the equator. Unlike influenza virus, respiratory syncytial virus had clear seasonal epidemics in both temperate and tropical regions, starting in late summer months in the tropics of each hemisphere, reaching most temperate sites in winter months. In most temperate sites, influenza virus epidemics occurred later than respiratory syncytial virus (by 0·3 months [95% CI −0·3 to 0·9]) while no clear temporal order was observed in the tropics. Parainfluenza virus epidemics were found mostly in spring and early summer months in each hemisphere. Metapneumovirus epidemics occurred in late winter and spring in most temperate sites but the timing of epidemics was more diverse in the tropics. Influenza virus epidemics had shorter duration (3·8 months [3·6 to 4·0]) in temperate sites and longer duration (5·2 months [4·9 to 5·5]) in the tropics. Duration of epidemics was similar across all sites for respiratory syncytial virus (4·6 months [4·3 to 4·8]), as it was for metapneumovirus (4·8 months [4·4 to 5·1]). By comparison, parainfluenza virus had longer duration of epidemics (6·3 months [6·0 to 6·7]). Our model had good predictability in the average epidemic months of influenza virus in temperate regions and respiratory syncytial virus in both temperate and tropical regions. Through leave-one-out cross validation, the overall prediction error in the onset of epidemics was within 1 month (influenza virus −0·2 months [−0·6 to 0·1]; respiratory syncytial virus 0·1 months [−0·2 to 0·4]). Interpretation: This study is the first to provide global representations of month-by-month activity of influenza virus, respiratory syncytial virus, parainfluenza virus, and metapneumovirus. Our model is helpful in predicting the local onset month of influenza virus and respiratory syncytial virus epidemics. The seasonality information has important implications for health services planning, the timing of respiratory syncytial virus passive prophylaxis, and the strategy of influenza virus and future respiratory syncytial virus vaccination. Funding: European Union Innovative Medicines Initiative Respiratory Syncytial Virus Consortium in Europe (RESCEU)

Resistance Profiles to Second-Line Anti-Tuberculosis Drugs and Their Treatment Outcomes: A Three-Year Retrospective Analysis from South India

Background: Patients with first-line drug resistance (DR) to rifampicin (RIF) or isoniazid (INH) as a first-line (FL) line probe assay (LPA) were subjected to genotypic DST using second-line (SL) LPA to identify SL-DR (including pre-XDR) under the National TB Elimination Program (NTEP), India. SL-DR patients were initiated on different DR-TB treatment regimens and monitored for their outcomes. The objective of this retrospective analysis was to understand the mutation profile and treatment outcomes of SL-DR patients. Materials and Methods: A retrospective analysis of mutation profile, treatment regimen, and treatment outcome was performed for SL-DR patients who were tested at ICMR-NIRT, Supra-National Reference Laboratory, Chennai between the years 2018 and 2020. All information, including patient demographics and treatment outcomes, was extracted from the NTEP Ni-kshay database. Results: Between 2018 and 2020, 217 patients out of 2557 samples tested were identified with SL-DR by SL-LPA. Among them, 158/217 were FQ-resistant, 34/217 were SLID-resistant, and 25/217 were resistant to both. D94G (Mut3C) of gyrA and a1401g of rrs were the most predominant mutations in the FQ and SLID resistance types, respectively. Favorable (cured and treatment complete) and unfavorable outcomes (died, lost to follow up, treatment failed, and treatment regimen changed) were recorded in a total of 82/217 and 68/217 patients in the NTEP Ni-kshay database. Conclusions: As per the testing algorithm, SL- LPA is used for genotypic DST following identification of first-line resistance, for early detection of SL-DR in India. The fluoroquinolone resistance pattern seen in this study population corelates with the global trend. Early detection of fluoroquinolone resistance and monitoring of treatment outcome can help achieve better patient management