Robust Video Watermarking Algorithm based on DCT-SVD approach and Encryption

Sharing of digital media content over the internet is increasing everyday .Digital watermarking is a technique used to protect the intellectual property rights of multimedia content owners. In this paper, we propose a robust video watermarking scheme that utilizes Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) for embedding a watermark into video frames. The proposed method uses encryption to make the watermark more robust against malicious attacks. The encryption key is used to modify the watermark before it is embedded in the video frames. The modified watermark is then embedded in the DCT and SVD coefficients of the video frames. The experimental results show that the proposed method provides better robustness against various attacks such as compression, noise addition, and filtering, while maintaining good perceptual quality of the watermarked video. The proposed method also shows better resistance against geometric attacks such as cropping, rotation, and scaling. Overall, the proposed method provides an effective solution for protecting the intellectual property rights of multimedia content owners in video distribution and transmission scenarios

Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic Techniques

Electric discharge machining is an essential modern manufacturing process employed to machine porous sintered metals. The sintered 316L porous stainless steel (PSS) components are widely used in diverse engineering domains, as interconnected pores are present. The PSS material has excellent lightweight and damping properties and superior mechanical and metallurgical properties. However, conventional machining techniques are not suitable for porous metals machining. Such techniques tend to block the micro-pores, resulting in a decrease in porous materials’ breathability. Thus, the EDM process is an effective technique for porous metal machining. The input process parameters selected in this study are peak current (Ip), pulse on time (Ton), voltage (V), flushing pressure (fp), and porosity. The response parameters selected are material removal rate (MRR) and tool wear rate (TWR). The present work aims to obtain optimum machining process parameters in the EDM of porous sintered SS316L using two meta-heuristic optimization techniques, i.e., Teaching Learning-Based Optimization (TLBO) and Particle Swarm Optimization (PSO) algorithms, to maximize the MRR and minimize the TWR values. In the case of PSS having a 12.60% porosity value, PSO and TLBO algorithms give same optimum machining parameters. However, for PSS having an 18.85% porosity value, the PSO algorithm improves by about 5.25% in MRR and by 5.63% in TWR over the TLBO. In the case of PSS having a 31.11% porosity value, the PSO algorithm improves about 3.73% in MRR and 6.46% in TWR over the TLBO. The PSO algorithm is found to be consistent and to converge more quickly, taking minimal computational time and effort compared to the TLBO algorithm. The present study’s findings contribute valuable information in regulating the EDM performance in machining porous SS316L

Ofatumumab versus Teriflunomide in Multiple Sclerosis

BACKGROUND: Ofatumumab, a subcutaneous anti-CD20 monoclonal antibody, selectively depletes B cells. Teriflunomide, an oral inhibitor of pyrimidine synthesis, reduces T-cell and B-cell activation. The relative effects of these two drugs in patients with multiple sclerosis are not known. METHODS: In two double-blind, double-dummy, phase 3 trials, we randomly assigned patients with relapsing multiple sclerosis to receive subcutaneous ofatumumab (20 mg every 4 weeks after 20-mg loading doses at days 1, 7, and 14) or oral teriflunomide (14 mg daily) for up to 30 months. The primary end point was the annualized relapse rate. Secondary end points included disability worsening confirmed at 3 months or 6 months, disability improvement confirmed at 6 months, the number of gadolinium-enhancing lesions per T1-weighted magnetic resonance imaging (MRI) scan, the annualized rate of new or enlarging lesions on T2-weighted MRI, serum neurofilament light chain levels at month 3, and change in brain volume. RESULTS: Overall, 946 patients were assigned to receive ofatumumab and 936 to receive teriflunomide; the median follow-up was 1.6 years. The annualized relapse rates in the ofatumumab and teriflunomide groups were 0.11 and 0.22, respectively, in trial 1 (difference, -0.11; 95% confidence interval [CI], -0.16 to -0.06; P<0.001) and 0.10 and 0.25 in trial 2 (difference, -0.15; 95% CI, -0.20 to -0.09; P<0.001). In the pooled trials, the percentage of patients with disability worsening confirmed at 3 months was 10.9% with ofatumumab and 15.0% with teriflunomide (hazard ratio, 0.66; P = 0.002); the percentage with disability worsening confirmed at 6 months was 8.1% and 12.0%, respectively (hazard ratio, 0.68; P = 0.01); and the percentage with disability improvement confirmed at 6 months was 11.0% and 8.1% (hazard ratio, 1.35; P = 0.09). The number of gadolinium-enhancing lesions per T1-weighted MRI scan, the annualized rate of lesions on T2-weighted MRI, and serum neurofilament light chain levels, but not the change in brain volume, were in the same direction as the primary end point. Injection-related reactions occurred in 20.2% in the ofatumumab group and in 15.0% in the teriflunomide group (placebo injections). Serious infections occurred in 2.5% and 1.8% of the patients in the respective groups. CONCLUSIONS: Among patients with multiple sclerosis, ofatumumab was associated with lower annualized relapse rates than teriflunomide. (Funded by Novartis; ASCLEPIOS I and II ClinicalTrials.gov numbers, NCT02792218 and NCT02792231.)