Statistical Image Watermarking In DWT with Capacity Improvement

Abundant techniques has been widely used to design robust image watermarking schemes but in most cases due significance is not given on capacity and data imperceptibility aspects. Robustness of an image-watermarking scheme is the ability to detect the watermark after intentional attacks and normal audio/visual processes. This paper proposes a well-organized blind watermark detection scheme using DWT coefficients. Discrete Wavelet Transform (DWT) is widely applied to image watermarking applications because it decomposes a cover image into spatial domain as well as frequency domain simultaneously. The proposed method improves the capacity of image watermarking. The proposed paper concentrates on some of the main attributes necessary for image watermarking. They are embedding scheme, maximum likelihood detection, decision threshold, and the Laplacian model for image watermarking. The embedding method is multiplicative and done at second level of DWT decomposition by most favorable choice of the embedding strength. The watermark detection is based on the maximum likelihood ratio. Neyman-Pearson criterion is used to reduce the missed detection probability subject to a fixed false alarm probability. The DWT coefficients are assumed to be modeled using the Laplacian distribution. The proposed method is tested for imperceptibility, robustness, and capacity and proved to have better robustness and better imperceptibility and better capacity than other conventional watermarking techniques that were proposed earlier in literature

Spin Textures in High-Aspect-Ratio Ni80Fe20 Nanodisk Arrays: Implications for Next-Generation Spintronic Devices

Recent progress in nanomagnetism has generated significant enthusiasm for the creation of high-aspect-ratio nanostructures. Nonetheless, fabricating large-area thick nanostructures encounters substantial hurdles due to inherent lithographic constraints. In this study, we showcase the fabrication of magnetic nanodisks patterned with deep UV, reaching thicknesses of up to 200 nm, accomplished through the creation of nanotrenches in the Si substrate. Subsequently, the evolution of spin texture and spin dynamics as a function of thickness (20−200 nm) has been presented. The magnetization reversal studies reveal that the disks have a vortex as their ground state configuration; the nucleation and annihilation fields associated with the vortex increase with increasing thickness. We observe an increase in the vortex core diameter as the disk thickness is increased. Micromagnetic simulations suggest that the presence of an out-of-plane magnetization component is observed along the circumference, in addition to the into-the-plane magnetization at the center for disks of higher thicknesses. The magnetization dynamics studies reveal that the center mode frequency decreases with increasing thickness, and there is a mirror symmetry in the excitation amplitude between the top and bottom layers for nanodisks with thicknesses greater than 50 nm. The results are substantiated with micromagnetic simulations. Our results open horizons in the utilization of the third dimension for emerging spin textures and their potential applications in future spintronic devices

CO2 sequestration: microalgae genome analysis and its application of effective green source technology

Microalgae genome technology for CO2 sequestration is an appropriate vehicle for articulating the importance of the current need and solution for reduction of CO2 at the atmospheric level. In comparison with C4 plants, microalgae have greater capability to fix atmospheric CO2.The rate of CO2 fixation differs in different strains of microalgae. The photosynthetic enzyme RuBisCO is widely responsible for photosynthetic carbon assimilation in all plants including phototrophic algae.The gene rbcL encodes this enzyme. The catalytic activity of carbonic anhydrase achieves the CO2 generation in the RuBisCO. CAH3 gene is essential for generating CO2 concentration for RuBisCO by dehydration of accumulated inorganic carbon. There are also few other microalgae genes which involves for carbon assimilation. Genomic resource databases and several other nucleotide databases are being used for sequencing the microalgal genomes. Even though, recent advances in genomic studies are providing thrust to enhance the research on microalgal species, they are expensive and resources available for microalgal genomic studies are limited. This review article attempts first as a combined revise on microalgae CO2 sequestration in the field of basic science, applied aspects, and the role of specific gene(s) in the algal system is well defined which could be a supportive involvement of carbon dioxide reduction as “Green-Gene Technology”. This Green biotechnology could be used for Global warming reduction as well as creating wealth from the waste through valuable by-products from the selected microalgae strains in future

Innovative Testing Investigations on the Influence of Particle Morphology and Oil Contamination on the Geotechnical Properties of Sand

Shear strength and the permeability in a soil mass are two prime parameters that characterize the geotechnical behaviour of the soil. These parameters (c', Ø’, k) help assess the bearing capacity and settlement characteristics of foundations, stability of slopes, lateral earth pressure on retaining walls and fluid infiltration. Geo environmental contamination resulting from chemicals and oil spills are becoming very common news and these  alter the inter-particle behaviour of the soil, making it to lose its strength and deformability considerably and also become less permeable. This study focuses on the effects of contamination of sands with different grading size and particle shapes on its shear strength and its coefficient of permeability. Well graded and gap graded sand samples were used in the research. A simple statistical approach was used to define not only the particle size but also its shape distribution. Comparison of the shear strength of these sand samples were tested in an automated motorised direct shear apparatus under both dry and fully saturated conditions (with water and also with oil). The coefficient of permeability of the two sands under clean and contaminated conditions was obtained using a modified falling head permeability test. It was observed that the well graded sand which was submerged in oil apparently had the lowest peak shear strength values. However, a higher order of cohesion was apparent when the soil was contaminated with oil. Permeability was also an issue, as by virtue of its viscosity, the oil hindered the water seepage through the sand samples when compared with clean sands. However, it appeared that with more viscous liquid contaminants, the rate of water infiltration was notably higher. Permeability was also affected by the particle grading and shape distribution. The significant loss in strength and the tortuosity of water flow in the soils can cause major problems such as unwarranted floods and potential failures in civil engineering works. Therefore, the extent of the problem that is caused by oil contamination needs to be truly understood to minimize unwarranted construction risk.&nbsp

G-protein α-subunit (GPA1) regulates stress, nitrate and phosphate response, flavonoid biosynthesis, fruit/seed development and substantially shares GCR1 regulation in A. <i>thaliana</i>

Heterotrimeric G-proteins are implicated in several plant processes, but the mechanisms of signal-response coupling and the roles of G-protein coupled receptors in general and GCR1 in particular, remain poorly understood. We isolated a knock-out mutant of the Arabidopsis G-protein α subunit (gpa1-5) and analysed its transcriptome to understand the genomewide role of GPA1 and compared it with that of our similar analysis of a GCR1 mutant (Chakraborty et al. 2015, PLoS ONE 10(2):e0117819). We found 394 GPA1-regulated genes spanning 79 biological processes, including biotic and abiotic stresses, development, flavonoid biosynthesis, transcription factors, transporters and nitrate/phosphate responses. Many of them are either unknown or unclaimed explicitly in other published gpa1 mutant transcriptome analyses. A comparison of all known GPA1-regulated genes (including the above 394) with 350 GCR1-regulated genes revealed 114 common genes. This can be best explained by GCR1–GPA1 coupling, or by convergence of their independent signaling pathways. Though the common genes in our GPA1 and GCR1 mutant datasets constitute only 26 % of the GPA1-regulated and 30 % of the GCR1-responsive genes, they belong to nearly half of all the processes affected in both the mutants. Thus, GCR1 and GPA1 regulate not only some common genes, but also different genes belonging to the same processes to achieve similar outcomes. Overall, we validate some known and report many hitherto unknown roles of GPA1 in plants, including agronomically important ones such as biotic stress and nutrient response, and also provide compelling genetic evidence to revisit the role of GCR1 in G-protein signalling

Applicability of innovative building materials for wall structures to maximise the energy efficiency of buildings in Sri Lanka

The CO2 emission is increased globally and the building sector is playing as the major industry with approximately a half percent. The carbon emission of building materials is directly affected by the energy efficiency of the building. Energy has become a limited resource in the whole world and all the sectors try to minimise their consumption to overcome the energyrelated issues. Also, the selection of building materials for wall structure is playing a major role due to the highest surface area, to make a better indoor environment within the specified and required level of performance. As a result, Innovative Building Materials (IBMs) for wall structure has emerged. Even though it is currently practiced worldwide, it is not much familiar in Sri Lanka. Therefore, this research aims to identify the applicability of IBMs for wall structures of buildings in Sri Lanka. Primarily, a comprehensive literature survey was done. Three expert semi-structured interviews were carried out for the pilot survey as the foundation for data collection. Then, a questionnaire survey was done among building-related professionals and collected data were analysed using the Relative Important Index (RII). As the finding result, hollow blocks and EPS wall panels only familiarising in Sri Lanka. Finally, challenges and strategies to overcome when selecting IBMs for the wall were recognized

Mitigation Approach for Significant Causes of Contractor’s Delays in Construction Projects in Sri Lanka

The construction industry has a dynamic and complex environment. The successful completion of a construction project depends on various factors. Accordingly, construction delay is observed to happen in construction projects. It is highly affecting the construction sector and the economy of the country too. Although previous research studies identified the causes, effects, and mitigation methods separately, this study adopts a linked approach and directs to identify the effective applicable mitigation methods and their practices on each significant cause of delay in construction projects. Moreover, contractors are noted as one of the main sources of construction delay from the previous studies. Hence, this research aims to develop a framework to determine the applicable mitigation strategies and the practices of each mitigation strategy for each significant cause of contractor’s delays in construction projects in Sri Lanka. A mixed research approach was adopted to generate the research process. A literature review was conducted on construction delays, organizational and project management factors, and professional competency, mitigation strategies in delay management. The significant causes of delays and effective mitigation strategies were ranked through a questionnaire survey using a Likert scale. Project Managers and Quantity Surveyors in the Sri Lankan construction industry were selected in the ratio of 1:3 respectively for the interview as they are mostly engaged with delay management. Also, the respondents were limited to 68 and the collected data were analysed through the Relative Important Index (RII) method, to rank the significant causes and mitigation strategies. Then techniques and possible mitigation strategies were found through interviews and content analysis was used to analyse the data. The findings indicated that most of the contractor’s delays can be mitigated through applying proper mitigation strategies as effective management approaches in the construction projects such as effective project planning and schedules of construction works, maintain positive financial stability and well qualified and experienced professionals and staff, effective strategic planning, risk analysis, and management, selection of suitable sub-contractor and management and effective site management and supervision. In addition to that, inaccurate planning and scheduling of the project, financial dishonesty, poor procurement of construction materials, ineffective time management of contractors, and incompetence of management professionals and staffs were identified as the most significant contractor’s causes of delays in construction management. Keywords: Delays, Significant Causes, Mitigation, Construction Management, Construction Projects

The World Wide Web includes semantic

relationships of various types that exist among diverse entities. Extracting the associations that exist linking two entities is an vital step in various Web-related tasks such as information recovery (IR), information mining, and social network extraction. A supervised relation extraction system that is eligible to extract a particular relation type (source relation) might not perfectly remove a new type of a relation (target relation) for which it has not been trained. In these paper the projected method to adapt an existing relation extraction system to extract new relation types by crating, bi-partite graph structure between relation specific (RS) and relation independent (RI) patterns to represent fundamental relationship between them. Spectral clustering technique is used to minimize the normalize cut on the graph there by aligning the two types of patterns in lower dimensional space. Using these lower dimensional mapping crated from this process, project attribute vectors and train a relation classifier for turning over a numerous relation type to a given entity pair. Key words—Relation extraction, domain adaptation, spectral clustering, web mining, web content mining 1