A New Robust Multi focus image fusion Method

In today's digital era, multi focus picture fusion is a critical problem in the field of computational image processing. In the field of fusion information, multi-focus picture fusion has emerged as a significant research subject. The primary objective of multi focus image fusion is to merge graphical information from several images with various focus points into a single image with no information loss. We provide a robust image fusion method that can combine two or more degraded input photos into a single clear resulting output image with additional detailed information about the fused input images. The targeted item from each of the input photographs is combined to create a secondary image output. The action level quantities and the fusion rule are two key components of picture fusion, as is widely acknowledged. The activity level values are essentially implemented in either the "spatial domain" or the "transform domain" in most common fusion methods, such as wavelet. The brightness information computed from various source photos is compared to the laws developed to produce brightness / focus maps by using local filters to extract high-frequency characteristics. As a result, the focus map provides integrated clarity information, which is useful for a variety of Multi focus picture fusion problems. Image fusion with several modalities, for example. Completing these two jobs, on the other hand. As a consequence, we offer a strategy for achieving good fusion performance in this study paper. A Convolutional Neural Network (CNN) was trained on both high-quality and blurred picture patches to represent the mapping. The main advantage of this idea is that it can create a CNN model that can provide both the Activity level Measurement" and the Fusion rule, overcoming the limitations of previous fusion procedures. Multi focus image fusion is demonstrated using microscopic images, medical imaging, computer visualization, and Image information improvement is also a benefit of multi-focus image fusion. Greater precision is necessary in terms of target detection and identification. Face recognition" and a more compact work load, as well as enhanced system consistency, are among the new features

Impulse Noise Removal Using Soft-computing

Image restoration has become a powerful domain now a days. In numerous real life applications Image restoration is important field because where image quality matters it existed like astronomical imaging, defense application, medical imaging and security systems. In real life applications normally image quality disturbed due to image acquisition problems like satellite system images cannot get statically as source and object both moving so noise occurring. Image restoration process involves to deal with that corrupted image. Degradation model used to train filtering techniques for both detection and removal of noise phase. This degeneration is usually the result of excess scar or noise. Standard impulse noise injection techniques are used for standard images. Early noise removal techniques perform better for simple kind of noise but have some deficiencies somewhere in sense of detection or removal process, so our focus is on soft computing techniques non classic algorithmic approach and using (ANN) artificial neural networks. These Fuzzy rules-based techniques performs better than traditional filtering techniques in sense of edge preservation

Salinity, livelihood and agricultural productivity: A case of Hafizabad District

Background: Soil salinity; concentration and or accumulation of salts may pose severe risk on soil productivity and in turn concerned population and farmers. Salt-influenced lands in Pakistan were spread over 6.63 million hectare which is diminishing the agrarian profitability. This study will explore the impact of salinity on livelihood of farmers in district Hafizabad.Methods: Data of 192 small, medium and large farmers was collected from four randomly selected villages of salinity affected area of Hafizabad district of Punjab province of Pakistan using multistage probability sampling technique. SPSS version 21.0 was utilized to analyze the data for generating logical results.Results: Farmers belonging to saline area communities were characterized on the basis of their education, experience, cultivated area, and method of irrigation and technological adoption for analyzing their livelihood typologies. Average yield of wheat was found to be 26mnds/acre, while marketable surplus was high for large farmers due to ownership of more area. Livelihood typologies were derived mainly from on-farm and off-farm income activities of the farmers. Agriculture farm earning in the saline area was estimated as Rs. 10 to 12 thousand per acre. Contribution of off-farm income in household cash flows was estimated in 79% of small, medium and large farmer as less than 15000 indicating the dependency status of the households.Conclusion: Major livelihood source in Salt-affected soils was still agricultural cash inflows beside their contribution to the food basket of consumers. Farmers were in favour of provision of farming inputs on subsidized rates i.e. lime and gypsum as a poverty alleviation strategy in the area for positive promotion of sharing culture with public sector.    Keywords: Salinity; Livelihood; Productivity; Farming experience; Farm size

Design of a CMOS Differential Operational Transresistance Amplifier in 90 nm CMOS Technology

In this paper, a CMOS differential operational transresistance amplifier (OTRA) is presented. The amplifier is designed and implemented in a standard umc90-nm CMOS technology. The differential OTRA provides wider bandwidth at high gain. It also shows much better rise and fall time and exhibits a very good input current dynamic range of 50 to 50 μA. The OTRA can be used in many analog VLSI applications. The presented amplifier has high gain bandwidth product of 617.6 THz Ω. The total power dissipation of the presented amplifier is also very low and it is 0.21 mW

Impulse Noise Removal Using Soft-computing

Image restoration has become a powerful domain now a days. In numerous real life applications Image restoration is important field because where image quality matters it existed like astronomical imaging, defense application, medical imaging and security systems. In real life applications normally image quality disturbed due to image acquisition problems like satellite system images cannot get statically as source and object both moving so noise occurring. Image restoration process involves to deal with that corrupted image. Degradation model used to train filtering techniques for both detection and removal of noise phase. This degeneration is usually the result of excess scar or noise. Standard impulse noise injection techniques are used for standard images. Early noise removal techniques perform better for simple kind of noise but have some deficiencies somewhere in sense of detection or removal process, so our focus is on soft computing techniques non classic algorithmic approach and using (ANN) artificial neural networks. These Fuzzy rules-based techniques performs better than traditional filtering techniques in sense of edge preservation

Application of Nanofluids for Thermal Management of Photovoltaic Modules: A Review

Mounting temperature impedes the conversion efficiency of photovoltaic systems. Studies have shown drastic efficiency escalation of PV modules, if cooled by nanofluids. Ability of nanofluids to supplement the efficiency improvement of PV cells has sought attention of researchers. This chapter presents the magnitude of improved efficiency found by different researchers due to the cooling via nanofluids. The effect of factors (such as, nanoparticle size, nanofluid concentration, flowrate of nanofluid and geometry of channel containing nanofluid) influencing the efficiency of PV systems has been discussed. Collective results of different researchers indicate that the efficiency of the PV/T systems (using nanofluids as coolant) increases with increasing flowrate. Efficiency of these systems increases with increasing concentration of nanofluid up to a certain amount, but as the concentration gets above this certain value, the efficiency tends to decline due to agglomeration/clustering of nanoparticles. Pertaining to the most recent studies, stability of nanoparticles is still the major unresolved issue, hindering the commercial scale application of nanofluids for the cooling of PV panels. Eventually, the environmental and economic advantages of these systems are presented

Titanium Dioxide: Advancements and Thermal Applications

Distinctive characteristics of titanium dioxide such as high refractive index, overwhelmingly high melting and boiling point, high toughness, and hardness, photocatalytic nature, ability to absorb or reflect UV-rays, DeNox catalyst, nontoxicity, inert behavior, etc., have brought about the massive use of TiO2 in a variety of conventional as well as advanced engineering applications. Broad commercial utilization of titanium dioxide in products including paints, anti-air pollutants, cosmetics, skincare and sunblock, pharmaceuticals, surface protection, building energy-saving, etc., accounts for its multibillion dollars market worldwide. Titanium dioxide carries unique thermal and optical characteristics and therefore has gained significance as a potential candidate for advanced applications such as clean hydrogen fuel harvesting, photoelectric solar panels, photothermal conversion, treatment of exhaust gases from combustion engines and power plants, thermal energy storage, thermal management of electronic devices and photovoltaics, and nano-thermofluids. This chapter presents a brief insight into some of the noteworthy characteristics and a comprehensive overview of advanced thermal applications of TiO2

Helicobacter pylori infection among type 2 diabetics: a case control study

Background: Helicobacter pylori infection has been associated with hyperglycemia among type 2 diabetics. The objective of this study was to compare the H. pylori infection frequency in diabetic and non-diabetic patients.Methods: This case-control study was done at Al-Tibri Medical College and Hospital from May 2019 to August 2019. After written and informed consent, patients between 18-75 years with epigastric burning, dyspepsia, regurgitation were included and with history of eradication therapy, antibiotic or NSAID use in the last 6 months or surgery of upper GI tract months were excluded. Type 2 diabetics were placed in one group and non-diabetic individuals in another. Both groups were compared for presence of H. pylori infection. Data was analysed using SPSS. Demographic variables included age, gender and status of H. pylori infection. Quantitative data was expressed as frequency and percentages. Chi-square test was applied to test for significance keeping p-value of <0.05 statistically significant.Results: From 480 patients, 355 patients showed positive H. pylori, among them 282 were diabetic and 73 non-diabetic (p-value <0.001). Amongst the 355 diabetics, 55% were male Among 73 non-diabetics, 64% were male. All the patients in the study had dyspeptic symptoms and complained of dyspepsia, epigastric burning and regurgitation.Conclusions: A substantial relationship between H. pylori infection among type 2 diabetes mellitus patients was observed compared to non-diabetics. As a result, diabetic patients having active dyspeptic symptoms should undergo further confirmatory tests for diagnosing H. pylori infection

Scalable heterogeneous nodes deployment algorithm for monitoring of underwater pipeline

Underwater Wireless Linear Sensor Networks (UW-LSNs) possess unique features as compared to the terrestrial sensor networks for pipeline monitoring. Other than long propagation delays for long range underwater pipelines and high error probability, homogeneous node deployment also makes it harder to detect and locate the pipeline leakage efficiently. Determining the exact leakage position with minimum delay stays a major issue where pipelines length is extremely long and expensive to deploy many underwater sensors. In order to tackle the problem of large scale pipeline monitoring and unreliable underwater link quality, many algorithms have been proposed and even some of them provided good solutions for these issues but the scalable nodes deployments still need focus and prime attention. In order to handle the problem of nodes deployment, we therefore propose a dynamic nodes deployment algorithm where every node in the network is assigned location in a quick and efficient way without needing any localization scheme. It provides an option to handle the heterogeneous types of nodes, distribute topology and mechanism in which new nodes are easily added to the network without affecting the existing network performance. The proposed distributed topology algorithm divides the pipeline length into segments and sub-segments in order to manage the higher delay issue. Normally nodes are randomly deployed for the long range underwater pipeline inspection yet it requires some proper dynamic nodes deployment algorithm assigning unique position to each nod