Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries

With advanced image journaling tools, one can easily alter the semantic meaning of an image by exploiting certain manipulation techniques such as copy-clone, object splicing, and removal, which mislead the viewers. In contrast, the identification of these manipulations becomes a very challenging task as manipulated regions are not visually apparent. This paper proposes a high-confidence manipulation localization architecture which utilizes resampling features, Long-Short Term Memory (LSTM) cells, and encoder-decoder network to segment out manipulated regions from non-manipulated ones. Resampling features are used to capture artifacts like JPEG quality loss, upsampling, downsampling, rotation, and shearing. The proposed network exploits larger receptive fields (spatial maps) and frequency domain correlation to analyze the discriminative characteristics between manipulated and non-manipulated regions by incorporating encoder and LSTM network. Finally, decoder network learns the mapping from low-resolution feature maps to pixel-wise predictions for image tamper localization. With predicted mask provided by final layer (softmax) of the proposed architecture, end-to-end training is performed to learn the network parameters through back-propagation using ground-truth masks. Furthermore, a large image splicing dataset is introduced to guide the training process. The proposed method is capable of localizing image manipulations at pixel level with high precision, which is demonstrated through rigorous experimentation on three diverse datasets

Productivity, Energy Use Efficiency and Economics of Organic Scented Rice Cultivation in Sub-Humid Agroecosystem

The increasing demand for organic cereals especially indigenous scented rice varieties in the recent years has peaked farmers’ interest towards its organic production. However, the threat of crop loss under organic cultivation has been holding back large scale initiatives. Inhana Rational Farming (IRF) Technology has come up as a promising organic package of practice towards mitigating this drawback of organic production that too at an affordable economics. The present study was conducted to generate scientific information regarding organic scented rice cultivation (Oryza sativa var. ‘Gobindobhog’) utilizing this organic POP in terms of productivity, energy use efficiency and economics. The yield of scented rice cultivated using organic POP was found to be 18% higher than the conventionally grown ones. In terms of energy use efficiency as well, organic POP was calculated to be more efficient signifying the role of organic practice in sustainable agriculture. Net profitability of organic paddy increased up to 17% with a minimum premium price of 25%. This increased higher income opportunity from same unit of land was an added benefit apart from improved soil quality in general; under organic management

Modified Bethe-Weizsacker mass formula with isotonic shift and new driplines

Nuclear masses are calculated using the modified Bethe-Weizsacker mass formula in which the isotonic shifts have been incorporated. The results are compared with the improved liquid drop model with isotonic shift. Mass excesses predicted by this method compares well with the microscopic-macroscopic model while being much more simple. The neutron and proton drip lines have been predicted using this modified Bethe-Weizsacker mass formula with isotonic shifts.Comment: 9 pages including 2 figure

An Innovative Approach towards Organic Management of Late Blight in Potato under Inhana Rational Farming Technology

Successful disease combat of crop can ensure healthy return for the farmers. However, limitation in the conventional disease management approach, especially in case of late blight of potato was the background for the present study that aimed at bringing forth an alternative pathway for effective disease management. Integrated farming under Inhana rational farming technology (IRF) was adopted as an alternate protocol. The approach works on the philosophy of the Trophobiosis theory that advocates pest/disease management through plant physiology management. The study was done in two major potato growing zones of West Bengal taking two major potato varieties i.e., Kufri Jyoti and Kufri Chandramukhi. Late blight incidence varied from 2.82 to 7.91% in the IRF integrated farming plots whereas it was relatively higher varying between 49.44 and 66.67% in case of plots receiving conventional treatment. The finding remained consistent irrespective of the study area and potato variety. Ineffective disease management influenced the net loss of 2400 kg potato ha-1 under conventional farming. Percent disease index (PDI) was significantly high in case of conventional farmers’ practice (11.37 to 32.81). However, lower values (PDI varies 1.45 to 2.59) under IRF integrated farming showed the effectiveness of its disease management schedule. Efficient disease management under IRF technology might have been brought about through a focused approach towards activation of plant physiology in order to re-instate plants’ structural and biochemical defense mechanisms. The findings encourage the possibility of economically sustainable potato production under the changing climatic patterns

Boosting Image Forgery Detection using Resampling Features and Copy-move analysis

Realistic image forgeries involve a combination of splicing, resampling, cloning, region removal and other methods. While resampling detection algorithms are effective in detecting splicing and resampling, copy-move detection algorithms excel in detecting cloning and region removal. In this paper, we combine these complementary approaches in a way that boosts the overall accuracy of image manipulation detection. We use the copy-move detection method as a pre-filtering step and pass those images that are classified as untampered to a deep learning based resampling detection framework. Experimental results on various datasets including the 2017 NIST Nimble Challenge Evaluation dataset comprising nearly 10,000 pristine and tampered images shows that there is a consistent increase of 8%-10% in detection rates, when copy-move algorithm is combined with different resampling detection algorithms

Evaluation of an Organic Package of Practice Towards Green Gram Cultivation and Assessment of its Effectiveness in Terms of Crop Sustainability and Soil Quality Development

Restoration of soil has been identified as the option; to ensure crop sustainability. However, as per Trophobiosis Theory of French Scientist F. Chaboussou, focus on development of healthy plants is necessary to abate pest and disease invasion so as to ensure sustained crop performance, even under unfavorable environmental conditions. The present study, in randomized block design with green gram as test crop; was undertaken in Krishi Vigyan Kendra (Howrah, West Bengal) to evaluate the effectiveness of Inhana Rational Farming (IRF) Technology towards crop yield and soil quality development under different sustainable models viz. organic cultivation, integrated soil with organic crop management and non- chemical crop management; as compared to conventional farming practice. Highest yield was recorded under organic (933 kg ha-1) followed by integrated (921 kg ha-1) and non- chemical plant management (902 kg ha-1). The results were well corroborated with the plant development index obtained under these treatments. Favorable trend of soil quality under sustainable models especially in terms of microbial properties indicated the role of quality compost towards speedy rejuvenation of soil dynamics. The study indicated that reduction of synthetic fertilizers and qualitative management of soil is essential to restrict yield decline. However, plant management shall be prerequisite for ensuring crop sustainability without any time lag and under the changing climatic patterns. In this respect the potential of IRF Technology has been well accounted

MeTA: Multi-source Test Time Adaptation

Test time adaptation is the process of adapting, in an unsupervised manner, a pre-trained source model to each incoming batch of the test data (i.e., without requiring a substantial portion of the test data to be available, as in traditional domain adaptation) and without access to the source data. Since it works with each batch of test data, it is well-suited for dynamic environments where decisions need to be made as the data is streaming in. Current test time adaptation methods are primarily focused on a single source model. We propose the first completely unsupervised Multi-source Test Time Adaptation (MeTA) framework that handles multiple source models and optimally combines them to adapt to the test data. MeTA has two distinguishing features. First, it efficiently obtains the optimal combination weights to combine the source models to adapt to the test data distribution. Second, it identifies which of the source model parameters to update so that only the model which is most correlated to the target data is adapted, leaving the less correlated ones untouched; this mitigates the issue of "forgetting" the source model parameters by focusing only on the source model that exhibits the strongest correlation with the test batch distribution. Experiments on diverse datasets demonstrate that the combination of multiple source models does at least as well as the best source (with hindsight knowledge), and performance does not degrade as the test data distribution changes over time (robust to forgetting).Comment: Under Revie

Origin of Ferroelectricity in Orthorhombic LuFeO3_3

We demonstrate that small but finite ferroelectric polarization ($\sim$0.01 $\mu$C/cm$^2$) emerges in orthorhombic LuFeO$_3$ ($Pnma$) at $T_N$ ($\sim$600 K) because of commensurate (k = 0) and collinear magnetic structure. The synchrotron x-ray and neutron diffraction data suggest that the polarization could originate from enhanced bond covalency together with subtle contribution from lattice. The theoretical calculations indicate enhancement of bond covalency as well as the possibility of structural transition to the polar $Pna2_1$ phase below $T_N$. The $Pna2_1$ phase, in fact, is found to be energetically favorable below $T_N$ in orthorhombic LuFeO$_3$ ($albeit$ with very small energy difference) than in isostructural and nonferroelectric LaFeO$_3$ or NdFeO$_3$. Application of electric field induces finite piezostriction in LuFeO$_3$ via electrostriction resulting in clear domain contrast images in piezoresponse force microscopy.Comment: 12 pages, 8 figure