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The move to a digital environment, where consumers may utilise, process, store, and transfer their data, has occurred in recent years. Furthermore, the quick and ongoing evolution of the Internet of Things (IoT) has resulted in a massive increase in the utilisation of digital signals and images. The Internet of Things (IoT) is a huge and varied network of connected devices, everyday objects, and gadgets that can communicate with one another over the Internet. The Internet of Things has a lot of potential to become a part of everyday life and improve people's lives. In recent decades, digital tattooing has been offered as a great way to handle numerous elements of IoT security. This technology works by embedding a digital signal called a digital tattoo into another digital signal called a host signal, which can be text, image, audio, or video. The principle of this approach is to detect changed pixels using the Cyclic Redundancy Check (CRC) code. The CRC is a data integrity check that is both powerful and simple to use. It is the most used method of mistake detection in telecommunications. For these reasons, it has been used in the context of the fragile tattoo to determine whether or not the picture has been altered. The experimental results show that the proposed schemes perform well in contrast to the existing scheme and use traditional evaluation criteria, proving that the new scheme is distinctive. [ABSTRACT FROM AUTHOR]

Transportation of incompatible items is a major problems for the logistic operators. Again today ceo-aware transportation is very much appreciated by the international bodies. In a transportation system, the realization of carbonemission can be incorporated as an important part of optimization. Now, the infrastructure of surface transportation is developed through the world including third world countries (like India, South-africa, Bangladesh, etc). In the present study, we incorporated the above problems and developed profit maximization of solid transportation problem with carbon emission under type-2 Fuzzy environment. So, a new concept to solve profit maximization transportation problem including sales revenue, purchase cost, transportation cost, procurement cost and carbon-emission cost has been proposed while transporting some goods from sources to destinations. In this model, two transportation schemes with carbon emission (WCE) and with out carbon-emission (WOCE) have been designed. We consider maximization of the total profit in these two models. In the model few parameters are treated as Gaussion fuzzy type-2 variable i.e. purchase cost, selling price, transportation and procurement cost. Critical Value (CV) based reduction help us to transform fuzzy type-2 to type-1 variable. To solve the problem in deterministic way we have to utilized Genetic Algorithm (GA). Finally, numerical results presented to establish the originality of the investigation. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic has a significant impact on the global economy and health. While the pandemic continues to cause casualties in millions, many countries have gone under lockdown. During this period, people have to stay within walls and become more addicted towards social networks. They express their emotions and sympathy via these online platforms. Thus, popular social media (Twitter and Facebook) have become rich sources of information for Opinion Mining and Sentiment Analysis on COVID‐19‐related issues. We have used Aspect Based Sentiment Analysis to anticipate the polarity of public opinion underlying different aspects from Twitter during lockdown and stepwise unlock phases. The goal of this study is to find the feelings of Indians about the lockdown initiative taken by the Government of India to stop the spread of Coronavirus. India‐specific COVID‐19 tweets have been annotated, for analysing the sentiment of common public. To classify the Twitter data set a deep learning model has been proposed which has achieved accuracies of 82.35% for Lockdown and 83.33% for Unlock data set. The suggested method outperforms many of the contemporary approaches (long short‐term memory, Bi‐directional long short‐term memory, Gated Recurrent Unit etc.). This study highlights the public sentiment on lockdown and stepwise unlocks, imposed by the Indian Government on various aspects during the Corona outburst. [ABSTRACT FROM AUTHOR]

Modern research in image watermarking focuses not only on security but also increasing the payload without having any detectable signature within the media. In this paper, a new Discrete Cosine Transform (DCT)-based image watermarking scheme has been proposed using Cellular Automata (CA). Here, a color cover image is split into three color channels: Red, Green and Blue. Then, DCT is applied on 8 x 8 non-overlapping blocks of each channel followed by a ZigZag scanning. Before embedding, the watermark is encrypted by applying CA rule-15 to make it more secure and robust. The encrypted watermark logo is embedded through DCT coefficients modification using CA rule-340 and mapping table. The proposed scheme is compared with existing state-of-the-art algorithms with respect to embedding capacity, imperceptibility and robustness. Results of the simulation show good imperceptibility measured in terms of Peak Signal-to-Noise Ratio (PSNR) with an average value of 54 dB and simultaneously having high payload of 1.48 bpp. Experimental results under different standard attacks show the superiority of the proposed algorithm as compared with other schemes in the field of image watermarking. [ABSTRACT FROM AUTHOR]

The basic philosophy behind RED is to prevent congestion. When the average queue length exceeds the minimum threshold, packets are randomly dropped, or the explicit congestion notification bit is marked. Since network requirements differ significantly, it is not an optimal approach to establish RED parameters with constant value. There is a new algorithm we are proposing called Critical Point on Target Queue (AQM-RED-CPTQ), provide greater congestion management over the network while also preserving the value of RED. To overcome the problem in RED without changing queue weight parameter, we have proposed few models to control the congestion by introducing range parameter with probability and control mechanism which will belong between minimum and maximum threshold. The current queue size is controlled together with average queue size. A new range variable has been introduced to improve the performance of priority queue of existing RED based algorithm which improves the overall performance of networks. For each packet, minimum and maximum threshold has been updated and dropped with probability (Pa) for a special condition. Instead of multiplicative increase and decrease the maximum probability, the scheme uses additive-increase and multiplicative-decrease. Once the AVG queue length is close to the minimum threshold value, our approach automatically sets queue parameter according to queue conditions and handles queuing delay and improve throughput. The simulated results proof that our approaches are better than RED in terms of throughput, end to end delay, packet delivery ratio and goodput. [ABSTRACT FROM AUTHOR]

Due to the rapid growth of internet technology and the advent of various image processing tools, people started using digital media for hidden communication to protect valuable information which is important for multimedia commercials, health-care, medical and defense applications. On the other hand, image authentication and tamper detection are essential, especially when it is utilized for evidence of legal action. In this paper, a weighted matrix based steganographic scheme has been designed for highly compressed (Quality Factor (QF) 40) color image through discrete cosine transform (DCT) to maintain a good balance between payload and imperceptibility. Here, the AC components are collected from (8 × 8) quantized DCT coefficient matrices of YCbCr channel. Then, a series of (3 × 3) original matrices are formed to hide secret data. The collection of AC components is controlled by 128 bits shared secret key. A predetermined weighted matrix is employed to select the embedding position within a (3 × 3) coefficient matrix of a cover image through the sum of the entry-wise multiplication operation. The proposed scheme provides good embedding capacity with the high visual quality compared to existing state-of-the-art methods. Finally, different steganographic analysis and attacks are carried out to observe its imperceptibility and robustness. [ABSTRACT FROM AUTHOR]

An innovative, real-life solid transportation problem is explained in a non-linear form. As in real life, the total transportation cost depends on the procurement process or type of the items and the distance of transportation. Besides, an impurity constraint is considered here. The proposed model is formed with fuzzy imprecise nature. Such an interesting model is optimised through two different fuzzy programming techniques and fractional programming methods, using LINGO-14.0 tools followed by the generalized gradient method. Finally, the model is discussed concerning these two different methods. [ABSTRACT FROM AUTHOR]

In this study, the authors have employed a special type of periodic boundary CA (called CA attractor) for image authentication and tamper detection through the watermarking scheme. Authentication code (AC) has been generated utilising secure hash algorithm‐512 on watermark image. The cover image (CI) is subdivided into four sub‐sampled interpolated image, where AC and secret watermark bits are embedded to enhance capacity, quality and security. At the receiver end, the secret watermark information and CI are successfully extracted without any distortion from four sub‐sampled watermarked images (WIs). Additionally, the proposed scheme can successfully determine any type of distortion within the WI that may be possible to occur by various steganographic attacks. Indeed, better results in terms of capacity and quality are experienced after having compared with similar schemes in vogue. The intended outcome brought into the limelight some remarkable sublime characteristics in the field of image authentication and ownership identification without which the technology life is stunted. Innumerable government and private sector facet including health care, commercial security, defence and intellectual property rights are immensely benefited from this scheme. [ABSTRACT FROM AUTHOR]

Till date, data hiding techniques using interpolated grayscale image were limited embedding capacity and visual quality. In this investigation, we have proposed a weighted matrix-based reversible data hiding scheme using the color image which provides image authentication and tampered detection. Here, we decomposed the original image into RGB color components and partitioned into pixel blocks then we performed the sum of entry-wise multiplication operations using modified weighted matrix to embed the secret data repeatedly in each block. The data embedding locations are stored within an index file to enhance security, increase data hiding capacity, gain good visual quality, achieve reversibility, and confirm authenticity. The proposed data hiding scheme also improved both data embedding capacity up to 8.03 (bpp) and visual quality PSNR 50.03(dB). Finally, the scheme is compared with other existing methods and achieve a reasonably better performance in terms of visual quality and payload. Our scheme has been evaluated through various steganographic analyses and observed that the scheme is secure and robust against various attacks. The Proposed scheme successfully performed tampered detection and authentication but may partially recovered original cover image from tampered stego image. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new dual-image based reversible data hiding scheme through (7,4) Hamming code (RDHHC) using shared secret key. A block of seven pixels are collected from cover image and copied into two arrays then it is adjusted redundant Least Significant Bits (LSBs) using odd parity such that any error creation is encountered at the sender end and recovered at the receiver end. Before data embedding, we first complement the bit at shared secret position. After that, secret message bit is embedded by error creation caused by tamper in any suitable position except secret position and that error is detected as well as corrected at the receiver end using Hamming error correcting code. One shared secret position κ and one shared secret key ξ help to perform data embedding, data extraction and recovery of the original image. The secret data and original cover image are successfully recovered at the receiver end from dual stego image. Finally, we compare our scheme with other state-of-the-art methods and obtain reasonably better performance in terms of PSNR. [ABSTRACT FROM AUTHOR]

In this paper, we propose a partial reversible data hiding scheme using (7,4) Hamming code (PRDHHC) with secret position ( κ). In this scheme, we partition the original cover image into (7 × 7) pixel block and adjust redundant LSB bits of each row using odd parity. Then we calculate secret position κ = ( δ mod 7) + 1, where δ is a shared secret key. The bit at position κ and a suitable location for hidden message bit is modified through error creation caused by tamper in each row of the selected block. For the next row, the κ is updated by the data embedding position ( ω) of the previous row. We repeat this process to embed secret message bits within the selected block. For each new block, the κ is updated by κ = ( κ × δ × ω) mod 7 + 1, where i = 0, 1, 2, 3, . . . , number of blocks. At the receiver end, we complement the bit at position κ then retrieve the secret message bit by applying Hamming error correcting code. The extraction process will be stopped when we find continuous no error within stego image. The propose PRDHHC scheme extract the hidden message successfully and recover hamming adjusted cover image by complement bits at both the κ and ω positions but can not recover original cover image, that is to say, our scheme is partial reversible. Finally, we compared our scheme with other state-of-the-art methods and obtained reasonably better performance in terms of visual quality (measured by PSNR). Also we analyze our generated stego image using some steganalysis techniques which give promising results. [ABSTRACT FROM AUTHOR]

We conduct different approaches to find out the access strategies and mental representation of semantic word using cross-modal experiment of priming in Bangla Language. We indicate that the words are semantically related triggering the priming effect. We observed that the word recognition time in Bangla language is strongly affected by semantically similar words. Also, it is noted that the average semantically related prime-target word pairs have intermediate priming and semantically unintelligible prime-target word pairs have either less or no priming. Our result appears to ensure existing word recognition and interactive methods where semantic trigger may regulate the processing of words. [ABSTRACT FROM AUTHOR]

In 2018, Tseng et al. proposed a dual-image reversible embedding method based on the modified Least Significant Bit matching (LSB matching) method. This method improved on the dual-image LSB matching method proposed by Lu et al. In Lu et al.'s scheme, there are seven situations that cannot be restored and need to be modified. Furthermore, the scheme uses two pixels to conceal four secret bits. The maximum modification of each pixel, in Lu et al.'s scheme, is two. To decrease the modification, Tseng et al. use one pixel to embed two secret bits and allow the maximum modification to decrease from two to one such that the image quality can be improved. This study enhances Tseng et al.'s method by re-encoding the modified rule table based on the probability of each hiding combination. The scheme analyzes the frequency occurrence of each combination and sets the lowest modified codes to the highest frequency case to significantly reduce the amount of modification. Experimental results show that better image quality is obtained using our method under the same amount of hiding payload. [ABSTRACT FROM AUTHOR]

Very often items that are substitutable and complementary to each other are sent from suppliers to retailers for business. In this paper, for these types of items, fixed charge (FC) four-dimensional (4D) multi-item transportation problems (MITPs) are formulated with both space and budget constraints under crisp and rough environments. These items are damageable/breakable. The rates of damageability of the items depend on the quantity transported and the distance of travel i.e., path. A fixed charge is applied to each of the routes (independent of items). There are some depots/warehouses (origins) from which the items are transported to the sales counters (destinations) through different conveyances and routes. In proposed FC 4D-MITP models, per unit selling prices, per unit purchasing prices, per unit transportation expenditures, fixed charges, availabilities at the sources, demands at the destinations, conveyance capacities, total available space and budget are expressed by rough intervals, where the transported items are substitutable and complementary in nature. In this business, the demands for the items at the destinations are directly related to their substitutability and complementary natures and prices. The suggested rough model is converted into a deterministic one using lower and upper approximation intervals following Hamzehee et al. as well as Expected Value Techniques. The converted model is optimized through the Generalized Reduced Gradient (GRG) techniques using LINGO 14 software. Finally, numerical examples are presented to illustrate the preciseness of the proposed model. As particular cases, different models such as 2D, 3D FCMITPs for two substitute items, one item with its complement and two non substitute non complementary items are derived and results are presented. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has a significant impact on the global economy and health. While the pandemic continues to cause casualties in millions, many countries have gone under lockdown. During this period, people have to stay within walls and become more addicted towards social networks. They express their emotions and sympathy via these online platforms. Thus, popular social media (Twitter and Facebook) have become rich sources of information for Opinion Mining and Sentiment Analysis on COVID-19-related issues. We have used Aspect Based Sentiment Analysis to anticipate the polarity of public opinion underlying different aspects from Twitter during lockdown and stepwise unlock phases. The goal of this study is to find the feelings of Indians about the lockdown initiative taken by the Government of India to stop the spread of Coronavirus. India-specific COVID-19 tweets have been annotated, for analysing the sentiment of common public. To classify the Twitter data set a deep learning model has been proposed which has achieved accuracies of 82.35% for Lockdown and 83.33% for Unlock data set. The suggested method outperforms many of the contemporary approaches (long short-term memory, Bi-directional long short-term memory, Gated Recurrent Unit etc.). This study highlights the public sentiment on lockdown and stepwise unlocks, imposed by the Indian Government on various aspects during the Corona outburst., Competing Interests: The author declares that they have no conflict of interest., (© 2022 The Authors. CAAI Transactions on Intelligence Technology published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology and Chongqing University of Technology.)