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Multimodal Emotion Recognition in HumanComputer Interaction Using MFF-CNN
The rise of technology in the digital era has amplified the importance of understanding human emotions in enhancing humancomputer interactions. Traditional interfaces, mainly focused on logical tasks, often miss the nuances of human emotion, creating a gap between human users and technology. Addressing this gap, the development of the HumanComputer Interface for emotional intelligence uses advanced algorithms and deep learning models to accurately recognize emotions from various cues like facial expressions, voice, and written text. This paper presented a significant approach for emotion detection in HCI and the challenges faced in capturing genuine emotional responses. Historically, the emphasis in HCI design was on operational tasks, neglecting emotional nuances. However, the tide is changing toward embedding emotional intelligence into these interfaces, leading to enhanced user experiences. This research introduces the MFF-CNN, a neural network model combining both textual and visual data for accurate emotion detection. Through sophisticated algorithms and the integration of advanced machine learning techniques, this paper presents a refined approach to emotion detection in HCI, supported by a comprehensive review of related works and a detailed methodology. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Multimodal Early Fusion Strategy Based on Deep Learning Methods for Cervical Cancer Identification
It is essential to enhance the accuracy of automatic cervical cancer diagnosis by combining multiple forms of information obtained from a patients primary examination. However, existing multimodal systems are not very effective in detecting correlations between different types of data, leading to low sensitivity but high specificity. This study introduces a deep learning system for automatic diagnosis of cervical cancer by incorporating multiple sources of data. First, a convolutional neural network (CNN) to transform the image database to a vector that can be combined with non-image datasets is used. Subsequently, an investigation of jointly the nonlinear connections between all image and non-image data in a deep neural network is performed. Proposed deep learning-based method creates a unified system that takes advantage of both image and non-image data. It achieves an impressive 89.32% sensitivity at 91.6% specificity when diagnosing cervical intraepithelial neoplasia on a wide-ranging dataset. This result is far superior to any single-source system or prior multimodal approaches. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Multimodal Classification on PET/CT Image Fusion for Lung Cancer: A Comprehensive Survey
Medical image fusion has become essential for accurate diagnosis. For example, a lung cancer diagnosis is currently conducted with the help of multimodality image fusion to find anatomical and functional information about the tumor and metabolic measurements to identify the lung cancer stage and metastatic information of the disease. Generally, the success of multimodality imaging for lung cancer diagnosis is due to the combination of PET and CT imaging advantages while minimizing their respective limitations. However, medical image fusion involves the registration of two different modalities, which is time-consuming and technically challenging, and it is a cause of concern in a clinical setting. Therefore, the paper's main objective is to identify the most efficient medical image fusion techniques and the recent advances by conducting a collective survey. In addition, the study delves into the impact of deep learning techniques for image fusion and their effectiveness in automating the image fusion procedure with better image quality while preserving essential clinical information. The Electrochemical Society -
Multimedia Enhanced Teaching and Learning with Special Reference to Developing Cognitive Skills
Indian Streams Research Journal, Vol-3 (7), pp. 25-28. ISSN-2230-7850 -
Multilingual Sentiment Analysis of YouTube Live Stream using Machine Translation and Transformer in NLP
YouTube has become one of the all-inclusive video streaming sources on the internet. Today, the news is streamed on YouTube, marketing of a product is done live on YouTube and it has become a platform for one of the biggest PR producers for companies. Various companies have proposed an optimized way of understanding and getting the opinions of the viewers from YouTube live chat and find the best possible way to provide relevant and informative content to boost the business strategy. This study uses Natural Language Processing (NLP) based approach along with NLP transformers to classify and analyses the sentiment. 2022 IEEE. -
Multilevel Security and Dual OTP System for Online Transaction Against Attacks
In the current internet technology, most of the transactions to banking system are effective through online transaction. Predominantly all these e-transactions are done through e-commerce web sites with the help of credit/debit cards, net banking and lot of other payable apps. So, every online transaction is prone to vulnerable attacks by the fraudulent websites and intruders in the network. As there are many security measures incorporated against security vulnerabilities, network thieves are smart enough to retrieve the passwords and break other security mechanisms. At present situation of digital world, we need to design a secured online transaction system for banking using multilevel encryption of blowfish and AES algorithms incorporated with dual OTP technique. The performance of the proposed methodology is analyzed with respect to number of bytes encrypted per unit time and we conclude that the multilevel encryption provides better security system with faster encryption standards than the ones that are currently in use. 2019 IEEE. -
Multilevel Quantum Inspired Fractional Order Ant Colony Optimization for Automatic Clustering of Hyperspectral Images
Hyperspectral images contain a wide variety of information, varying from relatively large regions to smaller manmade buildings, roads and others. Automatic clustering of various regions in such images is a tedious task. A multilevel quantum inspired fractional order ant colony optimization algorithm is proposed in this paper for automatic clustering of hyperspectral images. Application of fractional order pheromone updation technique in the proposed algorithm produces more accurate results. Moreover, the quantum inspired version of the algorithm produces results faster than its classical counterpart. A new band fusion technique, applying principal component analysis and adaptive subspace decomposition, is successfully proposed for the pre-processing of hyperspectral images. Score Function is used as the fitness function and K-Harmonic Means is used to determine the clusters. The proposed algorithm is implemented on the Xuzhou HYSPEX dataset and compared with classical Ant Colony Optimization and fractional order Ant Colony Optimization algorithms. Furthermore, the performance of each method is validated by peak signal-to-noise ratio which clearly indicates better segmentation in the proposed algorithm. The Kruskal-Wallis test is also conducted along with box plot, which establishes that the proposed algorithm performs better when compared with other algorithms. 2020 IEEE. -
Multilayer flow and heat transport of nanoliquids with nonlinear Boussinesq approximation and viscous heating using differential transform method
Multilayer fluid flow models are significant in various applications, namely, cooling electronic systems, solar thermal systems, and nuclear reactors. The density of a fluid fluctuates nonlinearly due to large temperature difference circumstances in thermal systems. Thus, the linear Boussinesq approximation is no longer relevant. Therefore, this article describes a multilayer flow of nanoliquids in the presence of nonlinear Boussinesq approximation. The hybrid nanoliquid layer is sandwiched between two nanoliquid layers. The single-phase khanafer-vafai-lightstone model is implemented to simulate the nanoliquids. The quadratic density temperature fluctuation and viscous heating are taken into account. The temperature and velocity across the interface are assumed to be continuous. The equations that govern the problem are solved analytically by using the differential transformation method. The results show that the presence of a hybrid nanoliquid layer affects the velocity and heat transfer properties of the nanofluid flow. Hybrid nanofluid can be used to achieve the desired multilayer flow properties of a nanofluid and its heat transfer properties. Further, the quadratic convection aspect increases the velocity distributions. 2021 Wiley Periodicals LLC -
Multilayer classification based Alzheimer's disease detection
Hippocampus, a small brain region plays a role in the initiation of the neurodegenerative pathways that leadto Alzheimer's. Humans with MCI are probable to develop Alzheimer's disorder. Hippocampal volume has been proven to indicate which patients with MCI will later develop Alzheimer's. Brain degeneration in MCI progresses over time and varies from person - to - person, making early detection difficult. Magnetic resonance imaging is a tool in diagnosing clinically suspected Alzheimer's disease. Information about the historical development of structural changes as the disease progresses from preclinical to overt stages is shaping understanding of the disease, and also guides diagnosis and treatment decisions in the future. In this study, we developed a new multilayer classification method to identify Alzheimer's disease from brain MRI using contour model and multilayer classifier. This method is evaluated on 436 samples of OASIS dataset and achieved accuracy of method is 93.75 %. 2024 Author(s). -
Multigene Genetic Programming Based Prediction of Concrete Fracture Parameters of Unnotched Specimens
This study explores the fracture energy of notched and unnotched concrete specimens subjected to the classical three-point bend test, instantiating a gradational step in the continued development of concrete fracture mechanics. An experimental campaign involving 18 notched test specimens and nine unnotched specimens of three different grades of concrete, an examination of the existing literature models for unnotched specimens, and a novel Multigene Genetic programming (MGGP) based concrete fracture energy model for unnotched specimens are integral to this study. As a salient result, the multiple approaches to quasi-brittle materials adopted in the study, highlighted the criticality of the determination of fracture energy, tensile strength and characteristic length for the crack width study. The failure modes of notched and unnotched specimens were found to be similar. The reported literature has mainly focused on a limited number of fracture energy influencing parameters. Therefore, six impact parameters have been chosen and incorporated into the present study to provide a more acceptable explanation of concrete fracture behaviour. A sensitivity analysis of the parameters and an error analysis of the model undertaken have established the accuracy and robustness of the developed MGGP model. 2023 by the authors. Licensee C.E.J, Tehran, Iran. -
Multifunctional SnO?-Chitosan-D-carvone Nanocomposite: A Promising Antimicrobial, Anticancer, and Antioxidant Agent for Biomedical Applications
Nanocomposite made up of inorganic and biocompatible polymer have gained significant attention for biomedical applications due to their enhanced multifunctional properties, offering solutions to serious issues like antimicrobial resistance and cancer treatment. Nanocomposite composed of SnO?, chitosan and D-carvone (SnO2-Cs-Dcar) was prepared to ascertain its efficacy in application for antimicrobial, anticancer activities, and antioxidant effects. The synthesized nanocomposite was characterized by XRD, UV-Vis, FTIR, PL, SEM, TEM, and XPS techniques, confirming successful integration. XRD results confirmed the tetragonal rutile phase of SnO2. The band gap energy was calculated as 4.32eV for SnO2 nanoparticles and 3.11eV for SnO2-Cs-Dcar nanocomposite as observed from UV-Visible spectra. PL emission results showed that SnO2-Cs-Dcar nanocomposite exhibited green emission at 507nm corresponds to number oxygen vacancy site. SEM and TEM results showed that the SnO2-Cs-Dcar nanocomposite entities appear more compact, and the single SnO2 particles are less differentiated, possibly because they have been covered by chitosan and D-carvone. Antimicrobial activity against the pathogens Klebsiella pneumoniae, Candida albicans, Shigella dysenteriae, Bacillus subtilis, and Staphylococcus aureus demonstrated that SnO2-Cs-Dcar exhibited enhanced bacteriostatic effect when compared to bare SnO2. MTT assay on MOLT-4 cancer cells revealed that SnO2-Cs-Dcar nanocomposite exhibited enhanced anticancer activity upon compared to SnO? nanoparticles. The IC50 values were calculated as 13.6 for SnO2 and 12.1 for SnO2-Cs-Dcar nanocomposite. SnO?-Cs-Dcar nanocomposites exhibits high antioxidant activity evidenced by improved free radical scavenging action in comparison with a bare SnO?. Experimental result indicates that the SnO?-Cs-Dcar nanocomposites can be used as biocidal agent for antimicrobial and anticancer therapies. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Multifunctional electrospun membranes incorporated with metal oxide nanoparticles, cellulose acetate, and polyvinylpyrrolidone for wastewater treatment: Oil/water separation, dye adsorption, and dye degradation
Multifunctional membranes have gained considerable attention as useful materials for the treatment of complex wastewater that contains dye and oil substances. Electrospun nanofiber membranes (ENM) have substantial advantages and potential for complex wastewater remediation, owing to their unique properties. In this study, an environmentally compatible ENM is fabricated by incorporating photocatalytic metal oxide nanoparticles of zinc oxide (ZnO) or silver-zinc Oxide (Ag-ZnO) into cellulose acetate (CA)/polyvinylpyrrolidone (PVP) nanofibers using electrospinning. Composite membranes ZnO/CA/PVP, Ag-ZnO/CA/PVP, ZnO/DCA/PVP (DCA: deacetylated cellulose acetate), and Ag-ZnO/DCA/PVP (deacetylated) were employed for oilwater emulsion separation, owing to their superhydrophilic and underwater superoleophobic nature, photocatalytic dye degradation due to the presence of ZnO or Ag-ZnO, and dye adsorption resulting from their high surface area. The composite membranes showed more than 95% efficiency for oil/water separation, malachite green adsorption, and photocatalytic methylene blue degradation. These membranes displayed simultaneous oilwater and dye separation efficiency, as well as antibacterial properties. The membrane we present here provides a simple and effective platform for wastewater remediation with a low energy consumption. 2024 Elsevier B.V. -
Multifunctional characteristics of biosynthesized CoFe2O4@Ag nanocomposite by photocatalytic, antibacterial and cytotoxic applications
Carissa carandas, a traditional medicinal herb with a high concentration of antioxidant phytochemicals, has been used for thousands of years in the Ayurveda, Unani, and homoeopathic schools of medicine. By employing Carissa carandas bark extract as a reducing and capping agent in green biosynthesis, we extend this conventional application to produce CoFe2O4 and CoFe2O4@Ag nanocomposite. A variety of techniques have been used to characterize the synthesised nanocomposite, including UVVis, FTIR, XRD, FESEM, EDX, and BET. The CoFe2O4 and CoFe2O4@Ag nanocomposite demonstrated promising antibacterial action against human bacterial pathogens like B. subtilis and S. aureus as gram positive and P. aeruginosa and E. coli as gram negative with inhibition zones of 24.3 0.57, 17.4 0.75 and 20.5 0.5, 19.8 1.6 mm respectively, and the obtained results were superior to the nanocomposite without silver. Moreover, in-vitro cytotoxicity effects of biosynthesized CoFe2O4 and CoFe2O4@Ag were performed on the human breast cancer cell MCF-7. It was found that the MCF-7 cells' 50% inhibitory concentration (IC50) was 60 ?g/mL. Additionally, biosynthesized CoFe2O4 and CoFe2O4@Ag nanocomposite was used to demonstrate the photocatalytic eradication of Rhodamine Blue (RhB). Due to the addition of Ag, which increases surface area, conductivity, and increased charge carrier separation, the CoFe2O4@Ag nanocomposite exhibits a high percentage of photocatalytic degradation of ? 98% within 35 min under UV light irradiation. The photocatalytic performance of as-synthesised nanocomposite was evaluated using dye degradation-adsorption in both natural light and dark condition. Under dark conditions, it was found that 2 mg mL?1 CoFe2O4@Ag in RhB aqueous solution (5 ppm) causes dye adsorption in 30 min with an effectiveness of 72%. Consequently, it is anticipated that the CoFe2O4@Ag nanocomposite will be a promising photocatalyst and possibly a noble material for environmental remediation applications. 2023 Elsevier Ltd -
Multifunctional biosensor activities in food technology, microbes and toxins A systematic mini review
Biosensors have its significant applications in various fields, its use in food processing, food safety and food technology has helped to enhance the overall health of the society as it can successfully determine the presence and concentration of different microorganisms including Escheichia coli, Vibrio cholera, Clostridium spp. etc., and also determination of various toxins present in food like acrylamides, benzene, ethylbenzene, toluene, xylene, nitrosamines, Benzo[a]pyrene (BaP) which are carcinogenic. The preface of biosensors has assisted food industries for monitoring and verification of raw materials, food processing, and composition of the food and assessment of product freshness. Symbolic biosensors have been developed in recent years and yet there is much immediate need for the development of more reliable, cost-effective, sensitive and novel biosensors for rapid detection and identification of food borne pathogens and toxins. Extensive review recapitulates overall food-pathogen testing research market trends, as well as commercialization of biosensors for the food safety industry as legislation creates novel standards for microbial monitoring. Furthermore, the world's concern about the food safety and human's healthcare, the one and only biosensor's exclusive demand is nothing but an alternative in real time diagnosis of diseases causing pathogens. 2022 Elsevier Ltd -
Multifractal analysis of volatility for detection of herding and bubble: Evidence from CNX Nifty HFT
This study delves into the herding and bubble detection in the volatility domain of a capital market underlying. Furthermore, it focuses on creating heuristics, so that common investors find it relatively easy to understand the state of the market volatility. Hence, it can be termed that this study is focused on the specific financial innovation regarding bubble and herding detection coupled with investor awareness. The traces of possible volatility bubble emerge when it is positioned against its own lags (both lag1 and lag2). The volatility trigger indicated clear traces of herding and an embedded parabola function. Continuous and repetitive parabola function hinted at a subtle presence of "fractals". Firstly, the detrended fluctuation analysis has been used with its multifractal variant. Secondly, the regularized form of Hurst calculation and analysis have been used. Both tests reveal the traces of nascent bubble formation owing to prominent herding in CNX Nifty HFT environment. They also indicate a clear link with Hausdorff topological patterns. These patterns would help to create heuristics, enabling investors to be aware of possible bubble and herd situations. Bikramaditya Ghosh, Emira Kozarevic, 2019. -
Multifarious Potential of Biopolymer-Producing Bacillus subtilis NJ14 for Plant Growth Promotion and Stress Tolerance in Solanum lycopercicum L. and Cicer arietinum L: A Way Toward Sustainable Agriculture
Diverse practices implementing biopolymer-producing bacteria have been examined in various domains lately. PHAs are among the major biopolymers whose relevance of PHA-producing bacteria in the field of crop improvement is one of the radical unexplored aspects in the field of agriculture. Prolonging shelf life is one serious issue hindering the establishment of biofertilizers. Studies support that PHA can help bacteria survive stressed conditions by providing energy. Therefore, PHA-producing bacteria with Plant Growth-Promoting ability can alter the existing problem of short shelf life in biofertilizers. In the present study, Bacillus subtilis NJ14 was isolated from the soil. It was explored to understand the ability of the strain to produce PHA and augment growth in Solanum lycopersicum and Cicer arietinum. NJ14 strain improved the root and shoot length of both plants significantly. The root and shoot length of S. lycopersicum was increased by 3.49 and 0.41cm, respectively. Similarly, C. arietinum showed a 9.55 and 8.24cm increase in root and shoot length, respectively. The strain also exhibited halotolerant activity (up to 10%), metal tolerance to lead (up to 1000?g/mL) and mercury (up to 100?g/mL), indicating that the NJ14 strain can be an ideal candidate for a potent biofertilizer. Graphical Abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
Multifarious pigment producing fungi of Western Ghats and their potential
Concerns about the negative impacts of synthetic colorants on both con-sumers and the environment have sparked a surge of interest in natural col-orants. This has boosted the global demand for natural colorants in the food, cosmetics and textile industries. Pigments and colorants derived from plants and microorganisms are currently the principal sources used by mod-ern industry. When compared to the hazardous effects of synthetic dyes on human health, natural colors are quickly degradable and have no negative consequences. In fact, fungal pigments have multidimensional bioactivity spectra too. Western Ghats, a biodiversity hotspot has a lot of unique eco-logical niches known to harbor potential endophytic pigment-producing fungi having enumerable industrial and medical applications. Most of the fungi have coevolved with the plants in a geographical niche and hence the endophytic associations can be thought to bring about many mutually ben-eficial traits. The current review aims to highlight the potential of fungal pigments found in the Western ghats of India depicting various methods of isolation and screening, pigment extraction and uses. There is an urgent need for bioprospecting for the identification and characterization of ex-tremophilic endophytic fungi to meet industry demands and attain sustain-ability and balance in nature, especially from geographic hotspots like the Western Ghats. 2022 Horizon e-Publishing Group. All rights reserved. -
Multifaceted Destination Personality Traits: A Short Communication on Understanding from Tourists Perspective
This short communication is an extract from a major research work on destination branding, and this cull out of analysis focused on the multifaceted destination personality traits that the destinations possess and perhaps how such perceptions of tourists differ based on the selected personal factors. Though there are many studies in the destination branding literature, the evidence regarding the personality traits is still at the stage of progression, and approaches referring to multifaceted personality traits are unseen. After the pilot testing, a structured questionnaire was floated to 400 tourists who visited the selected destinations a district in Tamil Nadu, India, between June 2019 and February 2020, where 327 responses were finalized. The questionnaire had statements measuring the destinations personality traits and other questions on tourists characteristics. Combined mean calculation and multivariate results revealed that two personality traits, welcoming and friendly, were emphasized by the tourists and perceived in common. Also, personality traits such as spiritual and charming were found to be commonly perceived. The mean values also indicated the existence of multifaceted destination personality traits some inherent and some perceived. Marketers and others thereof have been recommended on the branding and advertising strategies based on the outcome of this communication. The limitations and scope of this research have been indicated. 2022, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Multifaceted Anticancer Potential of Trigonella foenum-graecum
The past decade saw a revolution in the discovery of genetic and epigenetic factors paving way for various types of cancers. With a better understanding of the causes, comes a chance of wider possibility of targeting the root causes of cancer. Nature is a storehouse of natural anticancer molecules, many yet to be explored. Trigonella foenumgraecum (fenugreek) is one such plant, having a huge potential for modulating prophylactic and therapeutic aspects of cancer. Cuisines world over make uses of this legume in multiple ways. This small herb has been found to be loaded with many secondary metabolites like diosgenin, coumarin, trigonelline and so on that reduce inflammation, promote apoptosis, act as antioxidants, regulates cell proliferation, etc., thereby reducing the effects of various hallmarks of cancer. Components of T. foenum-graecum extracts have been found to be effective in alleviating both solid tumours and blood cancers. The milieu of phytochemicals present in T. foenum-graecum has already been shown to have antimicrobial, antioxidant and neuroprotective properties by several studies done in different parts of the world. The current chapter attempts to have a comprehensive look at the potential of various bioactive principles in Trigonella foenum-graecum to be used for the prevention and treatment of cancer. In today's global scenario, where cancer incidences are alarmingly rising, such natural remedies would indeed go a long way in preventing various types of cancer and imparting a better quality of life. 2021 Nova Science Publishers, Inc. -
Multidrug Resistant Bacteria: The Fatal Menace in Healthcare
Mapana Journal of Sciences, Vol-11 (1), pp. 31-47. ISSN-0975-3303