502 research outputs found

    Ergonomic Chair Design For Thermal Comfort Using Phase Change Materials

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    The metabolism process of humanoids is well designed for emitting the heat constantly. But no heat transfer phenomena occur from the spinal side of the body in sitting posture. The proper heat transfer is arrested in the sitting posture; this makes the human to feel discomfort. The bus drivers are the main victims who face this problem every day and cause of the disease called “hemorrhoid”. This project mainly focused to modify and construct a convenient chilled cushion chair with jam-backed Phase Change Material (PCM) to overcome such problems. This chair absorbs body heat when occupied and discharges while vacant. The stages when liquid change to solid and solid change to liquid occurs nearly by a constant temperature. The chair provides a cooling effect and also a cushioning effect to the occupier. The PCMs are having large latent heat and provide a cooling effect by maintaining nearly by constant temperature to the human body.  The jam-backed chilled cushion chair is invented for improved thermal comfort for the driver for some extended time by the proper temperature that acceptable level of the human. The performance tests are carried out to evaluate the working of the pad

    Reversible Data Hiding scheme using modified Histogram Shifting in Encrypted Images for Bio-medical images

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    Existing Least Significant Bit (LSB) steganography system is less robust and the stego-images can be corrupted easily by attackers. To overcome these problems Reversible data hiding (RDH) techniques are used. RDH is an efficient way of embedding confidential message into a cover image. Histogram expansion and histogram shifting are effective techniques in reversible data hiding. The embedded message and cover images can be extracted without any distortion. The proposed system focuses on implementation of RDH techniques for hiding data in encrypted bio-medical images without any loss. In the proposed techniques the bio-medical data are embedded into cover images by reversible data hiding technique. Histogram expansion and histogram shifting have been used to extract cover image and bio- medical data. Each pixel is encrypted by public key of Paillier cryptosystem algorithm. The homomorphic multiplication is used to expand the histogram of the image in encrypted domain. The histogram shifting is done based on the homomorphic addition and adjacent pixel difference in the encrypted domain. The message is embedded into the host image pixel difference. On receiving encrypted image with additional data, the receiver using his private key performs decryption. As a result, due to histogram expansion and histogram shifting embedded message and the host image can be recovered perfectly. The embedding rate is increased in host image than in existing scheme due to adjacency pixel difference

    Reversible Data Hiding scheme using modified Histogram Shifting in Encrypted Images for Bio-medical images

    Get PDF
    Existing Least Significant Bit (LSB) steganography system is less robust and the stego-images can be corrupted easily by attackers. To overcome these problems Reversible data hiding (RDH) techniques are used. RDH is an efficient way of embedding confidential message into a cover image. Histogram expansion and histogram shifting are effective techniques in reversible data hiding. The embedded message and cover images can be extracted without any distortion. The proposed system focuses on implementation of RDH techniques for hiding data in encrypted bio-medical images without any loss. In the proposed techniques the bio-medical data are embedded into cover images by reversible data hiding technique. Histogram expansion and histogram shifting have been used to extract cover image and bio- medical data. Each pixel is encrypted by public key of Paillier cryptosystem algorithm. The homomorphic multiplication is used to expand the histogram of the image in encrypted domain. The histogram shifting is done based on the homomorphic addition and adjacent pixel difference in the encrypted domain. The message is embedded into the host image pixel difference. On receiving encrypted image with additional data, the receiver using his private key performs decryption. As a result, due to histogram expansion and histogram shifting embedded message and the host image can be recovered perfectly. The embedding rate is increased in host image than in existing scheme due to adjacency pixel difference

    Channel-Aware Pretraining of Joint Encoder-Decoder Self-Supervised Model for Telephonic-Speech ASR

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    This paper proposes a novel technique to obtain better downstream ASR performance from a joint encoder-decoder self-supervised model when trained with speech pooled from two different channels (narrow and wide band). The joint encoder-decoder self-supervised model extends the HuBERT model with a Transformer decoder. HuBERT performs clustering of features and predicts the class of every input frame. In simple pooling, which is our baseline, there is no way to identify the channel information. To incorporate channel information, we have proposed non-overlapping cluster IDs for speech from different channels. Our method gives a relative improvement of ~4% over the joint encoder-decoder self-supervised model built with simple pooling of data, which serves as our baseline.Comment: 5 pages, 5 figure

    VALIDATING EFFECTIVE RESUME BASED ON EMPLOYER’S INTEREST WITH RECOMMENDATION SYSTEM

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    In current technological world, recruitment process of corporate has evolved to the greater extent. Both the candidates and the recruiters prefer resumes to be submitted as an e-document. Validating those resumes manually is not much flexible and effective and time saving. The team requires more man power to scrutinize the resumes of the candidates. The aim of our work is to help the recruiters to find the most appropriate resume that match all their requirements. The system allows the recruiter to post his/her requirement as query, and the system will recommend the relevant resume by calculating the similarity between the query and the resume using Vector Space Model (VSM)
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