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| 1 | A label-free silver wire based impedimetric immunosensor for detection of aflatoxin M1 in milk显示文摘 | Gautam Bacher Souvik Pal Lizy Kanungo Sunil Bhand | 2012 | Chemical2012，，： | 1 |
| 2 | Securing Technique Using Pattern-Based LSB Audio Steganography and Intensity-Based Visual Cryptography显示文摘With the increasing need of sensitive or secret data transmission through public network,security demands using cryptography and steganography are becoming a thirsty research area of last few years.These two techniques can be merged and provide better security which is nowadays extremely required.The proposed system provides a novel method of information security using the techniques of audio steganography combined with visual cryptography.In this system,we take a secret image and divide it into several subparts to make more than one incomprehensible sub-images using the method of visual cryptography.Each of the sub-images is then hidden within individual cover audio files using audio steganographic techniques.The cover audios are then sent to the required destinations where reverse steganography schemes are applied to them to get the incomprehensible component images back.At last,all the sub-images are superimposed to get the actual secret image.This method is very secure as it uses a two-step security mechanism to maintain secrecy.The possibility of interception is less in this technique because one must have each piece of correct sub-image to regenerate the actual secret image.Without superimposing every one of the sub-images meaningful secret images cannot be formed.Audio files are composed of densely packed bits.The high density of data in audio makes it hard for a listener to detect the manipulation due to the proposed time-domain audio steganographic method. | Pranati Rakshit Sreeparna Ganguly Souvik Pal Ayman AAly Dac-Nhuong Le | 2021 | Computers, Materials & Continua2021，，4： | 1 |
| 3 | A label-free silver wire based impedimetric immunosensor for detection of aflatoxin M1 in milk显示文摘 | Gautam Bacher Souvik Pal Lizy Kanungo Sunil Bhand | 2012 | Sensors & Actuators: B Chemical2012，，： | 1 |
| 4 | Spontaneous formation of vesicles by self-assembly of cationic block copolymer in the presence of anionic surfactants and their application in formation of polymer embedded gold nanoparticles 显示文摘 | Rakesh Banerjee Sujan Dutta Souvik Pal | 2013 | J Phys Chem B2013，117，13： | 1 |
| 5 | First report on chlorophyllin to protect mammalian and fish muscle cells from pesticide toxicity via activation of p53 and PARP显示文摘Objectives:Pesticide toxicity has become one of the major environmental menaces affecting all types of life forms of the ecosystem.Pesticides get washed off from agricultural fields into nearby water bodies and enter the aquatic organisms.Their bio-accumulated form finally reaches the human race,through consumption of pesticide infested aquatic animals,causing several physiological dysfunctions.Hence it becomes necessary to find a therapeutic cure/a preventive measure to stop the health hazard issues of pesticide.With this projection a search for a phyto-based-product was made whose primary objective would be to lower the pesticidal toxicity in fish and simultaneously in the human race.Methods:In this study we tried to check whether the phyto-chemical,Chlorophyllin(CHL),known for its anti-genotoxic,anti-oxidant activities,could render any kind of protection against Cypermethrin(CM)induced-toxicity in fish model and mammalian cell line L6.Both the model L6 and fish were pre-treated with CHL prior to exposure of CM.Different scientific parameters like%cellular cytotoxicity,reactive oxygen species(ROS)generation,nuclear condensation,etc were checked to validate the possibility of CHL in protecting CM-induced toxicity.Results:The overall results revealed that pre-treatment with CHL could restrict the ROS generation leading to modulation in associated cytokine proteins expression NFkβand IFNγ.Further,CHL lowered nuclear condensation and elevated expression of DNA repair proteins p53 and PARP,showing a kind of pre-activation of signalling cascades for overall protection against the severity of pesticidal toxicity.Conclusion:Thus,this phyto-based preventive approach would possibly solve many areas of human health issues related to pesticide toxicity in future. | Asmita Samadder Swatilekha Das Bakul Pal Sweta Das Anindita Mandal Priyanka Biswas Sujoy Ghosh Shamim Hossain Mandal Priyanka Sow Ruchira Das Souvik Biswas Ashis Kumar Panigrahi | 2021 | Aquaculture and Fisheries2021，6，4： | 0 |
| 6 | Information-Centric IoT-Based Smart Farming with Dynamic Data Optimization显示文摘Smart farming has become a strategic approach of sustainable agriculture management and monitoring with the infrastructure to exploit modern technologies,including big data,the cloud,and the Internet of Things(IoT).Many researchers try to integrate IoT-based smart farming on cloud platforms effectively.They define various frameworks on smart farming and monitoring system and still lacks to define effective data management schemes.Since IoT-cloud systems involve massive structured and unstructured data,data optimization comes into the picture.Hence,this research designs an Information-Centric IoT-based Smart Farming with Dynamic Data Optimization(ICISF-DDO),which enhances the performance of the smart farming infrastructure with minimal energy consumption and improved lifetime.Here,a conceptual framework of the proposed scheme and statistical design model has beenwell defined.The information storage and management with DDO has been expanded individually to show the effective use of membership parameters in data optimization.The simulation outcomes state that the proposed ICISF-DDO can surpass existing smart farming systems with a data optimization ratio of 97.71%,reliability ratio of 98.63%,a coverage ratio of 99.67%,least sensor error rate of 8.96%,and efficient energy consumption ratio of 4.84%. | Souvik Pal Hannah VijayKumar D.Akila N.Z.Jhanjhi Omar A.Darwish Fathi Amsaad | 2023 | Computers, Materials & Continua2023，，2： | 0 |
| 7 | Memetic Optimization with Cryptographic Encryption for Secure Medical Data Transmission in IoT-Based Distributed Systems显示文摘In the healthcare system,the Internet of Things(IoT)based distributed systems play a vital role in transferring the medical-related documents and information among the organizations to reduce the replication in medical tests.This datum is sensitive,and hence security is a must in transforming the sensational contents.In this paper,an Evolutionary Algorithm,namely the Memetic Algorithm is used for encrypting the text messages.The encrypted information is then inserted into the medical images using Discrete Wavelet Transform 1 level and 2 levels.The reverse method of the Memetic Algorithm is implemented when extracting a hidden message from the encoded letter.To show its precision,equivalent to five RGB images and five Grayscale images are used to test the proposed algorithm.The results of the proposed algorithm were analyzed using statistical methods,and the proposed algorithm showed the importance of data transfer in healthcare systems in a stable environment.In the future,to embed the privacy-preserving of medical data,it can be extended with blockchain technology. | Srinath Doss Jothi Paranthaman Suseendran Gopalakrishnan Akila Duraisamy Souvik Pal Balaganesh Duraisamy Chung Le Van Dac-Nhuong Le | 2021 | Computers, Materials & Continua2021，，2： | 0 |
| 8 | Optimized Energy Efficient Strategy for Data Reduction Between Edge Devices in Cloud-IoT显示文摘Numerous Internet of Things(IoT)systems produce massive volumes of information that must be handled and answered in a quite short period.The growing energy usage related to the migration of data into the cloud is one of the biggest problems.Edge computation helps users unload the workload again from cloud near the source of the information that must be handled to save time,increase security,and reduce the congestion of networks.Therefore,in this paper,Optimized Energy Efficient Strategy(OEES)has been proposed for extracting,distributing,evaluating the data on the edge devices.In the initial stage of OEES,before the transmission state,the data gathered from edge devices are supported by a fast error like reduction that is regarded as the largest energy user of an IoT system.The initial stage is followed by the reconstructing and the processing state.The processed data is transmitted to the nodes through controlled deep learning techniques.The entire stage of data collection,transmission and data reduction between edge devices uses less energy.The experimental results indicate that the volume of data transferred decreases and does not impact the professional data performance and predictive accuracy.Energy consumption of 7.38 KJ and energy conservation of 55.57 kJ was found in the proposed OEES scheme.Predictive accuracy is 97.5 percent,data performance rate was 97.65 percent,and execution time is 14.49 ms. | Dibyendu Mukherjee Shivnath Ghosh Souvik Pal D.Akila N.Z.Jhanjhi Mehedi Masud Mohammed A.AlZain | 2022 | Computers, Materials & Continua2022，，7： | 0 |
| 9 | A Novel Machine Learning-Based Hand Gesture Recognition Using HCI on IoT Assisted Cloud Platform显示文摘Machine learning is a technique for analyzing data that aids the construction of mathematical models.Because of the growth of the Internet of Things(IoT)and wearable sensor devices,gesture interfaces are becoming a more natural and expedient human-machine interaction method.This type of artificial intelligence that requires minimal or no direct human intervention in decision-making is predicated on the ability of intelligent systems to self-train and detect patterns.The rise of touch-free applications and the number of deaf people have increased the significance of hand gesture recognition.Potential applications of hand gesture recognition research span from online gaming to surgical robotics.The location of the hands,the alignment of the fingers,and the hand-to-body posture are the fundamental components of hierarchical emotions in gestures.Linguistic gestures may be difficult to distinguish from nonsensical motions in the field of gesture recognition.Linguistic gestures may be difficult to distinguish from nonsensical motions in the field of gesture recognition.In this scenario,it may be difficult to overcome segmentation uncertainty caused by accidental hand motions or trembling.When a user performs the same dynamic gesture,the hand shapes and speeds of each user,as well as those often generated by the same user,vary.A machine-learning-based Gesture Recognition Framework(ML-GRF)for recognizing the beginning and end of a gesture sequence in a continuous stream of data is suggested to solve the problem of distinguishing between meaningful dynamic gestures and scattered generation.We have recommended using a similarity matching-based gesture classification approach to reduce the overall computing cost associated with identifying actions,and we have shown how an efficient feature extraction method can be used to reduce the thousands of single gesture information to four binary digit gesture codes.The findings from the simulation support the accuracy,precision,gesture recognition,sensitivity,and efficiency rates.The Machine Learning-based Gesture Recognition Framework(ML-GRF)had an accuracy rate of 98.97%,a precision rate of 97.65%,a gesture recognition rate of 98.04%,a sensitivity rate of 96.99%,and an efficiency rate of 95.12%. | Saurabh Adhikari Tushar Kanti Gangopadhayay Souvik Pal D.Akila Mamoona Humayun Majed Alfayad N.Z.Jhanjhi | 2023 | Computer Systems Science & Engineering2023，46，8： | 0 |
| 10 | Dynamic Data Optimization in IoT-Assisted Sensor Networks on Cloud Platform显示文摘This article presents a new scheme for dynamic data optimization in IoT(Internet of Things)-assisted sensor networks.The various components of IoT assisted cloud platform are discussed.In addition,a new architecture for IoT assisted sensor networks is presented.Further,a model for data optimization in IoT assisted sensor networks is proposed.A novel Membership inducing Dynamic Data Optimization Membership inducing Dynamic Data Optimization(MIDDO)algorithm for IoT assisted sensor network is proposed in this research.The proposed algorithm considers every node data and utilized membership function for the optimized data allocation.The proposed framework is compared with two stage optimization,dynamic stochastic optimization and sparsity inducing optimization and evaluated in terms of reliability ratio,coverage ratio and sensing error.Data optimization was performed based on the availability of cloud resource,sensor energy,data flow volume and the centroid of each state.It was inferred that the proposed MIDDO algorithm achieves an average performance ratio of 76.55%,reliability ratio of 94.74%,coverage ratio of 85.75%and sensing error of 0.154. | Nguyen A.Tuan D.Akila Souvik Pal Bikramjit Sarkar Thien Khai Tran G.Mothilal Nehru Dac-Nhuong Le | 2022 | Computers, Materials & Continua2022，，7： | 0 |
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