Vipin Tiwari

@sitpune.edu.in

Associate Professor, Computer Science and Engineering
Symbiosis Institute of Technology.

Vipin Tiwari


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https://researchid.co/vipintiwari1

RESEARCH INTERESTS

Machine and Deep Learning, Soft Computing Techniques
21

Scopus Publications

428

Scholar Citations

7

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • A Survey on Privacy Preservation Techniques in Social Clustering via Federated Learning and Deep Learning
    Pravin Baban More, Vipin Tiwari
    International Journal of Computational Intelligence and Applications, 2026
    The rapid progress in information and communications technologies has made personal data a valuable resource, which can help data owners seamlessly meet the needs of their affiliates. Data owners are acquiring enormous and various amounts of personal data due to the widespread proliferation of digital tools and computing. Current efforts mostly concentrate on establishing Federated Learning (FL) methods that are optimized, ignoring the enduring and internal connections between users, like social relationships. This survey helps the researchers analyze several approaches to privacy preservation in social networks. 60 research articles that focus on different techniques for social clustering privacy preservation are analyzed. Moreover, this survey provides an analysis of the available privacy preservation techniques in social clustering on the basis of publication year, research techniques, tools used, dataset used, and performance assessment, along with the accomplishments of research techniques, paving the way for the establishment of innovative models in the future. Various researchers have developed models to address this issue, and the techniques can be categorized based on Deep Learning (DL), FL, and other techniques. The real-world datasets are most widely employed. Moreover, the research gaps and drawbacks of these techniques are discussed, highlighting the need for an effective approach to privacy preservation in social clustering using FL.
  • A novel hybrid approach for thyroid disease detection: Integrating cuttlefish algorithm and simulated annealing for optimal feature selection
    Kapil Shrivastava, Saroj Pandey, Rishav Dubey, Mayank Namdev, Vipin Tiwari, Aditi Sharma
    Methodsx, 2025
    Effective treatment relies on a timely diagnosis, which is critical in the case of thyroid disorder-one of the chronic endocrine disorders alongside diabetes and obesity-with profound health concerns. Thyroid disorders occur due to the malfunctioning of the thyroid gland, which may result in an imbalanced metabolic rate due to inappropriate hormone levels synthesis. An overactive gland results in hyperthyroidism, whereas an underactive or sluggish thyroid lead to hypothyroidism. Both disorders, if not detected and managed timely, can lead to severe health complications. Early identification is crucial to delay or avoid debilitating complications and achieve a better quality of life through the right medical interventions and precise hormonal readjustments. The proposed hybrid algorithm method finds the best features for finding thyroid disease uses performance measures such as accuracy, F1-score, precision, and recall. The research demonstrates promising results with an accuracy of 98.91 % and an F1-score of 94.83, showcasing the robustness of the proposed algorithms on a benchmark dataset. The findings hold potential to improve clinical decision-making processes. This study advances medical diagnostics by combining machine learning algorithms with nature-inspired optimization techniques to detect thyroid illnesses in their early stages.•This article proposes a novel hybrid algorithm that combines the Cuttlefish Optimization Algorithm (CFA) and Simulated Annealing (SA) to find the best features for finding thyroid disease.•The study uses machine-learning models for classification.•The integration of machine learning and nature-inspired optimization significantly enhances the diagnostic capabilities of healthcare systems, enabling prompt diagnosis and treatment planning for thyroid disorders.
  • Corrigendum to: “A novel hybrid approach for thyroid disease detection: Integrating cuttlefish algorithm and simulated annealing for optimal feature selection” [Journal: MethodsX, Volume 15 (December 2025), Article 103558] (MethodsX (2025) 15, (S2215016125004029), (10.1016/j.mex.2025.103558))
    Kapil Shrivastava, Saroj Pandey, Rishav Dubey, Mayank Namdev, Vipin Tiwari, Aditi Sharma
    Methodsx, 2025
    [This corrects the article DOI: 10.1016/j.mex.2025.103558.].
  • Generating Avatar Using HamNoSys and SiGML for British Sign Language
    Harshit Singh, Ashish Mishra, Rahul Dubey, Vipin Tiwari
    International Conference on Signal Processing and Communication ICSC, 2025
    In today's digital world online video lectures have become a crucial tool for learning. Yet, these resources aren't available to a big part of the world's population those who are deaf or hard of hearing. This study presents a new system that aims to make these resources available to everyone by turning spoken words from video lectures into sign language gestures. The system uses advanced video processing to change spoken words into text. It then turns this text into British Sign Language (BSL) glosses, which are then written in the Hamburg Notation System (HamNoSys). Using the Signing Gesture Markup Language (SiGML), the system creates a virtual avatar that can show complex sign language gestures. The heart of this research is in combining cutting-edge technologies to offer a deep learning experience that goes beyond hearing limits and tries to make online education for everyone. Early tests of the system show it has the power to close the current gap in education highlighting how important it is to include everyone in the digital age.
  • Smart Parking System using IOT and Image Processing
    Sunil Jakhar, Lokesh Chouhan, Madhuri Kanojiya, Vipin Tiwari, Mayank Namdev
    International Journal of Engineering Trends and Technology, 2025
    Considering the continuously increasing urban population and private vehicle ownership, a smart parking framework has become a fundamental necessity of the present times. According to various studies, nearly 30% of the urban traffic congestion occurs due to drivers searching for nearby parking spaces. To reduce traffic congestion and avoid the wastage of time and fuel, this research work offers an android-based smart parking system integrating IoT and image-processing technologies. The smart parking system proposed in this paper helps reduce the time and fuel consumption involved in searching for a nearby parking area, and also allows users to pre-book a parking slot in real-time. In addition, the app will also help the user to get to the parking area via the shortest route, for which the Google Maps API is used. Furthermore, the parking entrance will be fully automated, and charges will also be dynamic (time-based). A user may pay offline or online using a digital wallet or any payment gateway, resulting in the faster exit of vehicles. This approach helps to make the parking experience faster and smoother, and also reduces traffic inside the parking area. The suggested Smart parking system thus contributes to improving the operational efficiency of the parking operations, optimizing the utilization of parking space, and enhancing the overall user experience by providing a simple, automated, and congestion-free parking solution, which helps smooth traffic flow.
  • Detection of Leaf Disease in Plantation Process for Fruits, Vegetables, Grains and Cereals using Application
    , Vipin Vipin, , , , , , Lokesh Chouhan, Vipin Tiwari, Dheresh Soni, Devika A. Verma, Yashwant Dongre
    Fusion Practice and Applications, 2025
    One of the most important sectors for providing for daily human requirements is agriculture. At the same time, digitization has a big impact on a number of businesses, making it simpler to carry out a number of challenging tasks. In order to help the farmer and the consumer, technology and digitization must be adopted. Utilizing technology and routine monitoring, diseases can be identified and eliminated, increasing agricultural output. This paper suggests a system for recognizing and categorizing plant illnesses, initially focused on five separate classes: two fruit classes, one vegetable class, one edible pulse class, and one-grain class. The Plant Village and UCI ML Repository Dataset, which is well known as a freely accessible, accepted standard, and reliable data source, was used for this purpose. Based on them, a CNN model is prepared for analyzing them with an accuracy upto 95.42%. Image segmentation will also play a role in calculating precise amount of infection followingly, a good interface is must to utilize it in a proper way for a user which can be provided in the form of app, a feature that every user requires on daily basis.
  • Revolutionizing E-Commerce Security: Unveiling an Innovative Deep Learning-Based Strategy for Detecting Financial Fraud
    , Pradeep Pradeep, , , , , , S. Phani Praveen, Vipin Tiwari, Pradeep Kumar Arya, Deepak Parvathaneni Naga Srinivasu, Mukta Patel
    Fusion Practice and Applications, 2025
    An inventive deep learning-based method for identifying financial fraud, revolutionizing e-commerce security in the process. The research offers a state-of-the-art setup that makes use of deep learning computations in the dynamic world of online exchanges, where the possibility of fraudulent activity is a danger. Since frauds are known to be erratic and lack consistency, it might be challenging to spot them. Con artists exploit the latest developments in technology. They manage to evade security measures, which results in millions of dollars being lost. One method of tracking fraudulent exchanges is to use information-mining techniques to investigate and detect unusual behaviours. Interactions. In contrast to deep learning techniques as auto encoders, convolutional neural networks (CNN), restricted Boltzmann machines (RBM), and deep belief networks (DBN), this paper aims to benchmark several machine-learning techniques, such as k-nearest neighbour (KNN), irregular forest, and support vector machines (SVM). The three-evaluation metrics that are really employed are the Area Under the ROC Curve (AUC), the Matthews Correlation Coefficient (MCC), and the Cost of Failure.
  • IoT-Enabled monitoring system for Plant Health Growth
    , admin admin, , , , , , , Deepak S. Dharrao, Kapil Joshi, Vipin Tiwari, Sumit Kumar, Prabhat Kr. Srivastava, Rahul Sharma
    Journal of Intelligent Systems and Internet of Things, 2025
    In current scenario, plant health monitoring plays a crucial role in effective health maintenance of plants in climate changes. Internet of Things (IoT) played an efficient role in realizing the remote and real-time monitoring of any physical things and activities through internet connectivity. In this study we have proposed a system that is able to monitor the plant health with the assimilation of wireless sensors and wireless network. The proposed system is able to log the sensor values on the plants on the cloud server through internet connectivity.
  • Performance Exploration of Network Intrusion Detection System with Neural Network Classifier on The KDD Dataset
    Sellappan Devaraju, Dheresh Soni, Sundaram Jawahar, Jay Prakash Maurya, Vipin Tiwari
    International Journal of Safety and Security Engineering, 2024
    Network Intrusion Detection Systems (NIDS) are a difficult task for determining in any managerial information system or IT sectors, if a user is a normal user or an attacker.The main objectives of the proposed system are to enhance operational efficiency, decreasing the occurrence of false positives, to minimize the time complexity of the process.It is an excellent way for dealing with various types of network problems.Research focusses the various classifiers are applied to detect various types of network assaults.Performance of network intrusion detection by two classifiers are used to compare the results.Probabilistic Neural Network (PNN) and Feed Forward Neural Network (FFNN) classifiers are employed this suggested study.The performance results comparison between full featured and reduced features are presented.MATLAB software application is applied to test the performance of both test and train dataset.Detecting network intrusions is a critical challenge within managerial information systems and the IT sector, as it involves the complex task of distinguishing between legitimate users and potential attackers.Maintaining a secure network environment is paramount to safeguarding sensitive information and operations.In the arena of network intrusion detection, the research predominantly revolves around the deployment of diverse classifiers to identify various types of network attacks.This paper, proposes the evaluation of two specific classifiers, the PNN and the FFNN, with the objective of comparing their performance in the context of network intrusion detection.We systematically assess their effectiveness in both full-featured and reduced-feature scenarios, utilizing MATLAB software to rigorously analyze their capabilities across test and training datasets.In essence, this research delves into the intricate realm of Network Intrusion Detection Systems (NIDS), investigating how the PNN and FFNN classifiers function in the critical role of safeguarding networks against a multitude of potential threats.Through comprehensive analysis, we aim to illuminate the most efficient approach to enhancing network security in the constantly evolving landscape of cybersecurity.As a result, it is recommended that FFNN approaches be adopted as a means of improving detection efficiency and reducing the False Positive Rate (FPR) in network intrusion detection systems.
  • Big Data’s Ethical Frontier: Addressing Concerns in Data Acquisition and Analysis
    Kanhaiya Sharma, Deepak Parashar, Vipin Tiwari, Siddhanth Shah, Sandeep Singh Rawat
    Lecture Notes in Networks and Systems, 2024
  • Towards Safer Roads: Preventing Car Accident Probability with Machine Learning
    Siddhartha Arjaria, Shikha Singh, Vipin Tiwari, Ashish Mishra
    2023 International Conference on Power Energy Environment and Intelligent Control Peeic 2023, 2023
  • ISL Recognition of Emergency Words Using MediaPipe, CNN and LSTM
    Ashish Mishra, Shivansh Gupta, Deepanshu Goel, Vipin Tiwari
    2023 International Conference on Power Energy Environment and Intelligent Control Peeic 2023, 2023
  • Comparing the performance of machine learning algorithms using estimated accuracy
    Sunil Gupta, Kamal Saluja, Ankur Goyal, Amit Vajpayee, Vipin Tiwari
    Measurement Sensors, 2022
  • Automatic irrigation control system using Internet of Things(IoT)
    Satnam Singh Saini, Dheresh Soni, Simarjeet Singh Malhi, Vipin Tiwari, Ankur Goyal
    Journal of Discrete Mathematical Sciences and Cryptography, 2022
  • Selection of Optimum Grid Size and Unlabeled Data for Fingerprinting based Indoor Localization
    Sushil Tiwari, Vipin Tiwari, Sonam Maurya
    Proceedings 2021 2nd International Conference on Computational Methods in Science and Technology Iccmst 2021, 2021
  • Cloud computing security analysis based on RC6, AES and RSA algorithms in user-cloud environment
    Dheresh Soni, Vipin Tiwari, Bhupinder Kaur, M. Kumar
    Proceedings of the 1st International Conference on Advances in Computing and Future Communication Technologies Icacfct 2021, 2021
  • Neural network-based hardware classifier using CORDIC algorithm
    Vipin Tiwari, Ashish Mishra
    Modern Physics Letters B, 2020
  • A study on DeLC hybrid model for improvement of classification technique on sentiment analysis
    Sunil Malviya, Arun Kumar Jhapate, Ruchi Thakur, Vipin Tiwari
    2nd International Conference on Data Engineering and Applications Idea 2020, 2020
  • Personality Trait Identification for Written Texts Using MLNB
    S. Arjaria, A. Shrivastav, A. S. Rathore, Vipin Tiwari
    Data Engineering and Applications Volume 1, 2019
  • Hardware implementation of neural network with Sigmoidal activation functions using CORDIC
    Vipin Tiwari, Nilay Khare
    Microprocessors and Microsystems, 2015
  • Association rule mining: A graph based approach for mining frequent itemsets
    Vivek Tiwari, Vipin Tiwari, Shailendra Gupta, Renu Tiwari
    Icnit 2010 2010 International Conference on Networking and Information Technology, 2010

RECENT SCHOLAR PUBLICATIONS

  • A Survey on Privacy Preservation Techniques in Social Clustering via Federated Learning and Deep Learning
    PB More, V Tiwari
    International Journal of Computational Intelligence and Applications, 2630002 , 2026
    2026
  • Corrigendum to:“A novel hybrid approach for thyroid disease detection: Integrating cuttlefish algorithm and simulated annealing for optimal feature selection”[Journal: MethodsX …
    K Shrivastava, S Pandey, R Dubey, M Namdev, V Tiwari, A Sharma
    MethodsX 15, 103585 , 2025
    2025
  • A Novel Hybrid Approach for Thyroid Disease Detection: Integrating Cuttlefish Algorithm and Simulated Annealing for Optimal Feature Selection
    K Shrivastava, S Pandey, R Dubey, M Namdev, V Tiwari, A Sharma
    MethodsX, 103558 , 2025
    2025
    Citations: 7
  • IoT-Enabled monitoring system for Plant Health Growth.
    A Sharma, DS Dharrao, K Joshi, V Tiwari, S Kumar, PK Srivastava, ...
    Journal of Intelligent Systems & Internet of Things 14 (2) , 2025
    2025
    Citations: 2
  • Detection of Leaf Disease in Plantation Process for Fruits, Vegetables, Grains and Cereals using Application
    YD Madhuri Kanojiya, Lokesh Chouhan, Vipin Tiwari, Dheresh Soni, Devika A. Verma
    Fusion: Practice and Applications 19 (2), 253-264 , 2025
    2025
  • Generating Avatar Using HamNoSys and SiGML for British Sign Language
    H Singh, A Mishra, R Dubey, V Tiwari
    2025 10th International Conference on Signal Processing and Communication … , 2025
    2025
    Citations: 2
  • Revolutionizing e-commerce security: Unveiling an innovative deep learning-based strategy for detecting financial fraud
    A Sharma, S Phani, V Tiwari, P Kumar, D Parvathaneni, M Patel
    Fusion: Pract. Appl 17 (2), 366-376 , 2025
    2025
    Citations: 6
  • Revolutionizing e-commerce security: Unveiling an innovative deep learning-based strategy for detecting financial fraud
    P PRADEEP, S PRAVEEN, V Tiwari, PK ARYA, DPN SRINIVASU, M Patel
    FUSION: PRACTICE AND APPLICATIONS Учредители: American Scientific Publishing … , 2025
    2025
    Citations: 1
  • Performance Exploration of Network Intrusion Detection System with Neural Network Classifier on The KDD Dataset.
    S Devaraju, D Soni, S Jawahar, JP Maurya, V Tiwari
    International Journal of Safety & Security Engineering 14 (5) , 2024
    2024
    Citations: 2
  • IoT-Enabled monitoring system for Plant Health Growth
    RS Aditi Sharma, Deepak S. Dharrao, Kapil Joshi, Vipin Tiwari, Sumit Kumar ...
    Journal of Intelligent Systems and Internet of Things 14 (2), 252-259 , 2024
    2024
  • Real-Time Gesture Recognition Using Convolutional Neural Networks on Embedded Systems
    ES Groenewald, SB Dodda, D Dhabliya, CA Groenewald, V Tiwari, ...
    International Conference on Deep Learning and Visual Artificial Intelligence … , 2024
    2024
    Citations: 1
  • Toward General Artificial Intelligence via Federated Meta-Learning with Reinforcement Signals
    M Raparthi, N Bhat, SS Yerasuri, V Tiwari, A Sharma
    International Conference on Deep Learning and Visual Artificial Intelligence … , 2024
    2024
  • Real-Time Anomaly Detection in Industrial Systems Using Stream Processing and Online Machine Learning
    ES Groenewald, SB Dodda, M Soni, CA Groenewald, A Dhumane, ...
    International Conference on Deep Learning and Visual Artificial Intelligence … , 2024
    2024
    Citations: 4
  • Scalable Implementation of Random Forests for Big Data Classification on Cloud Infrastructure
    M Raparthi, M Soni, V Tiwari, A Dhumane, R Sharma
    International Conference on Deep Learning and Visual Artificial Intelligence … , 2024
    2024
    Citations: 6
  • Big Data’s Ethical Frontier: Addressing Concerns in Data Acquisition and Analysis
    K Sharma, D Parashar, V Tiwari, S Shah, SS Rawat
    International Conference on Advances in Computational Intelligence and … , 2023
    2023
  • ISL Recognition of Emergency Words Using MediaPipe, CNN and LSTM
    A Mishra, S Gupta, D Goel, V Tiwari
    2023 International Conference on Power Energy, Environment & Intelligent … , 2023
    2023
    Citations: 1
  • Towards Safer Roads: Preventing Car Accident Probability with Machine Learning
    S Arjaria, S Singh, V Tiwari, A Mishra
    2023 International Conference on Power Energy, Environment & Intelligent … , 2023
    2023
    Citations: 1
  • Comparing the performance of machine learning algorithms using estimated accuracy
    S Gupta, K Saluja, A Goyal, A Vajpayee, V Tiwari
    Measurement: Sensors 24, 100432 , 2022
    2022
    Citations: 131
  • Automatic irrigation control system using Internet of Things (IoT)
    SS Saini, D Soni, SS Malhi, V Tiwari, A Goyal
    Journal of Discrete Mathematical Sciences and Cryptography 25 (4), 879-889 , 2022
    2022
    Citations: 20
  • Selection of Optimum Grid Size and Unlabeled Data for Fingerprinting based Indoor Localization
    S Tiwari, V Tiwari, S Maurya
    2021 2nd International Conference on Computational Methods in Science … , 2021
    2021

MOST CITED SCHOLAR PUBLICATIONS

  • Comparing the performance of machine learning algorithms using estimated accuracy
    S Gupta, K Saluja, A Goyal, A Vajpayee, V Tiwari
    Measurement: Sensors 24, 100432 , 2022
    2022
    Citations: 131
  • Hardware implementation of neural network with Sigmoidal activation functions using CORDIC
    V Tiwari, N Khare
    Microprocessors and Microsystems 39 (6), 373-381 , 2015
    2015
    Citations: 95
  • Machine Learning Techniques for Sentiment Analysis: A Review
    S Malviya, AK Tiwari, R Srivastava, V Tiwari
    SAMRIDDHI: A Journal of Physical Sciences, Engineering and Technology 12 (02 … , 2020
    2020
    Citations: 57
  • Association rule mining: A graph based approach for mining frequent itemsets
    V Tiwari, V Tiwari, S Gupta, R Tiwari
    Networking and Information Technology (ICNIT), 2010 International Conference … , 2010
    2010
    Citations: 54
  • Automatic irrigation control system using Internet of Things (IoT)
    SS Saini, D Soni, SS Malhi, V Tiwari, A Goyal
    Journal of Discrete Mathematical Sciences and Cryptography 25 (4), 879-889 , 2022
    2022
    Citations: 20
  • Cloud computing security analysis based on RC6, AES and RSA algorithms in user-cloud environment
    D Soni, V Tiwari, B Kaur, M Kumar
    2021 First International Conference on Advances in Computing and Future … , 2021
    2021
    Citations: 14
  • A Novel Hybrid Approach for Thyroid Disease Detection: Integrating Cuttlefish Algorithm and Simulated Annealing for Optimal Feature Selection
    K Shrivastava, S Pandey, R Dubey, M Namdev, V Tiwari, A Sharma
    MethodsX, 103558 , 2025
    2025
    Citations: 7
  • Personality trait identification for written texts using mlnb
    S Arjaria, A Shrivastav, AS Rathore, V Tiwari
    Data, Engineering and Applications: Volume 1, 131-137 , 2019
    2019
    Citations: 7
  • Revolutionizing e-commerce security: Unveiling an innovative deep learning-based strategy for detecting financial fraud
    A Sharma, S Phani, V Tiwari, P Kumar, D Parvathaneni, M Patel
    Fusion: Pract. Appl 17 (2), 366-376 , 2025
    2025
    Citations: 6
  • Scalable Implementation of Random Forests for Big Data Classification on Cloud Infrastructure
    M Raparthi, M Soni, V Tiwari, A Dhumane, R Sharma
    International Conference on Deep Learning and Visual Artificial Intelligence … , 2024
    2024
    Citations: 6
  • Cloud computing security analysis based on RC6, AES and RSA algorithms
    D Soni, V Tiwari, BK Srao, M Kumar
    2021 1st international conference on advances in computing and future … , 2021
    2021
    Citations: 6
  • Neural network-based hardware classifier using CORDIC algorithm
    V Tiwari, A Mishra
    Modern Physics Letters B 34 (15), 2050161 , 2020
    2020
    Citations: 5
  • Real-Time Anomaly Detection in Industrial Systems Using Stream Processing and Online Machine Learning
    ES Groenewald, SB Dodda, M Soni, CA Groenewald, A Dhumane, ...
    International Conference on Deep Learning and Visual Artificial Intelligence … , 2024
    2024
    Citations: 4
  • Hardware for Calculation of SIN and COSINE Angle using CORDIC Algorithm
    V Tiwari, N Khare
    International Journal of Computer Applications 87 (6), 46-48 , 2014
    2014
    Citations: 3
  • IoT-Enabled monitoring system for Plant Health Growth.
    A Sharma, DS Dharrao, K Joshi, V Tiwari, S Kumar, PK Srivastava, ...
    Journal of Intelligent Systems & Internet of Things 14 (2) , 2025
    2025
    Citations: 2
  • Generating Avatar Using HamNoSys and SiGML for British Sign Language
    H Singh, A Mishra, R Dubey, V Tiwari
    2025 10th International Conference on Signal Processing and Communication … , 2025
    2025
    Citations: 2
  • Performance Exploration of Network Intrusion Detection System with Neural Network Classifier on The KDD Dataset.
    S Devaraju, D Soni, S Jawahar, JP Maurya, V Tiwari
    International Journal of Safety & Security Engineering 14 (5) , 2024
    2024
    Citations: 2
  • Hardware efficient implementation of neural network
    V Tiwari, S Vyas, N Khare
    Int. Ref. J. Eng. Sci.(IRJES) 2 (5), 20-23 , 2013
    2013
    Citations: 2
  • Revolutionizing e-commerce security: Unveiling an innovative deep learning-based strategy for detecting financial fraud
    P PRADEEP, S PRAVEEN, V Tiwari, PK ARYA, DPN SRINIVASU, M Patel
    FUSION: PRACTICE AND APPLICATIONS Учредители: American Scientific Publishing … , 2025
    2025
    Citations: 1
  • Real-Time Gesture Recognition Using Convolutional Neural Networks on Embedded Systems
    ES Groenewald, SB Dodda, D Dhabliya, CA Groenewald, V Tiwari, ...
    International Conference on Deep Learning and Visual Artificial Intelligence … , 2024
    2024
    Citations: 1