scholarly journals Xilinx Based Electronic Voting Machine

2019 ◽  
Vol 9 (1) ◽  
pp. 3935-3939
Keyword(s):  
Real Time ◽  
Input Signal ◽  
Electronic Voting ◽  
High Input ◽  
Verilog Hdl ◽  
Election Process ◽  
Switch Input ◽  
University Level ◽  
The Individual ◽  
Voting Machine

Conventional paper based voting procedure was terribly long process and extremely prone to errors. Polling by Electronic Voting Machine (EVM) is easy, safe and secure methodology that takes minimum of our time .In order to perform this mechanism, there were several phases in the design process such as designing a flow chart, algorithm and simultaneously the code is developed to implement & stimulate the logic. The proposed digital EVM was designed on Xilinx ISE using verilog HDL and can also be implemented on FPGA board for real time purpose. The proposed method consists of 3 stages, in the first stage we decide the total no. of voters and the total number of contestants taking part in the election process .we have assigned Voting enable which is active high input signal for the voter in order to cast his vote by using voter switch input signal for making this election process more secure and safe. In stage two, voting process begins when the voter casts his vote to a particular party or contestants the polled vote is registered in the individual contestant registry. In stage three after completion of voting process the votes are validated by comparing the votes polled to the contestants in their registries after which the election process ends by declaring the winner. The above proposed method can be implemented on FPGA board for real time applications ranging from university level elections to Assembly and LokSabha elections, as it has the advantage that it can be reprogrammed over and over for various tasks according to their requirement which helps in reducing the expenditure.

scholarly journals Improved Electronic Voting Machine with Real Time Data Analysis

2016 ◽  
Vol 6 (1) ◽  
pp. 47-49
Author(s):  
Anamika Sen ◽  
Malabika Sen ◽  
Aarti Ambekar
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Electronic Voting ◽  
Time Data ◽  
Real Time Data ◽  
Voting Machine

scholarly journals Designing of a Biometric Fingerprint Scanner-Based, Secure, and Low-Cost Electronic Voting Machine for India

2021 ◽  
Author(s):  
Shubhranil Chakraborty ◽  
Debabrata Bej ◽  
Dootam Roy ◽  
Sekh Arif Mahammad
Keyword(s):  
Human Resources ◽  
Low Cost ◽  
Electronic Voting ◽  
Election Process ◽  
User Data ◽  
Systematic Development ◽  
The Cost ◽  
Interactive User ◽  
Interactive User Interface ◽  
Voting Machine

A reliable Electronic Voting Machine (EVM) is proposed and implemented in this study, which is integrated with a biometric fingerprint scanner to ensure a secure election process. This biometric EVM includes features such as an interactive user interface, hack-free design and master lock. The EVM system has the capability of registering user data and storing them in a database through proper authentication. Moreover, the system proposed lowers the requirement for human resources. This paper provides a detailed description of the systematic development of the hardware and software used. The software part includes algorithm development and implementation. A thorough and in-depth understanding of the data and the communication protocols along with the pathways used for storage of data in the devices is provided. Additionally, the cost of the system is 62.82% less than the officially existing EVM machines of India. Furthermore, this study seeks to demonstrate the benefits of such an approach from a technological and a social standpoint.

scholarly journals Cloud Database Security in E-Voting System using Blockchain Technology

2020 ◽  
Vol 8 (5) ◽  
pp. 1361-1370 ◽  
Keyword(s):  
Real Time ◽  
Database Security ◽  
Electronic Voting ◽  
Time Data ◽  
Time Consumption ◽  
Election Process ◽  
Cloud Database ◽  
Real Time Data ◽  
Voting System ◽  
Electronic Voting System

In today’s era, the cloud database security is one of the main concerns for any of the real time data accessing web/mobile applications. The cloud database protection involves accessibility and vulnerability of data, data protection, storage space, integrity and confidentiality on sensitive data. Building an electronic voting system that tries to completely fulfill the needs of the people has always been a challenge to achieve. The existing E-Voting System (E-VS) is not that much compatible with that of the current trends and does not assure to provide more security A lot of distributed ledger technologies which has been an exciting approach during existing election voting process. If we take a look on the ways of implying E-VS in a distribute ledger then Blockchain would be the right choice. As we all know that nowadays, Blockchain is one of the emerging technologies in the field of Information Technology. It normally stores information in batches called blocks which are linked together in a chronological way or method to form chain of blocks using cryptography techniques. During online voting process, many fraudulent activities happens which corrupt the entire election process. One of the major problems faced are fake voting which is obviously done by unauthorized people, inconvenient to reach to the respective places, average security level which may lead to the chances of an electoral fraud or any other malpractices.. Our proposed E-Voting System is mainly to protect the cloud database for real time data and to reduce the time consumption in voting and vote counting processes. Instead of standing in the queue for casting the vote, people can cast their votes from anywhere they want through online. The E-VS gives complete privacy and security for the online voting and makes it an ease for every individual to access it and cast their votes from anywhere possible with full pronounced security. In our proposed E-VS, Blockchain security concept called Consensus algorithm is implemented which makes it impossible for any unwanted activities to occur during election process. The E-VS system also achieves a higher level of security. Hence, the proposed system achieves data integrity, data confidentiality, eliminates storage overhead, and reduces time consumption for overall electronic voting system.

A Back Allocation Methodology to Estimate the Real-Time Flow and Assist Production Monitoring

2021 ◽  
Author(s):  
Gabriela Chaves ◽  
Danielle Monteiro ◽  
Virgilio José Martins Ferreira
Keyword(s):  
Real Time ◽  
Input Data ◽  
Oil Field ◽  
Well Testing ◽  
Well Test ◽  
Time Data ◽  
Time Flow ◽  
Well Model ◽  
Operational Information ◽  
The Individual

Abstract Commingle production nodes are standard practice in the industry to combine multiple segments into one. This practice is adopted at the subsurface or surface to reduce costs, elements (e.g. pipes), and space. However, it leads to one problem: determine the rates of the single elements. This problem is recurrently solved in the platform scenario using the back allocation approach, where the total platform flowrate is used to obtain the individual wells’ flowrates. The wells’ flowrates are crucial to monitor, manage and make operational decisions in order to optimize field production. This work combined outflow (well and flowline) simulation, reservoir inflow, algorithms, and an optimization problem to calculate the wells’ flowrates and give a status about the current well state. Wells stated as unsuited indicates either the input data, the well model, or the well is behaving not as expected. The well status is valuable operational information that can be interpreted, for instance, to indicate the need for a new well testing, or as reliability rate for simulations run. The well flowrates are calculated considering three scenarios the probable, minimum and maximum. Real-time data is used as input data and production well test is used to tune and update well model and parameters routinely. The methodology was applied using a representative offshore oil field with 14 producing wells for two-years production time. The back allocation methodology showed robustness in all cases, labeling the wells properly, calculating the flowrates, and honoring the platform flowrate.

Prepare: P owe r -Awar e A p proximate Re a l-time Task Scheduling for Ene r gy-Adaptiv e QoS Maximization

2021 ◽  
Vol 20 (5s) ◽  
pp. 1-25
Author(s):  
Shounak Chakraborty ◽  
Sangeet Saha ◽  
Magnus Själander ◽  
Klaus Mcdonald-Maier
Keyword(s):  
Real Time ◽  
Task Scheduling ◽  
Processing Speed ◽  
Empirical Evaluation ◽  
Adaptive Mechanism ◽  
Approximate Computing ◽  
Thermal Safety ◽  
Time Task ◽  
Individual Task ◽  
The Individual

Achieving high result-accuracy in approximate computing (AC) based real-time applications without violating power constraints of the underlying hardware is a challenging problem. Execution of such AC real-time tasks can be divided into the execution of the mandatory part to obtain a result of acceptable quality, followed by a partial/complete execution of the optional part to improve accuracy of the initially obtained result within the given time-limit. However, enhancing result-accuracy at the cost of increased execution length might lead to deadline violations with higher energy usage. We propose Prepare , a novel hybrid offline-online approximate real-time task-scheduling approach, that first schedules AC-based tasks and determines operational processing speeds for each individual task constrained by system-wide power limit, deadline, and task-dependency. At runtime, by employing fine-grained DVFS, the energy-adaptive processing speed governing mechanism of Prepare reduces processing speed during each last level cache miss induced stall and scales up the processing speed once the stall finishes to a higher value than the predetermined one. To ensure on-chip thermal safety, this higher processing speed is maintained only for a short time-span after each stall, however, this reduces execution times of the individual task and generates slacks. Prepare exploits the slacks either to enhance result-accuracy of the tasks, or to improve thermal and energy efficiency of the underlying hardware, or both. With a 70 - 80% workload, Prepare offers 75% result-accuracy with its constrained scheduling, which is enhanced by 5.3% for our benchmark based evaluation of the online energy-adaptive mechanism on a 4-core based homogeneous chip multi-processor, while meeting the deadline constraint. Overall, while maintaining runtime thermal safety, Prepare reduces peak temperature by up to 8.6 °C for our baseline system. Our empirical evaluation shows that constrained scheduling of Prepare outperforms a state-of-the-art scheduling policy, whereas our runtime energy-adaptive mechanism surpasses two current DVFS based thermal management techniques.

Reconsidering the Resilience of Pastoralism from the Perspective of Reliability: The Case of Conflicts between the Samburu and the Pokot of Kenya, 2004-2009

2021 ◽  
Vol 25 (2) ◽  
pp. 253-277
Author(s):  
Shinya Konaka
Keyword(s):  
Mobile Phone ◽  
Real Time ◽  
Time Management ◽  
Ethnographic Case Study ◽  
High Input ◽  
Theoretical Frameworks ◽  
Mobile Phone Network ◽  
Process Variance ◽  
Output Variance

This article explores an overlooked aspect of the 'resilience of pastoralism' in crises through an ethnographic case study of a series of conflicts between the Samburu and the Pokot in Kenya that erupted in 2004. Emery Roe's concepts of reliability professionals and real-time management of pastoralists are utilised as theoretical frameworks for this study. It was observed that the 'logic of high input variance matched by high process variance to ensure low and stable output variance' occurred through the formation of clustered settlements and an inter-ethnic mobile phone network. This case illustrates how pastoralists endured the conflict as reliability professionals.

scholarly journals A modular approach to integrating multiple data sources into real-time clinical prediction for pediatric diarrhea

2020 ◽  
Author(s):  
Ben J. Brintz ◽  
Benjamin Haaland ◽  
Joel Howard ◽  
Dennis L. Chao ◽  
Joshua L. Proctor ◽  
...  
Keyword(s):  
Real Time ◽  
Prediction Models ◽  
Predictive Performance ◽  
Data Availability ◽  
Clinical Prediction ◽  
Multiple Sources ◽  
Statistical Framework ◽  
Multiple Data ◽  
Post Test ◽  
The Individual

AbstractTraditional clinical prediction models focus on parameters of the individual patient. For infectious diseases, sources external to the patient, including characteristics of prior patients and seasonal factors, may improve predictive performance. We describe the development of a predictive model that integrates multiple sources of data in a principled statistical framework using a post-test odds formulation. Our method enables electronic real-time updating and flexibility, such that components can be included or excluded according to data availability. We apply this method to the prediction of etiology of pediatric diarrhea, where “pre-test” epidemiologic data may be highly informative. Diarrhea has a high burden in low-resource settings, and antibiotics are often over-prescribed. We demonstrate that our integrative method outperforms traditional prediction in accurately identifying cases with a viral etiology, and show that its clinical application, especially when used with an additional diagnostic test, could result in a 61% reduction in inappropriately prescribed antibiotics.

scholarly journals Assess Reliability Parameters of an Electronic Voting Machine using a Neural Network Technique

2020 ◽  
Vol 9 (6) ◽  
pp. 269-275
Keyword(s):  
Neural Network ◽  
Storage System ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Descent Method ◽  
Electronic Voting ◽  
Gradient Descent Method ◽  
Neural Network Approach ◽  
Reliability Parameters ◽  
Voting Machine

The structure of Electronic Voting Machine (EVM) is an interconnected network of discrete components that record and count the votes of voters. The EVM system consists of four main subsystems which are Mother board of computer, Voting keys, Database storage system, power supply (AC and DC) along with various conditions of functioning as well as deficiency. The deficiency or failure of system is due to its components (hardware), software and human mismanagement. It is essential to reduce complexity of interconnected components and increase system reliability. Reliability analysis helps to identify technical situations that may affect the system and to predict the life of the system in future. The aim of this research paper is to analyze the reliability parameters of an EVM system using one of the approaches of computational intelligence, the neural network (NN). The probabilistic equations of system states and other reliability parameters are established for the proposed EVM model using neural network approach. It is useful for predicting various reliability parameters and improves the accuracy and consistency of parameters. To guarantee the reliability of the system, Back Propagation Neural Network (BPNN) architecture is used to learn a mechanism that can update the weights which produce optimal parameters values. Numerical examples are considered to authenticate the results of reliability, unreliability and profit function. To minimize the error and optimize the output in the form of reliability using gradient descent method, authors iterate repeatedly till the precision of 0.0001 error using MATLAB code. These parameters are of immense help in real time applications of Electronic Voting Machine during elections.

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