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Mathematics Behind the Zcash
(2020)
Among all the new developed cryptocurrencies from Bitcoin, Zcash comes out to be the strongest cryptocurrency providing both transparency and anonymity to the transactions and its users by deploying the strong mathematics of zk-SNARKs.
We discussed the zero knowledge proofs which is a basic building block for providing the functionality to zk-SNARKs. It offers schnorr and sigma protocols with interactive and noninteractive versions. Non-interactive proofs are further used in Zcash transactions where the validation of sent transaction is proved by cryptographic proof.
Further, we deploy zk-SNARKs proofs following common reference string as public parameter when transaction is made. The proof allows sender to prove that she knows a secret for an instance such that the proof is succinct, can be verified very efficiently and does not leak the
secret. Non-malleability, small proofs and very effective verification make zk-SNARKs a classic tool in Zcash. Since we deal with NP problems therefore we have considered the elliptic curve cryptography to provide the same security like RSA but with smaller parameter size.
Lastly, we explain Zcash transaction process after minting the coin, the corresponding transaction completely hides the sender, receiver and amount of transaction using zero knowledge proof.
As future considerations, we talk about the improvements that can be done in term of decentralization, efficiency by comparing with top ranked cryptocurrencies namely Ethereum and Monero, privacy preserving against the thread of quantum computers and enhancements in shielded transactions.
Digital innovation in the quality management system from supply chain to final product conformityy
(2019)
As the new revolution is happening in the industry 4.0 as digitalization and the new trend in innovation is taken place. So, we want to digitalize the process from the supply chain to the final product conformity of the aircraft.
So every document which is received from the supplier like (eg.CoC, Inspection report, concession) digitally. When the part is received at the warehouse of the OEM the warehouse personal has a system to say that part A serial no X is the perfect fit for the part no By with the help of QR code and book the part into the ERP.
The biggest challenge we have is to reduce in production inspection method to be done by a human. We want to bring one more upper step that is automation with edition with IOT in the process to give better data processing to the Automation process plus reduce the overall inspection time and what is needed in create a proper visual automation control system and also with help of gauge Rand R make the process more accurate and also certify the traceability of the process . At finally there was so much data and we need data security for that to create a proper data source and data storage for supplier data as well as internal data security.
In the practice of software engineering, project managers often face the problem of software project management.
It is related to resource constrained project scheduling
problem. In software project scheduling, main resources are considered to be the employees with some skill set and required amount of salary. The main purpose of software
project scheduling is to assign tasks of a project to the available employees such that the total cost and duration of the project are minimized, while keeping in check that
the constraints of software project scheduling are fulfilled. Software project scheduling (SPSP) has complex combined optimization issues and its search space increases exponentially when number of tasks and employees are increased, this makes software project scheduling problem (SPSP) a NP-Hard problem. The goal of software project scheduling problem is to minimize total cost and duration of project which makes it multi-objective problem. Many algorithms are proposed up till now that claim to give near optimal results for NP-Hard problems, but only few are there that gives feasible set of solutions for software project scheduling problem, but still we want to get more efficient algorithm to get feasible and efficient results.
Nowadays, most of the problems are being solved by using nature inspired algorithms because these algorithms provide the behavior of exploration and exploitation. For solving
software project scheduling (SPSP) some of these nature inspired algorithms have been used e.g. genetic algorithms, Ant Colony Optimization algorithm (ACO), Firefly etc.
Nature inspired algorithms like particle swarm optimization, genetic algorithms and Ant Colony Optimization algorithm provides more promising result than naive and greedy algorithms. However there is always a quest and room for more improvement. The main purpose of this research is to use bat algorithm to get efficient results and solutions for software project scheduling problem. In this work modified bat algorithm is implemented where a different approach of random walk is used. The contributions of this thesis are to: (1) To adapt and apply modified multi-objective bat algorithm for solving software project scheduling (SPSP) efficiently, (2) to adapt and apply other nature inspired algorithms like genetic algorithms for solving software project scheduling (SPSP) and (3) to compare and analyze the results obtained by applied nature inspired algorithms and provide the conclusion.
The impact of organisational structure and organisational culture on the efficiency of a business
(2020)
The fear of losing flexibility and effectiveness due to an increased organisational structure induced by personal growth is causing SME's to defer structural changes. The purpose of this work is to examine whether the structural and cultural demands of employees match the structure and predominant culture within such a medium-sized company. As part of this, a survey was made to evaluate the current status and to suggest furthermore where and how changes would make sense to regain or even improve organisational efficiency.
This thesis deals with the development of a methodology / concept to analyse targeted attacks against IIoT / IoT devices. Building on the established background knowledge about honeypots, fileless malware and injection techniques a methodology is created that leads to a concept of a honeypot analyzation system. The system is created to analyse and detect novel threats like fileless attacks which are often utilized by Advanced Persistent Threats. That system is partially implemented and later evaluated by performing a simulated attack utilizing fileless attacks. The effectiveness is discussed and rated based on the results.
The subject of the following paper is the analysis of global company motives for taking on sport sponsorships as a corporate social responsibility (CSR) initiative. This work is compilatory in nature because it is derived from literature released by experts as well as real-life case studies. The expert literature provides a basis of theories and models regarding the fundamental motives for CSR and sport sponsoring and visualizes them by means of statistics and real-life case studies. This paper aims to inform individuals, leaders and specifically global organizations about the benefits that taking on a sport sponsorship may have for fulfilling a company’s CSR objectives
Neural networks have become one of the most powerful algorithms when it comes to learning from big data sets and it is used extensively for classification. But the deeper the network models, the lesser is the interpretability of such models. Although many methods exist to explain
the output of such networks, the lack of interpretability makes them black boxes. On the other hand, prototype-based machine learning algorithms are known to be interpretable and robust.
Therefore, the aim of this thesis is to find a way to interpret the functioning of the neural networks by introducing a prototype layer to the neural network architecture. This prototype layer will train alongside the neural network and help us interpret the model. We present architectures of neural networks consisting of autoencoders and prototypes that perform activity recognition from heart rates extracted from ECG signals. These prototypes represent the different activity groups that the heart rates belong to and thereby aid in interpretability.
The set of transactions that occurs on the public ledger of an Ethereum network in a specific time frame can be represented as a directed graph, with vertices representing addresses and an edge indicating the interaction between two addresses.
While there exists preliminary research on analyzing an Ethereum network by the means of graph analysis, most existing work is focused on either the public Ethereum Mainnet or on analyzing the different semantic transaction layers using
static graph analysis in order to carve out the different network properties (such as interconnectivity, degrees of centrality, etc.) needed to characterize a blockchain network. By analyzing the consortium-run bloxberg Proof-of-Authority (PoA) Ethereum network, we show that we can identify suspicious and potentially malicious behaviour of network participants by employing statistical graph analysis. We thereby show that it is possible to identify the potentially malicious
exploitation of an unmetered and weakly secured blockchain network resource. In addition, we show that Temporal Network Analysis is a promising technique to identify the occurrence of anomalies in a PoA Ethereum network.
After creating a new blockchain transaction, the next step usually is to make miners aware of it by having it propagated through the blockchain’s peer-to-peer network. We study an unintended alternative to peer-to-peer propagation: Exclusive mining. Exclusive mining is a type of collusion between a transaction initiator and a single miner (or mining pool). The initiator sends transactions through a private channel directly to the miner instead of propagating them through the peerto-peer network. Other blockchain users only become aware of these transactions once they have been included in a block by the miner. We identify three possible motivations for engaging in exclusive mining: (i) reducing transaction cost volatility (“confirmation as a service”), (ii) hiding unconfirmed transactions from the network to prevent frontrunning and (iii) camouflaging wealth transfers as transaction costs to evade taxes or launder money. We further outline why exclusive mining is difficult to prevent and introduce metrics which can be used to identify mining pools engaging in exclusive mining activity.
Both cryptocurrency researchers and early adopters of cryptocurrencies agree that they possess a special kind of materiality, based on the laborious productive process of digital ‘mining’ [1]. This idea first appears in the Bitcoin White Paper [2] that encourages Bitcoin adopters to construct and justify its value in metaphoric comparison to gold mining. In
this paper, I explore three material aspects of blockchain: physical infrastructure, human language and computer code. I apply the concept of 'continuous materiality' [3] to show how these three aspects interact in practical implementations of blockchain such as Bitcoin and Ethereum. I start from the concept of ‘digital metallism’ that stands for ‘fundamental value’ of cryptocurrencies, and end with the move of Ethereum to ‘proof-of-stake’, partially as a countermeasure against ‘evil miners’. I conclude that ignoring material aspects of blockchain technology can only further problematize complicated relations between their technical, semiotic and social materiality.