Reviewerly/exHarmony huggingface dataset:
An Intelligent and Collaborative Multiagent System in a 3D Environment

Multiagent systems (MASs) allow facing complex, heterogeneous, distributed problems difficult to solve by only one software agent. The world of video games provides problems and suitable environments for the use of MAS. In the field of games, Unity is one of the most used engines and allows the development of intelligent agents in virtual environments. However, although Unity allows working in multiagent environments, it does not provide functionalities to facilitate the development of MAS. The aim of this work is to create a multiagent system in Unity. For this purpose, a predator&ndash;prey problem was designed in which the agents must cooperate to arrest a thief driven by a human player. To solve this cooperative problem, it is required to create the representation of the environment and the agents in 3D; to equip the agents with vision, contact, and sound sensors to perceive the environment; to implement the agents&rsquo; behaviors; and, finally but not less important, to build a communication system between agents that allows negotiation, collaboration, and cooperation between them to create a complex, role-based chasing strategy.
Quantum Key Distribution Under Attack

In this chapter we'll continue on the emerging science of quantum key distribution (QKD). This is a key technology and will undoubtedly play a big part in many a person's life in the near future. The concepts introduced in the last chapter will be greatly expanded upon, including the hardware side of things. But first, we'll cover various types of QKD-focused cryptographic attacks as these unfortunately will be an issue.
The AES and Other Established Cryptographic Technologies

By now, you're aware of some historically relevant cryptographic concepts and how prime numbers relate to encryption algorithms. In this chapter we're moving on to the current-day de facto cryptographic staple, the Advanced Encryption Standard (AES), in addition to tackling many other relevant concepts in the field. We will first visit some basics, including the two major numeric systems in computer science: binary and hexadecimal, for those who feel they need a refresher.
Identification of Entities in Scientific Documents

An important aspect of research is literature survey. Availability of large amount of scientific literature across different domains triggers the need for optimized systems which provide relevant literature to researchers. Scientific articles are indexed with keyphrases. These keywords or keyphrases give an insight of the entire scientific article. Labelled keyphrases help in organization of scientific papers and assist in further exploration and analysis. The presented work is a contribution to the large body of research on automatic extraction of keyphrases. This work makes use of sequence modelling approach of machine learning to identify entities in scientific articles and classify them into ‘Process’, ‘Task’ and ‘Material’. Features are extracted from scientific articles, and Conditional Random Field (CRF) is used to identify and classify the entities. To signify the effectiveness of the approach, we have carried out the experiment and evaluation on SemEval 2017 dataset. Results depict that the proposed approach is considerably successful in identifying and labelling keyphrases.
Comparative Performance of Prediction Methods for Digital Wallet Transactions in the Pandemic Period

A pandemic situation such as Covid-19 which is still ongoing has given significant impacts to various sectors such as education, economy, tourism, and social which is in turn impacting the community at a national scale. On the other hand, the pandemic situation has also brought a positive impact on companies engaged in finance that utilizes information technology, namely digital wallets, a company that runs a market place in the digital world. In an effort to anticipate a dynamic market place, the company needs to predict the movement of transactions from time to time by building a model and performain the simulation to such model. Based on this problem, this paper presents simulations on the prediction models based on methods namely, naïve, Single Moving Average (SMA), Exponential Moving Average (EMA), combined SMA-naive methods, combined EMA-naive methods, as well as did the comparison of the best performance of every model by using Mean Absolute Percentage Error (MAPE) measurement. From the results of comparison, it is concluded that exponential moving average method delivers the best performance as prediction tool with MAPE of 23,4%.
Augmented Reality Building Surveillance System

This electronic document explains one of the potential augmented reality use cases. This paper presents an augmented reality building surveillance system. This white paper explains the scope of augmented reality and how it can be implemented in order to develop a fully functional building surveillance system. Moreover, analysis of building surveillance related KPIs is visualized using different types of graphs and charts. The paper also stresses on the need of an augmented reality building surveillance system. The drawbacks of traditional surveillance systems are discussed, and we aim to resolve these drawbacks with our solution. Not only our solution helps save on manpower, electricity bill, and training costs, but it also helps an easy administration of the building and hence reduce any kind of loss due to administration negligence.
Enhancing Computational Time of Lempel-Ziv-Welch-Based Text Compression with Chinese Remainder Theorem.

The science and art of data compression is presenting information in a compact form. This compact representation of information is generated by recognizing the use of structures that exist in the data. The Lempel-Ziv-Welch (LZW) algorithm is known to be one of the best compressors of text which achieve a high degree of compression. This is possible for text files with lots of redundancies. Thus, the greater the redundancies, the greater the compression achieved. In this paper, the LZW algorithm is further enhanced to achieve a higher degree of compression without compromising its performances through the introduction of an algorithm, called Chinese Remainder Theorem (CRT), is presented. Compression Time and Compression Ratio was used for performance metrics. Simulations was carried out using MATLAB for five (5) text files (of varying sizes) in determining the efficiency of the proposed CRT-LZW technique. This new technique has opened a new development of increasing the speed of compressing data than the traditional LZW. The results show that the CRT-LZW performs better than LZW in terms of computational time by 0.12s to 15.15s, while the compression ratio remains same with 2.56% respectively. The proposed compression time also performed better than some investigative papers implementing LZW-RNS by 0.12s to 2.86s and another by 0.12s to 0.14s.&#x0D; Keywords: Data Compression, Lempel-Ziv-Welch (LZW) algorithm, Enhancement, Chinese Remainder Theorem (CRT), Text files.
Force of Gravity Oriented Classification Technique in Machine Learning

The level of impersonation from nature is astonishingly high in the domain of Evolutionary Computation and Computational Intelligence and attempts are being constantly made to develop more number of algorithms, which completely or partially imitate nature and the activities that occur in a particular natural phenomenon. The same can also be employed in various aspects of machine learning such as classification methodologies. This paper puts forward a novel approach for machine learning classification by employing the concept of center of mass and force of gravity. The performance of the proposed force of gravity (Fg)-based classification technique has been evaluated on a number of standard and popular datasets. The efficiency of the proposed method of classification can be perceived when the output obtained is compared with other standard and popular methods of classification such as Logistic Regression, KNN, Decision Tree, and SVM.
The First Era of Digital Encryption

You're probably used to entering passwords into devices by now; it's a part of everyday life, like locking and unlocking one's front door. From email services to mobile devices, we all guard our privacy to a varying extent in the digital realm. And that's exactly how it should be. In this chapter, we'll take a quick look at modern-era digital encryption. But first, we'll revisit some of the most game-changing moments in the historical context of all things cryptographic, as you may not be familiar with the incredibly long history of the science.
ANNINPTSIGTEST: MATLAB function to test the statistical significance of inputs

This code tests the statistical significance of inputs by using an artificial neural network with a flexible structure. The code tries to find the best number of neurons for the neural network for testing the significance of inputs.
Knowledge Visualization in Crystal Modeling

3D graphics visualization is equal part mathematics, geometry, and design. Based on the knowledge visualization framework, the author investigates the structure of a mineral to find if meaningful visualization pertaining to the field of art can be extracted from scientific resource. Working with the lines, spheres, and polygons that characterize crystal at the nanoscale provided the author an exceptional environment from which to extract coherent visualizations sustainable in the art environment. The outcome was tested in a variety of interactive platforms and opened a larger debate on cross-pollination between science and arts. Additionally, the experiment provided new ground of investigation for unexpected connections between mathematics, earth sciences, and local cultures.
Stored Procedures, Views, and Functions

In this chapter, we are going to look into ways to leverage the built-in programmable features of SQL Server that allow for maximum performance and efficiency.
A Novel Decentralized Blockchain Networks Model with High Concurrenc(Blockchain Networks Model with High Concurrency)

Blockchain is very important in finance field and electronic business field, so many researchers are attracted to study the technologies of blockchain. Since the transactions in blockchain takes much time, and they make the blockchain poor efficiency, business processes across organizations require the transactions as soon as possible. Concurrency is attracted much attention and is very important in blockchain field. In this paper, a novel decentralized blockchain network model with high concurrency is proposed. First, the idea of the proposed model is stated. Second, the high concurrency blockchain network model is proposed. Third, the corresponding algorithms are designed according to the proposed model. Furthermore, the experiment is conduced and the results show that proposed model works well.
Voting Based Constructive Covering Algorithm

As one of the typical neural networks from the geometric perspective, constructive covering algorithm (CCA) has received extensive attention since it came out. It constructs the network through randomly initializing the cover center, which also creates the randomization of the algorithm. This paper proposes a method called voting based constructive covering algorithm (V-CCA). The main mechanism of V-CCA is introducing the ensemble technique to overcome the above-mentioned shortcoming. V-CCA trains a group of classifiers each with random initialization instead of a single classifier to generate a stronger learner. Numerical experiments on 16 UCI datasets demonstrate the effectiveness of V-CCA.
Correction to: Scaling Laws of Paleoindian Projectile Point Design

Due to typesetting mistake, the correction to the formulas at the bottom of page 12 in H2 and H3 were overlooked. Also, Table 2 footnote was incorrectly presented.
Optimal Smart Contracts with Costly Verification

We study optimal smart contract design for monitoring an exchange of an item performed offline. There are two parties, a seller and a buyer. Exchange happens off-chain, but the status update takes place on-chain. The exchange can be verified but with a cost. To guarantee self-enforcement of the smart contract, both parties make a deposit and the deposits must cover payments made in all possible final states. Both parties have an (opportunity) cost of making deposits. We discuss two classes of contract: In the first, the contract only interacts with the seller, while in the second, the contract can also interact with the buyer. In both cases, we derive optimal contracts specifying optimal deposits and verification policies.
Quantum Computing: The Next Big Paradigm

As well established and world changing as the digital revolution has been, its days are numbered. The never-ending march of scientific progress will deliver us a new paradigm in the very near future: quantum computing. Its applications, while at first purely theoretical, will eventually cover many aspects of our lives: communications, medicine, security, and even world politics. In this chapter we'll take a glance at some of the ramifications of quantum computing before moving into specifics with the chapters to follow.
Modeling and Technical Analysis of Solar Tracking System to Find Optimal Angle for Maximum Power Generation using MOPSO Algorithm

This paper aims to determine the optimal performance characteristics of a solar tracking system in order to maximize the power generation through using the MOPSO algorithm. Considering the sun path during a day, the necessity of using solar tracking systems to achieve the maximum power output from photovoltaic (PV) panels has been investigated. The solar tracking system allows PV arrays to follow sunlight all day long. The unidirectional tracking system follows the sun path, thereby optimizing the angular motion of PV arrays relative to the sun resulting in higher power generation. To evaluate the performance of a PV system, the total solar radiation was calculated first for both fixed and unidirectional tracking systems. Analyzing the results indicates that for June 20th the power generation of the PV module equipped with a unidirectional tracker is 35% higher than the fixed PV module. The optimal value of the declination angle, Azimuth, and arrays’ tilting angles in a unidirectional tracking system calculated using the MOPSO algorithm are , and respectively.
Blockchain and Cryptocurrencies

By now you have seen and read quite a bit about blockchain technology. However, I want to close of this book with some final concepts that you should know and understand. These will allow you to zoom into some important aspects when you look at the crypto-markets and see how they function. Several new financial instruments have been devised with the creation of cryptocurrencies and existing financial assets have found their way into the world of cryptocurrencies.
ANNEARLY: MATLAB function to forecast univariate time series

This M-File forecasts univariate time series such as stock prices with a feedforward neural network. It finds the best (minimum RMSE) network automatically. It is revised for the replacement of obsolete functions of Matlab with the new functions.
Notai e commercialisti in biblioteca al servizio dei cittadini

The dossier “Innovative Libraries” presents a review of the experiences of libraries that have in common the search for solutions aimed at redefining their role, with particular attention to the social dimension and new paths of access to knowledge. From a library experience conceived as a community hub, we move on to examine a case of involvement of local businesses in a cultural welfare perspective. The case of Turin is original. Here libraries offer to citizens hospitality in their offices to meet with professionals (accountants, notaries, etc.) to obtain advice, while in Rome and Milan there is a growing commitment to the prison population. The case of proximity libraries and condominium libraries is unique, while the promotion of active citizenship and the practice of listening is growing. Innovating also means transferring skills to students that enable them to operate in a Wikimedian environment or use the collections as an opportunity for conversation with the community. Innovation for academic libraries also passes through their ability to present themselves as digital and participatory thanks to the opportunities offered by the Third Mission and the opportunities offered to academic libraries to respond to the strong drives towards open science. Finally in a short article is described the new alliance between a public library and a library for patients of an oncology institute.
The Rollicking World of Quantum Mechanics

Deepening one's knowledge on quantum mechanics and related physics paves the way for a greater understanding of the definite future of computing and cryptography. Quantum mechanics is a branch of physics focusing on the smallest scales known to us: the atomic and the sub-atomic realms. It has numerous implications for our world, as discussed in the previous chapter, and it comes with some controversy as well. We'll now go more or less clavicle deep into this sub-atomic level and explore its numerous paradigm-shifting phenomena.
Encryption of Data

You’ve implemented a system, and you’ve created the best database structure you can architect. Your system is taking off, and you have hundreds or thousands of clients and many gigabytes of customer data on your server. Things couldn’t be better, right? Then you get a notification that something has gone wrong with your database. Somehow, a malicious entity has gained information about all of your customers because you were storing that information in your database in plain text. This nightmare scenario could be you, if you don’t take at least some minimal measures to prevent it.
Robust Sequence Embedding for Recommendation

Sequential recommendation is a significant task that predicts the next items given user historical transaction sequences. It is often reduced to a multi-classification task with the historical sequence as the input, and the next item as the output class label. Sequence representation learning in the multi-classification task is of our main concern. The item frequency usually follows the long tail distribution in recommendation systems, which will lead to the imbalanced classification problem. This item imbalance poses a great challenge for sequence representation learning. In this paper, we propose a Robust Sequence Embedding method for the recommendation, RoSE for short. RoSE improves the recommendation performance from two perspectives. We propose a balanced k-plet sampling strategy to make each training batch balanced at the data level and propose the triplet constraint for each training sequence to make sure of balance and robust distribution in feature space at the algorithmic level. Comprehensive experiments are conducted on three benchmark datasets and RoSE shows promising results in the face of item imbalance.
Recording Services, Cost, and Revenue

This chapter shows how and in which detail to record the quantities, services, values, and sales actually produced. Entering the actual data is not only a prerequisite for determining the period results. By comparing the actual data with the plan data in Chap. 4 , one can determine all variances in sales, products, and inventories and analyze them. The analysis of what happens in the cost centers is explained in Chap. 6 .
Effects of Early Update Cost in Cloud Object Storage Scheduling

Object storage, a type of cloud storage as a service, allows organizations to have highly available storage with zero infrastructure investments and thus fewer operation costs. Usually, a fixed-selection of storage tier on the cloud service is not appropriate since the workload on the objects is not static, and each storage tier cost can be drastically different from another. To efficiently select the appropriate object storage tiers, tedious work is usually required for planning, which could be modeled as the job shop scheduling problem with a pre-calculated threshold. To the best of our knowledge, no solution considers an early update cost, a penalty cost when the objects are moved out to another tier or deleted before an agreed stored-time is reached. In this paper, we present the effect of the early update cost of the existing cloud object scheduling algorithms, particularly when objects in a cold tier are read heavily, or spike read. From the experiments, it is found that the performance of the algorithms can be enormously worse when the EUC is applied.
A method based on regin division for evaluating the laser disturbing picture

Evaluating the quality of disturbing picture is one of important issues in the field of laser and electric picture. The result of evaluating should be matched with human visual sense. The article analyzes the characteristics of laser and electric disturbing picture and the limitations of the common image evaluating methods. Then, basing on the human visual sense, we use the Otsu method for binary separating, and adjust the threshold T, and separate the disturbing picture. We use the different methods to evaluate the picture and get the consequence compared with the human visual sense. We summarize the method for evaluating the laser and electric picture. Then, we design the project. We use the real disturbing picture to verify the performance of the evaluating methods. And we get the consequence that the method based on Otsu separating matches mostly for human visual perception.
Self-Matching Moving Target Detection Algorithm Based On Gaussian Mixture Model And CSIFT

With the development of unmanned aerial vehicle (UAV) technology, more and more unmanned aerial vehicles have entered various fields, including the aspect of moving target detection. Due to the characteristics of the drone, the captured video does not have a fixed background, which makes the traditional moving target detection algorithm unusable. Herein, this paper proposes a self-matching detection algorithm based on Gaussian mixture model and CSIFT. This algorithm is applied to unmanned On board, under the background of moving targets, the target can be identified when there is relative movement between the target and the background.
Dual DPT for coherent accumulation of high-speed high-maneuvering target

With the development of stealth technology, the high-speed high-maneuvering target is too weak to detect. Traditional fractional Fourier transform (FRFT) and radon Fourier transform (RFT) have good performance in coherent accumulation but need rough estimation of velocity and acceleration in advance. To obtain the rough estimation, a dual discrete polynomial phase transform (DPT) algorithm is proposed in this paper. The DPTs with dual pulse delays are designed and superimposed together to obtain extra signal-to-noise ratio (SNR) gain. Theoretical derivation and experiment confirm that the output SNR of proposed DPT for high-speed high-maneuvering target has about 2dB gain without reducing the resolution, compared with traditional DPT algorithm.
Responsible Self-Funding in Dash Governance System

Decentralized voting and self-funding allow cryptocurrencies to make joint decisions and finance their development. Dash cryptocurrency has a working self-funding and decision-making system for supporting event and improvement proposals---the Dash Governance System. While it is fully operational, as currently designed, it does not incentivize voting efficiency. The Dash Governance System struggles to scale, with the number of proposals rising, as each participant needs to review each proposal. This work introduces a new mechanism for processing proposals. It meets scalability and makes thoughtful voting the most profitable strategy.
Zero-Knowledge User Authentication: An Old Idea Whose Time Has Come (Transcript of Discussion)

So, user authentication on the web: I don’t think it needs much introduction. Still, often, just a username and password, unfortunately. And I think it would be an understatement to say that this is suboptimal, both in terms of security and usability.