Reviewerly/exHarmony huggingface dataset:
Text-to-Image Classification Using AttnGAN with DenseNet Architecture

In this attentional generative adversarial networks (AttnGAN) for text-to-image conversion, we have used a CUB dataset with 12,000 images of 200 different birds with 10 captions for each image (12,000 * 10 captions). In random distribution splitting, we divided the data into training and testing sets with 49.2% of data and 50.8% of data, respectively. This method is able to synthesize fine-detailed images by the use of a global attention that gives more attention to the words in the textual descriptions. Also we have the deep attentional multimodal similarity model (DAMSM) that calculates the matching loss in the generator. Though this work produced images of high quality, there was some loss while training the system and it takes enough time for training. This paper proposes the DenseNet architecture with AttnGAN in order to reduce the loss and training time thereby synthesizing images with more distinct features. This technique was able to reduce the loss by 1.62% and could retrieve faster results by 768 s per iteration than the existing CNN architecture.
Scalability and precision by combining expressive type systems and deductive verification

Type systems and modern type checkers can be used very successfully to obtain formal correctness guarantees with little specification overhead. However, type systems in practical scenarios have to trade precision for decidability and scalability. Tools for deductive verification, on the other hand, can prove general properties in more cases than a typical type checker can, but they do not scale well. We present a method to complement the scalability of expressive type systems with the precision of deductive program verification approaches. This is achieved by translating the type uses whose correctness the type checker cannot prove into assertions in a specification language, which can be dealt with by a deductive verification tool. Type uses whose correctness the type checker can prove are instead turned into assumptions to aid the verification tool in finding a proof.Our novel approach is introduced both conceptually for a simple imperative language, and practically by a concrete implementation for the Java programming language. The usefulness and power of our approach has been evaluated by discharging known false positives from a real-world program and by a small case study.
Decay Momentum for Improving Federated Learning

We propose two novel Federated Learning (FL) algorithms based on decaying momentum (Demon): Federated Demon (FedDemon) and Federated Demon Adam (FedDemonAdam).In particular, we apply Demon to Momentum Stochastic Gradient Descent (SGD) and Adam in a Federated setting, which has shown to improve results in a centralized environment.We empirically show that FedDemon and FedDemonAdam have a faster convergence rate and performance improvements compared to state-of-the-art algorithms including FedAvg, FedAvgM and FedAdam.
Multi-Resolution Image Segmentation Based on a Cascaded U-ADenseNet for the Liver and Tumors

The liver is an irreplaceable organ in the human body, maintaining life activities and metabolism. Malignant tumors of the liver have a high mortality rate at present. Computer-aided segmentation of the liver and tumors has significant effects on clinical diagnosis and treatment. There are still many challenges in the segmentation of the liver and liver tumors simultaneously, such as, on the one hand, that convolutional kernels with fixed geometric structures do not match complex, irregularly shaped targets; on the other, pooling during convolution results in a loss of spatial contextual information of images. In this work, we designed a cascaded U-ADenseNet with coarse-to-fine processing for addressing the above issues of fully automatic segmentation. This work contributes multi-resolution input images and multi-layered channel attention combined with atrous spatial pyramid pooling densely connected in the fine segmentation. The proposed model was evaluated by a public dataset of the Liver Tumor Segmentation Challenge (LiTS). Our approach attained competitive liver and tumor segmentation scores that exceeded other methods across a wide range of metrics.
The use of training technology tools as the basis for its successful implementation in intra-organization training

The problem fields of research in the framework of the topic are the lack of classification of training methods in intra-organization training, the insufficient quality of the use of tools in the practice of intra-organization training, as well as the use of tools for evaluating and analyzing training activities. The highlighted aspects allowed us to determine the relevant vectors of the research: the competence of the coach, the systematization of training methods and techniques, the features of the use of the tools, the methodology of the tools for evaluation of training sessions. The most important characteristic of the competence of a corporate coach is the possession of the training technology tools at a high level. The article stands out the main competences of a corporate coach, such as focus on results, effective communication, effective self-presentation, persuasion and influence, confidence and stress resistance, creating a motivating educational environment. The authors pay particular attention to the phenomenon of pedagogical artistry, internal and external conditions of its development. The article introduces the basic training techniques (informational, stimulation, exercises for practical performance of work, group-dynamic exercises) and related training methods into the system. The authors consider the criteria and limitations that a trainer should to take into account when choosing training technology tools. The article introduces distinctions of tools when considering their arsenal (planning tools; direct implementation of the process; control (monitoring), evaluation and analysis of the results; post-training support). The authors indicate the following features of the use of training technology tools in intra-organization training: the formation of target guidelines for each stage of training implementation; determining tasks and the algorithm for training implementation; drawing up a training program; chronological planning of training units; planning of the necessary methodical support of training units; compliance with the principle of training planning based on an iterative model with one or more contours; the use of business and simulation games, exercises and tasks; using multiple studies scenarios for conducting classes; presenting information depending on the features of its perception; taking into account the target audience; taking into account the age characteristics of the audience, etc.
Text2Video

To make video creation simpler, in this paper we present Text2Video, a novel system to automatically produce videos using only text-editing for novice users. Given an input text script, the director-like system can generate game-related engaging videos which illustrate the given narrative, provide diverse multi-modal content, and follow video editing guidelines. The system involves five modules: (1) A material manager extracts highlights from raw live game videos, and tags each video highlight, image and audio with labels. (2) A natural language processor extracts entities and semantics from the input text scripts. (3) A refined cross-modal retrieval searches for matching candidate shots from the material manager. (4) A text to speech speaker reads the processed text scripts with synthesized human voice. (5) The selected material shots and synthesized speech are assembled artistically through appropriate video editing techniques.
Reinforcing the Innovation Performance of SMEs Through Innovation Culture and Government Support

Innovation has become an approach to create value to customer in order to remain competitive in the market. However, previous research on innovation performance particularly among Bumiputera SMEs has received little intention. Hence, Bumiputera SMEs need to inculcate the innovation culture in order to generate innovation performance. An interview was conducted with a sample of ten Bumiputera entrepreneurs in Malaysia which probing into their outlook on the innovation culture towards innovation performance. The results showed that innovation culture in Bumiputera SMEs is important and government support plays an important role to strengthen the relationship between innovation culture and innovation performance. Therefore, this study provides useful pointers to entrepreneurs and policy makers on the importance of innovative culture and enhancing innovation performance in Bumiputera SMEs.
Introduction to Digital Forensics

There are radical changes in the computing world each second. Significant advancements in computer technologies enable the cyberattackers to perform a high number of successful cyberattacks results in damaging critical infrastructures, financial loss, and health. Several nations adopt cyberforensics to investigate such cybercrimes, and however, with current technologies, it is hard to get the latent evidence from the crime scene. The evidence could be massive in size, and it is challenging to find the real culprit from that enormous information. Moreover, the evidence demands live acquisition, which is somehow not possible as an attacker always tries to destroy the digital footprint. Cybercrime’s data is getting astonishing day by day as it expands its horizon and costing millions of dollars to the government. Even the highest turnover companies are prone to cybercrime. This is not the biggest problem since an attacker can compromise the security of these companies and can use their resources to perform a nationwide attack that includes ransomware, identity theft, violating privacy, human and sex trafficking, selling weapons or drugs online and data breaches. The data breach is one of the most influential and fastest-growing cyberattacks in various countries, specifically in the USA. That includes the major data breaches suffered by Marriott exposed around 500 million user account and Yahoo data breach uncovered 3 billion user account and Equifax breach in 2017 exposed 150 million accounts, which are some of the most significant breaches ever occurred in the history of cyberspace. According to cybersecurity ventures, throughout 2017–2021, the global spending on cybersecurity exceeds $1 trillion, which is enormous spending for just preventing data breaches. Instead, we can use this spending on a real problem such as climate change. This chapter deals with a formal introduction to cyberforensics and how anyone can perform forensics on different platforms, such as computers and networks. We also elaborate on the different architecture of forensics to get a generalized idea about how to collect data and how to analyze it for a finite conclusion about the crime scene. The chapter also describes different open-source tools and technologies used by various forensic agencies in order to retrieve the data from the evidence.
Juvenile and youth crime: current state and prospects

The official decline in registered crime rates is associated with a high level of its latency, new forms and methods of its commission, «computerization of crime» and an artificial redistribution of public attention to extremist crime and corruption. Russian crime continues to be self-serving, violent, and organized. A factor of its latency is the problem of the young people’s career placing in the job and low pay for their work. The Internet is actively used by «criminal IT specialists» in drug trafficking, deliberately false reports of acts of terrorism; juveniles and young people are chosen as perpetrators of crimes and as victims of crimes. They are also characterized by participation in the organization of prostitution, illegal arms trafficking, and self-serving violent crimes. The family remains both the factor of juvenile and youth crime, and the main subject of its prevention. The adoption of the criminogenic draft law «On the prevention of domestic violence», the legalization of the drug market and the authorization of the use of methadone in Russia are unacceptable. Prevention of crimes committed by juveniles, young people and their families is a priority, it should be based on the developed state ideology. It is based on morality, patriotism, healthy lifestyle, and law-abiding behavior. A return to the priority of international law is essential. This will preserve the system of prevention and suppression of the most dangerous types of crimes using mechanisms of international control and interaction.
A graphical method of cumulative differences between two subpopulations

Abstract Comparing the differences in outcomes (that is, in “dependent variables”) between two subpopulations is often most informative when comparing outcomes only for individuals from the subpopulations who are similar according to “independent variables.” The independent variables are generally known as “scores,” as in propensity scores for matching or as in the probabilities predicted by statistical or machine-learned models, for example. If the outcomes are discrete, then some averaging is necessary to reduce the noise arising from the outcomes varying randomly over those discrete values in the observed data. The traditional method of averaging is to bin the data according to the scores and plot the average outcome in each bin against the average score in the bin. However, such binning can be rather arbitrary and yet greatly impacts the interpretation of displayed deviation between the subpopulations and assessment of its statistical significance. Fortunately, such binning is entirely unnecessary in plots of cumulative differences and in the associated scalar summary metrics that are analogous to the workhorse statistics of comparing probability distributions—those due to Kolmogorov and Smirnov and their refinements due to Kuiper. The present paper develops such cumulative methods for the common case in which no score of any member of the subpopulations being compared is exactly equal to the score of any other member of either subpopulation.
Distribution-Aware Counterfactual Explanation by Mixed-Integer Linear Optimization

Post-hoc explanation methods for machine learning models have been widely used to support decision-making. One of the popular methods is Counterfactual Explanation (CE), also known as Actionable Recourse, which provides a user with a perturbation vector of features that alters the prediction result. Given a perturbation vector, a user can interpret it as an "action" for obtaining one's desired decision result. In practice, however, showing only a perturbation vector is often insufficient for users to execute the action. The reason is that if there is an asymmetric interaction among features, such as causality, the total cost of the action is expected to depend on the order of changing features. Therefore, practical CE methods are required to provide an appropriate order of changing features in addition to a perturbation vector. For this purpose, we propose a new framework called Ordered Counterfactual Explanation (OrdCE). We introduce a new objective function that evaluates a pair of an action and an order based on feature interaction. To extract an optimal pair, we propose a mixed-integer linear optimization approach with our objective function. Numerical experiments on real datasets demonstrated the effectiveness of our OrdCE in comparison with unordered CE methods.
openSkies - Integration of Aviation Data into the R Ecosystem

Aviation data has become increasingly more accessible to the public thanks to the adoption of technologies such as Automatic Dependent Surveillance-Broadcast (ADS-B) and Mode S, which provide aircraft information over publicly accessible radio channels.Furthermore, the OpenSky Network provides multiple public resources to access such air traffic data from a large network of ADS-B receivers.Here, we present openSkies, the first R package for processing public air traffic data.The package provides an interface to the OpenSky Network resources, standardized data structures to represent the different entities involved in air traffic data, and functionalities to analyze and visualize such data.Furthermore, the portability of the implemented data structures makes openSkies easily reusable by other packages, therefore laying the foundation of aviation data engineering in R.
A Fast Covariance Union Algorithm for Inconsistent Sensor Data Fusion

We consider a challenging scenario in this research, where the sensors may receive spurious sensor data, potentially causing inconsistent state estimates. Covariance union (CU) is a fault-tolerant algorithm that can deal with inconsistent state estimation fusion. However, existing CU algorithms suffer from high computational costs due to optimizing nonlinear cost functions when generating fusion weights. To overcome this deficiency, an efficient CU algorithm named fast covariance union (FCU) is developed. We have proved that the fusion weight of FCU can be optimally generated by a closed-form algorithm without optimizing any nonlinear cost function, leading to better fusion efficiency. In addition, the FCU algorithm ensures the fused estimate be consistent as long as one of the estimates is consistent. Finally, the Monte Carlo simulation results show that the FCU algorithm has higher computational efficiency than the existing CU algorithms and handles the spurious sensor data fusion effectively.
Effective and Safe Trajectory Planning for an Autonomous UAV Using a Decomposition-Coordination Method

In this paper, we present a Decomposition Coordination (DC) method applied to solve the problem of safe trajectory planning for autonomous Unmanned Aerial Vehicle (UAV) in a dynamic environment. The purpose of this study is to make the UAV more reactive in the environment and ensure the safety and optimality of the computed trajectory. In this implementation, we begin by selecting a dynamic model of a fixed-arms quadrotor UAV. Then, we define our multi-objective optimization problem, which we convert afterward into a scalar optimization problem (SOP). The SOP is subdivided after that into smaller sub-problems, which will be treated in parallel and in a reasonable time. The DC principle employed in our method allows us to treat non-linearity at the local level. The coordination between the two levels is achieved after that through the Lagrange multipliers. Making use of the DC method, we can compute the optimal trajectory from the UAV's current position to a final target practically in real-time. In this approach, we suppose that the environment is totally supervised by a Ground Control Unit (GCU). To ensure the safety of the trajectory, we consider a wireless communication network over which the UAV may communicate with the GCU and get the necessary information about environmental changes, allowing for successful collision avoidance during the flight until the intended goal is safely attained. The analysis of the DC algorithm's stability and convergence, as well as the simulation results, are provided to demonstrate the advantages of our method and validate its potential.
Web censorship measurements of HTTP/3 over QUIC

Web traffic censorship limits the free access to information, making it a global human rights issue. The introduction of HTTP/3 (HTTP over QUIC) yields promising expectations to counteract such interference, due to its novelty, build-in encryption, and faster connection establishment. To evaluate this hypothesis and analyze the current state of HTTP/3 blocking, we extended the open-source censorship measurement-tool OONI with an HTTP/3 module. Using an input list of possibly-blocked websites, real-world measurements with HTTPS and HTTP/3 were conducted in selected Autonomous Systems in China, Iran, India, and Kazakhstan. The presented evaluation assesses the different blocking methodologies employed for TCP/TLS versus the ones employed for QUIC. The results reveal dedicated UDP blocking in Iran and major IP blocklisting affecting QUIC in China and India.
Effective Usage of Support Vector Machine in Face Detection

With the rapid growth in Technology in terms of multimedia contents such as Biometrics, Facial recognition etc. Facial detection got much attention over the past few years. Face recognition describes a biometric technology that attempts to establish an identity. In this paper, I would like to review about a facial recognition system using machine learning especially, using support vector machines. In any case, point of this exploration is to give extensive writing survey over face acknowledgment alongside its applications. Furthermore, after top to bottom conversation, a portion of the significant discoveries are given in end.
Learning to See by Looking at Noise

Current vision systems are trained on huge datasets, and these datasets come with costs: curation is expensive, they inherit human biases, and there are concerns over privacy and usage rights. To counter these costs, interest has surged in learning from cheaper data sources, such as unlabeled images. In this paper we go a step further and ask if we can do away with real image datasets entirely, instead learning from noise processes. We investigate a suite of image generation models that produce images from simple random processes. These are then used as training data for a visual representation learner with a contrastive loss. We study two types of noise processes, statistical image models and deep generative models under different random initializations. Our findings show that it is important for the noise to capture certain structural properties of real data but that good performance can be achieved even with processes that are far from realistic. We also find that diversity is a key property to learn good representations. Datasets, models, and code are available at this https URL.
Line following and beacon tracking robot based on Arduino Mega 2560

This paper introduces a kind of line following and beacon tracking robot based on Arduino mega2560. It is an intelligent robot with Arduino MCU as the control unit and combined with a variety of sensors to complete line following, obstacle detection and it also can locate the infrared beacon and navigate to the beacon area accurately. The circuit design of each part of the robot and the general structure of C program code are analyzed and displayed, and the performance of the robot in the actual field is discussed in this paper. The conclusion is that the robot can basically travel along with the guideline in a certain speed range, and can successfully track the beacon and stop at the beacon area.