Reviewerly/exHarmony huggingface dataset:
Green Cloud Computing-Oriented Algorithmic Approach-Based Virtual Machine Consolidation

Data centres are the hubs for global connectivity through networking. Cloud computing has become an indispensable need to fulfil the insatiable ever-expanding networking demand. More and more data centres are raised to fulfil this objective, consequently resulting in enhanced environmental pollution. Hence, server-related energy conservation is an indispensable need for minimizing carbon emissions. Factors like grid-related energy consumption and associated carbon emissions enhance electricity cost and carbon tax which results into total operating costs of data centres. The aim focuses on maximization of green energy usage with minimization of operating cost and carbon emission through process of virtual machine placement decision. Dynamic virtual machine consolidation emerges as a convincing solution for minimized energy consumption with optimized resource utilization in data centres. Virtual machine consolidation problems being truly NP-hard demand several heuristic algorithms for addressing the problem. Since most of the existing works are focussed for reducing number of hosts and their present resource utilization unmindful of future resource requirements, it results into unnecessary virtual machine migrations along with enhanced service-level agreement (SLA) violations. This problem can be duly addressed by considering current and future resource utilization by negotiating it as a bin-packing problem. The prediction of future resource utilization can be secured by using a k-nearest neighbour regression-based model.
Immersive Adventure Games Development using 360-degree video

Immersive Interactive 360° videos, experienced through Head-Mounted Displays (HMD), constitute a particular case of VR applications for which it is relatively easy to record content nowadays, and that can be explored as a game format. We therefore explore the idea of using live action 360° videos as the basis for immersive adventure games. In particular, we explore possible interactions in immersive adventure games based on 360° videos, in terms of game elements and mechanics, and the player's interface with those. To support this, we developed a browser-based framework for creating such games, and conducted a user study with a game created specifically for that purpose. The results obtained indicate a high level of satisfaction with the chosen control schemes and game mechanics, and suggest that the framework can be used to create this kind of experience.
Hash Constructions for CoAP under an IoT Environment

Hash construction is a very famous method. This is popular because the hash function is found in almost all security algorithms. Various uses of hash functions have been found since the early stages of computing and communication. The most fascinating thing of a hash construction is its one way property. One way property of a hash function has been used in many places for example, generating security key for two party communications and creating a digital signature to safeguard an important document. The hash functions are in use from very long, i.e. when the Uninterrupted Power Supply (UPS) based machines were communicated. Even at that time also the hash functions were of three types, i.e. MD, SHA and BLAKE. When it comes to lightweight computing, i.e. communicating machines without direct power supply or with stored energy only, the hash function is considered to be the best. A new design of hashing based on a sponge construction is proposed for the secure communication between constrained devices in lightweight fashion. There were many other developments in this field occurred before the sponge construction comes into existence those are JH, Keccak, BLAKE and SHA. Although there are a huge number of hash constructions are available, the original need of a lightweight IoT environment is still not fulfilled. In this presented paper, the authors will discuss all working methodology for hash constructions along with their positive and negative aspects. Also, a fair comparison of several hash design has be given for the easiness of its users.
Development of Marketplace User Interface Design with Virtual Booth Based on Mobile for Ornamental Fish SMEs

Ornamental fish have promising economic potential in Indonesia by being ranked 3rd in the world's ornamental fish exporters. With increasing production potential, Indonesia is also faced with a crucial problem, namely marketing. Marketing that is being done at this time still traditionally opens a place in certain markets so that buyers are only around that area. With the problems that occur in the marketing process that is carried out, it still does not support income from farmers and sellers. Therefore, it is necessary to expand marketing and sales to domestic and foreign countries. So in this study, we developed a combination of concepts in the market in the form of a virtual booth in a mobile application. Design the user interface of a mobile application using a user-centered design approach. This mobile-based virtual booth can make it easier for ornamental fish traders/breeders to display the ornamental fish products they produce in their respective booths in the form of video or live to consumers. With this design, it is hoped that it will make it easier for SMEs in the ornamental fish sector to communicate with buyers from within and outside the country so that transactions occur with each other. With this, it can increase the income of SMEs in the ornamental fish sector. In addition, it can provide an application platform that is easy for users to use.
Virtual Reality Exposure Therapy and Physiological Data Analysis for Treatment of Stress Disorders

Anxiety disorders are diagnosed when people become overreactive, disassociated, and feel emotionally unable to control feelings to the extent that their daily lifes are affected. Driving phobia is one of the widespread anxiety disorders in modern society, which cause problematic disruptions of a patient's daily activities. Exposure therapy is an approach gaining popularity for treating patients with stress disorders. Virtual reality (VR) technology allows people to interact with objects and stimuli in an immersive way. The VR for phobic therapy using indirect exposure, which can be safely discontinued or lowed in terms of intensity, is the area of research with literature published and patents granted. This research focuses on reviewing virtual reality exposure therapy (VRET) literature and patents. The chapter also presents the research and development of a novel driving phobia VRET system with the detailed experiments to demonstrate the design, development, implementation, enhancement, and verification of VRET.
Synergetic Approach to Describing the Cooperative System

The synergetic approach considers the processes of self-organization occurring in open systems. Modern views on cooperation in rural areas consider it as an element of self-organization in their development. The paper aims to study the system of consumer and production cooperation in agriculture. The paper implements the theory of complex systems to identify bifurcation points and determine the stability of the cooperation system. The input data includes the financial statements of agricultural production (20 units) and consumer cooperatives (23 units) of the Republic of Tatarstan. The authors choose the Republic of Tatarstan for their research since the region is a leader in developing agricultural cooperation in the Russian Federation. The selected study period is 2011–2019. The research results are presented graphically. The authors selected revenue and profit as the parameters of the system’s state. The authors determine the bifurcation points in the system of cooperation of the Republic of Tatarstan in 2017 and 2018, which characterize the loss of stability of the system and its transition to another state. This process is caused by the impact of external factors on the cooperation system, especially state support measures. A polynomial and logarithmic dependencies describe the trend dependencies of the development of the cooperation system. The authors proved that consumer cooperation is less sustainable than industrial cooperation. In the further development of the system of cooperation in the region, the growth of selected parameters and sustainability is expected.
The Approach to Flow Management in Virtual Computational Environment for Up-to-Day Telecom Networks

Data streams that are transmitted over communication networks are growing very quickly, this is facilitated by the progress of the service such as IoT, M2M, etc. The provision of high-quality communication services is increasingly influenced by the efficiency of performing calculations in the data centers of telecom operators, whose resources are limited. SDN technologies make it possible to redistribute transmitted data streams in networks to reduce their load, but they require more computing resources. Telecom operators’ networks not only transmit significant amounts of information, but also process very large information flows in their computing nodes, including virtual ones. Controlling the transfer process with a large number of threads becomes a bottleneck. To service flows in SDN, an application (at the application level) call is required, which entails overloading the computational resources involved in processing incoming flows. The main approach for dealing with the computing resources overload in such systems is load balancers that should distribute the load between computing nodes efficiently. However, such approaches lead to increased latency as the flow peak rate increases and there is a computing resources limitation. In this chapter, to reduce the time for making decisions when load balancing, «the endless train» method is proposed. This method, instead of analyzing the input flow state and simultaneously the resources state, analyses the state of the computational resources only to make a decision regarding needed resources based on the current task requirements. This allows reducing the time for making a decision on the choice of a server serving the input flow. To test the efficiency of the proposed method, an implementation scheme was developed using MS Azure. The process of dynamically deploying additional virtual servers (virtual machines) to handle threads in the event of overload was tested. The testing results show the effectiveness for overload prevention but the computational recourses usage is increased.
Digital competence framework for higher education students: suggesting approach derived from relevant publications to vietnamese institutions

Nowadays, digital competence is recognized as one of eight core key competencies for lifelong learning. University students, in the context of education digital transformation, necessarily possess digital competence to be able to study and work in today's open and global educational environment. To develop digital competencies for students, the most important, time-consuming and labor-intensive first step is to determine the conceptual definition and an appropriate digital competence framework. For countries conducting digital transformation in the later stages like Vietnam, inheriting the achievements of previous countries is the optimal and smart choice. Using theoretical research methods, this article synthesizes the concept and structure of digital competence in higher education context from relevant publications, as a basis to suggest an approach in selecting a digital competence framework that is suitable to develop digital competence for university students in Vietnam.
Infinite perimeter selective segmentation model

Accurate boundary determination and segmentation of an object of interest in an image is a difficult image segmentation task. In this paper, we propose a new model which improves the old selective segmentation of Rada et al. [23] by combining two penalization and two fitting terms. To better deal with oscillatory boundaries, a H^1 weighted length term and L^2 Lebesgue measure have been employed as penalization terms, whereas the fitting terms consist of a region-based and area fitting term. The model has the same speed as the previous one-level set interactive segmentation model by Rada et al. [23] and much faster compared to previously dual-level set models by Rada et al. [25, 24] by having the same segmentation accuracy and reliability. On the other hand, the model shows a better performance while dealing with irregular and oscillatory object boundaries compared to Rada et al. [25] model. Further comparison with segmentation algorithms of the same nature, such as the Nguyen et al. [21] method, shows that the proposed model shows the same or improved performance for object segmentation with transparent boundaries or inhomogeneous intensity of the aimed object. Through experiments, it is shown that the proposed model finds the aimed object boundaries successfully for smooth or challenging oscillatory topological structures.
Challenge handling flood disaster by recommendation system with Analytical Hierarchy Process Methods

Flood is water runoff that exceeds the average water level so that it overflows from the riverbed, which causes inundation on low land. The impact of inundation causes damage to production factors that affect property in the economic sector, casualties from the social sector, and damage to public facilities in the environmental sector. Prevent and resolve flooding events, both carried out by the government and the community. However, one of the weaknesses of prevention or resolution based on a priority scale is flood disaster management. Therefore, this research aims to analyze and provide recommendations on priority for flood disaster management in the city of Depok based on three sectors, namely: Economic, Social, and Environ-mental. Each criterion has sub-criteria; namely, Economic Sub-criteria is Agriculture/plantation, Industry, Services/Marketing, and Transportation. Social sub-criteria is Community, Health, Employment, and Social Activities. Meanwhile, the environmental sub-criteria include Housing, Water Sources, Public Facilities, and Security. The research used quantitative data involving people living in Depok using a questionnaire with a choices sample are 100 data. The results of flood disaster management recommendations are based on quantitative data using a Decision Support System (DSS) with the Analytical Hierarchy Process (AHP) method with recommendations on social criteria with a value of 0.417 and public facilities sub-criteria value of 0.133.
Exploration of Accounting Information Construction Under the Background of Big Data

Under the background of big data accounting informatization, accounting informatization develops from paper-based to paperless operation with the help of the rapid development of informatization, which makes accounting work more standardized. This article analyses problems in the production of accounting information in the context of large data by means of bibliographic analysis, surveys of questionnaires and staff interviews. At the same time, he interviews 200-year-old accountants and 50-year-old accountants. The results show that the development of accounting information in the context of large data remains unclear in the classification of management accountancy data (30%); poor real-time performance of data (25%); unreasonable information transmission process (24%); poor information extraction ability, unable to tap the value of data (21%); among the 200 accounting managers and 50 accounting experts surveyed, they have a high level of financial expertise Knowledge accounted for 80%, with a high level of computer knowledge accounted for 85%, with a high level of information management knowledge accounted for 70%. According to the modern business system, the updating of accounting management has become an unavoidable trend. The accounting information system has therefore also shifted from traditional accounting to management, paying more attention to the actual state of business development and to achieving sustainable business development.
A-A KD: Attention and Activation Knowledge Distillation

We propose a knowledge distillation method named attention and activation knowledge distillation (A-A KD) in this paper. By jointly taking advantage of the attention mechanism as an inter-channel method and activation information for intra-channel, the student model can overcome the insufficiency of feature extraction and effectively mimic features of the teacher model. A-A KD can outperform the state-of-the-art performance in various tasks such as image classification, object detection, and semantic segmentation. It can improve 1.8% of mAP on PASCAL VOC07 and 1.5% of mIoU on PASCAL VOC12 than conventional student models. Moreover, experimental results show that our student model (ResNet50) can reach 21.42% of top-1 error with A-A KD, which is better than the corresponding teacher model in ImageNet.
Fast Settlement Scheme of Aviation Business Privacy Preservation Based on Consortium Blockchain

In order to reduce the risk of privacy leakage in the process of aviation business consumption and settlement, a privacy preservation scheme for aviation business consumption data is proposed. The dual public key encryption mechanism is innovatively integrated into the consortium blockchain system. The additional recipient's public key is added to the ciphertext, so that both recipients can decrypt independently and obtain the same plaintext information. Experimental comparative analysis shows that the scheme only increases a little computational complexity, while an additional recipient is added with high execution efficiency. Not only the scheme realizes the privacy preservation for passengers and enterprise customers, but also ensures the precise settlement and rapid audit of consumption data between airlines and enterprise customers.
Reliability Assessment of 500kV Substation Based on Fault Tree Analysis

Substation is the important element in a power grid, its reliability is critical to the secure and stable operation of large power grid. In this paper, the fault tree analysis method in probabilistic risk assessment is used to analyze the power supply reliability of a 500kV substation, taking the insufficient power supply to the 220kV power grid as the undesired event. The fault tree describes the disruption of the transmission of energy from the power supply to the transformer. The fault combinations leading to the undesired event can be obtained by calculating the Minimum Cut Sets (MCSs) of fault tree, and quantitative reliability assessment was carried out by calculating the failure probability of undesired events based on the component reliability model and data. In addition, dominate failure contributions based on component importance measures is adopted for the weak parts identification in substation. Quantitative evaluation of the fault tree, which represents a understanding of the power supply reliability from the 500KV substation to 220kV grid, which can identify the most important components in the substation, and provide a scientific basis for power system planning, equipment reliability s Selection election and maintenance optimization.
Adaptive Recommendation in Online Environments

Recommender systems form a class of Artificial Intelligence systems that aim to recommend relevant items to the users. Due to their utility, it has gained attention in several applications domains and is high demanded for research. In order to obtain successful models in the recommendation problem in non-prohibitive computational time, different heuristics, architectures and information filtering techniques are studied with different datasets. More recently, machine learning, especially through the use of deep learning, has driven growth and expanded the sequential recommender systems development. This research focuses on models for managing sequential recommendation supported by session-based recommendation. This paper presents the characterization in the specific theme and the state-of-the-art towards study object of the thesis: the adaptive recommendation to mitigate the information overload in online environments.
Structural geology of mineral, oil and gas explorations

This chapter delivers the simple principles of structural control and demonstrates why so many ore deposits are strongly structurally controlled. This chapter also describes the best practices for structural data collection and analysis in mineral and hydrocarbon explorations. The chapter demonstrates the description and analysis of 3D structures and microstructures (structural geology sensu stricto). Finally, the chapter provides a conclusion about the possible relationships between geological structure features, for instance, fractures, faults, folds, boudins, shear zones, cleavages, foliations and lineation, and mineral and hydrocarbon explorations. In fact, hydrocarbon microseepage can cause oxidation-reduction reactions and produce altered minerals in surface sediments and soil. It can be said that the investigation of geologic structures has been of leading significance in economic geology, both petroleum geology and mining geology. It was demonstrated that folded and faulted rock strata generally create traps that amass and concentrate fluids such as petroleum and natural gas. Likewise, faulted and structurally complex areas are prominent as penetrable zones for hydrothermal fluids, consequential in intense areas of base and precious metal ore deposits.
The Virtual Applications in Support of the Studying in the Field of Visual Arts

Art education is based upon learning about cultural heritage and art masterpieces mostly through reproductions. The development of virtual and mixed reality platforms leads to variety of more and more learning apps that allow the students and pupils to explore different museum collections, antic cities and treasures from all around the world without leaving their classroom. This leads to a better quality of education for those who can’t afford to see the originals or have some disabilities. Those apps can help understanding complicated conceptions and display facts in more attractive ways. But their implementation in learning process should be supervised from teachers and professors because it can also lead to misunderstanding, if they are not chosen wisely for the purpose of the lesson or audience.
Analysis of KNN in Classification of Firearms Sounds using Fast Fourier Transform

K-Nearest Neighbor (KNN) is an algorithm that is able to recognize an object with the training and testing data. Sound is one of the objects that can be classified with KNN. one example of the sound of a sharp weapon varies in sound based on its type. So that in this paper, do a classification to recognize sound based on the type of weapon tested with several distance formulas. The variation of the tested distance formula shows different results, the Euclidian distance formula is better than the Chebyshev distance formula and the Monkowski distance formula. Comparison of accuracy 0.31667: 0.25833: 0.24583, comparison of precision 0.30878: 0.25855: 0.22838, comparison of recall 0.31667: 0.25833: 0.24583, comparison of F1-Score 0.30884: 0.25833: 0.23066.