Reviewerly/exHarmony huggingface dataset:
(Un)Corporate Crypto-Governance

Objective: creating the corporate governance structure and legal regulation mechanism of blockchain protocols.Methods: dialectical approach to cognition of social phenomena, allowing to analyze them in historical development and functioning in the context of the totality of objective and subjective factors, which predetermined the following research methods: formal-logical, comparative-legal, and sociological.Results: Blockchain technology was born out of a Cypherpunk vision for regulation without sacrificing privacy. This vision feeds a call by some in the blockchain technology ecosystem to view computer code as the only law applicable to blockchain protocols, transactions conducted on the protocols, and DAOs. The code of certain protocols, such as the Bitcoin blockchain and Ethereum, currently embody their Cypherpunk cultural origins, placing a premium on privacy and governance mechanisms that preserve privacy. But that code can change. In fact, laws enacted and enforced by governments may act as the stimuli for such change. Indeed, such stimuli, for better or worse, are already in play, with coders ceasing work for fear of legal repercussions. Adopting a contract-based governance system in which the rules and expectations are clearly defined empowers blockchain protocol communities to preserve as much of their cultures and visions as possible. Adopting these contracts also requires blockchain communities to engage in open, active, and thoughtful conversation about their collective culture and vision. Further, basing blockchain governance structures in contracts that loosely resemble corporate governance structures allows such communities to tap into centuries of scholarship and experimentation in a functionally equivalent governance arena. Scientific novelty: the work proves that the biggest cultural impact of (un)corporate crypto-governance may be on the culture of traditional corporations. Indeed, one significant lesson of a corporate governance model for off-chain governance may be a sharpened recognition that “code as law” is a subsystem of regulatory norms within the greater legal system. Viewed through systems analysis, the result is a two-way recognition of the interconnected roles of code and law in limiting behavior within the blockchain ecosystem. In other words, the code informs the law and its application to a blockchain ecosystem. Meanwhile, law informs behavior and activities undertaken through the code. The result is that the intersection of code and law can impact our understanding of how to apply the law in more traditional scenarios as well.Practical significance: the main provisions and conclusions of the article can be used in scientific, pedagogical and law enforcement activities when considering issues related to (un)corporate crypto-governance.
Development of financial and economic autonomy in the field of higher education

The development of alternative management tools to the old management models increasingly requires the expansion of autonomy in the activities of higher education institutions. A prominent place in the system of autonomy of the university is occupied by the aspect of financial independence. This article is devoted to the analysis and generalization of key global trends in the development of financial autonomy by higher education institutions, highlighting the complex process of autonomy of universities, studying the world experience of expanding their autonomy on the right to dispose of funds and organize other financial processes. The study outlined further prospects for increasing the financial and economic independence of universities, clarified the current and projected limits of the powers of universities in the paradigm of developed and legally established model of autonomy, identified effective solutions to the complex process of financial and economic autonomy. The results of the study can be used to learn the processes of expanding the financial and economic autonomy of higher education institutions in the global dimension.
Kontrol Frekuensi Wind-Diesel Menggunakan Hibrid Kontroller PID-BA-ANFIS

The wind diesel system is greatly influenced by the wind speed and which is then combined with the diesel engine. Optimization of wind-diesel systems is needed to get good frequency quality and optimal power. The optimal setting of the gain and time constant on the Load Frequency Control (LFC) causes the frequency stability to be weak. In practice, the wind-diesel system is controlled by a PID controller and Fuzzy Logic Controller. At present the gain value setting of the PID is still in the conventional method, so it is difficult to get the optimal value. In this study the control design is applied by using the Smart Method in finding the optimum Proportional Integral Derivative (PID) based on Bat Algorithm (BA). For comparison, the method is used without a control method, conventional PID method, PID auto tune matlab method, PID-BA method, and PID-BA-ANFIS. Wind-diesel modeling uses the transfer function of wind turbine and diesel diagrams. From the results of research that has been done shows that the smallest undershoot on PID-BA-ANFIS, the smallest overshot on PID-BA-ANFIS, and the fastest settling time is equal to PID-BA-ANFIS. This research can later be continued using other artificial intelligence methods.
Multibody Nonrigid Structure from Motion Segmentation Based on Sparse Subspace Clustering

Sparse subspace clustering (SSC) is one of the latest methods of dividing data points into subspace joints, which has a strong theoretical guarantee. However, affine matrix learning is not very effective for segmenting multibody nonrigid structure from motion. To improve the segmentation performance and efficiency of the SSC algorithm in segmenting multiple nonrigid motions, we propose an algorithm that deploys the hierarchical clustering to discover the inner connection of data and represents the entire sequence using some of trajectories (in this paper, we refer to these trajectories as the set of anchor trajectories). Only the corresponding positions of the anchor trajectories have nonzero weights. Furthermore, in order to improve the affinity coefficient and strong connection between trajectories in the same subspace, we optimise the weight matrix by integrating the multilayer graphs and good neighbors. The experiments prove that our methods are effective.
Psychological and Pedagogical Conditions and Means of Development of Professional Reflection of Teachers in the System of Methodical Work

The article considers general psychological and methodical patterns of mathematics teachers’ professional reflection in the system of methodical work. It proves the hypothesis that one can model and implement specific psychological and pedagogical conditions, thus promoting the development of professional reflection. Besides, the article shows that the specified pedagogical conditions for the successful development of professional reflection of teachers of mathematical disciplines in the system of methodical work are: ensuring awareness of the teacher of mathematical disciplines of the content, structure and means of development of professional reflection; formation of an objective self-assessment of the personality and own professional activity of teachers of mathematical disciplines; introduction of individual and group means of development of professional reflection in the system of methodical work of pedagogical college; creation of a reflective environment in the system of methodical work of a pedagogical institution. Psychological and pedagogical means for the development of professional reflection of teachers of mathematical disciplines in the system of methodological work of a pedagogical college are: means of individual reflection (repetition technique, counselling, individual reflection games, solving reflective problems, keeping a reflection diary); collective means of developing professional reflection of the teacher (reflective debates, reflex interviews, reflective classes, consultation, tutorial, group reflection games, development of programs for monitoring their (or colleagues) actions in professionally significant situations with subsequent analysis of the received materials, training on the development of professional pedagogical reflection); introduction of a special training course "Development of professional reflection of teachers of mathematical disciplines in the system of methodical work of the pedagogical college".
Quantum State Tomography of Qutrits by Single-Photon Counting with Imperfect Measurements

In this article, we introduce a framework for quantum state tomography of qutrits by projective measurements. The framework is based on photon-counting with measurement results distorted due to the Poisson noise and dark counts. Two different measurement schemes are investigated numerically and compared in terms of their efficiency for distinct numbers of photons per measurement. The accuracy of state reconstruction is quantified by figures of merit which are presented on graphs versus the amount of noise.
Formulation of a departmental COVID-19 contingency plan for contact tracing and facilities management

formulated this contingency plan with a main aim of facilitating the contact tracing of staff and patients to control the spread of coronavirus disease 2019 (COVID-19). 1 The plan also provided guidance to our staff on facilities management.
Target Tracking in Wireless Visual Sensor Networks: Challenges, Steps, and Metrics of Evaluation

In recent years, wireless sensor networks have been used in a wide range of applications such as smart cities, military, and environmental monitoring. Target tracking is one of the most interesting applications in this area of research, which mainly consists of detecting the targets that move in the area of interest and monitoring their motions. However, tracking a target using visual sensors is different and more difficult than that of scalar sensors due to the special characteristics of visual sensors, such as their directional limited field of view, and the nature and amount of the sensed data. In this paper, we first present the challenges of detection and target tracking in wireless visual sensor networks, then we propose a scheme that describes the basic steps of target tracking in these networks, we focus then on the tracking across camera nodes by presenting some metrics that can be considered when designing and evaluating this type of tracking approaches.
Innovative study on online ideological education in the era of new media, face recognition and blockchain

Innovative study on online ideological education in era of new media, face recognition and blockchain is conducted in this paper. This research work conducts an in-depth research on the information acquisition of smart contract runtime, smart contract virtual machine instrumentation and also the security threat detection technology, and propose a real-time defense framework for the blockchain security threats with a scalable detection algorithm. The face recognition is combined for the verification and the online system is designed based on the data media model. The experiment has shown the effectiveness.
Prediksi Energi Listrik Kincir Angin Berdasarkan Data Kecepatan Angin Menggunakan LSTM

Fossil energy is well known as the most energy resource consumed by humans. However, the exploitation leads to damage both in the process of taking raw materials and in the use of those. Furthermore, the amount has become decreasing nowadays. Renewable energy could solve the energy crisis. One kind of renewable energy that has been successfully used by a human is by utilizing wind turbines. However, there are still many problems in its implementation and usage. One of the problems is the unstable generated electricity that is caused by instability of the wind speed. Inappropriate plans for utilizing wind turbines in such areas with varying wind speed could harm renewable energy investment. Therefore, forecasting the wind speed is necessary to anticipate the stability and embrace optimal produced energy. This study proposes the Long Short Term Memory (LSTM) algorithm to predict the generated energy by using the wind speed dataset. Thus, wind turbines can be utilized effectively and efficiently in the right area with sufficient average wind speed.
UAV Collision Detection Algorithm based on Formulafor Fast Calculation

Collision Avoidance System (CAS) is known as a pre-collision system or a forward collision warning system, and research has first begun as a vehicle safety system. In this paper, we propose an algorithm for collision detection of UAV. The proposed algorithm uses a mathematical method and detects the collision of the UAV by modeling it in a two-dimensional plane. Using the mathematical modeling method, it is possible to determine the collision location of the UAV in advance. Experiments were conducted to measure the performance and accuracy of the proposed algorithm. In the experiment, we proceeded assuming three environments and were able to detect an accurate collision when the UAV moved. By applying the algorithm proposed in the paper to CAS, many collision accidents can be prevented. The proposed algorithm detects collisions through mathematical calculations. In addition, the movement time of the UAV was modeled in a 2D environment to shorten the calculation time.
effect of internal control on organizational performance in the telecommunications industry in South South and South East Nigeria

The study focused on effect of admin internal control on performance in telecommunications industry in South South and South East Nigeria. The study employed a descriptive survey research design. Instrument adopted for the study is a structured questionnaire based on simple random sampling method. In addition, interview was also employed to serve as a compliment for the questionnaire. Reliability of the research instrument was tested using the Cronbach Alpha method which revealed that the instrument is reliable. The result of Durbin Watson revealed that the data is free from autocorrelation. Data analysis was done using both descriptive and inferential analysis technique. Descriptive statistics was used to give insight on the respondents profile while inferential statistics was used in the conducting of hypotheses. The two research questions for the study were analyzed using multiple regression model. The study shows that the two null hypotheses were rejected while the two alternative hypotheses were accepted (organization’s internal control environment (p=0.000&lt;0.05, ?=0.890) and risk assessment (p=0.000&lt;0.05, ?=0.242); The study concluded that organization’s internal control environment and risk assessment, has a positive influence on organizational performance.
Biometric Based User Authentication and Privacy Preserving In Cloud Environment

Cloud technology provides advantage of storage services for individuals and organizations thus making file access easy and simple irrespective of location. The major concern is the security while the file is been outsourced. Maintaining integrity, file unchanged, gaining confidentiality during file outsourced plays an important role. In this paper, we propose identity based data outsourcing technique to provide data security during authorization and storage. For data authorization we propose finger print based authentication. The fingerprint based authentication is performed using Minutae Map algorithm (MM). For data security we convert the data owner files to hash values using SHA algorithm. Finally in the cloud storage stage, data security and data availability is addressed using multiple cloud storage system.
Optimal Crop Selection Using Gravitational Search Algorithm

For the economic growth of the crop, the optimal utilization of soil is found to be an open area of research. An efficient utilization includes various advantages such as watershed insurance, expanded biodiversity, and reduction of provincial destitution. Generally, soils present synthetic confinements for crop improvement. Therefore, in this paper, a novel diversified crop model is proposed to predict the suitable soil for good production of the crop. The proposed model utilizes a quantum value-based gravitational search algorithm (GSA) to optimize the best solution. Various features of soil are required to be investigated before crop selection. These features are refined further by applying quantum optimization. The crop selection based upon the soil requirement does not require any additional fertilizers which will reduce the production cost. Thus, the proposed model can select the optimal crop according to the soil components using the gravitational search algorithm. Therefore, the gravitational search algorithm is applied to the quantum values obtained from the crop and soil dataset. Extensive experiments show that the proposed model achieves an optimal selection of crops.
Gold, Cryptocurrency and Oil Adaptive Analysis and Forecasting

The work is devoted to identifying and tracking development trends, structural shifts in the economy under the influence of world markets, represented by non-stationary time series of gold, bitcoin and oil prices.The heuristic potential of the concept of the long and medium wave is used for forecasting purposes.The analysis of financial time series using the adaptive correlation coefficient is carried out.The dynamics of the traditional coefficient appears to be a significantly smoothed graph, which prevents sufficient qualitative analysis of the data.The results obtained are analysed to identify wave fluctuations, to determine the phases of growth, prosperity, recession and stagnation in the economy.An overview of the situation on the world markets for gold, bitcoin and oil based on the considered time series is presented.Based on the identified trends in the dynamics of these markets, short-term forecasting was carried out using ARIMA models and neural networks.The statistical calculations R environment is used.
Blended Learning as a form of Effective Organization of Professional Training of Future Social Workers / Social Pedagogues

The article reveals some of the most important aspects of the organization of blended learning on the example of training future social workers / social pedagogues. Describes the experience of using Moodle, Microsoft Teams and Zoom in blended learning. There are such aspects as the possibility and features of conducting online lectures and practical classes. The article reveals in detail the technical capabilities of Moodle, Microsoft Teams and Zoom, which were used by teachers and students majoring in 231 "Social Work. Social pedagogy. Practical Psychology ”at the Taras Shevchenko Luhansk National University during the period of self-isolation. The presented material allows us to conclude that, despite the urgency and generality of the introduction of blended learning during the pandemic, its organization was well thought out and allowed to effectively organize the educational process.
Have Attention Heads in BERT Learned Constituency Grammar?

With the success of pre-trained language models in recent years, more and more researchers focus on opening the "black box" of these models.Following this interest, we carry out a qualitative and quantitative analysis of constituency grammar in attention heads of BERT and RoBERTa.We employ the syntactic distance method to extract implicit constituency grammar from the attention weights of each head.Our results show that there exist heads that can induce some grammar types much better than baselines, suggesting that some heads act as a proxy for constituency grammar.We also analyze how attention heads' constituency grammar inducing (CGI) ability changes after fine-tuning with two kinds of tasks, including sentence meaning similarity (SMS) tasks and natural language inference (NLI) tasks.Our results suggest that SMS tasks decrease the average CGI ability of upper layers, while NLI tasks increase it.Lastly, we investigate the connections between CGI ability and natural language understanding ability on QQP and MNLI tasks.
PERANCANGAN SISTEM RESERVASI DAN PROMOSI HOTEL BERBASIS WEBSITE

The rapid development of information technology, triggering every area of life must be able to innovate so as not to lag or even disappear.One of the areas that has been utilizing many technologies is the economic and business areas.One of the businesses that is currently growing is the hospitality business.Regional potential in Indonesia that provides many benefits for tourists ranging from sport or recreation to make the business of hospitality become a promising effort.The number of hotels established, making business competition increasingly higher.facilities, promotion, service and convenience in obtaining information and transaction into a factor that can impact the business progress of the hotel.Fast information service especially for reservation is indispensable.This research aims to design a reservation and promotion system in a Web-based hospitality business.The methods used in this research are the Software Development Life Cycle (SDLC) method as well as system design using Unified Modelling Language (UML).This research generates a prototype reservation system and promotion of a website-based hospitality business that can be implemented to build information systems and can then be used to facilitate the dissemination of information/hotel promotion and facilitate consumers to make reservations online.
SIFAT-SIFAT DAN KEJADIAN KHUSUS DISTRIBUSI GAMMA

The gamma distribution is one of special continuous random variable distribution with scale parameter and shape parameter where is positive real numbers. On some conditions the gamma distribution astablishes other continuous distributions which are then called special cases of the gamma distribution. Therefore, this study was conducted to determine the properties of gamma distribution and the characteristics of the special cases of gamma distribution by analyzed the theories from literatures. The properties of gamma distribution include expectation value, variance, moment generating function, characteristic function, and estimation of gamma distribution parameters with the moment method to earn the special cases of the gamma distribution are Erlang, exponential, chi-square, and beta distributions.
Integrated Geo Cloud Solution for Seismic Data Processing

Oil industries generate an enormous volume of digitized data (e.g., seismic data) as a part of their seismic study and move it to the cloud for downstream applications. Moving massive data into the cloud can pose many challenges, especially to Commercial-off-the-shelf geoscience applications as they require very high compute and disk throughput. This paper proposes a digital transformation framework for efficient seismic data processing and storage comprising of: (a) Novel Data storage options, (b) Cloud-based HPC framework for efficient seismic data processing, and (c) MD5 hash calculation using the MapReduce pattern with Hadoop clusters. Azure cloud platform is used to validate the proposed framework and compare it with the existing process. Experimental results show a significant improvement in execution time, throughput, efficiency, and cost. The proposed framework can be used in any domain which deals with extensive data requiring high compute and throughput.