Reviewerly/exHarmony huggingface dataset:
Random Forests with Attentive Nodes

An extension of the attention-based random forest called ABRF-E for incorporating the attention mechanism into the random forest (RF) for improving the machine learning model performance is proposed. The main idea behind the proposed ABRF-E model is based on the Nadaraya-Watson kernel regression model. The attention weights with trainable parameters are assigned to each node of decision trees. The weights depend on the distance between an instance, which falls into a corresponding node of a tree, and instances, which fall in the same node. The attention weight are computed by using the Huber's contamination model which provides the linear relationship between the attention weights and their trainable parameters. The linear relationship leads to solving a quadratic optimization problem and allows us to avoid gradient-based algorithms for training attention parameters and attention weights. Numerical experiments with real datasets illustrate the proposed model.
Faster Hyperparameter Optimization via Finding Minimal Regions in Random Forest Regressor

In optimisation problems, it is often more convenient and efficient to approximate a target function with another function, which would be much easier to compute or analyse. Such approximations are called Surrogate Functions. A surrogate function can also be a fairly complex object itself. For example, a Random Forest Regressor (RFR) can be used to approximate target function in Hyperparameter Optimisation processes. Hyperparameter vectors define the feature space, and target algorithm performance is considered the target function. Thus, RFR trained on a set of examples, can approximate algorithm performance, using hyperpa-rameter vectors. However, it is hard to fnd its minima. Thus, “black-box” optimization algorithms are applied for optimization purposes, such as random or local searches. In this paper, we propose a method ShortestForestSearch to search RFR minimum points using branch and bound approach. We conducted several experiments for comparing the algorithm proposed with näıve approaches. ShortestForestSearch demonstrated significant performance improvements and the potential to improve other algorithms which use Random Forest internally as a surrogate function. Based on this, we propose ShortestForestSMAC, a new algorithm for hyperparameter optimization. It is based on the well-known SMAC algorithm and implements idea of ShortestForestSearch for selecting best new candidates on each optimization iteration. Experimental evaluation shows that ShortestForestSMAC outperforms SMAC by achieving similar results in considerably shorter time span.
Cryptocurrency in India and its impacts on Legislation

Due to the rapid development of information and communication technologies, many activities in our daily life have been done online and have become more effective. Due to the huge growth in the number of online users, the concept of virtual payment has become active and a new concept has emerged recently. Which is cryptocurrency. Which facilitates the process of financial activities like buying and selling. The use of virtual currency to make various payments has become widespread in recent years. Virtual money in which cryptocurrency has a prominent place. But it is not fully regulated so most of the countries have not accepted this currency in their economic activities. The current legality of this cryptocurrency as well as its impact on this currency is a subject of study. It has responded in terms of rules and laws to develop a clear picture of its impact on various laws in India to regulate crypto currencies. Taking this matter into consideration, the present research paper has been presented.&#x0D; Abstract in Gujarati Language:&#x0D; માહિતી અને સંચાર તકનીકોના ઝડપી વિકાસને કારણે, આપણા રોજિંદા જીવનમાં ઘણી પ્રવૃત્તિઓ ઓનલાઈન કરવામાં આવી છે અને તે વધુ અસરકારક બની છે. ઓનલાઈન વપરાશકર્તાઓની સંખ્યામાં ભારે વૃદ્ધિ થવાથી વર્ચ્યુઅલ ચુક્વણીનો કોન્સેપ્ટ સક્રિય બન્યો છે અને એક નવો જ કોન્સેપ્ટ હાલ મા જોવા મળ્યો છે. જે ક્રિપ્ટોકરન્સી છે. જે નાણાકીય પ્રવૃત્તિઓ જેમ કે ખરીદી અને વેચાણ ની પ્રક્રિયાને સરળ બનાવે છે. તાજેતરના વર્ષોમાં વિવિધ ચુક્વણી કરવા માટે વર્ચ્યુઅલ ચલણનો ઉપયોગ વ્યાપક બન્યો છે. વર્ચ્યુઅલ મની કે જેમા ક્રિપ્ટોકરન્સી નુ આગવું સ્થાન છે. પરંતુ તે સંપૂર્ણપણે નિયંત્રિત નથી તેથી મોટાભાગના દેશોએ તેમની આર્થિક પ્રવૃત્તિઓમાં આ ચલણને સ્વીકાર્યું નથી. આ ક્રિપ્ટોકરન્સીની વર્તમાન કાયદેસરતા તેમજ આ કરન્સી પર તેની અસર કેવી રહેસે તે અભ્યાસ નો વિષય છે. ક્રિપ્ટો કરન્સીને નિયંત્રિત કરવા માટે ભારતમાં વિવિધ કાયદાઓ પર તેની અસરનું સ્પષ્ટ ચિત્ર વિકસાવવા માટે નિયમો અને કાયદાઓના સંદર્ભમાં પ્રતિભાવ આપ્યો છે. એ બાબતને ધ્યાને લઈ પ્રસ્તુત સંસોધન પત્ર રજૂ કરેલ છે.&#x0D; Keywords: ક્રિપ્ટોકરન્સી, બિટકોઈન, ડિજીટલ કરન્સી, વર્ચ્યુઅલ કરન્સી
Nurturing socio-emotional skills in the context of schools

COVID 19 has led us to realise the significance of socio-emotional learning in the development of children. Social-emotional competence in children may differ but the good part is that it can be learned. Child-centred education somewhat went astray when the focus of school education shifted to learning outcomes, objectives, standards, and exam results. But the government policies, acts reforms have consistently stressed upon holistic education that also includes the ability to recognise and manage emotions, develop, and maintain effective relationships, take ethical decisions for self and others and to have an awareness of self. Socio-emotional learning comprises an array of personal and interpersonal skills and attitudes required by the children to succeed in school and life. The schools play a major role in nurturing these skills in children which is why it is important for the educators to find teachable opportunities in the classroom, beyond the classroom and in practices followed in school like mid-day meal or morning assembly.
Digital fraud and advancement of fraud mitigation mechanisms in India

Digital fraud is a distortion or thievery committed by utilizing internet services to unlawfully disburse cash from a financial institution and, furthermore, receive funds to the perpetrator's bank. Digital fraud is a sort of personality misrepresentation and is primarily driven by methodologies like spam emails, hacking, card skimming, etc. By and by, web banking is comprehensively used to check account statements, conduct online marketing, deposit fees, fund transfers, print account statements, etc. For availing the E-Banking facility, the Login Id is the customer's Id assigned by the bank. Additionally, a password is made available for protection of the amount in the customer's account. Be that as it may, as a result of some neglectfulness or senseless blunders, a client can, without a very remarkable stretch; fall into the trap of web tricks or fakes done by fraudsters. The methodologies for digital fraud are like malware, phishing scams, trojan horses, card cloning, data theft, etc. The manuscript is locked in to investigate and compile the same sorts of different procedures for Internet banking fraud that happen in our banking sector these days, and in a similar way, to understand and study the techniques for fraud protection for every individual bank.
Research on the Influence of School-based Teaching and Research System on Teaching Quality

Calling for school-based teaching and research activities and establishing a school-based teaching and research system is not imposed by the outside world, but merely promoting and institutionalizing this activity form consciously generated in the practice of the new curriculum. School-based teaching research system is of great theoretical and practical significance for creatively implementing the new curriculum, comprehensively implementing the goal of curriculum reform, practically improving the teaching quality, promoting the professional development of teachers, and improving the ability of curriculum construction and the level of running schools. The new ideas, new methods and new practices brought by the new curriculum are like a breeze blowing into the campus, turning up ripples, showing a new atmosphere, providing a broad space for the educational reform and development of our school, as well as a stage for teachers to display their talents. All these are attributed to the curriculum reform experiment, the implementation of the "school-based" teaching and research system, and the true return of teaching and research to schools, teachers, classrooms and practice.
Secure document and image transmission through an encrypted network system

Data communication and networks as a field gives high priority to data and network security. Presently, internet security issues have become very critical in sharing information. Perhaps, there is need for robust techniques for the protection of data shared via unsecured network channels. Since cryptography is a technique for securing plain text messages such as encrypted key exchange and authentication but reveals when and where communication is taking place, while steganography hides the existence of data to be transmitted. Thus, there is need for a tool that combines these two techniques in a single data transmission. As such, this paper intends to develop an application that combines both features of cryptography and steganography techniques for secure communication. The application is a cross-platform tool that can effectively hide information in many different carrier file formats such as image, audio or digital video file. The study adopt the requirements of Advanced Encryption Standard (AES) and Least Significant Bit (LSB) algorithm in order to come up with best technique that is more robust in securing confidential documents and images. The developed App accepts different file formats when hiding plaintext, messages, and images. The App is recommended to government security agencies, financial institutions, e-commerce websites/app, educational bodies, and individuals in sending personal data online.
Investigating relationship between using smartphones for learning and academic performance of secondary school students in Nigeria

Students are the primary users and recipients of smartphones and their persuasiveness has an impact on the general public. Several studies have found that there is a strong relationship between the use of smartphones and educational performance, as it led to behaviors that impair students' careers and learning habits. However, these studies only looked at smartphone usage patterns and presented a limited number of them. It is being proposed that the gap can be bridged by integrating smartphone usage and academic performance to keep track of users. The study involved 90 students in selected secondary schools in Sokoto State. According to the study, elements such as design functionality, design appeal, and design navigation influence students’ use of smartphones. Students are more likely to utilize their smartphones if they can quickly download pages, access e-learning systems and navigate between pages. It was also discovered that secondary school students in Sokoto frequently used their smartphones for some school learning activities, enhancing the perceived value of utilizing a smartphone for learning. They use their smartphones to access and share learning resources, chat with classmates and teachers, look up solutions to tasks, and even learn new things at any time from anywhere. In general, the study shows that using smartphones for learning improves general knowledge and has a good impact on secondary school students' academic performance.
Degradation-Oriented Adaptive Network for Blind Super-Resolution

Most of the super-resolution methods based on deep neural networks use a fixed image degradation model. However, when the real image degradation is inconsistent with the model assumptions, the performance of the network will be severely reduced. To address this issue, we propose a degradation-oriented adaptive network (DOANet), which can be used to solve multiple degradation super-resolution reconstruction. The network includes a degradation estimation network and an adaptive reconstruction network. The degradation estimation network extracts the abstract degradation of LR images using continuous residual blocks to provide necessary degradation information for reconstruction network. Then, the adaptive reconstruction network dynamically adjusts the parameters of the network layers based on the estimated degradation information using dynamic convolution and channel modulation to deal with various input images. Experimental results show that the proposed DOANet can cope well with multiple degradation and is superior to other recent blind methods in qualitative and quantitative comparison.
Speaker Age and Gender Estimation Based on Deep Learning Bidirectional Long-Short Term Memory (BiLSTM)

Estimating the age and gender of the speaker has gained great importance in recent years due to its necessity in various commercial, medical and forensic applications. This work estimates the speakers gender and ages in small range of years where every ten years has been divided into two subcategories for a span of years extending from teens to sixties. A system of speaker age and gender estimation uses Mel Frequency Cepstrum Coefficient (MFCC) as a features extraction method, and Bidirectional Long-Short Term Memory (BiLSTM) as a classification method. Two models of two deep neural networks were building, one for speaker age estimation, and the other for speaker gender estimation. The experimental results show that the deep neural network model of age estimation achieves 94.008 % as accuracy rate, while the deep neural network model of gender estimation achieves 90.816% as accuracy rate.
Novel location permutation encryption based on exponential numbers

The pattern of exponential number can achieve 99% ideal uniformity distribution level and is characterized with quasirandom nature. In this study exponential pattern is modified to possess an ideal uniform distribution property for operating location permutation. Cipher space of the proposed permutation scheme can achieve its factorial function upper bound. Brute-force restoration of permutation belongs to factorial complexity order which is more complex than exponential function. The proposed encryption scheme belongs to lightweight cryptographic function that is applicable to internet of things (IoT). This novel encryption technique can outperform the advanced encryption standard (AES) from the simplicity of algorithm, the availability, generation and distribution of long encryption key, and high confidentiality level points of view.
Using Your Warped Designs Between Other Adobe Apps

Chapter Goal: This concluding chapter looks at how you can use the content you have created along with this book—or your own projects—using Photoshop or Illustrator later in other Adobe software, and at how to move the assets using either the copy/paste method or the Library panel.
Desenvolvimento e produção técnico-científica em tempos de pandemia: um relato da liga acadêmica de fundamentos de enfermagem

The aim of this article is to describe an experience report based on the creation and development of the Academic League in a public university in the state of Rio de Janeiro. It is believed that the leagues contribute to the training of undergraduate students, in an attempt to offer different experiences and thus promote meaningful learning. The methodology is characterized as a descriptive study of the experience report type. Observing the results, it was seen that most of the target audience were nursing students, professionals and professors, with an average interaction of 33.4 likes on Instagram© and 108 likes on Youtube©. The academic league of Fundamentals of Nursing is still under construction, intending to bring even more practical and theoretical knowledge, focusing on the fundamental bases of nursing, regarding the training of practical nursing skills, dissemination of knowledge related to care and nursing theories.
Plug-and-play discrete modulation continuous variable quantum key distribution based on non-Gaussian state-discrimination detection

Plug-and-play discrete modulation continuous variable quantum key distribution can generate local oscillator light locally without using two independent lasers, and both signal light and local oscillator are generated from the same laser, which can effectively ensure the practical security of the system and have a completely identical frequency characteristic. In addition, this scheme has good compatibility with efficient error correction codes, and can achieve high reconciliation efficiency even at low signal-to-noise ratio. However, there exists large excess noise in the plug-and-play configuration based on the untrusted source model, which seriously limits the maximum transmission distance of the discrete modulation scheme. To solve this problem, we propose a plug-and-play discrete modulation continuous variable quantum key distribution based on non-Gaussian state-discrimination detection. That is to say, a non-Gaussian state-discrimination detector is deployed at the receiver. With adaptive measurement method and Bayesian inference, four non-orthogonal coherent states which are based on four-state discrete modulation can be unconditionally distinguished on condition that the error probability is lower than the standard quantum limit. We analyze the security of the proposed protocol by considering both asymptotic limit and finite-size effect. Simulation results show that the secret key rate and maximum transmission distance are significantly enhanced by using no-Gaussian state-discrimination detection even under the influence of the untrusted source noise compared with the original plug-and-play discrete modulation continuous variable quantum key distribution. These results indicate that the proposed scheme can effectively reduce the negative influence of the untrust source noise on the performance of the plug-and-play discrete modulation continuous variable quantum key distribution protocol. The proposed protocol can not only ensure the practical security of the system, but also achieve more efficient and longer transmission distance quantum key distribution.
A Lightweight Method for Defense Graph Neural Networks Adversarial Attacks

Graph neural network has been widely used in various fields in recent years. However, the appearance of an adversarial attack makes the reliability of the existing neural networks challenging in application. Premeditated attackers, can make very small perturbations to the data to fool the neural network to produce wrong results. These incorrect results can lead to disastrous consequences. So, how to defend against adversarial attacks has become an urgent research topic. Many researchers have tried to improve the model robustness directly or by using adversarial training to reduce the negative impact of an adversarial attack. However, the majority of the defense strategies currently in use are inextricably linked to the model-training process, which incurs significant running and memory space costs. We offer a lightweight and easy-to-implement approach that is based on graph transformation. Extensive experiments demonstrate that our approach has a similar defense effect (with accuracy rate returns of nearly 80%) as existing methods and only uses 10% of their run time when defending against adversarial attacks on GCN (graph convolutional neural networks).
Following SEIS Principles for Better FAIR Data Integration in EOSC

This study aimed to compare research trends regarding SEIS principles and FAIR data principles, in support of EOSC. Articles published in specific environmental policy areas, placed in the context of EU-Neighborhood South/East Regions Dialogue, were analyzed using content analysis. The evolution of EU interoperability was numerically classified in support of SEIS initiatives, compliant with FAIR principles, and able to benefit from the building of an EOSC community. The first proposed result refers to the extent of comparability of SEIS information storage and retrieval systems principles and FAIR data principles with respect to the implementation of the INSPIRE directive in Europe. This social comparison process occurred in two dimensions, trust concerning the resource FAIR and institutional loyalty according to SEIS. The relationships between SEIS and EOSC were estimated in its evolution according to five actions (cost, time, trust, best practices, cloud), and by exposing SEIS-friendly research infrastructures whose thematic data services points to the EOSC catalogue of services.
The Applications of Cryptocurrency: Evidence from Ethereum

Cryptocurrency (e.g., Ethereum and its currency Ether) presents an opportunity to completely change the way money is transacted, which perhaps even redefines the money. On this basis, this paper will investigate and discuss the basic principles and corresponding applications of Ethereum. As a matter of fact, operating on a decentralized platform while also using the global reach of the internet, transactions can be made with little cost, without interference of intermediaries and government intervention. Besides, it will keep the personal information of the user private. In addition, according to the analysis, each user can define how they use ether as they please, e.g., using Ethereum to store assets like art and reselling them through Ethereum. However, Ethereum still has many issues to fix ranging from security risks, privacy risks, and perceived stability due to Ethereum’s notorious volatility and previous illegal activities from other platforms (e.g., Bitcoin). More research is required to distinguish whether Ether can be a viable alternative that could be added to the economy or even completely replacing traditional money altogether and address the current concerns. These results shed light on guiding further exploration of cryptocurrency.
Application of Artificial Intelligence Technology in Criminal Risk Intelligent Assessment Model

This paper summarizes the latest research on criminal risk assessment at home and abroad, and it is a developing trend to use artificial intelligence technology for risk assessment. The method of static + dynamic information collection is adopted for data collection. Establish the data classification model, establish the criminal classification and evaluation model; Data analysis with artificial intelligence technology, instant warning.
DECOLONIALITY, INCLUSIVITY AND AUTONOMY IN REIMAGINING CITIES OF THE FUTURE

African Union has hope for a vision of an Africa that is thriving by 2063 (UNDP Africa, 2017). Historically Africa was under the gaze and submissive to the imaginings of western vision. Africans as drivers of development prove to be difficult as global coloniality continues to shape inclusivity, autonomy, and spatial activities. Reimagining the future of cities is aligned with the way global coloniality unpacks how modernisation takes place. Decoloniality becomes important in that it gives Africans the space to think about autonomy to plan how can issues of inclusivity be addressed in the context of providing sustainable cities in line with spatial justice. The main drivers of reimagining the cities of the future are environmental sustainability and disruptive technology. Environmental sustainability and technological vision/disruptive technology are very problematic in the African context. In the African context, environmental issues are secondary as social inequalities and political issues are at the forefront of African lived experiences. Technology although present continues to exacerbate the gap between the “haves and the have nots”. This paper critically explores the future of cities concerning decoloniality, inclusivity and autonomy. It highlights key discussions about decoloniality and helps to unpack an African perspective towards reimagining future cities. The purpose of this paper is to bring to the forefront what sustainability means for smart cities in Africa, and if they are ready to take on an autonomous role in defining the future of cities.