Reviewerly/exHarmony huggingface dataset:
A Hybrid Recommendation System based on Fuzzy C-Means Clustering and Supervised Learning

A recommendation system is an information filter tool, which uses the ratings and reviews of users to generate a personalized recommendation service for users.However, the coldstart problem of users and items is still a major research hotspot on service recommendations.To address this challenge, this paper proposes a high-efficient hybrid recommendation system based on Fuzzy C-Means (FCM) clustering and supervised learning models.The proposed recommendation method includes two aspects: on the one hand, FCM clustering technique has been applied to the item-based collaborative filtering framework to solve the cold start problem; on the other hand, the content information is integrated into the collaborative filtering.The algorithm constructs the user and item membership degree feature vector, and adopts the data representation form of the scoring matrix to the supervised learning algorithm, as well as by combining the subjective membership degree feature vector and the objective membership degree feature vector in a linear combination, the prediction accuracy is significantly improved on the public datasets with different sparsity.The efficiency of the proposed system is illustrated by conducting several experiments on MovieLens dataset.
Knowing Trends in Organizational Citizenship Behavior for the Environment (OCBE) using Bibliometric Analysis Based on the Scopus Database

Objective: The literature on OCBE trends is limited. Therefore, it is important to carry out a bibliometric analysis aimed at knowing the trend of publication analysis in OCBE. Bibliometric analysis was used to search the Scopus database from the oldest publication in 2009 to the newest issue in 2021. The purpose of this study was to determine the number of papers, trend of increasing and leading countries, leading journals, most frequently appearing variables and emerging themes, as well as leading authors in OCBE field. Methodology:This study uses a bibliometric method to analyze and visualize OCBE trends. In searching the Scopus database, assisted by Harzing's Publish or Perish software, mendeley and VOSviewer. Results: From 2009 to 2021 there were 69 papers in the Scopus database discussing the OCBE study and from 2019 to 2020 there was an increase in publications in the OCBE study. The leading countries in OCBE research are the United Kingdom and United States. The OCBE concept is published in a leading journal, namely the Tourism Management journal. Then environmental performance has the closest relationship with OCBE which shows that OCBE is active in the field of environmental management pioneered by Charbel Jose Chiappetta Jabbour from the United Kingdom. Implication: In addition to providing direction and opportunities for future study. This study can also be useful for academics, organizations, and business policymakers in understanding OCBE trends.
Implementasi Knowledge Management System Dalam Upaya Peningkatan Pengetahuan Sumber Daya Manusia Dengan Metode Seci

APF is an international textile company that focuses on producing textile yarns located in Kendal district, Semarang city. This study aims to create a system using knowledge storage and management that is useful for sharing HR knowledge and to increase the speed of all handling conflicts. . The author reveals that using the existence of news knowledge management can facilitate organization and provide information and knowledge for the company, it can also increase the speed of handling conflicts that occur in the company
Penerapan Machine Learning Untuk Mengategorikan Sampah Plastik Rumah Tangga

Plastic waste is the result of human needs for plastic-based products. Due to high needs, the manufacture and use of plastics as raw materials produced do not use plastics as raw materials for their manufacture. Side effects of this phenomenon cause plastic waste to be transferred to the Final Shelter (TPA). Plastic waste is divided into 7 types, some can be replaced, recycled, and reused. To be able to do better sorting and screening of plastic waste, human labor is needed. This causes humans to have the ability to sort and filter visual objects, but humans are less consistent in various influencing factors. However, if this is applied to a computing system, the plastic waste treatment system will provide consistent results. If this system is applied in various layers of waste treatment, the plastic waste that pollutes the environment will be reduced. With the help of Machine Learning and Deep Learning, we can apply human visual abilities to computer systems.
Video Analysis of Vehicle and Pedestrian Using Neural Network

In this paper, we suggest an algorithm for detection and tracking analysis of vehicles, pedestrians in video frames. The extracted features function for visual perception tasks and are used to address a tracking problem. The algorithm can be split into 2 sections the first part is classification algorithm, which is predicted on convolutional neural networks. The CNN model is implemented using the You Only Look Once (YOLO) algorithm in deep learning. And the second part is algorithm for tracking regions. Using this algorithm, we suggest an idea of detecting, counting of vehicles and pedestrian.
Deep-net-derived surface estimations from natural scenes predict voxel responses in scene-selective cortex

Our world is full of diverse types of visual information, yet visual attention and memory experiments focus almost exclusively on understanding attention/memory of basic visual features and discrete objects, in part because our understanding of how people represent scene surface information cognitively and neurally is very limited. Recent work (e.g., Lescroart & Gallant, 2019) has made headway in quantifying such surface representations, finding 3D surface information in scene-selective cortex, yet their results were limited to artificially generated images for which ground-truth 3D information exists. Here, we use DNNs (Zamir et al., 2018) to estimate ground-truth distance and surface-direction information based only on RGB stimulus images in the publicly available BOLD5000 fMRI data set. This procedure yielded artifact-free distance and surface-direction estimates for 978 of the 1000 scene images in the BOLD5000 stimulus set. Using a similar encoding model to Lescroart & Gallant (2019), we found significant predictions of voxel responses in scene-selective cortex (occipital place area and parahippocampal place area: 3/3 participants significant; retrosplenial complex: 2-3/3 participants significant depending on hemisphere). These results lay the foundation for investigating scene surface processing in more naturalistic environments and tasks, a critical step towards understanding visual and cognitive processes in the real world.
Symmetries in cavity models: Beyond the rotating wave approximation

The interaction of confined atoms with a single mode radiation field is the main subject in the theory of cavity quantum electrodynamics. The constraints imposed by the cavity on matter and radiation fields give rise to collective phenomena. One possible outcome is the enhanced and coherent spontaneous emission of photons by the atoms: the superradiance. As predicted by Dicke, conservation laws are essential in superradiance and are derived from the matter-interaction Hamiltonian. Here, we consider N two-level ultracold atoms interacting with a single mode bosonic field, in the Dicke Hamiltonian, and trapped inside a non-dissipative optical cavity. Numerical and analytical results derived from finite size regime indicate the matter–radiation coupling strength, λ, is insufficient to draw the complete picture of the system. Instead, they support the relevance of U(1) symmetry, which prompts the study of (i) particle and angular momentum conservation, (ii) the constraints imposed to correlation functions and (iii) the influence of symmetries in the system dynamics. Further exploring the U(1) and rotational symmetries permits a simple interpretation of antirotating contributions as spin–orbit operators. As application, we show two species of ultracold clouds develop interactions due to antirotating operators.
Sistem Informasi Pencocokan Data Pemilih Berbasis Web Pada Kantor KPUD Kabupaten Pangkep

There is still inaccurate voter data such as duplicate data, underage and inefficient recapitulation processes. The aims of the study was to reduce inaccurate voter data and to streamline the time of the recapitulation process. The proposed system is a web-based voter data matching system in Pangkep Regency KPUD office. The data was obtained through (1) Field Research, (2) interviews.The research method used is the profile matching method on voter data. The testing technique uses a black box and a questionnaire. The results of the study indicate that thebased voter data matching system at the KPUD Pangkep Regency Office web produces accurate voter data, streamlines the time of the recapitulation process.
О ФУНКЦИИ ВОЗДЕЙСТВИЯ МАССОВОЙ КОММУНИКАЦИИ

The article looks at the history of mass media impact function from the epoch of Antiquity to the present day. Different means of communication dominated at different times. During Antiquity and the Middle Ages, oratory reigned supreme. The second stage is associated with the emergence and then the dominance of the printed media. At the third stage, broadcast and then electronic means of communication appear and begin to dominate: first radio, then television, then the Internet. Technical change affects the nature of communication. The picture on the screen has a much greater impact on the recipient than the verbal description of the object in the newspaper. In addition, the image on the screen is often more important to the recipient than the referent that lies behind it. As a result, the picture on the screen often makes the recipient use stereotypes to interpret information which usually lead them to a simplified understanding of the message. In some cases, the impact function, effected, among other means, by the use of low colloquial vocabulary, is the leading one. Modern mass media have a huge audience. This is practically the entire (or almost all) population of the planet. Today, the function of impact is realized not only in the internal political struggle, but also in the international arena, and in the information and psychological warfare in particular.
Intelligent Optimization of Sliding-Mode Fuzzy Logic Controllers

Optimization is the selectionSelection process of the best elements with respect to some criterion from a feasible set of variables. There may be single or multiple objectives to be considered during optimization. The optimization process generally involves the minimization of a cost or maximization of a profit. Sliding mode controller design problem ends up with the selectionSelection of values for its parameters which may include trials and errors. In this chapter, using intelligent optimization approaches, the parameters of sliding mode controllers are optimized to minimize the effect of chattering while the tracking error is minimized. Since these two objective functions are conflicting objective functions, it is required to use multiobjective intelligent optimization approaches.
Reinvention or return to ‘normal’? Scholarly communications at a crossroads1

Will the events of 2020 lead to innovation or stagnation?At the onset of 2021, with a slow and difficult recovery from the global pandemic on the horizon, organizations throughout scholarly communications faced a strategic crossroads.Would they use this time to pursue new ideas, models, and programs that combatted losses and enhanced their missions?Or, desiring stability and security, not additional risk, would they stay the existing course?This opinion piece explores the scholarly communications community's resilience during the global pandemic, how recent history shaped this response, and what this may mean for the future.
Practical key recovery attacks on FlexAEAD

FlexAEAD is a block cipher candidate submitted to the NIST Lightweight Cryptography standardization project, based on repeated application of an Even-Mansour construction. In order to optimize performance, the designers chose a relatively small number of rounds, using properties of the mode and bounds on differential and linear characteristics to substantiate their security claims. Due to a forgery attack with complexity of $$2^{46}$$ , FlexAEAD was not selected to the second round of evaluation in the NIST project. In this paper we present a practical key recovery attack on FlexAEAD, using clusters of differentials for the internal permutation and the interplay between different parts of the mode. Our attack, that was fully verified in practice, allows recovering the secret subkeys of FlexAEAD-64 with time complexity of less than $$2^{31}$$ encryptions (with experimental success rate of 75%). This is the first practical key recovery attack on a candidate of the NIST standartization project.
Review of Feature Selection Methods and Semi Supervised Feature Selection Algorithms for Classification

Current evolution in technology has resulted in tremendous growth of data with respect to dimensionality and sample size. Knowledge discovery from these high dimensional data are becoming cumbersome. Though powerful machine learning algorithms are prevalent, noisy data, imperfect sensing and collection of data leads to poor and defective knowledge discovery. Noise and redundant features cannot be circumvented due to which data collection process is biased. Dimensionality reduction techniques namely feature extraction and feature selections are the two most popular techniques to remove redundant and irrelevant features in huge dimensional data. Compared to feature extraction, feature selection leads to better readability and interpretability of features. This paper presents an extensive preliminary understanding about feature selection and attempts a comprehensive recent survey of semi supervised feature selection methods. This summary enables the researcher to obtain a deep understanding in choice of semi supervised feature selection algorithms for improving the learning performance. Keywords: Feature Selection, Semi supervised learning, Filters, Wrappers, Hybrid methods. Cite this Article: A. Meena Kowshalya, M.Lincy, R. Suvarna. Review of Feature Selection Methods and Semi Supervised Feature Selection Algorithms for Classification. International Journal of Software Computing and Testing. 2020; 6(1): 39–51p.
RESPONSIBILITY FOR REFORMING THE SYSTEM OF ASSURANCE OF HIGHER EDUCATION QUALITY: ANALYSIS OF EMPLOYERS’ OPINIONS AND WAYS TO IMPROVE PUBLIC ADMINISTRATION MECHANISMS IN THE SPHERE OF HIGHER EDUCATION EDUCATION

The problematics of employers’ participation in assessing the effectiveness of the functioning of the system of ensuring by higher education institutions of the educational activities’ quality and higher education quality is researched in the article. The article highlights the features of using the survey method to obtain information about the level of higher education quality, as well as the results of analyzing the content of questionnaires and interviewing employers regarding the level of responsibility of individual stakeholders in implementing reforms of the assurance system of higher education quality. The article suggests ways to improve the state policy on ensuring the quality of higher education at the University and state levels.
Breve reseña sobre el estado actual de la Inteligencia Artificial

The main goal of this paper is to present a global view of the current state of Artificial Intelligence, its most important methods and achievements, as well as its applications in the solution of several socio-economics and scientific problems. Some tendencies of its development are discussed and the consequent challenges for the human society, because of its insertion in all dimensions of the human life, including the prevention of possible negative effects in the future.  This conceptual presentation serves as a presentation of the papers included in this number of the journal.
The expansion of e-learning in the UAE: Implications and opportunities in the post-COVID-19 era

The COVID-19 pandemic has forced higher education institutions (HEI) in the United Arab Emirates (UAE) and globally to hastily rework their systems and become more innovative in their online teaching and learning approach. This chapter presents the conceptual basis for understanding, analyzing, and designing an informed implementation plan for new e-learning systems in the UAE. Rogers' (2003) Diffusion Innovation Theory is used to assess which factors affect the UAE’s public higher education institutions’ intention and ability to adopt e-learning during the COVID-19 era. It is determined, to lower complexities the pandemic presents and promote the UAE’s post-crisis growth, public HEI must rework their traditional higher education model while safeguarding the UAE’s social and cultural standards for e-learning. Overall, with the observed benefits of increased access and developing a new generation of technologically skilled creative thinkers, the UAE’s advanced infrastructure is equipped and ready to become a global hub for e-learning.
Il ruolo delle emozioni in contesto glotto-geragogico

Emotions play a key role in human life. Indeed, emotions are essential for human life so much that the survival of the human species would be compromised in the absence of emotions. Emotions have an important biological function and they play a fundamental role in the human adaptation during the evolution processes. Emotions guide our decisions, goals, and interests. They are involved in the development of judgments and opinions on the world around us and they contribute significantly to the social and sentimental interaction of the individual within the society in which he/she lives. Given these premises, in this paper it will be argued the fundamental role of emotions in the learning processes and their deep connection with the cognitive functions. In particular, the increasing importance of emotions during human life will be taken in consideration. In this perspective, it will be highlighted that the elderly appreciate emotions and emotional experiences and several studies confirm that the processing of emotions do not deteriorate in the elderly, but rather they are improved. Therefore, for the language education of the elderly, emotions must be considered a central aspect.
Comparative Analysis of Service Quality Load Balancing Using NTH and PCC Methods in Internet Access Process

The quality of service on the network is very important. To improve internet performance without time constraints, a solution is needed to ensure its availability. One technique that can be used to ensure internet availability is load balancing, this technique works by providing two or more active links to divide data traffic between links, so that if one link dies or overloads it can be diverted to other links evenly. In this study, the methods that will be used as load balancing techniques are NTH and PCC. While the research methodology used is qualitative and comparative, where the comparative method will compare the results of testing load balancing techniques using the NTH and PCC methods. Testing is carried out by means of downloading files in sizes > 100 MB and < 100 MB. For QoS performance analysis based on parameters: delay, jitter packet loss and throughput. The results of the best Quality of Service (QoS) load balancing after being tested and compared based on predetermined parameters resulted in the conclusion that the NTH method was slightly better than PCC.
Visual Information Fidelity with better Vision Models and better Mutual Information Estimates

*INTRODUCTION*: Visual Information Fidelity [1] is a subjective image distortion measure based on: (i) a noisy observer model, and (ii) a method to quantify mutual information. Specifically, given two images A (original) and B (distorted), and their responses through the model R(A) and R(B), the visual fidelity is defined as the ratio between the amount of information about A that can be extracted from R(B) and the corresponding amount that can be extracted from R(A). The information about X that is available from Y is quantified via the mutual information, I(X,Y). Therefore: VIF(A,B) = I(A,R(B)) / I(A,R(A)). The original VIF used a too crude vision model (linear wavelet pyramid + Gaussian noise) and a too crude mutual information estimate (based on a simplified image statistics model). In this work we explore how better vision models and better information measures may lead to a better explanation of image quality psychophysics. *METHODS*: we improve the linear vision model in original VIF by using divisive normalization stages for brightness and contrast masking [2], we use a more accurate psychophysical estimate of neural noise [3], and an estimate of mutual information that does not rely on parametric assumptions [4]. *RESULTS AND CONCLUSION*: the correlation with human opinion with images from the TID-2008 database improves from 0.78 (using the original formulation of VIF) up to 0.90 using some of the proposed improvements. This suggests that an appropriate consideration of the neural noise and a non-parametrical measure of mutual information are critical in assessing subjective image quality. *REFERENCES*: [1] H. Sheikh, A. Bovik. IEEE Trans. Im. Proc., 15(2):430–444, 2006 [2] M. Martinez, P. Cyriac, T. Batard, M. Bertalmío & J. Malo. PLOS ONE, 13(10):1–49, 10 2018. [3] J.Esteve, G.Aguilar, M.Maertens, FA.Wichmann & J.Malo. https://arxiv.org/abs/2012.06608, 2020 [4] J. Malo. J. Math. Neurosci., 10, 18 (2020). https://doi.org/10.1186/s13408-020-00095-8