Reviewerly/exHarmony huggingface dataset:
Self-Actualization In The Process Of Consumption Of A Cultural Product

Social constructionism today is one of the relevant approaches to the study of questions about the possibilities of a person as an object of cognition, its practical and transformative abilities.The study presents the result of creating a social construction of the model of "self-actualization" and its interaction with the models of "self-realization", "human potential", "cultural product" and "consumption".The determination of the form and filling of the model took place in the process of studying the problem of needs and their satisfaction (consumption), in particular, the need for self-actualization as a certain act performed by the subject on the basis of goals that are consciously set for themselves in the course of selfrealization and their achievement.The model is developed taking into account the ontological aspect and reflects the functional orientation of human/society activities.The model of "self-actualization" was based on the following principles of the functioning of the individual subject, social group and society as a whole: the natural world, which characterizes everyday life, the need, the lack of satisfaction as in the condition of maintaining vitality; cultural (human) potential, i.e. human resources, human capital, life potential (overall vitality), intellectual potential, personal potential; cultural form as an initial sample for subsequent direct or variable reproduction; cultural filter, i.e. personal tastes of the subject of consumption, value norms of the subject and society at a certain stage of historical development; artificial world, i.e. the world of existing cultural forms, products of human activity.
Scalable Structure Learning of K-Dependence Bayesian Network Classifier

K-dependence Bayesian network classifier(KDB) has been widely used in data mining and machine learning.To enhance the expression ability and classification performance of KDB, the present study proposes a scalable k-dependence Bayesian classifier (SKDB), which is an extension of the classic KDB algorithm.SKDB introduces a novel attribute sorting method to pre-determine the optimal attribute order and a filtering mechanism to eliminate weak conditional dependence.Experimental results on 30 datasets from the University of California at Irvine (UCI) machine learning repository demonstrate that the above two techniques exert a positive impact on the classification performance of KDB.The proposed algorithm(SKDB) achieves better classification performance compared with several state-of-the-art BNCs (such as Naïve Bayes, tree-augmented Naïve Bayes, averaged one-dependence estimators, and KDB) in terms of 0-1 loss, bias, and variance.
On the failure of the smart approach of the GPT cryptosystem

This paper describes a new algorithm for breaking the smart approach of the GPT cryptosystem. We show that by puncturing the public code several times on specific positions, we get a public code on which applying the Frobenius operator appropriately allows to build an alternative secret key.
Image encryption scheme based on a Gaussian apertured reality-preserving fractional Mellin transform

An image encryption scheme based on a Gaussian apertured reality-preserving fractional Mellin transform (GARPFrMT) is proposed. The GARPFrMT was realized in the diffraction domain. The Gaussian aperture, like a soft aperture, improved the amount of light that passed through the lens compared to a hard aperture and reduced the light leakage at the edge of the lens, assisting to some extent in resisting direct attacks. In the proposed scheme, the reality-preserving transform was constructed in the diffraction domain to ensure that the cipher-text is real. The GARPFrMT is a nonlinear transformation used for eliminating potential insecurity existing in the linear image encryption system. In order to further enhance the security of the encryption system, an Arnold transform, and a bitwise XOR operation were employed for permutation and scrambling in the encryption process. Simulation results and theoretical analysis show that the proposed algorithm is feasible and capable of withstanding several common attacks.
Moving Load Robot Using Wifi Network and Android Based

A robot is a mechanical device that can perform physical tasks, either using human supervision or control by using predefined programs. In this research, a robot prototype will be designed that can move goods in the form of glasses and plates from one place to another using controls from Android. This system or robot can work as expected, the system is capable of mapping based on the path that has been made. The method used in developing this robot is the prototype method so that the robot is built according to the needs that the user wants directly and can be revised according to the user's wishes after making the design. The robot is also able to take a glass / plate from the table to move it to the desired place. From the experiments that have been carried out as many as 10 times on the movement of the robot to move glasses and plates, the research got a value of 50% perfect success rate, 30% who failed in the middle of the road, and 20% who failed to do the mapping of all the series of experiments that must be passed.
The Impact of the Educational Potential of School on Successful Development of the Motivation-value Attitude to the Learning Activities of Students

An analysis of the state of education at school leads to the conclusion that, in the secondary school age, the individual enters a new period of development and the definition of personal values changes.The psychological characteristics of students of this school age make it more urgent to develop the motivation and value of students of secondary school age in their educational activities.In order to achieve this goal, it is necessary to seek and explore conditions that encourage motivation to maintain interest in the cognitive activities of students.The article at the theoretical and empirical level proves that the level of development of motivation and cognitive activity depends on the conditions of education and upbringing defined pedagogical conditions that have the greatest impact on these personal characteristics.The authors identified the following conditions: training using the research method, based on the leading type of activity, taking into account the personal interests of students, building individual educational routes, by filling them with non-formal education funds as part of extra-time activities.These studies make a theoretical contribution to pedagogical science.The validity of the provisions is also proved by empirical research (questionnaires, observations, testing).The experimental study also applied mathematical methods to the results of the experiment (of variation, Whitney U-test).The results obtained by the authors can be useful for further research into the development of motivational and value attitude to cognitive activity of secondary school students in a digital educational environment.
OPTIMIZATION OF DUAL-TREE COMPLEX WAVELET PACKET BASED ENTROPY FEATURES FOR VOICE PATHOLOGIES DETECTION

The Dual-Tree Complex Wavelet Packet Transform (DT-CWPT) has been successfully implemented in numerous field because it introduces limited redundancy, provides approximately shift-invariance and geometrically oriented signal in multiple dimensions where these properties are lacking in traditional wavelet transform. This paper investigates the performance of features extracted using DT-CWPT algorithms which are quantified using k-Nearest Neighbors (k-NN) and Support Vector Machine (SVM) classifiers for detecting voice pathologies. Decomposition is done on the voice signals using Shannon and Approximate entropy (ApEn) to signify the complexity of voice signals in time and frequency domain. Feature selection methods using the ReliefF algorithm and Genetic algorithm (GA) are applied to obtain the optimum features for multiclass classification. It is observed that the best accuracies obtained using DT-CWPT with ApEn entropy are 91.15 % for k-NN and 93.90 % for SVM classifiers. The proposed work provides a promising detection rate for multiple voice disorders and is useful for the development of computer-based diagnostic tools for voice pathology screening in health care facilities.
An assessment of heavy metals concentration in water around quarries and barite mine sites in part of central Cross River State, Southeastern Nigeria

The assessment of the level of heavy metal concentrations in water sources around quarries and barite mine sites in central Cross River State, Southeastern Nigeria, was carried out to evaluate the degree of contamination due to mining and quarrying activity in the area. The investigation involved the collection of twelve water samples from ponds, streams, river and boreholes around the area. The water samples were passed through 0.45 µm filter paper and preserved with a drop of 0.1M HNO3 acid. The preserved samples were analyzed for their heavy metal (Ba, Cr, Cu, Fe, Mn, Pb and Zn) content, using inductively coupled plasma-mass spectrometry (ICP-MS). The results show that the average concentration of Ba, Cu, MN, Pb and Zn were above WHO guideline value for drinking water quality, hence not suitable for drinking. The average concentration of the metals is in the order Ba&gt;Mn&gt;Cu&gt;Fe&gt;Pb&gt;Zn&gt;Cr. Computed values of contamination index show that the samples from four locations were contaminated. Single factor pollution index computation indicates that the waters are not contaminated with Cr, but slightly polluted with Fe and Zn, moderately polluted with Ba and severely polluted with Cu, Mn and Pb. Further, Nemerow comprehensive pollution index indicates that samples from four locations were severely contaminated. The study revealed that the water sources around the barite mines had elevated level of heavy metal concentration compared to location around the quarries. It is recommended therefore, that the water be treated before use for drinking purpose.&#x0D; Keywords: heavy metals, contamination index, pollution index, barite mine, quarry
A Selection of Bandung City Travel Route Using The FLOYD-WARSHALL Algorithm

The rapid development of information and technology, the city of Bandung tourism has also increased. However, tourists who visit the city of Bandung have problems with a limited time when visiting Bandung tourist attractions. Traffic congestion, distance, and the number of tourist destinations are the problems for tourists travel. The optimal route selection is the solution for those problems. Congestion and distance data are processed using the Simple Additive Weighting (SAW) method. Route selection uses the Floyd-Warshall Algorithm. In this study, the selection of the best route gets the smallest weight with a value of 5.127 from the Algorithm process. Based on testing, from two to five tourist attractions get an average calculation time of 3 to 5 seconds. This application is expected to provide optimal solutions for tourists in the selection of tourist travel routes.
Peculiarities of superiority and inferiority complexes of Ukrainians

Introduction: The central concept of the Adlerian theory of personality is the feeling of inferiority, which main function is to activate compensatory processes that make a person want to improve, grow and overcome their perceived weakness (Adler, 1989). The evidence of such processes is the life choices of people in the sphere of education and occupation.&#x0D; Purpose: The main purpose of the present work is to highlight the study results of inferiority and superiority complexes peculiarities of Ukrainians, their relation to the education and occupation choices.&#x0D; Methodology: The study sample included 449 subjects (282 females, 168 male) between 17 and 85 years old (M=32,96, SD = 13.299). Subjects were recruited from the general population by students who participated in the data collection. Participation in the study was voluntary and anonymous. Inferiority and superiority complexes were assessed using Adlerian inferiority (COMPIN) and superiority (SUCOMP) complex shortened scales (Čekrlija et al., 2017); socio-demographic variables such as gender, age, education and occupation were included.&#x0D; Results: Results show that approximately 70% of respondents have an average level of inferiority and superiority complexes. There is no significant correlation between the mentioned complexes and gender, but there is a negative correlation between the inferiority complex and age (r=.187). The younger Ukrainians are the more intensive inferiority complex they have. Occupation correlates negatively with the inferiority complex (r=.-120) and positively with the superiority complex (r=. 119). The more intensive superiority complex is, the higher positions occupy the respondents. Only inferiority complex correlates negatively with a level of education (r=.-160). People with higher education have less intensive inferiority complex.&#x0D; Conclusion: In sum, it is peculiar to Ukrainians to overcome inferiority complex with age. The intensity of their inferiority and superiority complexes doesn’t depend on gender. Ukrainians who occupy the high positions have a lower inferiority complex and higher superiority complex. People with low educational level have inferiority complex propensity
PEMBELAJARAN MODEL GAMBAR DAN SUGESTI IMAJINER TERHADAP KEMAMPUAN MENULIS PUISI DAN SASTRA

Abstract - Growing the interest of writing students takes the teacher's efforts to motivate with various interesting and not boring teaching models. Through this research to obtain the effectiveness of picture and picture models and imaginary suggestions on the interest in writing literature poetry of grade VIII students at SMP Swadaya I Bandung. Simple research among others group 1 grade VIII-B using pinture and picture models and group 2 through imaginary suggestion, with quasi design design experiments with the form of model nonequivalent control group design. From the results of the study it is known that the image model is more effective and attractive to students, than the second model of imaginary suggestion in fostering the interest of learning to write poetry literary texts of students, especially in grade VIII junior high school. &#x0D; Abstrak. Menumbuhkan minat menulis siswa dibutuhkan upaya guru untuk memotivasi dengan berbagai model pengajaran yang menarik dan tidak membosankan. Melalui penelitian ini untuk memperoleh efektifvitas model picture and picture dan sugesti imajiner terhadap minat menulis puisi sastra siswa kelas VIII di SMP Swadaya I Bandung. Simple penelitian antara lain grup 1 kelas VIII-B menggunakan model pinture and picture dan grup 2 melalui sugesti imajiner, dengan desain quasi eksperimen desain dengan bentuk model nonequivalent control group desain. Dari hasil penelitian diketahui bahwa model gambar lebih efektif dan menarik bagi siswa, ketimbang model kedua sugesti imajiner dalam menumbuhkan minat belajar menulis puisi sastra teks siswa, khususnya di kelas VIII SMP.
Quality Assessment and Reserve Estimation of the Egnaeja Iron Ore Deposit, North-Central Nigeria using Integrated Approach

Field, Geochemical and Airborne Geophysical data were integrated in mapping the iron ore deposit around Egnaeja and environs.This research aimed at providing detail geological information that would help in the exploitation of the iron ore deposit in the area through the identification of its precise location, determination of its quality and estimation of its probable reserve.From the aeromagnetic data, strong magnetic signatures that are associated with Iron ore mineralization are well-spread within the study area.The SPI depth estimate to the magnetic sources in the area varies between 20 and 100 m.Areas with high magnetic intensity were observed to have high Thorium (Th) and Uranium (U) counts but low Potassium (K) count.Detailed geological mapping carried out indicates that pisolitic and oolithic ironstones outcrop in more than two-thirds of the study area.From field observation, the thickness of the deposits varied between 2 and 16 m with an average of 9 m while the specific gravity varies from 3.13 to 3.97 with an average of 3.54.The overburden thickness varies from 0 to 10m indicating a high possibility of near-surface exploitation of this resource at a profit.Geochemical analyses of twelve representative samples from the study area reported that the percentage of Iron oxide (Fe 2 O 3 ) in the samples ranges from 89.83 to 96.91% with an average of 93.04% while the phosphorus content varies from 0.53% to 1.75% with an average of 1.208% indicating high-grade iron ore deposit.An inferred reserve estimate of about 250 million tons of mineable ironstone deposit was calculated for the area.Although this inferred reserve of mineable iron ore deposit is quite encouraging, core drilling is recommended to inform adequate modelling of the reserve to make assurance a double sure prior to exploitation.
Automatic Analysis of Speech Prosody in Dutch

In this paper we present a publicly available tool for automatic analysis of speech prosody (AASP) in Dutch.Incorporating the state-of-the-art analytical frameworks, AASP enables users to analyze prosody at two levels from different theoretical perspectives.Holistically, by means of the Functional Principal Component Analysis (FPCA) it generates mathematical functions that capture changes in the shape of a pitch contour.The tool outputs the weights of principal components in a table for users to process in further statistical analysis.Structurally, AASP analyzes prosody in terms of prosodic events within the auto-segmental metrical framework, hypothesizing prosodic labels in accordance with Transcription of Dutch Intonation (ToDI) with accuracy comparable to similar tools for other languages.Published as a Docker container, the tool can be set up on various operating systems in only two steps.Moreover, the tool is accessed through a graphic user interface, making it accessible to users with limited programming skills.
Utilizing Debugging Information of Applications in Memory Forensics

The rapid development in the digital world has contributed to the dramatic increase in the number of cybercrimes. An application's volatile data that is kept in memory (RAM) could give clues on how a criminal has been using the application up to acquisition time. Unfortunately, application-level memory forensics has been conducted in an ad hoc manner because a forensic investigator has to come up with a new technique for a new application. This process has become problematic and exhausting. This paper proposes a general solution to investigate any application in memory. We heavily utilize applications' debugging information generated by compilers in our solution. Furthermore, we extend Volatility [Walters, 2007], an open-source memory forensic framework, by developing and integrating a plugin to investigate applications in memory. We design several experiments to evaluate the effectiveness of our plugin. Interestingly, our plugin can parse debugging information and extract variables' names and data types regardless of their scope and complexity. In addition, we experimented with a real world application and succeeded in collecting vital information out of it. By accurately computing the Virtual Addresses (VA) of variables along with their allocated memory sizes based on their types, we are able to extract their values out of memory. In addition, we trace call stacks as per threads to extract local variables' values. Finally, direct and indirect pointers are successfully dereferenced.
PENGEMBANGAN MEDIA PEMBELAJARAN TEKA-TEKI SILANG (TTS) PADA PEMBELAJARAN TEMATIK TEMA CITA-CITAKU KELAS IV DI MI AL BUSYRO

The use of instructional media really helps teachers develop and deepen the teaching and learning process in the classroom. The use of instructional media that varies appropriately can affect student learning activities, interests and motivation. Therefore, learning media that are not boring are needed. One of them is with game-based media, such as crossword puzzles. Based on the background and study of the theory, this research is expected to provide answers to the formulation of the problem: (1) What is the validity of the crossword puzzle media on the thematic learning of my ideals for grade IV at MI Al-Busyro? (2) What is the practicality of the crossword media in the thematic learning theme of my ideals grade IV at MI Al Busyro? (3) What is the effectiveness of the crossword puzzle media on the thematic learning of my ideals for grade IV at MI Al Busyro ?. The objectives in this study are (1) Knowing the validity of the crossword puzzle media on the thematic learning theme of my ideals grade IV at MI Al Busyro? (2) Knowing the practicality of the crossword media in the thematic learning theme of my ideals grade IV at MI Al Busyro? (3) Knowing the effectiveness of the crossword puzzle media in the thematic learning theme of my ideals grade IV at MI Al Busyro ?. This research is a type of research or development known as Research and Development (R&amp;D). This research was conducted in MI Al-Busyro class IV. The instrument used in the form of a validation sheet to measure validity, questionnaire responses of teachers and students to measure the level of practicality, and items to measure the level of effectiveness through student tests. The data that has been obtained is then analyzed using qualitative and quantitative descriptive data analysis. Based on the results of the validity analysis, (1) The crossword puzzle media developed are in the very valid category with a value of 90.5%. (2) The results of the teacher's response questionnaire were 93% and the results of the student's questionnaire responses were 90% and each was in the very good category. (3) The percentage of student graduation is more than 85%. Thus, it can be concluded that the developed crossword puzzle media meet valid, practical and effective categories.
Double-Wing Mixture of Experts for Streaming Recommendations

Streaming Recommender Systems (SRSs) commonly train recommendation models on newly received data only to address user preference drift, i.e., the changing user preferences towards items. However, this practice overlooks the long-term user preferences embedded in historical data. More importantly, the common heterogeneity in data stream greatly reduces the accuracy of streaming recommendations. The reason is that different preferences (or characteristics) of different types of users (or items) cannot be well learned by a unified model. To address these two issues, we propose a Variational and Reservoir-enhanced Sampling based Double-Wing Mixture of Experts framework, called VRS-DWMoE, to improve the accuracy of streaming recommendations. In VRS-DWMoE, we first devise variational and reservoir-enhanced sampling to wisely complement new data with historical data, and thus address the user preference drift issue while capturing long-term user preferences. After that, we propose a Double-Wing Mixture of Experts (DWMoE) model to first effectively learn heterogeneous user preferences and item characteristics, and then make recommendations based on them. Specifically, DWMoE contains two Mixture of Experts (MoE, an effective ensemble learning model) to learn user preferences and item characteristics, respectively. Moreover, the multiple experts in each MoE learn the preferences (or characteristics) of different types of users (or items) where each expert specializes in one underlying type. Extensive experiments demonstrate that VRS-DWMoE consistently outperforms the state-of-the-art SRSs.