Reviewerly/exHarmony huggingface dataset:
SpaceSheet: Navigating Conceptual Space with a Spreadsheet Interface

We introduce a new spreadsheet based interface called SpaceSheets for creating novel images and other me- dia. Unlike traditional digital tools, ours is parame- terized entirely by a neural network with no prepro- grammed rules or knowledge representations. The ca- pability of SpaceSheets to support visual exploration and communication is demonstrated within the context of several domains including facial images, fonts, and english words. SpaceSheets is demonstrated to support the experimentation and exploration of latent spaces en- abling more effective design experimentation.
FPGA Implementation of Adaptive Multiplier-Based Linear Image Interpolation

This work provides an image interpolation for multimedia applications by utilizing an adaptive multiplier-based stepwise linear interpolation with clam filter. Image interpolation is also termed as image up-scaling. Generally, while enlarging an image some vacant bit positions are introduced and due to this empty pixel positions, the quality of the image is decreased. Therefore to maintain the quality of the image, new pixels are introduced and those pixels are used to fill the vacant bit positions by using interpolation techniques. In the adaptive interpolation techniques, edge pixels are identified and filtered at prior to the interpolation process. This will improve the quality of the interpolated image. However, the adaptive interpolation scheme increases the complexity of the system. To reduce the complexity, this work uses low complexity stepwise linear interpolation and to maintain the quality it uses multiplier-based linear stepwise (MBLSI) and edge enhancement technique. The experimental results demonstrate that the complexity of the proposed work is less as compared with other related work as well as the quality is also maintained. The proposed work utilizes 275 LUTs to provide the average peak signal to noise ratio (PSNR) of 20.44 dB and structural similarity index (SSIM) as 0.8250. This proposed work increases the PSNR by 0.89 dB from the conventional multiplier-based stepwise linear interpolation. Further the proposed interpolation algorithm utilizes less number of resources in field programmable gate array (FPGA) by comparing with other related interpolation techniques.
Recommendation Model Using User Reviews and Deep Learning Approach

Due to the growing amount of information on the web, the information overload problem arises for users to discover relevant products easily and quickly.Collaborative Filtering (CF) is a recommender system which uses the user-item rating matrix to make suggestions to users by finding many users' similar preferences.User reviews have information about products and users' opinions than ratings.Using Opinionbased ratings in the rating prediction process of recommender system can reflect the detail preference of users effectively and accurately.In this paper, sentiment analysis is used to find the opinions of the user and matrix factorization that applied neural network is used to predict the ratings for the recommendation.The experiment is performed on the dataset of the hotel reviews and rating prediction accuracy is evaluated by measuring the prediction error called the Root Mean Square Error (RMSE).
Approaches of Authorship Verification

Nowadays, there are massive amounts of texts in digital form in digital libraries, online journalism, and social networks; for example, Twitter is estimated half a billion tweets are sent out each day.The expanded usage of Online Social Network (OSN) has become necessary to appear to grow of Authorship Verification (AV), OSN is the environment in which users can connect with other users to discuss ideas of any topics then expansion data and information.AV considered as a resource of researches and information in different ways, as is the case Sentiment Analysis (SA).Information that gained from Twitter and Facebook or any other OSN is considered valuable in some areas such as public opinion organizations and online marketing.The crimes also increased over on the internet with textual data.To reduce the problems raised on text through the internet, the researchers have attracted to authorship analysis which is one of the important areas.AV is a type of authorship analysis that is used to verify an author by checking whether the text document is written by the disputed author.The accuracy of AV depends primarily on the features used to distinguish the writing style of documents.In previous works of AV, researchers proposed several types of stylistic features for distinguishing the writing style of the authors.The researchers analyzed that the AV performance was weak when used stylistic features alone in the experiments.Therefore, researchers resorted to more accurate methods that compute the features by using the weight measures.The weight measures calculate the document weights of training, and test documents.Then, the competition between the weights of training document and the weights of test document were implemented; to verify the author of the document.
A Novel Fuzzy Model for Software Cost Estimation

It predicts the estimated cost at beginning periods of development life cycle is a challenging assignment for the powerful management of any software industry. This model essentially considered on the significance of the datasets was utilized for analysis, kinds of intelligence and Fuzzy Logic were applied to foresee estimated cost lastly, execution assessed of prediction methods. From our model, we found that the COCOMO dataset is the most conspicuous dataset, trailed by NASA, and DESHARNAIS dataset. The MARE and MMRE are noticeable execution assessment methods in the field of study. Further, we found that the Neural Networks technique was repetitively utilized when contrasted with different models pursued by the Hybrid techniques, at that point Fuzzy Logic, Decision Tree and Evolution Computation in a specific order. This model is serving to incredible for research apprentices in the arena of software cost Estimation.
Detection of Counterfeit Currency using Discrete Wavelet Transform in MATLAB

Counterfeit notes are one of the major issue in money transactions. In a growing country like India, it is becoming big problem for the economy. As the advances in printing and scanning technologies are developing, it is very easy for any person to print counterfeit notes with use of latest hardware machines. Identifying counterfeit notes in manual way takes a lot of time and manpower. Hence there is requirement of automation technique using which the counterfeit currency recognition process can be done effectively. Many methods have been proposed and implemented with MATLAB. By using Discrete cosine transform (DCT) algorithm blocks of the image are represented by coefficients of DCT. So, due to the presence of blocking articrafts in DCT, it is a drawback for this method. Hence, We have implemented a counterfeit note detection unit with a different algorithm which uses discrete wavelet transform (DWT) in MATLAB. This paper is another attempt on the same project to give a better solution for counterfeit currency problem.
PEMANFAATAN ALGORITMA FUZZY NAIVE BAYES DALAM PEMILIHAN BIDANG KEAHLIAN MAHASISWA TEKNIK INFORMATIKA UNIVERSITAS ISLAM LAMONGAN

One of the factors that can determine the smoothness of students in taking lectures well is the selection of areas of interest in accordance with the abilities of students, meaning that if students determine the choice of majors in accordance with their field of expertise then certainly there will be no difficulty to develop themselves in the lecture process.this study by utilizing two algorithms, namely Fuzzy and Naive Bayes to determine the areas of expertise of students. Informatics Engineering students have the opportunity to choose a field of expertise, namely: the field of network expertise, programming, and design. Not all students will master the area of expertise, so they must choose to accord to their skills, hobbies and favorite subjects, and grades. This research will create a system for classifying the expertise of UNISLA informatics engineering students. The algorithm is implemented, namely Fuzzy to categorize the values or input numbers, while Naïv e Bayes is used for classification
Protected multimodal emotion recognition

In this thesis, we propose Protected Multimodal Emotion recognition (PMM-ER), an emotion recognition approach that includes security features against the growing rate of cyber-attacks on various databases, including emotion databases. The analysis on the frequently used encryption algorithms has led to the modified encryption algorithm proposed in this work. The system is able to recognize 7 different emotions, i.e. happiness, sadness, surprise, fear, disgust and anger, as well as a neutral emotion state, based on 2D video frames, 3D vertices, and audio wave information. Several well-known features are employed, including the HSV colour feature, iterative closest point (ICP) and Mel-frequency cepstral coefficients (MFCCs). We also propose a novel approach to feature fusion including both decision- and feature-level fusion, and some well-known classification and feature extraction algorithms such as principle component analysis (PCA), linear discernment analysis (LDA) and canonical correlation analysis (CCA) are compared in this study.
COGNITIVE REFLECTION TEST - NEXT GENERATION

Purpose -The aim of this paper is to investigate the correlation between the short Cognitive Reflection Test and the long Cognitive Reflection Test (CRT), the gender effect and the educational level effect on short CRT and long CRT, as well as the Granger causality between the two ones. Design / Methodology / Approach -A statistical analyze was provided and econometric measures and tests were used, in EViews and SPSS, like the Pearson Correlation Coefficient and the Granger Causality. A critical assessment of literature review was made. For collecting the data, quantitative methods were used (questionnaires). Findings -There is a significant, strong and positive correlation between the short Cognitive Reflection Test version (short CRT) and the long version (long CRT), long CRT Granger causes short CRT, girls outperformed boys on each educational level. Practical implications -Long CRT could be an alternative for short CRT, which is now overexposed and widely known.Originality / Value -Once thinking system 2 is trigged by completing another questionnaire, the results on CRT in either version increased, even if the nature of the other questionnaire is completely different.Limitations -The other questionnaire was administrated only for high school students.Future research should be conducted in order to trig the thinking system 2 before administrating the test for secondary school and university students too.
Devnagari Handwritten Characters Image Super-Resolution based on Enhanced SRGAN

The difficulty in machine learning-based image super-resolution is to generate high-frequency component in an image without introducing any artifacts. In this paper, Devnagari handwritten characters image using a generative adversarial network with a classifier is generated in high-resolution which is also classifiable. The generator architecture is modified by removing all batch normalization layers in generator architecture with a residual in residual dense block. Batch normalization is removed because it produces unwanted artifacts in the generated images. A Devnagari handwritten characters classifier is built using CNN. The classifier is used in the network to calculate the content loss. The adversarial loss is obtained from the GAN architecture and both of the losses are added to obtain total loss. Generated HR images is validated using six different evaluation metrics among which MSE, PSNR determines pixel-wise difference and SSIM compares images perceptually. Similarly, FID is used to measure the statistical similarity between the batch of generated images and its original batch. Finally, the Gradient similarity is used to assess the quality of the generated image. From the experimental results, we obtain MSE, PSNR and SSIM as 0.0507, 12.95(dB) and 0.8172 respectively. Similarly, the FID value obtained was 27.5 with the classification accuracy of image data of 98%. The gradient similarity between the generated image and the ground truth obtained was 0.9124.
ADVANCES OF DIGITAL TECHNOLOGY IN HIGHER EDUCATION

The paper deals with the achievements of digital technologies in higher education.It's unthinkable today to live without technology.Technologies Involved in all areas of human activity and saves a lot of time and effort.Technologies have had and will continue to have a significant impact on higher education, while technological innovation will have a major impact on teaching methodologies.Through technology, the learning process becomes more diverse, more attractive, more stimulating.The use of information and communication technologies is also one of the most effective visualizations during the lesson, which makes it easy to perceive and understand the new information provided to students.Today's education process without technologies is less interesting and informative, hence the availability of information and communication technologies and the study of integration in education is topical.
Prediction of Employee Attendance Factors Using C4.5 Algorithm, Random Tree, Random Forest

Research on the performance of workers based on the determination of standard working hours for absences conducted by workers in a certain period. In disciplinary supervision, workers are expected to be able to provide the best performance in the implementation of work in accordance with predetermined working hours. The measurement of the level of discipline of admission hours for placement workers is carried out every working day, continuously and continuously. Attendance monitoring already uses online attendance by using data downloaded from the online attendance provider as the main data. In addition, data collection is done by filtering employee absentee data and supporting information on the categories that cause mismatches in meeting work schedules. Mobilization of workers according to location and working hours has been regulated in company regulations allowing the placement of workers in accordance with the residence so as not to affect the desired work results the company is still within reasonable limits and can be increased. The assessment of this study as a progression factor inhibiting the company in achieving company targets. From the results of the author's analysis of the prediction of employee delay factors using three algorithms, namely the C.45 algorithm accuracy = 79.37% and AUC value = 0.646, Random Forest Algorithm accuracy = 78.58% and AUC value = 0.807 while for the Random Tree algorithm accuracy = 76.26% and the AUC value = 0.610.
Interactive comment on “Estimation of phytoplankton pigments from ocean-color satellite observations in the Sénégalo-Mauritanian region by using an advanced neural classifier” by Khalil Yala et al.

This paper presents a new neural classifier model for estimating phytoplankton pigments from satellite data, by using an unsupervised learning method instead of the standard supervised learning approach, as the sample size is limited.The method involves blocking the variables as opposed to the unblocked approach in the standard self-organizing map (SOM) approach.I believe the writing needs considerable improvement, as the paper is difficult to read, and the advantage of their 2S-SOM over the standard SOM is not brought out.The English can also be improved.
Real Time Object Detection and Text Extraction

—this paper distinguishes and analyzes diverse stages during the time spent content discovery and acknowledgment and investigations distinctive methodologies utilized for content extraction from real time pictures. Two generally utilized techniques for this issue are stepwise strategies and coordinated techniques, though this undertaking is additionally partitioned into content discovery and confinement, grouping, division and content acknowledgment. Imperative methodologies used to experience these stages and their comparing favorable circumstances, disservices and applications are exhibited in this paper. Different content related applications for symbolism are additionally introduced here. This survey performs a similar examination of crucial procedures in this field. This paper thinks about different stages in the procedure of content discovery and acknowledgment and examinations and analyzes distinctive methodologies used to experience these stages. It presents the significance of each handling stage and focal points, weaknesses, and utilization of methodologies utilized by different supporters of take care of these issues. Different uses of content identification and acknowledgment are additionally assessed in this paper. Content acknowledgment arranges changes over pictures of content into a series of characters or words. It is essential to change over pictures of content into words as a word is a rudimentary substance utilized by a human for his visual acknowledgment. Diverse methodologies of acknowledgment are character acknowledgment and word acknowledgment. Character acknowledgment techniques separate the content picture into numerous patterns of single characters. The partition between contiguous characters is imperative for these techniques.
Modelling the Indigenous virtual self using fuzzy logic as a data filtering system

Virtual reality offers tremendous opportunities for Indigenous communities to experience themselves inside unreal settings not available in the real world. However, virtual reality as a technology is complex involving both an internal and external connection that is usually dependent on one’s attention shifting from the physical Indigenous environment to the virtual reality environment. Any deviance from heritage or known Indigenous relationships may result in a disconnected drift between the traditional and unreal digital world if wrongly presented. The concern virtual reality maybe replacing the traditional identity of users with a digital version of themselves. At the centre of this problem is the technology itself, not being exposed to Indigenous concepts during the construction of any virtual reality IT artefact? This study applies a multidisciplinary approach to tackle a key issue for virtual reality by locating a version of Indigenous identity of self within a digital setting during the construction of the virtual reality artefact.
Discussion and Research of Aviation Data Link Based on ADS

With the rapid development of the global aviation industry, air traffic flow has increased dramatically. In order to ensure the safe and orderly operation of air traffic, higher requirements are put forward for air traffic control and surveillance technology. This paper introduces ADS system which is widely used at present, briefly analyses its research status, communication channels and networking protocols used at the present stage, gives the typical application scenarios of the system, analyses the data integrity and security problems that restrict the development of ADS-B, and finally forecasts the future development direction of ADS-B, including ATN, FANS and BDS. Positioning and satellite-based ADS-B system.
VIRTUAL CAPSTONE WORKSPACE

- Virtual reality aims at immersing a user in a virtual environment. Dedicated virtual reality technologies of human–computer interaction enables linking the user and a virtual environment in capturing the user's motion. Our primary purpose is to improve communication between the students, especially the team members in STEM schools in Egypt. The application supports students in the capstone project for each grade. It is supported by tools to make a simulation for the project. Also, it is supported by a virtual reality headset. As we mentioned, VR is used in many fields, and it isolates the person from the surrounded environment altogether. VR is used instead of Anesthesia because of its effect in isolating humans from the surrounded environment. That will increase communication and concentration between the team members and make them feel that they are in an actual meeting. Every person will have an avatar in the application represent him. This avatar will translate every member's motion in the meeting by the sensor in the VR headset. A mic supports the VR headset. Every team will have a specific room, this room is where they can make all meetings, and all the work, achievements, and updates of the group will save in this room. Also, the application work as a director for the work
Smart Air Fertigation (SAF) without using Fertilizers through Air Irrigation for Sustainable Agriculture

In India approximately 80% of the total water is consumed for agriculture. India does not spend any money in conserving water consumed in agriculture. In the current scenario humans are concerned about potable water, more and more insufficient in relation to the increase of the population and as effect of pollution. Crops are watered using various irrigational methods with the ground water. Water consumption in irrigation also depends upon the crop which is cultivated. Sugarcane and rice cultivation consumes nearly 60% of the irrigation water. Further to ensure a bumper produce, farmers are encouraged to use chemical fertilizers. Many of these fertilizers give a promising crop produce but the after effects of consumption of such chemically treated produce leads to harmful effect on human health. Nevertheless, quite a many farmers are now focusing on Organic method of farming wherein chemical fertilizers are totally avoided. However, the produce under this method does not give a bumper crop produce. To tackle the problem of water waste during irrigation process, techniques like drip irrigation, dry farming, irrigation scheduling, and Smart irrigation using Information Technology are applied to ensure least wastage of irrigated water at the same time providing desirable conditions for bumper crop produce. To provide an alternate solution for reducing water wastage in irrigation and providing natural fertilizers to the crops, this research paper suggests the use of Smart Air Fertigation (SAF) without using fertilizers with the aid of Air Irrigation method. Further, by using various IT tools and sensors it is possible to provide Smart Air Fertigation system which will also help reduce labor and will be less time consuming.
FEATURES OF IMAGE COMPREHENSION THROUGH SYMBOLS

In modern conditions of personal development, aimed at self-learning, self-development, speech-thinking activity plays a special role as a component of the characteristics of a successful person.The main goal of literary education is to study the texts of works of art, to understand literature as an artistic reality, to develop on this basis the spiritual world of a person, his worldview, and to foster the need for systematic reading as a necessary part of continuous spiritual and moral improvement of the individual, and to develop his intellectual and emotional-volitional spheres.As an artistic phenomenon, the Word lived in the minds of people as an independent image that embodies the centuries-old experience of the people, since at all times its philosophical idea of life was understood and perceived as a great social mission.The article deals with the problem of understanding the image through symbols on the example Of V. Rasputin's story "Women's conversation".In the disclosure of the main idea of the text, the meaning of semantic groups is discussed.The article presents a situation in which a student, independently comprehending new information through reflection, reflects on the preservation of the spiritual and moral values of his people.