Reviewerly/exHarmony huggingface dataset:
Diagnosis Penyakit Tanaman Karet dengan Metode Fuzzy Mamdani

Like most plantation plants in general, rubber can be attacked by various diseases originating from fungi, pests, animals and even cancer cells. For that we need a method capable of diagnosing rubber disease. In previous research related to the diagnosis of plant diseases, among others, using the Dempster Shafer method, the Certainty factor method and forward chaining. This study developed an analysis of the results of the diagnosis of rubber plant disease using the Mamdany Fuzzy method. The choice of this method departs from research on fuzzy mamdany which states that the fuzzy mamdany method is able to resemble the intuitive way the human brain works. It is hoped that with this method, the diagnosis of rubber plant disease can help farmers detect symptoms earlier so that the productivity of rubber plantation products can be achieved. increased. This study used rubber plant disease data from the Jambi Provincial Plantation Office in Jambi City. From the results of calculations carried out in diagnosing rubber plant disease, as many as 161 rubber plant object data were equipped with 33 symptom identities and a diagnosis from plantation data, then tested 60 rubber plant data without a diagnostic label, we obtained an accuracy value of 81.28%. Likewise, testing by randomizing training data with Cross Validation obtained close results.
MAD-VAE: Manifold Awareness Defense Variational Autoencoder

Although deep generative models such as Defense-GAN and Defense-VAE have made significant progress in terms of adversarial defenses of image classification neural networks, several methods have been found to circumvent these defenses. Based on Defense-VAE, in our research we introduce several methods to improve the robustness of defense models. The methods introduced in this paper are straight forward yet show promise over the vanilla Defense-VAE. With extensive experiments on MNIST data set, we have demonstrated the effectiveness of our algorithms against different attacks. Our experiments also include attacks on the latent space of the defensive model. We also discuss the applicability of existing adversarial latent space attacks as they may have a significant flaw.
Vehicle Washing (Doorsmeer) Wastewater Treatment using Flotation Electroagulation Combination

Vehicle washing business services in the current era are growing in numbers, both simple and those that have used technology. As a consequence, the production of wastewater more and more, which if not controlled will have an impact on environmental pollution. Conventional wastewater treatment technology is sometimes less effective because it requires chemicals in the process and requires relatively longer, so the need for land to build a treatment unit is relatively wider. To provide an alternative treatment process that is simpler and has good results and does not require large tracts of land, it is necessary to develop electro-coagulation technology combined with flotation. Electrocoagulation is the process of clumping and precipitation of fine particles contained in water by using electrical energy. This study was to determine the ability of electrocoagulation-flotation technology in decreasing the parameters of COD, detergents, and oil in motor vehicle washing wastewater based on the type of electrodes used at 12 and 24-volt electric voltages with contact times of 30 and 60 minutes. This study is an experimental study with a "pre and post-test group design" design. The results showed that the combination of electrocoagulation-flotation at 24-volt voltage and 60 minutes contact time with aluminum electrodes could reduce COD 82.7%, oil 46.5%, and detergent 68.9%. Whereas with iron electrodes the COD decreased by 81.1%, oil by 43.7% and detergents by 65.1%. With an average reduction, aluminum electrodes are better than iron electrodes. Although aluminum and iron electrodes are better, statistically the two are not different (p &lt;0.05), this shows that there is no difference in the ability to decrease test parameters. Other than that, the longer the contact time, the greater the decrease in test parameters. The conclusion is that the electrocoagulation-flotation combination method can be used to reduce the COD, oil/fat and detergent parameters in motor vehicle washing wastewater. The results of this study are expected to be applied to motor vehicle washing activities by utilizing iron waste as an electrode.
Traditional Educational Tools In Modern School Education System

The intensity of the implementation of information and communication technologies (hereinafter -ICT) in the educational process in schools abroad falls on the last half a century.In schools of our country, technologies have been used for last 30-35 years.The emergence of modern teaching aids based on computer processing of information, their widespread distribution and application in the field of education from preschool to postgraduate, allow obtaining comparatively higher results than those provided by the traditional educational tools.Information technologies, the characteristics of which are being improved more and more, and the degree of their implementation has covered almost all areas of modern human activity, have changed the views on the idea and approaches to learning and education as a process.The questions arewhen and how to apply ICT, how to analyze the results, what place and role is given to a teacher, if ICT are used?What is a modern textbook?What vocabulary should be used in different regions?The benefits of using ICTs are beyond doubt.At the same time, their use carries unforeseen risks and above all others is a child health.The paper provides some practical examples describing ICT implementation, the opinions of some well-known experts in this field, including recognized world authorities.The paper material can be considered as an object for discussion by specialists in the field of education that aims to develop a unified policy regulating the ICT use for education purposes.
Electronic Aid Design of Fruits Image Classification for Visually Impaired People

Deep learning has attained immense achievement in many fields, such as computer vision and usual speech processing in recent years. It has a burly erudition capability and can create enhanced use of datasets for characteristic extraction when compared to traditional machine learning systems. The researchers start doing research work in this deep learning due to its popularity. In this manuscript, we chiefly initiate several superior neural networks of deep learning and their functions. Deep learning technologies are becoming the major approaches for natural signal and information processing, like image classification, speech recognition. Deep learning is a technology inspired by the functioning of human brain. Convolutional neural networks (CNN) become very popular for image classification in deep learning. CNN’s perform better than human subjects on many of the image classification datasets. In this project, a deep learning convolutional network based on Tensorflow is deployed using python for binary image classification.
Assessments on the Writing of Senior English for China Students’ Book 1 Based on Target Needs Analysis

Teaching material is a vital resource of language input, while the evaluation of teaching material is of great importance for both teachers and students.  This paper aims at evaluating of the New Senior English for China Students’ Book 1. Due to personal limited effort this paper just focuses on the writing part. The author will use the target needs analysis of Hutchinson & Waters to serve as analysis base, and will take the characteristics of New Senior English for China Students’ Book 1 as the subjective analysis and the requirements of teaching syllabus as objective analysis. At last, the paper tries to present some personal opinions based on the results of evaluation.
Digital Transformation in Financial Field

In this study, digital transformation applications in the business world and in finance field are discussed in detail. The current and potential effects of digitalization on a wide spectrum from operational finance to portfolio management are examined. Advantages and disadvantages of digital transformation have been examined in detail and a general evaluation has been made about the ongoing process. One of the most important milestones of digitalization in the financial world is cryptocurrency. It is totally based on blockchain technology that eliminates public authority intervention and intermediaries by establishing peer to peer (P2P) transactions via the decentralized platform. In particular, the possible effects of increasing digitalization efforts on the financial environment after Covid-19 are interpreted.
Application of Big Data Analysis in the Study of the Inheritance of Cultural Confidence in the Teaching of Ancient Literature in Chinese Department

Abstract China has a long history and culture for 5000 years. Ancient literature is an important carrier of traditional culture, but influenced by the concept of professional education talents, some colleges and universities have some problems in cultivating cultural self-confidence in ancient literature teaching. Ancient culture is the inexhaustible motive force for the development of the Chinese nation, and it is also the demand of the times. With the development of society, traditional culture plays a very important role in national development. By combining the teaching of ancient literature with the inheritance of traditional culture, we can not only effectively promote the teaching reform of ancient literature, but also build up the cultural self-confidence of the Chinese nation. This paper first analyses the importance of cultivating students’ cultural self-confidence. Then it combines big data technology to analyze the reasons for the lack of cultural self-confidence among college students. Finally, some suggestions are put forward.
Supplementary Materials Sections 1 and 2 from Integration of new information in memory: new insights from a complementary learning systems perspective

Provides theoretical and empirical investigations of the process of learning adjustments to known dimensions of knowledge in deep linear networks, and presents results on the dynamics of learning a new item in a pretrained linear autoassociative network.
Formally Verifying the Robustness of Machine Learning Models : A Comparative Study

Machine learning models have become increasingly popular in recent years, and not without reason. They enable software to become more powerful, and with less human involvement. As a consequence how ...
ANTISOCIAL DISORDER OF JOKER CHARACTER IN THE DARK KNIGHT MOVIE DIRECTED BY CHRISTOPHER NOLAN

The objective of this research is to know what is antisocial disorder that was conducted by watching the dark knight movie. In this paper, the writers used descriptive qualitative method by visited the library and browsed of internet to get the references and data that related to the topic. For data collection, all information was collected by librarian research to obtain the theories of literary work and all support information that related to the objective of the research. The next stage was analyzing of The Dark Knight movie by watching it several times . The result of this research indicated that; (1) there are seven symptopms of antisocial disorder that occurred in joker character such as failure to conform to social norm, deceitfulness, impulsivity, irritability and aggressiveness, reckless disregard for safety of self or others, consistent irresponsibility, and lack of remorse (2) antisocial disorder in joker character developed by childhood trauma and abuse which is caused by his father’s treatments (3) there are three moral messages that can learned from the dark knight movie such as humanity, teamwork, and consideration.
Building calibrated face-identification ability test with Item Response Theory

Accurate estimates of face-identification ability are crucial in applied forensic settings. Current face-identification datasets are often large and uncalibrated, making them sub-optimal for pre- and post-training evaluations. To optimize efficient and accurate performance assessments, small sets of well-labelled test items are needed. However, item-wise measures cannot be applied to the common forensic task of identity matching in image pairs, because items are either “matched” or “non-matched” identities. Therefore, in this case, an item response confounds item accuracy and response bias. Here, our goal was to construct flexible, well-calibrated subsets of face-identification items using Item Response Theory (IRT) applied to image triads. These triads were composed of two images of one identity and one image of a different identity; the task was to select the “different” identity. Participants (n=77) were tested on the full item pool of 224 face-image triads. Responses were analyzed using the IRT one-parameter model (Rasch model; Rasch, 1960). This approach provides measurements of subject ability and item difficulty on the same scale. Results of the model demonstrate the probability of endorsing a correct response given an item’s difficulty and a subject’s ability. Using these results, we constructed subsets of items that varied in item difficulty. To test the quality of these item subsets, we used responses to these subsets to estimate participants’ ability and predict accuracy for larger subsets of novel items. Leave-one-out cross validation results showed that we can predict both people’s accuracy on novel items and their individual responses. These calibrated face-identification tests can be used to develop face-identification tests with better flexibility, reliability, and time-efficiency.
Fine-grained Information Status Classification Using Discourse Context-Aware BERT

Previous work on bridging anaphora recognition (Hou et al., 2013a) casts the problem as a subtask of learning fine-grained information status (IS). However, these systems heavily depend on many hand-crafted linguistic features. In this paper, we propose a simple discourse context-aware BERT model for fine-grained IS classification. On the ISNotes corpus (Markert et al., 2012), our model achieves new state-of-the-art performance on fine-grained IS classification, obtaining a 4.8 absolute overall accuracy improvement compared to Hou et al. (2013a). More importantly, we also show an improvement of 10.5 F1 points for bridging anaphora recognition without using any complex hand-crafted semantic features designed for capturing the bridging phenomenon. We further analyze the trained model and find that the most attended signals for each IS category correspond well to linguistic notions of information status.
“LET YOU AND HIM FIGHT” GAME: PSYCHOLOGICAL ANALYSIS

The article examines Eric Berne's "Let you and him fight" game exemplified by its scenarios in the works of famous writers.Eric Berne is absolutely right in his claim that "LYAHF is the basis of much of the world's literature, both good and bad".This direction of research highlighted by Eric Berne's remark is marginalized in the theory of Psychology.The article tries to show the assets of this fruitful approach.All Eric Berne's examples deal with the traditional triangle, communication within which being directed and dominated by a female manipulator.Every development in the game, both verbal and non-verbal, is understood by Eric Berne to be invariably generated by a woman.This peculiarity seems to be a logical basis for Berne's treating the psychology of moves behind the cognitive scenario as "essentially feminine", though the woman does not merely initiate the game -she enjoys the fight provoked by her.Theoretically, "Let you and him fight" game does not exclude the possibility for the Manipulator's role to be played by a man.However, in Berne's examples only the woman is held responsible for pulling strings.For this reason it would be more accurate to apply a different formula to the cognitive scenario Eric Berne is really interested in: "Cherchez la femme".The cognitive scenario of the "Cherchez la femme" game is seen here in its French ménage: the original meaning is much more sexist than its literal translation ("look for the woman").The French meaning implies that no matter what the problem may be, a woman is at the root of each problem.Following in the wake of psychological case studies provided by L.S. Vygotsky, Karl Leonhard, Paul Watzlawick and others the article illustrates the "Let you and him fight" game by the cognitive scenarios taken from A. J. Cronin's "The Green Years", Guy de Maupassant's "Bel-Ami", A. Kuprin's "The Duel", I. Turgenev's "First Love", I. Shaw's "The Top of the Hill", J. London's "Martin Eden" and "White Fang".The presence of a woman in the cognitive frame shows her in negative colors: she is the trouble-maker.This arrangement of roles -she as the manipulator, he as the victim of manipulation -proves utter untenability of Eric Berne's statement "the psychology (behind the game) is essentially feminine": it is masculine and sexist.The examples of the "Cherchez la femme" game were not meant to cover all the possible developments in the scenario: Kurt Vonnegut was right suggesting that the "story lines" (the combinations of moves underlying the games) will not be exhausted in the next 10 000 years.
Usability Evaluation Aplikasi Berbasis Website dengan Menggunakan Metode Importance Performance Analysis

The Ministry of Environment and Forestry provides an appeal to waste banks to use online systems in managing waste bank activities. The online system referred to is the online waste management system through the banksampah.id account. However, the level of activity of garbage banks in using the online system is relatively low (36.46%). Besides, in 2019, the Bandung City DLH has used banksampah.id as an application in evaluating the performance of waste banks. Therefore, this study was conducted aiming to evaluate the level of usability of banksampah.id so that it can be known aspects of banksampah.id that need to be improved. Evaluation of usability level is carried out using the Importance Performance Analysis (IPA) method. The usability evaluation results show that there are 7 usability attributes in the "Concentrate Here" category, 10 usability attributes in the "Keep Up The Good Work" category, 8 usability attributes in the "Low Priority" category and 9 usability attributes in the "Possible Overkill" category. Improvements to usability banksampah.id focus on 7 attributes categorized as "Concentrate Here" namely (1) availability of procedures for the use of various applications, (2) procedures for using applications that have been available easily understood by users, (3) completeness of customer profile, (4) availability of up-to-date customer data, (5) speed in data processing, (6) availability of communication features between Garbage Banks, and (7) availability of communication features between Garbage Banks and collectors.
A Novel Barcode Generation and Verification System for Fraud Prevention

Barcode technology is an automatic identification system that provides an effective means of collecting data to facilitate the automatic scanning of information. It is typically used in the sale of goods in supermarkets to make the checkout as fast as possible. However, several security issues have come to light, most notably barcode substitution fraud. This paper therefore proposes the use of a digital watermarking technique to create a barcode that cannot be regenerated. To read this barcode, a novel authentication system was introduced that used a neural network. The proposed barcode and its system were implemented and evaluated through experimental studies of 5000 barcode samples. The results were extremely promising as they showed that the proposed barcode can successfully be identified as legitimate or fake.
PPKTP Applications: Quantum Encryption

Abstract Quantum encryption is also known as quantum cryptography, or quantum key distribution (QKD). It is an application in the field of communications, whereby quantum mechanics is used to encrypt messages on single photons, so that unintended recipients cannot read the messages. Quantum encryption allows two parties to establish private encryption keys in an extremely secure manner.
Employment Performance-Based Contract As A Tool To Manage University'S Development Of Transformations

The paper presents the results of conceptual development of the model of performance-based contract of employment as a functional tool to manage the strategic development of a university in the context of transformations.The obtained results are based on the adaptation of the methodology of the balanced system of indicators and key performance indicators to the specificity of the development management systems of educational organizations; decomposition of priority objectives and tasks of educational organizations in terminology of the classical management theory and modern concepts of management of educational organizations, as well as on the basis of definition of target functional blocks of performancebased contract of employment, which is aimed at fostering the resource potential of educational organizations.As a result of the study it can be concluded that the functionality of the performance-based employment contract used to manage the university's strategic development in the context of transformations is determined by the quality of scientifically sound methodological development of a balanced system of targets and the corresponding key performance indicators.
Gourds: a sliding-block puzzle with turning

We propose a new kind of sliding-block puzzle, called Gourds, where the objective is to rearrange 1 x 2 pieces on a hexagonal grid board of 2n + 1 cells with n pieces, using sliding, turning and pivoting moves. This puzzle has a single empty cell on a board and forms a natural extension of the 15-puzzle to include rotational moves. We analyze the puzzle and completely characterize the cases when the puzzle can always be solved. We also study the complexity of determining whether a given set of colored pieces can be placed on a colored hexagonal grid board with matching colors. We show this problem is NP-complete for arbitrarily many colors, but solvable in randomized polynomial time if the number of colors is a fixed constant.
Empirical Comparison of Deep Learning Networks on Backbone Method of Human Pose Estimation

Accurate estimation of human pose relies on backbone method in which its role is to extract feature map. Up to dated, the method of backbone feature extraction is conducted by the plain convolutional neural networks named by CNN and the residual neural networks named by Resnet, both of which have various architectures and performances. The CNN family network such as VGG which is well-known as a multiple stacked hidden layers architecture of deep learning methods, is base and simple while Resnet which is a bottleneck layers architecture yields fewer parameters and outperform. They have achieved inspired results as a backbone network in human pose estimation. However, they were used then followed by different pose estimation networks named by pose parsing module. Therefore, in this paper, we present a comparison between the plain CNN family network (VGG) and bottleneck network (Resnet) as a backbone method in the same pose parsing module. We investigate their performances such as number of parameters, loss score, precision and recall. We experiment them in the bottom-up method of human pose estimation system by adapted the pose parsing module of openpose. Our experimental results show that the backbone method using VGG network outperforms the Resent network with fewer parameter, lower loss score and higher accuracy of precision and recall.