Reviewerly/exHarmony huggingface dataset:
SURVEY : CRYPTOGRAPHY OPTIMIZATION ALGORITHMS

With the advent of e-commerce, it has become extremely essential to tackle the sensitive issues of affording data security, especially in the ever-blooming open network environment of the modern era. The encrypting technologies of the time-honored cryptography are generally employed to shelter data safety extensively. The term ‘cryptography’ refers to the process of safeguarding the secret data against access by unscrupulous persons in scenarios where it is humanly impossible to furnish physical protection. It deals with the methods which convert the data between intelligible and unintelligible forms by encryption/decryption functions with the management of key(s). Nowadays cryptographic key management issues that arise due to the distributed nature of IT resources, as well the distributed nature of their control. Recently these issues are solved by optimization algorithms utilized in the cryptographic algorithms. The purpose of this paper is to give a survey of optimal cryptographic keys that can be developed with the help of optimization algorithms, and to address their merits to the real-worldscenarios.AbstractWith the advent of e-commerce, it has become extremely essential to tackle the sensitive issues of affording data security, especially in the ever-blooming open network environment of the modern era. The encrypting technologies of the time-honored cryptography are generally employed to shelter data safety extensively. The term ‘cryptography’ refers to the process of safeguarding the secret data against access by unscrupulous persons in scenarios where it is humanly impossible to furnish physical protection. It deals with the methods which convert the data between intelligible and unintelligible forms by encryption/decryption functions with the management of key(s). Nowadays cryptographic key management issues that arise due to the distributed nature of IT resources, as well the distributed nature of their control. Recently these issues are solved by optimization algorithms utilized in the cryptographic algorithms. The purpose of this paper is to give a survey of optimal cryptographic keys that can be developed with the help of optimization algorithms, and to address their merits to the real-worldscenarios. Keywords:Cryptography; Encryption; Decryption; Key Management; Optimization algorithm;
Ablation Path Saliency

We consider the saliency problem for black-box classification. In image classification, this means highlighting the part of the image that is most relevant for the current decision. We cast the saliency problem as finding an optimal ablation path between two images. An ablation path consists of a sequence of ever smaller masks, joining the current image to a reference image in another decision region. The optimal path will stay as long as possible in the current decision region. This approach extends the ablation tests in [Sturmfels et al. (2020)]. The gradient of the corresponding objective function is closely related to the integrated gradient method [Sundararajan et al. (2017)]. In the saturated case (when the classifier outputs a binary value) our method would reduce to the meaningful perturbation approach [Fong & Vedaldi (2017)], since crossing the decision boundary as late as possible would then be equivalent to finding the smallest possible mask lying on the decision boundary. Our interpretation provides geometric understanding of existing saliency methods, and suggests a novel approach based on ablation path optimisation.
Perancangan Aplikasi Kompresi File Teks dengan Menerapkan Algoritma Sequitur

Text files or text data is one component that is very important for each person as well as for each agency in the form of printed or multi-media. Where files or data can store some important things in it, the greater the size of a file or data the greater the storage media that will be needed. By looking at the compression requirements of the file or data, there is a need for compression or compression on the data, so that it can reduce usage in the external storage media space, minimize bandwidth requirements, speed up the data transmission process, and compress the ratio higher than the data results before compression. The compression process is done to solve problems in storage media, where the algorithm for compression uses the sequitur algorithm.
Diversity Augmented Conditional Generative Adversarial Network for Enhanced Multimodal Image-to-Image Translation

Conditional generative adversarial networks (cGANs) play an important role in multimodal image-to-image translation. We propose Diversity Augmented conditional Generative Adversarial Network (DivAugGAN), a highly effective solution to further resolve the mode collapse problem and enhance the diversity for the generated images. DivAugGAN functions as a regularizer to maximize the distinction of the generating samples when different noise vectors are injected. We also exert extra constraint on the generator to ensure the relative variation consistency in the translation process. This guarantees that the changing scale of the generated images in the image space is coherent to the difference of the injected noise vectors in the latent space. It also reduces the chances to bring about unexpected mode override and mode fusion issues. Experimental results on both two-domain and multi-domain multimodal image-to-image translation tasks demonstrate its effectiveness. DivAugGAN leads to consistent diversity augmentations and visual quality improvements for the developed models. We also achieves state-of-the-art performances on multiple datasets in terms of widely used quantitative evaluation metrics. DivAugGAN can be easily integrated into any objectives in conditional generative models as a regularizer for diversity augmentations and quality enhancements without any additional computation overheads compromise The source code and pre-trained models of our method is available at https://github.com/anomymous-gan/DivAugGAN.
Driver Dizziness Detection Using Python

Accident is an incident that happensunexpectedly, for some mistake done, but if themistake is from our side, we can prevent it. Sincethe majority of accidents are caused because ofdistraction or the drowsiness of the driver, peopletaking a long drive often suffer from lack of sleepand are prone to an accident. To prevent suchaccidents we propose a system which alerts thedriver whenever he feels drowsy.We will build a system which takes thefacial features as input from a live recordingthrough a webcam, or camera and then processeach frame from the video, to detect the location ofeye and by using mathematical calculations,analysing whether the eye location points arechanging i.e. The eyelids are closing continuouslyor not, using the modules of Python i.e., Tkinter,Scipy, imutils, dlib, CV2, PyGame and alert thedriver with an audio alert, which makes him stayawake.
The Utilization of School Library to Grow a Literation Culture of Elementary School Students

This study aims to analyze the use of the school library in order to foster the literacy culture of elementary school students in Purwokerto. This type of research is descriptive qualitative. Respondents in this study were school principals, teachers and librarians. Data were collected through observation and semi-structured interviews. In this study, qualitative data analysis from Miles was used which consisted of three streams of activity that occurred simultaneously, which included data reduction, data presentation, and drawing conclusions or verification. The results showed that the use of the library in order to instill a culture of literacy was done in a way; 1) book corner, 2) library visit and 3) reading before class. The problems that are experienced are; 1) inadequate library space, 2) absence of librarian, 3) poorly maintained and limited library collections, 4) library control card is still manual, 5) students' lack of reading interest. The library as a learning resource which is expected to foster interest in reading for students must be well managed and organized, there must be an evaluation regarding the utilization and effectiveness of the library function. So that the central role of the library is increasingly functioning optimally in order to foster student interest in reading and literacy culture.
Traffic state monitoring by close coupling logic with OBU and cloud applications

Traffic state monitoring is important for improving and maintaining smooth traffic. Various factors that affect traffic can be considered as states. These factors to be detected can be not only conventional traffic congestion but also the volume of pedestrians at stops or pedestrian flooding into roads and blocking vehicles&apos; paths and bicycles weaving through traffic. The conventional approach to sensing is to deploy roadside units such as loop coil, sonic sensor, or camera sensor. The new approach is based on a vehicle probe system gathering mainly location and speed data. However, a more sophisticated approach is an image-recognition-based probe system. This approach can directly sense traffic states. Various sensing targets can be detected by developing image-processing logic specific to targets in collaboration with cloud applications. In short, the image-recognition-based onboard unit&apos;s (OBU&apos;s) probe system has flexibility for further possibilities.
OKUL YÖNETİCİLERİNİN KARAR ALMA YAKLAŞIMLARI: VERİYE DAYALI KARAR ALMAYA GEÇİŞ

In this study, it was aimed to examine how school administrators solve the problems they encounter and how they decide on macro or micro-level issues with a data-based approach according to the opinions of teachers. The research is a qualitative study in the phenomenology pattern. The study group was determined according to the appropriate sampling from purposeful sampling techniques. In this context, 19 teachers from different provinces of Turkey and different levels of education were included in the study group. In the research, a semi-structured interview form developed by the researchers was used as a data collection tool, and remote interviews in a virtual environment mostly provided the interviews. Research data were analyzed by using content analysis method. When the average depth levels of the codes revealed in the study were examined, it was seen that school administrators did not go beyond the law or regulation and the limits drawn by the legislator according to the perceptions of teachers. Findings revealed that data-based decision making was minimal, and there was a tendency towards more collaborative, experience-based, or listening stakeholders in data-based decision-making. It is thought that there needs to be a change of perspective in decision making and effective use of school-based data systems to be established in Turkey with digital transformation, and that school employees should gain competence in data use.
Changes in University Education and the Roles of Liberal Education : From the Perspectives of 「Performance and Productivity Improvement Plans for Higher Education in the United States」

Currently, Korean universities face the problem of ‘productivity’ along with problems of role acceptance as educational institutions that form the stage that follows secondary education. They no longer exist separately from secondary education. The United States, which first sensed such changes in social demands, announced a report titled 「Performance and Productivity Improvement Plans for Higher Education in the United States」, jointly written by the ‘National Center for Higher Policies and Higher Education’ and the ‘National Center of Higher Education Management Systems’ in 2007. This report handled contents that are slightly distant from the essence of education as it tried to identify higher education focused on ‘efficiency’ and ‘productivity’ problems and it presents university evaluation and incentive systems based upon the standards of academic achievement, new student recruitment rates, and student retention rates. The contents of this report are similar to the methods of Korea, which have managed the ‘productivity’ of higher education after 2010 through methods in which educational budgets are paid differentially according to university evaluations and it seems that a lot of the report reflects the university competency evaluations of Korea. When considerations are made that the educational plans of current Korean universities are established upon university evaluations of the Ministry of Education, an observation of this report’s contents will give a look into, not only the directions of higher education in the United States, but also directions for the higher education of Korea.<BR> This article attempts to search for implications by making focused observations of ‘connections of secondary and higher education’ and ‘universities as lifelong education institutes’, which are presented as university ‘productivity’ enhancement methods in the 「Performance and Productivity Improvement Plans for Higher Education in the United States」 report. Also, it explored the meanings and roles of higher education in ‘educational pipelines’ designed as secondary-higher-lifelong learning.
ANALISA LAPORAN KERJA KARYAWAN MENGGUNAKAN BALSAMIQ MOCKUP BERBASIS WEB PADA CV. ESOTECHNO KOTA JAMBI

Achievement Level of an employee work report on CV. Esotechno, which is one of the entrepreneurs engaged in Information Technology, is still developing complex systems and is far from efficient. One of them is the employee work report on the CV. Esotechno, which is now computerized and well integrated, is deemed inefficient, so it still has many shortcomings in dealing with problems when the work reports are used. In this study, the authors used the Object Oriented Analysis Design (OOAD) approach and the Prototype model. To design a new system and so that the design of this new system can overcome weaknesses in the old system, it is necessary to know how the input, process, and output are in the running system. The tools used are Data Flow Diagram Modeling (DFD) and Balsamiq mockups in building website designs. The results of this system analysis are expected to facilitate employee work reports at CV. Esotechno to process employee work reports and provide information about employee work reports in detail.
Task-Driven Image-to-Image Translation for Automotive Applications.

Image-to-image translation attempts at mapping an image from a given domain into a different domain. In this paper we introduce a novel image-to-image translation paradigm, where the translation itself is performed by a system of generative adversarial networks (GANs), guided by a set of pretrained networks, called task networks. The underlying hypothesis is that these task networks can guide the translation process of the GAN generator to focus on those aspects of the image which matter the most for the tasks in question. Moreover, our work is motivated by a real-life situation, created by the need to adapt existing, duly trained networks to work on images acquired with a different sensor than the one used to acquire the images used to train the networks. In order to optimize the image domain translation from the new sensor to the old one, we use the output loss of the trained neural networks to guide the training process of the image-to-image translation engine, thus forcing it to create images which improve the performances of the trained, guiding networks. Experimental results presented therein confirm the usefulness of our approach for an automotive application within the context of driver monitoring systems. More specifically we show that guiding the learning of the image-to-image translation module with the loss of a fixed neural network trained to estimate the driver eyelid opening, improves the performances of the latter when being fed with images output by the translation module.
Relocating the Antarctic Core Collection: The Story of a Large-Scale Data Rescue Initiative for an Historic Collection of Geologic Samples

The story the Antarctic Core Collection’s (ACC) transition from Florida State University (FSU) to Oregon State University (OSU) is one of the largest-scale data rescue efforts in recent history. The ACC is the world’s largest collection of seafloor sediment samples from the Southern Ocean. The collection was officially established in 1963 as the US Antarctic Program took shape. For the next fifty years, the collection grew to represent the scientific discoveries of over one-hundred and twenty research cruises and expeditions around Antarctica. FSU hosted the irreplaceable collection at its Antarctic Research Facility, an iconic lab in the center of campus. In 2016, the university chose not to renew its contract for supporting the facility. Recognizing the value and potential of the collection, the National Science Foundation began a search for another university to host these important samples and enable future research. In 2017, OSU’s Marine and Geology Repository (OSU-MGR) initiated a plan to relocate this historic collection of over eighteen kilometers of core samples from Tallahassee, FL to Corvallis, OR. The project began by planning and constructing a state-of-the-art facility with temperature-controlled space to house the next fifty years of coring expeditions to the Southern Oceans and beyond. In the summer of 2018, the ACC was carefully packaged, digitally inventoried, and shipped to OSU. In this process, the OSU-MGR staff have worked to improve metadata records to build an effective modern inventory of the ACC using new digital collection management techniques, including QR coded labels and scanners. These metadata are managed on tablets with the OSU-MGR App and indexed in an Elasticsearch cluster to streamline the repository’s workflows and to display summary statistics. Current and future curation projects will comply with FAIR data principles, with the goal of making all OSU-MGR collections and associated datasets more easily discoverable online.
Fisheye Images Correction Based on Different Angle of Views

A fisheye lens is a camera lens with a short focal length and a large field of view, which can shoot scenes with a viewing angle close to or even more than 180 degrees at one time. Due to its short focal length, large field of view, and constraints of optical principles, the images acquired by the fisheye camera have serious distortions and require geometric correction processing. In this paper, we use the method of transferring the optical center of the fisheye image to obtain the fisheye image after geometric correction in the left, middle and right perspectives, and stitch the three images together to achieve the fisheye image correction.
Multi-font Printed Amharic Character Image Recognition: Deep Learning Techniques

In this paper, we propose a technique to recognize multi-font printed Amharic character images using deep convolutional neural network (DCNN) which is one of the recent techniques adopted from the deep learning community. Experiments were done on 86,715 Amharic character images with different level of degradation and multiple font types. The proposed method has fewer pre-processing steps and outperforms the standard approach used in classical machine learning techniques. We systematically evaluated the performance of the recognition model and achieved 96.02% of character recognition accuracy.
Automatic Scoring System for CET-4 Compositions Based on Seq2Seq+Bi-LSTM Model

In National College English Test Band 4(CET-4), manual marking mechanism for each composition involves hard work and difficulty to guarantee the accuracy and objectivity of the scoring. It is imperative to adopt an objective, accurate and efficient automatic composition marking system. With the rapid development of artificial intelligence and deep learning in natural language processing, based on the combination of Seq2Seq and Bi-LSTM, this paper proposed a new composition scoring model for National College English Test Band 4. This model combines Bi-LSTM unit and CNN structure to realize an automatic text proof reading model. The comparison of the composition before and after proof reading will generate the resulting scores. The experimental results show that the results of this model have the highest agreement with manual scoring system compared with other classic models.
Искусствоведение в условиях цифровизации: проблемы организации научных конференций онлайн

In the article current problems of the organization of scientific conferences online are considered. Distance education showed a certain efficiency and small economic cost intensity of similar actions (videoconferences). It is not necessary to waste time and money for the road, settlement of participants, to rent rooms, etc. For the management of educational institutions and teachers of participants of conferences the problem of the admission of classes or replacement of the colleagues who left at a conference to other cities is removed. The author considers that the remote format of conferences will promote democratization and optimization of scientific communication, equalizing of domestic and foreign participants and also will give the chance of participation in them by age (physically handicapped) scientist. Also the format online will allow to do conferences more specialized and local on subject that will enhance sociability (connectivizm) of participants. At the same time a format online demands special concentration from speakers and moderators for maintenance of interest of listeners in content of reports. It is also necessary to increase technical equipment of the equipment and computer literacy of users, to improve skills of the presentation. It is possible that special courses within FPK for teachers in new working conditions will be required.
Digital Image Analysis of Immunohistochemistry CD103 Using QuPath Software in Acral Melanoma

Background: Nowadays, pathology services are more developed for quantitative diagnostic evaluation. The quantitative diagnostic evaluation requires detailed accuracy and can be done using digital image analysis (DIA). Assessment of the CD103 in acral melanoma needs to be done quantitatively. A visual microscopy evaluation of CD103 has difficulties in counting CD103 positive lymphocytes. These difficulties are due to the expression of CD103, which is very little, whereas the field of view of the tumor mass is considered quite exhaustive when viewed under a microscope. The evaluation of CD103 could be done digitally with the DIA technique to overcome these difficulties. The DIA technique is carried out automatically by counting the lymphocytes that express CD103 with bioimage analysis software. QuPath is one of the bioimage analysis software, has characteristics of cross-platform, intended for bioimage analysis and digital pathology. This study aims to compare the CD103 count by visual microscopy evaluation and DIA in acral melanoma.Methods: This study was a cross-sectional study. CD103 immunostained slides of 40 cases of acral melanoma were eyeballing assessed by two pathologists and automated digital images analyzed by one pathologist using QuPath.Results: Wilcoxon signed ranks test showed no significant difference between the visual microscopy evaluation and DIA of CD103 count (p = 0,580).Conclusions: Digital image analysis using QuPath can be used to count the CD103 automatically.