Reviewerly/exHarmony huggingface dataset:
Generative modeling of histology tissue reduces human annotation effort for segmentation model development

Segmentation of histology tissue whole side images is an important step for tissue analysis. Given enough annotated training data, modern neural networks are capable of accurate reproducible segmentation; however, the annotation of training datasets is time consuming. Techniques such as human-in-the-loop annotation attempt to reduce this annotation burden, but still require vast initial annotation. Semi-supervised learning—a technique which leverages both labeled and unlabeled data to learn features—has shown promise for easing the burden of annotation. Towards this goal, we employ a recently published semi-supervised method, datasetGAN, for the segmentation of glomeruli from renal biopsy images. We compare the performance of models trained using datasetGAN and traditional annotation and show that datasetGAN significantly reduces the amount of annotation required to develop a highly performing segmentation model. We also explore the usefulness of datasetGAN for transfer learning and find that this method greatly enhances the performance when a limited number of whole slide images are used for training.
Quintet margin loss for an improved knowledge distillation in histopathology image analysis

Digital and computational pathology tools often suffer from a lack of relevant data. Although more and more data centers publicize the datasets, high-quality ground truth annotations may not be available in a timely manner. Herein, we propose a knowledge distillation framework that can utilize a teacher network that is already trained on a relatively larger amount of data and achieve accurate and robust performance on histopathology images by a student network. For an effective and efficient knowledge distillation, we introduce a quintet margin loss that pushes the student network not only to mimic the knowledge representation of the teacher network but also to outperform the teacher network on a target domain. We systematically evaluated the proposed approach. The results show that the proposed approach outperforms other competing models with and without different types of knowledge distillation methods.
Deep learning combined with ball scale transform for circulating tumor cell enumeration in digital pathology

Circulating Tumor Cells, or CTCs, are cancerous cells that shed from a primary tumor and intravasate into the bloodstream. This type of screening, otherwise known as biopsy screening, is effective at determining the early stages of cancer and discussing treatment. Expert cytopathologists have been required to look at these images to screen for cancer. Anything between the numbers of hundreds to thousands of images must be gone through. At a heavy time cost and a basis of work effort, we thus proposed an idea using a U-Net to screen for these CTCs and enumerate them in a more efficient and time-costing method. The Ball-scale transform technique, a filter that allows us to determine the maximum sphericality in a thresholded homogeneity, was introduced into this field of digital pathology alongside our proposed novel deep learning-based (UNet) CTC detection and enumeration approach. We collected 466 images for CTC detection and another 198 images with 323 CTCs for testing CTC enumeration. We investigated two ways to use the Ball-scale image: using B-scale images in the input channel of deep learning and using B-scale images in the output layer by providing high-level information (size and shape) encoded in the B-scale image itself to do the enumeration. We also tested deep learning-based CTC detection by using different labels. Results show that our method is much better than those which utilize thresholding with a missing rate comparison of 0.04 to 0.30. Meanwhile, our method is certainly comparable and competitive with the results in recent publications and may facilitate other types of research.
A Comparative Study of On-Campus and Off-Campus Internet Facilities

This study aimed to compare the lived experiences of the graduate school students in accessing internet facilities inside and outside the university campus. Qualitative method using phenomenology as a design was utilized. The internet services in two campuses were compared. Aspects of comparison between the two lenses started with the on-campus followed by the off-campus were presented in terms of; internet connection: dawdling versus fast; Wi-Fi connection: difficult to access versus accessible; network: low versus hassle-free; accessibility: limited versus limitless; adequacy of facility units: discomfort versus comfortable; expert’s and mentor’s guidance: available versus difficult to avail; research environment: safe versus unsafe; power supply: sustainable versus susceptible to interruption. These results implied an urgency of the university to look into the problem that the students are facing in accessing internet facilities for their research activities.
Library Management System

A Library Management System (LMS) is a software application that is designed to manage the operations of a library. The LMS is used to automate a wide range of library tasks, including cataloging, circulation, acquisitions, and serials management. The Library Management System abstract describes the key features and functions of the LMS, which typically include the following: Cataloging: The LMS enables librarians to catalog and classify books, media, and other library resources. This includes adding new items to the library's collection, updating item information, and deleting items that are no longer in use. Circulation: The LMS tracks the circulation of library materials, including lending and returning items, managing reservations and requests, and tracking overdue materials. Serials Management: The LMS manages the subscriptions to periodicals, including tracking new issues, renewals, and cancellations. Key Word: Automate and Library the management of individual student details Book details, Faculty details.
Non-Conventional Spelling in Informal, Colloquial Arabic Writing on Facebook

Arabic has a standard form used in formal situations and print materials and a non-standard, colloquial form used in daily conversation. Each Arab country has its own dialect. Before social media, educated Arabs used to use Standard Arabic when they communicated in writing. But with the advent of social media, people started to use non-standard Arabic, i.e., their own dialects, when they communicate in writing on social media. A corpus of spelling errors in Arabic was collected from Facebooks posts and analyzed to find out the types of errors made, the strategies Arab Facebook spellers use, why educated Arabs make those errors and their effect on decoding ability and communication. It was found that Facebook users completely ignore Standard Arabic spelling rules. They spell words the way they pronounce them in their local dialects. They delete vowels, substitute long vowels by short ones and vice versa and confuse consonants with the same sound. Some graphemes are no longer used. They connect several words together as one word, ignoring the pauses between them. The same word or phrase, in the same dialect, is spelled differently by different users. Sometimes it is difficult to understand what some users are trying to say. It seems that the non-standard Arabic spelling used on Facebook is undergoing a simplification process. Users do not seem to recognize word boundaries, cannot connect phonemes with the graphemes they represent and cannot distinguish vowel length in their spoken dialect. A detailed classification of spelling anomalies, the faulty spelling strategies used and reasons for those spelling weaknesses detected are reported.
Course Management System

A course management system is a set of tools that enables the instructor to create online course content and post on the Web. It enables the college or university to provide individual user account to each student. All the user accounts (instructors and students) are password protected. So, the database can be termed as secured. In Course Management System, only administrative section is allowed to create the account, but students and instructor can register with application. After creating the account, the user can view his/her detail by using SQL query. In the existing system, we can store all the record manually that require large manpower &amp; place to store all the records but it does require only a database connectivity to store all the data. It can handle all details about a student. The details include college details, subject details, student personnel details, academic details, exam details. In this we can implement a facility that a faculty can be able to post Document such as word files and PDF in this and student those who have enrolled can able to access all of those documentations. Key Word: User, database, application registry, password authentication, academic details.
A object detection method based on attention mechanism and reinforcement learning

Object detection technology is now widely used in areas such as unmanned vehicles, public safety, and intelligent robotics. However, the complexity and variability of object detection contexts and the lack of ability of deep learning-based object detection techniques to store sequences of information and make decisions result in performance that is not adequate for real-world scenarios. As the main components of the two-stage algorithm, feature extraction and region selection play a key role in the classification and location of target detection. Due to the superposition of network layers in deep learning, the receptive field is increased, while the correlation between feature maps and the decline of network gradient over a long distance is ignored. The different sizes of feature maps make the network objects generated by regions less dependent. In this paper, a new target detection model is proposed, and the existing problems are studied and solved from the residual feature extraction network, the tree-like deep reinforcement learning area generation network, and the fine-tuning network, respectively. Finally, the experimental and visual results verify the superiority of the overall performance of the algorithm model.
Perancangan Infrastruktur Jaringan Komputer dalam Mendukung Pembelajaran dan Standar Prasarana Fasilitas Internet di SDN 138 Geger Kalong Girang

This research started with the need the implementation of Computer-Based National Assessment (ANBK) at SD Negeri 138 Geger Kalong Girang with the condition that computer and internet network infrastructure was not available, but the implementation of ANBK had to be carried out independently. The purpose of designing this computer network infrastructure is in addition to implementing ANBK well as supporting the learning process for teachers and students for the availability of adequate internet access which can be used for learning purposes. Design of computer network infrastructure to support learning and internet facility infrastructure standards in schools is applied using the PPDIOO concept, namely, Prepare, Plan, Design, Implement, Operate and Optimize. The results of this study indicate that the computer network infrastructure planning is as expected. The ANBK implementation running normally, the results of the bandwidth usage test as a whole running normally and the internet could be accessed very well in the school environment.
A Simple Method to Calculate Positions in Pose Tracking to Verify Work Procedures

Although manufacturing processes are becoming increasingly automated, many factories still rely on manual operations. In such facilities, there is a strong need to automatically detect human errors by checking whether specified procedures are being followed. For this purpose, studies have been conducted on utilizing deep neural network (DNN) based three-dimensional (3D) human pose-tracking methods to examine work procedures. However, most of these techniques require a high-end computer equipped with a graphics processing unit (GPU). On the other hand, in this study, we adopt MediaPipe Pose, a lightweight pose estimation network provided by Google, to perform pose tracking on a low-end personal computer (PC) to enable such systems to be deployed in small factories. However, MediaPipe Pose cannot track the location of a human body because it estimates poses in a coordinate system with the waist as the origin (that is, in a root‑relative coordinate system). Therefore, in this study, we developed a method to obtain the absolute coordinates of the root with a simple calculation. The results of an experimental evaluation show that the computational load of the proposed approach is negligible, and the repeatability of the estimation sufficed to evaluate a given operator's work on a predetermined working path. Therefore, the proposed methods enables work procedures to be checked using MediaPipe Pose on a low-end PC.
Analisis Korelasi Kecerdasan Emosional dengan Kepercayaan Diri Pada Mahasiswa

ABSTRACT Emotional intelligence affects the self-confidence of each individual. Everyone has different self-confidence and emotional intelligence. An individual who feels confident will have high emotional intelligence. Knowing the relationship between emotional intelligence and self-confidence in students. This research is quantitative with a cross-sectional research design. The population in this study was 118 undergraduate nursing students in semesters VI and VIII. This sampling technique is stratified random sampling and statistical tests using the Pearson Test. Emotional intelligence is mostly in the high category (74.7%), with self-confidence in the good category (100%). The results of the Pearson test show that the significance value is p=0.000&lt;0.05, and the correlation coefficient is 0.413. There is a relationship between emotional intelligence and self-confidence in students of the Nursing Study Program (S1). Keywords: Emotional Intelligence, Self Confidence ABSTRAK Kecerdasan emosional mempengaruhi kepercayaan diri setiap individu. Setiap orang memiliki kepercayaan diri dan kecerdasan emosional yang berbeda-beda. Sebagai individu yang merasa penuh percaya diri akan memiliki kecerdasan emosonal yang tinggi. Tujuan untuk mengetahui hubungan kecerdasan emosional dengan kepercayaan diri pada mahasiswa. Penelitan ini bersifat kuantitatif dengan rancangan peneltian cross sectional. Populasi dalam penelitian ini adalah mahasiswa prodi keperawatan S1 semester VI dan VIII yang berjumlah 118 orang. Teknik pengambilan sampel ini adalah stratified random sampling dan uji statistik menggunakan Uji Pearson. Kecerdasan Emosional sebagian besar dalam kategori tinggi (74,7,%), dengan Kepercayaan Diri dalam kategori baik (100 %). Hasil uji Pearson menujukkan bahwa nilai signifikansi p=0,000&lt;0,05, correlation coefisient 0,413. Ada hubungan antara kecerdasan emosional dengan kepercayaan diri pada mahasiswa prodi keperawatan (S1). Kata Kunci : Kecerdasan Emosional, Kepercayaan Diri
USING TELEGRAM TO IMPROVE ENGLISH PRONUNCIATION OF HIGH SCHOOL STUDENTS

This study investigated the use of social networking site Telegram in improving students’ pronunciation of eleventh grade students in one of senior high school in Tangerang, Indonesia. A total of 24 students were taken as the sample in the current study. Non-randomized one class pretest-posttest design was used in the study. Using quasi experimental research one-class pretest-posttest design, the students in the experimental class completed the process through Telegram. The tests and questionnaires were used to collect the data. In order to test whether there was an improvement within the class, the hypothesis was tested using the t-test and obtaining the gain scores. The result showed that the pronunciation of students was improved. They were interested in learning through the media, wanted to learn new things, and active throughout the learning process. Based on the percentages, students’ posttest showed that the pronunciation of students was improved after using social networking site Telegram. Moreover, this research also found that the evaluation of learning model was good, the students’ learning motivation was very good, and made a good class atmosphere in the experimental class throughout the learning process by using social networking site Telegram.
PENINGKATAN PROSES DAN HASIL BELAJAR MATEMATIKA MENGGUNAKAN MODEL PROBLEM BASED LEARNING KELAS V SEKOLAH DASAR NEGERI 116/II EMPELU KECAMATAN TANAH SEPENGGAL

ABSTRACT&#x0D; The problem in this study is the learning process and student learning outcomes in grade V SDN 116/II Empelu are still low, this is evidenced by the results of preliminary observations made by researchers of 20 students only 35% who scored in the completed criteria. The cause is students in the passive class, have not used a varied learning model, and have not used concrete in learning.&#x0D; The researcher's aim is to improve the process and learning outcomes of the mathematics through the Application of the Problem Based Learning model. The research method used in this research is classroom action research. This class action research consists of two cycles, each cycle consisting of four stages of activity namely planning, implementing, observing and reflecting.&#x0D; Data collection with observation sheets for student learning process and tests for student learning outcomes. The results showed that the use of the TGT type of Cooperative Learning Model can increase student process and learning outcomes. This&#x0D; can be seen from the increase in student learning process, in the first cycle reached 55% categorized quite active and in the second cycle increased to 85%.
The Impact of Economic Institutions as a Fundamental Factor of Economic Growth in South Africa

South Africa is a country that is open to trade, and this makes the study significant as economic institutions work better in such countries. The underperformance of South Africa's economy stems from the difficulties in achieving institutional change where state-owned companies such as Sasol benefit the most in the oil, gas and chemical industries. This is because SoEs are the main suppliers of natural gas sourced from Mozambique. This implies that Sasol’s customers are the price takers, meaning that whatever the price of gas set by Sasol, it will be difficult for Sasol’s customers to oppose it since there is no competition within the market. Entrepreneurs in developing countries with poor economic institutions struggle to grow their businesses due to property insecurity, barriers to market entry, and biased contract offering. The study employed the ARDL to determine the long-run relationship between economic institutions and economic growth, whilst the pairwise Granger causality test was used to determine the direction of the established cointegration. The study used annual time series data for the variables included in the model sourced from World Development Indicators (WDI), the global economy, and Transparency International for the period 1995 to 2020. The estimated ARDL model included the following variables; Gross Domestic Product Per Capita (GDPPC), Property Rights Index (PRI), Corruption Perception Index (CPI), Government Expenditure Per Capita (GOVEXPP), and Trade openness (TO). The study’s findings indicate that PRI as a proxy of economic institutions promotes economic growth in South Africa. The results further show that all other variables also promote growth except CPI. The pairwise Granger Causality test indicates that there is a direct causality between economic institutions and economic growth. The economic policy implication in this regard is that South Africa's government should invest the majority of its public expenditure on human capital to improve the skills of unemployed youth, potentially increasing their employability. Consequently, better economic institutions could be implemented or created.
Cybercrime and The Social Media

In this research, each of the electronic crimes will be analyzed in an attempt to reduce the dangerous effects that they entail, and to clarify their true meaning. A quantitative study was conducted based on a questionnaire, Survey on Cybercrime via Social Media which contains ten questions, with each other question having a measurable scale that was applied to the participants. The survey takes into account the different methods of defrauding innocent victims as well as the number of hours people spend on the internet and the different social media they use. The results showed that 70% of people spend more than 2 hours online and 60% belong to more than 5 social media platforms and 90% of them tried to cheat in a year and 60% of people have lost their money. Cybercrime was noted to be the most common. Mobile phone fraud represented 60% compared to inheritance fraud which represented 10% and fictitious tax refund of 40%. It was also found through the research that 73% of people did not inform the authorities, as 88% prefer not to report even when they suspected that they have been deceived, and 76% of them have seen and heard advertisements about cybercrime. It was also found that 62% are not interested in victims exposed to cybercrime. These results was enough for countries to enact laws and legislation that limit these crimes and intensify the punishment for the perpetrators, as well as educating societies about their danger to avoid them.
ESTIMATES OF EPICENTRAL DISTANCE AND MAGNITUDE FROM ONE SEISMIC STATION

Rapid assessment of epicentral distance and magnitude has fundamental importance for earthquake early detection and warning systems. We present a new method for estimating the epicentral distance using one seismic record in short time. To quantify the difference in the observed seismic signals, we introduced a simple function of the form Bt•exp(-At) and determined A and B from the point of view of the least squares method, fitting this function to the initial part of the signal envelope. We found that log B is inversely proportional to log Δ , where Δ represents the epicentral distance. This ratio is valid regardless of the magnitude of the earthquake. Using this ratio, we can estimate approximate epicentral distance almost immediately after the arrival of the P-wave. Then we can easily estimate the magnitude from the maximum amplitude observed during a given short time interval after the arrival of the P-wave, using the empirical magnitude-amplitude ratio, which includes the epicentral distance as a parameter.
On Interval-valued Anti Fuzzy Prime bi-ideal of Semigroup

In this paper, we introduce the notions of interval-valued anti fuzzy prime (resp. strongly prime and semiprime) bi-ideals of semigroup. By using these ideas, we characterize those semigroup for which each interval anti-fuzzy bi-ideal is semiprime and strongly prime.&#x0D; &#x0D; Introduction: The theory of fuzzy sets proposed by Zadeh [6], in his classic paper of 1965, deal with the applications of fuzzy technology in information processing. Mordeson, Malik and Kuroki gave a systematic exposition fuzzy semigroups in [2], where one can find theoretical results on fuzzy semigroups. Shabir and Kanwal [5], introduced the concept of prime bi-ideal, strongly prime bi-ideals and semiprime bi-ideal of a semigroup and studied those semigroups.&#x0D; &#x0D; In this paper we introduced the concept of interval valued anti fuzzy prime, strongly prime and semiprime bi-ideal of semigroups and give characterization of semigroups in terms of these notions we characterize those semigroups for which each interval-valued anti fuzzy bi-ideal is semiprime and strongly irreducible.