Reviewerly/exHarmony huggingface dataset:
SISTEM INFOMASI ADMINISTARSI KEUNGAN SISWA BERBASIS WEB DI SEKOLAH MAHABODHI VIDYA

The school payment system at the Mahabodhi Vidya School is still done manually both in term of transactions and data recap. Thus slowing down the payment process, recording and recap of payments. This causes the processes related to school payments have not run optimally. The overcome this problem, the authors propose to design and build applications that suport databases systems so that school payment processing is more effective and efficient. The application of  financial administration information systems at the Mahabodhi Vidya School was designed using the waterfall development method with several stages, namely requirements analysis, system design, writing program code, testing programs, and maintaining programs. This application is designed using UML model visualization and developed using the PHP dan MySql programming language as a database. The conclusion of this study is that the Financial Statement Informatin System at Mahabodhi Vidya School has been completed. This systems has a feature so that payments can be made by installments and payment data can be seen in detail. Keywords: system information, payment of SPP, database, waterfall
Teaching Students About Zone Theory Using the “Army of Electrons” Method

The article under discussion presents the results of the research on the development of new pedagogical technologies for teaching pupils and students of vocational technical schools. The method of teaching conditioned by the theory of similarity is proposed, the essence and order of the lesson is described and the results of the experiments are analyzed. The authors conclude that it is advisable to study the experience of teaching technical specialists in the country’s universities, to cover teaching methods of those specialists extensively and to analyze the results of various teaching methods.
Generative-Discriminative Probabilistic Model for Brain Lesion Segmentation

Brain has been the focus of recent research, most of which is dealing with glioma. Gliomas are the most frequent primary brain which originate from glial cells and grow by infiltrating the surrounding tissue. Tumor structures show a significant amount of variation in size, shape and localization precluding the use of related mathematical priors. Some structures such as necrotic or cystic region or the solid cannot easily be associated with local channel-specific intensity modifications, but are rather identified based on the wider spatial context and their relation with other compartments. This project proposes a joint generative and discriminative probabilistic model for segmentation of brain lesions. Generative models consider prior information about the structure of the observed data and exploit such information to estimate latent structure from new data. Moreover, it assumes that all voxels of a tissue class have about the same image intensity which is modeled through a Gaussian distribution. The segmentation method, whose parameters can be estimated very efficiently through the Expectation Maximization (EM) procedure, treats image intensities as nuisance parameters which makes it robust in the presence of the characteristic variability of the intensity distribution of MR images the discriminative model extensions maps the output of the generative model to arbitrary label with semantic and biological meaning, such as tumor core or fluid-filled structure, but without a one-to-one correspondence to the hypo-or hyper-intense lesion area identified by the generative model. Experimental results shows that the generative model that has been designed for lesions generative well to stroke images, and the extended discriminativediscriminative model to be one of the top ranking methods in glioma patient scans set.
Models of Information seeking behaviour : An overview

: Information can be defined as a collection of facts organized in such a way that they have additional value beyond the value of the facts themselves. In simple word “information” can be defined as a processed data. Information, in the most restricted technical sense; it is an ordered sequence of symbols that can be interpreted as a message. This study aims to propose an overview of the various models and to find out how models are related to each other. The article specifically aims to some models studies information seeking behaviour (e.g. Wilson 1981, Krikelas 1983; Ellis 1989; Kuhlthau 1991) sense making( Dervin ), non linear (Foster) and information searching on the web (Choo, 1999, 2000) that focus on these concepts for greater clarity and an understanding of their relationship and application in Library and information science research. Discuss above models and conclusion.
Desafíos de la aplicación del Bitcoin.

Bitcoin is a virtual currency that is now known as a decentralized payment system that can transfer money through the computer without having to go to a bank or institution. Bitcoin now becomes a popular method of payment in exchange for goods and services. This has been and continues to be used by some people for illegal activities and to promote crimes. Being decentralized means that it is issued without a central administration authority. To achieve a precise business with Bitcoin, it is necessary to eliminate current barriers and prepare for the acceptance of new technologies in digital currency. This document discusses the challenges of Bitcoin as a virtual currency and we do not intend to cover all aspects of Bitcoin.
Indoor Environment Assistance Navigation System Using Deep Convolutional Neural Networks

This chapter deals with the development of a smart and intelligent deep learning-based indoor landmark identification system. This work is proposed especially to improve the autonomy and the life quality for blind and visually impaired persons (VIP). The proposed indoor object recognition system highly contributes to build an indoor smart environment for this category of persons and facilitate for them more in life. Indoor object classification presents a key technology for indoor navigation assistance systems. Recognizing indoor objects widely helps VIP in their indoor navigation in order to fully participate in the daily life. A deep convolutional neural network (DCNN) is presented to perform indoor object classification. Indoor object detection from real-world images and videos is a highly recommended area of research in the field of artificial intelligence. In this work, we propose a robust technique for indoor object recognition based on deep CNN model. Experimental results performed on natural images with natural illumination shows that our approach achieves good performances with an accuracy of 99.9% for indoor object classification.
THE IMPACT OF STRATEGIC INTELLIGENCE ON STRATEGIC FLEXIBILITY IN BANK AL-ETIHAD IN JORDAN

This study aimed to demonstrate the effect of strategic intelligence on the strategic flexibility in the Jordan Al Etihad Bank. The study population included all employees working in the Jordan Al Etihad Bank. The study sample consisted of all employees from top and middle administrations of The Jordan Al Etihad Bank, who were randomly selected totaling (88)individuals. To achieve the objectives of the study, the quantitative (descriptive and analytical) method was used through many statistical methods, most notablythemultiple regression analysis. The study reached a number of results, the most prominent of which is the presence of a statistically significant effect of strategic intelligence (foresight, strategic vision, intuition) at the level of statistical significance (α ≤ 0.05) on the strategic flexibility in Jordan Al Etihad Bank There is a significant impact of strategic intelligence (strategic vision, intuition) at the level of statistical significance (α ≤ 0.05) on the flexibility of human capital in the Al Etihad Bank of Jordan. And the presence of a statistically significant effect of strategic intelligence (foresight, strategic vision, intuition) at the level of statistical significance (α ≤ 0.05) on the flexibility in technology in the Al Etihad Bank of Jordan. Also, the presence of a statistically significant effect of strategic intelligence (strategic vision, intuition) at the level of statistical significance (α ≤ 0.05) on the competitive flexibility in Jordan Al Etihad Bank. There is a significant impact of strategic intelligence (foresight, strategic vision) at the level of statistical significance (α ≤ 0.05) on the flexibility of service provision in the Al Etihad Bankof Jordan. According to the results, the study recommended, the study concluded that the interest in strategic intelligence by the Jordan Al Etihad Bank is necessary to take advantage of its implications in achieving integration at all administrative levels. Moreover, the need to pay attention to strategic flexibility in order to encourage the optimal use of resources within the Jordan Al Etihad Bank, which enhances the morale of workers and customers, achieving their satisfaction and improving efficiency.
Effectiveness of Using E-resources in Academic Libraries: A Study

This article focuses on the various facets of e-resources and the effectiveness of using e-resources in academic libraries. Digital technology has made application of the stored intellect faster, quicker and more relaxed. This gathered knowledge over the ages has to be used for forthcoming research; social change and overall growth. Electronic assets addresses storage problems and monitor knowledge flow thus digitized print and electronic sources of knowledge are becoming increasingly important to the academic institutes. The introduction of technology has led the libraries introducing new component to their catalog, e-resources are the most popular among them. This paper provides the need of e-resources, benefits of eresources, effectiveness of e-resources use, types of e-resources and its services, also offers a summary of these assets and explains some benefits and drawbacks
DELA Corpus - A Document-Level Corpus Annotated with Context-Related Issues

Recently, the Machine Translation (MT) community has become more interested in document-level evaluation especially in light of reactions to claims of human parity, since examining the quality at the level of the document rather than at the sentence level allows for the assessment of suprasentential context, providing a more reliable evaluation. This paper presents a document-level corpus annotated in English with context-aware issues that arise when translating from English into Brazilian Portuguese, namely ellipsis, gender, lexical ambiguity, number, reference, and terminology, with six different domains. The corpus can be used as a challenge test set for evaluation and as a training/testing corpus for MT as well as for deep linguistic analysis of context issues. To the best of our knowledge, this is the first corpus of its kind.
Depth-based removal of thermal reflection with the light-field theory

Thermal imaging is a useful imaging technique in many scenarios. It can capture the temperature distribution of scenes in the dark and see through sparse smoke and dust. However, some surfaces such as steel and glass with high reflectivity lead to a reflection problem in thermal imaging, while heavy mist and gases lead to the occlusion problem. We proposed an efficient algorithm to solve the occlusion problem in our earlier work. The reflection in thermal images causes errors in detection and temperature measurement. Therefore, the precise model and efficient algorithms to solve this problem are in high demand. In this paper, we mainly model the reflection problem in thermal imaging and propose an algorithm to deal with it. In our experiments, a thermal camera array is built to capture the thermal light-field images. We first separate a part of the reflection pixels from thermal images based on the depth information. After that, the thermal reflection is removed by optimizing a designed cost function. The experiment results show that our reflection removal method can separate the thermal reflection with high precision, retain the objects in the scene, and get better performance than existing methods.
PEMERIKSAAN DINI GOLONGAN DARAH PADA SISWA SMKN 2 BANGKALAN

Blood is one of the most important components in the body, considering its function as a means of transportation. Lack of blood in the body can spur a number of diseases starting from anemia, hypotension, heart attacks, and several other diseases. Law number 36 of 2009 concerning health states that a health service facility is a tool and / or place used to carry out promotional, preventive, curative and rehabilitative health service efforts which are carried out by the government, local government and / or the community (Kemenkes RI , 2015). Based on a survey through interviews with students of SMKN 2 Bangkalan that had been conducted, it was found that many students at SMKN 2 Bangkalan still did not know their blood type.The method used to carry out community service is by collecting data on the number of students at SMKN 2 Bangkalan, then conducting interviews with students about their blood group and then making a time contract with the students. The activity was continued with a blood group examination for santri santri who did not know their blood type.The participants of the activity were 37 students at SMKN 2 Bangkalan who took part in the blood group examination. While participating in the activities, the students were very enthusiastic about the activities being carried out. The results of the activities most of the gender of the students were male as many as 21 people (56.8%). And, most of the students' blood groups were O as many as 13 people (35.2%)
Modified prediction partitioning algorithm for Gaussian inverse Wishart probability hypothesis density filter using measurement labeling method

The Gaussian inverse Wishart probability hypothesis density filter is a promising approach for tracking multiple extended targets. However, if targets are closely spaced and performing maneuvers, the performance of a Gaussian inverse Wishart probability hypothesis density filter will decline. The reason for this is that the measurement partitioning approaches fail to provide accurate partitions, which influences the component updating process directly. This paper presents a modified prediction partitioning algorithm for the Gaussian inverse Wishart probability hypothesis density filter in order to solve the partitioning problem of closely spaced targets. The inaccuracy of the target prediction information occurred by target maneuvers leads to the above problem, thus a modified prediction partitioning algorithm will label the components and corresponding measurements to improve the prediction accuracy. Simulation results show that the use of modified prediction partitioning can improve the performance of a Gaussian inverse Wishart probability hypothesis density filter by providing more accurate partition results when targets are closely spaced and performing maneuvers.
EFFECT OF IMAGE RESOLUTION IN DETECTING CIRCULAR TRAFFIC SIGNS USING HOUGH CIRCLE TRANSFORM

The traffic signs have several shapes, one of which is circular. Hough Circle Transform is a function that detects a circular in an image based on the gradient. This function also needs some parameters, one of which is the image resolution. The traffic signs in the frame will have varying sizes. If after cropping, it will produce images with varying resolution sizes. Therefore, resizing image resolution is required so that all image data have the exact image resolution. Image resolutions to be tested are 25 × 25 pixels, 50 × 50 pixels, 75 × 75 pixels, 100 × 100 pixels, 125 × 125 pixels, 150 × 150 pixels, 175 × 175 pixels, and 200 × 200 pixels. This research proves that the image resolution in shape detection using Hough Circle Transform affects the shape detection accuracy. The data used are No Stopping signs and No Parking signs for True detection test, whereas Other Dangers signs and Pedestrian Crossing signs for False detection test. The highest accuracy was generated at a resolution of 75 × 75 pixels.
A systematic literature review on emotional text for Malay corpus

The existence of corpus, especially online corpus, fabricates benefits not only to the linguistic area, but also benefits to others, for instance to academicians especially researchers. Research trends on corpus shows that study is done to upgrade the performance and functionality, for example toward the emotional corpus. These emotional corpora been used widely not only by researcher in linguistic but also by psychologist, the legal firm and also by stakeholder by referring to the emotional annotation in the corpus to understand about their client emotion and behavior. However, the study on the Malay emotional corpus is still left behind where currently there is no available study or paper been published regarding on Malay emotional corpus and also no development method yet been study on Malay Emotional Corpus. Therefore, this paper aims to focus on applying the systematic literature review (SLR) regarding the emotional corpus. The objective of this study is to understand and identify the available technique and methods that have been used in developing the emotional corpus based on text. The methodology used in this paper is by applying a systematic approach known as the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA). The articles that have been reviewed through SLR are obtained from the Scopus online database. Articles are selected based on the time range between years 2011 until years 2020.These articles are reviewed and analyzed through four PRISMA approaches which is the Identification, Screening, Eligibility and Included approach. After going through the process, this paper managed to get 35 articles for the purpose of SLR for detail reviewed. Initiating SLR in this study, several components or areas are identified for the reviewing purpose. This paper review regarding the method applied, the domain or application, modality, name of the corpus involved, the label of corpus (language) and then what is the measurement based they used in the methodology in their study. At the end of the study, this paper significantly brought a summary in helping to understand the available method and technique used for emotion recognition based on text for the purpose of emotional Corpus development hence identifying the most applicable method used. This bring as a source based for the future works in developing Malay emotional Corpus.
Content analysis of select university library websites of Delhi: An Indian scenario during Covid-19 pandemic

The digitization of information has brought a new concept altogether and has marked the beginning of 'information era ’which nonetheless left libraries behind to reach their users in the present digital world through their websites as a linkage without physical presence. At this time of pandemic websites are serving at its most for online teaching and learning as well. Considering the importance of information resources available on the library websites the study is conducted to analyse the contents of University of Delhi, Jawaharlal Nehru University, Indira Gandhi National Open University, Jamia Millia Islamia, Guru Gobind Singh Indraprastha University, Ambedkar University Delhi, Indraprastha Institute of Information Technology and National Law University by preparing checklist based on general information, collection, facilities, services, best practices and application of web 2.0 technologies provided on the websites. Analysis reveals that all the libraries under study are providing substantial resources and information on their websites which includes e-books, e-journals, e-databases, link to institutional repositories, consortia resources and digital libraries, open access resources as well as password access resources for their registered users, study also provides suggestive measures. Further, it is anticipated that the present study will be useful not only for said universities but for other universities also to update their library websites to serve their patrons during this pandemic and thereafter.
Cyberbullying via Social Media: Case Studies in Malaysia

Cyberbullying is generally defined as employing electronic communication to bully or harass a person on the Internet, particularly on the social media sites. Advances in technology and better Internet access have enabled cyberbullies to find their way into the IT world. This paper presents two cyberbullying cases through the social media platforms in Malaysia involving suicide attempts. It highlights and presents a detailed discussion on the investigation and analysis process that reveals frightful and alarming facts on how social media are manipulated negatively which can lead to death. This paper also shares a learning module entitled the National Cybersecurity Awareness Module, an initiative by CyberSecurity Malaysia in ensuring safer Internet usage in Malaysia. The module consists of six topics including cyberbullying and is aimed at providing awareness and exposure to the need for safe conduct while using the social media. The suggestions and recommendations offered are towards ensuring a secure, resilient, and sustainable social media.
Blockchain Technology for Healthcare

The research methodology is based on the preferred reporting items for systematic review & meta-analysis guidelines & a systematic mapping study process, in which a well-designed search protocol is used to search 4 scientific databases to identify, extract &analyze all relevant publications. These shows that a number of studies have proposed different use, cases for the application of blockchain in healthcare; However there is lack of adequate prototype implementations & studies to characterize the effectiveness of these proposed use cases & further highlights the state-of-the-art in the development of blockchain applications for healthcare.
Segmentation Free FragNet and GRRNN for Writer-Identification in Cursive Handwriting

Writer identification is a method in which a handwritten sample is assigned to the corresponding author of that sample. Since handwriting is a behavioral biometric application like the signature, writer identification will also confirm the authenticity of the document. Major applications of the writer identification process come in forensics, banking, and paleography which is a study of historical books and writings. Different writers have their own style of handwriting which has different characteristics, so they require different handling. Due to this difference, it is difficult to identify the author of the manuscript. Slant, curvature, orientations, etc may vary. The writer identification task predicts the writer by identifying various features involved in the handwrit- ten sample. The proposed method identifies the writer of a handwritten sample by combining both local and global features. This is accomplished by a combination of FragNet and Global Recurrent Neural Network. FragNet captures local features and to make them spatially correct, global features are captured from local features by Global Residual Recurrent Neural Network. A segmentation-free method is used so that writers of cursive handwriting can also be identified.