Reviewerly/exHarmony huggingface dataset:
Bounding the edge cover of a hypergraph

Let $H=(V,E)$ be a hypergraph. Let $C\subseteq E$, then $C$ is an {\it edge cover}, or a {\it set cover}, if $\cup_{e\in C} \{v|v\in e\}=V$. A subset of vertices $X$ is {\it independent} in $H,$ if no two vertices in $X$ are in any edge. Let $c(H)$ and $α(H)$ denote the cardinalities of a smallest edge cover and largest independent set in $H$, respectively. We show that $c(H)\le {\hat m}(h)c(H)$, where ${\hat m}(H)$ is a parameter called the {\it mighty degeneracy} of $H$. Furthermore, we show that the inequality is tight and demonstrate the applications in domination theory.
Online, Digital or Distance? – Spread of Narratives in ICT-supported Education

Digitization and digitalization have transformed educational practices. The COVID-19 pandemic triggered a sudden change in the mode of the delivery of education and forced schools and universities to relocate education to digital platforms and revolutionize educational processes. The shift to online platforms brought terms like digital education/learning, online education/learning, blended and hybrid education/learning to the forefront, while traditional terms like eLearning, distance learning and mobile learning remain popular. This paper studies these terms and by backing the educational process redesign with ICT development and the time-space-group dimensions, it highlights the viral nature of the narratives of the terms.
A Simple Framework for 3D Lensless Imaging with Programmable Masks

Lensless cameras provide a framework to build thin imaging systems by replacing the lens in a conventional camera with an amplitude or phase mask near the sensor. Existing methods for lensless imaging can recover the depth and intensity of the scene, but they require solving computationally-expensive inverse problems. Furthermore, existing methods struggle to recover dense scenes with large depth variations. In this paper, we propose a lensless imaging system that captures a small number of measurements using different patterns on a programmable mask. In this context, we make three contributions. First, we present a fast recovery algorithm to recover textures on a fixed number of depth planes in the scene. Second, we consider the mask design problem, for programmable lensless cameras, and provide a design template for optimizing the mask patterns with the goal of improving depth estimation. Third, we use a refinement network as a post-processing step to identify and remove artifacts in the reconstruction. These modifications are evaluated extensively with experimental results on a lensless camera prototype to showcase the performance benefits of the optimized masks and recovery algorithms over the state of the art.
Transplant of Bone Marrow

A bone marrow transplant is a medical procedure that replaces your healthy cells in your bone marrow. Replacement cells can come from either your own body or a donor. A stem cell transplant or, more specifically, a hematopoietic stem cell transplant is another name for a bone marrow transplant. Transplantation can be used to treat cancers that affect the bone marrow, such as leukaemia, myeloma, and lymphoma, as well as other blood and immune system illnesses. Hematopoietic stem cells are found in bone marrow, which is a soft, spongy tissue in the body. Most bones include it in the core.
PENERAPAN METODE PIECES DALAM PENGEMBANGAN SISTEM INFORMASI MANAJEMEN TUGAS AKHIR (STUDI KASUS : PRODI SISTEM INFORMASI UNIYAP)

Information Systems study program is one of the study program at the Yapis University of Papua. One of its academic activities, the processing of the Final Project, has not utilized technology optimally which the collection of final project documents are still in print out. This becomes problems faced by study program administrations such as limited storage space, damage and loss of documents, besides that the costs incurred by students are quite large for printing documents. The purpose of this study is to create an integrated final project management system so that it can facilitate the work of all parties that are directly related to student final project management. The analysis method used in this research is the PIECES method, the UML method as the system design, the waterfall as the development method and the Black box testing method used as testing method. For the data collection process, this research uses interview, observation and literature study techniques. The result of this research is a Final Project Management Information System which aims to make easier for students in managing their Final Projects and for facilitate the study program in managing student Final Projects
Numerical Investigation of Geophysical Monitoring Based Upon Co2 Geological Storage and Leakage

In this study, we conducted numerical simulations on long-term behaviour of CO2 injected into a saline aquifer and resulting changes of geophysical data to investigate which combination of the methods and measurement locations will be effective for the CCS monitoring based upon hypothetical CO2 geological storage and leakage calculations. Predicted geophysical data include seismic reflection, microgravity, and seafloor surface displacement.Simulated results indicated that time-lapse 3D seismic reflection surveys will be a primarily reliable tool for the CCS monitoring, while other methods also can provide additional and/or complementary data which will be helpful for a decision of whether to conduct a close investigation using methods with more cost. These investigations will be useful for constructing efficient and effective monitoring network for the future planning of CCS project.
Review Paper on Introduction to Cyber Forensics

Abstract: Cyber Forensics is termed as scientific methods or applications in association with the judiciary or court of laws. The aim behind these methods is to unveil the digital evidence to be utilized in court for solving crime cases. This sort of technology wasn’t practiced before therefore most criminals tend to urge away with their criminal acts without valid proof to incriminate or prosecute them. During that time the oaths, confessions, testimonies from witnesses were the sole determining factors of evidence Crimes committed within electronic or digital domains, particularly within cyberspace, have become common. Criminals are using technology to commit their offenses and make new challenges for law enforcement agents, attorneys, judges, military, and security professionals. Digital forensics has become a vital instrument in identifying and solving computer-based and computerassisted crime. This paper provides a quick introduction to cyber forensics. During this paper we present a typical model for both Incident Response and Computer Forensics processes which mixes their advantages in an exceedingly flexible way: It allows for a management oriented approach in digital investigations while retaining the chance of a rigorous forensics investigation. Keywords: cyber forensics, digital forensic science, computer forensics, evidence, judicial system.
ExamGAN and Twin-ExamGAN for Exam Script Generation

Nowadays, the learning management system (LMS) has been widely used in different educational stages from primary to tertiary education for student administration, documentation, tracking, reporting, and delivery of educational courses, training programs, or learning and development programs. Towards effective learning outcome assessment, the exam script generation problem has attracted many attentions and been investigated recently. But the research in this field is still in its early stage. There are opportunities to further improve the quality of generated exam scripts in various aspects. In particular, two essential issues have been ignored largely by existing solutions. First, given a course, it is unknown yet how to generate an exam script which can result in a desirable distribution of student scores in a class (or across different classes). Second, while it is frequently encountered in practice, it is unknown so far how to generate a pair of high quality exam scripts which are equivalent in assessment (i.e., the student scores are comparable by taking either of them) but have significantly different sets of questions. To fill the gap, this paper proposes ExamGAN (Exam Script Generative Adversarial Network) to generate high quality exam scripts, and then extends ExamGAN to T-ExamGAN (Twin-ExamGAN) to generate a pair of high quality exam scripts. Based on extensive experiments on three benchmark datasets, it has verified the superiority of proposed solutions in various aspects against the state-of-the-art. Moreover, we have conducted a case study which demonstrated the effectiveness of proposed solution in a real teaching scenario.
LibGuides: Market Research: Get Help

Sources of information about the potential consumers, competitors and/or industry information.
Exploring Data Aggregation and Transformations to Generalize across Visual Domains

Computer vision has flourished in recent years thanks to Deep Learning advancements, fast and scalable hardware solutions and large availability of structured image data. Convolutional Neural Networks trained on supervised tasks with backpropagation learn to extract meaningful representations from raw pixels automatically, and surpass shallow methods in image understanding. Though convenient, data-driven feature learning is prone to dataset bias: a network learns its parameters from training signals alone, and will usually perform poorly if train and test distribution differ. To alleviate this problem, research on Domain Generalization (DG), Domain Adaptation (DA) and their variations is increasing. This thesis contributes to these research topics by presenting novel and effective ways to solve the dataset bias problem in its various settings. We propose new frameworks for Domain Generalization and Domain Adaptation which make use of feature aggregation strategies and visual transformations via data-augmentation and multi-task integration of self-supervision. We also design an algorithm that adapts an object detection model to any out of distribution sample at test time. With through experimentation, we show how our proposed solutions outperform competitive state-of-the-art approaches in established DG and DA benchmarks.
Students’ perceptions of learning English independently in e-learning

The aim of this study is to discover students’ independent learning in English during E-learning. The shift from face-to-face learning to E-learning during Covid-19 pandemic has made teaching strategy change. The students learn more independently based on the materials given in E-learning. Independent learning needs strategy, self-efficacy, motivation, and independent monitoring in learning. Hence, this study would like to explore more about independent learning in the university level. This study used survey method. The instrument in this study was questionnaire. The questionnaire was validated first. The result of this study was the students in the transformation process of independent learning in learning English during E-learning. Students' motivation, learning comprehension, strategy in learning independently, assignment, confidence, self-monitoring in independent learning were moderate during E-learning. However, the students tried hard to understand the materials given in E-learning along with the challenges that the students faced during E-learning. Further study can explore more about the correlation of independent learning and English skills competences.
APLIKASI PENCARIAN AGEN STOKIS HERBAL HPAI BERBASIS ANDROID MENGGUNAKAN LOCATION BASED SERVICE (LBS)

HPAI Herbal Stockist Agent is a distributor of various types of herbs produced by HPAI. Stockist agents who have large capital tend to have specialized stores to distribute their herbs and have a large stock of various herbs. Usually, the store is already listed on google so that consumers can find it. Then, what about stockist agents who have small capital? They do not have a specialty shop and an adequate supply of herbs. Then, what if the shop is far from our position? What if there is a stockist agent around us, but not listed on google? To solve this problem, an application was designed to help distributors and consumers of HPAI herbs, namely an Android-based Stockist Agent Search Application using Location Based Service (LBS). The research objective to be achieved is to produce an application that makes it easier for consumers to find HPAI herbal stockist agents as well as help HPAI stockist agents in their herbal distribution. Location Based Service (lbs) is an information service that can be accessed via a mobile device using a mobile network, which is equipped with the ability to take advantage of the location of the mobile device. With this application, we as HPAI herbal stockists and consumers can be helped in finding and obtaining herbs (consumers), as well as distributing herbs (stockist agents) more widely.
Sistem Pakar dalam Menganalisis Defisiensi Nutrisi Tanaman Hidroponik Menggunakan Metode Certainty Factor

Currently the Expert system has become a field of research for computer scientists as well as agricultural scientists for applications in various information development. The Expert System can be designed to simulate one or more of the ways an agricultural expert uses his knowledge and experience in making the diagnosis and passing on the necessary recommendations regarding nutritional deficiencies. Nutrient deficiency is a lack of food for survival in plants. The nutrient content of plant parts, especially the leaves, is very relevant to be used to identify nutritional deficiencies. Provide the results of a diagnosis of nutritional deficiency to farmers to be a benchmark for improving plant nutrients and providing good nutrition for hydroponic plants. The data used are nutritional deficiency data and symptoms as well as nutritional solutions obtained from farmer data at the Payakumbuh City Agriculture Office. The method used in this expert system is the Certainty Factor (CF) method. This method provides a diagnosis in the form of certainty or uncertainty of conditions in the rules used to conclude. The results of testing this method showed as many as 12 nutritional deficiencies were detected with 41 symptoms experienced. So that it can measure the level of nutritional deficiency that occurs. Expert System in Analyzing Hydroponic Plant Nutrient Deficiency Using Certainty Factor Method can show that predictions are almost 94% accurate.
Shot-Noise Limited Hot Electron Bolometer Integrated on Silicon-On-Insulator Photonics

Shot-noise limited (SNL) detectors that can be integrated on several photonic platforms are essential for photonic quantum technologies. We integrated small-area Hot Electron Bolometers on SOI photonics, demonstrating SNL operations with only 1.1μW of input power.
Survival Study On Website Phishing Attack Detection

In World Wide Web, cybercriminalsutilize the opportunities to hack the personalinformation like username, password, account number and national insurance numberscalled Web phishing attack (WPA). WPA is performed viasending link to emails. Victimsreceive email to update information. When link is clicked by victims, Web browser sendsphishing website that appears likeoriginal website.Phishing website is identifiedthroughthe characteristics such as URL and domain identity. The data mining techniquesisemployed to identifywebsite is phishing website or not. However, the WPAdetection(WPAD) waschallenging task. Our main objective is to improve the WPAD performancethrough studying the existing problems.
Geometrical Pattern Recognition for Rearranging Chairs

Currently, furniture is used by every person and all working people in their lives. In office hours, it is necessary for the people to keep the furniture organized after the completion of meeting or event. Now a day’s every student, every employee and all the working people having rush in their life. So they forget to arrange their furniture in working space which will create bad look for professional environment and also affect the psychology. The common thoughts now a day in educational institutions is that after every laboratory session is over, the students left the chair unarranged and the corresponding lab assistant’s need to arrange the chairs after session is over in order to keep laboratory ready for the upcoming sessions. For this situation, in this paper we proposed a robotic chair which move automatically and follow the tag. These tags are predefined and fixed at valve or table. Whenever program runs these chairs automatically goes to the tag nearby and will aligned at its original position.
Setting up Python, numpy, and PyTorch natively on Apple M1

The new Apple M1 devices have received quite the attention in the past months. However, data scientists and engineers have been wary of upgrading too soon, and in my opinion rightfully so. However, it is possible to run a development setup natively on the ARM-architecture. In this post, I describe how.
Elizabeth Warren rails against Amazon in series of tweets

Amazon, Warren has argued, uses its status as an e-commerce behemoth to elevate its own products above those of third parties.
자기주도적 영문 보고서 글쓰기를 위한 텍스트언어학적 전략에 대하여

Academic reports are considerably different than essay writings in that they are used to present the results of an experiment, survey, or other research method. In addition, these reports should inform, explain and persuade by well-organized paragraphs. One of the most important challenges that English as foreign language (EFL) learners face when writing a report is the orderly treatment of a set of linked elements. Therefore, in this study, an English written report is examined and then text-linguistic strategies for self-directed English reports are presented. The English report was examined focusing on the cohesion, coherence, and intertextuality among the seven properties of the text. In terms of coherence, the connection between the topic and the sentences was strongly captured and local/ conditional coherence were also observed throughout the report. In lexical cohesion, junctions and pro-forms were mainly used while grammatical cohesion structures such as paraphrasing, recurrence, and parallelism were found to be weak, revealing the limitations of text producers using English as a foreign language. In terms of intertextuality, the type of indicating different texts was mostly used, implying that it is a monotonous text composition. This study is meaningful because it guides students to write a more complete academic report through self-directed checklists consisted of textlintuistic strategies. It is expected to be applied and utilized in the field of English teaching and learning as well as the improvement of general process-oriented writing.
Inferring Dataset Relations using Knowledge Graph Metadata

The web site dataportalen.se aims to increase the availability of Swedish open datasets. This is achieved by collecting metadata about the open datasets provided by Swedish organizations. At the ti ...
The Emojification of Everyday Life

The final chapter looks at how emoji have been commercialized and the extent to which we’re now seeing the ‘emojification’ of modern society in much the same way that the late twentieth century was marked by a process of ‘Disneyfication’. Not only are brands and advertisers embracing emoji culture for marketing purposes, but the large tech companies are increasingly commodifying them as part of their commercial strategies. This is having implications for the evolution of language which are markedly different from what we’ve seen before and raises interesting ethical questions about the politics and economics of communication.
A Theoretical Framework for Online Information Search

A significant part of human activity today consists of searching for a piece of information online, utilizing knowledge repositories. This endeavor may be time-consuming if the individual searching for the information is unfamiliar with the subject matter of that information. However, experts can aid individuals find relevant information by searching online. This paper describes a theoretical framework to model the dynamic process by which requests for information come to a system of experts, who then answer the requests by searching for those pieces of information.
Continuous Variable Cluster State Computation

We demonstrate large-scale cluster state generation for quantum computation. We proceed to implement a universal Gaussian gate set by projective measurement. Finally, we show that fault-tolerant computation is possible with a reasonable squeezing threshold.
Role of Strategic Human Resource Management Practices on the Achieving of Sustainable Competitive Advantages: The Mediation Role of Strategic Leadership and Organizational Culture

Like other business organizations, the banking sector endeavors to achieve and sustain its competitive advantages in the business market. The aim of this study to investigates the role of strategic human resources management practices in achieving sustainable competitive advantages, with the mediating role of organizational culture and strategic leadership in the banking sector of Saudi Arabia. A resource-based view was applied to establish and understand the study model.  Convenience sampling techniques were used to collect data from 181 respondents through a cross-sectional research design. Primary data were collected from different public and private banks’ employees from the Western region of Saudi Arabia. Structural equation modelling techniques were applied to analyze the data through Smart PLS software. This study findings presents that the strategic human resource management practices directly influence strategic leadership and organizational culture. Whereas strategic leadership and organizational culture were mediate the relationship between strategic human resource management and sustainable competitive advantages. Finally, this study extended the literature on the association between strategic human resource management practices, strategic leadership, organizational culture, and sustainable competitive advantages of the banking sector of Saudi Arabia.
Neural Photofit: Gaze-based Mental Image Reconstruction

We propose a novel method that leverages human fixations to visually decode the image a person has in mind into a photofit (facial composite). Our method combines three neural networks: An encoder, a scoring network, and a decoder. The encoder extracts image features and predicts a neural activation map for each face looked at by a human observer. A neural scoring network compares the human and neural attention and predicts a relevance score for each extracted image feature. Finally, image features are aggregated into a single feature vector as a linear combination of all features weighted by relevance which a decoder decodes into the final photofit. We train the neural scoring network on a novel dataset containing gaze data of 19 participants looking at collages of synthetic faces. We show that our method significantly outperforms a mean baseline predictor and report on a human study that shows that we can decode photofits that are visually plausible and close to the observer's mental image.
A Generalized Distance-Based Total Uncertainty Measure in Complex Evidence Theory

Abstract In this paper, a generalized total uncertainty ( GTU ) measure method is presented directly under the complex evidence theory framework, rather than under the probability framework. GTU is defined based on the distance between the belief interval of each singleton and the most uncertain case, which is normalized by the normalization factor. We proved the properties of GTU . There is an average evidence that represents the average acceptable environment for data from sensors. According to the GTU difference of each data and the average evidence, data from different sensors are given different weights. Each weight represents the trustworthiness of each sensor data in the fusion process, and giving a low weight to abnormal data can avoid false conclusions. The practicability and rationality of the method are verified by numerical examples and applications.