Reviewerly/exHarmony huggingface dataset:
Clinically Relevant Latent Space Embedding of Cancer Histopathology Slides Through Variational Autoencoder based Image Compression

In this paper, we introduce a Variational Autoencoder (VAE) based training approach that can compress and decompress cancer pathology slides at a compression ratio of 1:512, which is better than the previously reported state of the art (SOTA) in the literature, while still maintaining accuracy in clinical validation tasks. The compression approach was tested on more common computer vision datasets such as CIFAR10, and we explore which image characteristics enable this compression ratio on cancer imaging data but not generic images. We generate and visualize embeddings from the compressed latent space and demonstrate how they are useful for clinical interpretation of data, and how in the future such latent embeddings can be used to accelerate search of clinical imaging data.
Location-Guided Multi-Modality Collaborative Learning for Prostate Tumor Segmentation

Prostate tumor segmentation from multi-modality magnetic resonance (MR) images is indispensable for diagnosis and treatment of prostate cancer. Existing methods typically over-look the specific distribution of prostate tumors in MR images and also the efficacy of extracting features from different MR modalities in the tumor segmentation task. In this paper, we address these limitations by proposing a novel localization-to-segmentation framework. First, we design a localization stage to locate tumor slices precisely via a label order consistency (LOC) strategy, by explicitly utilizing tumor distribution prior. Then, in the subsequent segmentation stage, we develop an attention-based multi-modality collaborative learning (MCL) module, to extract high-level modality-specific features while focusing on aggregating complementary features across modalities, for segmenting tumors from the localized tumor slices. Experimental results demonstrate that our method achieves state-of-the-art segmentation performance on an in-house prostate MRI dataset, especially for tumors with low contrast to the surrounding tissues.
MAGNET: A Modality-Agnostic Network for 3d Medical Image Segmentation

In this paper, we proposed MAGNET, a novel modality-agnostic network for 3D medical image segmentation. Different from existing learning methods, MAGNET is specifically designed to handle real medical situations where multiple modalities/sequences are available during model training, but fewer ones are available or used at time of clinical practice. Our results on multiple datasets show that MAGNET trained on multi-modality data has the unique ability to perform predictions using any subset of training imaging modalities. It outperforms individually trained uni-modality models while can further boost performance when more modalities are available at testing.
THE DIFFICULTIES OF WRITING A RESEARCH PROPOSAL BY STUDENTS OF STIBA IEC JAKARTA

This research aims to analyze the English Literature students’ of STIBA – IEC Jakarta problems in writing final project in English. The causes are viewed from students’ and the lecturers perspective as the advisor and also what are supposed to do to help the student minimize the problems in writing final project. This study used descriptive qualitative method that fully describe the problems as well as solutions in writing final projects. The deep analysis has been done from the student’s and the lecturer’s perspectives. After conducting a survey by doing some interviews and distributing questionnaires, we found that there are so many factors that affects the studnts’ difficulties in finishing their final projects. This research method is a method of classroom action research conducted to improve the ability of students to make a research proposal through a direct learning model. The process of implementation of the measures is implemented in stages until the research is successful. The procedure initiated actions of (1) the action plan, (2) implementation of the action, (3) observation, and (4) reflection. Results research shows that the ability to write a student thesis research proposal in semesters 7-8 English Literature Study Program 2018 academic year belongs to sufficient qualifications. Semester 7-8 students of the English Literature Study Program STIBA - IEC Jakarta should be helped to really understand how to prepare a thesis research proposal so that they can write research proposals well and in the end students will be able to complete the thesis quickly and on time.
Performance Analysis of IOTA Tangle and a New Consensus Algorithm for Smart Grids

Blockchain is an effective technology that enables secure data sharing and trusted energy trading in smart grids (SGs). The consensus algorithm plays a key role in the blockchain’s security and consistency. However, due to nonconcurrency, long consensus time, low throughput, and high transaction fees, current consensus algorithms are not suitable for SGs, where there is a large-scale distributed wireless field area network (FAN) with limited resources and frequent small transactions. In this paper, we propose a performance analysis model and a new consensus algorithm for the tangle in the FAN. First, we propose an analytical analysis model for the consensus time and probability of a successful parasitic chain attack on the FAN by comprehensively considering the number of data transmission hops, communication protocols, computing resources and checked tips. Furthermore, based on the analysis, a new consensus algorithm is proposed by clustering nodes cooperating with each other to complete the proof of work (PoW). Finally, we show the accuracy of the analysis results by comparing them with the simulation results. Additionally, we show that the proposed consensus algorithm can reduce the required consensus time by approximately 50%.
Focus-Shifting Attack: An Adversarial Attack That Retains Saliency Map Information and Manipulates Model Explanations

With the increased use of deep learning in many fields, a question has been raised: “How much should we trust the results generated by deep learning models?” Thus, there has been much research into the interpretations of model results, in order to open the black box of deep learning. The focus is more on interpretation than prediction in some fields such as medicine. Adversarial attacks are the most direct threats to deep learning models. They can add undetectable perturbations to the data to make the models give incorrect results, and model explanations are also susceptible to attacks. This leads to a loss of trust in explanations provided by the models, limiting the application and commercial value of deep learning. This research proposes a targeted adversarial attack algorithm that manipulates the interpretation of the model. Unlike other adversarial attacks on model interpretation, focus-shifting attack (FS Attack) can preserve the numerical depth of the original saliency map without specifying a perturbation budget. Experiments have shown that the FS Attack has a higher degree of image similarity and misleading interpretation than other adversarial attacks, and the property of preserving the numerical depth of the original saliency map makes it more difficult to detect. This study uses several common explanation methods as experimental subjects to investigate how these explanations can be manipulated and evaluate the effectiveness of the attack under different conditions. Under a particular interpretation, the FS Attack has a highly successful attack rate of 94.6 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$%$</tex-math></inline-formula> , which is a critical adversarial attack.
RE-INVESTIGATING ORGANIZATIONAL EXCELLENCE

This study aims to assess organizational excellence (OE) performance among selected industrial companies operating in Jordan. To achieve the study objective, the researcher developed a questionnaire consisting of 20 items, distributed among Four dimensions. The study population consisted of Eighty 80 industrial companies listed on the Amman Stock Exchange, employing 1262 managers. A random sample was drawn from the listed companies consisting of 26 companies, i.e. 32.5%. The random sample size was determined to be 295 managers. The researcher then collected the data and used SPSS for analysis. The most important results of the study is OE performance assessment scored 3.95 on 5-point rating scale. Four critical pillars of OE were analyzed: people excellence, operational excellence, leadership excellence, and strategy excellence. The main recommendations of the study are the following: 1) To enhance the OE concept and wide spread OE indicators in the industrial companies operating in Jordan so as to promote the company's image and enhance performance; 2) Adopt learning, development, and creativity at work; 3) Encourage employees to outperform by educating them on the importance of excellence through training courses, lectures, and workshops. Keywords: Organizational Excellence, Strategy Excellence, Structure Excellence, Leadership Excellence, Employee Excellence, Industrial Companies, Jordan DOI： https://doi.org/10.35741/issn.0258-2724.58.4.49
Pengembangan PENGEMBANGAN KEMAMPUAN MAHASISWA PGSD DALAM MEMBUAT MEDIA PEMBELAJARAN MELALUI METODE PEMBELAJARAN RESITASI BERBANTUAN YOU TUBE

This study aims to find out how the situation of the learning process by using the tube-assisted recitation method and knowing the ability of students to create learning media through you tube assisted recitation learning methods can develop. This research is a descriptive qualitative study. The subjects of this study were 5th semester students, PGSD FKIP Pakuan University. The instruments used were observation, interviews and documentation. The results showed that you tube assisted recitation method can improve student independence, motivation to display the best, creativity and self-confidence of students in making learning media in elementary school. But there needs to be an emphasis on the importance of involving IT and the importance of including a reference list.&#x0D;
PENGARUH PENGGUNAAN WORKSHEET IPA BERORIENTASI HOTS TERHADAP HASIL BELAJAR KOGNITIF SISWA SD MUHAMMADIYAH 4 DAN 5 JAKARTA

This study aims to determine the effect of using Science Worksheet Based-HOTS on cognitive learning outcomes of fifth grade students of SD Muhammadiyah 4 and 5 Jakarta. Design research in this research is Quasi Experimental Design or commonly called a quasi experiment. with the aim that researchers can control all variables that affect the course of the experiment. The independent variable is the use of Science Studentâ€™s Worksheet based-HOTS and the dependent variabel is students' cognitive learning outcomes. The research subjects were 62 students, consisting of 34 students for the experimental class, and 28 control class students. The research instrument used to collect data is a test of students' Cognitive Science learning outcomes. Data from the pretest and posttest results were analyzed using independent t-test with a significance level of 5% (Î± = 0.05). Based on the data from the t-test analysis results obtained for pretest values, t-count â‰¥ t-table is 1,810 35 2,035 so it can be concluded that there is no significant difference between the control class and the experimental class. Whereas for the posttest value, the value of t-table is 10,053 â‰¥ 2,035, it can be concluded that there are significant differences between the results of the post-test control class and the experimental class. This shows that there is a significant effect of the application of Science Worksheet Based-HOTS to Studentâ€™s science cognitive learning outcomes of elementary school students of Class V Muhammadiyah 4 and 5 Jakarta
An Introduction to Quantum Computing

We present an overview of quantum computing, including relevant physics, processes, and applications. This includes describing the basic framework of the quantum bit, which serves as the foundation for the rest of this paper. We found rapid developments in quantum computing, which will have important consequences for future applications in scientific fields.
Message from the Workshop General Chair

Welcome to the ICCCN 2023 Workshops! As an integral part of the main conference, the ICCCN workshop program provides international forums for scientists and engineers from both academia and industry to exchange and share their experiences, research results, and new ideas on hot and emerging topics on computer communications and networks. This year we enjoyed the great privilege to have worked with researchers across the world in organizing three workshops covering a variety of important, exciting and timely topics in the area of computer communications and networks. We received a good number of high-quality papers. These workshops are:
Youth sociolect of the network space and its written form as an attribute of modern Japanese youth subculture

The present study outlines a comprehensive analysis of the Japanese youth sociolanguage of the network space as an attribute of modern youth linguoculture and its component part of the written form of communication. The article considers the youth sociolanguage of the network space 「若者語の SNS言葉」[wakamonogo no SNS kotoba] as the newest linguistic phenomenon in the modern Japanese language, which functions in youth communities of the network space, transforms the communication of young people and has its own “written and spoken” form of speech, where the function of intonation is performed by paralinguistic means of language. For the first time, the lexical items of the youth sociolect of the network space are classified in order to systematise them depending on the method of notation. The author focuses on the uniqueness of the Japanese writing system and thus distinguishes four methods of notation acts: hybrid input method; incorrect conversion; graphemic similarities; representative symbols of emotional expression. Special attention is paid to monitoring of paralinguistic means of communication as a resource for textualisation of youth oral speech. The study also identifies and analyses the differences between the oral language 「話し言葉」 and the written language 「書き言葉」 of youth network communication. The analysis of the factual material shows the presence of a significant number of written units of the youth sociolect, which entered the circulation of oral communication through secondary transformation, and it indicates their interaction and complementarity. The analysis of the Japanese youth sociolanguage of the network space, in particular its written form, is quite appropriate and promising in predicting the process of change and enrichment of the standard Japanese language. It opens up new perspectives in the study of youth sociolects at different levels and expands understanding of the linguistic worldview of the modern Japanese youth.
European transformation of higher education in Ukraine – an opinion translated into action: the case for Computational Linguistics at Kyiv National Linguistic University

In this paper, we show how the new educational value is created and managed at Kyiv National Linguistic University taking its strategic direction towards the transformation that the higher education of Ukraine begins to undergo in its harmonization with that of Europe, in the face of the grand challenges and in response to the grand changes that are now revamping Ukraine and the world.We seek to add an interpretive depth to the concept of transformation by particularizing that this must necessarily be a change in the content, rather than merely a change in the form, which generally is the case with metamorphoses, when it is an input to the content that causes the form to change. To this end, we document the onset and the stage-by-stage development of an academic course in Computational Linguistics that in its evolution migrated from the periphery to the core of the educational program it is part of, creating a sustainable European educational culture in the educational space of the University.We give a comprehensive account of our concerted educational action in launching the course, and unpack our understanding of how exactly the course contributes to the professional and personal transformation of its students, on the one hand, and to the big transformation of higher education in Ukraine, on the other. We show that our action was informed by our educational praxis with which we continuously engaged in making the artifacts constitutive of the culture: the educational materials that we developed, and the pedagogical and psychological choices that we made when tailoring particular learning experiences for the students. All these in a tandem form our educational practice that we in this paper specify as one endowed with a European spirit. This practice is the input that we prove was transformative throughout the educational change.The course in Computational Linguistics at Kyiv National Linguistic University ensures the quality of higher education according to European standards, contributing to the national repute and internationalization of the University.
Comparative Analysis of the Use of State Management in E-commerce Marketplace Applications Using the Flutter Framework

This research aims to analyze the performance of two popular state management tools that have different system approaches, namely Riverpod and GetX, in developing marketplace applications using the Flutter framework. The marketplace type application used is Flutter ecommerce which is available as open source on the GitHub platform. This research aims to provide benefits to Flutter application developers in choosing the right state management tools for marketplace applications. The method used is to compare memory usage, execution time and CPU utilization of the two tools. Testing is done on the feature of displaying the home screen, search and add features. The results of the analysis obtained are that there are differences in memory usage and execution time for the three features and scenarios, GetX provides less memory usage with faster execution time. While in CPU utilization, there tends to be no performance difference between GetX and Riverpod. The conclusion is that GetX state management uses memory more efficiently and is able to provide faster execution time than Riverpod state management with better performance.
Meta’s Oversight Board

The regulatory framework of international human rights law (IHRL) was originally designed to protect individuals from the power of states. However, the global expansion of private entities’ power raised social awareness of the impact of business on human rights. The discussion around businesses and human rights has not been oblivious to the debates surrounding freedom of expression in the era of digitalisation. While the digital public sphere has undoubtedly democratised the public conversation, it has also generated risks and challenges around content moderation and freedom of expression. Platforms have therefore expanded their powers, creating a growing number of content rules and increasing the amount of content they remove. This has led to the rise of legitimate complaints concerning the lack of remedies for the proliferation of harmful speech and the ‘excessive’ content moderation that limits or excludes content protected by the freedom of expression. Within this framework, the discussion remains open as to who should regulate social media and how it must be done, what oversight mechanisms should be implemented to ensure people the protection of their rights online and prevent negative on- and offline impacts. This article provides an outline of the challenges generated by communication in the digital sphere and addresses the discussions on public/private regulation of content moderation. Additionally, this article addresses the importance of ensuring that the rules applied by the platforms are based on IHRL and discusses the creation of Meta’s Oversight Board as a self-regulatory mechanism, as a novel and complementary alternative to governing social media.
FOREIGN DIRECT INVESTMENT, AGRICULTURAL PRODUCTIVITY AND FOOD SECURITY IN SUB-SAHARAN AFRICA

This study examines the impact of foreign direct investment in agricultural productivity on food se­curity in sub-Saharan Africa covering the period 2010-2020. The data were obtained from World Bank World Development Indicators, United Nations Food and Agricultural Organization and United Nations Conference on Trade and Development. The technique used for data analysis is System Generalized Meth­od of Moment. The results of Arrelano-Bond tests show no autocorrelation. The estimated GMM-SYS results show that foreign direct investment in agriculture is positive and statistically significant in influencing food security variables including food consumption score (with the coefficient of 0.042) and dietary energy consumption (with the coefficient of 0.317). The control variables like crop production, food exports, age dependency and rural population are significant determinants of food consumption score. Also, GDP per capita, crop production, age dependency and rural population are significant factors influencing dietary energy consumption in Sub-Saharan Africa. Based on the findings of the study, there is need for regional governments to ensure tenure reforms by formalization of customary rights to enhance tenure security for a more equitable access to land. It is also essential that proper monitoring and impact assessment systems are developed to ensure transparency of the processes associated with agricultural investments. Furthermore, countries with currently high foreign direct investment transaction costs or that have a generally less conducive investment environment can improve agriculture by eliminating these obstacles.
Retrospective Evaluation of the COVID-19 Contact Tracing Program at the Maine Center for Disease Control and Prevention

Introduction: Despite the widespread use of contact tracing efforts throughout the COVID-19 pandemic, there are limited findings available about best practices and recommendations. The Maine Center for Disease Control and Prevention contracted staff to conduct COVID-19 contact tracing from August 2020 through February 2022. A retrospective evaluation of this program was conducted to share lessons learned with public health and health care leaders for future use.
The NumPy Library

NumPy is a basic package for scientific computing with Python and especially for data analysis. In fact, this library is the basis of a large amount of mathematical and scientific Python packages, and among them, as you will see later in the book, is the pandas library. This library, specialized for data analysis, is fully developed using the concepts introduced by NumPy. In fact, the built-in tools provided by the standard Python library could be too simple or inadequate for most of the calculations in data analysis.
Seismic Soundoff: How to unlock the power of networking

Lia Martinez shares critical skills that are necessary to network successfully. She explains why seven follow-ups is the magic number, the importance of establishing credibility early, and how to use note-taking to your advantage.