Reviewerly/exHarmony huggingface dataset:
CORRUPTION AND THE LEAST DEVELOPED COUNTRIES (LDCS): AN ANALYSIS OF THE CAUSES, SCOPE, AND IMPACT OF CORRUPTION ON THE LDCS

The article examines the links between corruption and development in the developing world. There is a close relationship between corruption and development, which is why ending corruption needs to be at the core of any developmental agenda for the least developed countries (henceforth LCDs). Moreover, this article includes a discussion on the causes, scope, and impact of corruption on the state and society in the LCDs. As there is a lack of oversight, transparency, central guidance and direction, coupled with institutional deficiencies and incompetence, there is a tendency towards predatory, rentier state in the LDCs. Besides this, there exists a kind of shadow state in the LDCs as corruption leads to the emergence of an informal economy. Furthermore, this article explores the detrimental effects of corruption on equality in society, investment in the public as well private sectors, and on the state budget. Finally, this articles not only sheds lights on the internal ecology of corruption and its external repercussions, but also points out some mechanism whereby corruption can be combated and contained. Keywords: Corruption, causes of corruption, reasons behind corruption, measures to stop Corruption.
COMPARATIVE ANALYSIS OF SPECIAL EDUCATION DEGREE PROGRAMS IN THE USA

Based on the analysis of materials it was revealed that during a significant period of time in the United States the main goal of children with limited capabilities was to gain access to proper general education. Due to the active movement of civil rights for all citizens of the United States the U.S. government adopted a number of legislative acts that could access students with special educational needs to general education. A large number of students who needed special educational conditions provoked a deep rethinking of the training process that could professionally provide necessary training. By analyzing, it was revealed that the training of a teacher of special education involves producing information about the development of students with special educational needs and methods of their correction during learning and education. For this reason, all special education training programs are generally included following subjects relating to applied behavior analysis, mental disorder practice, auxiliary technologies, ways to eliminate language learning, educating pupils with autism or deep mental disorders, typical and atypical early child development, etc. However, it was revealed that every University has certain variations on initial requirements for the introduction, methods of teaching, training duration, internship passage, obtaining the final document and so on.
Integrated multi-operand optical neurons for scalable and hardware-efficient deep learning

The optical neural network (ONN) is a promising hardware platform for next-generation neuromorphic computing due to its high parallelism, low latency, and low energy consumption. However, previous integrated photonic tensor cores (PTCs) consume numerous single-operand optical modulators for signal and weight encoding, leading to large area costs and high propagation loss to implement large tensor operations. This work proposes a scalable and efficient optical dot-product engine based on customized multi-operand photonic devices, namely multi-operand optical neurons (MOON). We experimentally demonstrate the utility of a MOON using a multi-operand-Mach-Zehnder-interferometer (MOMZI) in image recognition tasks. Specifically, our MOMZI-based ONN achieves a measured accuracy of 85.89% in the street view house number (SVHN) recognition dataset with 4-bit voltage control precision. Furthermore, our performance analysis reveals that a 128x128 MOMZI-based PTCs outperform their counterparts based on single-operand MZIs by one to two order-of-magnitudes in propagation loss, optical delay, and total device footprint, with comparable matrix expressivity.
Development of STEM-based Worksheet in Elementary School

To develop students’ 21st century skills, it is necessary to develop STEM-based worksheet to provide learning that links knowledge and technology with contexts in everyday life so as to create learning that is able to prepare students to compete in the future. The main focus of this research is the development of a feasible STEM-based worksheet in science education in elementary school. This research is a Design and Development study with the ADDIE model which consists of the analysis, design, development, implementation and evaluation stages. Based on the analysis of the curriculum, needs, and the learning environment of students, STEM-based worksheet is developed. The worksheet was assessed for its feasibility by experts and teachers. In addition, user parents/guardians and students are given response assessments. The evaluation of experts and teacher practitioners shows that the teaching material is considered very suitable for use .
Time series analysis as an emerging method for researching L2 affective variables

<h2>Abstract</h2> In language studies, marked by a myriad of psychological and social, and linguistic factors, linear modeling fails to represent the creativity, irregularity and emergent patterns of behavior. To adequately represent the dynamicity and complexity of psychological or affective variables, time-sensitive non-linear modeling is needed, especially the time series analysis (TSA), which accommodates incompatibility over time. TSA is a mathematical framework that can effectively show whether and to what degree the measured time series represent nonlinear variation through time. TSA makes prediction or retrodiction of complex and dynamic phenomena possible in future or past and, thus, can significantly contribute to the unraveling of the nuanced changes in the progress of different learner-related constructs during learning a new language. The present paper, at first, offers an introductory overview of the TSA, and then pinpoints its technical features and procedures. Exemplary works of research in language studies will be reviewed next, followed by useful conclusive remarks about the subject. Finally, suggestions will be made for further investigation of language-related affective variables using this innovative method.
Peer review declaration

All conference organisers/editors are required to declare details about their peer review. Therefore, please provide the following information: • Type of peer review: Double-blind • Conference submission management system: Iconf submission system • Number of submissions received: 202 papers • Number of submissions sent for review: 202 papers • Number of submissions accepted: 102 papers • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 50.5% • Average number of reviews per paper: 2 reviews • Total number of reviewers involved: 119 reviewers • Any additional info on review process: 1. Preliminary Review 2. The papers passed the first review will be reviewed again from the following aspects: Originality, Innovation, Technical Merit, Applicability, Clarity of presentation and Relevance Contact person for queries: Name: Wen Zhang Affiliation: National University of Defense Technology, China Email: zhangwen06@nudt.edu.cn
A review of enhanced image techniques using chaos encryption

Secured multimedia data has grown in importance over the last few decades to safeguard multimedia content from unwanted users. Generally speaking, a number of methods have been employed to hide important visual data from eavesdroppers, one of which is chaotic encryption. This review article will examine chaotic encryption methods currently in use, highlighting their benefits and drawbacks in terms of their applicability for picture security.
Using Songs to Teach English Vocabulary to Young Learners in Kindergarten

From the phenomena around them, young learners find it difficult to learn vocabulary because they are still in e active phase, especially learning English. Therefore, knowing a good and effective way to teach English vocabulary using songs is essential. This study aims to determine the use of songs to teach English vocabulary by teachers at TK 'Aisyiyah Bustanul Athfal (ABA) 51. To be able to answer research questions, researchers conducted classroom observations and interviews with teachers who teach English in class. The subjects of this study were class B students, namely classes B1, B2, and B3. From the observations and interviews that researchers have conducted, it is known that teachers have taught well according to the correct stages and enabled children to recognize vocabulary well at each meeting. Students have high learning enthusiasm when the teacher teaches vocabulary using songs that are shown by being active students. The study results show that songs are very effective for teaching English vocabulary to students because they can foster learning motivation so that students can easily remember the vocabulary being taught and that the objectives of teaching vocabulary are well achieved.
Use of Mindray MC-80 digital morphology analyzer’s estimated platelet counts as adjunct to automated hematology analyzer

Introduction: Automated hematology analyzer platelet counts can be performed using either the impedance (PLT-I) method or the fluorescent nucleic acid staining (PLT-O) method. Estimated platelet counts (PLT-E) can be calculated using a digital morphology analyzer by evaluating the peripheral blood smear. Our objective was to compare the platelet values detected on a Mindray BC-6200 device to the PLT-E count on a Mindray MC-80 digital morphology analyzer. Material and methods: Complete blood cell count findings between 1 September and 11 October, 2022 were obtained from the data storage units of the devices. We selected two groups of blood: a first group with thrombocytopenia (n = 49) and a second group that gave an aggregation and/or platelet clumping flag (n = 32). The results of 190 consecutive patients with normal platelet counts, and no aggregation flag, were evaluated as a control group. Pearson’s correlation coefficients, Bland-Altman plots, and paired t-tests were calculated. Results: The plot of the difference between PLT-I and PLT-O counts showed that the mean difference was –43.6 (95%: –17.2 to –69.9); when we compared PLT-O to PLT-E, bias was improved to –6.1 (95%: –18.26 to 6.1) in samples with aggregation and/or clumping flags (Bland-Altman plots). In samples with thrombocytopenia without aggregation and/or clumping, on the Bland-Altman plot, the differences in means were all close to zero, and there were no definite biases. Conclusions: Examining blood samples using the Mindray MC-80 digital morphology analyzer system on samples that show platelet clumps has the potential to improve PLT-I results in day-to-day laboratory routine.
Evaluation of the Android-based Learning Outcomes Report for Effective and Effective Student Learning Outcomes

In the implementation of submitting reports on student learning outcomes both daily scores, midterm exam scores, and final semester exam scores still use e-reports. thus causing a lack of interest in student learning because learning outcomes cannot be obtained by students/parents in an updated manner. Parents experience difficulties in knowing their children's learning outcomes because parents only get their children's learning results in the middle of the semester and the end of the semester. Schools also experience difficulties, namely: in archival storage. Related to these conditions, good cooperation is created for the application of the SIHABEL software Android-Based Learning Outcomes Evaluation Report as an information system for reporting learning outcomes so that later the reporting process will run effectively. The method used in this research is R&amp;D (Research and Development) version 4D (Define, Design, Develop, Disseminate). Based on the results of this product test it can be concluded that the SIHABEL software Evaluation of Android-Based Learning Outcomes Reports helps schools in carrying out student learning outcomes reporting effectively and can provide the information needed by stakeholders quickly and validly
News from the Field

25 recordings chosen for National Recording Registry ACRL launches Academic Library Advocacy Toolkit CCAHA, Lyrasis announce Collections Stewardship Succession Planning Initiative New from ACRL—Integrated Library Planning: A New Model for Strategic and Dynamic Planning, Management, and Assessment Bloomsbury announces Bloomsbury Open Collections New from ACRL—Conducting a Map Collection Review: A Workbook to Help You on the Journey EBSCO joins ReShare community ARL releases final report of Research Library Impact Framework pilot initiative
Active Learning Strategies for Textual Dataset-Automatic Labelling

The Internet revolution has resulted in abundant data from various sources, including social media, traditional media, etcetera.Although the availability of data is no longer an issue, data labelling for exploiting it in supervised machine learning is still an expensive process and involves tedious human efforts.The overall purpose of this study is to propose a strategy to automatically label the unlabeled textual data with the support of active learning in combination with deep learning.More specifically, this study assesses the performance of different active learning strategies in automatic labelling of the textual dataset at sentence and document levels.To achieve this objective, different experiments have been performed on the publicly available dataset.In first set of experiments, we randomly choose a subset of instances from training dataset and train a deep neural network to assess performance on test set.In the second set of experiments, we replace the random selection with different active learning strategies to choose a subset of the training dataset to train the same model and reassess its performance on test set.The experimental results suggest that different active learning strategies yield performance improvement of 7% on document level datasets and 3% on sentence level datasets for auto labelling.
Engaging with campus and community: Insights from a traveling exhibition

E xhibitions draw people to libraries.They encourage visitors to engage with objects and media in a public space and provide opportunities for discovery within the library's collection.Not every library has the resources to create original exhibitions, however.Traveling exhibitions, which arrive ready to set up in the library's existing space, can alleviate some of the labor involved in creating exhibitions while providing the same benefits for the library.The Penn State University Libraries, Georgia Southern University Libraries, and University of Mississippi Libraries each hosted Americans and the Holocaust, a traveling exhibition from the United States Holocaust Memorial Museum, in late 2021 and early 2022. 1 In this article, we describe the ways each library leveraged the exhibition for community engagement, as well as some of the keys to success that can inform other academic libraries considering hosting a traveling exhibition. Traveling exhibitions and librariesThe academic library is a scholarly space that promotes reflection and discovery.Because it does not belong exclusively to any discipline or department, it is ideally situated to host a campus exhibition that is welcoming to all.Andrew Dutka, Sherman Hayes, and Jerry Parnell describe the reasons for academic libraries of all sizes to develop the capacity to host exhibitions, including providing opportunities for self-learning, presenting unique collections, drawing visitors to the library, and developing partnerships. 2Beth Auten and colleagues reflected on the experience of hosting four traveling exhibitions from the National Library of Medicine (NLM) and found that partnerships with campus and community organizations brought in additional expertise and in new audiences for the exhibition. 3 When the host is an academic library, as in the cases described here, public libraries can contribute expertise in programming as well as their existing partnerships with community organizations for marketing and joint programming. 4 Americans and the Holocaust, the exhibition described here, examines the motives, pressures, and fears that shaped Americans' responses to Nazism, war, and genocide in Europe during the 1930s and 1940s, drawing on extensive new research and a collection of primary sources from the time.
Blockchain Based E-Voting System (Review)

Abstract: New opportunities to create new kinds of digital services are being provided by blockchain. Although study on the subject is still in its early stages, it has largely concentrated on the technological and legal difficulties rather than making use of this innovative idea and developing improved digital services. In this study, we assess a distributed E-voting system implementation using block-chain as a service. The study offers a novel block-chain based E-voting system that tackles some of the drawbacks of current systems and assesses some of the well-known blockchain frameworks in order to build a block-chain based E-voting system. It has long been challenging to develop a secure electronic voting system that maintains the fairness and privacy of paper ballots while providing the transparency and flexibility given by electronic systems in present voting schemes. Through the explanation of a case study, including the election process and the implementation of a blockchain-based application, which increases security and lowers the cost of hosting a national election, we specifically assess the potential of technology.
Healing Center With The Orgonite Method in Mojokerto District

Jolotundo is a village in the Mojokerto Regency area that is located on the slopes of Mount Penanggungan, close to the forest and Majapahit kingdom relics. In Indonesia, public awareness of the importance of health is declining, causing bad behavior and unhealthy environmental conditions in the community. As technology advances, health technology such as orgonite becomes an effective method of treatment or restoration for both physical and psychological health. Unfortunately, no facilities provide a place to support this method. Therefore, it is necessary to have a facility that provides a place of recovery within the orgonite method based on healing and negative energy elimination for physical, mental, environmental, and spiritual well-being. This research employed field studies and literature studies as well as several methods such as observation, documentary, and interview to obtain data, both primary data as a direct data source and secondary data as other supporting data sources. The design applies the theme of therapeutic architecture, the macro concept of tropical architecture, and the micro concept of adaptive land use. The design environment involves green open spaces and maximizes landscape arrangements.
Platform Capitalism – Boon or Bane to Society

In this essay, the rise of platform capitalism and its claims to a utopian economic world is explored. Using the tawḥīdī worldview, I trace its emergence within the context of the growth of modern capitalism itself. The study reveals that there are certain core elements within the institutional framework of the modern economy that empowers capitalism to hegemonize society and its structures. In its drive
Development of Science Learning Media Using Supcath Educational Games to Improve Student Learning Outcomes

Technological developments have a rapid influence on the world of education so there is a need for innovation. The student’s ability to solve problems is still relatively low, especially in solid pressure material. This study aims to produce educational game-based learning media that is valid, effective, and able to improve student learning outcomes. The instructional media developed by this researcher specifically focus on material related to pressure for grade 8. This research is a Research and Development study with the ADDIE research design (Analysis, Design, Development, Implementation, and Evaluation). Data was collected using expert validation sheets, student test sheets, and student response sheets. The results showed that learning media was valid and effective with an average percentage of validator ratings of 92.6% and an average N-gain value of 0.6. Referring to the results of the analysis that has been carried out, this learning media can be concluded as the learning media that are valid, effective, and able to improve student learning outcomes.
Adversarial Clean Label Backdoor Attacks and Defenses on Text Classification Systems

Clean-label (CL) attack is a form of data poisoning attack where an adversary modifies only the textual input of the training data, without requiring access to the labeling function. CL attacks are relatively unexplored in NLP, as compared to label flipping (LF) attacks, where the latter additionally requires access to the labeling function as well. While CL attacks are more resilient to data sanitization and manual relabeling methods than LF attacks, they often demand as high as ten times the poisoning budget than LF attacks. In this work, we first introduce an Adversarial Clean Label attack which can adversarially perturb in-class training examples for poisoning the training set. We then show that an adversary can significantly bring down the data requirements for a CL attack, using the aforementioned approach, to as low as 20% of the data otherwise required. We then systematically benchmark and analyze a number of defense methods, for both LF and CL attacks, some previously employed solely for LF attacks in the textual domain and others adapted from computer vision. We find that text-specific defenses greatly vary in their effectiveness depending on their properties.
Data-driven Decisions of Higher Education Instructors in an Era of a Global Pandemic

The impact of the COVID-19 pandemic on the higher education sector has been overwhelming, with emergency responses that have affected decision-making processes. Yet, our understanding of higher education instructors’ perspectives regarding the process of data-driven decisions, especially in times of emergency, is still limited. We aimed at characterizing the types of data-driven decisions that higher education instructors have made in their courses. This was done while asking the instructors to reflect upon a face-to-face (F2F) course that was suddenly shifted to emergency remote teaching (ERT), due to the COVID-19 pandemic outbreak. Taking a qualitative approach, data were collected via an open-ended online questionnaire distributed among 109 higher education instructors from different countries. The findings suggest that the instructors mentioned a wider range of data sources, and a wider range of data-driven decisions while referring to the ERT mode, compared with their F2F instruction. In F2F teaching, the instructors mostly provided students with real-time educational assistance. In ERT, the instructors mostly adjusted the course requirements, promoted collaboration among students, and offered them social and emotional support.