Program Library Research Articles

A New Generation Communication System Based on Deep Learning Methods for the Process of Modulation and Demodulation from the Modulated Images

Demodulating the modulated signals used in digital communication on the receiver side is necessary in terms of communication. The currently used systems are systems with a variety of hardware. These systems are used separately for each type of communication signal. A single algorithm facilitates the classification and subsequent demodulation of signals without needing hardware instead of extra hardware cost and complex systems. This study, which aims to make modulation classification by using images of signals, provides this convenience. In this study, a classification and demodulation process is done by using images of digital modulation signals. Convolutional neural network (CNN), a deep learning algorithm, has been used for classification and recognition. Images of the signals of quadrate amplitude shift keying (QASK), quadrate frequency shift keying (QFSK), and quadrate phase shift keying (QPSK) digital modulation types at noise levels of 0 dB, 5 dB, 10 dB, and 15 dB were used. Thanks to this algorithm, which works without hardware, the success achieved is around 98%. Python programming language and libraries have been used in training and testing the algorithm. Demodulation processes of these signals have been performed for demodulation using the nonlinear autoregressive network with exogenous inputs (NARX) algorithm, an artificial neural network. As a result of using MATLAB, the NARX algorithm achieved approximately 94% success in obtaining the information signal. Thanks to the work done, it will be possible to classify and demodulate other communication signals without extra hardware.

“Everybody Thinks Public Libraries Have Only Books”: Public Library Usage and Settlement of Bangladeshi Immigrants in Canada

ABSTRACT Many public libraries in Canada offer services and programs for immigrants, including employment assistance to assist newcomers with their settlement in Canada. Using a mixed method research design, this study explores the use of public libraries by Bangladeshi immigrants in Canada including their use of public library settlement services, along with their pre-migration access to public library services. The study finds immigrants’ use of public libraries declines over time. However, it is also evident in this study that public libraries played a positive role in newcomers’ settlement into Canadian society. The findings related to the lack of familiarity with public libraries in a pre-arrival context highlight the importance of having a strong public library outreach program for immigrant populations. The author urges public libraries offering services to immigrants to make meaningful partnerships with pre-and post-arrival settlement agencies, local ethnic community and religious organizations, and ethnic media to spread the word about public library programs and services for immigrants.

Upaya TBM Kuncup Mekar Dalam Membangun Budaya Literasi Masyarakat Pesisir dan Pedesaan di Gunung Kidul, Yogyakarta

Building a society that is literate to information in rural coastal areas is a challenge for information activists. The lack of access to information such as reading materials and low awareness of the importance of knowledge are often obstacles. This study examines the efforts of the Kuncup Mekar Community Reading Park (TBM) in the village of Kepek Gunungkidul Yogyakarta in building information literacy for people living in coastal and rural areas through the One Home One Library program, so that it has an impact on improving the quality of education and the economy. The author uses qualitative methods with data collection techniques through interviews, observation and documentation. Informants were selected through a purposive technique, namely people who are considered very instrumental and understand the One Home One Library program. Based on the data obtained, TBM Kuncup Mekar conducted the One Home One Library program through 5 (five) stages, namely socialization, preparing bookshelves in each house, distributing books, making book control tools, and arranging book lending schedules. The One Home One Library program has been able to instill public information literacy skills which have an impact on the education and economic aspects of the community. The impact of information literacy skills include; increasing children's interest in reading and learning, the emergence of parents' desire to provide access to learning and information for their children, as well as increasing community understanding in agricultural and livestock cultivation.

Preserving the Wonder of Stories: The Role of Reflection in Reading Education in Library and Information Science Programs

Building on the concept of transformative learning and exploring the role of reflection in graduate professional education, this article uses student and educator reflections from the graduate course on reading practices to narrate four stories of learning. These stories, structured based on the “4Ls” model of reflection, describe what was Learned and Liked in the course and what both the student and the educator Lacked and Longed for as a result of the course. An argument is made in support of not limiting Library and Information Science reading education to techniques and skills for providing reading suggestions (i.e., readers’ advisory) but for enriching this education with reflective exercises, a theoretical foundation of reading behaviors, and challenging intellectual and affective engagements that will contribute to a well-rounded practitioner education that facilitates the reading experience.

The Public Library’s Role in Youth Learning: Remediation and Acceleration During COVID

This article summarizes key research findings about academic learning loss during the COVID-19 pandemic and how public libraries can help youth with learning remediation and acceleration. Given the educational crisis, it is urgent that public library services and programs create more equitable practices for all children, particularly children of color. Finally, the article highlights specific practices instituted by several library systems that address COVID-related learning loss and are aligned to two areas of national priority: summer learning and out-of-school time.

Public Library Play-based Early Literacy Programs: What is the Parental Experience?

Many public libraries offer early literacy storytime programs to child patrons and their parents. Based on current research and best-practice periodicals, more children’s librarians are incorporating and modeling play-based activities in their storytime programs at the public library to emphasize the importance of parent-child interaction in guiding early literacy learning. Play as a method of learning is often underutilized and misunderstood by parents. This literature review aims to investigate the role of public libraries (and librarians) in informal early literacy education, the shift towards play-based practices in early literacy programs at the public library, the importance and significance of quality parent-child interaction in early literacy experiences, and the documentation of the experiences and perceptions of parents attending early literacy programs at the public library with their children. As previous studies correlate the benefits of parent-child interaction in play-based activities with early literacy learning, it is evident that further qualitative research into the actual experiences of parents attending play-based early literacy public library programs is needed in order to identify moreareas for improvement of public library services and storytime programs for child patrons and their parents.

Book Review: Library programming for autistic children and teens

Book Review: Library programming for autistic children and teens

ZhuSuan: design and implementation of differentiable probabilistic programming libraries

Probabilistic models provide a set of powerful tools to deal with uncertainty that is pervasive in machine learning applications. Probabilistic programming utilizes computer programs to represent probabilistic models, and it supports the functions of sampling as well as probabilistic inference conditioned on arbitrary observations. Traditionally, the dependency relationship in probabilistic programming is mainly linear or generalized linear, which serves as the basis of many successful models and inference algorithms. However, such linearity also limits the expressiveness and flexibility of probabilistic programs. Differentiable probabilistic programming allows probabilistic programs to have nonlinear dependency under a proper parameterization form (e.g., neural networks) and can learn unknown parameters from data via gradient-based methods. This programming paradigm is easy to extend, largely avoids the tedious model selection process, and makes the deployment of probabilistic models possible in an end-to-end manner. This article presents ZhuSuan, an open-source library for differentiable probabilistic programming. Taking ZhuSuan as an example, we discuss the design and implementation of differentiable probabilistic programming systems.

Analyzing large-scale Data Cubes with user-defined algorithms: A cloud-native approach

Recent advances in cloud-based remote sensing platforms have revoluted the routines for remote sensing big data (RSBD) analysis. However, it is challenging to make user-defined algorithms reusable for RSBD applications if not pre-implemented in RSBD platforms, especially legacy algorithms written with specific programming languages and libraries. In recent years, the emergence of containerization, which is the core feature of cloud native, provided effective solutions to port user-defined algorithms to the cloud environment. In this research, we present a novel approach to deploy user-defined remote sensing algorithms for large-scale analysis based on Data Cube and cloud-native containerization. A processing model is introduced to organize workflows of remote sensing analysis based on Data Cube. The workflows can be decomposed into multiple independent steps and parallelizable tasks following the homogeneity of Data Cube and the parallelizability of remote sensing analysis. Subsequently, the Composite Container is designed to process tasks with user-defined algorithms as built-in algorithms. Then, we introduce Data Cube Resilient Distributed Dataset (DRDD) to implement workflows with Composite Containers following the MapReduce paradigms. The proposed approach was implemented with Science Earth Platform and validated with two sets of up to 10-m resolution continental-scale land cover mapping. Experiment results show that the proposed approach can effectively implement remote sensing analysis with user-defined algorithms and show good performance for continental-scale analysis.

Hyper content e-module in information behavior course with the assistant of screencast

In the 21st century, continuous innovation and adaptation in every component of learning is required in education, both in the competency component, material content, strategy and media, as well as its evaluation. This study emphasized the development of an electronic or digital module in the information behavior course, it is one of the courses regarding the characteristics of the student activity level that accommodates information retrieval and strives to use appropriate information. The e-module design is developed utilize the 4D model by define, design, develop and disseminate. The participants of this research involved media experts, material experts and students of the Library and Information Science study program at two universities, which are are Universitas Pendidikan Indonesia and Universitas Negeri Malang, there are 20 people in total who used e-modules in limited dissemination on information behavior course. This research revealed the electronic module in the course, the emphasis of the module content design which is enriched with digital-based information sources or in another word called as hyper content that becomes a differentiator in presenting the module content, coupled with the power of audio and visual media or called as screencast. Through this research, lecturers able to prepare independent learning materials by utilizing digital technology.

Structure–Activity Relationships of a Negative Allosteric Modulator of the D3 Dopamine Receptor and Investigation of its Binding Site

Dopamine receptors (DARs) are G protein‐coupled receptors (GPCRs) that regulate diverse physiological functions and are involved in the treatment and/or etiology of many neuropsychiatric disorders including schizophrenia and substance use disorder (SUD). DARs are classified as either D1‐like (D1R and D5R) or D2‐like (D2R, D3R, and D4R) based on structural homology and pharmacological profiles. Antagonists of D2‐like DARs are currently used in the therapies for many neuropsychiatric disorders. D3R‐selective antagonists have the potential to be better therapeutics for schizophrenia or SUD as they could attenuate psychotic or drug craving symptoms without the motor side effects frequently produced by D2R‐preferring antagonists. Unfortunately, discovery of subtype‐selective compounds for the D3R and D2R has been challenging due to high sequence homology within the orthosteric binding sites of DARs. However, compounds that modulate receptor activities through interactions with less conserved allosteric sites have the potential to be highly selective. To find highly selective allosteric antagonists of the D3R, we screened the NIH Molecular Libraries Program 400,000+ small molecule library with a D3R‐mediated β‐arrestin recruitment assay. We found that one compound, MLS6357, was selective for the D3R over the D2R and D4R in several functional outputs including β‐arrestin recruitment and G‐protein activation. Radioligand binding and functional assays using closely related GPCRs revealed that MLS6357 has very limited cross‐reactivity with other GPCRs. Additionally, Schild‐type functional assays showed that MLS6357 acts as a purely non‐competitive negative allosteric modulator (NAM) of the D3R. We synthesized and characterized >60 analogs of MLS6357 using iterative medicinal chemistry approaches, which revealed structure–activity relationships and enabled further optimization of the scaffold. These efforts produced analogs that are 10‐fold and 30‐fold more potent than the parent compound in D3R‐mediated β‐arrestin recruitment and G‐protein activation assays, respectively. Moreover, some analogs appear to display functional selectivity for inhibition of G‐protein activation versus inhibition of β‐arrestin recruitment, and vice versa, and some also display inverse agonist activity. To identify the allosteric binding site for the MLS6357 scaffold on the D3R, we utilized various D3R/D2R chimeras, receptor mutants, and molecular modeling techniques to reveal and characterize receptor regions necessary for compound efficacy. Further refinement of the binding pocket for MLS6357 will inform future medicinal chemistry efforts. Ultimately, this novel scaffold may be of benefit as a pharmacological probe or therapeutic lead for D3R‐related pathophysiology.

PENERAPAN MODEL PEMBELAJARAN VALUE CLARIFICATION TECHNIQUE (VCT) PADA PEMBELAJARAN IPS SISWA SEKOLAH DASAR: LITERATUR REVIEW

The purpose of this study is to determine the application of the value clarification technology learning model (VCT) in social studies learning for elementary school students. The research method in this study used documents obtained from previous studies. Sources of library program information are also from a review of previous research that has the same goal. The test in this study was intended to obtain and analyze several VCT learning models in social studies learning for elementary school children. The results of this study include eight articles that were reviewed based on references, research methods, and interventions. The conclusion reached in this study is the Value Clarification Technology (VCT) learning method improves learning outcomes, problem solving skills, aspects of religious values, worship obedience, tolerance, discipline, caring for friends, discussion and having a sense of responsibility to complete tasks correctly. time, imitating the heroism and patriotism of the figures in their environment, and learning motivation in social studies learning for elementary school students.

PENERAPAN MODEL PEMBELAJARAN VALUE CLARIFICATION TECHNIQUE (VCT) PADA PEMBELAJARAN IPS SISWA SEKOLAH DASAR: LITERATUR REVIEW

The purpose of this study is to determine the application of the value clarification technology learning model (VCT) in social studies learning for elementary school students. The research method in this study used documents obtained from previous studies. Sources of library program information are also from a review of previous research that has the same goal. The test in this study was intended to obtain and analyze several VCT learning models in social studies learning for elementary school children. The results of this study include eight articles that were reviewed based on references, research methods, and interventions. The conclusion reached in this study is the Value Clarification Technology (VCT) learning method improves learning outcomes, problem solving skills, aspects of religious values, worship obedience, tolerance, discipline, caring for friends, discussion and having a sense of responsibility to complete tasks correctly. time, imitating the heroism and patriotism of the figures in their environment, and learning motivation in social studies learning for elementary school students.

What's Working?

The role of the school librarian (SL) is evolving to better meet the needs of a school in an increasingly digital learning environment. This case study research of an exemplary district level library program explores what is currently working by examining the valued competencies of SLs and contextual factors that enable strong library programs in 1:1 device settings. The findings suggest that SLs are expected to be change agents, relationship builders, curriculum developers, and creators of virtual library services. Critical contextual factors are district buy-in, rebranding, and an integrated approach to library services. The findings could inform curricular improvements for educator preparation programs and professional developers as well as increase SLs’ understanding of how they can strengthen their own practice and raise administrators’ awareness of the powerful ways they can support the school community.

E-Support for E-Learning: A Tool to Empower Students in Online Courses

E-learning has increased through the years in MLIS programs, a trend that has been intensified during the COVID-19 pandemic. Some students choose to take online classes; others have been required to do so by the pandemic. This raises the question: Are students properly prepared to learn online? For this study, researchers created an E-Learning Guide with resources and tips for e-learning. Several sessions were offered during orientation for incoming graduate students in a Library and Information Science program in the northeast United States. During these sessions, the researchers reviewed the E-Learning Guide. Students were surveyed immediately after the sessions and at the end of the semester to learn what, if any, resources were useful. Based on the results, students appreciated having a synchronous session wherein the researchers reviewed the E-Learning Guide, having specific resources to use for e-learning, and having access to a guide with resources for e-learning.

US Black Maternal Health Advocacy Topics and Trends on Twitter: Temporal Infoveillance Study

BackgroundBlack women in the United States disproportionately suffer adverse pregnancy and birth outcomes compared to White women. Economic adversity and implicit bias during clinical encounters may lead to physiological responses that place Black women at higher risk for adverse birth outcomes. The novel coronavirus disease of 2019 (COVID-19) further exacerbated this risk, as safety protocols increased social isolation in clinical settings, thereby limiting opportunities to advocate for unbiased care. Twitter, 1 of the most popular social networking sites, has been used to study a variety of issues of public interest, including health care. This study considers whether posts on Twitter accurately reflect public discourse during the COVID-19 pandemic and are being used in infodemiology studies by public health experts.ObjectiveThis study aims to assess the feasibility of Twitter for identifying public discourse related to social determinants of health and advocacy that influence maternal health among Black women across the United States and to examine trends in sentiment between 2019 and 2020 in the context of the COVID-19 pandemic.MethodsTweets were collected from March 1 to July 13, 2020, from 21 organizations and influencers and from 4 hashtags that focused on Black maternal health. Additionally, tweets from the same organizations and hashtags were collected from the year prior, from March 1 to July 13, 2019. Twint, a Python programming library, was used for data collection and analysis. We gathered the text of approximately 17,000 tweets, as well as all publicly available metadata. Topic modeling and k-means clustering were used to analyze the tweets.ResultsA variety of trends were observed when comparing the 2020 data set to the 2019 data set from the same period. The percentages listed for each topic are probabilities of that topic occurring in our corpus. In our topic models, tweets on reproductive justice, maternal mortality crises, and patient care increased by 67.46% in 2020 versus 2019. Topics on community, advocacy, and health equity increased by over 30% in 2020 versus 2019. In contrast, tweet topics that decreased in 2020 versus 2019 were as follows: tweets on Medicaid and medical coverage decreased by 27.73%, and discussions about creating space for Black women decreased by just under 30%.ConclusionsThe results indicate that the COVID-19 pandemic may have spurred an increased focus on advocating for improved reproductive health and maternal health outcomes among Black women in the United States. Further analyses are needed to capture a longer time frame that encompasses more of the pandemic, as well as more diverse voices to confirm the robustness of the findings. We also concluded that Twitter is an effective source for providing a snapshot of relevant topics to guide Black maternal health advocacy efforts.

Drawing Random Floating-point Numbers from an Interval

Drawing a floating-point number uniformly at random from an interval [ a , b ) is usually performed by a location-scale transformation of some floating-point number drawn uniformly from [0, 1). Due to the weak properties of floating-point arithmetic, such a transformation cannot ensure respect of the bounds, uniformity or spatial equidistributivity. We investigate and quantify precisely these shortcomings while reviewing the actual implementations of the method in major programming languages and libraries, and we propose a simple algorithm to avoid these shortcomings without compromising performances.

How can natural language processing help model informed drug development?: a review.

ObjectiveTo summarize applications of natural language processing (NLP) in model informed drug development (MIDD) and identify potential areas of improvement.Materials and MethodsPublications found on PubMed and Google Scholar, websites and GitHub repositories for NLP libraries and models. Publications describing applications of NLP in MIDD were reviewed. The applications were stratified into 3 stages: drug discovery, clinical trials, and pharmacovigilance. Key NLP functionalities used for these applications were assessed. Programming libraries and open-source resources for the implementation of NLP functionalities in MIDD were identified.ResultsNLP has been utilized to aid various processes in drug development lifecycle such as gene-disease mapping, biomarker discovery, patient-trial matching, adverse drug events detection, etc. These applications commonly use NLP functionalities of named entity recognition, word embeddings, entity resolution, assertion status detection, relation extraction, and topic modeling. The current state-of-the-art for implementing these functionalities in MIDD applications are transformer models that utilize transfer learning for enhanced performance. Various libraries in python, R, and Java like huggingface, sparkNLP, and KoRpus as well as open-source platforms such as DisGeNet, DeepEnroll, and Transmol have enabled convenient implementation of NLP models to MIDD applications.DiscussionChallenges such as reproducibility, explainability, fairness, limited data, limited language-support, and security need to be overcome to ensure wider adoption of NLP in MIDD landscape. There are opportunities to improve the performance of existing models and expand the use of NLP in newer areas of MIDD.ConclusionsThis review provides an overview of the potential and pitfalls of current NLP approaches in MIDD.

Contributing to HathiTrust on a Smaller Scale

In 2021, the Oklahoma State University Library contributed titles from the Bureau of Indian Affairs in their regional depository library collection to the HathiTrust Digital Library. A coordinated effort, this allowed the university library to expand the mission and outreach of the Federal Depository Library Program and also disseminate information and further education as part of the responsibility of a land-grant institution. Contributing Bureau of Indian Affairs materials enhanced the OSU Library’s role as a preservation partner with the Federal Depository Library Program, supported the state with the importance of Native American tribes in Oklahoma, and complemented the goals of the HathiTrust Federal Documents Collection Framework as a key agency to complete as to a comprehensive collection.

Bring Your Own Story: The Evolution of a Library Program to Celebrate Diverse Voices

The Harriet F. Ginsburg Health Sciences Library at the University of Central Florida College of Medicine collaborated with the college’s Office of Diversity, Equity and Inclusion to enhance its existing diversity programming, created to foster a sense of community throughout the college. Through this partnership, a library-driven idea for an occasional diversity-themed lunch and learn session gained valuable institutional support and transformed into a larger event series. A second related project emerged with a goal of creating a diversity corner for the college. These collaborative efforts have helped the library further its mission to be an inclusive entity within the college and have afforded the library greater programming reach.