Class Library Research Articles

Curricular support, equipment lending, and a defense of evolving classic library services

“All change is not growth, as all movement is not forward.” –Ellen GlasgowThe library field has been dominated by conversations around new initiatives, changes, and ways to update the library field to remain relevant in the contemporary academy. In this article, the authors argue for the impact that recontextualization of extant services and expertise coupled with a mutually beneficial approach to partnerships can have as library's look to evolve their services. A case study about the success of Course Reserves-Equipment Lending at the Georgia Tech Library is provided as illumination, saving 2389 students nearly $420,000 over two years. The authors argue that the future of library success does not depend on stretching into new areas but rather a redefining and reinvestment in existing library services and leveraging truly equitable partnerships to meet contemporary needs.

Application of UVM Methodology to Modeling Precision Digital Signal Processing Devices

The purpose of the article is to analyze the Universal Verification Methodology (UVM) approach and develop its modification for modeling precision digital signal processing devices as part of periodic signal phase meters. The article proposes a partial implementation of UVM techniques and methods based on general-purpose programming languages, which is distinguished by the presence of a subsystem for metrological evaluation of the characteristics of the simulated measuring device, while the UVM approach, implemented in the Accelera class library in the System Verilog language, assumes the presence of a reference response with which comparison is made. Thus, the proposed approach, while preserving the methodological basis of UVM, allows modifying it for use in systems where the reference response is not assumed, since it is the subject of the study.

CyberUnits Bricks: An Implementation Study of a Class Library for Simulating Nonlinear Biological Feedback Loops

Feedback loops and other types of information processing structures play a pivotal role in maintaining the internal milieu of living organisms. Although methods of biomedical cybernetics and systems biology help to translate between the structure and function of processing structures, computer simulations are necessary for studying nonlinear systems and the full range of dynamic responses of feedback control systems. Currently, available approaches for modelling and simulation comprise basically domain-specific environments, toolkits for computer algebra systems and custom software written in universal programming languages for a specific purpose, respectively. All of these approaches are faced with certain weaknesses. We therefore developed a cross-platform class library that provides versatile building bricks for writing computer simulations in a universal programming language (CyberUnits Bricks). It supports the definition of models, the simulative analysis of linear and nonlinear systems in the time and frequency domain and the plotting of block diagrams. We compared several programming languages that are commonly used in biomedical research (S in the R implementation and Python) or that are optimized for speed (Swift, C++ and Object Pascal). In benchmarking experiments with two prototypical feedback loops, we found the implementations in Object Pascal to deliver the fastest results. CyberUnits Bricks is available as open-source software that has been optimised for Embarcadero Delphi and the Lazarus IDE for Free Pascal.

Enhancing the security of web applications through innovative patterns of integration of artificial intelligence

Ensuring the security of digital operations, especially in the areas of e-commerce and financial transactions, remains increasingly relevant. Therefore, the subject of research is the development of a specialized software library. This library aims to improve the security of web applications. The purpose of this study is to develop a software library that uses artificial intelligence and machine learning methods to analyze and improve the level of security of financial transactions. The use of these advanced technologies helps automate the detection of potentially fraudulent or risky transactions, thereby providing a higher level of user protection. The following tasks are solved in the article: analysis of modern methods of processing financial transactions and identification of possible security threats; development of a UML diagram of library classes for processing and analyzing financial transactions; testing and validation of the developed artificial intelligence model for assessing the security of financial transactions on real financial data. Machine learning methods were defined and applied using the scikit-learn library in Python, the algorithms of which are capable of analyzing large volumes of data and identifying potential risks with high accuracy. This ensures effective integration of artificial intelligence technologies. The following results were obtained in the work: the criteria for assessing the riskiness of financial transactions for the identification of potential risks are defined; the program operation algorithm is described, which includes procedures for determining and classifying transaction risks; pseudocode is presented, which illustrates the structure of classes and methods of the model, opening opportunities for its adaptation and scaling; methods of generating test data reproducing realistic scenarios of financial transactions have been developed; an analysis of the results was carried out to assess the effectiveness of the developed model. In conclusion, the results of research and testing allow us to evaluate the model's response to various data and its effectiveness in real conditions, as the work presents examples of processing various types of transactions. In addition, the study presents not only the development and validation of the developed model, but also the prospects of its use on a larger scale, integration with existing web applications.

A Comparative Study on the English Translation of The Travel Dairies of Xu Xiake from the Perspective of Eco-translatology

Chinese classics are one of the representatives of traditional Chinese culture, and translating excellent classics is a way to inherit and spread brilliant Chinese culture. The Travel Dairies of Xu Xiake is of great value, and its two latest English translations, namely The Travels of Xu Xiake translated by Lu Changhuai and Jia Xiuhai and The Travel Dairies of Xu Xiake by Li Weirong et al. (i.e. the version of “Library of Chinese Classics”), are selected. The two translations of its first diary entitled “A Visit to the Tiantai Mountain” and “Tiantai SHAN” respectively are selected as main research objects. Based on the three-dimensional transformations of eco-translatology, the two translations are compared and analyzed in linguistic, cultural and communicative dimensions, and the reasons why the latter is superior to the former are concluded in hopes of providing certain references for the translation of similar Chinese classics, helping more Chinese classics enter the world, and further promoting the improvement of Chinese cultural soft power.

Design and Analysis of a Mobile Automation Testing Framework: Evidence and AI Enhancement from Chinese Internet Technological Companies

This present study mainly describes the implementation and ideas of the mobile automation framework, which supports iOS and Android mobile automation testing technology. This study mainly uses a combination of qualitative and documentary analysis methods, designs some technical architecture diagrams, and writes some open-source code to implement respectively. Meanwhile, The automation code is not made public due to mobile automation security and privacy concerns. The paper is mainly driven by the so file inside Android and the ADB command, while iOS uses some class libraries based on the iOS system. The research framework also uses the Appium framework for encapsulation and research and carries out secondary encapsulation and call based on the internal Appium framework. It is convenient for the internal quality team's automated testing staff to use and execute and improve the efficiency and speed of automated software testing, which is the contribution of this research. Beside, The limitation of this research is that the framework is based on the secondary development and encapsulation of Appium framework, so this study are inevitably some imperfections and bugs that need to be continuously improved and used. Moreover, these contribution results demonstrate that it can combine the businesses of different china internet enterprises to complete. Next, the paper discusses specific cases of mobile automation testing framework and artificial intelligence in mobile framework design and evaluates their effects and impacts. Finally, the paper summarizes the roles and challenges of mobile automation testing framework design and AI enhancement elements and looks ahead to the future.

Implementation of the School Literacy Movement (GLS) for Students of Junior High School (SMP) Al-Azhar 3 Bandar Lampung

School literacy in the context of the School Literacy Movement (GLS) is the ability to access, understand, and use things intelligently through various activities including reading, viewing, listening, writing, and speaking. This research aims to find out and describe how the School Literacy Movement (GLS) is implemented among students and the obstacles they face. In this research, the researcher chose SMP Al-Azhar 3 Bandar Lampung as the place for carrying out the research. This research is descriptive qualitative research, with data collection techniques in the form of observation, interviews, and documentation, and the researcher uses data analysis in the form of source triangulation. Based on the results of this research, it was found that the implementation of the school literacy movement (GLS) at SMP Al-Azhar 3 Bandar Lampung has fulfilled three stages of the chool literacy movement (GLS), namely habituation, development, and learning based on the school literacy movement guidelines in junior high school, which was determined by the Directorate General of Primary and Secondary Education, Ministry of Education and Culture in 2016. Activities at the familiarization stage include opening class (Tadarus Al-Qur’an), daily reading journals, class library media, moving book media, literacy-themed poster media, creating a text-rich environment, alumni donating books to the library, and activities for selecting reading books. The development stage includes opening class (tadarus Al-Qur’an), vocabulary game activities, BBQ activities (Bina Baca Qur’an), tasmi’ activities, activities responding to reading results, and independent reading hours. The learning stage includes opening class (Tadarus Al-Qur’an), vocabulary games, activities responding to reading results, and reading challenge activities. The obstacles faced in implementing the School Literacy Movement (GLS) at SMP Al-Azhar 3 Bandar Lampung include general obstacles and specific obstacles. The general obstacles consist of a lack of literacy-themed collections and inadequate library facilities. This results in a lack of interest in reading in the library, while special obstacles appear in moving book activities. This is due to the lack of supervision carried out by library staff, whose number is still minimal.
 Keywords: implementation, obstacles, school literacy movement (GLS), student

Research on Intelligent Design of Geometric Factor Encoding for Aircraft Engine Turbine Structures

In recent years, with the rapid development of computer technology and artificial intelligence design technology, multiple possible design solutions can be quickly generated by transforming the experience and knowledge of structural design into computer executable rules and algorithms. To achieve intelligent design of aircraft engines, this paper proposes an encoding model for the turbine rotor structure of aircraft engines using geometric encoding technology. The turbine rotor structure of aircraft engines is divided into several units according to geometric similarity types, these units continue to be divided into attribute sets according to their functional types, connection relationships, and material properties. These attribute sets can be encoded using geometric encoding technology. The experiment simulated that these codes, for the point cloud modeling of turbine rotor structure, can be quickly achieved and they combine various algorithms to display the point cloud model of the turbine rotor in the Microsoft Visual studio MFC class library. The results show that by creating geometric codes for the turbine rotor of aircraft engines, it is possible to quickly create and display point cloud models of the turbine rotor structure, laying the foundation for subsequent application of machine learning to solve and find the optimal design solution.

The Role of Libraries in Raising the Efficiency of Students with Special Needs in Academic Performance from The Point of View of Teachers

Purpose: This study explores the role of school libraries in promoting the educational level of students with LDs according to their teachers. The study also aimed to identify the difficulties and obstacles facing students with LDs and teachers that prevent the optimal use of the school library. Method: The descriptive approach was implemented. The participants were 40 teachers from both genders, who were asked to answer questions on the role of the library in enhancing the levels of students with LDs. The questionnaire included 16 questions on three main dimensions. Results and conclusion: The results showed that the students use the library for scientific research, and their goal is to solve scientific problems and complete projects. Teachers noticed that the library does not cover their creative needs and superior talents. The borrowing system does not allow the student to pass more than one book while he is in the library class and the fact that the librarian considers the library’s holdings of books and supplies as one of his responsibilities. Research implications: The study provides appropriate proposals to overcome these difficulties and make school libraries look their best. It also provides some appropriate solutions and suggestions in light of identifying the reality of their use.

Selección y valoración de LIJ para bibliotecas de aula: comparativa entre España, Ecuador y Colombia / Selection and appraisal of LIJ for the library of the class: comparison between Spain, Ecuador and Colombia

The aim of this study comparison is the clarification of the kind of youth and children’s literature in order to create a class library, selected by Spaniards, Colombians and Ecuadorians teachers. Minor differences were observed trough data collection and analysis of one of the activities –“Selection and evaluation of a small library”- of the subject “Didáctica de la Lectura” of UNIR’s MFA in “Didáctica de la Lengua en Educación Infantil y Primaria”, answered by current teachers of Spain, Colombia and Ecuador. Nevertheless, a few particularities are detectable in the selection of certain books, as well as in the reasons to exclude other titles. Putting all the data together, is possible to conclude that the selection of the works is not always guided by rigorous criteria, instead the tradition and the personal experience -which is mutable from class to class- seem to be the leading motivations.

"Navigating Innovation: The Experience of Developing the HydroUz Information and Reference System"

This article discusses the use of the DotSpatial library to develop a desktop GIS in Visual Studio using the C# language. The library provides features like memory management, security and exception handling etc. The class library provides the developer with libraries for web application development, user interface design, database connectivity, network connectivity etc. The article describes the main working functions of the software for the information and reference system HydroUZ

Application of Hierarchical Agglomerative Clustering to Create a Library of Basic Classes of Acoustic Events of the VVER-1000/1200

Application of Hierarchical Agglomerative Clustering to Create a Library of Basic Classes of Acoustic Events of the VVER-1000/1200

High Throughput Microfluidics Platform to Assess Synthetic Lethality and Novel Therapeutic Drug Combinations

Molecularly targeted therapies have reshaped cancer treatment in recent decades; however, not all patient cancers are eligible for or effectively treated by such approaches. In addition, resistance mechanisms (both pre-existing and acquired) limit clinical benefit. To these ends, combination therapies involving targeted agents are increasingly being developed for their potential to induce potent synthetic lethalities, bypass drug resistance, promote durable responses, limit adverse side effects via reduced dosing, and expand treatment options. In the context of acute myeloid leukemia (AML) specifically, several efficacious combination therapies have been approved for specific patient subsets, such as all-trans retinoic acid (ATRA) plus arsenic trioxide in the PML-RARA fusion acute promyelocytic subtype and Midostaurin plus Cytarabine and Daunorubicin in FLT3-mutant AML. Despite the availability of these and other therapies, there remains an unmet need for treatments against AML subtypes lacking actionable driver alterations or for which current therapies are insufficient. A major hurdle limiting novel combination therapy discovery is the sheer combinatorics associated with mixing two or more agents (e.g., screening all possible pairs of 100 drugs in a single cell line requires nearly 5,000 combination experiments). Thus, there is a practical need for methodologies that prioritize test compounds among broad candidate sets and high throughput technologies for rapid and efficient screening. We have developed a combination drug screening workflow that integrates machine learning-based predictions of potentially synergistic compound pairs with a droplet microfluidics-based screening platform. Our physical platform, termed the FlowMatrix, contains a series of nano wells arrayed in a 96 x 96 grid (for 9,216 total wells) in which cells are incubated and compounds delivered via emulsified droplets. To facilitate drug combination screening, the FlowMatrix is loaded column-wise with a 96-element library and subsequently loaded a second time along its rows with either the same or an independent drug library. In our current setup, one FlowMatrix can capture complete data for up to 100 unique drug pairs, which includes control, single-agent, and 4x4 dose combination measurements for each pair. Following multi-day incubation, viability for each well is assessed by the number of live cells imaged with fluorescence microscopy. Combinations with high scoring synergy based on Bliss independence criteria are then pushed to validation and further characterization pipelines. We are currently focused on identifying novel combination therapies for AML. Using small molecule libraries of diverse compound classes and machine learning to prioritize initial screening candidates, we have to-date profiled >8,500 AML cell line-drug combinations in our system. This encompasses >2,900 unique drug combinations profiled in 7 distinct AML cell lines. Among ~270 hits that emerged from these screens are established clinical and preclinical AML combination therapies, in addition to candidates that, to the best of our knowledge, are novel in the context of AML. Strong established hits in our screen include ATR inhibition plus Gemcitabine treatment as well as several combinations involving the BCL-2 inhibitor Venetoclax with chemotherapies (Decitabine and Daunorubicin), Quizartinib, Idasanutlin, and mTOR inhibitors. Thus, we have developed an efficient and cost-effective high throughput drug combinations profiling system that has uncovered candidate therapies that may expand treatment options for patients afflicted by AML.

Fusing logic rule-based hybrid variable graph neural network approaches to fault diagnosis of industrial processes

It is practical that industrial processes are regarded as hybrid systems involving both continuous and discrete variables. Particularly, process discrete variables are usually rather crucial to process normal operations. However, existing data-driven fault diagnosis methods have been rarely applied for industrial processes concerning hybrid system characteristics. In response to this issue, this paper proposes a novel industrial process fault diagnosis approach based on fusing logic rule-based hybrid variable graph neural networks (GNNs) able to learn hybrid variable spatial structures. Therein, continuous variables samples are regarded as learning objects, while logic rule information is utilized to guide the learning process. Specifically, a mixed 0–1 integer linear programming algorithm is used to extract logic rules with fault labels from discrete variable data. Subsequently, a rule classification method is used to classify the logic rules with fault labels into independent and interdependent rule classes which are filed in a rule class library using as the basis for topological connections among data samples. In addition, an edge pruning-based graph optimization is employed to reduce redundant connections of the nodes. It is found that the established hybrid variable GNNs is able to learn the spatial topological structure of hybrid industrial process variables, providing rich heuristic knowledge for process fault classifications so as to effectively improve the fault diagnose performance. Simulation experiments are carried out in an industrial coal gasification process platform and a storage tank systems simulation platform, achieving satisfactory results.

대학 캠퍼스 내에서의 범죄데이터 분석을 통한 취약요소 개선 연구

The aim of this study is to derive the design factors of CPTED through the analysis of crime data on university campuses. Through prior research, campus crime analysis was reflected based on the Routine activity theory, and campus crime data was analyzed from four perspectives: criminal with motivated offender, suitable target, absence of guardians, and matching place and the time of crime.
 First, it is the result of analyzing criminals with motivated offender. There were many crimes by insiders, especially college students, who are members of the school, and sexual assault and violence were committed by outsiders, not by school members. And It has been showed that some violent offenders are under the influence of alcohol.
 Second, in the results of analysis about suitable target, The proportion of victims of insider, such as students and faculty members, accounted for the majority with 97.7% of theft, 97.4% of sexual assault, and 80.8% of violence. In the analysis by gender, men accounted for 51.9% and women 48.1% of theft damage, while women accounted for 97.4% of sexual assault, but men accounted for 76.9% of violence. As a result of the analysis, most of the items damaged by theft were laptops, wallets, and cash that could be easily accessed and moved.
 Third, it is the result of the analysis of the absence of guardians. The state of not protecting the victim or the damaged item was analyzed. The theft was damaged while 93.2 percent were away, and in the case of sexual violence, 76.3 percent had no one to ask for help. However, violence occurred even in situations where 73.1% were around when it occurred. As a result of spatial analysis, theft and sexual assault were common in places such as closed lecture rooms and club rooms without being seen from the outside, and violence was mostly committed in open spaces outside. In terms of CCTV installation, theft occurred more in places where CCTVs were installed than in places where CCTVs were not installed.
 Fourth, in the result of analyzing the place and the time of the crime. As classifying by campus places, crimes occurred in the order of class room(40.1%), living space(15.2%), outdoor space(12.2%), and library(8.1%). As for the total crime time, crimes occurred the most during the afternoon from 12:00 to 6:00 pm, and violence occurred during the night time, which is the time after class.
 Through campus crime data analysis, comprehensive campus security plans are needed to take into account the user needs for security and spatiotemporal risk characteristics, and crime prevention measures should be established through CPTED's strategies.
 It is important to establish crime prevention measures through CPTED strategies and to design them so that they do not go against autonomy, creative studies, and a pleasant natural environment.

Initiating Action Guru SKI dalam Mewujudkan Budaya Literasi di Madrasah Ibtidaiyah Kementerian Agama Kota Banda Aceh

Madrasah Ibtidaiyah teachers have not all realized literacy-based learning. This is because teachers' initiating actions are not all very good, so an in-depth study is needed in this regard. The purpose of this study is to explain the literacy culture of SKI teachers and the initiating action of SKI teachers in shaping literacy culture in Madrasah Ibtidaiyah of the Ministry of Religious Affairs in Banda Aceh. This research is field research with descriptive analysis. The data were obtained from SKI teachers in Madrasah Ibtidaiyah in Banda Aceh. Data were collected by purposive sampling through questionnaires, observations, interviews, and documentation. Data analysis began with reducing data, displaying data, and constructing data interactively. includingThe results of this study show that the literacy culture of SKI teachers in Madrasah Ibtidaiyah is manifested through (1) daily activities, including reading activities 15 minutes before learning and reading the Quran; (2) weekly activities, including literacy every Saturday and Minimoli (Mini Moving Lybrary); (3) semesterly activities, including book summarizing programs, reading camps, book donations, book worms, book presentations, and story telling; and (4) annual activities, including making class libraries and hunting literacy programs. (good) forIn addition, the initiating action of SKI teachers in shaping a culture of literacy in Madrasah Ibtidaiyah of the Ministry of Religious Affairs in Banda Aceh City is divided into 3, namely a score of 50–70 (not good) for as many as 3 SKI teachers; a score of 71–80 (good) for as many as 8 SKI teachers; and a score of 81–100 (very good) for as many as 4 SKI teachers. Initiating action is not influenced by length of service, latest education, or school status but is determined by being responsive, acting independently, and doing more than required.

Upaya Guru Dalam Meningkatkan Budaya Literasi Siswa Di MI Ma'arif NU Manbaur Rohmah Gresik

This study aims to determine literacy activities, obstacles, and efforts made by schools in increasing elementary school students' interest in reading. This study used a descriptive qualitative method with interview and observation data collection techniques. The results of the study show that 2 factors influence literacy culture, namely inhibiting factors and supporting factors. Inhibiting factors include students' lack of interest in reading, the influence of gadgets due to increasingly sophisticated technological developments, lack of awareness from students, and lack of parental involvement in literacy activities. Supporting factors from parents, teachers, and facilities and infrastructure. Efforts made by the teacher in improving literacy culture are making class libraries or reading corners, moving class activities used for literacy once a week, muhadhoro activities which are carried out once a month on the last Friday of the week where children display creations such as speeches and sholawat, Providing tiered pin rewards starting from beetle pins to lions, Providing a representative library and providing 70% fiction books (story books) and 30% non-fiction books.

Implementation of Basic Operations for Sparse Matrices when Solving a Generalized Eigenvalue Problem in the ACELAN-COMPOS Complex

Introduction. The widespread use of piezoelectric materials in various industries stimulates the study of their physical characteristics and determines the urgency of such research. In this case, modal analysis makes it possible to determine the operating frequency and the coefficient of electromechanical coupling of piezoelectric elements of various devices. These indicators are of serious theoretical and applied interest. The study was aimed at the development of numerical methods for solving the problem of determining resonance frequencies in a system of elastic bodies. To achieve this goal, we needed new approaches to the discretization of the problem based on the finite element method and the execution of the software implementation of the selected method in C# on the .net platform. Current solutions were created in the context of the ACELAN-COMPOS class library. The known methods of solving the generalized eigenvalue problem based on matrix inversion are not applicable to large-dimensional matrices. To overcome this limitation, the presented scientific work implemented the logic of constructing mass matrices and created software interfaces for exchanging data on eigenvalue problems with pre- and postprocessing modules.Materials and Methods. A platform was used to implement numerical methods .net and the C# programming language. Validation of the research results was carried out through comparing the values found with solutions obtained in well-known SAE packages (computer-aided engineering). The created routines were evaluated in terms of performance and applicability for large-scale tasks. Numerical experiments were carried out to validate new algorithms in small-dimensional problems that were solved by known methods in MATLAB. Next, the approach was tested on tasks with a large number of unknowns and taking into account the parallelization of individual operations. To avoid finding the inverse matrix, a modified Lanczos method was programmatically implemented. We examined the formats for storing matrices in RAM: triplets, CSR, СSC, Skyline. To solve a system of linear algebraic equations (SLAE), an iterative symmetric LQ method adapted to these storage formats was used.Results. New calculation modules integrated into the class library of the ACELAN-COMPOS complex were developed. Calculations were carried out to determine the applicability of various formats for storing sparse matrices in RAM and various methods for implementing operations with sparse matrices. The structure of stiffness matrices constructed for the same task, but with different renumbering of nodes of a finite element grid, was graphically visualized. In relation to the problem of the theory of electroelasticity, data on the time required to perform basic operations with stiffness matrices in various storage formats were summarized and presented in the form of a table. It has been established that the renumbering of grid nodes gives a significant increase in performance even without changing the internal structure of the matrix in memory. Taking into account the objectives of the study, the advantages and weaknesses of known matrix storage formats were named. Thus, CSR was optimal when multiplying a matrix by a vector, SKS was optimal when inverting a matrix. In problems with the number of unknowns of the order of 103, iterative methods for solving a generalized eigenvalue problem won in speed. The performance of the software implementation of the Lanczos method was evaluated. The contribution of all operations to the total solution time was measured. It has been found that the operation of solving SLAE takes up to 95% of the total time of the algorithm. When solving the SLAE by symmetric LQ method, the greatest computational costs were needed to multiply the matrix by a vector. To increase the performance of the algorithm, parallelization with shared memory was resorted to. When using eight threads, the performance gain increased by 40–50%.Discussion and Conclusion. The software modules obtained as part of the scientific work were implemented in the ACELAN-COMPOS package. Their performance for model problems with quasi-regular finite element grids was estimated. Taking into account the features of the structures of the stiffness and mass matrices obtained through solving the generalized eigenvalue problem for an electroelastic body, the preferred methods for their processing were determined.

Peran Kepemimpinan Transformasional Kepala Sekolah Dalam Progam Gerakan Literasi Sekolah di SMA Negeri 1 Cibungbulang

The school literacy movement (GLS) is an effort made by educational institutions related to increasing the awareness of students to read and write so that they will gain broader knowledge and insights. The purpose of this study was to describe the influence of the school principal's transformational leadership on the school literacy movement at SMA Negeri 1 Cibungbulang, Bogor Regency. The research method used is a type of literature study research. Data collection in this study was obtained by examining and then linking reading sources to problems in the research area with the transformational leadership contributions of school principals to the school literacy movement. The principal of SMA Negeri 1 Cibungbulang has strategies and efforts to support the GLS program, namely making literacy journals, procuring class libraries, geulis trees, class bulletin boards, and literacy ambassadors. The GLS program that is being implemented is able to motivate students to increase their interest in reading, to be able to make good use of time, especially with the Geulis tree program and class madding. Besides reading, students can imagine and be creative in expressing their ideas from something they read. This is proven to be able to eliminate boredom during literacy hours.
 Keywords: School Literacy Movement, Transformational Leadership

Register Tiling for Unstructured Sparsity in Neural Network Inference

Unstructured sparse neural networks are an important class of machine learning (ML) models, as they compact model size and reduce floating point operations. The execution time of these models is frequently dominated by the sparse matrix multiplication (SpMM) kernel, C = A × B , where A is a sparse matrix, and B and C are dense matrices. The unstructured sparsity pattern of matrices in pruned machine learning models along with their sparsity ratio has rendered useless the large class of libraries and systems that optimize sparse matrix multiplications. Reusing registers is particularly difficult because accesses to memory locations should be known statically. This paper proposes Sparse Register Tiling, a new technique composed of an unroll-and-sparse-jam transformation followed by data compression that is specifically tailored to sparsity patterns in ML matrices. Unroll-and-sparse-jam uses sparsity information to jam the code while improving register reuse. Sparse register tiling is evaluated across 2396 weight matrices from transformer and convolutional models with a sparsity range of 60-95% and provides an average speedup of 1.72× and 2.65× over MKL SpMM and dense matrix multiplication, respectively, on a multicore CPU processor. It also provides an end-to-end speedup of 2.12× for MobileNetV1 with 70% sparsity on an ARM processor commonly used in edge devices.