Reviewerly/exHarmony huggingface dataset:
Safer Linux Kernel Modules Using the D Programming Language

Since its creation, the Linux kernel has gained international recognition and has been employed on a large range of devices: servers, supercomputers, smart devices and embedded systems. Given its popularity, the security of the kernel has become a critical research topic. As a consequence, a wide range of third party tools were created to detect bugs in its implementation. However, new vulnerabilities are discovered and exploited every year. The explanation for this phenomenon lies in the fact that the programming language that is used for the kernel implementation, C, is designed to allow unsafe memory operations. In this paper, we show that it is possible to incrementally transition the kernel code from C to a memory safe programming language, D, by porting and integrating a device driver. In addition, we propose a series of code transformations that allow the D compiler to reason about the safety of certain memory operations. Our implementation increases the security guarantees of the kernel without incurring any performance penalties.
Impact of Redox Dynamics on Biogeochemical Cycling of Elements in a Changing Environment

Environmental change, particularly the impact of climate change, is having a profound impact on humankind.Rising seas and temperatures, as well as other extreme events, will increasingly impact the biogeochemical cycling of metal(loid)s, nutrients and carbon in terrestrial and aquatic environments.Dynamic redox reactions involving elements such As, C, Cr, Fe, Mn, S, and others play a significant role in controlling biogeochemical cycling and speciation in the environment.How these processes will be impacted in our changing climate is not well understood.For example, how do rising seas, which cause inundation with saline water, affect cycling of redox active elements, carbon, and nutrients?Complexation of carbon with iron-bearing minerals is a major mechanism for carbon retention.Under changing climatic conditions, how will carbon cycling be impacted?This presentation will explore these questions, and others, over a range of spatial and temporal scales using advanced analytical tools.
Diving Deep into Dissertations: Analyzing Graduate Students’ Methodology and Data Practices to Inform Research Data Services and Subject Liaison Librarian Support

We present findings from an exploratory quantitative content analysis case study of 156 doctoral dissertations from Georgia State University that investigates doctoral student researchers’ methodology practices (used quantitative, qualitative, or mixed methods) and data practices (used primary data, secondary data, or both). We discuss the implications of our findings for provision of data support services provided by the Georgia State University Library’s Research Data Services (RDS) Team and subject liaison librarians in the areas of instructional services, data software support and licensing advocacy, collection development, marketing/outreach, and professional development/expansion.
Improved Ability To Study Persuasion Structure Using The Student Teams Achievement Division Learning Model

This study aims to improve students' ability to study the structure of persuasion texts using the Student Teams Achievement Division learning model. The subjects of this study were 25 students of class VIII-A of SMP Negeri 2 Gunungsitoli Utara, totaling 25 students, 8 male students and 17 female students. This study uses a Classroom Action Research model with the implementation procedures of planning, action, observation, and reflection. This research activity was carried out in two cycles using data collection techniques, observation sheets, and assessment sheets. Based on the results of the study, there was an increase in the ability of students to study the structure of persuasion texts using the Student Teams Achievement Division learning model. It can be seen in the results of the first cycle that the lowest value is 43.75, and the highest is 75, with an average value of 57.25. In contrast, the second cycle obtained the lowest value of 56.25 and the highest of 93.75. Based on the study results, it can be concluded that the Student Teams Achievement Division learning model can improve students' ability to study the structure of persuasion texts for class VIII-A students of SMP Negeri 2 Gunungsitoli Utara.
READABILITY OF TEACHING MATERIALS BY STUDENTS OF STABN SRIWIJAYA BASED ON FLESCH FORMULA

As prospective educators, students must have the competence to write good teaching materials. One indicator of good teaching materials is readability in accordance with the level of education of students. This study aims to determine the legibility of teaching materials by students using the Flesch Formula. The research method used is descriptive quantitative with instruments in the form of performance tests as a data collection tool. The results of this study indicate: (1) based on measurements using the Flesch Formula, 24% of teaching materials are in accordance with the specified readability level and 76% of teaching materials are not in accordance with the specified readability level; (2) A total of 17% of teaching materials are included in the category of moderately easy, 4% easy, 31% moderate, 24% quite difficult, 21% difficult, and 3% very difficult; and (3) other factors that cause incompatibility of teaching materials made by students are sentences that are too complex with the number only ranging from 2-7 sentences every 100 words. Therefore, prospective teachers should develop the skills of writing teaching materials well by practicing independently or under the guidance of the lecturer. Institutions can also make policies to deepen the writing of teaching materials for students in existing courses or insert new courses in the curriculum structure.
Lazy Compilation in Classical Planning (Extended Abstract)

Classical planning is a task of finding a sequence of actions that achieve a given goal. One of many approaches to classical planning is compilation into propositional satisfiability (SAT). In this work, we propose a new method that uses lazy compilation into SAT. Different from the standard compilation method, lazy compilation constructs the target propositional formula step by step while the SAT solver is consulted at each step and refinements of the formula are suggested according to SAT solver's answers. The performed experiments pointed out that lazy compilation has the potential to improve the performance of the planners.
Experiential Dialogues: Extended Reality (XR) as an Attentive Means of Listening and Knowing Care Identity.

The research is represented as prototype digital ethnographic artefacts to be experienced in the Magic Leap headset and on mobile devices.The artefacts represent outcomes that were co-constructed during Research through Design (RtD) workshops with care experienced young people.The collaborative workshops enacted generative design research techniques as playful ways of being at the intersections of Applied Theatre and Human-Computer Interaction (HCI).This syncretism elicited novel meaning-making modalities of experience with the participants and lens-based technologies.The next phase of the research extends the participative workshop experience to explore new ways of knowing and understanding the agential and affective affordances of extended reality (XR) technologies with audiences.
Mobile Web-Based Learning Application at Gotong Royong Junior High School

Teaching and Learning activities in gotong royong junior high schools are currently conventional only limited to meetings in schools. The time available for teachers and students to meet face to face in the classroom is very limited, in addition, the process of delivering the material is almost completely carried out in the classroom which causes the delivery of the material to be late, when a student does not enter school, the student will later find it difficult to follow the learning process. therefore, a Mobile Web-Based Learning Application was created at Gotong Royong Junior High School, using the Prototype model system development method, the results of this research are a mobile webbased learning application, it can be concluded that the learning application has been designed and implemented with facilities including downloading materials, assignments or online quiz and student scores.
ADeLA: Automatic Dense Labeling with Attention for Viewpoint Shift in Semantic Segmentation

We describe a method to deal with performance drop in semantic segmentation caused by viewpoint changes within multi-camera systems, where temporally paired images are readily available, but the annotations may only be abundant for a few typical views. Existing methods alleviate performance drop via domain alignment in a shared space and assume that the mapping from the aligned space to the output is transferable. However, the novel content induced by viewpoint changes may nullify such a space for effective alignments, thus resulting in negative adaptation. Our method works without aligning any statistics of the images between the two domains. Instead, it utilizes a novel attention-based view transformation network trained only on color images to hallucinate the semantic images for the target. Despite the lack of supervision, the view transformation network can still generalize to semantic images thanks to the induced “information transport” bias. Furthermore, to resolve ambiguities in converting the semantic images to semantic labels, we treat the view transformation network as a functional representation of an unknown mapping implied by the color images and propose functional label hallucination to generate pseudo-labels with uncertainties in the target domains. Our method surpasses baselines built on state-of-the-art correspondence estimation and view synthesis methods. Moreover, it outperforms the state-of-the-art unsupervised domain adaptation methods that utilize self-training and adversarial domain alignments. Our code and dataset will be made publicly available.
GEOCHEMISTRY AND GEOCHRONOLOGY OF THE SEMARULE SYENITE COMPLEX (SSC) IN SE BOTSWANA

The Semarule syenite is considered to be a peralkaline anorogenic intrusion within the Neoarchean Gaborone Granite Complex in the northern margin of the Kaapvaal Craton.The intrusion is regarded to be rift-related in origin and associated with the Bushveld LIP event.Semarule syenite intrusion is a small multi-phase complex body with five texturally different units.Recent collaborative studies between the British Geological Survey and the Geological Survey of Botswana (now Botswana Geoscience Institute) have identified elevated rare earth elements (REE) values in the Semarule syenite complex.Despite this, its formation, geological setting, crystallization histories and emplacement age are not well understood.This study aims to understand the petrogenesis of the Semarule syenite complex by generating a petrogenetic model for the complex.Henceforth, geochemical, radiogenic isotope, stable isotope and geochronological studies of the complex will be employed in this study to achieve the set objective.The outcome of the study will have impact on understanding the evolution of the syenite complex and the relationship with the high REE contents recorded by previous investigations.The understanding of relationship of high REE contents in the syenite and the evolutionary history of the complex will guide the exploration companies in formulating exploration criteria that might lead to successful discovery of the REE deposit in the study area and possibly other syenite complexes in Botswana.
SAFE TRAFFIC, REFLECTED IN THE DAILY NEWSPAPER CRISANA (2021)

Accidents and informative-preventive materials have always had a special echo in the media, whether we refer to the written press, radio, television or online journalism, arousing the interest of the public eager for fresh and exciting information.&#x0D; This article aims to observe the current importance of safe traffic in a local newspaper during 2021 (until the time of writing this material) and to identify the most interesting news and stories on this topic.&#x0D; The researched materials could be divided into several categories, due to their specificity: information, prevention, accidents and materials related to traffic safety.
Indigenous Student’s Perception of Multimedia Learning as an Approach for Enhancing Reading Comprehension Skills

Reading comprehension is one of the language skills needed in processing the language, especially in comprehending information. Despite its importance, many of the students failed to perform comprehension skills well. Some of the reason was their lack of language proficiency and divergent approaches used by the teachers. Technology has been in favor of teachers and students in teaching practices such as multimedia learning because it has proven to help them in learning the language. Thus, this study aimed to find out indigenous students’ perception of multimedia learning as an approach to enhancing their reading comprehension skills. Besides, the alluring features of multimedia learning have ignited the need to explore its potential in helping indigenous students learn comprehension skills better. This study relied heavily on the questionnaire to obtain comprehensive data from the students’ perspective. The surveys employed four sections that covered attention, motivation, relevance, and satisfaction. The findings showed the students agreed that multimedia learning is an excellent tool in enhancing their reading comprehension skills. Despite that, the students disagree with the use of audio in multimedia learning.
Visual Cryptography Authentication for Locker Systems using Biometric Input

Visual Cryptography is an encryption method that uses visuals to conceal data that can then be decoded visually with the right "key" image.In this method, a hidden picture is split into many "shares," each of which is divided into smaller "parts" based on the variance of its pixels.Identity may be confirmed automatically using a person's unique physiological or behavioural features; this is the field of study known as biometrics.An encrypted and biometrically authenticated locker system is the goal of this project.In order to produce shares that will be divided between the admin database and the user, the fingerprint image of the user is treated as a secret image.The user's identity will be verified by comparing their live fingerprint scan to a synthetic fingerprint created by combining their shares.
A Eunuch in a Harem

Abstract The Abominatron was an unexpected hit at the 1964 Audio Engineering Society (AES) convention, attracting the attention of luminaries and musical heavy-hitters such as Alwin Nikolais, Eric Siday, Lejaren Hiller, and people from the Columbia-Princeton Electronic Music Center. Bob found himself taking orders for modules, something he’d never anticipated. Nikolais and Siday become his first customers. But in the meantime, he needed to roll out the high-end amp (dubbed the PMS-15) because the business had lost $28,000. Tooling up to produce 100, he ended up selling three—a catastrophic end to a two-year project. But success at AES gave him hope and he threw himself into hawking the new equipment, taking an ad in a 1965 AES journal, and attending the Music Teacher’s National Association (MTNA) convention. No sales were secured at the convention, but Bob met George Kelischek, an instrument builder who would become very influential in his life.
Dual-level Hypergraph Representation Learning for Group Recommendation

Group Recommendation (GR) is the task of recommending items for a group of users. Most of existing studies adopt heuristic or attention-based preference aggregation strategies to learn group preferences, which ignores the composition of the group and suffers seriously from the problem of group-item interactions sparsity. In this paper, we propose a new group recommendation model based on Dual-level Hypergraph Representation Learning (called DHRL), which well models the group decision-making process by considering user-item interactions, group-item interactions and group-group interactions. Specifically, we design a member-level hypergraph convolutional network to learn group members’ personal preferences from user-item interactions. We also design a group-level hypergraph convolutional network to capture group preferences with full consideration of both group-item interactions and group-group interactions. Finally, we propose a joint training strategy to ease data sparsity by combining the group recommendation task with the user recommendation task. The experiments demonstrate the effectiveness and the efficiency of our proposed method compared to several state-of-the-art methods in terms of HR and NDCG.
WAZIUP: Open Innovation Platform for IoT-Big Data in Sub-Sahara Africa

ICT developments in Sub-Saharan Africa has the potential to cut across traditional sectors: notable examples are the introduction of micro-health insurance and health-savings accounts through mobile devices; index-based crop insurance; crowd-sourcing to monitor and manage the delivery of public services. These innovative applications recognize and leverage commonalities between sectors, blur traditional lines, and open up a new field of opportunities. The opportunity for ICT intervention in Africa is huge especially of IoT and big data: those technologies are promising a big wave of innovation for our daily life. The era of IoT can connect billions of sensors, devices, equipment, systems. In turn, the challenge is about driving business outcomes, consumer benefits, and the creation of new value. The new mantras for the IoT era is the collection, convergence and exploitation of data. The information collection involves data from sensors, devices, gateways, edge equipment and networks. This information allows increasing process efficiency through automation while reducing downtime and improving people productivity. The WAZIUP project will show:
Explaining Robust Classification Through Prime Implicants

In this paper, we investigate how robust classification results can be explained by the notion of prime implicants, focusing on explaining pairwise dominance relations. By robust, we mean that we consider imprecise models that may abstain to classify or to compare two classes when information is insufficient. This will be reflected by considering (convex) sets of probabilities. By prime implicants, we understand a minimal number of attributes whose value needs to be known before stating that one class dominates/is preferred to another.
VERJava: Vulnerable Version Identification for Java OSS with a Two-Stage Analysis

The software version information affected by the CVEs (Common Vulnerabilities and Exposures) provided by the National Vulnerability Database (NVD) is not always accurate. This could seriously mislead the repair priority for software users, and greatly hinder the work of security researchers. Bao et al. improved the well-known Sliwerski-Zimmermann-Zeller (SZZ) algorithm for vulnerabilities (called V-SZZ) to precisely refine vulnerable software versions. But V-SZZ only focuses on those CVEs of which patches only have deleted lines.In this study, we target Java Open Source Software (OSS) by virtue of its pervasiveness and ubiquitousness. Due to Java’s object-oriented characteristic, a single security patch often involves modifications of multiple functions. Existing patch code similarity analysis does not consider patch existence from the point of view of an entire patch, which would generate too many false positives for Java CVEs. In this work, we address these limitations by introducing a two-stage approach named VERJava, to systematically assess vulnerable versions for a target vulnerability in Java OSS. Specifically, vulnerable versions are calculated respectively at a function level and an entire patch level, then the results are synthesized to decide the final vulnerable versions. For evaluation, we manually annotated the vulnerable versions of 167 real CVEs from seven popular Java open source projects. The result shows that VERJava achieves the precision of 90.7% on average, significantly outperforming the state-of-the-art work V-SZZ. Furthermore, our study reveals some interesting findings that have not yet been discussed.
Kemampuan Membaca Memahami Teks Bahasa Jerman

Abstract. The purpose of this research was to determine the level of ability to read and understand German texts for students of class XI MIPA 3 of SMA Negeri 1 Tolitoli. This research uses a descriptive method. For data collection, a written test was used. The test consists of multiple choice, matching test and true-false test. Furthermore, the data were analyzed by using the percentage technique. The population in this study were all students of class XI MIPA at SMA Negeri 1 Tolitoli which consisted of 5 classes with 180 students. The sample of this study was the students of class XI MIPA 3 as many as 26 students who were selected using random sampling. The results of this study indicate that the ability to read and understand German texts in class XI MIPA 3 SMA Negeri 1 Tolitoli is in the good category (80.5%).
Autonomous driving with safe reinforcement learning using rule-based judgment

Reinforcement learning (RL) in safety critical domains like autonomous driving requires safe exploration, but conventional safe reinforcement learning methods have low performance at the initial stage of learning. In this paper, we present a RL method that selects action using independent Q-functions on rule-based policy and RL policy to address this issue. In our method, Q-function on rule-based policy is pre-trained using offline data and Q-function on RL policy is initialized randomly. Our method selects action by comparing both Q-functions and increases probability of selecting rule-based action at initial stage of learning. We conduct experiments on driving lane selection task, and find that our approach can improve performance at the initial stage of learning.
Heterogeneous Data-Centric Architectures for Modern Data-Intensive Applications: Case Studies in Machine Learning and Databases

Today's computing systems require moving data back-and-forth between computing resources (e.g., CPUs, GPUs, accelerators) and off-chip main memory so that computation can take place on the data. Unfortunately, this data movement is a major bottleneck for system performance and energy consumption [1], [2]. One promising execution paradigm that alleviates the data movement bottleneck in modern and emerging applications is processing-in-memory (PIM) [2]–[12], where the cost of data movement to/from main memory is reduced by placing computation capabilities close to memory. In the data-centric PIM paradigm, the logic close to memory has access to data with significantly higher memory bandwidth, lower latency, and lower energy consumption than processors/accelerators in existing processor-centric systems.
PENGABDIAN KEPADA MASYARAKAT PELATIHAN PEMANFAATAN TEKNOLOGI INFORMASI INTERNET DAN WEB GOVERMNET BAGI APARATUR DESA

Technology is a form of development. All humans on earth are forced to open their eyes to technological changes that are so fast and affect all aspects of life. Inpres no 3 of 2003 formulated that the goal of e-Government development is an effort to develop (using) electronic-based governance in order to improve the quality of public services effectively and efficiently. Training on the use of Information Technology for the Pekon apparatus in Pringsewu Regency will provide additional knowledge regarding the functions and benefits of implementing e-government.