Reviewerly/exHarmony huggingface dataset:
Digital Collaborative Governance of Library in Developing E-Library in the Technical Implementing Unit of Universitas Sebelas Maret’s Library

Abstract: Rapid information technology development leads to temporally and spatially borderless information. Library is required to manage library and information technology-based services innovatively. This research aims to study digital collaborative governance of library in developing e-library in Technical Implementing Unit of Universitas Sebelas Maret (UNS) Library. The research method used was descriptive qualitative. Data collection was conducted using observation, in-depth interview with users, librarians, and IT manager of UNS’ library, and documentation. Data was validated using source triangulation, and data were analyzed using an interactive model. The result shows library activity managed using information technology-based hybrid system, in which the collections were transferred into digital media with online- and offline-based library service. Technical Implementing Unit of UNS Library facilitates the need for smooth and fast internet access, software and hardware are always updated, and socialization about UNS e-library is conducted through website: library.uns.ac.id. Intense collaboration of digital libraries between universities, schools, governmental and private institutions is improved and sustainable. In digital maintenance of library, IT Division of library collaborates with IT Division of UNS Communication Center. Digital collaborative governance of library makes the library services faster, more efficient and systematic.
Shop Drawing Workshop for cadets of Fisheries Mechanization Study Program Sorong Polytechnic of Marine and Fisheries Using Autocad

The lack of competence of Sorong Marine and Fisheries Polytechnic cadets in the field of drawing techniques is one of the causes of the low absorption of graduates in the field of engineering, where the Fisheries Mechanization study program has a curriculum syllabus that is suitable for various engineering industries such as shipbuilding, food processing machinery, ship machinery factories, fishing gear factory, pump factory. While the technical drawing courses taught in the fishery mechanization study program are still limited to manual drawings with paper, as well as tasks in other courses in the form of drawings are also still carried out by manual drawing processes, while technical drawings in industry require accuracy and speed which are difficult to rely on. manual drawing techniques. AutoCad software is one of the computer applications that is considered very effective as a tool in learning and improving students' understanding of technical drawing. Activation of the legal licensed AutoCAD software is expensive, so in this Community Service activity, the AutoCad free Student License activation is carried out, in addition to providing an increase in the soft skills of cadets. The stages of activities in this PKM are: computer inventory in the KP Sorong Polytechnic Computer laboratory, registering the official Autocad student version license for computers in the KP Sorong Polytechnic Computer laboratory, installation &amp; activation of Autocad software on computers in the KP Sorong Polytechnic Computer laboratory, Autocad training for cadets Fisheries Mechanization Study Program KP Sorong Polytechnic, and evaluation of Autocad training for cadets of the Fisheries Mechanization Study Program at KP Sorong Polytechnic. The results achieved are the activation of the AutoCad software with a student license on 34 computers in the computer and telematics lab of the KP Sorong Polytechnic, as well as the improvement in the soft skills of cadets in making shop drawings that can be measured through evaluation, namely as many as 13 cadets passed the training with 8 cadets getting value over 75.
Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) for Predicting the Kinematic Viscosity

Adaptive Neuro-Fuzzy Inference System (ANFIS) andArtificial Neural Network (ANN) for Predicting the KinematicViscosity
General Intelligent Architectures of the Hybrid Neuro-Fuzzy Models

General Intelligent Architectures of the HybridNeuro-Fuzzy Models
S3 Object Storage

.NET applications running on-premises usually store application data – text and binary files, static website assets, etc. – on local or networked file storage. While cloud-based network storage is still a possibility with services such as Amazon FSx for Windows File Server and others, you’ll probably begin using cloud-based object storage with Amazon Simple Storage Service (S3).
Serverless

In our final look at compute options on AWS, we will be working at an even higher level of abstraction. Since the launch of AWS Lambda in November 2014, the term serverless has grown to encompass several domains, and you’ll now find it applied by AWS to additional services that all pre-date the introduction of Lambda. Some of these go back to the earliest days of the AWS Cloud itself – presumably, this is because these services don’t require you to provision and manage infrastructure. As of late 2021, it’s now possible to adopt a serverless approach for
SimVTP: Simple Video Text Pre-training with Masked Autoencoders

This paper presents SimVTP: a Simple Video-Text Pretraining framework via masked autoencoders. We randomly mask out the spatial-temporal tubes of input video and the word tokens of input text and then feed them into a unified autencoder to reconstruct the missing pixels and words. Our SimVTP has several properties: 1) Thanks to the unified autoencoder, SimVTP reconstructs the masked signal of one modality with the help from another modality, which implicitly learns the cross-modal alignment between video tubes and text tokens. 2) SimVTP not only benefits from a high video masking ratio (e.g. 90%) due to the temporal redundancy of video, but also needs a high text masking ratio (e.g. 75%), which is much higher than BERT (e.g. 15%), to achieve optimal performance. This is because the aid of video modality makes text reconstruction less challenging, which thus needs a higher mask ratio to make the pretext harder for useful feature learning. 3) Equipping SimVTP with video-text contrastive learning (VTC) and video-text matching (VTM), which are two commonly used cross-modal training strategies, could further improve the transferable performance significantly. 4) SimVTP is dataefficent, e.g., pre-training only on 10% data of WebVid-2M, SimVTP achieves surprisingly good results (43.8 R@1) on MSRVTT, which is far above recent state-of-the-art methods pre-trained on both CC3M and WebVid-2M. We transfer our pre-trained model to various downstream tasks and achieve superior performance. The codes and models will be released at https://github.com/mayuelala/SimVTP.
Fairness and Explainability: Bridging the Gap Towards Fair Model Explanations

While machine learning models have achieved unprecedented success in real-world applications, they might make biased/unfair decisions for specific demographic groups and hence result in discriminative outcomes. Although research efforts have been devoted to measuring and mitigating bias, they mainly study bias from the result-oriented perspective while neglecting the bias encoded in the decision-making procedure. This results in their inability to capture procedure-oriented bias, which therefore limits the ability to have a fully debiasing method. Fortunately, with the rapid development of explainable machine learning, explanations for predictions are now available to gain insights into the procedure. In this work, we bridge the gap between fairness and explainability by presenting a novel perspective of procedure-oriented fairness based on explanations. We identify the procedure-based bias by measuring the gap of explanation quality between different groups with Ratio-based and Value-based Explanation Fairness. The new metrics further motivate us to design an optimization objective to mitigate the procedure-based bias where we observe that it will also mitigate bias from the prediction. Based on our designed optimization objective, we propose a Comprehensive Fairness Algorithm (CFA), which simultaneously fulfills multiple objectives - improving traditional fairness, satisfying explanation fairness, and maintaining the utility performance. Extensive experiments on real-world datasets demonstrate the effectiveness of our proposed CFA and highlight the importance of considering fairness from the explainability perspective. Our code is publicly available at https://github.com/YuyingZhao/FairExplanations-CFA .
Emerging Technological Advancements for Educational Institutions

The education industry has undergone a dramatic transition; we have entered an era dominated by technology and networks. To sustain business value and impart education effectively in such an environment requires a new perspective on the use of emerging technologies. This chapter explores how educational institutions can leverage emerging technologies such as data analytics, Internet of Things (IoT), cloud and augmented reality (AR)/airtual reality (VR) in education delivery to expand the reach of the university to improve student engagement and retention rates and support employers with competency-based accreditation. In this chapter, we will make references to real-world case studies.
Coverage search for UUV in unknown underwater environments

Aiming at the problem of coverage search for Unmanned Underwater Vehicle (UUV) in unknown underwater environments, this paper proposes South-First (SF) coverage algorithm based on the scanning line. A template-based patrol marking method is proposed to solve the problem of marking obstacles. For the deadlock situation, a backtracking mechanism is established, and the improved A* algorithm is used to plan the escape path from the dead point to the backtracking point. Simulation experiments show that SF algorithm can complete the coverage search of the unknown area, and the generated path have less steering times, which is suitable for UUV coverage search.
Trajectory planning of a manipulator based on the DDPG algorithm

Trajectory planning is one of the key technologies in the manipulator motion system, and the effectiveness of the manipulator as a whole is directly influenced by this technology. Thus, accurate and effective trajectory planning is crucial. In this study, a reinforcement learning system is used to plan a manipulator's trajectory. A trajectory planning of a manipulator based on the deep deterministic policy gradient (DDPG) method, which is easier to converge on than the Actor-Critic (AC) approach, is proposed in order to address the issue that the AC algorithm is difficult to converge on. A guiding reward function is provided in the reward function area to address the issue that the manipulator can't contact the target rapidly due to blind exploration. This can help the manipulator touch the target more quickly. In this paper, a two-degree of freedom manipulator is selected as the experimental object. The obstacle avoidance reward function based on the AC algorithm, the obstacle avoidance reward function based on the DDPG algorithm, and the obstacle avoidance reward function and guiding reward function based on the DDPG algorithm are compared. The findings demonstrate that the DDPG method converges easier than the AC algorithm, and that the directed reward function can help the manipulator avoid obstacles.
Aplikasi Pencarian Showroom Yamaha di Kota Tasikmalaya Berbasis Android Menggunakan Metode Location-Based Service (LBS) dan Framework React Native

The Yamaha Showroom is a place for repairing and selling spear parts. Not all Yamaha showroom locations can be known by the public, both those from the City of Tasikmalaya and those from outside the city. This is due to a lack of information about the Yamaha showroom in Tasikmalaya City. This study aims to build an android-based Yamaha showroom search application as a source of information to find out the location and route to the showroom location in Tasikmalaya City. The application design method involves modeling using UML (Unified Modeling Language) and location-based service (LBS) applied to the Yamaha showroom search application that was built. The results of the research resulted in a Yamaha showroom search application in Tasikmalaya City that can help the community in finding Yamaha showroom locations in Tasikmalaya City. This showroom search application in the city of Tasikmalaya can help show the direction to go. This application provides information about the opening hours and location of the Yamaha showroom. The LBS method applied to this application is for coordinate points that are more accurate and can be used anywhere and anytime by the public and easy to use.
Perancangan Sistem Informasi untuk Estimasi Bobot Daging Sapi Berbasis Android

Calculation of the weight of an animal is very important because in the body of an animal there are many things that can be utilized, one of which is cattle. Therefore, beef cattle weigh the cattle in order to estimate the weight of the beef using a conventional method. However, this use is considered inefficient because the number of scales is very limited and it is not easy to carry around. Therefore, for the process of estimating the body weight of the cattle, it is very important for livestock owners to know the body weight of the cattle. Information System for Estimating Beef Weight Based on Android is designed on Android operating system with minimum API 22 (Lollipop) and target API 26 or 27 (Oreo). For testing the application will be carried out on Asus Zenfone 2 with the Marshmallow version of the Android operating system (API 23). In this case the method used is the Indonesian Winter Formula, namely by measuring the chest circumference and body length. Based on the test results on the design of information systems for estimating the weight of beef based on Android, it can be identified and can be concluded as follows; based on the results of testing and measurements on 5 (five) cows showing an accuracy value of up to 98.75%, and the results of measuring the body weight of the cow depend on the calculation of the length and chest circumference of the cow where the process will greatly affect the calculation results.
Visual Branding : Pemanfaatan FIGMA dalam Perancangan Logo HIMA Akuntansi Universitas Nahdlatul Ulama Kalimantan Timur

Visual branding is an effort to presented and introduced a work (design) to the public or the market. There are many things that must be prepared, including how to process ideas into works. The use of Figma is an option in visualizing the Logo from HIMA Accounting UNU East Kalimantan, besides Figma being online-based and having Cloud Storage, Figma also provides results that are able to compete with other editing applications that require quite high laptop/pc specifications. The convenience provided by Figma makes designers more efficient in terms of time and results. The logo is processed using a practice-based method (Practice Based Research) which uses 3 stages of the creative process from Hawkins: 1) Exploration Stage, 2) Improvisation Stage, 3) Manifestation Stage. The visual branding that is carried out is expected to be able to provide a positive response from the campus community and activities around it later, but it still requires additional introduction efforts in the form of optimizing social media and websites.
Rancangan Aplikasi Sistem Reservasi Tamu Balai Besar Pelatihan Kesehatan Jakarta Kampus Hang Jebat Berbasis Web Dengan Metode Rapid Application Development (RAD)

The Jakarta Health Training Center, the Hang Jebat Campus, is a government agency that operates in the health training center to facilitate room reservations. So far, the Jakarta Health Training Center, the Hang Jebat campus, accepts reservations via telephone, fax, or consumers come directly to the Jakarta Health Training Center, Hang Jebat Campus. The purpose of this research is to build a web-based application program that is expected to have a very important impact in getting accurate and fast information and to design a web-based guest reservation application by making it easier for participants to make room reservations online and can control the number of training participants if it is limited to the maximum. So that the work becomes more effective in terms of time for reservations for both guests and receptionists. The system development method used is the Rapid Application Development (RAD) method. Based on the results of the study, to overcome the problems that exist in the Jakarta Health Training Center, Hang Jebat Campus, from the overall results of this study, it can be concluded that the Application Design of the Guest Reservation System for the Jakarta Health Training Center, Hang Jebat Campus, Guest reservation application at the Jakarta Health Training Center, Campus Hang Jebat is very interesting in terms of appearance because there are several features that are easy for guests and receptionists to understand.
Improved Aerodynamic Coefficient Identification Using Non-Conservative Robust Kalman Smoother

The aerodynamic coefficient identification problem is newly formulated within the framework of linear robust state estimation and effectively solved by using the non-conservative robust Kalman smoother. The proposed algorithm shows the superior and reliable performance over the existing techniques involving various known practical limitations caused by the inherent nonlinearity of the aerodynamics identification problem.
Complexity limitations on one-turn quantum refereed games

This paper studies complexity theoretic aspects of quantum refereed games, which are abstract games between two competing players that send quantum states to a referee, who performs an efficiently implementable joint measurement on the two states to determine which of the player wins. The complexity class $\mathrm{QRG}(1)$ contains those decision problems for which one of the players can always win with high probability on yes-instances and the other player can always win with high probability on no-instances, regardless of the opposing player's strategy. This class trivially contains $\mathrm{QMA} \cup \text{co-}\mathrm{QMA}$ and is known to be contained in $\mathrm{PSPACE}$. We prove stronger containments on two restricted variants of this class. Specifically, if one of the players is limited to sending a classical (probabilistic) state rather than a quantum state, the resulting complexity class $\mathrm{CQRG}(1)$ is contained in $\exists\cdot\mathrm{PP}$ (the nondeterministic polynomial-time operator applied to $\mathrm{PP}$); while if both players send quantum states but the referee is forced to measure one of the states first, and incorporates the classical outcome of this measurement into a measurement of the second state, the resulting class $\mathrm{MQRG}(1)$ is contained in $\mathrm{P}\cdot\mathrm{PP}$ (the unbounded-error probabilistic polynomial-time operator applied to $\mathrm{PP}$).
Efficient tomography of coherent optical detectors

We propose an efficient tomography method to address the reconstruction complexity of any general quantum coherent-optical detectors. By extracting the linear loss from the entire detection system, we obtain the effective positive-operator-valued measure in matrix representations with a much smaller size. We apply this method to reconstruct a typical coherent detector: the weak-field homodyne detector. The method also highlights the effects of linear loss on nonclassical features of coherent optical detectors.Received 14 August 2022Accepted 16 November 2022DOI:https://doi.org/10.1103/PhysRevA.106.L051702©2022 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasQuantum tomographyQuantum Information
Panel Extraction and Plane Background Estimation for Motion Comic Creation of Manga Image

We propose methods of panel extraction and plane background estimation for motion comic creation of a manga image. In the panel extraction, the speech balloon extraction method proposed by the authors is utilized for sharpening a dividing line of the panels. Frequency of use of background techniques is investigated, and it indicates that the frequency of the plane background is high. The targets of the plane background techniques are blank space, solid, and screen tone, and the plane backgrounds is estimated in this paper. In the experiment, recall values of the panel extraction and plane background estimation were 88.6% and 93.5%.
Abstract IA005: Artificial intelligence for breast pathology: Challenges and opportunities (and more challenges!)

Abstract This presentation will review some fundamental aspects of breast pathology, introduce PathAI’s approach to building algorithms for computer vision applications, and highlight some applications where AI has shown capacity to yield clinically-relevant insights from breast cancer specimens. I will also highlight some interesting challenges in breast pathology practice pertinent to intraductal proliferations, and how these challenges are beginning to be addressed in the field of AI. Citation Format: Michael G. Drage. Artificial intelligence for breast pathology: Challenges and opportunities (and more challenges!) [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA005.
Relevance-Based Prediction: A Transparent and Adaptive Alternative to Machine Learning

The authors describe a new prediction system based on relevance, which gives a mathematically precise measure of the importance of an observation to forming a prediction, as well as fit, which measures a specific prediction’s reliability. They show how their relevance-based approach to prediction identifies the optimal combination of observations and predictive variables for any given prediction task, thereby presenting a unified alternative to both kernel regression and lasso regression, which they call CKT regression. They argue that their new prediction system addresses complexities that are beyond the capacity of linear regression analysis but in a way that is more transparent, more flexible, and less arbitrary than widely used machine learning algorithms.