Reviewerly/exHarmony huggingface dataset:
TEASMA: A Practical Approach for the Test Assessment of Deep Neural Networks using Mutation Analysis

Successful deployment of Deep Neural Networks (DNNs), particularly in safety-critical systems, requires their validation with an adequate test set to ensure a sufficient degree of confidence in test outcomes. Mutation analysis, a well-established technique for measuring test adequacy in traditional software, has been adapted to DNNs in recent years. This technique is based on generating mutants that ideally aim to be representative of actual faults and thus can be used for test adequacy assessment. In this paper, we investigate for the first time whether and how mutation operators that directly modify the trained DNN model (i.e., post-training operators) can be used for reliably assessing the test inputs of DNNs. Our results show that these operators, though they do not aim to represent realistic faults, exhibit strong, non-linear relationships with faults. Inspired by this finding and considering the significant computational advantage of post-training operators compared to the operators that modify the training data or program (i.e., pre-training operators), we propose and evaluate TEASMA, an approach based on posttraining mutation for assessing the adequacy of DNNs test sets. In practice, TEASMA allows engineers to decide whether they will be able to trust test results and thus validate the DNN before its deployment. Based on a DNN model`s training set, TEASMA provides a methodology to build accurate DNNspecific prediction models of the Fault Detection Rate (FDR) of a test set from its mutation score, thus enabling its assessment. Our large empirical evaluation, across multiple DNN models, shows that predicted FDR values have a strong linear correlation (R2 >= 0.94) with actual values. Consequently, empirical evidence suggests that TEASMA provides a reliable basis for confidently deciding whether to trust test results or improve the test set of a DNN model.
Graph Anomaly Detection at Group Level: A Topology Pattern Enhanced Unsupervised Approach

Graph anomaly detection (GAD) has achieved success and has been widely applied in various domains, such as fraud detection, cybersecurity, finance security, and biochemistry. However, existing graph anomaly detection algorithms focus on distinguishing individual entities (nodes or graphs) and overlook the possibility of anomalous groups within the graph. To address this limitation, this paper introduces a novel unsupervised framework for a new task called Group-level Graph Anomaly Detection (Gr-GAD). The proposed framework first employs a variant of Graph AutoEncoder (GAE) to locate anchor nodes that belong to potential anomaly groups by capturing long-range inconsistencies. Subsequently, group sampling is employed to sample candidate groups, which are then fed into the proposed Topology Pattern-based Graph Contrastive Learning (TPGCL) method. TPGCL utilizes the topology patterns of groups as clues to generate embeddings for each candidate group and thus distinct anomaly groups. The experimental results on both real-world and synthetic datasets demonstrate that the proposed framework shows superior performance in identifying and localizing anomaly groups, highlighting it as a promising solution for Gr-GAD. Datasets and codes of the proposed framework are at the github repository https://anonymous.4open.science/r/Topology-Pattern-Enhanced-Unsupervised-Group-level-Graph-Anomaly-Detection.
Quantum error correction with an Ising machine under circuit-level noise

Efficient decoding to estimate error locations from outcomes of syndrome measurement is the prerequisite for quantum error correction. Decoding in presence of circuit-level noise including measurement errors should be considered in case of actual quantum computing devices. In this work, we develop a decoder for circuit-level noise that solves the error estimation problems as Ising-type optimization problems. We confirm that the threshold theorem in the surface code under the circuitlevel noise is reproduced with an error threshold of approximately 0.4%. We also demonstrate the advantage of the decoder through which the Y error detection rate can be improved compared with other matching-based decoders. Our results reveal that a lower logical error rate can be obtained using our algorithm compared with that of the minimum-weight perfect matching algorithm.
Decision Support System for Promotion Selection using the Multi Factor Evaluation Process Method

Company PT. ALS is a ground transportation service company that transports passengers between cities and provinces. Buses from PT. ALS has been a mainstay and pride of the community, especially in its timely service in taking passengers to their destination. Promotion at PT. Currently, the ALS assessment process for selecting employee promotions is carried out by supervisors in each division who directly evaluate employee performance. Then in the process of selecting the position of the candidate who has the highest score based on certain criteria who will occupy the required position in accordance with the required criteria. Data calculations are done manually using Microsoft Excel but have not used the computer system optimally. The basis for this research is to help PT. ALS in making a decision in selecting employee promotions. Position is a group of positions that are almost the same in an agency, institution or company. For employees, the results of the assessment can be used as feedback on work performance, so that they have a basis for consideration for planning their career development. This research will be conducted using the Multi Factor Evaluation Process method by processing several criteria for decision making. Meanwhile, on the other hand, the results of this assessment can be used by the company to base decision-making in terms of reward system (compensation), promotion, training and career planning.
Upaya Meningkatkan Hasil Belajar Materi Menggiring dan Mengumpan Menggunakan Pendekatan Permainan Gobak Sodor

The purpose of this study was to improve the learning outcomes of dribbling and baiting the ball using the Gobak Sodor Game Approach for Class VIIB Students of SMPN 10 Mataram. The method used in this research is Action Research which consists of 2 (two) cycles, and each cycle consists of: Planning, Implementation, Observation, and reflection. Based on the results of action research that the Gobak Sodor Game Approach can Improve Learning Outcomes in Herding and Feeding the Ball for Class VIIB Students of SMPN 10 Mataram. Furthermore, the researcher recommends: (1) Teachers who have the same difficulties can apply the Gobak Sodor Game Approach to improve learning outcomes. (2) In order to get maximum results, it is hoped that the teacher will make the Gobak Sodor Game Approach more interesting and varied.
Penerapan Pembelajaran Kooperatif Tipe Nht untuk Meningkatakan Aktivitas dan Hasil Belajar IPA Pokok Bahasan Gaya pada Siswa Kelas IV SD Negeri 41 Mataram

The purpose of this study was to increase learning activities and science learning outcomes in fourth grade students at SD Negeri 41 Mataram, given the low level of student learning activities in that class so that their learning outcomes were far below standard. This type of research is descriptive which means that it describes the data obtained through observation, practice questions and learning achievement tests in each cycle. This research was conducted at SD Negeri 41 Mataram learning 2017 / 2018, with the research subjects being class IV students, totaling 14 students. The research instrument used was Student Worksheets, observations of students and teachers. Retrieval of learning outcomes data using an evaluation test instrument of 15 multiple choice questions and observation sheets to calculate student activity. Analysis of learning outcomes data using individual completeness and classical completeness, so that the average achievement of student learning activities in cycle 1 is 73, and for learning outcomes is 79 while in cycle 2 student learning activities is 96 and for student learning outcomes is 93. So that it can be said that cooperative learning of the Numbered Heads together (NHT) type can increase the achievement and learning activities of class IV students at SD Negeri 41 Mataram in the 2017/2018 academic year.
Impacts of training service quality on student satisfaction and Word-of-mouth in online English training

This article aims at investigate components that comprise training services quality and the impacts of training service quality on student satisfaction and word-of-mouth in online English training. The combined quantitative and qualitative research methods were applied. Data were surveyed from 502 students studying online English programs, mainly at Universities in Ho Chi Minh city. Analytical methods such as cronbach's alpha, exploratory factor analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM) were used to test the quality relationship of online English training services to student satisfaction and student word of mouth. The SPSS and AMOS programs are also used for data analysis. The findings show that the quality of service provided by online English training has a direct influence on student satisfaction. The service quality of online English teaching has an immediate and indirect influence on student word-of-mouth. Student satisfaction has a direct influence on student word of mouth. Moreover, the research points out that service quality of online English training consists of six components: (1) responsiveness; (2) reliability; (3) empathy; (4) assurance; (5) privacy and (6) website design. Based on these findings, some administrative implications for educational administrators are proposed in order to improve the quality of training services toward learner satisfaction, so that they will have positive oral communication from learners, which is the most effective and reliable channel for communication and promotion.
Analisis Mekanisme Kurikulum dan Evaluasi (Aphasia) serta (Diskalkulia) pada Siswa Kelas 1 SDN Sukasari 5 Kota Tangerang

This research uses qualitative research. The data collection technique in this research is by conducting interviews, documentation and observations of class I (a) and I (b) teachers as well as accompanying teachers for children with special needs and school principals. The research was conducted to find out how the mechanism of curriculum and evaluation regarding language/communication difficulties and learning difficulties in mathematics. The method given by the teacher to children with special needs who have language/communication difficulties is the same as other students as well as students who have difficulty learning mathematics. The assessments are given both in terms of academic and non-academic. Assessments are made for children with special needs to see the child's initial abilities, after which the PPI program is made. And in the evaluation process the teacher will review every observation made when students face other difficulties. The conclusions obtained by the researcher are, the curriculum applied by SDN Sukasari 5 Tangerang City is a regular curriculum with a modification of the PPI program. The assessment is carried out before the acceptance of students in the new school year with indications that have been notified to the teacher from the students' parents.
MENGUKUR TINGKAT KEMAPANAN PENERAPAN TEKNOLOGI RADIO FREQUENCY IDENTIFICATION (RFID) DI PERPUSTAKAAN

The implementation of various forms of information technology in the library has been carried out in an effort to meet the diverse needs of library users. One of them is RFID technology. The technology that was originally used in the manufacturing industry has now been used in libraries. Several libraries in Indonesia have implemented this technology since 2007. At this time the libraries were quite familiar with the technology. But the library that applies RFID technology requires a study of the application of this technology. It aims to determine the reliability of the application of RFID technology in the library. In addition to knowing what deficiencies need to be corrected. This article aims to offer a method as a means to measure the level of establishment of a library in applying RFID technology in it. The method offered is with the COBIT framework, or COBIT Framework.
The use of comic strips to improve the student's reading comprehension of narrative text (An Action Research at the Students of English for Teens Program in Language Learning Center)

This research presented the findings of a study aiming to investigate whether comic strips can help students to improve their reading comprehension skills in English. This research was conducted at the English for Teens Program in Language Learning Center with 21 students as the participants. The text in focus was narrative. This research used action research using Kemmis and Taggart's design, which consists of four steps: planning, action, observation, and reflection. The data were collected from observation and tests. The data observation has obtained the teacher and students' teaching and learning reading comprehension activities. Nevertheless, test results were collected from student tests in each cycle. It illustrates that despite some parts that need improvement, using comic strips can improve students' reading comprehension skills in narrative text. The portraits of students' progress in reading comprehension of the narrative text of some cycles show that in the first cycle, only 19% of students could reach the Value of 80 or more as the success criteria. In the second cycle, 100% of students successfully passed the test. Observation data shows that the students were encouraged to learn reading comprehension of narrative text using comic strips in group or individual works. Based on the study results, that comic strip is recommended to implement in other genres, especially narrative text or other language skills.
Latent-Shift: Gradient of Entropy Helps Neural Codecs

End-to-end image/video codecs are getting competitive compared to traditional compression techniques that have been developed through decades of manual engineering efforts. These trainable codecs have many advantages over traditional techniques such as easy adaptation on perceptual distortion metrics and high performance on specific domains thanks to their learning ability. However, state of the art neural codecs does not take advantage of the existence of gradient of entropy in decoding device. In this paper, we theoretically show that gradient of entropy (available at decoder side) is correlated with the gradient of the reconstruction error (which is not available at decoder side). We then demonstrate experimentally that this gradient can be used on various compression methods, leading to a $1-2\%$ rate savings for the same quality. Our method is orthogonal to other improvements and brings independent rate savings.
TimePool: Visually Answer "Which and When" Questions On Univariate Time Series

When exploring time series datasets, analysts often pose "which and when" questions. For example, with world life expectancy data over one hundred years, they may inquire about the top 10 countries in life expectancy and the time period when they achieved this status, or which countries have had longer life expectancy than Ireland and when. This paper proposes TimePool, a new visualization prototype, to address this need for univariate time series analysis. It allows users to construct interactive "which and when" queries and visually explore the results for insights.
Stake Your Claim: Zero-Trust Validator Deployment Leveraging NFTs and Smart Contracts in Proof-of-Stake Networks

We present a novel method for a multi-party, zero-trust validator infrastructure deployment arrangement via smart contracts to secure Proof-of-Stake (PoS) blockchains. The proposed arrangement architecture employs a combination of non-fungible tokens (NFTs), a treasury contract, and validator smart contract wallets to facilitate trustless participation in staking mechanisms. The NFT minting process allows depositors to exchange their capital for an NFT representing their stake in a validator, while the treasury contract manages the registry of NFT holders and handles rewards distribution. Validator smart contract wallets are employed to create a trustless connection between the validator operator and the treasury, enabling autonomous staking and unstaking processes based on predefined conditions. In addition, the proposed system incorporates protection mechanisms for depositors, such as triggered exits in case of non-payment of rewards and a penalty payout from the validator operator. The arrangement benefits from the extensibility and interoperability of web3 technologies, with potential applications in the broader digital ecosystem. This zero-trust staking mechanism aims to serve users who desire increased privacy, trust, and flexibility in managing their digital wealth, while promoting greater decentralization and transparency in the PoS ecosystem.
The ACAC_D Model for Mutable Activity Control and Chain of Dependencies in Smart and Collaborative Systems

With the integration of connected devices, artificial intelligence, and heterogeneous networks in IoT-driven cyber-physical systems, our society is evolving as a smart, automated, and connected community. In such dynamic and distributed environments, various operations are carried out considering different contextual factors to support the automation of collaborative devices and systems. These devices often perform long-lived operations or tasks (referred to as activities) to fulfill larger goals in the collaborative environment. These activities are usually mutable (change states) and interdependent. They can influence the execution of other activities in the ecosystem, requiring active and real-time monitoring of the entire connected environment. Recently, a vision for activity-centric access control(ACAC) was proposed to enable security modeling and enforcement from the perspective and abstraction of interdependent activities. The proposed ACAC incorporates four decision parameters: Authorizations(A), oBligations(B), Conditions(C), and activity Dependencies(D) for an object agnostic access control in smart systems. In this paper, we take a step further towards maturing ACAC by focusing on activity dependencies(D) and developing a family of formal mathematically grounded models, referred to as ACAC_D. These formal models consider the real-time mutability of activities in resolving active dependencies among various activities in the ecosystem. Activity dependencies can form a chain where it is possible to have dependencies of dependencies. In ACAC, we also consider the chain of dependencies while handling the mutability of an activity. We highlight the challenges while dealing with chain of dependencies, and provide solutions to resolve these challenges. We also present a proof of concept implementation of with performance analysis for a smart farming use case.
PressureTransferNet: Human Attribute Guided Dynamic Ground Pressure Profile Transfer using 3D simulated Pressure Maps

We propose PressureTransferNet, a novel method for Human Activity Recognition (HAR) using ground pressure information. Our approach generates body-specific dynamic ground pressure profiles for specific activities by leveraging existing pressure data from different individuals. PressureTransferNet is an encoder-decoder model taking a source pressure map and a target human attribute vector as inputs, producing a new pressure map reflecting the target attribute. To train the model, we use a sensor simulation to create a diverse dataset with various human attributes and pressure profiles. Evaluation on a real-world dataset shows its effectiveness in accurately transferring human attributes to ground pressure profiles across different scenarios. We visually confirm the fidelity of the synthesized pressure shapes using a physics-based deep learning model and achieve a binary R-square value of 0.79 on areas with ground contact. Validation through classification with F1 score (0.911$\pm$0.015) on physical pressure mat data demonstrates the correctness of the synthesized pressure maps, making our method valuable for data augmentation, denoising, sensor simulation, and anomaly detection. Applications span sports science, rehabilitation, and bio-mechanics, contributing to the development of HAR systems.
Influences of some families of error-correcting codes

Binary codes of length $n$ may be viewed as subsets of vertices of the Boolean hypercube $\{0,1\}^n$. The ability of a linear error-correcting code to recover erasures is connected to influences of particular monotone Boolean functions. These functions provide insight into the role that particular coordinates play in a code's erasure repair capability. In this paper, we consider directly the influences of coordinates of a code. We describe a family of codes, called codes with minimum disjoint support, for which all influences may be determined. As a consequence, we find influences of repetition codes and certain distinct weight codes. Computing influences is typically circumvented by appealing to the transitivity of the automorphism group of the code. Some of the codes considered here fail to meet the transitivity conditions requires for these standard approaches, yet we can compute them directly.
Multi-robot Path Planning with Rapidly-exploring Random Disjointed-Trees

Multi-robot path planning is a computational process involving finding paths for each robot from its start to the goal while ensuring collision-free operation. It is widely used in robots and autonomous driving. However, the computational time of multi-robot path planning algorithms is enormous, resulting in low efficiency in practical applications. To address this problem, this article proposes a novel multi-robot path planning algorithm (Multi-Agent Rapidly-exploring Random Disjointed-Trees*, MA-RRdT*) based on multi-tree random sampling. The proposed algorithm is based on a single-robot path planning algorithm (Rapidly-exploring Random disjointed-Trees*, RRdT*). The novel MA-RRdT* algorithm has the advantages of fast speed, high space exploration efficiency, and suitability for complex maps. Comparative experiments are completed to evaluate the effectiveness of MA-RRdT*. The final experimental results validate the superior performance of the MA-RRdT* algorithm in terms of time cost and space exploration efficiency.