Reviewerly/exHarmony huggingface dataset:
Distributed asynchronous measurement system fusion estimation based on inverse covariance intersection algorithm

Authors:
raw_author_name: Taishan Guo
raw_affiliation_string: School of Instrumentation and Electronic, North University of China, Taiyuan, 030051, China
raw_author_name: Mingquan Wang
raw_affiliation_string: School of Instrumentation and Electronic, North University of China, Taiyuan, 030051, China
raw_author_name: Shuyu Zhou
raw_affiliation_string: Academy for Advanced Interdisciplinary Research, North University of China, Taiyuan, 030051, China
raw_author_name: Wenai Song
raw_affiliation_string: School of Software, North University North University of China, Taiyuan, 030051, China

Abstract: For state estimation of multi-source asynchronous measurement systems with measurement missing phenomena, this paper proposes a distributed sequential inverse covariance intersection (DSICI) fusion algorithm based on conditional Kalman filtering method. It is mainly divided into synchronized state space module, local filtering module and fusion estimation module. The missing measurements occurring in the system are modelled and described by a set of random variables obeying a Bernoulli distribution. The synchronized state space module uses a state iteration method to synchronize the asynchronous measurement system at the moment of measurement update and it ensures the integrity of the measurement information. The local filtering module uses a conditional Kalman filtering algorithm for filter estimation. The reliability of the local filtering results is guaranteed because the local estimator designs a method to interact information with the domain sensors. The fusion estimation module designs a DSICI fusion algorithm with higher accuracy and satisfying consistency, which fuses the filtering results provided by each sensor when the relevant information between multiple sensors is unknown. Simulation examples demonstrate the excellent performance of the proposed algorithm, with a 33% improvement in accuracy over existing algorithms and an iteration time of less than 3 ms.
Efficient image restoration with style-guided context cluster and interaction

Authors:
raw_author_name: Yonggui Zhu
raw_affiliation_string: School of Data Science and Intelligent Media, Communication University of China, Beijing, 100024, China
raw_author_name: Ming Meng
raw_affiliation_string: School of Data Science and Intelligent Media, Communication University of China, Beijing, 100024, China

Abstract: Abstract Recently, convolutional neural networks (CNNs) and vision transformers (ViTs) have emerged as powerful tools for image restoration (IR). Nonetheless, they encountered some limitations due to their characteristics, such as CNNs sacrificing global reception and ViTs requiring large memory and graphics resources. To address these limitations and explore an alternative approach for improved IR performance, we propose two clustering-based frameworks for general IR tasks, which are style-guided context cluster U-Net (SCoC-UNet) and style-guided clustered point interaction U-Net (SCPI-UNet). The SCoC-UNet adopts a U-shaped architecture, comprising position embedding, Encoder, Decoder, and reconstruction block. Specifically, the input low-quality image is viewed as a set of unorganized points, each of which is first given location information by the continuous relative position embedding method. These points are then fed into a symmetric Encoder and Decoder which utilize style-guided context cluster (SCoC) blocks to extract potential context features and high-frequency information. Although SCoC-UNet has obtained decent performance for image restoration, its SCoC block can only capture connectivity at points within the same cluster, which may ignore long-range dependencies in different clusters. To address this issue, we further propose a SCPI-UNet based on SCoC-UNet, which leverages a style-guided clustered point interaction (SCPI) block in place of the SCoC block. The SCPI block utilizes a cross-attention mechanism to establish the connections of feature points between different clusters. Extensive experimental results demonstrate that the proposed SCoC-UNet and SCPI-UNet can handle several typical IR tasks (i.e., JPEG compression artifact reduction, image denoising, and super-resolution) and achieve superior quantitative and qualitative performance over some state-of-the-art methods.
Interactive Video Aided Interactional on Students’ Listening Skill

Authors:
raw_author_name: Candraning Prihatini
raw_affiliation_string: English Education Department, Universitas Muhammadiyah Lampung, Kedaton Bandar Lampung

Abstract: This research aimed to investigate the effect of interactive video on students' listening skills of the seventh grade at SMPN 1 Gedung Surian and to know where the better media used interactive or Powerpoint media in teaching listening skills. The research employed a quasi-experimental design with a pre-test post-test control group. The sample of this research consisted of 60 seventh-grade students who were cluster random sampling selected and divided into two groups: experimental group and control group. The experimental group was taught using interactive video, while the control group was taught using conventional methods. Data were collected through a listening test before and after the treatment. The data were analyzed using independent samples t-test. The results showed that the experimental group's mean score (73.67) was significantly higher than the control group's mean score (47.23) with a p-value of 0.000. The findings indicated that the use of interactive video had a positive effect on students' listening skills, and as the result of the mean score of both classes the interactive video was more significant than PowerPoint media. Therefore, it is recommended that English teachers use interactive videos as a teaching method to improve students' listening skills.
PENGARUH PENGGUNAAN KOIL RACING TERHADAP PERFORMA MESIN 4 LANGKAH 125 CC

Authors:
raw_author_name: Valiant Lukad Perdana Sutrisno
raw_affiliation_string: MECHANICAL ENGINEERING EDUCATION PROGRAM
The Faculty of Teacher Training and Education
Sebelas Maret University

Abstract: &lt;p class="abstrak" align="left"&gt;&lt;em&gt;The aims of this study are : (1) To determine the effect of using racing coil on the power generated of 4 step motorcycle 125 cc, (2) To determine the effect of using racing coil on the torque generated of 4 step motorcycle 125 cc. The research method used is experimental. The data of this research was obtained by taking measurements on sample of Honda Blade 125 FI 2014 motorcycle. The independent variables were standard ignition coil and racing ignition coil. The variables were maximum shaft power dan maximum shaft torque measured using a dynamometer. The data obtained were then analyzed using quantitative descriptive techniques by describing in the form of graphs and tables. The result of the study are : (1) The use of racing ignition coil has a higher effect on the power produced. (2) The use of racing ignition coil has a lower&lt;/em&gt; effect on the torque produced.&lt;/p&gt;
EcoSketch: promoting sustainable design through iterative environmental assessment during early-stage product development

Authors:
raw_author_name: Lise Laurin
raw_affiliation_string: EarthShift Global, Hanover, United States
raw_author_name: Elizabeth L. Murnane
raw_affiliation_string: Dartmouth College, Hanover, United States

Abstract: Sustainability has long been a topic of substantial interest the design and human-centered computing communities. With industries increasingly prioritizing climate targets, there is a growing demand for sustainable product design. This paper addresses this need through EcoSketch, a digital tool designed to democratize environmental impact assessments for product designers. Shifting typically retrospective evaluations to the early stages of product development, EcoSketch enables proactive consideration and adoption of sustainable alternatives. Unlike software tailored to environmental scientists, it minimizes the need for specialized training or extensive data inputs. We delve into the development and evaluation of EcoSketch, highlighting its unique features and usability strengths. The paper concludes by discussing design implications and proposing future research avenues to strengthen the intersection of human-computer interaction and sustainable product design, advancing progress on environmental challenges at the systems level.
The impact of servant leadership on team innovative performance: Mediating role of employee innovative behavior

Authors:
raw_author_name: Hui Guo
raw_affiliation_string: Innovation College, North-Chiang Mai University, Chiang Mai, Thailand.

Abstract: This study is aimed at exploring the impacts of servant leadership on team innovation performance, examining the role of employee innovative behavior as a mediator and team innovation atmosphere as a moderator. By conducting a questionnaire survey involving 647 employees from the hotel industry and utilizing structural equation modelling for data analysis. Additionally, the study shows that servant leadership significantly improves employees' innovative behavior, which in turn acts as a mediator between servant leadership and team innovation performance. The team innovation climate was identified as a positive moderator reinforcing the link between service-oriented leadership and employee innovation behavior, as well as employee innovation behavior and team innovation performance. This study provides an incisive view of the beneficial impact of service-oriented leadership on team innovation performance, emphasizing the mediating and moderating role played by employee innovation behaviour and team innovation atmosphere. Based on hotel management, the pursuit of timely and effective responses within an intensely competitive market environment is critical to safeguarding the hotel's competitive standing. To address this challenge, the study offers the following recommendations: the foremost emphasis should be on bolstering employees' innovation capabilities. Second, hotel managers are advised to meticulously select, train, and cultivate leaders with a strong service orientation. Thirdly, enterprise leaders should continually elevate their personal knowledge to provide superior guidance to subordinates.
Utilization of Reading Bags as a Strategy to Improve Reading Habits for Secondary Schools Learners

Authors:
raw_author_name: Tsebe Wilfred Molotja
raw_affiliation_string: Language Unit, Department of Language, Social Sciences, Economics and Management Studies (LSEMS), University of Limpopo, South Africa.

Abstract: The main purpose of this chapter was to investigate the utilization of reading bags to inculcate the love for reading among secondary school learners living in impoverished social settings. A quantitative descriptive cross-sectional design was used to measure the shift in reading strategies after the use of the reading bags strategy to inculcate the love for reading. A total of 155 learners in schools who have interest in the presentations from grade to grade on reading are identified from the Capricorn district in Limpopo province, enlisted for the reading project. The survey with 185 questionnaires on metacognitive reading strategies was applied to collect data. Data were collected in two phases and analysis through using descriptive statistics using the Statistical Package for Social Sciences, version 17. Learners reported a high percentage of 72.3% for global reading strategies, 80.2% for problem-solving strategies and 76.4% for support reading strategies. This study revealed the positive effect of using reading bags to enhance learners' reading habits and develop useful strategies in academic reading.
HIFINet: Examination-Diagnosis-Treatment Hierarchical Feedback Interaction Network for Medication Recommendation

Authors:
raw_author_name: Shangming Yang
raw_affiliation_string: Knowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, North Jianshe Road, Chengdu, 610054, Sichuan, China
raw_author_name: Yun Zhang
raw_affiliation_string: Knowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, North Jianshe Road, Chengdu, 610054, Sichuan, China
raw_author_name: Jiajing Zhu
raw_affiliation_string: Knowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, North Jianshe Road, Chengdu, 610054, Sichuan, China

Abstract: Abstract Medication combination recommendation is critical in clinic, since accurately predicting therapeutic drug can provide essential decision support to physicians. However, current approaches do not consider the multilevel structure of electronic health record (EHR) data or the hierarchical dependencies between multiple visits, leading to suboptimal recommendations. To address these limitations, we propose a novel hierarchical feedback interaction network (HIFINet) to utilize an examination-diagnosis-treatment hierarchical network for modeling the inherent multilevel structure of EHR data. The feedback long short-term memory network called FeLSTM, which is the basic unit of our hierarchical network, performs hierarchical interactions and leverages change information as feedback to propagate forward among different levels. Additionally, HIFINet contains four modules. First, an embedding module is designed to learn the health information representation of patients. Second, a three-layer time-series learning module is employed to capture temporal dependencies within each sequence. Next, a differential feedback interaction module is developed to capture the difference features between visits. Finally, an attention fusion module is used to learn a comprehensive representation of the patient’s health information and to recommend next multiple treatment medications. HIFINet is compared with state-of-the-art approaches on a real-world dataset. The results indicate that HIFINet outperforms other approaches, offering more accurate recommendations.
MGSGA: Multi-grained and Semantic-Guided Alignment for Text-Video Retrieval

Authors:
raw_author_name: Xiaoyu Wu
raw_affiliation_string: State Key Laboratory of Media Convergence and Communication, Communication University of China, No.1 Dingfuzhuang East Street, Beijing, 100024, Beijing, China
raw_author_name: Jiayao Qian
raw_affiliation_string: State Key Laboratory of Media Convergence and Communication, Communication University of China, No.1 Dingfuzhuang East Street, Beijing, 100024, Beijing, China
raw_author_name: Lulu Yang
raw_affiliation_string: State Key Laboratory of Media Convergence and Communication, Communication University of China, No.1 Dingfuzhuang East Street, Beijing, 100024, Beijing, China

Abstract: Abstract In the text-video retrieval task, the objective is to calculate the similarity between a text and a video, and rank the relevant candidates higher. Most existing methods only consider the text-video semantic alignment in the global view. But using mean-pooling to obtain global semantics and simply aligning text and video in the global view may lead to semantic bias. In addition, some methods utilize offline object detectors or sentence parsers to obtain entity-level information in text and video and achieve local alignment. However, inaccurate detection introduces possible errors and such approaches prevent models from being trained end-to-end for retrieval. To overcome these limitations, we propose multi-grained and semantic-guided alignment for text-video retrieval in this paper, which can achieve fine-grained alignment based on video frames and text words, local alignment based on semantic centers, and global alignment. Specially, we explore summary semantics of text and video to guide the local alignment based on semantic centers for we believe that the importance of each semantic center is determined by summary semantics. We evaluate our approach on four benchmark datasets of MSRVTT, MSVD, ActivityNet Captions, and DiDeMo, achieving better performance than most existing methods.
Implementation of Fuzzy K-Nearest Neighbor Method in Dengue Disiase Classification

Authors:
raw_author_name: Aulia Jannah
raw_affiliation_string: Universitas Muhammadiyah Sumatera Utara
raw_author_name: Mulkan Azhari
raw_affiliation_string: Universitas Muhammadiyah Sumatera Utara

Abstract: Dengue hemorrhagic fever (DHF) is a condition brought on by infection with the dengue virus. DHF is a severe illness with hemorrhagic clinical signs that can result in shock and death. One of the four viral serotypes of the genus Flavivirus is responsible for DHF. DHF symptoms include fever, joint pain, red skin patches, and others that are similar to those of other illnesses. So that there are no errors in illness prediction, strong accuracy and accuracy are required when classifying DHF patients or not. The Fuzzy K-Nearest Neighbor (FKNN) method is used in this study to classify dengue sickness in order to obtain the best classification outcomes. In this investigation, k was searched for eight times, with values of 3,5,7,9,11,13,15, and 20. Each K's accuracy statistics are 75.15, 75.16, 77.58%, 79.51%, 85.01%, 78.14%, and 75.20 percent. K = 13, which has an accuracy score of 85.01%, yields the highest accuracy.
Low Communication-Cost PSI Protocol for Unbalanced Two-Party Private Sets

Authors:
raw_author_name: Jingyu Ning
raw_affiliation_string: Software College, Northeastern University, Shenyang 110819, China
raw_author_name: Zhenhua Tan
raw_affiliation_string: Software College, Northeastern University, Shenyang 110819, China

Abstract: Two-party private set intersection (PSI) plays a pivotal role in secure two-party computation protocols. The communication cost in a PSI protocol is normally influenced by the sizes of the participating parties. However, for parties with unbalanced sets, the communication costs of existing protocols mainly depend on the size of the larger set, leading to high communication cost. In this paper, we propose a low communication-cost PSI protocol designed specifically for unbalanced two-party private sets, aiming to enhance the efficiency of communication. For each item in the smaller set, the receiver queries whether it belongs to the larger set, such that the communication cost depends solely on the smaller set. The queries are implemented by private information retrieval which is constructed with trapdoor hash function. Our investigation indicates that in each instance of invoking the trapdoor hash function, the receiver is required to transmit both a hash key and an encoding key to the sender, thus incurring significant communication cost. In order to address this concern, we propose the utilization of a seed hash key, a seed encoding key, and a Latin square. By employing these components, the sender can autonomously generate all the necessary hash keys and encoding keys, obviating the multiple transmissions of such keys. The proposed protocol is provably secure against a semihonest adversary under the Decisional Diffie–Hellman assumption. Through implementation demonstration, we showcase that when the sizes of the two sets are <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"><msup><mn>2</mn><mn>8</mn></msup></math> and <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"><msup><mn>2</mn><mn>14</mn></msup></math> , the communication cost of our protocol is only 3.3% of the state-of-the-art protocol and under 100 Kbps bandwidth, we achieve 1.46x speedup compared to the state-of-the-art protocol. Our source code is available on GitHub: https://github.com/TAN-OpenLab/Unbanlanced-PSI.
Balancing Motivation and Burnout in The Learning of Foreign Languages

Authors:
raw_author_name: Nurul Amirah Khairul Amali
raw_author_name: Irma Wahyuny Ibrahim
raw_author_name: Saidah Ismail

Abstract: Being motivated and experiencing burnout during study is a common occurrence, and there appears to be a number of dimensions in which they are related. Despite having the most sophisticated educational frameworks, students always rely on their own motivation to meet their learning goals and avoid burnout at the same time. However, motivation is the driving force behind learning and can act as a mediator in reducing burnout in students. Hence, this study investigates the balancing motivation and burnout in the learning of foreign languages. A quantitative method is used to explore the relation of motivation and burnout in the learning of foreign languages. The data was collected using a five-point Likert scale survey adapted from (Pintrich & DeGroot, 1990; Campos, et al., 2011). There are four sections in the survey. Section A are items on the demographic profile, Section B are 24 items on motivational factors and Section C are the 16 items on burnout factors. 125 undergraduate students studying French at a public university in Malaysia were selected using purposive sampling to answer the survey. The study found that task beliefs and extrinsic motivation drive learners more than intrinsic motivation. Though students are motivated, they are also found to be burned out. This demonstrates the connection between motivation and burnout. The data evaluated using SPSS further supports this, demonstrating a moderate positive correlation between motivation and burnout. The results indicated a significant pedagogical outcome and issued invaluable aspects and future research exploring the correlation between motivation and burnout in the learning of foreign languages is recommended.
Effects of blockchain technology (BT) on the university librarians and libraries: a systematic literature review (SLR)

Authors:
raw_author_name: Khurram Shahzad
raw_author_name: Shakeel Ahmad Khan
raw_author_name: Abid Iqbal

Abstract: Purpose The objectives of the study were to identify the effects of blockchain technology (BT) on the university librarians, the impact of BT on the university library services and to reveal the challenges to adopt BT in the university libraries. Design/methodology/approach A systematic literature review was applied to address the objectives of the study. Around 25 studies published in peer-reviewed journals were selected to conduct the study. Findings The findings of the study revealed that blockchain technology (BT) has positive effects on the university librarians as it assists them in digital resources management, provision of integrated library services, effective records management and continued professional development. The study also displayed that BT has a positive impact on the university libraries through effective information management, user privacy, collaboration, technological innovation and access control. Results also revealed that technical issues, financial constraints, security problems, skill issues and sociocultural issues created challenges to adopt BT in the university libraries. Originality/value The study has offered theoretical implications for future investigators through the provision of innovative literature on the prospectus and challenges associated with blockchain in the context of librarianship. The study has also provided practical implications for management bodies by offering recommendations for the successful adoption of blockchain in the university libraries. Additionally, a framework has been developed to adopt BT successfully in the university libraries for the delivery of smart library services to library patrons.