Reviewerly/exHarmony huggingface dataset:
Exploring Text Decoding Methods for Portuguese Legal Text Generation

In recent years, there has been considerable growth in the volume of legal proceedings in Brazil. In this context, there is a lot of potential in using recent advances in Natural Language Processing to automate tasks and analysis in the legal domain. In this article, we investigate text decoding methods for automating the writing of keyphrases, a sequence of key terms present in documents used in courts throughout Brazil. For this purpose, a text-to-text framework based on generative Transformers is used to generate keyphrases and evaluate three decoding techniques: greedy, top-K, and top-p. Since the keyphrases are designed to improve retrieval tasks, we evaluated keyphrases generated by the decoding methods in legal document retrieval. Traditional retrieval methods (TF-IDF and BM25) were used to evaluate the quality of the generated keyphrases. The results obtained (in terms of IR metrics) were statistically significant, and they indicate that greedy decoding generates high-quality keyphrases for the dockets used in this work, providing keyphrases close to the ones generated by human specialists.
Information Technology Development in Alumni Search: Validity Analysis

Alumni data collection activities as material for recapitulating the data needed as the completeness of accreditation documents and performance evaluation documents for tertiary institutions. This will not be achieved if the data collection is still using manual methods such as contacting the graduates one by one. This activity will take up time and the data that has been collected so far is not optimal. The purpose of conducting this research is to develop information technology in tracing graduates using the Google form at the product validity testing stage. This research is development research using 4D models. The validation test was carried out at the development stage, for this reason, the research was limited to the product development phase only. The instrument used for the validation test is in the form of a validity questionnaire for the product being developed. Questionnaires will be distributed and then the product will be validated based on the statements that have been prepared beforehand. The validators who validate the product are 4 expert lecturers. The assessment is carried out based on material aspects and media aspects. The results of product research developed with an information technology approach are in the valid category. Not until this stage, the product that has been declared valid, then revised again based on suggestions by experts. It is hoped that after obtaining validation data for the product, the next step is to carry out practicality tests and effectiveness tests so that the product can be disseminated and can be used in education, especially in the graduate study tracer at the Department of Automotive Engineering FT-UNP
A powerful heuristic method for generating efficient database systems

Heuristic functions are an integral part of MapReduce software, both in Apache Hadoop and Spark. If the heuristic function performs badly, the load in the reduce part will not be balanced and access times spike. To investigate this problem closer, we run an optimal database program with numerous different heuristic functions on database. We will leverage the Amazon elastic MapReduce framework. The paper investigates on general purpose, implementation, and evaluation of heuristic algorithm for generating optimal database system, checksum, and special heuristic functions. With the analysis, we present the corresponding runtime results. For the coding part, the records counting part is hasty and can only work for local Hadoop part, it can be debugged and optimized for general purpose implement on Hadoop and Spark and turn into an effective performance monitor tool. As mentioned before, there are strange issue, also the performance of BLAKE2s is unexpectedly slow in that it’s widely accepted the performance of BLAKE2s is much better than MD5 and SHA256, we would like to figure out why the common-sense performance of heuristics is deferent from what we got in distributed frameworks.
Multi-view fusion-based local-global dynamic pyramid convolutional cross-tansformer network for density classification in mammography

Abstract Object. Breast density is an important indicator of breast cancer risk. However, existing methods for breast density classification do not fully utilise the multi-view information produced by mammography and thus have limited classification accuracy. Method. In this paper, we propose a multi-view fusion network, denoted local-global dynamic pyramidal-convolution transformer network (LG-DPTNet), for breast density classification in mammography. First, for single-view feature extraction, we develop a dynamic pyramid convolutional network to enable the network to adaptively learn global and local features. Second, we address the problem exhibited by traditional multi-view fusion methods, this is based on a cross-transformer that integrates fine-grained information and global contextual information from different views and thereby provides accurate predictions for the network. Finally, we use an asymmetric focal loss function instead of traditional cross-entropy loss during network training to solve the problem of class imbalance in public datasets, thereby further improving the performance of the model. Results. We evaluated the effectiveness of our method on two publicly available mammography datasets, CBIS-DDSM and INbreast, and achieved areas under the curve (AUC) of 96.73% and 91.12%, respectively. Conclusion. Our experiments demonstrated that the devised fusion model can more effectively utilise the information contained in multiple views than existing models and exhibits classification performance that is superior to that of baseline and state-of-the-art methods.
Highly efficient and pure few-photon source on chip

We report on multiphoton statistics of correlated twin beams produced in a periodic poled microring resonator on thin-film lithium niobate. Owing to high-cavity confinement and near-perfect quasi-phase-matching, the photon pairs are produced efficiently in single modes at rates reaching 27 MHz per $\text{\ensuremath{\mu}}\mathrm{W}$ pump power. By using a pump laser whose pulse-width impedance matches with the cavity, those photons are further created in single longitudinal modes with purity reaching 99%, without relying on later-on filtering. With a dual-channel photon-number-resolving detection system, we obtain directly the joint detection probabilities of multiphoton states up to three photons, with high coincidence to accidental contrast for each. Used as a single-photon source, it gives heralded ${g}_{H}^{(2)}(0)$ around 0.04 at a single-photon rate of 650 kHz on chip. The findings of our research highlight the potential of this nanophotonic platform as a promising platform for generating nonclassical, few-photon states with ideal indistinguishability, for fundamental quantum optics studies and information applications.
Universal device for two-qubit entangled measurements via photonic quantum walks

Sophisticated positive-operator-valued measures (POVMs) are fundamental to obtain a quantum advantage in many informational problems but are difficult to implement. We design a universal measurement device composed of cascaded quantum-walk modules able to realize arbitrary entangled POVMs on two qubits. Only parameters in the modules need reprogramming for different POVMs. We apply our device to the task of direction guessing, realizing nine different five-outcome entangled measurements (fidelities above 0.9850) via nine-step photonic quantum walks, recovering optimal direction guessing from nonideal input states. Our work marks an important step toward building a universal versatile quantum measurement device able to implement optimal measurements for various quantum information tasks.
Five Steps for Personalizing Your Website

Nonprofit Communications ReportVolume 21, Issue 11 p. 4-4 Website Design Essentials Five Steps for Personalizing Your Website First published: 11 October 2023 https://doi.org/10.1002/npcr.32271Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume21, Issue11November 2023Pages 4-4 RelatedInformation
PENGARUH MODEL TALKING STICK TERHADAP HASIL PEMBELAJARAN MENYIMAK TEKS TANGGAPAN

The Effect of Talking Stick Model to Learning Result of Listening Response Text Students Class IX SMPI Athirah Bukit Baruga aims to: (1) describe the results of studying to listening response text before use the talking stick model Class IX SMPI Athirah Bukit Baruga; (2) describe the results of studying to listening response text after use the talking stick model Class IX SMPI Athirah Bukit Baruga; and (3) proving the impact of the use a talking stick model has on the results of studying to listening response text Class IX SMPI Athirah Bukit Baruga. This research is kind of quantitative research. The research design was in One Group Pretest-Posttest Design. Data analysis shows that: (1) the results of studying to listening response text before use the talking stick model Class IX SMPI Athirah Bukit Baruga is categorized less with an average of 56.068; (2) the results of studying to listening response text after use the talking stick model Class IX SMPI Athirah Bukit Baruga are categorized sufficiently with an average of 74.781; (3) Hypothetical tests results show that the value of sig (2-tailed) is 0,000 &lt; 0.05. So, the conclusive is there is an average value difference from learning listening responses text to pretest and posttest. Therefore, accepted hypothesis is be found effect on the use talking stick model on results listening response text Class IX SMPI Athirah Bukit Baruga.
Assessment of Elemental Composition of Kaolin from Kankara and Dutsinma Mine Sites, Katsina State, Nigeria

This research aimed to assess the health hazards associated with heavy metals contamination around Kankara and Dutsinma Kaolin mining sites. The analysis was done by using Energy Dispersive X-ray Fluorescence (EDXRF) at the Central Laboratory, Umaru Musa Yar-adua University, Katsina. In which health hazards were evaluated. using numerous Statistical and United States Environmental Protection Agency (USEPA) models. Thirty nine (39) different elements were analyzed using the most associated environmental and health risk of priority in which seven (07) of them are heavy metals of interest; Among them are: Nickel (Ni), Copper (Cu), Zink (Zn), Thallium (Ti), Chromium (Cr), Lead (Pb), and Arsenic (As), with an average concentrations of 20.02, 12.59, 54.03, 1344.4, 21.94, 140.00, and Not Available Value (NA) in the studied area. The Values obtained for overall hazard index (HI) are within the accepted values by (USEPA) which indicates no cancer risk for both adults and Children. While the overall excess lifetime cancer risk for a heavy metal was 8.5555E-06 (a maximum of 9 people per 1 million may be affected) for children and 7.5773E-05 (a maximum of 8 people per 1 million may be affected) for adults.
MOTIVATION OF A RURAL TEACHER TO IMPLEMENT THE TECHNOLOGY OF EDUCATIONAL ACTIVITY

The article presents the results of one of the stages of the research on scientifically qualified work. Determining the level of motivation, desire for professional growth, further self-education and self-development of a rural teacher in postgraduate professional activity is one of the most important tasks today. This will help to understand the main reasons for the loss of interest in their professional activities among teachers, identify the main motives and develop further work on training and maintaining the creative potential of teachers. In achieving the goals of this stage of the study, a whole range of scientific methods was used: surveys, conversations, analysis and synthesis of tests conducted according to various methods of outstanding educational psychologists. The results were summed up, the main needs and desires of teachers for further self-development were determined. Conclusions and recommendations are formulated to increase the interest and motivation of teachers to implement the technology of educational activities. The results may be of interest to heads of general education institutions, advanced training courses and institutes of continuing profes- sional education.
Evaluating the impact on health outcomes of an event that resulted in a delay in contact tracing of COVID-19 cases in England, September 2020: an observational study

Objective In September 2020, 15 861 SARS-CoV-2 case records failed to upload from the Second Generation Surveillance System (SGSS) to the Contact Tracing Advisory Service (CTAS) tool, delaying the contact tracing of these cases. This study used CTAS data to determine the impact of this delay on population health outcomes: transmission events, hospitalisations and mortality. Previously, a modelling study suggested a substantial impact. Design Observational study. Setting England. Population Individuals testing positive for SARS-CoV-2 and their reported contacts. Main outcome measures Secondary attack rates (SARs), hospitalisations and deaths among primary and secondary contacts were calculated, compared with all other concurrent, unaffected cases. Affected SGSS records were matched to CTAS records. Successive contacts and cases were identified and matched to hospital episode and mortality outcomes. Results Initiation of contact tracing was delayed by 3 days on average in the primary cases in the delay group (6 days) compared with the control group (3 days). This was associated with lower completion of contact tracing: 80% (95% CI: 79% to 81%) in delay group and 83% (95% CI: 83% to 84%) in control group. There was some evidence to suggest increased transmission to non-household contacts among those affected by the delay. The SAR for non-household contacts was higher among secondary contacts in the delay group than the control group (delay group: 7.9%, 95% CI: 6.5% to 9.2%; control group: 5.9%, 95% CI: 5.3% to 6.6%). There did not appear to be a significant difference between the delay and control groups in the odds of hospitalisation (crude OR: 1.1 (95% CI: 0.9 to 1.2)) or death (crude OR: 0.7 (95% CI: 0.1 to 4.0)) among secondary contacts. Conclusions Our analysis suggests that the delay in contact tracing had a limited impact on population health outcomes; however, contact tracing was not completed for all individuals, so some transmission events might not be captured.
Multi3Generation: Multitask, Multilingual, and Multimodal Language Generation

<ns3:p>The purpose of this article is to highlight the critical importance of language generation today. In particular, language generation is explored from the following three aspects: multi-modality, multilinguality, which play crucial role for NLG community. We present the activities conducted within the Multi3Generation COST</ns3:p><ns3:p> Action (CA18231), as well as current trends and future perspectives for multitask, multilingual and multimodal language generation.</ns3:p>
Pengaruh Limbah Industri Tahu Terhadap Kualitas Air Sungai Berdasarkan Parameter Biochemical Oxygen Demand, Chemical Oxygen Demand, Total Suspended Solid (Studi Kasus Industri Tahu di Dusun Janten, Ngestiharjo, Kasihan, Bantul)

This research aims to evaluate the influence of wastewater treatment plant (WWTP) outlets on the water quality of the Kalibayem River in the Dusun Janten, Ngestiharjo, Kasihan, Bantul area. The research method employed involved collecting river water samples from points before and after the WWTP outlets, as well as analyzing water quality parameters such as BOD, COD, and TSS. The research findings indicate that the WWTP outlets have a significant impact on the water quality of the Kalibayem River. After undergoing treatment processes at the WWTP, there was a reduction of 0.85% in BOD, 1.28% in COD, and 62% in TSS levels in the river water. Thus, the results of this study demonstrate that the WWTP outlets of the tofu industry do not have a significant impact on pollution in the Kalibayem River in the Dusun Janten, Ngestiharjo, Kasihan, Bantul area. This means that the WWTP has been successful in reducing pollution loads and maintaining the water quality of the river. The implications of this research can be used as a reference for managing and controlling industrial waste and preserving the sustainability of the river ecosystem in that area.
Ensemble Learning Approach to Chatbot Design Based on Paraphrase Detection

In this paper, we present a design for an ensemble chatbot based on paraphrase detection. Our proposed chatbot is intended to assist companies in reducing the need for costly call center operations by providing a 24-hour service to customers seeking information about products or services. Our algorithm is designed to work effectively on small data sets, such as an existing FAQ, and does not require a large number of instances. We evaluated the performance of our chatbot using publicly available data from the websites of major telecommunication companies and found that the ensemble model improved success rates by 6% compared to the single best model, with a top 3 accuracy of 84.54% and a top 1 accuracy of 70.10%.
Translation of Substitution and Ellipsis by Professional Translators and Translators in Training: A Contrastive Study

Creating a coherent and logically connected text requires the effective use of cohesive devices. Accurate translation of cohesive devices is essential to preserve the intended meaning of the original text. The present study investigates errors made by professional translators and novice translators when translating substitution and ellipsis from English into Arabic. Specifically, the study aims to answer the research question: What are the errors made by professional translators and translators in training when translating substitution and ellipsis? To gather data, the researcher conducted a survey and included a sample of both professional translators and translators in training. The results show that both groups had difficulty accurately translating substitution and ellipsis. The most prevalent errors included preserving the English sentence structure, omitting the cohesive device entirely, and modifying the meaning of the original text. Notably, both groups found identifying and translating ellipses particularly challenging, which led to errors in the final translation. Experienced translators produced higher quality translations than novice translators, indicating the significant impact of experience on the translation process. Based on the findings, the study recommends providing targeted training on cohesive devices through practical exercises to improve accuracy and offer more opportunities for practice in a supportive environment. Addressing these challenges can enhance the quality of translations and preserve the meaning of the original text.
U-Net Based Single Image Deraining Using the Wavelet Residue Channel Fusion Strategy

Single image deraining aims to reconstruct a clean rain-free background image from a single image deteriorated by rain streaks and rain accumulation. However, actual rain streaks have various densities, shapes, and directions, so it is not easy to decompose rainy image into a clean background layer and rain steaks layers. This paper proposes an U-Net based single image deraining network using the wavelet residue channel fusion strategy. The proposed residue channel is computed in wavelet low-frequency domain to learn enough background information, and combined with four wavelet subbands in fusion block, allowing them to take advantage of their respective strengths. To extract the main features for rain removal, we propose the extraction module based on LSTM and SE_Res. Furthermore, we present an encoder-decoder subnetwork based on U-Net structure to capture multiscale information of rain steaks. To evaluate the performance of the proposed network, experiments were performed on widely used benchmarks, and the results show that our method outperforms some popular single image deraining methods.
Creative Approach in Teaching CEFR Reading Comprehension Using Bubble Map and Tree Map Method

In Malaysian secondary schools, the dynamic tool of teaching CEFR reading comprehension is to give students a greater exposure and increase their motivation in conducive learning environment. The topmost objective of this study is to investigate whether the use of Bubble Map and Tree Map method improves students’ learning of open ended and cloze test questions in the CEFR reading comprehension framework. For this purpose, the researcher employed a quasi-experimental design with a sample of 105 Form One students (13 years old) from three different schools (school A, B and C) from Petaling Jaya, Selangor. Three groups of students were taken as intact groups to fulfill the requirement of this study. All the three groups were comprised with equal participants (35 students in each group). The Experimental Group 1 (EG1) from school A was taught using Bubble Map, Experimental Group 2 (EG2) from school B was taught using Tree Map and the Control Group (CG) from school C was taught using conventional method. In order to collect the data, the researcher administered pre-test and post-test (instruments for this study). First, the quantitative data was analyzed using MANCOVA test and Tukey HSD (SPSS program for Windows version 26). The findings from the MANCOVA test demonstrated that EG1 (using Bubble Map) significantly outperformed EG2 and CG in answering open ended comprehension questions and the cloze test questions. The results of Tukey HSD also indicated that EG2 (using Tree Map) performed significantly better than CG (using conventional method) in answering the open ended and the close test comprehension questions. This study has crucial pedagogical implication because it revealed that utilizing Bubble Map and Tree Map methods can enhance students CEFR reading comprehension. As such, teachers can use Bubble Map and Tree Map method as an alternative method to teach CEFR reading comprehension in the ESL classroom.
Adaptive IQ and IMQ-RBFs for Solving Initial Value Problems: Adams–Bashforth and Adams–Moulton Methods

In this paper, our objective is primarily to use adaptive inverse-quadratic (IQ) and inverse-multi-quadratic (IMQ) radial basis function (RBF) interpolation techniques to develop third and fourth-order methods such as Adams–Bashforth (AB) and Adams–Moulton (AM) methods. By utilizing a free parameter involved in the RBF, the local convergence of the numerical solution is enhanced by making the local truncation error vanish. Consistency and stability analysis is presented along with some numerical results to back up our assertions. The accuracy and rate of convergence of each proposed technique are equal to or better than the original AB and AM methods by eliminating the local truncation error thus in that sense, the proposed adaptive methods are optimal. We conclude that both IQ and IMQ-RBF methods yield an improved order of convergence than classical methods, while the superiority of one method depends on the method and the problem considered.