Reviewerly/exHarmony huggingface dataset:
New media art design based on fast visual segmentation and 3D image processing

Acquiring innovative styles and compositions from intricate and heterogeneous artistic imagery has emerged as a pivotal research quandry within contemporary new media art image conception. In a concerted effort to adeptly distill the quintessence of artistic styles and elements embedded within these visuals, an innovative methodology is posited herein, underpinned by an enhanced U-net segmentation framework and harmoniously fused with the surface extraction image reconstruction algorithm. This meticulous amalgamation endeavors to attain accurate segmentation and tridimensional reconstruction of the artistry encapsulated in these images. Primarily, the imagery is meticulously partitioned, culminating in an output that artfully encapsulates the inherent artistic attributes. Subsequently, this segmentation outcome is adeptly reconstituted, bestowing form to a three-dimensional artistry model. Empirical validation substantiates the efficacy of this approach, with the method’s Mean Intersection over the Union (MIoU) parameter yielding an impressive score of 0.939 in segmentation performance. Moreover, the peak signal-to-noise ratio and structural similarity attain commendable zeniths of 38.16 and 0.9808, respectively, underscoring the excellence of the reconstruction process. The proposed methodology demonstrates its prowess in exacting segmentation and comprehensive reconstruction of semantic intricacies and nuanced features pervading the realm of artistic imagery. Consequently, this novel methodology augments artists’ capacity to discern diverse artistic paradigms and fabricate superlative new media art compositions of heightened caliber.
Blockchain Based Framework for Enhancing Cybersecurity and Privacy in Procurement

An imperative issue that impedes economic, social, and environmental progress is the involvement of the middle tier in public institutions. Due to inadequate transparency and clandestineness in establishments, the trust in procurement process has become a predominant concern that affects many nations around the world. Governments across the globe have begun exploring cutting-edge technologies to improve procurement transparency and integrity. Blockchain is an emerging technology that comprises the potential for generating substantial advancement in the public procurement domain by establishing transparent, immutable, and autonomous processes. Even though contributions are constantly rising, adequate research and implementation are pivotal in order to fully comprehend the technology to attain these advantages. In this study, the typical procurement process was examined to evaluate the associated issues and how the digitization of the process through Blockchain technology can mitigate them by using digital identities towards maintaining the security and privacy of the entity.
Trajectory planning of the shortest path and optimal time of the retort robot

There are problems such as labor-intensive and the need for a large number of experienced masters, and the replacement of labor by retort robots is the trend of wineries and technological development. Aiming at the trajectory planning problem of retort robot, an RUN optimization algorithm is proposed to optimize the trajectory of retort robot. First, the kinematic model of the robot is established. Secondly, the convergence speed of the ocean predator algorithm and the Rungekuta optimization algorithm in the trajectory planning of retort robot with the shortest path and the best time is compared; The 5-4-5 mixed polynomial is combined with the Rungekuta optimization algorithm for optimal time trajectory planning; Finally, the MPA algorithm is compared with the RUN optimization algorithm, which shows that the RUN optimization algorithm is more suitable for the trajectory planning of retort robot with the shortest path and the best time.
A Spinwave Time-Multiplexed Ising Machine

We present a spinwave-based time-multiplexed Ising Machine (SWIM) where artificial Ising spins are formed with ns-long spinwave RF pulses propagating in a delay line based on <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$5-\mu m$</tex> thick Yttrium Iron Garnet (YIG) film. The phase of artificial Ising spins is binarized using an off-the-shelf phase-sensitive microwave amplifier and the coupling between spins is implemented with microwave delay cables. Thanks to the very low spinwave group velocity, the 7-mm long YIG delay line can host an 8-spin MAX-CUT combinatorial optimization problem and solve it in less than 4 <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mu s$</tex> while consuming only 7 <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mu J$</tex> .
FIACCEL: Memory Efficient Frame Interpolation Accelerator for Full-HD Video

Frame interpolation(FI) is a challenging task that involves generating intermediate frames between two consecutive frames of a video to achieve smooth motion. Although several approaches, including deep learning-based and hybrid methods, have been proposed, most target GPU systems with high computational costs, making it difficult for real-time on-device systems. This paper proposes a memory-efficient and low-complexity accelerator for FI by analyzing the most memory-inefficient part of the encoder-decoder structure and applying schemes such as feature map reuse, selective transfer to DRAM, row-wise layer fusion, kernel decomposition, and parallelized horizontally dilated convolutions. The proposed hardware is verified on an FPGA environment and can synthesize 1920×1080 video from 90 fps to 180 fps in real-time with an average PSNR quality of 31.98 dB on the Vimeo90K dataset. Our design is available at https://github.com/Miinuuu/FIACCEL.
Polymorphonuclear-Mononuclear Ratio in Peripheral Blood as Hematologic Malignancy Predictor in Pancytopenia

Pancytopenia is a laboratory finding of decreased hematological cells characterized by hemoglobin of &lt;13.5 g/dL for males or &lt;11.5 g/dL for females, leukocytes of &lt;4x109/L and platelets of &lt;150x109/L. The data from Dr. Moewardi Hospital reported 56 cases of pancytopenia in 2020. Follow-up tests such as reticulocyte test, Bone Marrow Puncture (BMP), or bone marrow biopsy are needed to determine the cause of pancytopenia. This study aimed to assess the performance of the Pm/M ratio of peripheral blood as a screening instrument to predict the cause of pancytopenia. A cross-sectional study was carried out on pancytopenia patients undergoing laboratory tests at the Clinical Pathology Laboratories of Dr. Moewardi Hospital from January 2020 to June 2021. The cut-off point of the Pm/M ratio was determined by ROC and AUC curves. The results were presented in a 2x2 table. The Pm/M ratio &lt;0.91 as a predictor of hematological malignancy had a sensitivity of 82.9%, specificity of 82.9%, PPV 82.9, NPV 82.9%, LR positive 4.833 and LR negative 0.207. The Pm/M ratio can be used as a screening biomarker to predict the cause of pancytopenia before performing BMP and to distinguish between hematological malignancy and non-hematological malignancy.
Perancangan Sistem Informasi Percetakan Toko Denis Palembang Berbasis Web

The author made observations at Denis Palembang Printing Shop, in the printing press. The data processing has been computerized using a simple application, Microsoft Word and Microsoft Office, in processing data and making reports. To support several theories such as UML the data processing method used is the waterfall model. and AppServ software (Apache, MySql), PHP and MySQL, Microsoft Office and Microsoft Visio as supporting software. Web-based data processing will make it easier to process ordering data, goods data, customer data, payment data and making reports in Denis Palembang Shop Printing so that it can help employees at Denis Palembang Printing Shop process and make reports and other matters needed
Intercultural competence in the training and daily professional lives of police officers

This article explains the role of intercultural competence in the training and daily professional lives of police officers,and proposes ways to improve the acquisition of this competence. The goal is to describe intercultural competence,highlighting its importance and the possibilities for its acquisition in the training and professional everyday lives ofpolice officers. The article uses general scientific methods – analysis of scientific literature and documents, as well asthe induction–deduction method, drawing conclusions and making proposals, and (grammatical, historical, systemic,teleological) methods of interpretation of legal regulations, analysing applicable legislation and policy planning docu-ments. The study concludes that the daily work of the police in today’s environment requires good management andcultural awareness in dealing with residents, with the consequent development of intercultural competence amongpolice officers as a prerequisite for successful performance and cooperation with different communities in a multicul-tural society. The acquisition and development of intercultural competence should be included in police training pro-grammes, complementing professional standards as appropriate, and in professional development activities for policeofficers. At the same time, the structural changes in the State Police should be addressed, with responsible officersbeing identified to deal with culturally diverse populations, and professional models for police dealing with culturallydiverse populations should be developed.
Students’ Attitudes Toward English Writing Activities at SMP Negeri 29 Medan

This study aimed to analyze the students’ attitudes toward English writing activities. The method of this study was descriptive qualitative by conducting the in-depth interview and questionnaire sheets. The data of this study were transcription of the students’ attitudes toward English writing activities especially in recount text topic. Moreover, the data sources were 31 students at grade 8 of SMP Negeri 29 Medan. The results showed that the dominant components of students’ attitudes in English writing activities was affective component (60,75%), followed by conative component (58,06%) and cognitive component (54,8%) which could be interpreted that the students had positive attitude regarding to the writing of recount text. It was reflected from three components. For cognitive component, the students believed that their writing skills will be better after studying the material despite the many difficulties encountered when writing recount text. For affective component, the students felt happy, interested and really enjoyed the lesson. And for conative component, the students were able to pay attention during teacher explained about material, asked questions about material that has been understood and always discussed it with friends. So that, this indicated that their overall attitude was positive.
ASTER and Aerospectrometric Data Analysis for Gold Exploration: Case Study at Um Balad Area, North Eastern Desert, Egypt

The Um Balad area is a part of the Arabian Nubian Shield (ANS), which hosts various gold and base metal deposits. Gold can be prospected in the alterations and sheared zones in the widely exposed metagabbro-diorite rocks in the Um Balad area. In this regard, the integration of ASTER multispectral data processing, gamma-ray spectrometry data analysis, GIS modeling, and fieldwork gave us a good indication of which areas are most likely to contain gold-related alteration zones in the study region. Three remote sensing techniques were applied, including Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and Mixture Tuned Matched Filtering (MTMF). Key alteration mineral types are mostly related to the spatial distribution of mineral-bearing alteration zones. Careful interpretation of the gamma-ray spectrometry data is reliable for mapping alterations related to hydrothermal activity. The potassium distribution (%) of the study area was analyzed, where the radioelement ratio maps [eTh/K and eU/K] were obtained. The F-parameter and the Th-normalization techniques (Ud % and Kd %) were respectively applied for identifying potential mineralization zones. The GIS (weight overlay analysis) tool was used to combine the results of the three methodologies (remote sensing approaches, gamma-ray spectrometry data interpretation, and automatic lineament extraction) by combining ten layers (ASTER-SAM, ASTER-SID, ASTER-MTMF, lineament density, [K%], [eTh/K], [eU/K], [K*(eU/eTh)], [Kd], [Ud]). A final gold-related alteration zone map was generated. For validation, spectral signatures of the acquired rock samples as well as scanning electron microscopy (SEM) were used for the result verification of such a study. Finally, going forward, the adopted methodologies are considered the basis for gold-related alteration mapping in comparable environments.
Fibrosis Grading Methods for Renal Whole Slide Images Based on Uncertainty Estimation

Fibrosis gradings are a valuable indicator to provide diagnostic information for chronic kidney disease. The assessment of the percentage of renal fibrosis by physicians is based mainly on visual estimation, which is highly subjective and varies widely between physicians, hence the need for objective and reliable morphological assessment algorithms. For ultra-high resolution images, acquiring patch-level labels imposes a heavy annotation burden; conversely, indiscriminately assigning WSI-level labels to each patch poses a significant label noise problem. In this paper, we propose a weakly supervised two-stage framework. In the first stage (Patches Selection Stage), patches with low uncertainty, i.e., strongly correlated with WSI labels, are screened using approximate Bayesian inference. In the subsequent second stage (Decision Aggregation Stage), low uncertainty patches are merged into a large map and fed into a classification network to obtain WSI-level diagnostic results. The uncertainty estimation efficiently targets local regions of interest in high-resolution pathology slice images and excludes noise unrelated to WSI labels. We compared this method with previous methods for grading renal fibrosis in a self-constructed dataset of renal pathology provided by the Institute of Nephrology, Southeast University. We used the quadratic weighted kappa coefficient as a grading consistency evaluation index. The results show that this method is superior in accuracy and kappa consistency.
Specifics of Chinese students’ cognitive orientations in mastering technical disciplines

Introduction. Currently, the leadership of the People’s Republic of China pays special attention to the issues of technical vocational education. The learners from the PRC studying in Russia have specific cognitive orientations in mastering technical disciplines. The aim of the article is studying the specifics of academic resilience in mastering technical sciences by PRC students of Ural Federal University. Materials and methods. The academic resilience of PRC students from Ural Federal University in terms of mastering technical sciences was measured using the ‘Technics Resilience Scale for University Students’ (TRSUS). TRSUS aims to build Feedback literacy and Self-assessment with a view to help a student to pursue technical studies productively. The survey involved 659 students who had a technical science learning experience in one of the educational programmes: “Civil Engineering”, “Architecture”, “Geodesy and Remote Sensing”, “Steam Power Industry and Heat Engineering”, “Water Supply and Drainage”. The students assessed their resilience in technical sciences under a 5-score Likert response scale, with the use of Tencent Questionnaire in English. The statistical processing of measurement results was carried out using Structural Equation Modelling (SEM) methodology with the use of SPSS 23.0 and Amos 18.0 software packages. Results. The statistical analysis of results of PRC students from Ural Federal University in terms of measuring resilience in technical sciences under the TRSUS scale showed that the wording of the questions was adequate to the measurement context. The primacy of students’ incremental beliefs/goals towards improving the efficiency of learning activities was revealed. A strong correlation between students’ answers with the TRSUS questions was found. Cronbachs alpha was equal to 0.977, which is evident of high internal consistency of students’ answers. The structural model of confirmatory factor analysis of TRSUS data including four indicators (factors) – “Persistence”, “Perceived Value”, “Cognitive Complexity” and “Incremental Beliefs” – has the best source data fitting criteria. The method of exploratory factor analysis of TRSUS data revealed the specificity of cognitive orientations of PRC students from Ural Federal University: the choice of educational programme influences most prominently the indicator “Perceived Value”, which is explained by the peculiarities of Chinese technological culture. Conclusion. An original methodology for measuring university students’ academic resilience in technical sciences – ‘Technics Resilience Scale for University Students’ (TRSUS) – is presented. The use of TRSUS makes it possible to determine the specifics of students’ cognitive orientations in mastering technical disciplines and to form their competent feedback and self-assessment for efficient continuation of education.
ReviewLocator: Enhance User Review-Based Bug Localization with Bug Reports

Improving and updating applications based on user reviews is crucial to the continuous development of modern mobile applications. However, software bug descriptions in user reviews are often written by non-professional users, and contain a lot of irrelevant text, making it challenging to conduct bug localization. The current software bug localization technologies based on user reviews are not able to address these challenges effectively, resulting in suboptimal results. To address this issue, we propose ReviewLocator, which focuses on key phrases and learning from historical bug reports. It first utilizes syntactic analysis or source file parsing to convert each user review or source file into phrase representations. Then it depends on Key Phrase-based Ranking using a newly proposed Bug Report-based Term Weight to map review phrase sets to source file phrase sets. In our experiments on eight applications from the Google Play Store, the results prove our proposal surpasses ChangeAdvisor and Where2Change with an absolute improvement of 0.076 and 0.055 in terms of MAP correspondingly.
Characterizing national document flow in the domain of open access to information

The author discusses the findings of the bibliometric study of the national document flow (as presented in the RISC database) on the issues of open access to scientific and research information. The general volume of microflow made 1,076 publications of various types, including articles in periodicals and serials, as well as books, conference proceedings, reports, theses, and deposited manuscripts. The journal articles made the main bulk (74%) followed by the proceedings (20%). The dynamics demonstrates the upward trend though the growth rate is rather low. The publication dispersion in periodicals is characterized. In general, it can be described by Bradford – Vickery law. The most productive (core) journals with the greatest number of relevant publications are defined. All of them are not specialized publications. The subject areas are defined. The analysis of the first and second zone journals demonstrates that they belong to 19 subject headings of the State Rubricator of Sci-tech Information which evidences on the interdisciplinary character of the problem under study.
A Feature Selection Technique Using Self-Organizing Maps for Software Defect Prediction

An important goal of Software Defect Prediction is to help increase the efficiency of software development. Increase in defect prediction accuracy would result in less resource consumption, and hence, effective feature selection techniques are needed to provide better inputs to the classifier. A carefully selected subset of features can not only increase prediction accuracy, but also result in less expensive computation. Wrapper methods for feature selection are based on evaluating feature subsets with a predetermined criterion. In this paper, the authors suggest an approach for feature selection by carefully evaluating feature subsets using clustering-based method. Cost based feature selection method based on Self-Organizing maps (CFSSOM) can be divided into three steps. First, computing the subsets of the feature set which are to be considered for evaluation. Second, clustering each of those feature subsets into two clusters. We use an ANN-based learning algorithm called self-organizing maps for clustering feature subsets. Third, applying labels on those two clusters based on data representation and measuring how strongly they are related to original labels. We have successfully implemented and proved that this feature selection technique improves prediction results based on experiments on PROMISE repository datasets.
The Interplay of social media and English Proficiency of Indonesian University Students’ Exchange

This research uses the descriptive qualitative method as the research methodology. This research was conducted to know what is the most common social media influence student’s English-Speaking ability and how does social media influence student English speaking ability. The population in this research were the students of Pertukaran Mahasiswa Merdeka Inbound State University of Malang in this research were 10 students. The data collection method used in this research was an interview. The results shown that the most social media that influence students to improve their speaking ability is YouTube. Social can influence the students to improve their speaking ability because in social media there are so many contents that provide them to learn English especially to improve their speaking ability such as video, picture, photo, etc.
Mobile incident command dashboard (MIC-D)

Incident Command Dashboard (ICD) plays an essential role in Emergency Support Functions (ESF). They are centralized with a massive amount of live data. In this project, we explore a decentralized mobile incident commanding dashboard (MIC-D) with an improved mobile augmented reality (AR) user interface (UI) that can access and display multimodal live IoT data streams in phones, tablets, and inexpensive HUDs on the first responder&#x2019;s helmets. The new platform is designed to work in the field and to share live data streams among team members. It also enables users to view the 3D LiDAR scan data on the location, live thermal video data, and vital sign data on the 3D map. We have built a virtual medical helicopter communication center and tested the launchpad on fire and remote fire extinguishing scenarios. We have also tested the wildfire prevention scenario &#x201C;Cold Trailing&#x201D; in the outdoor environment.
Wearable multispectral imaging and telemetry at edge

We present a head-mounted holographic display system for thermographic image overlay, biometric sensing, and wireless telemetry. The system is lightweight and reconfigurable for multiple field applications, including object contour detection and enhancement, breathing rate detection, and telemetry over a mobile phone for peer-to-peer communication and incident commanding dashboard. Due to the constraints of the limited computing power of an embedded system, we developed a lightweight image processing algorithm for edge detection and breath rate detection, as well as an image compression codec. The system can be integrated into a helmet or personal protection equipment such as a face shield or goggles. It can be applied to firefighting, medical emergency response, and other first-response operations. Finally, we present a case study of "Cold Trailing" for forest fire prevention in the wild.