Reviewerly/exHarmony huggingface dataset:
Islamophobic Tweet Detection using Transfer Learning

Segregating Islamophobic hate speech from other instances of offensive language is a serious hurdle for automatic hate-speech detection on social media platforms such as Twitter. Because lexical detection methods classify all messages containing particular terms like hate speech, previous work using supervised learning has failed to differentiate between these categories. This task is complex due to the level of difficulty in natural language constructs. We have worked on a transfer learning approach using Universal Language Model Fine-tuning (ULMFIT), an efficient method that can be applied to classification tasks. Our method gave more than 80 percent accuracy and the confusion matrix thus formed was successfully able to classify those datasets proportionally into each block. The use of Deep learning in text classification has been underutilized. This method will contribute to solving the spread of Islamophobia which hasn't been taken into consideration when taking action against online hate
Importing Data: readr

Before we can analyze data, we need to load it into R. The main Tidyverse package for this is called readr, and it is loaded when you load the tidyverse package:
Intelligent water surface waste disposal device based on image recognition technology

In order to respond to the construction requirements of “beautiful city” in China, this project has developed an intelligent water surface garbage disposal device based on image recognition technology in response to the serious pollution of existing small urban water bodies, low efficiency and high cost of manual salvage, and the inability to operate manually in dangerous waters.
Feature High-Boosting for Semantic Segmentation

Semantic segmentation has been actively studied with the great success of deep learning. Various network architectures for this task have been introduced over last few years, and the current state-of-the-art methods have shown significant advances enough to be applied to practical applications. However, previous methods often fail to segment small objects due to the limit on the spatial resolution of the feature map encoded through the deep network architecture. In this paper, we propose a simple yet effective module for semantic segmentation. Its key components include feature high-boosting, which efficiently highlights boundaries of small objects by simple operations, i.e., sum of the original feature and the corresponding residual, in the latent space. This is fairly desirable to guide network parameters to focus on features of small objects. Experimental results on various benchmarks show that the proposed method successfully improves the performance of semantic segmentation regardless of backbone networks. In particular, the proposed method with the transformer-based decoder achieves 56.4 mIoU on the ADE20K dataset.
Qualidade de vida de idosos pertencentes a grupos de atividade física/terapêuticos: uma revisão integrativa

Population aging is an increasingly present reality. Population projections indicate that in about 20 years, the elderly population will account for more than 30% of the Brazilian population. On the other hand, healthy aging is still a distant reality, a factor that directly impacts the quality of life of this population. The present study aims to carry out a bibliographic survey to analyze the quality of life of elderly people belonging to physical activity/therapeutic groups. A survey was carried out in the bases of scientific literature, listing a total of 11 studies for the composition of this review. Of the studies listed, a low overall methodological quality can be observed. The great variety of interventions carried out with the elderly was noted, in different types of environments: coexistence centers, health units, universities and intradomiciliary. The analysis of the works allowed us to observe that the most varied types of environment, frequency and types of activities performed resulted in an improvement in the perception of quality of life in this population, whether reported by the elderly or evaluated by specific scales. Therefore, it is important to carry out health promotion activities with this population, aiming to promote healthy aging. &nbsp; Keywords: Quality of life; Elderly; Physical activity group; Therapeutic group; Primary Health Care.
Revisiting Outer Optimization in Adversarial Training

Despite the fundamental distinction between adversarial and natural training (AT and NT), AT methods generally adopt momentum SGD (MSGD) for the outer optimization. This paper aims to analyze this choice by investigating the overlooked role of outer optimization in AT. Our exploratory evaluations reveal that AT induces higher gradient norm and variance compared to NT. This phenomenon hinders the outer optimization in AT since the convergence rate of MSGD is highly dependent on the variance of the gradients. To this end, we propose an optimization method called ENGM which regularizes the contribution of each input example to the average mini-batch gradients. We prove that the convergence rate of ENGM is independent of the variance of the gradients, and thus, it is suitable for AT. We introduce a trick to reduce the computational cost of ENGM using empirical observations on the correlation between the norm of gradients w.r.t. the network parameters and input examples. Our extensive evaluations and ablation studies on CIFAR-10, CIFAR-100, and TinyImageNet demonstrate that ENGM and its variants consistently improve the performance of a wide range of AT methods. Furthermore, ENGM alleviates major shortcomings of AT including robust overfitting and high sensitivity to hyperparameter settings.
Minimalist Coverage and Energy-Aware Tour Planning for a Mobile Robot

We study a coverage and tour planning problem wherein a robot with limited sensor coverage is assigned to serve n known points in an environment. A location is served if it is within the visibility range of the robot’s sensor. However, the robot is equipped with a battery that powers the robot to travel a maximum distance of B. Several charging stations are placed in the environment so that the robot can charge itself (if needed) to complete the mission. The objective is to compute an energy-constrained tour that starts at a given start location, visits a minimum set of service locations for serving the n points of interest, and returns to the start location. We also aim to minimize the distance traveled between any two consecutive service locations in the tour via a subset of charging stations. This problem has applications in search-and-rescue and surveillance missions where such coverage and energy-aware path planning are of utmost importance. We propose a new algorithm for this problem and show its efficacy using experiments with up to 1000 points of interest on a plane. The running time of our algorithm for such a scenario was a negligible 5.33 sec.
Cryptocurrency Awareness in Kosovo

Even after more than a decade since the first issue of bitcoinBitcoin, the cryptocurrenciesCryptocurrency are not yet used and recognized for the purpose they are created, i.e. cash for online transactionsTransactions. KosovoKosovo, a new developing country, still in transition, makes no exception to this issue. KosovoKosovo has a young population and very high internet use, even so, the trust in a currencyCurrency without insurance, is understandably low, especially when the method in which the currencyCurrency is created is not fully comprehended by the majority. While most of the persons who participated in the survey have heard of cryptocurrenciesCryptocurrency, they have none or very little knowledge of the blockchain technologyBlockchain technology, which is the very foundation of the currencyCurrency itself. In this study, we have analyzed the relation between age, level of education, use of digital options for payments, and cryptocurrencyCryptocurrency awareness and perception among the population. A factor with a direct impact on the possible use of bitcoinBitcoin is its legal regulation, the absence of which impacts also on the perception about cryptocurrencyCryptocurrency. Therefore, the issue of normative framework seems to be crucial for the future of cryptocurrenciesCryptocurrency so that the perception of many may be changed and trust in a currencyCurrency created by a new technology may be gained. We determine that the millennials could be the generation that will use the cryptocurrencyCryptocurrency in the future since their perception of this issue is considerably different from the ones that now are holders of the capital.
Friendly Secret Sharing Using Integer Number Representation

This paper presents a simple technique for friendly secret sharing using integer representation and eXclusive-OR (XOR) operation. The proposed method firstly converts the meaningful secret image into the quotient and remainder part by selecting an appropriate constant. Subsequently, the XOR operation is applied to these parts to yield coupled shared images by involving a cover image. The proposed method effectively hides the secret information into two meaningful shared images. As documented in Experimental Section, the proposed method offers a good result with a perfect recovered secret image under no attack and image distortion.
Prevalence of color vision deficiency and it’s relation with ABO blood group among medical students

Background: Normal human beings can appreciate color in all three of it’s attributes; Hue, intensity, and saturation. Human beings can perceive three primary colors, that is, red, green, and blue. Any defect in appreciation of colors is known as color vision deficiency (CVD). Complete inability to appreciate color is known as color blindness. The genes for red and green cone pigments are found in the q arm of the X chromosome. Hence, red and green CVD are inherited as X-linked recessive diseases. Blue CVD is autosomaly inherited. Blood groups are genetically inherited as well. Although it is a known fact that there is a preponderance of genetic diseases in subjects belonging to a specific blood group, no such study was available in Western Odisha as per our knowledge. This becomes more relevant as consanguineous marriages are a serious social problem in that part of Odisha. Aim and Objectives: Therefore, the study was undertaken to find out the prevalence of CVD among Medical students in Western Odisha and to find out it’s relation, if any, with ABO blood groups, as these two entities are genetically inherited. Record should be kept for future use, especially for counseling at the time of marriage and if necessary, to choose a subject for further study, where color detection does not play an important part. Materials and Methods: Prior permission was taken from the Institutional Ethics Committee to carry out this study. The study was carried out among the 1st–4th year medical students of V.S.S. Medical College and Hospital (n = 690) from August 2022 to October 2022. Ishihara test plates for color vision and agglutination method for ABO blood grouping were employed to get the prevalence of CVD and to get the percentage of subjects belonging to each blood group among those having CVD. The observations were noted carefully. Results: After careful screening, it was seen that 647 (93.76%) were normal, 42 (6.08%) had CVD, and 1 (0.14%) subject was completely color blind. All those affected were males. Distribution of blood group in CVD subjects showed 7 (16.27%) numbers belonging to blood group A, 22 (51.16%) belonging to blood group B, 1 (2.3%) belonging to blood group AB, and 12 (27.9%) belonging to blood group O. The only color blind student belonged to blood group B (2.3%). Conclusion: As medical students have to deal with colors throughout their career, the study helps the subjects to be aware of their condition early in their professional life. It also tried to find out the percentage distribution into ABO blood groups. A larger population should be included to get more accurate results.
POLYPHONY OF FORMATIVE ASSESSMENT FORMS

The postulation of assessment is tackled comparatively: in the realms of philosophy and pedagogy. The global mission of formative assessment is to enhance the results of cognitive activity by expanding the array of assessment procedures not only for subject, but also for meta-subject results, which is crucially important in online and blended learning. In activity pedagogy, formative assessment is recognized as an indispensable attribute of effective learning and a critical skill of pedagogical foresight, since it holds forth prompt feedback from the teacher at all stages of mastering the educational program. On the examples of tasks for video lectures hosted by TED.com., the author proves that the polyphony of five Cs opens up opportunities not only to teach, but also to inspire. The article traces the extent to which not only the educational course, but also the assessment model can be inverted; reveals a teacher’s readiness for the necessary curriculum adaptation. The author proposes a clear algorithm for implementing the formative assessment model in the Just in Time Teaching (JiTT) paradigm: videolectures – classroom collaboration – observation – feedback – evaluation. The ‘Effort grading’ material of the Mazur Group JiTT Rubric is offered as a resource with practical recommendations. The article features the results of students-economists’ survey on their perception of formative assessment.
A study of factors for the adoption of international standards in digital forensic

Cybersecurity incidents have been growing in number with high severity. To response to the Cybersecurity incidents, the attacked organizations generally execute predetermined procedures and then apply digital forensics to recover and investigate material on digital media and networks. The digital forensics procedure composes of four important processes including identification, preservation, analysis, and presentation of digital evidence which is legally admitted in any legal proceedings. This paper is aimed to study effecting factors on selecting methods of digital forensics according to standards and international practices from reliable international organizations. The paper demonstrated internal and external organization factors that used for determining the digital forensic methods to conform to enforced laws or principal rules in the organizations. Additionally, it revealed viewpoints from information security professionals to determine standards and international practices for digital forensics to apply in an organization. The study pointed out that factors relating to law and regulations was the most significant factor that most of organizations (67 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> ) used to determine international approach or standards for digital forensic. This made the standards of NIST more reliable, and it has been adopted by most organizations for digital forensic. This research can be further applied to develop the methods for digital forensics in near future.
Time Series Multi-task Learning for Prognosis of MICU and SICU

The prognostic assessment of an ICU patient involves assessing the severity of their condition, interventions, and length of ICU stay. Over the past 30 years, researchers have proposed numerous predictive models and severity assessment scales for ICU patients in specific regions, including APACHE II and SAPS II. However, most existing methods rely heavily on curve fitting which do not account for misclassifications caused by false negatives and positives. Specificity and sensitivity must be provided as an indicator of model performance. The primary aim in this study is to develop a machine-learning model to formulate a prognosis for MICU and SICU patients by using data from the MIMIC-IV for training. The predictive models developed in this study facilitate the prediction of mortality and other outcomes across various treatment regimens.
SISTEM INFORMASI PENCATATAN KAS MASUK PADA LEMON FRESH LAUNDRY JAMBI

Laundry business is a business related to laundry services with washing machines and automatic dryers and special cleaning and fragrance fluids. This business is mushrooming in big cities where there are many boarding houses and rented houses, where renters of boarding or rented houses do not have time or cannot do their own washing and ironing of clothes due to busyness as students and workers. Lemon Fresh Laundry, one of the kilogram laundry in Kisaran. Its strategic location, precisely on Jl. Lkr. Barat 3, Bagan Pete, Kec. Kota Baru, Jambi City, makes many customers visit every day to use Lemon Fresh Laundry services. Until now Lemon Fresh Laundry does not have its own information system and still uses a manual system, this laundry also does not have an accurate database storage system so that all data is still stored in a book. With the use of this manual system, various problems arise such as the difficulty of finding customer data in a book. The purpose of this Web-based cash-in recording system application is to provide professional services to customers and minimize errors that may occur. This Web-based cash recording information system uses ERD and MYSQL flow diagrams for data processing.
An Investigation of Library Automation Status in Private Aided Colleges of Belagavi, Karnataka

This paper unfolds the status and problems of library automation in aided degree colleges of Belagavi district, Karnataka. The study reveals that 83% of libraries are automated and the remaining libraries are not found to be automated owing to inadequate staff, lack of infrastructure, insufficient funds, lack of training among professional staff etc. This study also depicts the status of the software packages used by libraries and modules used in library automation software. The study finds that out of a total of 24 college libraries, 15(75%) libraries are using proprietary software ‘e-Lib’. The lack of funds for improvements, and lack of facility to implement the improvised software versions are identified as major post automation issues.
Development and Application of a Support Device for Checking Leakage of Heat Exchange Tubes of Spring Base Supporting Condenser in the Form of Filling Water

Abstract The installation and removal workload of the original water filling support of the condenser is huge. For example, the water filling leak detection of the condenser during outage takes a lot of time on the main line of the conventional island, which cannot meet the requirements of the outage period. Moreover, the support can only be removed after the condensate side of the condenser is filled with water and emptied, which needs to be further optimized. Based on the stress analysis and load modeling calculation of the original water-filled support and its legs, the stress distribution and deformation of the water-filled leak detection support of the condenser are determined, and the design is improved according to the demonstration results. Through rapid fixed function of self-locking wedge device design, design of jack-up device and synchronization automated design of hydraulic equipment, a new type of spring water filling pedestal supporting type condenser leakage inspection support device was developed, and thus the condenser water filling leak quick installation and dismantling becomes convenient, safe and reliable, which significantly shortens the condenser leakage in the process of water filling to check support operation time. At the same time, the synchronous lifting of the water-filled leak detection support ensures the structural safety of the condenser during the process of condenser descent when the condensate side of the condenser is drained to the operating level.
CNN-Based Ruled Line Removal in Handwritten Documents

Even state-of-the-art neural approaches to handwriting recognition struggle when the handwriting is on ruled paper. We thus explore CNN-based methods to remove ruled lines and at the same time retain the parts of the writing overlapping with the ruled line. For that purpose, we devise a method to create a large synthetic dataset for training and evaluation of our models. We show that our best model variants are capable of reconstructing characters that are overlapping with the line to be removed, which is a problem that simpler approaches often fail to solve. On a dataset of children handwriting, we show that removing the ruled lines improves character recognition. We made our synthetic dataset and all experimental code available to foster further research in this area.
Proposal of Film-penetrating Transducers for a Spin-wave Reservoir Computing Chip

We propose a spin-wave antenna structure that penetrates a garnet film, which we named film-penetrating transducers (FPTs). FPTs possess a zero-dimensional feature that allows flexible placements and sufficient numbers of input/output electrodes for spin-wave reservoir computing. We first explain the structure and operation of FPTs. Then, we numerically construct and analyze a basic spin-wave reservoir chip model. We obtain intricate patterns of spin-wave propagation and interference that reflect the high dimensionality of the system. We also demonstrate the nonlinearity of the output electrical signal from an FPT detector of the system. Our results strongly suggest that FPTs preserve the important properties of a physical reservoir while ensuring large degrees of freedom for both the arrangements and amounts of spin-wave exciters and detectors.
An analytical study of content and context of keywords on physics

This paper is based on the analysis of author-assigned and title keywords and their constituent component words collected from 769 articles published in the journal Low Temperature Physics since the year 2006 to 2010. The total number of distinct keywords is 1155 of which 869 are single keywords having total frequency of occurrence of 2287. The single keywords have been categorized in four broad classes, viz. eponymous word, form word, acronym and semantic word. A semantic word bears several contexts and thus it may be considered as relevant in several other subject areas. The probable subject areas have been found with the aid of two popular online reference tools. The semantic words are further categorized in twelve classes according to their contexts. Some parameters have been defined on the basis of associations among the words and formation of keywords in consequence, i.e. Word Association Density, Word Association Coefficient and Keyword Formation Density. The values of these parameters have been observed for different word categories. The statistics of word association tending keyword formation would be known from this study. The allied subject domains also become predictable from this study.
Securing File sharing System in cloud environment using AES Algorithm

In the prevailing paper, delivered a fuzzy weakly ordering the use of fuzzy metric area and fuzzy partial metric area.
Cloud Task Scheduling Based on Improved Particle Swarm optimization Algorithm

Aiming at the problem of task scheduling in cloud computing resource scheduling, a scheduling strategy combining genetic algorithm (GA) and improved particle swarm optimization algorithm (GA-IPSO) is proposed. Firstly, a multi-objective evaluated model is established considering the task completion time, maximum completion time and load balance. Secondly, GA is used to optimize the randomly generated solution space to generate the basic solution. Finally, the improved particle swarm optimization algorithm is proposed to obtain the optimal solution of cloud task scheduling. In this paper, particle swarm optimization (PSO) is improved by establishing nonlinear negative correlation between inertia weight and iteration times and combining individual cognitive learning factors with evaluation function values. Simulation results show that GA-IPSO reduces the fitness value, maximum completion time, task completion time and load balancing degree of virtual machines by 12.8%, 15.3%, 12.0%, 50.8% on average in small-scale tasks and by 18.9 %, 25.3 %, 15.6 %, 41.8 % on average for large-scale tasks compared with other algorithms.