Reviewerly/exHarmony huggingface dataset:
Survey on Semantic Based Video Hierarchy for Browsing Large Video Repositories

The number of videos exploding on the web is a good challenge in automatic video search. Existing Video search engines, like YouTube, imagine the sorted list of search results. The straightforward list system may be suitable for finding an ad or a music video, although queries cannot be handled with complex header systems, so users create difficulties to find the necessary information. During this event, the best way to a semi-structured array in the nodes that covers all the main headings. Obviously, each question manually changes headlines and thanks for a good range of search titles. By implementing video descriptions on their linguistic information page, we use a prototype-based streamline cluster regime. We will take this information from linguistic information to the complete linguistic information we make by utilizing a sub-ontology conception in our site.
A Study on Biometric Authentication Systems Challenges and Future Trends

Client confirmation in PC framework is done in view of certain safety efforts like passwords, keys, identityd cards, stick and so forth be that as it may, the abuse and robbery of these safety efforts are likewise expanding because of step by step headway of innovation. This prompted the introduction of biometric security frameworks in which the confirmation of an individual is done in light of a component vector got from physiological as well as behavioral attributes of a person by utilizing biometrics innovation, an individual can be validated in view of his identity rather. With a specific end goal to help tenderfoots picked their examination range or a specific biometric innovation, all the developing biometric advancements and difficulties in every innovation have been talked about in this paper in detail. Future patterns in biometric advancements are likewise talked about.
Meningkatkan Hasil Belajar Siswa SMP Melalui Pendekatan Belajar Saintific Pada Mata Pelajaran Prakarya

The purpose of this study was to determine the increase in student learning outcomes regarding the Processing of Animal Husbandry and Fishery Products in Craft subjects through the use of a Scientific Learning Approach. This research was conducted in a junior high school (SMP Negeri 19 Bogor City) with the research subjects being students of class IX.F. The method used is a classroom action research method which consists of two cycles. In the first cycle, the learning is carried out using the Scientific Learning Approach, while in the second cycle, the Scientific Learning Approach has been refined. Each cycle consists of four stages of research, namely planning, implementing actions, observing, and reflecting. The research data were analyzed using comparative descriptive followed by reflection. Comparative descriptive is done by comparing the initial condition data, cycle 1 and cycle 2, both for learning outcomes. The results of this study indicate that: First, the use of the Scientific Learning Approach can improve student learning outcomes about the Processing of Foodstuffs from Animal Husbandry and Fisheries in Craft subjects. It is proven that the percentage of student learning outcomes has increased from the initial condition the average daily test score of 63.69 in the first cycle to 72.88 and in the second cycle to 78.16 or in the final condition it increased by 22.7% from the initial condition. . It is proven that the percentage of student learning mastery increases from the initial condition of 64.52% in the first cycle and becomes 93.55% in the second cycle or in the final condition, an increase of 44.99% from the initial condition.
Relevance of Reaction Surface Strategy and Artificial Neural Network Proposal in Representing and Development of Confession-Suction Procedure

A survey on the use of reaction surface strategy (RSS) and Artificial neural network (ANN) in confession-suction demonstrating and improvement is displayed. The hypothetical foundation of the examined strategies with the application strategy is clarified. The paper portrays most every now and again utilized trial outlines, concerning their constraints and normal applications. The paper additionally exhibits approaches to decide the precision and the hugeness of model fitting for the two strategies depicted in this. Moreover, late references on confession-suction demonstrating and advancement with the utilization of RSS and the ANN approach are appeared. Uncommon consideration was paid to the choice of variables and reactions, and in addition to factual examination of the displaying comes about.
Understanding the viability of integrating WSN with IoT using cloud infrastructure

IEEE 802.15.4, Wireless Sensor Networks, have increasingly become an important part of many sustainable development applications. However, due to the energy expenditure restrictions of Wireless Sensor Networks, it has become imperative to optimize its usage and reach ability through a amalgam of nature inspired techniques, Internet of things and cloud. In our study, we have used CupCarbon simulator to first establish the workability of such a model and to see if nature inspired algorithms technique may be used to develop and optimization wireless sensor network integrated Internet of Things cloud based modals as efficient solutions to modern problems. A resultant application was designed to handle healthcare facilities through the specified infrastructure. On the basis of the feedback from the usage of application, the study was able to infer that despite the challenges, Internet of Things, wireless sensor networks and cloud, although separate technologies, may be used together to deliver ‘smart’ applications in the field of smart town, smart residences and smart security.
DTMF: Decision Based Trimmed Multimode Approach Filter for Denoising MRI Images

The brain MRI image denoising is a challenging and attracting field for young researchers because it enhances the quality of medical images. Salt and pepper noise is the most dangerous noise which reduces the accuracy of brain diagnosis, and it damages the brain medical images severely, that leads to neurologists to fix incorrect treatments or surgery. The pitfalls raised in the existing denoising methods are less Peak signal to noise ratio, high time consumption and incapable for enormous level of noise range. Hence, this research proposes a novel denoising filter which is entitled as ‘Decision based Trimmed Multimode approach oriented Filter (DTMF)’ for salt and pepper noise removal. Herein, the noise removal section is branched into six steps which efficiently reduce noises based on multimode of majority strength. The main concepts used in this research are viz. decision based approach, trimming process, majority of intensity, median, mean, dynamic windows and Square shaped Exemplar Modeled Patch Mechanism (SEMPM). The essential contributions of this approach are i) designing rule set for majority strength structured multimode denoising, ii) computation of majority property oriented parameters like majority-instance, majority strength and majority value, iii) novel SEMPM mechanism to predict noise-free data. The novel SEMPM mechanism grants a solution for the prediction of noise-free pixel in account of the noisy pixels whose surrounding window is completely packed by noisy data. The proposed decision-based approach removes the salt and pepper noise with high peak signal to noise ratio even for huge noise range, with reasonable time consumption.
Modeling acute care utilization: practical implications for insomnia patients

Abstract Machine learning models can help improve health care services. However, they need to be practical to gain wide-adoption. In this study, we investigate the practical utility of different data modalities and cohort segmentation strategies when designing models for emergency department (ED) and inpatient hospital (IH) visits. The data modalities include socio-demographics, diagnosis and medications. Segmentation compares a cohort of insomnia patients to a cohort of general non-insomnia patients under varying age and disease severity criteria. Transfer testing between the two cohorts is introduced to demonstrate that an insomnia-specific model is not necessary when predicting future ED visits, but may have merit when predicting IH visits especially for patients with an insomnia diagnosis. The results also indicate that using both diagnosis and medications as a source of data does not generally improve model performance and may increase its overhead. Based on these findings, the proposed evaluation methodologies are recommended to ascertain the utility of disease-specific models in addition to the traditional intra-cohort testing.
A Randomized Dot Pattern Character Encoding Scheme (R-DPCES) for Steganography

Randomization is popularly used in encryption techniques to improve cryptographic security compared to their deterministic counterparts. A cipher text is chosen randomly from a set of cipher texts matching the message to encipher a message. This paper proposes randomizing the existing DPCES to secure information transmission in a steganography system. The randomization concept is applied to a flexible DPCES, a Character Binary encoding scheme used in steganography. This would significantly improve the effectiveness of defense against statistical analysis aimed at revealing the message of suspecting the steganography method is under attack. Knowledge of the exact mapping dot pattern applied to encode the message is required to extract the message. An attacker's probability of knowing the encoding scheme would be very low, if not zero. Thus, the Steganography system becomes highly secured with a randomized encoding scheme. The binary data is computed using R-DPCES and inserted into the cover. The stego-cover is transmitted to the intended recipient through the public channel.
Modern Dance Virtual Person Tracking Technology Based on AdaBoost Algorithm

With the development of science and technology, more and more high-tech technologies are applied to the tracking system of dance virtual human. The remote dynamic interaction detection method designed based on AdaBoost algorithm is widely used in real life. This paper mainly designs the remote dynamic interaction, dynamic monitoring and auxiliary functions based on AdaBoost algorithm (image processing and matching algorithm). Firstly, digital coding and compression are widely used in video transmission. Secondly, it makes a brief theoretical analysis of AdaBoost and its related mathematical models, and then establishes a virtual human tracking system using MATLAB software, and gives the corresponding experimental results. The final experimental results show that the detection accuracy of the virtual person tracking technology is more than 90%, and the false detection rate is low.
Explicit deflation in Golub-Kahan-Lanczos bidiagonalization methods

We discuss a simple, easily overlooked, explicit deflation procedure applied to Golub-Kahan-Lanczos Bidiagonalization (GKLB)-based methods to compute the next set of the largest singular triplets of a matrix from an already computed partial singular value decomposition.Our results here complement the vast literature on this topic, provide additional insight, and highlight the simplicity and the effectiveness of this procedure.We demonstrate how existing GKLB-based routines for the computation of the largest singular triplets can be easily adapted to take advantage of explicit deflation, thus making it more appealing to a wider range of users.Numerical examples are presented including an application of singular value thresholding.
Life Skills as a resource to start inclusion processes at school: a study on TFA participants

Twenty-first century teachers are faced with challenges and rapid societal changes that inevitably require skills that facilitate the development of resilience and coping factors. These factors become fundamental above all for specialized teachers, who today are indispensable figures for integrating and supporting not only the individual student with difficulties, but the entire class group. In this regard, the contribution presents some results of a research carried out on 139 enrolled in the Active Formative Training (AFT) course on Information and Communication Technologies (ICT) for special teaching, to identify the skills and limitations perceived during their professional career. From the results of the interviews, it emerges that the participants in the training, mostly teachers, consider some aspects related to teaching practices and the working context as indispensable to develop processes of inclusion at school, which in turn are associated with perceived emotional, social, and cognitive competencies.&#x0D; &#x0D; Le Life Skills come risorsa per avviare processi di inclusione a scuola: uno studio sui partecipanti al TFA.&#x0D; Gli insegnanti del XXI secolo si trovano di fronte a sfide e a rapidi cambiamenti sociali, che richiedono inevitabilmente delle competenze che facilitino lo sviluppo di fattori di resilienza e di coping. Tali fattori diventano fondamentali soprattutto per gli insegnanti specializzati, che ad oggi sono delle figure indispensabili per integrare e sostenere non soltanto il singolo alunno con difficoltà, ma l’intero gruppo classe. A tale proposito il contributo presenta alcuni risultati di una ricerca svolta su 139 iscritti al corso Tirocinio Formativo Attivo (TFA) sulle Tecnologie Informatiche e di Comunicazione (TIC) per la didattica speciale, per identificare le competenze e i limiti percepiti durante il proprio percorso professionale. Dai risultati delle interviste emerge come i partecipanti alla formazione, per lo più insegnanti, considerino alcuni aspetti legati alle pratiche didattiche e al contesto lavorativo come indispensabili per sviluppare processi di inclusione a scuola, che a loro volta sono associati alle competenze emotive, sociali e cognitive percepite.
Long Messages Segmentation for Efficient Message Cryptography

Protecting LSB method of data steganography is a vital issue. In this paper research a secure LSB method will be introduced. The method will use a private key to divide a covering image into block and a secret block will be selected to apply message hiding and message extracting. The extracted message will be very sensitive the selected block size and the selected block number. The proposed method will simplify the hiding and extraction functions by using patch method, this simplification will increase the method efficiency. The proposed method will be tested for sensitivity, several images and several messages will be selected and the quality of the stego images will be examined.
THYROID DISORDERS IN NORTH INDIA AND THEIR REPORTING BY BETHESDA SYSTEM Â€“ 1 YEAR RETROSPECTIVE STUDY

Background: Thyroid nodules are very common clinical problem and thyroid cancer is becoming more prevalent. Fine needle aspiration cytology (FNAC) has become a well established modality in the diagnosis, staging and follow up of thyroid nodules. FNAC results are routinely classified using the Bethesda system for reporting thyroid cytopathology. The Bethesda system for reporting thyroid cytopathology is a significant step to standardize the thyroid FNA reporting. It has high reproducibility, predictive value and improved clinical significance. Aims And Objectives: To determine the spectrum of thyroid disorders in north India and to determine the accuracy and reliability of FNAC in our center. Material And Method: A retrospective study of FNAC thyroid nodules was carried out on 133 patients referred to our Department from July 2021 to August 2020. Slides were retrieved from the cytopathology section of the Department of Pathology, GMCH, reviewed and then classified as per the Bethesda system for reporting thyroid cytopathology. Patients of all ages and gender were included in the study. Results: Total 133 FNAC procedures were performed during the study period. 86 cases were females and 47 were males with male to female ratio of 1:1.83. The nodules of 9 patients were classified as Bethesda category-I, 74 patients as Bethesda category-II, 11 patients as Bethesda category-III, 8 patients as Bethesda category-IV, 9 patients as Bethesda category-V and 22 patients as Bethesda category VI. Out of 133 patients, only 36 patients underwent for surgery among these 36 cases, 4 were classified as Bethesda category-IV , 9 as Bethesda category-V and 22 as Bethesda category-VI on cytology which were further confirmed as cases of thyroid malignancy on histopathology reports. Conclusion: Our study substantiates greater reproducibility among Pathologists using TBSRTC to arrive at a precise diagnosis with an added advantage of predicting the risk of malignancy which enables the clinician to plan for surgery, extent of surgery or follow-up of the patients by repeating the FNA of thyroid nodules at specific intervals.
PENGARUH PENERAPAN SISTEM INFORMASI AKUNTANSI PENERIMAAN KAS DANA DEPOSITO DALAM MENINGKATKAN PENGENDALIAN INTERN DI PT BPR KERTA RAHARJA CABANG BANJARAN

The purpose of this study is to investigate the extent to which the accounting information System for Cash Receipts on Deposit Funds has an impact on improving internal control at PT BPR Kerta Raharja. The descriptive quantitative research approach was employed, with data collected through field investigations, interviews, and questionnaires. The sample size for this study was 22 employees from PT BPR Kerta Raharja. Based on the study's findings, the hypothesis was accepted after the results of hypothesis testing using the t-test showed a significant level of 0.001 0.000. This indicates a substantial association between the Accounting Information System for Cash Receipts, Deposits, and Internal Control, which validates the premise. Based on the coefficient of determination calculations, the effect of the Accounting Information System for Cash Receipts on Deposit Funds on Internal Control at PT BPR Kerta Raharja Banjaran Branch is 45.7 percent, with the remaining 54.3 percent influenced by other factors not investigated by the author.
PENTINGNYA BAHASA INGGRIS UNTUK ANAK USIA DINI DI DESA PURWOASRI, 28 METRO UTARA

This paper discusses about the importance of English education for early childhood. English education is needed along with the progress of a country. Therefore, education English as an international language was introduced as early as possible to the students before the age of 12 years. Early childhood is children in the age range 2-7 years and is a golden period for language development. They were able to learn to speak like native speakers. However, they are still on the cognitive development of preoperational that has a high self-centered, do not understand abstract things, just to understand the symbols and still pre-logical thinking. Therefore, English language education for children in need of methods and processes appropriate and effective teaching, for example through song, music and movement. The method is considered successful and very suitable for early childhood in learning English. To develop the method also requires the teacher's role as an educator in the process of learning English.
Balanced Even-Variable Rotation Symmetric Boolean Functions with Optimal Algebraic Immunity, Maximum Algebraic Degree and Higher Nonlinearity

Rotation symmetric Boolean functions are good candidates for stream ciphers because they have such advantages as simple structure, high operational speed and low implement cost. Recently, Mesnager et al. proposed for the first time an efficient method to construct balanced rotation symmetric Boolean functions with optimal algebraic immunity and good nonlinearity for an arbitrary even number of variables. However, the algebraic degree of their constructed [Formula: see text]-variable ([Formula: see text]) function is always less than the maximum value [Formula: see text]. In this paper, by modifying the support of Boolean functions from Mesnager et al.’s construction, we present two new constructions of balanced even-variable rotation symmetric Boolean functions with optimal algebraic immunity as well as higher algebraic degree and nonlinearity. The algebraic degree of Boolean functions in the first construction reaches the maximum value [Formula: see text] if [Formula: see text] is odd and [Formula: see text] or [Formula: see text] for integer [Formula: see text], while that of the second construction reaches the maximum value for all [Formula: see text]. Moreover, the nonlinearities of Boolean functions in both two constructions are higher than that of Mesnager et al.’s construction.
RANCANG BANGUN MODEL PENGIDENTIFIKASI SUARA HURUF HIJAIYAH DENGAN METODE MEL FREQUENCY CEPSTRUM COEFFICIENT DAN CONVOLUTIONAL NEURAL NETWORK

Learning the Qur'an is a necessity for a Muslim, because the Qur'an acts as a guideand way of life. One thing that is learned in the Qur'an is how to pronounce Hijaiyah letters orMakharijul letters. In learning Makharijul Letters it takes an ustaz or accompanying teacher whois limited by distance and time. To overcome the limitations of distance and time, a learningapplication model is needed that can be accessed without the limitations of distance and thetime. This is studied aim to develop the Hijaiyah letter recognition model using the MelFrequency Cepstrum Coefficient (MFCC) and Convulational Neural Network (CNN) methods.Based validation results, the model built using the MFCC and CNN methods can identify theletters read with an accuracy of 49.1%. Then based of the test result with Confusion Matrix, thismodel have a precision value of 50%, recall is 53%, and F-Measure is 0.514.
Interference Suppression of Small Weak Scattering Targets in High-resolution SAR Image

SAR images play an important role in target detection. However, speckle noise, thermal noise and azimuth blur in SAR images can interfere with the small weak scattering targets detection. The denoising algorithm based on Doppler power spectrum can simultaneously remove the speckle noise, thermal noise and azimuth blur of SAR images at the expense of resolution. We draw on the ideas of sparse representation and image fusion, and propose image restoration fusion based on sparse representation (IRF), which makes it possible to keep the contours of inland waters clear while suppressing SAR image noise.
A Layered Tracking Method for Group Space Object

It is a great challenge to accurately estimate space target state with low SNR induced by long range. And power acting on space target is complex and difficult to be exactly described. Thus, a layered tracking method (LTM) is proposed for simultaneously tracking the centre and individuals of dispersed-spaced space target group. Based on the difference between target and centre of group, the model of local motion defined as the target motion relative to the centre is derived to be simply linear. And the error in space target motion model is counteracted. Accordingly, a two-layer tracking scheme is presented, in which the top and bottom layers are respectively represented by the centre and individuals. At the top layer, with more accurate centre measurement via fusing measurements of each target, the centre of space targets can be estimated more accurately than individual target within the group. At the bottom layer, the local motion state is estimated and combined with relatively more accurate centre state estimate to acquire each target state, as opposed to tracking space target directly. Compared with other traditional methods, it is validated that the proposed tracking method can provide higher target state estimation accuracy. Numerical simulations are performed to illustrate the effectiveness of the proposed technique.