Substantial Content Reclamation for Clustering

The massive volume of data stored in computer files and databases is rapidly increasing. Users of these data, on the other hand, demand more complex information from databases. The video data have exponential growth towards accessing and storing. The vital problem associated to video data is efficient, qualitative and fast accessing. We talk about how video pictures are clustered. We presume video clips have been divided into shots, each of which is denoted by a collection of key frames. As a result, video clustering is limited to still key frame pictures. In amble database finding the qualified data set (clusters) is quite time-taking job. The video data mining relate to multi–lingual text, numeric, image, video, audio, graphical, temporal, relational and categorical data. It may be any kind of information medium that can be represented, processed, stored, fast accessing or summarization of clusters are required due to which significant frame-set is formed. Due to sampling error and test reliability in video, substantial changes of more than one frame are predicted. The goal of this article is to show how to employ a familiar and easy nonparametric statistical approach (chi-square) to select eligible data/framesets for analysis. The chi-square model illustrated here is a straightforward, sensible, fast, reduce saddle, and easiest method. Skimming/ Summarization and clipping technique are further enhanced by this technique along with video database maintenance technique from simple descriptors to a complex description schemes like spatial and temporal or high dimensional indexing.

865 Reducing Delays in Cholecystectomy Surgery of Patients Admitted with Gallstone-Related Disease Within Gold Standard Time Frame Set Out By NICE

Introduction As per NICE guidelines, Cholecystectomy Quality Improvement Collaborative (Chole-QuIC) aims for 80% of eligible patients with gallstone-related disease to receive their cholecystectomy within 8 days of presentation1. Only 63.6% of eligible patients at East Lancashire Hospitals NHS Trust (ELHT) had their surgery within the target time. This project was done to identify the reasons behind ELHT not achieving the set target and to implement changes to overcome this. Method This was a retrospective review of a prospectively collected data of 444 patients from the ELHT Chole-QuIC database (July 2019-November 2020). Data were analysed in three periods: initial period (July 2019-November 2019), pre-COVID-19 period (December 2019-February 2020), COVID-19 period (March 2020-November 2020). Time to surgery was established. If the 8-day target was not met, reasons behind the delay were recorded. Results During the first cycle, the main reasons delays included the patients being temporarily unfit (13.8%), insufficient theatre capacity (13.8%) and variations in treatment plans (11.32%). 8% of patients had re-admissions related to their gallstone disease. Changes were implemented forward included a clear local gallstone disease management pathway and CholeQuIC referral system, increasing theatre capacity, and allocating pre-operative assessment slots. Gold standard cholecystectomy target period improved from 63.6% to 67.4% within three months of changes. However, the figure drastically reduced during the COVID-19 pandemic (36.3%) as elective surgeries were temporarily suspended. Conclusions The implementation of a gallstone disease management pathway, a coordinated referral system and additional theatre capacity contributed to the increase in cholecystectomies that were performed within the 8-day national target period.

FRAME ANALYSIS OF THE NOTION «CONTROL» IN GERMAN FOREIGN LANGUAGE TEACHING DISCOURSE

The article discusses the terminological competence of students in foreign language teaching. Terminological competence means knowledge of terms of the subject area and ability to apply them in professional activity according to the set tasks. A frame analysis of terms is proposed as one of the methods that contribute to faster and better formation of terminology competence. Frame analysis includes the compilation of a frame and a detailed description of its slots. There is an example of a frame analysis of the concept of «control» in German in foreign language teaching discourse. As a result of the analysis of this discourse, a two-level frame was compiled, whose slots of the first order are «management», «diagnostics», «examination», «teaching». Second-order slots include «teacher» and «student» slots that relate to the first-level slot «management». It is concluded that slots of the frame set projection to functions of control in foreign language teaching discourse. Frame analysis is seen as a method to reveal the semantic potential of terms and to better understand their correlation in the term system.

Using INTEGRATE-HTA for the assessment of videorasterstereography in idiopathic scoliosis

Objective For the assessment of videorasterstereography compared with radiography for monitoring idiopathic scoliosis, new tools given by the INTEGRATE-HTA methodology were included within the frame set by the authority. In contrast to the usual linear approach by covering the single domains' safety and efficacy, costs, and ethical, legal, socio-cultural and organizational issues (ELSOI) separately, the methodology is based on the assumption of interactions of different aspects of the domains. From the very beginning, these interactions are captured systematically using various tools and are repeatedly discussed with stakeholders. Methods Relevant databases were systematically searched for studies and question catalogues were processed in order to be able to search for specific aspects in orienting bibliographic research. An initial logic model was developed and successively expanded. A synoptic table showing multiple mapping of aspects to domains, a complexity checklist, and a semantic complex highlighting the socio-cultural impact of the disease were newly developed. Results Four diagnostic studies with high risk of bias were included. For the clinical outcome, Cobb angle standard deviations up to 8.2 degrees and average measurement differences up to 8.8 degrees were determined. These differences in measurement accuracy correspond to those observed for purely radiographic measurements in other studies. In addition to freedom from radiation as the greatest advantage, there were clear arguments in favor of videorasterstereography when considering ELSOI, for example less harm. Conclusions Using INTEGRATE-HTA contributes to identify interactions between domains and to significantly expand the perspective on a technology. It improves patient-centered understanding and facilitates discussions.

Video analysis method of basketball training assistant based on deep learning theory during COVID-19 spread

During covid-19, basketball training was stopped. Instead, the basketball video analysis is used. In this paper, literature, theoretical analysis, numerical simulation, experimental research and other research methods are used. The ant colony algorithm model of deep learning optimization for basketball technical and tactical decision-making is established to solve the optimization problem of actual technical and tactical decision-making. In this paper, video image correlation algorithm is used. In the video of players’ free throw basket, there are many independent frames. The real frame set of free throw basket includes the whole process of jumping, arm lifting, squatting and stretching. The shooting frame set and shooting information of the ball are obtained. In this paper, a shot frame detection algorithm is proposed by analyzing multiple samples of multi shot video. The mathematical model of the shooting frame is established, which can locate the shooting frame quickly and accurately and determine the penalty frame set. Further obtain the basketball release status information for preparation. The reliability and robustness of the algorithm are verified by experiments on several samples. It provides a new method for basketball training during covid-19.

Some curious results related to a conjecture of Strohmer and Beaver

We study results related to a conjecture formulated by Strohmer and Beaver about optimal Gaussian Gabor frame set-ups. Our attention will be restricted to the case of Gabor systems with standard Gaussian window and rectangular lattices of density 2. Although this case has been fully treated by Faulhuber and Steinerberger, the results in this work are new and quite curious. Indeed, the optimality of the square lattice for the Tolimieri and Orr bound already implies the optimality of the square lattice for the sharp lower frame bound. Our main tools include determinants of Laplace–Beltrami operators on tori as well as special functions from analytic number theory, in particular Eisenstein series, zeta functions, theta functions and Kronecker’s limit formula. We note that our results also carry over to energy minimization problems over lattices and a heat distribution problem over flat tori.

Penerapan K-Means Clustering Untuk Seleksi Frame Dominan Berbasis NTSC Pada Obyek Bergerak

<p class="Abstrak">Obyek dinyatakan bergerak jika terjadi perubahan posisi dimensi disetiap <em>frame</em>. Pergerakan obyek menyebabkan obyek memiliki perbedaan bentuk pola disetiap <em>frame-</em>nya. <em>Frame</em> yang memiliki pola terbaik diantara <em>frame</em> lainnya disebut <em>frame</em> dominan. Penelitian ini bertujuan untuk menyeleksi <em>frame</em> dominan dari rangkaian <em>frame</em> dengan menerapkan metode K-means <em>clustering</em> untuk memperoleh <em>centroid</em> dominan (<em>centroid</em> dengan nilai tertinggi) yang digunakan sebagai dasar seleksi <em>frame</em> dominan. Dalam menyeleksi <em>frame</em> dominan terdapat 4 tahapan utama yaitu akuisisi data, penetapan pola obyek, ekstrasi ciri dan seleksi. Data yang digunakan berupa data video yang kemudian dilakukan proses penetapan pola obyek menggunakan operasi pengolahan citra digital, dengan hasil proses berupa pola obyek RGB yang kemudian dilakukan ekstraksi ciri berbasis NTSC dengan menggunakan metode statistik orde pertama yaitu <em>Mean</em>. Data hasil ekstraksi ciri berjumlah 93 data <em>frame</em> yang selanjutnya dikelompokkan menjadi 3 <em>cluster</em> menggunakan metode K-Means. Dari hasil <em>clustering</em>, <em>centroid</em> dominan terletak pada <em>cluster</em> 3 dengan nilai <em>centroid</em> 0.0177 dan terdiri dari 41 data <em>frame</em>. Selanjutnya diukur jarak kedekatan seluruh data <em>cluster</em> 3 terhadap <em>centroid</em>, data yang memiliki jarak terdekat dengan <em>centroid</em> itulah <em>frame</em> dominan. Hasil seleksi <em>frame</em> dominan ditunjukkan pada jarak antar <em>centroid</em> dengan anggota <em>cluster</em>, dimana dari seluruh 41 data frame tiga jarak terbaik diperoleh adalah 0.0008 dan dua jarak bernilai 0.0010 yang dimiliki oleh <em>frame</em> ke-59, ke-36 dan ke-35.</p><p class="Abstrak"> </p><p class="Abstrak"><em><strong>Abstract</strong></em></p><p class="Abstract"><em>The object is declared moving if there is a change in the position of the dimensions in each frame. The movement of an object causes the object to have different shapes in each frame. The frame that has the best pattern among other frames is called the dominant frame. This study aims to select the dominant frame from the frame set by applying the K-means clustering method to obtain the dominant centroid (the highest value centroid) which is used as the basis for the selection of dominant frames. In selecting dominant frames, there are 4 main stages, namely data acquisition, determination of object patterns, feature extraction and selection. The data used in the form of video data which is then carried out the process of determining the pattern of objects using digital image processing operations, with the results of the process in the form of an RGB object pattern which is then performed NTSC-based feature extraction using the first-order statistical method, Mean. The data from feature extraction are 93 data frames which are then grouped into 3 clusters using the K-Means method. From the results of clustering, the dominant centroid is located in cluster 3 with a centroid value of 0.0177 and consists of 41 data frames. Furthermore, the proximity of all data cluster 3 to the centroid is measured, the data having the closest distance to the centroid is the dominant frame. The results of dominant frame selection are shown in the distance between centroids and cluster members, where from all 41 data frames the three best distances obtained are 0.0008, 0.0010, and 0.0010 owned by 59th, 36th and 35th frames.</em></p><p class="Abstrak"><em><strong><br /></strong></em></p><p> </p>

Automatic Coconut Tree Climber with Expropriator

In this new era, modernization plays a key role. Many human tasks are now being replaced with innovations and robots. There is an urge to handle modern technology. Only a few are interested in climbing trees due to many disparities faced by hikers but demand high pay. This results in a tremendous demand for tree climbing manpower. There are different approaches available for the climbing of coconut trees, however, they require people to accompany the mechanical structure. The idea of a smart remote-controlled tree climbing mechanism is proposed to make the climbing process easier and convenient. Coconut tree climber is a machine used without human effort to climb coconut trees and harvest coconut. It consists of a hexagonal frame holding all the devices inside it and by adjusting the driver circuit, the complete structure can be driven up and down. This mechanical frame set-up is made of lightweight material. Gear motors are powered by the driver circuit wherein the battery supplies. The treewidth usually differs between 45 cm and 55 cm. By considering the tree structure the frame size is designed accordingly. Since width changes between trees, the mechanical frame is constructed with various diameters using spring mechanism. Grip wheels are used to produce friction. Gear motors are used which produces small quantity of regeneration. The battery can store this energy and reuse it. The Robotic arm is placed on the mechanical frame to pick the coconut without any crew from the tree. The machine's cost is about ₹ 20k. This automated remotecontrolled coconut climber is supposed to be very obligatory for farmers.

Frame sets for a class of compactly supported continuous functions

The frame set of a function [Formula: see text] is the subset of all parameters [Formula: see text] for which the time-frequency shifts of [Formula: see text] along [Formula: see text] form a Gabor frame for [Formula: see text] In this paper, we investigate the frame set of a class of compactly supported continuous functions which includes the [Formula: see text]-splines. In particular, we add some new points to the frame sets of these functions. In the process, we generalize and unify some recent results on the frame sets for this class of functions.