Threshold adaptation and XOR accumulation algorithm for objects detection

Object detection, tracking and video analysis are vital and energetic tasks for intelligent video surveillance systems and computer vision applications. Object detection based on background modelling is a major technique used in dynamically objects extraction over video streams. This paper presents the threshold adaptation and XOR accumulation (TAXA) algorithm in three systematic stages throughout video sequences. First, the continuous calculation, updating and elimination of noisy background details with hybrid statistical techniques. Second, thresholds are calculated with an effective mean and gaussian for the detection of the pixels of the objects. The third is a novel step in making decisions by using XOR-accumulation to extract pixels of the objects from the thresholds accurately. Each stage was presented with practical representations and theoretical explanations. On high resolution video which has difficult scenes and lighting conditions, the proposed algorithm was used and tested. As a result, with a precision average of 0.90% memory uses of 6.56% and the use of CPU 20% as well as time performance, the result excellent overall superior to all the major used foreground object extraction algorithms. As a conclusion, in comparison to other popular OpenCV methods the proposed TAXA algorithm has excellent detection ability

Effective Web Page Crawler

The World Wide Web (WWW) has grown from a few thousand pages in 1993 to more than eight billion pages at present. Due to this explosion in size, web search engines are becoming increasingly important as the primary means of locating relevant information. This research aims to build a crawler that crawls the most important web pages, a crawling system has been built which consists of three main techniques. The first is Best-First Technique which is used to select the most important page. The second is Distributed Crawling Technique which based on UbiCrawler. It is used to distribute the URLs of the selected web pages to several machines. And the third is Duplicated Pages Detecting Technique by using a proposed document fingerprint algorithm

A New Approach for Hiding Image Based on the Signature of Coeficients

This paper presents a new approach for hiding the secret image inside another image file, depending on the signature of coefficients. The proposed system consists of two general stages. The first one is the hiding stage which consist of the following steps (Read the cover image and message image, Block collections using the chain code and similarity measure, Apply DCT Transform, Signature of coefficients, Hiding algorithm , Save information of block in boundary, Reconstruct block to stego image and checking process). The second stage is extraction stage which consist of the following steps ( read the stego image, Extract information of block from boundary, Block collection, Apply DCT transform, Extract bits of message and save it to buffer, Extracting message)

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

SETIT 2007 Object Oriented Classification of Forest Images Using Soft Computing Approach

Abstract: In this paper the searching capability of build up an object oriented classification system which is capable of classification a given forest scene into its various constituents. To simplify the problem, six categories of forest structures were defined. These categories are trees, bushes, grasses, foliage, sky and background sky .They are sufficient to represent typical forest scenes dealt with in this application. To implement such classification system. We proposed a Genetic Algorithm (GA) to segmentation image and find the best seed for each category. According to this scheme, an image is divided evenly into small block. Then it is processed block by block. For each block, Discrete Cosine Transform (DCT) is applied to determine some of DCT coefficient in compressed domain as the feature vectors. Then take the seed values for each segment and the DCT coefficients to represented the inputs of feed forward neural network. These system successes in classification all objects in image although used different kinds of activation functions (hyperbolic functions), compares among them and find the best of it in obtaining on fast results. As a result the A soft computing method will be higher classification accuracy than that of traditional pixel-based supervised classification and gives convenient environment to use

Opinion Mining in Arabic Extremism Texts: A Systematic Literature Review

In this paper, a systematic literature review was provided that investigated the present evidence regarding extremist words in Arabic opinion mining methods. This study aimed to perform a Systematic Literature Review (SLR) in order to detect, evaluate, and synthesize the existing evidence regarding opinion mining techniques for extremist Arabic text. From the SLR, it is evident that opinion-mining techniques have several opportunities for detecting extremism in the Arabic text. Over the past few years, multimedia sentiment analysis has gained traction as visual content is becoming more incorporated into social media networking. Opinion mining is the process of identifying, extracting, and categorizing views about anything. It is a sort of Natural Language Processing (NLP) used to track public sentiment about a certain law, policy, or marketing, for example. It entails the creation of a method for collecting and analyzing comments and opinions concerning legislation, regulations, policies, and so on that are posted on social media. The process of information extraction is critical since it is both a beneficial tool and a difficult undertaking. In this article, we have examined the recent and advanced methodologies to extract sentiment from a web-wide item, opinion-mining methods must be automated. Also, we have analyzed the novel Artificial Intelligence and lexical-based algorithms for sentiment analysis. These methodologies find better applications in the customer feedback analysis of any organization

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. Methods: A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Findings: Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Interpretation: Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. Funding: National Institute for Health and Care Research