Real-Time Face Recognition System Using KPCA, LBP and Support Vector Machine

With increasing security threats, Biometric systems have importance in different fields. This appears clearly exactly after the rapid development that happened in power of computing. In this paper, the Design and implementation of a real-time face recognition system are presented. In such a system, Kernel principal component analysis (KPCA) and Local binary pattern (LBP) are used as feature extraction methods with the aid of support vector machine (SVM) to work as a classifier. A comparison between traditional feature extraction methods as (PCA and LDA) and a proposal methods are performed as well as a comparison between support vector neural network and artificial neural network classifier are also implemented. Two types of experiments, On-line, and Off-line experiments are done. In the On-line experiment, a new database is created and used. While in the off-line experiment, two types of databases (ORL and YALE) are used to estimate the performance and efficiency of the system. The combinations of these methods together enhances the experimental results in compare with other methods

Face Recognition System Based on Kernel Discriminant Analysis, K-Nearest Neighbor and Support Vector Machine

Although many methods have been implemented in the past, face recognition is still an active field of research especially after the current increased interest in security. In this paper, a face recognition system using Kernel Discriminant Analysis (KDA) and Support Vector Machine (SVM) with K-nearest neighbor (KNN) methods is presented. The kernel discriminates analysis is applied for extracting features from input images. Furthermore, SVM and KNN are employed to classify the face image based on the extracted features. This procedure is applied on each of Yale and ORL databases to evaluate the performance of the suggested system. The experimental results show that the system has a high recognition rate with accuracy up to 95.25% on the Yale database and 96% on the ORL, which are considered very good results comparing with other reported face recognition systems

Breast Cancer Diagnostic System Based on MR images Using KPCA-Wavelet Transform and Support Vector Machine

Automated detection and accurate classification of breast tumors using magnetic resonance image (MRI) are very important for medical analysis and diagnostic fields. Over the last ten years, numbers of methods have been proposed, but only few methods succeed in this field. This paper presents the design and the implementation of CAD system that has the ability to detect and classify the tumor of the breast in the MR images. To achieve this, k-mean clustering methods and morphological operators are applied to segment the tumor. The gray scale, Texture and symmetrical features as well as discrete wavelet transform (DWT) are used in feature extracted stage to obtain the features from MR images. Kernel principle components analysis (K-PCA) are also applied as a feature reduction technique and support vectors machine (SVM) are used as a classifier. Finally, the experiments results have confirmed the robustness and accuracy of proposed syste

Modelling the Ecosystem Behavior of Abu-Ziriq Marsh in South of Iraq Under Different Water Discharges Scenarios

The marshlands are of fundamental importance to Iraq, a unique ecosystem providing local inhabitants with an essential source of habitat and livelihoods. This paper aims to study the ecosystem behavior of Abu-Ziriq Marsh in the south of Iraq under different scenarios using the Ecosystem Functions Model Program (HEC-EFM) and Hydrologic Engineering Center Data Storage System Visual Utility Engine (HEC-DSSVue). To this end, data was converted from tri-monthly and semi-monthly to daily data using the HEC-DSSVue program. The daily data natural(flow, stage) was used for five years between 2013 and 2018. The prediction process was evaluated using three criteria: correlation coefficient (R), root mean square error (RMSE), and the Nash–Sutcliffe effectivity coefficient (NSE). Results of R, RMSE and NSE for the daily inflow discharge (stage) of natural were 0.98 (0.93), 1.55 (0.19) and 0.95 (0.73). Five scenarios of a percentage decrease in gage(flow, stage) with 2%, 4%, 6%, 8% and 10% were investigated. Results showed that the decrease in discharge from 2% to 8% did not significantly affect environmental relations and could be used by the competent authorities. However, when the discharge was reduced to 10%, the environmental relations were greatly affected and threatened the life of the organisms. In addition to that, results for wetland health reverse lookup at the fifth scenario show that Abu–Ziriq Marsh need (70.2%) as a percent of the time, when flows equal or exceed four m3/sec. This discharge was chosen because it can be supplied on most days of the year, which is the time needed to be revived when flows equal or exceed 4 (m3/sec)

Study the Effect of Silica Gel Powder on Clathrate Hydrate Formation Behavior for HFC-134a Gas.

الكلاثريت هيدرات عبارة عن جزيئات معقدة تتكون من الاتصال بين الماء والغاز عند الضغط العالي ودرجات الحرارة المنخفضة. أحد الأهداف الهامة لتكنولوجيا هيدرات الغاز هو تعزيز تكوين الهيدرات أو تقليل وقت التنوي لتشكيل الكلاثريت . تم دراسة تأثير مسحوق هلام السيليكا كمحفز على تركيبة هيدرات الغاز R-134a في تجربة نظام ايزوكوريك (حجم ثابت). من الملاحظ أن للوسط المسامي  تأثير كبير في زيادة سرعة التنوي وكذلك تحسين نمو الهيدرات. في التجربة ، تمت دراسة تأثير مسحوق هلام السيليكا لتحديد تأثيرها على تكوين وتبريد 134 هيدرات  و تم الحصول على العديد من الوظائف الموضوعية من النماذج الحركية مثل كمية الغاز المستهلكة (∆n) ومعدل النمو (r (t)) وثابت المعدل الظاهري (Kapp) وتحويل الماء إلى هيدرات. ازدادت كمية الغاز المستهلكة (∆n) في النظام الثنائي مع زيادة الضغط الأولي لتكوين الهيدرات ، وأيضا معدل نمو الهيدرات (r (t)) وزيادة تحويل الماء لزيادة الهيدرات عندما تكون هذه هي المرة الأولى التي يؤثر فيها مسحوق هلام السيليكا. على هذه الوظائف  بمتوسط ​​ حجم  نشط (900) نانومتر ، مساحة سطح (0.65) م 2 / جم ، حجم المسام 210.85 سم 3 / جم ومتوسط ​​حجم المسام (900) نانومتر الذي درس للاستخدام في التطبيقات الصناعية ومعالجة المياه. بإضافة مسحوق هلام السيليكا يتحسين نمو الهيدرات و   ذلك لانه يزيد من ذوبان غاز الهيدرات ويقلل من زاوية التلامس. بالإضافة إلى ذلك ، مسحوق هلام السيليكا يؤثر بشكل إيجابي على الاتصال الماء مع الغاز من خلال زيادة سطح التفاعل بين الغاز والماء وهذا يزيد من معدل تكوين الهيدرات.One of the important aims of gas hydrate technology is to enhance the formation of hydrate or reduction the induction time for clathrate formation. The effect of the different promoter silica gel powder on R-134a gas hydrate formation has been investigated in the isochoric system experiment. It is noted that the purse media have a significant effect in increasing the speed of nucleation as well as improving the growth of hydrate. In the experiment, the effect of silica gel powder was studied to determine their effect on the composition and cooling capacity of 134 hydrates. From kinetic models were obtained many objective functions such as the amount of gas consumed (∆n), the growth rate (r (t)), and conversion of the water to hydrate. The gas consumed (∆n) of binary system increased with increase initial pressure of hydrate formation, also the hydrate growth rate (r (t)) and increase conversion of water to hydrate increase  when this the first time that the effect of silica gel pweder on these functions with average active size (900) nm, BET surface area (0.65) m2/g, pore volume 210.85 cm3/g and average pore size (900) nm that studied for use in industrial applications and water treatment. The improvement of hydrate growth is marked by the addition of silica gel powder, which in turn increase the solubility of hydrate gas and reduce the contact angle. In addition,   silica gel powder positively the contact with the gas through the increase of the interaction surface between gas and water and this increases the rate of formation of hydrate

Exploiting Wavelet Transform, Principal Component Analysis, Support Vector Machine, and K-Nearest Neighbors for Partial Face Recognition

Facial analysis has evolved to be a process of considerable importance due to its consequence on the safety and security, either individually or generally on the society level, especially in personal identification. The paper in hand applies facial identification on a facial image dataset by examining partial facial images before allocating a set of distinctive characteristics to them. Extracting the desired features from the input image is achieved by means of wavelet transform. Principal component analysis is used for feature selection, which specifies several aspects in the input image; these features are fed to two stages of classification using a support vector machine and K-nearest neighborhood to classify the face. The images used to test the strength of the suggested method are taken from the well-known (Yale) database. Test results showed the eligibility of the system when it comes to identify images and assign the correct face and name

Monitoring and Modelling Morphological Changes in Rivers Using RS and GIS Techniques

River geomorphological investigation issues have received little attention in most countries of the world. Such processes become a pressing necessity due to climate change and anticipated events of extraordinary surges and dry seasons, which may debilitate the security of adjacent and downstream cities, particularly in locales that are exceedingly delicate and influenced by climatic changes. Al-Abbasia reach is a river that runs through the middle of the Euphrates River and is known for its numerous bends and meanders. The study of hydraulic structures such as barrages can provide important information about their influences on morphological processes in river reaches near the barrage upstream and downstream. Hydraulic analysis is made of the river behavior in u/s and d/s of hydraulic structures like barrages as a result of sediment deposition and erosion in u/s and d/s. A study, i.e., research on the impacts of the Abbassia barrage on the river system, has been conducted to address this issue using multi-temporal Landsat satellite data from 1976 to 2022 provided by the USGS. The study reach is located 5 kilometres upstream and 5 kilometres downstream of the Abbassia reach. Following the construction of the barrage, which had an impact on the sedimentation and geometry of the river, morphological variations took place in this part of the Al Abbassia reach. In this study, morphological changes throughout 49 years between 1976 and 2022 were investigated utilising remote sensing (RS) and geographic information system (GIS) approaches. Additionally, four image groups from three separate decades were used to perform change detection (1990–2000, 2000–2010, and 2010–2022). In this study, a monitoring system using Landsat-3 MSS: 1985, Landsat-5 TM: 1990, 1995, 2000, 2005, and Landsat-8 OLI: 2010, 2011, 2015, 2021, 2022 were employed to map river planform changes. The long-term comparison of this series of satellite images and historical maps for the period 1976–2022 indicates a continuation of change in the reach study with a rate of approximately 56, 33, 97, and 55% for upstream and 19%, 26%, 3%, and 45% for downstream for the width, area, deposition, and erosion, respectively. Furthermore, it is observed that there is a shift in river course within 200 m downstream of the barrage for the period of 1985–1990. The findings of this study, which monitor river morphological change at finer temporal and spatial resolutions, are crucial for promoting sustainable river management. They also aid in the investigation of river behaviour, which is necessary for providing the best management possible and overcoming the difficulties posed by this important research issue. Doi: 10.28991/CEJ-2023-09-03-03 Full Text: PD

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

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks