Deep learning based advanced facial expression recognition system

Yüz duygularının ifadesini tanıma, insanların yüz duygularının yüzlerindeki ifadelere göre sınıflandırılmasını içeren bir araştırma alanıdır. Akıllı insan-bilgisayar etkileşimi, biyometrik güvenlik, robotik ve depresyon, otizm için klinik tıp ve ruh sağlığı sorunları gibi birçok farklı uygulamada kullanılabilir. Bu tez, yüz ifadesi tanıma (FER) için ileri teknikleri araştırır ve analiz eder ve pratik uygulamalar için bir zeka sistemleri geliştirir. Bu çalışmada, FER doğruluğunu artırmak için birkaç derin öğrenme tabanlı çerçeve geliştirilmiştir. Belirli katmanlarda özellik çıkarma amacıyla üç ana tip önceden eğitilmiş ağ (AlexNet, GoogleNet ve SqueezeNet) kullanılır. Ayrıca, k-en yakın komşular (KNN), Destek Vektör Makinesi (SVM) ve Karar Ağacı sinir ağları algoritmaları, her tür önceden eğitilmiş ağ için sınıflandırıcı olarak kullanılır. Bu araştırmada, Yedi tür yüz ifadesini temsil eden çok sayıda görüntü içeren iki veri seti kullanılmıştır. SVM ile GoogleNet için elde edilen maksimum doğruluk 91.09, SVM 98.2766 ile SqueezeNet ve KNN ile AlexNet için yaklaşık %100'dür. Elde edilen sonuçlar, en iyi sınıflandırma sonuçları için yeniden eğitim zamanı ve kaynakları sağlayan öznitelik çıkarımı olarak önceden eğitilmiş bir ağ kullanabileceğimizi göstermektedir.Facial emotion expression recognition is a field of research that comprises the classification of face emotions of humans by expressions on their faces. It can be used in many different applications including intelligent human-computer interaction, biometric security, robotics and depression, and clinical medicine for autism, and mental health problems. This thesis explores and analysis advanced techniques for facial expression recognition (FER) and develops intelligence systems for practical applications. In this study, several deep learning-based frameworks have been developed to improve FER accuracy. Three main types of pre-trained networks (AlexNet, GoogleNet, and SqueezeNet) are utilized for feature extraction purposes at a certain layer. Moreover, k-nearest neighbors (KNN), Support Vector Machine (SVM), and Decision Tree neural networks algorithms are employed as a classifier for each type of pre-trained network. Two datasets are used in this research including a large number of images representing Seven types of facial expressions. The maximum accuracy obtained for GoogleNet with SVM is 91.09, SqueezeNet with SVM 98.2766, and AlexNet with KNN at about 100%. The results obtained indicate that we can use a pre-trained network as feature extraction which provides a pre-training time and resources for best classification results

Turkish-French Relations 1923-1939 A.D

In 1921, the League of Nations placed Alexandretta under the French mandate. The Mandatory began to formulate a special political situation in the district, which later became an independent republic.        During the period from the establishment of the modern Turkish Republic in 1923 until the outbreak of World War II in 1939, French-Turkish relations witnessed several developments, events and agreements that resulted from the tense international situations between the two world wars. The issue of the Alexandretta Brigade was the most important and fundamental detail in the nature of relations between the two countries, especially through the Turks' continuous efforts to return the brigade that was stripped from it to the Turkish border again. This is why it is noted how large the volume of diplomatic activity of the two countries is through the frequent meetings and constant visits of the two parties.      France, as the mandatory power in Syria, agreed to include the Alexandretta Brigade with the aim of ensuring Turkey's neutrality in the eastern Mediterranean, especially when the signs of World War II began to appear on the horizon

Thermal Performance of Hybrid Solar Swimming Pool and Heating of Building in Kirkuk City-Iraq

In the latest development, a solar hybrid system maintains the outdoor pool at a constant 30°C year-round. Solar energy, a crucial renewable energy source, is harnessed through a novel collector design emphasizing the importance of tourism designs and heating concepts with environmental considerations. The technology, widely used in homes, involves measuring unglazed flat solar collectors (3.12 m2) for outdoor dome swimming pools in winter. A 2 m2- collector was integrated into a building and studied for seven daily hours over three months (December, January, and February). The internal heating system relied on a fan for electrical energy, reaching peak efficiency in February. Operating at 700 W/m2 radiation intensity and a 0.16 kg/sec flow rate, parameters such as sun intensity, ambient temperature, pond water conditions, solar output, water flow, and humidity were recorded. Thermal losses from the pool were calculated using a flat, oval-shaped tube solar collector, along with the room temperature after the pool had stabilized. The results showed a 0.16 kg/s flow rate optimized collector efficiency, prioritizing these findings for achieving thermal comfort, effective building heating, and preserving indoor pool temperature

Ten golden rules for optimal antibiotic use in hospital settings: the WARNING call to action

Antibiotics are recognized widely for their benefits when used appropriately. However, they are often used inappropriately despite the importance of responsible use within good clinical practice. Effective antibiotic treatment is an essential component of universal healthcare, and it is a global responsibility to ensure appropriate use. Currently, pharmaceutical companies have little incentive to develop new antibiotics due to scientific, regulatory, and financial barriers, further emphasizing the importance of appropriate antibiotic use. To address this issue, the Global Alliance for Infections in Surgery established an international multidisciplinary task force of 295 experts from 115 countries with different backgrounds. The task force developed a position statement called WARNING (Worldwide Antimicrobial Resistance National/International Network Group) aimed at raising awareness of antimicrobial resistance and improving antibiotic prescribing practices worldwide. The statement outlined is 10 axioms, or “golden rules,” for the appropriate use of antibiotics that all healthcare workers should consistently adhere in clinical practice

Complex T-spherical fuzzy Dombi aggregation operators and their applications in multiple-criteria decision-making

AbstractComplex fuzzy (CF) sets (CFSs) have a significant role in modelling the problems involving two-dimensional information. Recently, the extensions of CFSs have gained the attention of researchers studying decision-making methods. The complex T-spherical fuzzy set (CTSFS) is an extension of the CFSs introduced in the last times. In this paper, we introduce the Dombi operations on CTSFSs. Based on Dombi operators, we define some aggregation operators, including complex T-spherical Dombi fuzzy weighted arithmetic averaging (CTSDFWAA) operator, complex T-spherical Dombi fuzzy weighted geometric averaging (CTSDFWGA) operator, complex T-spherical Dombi fuzzy ordered weighted arithmetic averaging (CTSDFOWAA) operator, complex T-spherical Dombi fuzzy ordered weighted geometric averaging (CTSDFOWGA) operator, and we obtain some of their properties. In addition, we develop a multi-criteria decision-making (MCDM) method under the CTSF environment and present an algorithm for the proposed method. To show the process of the proposed method, we present an example related to diagnosing the COVID-19. Besides this, we present a sensitivity analysis to reveal the advantages and restrictions of our method.</jats:p

Comparing Somatostatin Analogs in the Treatment of Advanced Gastroenteropancreatic Neuroendocrine Tumors

&lt;b&gt;&lt;i&gt;Background:&lt;/i&gt;&lt;/b&gt; The 2 approved somatostatin analogs (SSAs) in the first-line treatment of advanced, well-differentiated gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are octreotide long-acting release (Sandostatin LAR) and somatuline depot (Lanreotide). The study’s objective was to compare progression-free survival (PFS) and overall survival (OS) of patients (pts) with GEP-NETs treated with somatuline or octreotide LAR. &lt;b&gt;&lt;i&gt;Pts and Methods:&lt;/i&gt;&lt;/b&gt; Pts with advanced well-differentiated GEP-NET who received either SSA at Emory University between 1995 and 2019 were included after institutional review board approval. The primary end point was PFS, defined as time to disease progression (according to the Response Evaluation Criteria in Solid Tumors, version 1.1, or clinical progression) or death. The secondary end point was OS. Kaplan-Meier curves were generated, and log-rank tests were conducted to compare the survival outcomes. &lt;b&gt;&lt;i&gt;Results:&lt;/i&gt;&lt;/b&gt; A total of 105 pts were identified. The mean age was 62.1 years (SD ± 11.8). The male-to-female ratio was 51:54. The majority (&lt;i&gt;N&lt;/i&gt; = 69, 65.7%) were white. Most pts had grade 2 (G2) disease (&lt;i&gt;N&lt;/i&gt; = 44, 41.9%). Primary location was small bowel in 58 (55.2%), pancreas in 27 (25.7%), and other in 20 (19.0%). Functional tumors were defined in 32 pts distributed equally between the 2 groups. Distribution of treatment was similar in the 2 groups, with 54 receiving octreotide LAR and 51 receiving somatuline depot. The median PFS for the octreotide LAR and somatuline depot groups was 12 months (95% CI, 6–18 months) and 10.8 months (95% CI, 6–15.6 months), respectively, and the difference was not statistically significant (&lt;i&gt;p&lt;/i&gt; = 0.2665). For pts with G1 disease, the median PFS for the octreotide LAR and somatuline depot was 8.4 versus 32.4 months, respectively, and the difference was not statistically significant (&lt;i&gt;p&lt;/i&gt; = 0.159). For G2 disease, the difference in median PFS between octreotide LAR and somutaline depot groups was statistically significant (12 vs. 7.2 months, respectively; &lt;i&gt;p&lt;/i&gt; = 0.0372). The mean follow-up time for octreotide LAR was 21.6 months versus 11.3 months for somatuline depot. &lt;b&gt;&lt;i&gt;Conclusions:&lt;/i&gt;&lt;/b&gt; Overall, there was no difference in PFS between octreotide LAR and somatuline depot for pts with well-differentiated, metastatic GEP-NETs. A prospective study is worth designing selecting for G. </jats:p

Safety and immunogenicity of a variant-adapted SARS-CoV-2 recombinant protein vaccine with AS03 adjuvant as a booster in adults primed with authorized vaccines: a phase 3, parallel-group studyResearch in context

Summary: Background: In a parallel-group, international, phase 3 study (ClinicalTrials.gov NCT04762680), we evaluated prototype (D614) and Beta (B.1.351) variant recombinant spike protein booster vaccines with AS03-adjuvant (CoV2 preS dTM-AS03). Methods: Adults, previously primed with mRNA (BNT162b2, mRNA-1273), adenovirus-vectored (Ad26.CoV2.S, ChAdOx1nCoV-19) or protein (CoV2 preS dTM-AS03 [monovalent D614; MV(D614)]) vaccines were enrolled between 29 July 2021 and 22 February 2022. Participants were stratified by age (18–55 and ≥ 56 years) and received one of the following CoV2 preS dTM-AS03 booster formulations: MV(D614) (n = 1285), MV(B.1.351) (n = 707) or bivalent D614 + B.1.351 (BiV; n = 625). Unvaccinated adults who tested negative on a SARS-CoV-2 rapid diagnostic test (control group, n = 479) received two primary doses, 21 days apart, of MV(D614). Anti-D614G and anti-B.1.351 antibodies were evaluated using validated pseudovirus (lentivirus) neutralization (PsVN) assay 14 days post-booster (day [D]15) in 18–55-year-old BNT162b2-primed participants and compared with those pre-booster (D1) and on D36 in 18–55-year-old controls (primary immunogenicity endpoints). PsVN titers to Omicron BA.1, BA.2 and BA.4/5 subvariants were also evaluated. Safety was evaluated over a 12-month follow-up period. Planned interim analyses are presented up to 14 days post-last vaccination for immunogenicity and over a median duration of 5 months for safety. Findings: All three boosters elicited robust anti-D614G or -B.1.351 PsVN responses for mRNA, adenovirus-vectored and protein vaccine-primed groups. Among BNT162b2-primed adults (18–55 years), geometric means of the individual post-booster versus pre-booster titer ratio (95% confidence interval [CI]) were: for MV (D614), 23.37 (18.58–29.38) (anti-D614G); for MV(B.1.351), 35.41 (26.71–46.95) (anti-B.1.351); and for BiV, 14.39 (11.39–18.28) (anti-D614G) and 34.18 (25.84–45.22 (anti-B.1.351). GMT ratios (98.3% CI) versus post-primary vaccination GMTs in controls, were: for MV(D614) booster, 2.16 (1.69; 2.75) [anti-D614G]; for MV(B.1.351), 1.96 (1.54; 2.50) [anti-B.1.351]; and for BiV, 2.34 (1.84; 2.96) [anti-D614G] and 1.39 (1.09; 1.77) [anti-B.1.351]. All booster formulations elicited cross-neutralizing antibodies against Omicron BA.2 (across priming vaccine subgroups), Omicron BA.1 (BNT162b2-primed participants) and Omicron BA.4/5 (BNT162b2-primed participants and MV D614-primed participants). Similar patterns in antibody responses were observed for participants aged ≥56 years. Reactogenicity tended to be transient and mild-to-moderate severity in all booster groups. No safety concerns were identified. Interpretation: CoV2 preS dTM-AS03 boosters demonstrated acceptable safety and elicited robust neutralizing antibodies against multiple variants, regardless of priming vaccine. Funding: Sanofi and Biomedical Advanced Research and Development Authority (BARDA)