A Novel Framework for Robustness Analysis of Visual QA Models

Deep neural networks have been playing an essential role in many computer vision tasks including Visual Question Answering (VQA). Until recently, the study of their accuracy was the main focus of research but now there is a trend toward assessing the robustness of these models against adversarial attacks by evaluating their tolerance to varying noise levels. In VQA, adversarial attacks can target the image and/or the proposed main question and yet there is a lack of proper analysis of the later. In this work, we propose a flexible framework that focuses on the language part of VQA that uses semantically relevant questions, dubbed basic questions, acting as controllable noise to evaluate the robustness of VQA models. We hypothesize that the level of noise is positively correlated to the similarity of a basic question to the main question. Hence, to apply noise on any given main question, we rank a pool of basic questions based on their similarity by casting this ranking task as a LASSO optimization problem. Then, we propose a novel robustness measure, R_score, and two large-scale basic question datasets (BQDs) in order to standardize robustness analysis for VQA models.Comment: Accepted by the Thirty-Third AAAI Conference on Artificial Intelligence, (AAAI-19), as an oral pape

Mechanism to Detect Pesticide Residues in Tealeaves Based on CdZnSe/ZnS Ternary Alloy Quantum Dots

In this report, we present the optical properties of the biosensors fabricated from CdZnSe/ZnS quantum dots. The optical properties such as absorption and emission of the ternary quantum dots before and after coupling with the protein molecules like streptavidine (SA) and acetylcholinesterase enzymes (AChE), to form a biosensor structure, will be presented. In particular, the changes in luminescence intensity according to the pH value of the solution environment containing biosensor have been considered, before and after the presence of pesticides. The changes in luminescence intensity of the biosensor after the presence of pesticide over time from 2 seconds to 26 minutes were also surveyed. We have been carried out the tests to determine the trace amounts of commercial pesticides like Motox 5EC, containing 5% cypermethrin and Tungatin 10 EC, containing 10% abamectin, on the real samples of tealeaves. Some characteristics of the relationship between composition, structure, and special optical properties of ternary alloy quantum dots will also be presented. These studies open up the potential applications of  ternary quantum dots for agricultural production

A Framework for paper submission recommendation system

Nowadays, recommendation systems play an indispensable role in many fields, including e-commerce, finance, economy, and gaming. There is emerging research on publication venue recommendation systems to support researchers when submitting their scientific work. Several publishers such as IEEE, Springer, and Elsevier have implemented their submission recommendation systems only to help researchers choose appropriate conferences or journals for submission. In this work, we present a demo framework to construct an effective recommendation system for paper submission. With the input data (the title, the abstract, and the list of possible keywords) of a given manuscript, the system recommends the list of top relevant journals or conferences to authors. By using state-of-the-art techniques in natural language understanding, we combine the features extracted with other useful handcrafted features. We utilize deep learning models to build an efficient recommendation engine for the proposed system. Finally, we present the User Interface (UI) and the architecture of our paper submission recommendation system for later usage by researchers

CHẾ TẠO VÀ TÍNH CHẤT CỦA VẬT LIỆU TỔ HỢP GRAPHENE – ỐNG NANO CÁCBON – HẠT NANO VÀNG

In this work, a composite nanomaterial consisting of graphene (Gr), double-wall carbon nanotube (DWCNTs) and gold nanoparticles (AuNPs), designated as DWCNTs-AuNPs-Gr was synthesized via the thermal chemical vapour deposition technique. The morphology and electrical and electrochemical properties of the material were characteried by using field emission scanning electron microscopy, Raman spectroscopy, four-probe sheet resistance measurement, and cyclic voltammetry (CV). The average sheet resistance value of DWCNTs-AuNPs-Gr is 549 W/sq, 2.3 times lower than that of graphene. The current response of a DWCNTs-AuNPs-Gr-modified electrode in a 2 mM K3[Fe(CN)6]/K4[Fe(CN)6] solution with 0.1 M PBS is 15.79 µA, 1.48 times higher than that of a graphene-modified electrode and 2.57 times higher than that of a bare electrode. The DWCNTs-AuNPs-Gr material can be used for electrochemical biosensors to detect various bioelements.Trong công trình này, màng tổ hợp của vật liệu graphene (Gr) – ống nano cácbon hai tường (DWCNT) và hạt nano kim loại vàng (AuNPs) (DWCNT-AuNPs-Gr) đã được chế tạo bằng phương pháp lắng đọng pha hơi nhiệt hóa học (CVD). Hình thái học bề mặt và các tính chất điện, điện hóa của vật liệu tổ hợp đã được khảo sát thông qua kính hiển vi điện tử quét phát xạ trường, phổ Raman, điện trở bốn mũi dò và kỹ thuật quét thế vòng (CV). Với nồng độ DWCNTs 0,3 g/L và tốc độ quay phủ 4000 vòng/phút, vật liệu DWCNTs-AuNPs-Gr có điện trở bề mặt giảm 2,3 lần so với màng Gr và đạt khoảng 549 W/sq; dòng đỉnh đáp ứng trong dung dịch 2 mM K3[Fe(CN)6]/K4[Fe(CN)6] trong 0,1 M PBS đạt 15,79 µA tại 50 mV/s, cao gấp 1,48 lần so với điện cực biến tính màng Gr và gấp 2,57 lần so với điện cực trần. Vật liệu DWCNTs-AuNPs-Gr có tiềm năng ứng dụng trong cảm biến điện hóa để phát hiện các phần tử sinh học khác nhau

Functional-Antioxidant Food

Nowadays, people face many different dangers, such as stress, unsafety food, and environmental pollution, but not everyone suffers. Meanwhile, free radicals are the biggest threat for humans because they lead to over 80 different diseases composed of aging. Free radicals can only be eliminated or minimized with antioxidant foods or antioxidants. The chapter on the functional-antioxidant food presents the antioxidant functional food concept, the classification, the structure, and the extraction process of antioxidant ingredients. Various antioxidant substances such as protein (collagen), polysaccharides (fucoidans, alginates, glucosamines, inulins, laminarins, ulvans, and pectins), and secondary metabolites (polyphenols (phlorotannins, lignins, polyphenols), alkaloids, and flavonoids) also present. The production technology, the mechanism, the opportunity, and the challenge of antioxidants functional food also present in the current chapter. The current chapter also gives the production process of functional-antioxidant food composed of the capsule, the tablet, tube, the pills, the powder, and the effervescent tablet

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Inkludering av gles attention i en transformer för objektdetektering i bilder

DEtection TRansformer, DETR, introduces an innovative design for object detection based on softmax attention. However, the softmax operation produces dense attention patterns, i.e., all entries in the attention matrix receive a non-zero weight, regardless of their relevance for detection. In this work, we explore several alternatives to softmax to incorporate sparsity into the architecture of DETR. Specifically, we replace softmax with a sparse transformation from the α-entmax family: sparsemax and entmax-1.5, which induce a set amount of sparsity, and α-entmax, which treats sparsity as a learnable parameter of each attention head. In addition to evaluating the effect on detection performance, we examine the resulting attention maps from the perspective of explainability. To this end, we introduce three evaluation metrics to quantify the sparsity, complementing the qualitative observations. Although our experimental results on the COCO detection dataset do not show an increase in detection performance, we find that learnable sparsity provides more flexibility to the model and produces more explicative attention maps. To the best of our knowledge, we are the first to introduce learnable sparsity into the architecture of transformer-based object detectors.DEtection Transformer, DETR, introducerar en innovativ design för objektdetektering baserad på softmax attention. Softmax producerar tät attention, alla element i attention-matrisen får en vikt skild från noll, oberoende av deras relevans för objektdetektering. Vi utforskar flera alternativ till softmax för att inkludera gleshet i DETRs arkitektur. Specifikt så ersätter vi softmax med en gles transformation från α-entmax familjen: sparsemax och entmax1.5, vilka inducerar en fördefinierad mängd gleshet, och α-entmax, som ser gleshet som en träningsbar parameter av varje attention-huvud. Förutom att evaluera effekten på detekteringsprestandan, så utforskar vi de resulterande attention-matriserna från ett förklarbarhetsperspektiv. Med det som mål så introducerar vi tre olika metriker för att evaluera gleshet, som ett komplement till de kvalitativa observationerna. Trots att våra experimentella resultat på COCO, ett utmanande dataset för objektdetektering, inte visar en ökning i detekteringsprestanda, så finner vi att träningsbar gleshet ökar modellens flexibilitet, och producerar mer förklarbara attentionmatriser. Såvitt vi vet så är vi de första som introducerar träningsbar gleshet i transformer-baserade arkitekturer för objektdetektering

Existence of solutions to the Riemann problem for a model of two-phase flows

We study the existence of solutions of the Riemann problem for a model of two-phase flows. The model has the form of a nonconservative hyperbolic system of balance laws. Based on a phase decomposition approach, we obtain all the wave curves. By developing an analytic method, we can establish a system of nonlinear algebraic equations for each solution of the Riemann problem. The system is under-determined and can be parameterized by the volume fraction in one phase. Therefore, an argument relying on the Implicit-Function Theorem leads us to the existence of solutions of the Riemann problem for the model for sufficiently large initial data. Furthermore, the structure of the Riemann solutions obtained by this method can also be obtained