Verification Strategy Research Articles

Is it real? A study on detecting deepfake videos

AbstractWe present an exploratory study of how people detect deepfake videos. Through watching a set of real and fake videos, and semi‐structured interviews, participants identified a set of characteristics such as blurred faces and unnatural voices, present in deepfake videos. A list of verification strategies, including checking other sources and repeated viewing, were also derived.

Trend and fact-checking narratives on Twitter. Verification codes and fake news in the Procés riots (14-O)

Un entorno digital dominado por la inteligencia artificial, la influencia de los líderes políticos, el activismo de las audiencias y la eclosión de desinformación y fake news definen los códigos de la agenda. Se dibuja además un escenario en el que el papel de las agencias de fact-checking como propulsoras o detractoras de lo fake está cuestionado. En un contexto marcado por la convocatoria continuada de elecciones generales en España y por el conflicto de la Independencia de Cataluña se publica la Sentencia del Tribunal Supremo sobre los juicios del Procés (14-O). Una cadena de movilizaciones ciudadanas inunda la red. El objetivo general del estudio es conocer en Twitter las fake news sobre los disturbios catalanes, las estrategias de verificación en las agencias seleccionadas (@malditobulo, @Newtral y @veri_fi_cat), el nivel de impacto y la reacción de los públicos. Aplicamos una metodología triangular de análisis de contenido comparado y sobre una muestra general de tweets (n1=4500) se analiza el tratamiento de los bulos detectados por los fact-checkers (n2=62). Los resultados confirman que la autoría de las noticias falsas corresponde a cuentas de particulares y que las estrategias de fact-checking pueden favorecer más la viralización que el desmentido.

O desafio da construção das marcas: proposta de um modelo

Objetivo: Este estudo teve como objetivo propor um modelo de construção de marca, analisar os modelos de construção de marca de Aaker e Joachismthaler e Keller e verificar a relevância de cada pilar que compõe o novo modelo, proporcionado pelas lacunas percebidas e suas implicações nos modelos anteriores.Método: A pesquisa foi fundamentada em uma abordagem metodológica, de um estudo qualitativo tendo como estratégia de verificação empírica o método de estudo de casos múltiplos, por meio da análise as marcas Arezzo e Schutz.Originalidade/Relevância: A relevância do modelo proposto inspira novos olhares para o campo gerencial e do marketing, buscando contribuir com a teoria e a gestão de marca, no sentido de discutir as lacunas existentes nos modelos apresentados pelos autores Aaker e Joamchimstaler (2007) e Keller (2013).Resultados:Após testar os pilares que compõe o modelo proposto, percebeu-se sua importância dado o contexto global das marcas e as exigências do mercado competitivo. Assim, pode-se detectar a interação com o consumidor em todos os seus pilares.Contribuições teóricas/metodológicas:Este estudo contribui com a teoria do marketing como referência, introdução ou mecanismo exploratório para possíveis estudos futuros, frente as dimensões socioeconômicas no mundo acadêmico e gerencial global.

Representations of farmers' in social systems and their agro-pastoral choices in semi-arid environments in Morocco, a comparative study of the regions of Doukkala- Abda

يعالج هذا البحث موضوع «تمثلات الفلاحين للأنظمة الاجتماعية وعلاقتها باختياراتهم الرعي – زراعية بالبيئات شبه الجافة بالمغرب دراسة مقارنة لمنطقتي دكالة –عبدة». كما يهدف البحث بلوغ الأهداف التالية: أولا: وصف وتفسير بنية مجتمع الفلاحين وعلاقتها باختياراتهم الرعي – زراعية (المزروعات الأساسية وتربية الغنم). ثانيا: وصف وتفسير وضعية النظام العقاري وعلاقته باختيارات الفلاحين الرعي –زراعية (المزروعات الأساسية وتربية الغنم). ثالثا: وصف وتفسير أهمية التضامن الحضر- ريفي وعلاقته باختيارات الفلاحين الرعي – زراعية (المزروعات الأساسية وتربية الغنم). اعتمد البحث الفرض العدم التالي: لا توجد فروقات ذات دلالة إحصائية (H0) في اختيارات الفلاحينالرعي- الزراعية (المزروعات الأساسية وتربية الغنم) بالوحدتين الترابيتين حد احرارة (منطقة عبدة) واثنين الغربية (منطقة دكالة) حسب تمثلاتهم لنظام الاجتـــــــماعي (فئات الأعمار المتوسطة [45- 54 سنة]، وفئات الحـــيازات الصـغرى والمتوسطة [4- 19هـ])، ووضعية النظام العقاري (أراضي الملك)، والتضامن الحضر- ريفي (النشاط الزراعي))). اعتمدنا استراتيجية تمحيص كمية تجمع بين البحث الميداني والتحليل الاحصائي الذي تضمن البيانات المعلمية والبيانات للامعلمية بناء على أسلوبين: أولهما الأسلوب غير الميداني (المونوغرافيات، الإحصاءات...)، وثانيهما الأسلوب الميداني المتمثل في اختيار عينة عشوائية بواسطة السحب الطبقي الأمثل والاستمارة التي شملت استجواب حوالي (465 فلاحا) موزعة بين منطقتين على النحو التالي: 227 فلاحا بمنطقة دكالة (جماعة اثنين الغربية) و238 فلاحا بمنطقة عبدة (جماعة حد احرارة) خلال سنة 2016. توصل البحث إلى أهمية الفئات العمرية المتوسطة [45- 54 سنة]، وفئات الحيازات الصـغرى والمتوســــطة [4- 19هـ] في توجيه اختيارات الفلاحين الرعي – زراعية بمنطقتي دكالة وعبدة مع سيادة أراضي الملك في صفوف الفلاحين إضافة إلى أهمية المساعدات التي يستقبلها الفلاحون في إطار التضامن الحضر – ريفي. كذلك رفض الفرض العدم مع تأكيد الفرض البديل «وجود فروقات ذات دلالة إحصائية (1H) في اختيارات الفلاحين الرعي – زراعية حسب تمثلات الأنظمة الاجتماعية». وأخيرا فقد تبنى البحث منهجية «IMRAD» التي تشمل الخصائص العلمية التالية: المقدمة (I) والمنهجية (M) والنتائج (R) والمناقشة (D).

Quantum gate verification and its application in property testing

To guarantee the normal functioning of quantum devices in different scenarios, appropriate benchmarking tool kits are quite significant. Inspired by the recent progress on quantum state verification, here we establish a general framework of verifying a target unitary gate. In both the non-adversarial and adversarial scenarios, we provide efficient methods to evaluate the performance of verification strategies for any qudit unitary gate. Furthermore, we figure out the optimal strategy and its realization with local operations. Specifically, for the commonly-used quantum gates like single qubit and qudit gates, multi-qubit Clifford gates, and multi-qubit Controlled-Z(X) gates, we provide efficient verification protocols. Besides, we discuss the application of gate verification for the detection of entanglement-preserving property of quantum channels and further quantify the robustness measure of them. We believe that the gate verification is a promising way to benchmark a large-scale quantum circuit as well as to test its property.

Bioinformatic analysis and experimental identification of blood biomarkers for chronic nonunion

BackgroundIncomplete fracture healing may lead to chronic nonunion; thus, determining fracture healing is the primary issue in the clinical treatment. However, there are no validated early diagnostic biomarkers for assessing chronic nonunion. In this study, bioinformatics analysis combined with an experimental verification strategy was used to identify blood biomarkers for chronic nonunion.MethodsFirst, differentially expressed genes in chronic nonunion were identified by microarray data analysis. Second, Dipsaci Radix (DR), a traditional Chinese medicine for fracture treatment, was used to screen the drug target genes. Third, the drug-disease network was determined, and biomarker genes were obtained. Finally, the potential blood biomarkers were verified by ELISA and qPCR methods.ResultsFifty-five patients with open long bone fractures (39 healed and 16 nonunion) were enrolled in this study, and urgent surgical debridement and the severity of soft tissue injury had a significant effect on the prognosis of fracture. After the systems pharmacology analysis, six genes, including QPCT, CA1, LDHB, MMP9, UGCG, and HCAR2, were chosen for experimental validation. We found that all six genes in peripheral blood mononuclear cells (PBMCs) and serum were differentially expressed after injury, and five genes (QPCT, CA1, MMP9, UGCG, and HCAR2) were significantly lower in nonunion patients. Further, CA1, MMP9, and QPCT were markedly increased after DR treatment.ConclusionCA1, MMP9, and QPCT are biomarkers of nonunion patients and DR treatment targets. However, HCAR2 and UGCG are biomarkers of nonunion patients but not DR treatment targets. Therefore, our findings may provide valuable information for nonunion diagnosis and DR treatment.Trial registrationISRCTN, ISRCTN13271153. Registered 05 April 2020—Retrospectively registered.

Multiple Intelligences in Classrooms: The Case of Okyeso Primary School in Cape Coast, Ghana

The understanding of multiple intelligences in our schools is very paramount. Multiple intelligences unearth diverse inherent talents in children through interactions in the classrooms. The ability to tap these potentialities and capabilities facilitates their career paths and placements. Unfortunately the education system in Ghana precisely our pre- schools appear not to have adequately set up mechanisms to take advantage of multiple intelligences in children. There seems to be cognitively spread approach using one-sided performance appraisal to examine and assess children’s intellectual abilities. The paper therefore identifies multiple intelligences strategy as a missing link in classroom interactions. A careful look is to examine the potentialities in children by critical investigation whether there are diverse levels of abilities and processing skills to solve problems. The inquiry was a case study and a mixed method. Primary 3 class was used and sample selection of 20 children and 5 teachers was employed using the purposive technique. Observation and interview were the main instruments. Bar charts and percentage scores were analytical procedures for the quantitative data while the thematic approach was used as concurrent analytical tool for the qualitative data. Verification strategy was by triangulation. Results were so appealing that, both pupils and teachers were able to identify some areas of multiple intelligences in the classrooms. However, these traits and characteristics were exhibited unknowingly. It is recommended that talents in the classrooms should be tapped using holistic approach to assess children’s abilities.

A refinement checking based strategy for component-based systems evolution

We propose inheritance and refinement relations for a CSP-based component model (BRIC), which supports a constructive design based on composition rules that preserve classical concurrency properties such as deadlock freedom. The proposed relations allow extension of functionality, whilst preserving behavioural properties. A notion of extensibility is defined on top of a behavioural relation called convergence, which distinguishes inputs from outputs and the context where they are communicated, allowing extensions to reuse existing events with different purposes. We mechanise the strategy for extensibility verification using the FDR4 tool, and illustrate our results with an autonomous healthcare robot case study.

Precise proximal femur fracture classification for interactive training and surgical planning.

Demonstrate the feasibility of a fully automatic computer-aided diagnosis (CAD) tool, based on deep learning, that localizes and classifies proximal femur fractures on X-ray images according to the AO classification. The proposed framework aims to improve patient treatment planning and provide support for the training of trauma surgeon residents. A database of 1347 clinical radiographic studies was collected. Radiologists and trauma surgeons annotated all fractures with bounding boxes and provided a classification according to the AO standard. In all experiments, the dataset was split patient-wise in three with the ratio 70%:10%:20% to build the training, validation and test sets, respectively. ResNet-50 and AlexNet architectures were implemented as deep learning classification and localization models, respectively. Accuracy, precision, recall and [Formula: see text]-score were reported as classification metrics. Retrieval of similar cases was evaluated in terms of precision and recall. The proposed CAD tool for the classification of radiographs into types "A," "B" and "not-fractured" reaches a [Formula: see text]-score of 87% and AUC of 0.95. When classifying fractures versus not-fractured cases it improves up to 94% and 0.98. Prior localization of the fracture results in an improvement with respect to full-image classification. In total, 100% of the predicted centers of the region of interest are contained in the manually provided bounding boxes. The system retrieves on average 9 relevant images (from the same class) out of 10 cases. Our CAD scheme localizes, detects and further classifies proximal femur fractures achieving results comparable to expert-level and state-of-the-art performance. Our auxiliary localization model was highly accurate predicting the region of interest in the radiograph. We further investigated several strategies of verification for its adoption into the daily clinical routine. A sensitivity analysis of the size of the ROI and image retrieval as a clinical use case were presented.

Runtime Verification of Business Cloud Workflow Temporal Conformance

Business cloud workflows are often designed with multiple time constraints for timely response to business requests. To ensure on-time completion of workflow instances, workflow temporal conformance state needs to be constantly monitored and verified at runtime. Considering the fact that there are a large number of workflow instances running in a parallel fashion in many business scenarios, conventional verification approaches for time-related properties using such as temporal logic or timed Petri nets are not feasible due to the limitation of low efficiency at runtime. To address this issue, we propose a new approach to automated runtime verification of temporal conformance for parallel workflow instances in a cloud environment. Instead of using response time to verify temporal conformance of every single workflow as in conventional strategies, workflow throughput is employed as the performance measurement to efficiently monitor a large number of parallel workflow instances. On this basis we present a novel conformance verification strategy. This strategy considers the effect of time delay propagation in the cloud workflow systems to accurately verify workflow runtime temporal conformance. Our verification strategy is implemented in a prototype cloud workflow system and the evaluation results show that it outperforms the state-of-the-art workflow temporal verification strategy.

Authorship Attribution in Latin Languages using Stylometry

In this paper we presented a computational approach to authorship attribution in a multilingual environment, based on latin languages. Initially, we defined the databases of literary texts, written by consecrated authors of Portuguese, Spanish and French literature. Subsequently, we established a set formed by groups of stylometric characteristics, which are: morphological, flexors, syntactic and auxiliary. The main objective is to extract from the grammatical structures of the sentences, the stylometric pattern of each author. We perform experiments with author-dependent approach, using verification and identification strategies. In the classification process we use the Support Vector Machines - SVM, with a linear kernel.

Performance determination of high-purity N2-PSA-plants

The global demand on highly purified gases provided by energy-efficient separation processes grows steadily since decades. An example of particular industrial relevance is nitrogen generated by pressure swing adsorption from compressed air. A kinetically based separation of oxygen from nitrogen is possible by means of carbon molecular sieves (CMS) since oxygen adsorbs remarkably faster in CMS than nitrogen. Even high product purities (5–1000 ppm O2) are easily achievable in commercial generators. However, only a few studies present experimental findings in this purity range. That comes as no surprise, since experimental conditions are not standardised and the determination of N2-PSA performance indicators still creates an experimental challenge. Moreover, the design of the set-up remarkably influences the experimental results. Thus it is the motivation of this study to develop a multi-step strategy, comprising the definition of a reference process, the derivation of explicit and implicit performance indicators based on either flow meter readings or macroscopic material balances, a verification strategy for experimentally obtained data, and an error consideration, which advices accuracy requirements for analysers and flow meters. The effect of cycle time and operating temperature on the performance indicators is exemplarily studied at high purities by means of the proposed strategy.

Age Verification and Online Sales of Little Cigars and Cigarillos to Minors

In our cross-sectional study, we aimed to determine age verification and sales of little cigars and cigarillos (LCCs) online to underage teens. We selected 100 popular Internet Little Cigar and Cigarillo Vendors (ILVs) for order attempts. From August to December 2015, we supervised 14 teens 14-17 years old making order attempts for LCCs. Of the 91 valid orders attempted, we received 89. For the valid orders attempted, 9.9% of ILVs used no age verification strategies at all, 84.6% used less effective forms of age verification, and 50.5% used more effective ones. Only one order was blocked during the order attempt and only one attempt was made to verify age at delivery. Most (79.8%) deliveries were left at the door and only 2 order attempts were rejected because of age verification strategies, resulting in a successful or valid buy rate of 97.8%. Our study demonstrated that ILVs selling LCCs were not making adequate efforts to verify the age of their customers, at the point-of-sale or point-of-delivery, facilitating easy access by minors. Few ILVs utilized age verification strategies that prevented online sales of LCCs to underage teens.

Identity Verification in Virtual Education Using Biometric Analysis Based on Keystroke Dynamics

Virtual education has become one of the tools most widely used by students at all educational levels, not just because of its convenience and flexibility, but also because it can expand educational coverage. All these benefits also bring along multiple issues in terms of security and reliability in the evaluation the of student’s knowledge because traditional identity verification strategies, such as the combination of username and password, do not guarantee that the student enrolled in the course really takes the exam. Therefore, a system with a different type of verification strategy should be designed to differentiate valid users from impostors. This study proposes a new verification system based on distances computed among Gaussian Mixture Models created with different writing task. The proposed approach is evaluated in two different modalities namely intrusive verification and non-intrusive verification. The intrusive mode provides a false positive rate of around 16 %, while the non-intrusive mode provides a false positive rate of 12 % In addition, the proposed strategy for non-intrusive verification is compared to a work previously reported in the literature and the results show that our approach reduces the equal error rate in about 24.3 %. The implemented strategy does not need additional hardware; only the computer keyboard is required to complete the user verification, which makes the system attractive, flexible, and practical for virtual education platforms.

Towards trusted and efficient SDN topology discovery: A lightweight topology verification scheme

Discovering network topology is critical for Software-defined Networking (SDN) controllers to establish the centralized network visibility. However, during the process of SDN topology discovery, SDN controllers tend to suffer from the topology poisoning attacks due to a lack of authentication. Existing methods can hardly solve the problems of SDN topology poisoning attacks in a comprehensive and lightweight manner. To fill this gap, we propose TrustTopo, a lightweight and efficient SDN topology verification scheme. Specifically, we first establish a security threat model to analyze key service vulnerabilities in the SDN controller. Then, we design two verification strategies (i.e., host location verification and link verification) to cope with the host hijacking attack and link fabrication attack, respectively. In more detail, our host location verification strategy is based on the path tracking and asynchronous rollback technique, while our link verification strategy is designed using the chaotic model and dynamic password generation technique. We implement TrustTopo in the mainstream SDN controller (i.e., Floodlight). Experimental results in the Mininet virtual network environment show that TrustTopo can effectively secure the network topology against the representative topology poisoning attacks, while bringing negligible runtime overhead.

An Experimental Evaluation of Global Navigation Satellite System/Inertial Navigation System-Verification Strategies for Vehicular Applications

An effective way to detect the presence of a spoofing attack is to verify Global Navigation Satellite System (GNSS) data with measurements from other sensors, such as inertial navigation systems (INSs). In this article, uncoupled GNSS/INS-verification approaches are experimentally evaluated in an automotive context. The approaches are uncoupled in the sense that GNSS and INS sensors are operated independently without an exchange of information. The techniques considered are the magnitude verification (MAV) technique, where the acceleration and angular velocity magnitudes are compared, and the horizontal components (HoCs)-verification strategy, which requires the vertical alignment of GNSS and INS sensor frames. The analysis shows the effectiveness of these types of procedures and discusses their limitations; for example, in low-dynamic conditions, when low accelerations and angular velocities are recorded. Possible enhancements are also discussed.

An ensemble of neural networks for nonlinear segmentation of overlapped cursive script

Precise character segmentation is the only solution towards higher Optical Character Recognition (OCR) accuracy. In cursive script, overlapped characters are serious issue in the process of character segmentations as characters are deprived from their discriminative parts using conventional linear segmentation strategy. Hence, non-linear segmentation is an utmost need to avoid loss of characters parts and to enhance character/script recognition accuracy. This paper presents an improved approach for non-linear segmentation of the overlapped characters in handwritten roman script. The proposed technique is composed of a sequence of heuristic rules based on geometrical features of characters to locate possible non-linear character boundaries in a cursive script word. However, to enhance efficiency, heuristic approach is integrated with trained ensemble neural network validation strategy for verification of character boundaries. Accordingly, correct boundaries are retained and incorrect are removed based on ensemble neural networks vote. Finally, based on verified valid segmentation points, characters are segmented non-linearly. For fair comparison CEDAR benchmark database is experimented. The experimental results are much better than conventional linear character segmentation techniques reported in the state of art. Ensemble neural network play vital role to enhance character segmentation accuracy as compared to individual neural networks.

A Fast and Precise Spatial Verification Strategy for Duplicate Image Retrieval

A Fast and Precise Spatial Verification Strategy for Duplicate Image Retrieval

A Deep Model for Multi-Focus Image Fusion Based on Gradients and Connected Regions

In this paper, we propose a novel unsupervised model for multi-focus image fusion based on gradients and connected regions, termed as GCF. To overcome the stumbling block of vanishing gradients in applying deep networks for multi-focus image fusion, we design the Mask-Net which can directly generate a binary mask. Thus, there is no need for hand-crafted feature extraction or fusion rules. Based on the fact that objects within the depth-of-field (DOF) have shaper appearance, i.e., larger gradients, we use the gradient relation map obtained from source images to narrow the solution domain and speed up convergence. Then, the constraint of connected region numbers is conductive to finding the more accurate binary mask. With the consistency verification strategy, the final mask can be obtained by adapting the initial binary mask to generate the fused result. Therefore, the proposed method is an unsupervised model without the need of the ground-truth data. Both qualitative and quantitative experiments are conducted on the publicly available Lytro dataset. The results show that GCF can outperform the state-of-the-art in both visual perception and objective metrics.

Multi-Modal Authentication Using Machine Learning Algorithm

In the present era of information technology, there is a need to implement verification and approval strategies for security of resources. Whereas, there are number of approaches to demonstrate validation and approval, yet the biometric verification beat every other method. At first, biometrics began off with straightforward unimodal framework, the higher requirement for security had offered ascend to a prevalent framework known as multimodal verification framework. Multimodal verification confirmation has pulled in compelling interest, on account of its hugeness towards the constant application In this research proposal, an effective framework for multimodal verification authentication systems based on machine learning algorithm is employed.