scholarly journals Interactive key (Lucid) for identification of fungi in vegetable seeds

2020 ◽  
Vol 46 (1) ◽  
pp. 14-19
Author(s):  
Caroline Geraldi Pierozzi ◽  
Ricardo Toshio Fujihara ◽  
Efrain de Santana Souza ◽  
Marília Pizetta ◽  
Maria Márcia Pereira Sartori ◽  
...  
Keyword(s):  
High Resolution ◽  
Prior Knowledge ◽  
Undergraduate Students ◽  
Morphological Characters ◽  
Fungal Species ◽  
Ease Of Use ◽  
Identification Accuracy ◽  
Difficulty Level ◽  
Identification System ◽  
Correct Identification

ABSTRACT Interactive keys are tools that aid research and technical work since identification of organisms has become increasingly present in the scientific and academic context. An interactive key was developed with the software Lucid v. 3.3 for the identification of eleven fungal species associated with onion, carrot, pepper and tomato seeds. It was based on a matrix composed of six features: crop, conidium, conidiophore, color of long conidiophore, color of mycelium and presence of setae, besides 21 character states. In addition, descriptions, illustrations and high-resolution photographs of the morphological characters and states were made available to aid in the correct identification of fungal species. Validation of the interactive key was performed by distinct groups of volunteers: (i) graduate students with prior knowledge and using the interactive key; (ii) undergraduate students with little prior knowledge and using the interactive key, and (iii) undergraduate students with little prior knowledge and using the conventional identification system such as the printed manuals used in seed pathology laboratories. We analyzed the time spent by each volunteer to evaluate 25 seeds infected with the fungal species in the key, as well as the percentage of success and the difficulty level for each participant. The high percentage of correct answers with the use of the interactive key and the ease of use by the volunteers confirmed its efficiency because there was an increase in the identification accuracy when compared to the conventional system. Furthermore, the rate of success and the difficulty level presented low variability within groups (i) and (ii). These results are a consequence of the interaction of the user with characteristics of the developed tool, such as high-resolution photographs, which faithfully reproduce the fungal characteristics observed in the seeds under a stereomicroscope. Thus, the interactive key presented here can aid in teaching, institutional and commercial research, inspection and certification of seeds, making diagnosis safer and more accurate. The key is available for free at https://keys.lucidcentral.org/keys/v3/seed_fungi/.

scholarly journals A machine learning approach for accurate and real-time DNA sequence identification

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yiren Wang ◽  
Mashari Alangari ◽  
Joshua Hihath ◽  
Arindam K. Das ◽  
M. P. Anantram
Keyword(s):  
Real Time ◽  
Dna Sequence ◽  
Single Molecule ◽  
Identification Accuracy ◽  
Measuring System ◽  
Identification System ◽  
Genetic Sequencing ◽  
Sequence Identification ◽  
Tree Classifier ◽  
Single Mismatch

Abstract Background The all-electronic Single Molecule Break Junction (SMBJ) method is an emerging alternative to traditional polymerase chain reaction (PCR) techniques for genetic sequencing and identification. Existing work indicates that the current spectra recorded from SMBJ experimentations contain unique signatures to identify known sequences from a dataset. However, the spectra are typically extremely noisy due to the stochastic and complex interactions between the substrate, sample, environment, and the measuring system, necessitating hundreds or thousands of experimentations to obtain reliable and accurate results. Results This article presents a DNA sequence identification system based on the current spectra of ten short strand sequences, including a pair that differs by a single mismatch. By employing a gradient boosted tree classifier model trained on conductance histograms, we demonstrate that extremely high accuracy, ranging from approximately 96 % for molecules differing by a single mismatch to 99.5 % otherwise, is possible. Further, such accuracy metrics are achievable in near real-time with just twenty or thirty SMBJ measurements instead of hundreds or thousands. We also demonstrate that a tandem classifier architecture, where the first stage is a multiclass classifier and the second stage is a binary classifier, can be employed to boost the single mismatched pair’s identification accuracy to 99.5 %. Conclusions A monolithic classifier, or more generally, a multistage classifier with model specific parameters that depend on experimental current spectra can be used to successfully identify DNA strands.

scholarly journals BonZeb: open-source, modular software tools for high-resolution zebrafish tracking and analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicholas C. Guilbeault ◽  
Jordan Guerguiev ◽  
Michael Martin ◽  
Isabelle Tate ◽  
Tod R. Thiele
Keyword(s):  
High Resolution ◽  
Open Loop ◽  
Ease Of Use ◽  
Neural Mechanisms ◽  
Animal Tracking ◽  
Larval Zebrafish ◽  
Optogenetic Stimulation ◽  
Modular Software ◽  
Behavioral Tracking ◽  
Experimental Protocols

AbstractWe present BonZeb—a suite of modular Bonsai packages which allow high-resolution zebrafish tracking with dynamic visual feedback. Bonsai is an increasingly popular software platform that is accelerating the standardization of experimental protocols within the neurosciences due to its speed, flexibility, and minimal programming overhead. BonZeb can be implemented into novel and existing Bonsai workflows for online behavioral tracking and offline tracking with batch processing. We demonstrate that BonZeb can run a variety of experimental configurations used for gaining insights into the neural mechanisms of zebrafish behavior. BonZeb supports head-fixed closed-loop and free-swimming virtual open-loop assays as well as multi-animal tracking, optogenetic stimulation, and calcium imaging during behavior. The combined performance, ease of use and versatility of BonZeb opens new experimental avenues for researchers seeking high-resolution behavioral tracking of larval zebrafish.

RF-Identity

2021 ◽  
Vol 5 (1) ◽  
pp. 1-23
Author(s):  
Chao Feng ◽  
Jie Xiong ◽  
Liqiong Chang ◽  
Fuwei Wang ◽  
Ju Wang ◽  
...  
Keyword(s):  
Data Augmentation ◽  
Critical Role ◽  
Training Data ◽  
Identification Accuracy ◽  
Identification System ◽  
Frequency Bandwidth ◽  
Person Identification ◽  
Data Set ◽  
Rf Devices ◽  
Large Frequency

Person identification plays a critical role in a large range of applications. Recently, RF based person identification becomes a hot research topic due to the contact-free nature of RF sensing that is particularly appealing in current COVID-19 pandemic. However, existing systems still have multiple limitations: i) heavily rely on the gait patterns of users for identification; ii) require a large amount of data to train the model and also extensive retraining for new users and iii) require a large frequency bandwidth which is not available on most commodity RF devices for static person identification. This paper proposes RF-Identity, an RFID-based identification system to address the above limitations and the contribution is threefold. First, by integrating walking pattern features with unique body shape features (e.g., height), RF-Identity achieves a high accuracy in person identification. Second, RF-Identity develops a data augmentation scheme to expand the size of the training data set, thus reducing the human effort in data collection. Third, RF-Identity utilizes the tag diversity in spatial domain to identify static users without a need of large frequency bandwidth. Extensive experiments show an identification accuracy of 94.2% and 95.9% for 50 dynamic and static users, respectively.

GaitSense: Towards Ubiquitous Gait-Based Human Identification with Wi-Fi

2022 ◽  
Vol 18 (1) ◽  
pp. 1-24
Author(s):  
Yi Zhang ◽  
Yue Zheng ◽  
Guidong Zhang ◽  
Kun Qian ◽  
Chen Qian ◽  
...  
Keyword(s):  
Data Augmentation ◽  
Gait Recognition ◽  
Wearable Sensors ◽  
Human Identification ◽  
Training Data ◽  
Identification Accuracy ◽  
Identification System ◽  
Gait Patterns ◽  
Training Samples ◽  
Augmentation Techniques

Gait, the walking manner of a person, has been perceived as a physical and behavioral trait for human identification. Compared with cameras and wearable sensors, Wi-Fi-based gait recognition is more attractive because Wi-Fi infrastructure is almost available everywhere and is able to sense passively without the requirement of on-body devices. However, existing Wi-Fi sensing approaches impose strong assumptions of fixed user walking trajectories, sufficient training data, and identification of already known users. In this article, we present GaitSense , a Wi-Fi-based human identification system, to overcome the above unrealistic assumptions. To deal with various walking trajectories and speeds, GaitSense first extracts target specific features that best characterize gait patterns and applies novel normalization algorithms to eliminate gait irrelevant perturbation in signals. On this basis, GaitSense reduces the training efforts in new deployment scenarios by transfer learning and data augmentation techniques. GaitSense also enables a distinct feature of illegal user identification by anomaly detection, making the system readily available for real-world deployment. Our implementation and evaluation with commodity Wi-Fi devices demonstrate a consistent identification accuracy across various deployment scenarios with little training samples, pushing the limit of gait recognition with Wi-Fi signals.

scholarly journals Comparison of feature extraction and normalization methods for speaker recognition using grid-audiovisual database

2020 ◽  
Vol 18 (2) ◽  
pp. 782
Author(s):  
Musab T. S. Al-Kaltakchi ◽  
Haithem Abd Al-Raheem Taha ◽  
Mohanad Abd Shehab ◽  
Mohamed A.M. Abdullah
Keyword(s):  
Feature Extraction ◽  
Speaker Recognition ◽  
Speaker Identification ◽  
Gaussian Mixture ◽  
Identification Accuracy ◽  
Identification System ◽  
Good Representation ◽  
Mel Frequency Cepstral Coefficients ◽  
Normalization Methods ◽  
Cepstral Coefficients

<p><span lang="EN-GB">In this paper, different feature extraction and feature normalization methods are investigated for speaker recognition. With a view to give a good representation of acoustic speech signals, Power Normalized Cepstral Coefficients (PNCCs) and Mel Frequency Cepstral Coefficients (MFCCs) are employed for feature extraction. Then, to mitigate the effect of linear channel, Cepstral Mean-Variance Normalization (CMVN) and feature warping are utilized. The current paper investigates Text-independent speaker identification system by using 16 coefficients from both the MFCCs and PNCCs features. Eight different speakers are selected from the GRID-Audiovisual database with two females and six males. The speakers are modeled using the coupling between the Universal Background Model and Gaussian Mixture Models (GMM-UBM) in order to get a fast scoring technique and better performance. The system shows 100% in terms of speaker identification accuracy. The results illustrated that PNCCs features have better performance compared to the MFCCs features to identify females compared to male speakers. Furthermore, feature wrapping reported better performance compared to the CMVN method. </span></p>

scholarly journals Avaliação de um Ambiente Virtual de Aprendizagem de Imunologia

EAD em FOCO ◽  
2016 ◽  
Vol 6 (2) ◽  
Author(s):  
Adriano Theodoro ◽  
Gerlinde Agate Platais Brasil Teixeira ◽  
Claudia Marcia Borges Barreto
Keyword(s):  
Learning Environment ◽  
Undergraduate Students ◽  
Learning Experience ◽  
Virtual Learning ◽  
Virtual Learning Environment ◽  
Ease Of Use ◽  
Classroom Teaching ◽  
First Year ◽  
Face To Face ◽  
Teaching Concept

Descrevemos o processo de criação colaborativa de um ambiente virtual de aprendizagem (AVA) de acordo com os princípios das metodologias ativas de ensino e a sua avaliação. O ambiente virtual foi usado no apoio ao ensino presencial. Participaram dessa experiência híbrida de aprendizagem estudantes da disciplina Imunobiologia, oferecida no primeiro ano de um curso tradicional de graduação em Medicina. Ao término da disciplina, foi aplicado um questionário para avaliar a facilidade de uso e a percepção dos estudantes sobre a qualidade do aprendizado adquirido. A maioria dos estudantes que avaliaram a intervenção pedagógica afirmou que o ambiente foi fácil de usar, atendeu às expectativas de apoio ao ensino presencial e as atividades didáticas foram importantes para o aprendizado de habilidades como reflexão, pesquisa e discussão. Portanto, o ambiente virtual desenvolvido foi bem-sucedido e bem-aceito pelos estudantes.Palavras-chave: Educação a distância, Moodle; Ensino de Imunologia, Mapa conceitual.? Evaluation of a Virtual Learning Environment of ImmunologyAbstractWe herein describe the process of collaborative creation and evaluation of a Virtual Learning Environment of Immunology according to the principles of active learning. The Web-based platform was used in support of face to face classroom teaching. First year Medicine undergraduate students attending Immunobiology? course participated in this blended learning experience. At the end of the course, a questionnaire was applied to evaluate the ease of use and the students' perception of the quality of the acquired learning. Most students assessed the educational intervention said that the environment was easy to use, supports the classroom teaching and the educational activities were important for learning skills such as reflection, research and discussion. Therefore, the developed virtual environment was successful and well accepted by the students. Keywords: Distance learning, Moodle, Immunology teaching, Concept map.

ITVT-10. Using functional Ultrasound (fUS) for real-time, depth-resolved functional and vascular delineation of brain tumors with micrometer-millisecond precision

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi230-vi230
Author(s):  
Sadaf Soloukey ◽  
Luuk Verhoef ◽  
Frits Mastik ◽  
Bastian Generowicz ◽  
Eelke Bos ◽  
...  
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Cerebral Blood Volume ◽  
Imaging Technique ◽  
Power Doppler ◽  
Ease Of Use ◽  
Frame Rate ◽  
Neurosurgical Procedures ◽  
Vascular Morphology

Abstract BACKGROUND Neurosurgical practice still relies heavily on pre-operatively acquired images to guide tumor resections, a practice which comes with inherent pitfalls such as registration inaccuracy due to brain shift, and lack of real-time functional or morphological feedback. Here we describe functional Ultrasound (fUS) as a new high-resolution, depth-resolved, MRI/CT-registered imaging technique able to detect functional regions and vascular morphology during awake and anesthesized tumor resections. MATERIALS AND METHODS fUS relies on high-frame-rate (HFR) ultrasound, making the technique sensitive to very small motions caused by vascular dynamics (µDoppler) and allowing measurements of changes in cerebral blood volume (CBV) with micrometer-millisecond precision. This opens up the possibility to 1) detect functional response, as CBV-changes reflect changes in metabolism of activated neurons through neurovascular coupling, and 2) visualize in-vivo vascular morphology of pathological and healthy tissue with high resolution at unprecedented depths. During a range of anesthetized and awake neurosurgical procedures we acquired vascular and functional images of brain and spinal cord using conventional ultrasound probes connected to a research acquisition system. Building on Brainlab’s Intra-Operative Navigation modules, we co-registered our intra-operative Power Doppler Images (PDIs) to patient-registered MRI/CT-data in real-time. RESULTS During meningioma and glioma resections, our co-registered PDIs revealed fUS’ ability to visualize the tumor’s feeding vessels and vascular borders in real-time, with a level of detail unprecedented by conventional MRI-sequences. During awake resections, fUS was able to detect distinct, ESM-confirmed functional areas as activated during conventional motor and language tasks. In all cases, images were acquired with micrometer-millisecond (300 µm, 1.5–2.0 ms) precision at imaging depths exceeding 5 cm. CONCLUSION fUS is a new real-time, high-resolution and depth-resolved imaging technique, combining favorable imaging specifications with characteristics such as mobility and ease of use which are uniquely beneficial for a potential image-guided neurosurgical tool.

scholarly journals Defining high-resolution dredge fishing grounds with Automatic Identification System (AIS) data

2017 ◽  
Vol 30 ◽  
pp. 39 ◽  
Author(s):  
Damien Le Guyader ◽  
Cyril Ray ◽  
Françoise Gourmelon ◽  
David Brosset
Keyword(s):  
High Resolution ◽  
Data Access ◽  
Relevant Information ◽  
Fishing Effort ◽  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Local Decision ◽  
Bay Of Brest ◽  
Maritime Spatial Planning

High resolution estimates of bottom towed fishing gears are needed to provide relevant information for natural resource management, impact assessment and maritime spatial planning. The use of satellite-based vessel monitoring system (VMS) data is constrained by data access restrictions as well as rather coarse data resolution. This study focuses on mapping dredge gear fishing grounds using fishing effort estimates at the métier level based on automatic identification system (AIS) data. The performance of the approach was evaluated in terms of correct discrimination between fishing and non-fishing activities for known fishing positions as well as appropriate error propagation. The test was conducted in the Bay of Brest (France) in partnership with a committee of local fishers. The results identified dredge fishing grounds for great scallop (Pecten maximus) in the western part of the Bay of Brest and provided high-resolution information for scientists and local decision makers on the spatial and temporal seasonal variability of fishing effort. The proposed method is semi-automatic and generic making it suitable for other applications.

Learners’ Technological Acceptance of VR Content Development: A Sequential 3-Part Use Case Study of Diverse Post-Secondary Students

2019 ◽  
Vol 13 (03) ◽  
pp. 343-366 ◽  
Author(s):  
Vinh T. Nguyen ◽  
Rebecca Hite ◽  
Tommy Dang
Keyword(s):  
Secondary Students ◽  
Undergraduate Students ◽  
Lessons Learned ◽  
Ease Of Use ◽  
Use Case ◽  
Web Based ◽  
Post Secondary ◽  
Content Development ◽  
Short Period ◽  
Post Secondary Students

Web-based virtual reality (VR) development tools are in ubiquitous use by software developers, and now, university (undergraduate) students, to move beyond using, to creating new and energizing VR content. Web-based VR (WebVR), among other libraries and frameworks, have risen as a low-cost platform for users to create rich and intuitive VR content and applications. However, the success of WebVR as an instructional tool relies on post-secondary students technological acceptance (TA), the intersectionality of a user’s perceived utility (PU) and perceived ease of use (PEOU, or convenience) with said technological tool. Yet, there is a dearth of exploratory studies of students’ experiences with the AR/VR development technologies to infer their TA. To ascertain the viability of WebVR tools for software engineering undergraduates in the classroom, this paper presents a 3-case contextual investigation of 38 undergraduate students tasked with creating VR content. In each use case, students were provided increasing freedom in their VR content development parameters. Results indicated that students demonstrated elements of technological acceptance in their selection of webVR and other platforms, and not only successfully creating rich and robust VR content (PU), but also executing these projects in a short period (PEOU). Other positive externalities observed were students exhibitions of soft skills (e.g. creativity, critical thinking) and different modes of demonstrating coding knowledge, which suggest further study. Discussed are the lessons learned from the WebVR and VR/AR interventions and recommendations for WebVR instruction. This work may be helpful for both learners and teachers using VR/AR in selecting, designing, and developing coursework materials, tools, and libraries.

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