Sentiment Analysis (SA) is an opinion mining study analyzing people's opinions, sentiments, evaluations and appraisals towards societal entities such as products, services, individuals, organizations, events, etc. Of late, most of the research works on SA in natural language processing (NLP) are focused English language. However, it noted that Bangla does not have a proper dataset both large standard. As result, recent with fallen short to produce results can be comparable done by others...

How do the pioneer networks in axial core of vertebrate nervous system first develop? Fundamental to understanding any full-scale neuronal network is knowledge constituent neurons, their properties, synaptic interconnections, and normal activity. Our novel strategy uses basic developmental rules generate model that retain individual neuron synapse resolution are capable reproducing correct, whole animal responses. We apply our young Xenopus tadpoles, whose brainstem spinal cord share a plan,...

Long Short Term Memory (LSTM) has been a very successful augmented recurrent neural network model employed to learn sequential information with long term dependencies where LSTM can store and compute for period of time. In this study, biologically inspired variation incorporated in by introducing additive cell state into the functionally computational system. The novel biological variant conduct sentiment analysis textual data. As learning dataset, fifty thousand movie reviews have used from...

Early detection of fish diseases and identifying the underlying causes are crucial for farmers to take necessary steps mitigate potential outbreak thus avert financial losses with apparent negative implications national economy. Typically, caused by viruses bacteria; according biochemical studies, presence certain bacteria may affect level pH, DO, BOD, COD, TSS, TDS, EC, PO43-, NO3-N, NH3-N in water, resulting death fishes. Besides, natural processes, e.g., photosynthesis, respiration,...

Sentiment Analysis (SA) is an action research area in the digital age. With rapid and constant growth of online social media sites services, increasing amount textual data such as - statuses, comments, reviews etc. available them, application automatic SA on rise. However, most works natural language processing (NLP) are based English language. Despite being sixth widely spoken world, Bangla still does not have a large standard dataset. Because this, recent failed to produce results that can...

The growth of abnormal cells in the brain's tissue causes brain tumors. Brain tumors are considered one most dangerous disorders children and adults. It develops quickly, patient's survival prospects slim if not appropriately treated. Proper treatment planning precise diagnoses essential to improving a life expectancy. mainly diagnosed using magnetic resonance imaging (MRI). As part convolution neural network (CNN)-based illustration, an architecture containing five layers, max-pooling...

Relating structure and function of neuronal circuits is a challenging problem. It requires demonstrating how dynamical patterns spiking activity lead to functions like cognitive behaviour identifying the neurons connections that appropriate circuit. We apply "developmental approach" define connectome simple nervous system, where between are not prescribed but appear as result neuron growth. A gradient based mathematical model two-dimensional axon growth from rows undifferentiated derived for...

ORIGINAL RESEARCH article Front. Neuroinform., 23 September 2011 Volume 5 - | https://doi.org/10.3389/fninf.2011.00020

The application of Internet Things (IoT) in a poultry farm allows real-time monitoring the context through notification to smartphone, predicts advance, advises right decision at time that saves lives, minimize economic loss, and improves productivity quality. Monitoring weather is one important issues involves status temperature, humidity, etc. has impact on raw materials quality food, health condition poultry, feeding time, food management, Considering fact, improve management increase...

We study a novel phenomenon for coupled identical bursters: synchronized bursts where there are changes of spike synchrony within each burst. The examples we normal form elliptic bursters is periodic slow passage around Bautin (codimension two degenerate Andronov–Hopf) bifurcation. This burster has subcritical Andronov–Hopf bifurcation at the onset repetitive spiking, while end burst occurs via fold limit cycle synchronization behavior and three Bautin-type linear direct coupling scheme as...

Automatic image captioning task in different language is a challenging which has not been well investigated yet due to the lack of dataset and effective models. It also requires good understanding scene contextual embedding for robust semantic interpretation images natural descriptor. To generate descriptor Bangla, we created new Bangla paired with target label, named as Natural Language Image Text (BNLIT) dataset. deal understanding, propose hybrid encoder-decoder model based on...

Land use and transportation planning have a significant impact on the performance of cities’ traffic conditions quality people’s lives. The changing characteristics land will affect challenge how city is able to manage, organize, plan for new developments transportation. These challenges can be better addressed with effective methods monitoring predicting, which enable optimal efficiency in growing like Calgary, Canada, perform. Using ontology initiative currently being researched explored....

We presented a learning model that generated natural language description of images. The utilized the connections between and visual data by produced text line based contents from given image. Our Hybrid Recurrent Neural Network is on intricacies Convolutional (CNN), Long Short-Term Memory (LSTM), Bi-directional (BRNN) models. conducted experiments three benchmark datasets, e.g., Flickr8K, Flickr30K, MS COCO. hybrid LSTM to encode or sentences independent object location BRNN for word...

Automated image to text generation is a computationally challenging computer vision task which requires sufficient comprehension of both syntactic and semantic meaning an generate meaningful description. Until recent times, it has been studied limited scope due the lack visual-descriptor dataset functional models capture intrinsic complexities involving features image. In this study, novel was constructed by generating Bangla textual descriptor from visual input, called Natural Language...

As an on-going pandemic caused by the out-break of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or simply COVID-19 sweeps through globe at unprecedented rate leaving behind trails high infection and mortality, it is crucial to understand propagation dynamics virus in a host population order take urgent effective remedial mitigating steps save life. It already observed many countries communities that accurate timely testing, tracing, tracking lead better containment slowing...

Image noise is a prevalent issue often created by inadequate lighting, cameras of low quality, compression images and other factors. While image quality anticipated to degrade visual identification outcomes, most present object recognition techniques benchmarks, such as Pascal Visual Object Classes Challenge Microsoft Common Objects in Context Challenge, concentrate on comparatively high quality. Meanwhile, the objects noisy surveillance fields issue. In this paper we discuss detection...

Understanding the mechanisms underlying self-assembly and organization of functional neuronal networks is a crucial problem confronting both experimental theoretical neuroscience alike. Early in development, self-assemble with astonishing rapidity. It is, therefore, imperative to investigate understand how far simple basic can allow primary functioning circuits develop. To address this ‘structure-function’ issue, we model anatomy electrophysiology young hatchling Xenopus tadpole’s spinal...

This paper compared two different models for predicting traffic counts based on land use and demographic variables the City of Calgary. Land characteristics were used as independent vari ables at Dissemination Area (DA) (small geographic unit having a population range 400–700) level in Traffic count data from Calgary dependent variable to devel op statistical Neural Network models. Negative Binomial (with log-link) developed, observed be over-dispersed. developed mul tilayered, feed-forward,...

Object detection systems based on deep learning have been immensely successful incomplex object tasks images and shown potential in a wide range of real-life applicationsincluding the COVID-19 pandemic. One key challenges containing mitigating infectionamong population is to ensure enforce proper use face masks. The objective this paperis detect facial masks among urban megacity. In study, wetrained validated new dataset such as ‘with mask’, ‘without ‘masknot position’ using YOLOv5....

Cricket is an unpredictable sport in which two teams compete. The most challenging task cricket to predict possible scores, where reliability (in terms of accuracy score prediction) crucial. Traditional approaches and methods are limited regarding timely prediction, particularly the case hundred-ball forecast probable scores. In this paper, we study game events related datasets perform prediction matches. To make match employ a deep learning method, not yet applied cricket, especially apply...