Alzheimer's disease (AD) may cause damage to the memory cells permanently, which results in form of dementia. The diagnosis at an early stage is a problematic task for researchers. For this, machine learning and deep convolutional neural network (CNN) based approaches are readily available solve various problems related brain image data analysis. In clinical research, magnetic resonance imaging (MRI) used diagnose AD. accurate classification dementia stages, we need highly discriminative...

Brain tumors have become a leading cause of death around the globe. The main reason for this epidemic is difficulty conducting timely diagnosis tumor. Fortunately, magnetic resonance images (MRI) are utilized to diagnose in most cases. performance Convolutional Neural Network (CNN) depends on many factors (i.e., weight initialization, optimization, batches and epochs, learning rate, activation function, loss network topology), data quality, specific combinations these model attributes. When...

The rapid growth of electronic documents are causing problems like unstructured data that need more time and effort to search a relevant document. Text Document Classification (TDC) has great significance in information processing retrieval where organized into pre-defined classes. Urdu is the most favorite research language South Asian languages because its complex morphology, unique features, lack linguistic resources standard datasets. As compared short text, sentiment analysis, long text...

Alzheimer's is an acute degenerative disease affecting the elderly population all over world. The detection of at early stage in absence a large-scale annotated dataset crucial to clinical treatment for prevention and (AD). In this study, we propose transfer learning base approach classify various stages AD. proposed model can distinguish between normal control (NC), mild cognitive impairment (EMCI), late (LMCI), regard, apply tissue segmentation extract gray matter from MRI scans obtained...

<p>The main objective of this study was to determine if a minimal increase in road light level (luminance) could lead improved driving performance among older adults. Older, middle- aged and younger adults were tested simulator following vision cognitive screening. Comparisons made for the simulated night under two conditions (0.6 2.5 cd/m 2 ). At each level, effects self reported avoidance examined along with vision/cognitive performance. It found that increasing from 0.6 resulted...

Brain tumors, which are uncontrolled growths of brain cells, pose a threat to people worldwide. However, accurately classifying tumors through computerized methods has been difficult due differences in size, shape, and location the limitations medical field. Improved precision is critical detecting as small errors human judgments can result increased mortality rates. This paper proposes new method for improving early detection decision-making tumor severity using learning methodologies....

The most significant factor of interaction among human being is language and speech utilized as the medium. A parametric form a signal used by recognizers to attain peak imperative distinct features communication for recognition reasons. Different feature extraction techniques extract distinguishable characteristics signal. In this paper, performance Gaussian Mixture Model (GMM) based Mel-frequency Cepstral Coefficients (MFCC) bark frequency coefficients (BFCC) speaker identification system...

The popularity of the internet, smartphones, and social networks has contributed to proliferation misleading information like fake news reviews on blogs, online newspapers, e-commerce applications. Fake a worldwide impact potential change political scenarios, deceive people into increasing product sales, defaming politicians or celebrities, misguiding visitors stop visiting place country. Therefore, it is vital find automatic methods detect online. In several past studies, focus was English...

Abstract: Highway agencies are continually facing safety problems on highways, especially horizontal alignments. Traditionally, the geometric design implicitly considers through satisfying minimum requirements for different elements. This article presents a new substantive‐safety approach of alignments based not only guidelines, but also actual collision experience. The curve radii, spiral lengths, lane width, shoulder and tangent lengths determined to optimize mean frequency along highway....

Large volume of Genomics data is produced on daily basis due to the advancement in sequencing technology. This no value if it not properly analysed. Different kinds analytics are required extract useful information from this raw data. Classification, Prediction, Clustering and Pattern Extraction techniques mining. These require appropriate selection attributes for getting accurate results. However, Bioinformatics high dimensional, usually having hundreds attributes. Such large a number...

Alzheimer's disease (AD) is a neurodegenerative disorder, causing the most common dementia in elderly peoples. The AD patients are rapidly increasing each year and sixth leading cause of death USA. Magnetic resonance imaging (MRI) modality used for diagnosis AD. Deep learning based approaches have produced impressive results this domain. early depends on efficient use classification approach. To address issue, study proposes system using two convolutional neural networks (CNN) an...

Various supervised machine-learning algorithms for wind power forecasting have been developed in recent years to manage fluctuations and effectively correlate energy consumption; Meanwhile, the performance of model does suffer from missing values. To address issue values forecast, this paper proposes two methods: Clue-based at random (CMAR) patterned k-nearest Neighbor (PkNN). In addition, a hybrid system has created that is built on 1D-Convolutional neural networks, which are used extract...

<p>In computer vision, image classification is one of the potential processing tasks. Nowadays, fish a wide considered issue within areas machine learning and segmentation. Moreover, it has been extended to variety domains, such as marketing strategies. This paper presents an effective method based on convolutional neural networks (CNNs). The experiments were conducted new dataset Bangladesh’s indigenous species with three kinds splitting: 80-20%, 75-25%, 70-30%. We provide...

Breast cancer (BC) significantly contributes to cancer-related mortality in women, underscoring the criticality of early detection for optimal patient outcomes. Mammography is a key tool identifying and diagnosing breast abnormalities; however, accurately distinguishing malignant mass lesions remains challenging. To address this issue, we propose novel deep learning approach BC screening utilizing mammography images. Our proposed model comprises three distinct stages: data collection from...