Hareesha K. S.

Manipal Institute of Technology, MAHE, India · Data Science and Computer Application

Introduction Spontaneous intracerebral hemorrhage is the second most common type of stroke with high morbidity and mortality. Outcome prediction is very important in this disease, to enable us tailor treatment strategies especially in a low- and middle-income countries. Today, prediction is predominantly limited to few clinical factors and may not...

Network Intrusion Detection is one of the most researched topics in the field of computer security. Hacktivists use sophisticated tools to launch numerous attacks that hamper the confidentiality, integrity and availability of computer resources. There is an incessant need to safeguard these resources to avoid further damage. In the proposed study,...

This book presents the state of the art of Internet of Things (IoT) from the perspective of healthcare and Ambient Assisted Living (AAL). It discusses the emerging technologies in healthcare services used for healthcare professionals and patients for enhanced living environments and public health. The topics covered in this book include emerging eH...

Essential predictions are to be made by the parties distributed at multiple locations. However, in the process of building a model, perceptive data is not to be revealed. Maintaining the privacy of such data is a foremost concern. Earlier approaches developed for classification and prediction are proven not to be secure enough and the performance i...

Due to the emerging technological advances, cyber-attacks continue to hamper information systems. The changing dimensionality of cyber threat landscape compel security experts to devise novel approaches to address the problem of network intrusion detection. Machine learning algorithms are extensively used to detect intrusions by dint of their remar...

Network data is expanding and that too at an alarming rate. Besides, the sophisticated attack tools used by hackers lead to capricious cyber threat landscape. Traditional models proposed in the field of network intrusion detection using machine learning algorithms emphasize more on improving attack detection rate and reducing false alarms but time...

Drug‐Target interaction (DTI) plays a crucial role in drug discovery, drug repositioning and understanding the drug side effects which helps to identify new therapeutic profiles for various diseases. However, the exponential growth in the genomic and drugs data makes it difficult to identify the new associations between drugs and targets. Therefore...

The problem of network intrusion detection poses innumerable challenges to the research community, industry, and commercial sectors. Moreover, the persistent attacks occurring on the cyber-threat landscape compel researchers to devise robust approaches in order to address the recurring problem. Given the presence of massive network traffic, convent...

Data with respect to individuals are available at multiple sites. Essential inferences can be made based on the collective information that is distributed. However, privacy of the data maintained be different organizations becomes a major concern. There is a necessity to construct precise models to mine crucial information from the distributed data...

Objective: Automated Pap smear cervical screening is one of the most effective imaging based cancer detection tools used for categorizing cervical cell images as normal and abnormal. Traditional classification methods depend on hand-engineered features and show limitations in large, diverse datasets. Effective feature extraction requires an effici...

Three out of every 100 people in this world have some form of scoliosis. A doctor would suggest surgery if scoliosis is severe in certain conditions to prevent it from getting worse. The deformity of spine can be visualized well in 3D rather than in 2D as it is time-consuming to evaluate the degree of deformity. CATIA V5 is used to develop feature-...

Data maintained at various sectors, needs to be mined to derive useful inferences. Larger part of the data is sensitive and not to be revealed while mining. Current methods perform privacy preservation classification either by randomizing, perturbing or anonymizing the data during mining. These forms of privacy preserving mining work well for data...

Virtual reality is an interactive artificial environment simulated using computers and devices like VR headsets. The use of VR in medical science has increased immensely. The future prospects indicate that, excluding games, healthcare will be the largest growing market for AR/VR. Virtual reality helps to provide better solution for diagnostics, tra...

3D deformity of the spine-like scoliosis is commonly assessed using stereo-radiographic technique. The Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) modelling fail in this case, as they are obtained with the patient in sleeping position. Also, they are associated with heavy cost and radiation hazards. We have developed two models na...

The invention relates to system for diagnosis of bone deformities. More particularly the present invention relates to system for diagnosis and planning treatment for Spinal Deformities converting 2D x-ray images and processing the acquired 2D x-ray images to generate 3D images and eventually a 3D model and a diagnostic report.

About psycho-acoustic test on Android platform

 Aphasia is an impairment of language, affecting the production or comprehension of speech and the ability to read or write [2]  Manual therapy requires patient to be present with SLP(Speech Language Therapist)  Automated version MATApp(PCA) allows for remote therapy sessions  Patient: Provides day-wise and overall progress report  SLP: Analys...

Comparative study between the results given by the Android App and the MATLAB application provides insight into the differences in way these platforms handle audio-related applications. The ability of mobile platforms/ OS to be used for applications involving high-level of audio precision is tested. It also raises the question whether modern mobile...

Essential predictions are to be made by the parties distributed at multiple locations. However, in the process of building a model, perceptive data is not to be revealed. Maintaining the privacy of such data is a foremost concern. Earlier approaches developed for classification and prediction are proven not to be secure enough and the performance i...

Privacy preserving data mining engrosses in drawing out information from distributed data without disclosing sensitive information to collaborating sites. This paper aims on the construction of a vertically distributed privacy preserving support vector machine classifier. The learning model is build for datasets, where one of the collaborating part...

Replication has been a feasible solution for increasing the data availability and improving overall system performance. In mobile ad hoc networks (MANETs), a proficient replica management is a challenging problem due to its unreliability, dynamic, and unstable and resource constrained nature. The data replication improves the data availability and...

Mobile Ad hoc NETworks (MANETs) comprise of hosts moving freely thereby resulting in disconnections very frequently, and this causes frequent network partitioning. In such scenarios data replication profoundly improves data availability. With replicas the consistency among the replicas is a major issue. In this paper, a consistency method based on...

Pair programming is one of the widely used practices of Extreme Programming (XP). XP is a software development process which intends to enhance quality of software code in order to cater to the ever increasing demands of customers looking for IT solutions. Pair programming promotes team building, raises confidence among individuals and eventually r...

Hyperchromasia is one of the most common dysplastic change occur in cervical cell images particularly in the nucleus region. The texture of an image is a function of spatial variations of the gray level values and it is used to measure the variations of the pixel intensity of the surface in an image. Gray level co-occurrence matrix (GLCM) is widely...

Abstract Three dimensional reconstruction is essential in accurate diagnosis of numerous spinal deformities which are 3D in nature. The stereo-radiographic reconstruction involving bi-planar X-rays is one of the most commonly used methods. Algorithms with stereo-corresponding point (SCP) or non-stereo-corresponding point (NSCP) can be used to achie...

Data maintained at various sectors, needs to be mined to derive useful inferences. Larger part of the data is sensitive and not to be revealed while mining. Current methods perform privacy preservation classification either by randomizing, perturbing or anonymizing the data during mining. These forms of privacy preserving mining work well for data...

The 3D reconstruction of the human spine is essential for accurate diagnosis of deformities like scoliosis. Here, a low cost stereo-radiographic 3D reconstruction method is proposed. A generic model is built using biomedical modeling of a cadaveric spine. Biplanar radiographs are obtained from the subject using a calibration apparatus. Six stereo-c...

A novel intelligent automated model to recognize and classify a cashew kernels using Artificial Neural Network (ANN). The model primarily intends to work on two phases. The phase one, built with a proposed method to extract features, which includes 16 morphological features and also 24 color features from the input cashew kernel images. In phase tw...

Three-dimensional reconstruction of the spine is necessary in proper diagnosis of various spinal deformities. This is normally achieved using stereo-radiographic techniques involving biplanar (frontal and lateral) radiographs. Either stereo-corresponding point (SCP) algorithm or non-stereo-corresponding point (NSCP) algorithm is used for this purpo...

Complex deformities of the spine, like scoliosis, are evaluated more precisely using stereo-radiographic 3D reconstruction techniques. Primarily, it uses six stereo-corresponding points available on the vertebral body for the 3D reconstruction of each vertebra. The wireframe structure obtained in this process has poor visualization, hence difficult...

In this paper, the method for building a supervised intelligent classification model for white wholes (WW) grades of cashew kernel using different images was discussed. The morphological, colour, and texture features were used to train or test different classifiers for recognition and classification. In order to achieve the best prediction accuracy...

Three dimensional models have their principal part of application in the medical domain. In the medical field, a three dimensional model gives a more accurate and visually viable version of the internal organs, bone structures, blood vessels and tissue structures. Hence various algorithms and software have been developed in the recent years for acc...

The purpose of this study is to validate the feature based 3D model obtained from deformation of calibrated stereo-radiographic reconstruction. At present, this 3D spine deformation is evaluated in 2-D using frontal and lateral radiographs which is inaccurate. Advanced imaging modalities such as CT and MRI are not suitable as they are obtained with...

Distributed computing demands training methods that handle distributed input data. While training, as the parties that collaborate are concerned about the privacy of their data, the concept of privacy preservation should be extended in data mining classifiers. In this paper, data holders make practical use of their data to construct a precise class...

The poster briefly explains the design and development of calibration apparatus used in this work. Different enhancement and segmentation techniques used to obtain an efficient landmark identification procedure is also discussed. Design and development of a geometric spine model (generic model) are one of the highlights of the poster. A novel stere...

The mobile ad-hoc networks (MANETs) are decentralized network with resource constrained and mobile nodes. This characteristics of MANETS has a direct impact on the data availability. Replication has been used as one technique to improve the data availability both in MANETs and fixed networks [1][2]. Data replication has an impact on the network res...

In Mobile Adhoc Networks (MANETs), data availability is lower in comparison to the conventional fixed networks because of their mobility and resource-constrained characteristics. Replication and caching have been adapted to improve the performance in these constrained environments. These techniques significantly improve the efficiency of informatio...

Diagnosis of spinal deformities like scoliosis remains a challenging task till date. The method of bi-planar radiography is mostly recommended for diagnosis of this pathology. Since it is a three dimensional deformity 2-D evaluations are inaccurate. Lot of research works have been done in this area leading to the development of different 3-D evalua...

In order to extract interesting patterns, data available at multiple sites has to be trained. The data available in these sites should not be revealed while extorting patterns. Distributed Data mining enables sites to mine patterns based on the knowledge available at different sites. In the process of sites collaborating to develop a model, it is e...

In order to extract interesting patterns, data available at multiple sites has to be trained. Distributed Data mining enables sites to mine patterns based on the knowledge available at different sites. In the process of sites collaborating to develop a model, it is extremely important to protect the privacy of data or intermediate results. The feat...

This paper confers an approach of categorizing multiple datasets that are distributed at various sites. The variation in this method of classification is that all the parties jointly build a decision tree model revealing only sufficient information and hiding superfluous data. We have used secure protocols such as secure sum and secure union using...

The deposition of amyloid fibrillar aggregates in human brain results in amyloid illnesses. As these aggregates may spread like virus, it is of primary importance to spot such motif regions in protein sequences. Limitations of molecular techniques in identifying them offer sophisticated computational methods for their efficient retrieval. In this p...

The failure of proteins to fold correctly result in amyloidosis. Therefore, amyloid plaque prediction has become significant to narrow down the exploration of anti-amyloidosis and related drugs. In this research article, we propose a unique hybrid approach to computationally predict the formation of amyloid plaques by exploiting diversity in the fe...

Unreliable wireless communication, mobility of network participants and limited resource capabilities of mobile devices make conventional replication techniques non suitable for MANETs. Frequent network partitions and dynamic disconnection should be handled to improve data availability. In this paper, a novel node failure fault tolerant data replic...

Several data mining processes include privacy preservation in order to avoid disclosure of sensitive information while discovering knowledge. Data mining algorithms uses numerous modification techniques to construct models or patterns from private data. It is essential to evaluate the quality of the data resulting from the alteration applied by eac...

We present an efficient computational architecture designed using supervised machine learning model to predict amyloid fibril forming protein segments, named AmylPepPred. The proposed prediction model is based on bio-physio-chemical properties of primary sequences and auto-correlation function of their amino acid indices. AmylPepPred provides a use...

We present an efficient computational architecture designed using supervised machine learning model to predict amyloid fibril forming protein segments, named AmylPepPred. The proposed prediction model is based on bio-physio-chemical properties of primary sequences and auto-correlation function of their amino acid indices. AmylPepPred provides a use...

Carrying out Food and Agricultural product Quality Inspection manually is a laborious task. Maintaining consistent product quality is not possible due to human errors. Customer expectations are increasing day by day and seek products of high quality. However, in India the Inspection of Food and Agricultural produce is done manually in most of the c...

The top and bottom of the pedicles are used as landmarks for 3D stereo radiographic reconstruction of vertebrae. At present the landmark identification is manual that can cause observer variability which in turn reduces the accuracy of 3D stereo radiographic reconstruction. A semiautomatic method for segmenting pedicles from biplanar (PA and Late...

It is important to understand the cause of amyloid illnesses by predicting the short protein fragments capable of forming amyloid-like fibril motifs aiding in the discovery of sequence-targeted anti-aggregation drugs. It is extremely desirable to design computational tools to provide affordable in silico predictions owing to the limitations of mole...

Amyloid fibril forming regions in protein sequences are associated with a number of diseases. Experimental evidences compel in favor of the hypothesis that short motif regions are responsible for its amyloidogenic behavior. Thus, identifying these short peptides is critical in understanding the cause of diseases associated with aggregation of prote...

A special class of mobile application has been made feasible by Mobile ad-hoc networks. They benefit from the fast deployment and reconfiguration of the networks, are mainly characterized by the need to support many-to-many interaction schema within groups of cooperating mobile hosts and are likely to use replication of data objects to achieve perf...

Prediction of short stretches in protein sequences capable of forming amyloid-like fibrils is important in understanding the underlying cause of amyloid illnesses thereby aiding in the discovery of sequence-targeted anti-aggregation pharmaceuticals. Due to the constraints of experimental molecular techniques in identifying such motif segments, it i...

Amylhexset This file contains the Genbank / Swissprot Accession Nos. of positive and negative data samples collected from the literature, which have been used for training and testing.

AAindex Ids or Accession Nos. of 40 BPC properties used. This file shows the BPC properties selected by the memetic algorithm.

Identifying amyloidogenic regions in protein sequences is useful in understanding the underlying cause of several human diseases and finding potential therapeutic targets. Given the laborious nature of experimental validation of segments most prone to form fibrils, it was essential that computational approaches be developed that could produce relia...

Edges characterize boundaries and are therefore a problem of fundamental importance in quality assessment of agricultural and food products. Since edge detection is in the forefront of computer vision system for detection of vegetables, fruits and food grains needs to quality inspection and evaluation, it is crucial to have a good understanding of...

Amyloidogenic regions in polypeptide chains are associated with a number of diseases. Experimental evidence is compelling in favor of the hypothesis that small segments of proteins are responsible for its amyloidogenic behavior. Thus, identifying these short peptides is critical for understanding diseases associated with protein misfolding and deve...

Privacy Preserving Data mining techniques depends on privacy,which captures what information is sensitive in the original dataand should therefore be protected from either direct or indirectdisclosure. Secrecy and anonymity are useful ways of thinkingabout privacy. This privacy should be measureable and entity tobe considered private should be valu...

Amyloidogenic regions in polypeptide chains are associated with a number of pathologies including neurodegenerative diseases. Recent studies have shown that small regions of proteins are responsible for its amyloidogenic behavior. Therefore, identifying these short peptides is critical for understanding diseases associated with protein aggregation....

The paper presents the recent development andapplication of image analysis and computervision system in quality evaluation of productsin the field of agricultural and food. It is verymuch essential to through light on basicconcepts and technologies associated withcomputer vision system, a tool used in imageanalysis and automated sorting and grading...

Classification is one of the most ubiquitous data mining problems found in real life. Decision tree classification is one of the best-known solution approaches. This paper describes the construction of a decision tree classifier on vertically partitioned data owned by different owners, by concealing the data held by the parties. Our protocol uses a...

The paper presents the recent development and application of image analysis and computer vision systems in sorting and grading of products in the field of agricultural and food. Basic concepts and technologies associated with computer vision, a tool used in image analysis and automated sorting and grading is highlighted.For the ever-increasing popu...

Face recognition is one of the challenging problems in human-computer interaction. An automated face recognition system requires an efficient method for detection of face region in the image sequence, extraction of facial features, and construction of a recognition model. In recent years, support vector machines (SVMs) have demonstrated excellent p...