The centroid of a set of points can be used by a sensor to compute its location provided that each point represents an anchor with a known location. In this paper, we present mathematical characteristics of centroid based localization in a wireless sensor network. We prove that the centroid of a set of points minimizes an objective function, which is the summation of squares of distances from individual

The Government land is a very important, costly and a crucial part of land as per revenue records. The encroachment/unauthorised activities on the Government land is a very common phenomenon as well as a very challenging issue for the district revenue administration. In the present era, the Geo-Spatial technology plays an enabling role to monitor land usage and contain such issues. To monitor and protect

In this paper, we focus on novel designs for digital code converter and parity generator circuits in quantum-dot cellular automata (QCA) technology, which is transistor less computation approach and encodes binary information through the configuration of charges among quantum dots. In existing works, code converters and parity generators have been designed using majority gate and inverter-based XOR

Machine learning has emerged as the most widely used tool in resolving administrative and other educational-related problems like student dropout. Most of the research in the educational field centers on demonstrating the student’s potential rather than focusing on faculty quality. This paper proposed a model, which is the fusion of stacking and voting ensemble, to evaluate faculty performance. We

In the present era, the internet of things (IoT) plays an important role in diverse domains, including weather prediction. Accurate weather forecasting is very crucial for the huge production of crops. Different methods such as mathematical and statistical models have been developed to predict the weather condition of Bangladesh. In this paper, we have proposed an IoT-based low-cost smart weather prediction

This paper proposes the right and left motor velocity based multi-objective genetic algorithm controlled navigation method for Two-Wheeled Pioneer P3-DX Robot (TWPR) in Virtual Robot Experimentation Platform (V-REP) software scenarios. The first objective function is made by taking front, left, and right ultrasonic sensors data and right motor velocity. Similarly, the second objective function is designed

Pattern Recognition is the method of mapping the inputs to their respective target classes based on features of data. In this paper a stacked ensemble meta-learning approach for customized convolutional neural network is proposed for Marathi handwritten numeral recognition. Stacked ensemble merges the pre-trained base pipe lines to create a multi-head meta-learning classifier that outputs the final

To enhance the Assamese stemmer several approaches and solutions by researchers have been proposed. Such stemmers are important as the features are often applied for application-oriented projects, and especially, to develop information retrieval (IR) systems. Assamese stemming could be defined as a process that strips off a set of suffixes from words. But this process also has certain set back such

In recent years, cloud computing is becoming an attractive research topic for its emerging issues and challenges. Not only in research but also the enterprises are rapidly adopting cloud computing because of its numerous profitable services. Cloud computing provides a variety of quality of services (QoSs) and allows its users to access these services in the form of infrastructure, platform and software

Smart cities still promise a lot for residents, despite the millions of smart services and applications that have changed many of our lifestyles for the better in various fields such as transportation, health, education, services, business, and others. However, users want more of these services that make their lives easier and more sophisticated. Traffic congestion is one of the most common problems

The efficacy of content-based image classification is dependent on the richness of the feature vectors extracted from the image data. Traditional feature extraction techniques highlight single low level image characteristics like shape, size, texture, color etc. for feature generation. The process often fails to extract meaningful descriptors since considering a single image characteristic will ignore

FPGA is widely used as hardware accelerator to improve the performance of convolutional neural network (CNN). Performance of CNN can be improved by increasing the throughput of convolution layer using any parallelism technique/s, as convolution operation occupies around ninety percent of total computations in CNN. Usually a CNN model will be configured to support one of the dominant parallelism styles

A large amount of textual data is generated online with rapid growth and technological advancement. Deriving interesting patterns like opinions, summaries and facts from the text data is a challenging task. Currently, there is no dataset for subjectivity/objectivity classification data in Indian National Security domain. A News dataset has been created for purpose of subjective/objective sentence classification

Physical inactivity in youth is one of the major concerns in today’s world because the technological developments in various areas have made them lethargic, since just clicking a button fulfills most of their daily requirements. Sedentary behavior that is prolonged sitting with no physical activity is the reason behind numerous physiological diseases in human beings such as obesity, diabetes, cardio-vascular

Internet of Medical Things (IoMT) and embedded systems have improved the healthcare systems by enabling remote monitoring the patients’ health conditions anywhere and anytime especially during novel COVID-19 pandemic. In this paper, an IoT-based predicting model is proposed to predict colorectal cancer (CRC) in elderlies. It provides a CRC predicting model for the involved medical team to continuously

Encryption algorithms based on chaos theory are frequently used due to the sensitivity of initial conditions, control parameters, and pseudo-randomness. They are very useful for data encryption for images, audio, or videos. In this paper, a novel audio encryption method is proposed to provide information security. Firstly, the one-dimensional uncompressed 16-bit audio file of even length is taken.

Identification of human physical activities is an active research area since long due to its application in personalized health and fitness monitoring. The performance accuracy of human activity recognition (HAR) models mainly depend on the features which are extracted from domain knowledge. The features are the input of the classification algorithm to efficiently identify human physical activities

The Internet-of-Things (IoT) aims to combines physical objects in the world under a common infrastructure, it gives not only control of things, but also notify the state of the things. The automation for power saving based on the IoT has great business potential. The serious concern about the wastage of energy and this paper proposes an innovative hybrid method for automation system to reduce the wastage

The digital transformation of all the conventional systems in the field, such as healthcare, transportation and education, has led to the massive outflow of data. The bulk of data generated by the digital devices is challenging to handle, resulting in latency issues while provisioning services to the end-users. To address this issue, a promising solution is provided by osmotic computing, which exploits

Speckle noise is a commonly known phenomenon for ultrasound imaging systems, which got introduced due to random interference of coherent waves. The measurement of uncertainty, called as Entropy, shows a considerable effect on medical contrast enhanced ultrasound images. An approach has been implemented and tested on various images using a filter bank and presented an effective nature of filtered images

In the field of wireless sensor network (WSN), anomaly detection is an important task. In this work, we have presented an anomaly detection process using ensemble random forest (ERF) in wireless sensor networks. We choose Decision Tree, Naive Bayes, and K-Nearest Neighbor as the base learners of the ensemble. We also used bootstrap sampling to construct the random forest. Here, we used python 3.7.7

Mobile devices are no less than ticking time bombs if examined from security perspective, as their exertion is intense and relative security measures are quite a few. Attackers at present scenario are switching over to techniques that easily obfuscate the existing state-of-art tools and victims to get their work done. Evasion is one such tactic to confuse security system or obfuscate the information

Diagnosing the neurodegenerative disorder called Parkinson’s disease (PD) is based on the symptoms that could be found only when 60% of dopamine content is lost (advanced stage) in the midbrain. The disease has no clinical tests in its earlier stage which leads to investigate an innovative method to diagnose PD in its early stage. The novelty of the work is to frame a mathematical model for the neurotransmitter

Path planning plays an important role while moving the robot from one location to another. The present paper is concerned with solving the path planning problem of the biped robot in a static environment. Here, an attempt is made to combine the benefits of established rapidly exploring random trees (RRT) algorithm and visibility graph algorithm. Various approaches, such as normal RRT that starts the

Semantic text similarity (STS) is a challenging issue for natural language processing due to linguistic expression variability and ambiguities. The degree of the likelihood between the two sentences is calculated by sentence similarity. It plays a prominent role in many applications like information retrieval (IR), plagiarism detection (PD), question answering platform and text paraphrasing, etc. Now

The processing power of today's smart mobile devices allows real-time geolocation sharing. On the other hand, the Public Universities have their own transportation system for their students, teachers and administrative personnel; The National Universities in Peru are not the exception, the location, whereabouts and schedules that are constantly updated by the administration of the service are unknown

With rapid growth in user generated contents on the Web, various NLP research areas are emerging to utilize this information in ways that will facilitate users to manipulate the data efficiently. Opinion mining is one such area of research gaining interest among researchers to develop automated NLP systems that will be able to analyze sentiments expressed in natural languages. Being language and domain

ZeroAccess is a distributed Peer-to-Peer (P2P) botnet used by attackers for various monetary benefits—including click-fraud, bitcoin mining, pay-per-install and information theft. ZeroAccess infected tens of millions of computers. It creates the hidden file system for stolen credentials, and employ the root-kit techniques for covert communication. In this paper, we have analyzed a ZeroAccess malware

Tibet is known for its enumerable collection of Nalanda based Buddhism manuscripts that need to be digitized for immortalization of the teachings of Buddha and various Buddhist scholars. Handwritten Tibetan numeral recognition is relatively unexplored as compared to Roman and Chinese numerals. Recognition of handwritten documents for digitalization has been under study from past many years. This work

Radio frequency identification (RFID) is becoming one of the best optimistic technology in the area of ubiquitous computing that plays the most crucial role in object identification as a ubiquitous infrastructure. Indeed, an important role of RFID technology is to provide wireless communication between the RFID tags and readers without line-of-sight (LoS) readability. The tags store the sensitive information

A number of service models have been innovated in the software industry so as to meet customers’ special demands and preferences. In order to develop a service-dominant business model, this project researches the existing molding simulation software, analyses the chosen market and industrial users, defines technical requirements, and then categorizes those demands into different priority levels. Although

The high-frequency trading (HFT) uses the discrete and finite precision Gaussian cumulative distribution table, which leads to the erroneous computation of modern option pricing models. In this context, this paper provides two fast and tight approximations for the Gaussian cumulative distribution function which takes continuous input values and provides a wide range of precision values correct up to

The face recognition under the uncontrolled conditions is a widely debated research topic since from last decade due to technology advancement and the emergence of face recognition applications. The uncontrolled conditions such as illumination and pose variations, light intensity variations, etc. lead the poor face recognition performances. The extraction of invariant features in the presence of illumination

Heterogeneous wireless networks are an integration of dissimilar networks for better coverage and spectral efficiency. These networks differ in cost, reliability, bandwidth, coverage, security, and other related parameters. And cell users roam across these networks and gets connected to the new candidate network during handoff to maintain call continuity for uninterrupted service delivery. But the

Flood is the most common type of natural disaster in sub-Saharan Africa, and causes tremendous damage to life, economy and agriculture. Effective and accurate means of predicting flood and its magnitude are still lacking to a large extent. This study is aimed at designing a concise and efficient model that can determine or predict flood and its magnitude using available data from areas prone to flood

In this research, machine vision system is developed for the automatic identification of plant disease symptoms, from color images. Visual symptoms based identification of viral and bacterial diseases in plants using image processing and pattern classification is presented. Viral and bacterial plant disease symptoms affecting leaf, stem and fruit are segmented and features are selected based on co-occurrence

A significant quality factor reliability is an important requirement for all software systems. Reliability analysis and evaluation for a system is necessary for the success of these systems. This paper proposes a fault metric called use case fault metric (UCFM) for object-oriented systems using use case diagram and is built on the theory of Fault Tree Analysis (FTA). The goal is to address an important

The Associative Classification approach combining the classification and association rule mining techniques is now becoming reliable classification strategy for obtaining moderate sized classifiers with enhanced accuracy rate. The associative classification techniques when applied on large databases produce huge number of rules and make difficult to achieve effective classification model. To overcome

Video surveillance has become a major tool in security maintenance. But analyzing in a playback version to detect any motion or any sort of movements might be tedious work because only for a short length of the video there would be any motion. There would be a lot of time wasted in analyzing the video and also it is impossible to always find the accurate frame where the transition has occurred. So

Modern apps based businesses are increasingly interested in data driven decision making to achieve business goals as well as retaining their customer base. In this paper, we propose a Bayesian network approach to assess the mobile apps user behavior. We propose a strategy to build Bayesian networks and further improve the causal networks using re-sampling methods to best represent the causal representation

The collection of pervasive data from e-healthcare system inherits potential medical significance through the mode of data exchange with the service providers of professional health care. The sensitive data exchange between the health care providers need to satisfy the requirements of user privacy, since the environment of fog computing is highly vulnerable due to the injection of false data from the

The systems that filter the information and help the users in opting the desired items based on their previous transactions are the recommender systems. These systems are vital and are currently being used widely in various areas of social importance—tourism being one of them. Using a recommendation technique in travel and tourism related activities enhances the quality of decision making and gives

Offline signature verification paves way to an effective automation of authorizations needed in various real world applications. The use of a neural network in the automatic identification of signatures supports a faster validation that involves lowering labor costs as well as eliminating any form of bias. The models presently in use perform an image embedding based comparison between the test signature’s

The symptoms of disease manifest in the pulse long before they do in the body. This technique helps to get to the root cause of the disease instead of just treating it based on the visible signs and symptoms. Unfortunately, Indian Ayurveda/Traditional Medical System using Pulse signals, Tridosha and Panchamahabhutas diagnosis has not been optimally exploited. The existing Tridosha based diagnosis are

Vehicular adhoc networks is one of the tangible applications of MANETs which is designed to facilitate road safety application in a messy road environment. The sharing of location information between the vehicles plays a vital role in avoiding fatal accidents. The communication is established via direct communication for transmitting emergency messages between the vehicles. But the presence of interference

Massive MIMO is considered as promising technology enabling 5G and beyond 5G cellular communication networks. High-resolution gain and angle estimation of the channel are significant challenges in the design of massive MIMO. The existing signal subspace-based estimation techniques lack the resolution for the detection of slight angles. The severity increases when both azimuth and elevation angle are

Deadlock in a shared resource system is a well-known problem. It has been extensively studied and recently a new class of resource reservation technique is researched upon for deadlock free resource management. This class of technique reserves a portion of the resources. The unreserved resources are freely allocated to any process demanding it. When the unreserved resources are not sufficient for a

The global pandemic of COVID-19 has been going on for over sixteen months. During this period, we have witnessed a colossal loss of life, property, business, and a degradation of social life. Several different variants or strains of SARS-CoV-2, which causes COVID-19, have been found in different parts of the world. This pandemic has so far infected more than one hundred and thirty five million people

Due to the increasing demands of minimizing the delay for Internet of things (IoT) applications, cloud computing researchers are now moving towards the research in fog computing and edge computing area. Fog computing serves the purpose of bringing devices closer to the proximity of data centre by performing some specific possible tasks nearest to the vicinity of devices requiring the services and ultimately

A patient centric social network enables connecting patients suffering from the same disease or health conditions. The growth of such a network depends highly on the recommendations like ‘patient to patient’ and ‘caregivers to a patient’. From a patient’s point of view, discovering a person with similar conditions like him gives him some sort of solace thereby encouraging him to extend support to the

In the era of climate change, monitoring and effective retrieval of soil, water bodies, vegetation parameters etc. are of utmost importance which is successfully being executed using remote sensing from last few decades. The advancement of technologies has enabled us to reach effective decision making through these sensors. The advantage of acquiring multitemporal spatially continuous data sometimes

The 5G technology will revolutionize the world more than 3G or 4G. 5G means a world where not only people but all the things are also connected. Thus, a new version of wireless technology gives us a lot of advantages which include a boost in speed, reduce reluctance, and provides a more reliable connection for a wide range of users. In this paper, the design of 5G Multiple Inputs and Multiple Outputs

The automation in all walks of daily life is required for secure communication by overcoming with traditional techniques like Badges, Personal ID cards etc., In the proposed research work Dual Tree Complex Wavelet Transformation (DTCWT) fingerprint recognition method for data base FVC 2004 DB 3_A is carried out. The Preprocessing has been carried out for all the images to obtain uniform size i.e.,

Quantum-dot cellular automata (QCA) has the capability to scale down beyond the range of CMOS. Besides wide acceptance of QCA, it suffers from different challenges, regular structure and configurability is one of them. The disparate design in QCA increases design complexity as well as cost. The disparity of design needs different clocking layout for the correct propagation of signals. Moreover, the

Useful real-life images meant for computer vision applications appear in complex forms with varied backgrounds. Convolutional neural networks with their invariance outperforms capsule networks (CapsNets) on such images. Recent research to improve the accuracy of CapsNets on complex images such as CIFAR10 involves the increase in depth of the networks. However, smaller architectures with efficient feature

In this paper, we propose a novel data structure and the algorithms to build, update and perform range query operations of transitive function. The update and query operation takes O(log(n)) time, and the space required for operating data is also O(cn), where c=3 proving it to be efficient than other data structures such as segment tree and sparse table. Experimental analysis shows the statistical

A large part of the world population has been engaged in agriculture and its related activities since ancient times. Farmers have usually relied on their own experiences to make any decision about agriculture or farm management. As agriculture is greatly affected by unpredictable weather conditions, it becomes difficult to take decisions with total confidence, and many a times farmers have to suffer

Healthcare Industry experiences a rapid change in the traditional way of providing Medical Services to Patients with the revolution of the Internet of Things (IoT) and the Digitization of services. The Healthcare IoT (HIoT) provides Hospitals to render excellent services to Patients at an optimized cost. The Healthcare IoT must ensure not to disrupt or tamper with sensitive Medical Information of the

The golden rule developed by Gordon E. Moore in 1965 stands forth and upholds its perception, which is observant with trending technology and making organizations, groups and individuals extract benefits from machine. AI, Robotics, Business Intelligence, Big Data and Analytics, Edge Computing, Hyperautomation, Blockchain, Democratization, Human Augmentation, Multiexperience are technical domains and

Recently, Deep Neural Networks (DNNs) have played a major role in revolutionizing Artificial Intelligence (AI). These methods have made unprecedented progress in several recognition and detection tasks, achieving accuracy close to, or even better, than human perception. However, their complex architectures requires high computational resources, restricting their usage in embedded devices due to limited