bluuebunny/crossref_metadata_2025 huggingface dataset:
ENABLING KNOWLEDGE SHARING BY MANAGING DEPENDENCIES AND INTEROPERABILITY BETWEEN INTERLINKED SPATIAL KNOWLEDGE GRAPHS
Authors: McEachen N. , Lewis J.
Published: June 2023

Abstract. Knowledge sharing is increasingly being recognized as necessary to address societal, economic, environmental, and public health challenges. This often requires collaboration between federal, local, and tribal governments along with the private sector, nonprofit organizations, and institutions of higher education. To achieve this, there needs to be a move away from data-centric to knowledge sharing architectures, such as a Geospatial Knowledge Infrastructure (GKI). Data from multiple organizations need to be properly contextualized in both space and time to support geographically based planning, decision making, cooperation and coordination. A spatial knowledge graph (SKG) is a useful paradigm for facilitating knowledge sharing and collaboration. However, interoperability between independently developed SKGs from different organizations that reference the same geographies is often not automated in a machine-readable way due to a lack of standardization. This paper outlines an architecture that automates interoperability and dependency management between SKGs as they are formally published by version and period of validity. We are calling this approach a spatial knowledge mesh (SKM), as it is a specialization of the data mesh architecture along with the concept of a common geo-registry to facilitate knowledge sharing more easily. The initial implementation, called GeoPrism Registry, is being developed as an open-source spatial knowledge infrastructure as a platform to help countries meet their NSDI and GKI objectives. It was fist funded and deployed to support ministries of health and is more recently being utilized in GeoPlatform.gov.
ROLE OF 3D CITY MODEL DATA AS OPEN DIGITAL COMMONS: A CASE STUDY OF OPENNESS IN JAPAN'S DIGITAL TWIN "PROJECT PLATEAU"
Authors: Seto T. , Furuhashi T. , Uchiyama Y.
Published: June 2023

Abstract. This study aims to clarify the development and utilization of highly accurate and open 3D city models (3DCMs), which began in Japan in 2020. The background of the project is explained based on a review of past efforts in Japan for making geospatial information accessible, the flow of data standardization around CityGML, and the introduction of Free and Open Source Software for Geo-spatial (FOSS4G) tools for data management and visualization. Two aspects of the analysis are reported: quantitative geospatial analysis of LOD1 building data and qualitative evaluation of 40 use cases using these data. The results indicate that approximately 18 million building data points covering 150 cities in Japan have been converted to open data in formats such as CityGML with high accuracy, complementing OpenStreetMap (OSM) data in urban areas. In addition, a total of 40 use cases for these data are demonstrated in new fields, such as urban planning, citizen participation, and even entertainment, with a few of these tools becoming open-source software. Through this project, data related to 3DCMs, which have not necessarily been produced in a unified format or specification in Japan, can now be easily handled as CityGML through a one-stop viewer, and the data are expected to be enhanced, and new geo-services using 3DCMs will be provided under the concept of openness, regardless of the city scale.
GEOAI FOR MARINE ECOSYSTEM MONITORING: A COMPLETE WORKFLOW TO GENERATE MAPS FROM AI MODEL PREDICTIONS
Authors: Talpaert Daudon J. , Contini M. , Urbina-Barreto I. , Elliott B. , Guilhaumon F. , Joly A. , Bonhommeau S. , Barde J.
Published: June 2023

Abstract. Mapping and monitoring marine ecosystems imply several challenges for data collection and processing: water depth, restricted access to locations, instrumentation costs or weather constraints for sampling, among others. Nowadays, Artificial Intelligence (AI) and Geographic Information System (GIS) open source software can be combined in new kinds of workflows, to annotate and predict objects directly on georeferenced raster data (e.g. orthomosaics). Here, we describe and share the code of a generic method to train a deep learning model with spatial annotations and use it to directly generate model predictions as spatial features. This workflow has been tested and validated in three use cases related to marine ecosystem monitoring at different geographic scales: (i) segmentation of corals on orthomosaics made of underwater images to automate coral reef habitats mapping, (ii) detection and classification of fishing vessels on remote sensing satellite imagery to estimate a proxy of fishing effort (iii) segmentation of marine species and habitats on underwater images with a simple geolocation. Models have been successfully trained and the models predictions are displayed with maps in the three use cases.
TEACHING GEOGRAPHIC INFORMATION SCIENCE CONCEPTS WITH QGIS AND THE LIVING TEXTBOOK – TOWARDS A SUSTAINABLE AND INCLUSIVE DISTANCE EDUCATION
Authors: da Silva Mano A. , Augustijn P. W. M.
Published: June 2023

Abstract. In 2020, many students could not travel due to the restrictions imposed by the COVID pandemic. In response, Faculty ITC of the University of Twente offered the online course Principles and Applications of Geographic Information Systems and Earth Observation as the first quartile of a full presential MSc. Programme. The course used the flipped classroom strategy to enhance student's ability to choose the learning strategy that best fitted their learning styles and was developed around four principles: (1) The course was Exercise led - students were introduced to concepts from the exercise descriptions; (2) Every concept taught was demonstrated and operationalized; (3) To emphasize the focus on concept learning, only two software tools were used - QGIS and the Living Textbook; (4) The software tools should be inclusive and encourage technological independence. The first three elements were evaluated by comparing the student feedback, the evaluation questionnaires and the academic attainment levels of the 2020 course with the in-house. The inclusiveness and technological independence were measured via the institutional impact. The results were positive for the new course setup, with students performing slightly better when compared with 2019 in-house edition of the course. The course had a significant institutional impact by contributing to a deeper commitment to open-source software tools. Open source is now the primary choice for teaching, with ITC becoming a QGIS-certified organization.
MAPPING COVID-19 EPIDEMIC DATA USING FOSS
Authors: Zatelli P. , Ciolli M. , Besana A. , Gabellieri N.
Published: June 2023

Abstract. The recognition of spatial and temporal patterns in the distribution of a pandemic plays a pivotal role in guiding policy approaches to its management, containment and elimination. For this purpose, a database has been built for the COVID-19 pandemic in the Trentino Province, in the eastern Italian alps, near the border between Italy and Austria. The database management system and the WebGIS mapping these data is based on Free and Open Source Software. The Data Base Management System (DBMS) runs on MySQL, available under the GNU General Public License, storing and processing geographic data. A custom procedure has been created to update the dataset, with the capability to import data from suitably formatted spreadsheets by an authenticated administrator. To ensure flexibility and responsiveness on desktop and mobile devices, the WebGIS has been created with a client-side approach, using the Leaflet and Bootstrap JavaScript language libraries, available with Open Source Licenses. These libraries, with additional custom scripts, create the user interface and render geographic data into maps. The exchange of data between the DBMS server and the client is performed using geojson tables. To protect the privacy of the patients, WebGIS users cannot access the source data even though maps and graphs can be downloaded as pictures. Geo-statistical analysis aimed at the detection of spatial and temporal patters is underway.
3D4DT: AN APPROACH TO EXPLORE DECISION TREES FOR THEMATIC MAP CREATION AS AN INTERACTIVE 3D SCENE
Authors: Bagert J. , Degbelo A.
Published: June 2023

Abstract. Several tools have been proposed to automatically create thematic maps. A common drawback of these tools is that they rarely provide means for users to explore their decision trees. Users may thus create maps or get some maps proposed, but not know why some suggestions of maps were made. To address this gap, this work introduces 3D4DT, an approach to explore decision trees as a three-dimensional interactive scene. The 3D4DT approach uses JSON as a machine-readable format to represent decision trees and maps JSON elements to user interface elements (e.g. radio buttons and cubes). A preliminary evaluation of 3D4DT has shown effectiveness gains in comparison to information displayed as text+picture, for a decision tree with a simple hierarchical structure. The contributions of this work are relevant to the design of more transparent software for automated thematic map creation.
TOWARDS A PAN-EU BUILDING FOOTPRINT MAP BASED ON THE HIERARCHICAL CONFLATION OF OPEN DATASETS: THE DIGITAL BUILDING STOCK MODEL - DBSM
Authors: Florio P. , Giovando C. , Goch K. , Pesaresi M. , Politis P. , Martinez A.
Published: June 2023

Abstract. This paper presents a hierarchical conflation process applied to open datasets for the creation of a seamless pan-European map of building footprints in vector format, named Digital Building Stock Model – DBSM. The objective is the sequential addition of input components (which currently include OpenStreetMap, Microsoft GlobalML Building Footprints, European Settlement Map), taking into account their limitations, and aiming at the highest level of completeness possible, for planning and evaluating energy transition scenarios at the EU level. The results indicate how DBSM compares robustly against cadastral data from Estonia, used as reference area. The comparison of DBSM with GHS-BUILT-S, a 10 metres resolution grid with worldwide coverage that encodes the built-up surface in each pixel as derived from Sentinel-2 imagery for the year 2018, reveals a relative overestimation of the latter, factored by 0.68 at the EU scale for a sound match.
BULLDOZER, A FREE OPEN SOURCE SCALABLE SOFTWARE FOR DTM EXTRACTION
Authors: Lallement D. , Lassalle P. , Ott Y.
Published: June 2023

Abstract. The paper introduces a software called Bulldozer, designed to extract a Digital Terrain Model (DTM) from a Digital Surface Model (DSM) obtained from various sensors. The software is based on a modified version of the multi-scale Drap Cloth principle to process noisy DSMs of any size, employing a tiling strategy and a stability margin to ensure consistent results. A parameter called max object size is introduced to differentiate objects from the ground during the drap cloth process. Gravity steps and ground distance sampling resolution are adjusted based on the input DSM. No-data and noisy values present in the DSM are detected and converted into no-data values to improve the quality of the Cloth simulation. The paper describes a memory-aware parallel execution strategy using both the multiprocessing and the shared memory Python modules. A benchmark dataset has been created to analyze the results and compare them with alternative approaches and reference datasets. Bulldozer offers an extensive Python API. It is open-source and available on PyPi and GitHub. Additionally, a QGIS plugin has been developed.
Differential impact of isolated topographic bumps on ice sheet flow and subglacial processes
Authors: McKenzie Marion A. , Miller Lauren E. , Slawson Jacob S. , MacKie Emma J. , Wang Shujie
Published: June 2023

Abstract. Topographic highs (“bumps”) across glaciated landscapes have the
potential to temporarily slow ice sheet flow or, conversely, accelerate ice
flow through subglacial strain heating and meltwater production. Isolated
bumps of variable size across the deglaciated landscape of the Cordilleran
Ice Sheet (CIS) of Washington State present an opportunity to study the
influence of topographic highs on ice–bed interactions and ice flow
organization. This work utilizes semi-automatic mapping techniques of
subglacial bedforms to characterize the morphology of streamlined subglacial
bedforms including elongation, surface relief, and orientation, all of which
provide insight into subglacial processes during post-Last Glacial Maximum
deglaciation. We identify a bump-size threshold of several cubic kilometers
– around 4.5 km3 – in which bumps larger than this size will
consistently and significantly disrupt both ice flow organization and
subglacial sedimentary processes, which are fundamental to the genesis of
streamlined subglacial bedforms. Additionally, sedimentary processes are
persistent and well developed downstream of bumps, as reflected by enhanced
bedform elongation and reduced surface relief, likely due to increased
availability and production of subglacial sediment and meltwater. While
isolated topography plays a role in disrupting ice flow, larger bumps have a
greater disruption to ice flow organization, while bumps below the
identified threshold seem to have little effect on ice and subglacial
processes. The variable influence of isolated topographic bumps on ice flow
of the CIS has significant implications for outlet glaciers of the Greenland
Ice Sheet (GrIS) due to similarities in regional topography, where local
bumps are largely unresolved.
Advanced Wireless Automated Toll Tax System
Authors: Jeevanandham J. , Pandiselvam R.
Published: June 2023

This project is aiming at reducing the running cost of the Tollgate and to increase the functionality and reliability of the system. This is being achieved with the help of wireless transmitter and receiver modules.
Balanced Energy Efficient Spanning Tree Approaches for Wireless Sensor Network with Sleep Scheduling Algorithm
Authors: Sujithra T. , Anbarasu S.
Published: June 2023

We Propose Balanced, Localized, Robust, Dynamic state changing and energy efficient spanning tree approaches for Wireless sensor networks which we call Balanced energy Efficient Spanning Tree with Sleep scheduling(BEESP-SS). They are based on the topologies. It is constructed using RNG. Localized Minimum Spanning tree is constructed based on these topologies(LMST).The actual routing tree is constructed based on the transmitter and receiver residual energy. We also consider different parent selection strategies while constructing routing tree and select the best among them. Our solution also involves the load balancing by measuring the energy level of the nodes in the spanning tree, because energy is drain out when large number of messages travelling through the particular node by limiting the messages travelled through the sensor nodes we can improve the lifetime of the spanning tree, it is done by partitioning the messages based on the energy level of the node in the spanning tree and redirect the messages to the some other nodes in the spanning tree. The proposed solution also adapted the Sleep Scheduling Algorithm, it wake up the sensor nodes in the network when it is needed. This paper also handles the route maintenance it includes node insertion and node deletion.
An Experimental Study on Energy Consumption of Cryptographic Algorithms for Mobile Hand-Held Devices
Authors: Asrin Banu P. , Sathish Kumar K.
Published: June 2023

Due to the continuous advancement in technology, mobile devices are playing important role in everyone’s day to day life. Everyone is moving towards wireless mobile systems, but power consumption is an important concern in such devices. While designing, a lot of care has to be taken especially in power optimization because there is no regular power supply in this kind of devices. This paper represents software level cryptographic protocols for optimizing the power consumption in wireless mobile devices. The capacity of battery grows up very slowly, which is insufficient for the electricity that the handheld devices demand, and thus designs and implementations of battery-efficient systems are in urgent need. This work focuses on one important constraint of such devices-battery life-and examines how it is impacted by the use of various security mechanisms.The energy consumption of these algorithms is measured by loading their software level cryptographic protocol implementations through the device’s serial port, running them and measuring their power consumption. Our results will show that proposed cryptographic protocol provides a better security guarantee and acquires much less energy consumption than the existing cryptographic protocols. Finally, performance analysis will show that compared with existing cryptographic protocols, our proposed scheme is to be more simple, secure and efficient.
Scalable Compression of 3-D Medical Image Data Using EBCOT with Volume of Interest Coding
Authors: Manimekalai  , Anusuya
Published: June 2023

Volumetric medical image data usually require a vast amount of resources for storage and transmission. With the wide pervasiveness of medical imaging applications in healthcare settings and the increased interest in telemedicine technologies, it has become essential to reduce both storage and transmission bandwidth requirements needed for archival and communication of related data, preferably by employing lossless compression methods to avoid any negative effects of lossy compression on image quality and diagnostic capabilities. The main objective is to present a 3-D medical image compression method with scalability properties, by quality and resolution up to lossless reconstruction and optimized Volume of Interest (VOI) coding at any bit-rate. The proposed method named as “EBCOT with VOI coding” employs a 3-D integer wavelet transform (3D-IWT) and a modified EBCOT with 3-D contexts to compress the 3-D medical imaging data into a layered bit-stream that is scalable by quality and resolution. VOI coding capabilities are attained after compression by employing a bit-stream reordering procedure, which is based on a weight assignment model that incorporates the position of the VOI and the mean energy of the wavelet coefficients. Optimized VOI coding at any bit-rate is attained by an optimization technique that maximizes the reconstruction quality of the VOI, while allowing for the decoding of background information with peripherally increasing quality around the VOI. Performance evaluations based on real 3-D medical imaging data showed that the proposed method achieves a higher reconstruction quality, in terms of the peak signal-to-noise ratio, than that achieved by 3D-JPEG2000 with VOI coding, when using the MAXSHIFT and general scaling-based methods.
Applications of Fuzzy Sets in the Area of Group Decision for N – Person Game
Authors: Deepa S.
Published: June 2023

Applications of fuzzy sets within the field of decision making were based on the extensions of the classical theories of decision making. Decision making may include any choice or selection of alternatives and is therefore of prime importance in many fields of science. Many managerial decisions are however made with some uncertainty. In case of decision making under conditions of risk or uncertainty more than one states of nature exists, and probabilities or fuzzy decision theories are used to deal with fuzziness. Therefore the quality of the decisions may get diverted from the actual decisional aspects. This paper proposes a set of guidelines based on fuzzy model to be applied for game theories and also work out fuzzy to crisp conversion on the analyzed group decision sets.
Efficient Face Recognition Method Using Multi Algorithm and Average Half Face
Authors: Sumathi S. , RaniHema Malini R. , Thulasi Bai V.
Published: June 2023

Face recognition has received much attention in recent years due to its many applications such as human computer interface, video surveillance and face image database management. It is a challenging technique due to under different lighting conditions, facial expressions and changes in head pose. Single class of feature is not enough to capture all the available information in face. Multi algorithm approach of face recognition improves the accuracy using feature level fusion. This paper proposes an efficient technique for identification of an individual by using Average Half Face (AHF). We propose feature fusion technique using Principal component Analysis (PCA) and Discrete Wavelet Transform (DWT). For classification, distance classifier is used. The proposed method was tested using the cropped extended Yale B database, where the images vary in illumination and expression. High recognition performance has been obtained by fusion of PCA and Wavelet features at feature level for average half face compared to full face.
Online Credit Card Fraudulent Detection Using Data Mining
Authors: Aravindh S. , Venkatesan S. , Kumaravel A.
Published: June 2023

As e-commerce sales continue to grow, the associated online fraud remains an attractive source of revenue for fraudsters. These fraudulent activities impose a considerable financial loss to merchants, making online fraud detection a necessity. The problem of fraud detection is concerned with not only capturing the fraudulent activities, but also capturing them as quickly as possible. This timeliness is crucial to decrease financial losses. In this research, a profiling method has been proposed for credit card fraud detection. The focus is on fraud cases which cannot be detected at the transaction level. In the proposed method the patterns inherent in the time series of aggregated daily amounts spent on an individual credit card account has been extracted. These patterns have been used to shorten the time between when a fraud occurs and when it is finally detected, which resulted in timelier fraud detection, improved detection rate and less financial loss.
Malicious Packet Loss Identification in Disruption Tolerant Network
Authors: Shaldit Sheni J. , Jayashree K. , Fowzia Sihana B.
Published: June 2023

In recent days network is suffering serious problems with the packet loss. Dropping of received packets, even it has adequate buffers is very common in Disruption Tolerant Network. The DTN node facilitates communication between mobile nodes. Sometimes the mobile node selects the DTN with lowest reputation that affects packet delivery ratio. If there is a malicious node in the route, the data packet does not reach its destination. Repeatedly the misbehaving nodes may forge some records to avoid being spotted. To solve these issues we propose a scheme to limit the packet rolling in the direction of misbehaving node. The contact record preserves the previous performance of DTN and the mobile nodes select the best rated DTN for its communication. The record handler is maintained to keep track of incoming and outgoing packets. The witness nodes identify the real misbehaving node. The malicious node needs to be identified and is barred. The genuine packet loss, malicious packet loss are differentiated.
Survey on Security Challenges in Warning Message Dissemination and Possible Solutions
Authors: Balakrishnan Salini , Tripti and Robin Cyriac C.
Published: June 2023

The recent advances in the area of Wireless Communications in Vehicular Ad-hoc Networks (VANET) have brought an emerging platform for both industrialists and for researchers. VANET possess a dynamic topology with multi-hop networks leading to an infrastructure less nature. Communication happens in two ways, one between the moving vehicles and with the Road Side Units (RSU). The usage of wireless medium would surely make it vulnerable to different attacks. By enabling prompt and correct warning messages on road conditions, accident cases etc. VANET can be used to save lives of people, which is the most important application of VANET. Distributing warning messages over a long range is however a very challenging task since message integrity has to be ensured. Also for making the system more reliable nonrepudiation should also be included in the security module. A survey of security issues in notification and warning message dissemination is done in this paper.
A Comparative Study of K-Erlang Distribution and M/M/1 Model in Cloud Computing
Authors: Ruth Evangelin K. , Dhikhi T.
Published: June 2023

Cloud computing is a new emerging computing paradigm in which information and computer resources can beaccessed from Web browser by the users. Arriving customers who find the server busy may retry for service after a period of time in Queuing systems is a Retrial queue. If a new customer, after connected to the cloud service does not find any server free, the system automatically redirects the request towards a waiting queue. At that moment, if that waiting queue is also fully occupied by other customers, then the newly arrived customer has to retry for service after certain time period. This technique is known as Retrial queues. Priority of service request is an important issue because some requests have to be serviced earlier than others. These are requests which can’t stay for a long time in the queueing system. A comparative study on the waiting time of M/Ek/n ( n=1) and M/M/1 queuing system with cloud computing service station. This influences the queueing system to reduce the mean waiting time.
A Novel Approach to Encrypt and Decrypt Color Images
Authors: Giridhar Akula V. S.
Published: June 2023

The proposed cryptosystem avoids all the crypto graphical weaknesses of earlier chaos-based encryption systems. Number of security analysis were carried out on the new algorithm and simulation results show that encryption and decryption are good and the proposed chaotic algorithm is proven to be the good procedure in terms of robustness.
An Enhanced Biometric System for ATM Amount Withdrawals Using Iris Biometric Recognition Method
Authors: Senthil Kumar S. , Usha Nandhini S. , Sangeetha G.
Published: June 2023

A biometric system provides automatic recognition of an individual based on some sort of unique feature or characteristic possessed by the individual. Biometric systems have been developed based on fingerprints, facial features, voice, hand geometry, handwriting, the retina / iris. We are living in the age, in which the demand on security is increasing greatly. Consequently, biometric recognition, which is a safe, reliable and convenient technology for personal recognition, appears. This technology makes use of physiological or behavioral characteristics to identify individual. A biometric system is a pattern recognition system including acquiring the biometric feature from individual, extracting the feature vector from the raw data and comparing this feature vector to another person’s feature vector. Fingerprint, palm-prints, face, iris, gait, speech and signature are widely used biometric features. Biometric recognition can be used in computer network login, internet access, ATM, credit card, national ID card, driver’s license and so on. Nowadays, fingerprint recognition is used widely and successfully. Face recognition is studied by many scholars and experts. Iris recognition is a relatively new branch of biometric recognition. The human iris is the annular part between pupil and sclera. It has distinct feature such as freckles, coronas, stripes, furrows and so on. The retina is the neural part of the eye responsible for vision and the pattern of blood vessels serving the retina is as unique as a fingerprint. The iris is biological feature of a human. It is a unique structure of human which remains stable over a person lifetime. The iris is the annular region of the eye. The left and right irises of an individual can be treated as separate unique identifier. A sample human eye image is given in the below diagram. The iris information can be collected by iris image. The accuracy of iris based recognition system is promising. Each iris is believed to be distinctive and even the irises of identical twins are also different [1]. The iris recognition system has become more users friendly and cost effective. The iris have a very low false accept rate as compared to other biometrics like finger print, face, hand geometry and voice. Iris scans use the characteristics more similar to fingerprints than to the retinal vein pattern. The colored part of the eye appears to be as unique as fingerprints and retina. Scanning technology takes advantage of crypts, furrows, ridges, striatations, ligaments, and collaret. While 240 points are recorded, the image size is 512 bytes, over ten times larger than a retinal scan. The main advantage of the iris scans is the ability to perform them from a distance of up to three feet and short time of scan of only 20 seconds initially, with subsequent identification requiring only two seconds. Glasses and contact lenses do not interfere with the scanning process and identification.
Enormous Possibilities in Big Data: Trends and Applications
Authors: Gill Jasmeen , Singh Shaminder
Published: June 2023

Big data is a relative term describing a situation where the volume, velocity and variety of data exceed an organization’s storage or compute capacity for accurate and timely decision making. In this article, the trends in big data are analyzed with respect to its characteristics. In addition the processing of data is discussed along with various methods and tools like Hadoop. This article also specifies the possibilities of big data in different application areas like IT, Fraud detection, Medical, Retail, Manufacturing, Real estate, Banking etc.
Design and Development of Collaborative Detection and Taxonomy of DDoS Attacks Using ESVM
Authors: Ravichandran S. , Umamaheswari M.
Published: June 2023

Distributed Denial of Service (DDoS) assault is a ceaseless basic risk to the web. Application layer DDoS Attack is gotten from the lower layers. Application layer based DDoS assaults utilize honest to goodness HTTP asks for after foundation of TCP three-way handshaking and overpowers the casualty assets, for example, attachments, CPU, memory, circle, database transfer speed. Arrange layer based DDoS assaults sends the SYN, UDP and ICMP solicitations to the server and debilitates the transfer speed. An oddity discovery system is proposed in this paper to identify DDoS assaults utilizing Enhanced Support Vector Machine (ESVM). The Application layer DDoS Attack, for example, HTTP Flooding, DNS Spoofing and Network layer DDoS Attack, for example, Port Scanning, TCP Flooding, UDP Flooding, ICMP Flooding, Land Flooding. Session Flooding is taken as test tests for ESVM. The Normal client gets to conduct characteristics is taken as preparing tests for ESVM. The movement from the testing tests and preparing tests are Cross Validated and the better arrangement exactness is acquired. Application and Network layer DDoS assaults are arranged with order exactness of 99 % with ESVM.
Spectral Analysis of Harmonic Measurement Using Wavelet Transformation in IEEE -13 Bus System
Authors: Anil Kumar S. V. D.
Published: June 2023

An efficient compensation method and design for sizing the three phase four wire shunt Active Power Filter (APF) based on wavelet transformation is presented in this paper. The compensation currents injected by shunt active power filter are determined to eliminate harmonic currents of the non linear loads as well as to compensate reactive power and maintain the source currents as sinusoidal. In this paper Fast Fourier Transforms (FFTs) is used for APF to calculate reference compensation current. Proposed APF has the capability to operate in balanced, unbalanced and variable load conditions. The proposed auto tuned filter meet the IEEE – 519 harmonic current limits and other constraints like power factor improvement and reactive power compensation. The proposed methodology is tested for different loads with good dynamic behavior of APF using wavelet controllers. The results obtained by simulations with MATLAB/Simulink shows that the proposed approach is very effective and simple for compensating harmonic currents generated by the nonlinear loads with an optimal size of the shunt active power filter.
Secure Dynamic Data Aggregation Routing Protocol for Wireless Sensor Networks
Authors: Mathur Bhawana
Published: June 2023

Routing in sensor networks is complicated due to several issues ranging from security to energy constraints of wireless sensor nodes. This distinguishes them from contemporary wireless ad hoc networks. Adversaries can launch DoS attacks by injecting false data reports via compromised nodes. Previously a Hill Climbing key dissemination filtering scheme was developed where each node disseminates its key to forwarding nodes and later transmits reports along with the key. The forwarding nodes validate the credibility of the reports based on the key obtained earlier. This approach assures stronger filtering capacity for nodes closer to data sources and achieves secure and reliable transmissions. Sensor nodes process capability, bandwidth and battery capacity is still scarce. It is necessary to save resources of sensor nodes with the purpose of prolonging network lifetime. In that regard we propose to use a dynamic data aggregation routing protocol, named DABDR along with the earlier filtering scheme for secure and dynamic transmissions in Wireless Sensor Networks.
Analysis and Design of Multicarrier Modulation Protocols in Cognitive Radios
Authors: Ravinder Kumar P. , Narayandas Vikram , Leelavathi P.
Published: June 2023

In this paper new techniques that deal with the issue of spectrum management have to be developed. It is possible to increase the spectral efficiency by either shifting carrier frequencies closer together or altering the roll off factor .The second approach does not seems to be efficient than the first, due to increase in bandwidth, which leads to increase in noise, interference, multipath fading The first concept is able to control the Guard band dynamically. Possibilities to reduce the guard band between successive channels dynamically are to beinvestigated, thus improving spectral efficiency. This can be done efficiently by Multicarrier modulation Multicarrier modulation which has an ability to increase in the data rates and simultaneously we can decrease in the interference due to multipath fading channels. Multicarrier modulation schemes are of two types namely, Non-contiguous orthogonal frequency division multiplexing and Non-contiguous non orthogonal frequency division multiplexing. The proposed paper aims to investigate the various features of Multicarrier, Multipath system to address the challenges in wireless communications and provide a solution for the optimum utilization of the resources.
Artificial Intelligence and Expert Systems: Its Emerging Interaction and Importance in Information Science – An overview
Authors: Prantosh Kr. Pau C. , Senthamarai R. , Shivraj K. S. , Chatterjee D. , Karn B.
Published: June 2023

This paper mainly deals with overview of artificial intelligence and Expert System. Artificial Intelligence primarily responsible for developing computer programs which are able to read, speak, and understand as like man. Other hand Expert System refers to expert System needed for advance decision and intelligence robotics application. Expert System can communicate with user in their natural language and processes the capacity to catch to the individual desire. Here in this paper role of Artificial Intelligence and Expert System elaborate briefly, where as application of these computer techniques get most priority. We also discuss the need of Artificial Intelligence and emerging Expert System in the working and academic field of information Science.
Load Balancing in Cloud Computing System
Authors: Sharma Rashmi , Kumar Abhishek
Published: June 2023

The conception of Cloud computing has not only reshaped the field of distributed systems but also fundamentally changed how businesses potential extend today. Load balancing is a core and challenging issue in Cloud Computing. How to use Cloud computing resources efficiently and gain the maximum profits with efficient load balancing algorithm is one of the Cloud computing service providers’ ultimate goals. In this paper firstly a analysis of different Virtual Machine (VM) load balancing algorithms was done a new VM load balancing algorithm has been proposed and Implemented in Virtual Machine environment of cloud computing in order to achieve better response time.
Hybrid Method for Retinal Image Segmentation and Identifying True Vessels
Authors: Prabin A. , Veerappan J. , John Wiselin M. C. , Binu Sathiya S.
Published: June 2023

As digital imaging and computing power increasingly develop, so too does the potential to use these technologies in ophthalmology. Image processing, analysis and computer vision techniques are increasing in prominence in all fields of medical science, and are especially pertinent to modern ophthalmology, as it is heavily dependent on visually oriented signs. We describe a novel technique that utilizes the global information of the segmented vascular structure to correctly identify true vessels in a retinal image. The model segmented vascular structure as a vessel segment graph and transform the problem of identifying true vessels to that of finding an optimal forest in the graph. An objective function to score forests is designed based on directional information. Our proposed solution employs candidate generation and expert knowledge to prune the search space. Each vessel is tracked individually by repeatedly finding the next vessel point with a scoring function that considers the pixel intensity and orientation in the vicinity of the current point in the image. Bifurcations and crossovers are detected using some intensity profile. Tracking for the same vessel then continues along the most likely path. The importance of our proposed work disambiguate between vessels at bifurcations and crossovers, we need to figure out if linking a vessel segment to one vessel will lead to an adjacent vessel being wrongly identified .
Retinal Blood Vessels Segmentation Using the Curvlet Transform
Authors: John Wiselin M. C. , Prabin A.
Published: June 2023

Retinal image having very vital information. It plays important roles in finding of some diseases in early stages, such as diabetes, and cardiovascular disease. In this proposed system a new algorithm used to detect the blood vessels effectively from the retinal image. The initial image enhancement is carried out by using Adaptive Histogram Equalization, followed by the curvelet Transforms are applied to the equalized image and the curvelet coefficients are obtained. The modifications to the Curvelet transform coefficients are carried out by suppressing all the coefficients of one band. This combined effect of the equalization and the Curvelet Transforms provides a better enhancement to the image. This enhanced image is used for the extraction of blood vessels. Afterward, eliminate the ridges not belonging to the vessels tree by morphological operators by reconstruction while trying to preserve the thin vessels unchanged. In order to increase the efficiency of the morphological operators by reconstruction, they were applied using multi-structure elements and local adaptive thresholding method along with connected components analysis (CCA) indicates the remained ridges belonging to vessels.
Approaching Vehicle Identification for the Visually Challenged
Authors: John Wiselin M. C. , Aravind C. V. , Rajparthiban R. , Kumar Uthaya
Published: June 2023

The paper presents the development of a novel information system for the visually impaired. The objective of the developed system is to enable the visually impaired people to get information of the incoming source of vehicle without any other physical help and to travel by vehicle such as buses to their desired destinations. This device works in such a way, where the visually impaired people are able to detect the arrival of a particular vehicle as their only source of transportation. The system incorporated is designed to be simple and portable hand held for the convenient usage. A simple wireless communication system with frequency modulation is employed for the signal transmission. The microcontroller in the system is used to generate the automatic signal that is transmitted through the FM transmitter. The signal picked up by a single chip FM receiver and announces voice message of the coming vehicle information using the voice record and playback device. In this way the visually impaired will manage to catch the vehicle by their own ability. However the model developed aims for identify only one vehicle but can be extended to any number of systems. The FM carrier frequency used for communication between the transmitter and receiver is 89.3MHz. The maximum transmission distance for transceivers signal is roughly about 0.5 to 1 meter.
Vehicle Braking Performance Improvement By SVM Based Road Surface Detection
Authors: Anbalagan T. , Gowrishankar C. , Shanmugam A.
Published: June 2023

Advance information about the road surface a vehicle is going to encounter can improve the performance of Antilock Braking System (ABS). For e.g. the initial slip cycles caused by the ABS could be avoided, if it is already known that the vehicle is on a surface having a low coefficient of friction (μ). In this paper, an algorithm is developed that detects different road surfaces using streaming video acquired from a camera mounted on the hood of the vehicle. The road surfaces detected here are asphalt road, cement road, sandy road, rough asphalt road (asphalt road which is deteriorating), grassy road and rough road. The value of coefficient of friction (μ) is also given out with the detected surfaces to obtain additional information about the road surfaces. Split μ (a road having different μ conditions on the left and right side of the vehicle) and μ jump (different μ conditions on the front and rear of the vehicle) are also pre detected. One method was not sufficient to achieve the goals of this algorithm. Here several simple techniques like the Canny edge algorithm, intensity histogram, contours, Hough transform and image segmentation were employed and compared with the Support Vector Machine (SVM). To prevent misdetections, the road surface detection during high motion blur is prohibited.
Optimization of Location Management Cost by Mobility Pattern
Authors: Thabasu Kannan S. , Shakeela N.
Published: June 2023

As per one survey, every mobile user possesses two mobiles in the ratio of 1:2. Out of this 75% of the mobiles belongs to the category of smart phones. In this situation, the technology also fulfills the requirements for future advanced usage. Now-a-days mobile plays a pivotal role for connecting the global matters with in the hold of our palm. The main factor which influences the availability of mobile system in the market is speed and portability. Hence the speedy retrieval is the tharaga manthra pronounced in the minds of mobile users. In the instant world, time is the major constraint for the user who relies on the performance. If the system contains intelligence the reliability level of the system also increases, otherwise it will go down even to the point of zero.In this paper, we proposed a new mobility management schemes based on mobility pattern to minimize the total cost and to balance the Location update and search Paging. The new system its main aim is to get the speedy retrieval by using mobility pattern. In the new system one mobility pattern is maintained in each and every visited cell. If the number of pattern is increased then the movement weight is reduced and the updation cost and seeking cost is also reduced. Here some cells in the network are designated as reporting cells, mobile terminals update their positions upon entering one of these reporting cells. Due to the popularity and robustness, Genetic algorithm is used to solve the reporting cells planning problem. The new system not only satisfies the requirements of the mobile environment but also fulfills the pervasive environment, because it integrates the concepts of mobile and intelligence. By use of this intelligence, the extraction of output and its level of accuracy are very high. Here intelligence is used to identify the shortest path. The main drawback here is same time taken for first call and maintain less time for subsequent calls only. The performance of the new system can be tested by generating random data sets for number of generations 500 and 1,000, the network size taken is 4X4. Here we have evaluated the performance of the new system by comparing with some existing systems like POFLA, UPBLA and MIPN. The performance can be measured by call-to-mobility ratio, locating time ratio, the update cost ratio, time-data routed ratio. Comparatively the new system is better than any other existing system we have mentioned.
Automatic Circular Blade Sharpening Machine
Authors: Hari Shankar Elango S. , Esakki Vigneswaran E.
Published: June 2023

The main purpose of this paper is to design and implement an Automatic circular blade sharpening machine using PIC16F877A and latest motor drivers .In this system we are having four outputs and two inputs. The four output devices are turntable motor, grinder motor, feed motor and a solenoid coil. And the two inputs are cycle start switch and home position sensor. This machine is designed to grind the blade in the shape of circular automatically which is designed for the beef flesh cutting application. The circular blade is to be mounted on the blade holder only by adjusting the center screw of the blade holder. Then we have to adjust the grinder motor position according to the diameter of the blade. By pressing the auto cycle start button after the completion of all the settings, the grinding cycle begins. After the grinding process the grinder motor will be settled down in its home position. And then the solenoid will be activated and it removes the burr with the help of turn table motor movement and thus the cycle will be completed.
Advanced Vehicle Tracking System Using ARM7
Authors: Kishore L. , Raja Arun
Published: June 2023

To Track the position of the vehicle by means of GPS device and automatically sending the data to the remote server webpage and display the current position of the device in the Google map to the authorities. In institution or in ATM cash filling vehicle, most of the time we need to monitor position or path vehicle whether it’s moving in correct direction or not. This system used the ARM7 controller. The real time vehicle tracking and monitoring system tracks the vehicle and displays the current location of the vehicle in the remote server using Google maps. It has the ability to communicate over the remote areas where user needs the current location of vehicle. It can provide Tele-monitoring system for inter-cities transportation vehicles such as taxis and buses. This system is integrated with GPS and GSM to provide features like Location information and Real time tracking using SMS.
NFC Enabled E-Services for Employees
Authors: Sowmya P. , Banu Priya N.
Published: June 2023

This project establish a easy shopping for the employees through their smart phones. Whenever they went shop they can pay the Bill through this mobile application. Also the employees in companies pay their transport charges through mobile phone with NFC technology. The application installed in the phone has been paired with the RASBERRY-PI Controller through BLUETOOTH. Already thriving within the telecommunications market, wireless technology is preparing to embrace computing on an even larger scale. Presently, most people encounter wireless local area networks (WLANs) in airport lounges and tech-savvy offices. Everywhere around the world, this new generation prefers the wireless technology for their work and also the technologies are growing by leaps and bound to carry out all the desires of the customers to fulfill their demands. Here we use that wireless technology into the on chip computer (raspberry PI). We are going to implement multiple applications in a single unit. From this we can learn how embedded units are flexible with real time applications. In our project we use two concepts. First one is E-vouchers for employees second one is a E-ticket system all are done with the help of Near field communication (Bluetooth) technology.