bluuebunny/crossref_metadata_2025 huggingface dataset:
Frameless neuronavigation with computer vision and real-time tracking for bedside external ventricular drain placement: a cadaveric study
Authors: Robertson Faith C. , Sha Raahil M. , Amich Jose M. , Essayed Walid Ibn , Lal Avinash , Lee Benjamin H. , Calvachi Prieto Paola , Tokuda Junichi , Weaver James C. , Kirollos Ramez W. , Chen Min Wei , Gormley William B.
Published: October 2021

OBJECTIVE

A major obstacle to improving bedside neurosurgical procedure safety and accuracy with image guidance technologies is the lack of a rapidly deployable, real-time registration and tracking system for a moving patient. This deficiency explains the persistence of freehand placement of external ventricular drains, which has an inherent risk of inaccurate positioning, multiple passes, tract hemorrhage, and injury to adjacent brain parenchyma. Here, the authors introduce and validate a novel image registration and real-time tracking system for frameless stereotactic neuronavigation and catheter placement in the nonimmobilized patient.

METHODS

Computer vision technology was used to develop an algorithm that performed near-continuous, automatic, and marker-less image registration. The program fuses a subject’s preprocedure CT scans to live 3D camera images (Snap-Surface), and patient movement is incorporated by artificial intelligence–driven recalibration (Real-Track). The surface registration error (SRE) and target registration error (TRE) were calculated for 5 cadaveric heads that underwent serial movements (fast and slow velocity roll, pitch, and yaw motions) and several test conditions, such as surgical draping with limited anatomical exposure and differential subject lighting. Six catheters were placed in each cadaveric head (30 total placements) with a simulated sterile technique. Postprocedure CT scans allowed comparison of planned and actual catheter positions for user error calculation.

RESULTS

Registration was successful for all 5 cadaveric specimens, with an overall mean (± standard deviation) SRE of 0.429 ± 0.108 mm for the catheter placements. Accuracy of TRE was maintained under 1.2 mm throughout specimen movements of low and high velocities of roll, pitch, and yaw, with the slowest recalibration time of 0.23 seconds. There were no statistically significant differences in SRE when the specimens were draped or fully undraped (p = 0.336). Performing registration in a bright versus a dimly lit environment had no statistically significant effect on SRE (p = 0.742 and 0.859, respectively). For the catheter placements, mean TRE was 0.862 ± 0.322 mm and mean user error (difference between target and actual catheter tip) was 1.674 ± 1.195 mm.

CONCLUSIONS

This computer vision–based registration system provided real-time tracking of cadaveric heads with a recalibration time of less than one-quarter of a second with submillimetric accuracy and enabled catheter placements with millimetric accuracy. Using this approach to guide bedside ventriculostomy could reduce complications, improve safety, and be extrapolated to other frameless stereotactic applications in awake, nonimmobilized patients.
Long-term surgical outcomes of intracranial epidermoid tumors: impact of extent of resection on recurrence and functional outcomes in 63 patients
Authors: Hasegawa Hirotaka , Vakharia Kunal , Carlstrom Lucas P. , Van Gompel Jamie J. , Driscoll Colin L. W. , Carlson Matthew L. , Meyer Fredric B. , Link Michael J.
Published: October 2021

OBJECTIVE

The authors’ objective was to reevaluate the role of microsurgery for epidermoid tumors by examining the associations between extent of resection (EOR), tumor control, and clinical outcomes.

METHODS

This was a retrospective study of patients with microsurgically treated intracranial epidermoid tumors. The recurrence-free and intervention-free rates were calculated using the Kaplan-Meier method. EOR was graded as gross-total resection (GTR) (total resection without residual on MRI), near-total resection (NTR) (a cyst lining was left in place), subtotal resection (STR) (> 90% resection), and partial resection (PR) (any other suboptimal resection) and used to stratify outcomes.

RESULTS

Sixty-three patients with mean clinical and radiological follow-up periods of 87.3 and 81.8 months, respectively, were included. Sixteen patients underwent second resections, and 5 underwent third resections. The rates of GTR/NTR, STR, and PR were 43%, 35%, and 22%, respectively, for the initial resections; 44%, 13%, and 44% for the second resections; and 40%, 0%, and 60% for the third resections (p < 0.001). The 5- and 10-year cumulative recurrence-free rates after initial resection were 64% and 32%, respectively. When stratified according to EOR, the 10-year recurrence-free rate after GTR/NTR was marginally better than that after STR (61% vs 35%, p = 0.130) and significantly better than that after PR (61% vs 0%, p < 0.001). The recurrence-free rates after initial microsurgery were marginally better than those after second surgery (p = 0.102) and third surgery (p = 0.065). The 5- and 10-year cumulative intervention-free rates after initial resection were 91% and 58%, respectively. When stratified according to EOR, the 10-year intervention-free rate after GTR/NTR was significantly better than that after STR (100% vs 51%, p = 0.022) and PR (100% vs 27%, p < 0.001). The 5-year intervention-free rate after initial surgery was marginally better than that after second surgery (52%, p = 0.088) and significantly better than that after third surgery (0%, p = 0.004). After initial, second, and third resections, permanent neurological complications were observed in 6 (10%), 1 (6%), and 1 (20%) patients, respectively. At the last follow-up visit, 82%, 23%, and 7% of patients were free from radiological recurrence after GTR/NTR, STR, and PR as the initial surgical procedure, respectively.

CONCLUSIONS

GTR/NTR seems to contribute to better disease control without significantly impairing functional status. Initial resection offers the best chance to achieve better EOR, leading to better disease control.
Identification of Sickle Cells in Erythrocytes Images Using Shape Descriptors
Authors: Yamini L. , Priyadharsini R. , Beulah A.
Published: October 2021

Sickle cell anemia is a blood disorder which is widespread across world with an estimate that about 30% of total population will be affected by the end of 2050. Especially in India, the frequency of sickle cell trait can reach up to 35%, thereby increasing attention over the topic for research. It is necessary to detect the disorder as much as it is for finding a cure to it. Therefore, a system that detect the sickle cells from the blood smear images or erythrocytes images is required. The affected cells change their shape from circular to sickle shape, due to the presence of typical hemoglobin called hemoglobin S. Nowadays, the elongated affected cells are identified using image processing techniques. The shape descriptors which are the vital features used to identify any shapes in an image. The contrast and brightness of blood smear images may not be consistent as the acquisition of these images depends on various factors like luminance and chrominance. To detect the sickle cells properly in the blood smear images, the histogram equalization technique is applied to improve the contrast of the image. The image is converted to binary in order to find the boundary of the cells in the image. In the binary image, each normal cell will have holes, Since the normal red blood cell have the shape of a doughnut that has been pressed in the middle slightly. The boundary of all the cells in the image is traced and the holes inside each cells are filled. Each cell is considered as a connected component for which the eccentricity is calculated. The eccentricity is the shape descriptor which is the ratio of the major axis and minor axis of the connected components. If the eccentricity is greater than threshold, the cells are identified as sickle cells.
Impact of Personality Traits on Interpersonal Dependency
Authors: Jainab Zareena S. , Krithika M.
Published: October 2021

Every person has a unique personality. A set of characteristics or qualities possessed by an individual is called as the personality traits. Interpersonal dependency refers to the amount of support that an individual gets from the other person and the level of it gets varied among the people. Those who have higher interpersonal dependency are labeled as low self- esteemed person. The present study is initiated to identify the traits possessed by an interpersonal dependent. An adapted questionnaire is used for the study. Totally the questionnaire consists of seventeen questions among which ten questions measured the variable personality traits and the remaining seven questions measured the variable interpersonal dependence. The data was collected from fifty employees working in corporate for the present study. Content and face validities are used to assess the validity. Inferences are drawn through the use of descriptive and inferential statistic.
Lane Detection and Tracking Algorithm Based on Curve Fitting Model
Authors: Rajakumar.R  , Pandian.R  , PremJacob.T
Published: October 2021

Lane Detection is the fundamental vehicle driving system and self-driving. The proposed concept is to employ the pixel difference in the expected lane and the road backdrop to detach the lane from the road, and then the Curve fitting model is made use of in the segregated lanes to locate the straight line in the image as the lane line. This paper offers a lane detection method based on the Sobel filter and Curve-fitting model for lane line tracking in different conditions. The main objective is to improve the accuracy of the Xi’an city database and the KITTI vision benchmark suite dataset. To achieve this HLS color space was performed which identifies the lane by adding pixel values.
Clinical Data Based Classification of Osteoporosis and Osteopenia Using Support Vector Machine
Authors: Ramesh.T  , Santhi.V
Published: October 2021

In the current world millions of people are suffering with bone diseases such as osteoporosis and osteopenia. The early detection of osteoporosis and osteopenia disease is very important as it helps people to be cautious and get treated on time. Hence research on early detection of osteoporosis and osteopenia disease has gained importance across the world. In this paper, analysis of suitable kernel for Support Vector Machine (SVM) focussing on the classification of osteoporosis and osteopenia disease has been carried out and presented. The kernel functions considered includes polynomial, linear, RBF and Gaussian to find the optimal one for the classification of osteoporosis and osteopenia disease with improved accuracy.
Decentralized Loan Management Application Using Smart Contracts on Block Chain
Authors: Arikumar K S  , Deepak Kumar A  , GowthamC  , SahayaBeniPrathiba
Published: October 2021

The most shocking events were was the recent discovery of the fraudulent activities in the Punjab National Bank. This is due to frequent systemic failures that detect human errors. Blockchain technology is the greatest solution for this issue. It is surprisingly common for the information settlement mechanism like SWIFT to be on a isolated ledger from the payment settlement mechanism. If the banks uses a ledger that stores information settlement distributed across all the participants, then the fraudulent user may reflect on all the available participants in the transactions, auditors and regulators. Our Paper is a Decentralised Loan Management Web Application (DApp) built on Ethereum blockchain which targets on preventing such fraudulent attacks on Loans sanctions by decentralising the processes. The security features authentication of the user identity, authentication of bank officials and multiple levels of verification of details are implemented using Public Key Infrastructure (PKI).
Evaluation of Existing Methods in Cervical Cancer Detection and Related Issues
Authors: Saravanan.M.S  , Rajesh A.
Published: October 2021

In day-to-day life cancer is the severe disease to cure. This paper deals about the cervical cancer and its related issues. The cervical cancer is a preventable disease, but it is one of the second most leading causes of cancer deaths in women. There are two main types of cervical cancer namely squamous cell carcinoma, adenocarcinoma. The major stages of cervical cancer will be dealt by evaluating with clear diagrams and also the major risk factors of cervical cancer are discussed. Finally the various treatment methods of cervical cancer are used to analyze and present the related issues.
Survey on Food Recognition System Using Machine Learning
Authors: GaneshGaurav D. , Parthasarathy G  , Dhananja  , Chiranthan YC  , KomalBharti
Published: October 2021

Food recognition system is essential framework in modern world, the motivations behind this recognition systems are assessing calorie and nutrients of food varieties and show the formula of the food. As all the processing on picture recognition is performed on a personal digital assistant (PDA), the framework doesn’t have to send pictures to a server and runs solution to a normal advanced mobile phone in a constant one. Spontaneous image-based food acknowledgment is an isolated inspiring task. Conventional picture analysis preparing methodologies have fallen off with low order classification prediction in the past, while deep learning methodologies permitted the recognizable proof of food things. To recognize food items, a client ought to need to draw bounding boxes by contacting the screen first, and afterward the framework starts food thing acknowledgment inside the showed bounding boxes. Moreover, the framework assesses the direction of food areas with the higher SVM (Support Vector System) yield score is expected upon to be acquired, show it as an arrow on the screen to request that a client move an advanced mobile phone camera. This acknowledgment cycle is performed on and on about once each second. We will carry out this task as an Android advanced mobile phone application to utilize numerous CPU cores effectively for modern real-time food recognition system.
Intelligent Vehicle Scrutiny to Eradicate Malversation
Authors: Suthanthara Raja PushpaJ  , Valarmathi K
Published: October 2021

In this modern world, there is an increasing crisis in monitoring the safety measures in the traffic field. Though there are many methods and techniques developed to find a solution to this particular problem, there is an empty or faulty field which each and every one tried to cover at each of their findings. One such problem is the malversation. This plays the major role in the traffic field through which the public who don’t have enough driving experience, alcohol consumer and those who park their vehicle in no parking area which lead to the congestion and many other facts have been roaming freely without any fear causing disturbance to the public. Even the cops who are responsible for the safety of public and to monitor the traffic with full dedication they allow the criminals to flew away by getting bribes. So, in order to terminate this system, there is an urgent need to find an appropriate solution in this fields. Our paper has been proposed with this problem statement as their main goal and developed a system in Internet of things.
Facilitation of Smart car Assistant System Using IoT
Authors: Nithya M. , SoundaryaLahari M.V.S. , Sai Sumitra J.C.E , Lalitha V.
Published: October 2021

Human protection in cars has been the primary area of study in the past few years. A significant issue for groups of researchers and industrialists around the world is -crash-. Car users often overcome problems related to trapping in a car of car causing suffocation kind of problems, where immediate communication is very much essential. Similarly a problem often arises when it comes to the collision of vehicles from back side. This paper proposes a smart car personal assistant system that provides an efficient solution for the problems like collision detection, being trapped inside a car and also provides a necessary support by using IoT and Creation of an android application consisting of critical characteristics such as contact in the above potential problems, renewal of PUC, periodic expenditure of vehicle-related items, regular check-ups and maintenance, car database and user information of the car, which will minimize user efforts.
Detection of Malicious Web Applications Using Machine Learning Algorithm
Authors: Sivagurunathan M  , SivakumarP  , Somasundaram. S K
Published: October 2021

The emerging development of the internet everyone using web applications for their products or services. The large number of web applications created day by day. Since the demand is very high for web development, developers are creating an application not in a secure manner and hosting without the testing process. Web clients regularly store and oversee basic data that draws in cybercriminals who exploitation the web weaknesses for their benefits. Pernicious website pages are coming to pass undermining issue over the web on account of the reputation and their capacity to impact. Recognizing and examining them is exorbitant due to their characteristics and complexities. The complexities of assaults are expanding step by step in light of the fact that the assailants are utilizing mixed methodologies of different existing assaulting procedures. Using this opportunityattacker used their malicious script in their web application. Attacker, theft user’s data, or redirect to malicious websites. In this project, we are proposing detection methods, to prevent the users from approaching the malicious web application. Using a Machine learning algorithm, extract the feature of the web application that is URL features and static features of the network. From the trained model of date set, using the Random forest algorithm detect the malicious web application.
Attaining Cloud Security Solution Over Machine Learning Techniques
Authors: Muthulakshmi K. , Valarmathi K.
Published: October 2021

Cloud computing provides physical and logical computation resource on demand for the set of service. Cloud environment reduce the infrastructure cost and easy to use without any extra burden. Cloud storage an access raised the several security issues like data privacy, access control, authentication, virtual machine security, web security etc., In one side hackers, breaches, cloud security issues and threats get expanded. But in another side many technologies are keep increased to secure cloud data. Technology may be cryptographic technique, anonymization technique, machine learning technique etc., In this paper we analyse cloud computing basics, models, machine learning technique and some security solution through machine learning technique such as support vector machine (SVM), K-Nearest Neighbour (KNN), Decision tree and Naïve Bayes classifier technique.
Product Review Based on Machine Learning Algorithms
Authors: Elangovan D. , Subedha V.
Published: October 2021

The purchase of products or administrations through an electronic trade called web based shopping over internet using a web browser. Online Product surveys are significant for up and coming purchasers in helping them decide. To this end, distinctive sentiment mining systems have been proposed, where making a decision about a survey sentence’s direction (e.g., positive or negative) is one of their key difficulties. As of late, Machine learning has risen as powerful methods for taking care of assumption order issues. An AI model inherently learns a helpful portrayal consequently without human endeavors. In any case, we propose a regulated AI structure for item audit conclusion arrangement which utilizes pervasively accessible evaluations as powerless supervision signals. To assess the proposed system, we build a dataset containing 2, 00,000 pitifully named survey sentences and 15000 marked audit sentences from Amazon. Trial results show the more exactness contrasted with past one.
Detection of Body Movement for Comatose Patient Using IoT
Authors: Nisha.Y  , Valarmathi K.
Published: October 2021

Coma is the state of anesthetized or unconscious state where the patient doesn’t respond to the actions or any activities. Since the patients are in unconscious state the patients at tender or the doctors don’t have time to observe the patient activities continuously. In order to overcome this problem an IoT based system is designed to monitor the body movements and the actions of the coma patient using various sensors. The equipment has been planned that utilizes Arduino controller board. In addition with the Arduino board various sensors have been associated through the controller board interface. The sensors values will be transferred to the cloud server. The movement of eye ball retina and motion of the body detected by the wearable motion sensors state are monitored. By using the sensors it is helpful for the doctor and the specialist about the well-being condition of the patients and continuously monitoring their physical condition. The challenging task is focused on the limitation of the existing techniques are discussed.
Deciding Bank Client’s Credit Limit and Home Loan Using Machine Learning
Authors: Ganga A  , Vijayalakshmi S  , Kalpana R A
Published: October 2021

Bank customer’s profile helps the bankers to whom the banking facilities may be given and what credit limit to produce. The profile includes both demographic and transaction data. By the best technique, the exactness might be accomplished and furthermore the banks can get higher gainfulness by fulfilling the purchasers. The various data analytic techniques are used for the credit limit prediction and the loan amount for that credit limit is also determined. The regression algorithms are employed for improving high accuracy in predicting the credit card limit.
Underwater Image Enhancement and Fish Detection
Authors: Nelson I. , Annadurai C. , Venkatasubramani Shriraam , Yogesh.I  , Shrinivas Badri.S
Published: October 2021

The oceans cover over 70 percent of the surface of the earth. Underwater images are vital to explore these oceans, but they are impacted by quality degradation. The quality degradation occurs mainly due to absorption and scattering of light in water. Degradation in underwater images is caused by problems like low contrast, haziness, colour deviation and blurring. This in turn has made it difficult to explore, study and unravel the mysteries of the oceans. Good quality images are vital to study and research about existing marine ecosystems and also to discover numerous undiscovered species present underwater. There are various dehazing, restoration and enhancement techniques available to improve this scenario. We in this paper look to study and analyse the idea of building a system to combine some of the dehazing, restoration and enhancement algorithms available to obtain quality enhanced images. Further the system would also perform fish detection to obtain better accuracy using the enhanced images. We go about studying and analysing the image outputs obtained from individual algorithms and combination of algorithms and look to open up a possibility of further study of combining restoration and enhancement algorithms to improve the quality of images. We have proposed the idea of adding fish detection to this system as there has always been a difficulty of identifying and differentiating fish from other objects and marine life in underwater images. Doing so would help in studying about and even discovering new species. The fish detection models suffer from the image quality degradation problems and it impacts the accuracy. Hence, we have brought about the idea to enhance images to improve the efficiency and accuracy of fish detection. Therefore, we propose a system which would have various dehazing, restoration and enhancement algorithms working in tandem to produce an enhanced version of the input image. Next, the enhanced image is used to improve the accuracy of fish detection. Our review of combining restoration algorithms with enhancement algorithms and analysing the improvement in accuracy of fish detection by enhancing would provide researchers to further look into the opportunities available for improvement.
An Analysis on Monitoring of Healthcare by Means of Internet of Things
Authors: Sathish N  , Valarmathi K  , Elangovan G
Published: October 2021

The convergence of computer science and electronics domain has resulted in the Internet of Things, which is perhaps the most striking innovative outcome (IOT). The Internet of Things (IoT) is a innovative technology with the aim of rapid evolvement by means of numerous new advancements in clinical and wellness areas. Over the last few years, the impact of IOT in medical services has significantly increased. Internet of Things (IoT) based Health-related wearable devices are posing new challenges by incorporating creative innovation and assets. In/out understanding’s wellbeing status can be observed intermittently and routinely using wellness wearable gadgets.The Internet of Things (IoT) will profoundly help patient investigation and testing methods due to tiny internet protocol based sensors in a remote location that can be mounted on the patient’s body. Currently there are devices with seven billion in value, with expertise predicting the number will rise to ten billion by 2020 and 22 hundred million by 2025. This paper aims to examine and comprehend the utilization of Internet of Things in redesigned healthcare services, as well as how outstanding medical care can be obtained with ease. To summarise, the discussion has been projected on IoT capabilities on remote and detection frameworks and on the relevances utilized on effective medical care applications.
Implementation of IoT in Workplace Monitoring and Safety Systems
Authors: Annadurai C. , Nelson I. , Ranald Nivethan X.N. , Vinod Suraj , Senthil Kumar M.
Published: October 2021

The continuous and rapid development in facilities in the workplace eventually calls for safety of the workplace premises as well as improved monitoring system. For instance, an intruder alert will be sent even if a client enters the premises. To eradicate this issue, an alert notification has to be sent only when required i.e., during an intruder detection or mishap detection. The data is collected by Raspberry Pi using the sensors interfaced to it. By employing the usage of IoT, data received from the sensors are sent to an IoT platform from where the information is passed as a notification through an email. The detected face from the video recorded by PiCam is sent to a local server using socket programming and the Face recognition is performed in the local server using Haar cascade and LBPH algorithm in Open CV. In case of an intruder detection, an e-mail notification is sent to the user. Similarly, when an accident or disaster is detected such as a fire accident or air pollution, an alert notification is sent to the user through an e-mail.
IoT Based Smart Energy Meter System Using Machine Learning
Authors: Nelson I. , Annadurai. C  , Ramya. E  , Shivani. R  , Mathusathana. V
Published: October 2021

India is the world’s third largest producer and third largest consumer of electricity [1]. The per person energy consumption in India in 2019 is 1181 kWh. With increasing demand and value for energy, it has become tedious to keep track of consumption of energy units. Smart Meters can override these difficulties by providing a more appropriate solution which includes accurate billing, better information on energy consumption thus leading to better utilization. These Smart energy meters are beneficial to both the consumer and the supplier. They provide a more efficient solution in determining tariffs for the latter. Internet of Things is an emerging technology and IoT based devices have revolutionized the field of electronics and IT. The proposed project is an Iot Based Smart Energy meter system developed to efficiently manage the energy consumption in households by avoiding wastage, to provide accurate information to small scale users and to avoid manual meter reading and automate bill data entry process.
Enhancement of Routing Protocols for Mobile Adhoc Network
Authors: Rajakumar.R  , PandianR  , PremJacob.T  , Pravin.A  , Indumathi.P
Published: October 2021

The primaryaim of an ad-hoc network routing protocol is accurate and efficient route creation between node pairs so that messages may be delivered promptly. Route creation need to be done with reduced overhead and bandwidth. This paper presents a scheme to reduce bandwidth and power by the hibernation of nodes for a limited time. The effect of our proposal is then studied by simulation under various conditions and the analysis of the simulation results is done to comprehend the working of our protocol in various areas and how it fares in an application specific scenario.
FPGA Implementation of Protected Compact AES S–Box Using CQCG for Embedded Applications
Authors: Sornalatha R. , Janakiraman N. , Balamurugan K. , Kumar Sivaraman Arun , Vincent Rajiv , Muralidhar A.
Published: October 2021

In this work, we obtain an area proficient composite field arithmetic Advanced Encryption Standard (AES) Substitution (S) byte and its inverse logic design. The size of this design is calculated by the number of gates used for hardware implementation. Most of the existing AES Substitution box hardware implementation uses separate Substitution byte and its inverse hardware structures. But we implement the both in the same module and a control signal is used to select the substitution byte for encryption operation and its inverse for the decryption operation. By comparing the gate utilization of the previous AES S–Box implementation, we reduced the gate utilization up to 5% that is we take only 78 EX-OR gates and 36 AND gates for implementing the both Substitution byte and its inverse. While implementing an AES algorithm in circuitry or programming, it is liable to be detected by hackers using any one of the side channel attacks. Data to be added with a random bit sequence to prevent from the above mentioned side channel attacks.
Proficient Mining of Informative Gene from Microarray Gene Expression Dataset Using Machine Intelligence
Authors: Ravindran Priya , Jayanthi S. , Kumar Sivaraman Arun , Dhanalakshmi R  , Muralidhar A. , Vincent Rajiv
Published: October 2021

The quick improvement of DNA microarray innovation empowers analysts to quantify the expression levels of thousands of genomic data and permits scientists effortlessly pick up and understanding the mind-boggling prediction in tumors based on genomic expression levels. The application in malignancy has been demonstrated and extraordinary achievement has been performed in both conclusion and clarification using the neurotic methodologies. In many cases, DNA microarray information about gene contains a large number of qualities and the majority of them are turned out to be uninformative and excess. In the interim, little size of tests of microarray information undermines the determination precision of factual models. In this way, choosing profoundly discriminative qualities from crude quality genetic expression can enhance the execution of genetic prediction and chopped down the cost of medicinal analysis. Pearson Correlation based Feature Selection strategy with machine learning methodologies is effective to locate a conspicuous arrangement of components which can be utilized to anticipate and idealize the blend of quality to analyze the disease. As conflicting to the customary cross approval, filter one cross approval technique is connected for the analyses. As needs be, the proposed blend between the PCBFS and Machine Learning methodology is an effective apparatus for disease grouping and can be actualized as a genuine clinical supportive system.
Investigation and Suppression of RF Leakage Power in Front End Wireless Devices
Authors: Kanchana Devi A  , Bhuvaneswari B
Published: October 2021

In this modern Communication Wireless System, Frequency Division Duplex (FDD) is mostly used. Duplex is a device to separate Transmitter and Receiver signals. Transmitter or Power leakage causes from limited isolation performance of the duplexer. Various Techniques of Modulation using Orthogonal Frequency Division Multiplexing (OFDM) provided better solution to cancel this leakage. The OFDM provides high spectral efficiency, lower multi-path distortion and to eliminate inter symbol interference (ISI). Fast Fourier Transform implemented modulation and demodulation functions more efficiently. Using simulation result of the various parameters are analysed. In addition, Comparison of the table between Bit rate error value, Signal strength throughput, Power consumption and Mean square error values obtained in the OFDM systems.
Hand Movement Based Message Transmission and Body Physical Parameters Remote Monitoring Device for Disabled People
Authors: Kalaiyarasi D , Shruthi. V  , VishnuPraba.A  , Vanaja.S
Published: October 2021

The main focus of the proposed model is to manifest a system that is reliable and also effective interms of communication between Disabled/paralyzed people with the caretaker. When it comes to looking after the disabled or paralytic people who are in large numbers such as in old age homes, Non-Governmental Organizations, and hospitals, it is considerably difficult to monitor the patients based on their needs immediately. To overcome this difficulty a simple yet effective module is developed to establish the communication between the patient (Transmitter) and caretaker (receiver) by mounting a device on the hand of the patient so that by simple movements made using the hand aspecific message is communicated to the device which is in a form of a board consisting of the LCD screen and voice module to indicate the message and the board is held by the caretaker separately. The transmission mode is wireless and the range is about 10 meters. The physical parameters of the patient’s body are measured and monitored remotely. When there is any abnormal pattern in the parameters such as pulse rate and temperature it is indicated to the caretaker immediately.
Radio Resource Allocation and Mobility Accessment of 5G Wireless Network Using Adaptive Q-LEACH Routing Protocol
Authors: Premi.A  , Rajakumar.S
Published: October 2021

The implementation and operation of a Fifth Generation (5G) network aims to achieve a maximum speed, low potential, improved flexibility, and a change in requirements and technologies from service-oriented to user-oriented. The users need resource allocation and management that is effective. Established networks’ closed infrastructure and ossified services result in particularly in wireless networks, inefficient resource allocation and underutilized network resources. On the basis the standard of a service provider’s utility benefit then customer gratification, various allocation strategies are suggested. Wireless system based 5G another research area aimed at supply distribution and 5G access links is network. In this project, radio resource allocation and mobility assessment of 5G wireless network LEACH routing protocol is implemented. In terms of wireless networks, various architectural integrations of other wireless technologies such as 5G, LTE, Wi-MAX, and so on are highlighted. Furthermore, the project focuses on resource allocation approaches and strategies for cellular networks, as well as comprehensive criteria for future 5G networks
An Extended Mondrian Algorithm – XMondrian to Protect Identity Disclosure
Authors: Padmaja R. , Santhi V.
Published: October 2021

In recent days, Privacy Preserving Data Publishing (PPDP) is considered as vital research area due to rapid increasing rate of data being published in the Internet day by day. Many Organizations often need to publish their data in internet for research and analysis purpose, but there is no guarantee that those data would be used only for ethical purposes. Hence data anonymization comes into picture and play a vital role in preventing identity disclosure, also it restricts the amount of data that can be seen or used by the external users. It is an extensively used PPDP technique among data encryption, data anonymization and data perturbation methods. Mondrian is considered as one such data anonymization technique that has outperformed compare to many anonymization algorithms, because of its fast and scalable nature. However, the algorithm insists to encode the categorical values into numerical values and decode it, to generalize the data. To overcome this problem, a new extended version of Mondrian algorithm is proposed, and it is called XMondrian algorithm. The proposed algorithm can handle both numerical and categorical attributes without encoding or decoding the categorical values.The effectiveness of the proposed algorithm has been analysed through experimental study and observed that the proposed XMondrian algorithm outshine the existing Mondrian algorithm in terms of anonymization time and Cavg. Cavg is one of the metric used to quantify the utility of data.
Factual Question Generation System Using Pro Semantic Ranker
Authors: Dafni Rose J , Sakthi U , Ajithkumar S S
Published: October 2021

In today’s internet world the amount of materials available to learn and gain knowledge is immense in numbers, which has given access to a lot of people to gain knowledge easily. Is it possible to find out if someone has read this sentence? To arrive at a conclusion of whether or not someone has read something, we can ask them to summarize its contents or question them about it. We can start with basic questions that deal with the title or the abstract, and progress to more challenging questions. A good example of this process would be a primary school teacher questioning his or her students on the basics of what they are reading to make sure that they are learning. It is a time-consuming process to create the basic questions and reading assessments that are commonly used, and can be quite taxing on the educator. This paper focuses on automating that time-intensive process. To be precise, this paper deals with the problem of generation of the factual questions in an automated manner from stand-alone texts.
A Survey on HetNet to Enhance QoS in 5G Network Using Various Techniques
Authors: Lydia Sharon Rose G  , Ameelia Roseline A
Published: October 2021

HetNet (Heterogeneous Network) has been suggested for next age group wireless systems to meet the exceptional difficulties of advanced data rates. The specifications for various levels of QoS (Quality of Service) from various kinds of wireless requests and service areas are met. In this HetNet in to improve the QoSand SINR (Signal to Interference plus Noise Ratio), many techniques have been performed to provide satisfactory outcomes. This paper gives a comparative survey on the QoS and various techniques used, which are used to enhance QoS.
5G Wireless/Wired Convergence of UFMC Based Modulation for Intensity Modulation Direct Detection
Authors: Keerthivasan K  , Shibu S
Published: October 2021

Faster data speeds, shorter end-to-end latencies, improved end-user service efficiency, and a wider range of multi-media applications are expected with the new 5G wireless services. The dramatic increase in the number of base stations required to meet these criteria, which undermines the low-cost constraints imposed by operators, demonstrates the need for a paradigm shift in modern network architecture. Alternative formats will be required for next-generation architectures, where simplicity is the primary goal. The number of connections is expected to increase rapidly, breaking the inherent complexity of traditional coherent solutions and lowering the resulting cost percentage. A novel implementation model is used to migrate complex-nature modulation structures in a highly efficient and cost-effective manner. Theoretical work to analyses modulations’ behavior over a wired/fiber setup and wireless mode is also provided. The state-of-the-art computational complexity, simplicity, and ease of execution while maintaining efficiency throughput and bit error rate.
Study of Microstrip Dual-Band Band Pass Filter
Authors: Anciline V  , Maheswari S
Published: October 2021

The main component widely used in wireless communication system is dual-band band pass filter. This band pass filter is intended in many ways and some are microstrip, waveguide, etc. The dual-band will works in two different frequency ranges which will provide a huge application. This paper compares different microstrip dual-band band pass filter based on the techniques, insertion loss, frequency, etc.
Smart Security System Using IoT, Face Recognition and Processor to Processor Communication
Authors: Indhuja G  , Aashika V  , Anusha K  , Dhivya S  , Meha Soman S
Published: October 2021

In the present world the security of the home, banks, shops, etc., are the prime concerns. The traditional security such as Closed-Circuit Television (CCTV) cameras are very easy to break and lead to theft. And moreover, the installation cost of the security systems is costlier. To overcome these problems, we are presenting Internet of Things (IoT) based solution where we can setup a smart security system. In this paper, we are proposing the system with the help of face detection and face recognition algorithms to secure our home which gives us the facility of entire surveillance of our buildings remotely and take appropriate action if anything goes wrong. The Camera Serial Interface (CSI) is attached to the Raspberry PI which detects presence of person using Face detection and recognition algorithms. The multiple Raspberry PIs attached in different areas of our buildings are connected to the main Raspberry PI which acts as hub module. If the person is identified as unknown, the information is sent to Hub module which in turn sends the alert message and live video streaming to the user using an app which we developed.
Role of Digital Marketing Data Analytics in Film Industry: Telugu Cinema into Pan India Magnum Opus
Authors: Juvvigunta Janardhan , Surender Dhanunjay Gondi , Kumar Adesh , Kumar Padhy Manoj , Kumar Abhishek , Singh Pranjal
Published: October 2021

The Indian film industry is at average growth rate of 11.5% year-on-year basis. After the Hindi film industry, regional cinema like the Telugu industry (popularly known as Tollywood) is the next big industry in the country in terms of both quantitative and qualitative values (Neway, 2020). Despite having limitations of language, nativity audience, market size, the Telugu film industry has emerged as synonyms for magnum opus with the help of digital marketing approaches in the 21st Century. S.S. Rajamouli’s visually spectacular, Baahubali franchise garner incredible national appeal and emerged as the biggest box-office opener in the country. With INR 600 crore gross worldwide, Bahubali: The Beginning not only became a benchmark for technical and aesthetic values but also became a well-studied case for its marketing approaches which changed the entire style of film promotions in the digital era. Similar kind of strategy has been followed by Syraa and Saaho in the Telugu film industry. At this juncture, the researcher aims to study the film audience pulling marketing strategies that applied particularly in all three stages (pre, post & production stages) of film production in Telugu Cinema. Purposively the researcher selected Syraa and Saaho as samples to study the objectives of this research work and adopted the content analysis to interpret the secondary data to present the research findings.
Relationship Between Brain Volumes and Objective Balance and Gait Measures in Parkinson’s Disease
Authors: Ragothaman Anjanibhargavi , Miranda-Dominguez Oscar , Brumbach Barbara H. , Giritharan Andrew , Fair Damien A. , Nutt John G. , Mancini Martina , Horak Fay B.
Published: October 2021

Background: Instrumented measures of balance and gait measure more specific balance and gait impairments than clinical rating scales. No prior studies have used objective balance/gait measures to examine associations with ventricular and brain volumes in people with Parkinson’s disease (PD). Objective: To test the hypothesis that larger ventricular and smaller cortical and subcortical volumes are associated with impaired balance and gait in people with PD. Methods: Regional volumes from structural brain images were included from 96 PD and 50 control subjects. Wearable inertial sensors quantified gait, anticipatory postural adjustments prior to step initiation (APAs), postural responses to a manual push, and standing postural sway on a foam surface. Multiple linear regression models assessed the relationship between brain volumes and balance/gait and their interactions in PD and controls, controlling for sex, age and corrected for multiple comparisons. Results: Smaller brainstem and subcortical gray matter volumes were associated with larger sway area in people with PD, but not healthy controls. In contrast, larger ventricle volume was associated with smaller APAs in healthy controls, but not in people with PD. A sub-analysis in PD showed significant interactions between freezers and non-freezers, in several subcortical areas with stride time variability, gait speed and step initiation. Conclusion: Our models indicate that smaller subcortical and brainstem volumes may be indicators of standing balance dysfunction in people with PD whereas enlarged ventricles may be related to step initiation difficulties in healthy aging. Also, multiple subcortical region atrophy may be associated with freezing of gait in PD.
Formations of bimolecular barbituric acid complexes through hydrogen bonding interactions: DFT analyses of structural and electronic features
Authors: Hajali Narjes , Taghva Manesh Afshin , Seif Ahmad
Published: October 2021

Formations of bimolecular barbituric acid (BA) complexes through hydrogen-bonding (HB) interactions were investigated in this work. BA has been known as a starting compound of pharmaceutical compounds developments, in which the molecular and atomic features of parent BA in homo-paring with another BA molecule were investigated here. The models were optimized to reach the stabilized structures and their properties were evaluated at the molecular and atomic scales. Density functional theory (DFT) calculations were performed to provide required information for achieving the goal of this work. Six dimer models were obtained finally according to examining all possible starting dimers configurations for involving in optimization calculations. N-H . . . O and C-H . . . O interactions were also involved in dimers formations besides participation of the X-center of parent BA in interaction. Molecular and atomic scales features were evaluated for characterizing the dimers formations. As a consequence, several configurations of BA dimers were obtained showing the importance of performing such structural analyses for developing further compounds from BA.