scholarly journals Robust Watermarking Technique for Sharing Family Photos on Social Media using Aadhar Number and DCT

2020 ◽  
Vol 9 (3) ◽  
pp. 381-387
Keyword(s):  
Personal Information ◽  
Smart Phone ◽  
Routine Activity ◽  
Experimental Result ◽  
Legal Issue ◽  
Multimedia Content ◽  
Daily Routine ◽  
Multimedia Contents ◽  
The Mind ◽  
Text Images

The mind setup of persons has been changed in today’s environment due to the easily available of internet and smart phone on very low-price cost. Smart phone and internet are two main resources which are being used by persons most of the time in his/her daily routine specially in lockdown due to COVID-19. In this lockdown, persons are doing some creative activity, making fun, etc and recording all his/her this personal information in the form of multimedia contents like text, images, audio and video. This created multimedia content is shared by persons frequently on globe through internet in the daily routine life and some other persons are watching this daily routine activity and making huge business with these data by sometimes with original content or sometimes with modified content without concerns/information/permission of the originator. In this process if everything is going in right way then no issues but if something going wrong then require legal issues and for this, we need to protect our data legally through some methodology. So this paper proposed secure watermarking technique for protecting multimedia content like images using Aadhar number and Discrete Cosine Transform (DCT) technique. In this proposed methodology individual can share the information’s with watermarked information which is hidden in shared images and on demand at the time of legal issue originator will show the actuality and its ownership. This paper explained details concepts of the embedding and reverse of embedding ( i.e. extracting) process for authentication of the images and its protection from the misuse or fraud. The experimental result of the proposed methodology is shown on different family photos shared on globe and found robust results.

Role of Vaitarana Basti in the management of Gridhrasi w.s.r. to Sciatica

2018 ◽  
Vol 3 (5) ◽  
Author(s):  
Dr. Suresh N. Hakkandi ◽  
Dr. Manjunath Akki ◽  
Dr. Bhavana KS
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Clinical Practice ◽  
Routine Activity ◽  
Daily Routine ◽  
Low Back ◽  
Common Condition ◽  
Locomotor System

Vata Vyadhi is one of the most prevailing health problems in our day today clinical practice, Gridhrasi is one among them. Gridhrasi is Shoola Pradhana Nanatmaja Vatavyadhi, affecting the locomotor system and disable from daily routine activity. Gridhrasi the name itself indicates the way of gait shown by the patient due to extreme pain i.e. like Gridhra or Vulture. Gridhrasi is a condition characterized by Ruk, Toda, Stambha, Spandana in Sphik Pradesha and radiates downwards to Kati, Prusta, Uru, Janu, Jangha and Pada. Gridhrasi can be compared with Sciatica. Pain is the chief cause of person to visit a doctor. Although low back pain is a common condition that affects as many as 80 to 90 percent of people during their lifetime. Gridhrasi can be cured by the help of Vaitarana Basti. Hence in the case study of male patient of age 30 yrs presenting with cardinal clinical sign and symptoms of Gridhrasi are Ruka, Toda and Muhu Spandana in the Sphika, Kati, Uru, Janu, Jangha and Pada in order and Sakthikshepanigraha that is restricted lifting of the leg.

scholarly journals The Role of Campus Data in Representing Depression Among College Students: Exploratory Research (Preprint)

2018 ◽  
Author(s):  
Guang Mei ◽  
Weisheng Xu ◽  
Li Li ◽  
Zhen Zhao ◽  
Hao Li ◽  
...  
Keyword(s):  
Academic Performance ◽  
Depressive Symptoms ◽  
Correlation Analysis ◽  
Personal Information ◽  
Influencing Factor ◽  
Depression Scale ◽  
Machine Learning Algorithms ◽  
Daily Routine ◽  
Exploratory Research ◽  
Online Questionnaire

BACKGROUND Depression is a predominant feature of many psychological problems leading to extreme behaviors and, in some cases, suicide. Campus information systems keep detailed and reliable student behavioral data; however, whether these data can reflect depression and we know the differences in behavior between depressive and nondepressive students are still research problems. OBJECTIVE The purpose of this paper is to investigate the behavioral patterns of depressed students by using multisource campus data and exploring the link between behavioral preferences and depressive symptoms. The campus data described in this paper include basic personal information, academic performance, poverty subsidy, consumption habit, daily routine, library behavior, and meal habit, totaling 121 features. METHODS To identify potentially depressive students, we developed an online questionnaire system based on a standard psychometric instrument, the Zung Self-Rating Depression Scale (SDS). To explore the differences in behavior of depressive and nondepressive students, the Mann-Whitney U test was applied. In order to investigate the behavioral features of different depressive symptoms, factor analysis was used to divide the questionnaire items into different symptom groups and then correlation analysis was employed to study the extrinsic characteristics of each depressive symptom. RESULTS The correlation between these factors and the features were computed. The results indicated that there were 25 features correlated with either 4 factors or SDS score. The statistical results indicated that depressive students were more likely to fail exams, have poor meal habits, have increased night activities and decreased morning activities, and engage less in social activities (eg, avoiding meal times with friends). Correlation analysis showed that the somatic factor 2 (F4) was negatively correlated with the number of library visits (<i>r</i>=–.179, <i>P</i>&lt;.001), and, compared with other factors, had the greatest impact on students’ daily schedule, eating and social habits. The biggest influencing factor to poor academic performance was cognitive factor F1, and its score was found to be significantly positively correlated with fail rate (<i>r</i>=.185, <i>P</i>=.02). CONCLUSIONS The results presented in this study indicate that campus data can reflect depression and its symptoms. By collecting a large amount of questionnaire data and combining machine learning algorithms, it is possible to realize an identification method of depression and depressive symptoms based on campus data.

scholarly journals The Role of Campus Data in Representing Depression Among College Students: Exploratory Research

10.2196/12503 ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. e12503 ◽  
Author(s):  
Guang Mei ◽  
Weisheng Xu ◽  
Li Li ◽  
Zhen Zhao ◽  
Hao Li ◽  
...  
Keyword(s):  
Academic Performance ◽  
Depressive Symptoms ◽  
Correlation Analysis ◽  
Personal Information ◽  
Influencing Factor ◽  
Depression Scale ◽  
Machine Learning Algorithms ◽  
Daily Routine ◽  
Exploratory Research ◽  
Online Questionnaire

Background Depression is a predominant feature of many psychological problems leading to extreme behaviors and, in some cases, suicide. Campus information systems keep detailed and reliable student behavioral data; however, whether these data can reflect depression and we know the differences in behavior between depressive and nondepressive students are still research problems. Objective The purpose of this paper is to investigate the behavioral patterns of depressed students by using multisource campus data and exploring the link between behavioral preferences and depressive symptoms. The campus data described in this paper include basic personal information, academic performance, poverty subsidy, consumption habit, daily routine, library behavior, and meal habit, totaling 121 features. Methods To identify potentially depressive students, we developed an online questionnaire system based on a standard psychometric instrument, the Zung Self-Rating Depression Scale (SDS). To explore the differences in behavior of depressive and nondepressive students, the Mann-Whitney U test was applied. In order to investigate the behavioral features of different depressive symptoms, factor analysis was used to divide the questionnaire items into different symptom groups and then correlation analysis was employed to study the extrinsic characteristics of each depressive symptom. Results The correlation between these factors and the features were computed. The results indicated that there were 25 features correlated with either 4 factors or SDS score. The statistical results indicated that depressive students were more likely to fail exams, have poor meal habits, have increased night activities and decreased morning activities, and engage less in social activities (eg, avoiding meal times with friends). Correlation analysis showed that the somatic factor 2 (F4) was negatively correlated with the number of library visits (r=–.179, P<.001), and, compared with other factors, had the greatest impact on students’ daily schedule, eating and social habits. The biggest influencing factor to poor academic performance was cognitive factor F1, and its score was found to be significantly positively correlated with fail rate (r=.185, P=.02). Conclusions The results presented in this study indicate that campus data can reflect depression and its symptoms. By collecting a large amount of questionnaire data and combining machine learning algorithms, it is possible to realize an identification method of depression and depressive symptoms based on campus data.

SUITABILITY OF HEART RATE RECORDING AS PHYSIOLOGICAL MEASURES TOOL TO DETERMINE DRIVERS’ PERFORMANCE IMPAIRMENT: A PRELIMINARY STUDY

2016 ◽  
Vol 78 (6-9) ◽  
Author(s):  
Nor Kamaliana Khamis ◽  
Faizul Rizal Ismail ◽  
Benjamin Hesse ◽  
Dieter Schramm ◽  
Niko Maas ◽  
...  
Keyword(s):  
Heart Rate ◽  
Performance Measure ◽  
Driving Simulation ◽  
Physiological Adaptation ◽  
Experimental Result ◽  
Daily Routine ◽  
Driver Performance ◽  
Performance Impairment ◽  
Simulation Scenario ◽  
Entire Experiment

Performance impairment may occur if the driver feels fatigue while driving. This study investigated the drivers’ condition while performing one hour driving simulation in a controlled environment. The aim of this study was to evaluate whether heart rate measures can be used to detect impaired driver performance as well as reduced alertness. There are two different experiments conducted among the subjects; (i) without vibration and (ii) with vibration. A monotonous driving simulation scenario with low demand of traffic flow was utilized to detect drivers’ performance impairment. Heart rate (HR) was recorded over the entire experiment; (i) 30 minutes before driving, (ii) one hour during driving and (iii) 30 minutes after driving in the morning before lunch break.  The baseline measurement was recorded when the subject has performed his daily routine in the same hours of experiment, which is about three hours. HR measures were derived and correlated to variation of lane deviation (VLD), a driving performance measure, and to the driver's state, which was estimated by the Karolinska Sleepiness Scale (KSS). Experimental result shows all subjects’ HR data were lower at the end of the driving task, particularly when driving in the simulator without vibration. Based on KSS evaluation, subjects tend to feel sleepy during driving and become less sleepy when they reach the destination. In term of VLD, all subjects tend xto cross the lane, which means they were not focused to the task. In conclusion, HR can be used as a tool to detect drivers’ performance and it is a useful indicator of physiological adaptation and intensity of effort. 

scholarly journals Multimedia Vision for the Visually Impaired through 2D Multiarray Braille Display

2019 ◽  
Vol 9 (5) ◽  
pp. 878 ◽  
Author(s):  
Seondae Kim ◽  
Eun-Soo Park ◽  
Eun-Seok Ryu
Keyword(s):  
Visually Impaired ◽  
Low Vision ◽  
Functional Limitations ◽  
Indoor Environments ◽  
Multimedia Contents ◽  
Accessible Information ◽  
Efficient Communication ◽  
Processing Information ◽  
Text Images ◽  
Braille Display

Visual impairments cause very limited and low vision, leading to difficulties in processing information such as obstacles, objects, multimedia contents (e.g., video, photographs, and paintings), and reading in outdoor and indoor environments. Therefore, there are assistive devices and aids for visually impaired (VI) people. In general, such devices provide guidance or some supportive information that can be used along with guide dogs, walking canes, and braille devices. However, these devices have functional limitations; for example, they cannot help in the processing of multimedia contents such as images and videos. Additionally, most of the available braille displays for the VI represent the text as a single line with several braille cells. Although these devices are sufficient to read and understand text, they have difficulty in converting multimedia contents or massive text contents to braille. This paper describes a methodology to effectively convert multimedia contents to braille using 2D braille display. Furthermore, this research also proposes the transformation of Digital Accessible Information SYstem (DAISY) and electronic publication (EPUB) formats into 2D braille display. In addition, it introduces interesting research considering efficient communication for the VI. Thus, this study proposes an eBook reader application for DAISY and EPUB formats, which can correctly render and display text, images, audios, and videos on a 2D multiarray braille display. This approach is expected to provide better braille service for the VI when implemented and verified in real-time.

scholarly journals Qualitative and Quantitative Assessment of Vata Dosha in a Case of Gridhrasi (Sciatica) by Nadi Tarangini Device – A Case Study

2021 ◽  
pp. 188-197
Author(s):  
Pradeep G. Desai ◽  
Mukund P. Dhule
Keyword(s):  
Quantitative Assessment ◽  
Clinical Signs ◽  
Signs And Symptoms ◽  
Routine Activity ◽  
Careful Examination ◽  
Daily Routine ◽  
Time Saving ◽  
Qualitative And Quantitative ◽  
Detailed Medical History

Aims: To evaluate the qualitative and quantitative assessment of vata doshain a case of gridhrasi by nadi tarangini device. Introduction: Ayurveda has an unique method of patient examination by ashtavidha pareeksha. i.e. nadi, mutra, mala, jivha, shabda, sparsha, drik and akruti. Amongst which examination of nadi becomes prominent examination which helps in better diagnosis of a disease/vyadhi. Gridhrasi is shoola pradhana vataja nanatmaja vatavyadhi, affecting the back involving lower limb which hampers patient’s daily routine activity. Line of Management of gridhrasi includes siravyadha, bastikarma and agnikarma. Siravyadha and agnikarma are considered as instant pain relieving methods. Raktamokshana by siravyadha is considered to be ardha chikitsa according to Sushruta. Siravyadha is specially indicated in case of gridhrasi. It is a simple OPD level procedure affordable/economical to all categories of patients and time saving. As siravyadha gives instant relief and gridhrasi is vataja nanatmaja vyadhi, it is easy for the assessment and understanding of reduction in symptoms by nadi tarangini device. Hence, in this case study an attempt is made to assess the quantitative and qualitative analysis of vata dosha before and after the procedure of siravyadha. Case Study: A patient, 45 years old; he showed the main clinical signs and symptoms of gridhrasi came to our OPD, had a history of 2 years, and had worsened in the past two days. He underwent a careful examination and we recorded a detailed medical history. With all purva, pradhana and paschat karma, siravyadha procedure was done and nadi tarangini readings were taken before, after and on 10th day of siravyadha procedure. Place and Duration of the Study: Study was conducted in ‘Sri Jain AGM Ayurved Medical College & Hospital, Varur-Hubballi (Karnatak). Study duration was 10 days. Results: Patient got marked relief in subjective criteria i.e. stambha, toda, ruk, toda, spandana, gaurava and also in objective parameters i.e. straight leg raise test, lassegue’s test and Oswestry low back pain score. It was seen that, there was visible difference in the analysis of nadi tarangini report. Conclusion: It can be concluded that, siravyadha gives better relief in gridhrasi. And it was found that nadi tarangini can be used to assess the dosha dushti and many other parameters.

scholarly journals Botnet Detection Using On-line Clustering with Pursuit Reinforcement Competitive Learning (PRCL)

2018 ◽  
Vol 6 (1) ◽  
pp. 1-21
Author(s):  
Yesta Medya Mahardhika ◽  
Amang Sudarsono ◽  
Ali Ridho Barakbah
Keyword(s):  
Reinforcement Learning ◽  
Personal Information ◽  
Competitive Learning ◽  
Classification Model ◽  
Experimental Result ◽  
Classification Methods ◽  
New Paradigm ◽  
Botnet Detection ◽  
Online Clustering ◽  
On Line

Botnet is a malicious software that often occurs at this time, and can perform malicious activities, such as DDoS, spamming, phishing, keylogging, clickfraud, steal personal information and important data. Botnets can replicate themselves without user consent. Several systems of botnet detection has been done by using classification methods. Classification methods have high precision, but it needs more effort to determine appropiate classification model. In this paper, we propose reinforced  approach to detect botnet with On-line Clustering using Reinforcement Learning. Reinforcement Learning involving interaction with the environment and became new paradigm in machine learning. The reinforcement learning will be implemented with some rule detection, because botnet ISCX dataset is categorized as unbalanced dataset which have high range of each number of class. Therefore we implemented Reinforcement Learning to Detect Botnet using Pursuit Reinforcement Competitive Learning (PRCL) with additional rule detection which has reward and punisment rules to achieve the solution. Based on the experimental result, PRCL can detect botnet in real time with high  accuracy (100% for Neris, 99.9% for Rbot, 78% for SMTP_Spam, 80.9% for Nsis, 80.7% for Virut, and 96.0% for Zeus) and fast processing time up to 176 ms. Meanwhile the step of CPU and memory usage which are 78 % and 4.3 GB  for pre-processing, 34% and 3.18 GB for online clustering with PRCL, and  23% and 3.11 GB evaluation. The proposed method is one solution for network administrators to detect botnet which has unpredictable behavior in network traffic.

scholarly journals A personalized multimedia contents recommendation using a psychological model

2012 ◽  
Vol 9 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Won-Ik Park ◽  
Sanggil Kang ◽  
Young-Kuk Kim
Keyword(s):  
Mobile Devices ◽  
Mobile Device ◽  
Behavior Pattern ◽  
Personal Information ◽  
Rapid Development ◽  
Personal Characteristic ◽  
Multimedia Content ◽  
Prototype System ◽  
Server Side ◽  
Personal Content

With the development and diffusion of compact and portable mobile devices, users can use multimedia content such as music and movie on personal mobile devices, anytime and anywhere. However, even with the rapid development of mobile device technology, it is still not easy to search multimedia content or manage large volume of content in a mobile device with limited resources. To resolve these problems, an approach for recommending content on the server-side is one of the popular solutions. However, the recommendation in a server also leads to some problems like the scalability for a lot of users and the management of personal information. Therefore, this paper defines a personal content manager which acts between content providers (server) and mobile devices and proposes a method for recommending multimedia content in the personal content manager. For the recommendation based on user's personal characteristic and preference, this paper adopts and applies the DISC model which is verified in psychology field for classifying user's behavior pattern. The proposed recommendation method also includes an algorithm for reflecting dynamic environmental context. Through the implements and evaluation of a prototype system, this paper shows that the proposed method has acceptable performance for multimedia content recommendation.

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