Reviewerly/exHarmony huggingface dataset:
Impact of Performance Appraisal on Employee Performance in Private Sector Banks of District Aligarh

As we all know Human Resources are the most vital component of an organization. To succeed in this competitive era, an organization must possess effective and efficient human resource in every manner. Hence after the selection employee, he has been trained and motivated. For this evaluation of the performance of an employee is needed. This process of evaluation is known as Performance Appraisal. With the help of systematic appraisal methods, corporate performance can be enhanced. It is basically to know the value of an employee qualitatively. It is indispensable tool for every organization for measuring the effectiveness of the employee. This research study has been done to understand the impact of Performance Appraisal on Employee performance in Private sector banks of district Aligarh. In this study, researcher selected two private sector banks ICICI and Axis bank with the sample size of 100. Researcher used Linear Regression as statistical tool for data analysis.
Self-regulated Learning Strategies of Grades 9-12 Students in Design Project: Viewed From Performance and Gender Perspectives

Exploring self-regulated learning skills in grades 9-12 students' design activities promotes a better understanding of how students deal with problem solving.This study focuses on students' understanding of task demand and Self-Regulated Learning (SRL) strategies including planning, and cognitive and monitoring/fix-up strategies.A mixed-methods approach to research was applied to gather comprehensive and valid information about students' SRL strategies.The objectives of this preliminary study were to investigate high school students' design activities that reflect their understanding of task demand and SRL strategies to accomplish the design task from the perspective of design performance (i.e., high-and low-performing students) and gender.A better understanding of these issues will specifically benefit technology and preengineering educators as well as the high school curriculum developer.Students at a high school in Colorado participated in this preliminary study (n = 29); 22 students participated in a robotics project and 7 students conducted an architecture project.Based upon a data review process, the researchers accepted 27 data sets for data analysis.Butler and Cartier's SRL model was used to frame a survey questionnaire and design journal.Because SRL is contextual, Dym and Little's prescriptive model of design process was also used to frame the questionnaire items for this study.Two subsections of survey questionnaire were used at the early and middle stages of the design projects, respectively.Each subsection assessed different SRL strategies.The SRL mean values of each design sub-phase were calculated and compared between high-and low-performing students, and also between males and females.For the design journal, participant responses were categorized and tabulated according to SRL features.The class instructor was asked to score the students' journal based upon clarity and specificity of the journal writing.The findings of the design journal were used to confirm the results of the questionnaire analysis.The results suggested that high-performing students exhibited a better awareness than did lowperforming ones on task interpretation, cognitive strategies, and monitoring/fix-up strategies during the design project.On the other hand, the low-performing students performed very well on planning strategies.From a gender perspective, while males reported a good awareness on task interpretation and planning strategies, females showed a good awareness on cognitive and monitoring/fix-up strategies.The analysis of the design journals confirmed that high-performing students outperformed the low-performers.The findings from design journals also revealed that female students had a good awareness in understanding task demand, executing plans and monitoring and regulating their strategies.In addition, limitations and suggestions for further work on this study will also be discussed.
Inform Me- Family Location Tracker App

Inform Me is an android mobile application which is designed to track the location of family members or anyone in general in real-time, without worrying about their whereabouts in amidst their busy life. Also, you can know their battery status provided they have agreed to share location with you, and have installed inform me application on their phone. People can save daily routine places in the app like college, workplace, school, etc. In this application, the family members get notifications whenever someone in the family has entered or left the saved location. Messaging tool in this app allows you to chat with the family members whenever you are at a new place irrespective of the places you saved in the application. There is also a panic button that will send a message to all the family members in case of emergency.
Automatic Detection and Classification of Lung Carcinoma using Image Processing Techniques in Lab VIEW

Lung cancer screening saves human lives by detecting cancer earlier, when it may be treated more successfully. The most familiar methods for the diagnosis of lung cancer includes bronchoscope guided BronchoAlveolar Lavage (BAL) samples and the CT scan. In this paper, we propose a technique to automatically analyze the microscopic images of BAL samples and CT scan images in the same platform. This method will help in reducing the manual intervention and provides many useful parameters such as location, size and number of clusters present in the images. We have processed the images using the specialized software in LabVIEW, NI vision Assistance. The detection is done with the microscopic images of BAL and the stages are classified with the analysis of CT scan images. For this, separate algorithms have been developed using Vision Assistant and the common user interface has been designed using LabVIEW.
Data as a Service using Data Hibernation and Service Oriented Architecture in Cloud Computing

Nowadays, Cloud Computing is a promising research field. With the advancement of modern technology, performance improvement of the cloud network has become the buzzword today. Here in this paper, we have proposed the new technique, called ‘Data Hibernation’ where service-oriented architecture plays the key role for the improvement of the cloud network. Moreover, we have designed our algorithm and demonstrated our work graphically that how the overall efficiency or the throughput has reached its apex level of Quality of Service with the subtle benefit of much higher degree of parallelism.
Extract Genuine Healthcare Posts on Social Media

Social media plays an important role in spreading the news. People who search for health online and those who rely on social media for small health issues and diet management are increasing periodically. Nowadays, food habits are greatly influenced by social media. Health-related data such as home remedies, diet management, and beauty tips are mainly focused in this paper. Such data available in social media may be genuine or might be not, just because of business strategy to promote products suggested. There is a huge scope for misleading vital content in this scenario. This paper gives an overview on how to process data using machine learning techniques and/or deep learning techniques available on social media by applying social media analytics and revile trustworthy information at one place. As well as describes how to create a platform for genuine information about health care.
CYBERSECURITY ENGINEERING: THE GROWING NEED

Cybersecurity job openings continue to grow rapidly and is why the need for cybersecurity jobs has arisen so quickly.With 3.5 million cybersecurity jobs expected to open by 2021, employers will continue to seek out prospective job candidates from technical schools and undergraduate programs to fill them.This may satisfy the immediate need well enough, but it does not address the demand for cybersecurity professionals with advanced degrees such as Cybersecurity Risk Management and Cybersecurity Engineering, which is becoming even more acute.This journal article provides and in depth look at what Cybersecurity Engineers do, why more are needed, and how universities are creating programs to tackle the need.
Assessment of Ecological Consciousness Formation among Adolescent Girls in the Learning Process by Means of Specialized Computer Systems

The article discusses the results of empirical research in the framework of ascertaining experiment, the purpose of which was to assess the level of environmental consciousness formation of the secondary school adolescent girls. The results analysis was carried out on the intensity levels of subjective relations, such as: perceptive-affective, cognitive and behavioral. To diagnose each component the technique of "Naturafil" was used, which helped to identify the nature of development level of ecological consciousness. Information processing within the framework of the expected results evaluation criterion was carried out on the basis of mathematical statistics methods included in the data analysis package of MS Excel software application. Significant differences in the studied parameters between the groups were revealed by the determination coefficient.
Audio- Drama Nursing Intervention Utilizing Peer Education on Menstrual Hygiene and Sickness Management among Blind Adolescents

Adolescence is a critical developmental stage.Blind adolescent girls are a group of disabled girls who needs a special care specifically during the menstruation.The study aimed to examine the effect of audio-drama nursing intervention utilizingpeer education on menstrual hygiene and sickness management among blind adolescents.Design: Quasi-experimental design (pre and posttest) was used to accomplish the present study.Setting: Al Noor institute for visually impaired students at Shebein El-kom City in Menoufia Governorate, Egypt.Subjects: A Convenient sample of 40 blind girls aged between (12-18years) was recruited in this study.Tools: four instruments were used for data collection; I: Structured interviewing questionnaire which consist of two parts; first part:Socio-demographic data; second part: Menstrual data.II: An interviewing questionnaire on knowledge about menstruation; Knowledge about menstrual hygiene questionnaire; andKnowledge about management of menstrual sickness questionnaire.III: Non -observational checklist on practice of menstrual hygiene and management of menstrual sickness.IV: An interviewing questionnaire on satisfaction level.Results: There were lack knowledge and practices regarding menstruation before implementing the audio drama nursing intervention using peer education sessions.Also, there were an improvement and highly statistically significant differences in the totalscores of knowledge and practices of blind adolescent girls regarding menstruation after provision of the audio drama nursing intervention using peer education (P<0.001). Conclusion:The audio drama nursing intervention using peer education were effective in the improvement of the blind adolescent girls' knowledge and practices regarding menstrual hygiene and menstrual sickness management.Recommendation: Continues health education programs should be applied to raise the awareness of blind adolescent girls regarding menstruation in different setting.
Challenges and Coping Strategies of College English Education Based on MOOC Education

As a new attempt and bold exploration in the field of education, the MOOC education model is an innovative breakthrough in the traditional teaching mode.It effectively breaks the limitations of time and space in English classroom teaching, further promotes the stable development of education in higher education, guides its development towards innovation, and realizes the optimization and adjustment of education structure in college English.However, it also puts forward some challenges to the education of college English, and urges the reform of education of college English.Based on this, this paper analyzes and discusses the challenges faced by China's college English teaching activities in the context of MOOC education, and analyzes the countermeasures to provide a diversified teaching model for college English education.
Nuvo Pharm. (Ireland) Designated Activity Co. v. Dr. Reddy's Labs. Inc. United States Court of Appeals of the Federal Circuit, 2019 923 F.3d 1368

Biotechnology Law ReportVol. 38, No. 4 As presented by Chris HolmanNuvo Pharm. (Ireland) Designated Activity Co. v. Dr. Reddy's Labs. Inc. United States Court of Appeals of the Federal Circuit, 2019 923 F.3d 1368Edited for Biotechnology Law Report by CHRISTOPHER M. HOLMAN*Published Online:8 Aug 2019https://doi.org/10.1089/blr.2019.29132.cmhAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetailsCited byThe Death of the Genus ClaimSSRN Electronic Journal Volume 38Issue 4Aug 2019 InformationCopyright 2019, Mary Ann Liebert, Inc., publishersTo cite this article:Nuvo Pharm. (Ireland) Designated Activity Co. v. Dr. Reddy's Labs. Inc. United States Court of Appeals of the Federal Circuit, 2019 923 F.3d 1368.Biotechnology Law Report.Aug 2019.249-255.http://doi.org/10.1089/blr.2019.29132.cmhPublished in Volume: 38 Issue 4: August 8, 2019PDF download
A Secure Boot Loader System for Loading an Operating System with Fingerprint Authentication

In today’s world, people are constantly on move and portable systems are in demand. With technology advancement, people exploit different types of memory devices for a portable system. For any external boot medium, the BIOS boot order setting change is required. The dynamic boot loader successfully eliminated this dependency and allowed the user to directly boot from any portable USB. The usage of USB has grown exponentially in recent years and securing it has become a major concern. In this paper, the USB is devised as a highly secured portable boot medium with fingerprint authentication to ensure data security. It performs feature extraction by combining both Local Directional Pattern (LDP) and Histograms of Oriented Gradients (HOG) which improves the accuracy rate. The classification is performed by random forest classifier, such that the intended users alone are granted access to the private storage area of the USB drive.
Emotion Recognition from Facial Expressions using GFE, LBP And Hog Feature Extraction Techniques

The social interaction of human beings is many times influenced by non-verbal communication, especially facial expressions. In societal life face of a human being is mostly observed by surrounding people to know the inner feelings. Thus, face forms a significant source of expressing human emotions, typically categorized into surprise, anger, fear, disgust, sad and happy. In the variety of behavioral science fields, emotion recognition has a significant role to play. The present paper describes a system in which preprocessing is performed by median filtering. Before extracting features, the watershed segmentation is applied to get the required characteristics of an image. In this paper, the Gamma based Feature Extraction (GFE), Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG) technique have been used for feature extraction. The LBP algorithm is additionally tested with and without application of gamma correction using GFE. Two classifiers, namely kNN and SVM, have been employed, and their performance is compared. kNN and SVM, being supervised classifiers, can aid in better accuracy with proper training.
Empirical Models for the Evaluation of Global Solar Radiation in the Different Sites of Nepal

To operate many phenomenon’s on the earth surface such as physical, chemical and biological process solar radiation plays vital role. A common practice is to estimate average daily global solar radiation (GSR) using appropriate empirical models for the areas lacking the actual measured values. In this context several single and multiple meteorological parameters were selected to estimate the GSR for Jumla, Nepalgunj and Kathmandu. In order to validate the selected models various statistical test were employed. The selected models were compared on the basis of statistical errors. In the statistical analysis the value of root mean square error (RMSE) and coefficient o determination R2 is found to 0.15.0.23, 0.26 and 0.98, 0.96, 0.96 respectively for Jumla, Nepalgunj and Kathmandu in Samuel model. These values were comparatively better than other models. It is concluded that Samuel model (order three) is the best among the used models. The established result uncover that there is a good possibility of solar energy as a alternative energy source in Nepal.
2D Information Space Based Action Recognition

Video based human action recognition has attained more attraction from the researchers and it predominates in the field of computer vision and pattern recognition. In this paper we deliver a new approach to suppress the background data and to extract 2D data of foreground human object of the video sequence. A combination of convex hull area, convex hull perimeter, solidity and eccentricity is used to represent the feature vector. Experiments are conducted on Weizmann video dataset to assess how the system is doing. The discriminative nature of the feature vectors assures accuracy in action recognition.
Glacial dispersion study of kimberlitic material in Quaternary till from the Lahtojoki pipe, eastern Finland

In 2001-2002 the Geological Survey of Finland (GTK) carried out sampling of Quaternary till around the Lahtojoki kimberlite (Pipe 7) in eastern Finland.The objective was to study the mineralogical and geochemical signatures of the kimberlite in the surrounding basal till.Pipe 7 belongs to the Kaavi cluster of the Neoproterozoic Eastern Finland Kimberlite Province situated at the edge of the Karelian Craton.It has mineralogy typical of Group I kimberlite.The 2-ha pipe is located in a swamp and covered by thick glacial overburden.The 2 x 2.5 km sampling area was situated down-ice from Pipe 7, samples being taken by an excavator and a drill rig.The concentration of indicator grains (0.25-1.0 mm) was based on a GTK modified 3"Knelson Concentrator.Chemical analysis of the till fine fraction (< 0.063 mm) was performed using XRF and ICP-MS instruments.The indicator grains form a relatively well-defined fan in the basal till that can be followed at least 2 km down-ice from the pipe.The maximum concentration of indicators is found at 1.2 km distance.Another small kimberlitic body was discovered by drilling 300 m down-ice from the pipe.The indicator population in till corresponds to that of the pipe in grain size, mineralogy and texture.All till samples turned out to be uniform in their chemical composition; no obvious correlation was found between fine fraction geochemistry and indicator content.
Internet of Things (IoT) Security: Present Status and Future Direction

As in light of the fact that we rest in principal world, where several undertaking are done carefully in our way of life.As of now these days, we see that things are connected with web by utilizing Web of Things several regions like Prosperity, Homes, Agribusiness, and Transport then on and therefore its wound up being incredibly huge for individuals.The online of Things alludes to the interconnection by means of the online of processing gadgets inserted in each item privilege them to send and get information.Privacy and Security are the concerned issue for an IoT application and as yet confronting some immense difficulties.The information gathered from the IoT sensors, contain numerous private data which should be protected.Henceforth this paper endeavor to clarify the current status of web of Thing associated with thing and giving the new methodology of growing world and in future how it'll ascend in new computerized world.
Emotional intelligence creating a new roadmap for artificial intelligence

Artificial intelligence (AI) changing the world with the power of creating intelligent solutions capable of autonomous decision-making and self-diagnostic abilities. Recent research on AI tends towards the use of emotional intelligence in artificial systems. A clear understanding of human emotion or cognitive behaviour can help an artificial system to become more rational and unbiased while making any decision. If a machine can think or feel like a human, it can be converted into a better decision-making system. This paper has performed a thorough review of state-of-the-art technologies and researches going in this particular field and tries to find out the current roadmap as well as the future trends in this area. This paper presents several types of research that are going on in this area and future trends.
The Implementasi Metode On-Page Search Engine Optimization untuk Meningkatkan Peringkat Website sebagai Hasil Pencarian Google

Current development of the internet world has been growing rapidly, especially in the field of website. People use search engines to find the news or information they needed on a website. One of the many indications of the success of a website is traffic. Traffic could be received from various factors, one of which is website rank in Search Engine Result Page (SERP). To improve the SERP, SEO methods are required. This research will implement SEO to website especially on the image, and then analyzed by using a tester tools, for example SEOptimer, Pingdom Tools, and SEO Site Checkup. After the website has been optimized, tested with the same tester tools. From the research results can be seen whether image optimization can affect SERP.
Design of Cognitive MCQ test in Virtual Learning Systems to Determine Learner Affect

Virtual learning systems are expected to be adaptive to the grasp exhibited by the learner. Learner affects like confusion and confidence are displayed by the learner through behavioural cues. Identifying affect in a non-intrusive, sensor-free and scalable setting is preferable. Using interaction based behavioural log features; methodology for determining learner affect is presented. The MCQ test questions in the system are based on Bloom’s Taxonomy Cognitive levels. The system records interactions of the learner. The regression analysis result on the dataset shows accuracy of confusion detection above 70%.
Deep Network for Content and Context Based Image Retrieval System

The brisk improvement in sight and sound and imaging advancement, the amounts of pictures moved and shared on the web have extended. It prompts to develop the particularly reasonable picture recovery system to satisfy human needs. The substance setting and contain picture recovery structure which recovers the picture subject to the likeness of the huge highlights, for instance, names which are unquestionably not satisfactory to depict the customer's low-level insight for pictures. In this exploration paper lessening this semantic issue of picture recovery is a difficult errand. Presumably the most critical considerations in picture recovery are watchwords, terms or thoughts. Here separated picture highlights from a pre-prepared profound system (RESNET), and utilize that highlights to prepare profound learning classifier. Remaining profound systems make include extraction most effortless and quickest approach to use than some other profound system strategy. In this exploration paper, we portray Image recovery utilizing proposed lingering profound systems.