Reviewerly/exHarmony huggingface dataset:
EMOSIS Sentiment Analysis on Tweets with Emotion and Intensity Level Recognition Considering Ending Punctuation Marks

Sentiment Analysis is a tool used for determining the Polarity or Emotion of a Sentence. It is a field of Natural Language Processing which focuses on the study of opinions. In this study, the researchers solved one key challenge in Sentiment Analysis, which is to consider the Ending Punctuation Marks present in a sentence. Ending punctuation marks plays a significant role in Emotion Recognition and Intensity Level Recognition. The research made used of tweets expressing opinions about Philippine President Rodrigo Duterte. These downloaded tweets served as the inputs. It was initially subjected to pre-processing stage to be able to prepare the sentences for processing. A Language Model was created to serve as the classifier for determining the scores of the tweets. The scores give the polarity of the sentence. Accuracy is very important in sentiment analysis. To increase the chance of correctly identifying the polarity of the tweets, the input undergone Intensity Level Recognition which determines the intensifiers and negations within the sentences. The system was evaluated with overall performance of 80.27%.
A subject librarian’s pedagogical path in the digital humanities

As academic libraries evolve with digital humanities scholarship, subject librarians may find themselves teaching in this new pedagogical landscape before colleagues with digital humanities expertise arrive on their campus. The author provides a practical pedagogical path specifically for the subject librarian for planning, providing instruction, and evaluating a course with a significant digital humanities component. An examination of an English course is offered in addition to a detailed background of the challenges and opportunities encountered in revisiting information literacy pedagogy through student-led projects in digital humanities.
Recommendation System for Video Streaming Websites Based on User Feedback

Now a days world business organizations are mostly focused in e-commerce for enlightening their business as well as supporting their users. In the modern era, vast amount of information is generated from the internet which is open to the users. Recommendation system is midway between internet and user which expects user interests. This paper primarily focusing on developing the recommendation system for video streaming sites. The recommendation engine mainly works on content based, collaborative based filtering algorithms. But both has limitations in their own way. The content-based filtering has a shortcoming that, it restricts recommendations of the items that are of same category. Whereas in the collaborative-based filtering algorithm, it doesn’t recommend items based on the user’s past behavior. So, this system is developed using a hybrid algorithm to overcome the problems of above two algorithms by retrieving feedback from the users and calculating semantic factor from the feedback to improve the efficiency of the recommendation system. So that lets companies can better understand the user, make available personalized stores, and increases the satisfaction of the customer and their loyalty
Credit Card Fraud Detection using Machine Learning and Deployment of Model in Public Cloud as a Web Service

In recent times, usage of credit cards has increased exponentially which has given way to an increase in the number of cybercrimes related to transactions using credit cards. In this paper, the aim is to reduce the fraudulent credit card transactions happening around the world. Latest technologies like machine learning algorithms, cloud computing and web service implementation has been used in this paper. The model uses Local outlier factor algorithm and Isolation forest algorithm to develop the credit card fraud detection model using unsupervised learning techniques. The model has been implemented as a Web service to make the solution integratable with other applications and clients across the world. A third party prototype application is developed and integrated to the Fraud Detection Model using Web Services. The complete Fraud Detection System is deployed on the cloud. The Fraud Detection Model shows exceptionally high accuracy when compared to other models already existing.
Analysis and Recognition of Bilingual Handwritten Scripts

In this work, offline handwritten character recognition (HWCR) is involved, which is an open area of research for Indian languages. The recognition accuracy for HWCR is around 60% as per the literature survey. The main obstacle for the research in this area is the non-availability of a standard database. Character Recognition (CR) is an application of pattern recognition. Pattern recognition has many applications like security services, defense organizations, banking, post offices, archeological field, weather forecasting, library automation, reading aids for the visually challenged, etc. There are very less number of users for Indian languages when compared to English and hence the research for HWCR is at early stage. In this work, transform based recognition techniques are used on two languages namely Hindi and English. The best recognition accuracy obtained for the bilingual handwritten scripts is 73.33% which is in line with the existing research publications.
Secure the Data by using Image Compression in Multi-Cloud Storage

Cloud storage providers are in ability for trust the data available and accessible that makes physical condition to be secure and running. Organizations bargain storage capacity from the providers to store user data, business, or request data. Clients desires to furnish their data to public cloud servers (PCSs). Recently got security troubles take to solve and aid more client’s improvement their records in multi-cloud Storage. The customers allow saving information in the cloud the use of services supplied by using more than one cloud storage companies (CSPs). It is a hopeful method to enlarge the degree of records availability and confidentiality, as all at once these distinctive CSPs are out of provider at the identical time or collude with each other to extract records of a user. This suggest a survey on the viable protection merits by means of creating use of multiple wonderful clouds at the identical time. In addition, this advice work as merging and splitting standards at some point of storage in cloud environment. In file access, personal keys produced the use of digital key generator. 3DES encryption algorithm generates key in a cipher text format to the users. Towards facts confidentiality, this advocate an assured facts hiding and spitting picture technique in cloud storage. In propose work, essential purpose will be photo compression with mutable statistics hiding approach whilst storing in the real cloud for data hiding &amp; photo compression via the use of Discrete Wavelet Transform (DWT) algorithm.
Correction: Comparative validity of energy expenditure prediction algorithms using wearable devices for people with spinal cord injury

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Architectural Framework for Cloud Reliability Model using Fault Tolerance Techniques

Cloud Computing is an essential podium for workable and impracticable users. It achieves high quality reliable services provided to the users via data storage servers. The key challenge in cloud architecture is to run the facilities without any hazel to the users. In today’s world of information technology, most of the applications are real time. The major constraint of the systems used in real time applications is that, they are prone to failure. The failure may be due to the following reasons: a) Failure to complete the task in prescribed time threshold value. b) Failure to achieve prescribed reliability value. Virtualization and Internet-based Cloud computing causes diverse types of failures to occur and so necessity for reliability and availability have turn out to be of vital concern. To ensure reliability and availability of cloud technologies, methods for fault tolerance need to be developed and deployed. The proposed work will focus on adaptive behavior during the assortment of replication and fine-grained check pointing methods for achieving a reliable cloud platform that can grip diverse client requests. In addition to this, the proposed work will also conclude the best suitable fault tolerance scheme to each chosen virtual machine.
FLIPPED LEARNING AND DISTANCE LEARNING: POSSIBLE COMBINATION IN A UNIVERSITY EXPERIENCE

The work describes a university experience of distance learning imposed by the health emergency in which, as part of the "Methodologies and teaching in early childhood" course for the training of future educators, a Flipped Learning approach with the support of telematic technologies has been tested with 381 students.The methodologies used will be described, with reference to the theoretical principles of active and collaborative teaching.Through the data collected by a questionnaire addressed to the participants, the results of the experiment will be reported in terms of students' perception of the learning and the dynamics of the relationship with the teacher and colleagues in the course.
Influence of classical field on entanglement and photon statistics of n-level atom interacting with a two two-level atom

In this study, we consider three interacting atoms, one of them represented by N-level atom based on SU(2) Lie algebra and the other represented by a two two-level atom in presence of the external field. The effect of the external field on the dynamics of the proposed system is discussed in detail for certain values for the external field. The dynamical expression of the observable operators is obtained by using the Heisenberg equation of motion. The general solution via solving Schrodinger equation is obtained. The fidelity and concurrence formula as a measure of entanglement between two two-level atom are calculated and discussed in detail. We explore the sudden death and sudden birth phenomena with and without the presence of external field. Finally, we compare the results of the fidelity, concurrence and second-order correlation function for some values of the initial state and the external field parameters.
An Advanced Education Prognostic Miniature Exploitation Random Forest Technique

The precept goal of the higher instructive affiliation is to offer excessive notable and important education to its understudies. the 2 desires of statistics mining in Indian guidance framework is to have a look at and enhance the account technique facts mining propels development;, type out &amp; speak approximately very last outcomes this is created via the usage of the usage of an information mining technique. This paper centers at some stage in the model portrayal for reading the numerous records mining techniques in Indian guidance framework. moreover the paper surveys a similar research of ID3, k-manner, Naïve Bayes, Random wooded vicinity calculation. in this paper, we've got have been given proposed the approach of Random wooded location to foresee the profession choice for the 12th going out understudies. The usage of Random wooded location has helped the understudies to truely receive a proper desire consistent with their advantage and aptitudes and acts a lifelong advertising representative tool package deal.
Other Easement Gift Litigation

Bruce R. Hopkins' Nonprofit CounselVolume 37, Issue 9 p. 4-4 Articles Other Easement Gift Litigation First published: 07 August 2020 https://doi.org/10.1002/npc.30763Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume37, Issue9September 2020Pages 4-4 RelatedInformation
Mineralogy and geochemistry of Wajrakarur kimberlites, southern India

Petrography, mineral chemistry and bulk-rock major and trace element data of 42 kimberlite samples from 17 pipes covering three clusters of the Wajrakarur Kimberlite Field (WKF) of southern India allow recognition of similarities and differences in their mineralogy, and provide constraints to be placed on their genesis.The samples examined are from KL1 to KL3 pipes of the Kalyandurg cluster, P1 to P13 (except P6, P7 and P9) pipes of the Wajrakarur-Lattavaram cluster, and CC1 to CC5 (except CC3) pipes of the Chigicherla cluster.The kimberlite pipes were emplaced into the eastern Dharwar craton at ~ 1100 Ma.Most of the WKF pipes are diamondiferous.
The geochemistry of Diavik kimberlites, Lac de Gras, NWT., Canada

The Diavik diamond mine is located on a 20-square kilometre island in Lac de Gras, approximately 300 kilometres northeast of Yellowknife.Diamonds are currently mined from three kimberlites; A154 South, A154 North and A418.Sixty-eight kimberlites are currently recognized on the Diavik property and several of these have been dated, yielding emplacement ages between 54.7 and 56 Ma (Graham et al. 1999;Creaser 2004).Fresh macrocrystal phlogopite extracted from two samples in this study, Anik and A841, yield Rb-Sr ages of 55.8 Ma and 56.7 Ma, respectively.These emplacement ages are in excellent agreement with previous ages from the Diavik property.Further attempts at emplacement ages were unsuccessful due to the absence of perovskite and extreme alteration and replacement of macrocrystal phlogopite.
Exploring the Extrinsic and Intrinsic Reading Motivations among Malaysian ESL Undergraduates

Purpose of Study: Reading for pleasure is scarce among today's undergraduates. It is believed that undergraduates read books because of their grades and reading not for pleasure. Undergraduates distinguish reading as a chore that they must take upon to excel academically. This paper sets out to conduct a preliminary study of reading motivations among Malaysian undergraduates of English as Second Language Learners. Methodology: A survey was carried out among UiTM undergraduates using the Reading Motivation Questionnaire (RMQ) to investigate their reading motivation towards extensive reading narratives. Results: Results revealed that there were 11 elements of reading motivation of the intrinsic and extrinsic motivation dimensions among young adults. Reading efficacy, reading challenge, reading curiosity, reading involvement, the importance of reading, reading work avoidance, competition in reading, recognition for reading. reading for grades and social reasons for reading and compliance were assessed. The results revealed the importance of reading motivation in second language learners Implications/Applications: It is hoped by identifying the relationship of reading motivation will help in fostering a culture of reading among second language young adult readers.
Keynote Talk: The challenges of eXplainable AI for early detection of cognitive decline

Our ageing society claims for innovative tools to early detect symptoms of cognitive decline. Sensorized smart-homes and artificial intelligence (AI) methods allow detecting a decline of the cognitive functions of the elderly. However, existing tools provide limited support to clinicians in making a diagnosis. Indeed, most existing AI systems do not provide any explanation of the reason why a given prediction was computed. In this talk, I will survey this challenging problem and existing solutions. I will also present a novel AI system to recognize early symptoms of cognitive decline in smart homes, which is able to explain the reason of predictions in natural language. The method relies on clinical models that consider behavioral anomalies, spatial disorientation, and wandering behaviors. An AI-fueled dashboard allows clinicians to inspect anomalies together with the explanations of predictions. I will also report on preliminary experiments carried out with a large set of real-world subjects, including people with MCI and people with dementia.
Otsu and Mathematical Morphology for Breast Cancer Classification

Segmentation is one of the essential components in Computer Aided Diagnosis (CADx).This paper proposed a combination of Otsu and mathematical morphology for segmentation phase in classifying breast cancer.Then, the features of the segmented images will be extracted by using Speed Up Robust Features (SURF).Finally, the corresponding features will be classified using several classifiers.It is found that the Support Vector Machine (SVM) classifier shows the highest accuracy rate among other classifiers.Moreover, experimental results show that the proposed combination method shows promising results.
CIS Society Officers

T ime really flies!It seems, it was not long back when I wrote my first message as the President of the IEEE Computational Intelligence Society (CIS).In reality, a year has gone!I hope that you all had a happy, healthy, productive, and peace-filled 2018.But in life for many of us due to various reasons things do not always happen the way we want them to.We need to take those as compliments and lessons for the future.Nevertheless, I can certainly and sincerely wish and hope you to have a great 2019.Let the year 2019 bring you all happiness and help you achieve all your unfulfilled goals.For CIS the year 2018 was a successful one.The IEEE World Congress on Computational Intelligence, WCCI 2018, held in the beautiful city of Rio de Janeiro, was very successful.It was very well attended.Apart from the academic program comprising WCCI-level plenary talks, conference level keynote talks, regular and special sessions, we had very exciting panel discussions including one in memory of Prof. Lotfi Zadeh, the father of fuzzy logic.In addition, there were industry forum and different receptions including one on Women in Computational Intelligence (WCI).WCCI 2018 had a packed "heavy-duty" academic program, but the organizers realized, "All work and no play is not good for the soul" (Felix Sabates).They organized an excellent banquet program.I believe, most participants, like I, were surprised to see the sudden appearance of a very lively "samba-dance" troupe giving us an exciting and rhythmical performance.This made everyone happy and energized many to share the floor with the skilled troupe.The CIS is a member-centric society that always works for the benefits of its members.Our members play a key role in advancing computational intelligence technology.The young researchers and undergraduates are the future leaders.Keeping their needs in mind, I am very glad to share that we have extended the scope of our Distinguished Lecture program to accommodate mentoring of young researchers and special talks for undergraduate students.Now when a Distinguish Lecturer (DL) visits a chapter, local young researchers may take this opportunity of interacting with the DL to discuss their research problems and get useful suggestions/guidance.In addition to the distinguished lecture, now the Chapter can also organize a special talk by the DL for undergraduate students of nearby universities/institutes or for local industries.This is likely to promote computational intelligence (CI) among the undergraduates.In line with the IEEE level Member-Get-a-Member (MGM) Referral program, we are planning to have a CIS MGM referral program.The CIS-MGM program will give an opportunity to a CIS member to share his/her rewarding experience of joining CIS to a friend/colleague and motivate him/her to join CIS.Through this referral, one can earn awards that can be used to pay for his/her CIS membership dues.In order to have a better interaction with our members and others who are interested in CI and CIS, and to share information in a more effective manner, we have launched our new website in October 2018.
IMPLEMENTASI METODE DATA MINING APRIORI PADA APLIKASI PENJUALAN PT. TIGA RAKSA SATRIA

been done computerized, but the sales data has not been processed optimally. there is no application that analyzes sales data for category, planning and service to consumers. Analyzing sales data is an important part of the company, an analysis of sales results has an impact on the profits to be gained by the company. Datamining is the science of digging up valuable information and knowledge in databases. One algorithm in data mining is a priori algorithm. Datamining is widely implemented in various fields such as business, commerce, and others. This research aims to make an application with the Application of Data Mining Basketball Analysis Method with Apriori Algorithm to process the sales data in a more structured, detailed and know the problems in product sales. This application generates rules that help draw conclusions needed for drawing conclusions of strategic information for companies regarding sales data. Application made with the application of a priori methods helps in the analysis of sales data that is owned.
Towards a JSON-based Algorithm Animation Language

The ninth IEEE Working Conference on Software Visualization (VISSOFT 2021) builds upon the success of the previous eight editions of VISSOFT, which in turn followed after six editions of the IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT) and five editions of the ACM Sympo0sium on Software Visualization (SOFTVIS). In 2021, VISSOFT will take place and be co-located with ICSME.
Service innovation and firm performance: operational experiences in uncertain environments

Innovation is one of the main factors affecting the firms' performance; however, it is less investigated in service firms. This study aims to assess the effect of service innovation on firms' performance in uncertain environments when the market orientation capabilities can help firms to operate more efficiently. Data was collected from travel agency managers in Iran. The results revealed that in stable environments, service innovation affects firm performance indirectly via quality of service and customer satisfaction. But having considered environmental uncertainties, service innovation showed a direct effect on firm performance in addition to indirect effects. Moreover, market sensing and customer linking capabilities are moderating the relationship between service innovation and firm performance in uncertain environments.
Evolutionary Computing and Swarm Intelligence for Hyper Parameters Optimization Problem in Convolutional Neural Networks

In recent years, deep learning has become most popular and ia used in various applications like agriculture, business, healthcare and many other domains. Convolutional neural networks (CNN) is most widely used and it has attained notable improvements in the various real-world scenarios and problems. The network for the specified task results in improved accuracy by applying hyperparameters configuration. This chapter aims to offer a summary of deep learning, metaheuristic in hyperparameter optimizations, problems, challenges, and future perspectives. The working strategy of CNNs with its structure, characteristics and problems are discussed. Evolutionary computing, CNN and swarm intelligence are also summarized.
Analysis on FPGA Designs of Parallel High Performance Multipliers 

For many applications from the areas of cryptography and coding, finite field multiplication is the most resource and time consuming operation. In this paper, optimized high performance parallel GF(2233) multipliers for an FPGA realization were designed and the time and area complexities were analyzed. One of the multipliers uses a new hybrid structure to implement the Karatsuba algorithm. For increasing performance, we make excessive use of pipelining and efficient control techniques and use a modern state-of-the-art FPGA technology. As a result we have, to our knowledge, the first hardware realization of sub quadratic arithmetic and currently the fastest and most efficient implementation of 233 bit finite field multipliers