Reviewerly/exHarmony huggingface dataset:
Understanding Customer Voice of Project Portfolio Management Software

Project Portfolio Management (PPM) has gained success in many projects due to its large number of features that covers effective scheduling, risk management, collaboration, and third-party software integrations to mention a few.A broad range of PPM software is available; however, it is essential to select the PPM with minimum usage issues over time.While many companies use surveys and market research to get users feedback, the PPM product software reviews carry the voice of users; the positive and negative sentiments of the PPM software reviews.This paper collected 4,775 reviews of ten PPM software from Capttera.com.Our approach has these phases-text preprocessing, sentiment analysis, summarization, and categorizations.The software reviews are filtered and cleaned, then negative sentiments of user reviews are summarized into a set of factors that identify issues of adopted PPM software.We report the most important issues of PPM software which were related to missing technological features and lack of training.Results using Latent Dirichlet Allocation (LDA) model showed that the top ten common issues are related to software complexity and lack of required features.
The Implementation, Actual Use and User Experience of an Online Home Exercise Program That Fits the Needs of Older Adults with Mild Cognitive Impairments

As the population ages, the number of people in our communities suffering with mild cognitive impairment (MCI) will increase.Individuals with MCI may benefit from e-health interventions for exercise promotion, but there is a need for such an e-health program that fits the needs of older adults with MCI.The objective of this study was to evaluate the implementation, actual use and user-experience of a home-based exercise program developed for older adults with MCI.Questionnaires were filled in about the implementation strategy, actual use and user-experience (usefulness, usability and satisfaction).Fifty-seven older adults and eight formal caregivers participated in the study.Mean duration of the sessions was 18 minutes (+/-15).The user-experience of the older adults was higher than that of the formal caregivers.Formal caregivers mainly offered the program at the home care organization, but some older adults indicated that they were willing to try it at home.In conclusion, the online exercise program is feasible and potentially beneficial for older adults when taking into account the e-health literacy of older adults and attitude towards e-health of formal caregivers in the implementation strategy.
Scribe Hero: An Online Teaching and Learning Approach for the Development of Writing Skills in the Undergraduate Classroom

This study examined whether or not writing skills could be taught to post-secondary students via online learning modules and what student perceptions of such a learning process were like. A pilot study of the modules developed—called Scribe Hero—was conducted in the Fall of 2017. Statistical analysis of quantitative data reveals an improvement in student writing skills following their engagement with the online learning modules. Thematic analysis of qualitative data revealed that the students were engaged by the experience, finding it educational and refreshingly different from in-class options. The feedback also suggested that user-friendly technology, tone of the online environment, incentivising meaningful feedback, and maintaining a sense of direct applicability of content are essential to capitalising on this sort of teaching and learning methodology. Overall, the findings of this small-scale research study support further development of this technology while also offering lessons that can be transferred to other contexts for teaching writing.
Requirements Practices in Software Startups

In a dynamic environment full of uncertainties in software startups, software development practices must be carefully approached.It is vital that startups determine the right time to make advancements and evolve their company to the next level.We will discuss the importance of requirements practices in startups and their impact on company culture, work environments, and product quality.
The Effects of the Multimedia, Modality, and Redundancy Principles in a Computer- Based Environment on Adult Learners

Computer-based training (CBT) has become a common form of instructional delivery in business and educational environments.A standard practice during the design and development of CBT, is to incorporate the multimedia principle to aid learning.However, a recent meta-analysis by Pastore, Briskin, and Asino (2016) revealed that very little research has actually examined the multimedia principle (single vs. multiple representations) on adult learners in a computer-based environment.Instead, much of the research has focused on K-12, used paper and pencil rather than a computer, did not compare single vs multiple representations, or had methodological issues (i.e. did not report the type of knowledge assessed).As a result, the current study examines the multimedia, modality, and redundancy principles in a computer-based environment with adult learners on learning (high-and low-level knowledge) and cognitive load measures.The results of the low (recall) and high (transfer) level learning tasks in this study supported the multimedia principle.Multiple representations were found to better support learning than just one.However, this was not the case for modality or redundancy principles.Learners presented duplicate text and narration or text with optional narration performed just as well as those with no duplication, indicating reverse redundancy.Additionally, the narration and images groups did not outperform text and image groups.
Multi-Carrier Steganographic Algorithm Using File Fragmentation of FAT FS

Steganography is considered to be not only a science, but also a craft of concealing ongoing communication by hiding messages in unsuspicious cover documents, such as texts, digital images, audio and video sequences. Its essential feature is the constant search for - often exceptionally creative - possibilities of concealing information. In computers, steganography often uses secondary memory and exchangeable memory media utilising file systems. This paper deals with the current state of the issues related to information hiding by means of hard disks, being the most important source of forensic data. This paper focuses on information hiding using the File Allocation Table (FAT) file system. It also proposes a novel multi-carrier algorithm of hiding information in file fragmentation. The algorithm provides flexibility of encoding the information to be hidden and makes steps toward optimization that allows reduction of interference with the current state of the file system, represented by the statistical values of the file fragmentation parameters.
ACADEMIC FREEDOMS AND BUREAUCRATIC BONDS OF THE LECTURERS: RESULTS OF FIELD RESEARCH IN BRITISH AND FRENCH UNIVERSITIES

This case-study article presents the results of a field 2016–2017 study done in the universities of Great Britain and France. The purpose of the research was to identify the features of the professional identity of university lecturers in these countries including the applicability of their experience to harmonize Russian higher education. According to this purpose, there were in-depth interviewed about 50 representatives of British (more than 20 interviews) and French (about 30 interviews) higher education institutions. In advance, there had been worked out a guide containing five blocks of questions. In the course of the study, there were clarified typical reasons for choosing the profession of a university lecturer; the lecturers’ views on the competencies required to work at the university, on the advantages and disadvantages of their profession, on the existence of a code and/or unwritten rules of the relationship within the team, on typical conflict situations. The problem of the relationship between academic freedoms and bureaucratic bonds has become the leitmotif of the whole study. As result, there have been distinguished the deep foundations of the transformation processes at the university. The study showed that British and French lecturers understand their profession, as a rule, in a similar way. The differences identified are not serious. The results can be applied to the Russian university system, which is at the initial stage of transforming towards innovative-entrepreneurial type. British and French universities have already gained the skill to overcome the difficulties of this transformation. The article written on the unique author’s material summarizes the experiences of several dozens of modern university professors from Europe. It is important to fix the state of affairs and developments in British and French higher education today.
Observations on the effect of retrace error in scanning white light interferometry of smooth optical surfaces

Retrace errors in interferometric measurements is a known phenomenon. The impact of retrace error in stitching CSI measurements is studied, estimates of retrace error in a CSI instrument and methods in correcting it is outlined.
Intelligent Chatbot for Guided Navigation of Repository Contend

Chatbot's are computer application that interact with users using normal language.This technology started in the 1960 and the aim of technology was to see if chatbot systems could fool users that they were real humans.However, chatbot systems are not only built to copy human conversation, and entertain users.In this paper, we examine other applications where chatbots could be useful such as education, information retrival, business, and e-commerceA chatbot aims to make a conversation between human and machine.The machine has been embedded knowledge to determine the sentences and making a decision itself as response to answer a question.The response purpose is matching the input sentence from user.From input sentence, it will be scored to get the similarity of sentences, the higher score obtained the more similar of reference sentences.The sentence similarity calculation in this paper using web application which divides input sentence as two letters of input sentence.The information of chatbot are stored in the database.The chatbot consists of core and interface.The database has been considered as information storage and interpreter has been considered as stored programs of function and procedure sets for pattern-matching requirement.The interface is standalone which has been built using programming language of Java.In our system Natural Language Processing is used.Our system understands content of conversation based on recent Natural Language Processing (NLP).
A learning based approach to additive, correlated noise removal

In this paper, removal of additive, signal-independent, correlated noise from images is considered. We consider the non-blind case, meaning that the stationary autocovariance function of the noise is assumed to be known. The denoising method is based on unrolled optimization where in the half-quadratic energy minimization each proximal step is replaced by a learnt convolutional neural network. The proximal steps take place in learnt transform domains. Functions producing the regularization parameters are also learnt. We assume that we have a distribution for autocovariance functions in order to be able to draw samples. For simplicity, we assume that the noise has low-pass spectral character and a typical autocovariance function has a relatively simple form. The experimental results demonstrate that in terms of PSNR values, the method performs better than two classical methods and a method based on a learnt patch prior.
Two-channel convolutional neural network for facial expression recognition using facial parts

This paper proposes the design of a facial expression recognition system based on the deep convolutional neural network by using facial parts. In this work, a solution for facial expression recognition that uses a combination of algorithms for face detection, feature extraction and classification is discussed. The proposed method builds a two-channel convolutional neural network model in which facial parts are used as inputs: the extracted eyes are used as inputs to the first channel, while the mouth is the input into the second channel. Feature information from both channels converges in a fully connected layer which is used to learn global information from these local features and is then used for expression classification. Experiments are carried out on the Japanese female facial expression dataset and the extended Cohn-Kanada dataset to determine the expression recognition accuracy for the proposed facial expression recognition system based on facial parts. The results achieved shows that the system provides state of art classification accuracy with 97.6% and 95.7% respectively when compared to other methods.
Nauczanie języka obcego w grupie uczniów niewidomych i słabowidzących – przegląd badań

The paper concerns foreign language typhlomethodology and presents an overview of available research findings in the field, arranged in chronological order. The studies discussed in the paper have insight into either first language acquisition or foreign language learning by visually impaired learners. The former shed light on the potential problems the visually impaired might have while learning foreign languages. The problems might emerge both in the phonological or semantic domain. The latter, in turn, discuss such issues as the use of foreign language vocabulary learning strategies and the role of affective factors which facilitate the language learning process. Nowadays the European Union promotes ‘Languages to All’ principle, i.e. teaching languages to all groups of learners, regardless of their disabilities and impairments, preferably in inclusive education setting. Therefore, foreign language teachers should be acquainted with the research findings and their implications presented herein.
Real time data analysis and visualization for the breast cancer disease

Today, the amount of data that are digitally collected in the healthcare sector is tremendous and expanding rapidly, these data are inherently geospatial and temporal ranging from individual families to whole states and from minutes to decades. Therefore, they need sophisticated data management and analysis to be transformed into valuable knowledge. Healthcare professionals are faced with several challenges regarding extracting knowledge from this massive amount of data in order to support the decision-making process. To gain advantage of health care big data, big data analytics need to be exploited to utilize and understand patterns associations within these data thus make the right decision. In this research, an interactive data analysis and visualization tool is proposed to visually compare the performance of three machine learning algorithms on Wisconsin Diagnostic Breast Cancer (WDBC) dataset. The proposed model consists of two phases: input phase and analysis/visualization phase. It aims to allow the user to interactively compare the performance of three different ML algorithms (KNN, SVM and NB) in terms of accuracy, sensitivity and error rate in a user-friendly way. Here, SVM classifier has proven its efficiency and it is concluded as the best classifier with the highest accuracy as compared to the other two classifiers.
MEDIA PERMAINAN TEBAK GAMBAR EFEKTIF DALAM PENINGKATAN PENGETAHUAN DAN TINDAKAN MENYIKAT GIGI DIBANDINGKAN MEDIA BOOKLET

The high number of dental and oral diseases is influenced by the main factors, lack of knowledge about oral hygiene and poor diet. Information about dental health and dental care can be obtained from various media both print media and electronic media. Purpose of this study was to determine the effectiveness of booklet media and picture guessing games to increase knowledge and actions of brushing teeth for students at Padangsari 02 Elementary School Semarang. Study design is a quasi-experimental design with a pre and post test group with two group design. The population of the researchers is students in grades 4 and 5 at Padangsari 02 Elementary School Semarang. Samples were taken by purposive sampling as many as 50 students, divided into two groups, namely 25 students in the booklet group and 25 students in the guessing game group. The data obtained are analyze using Wilcoxon-test and Mann-Whitney test. There was a significance differences with value of p = 0,000 between knowledge and action before and after of both groups. ,The Mann-Whitney Test showed difference in effectiveness between the two media. Game guess images is more effective than booklet with mean rank of game guess images and booklte was 29.27 and 24.25.
Neuromorphic Computing: Artificial Neuron and Synapse Realized in an Antiferromagnet/Ferromagnet Heterostructure Using Dynamics of Spin–Orbit Torque Switching (Adv. Mater. 23/2019)

In article number 1900636, Shunsuke Fukami and co-workers show a uniform approach for the realization of artificial synapses and neurons, which is based on the inherent dynamics of a magnetic heterostructure and thus allows a single material system and simple operating pulses. The proposed devices may form a hardware basis, which is currently lacking, for large-scale artificial neural networks.
CAMERA CALIBRATION WITH IRRATIONAL RADIAL DISTORTION MODEL WITH ANALYTICAL SOLUTIONS

Abstract. Consumer grade digital cameras are widely used in many applications including Photogrammetric mapping and 3D modelling. One common limitation found in such cameras is radial lens distortions. To produce wide angle lenses camera manufacturers reduce the amount of barrel distortion by minimizing both the central and edge distortion profiles, resulting in a mixture of pincushion and barrel distortions for a single lens. These lenses also lack symmetry, making some of the existing distortion models almost ineffective. The mostly used model for radial distortion corrections is the polynomial model which is difficult to solve analytically especially when the model possesses many quadratic terms. Suggestions were made for division models but such models are not suitable when the lens field of view exceeds 180 degrees and exhibit some instabilities when dealing with large magnitude of distortion coefficients. Moreover mathematical formulations of some models cannot handle negative distortion coefficients. Attempts to improve the division models were made with proposals for rational models which present the advantage of handling larger distortion magnitude with fewer terms. However some of these models do not account for all the distortion coefficients in their solutions, limiting the potential of the techniques. This study presents an irrational distortion model with analytical solutions. The proposed model was tested with imagery captured by wide angle lenses and the experimental results reveal that the technique produced the best estimates of radial distortion coefficients. The proposed model was also able to capture image distortions originating from projection errors by the wide angles lenses used in this study.
Probabilistic software product lines

We introduce a probabilistic extension of our previous work SPLA: a formal framework to specify and analyze software product lines. We use probabilistic information to identify those features that are more frequently used. This is done by computing the probability of having a feature in a specific software product line, from now on SPLAP. We redefine the syntax of SPLA to include probabilistic operators and define new operational and denotational semantics. We prove that the expected equivalence between these two semantic frameworks holds. Our probabilistic framework is supported by a set of scripts to show the model behavior. We briefly comment on the characteristics of the scripts and discuss the advantages of using probabilities to quantify the likelihood of having features in potential software product lines.
CapBAC in Hyperledger Sawtooth

In the Internet of Things (IoT) context, the number of connected devices can be too large for a centralised server. This paper focuses on how to enforce authorisation in such a distributed and dynamic environment. The key idea is to use a blockchain-based technology both as a way to maintain a common distributed ledger to store and use access control information, and as a way to enforce Access Control policies in the form of smart contracts. An implementation of an access-control system is presented as a proof of concept: it corresponds to an adaptation of the Capability-based Access Control Model (CapBAC) in the form of a transaction family in Hyperledger Sawtooth. The main claim is that the features and simplicity of CapBAC magnify the usefulness of a blockchain to control the access in the IoT.
NEURON

A core component of a database systems course at the undergraduate level is the design and implementation of the query optimizer in an rdbms. The query optimization process produces aquery execution plan (qep ), which represents an execution strategy for an sql query. Unfortunately, in practice, it is often difficult for a student to comprehend a query execution strategy by perusing its qep, hindering her learning process. In this demonstration, we present a novel system called neuron that facilitates natural language interaction with qep s to enhance its understanding. neuron accepts an sql query (which may include joins, aggregation, nesting, among other things) as input, executes it, and generates a simplified natural language description (both in text and voice form) of the execution strategy deployed by the underlying rdbms. Furthermore, it facilitates understanding of various features related to a qep through anatural language question answering (nlqa ) framework. We advocate that such tool, world's first of its kind, can greatly enhance students' learning of the query optimization topic.
Superpixel Tensor Pooling for Visual Tracking Using Multiple Midlevel Visual Cues Fusion

In this paper, we propose a method called superpixel tensor pooling tracker which can fuse multiple midlevel cues captured by superpixels into sparse pooled tensor features. Our method first adopts the superpixel method to generate different patches (superpixels) from the target template or candidates. Then for each superpixel, it encodes different midlevel cues including HSI color, RGB color, and spatial coordinates into a histogram matrix to construct a new feature space. Next, these matrices are formed to a third order tensor. After that, the tensor is pooled into the sparse representation. Then the incremental positive and negative subspaces learning is performed. Our method has both good characteristics of midlevel cues and sparse representation hence is more robust to large appearance variations and can capture compact and informative appearance of the target object. To validate the proposed method, we compare it with state-of-the-art methods on 24 sequences with multiple visual tracking challenges. Experiment results demonstrate that our method outperforms them significantly.
Different Kinds of Modern Technique to Develop Various Information Systems

Basically, information system design is fundamental to the long-term sustainability of information systems.Information system architecture is a reference in developing and building new information systems if the current system is no longer able to support the activities of an organization or company.There are various information system development methods and there are various information systems architecture models.The choice of using methods and models must be carefully considered so that the information system created is right on target.A variety of techniques will be introduced to enrich knowledge in choosing development methods and architectural models that suit the needs of the organization.