Reviewerly/exHarmony huggingface dataset:
Role of WhatsApp in improving learning among medical students

Background: WhatsApp is one of the most famous messaging services which everyone including youngsters use. This service is easy, cheaper, and faster. It is used to transmit information. Slow learners are the students who do not perform well which may be due to disinterest or pressure. The biggest challenge for any teacher is to uplift the slow learners. Objectives: The objectives of this study were to find out the role of WhatsApp in augmenting learning in ENT among the third professional MBBS students. Materials and Methods: Students of the third professional MBBS who use smartphones and have WhatsApp facility and willing to study through WhatsApp along with their regular teaching schedule was identified as slow learners and fast learners depending on their performance in the first semester examinations. All these students were put into a single WhatsApp group and were given assignments that they had to write and submit in JPG format and also upload one latest research article on that topic. After 5 months, the students were analyzed for performance in the second semester examinations and feedback was taken regarding their experience with this study method. Results: Most of the students showed that interest in this method among both slow learners (88%) and fast learners (87%) and felt their knowledge has improved (80% in slow and 77% in fast learners). The overall performance also improved in the second semester examinations. Conclusion: WhatsApp can improve learning, especially among slow learners by creating their interest and improving communication among students. It can motivate and play an augmenting role to traditional learning methods to improve learning.
Tightly Secure Lossy Trapdoor Functions: Constructions and Applications

Lossy trapdoor functions (LTFs), introduced by Peiker and Waters in STOC’08, are functions that may be working in another injective mode or a lossy mode. Given such a function key, it is impossible to distinguish an injective key from a lossy key for any (probabilistic) polynomial-time adversary. This paper studies lossy trapdoor functions with tight security . First, we give a formal definition for tightly secure LTFs. Loosely speaking, a collection of LTFs is tightly secure if the advantage to distinguish a tuple of injective keys from a tuple of lossy keys does not degrade in the number of function keys. Then, we show that tightly secure LTFs can be used to construct public-key encryption schemes with tight CPA security in a multiuser, multichallenge setting, and with tight CCA security in a multiuser, one-challenge setting. Finally, we present a construction of tightly secure LTFs from the decisional Diffie-Hellman assumption.
Exploring and Processing Text Data

In this chapter, we are going to cover various methods and techniques to preprocess the text data along with exploratory data analysis.
STUDI FENOMENOLOGI FILM ANIMASI UPIN DAN IPIN DI MNC TV DALAM MEMBENTUK PERILAKU IMITASI PADA ANAK DI TK AL-MUHIBBIN KECAMATAN SUMBER KABUPATEN CIREBON

ABSTRACT Upin and Upin animation is an animation aired by MNC TV station and produced by Les't Copaque and began airing in 2007 aimed at welcoming the holy month of Ramadan, which airs at 5.00 pm. This animation carries a story to educate children about the meaning and importance of the holy month of Ramadan. Animation Upin and Ipin tell about the world of children full of fun and diversity, all the stories told in animation Upin and Ipin provide education to children about the life of society, togetherness and mutual respect between each other and against the elderly. This animation teaches children to be a better person and always thinking optimistic for the future. Animation Upin and Ipin have many educational aspects for children. The style of the language and the motivation to learn to achieve these goals are potentially imitated or can shape imitation behavior for the child. The purpose of this study are: (1) To find out how the animated film Upin and Ipin that aired on MNC TV; (2) To know the child's behavior in watching Upin and Ipin Animation Movies on MNC TV; (3) And to know what efforts made by parents to accompany their children in watching Upin and Ipin Animated Movies on MNC TV. The research method used is phenomenology study method. The research concept identifies Upin and Ipin animated films aired on MNC TV, to know the behavior of the kindergarten children of AL-Muhibbin Sources when watching the Animation Upin and Ipin films on MNC TV, and to find out what efforts are made by parents to assist his son in watching Animation Upin and Ipin for child's imitation behavior can be controlled with the guidance and assistance of parents. The conclusion of the research on the Phenomenology of Upin and Ipin Animation films in shaping imitation behavior in children is Upin and Ipin Animation has an interesting storyline, tells about the good life of society and tells about the playground of children full of fun. Involvement on Upin and Ipin animation shows among the Kindergarten children AL-Muhibbin Sumber Cirebon relates to time, duration and presentation. Imitation behavior performed by the child including into positive and negative imitation behavior in children, is said to be negative because of the fear of local language refraction (original) which is replaced with the language used in animation Upin and Ipin (Malay) imitation in terms of language style and said positive because animation Upin and Ipin can motivate children in learning and ideas. Parents' efforts to ensure the child's imitation behavior can be controlled by accompanying and guiding the child while watching the Upin and Ipin Animation films. Keywords: Upin and Ipin Animation Movies, Imitation Behavior Formation.
Impact of Requirements Volatility and Flexible Management on GSD Project Success: A Study Based on the Dimensions of Requirements Volatility

Global software development (GSD) is a modern approach that is currently being adopted by software organisations, mainly because of significant return on investment it produces. In the GSD projects, the development teams operate under the three distributed dimensions: geographical, cultural and temporal distances which increases substantial communication difficulties and becomes the development activities more challenging especially related to requirement volatility. The objective of this study is to identify the relationship between requirements volatility, and GSD project success. We have proposed a GSD risk-based model that consider project performance risk as a mediating variable for analysing the impact of requirement volatility on GSD project success. A questionnaire study was conducted from the 103 GSD experts to validate the proposed model. The findings reveal that requirements volatility increases the project performance risk which has a negative impact on the GSD project success which can be managed by the flexible management.
An ICT Tool in a Rural School: A Drawback for Language Students at School?

Technology involves a vast number of advantageous usages that range from the sciences to the educational settings. Limited access to computers and the internet, among other factors, are a drawback, thus, creating a digital gap. Nonetheless, the panorama for English as a Foreign Language (EFL) and the use of internet communication technologies (ICT) in Colombia is promising given the countless number of new resources found online. However, using ICT tools requires not only the teacher’s attention, but also governmental aid before they can be implemented in the EFL class. The scope of the ICT tools in the rural setting is vast and has a great impact on students. Therefore, if factors, such as equipment in decent conditions, updated applications, and training, are not provided the real amplitude of these tools cannot be measured.
A Flight Control System for a Vehicle

The most common problem of a city is its traffic jam in busy and important areas. Nevertheless, ideas have already been pragmatic, traffic jam can’t be controlled completely nor it gets alternative. Vehicles are increasing in the proportion of population growth and technological enrichment. Moreover, road blockage, emergency aspects, armed security purpose etc. are also a fact to be solved now-a-days. Therefore, we have got an idea of overpassing the vehicles so that the road becomes traffic free. After researching various theories with the help of Bernoulli’s principle and duct theory, a new standard flight control system has been visualized. Here, a balanced, portable, comfortable and a universal system with instant flight facility has been introduced, which is more advantageous than quadcopter system. The system can be installed on any existing vehicle with an initial feature of instant flight and forward-backward movement along with left/right turns later. After having a lift, the vehicle can move on the air like a comfortable jerk-less vehicle on the road.
A Probabilistic Model to Support Radiologists’ Classification Decisions in Mammography Practice

We developed a probabilistic model to support the classification decisions made by radiologists in mammography practice. Using the feature observations and Breast Imaging Reporting and Data System (BI-RADS) classifications from radiologists examining diagnostic and screening mammograms, we modeled their decisions to understand their judgments. Our model could help improve the decisions made by radiologists using their own feature observations and classifications while maintaining their observed sensitivities. Based on 112,433 mammographic cases from 36,111 patients and 13 radiologists at 2 separate institutions with a 1.1% prevalence of malignancy, we trained a probabilistic Bayesian network (BN) to estimate the malignancy probabilities of lesions. For each radiologist, we learned an observed probabilistic threshold within the model. We compared the sensitivity and specificity of each radiologist against the BN model using either their observed threshold or the standard 2% threshold recommended by BI-RADS. We found significant variability among the radiologists’ observed thresholds. By applying the observed thresholds, the BN model showed a 0.01% (1 case) increase in false negatives and a 28.9% (3612 cases) reduction in false positives. When using the standard 2% BI-RADS-recommended threshold, there was a 26.7% (47 cases) increase in false negatives and a 47.3% (5911 cases) reduction in false positives. Our results show that we can significantly reduce screening mammography false positives with a minimal increase in false negatives. We find that learning radiologists’ observed thresholds provides valuable information regarding the conservativeness of clinical practice and allows us to quantify the variability in sensitivity across and within institutions. Our model could provide support to radiologists to improve their performance and consistency within mammography practice.
Adaptive Quality Control Scheme Based on VBR Characteristics to Improve QoE of UHD Streaming Service

Recently, with the development of networks and smart devices, the demand for Ultra High Definition (UHD) video has risen, and HTTP adaptive streaming has attracted attention. HTTP adap ...
Probability based Proof Number Search

Probability based proof number search (PPN-search) is a game tree search algorithm improved from proof number search (PN-search) (Allis et al., 1994), with applications in solving games or endgame positions. PPN-search uses one indicator named “probability based proof number” (PPN) to indicate the “probability” of proving a node. The PPN of a leaf node is derived from Monte-Carlo evaluations. The PPN of an internal node is backpropagated from its children following AND/OR probability rules. For each iteration, PPN-search selects the child with the maximum PPN at OR nodes and minimum PPN at AND nodes. This holds from the root to a leaf. The resultant node is considered to be the most proving node for expansion. In this paper, we investigate the performance of PPN-search on P-game trees (Kocsis and Szepesvari, 2006) and compare our results with those from other game solvers such as MCPN-search (Saito et al., 2006), PN-search, the UCT solver (Winands et al., 2008), and the pure MCTS solver (Winands et al., 2008). The experimental results show that (1) PPN-search takes less time and fewer iterations to solve a P-game tree on average, and (2) the error rate of selecting a correct solution decreases faster and more smoothly as the iteration number increases.
Information Theory: Information Theory for Fields (Ann. Phys. 3/2019)

Feynman graph representation of an algorithm based on information field theory to estimate the level of non-Gaussianity in the Cosmic Microwave Background, which is shown in the background. As described by Enßlin in article number andp.201800127, each of the diagrams expresses a term that depends on the data in a non-linear way and has to be evaluated numerically. The terms are combined by addition and division.
Adaptive Ensemble Prediction for Deep Neural Networks based on Confidence Level

Ensembling multiple predictions is a widely used technique for improving the accuracy of various machine learning tasks. One obvious drawback of ensembling is its higher execution cost during inference. In this paper, we first describe our insights on the relationship between the probability of prediction and the effect of ensembling with current deep neural networks; ensembling does not help mispredictions for inputs predicted with a high probability even when there is a non-negligible number of mispredicted inputs. This finding motivated us to develop a way to adaptively control the ensembling. If the prediction for an input reaches a high enough probability, i.e., the output from the softmax function, on the basis of the confidence level, we stop ensembling for this input to avoid wasting computation power. We evaluated the adaptive ensembling by using various datasets and showed that it reduces the computation cost significantly while achieving accuracy similar to that of static ensembling using a pre-defined number of local predictions. We also show that our statistically rigorous confidence-level-based early-exit condition reduces the burden of task-dependent threshold tuning better compared with naive early exit based on a pre-defined threshold in addition to yielding a better accuracy with the same cost.
Elliptical local binary co-occurrence pattern for face image retrieval

Face image retrieval is considered as an active research field in computer vision. This paper describes a novel feature descriptor called elliptical local binary co-occurrence pattern (ELBCoP) for face image retrieval. This descriptor employs a combination of sparse elliptical local binary pattern (ELBP) and grey level co-occurrence matrix (GLCM). Unlike previous approaches, the sparse ELBP consider only 4 horizontal and 4 vertical neighbors from the elliptic shaped neighborhood, and uses 4 simple diagonal neighbors. Then the co-occurrence of pixel pairs, in the three local pattern maps obtained using sparse ELBP, are calculated using GLCM in two selected directions. These two directions of GLCM are selected according to the shape of the elliptic neighborhood. Through GLCM, the proposed ELBCoP extracts the frequency details and also the spatial relationship between the local pattern pairs very effectively. It is also shown that a properly selected subset of ELBCoP can still provide a robust and efficient description of face images, with significant reduction in feature vector dimensions. Experimental results on two benchmark face image databases show superior retrieval performance of ELBCoP and also subset of ELBCoP, when compared to various state of the art methods including a few very recent ones.
Learning URI Selection Criteria to Improve the Crawling of Linked Open Data

As the Web of Linked Open Data is growing the problem of crawling that cloud becomes increasingly important. Unlike normal Web crawlers, a Linked Data crawler performs a selection to focus on collecting linked RDF (including RDFa) data on the Web. From the perspectives of throughput and coverage, given a newly discovered and targeted URI, the key issue of Linked Data crawlers is to decide whether this URI is likely to dereference into an RDF data source and therefore it is worth downloading the representation it points to. Current solutions adopt heuristic rules to filter irrelevant URIs. Unfortunately, when the heuristics are too restrictive this hampers the coverage of crawling. In this paper, we propose and compare approaches to learn strategies for crawling Linked Data on the Web by predicting whether a newly discovered URI will lead to an RDF data source or not. We detail the features used in predicting the relevance and the methods we evaluated including a promising adaptation of FTRL-proximal online learning algorithm. We compare several options through extensive experiments including existing crawlers as baseline methods to evaluate their efficacy.
Periodizing Web Archiving: Biographical, Event-Based, National and Autobiographical Traditions

The purpose of this chapter is to periodize web archiving, in order to discuss four ongoing traditions that form an overlapping and layered history of both the implementation but more so the study and use of archived websites. The most contemporary period of web archiving, as with most recent periods generally, is perilous to characterize, but the self-archiving and selfie culture undertaken most visibly on social media platforms such as Facebook and Instagram appears to sit at the end of a spectrum that commenced with the Internet Archive and preserving single websites, and has witnessed a chronology of efforts that include both event-based as well as national web making. I argue that each of these periods corresponds to a particular historiographical tradition, inviting certain kinds of content-based history-writing with the web archives.
Application of Blockchain Protocol to Wealth Management

Blockchain promises to reduce costs in the front, middle- and back-office operations and increase revenues for the service providers. It also increases product choices and results in higher income for the clients, especially new generations who are technology savvy. Wealth managers would benefit as they succeed in the competitive market against those who do not use the technology. <b>TOPICS:</b>Wealth management, quantitative methods
Lossy Algebraic Filters with Short Tags

Lossy algebraic filters (LAFs) are function families where each function is parametrized by a tag, which determines if the function is injective or lossy. While initially introduced by Hofheinz (Eurocrypt 2013) as a technical tool to build encryption schemes with key-dependent message chosen-ciphertext (KDM-CCA) security, they also find applications in the design of robustly reusable fuzzy extractors. So far, the only known LAF family requires tags comprised of $$\varTheta (n^2)$$ group elements for functions with input space $$\mathbb {Z}_p^n$$ , where p is the group order. In this paper, we describe a new LAF family where the tag size is only linear in n and prove it secure under simple assumptions in asymmetric bilinear groups. Our construction can be used as a drop-in replacement in all applications of the initial LAF system. In particular, it can shorten the ciphertexts of Hofheinz’s KDM-CCA-secure public-key encryption scheme by 19 group elements. It also allows substantial space improvements in a recent fuzzy extractor proposed by Wen and Liu (Asiacrypt 2018). As a second contribution, we show how to modify our scheme so as to prove it (almost) tightly secure, meaning that security reductions are not affected by a concrete security loss proportional to the number of adversarial queries.
New technique for chosen-ciphertext security based on non-interactive zero-knowledge

In this study, we propose a new method for conversion from a one-way (OW)-secure key encapsulation mechanism (KEM) into a chosen-ciphertext (CCA) secure KEM in the random oracle model. Our conversion method is based on the non-interactive zero-knowledge (NIZK) proof system for proving the relationships (e.g., equality or linearity) of discrete logarithms, where the security analysis of our conversion method depends on the NIZK properties of soundness and zero-knowledge. Our conversion method achieves tight security reduction and it is semi-generic in the sense that other than OW-security, a KEM should be NIZK-compatible. From a theoretical viewpoint, our conversion method can be considered as the corresponding approach for obtaining an efficient signature by applying the Fiat–Shamir transform to the NIZK system. We applied our conversion method to several OW-secure (identity-based) KEMs and compared the results with those obtained by previous methods for achieving CCA security.
Vote For Me!: Election Control via Social Influence in Arbitrary Scoring Rule Voting Systems

Online social networks are used to diffuse opinions and ideas among users, enabling a faster communication and a wider audience. The way in which opinions are conditioned by social interactions is usually called social influence. Social influence is extensively used during political campaigns to advertise and support candidates. We consider the problem of exploiting social influence in a network of voters to change their opinion about a target candidate with the aim of increasing his chance to win or lose the election in a wide range of voting systems. We introduce the Linear Threshold Ranking, a natural and powerful extension of the well-established Linear Threshold Model, which describes the change of opinions taking into account the amount of exercised influence. We are able to maximize the score of a target candidate up to a factor of 1-1/e by showing submodularity. We exploit such property to provide a 1/3(1-1/e)-approximation algorithm for the constructive election control problem and a 1/2(1-1/e)-approximation algorithm for the destructive control problem. The algorithm can be used in arbitrary scoring rule voting systems, including plurality rule and borda count.
Reversible Data Hiding Scheme for Video

With the exponential progression in communication technology, advanced mixed media content such as image, sound and video can be effectively duplicated and put away effortlessly without any loss in their original content. Therefore, it is distinctly critical to beat this and the need of a reasonable sort of copyright insurance framework inside the data. Reversible Data Hiding (RDH) keeps up the brilliant property that the first cover can be losslessly recouped after inserted information is separated while securing the picture substance's privacy. This may be liable to a few cause errors on information extraction and image reclamation. We propose to maintain the incredible property that the original cover has which can be losslessly recovered after embedded data is extracted while securing the image content's confidentiality. This strategy protects against different sorts of attacks on the computerized information and hence provides a robust answer for information theft cases.