Reviewerly/exHarmony huggingface dataset:
A Nondisturbing Service to Automatically Customize Notification Sending Using Implicit-Feedback

This paper addresses the problem of automatically customizing the sending of notifications in a nondisturbing way, that is, by using only implicit-feedback. Then, we build a hybrid filter that combines text mining content filtering and collaborative filtering to predict the notifications that are most interesting for each user. The content-based filter clusters notifications to find content with topics for which the user has shown interest. The collaborative filter increases diversity by discovering new topics of interest for the user, because these are of interest to other users with similar concerns. The paper reports the result of measuring the performance of this recommender and includes a validation of the topics-based approach used for content selection. Finally, we demonstrate how the recommender uses implicit-feedback to personalize the content to be delivered to each user.
COGNITIVE PERSPECTIVES OF TRANSLATION TEACHING

Based on the principles of psychology's behaviorism, cognition, and humanism, this paper proposes a translational teaching model involving 6 variables: goals, assessments, teachers, students, textbooks, and teaching methods. In addition, the ability level of the translator (primary, intermediate, and advanced) is also included in the translation teaching. This paper also attempts to combine behaviorism (e.g., instructional teaching), cognitivist/constructivism (e.g., Bruner's discovery pedagogy, and Vygotsky's social interactions and the role of scaffolding) and humanism (e.g., cooperation learning or individualized teaching methods). The principles of these teaching concepts will be integrated. This model provides a comprehensive reference architecture for the design of translational instructional courses. Article visualizations:
Verifying and Stubbing Intents with IntentMatchers

Throughout this chapter, we will discuss how to verify and stub application intents. An intent is a messaging object you can use to request an action from another app component. Intents facilitate communication between components in several ways. According to the Android Intent and Filters documentation ( ), there are three fundamental use cases:
Facial Landmarks Detection Using a Cascade of Recombinator Networks

Nowadays, Convolutional Neural Nets (CNNs) have become the reference technology for many computer vision problems, including facial landmarks detection. Although CNNs are very robust, they still lack accuracy because they cannot enforce the estimated landmarks to represent a valid face shape. In this paper we investigate the use of a cascade of CNN regressors to make the set of estimated landmarks lie closer to a valid face shape. To this end, we introduce CRN, a facial landmarks detection algorithm based on a Cascade of Recombinator Networks. The proposed approach not only improves the baseline model, but also achieves state-of-the-art results in 300W, COFW and AFLW that are widely considered the most challenging public data sets.
DEVELOPMENT OF TELEVISION AND VIDEO ENGINEERING

This paper presents the potential of Ultra-High Definition (UD), that has sixteen times the definition of High Definition (HD), cable tv broadcasting. we tend to assume that future audio and video codec technology, viz. H.265, provides or so a twenty fifth bit rate savings for equivalent quality over MPEG-2. concerning 80Mbps is needed per UD service, however this exceeds the technologist capability for a 6MHz channel. Hence, we tend to study the potential of UD transmission via 2 TV channels, to attain each a satisfactory bit rate and threshold of visibility. This paper analyses the background of the procedures to assess video quality. It outlines the methodology to perform valid subjective tests, yet because the basic aspects of objective ways. right along the paper some experiences, resources and tools developed by the VQI Project (http://ingenieria.um.edu.uy/vqi) or given, especially a constant quantity model for digital tv coded with H.264.
FACTORS AFFECTING DIGITAL CUSTOMER EXPERIENCE IN BANKING SECTOR: CASE STUDY ON BANKS IN SAUDI ARABIA

ABSTRACT In today’‘s highly competitive market, differentiation from competitors through banking products and services alone is not possible. Although the bank can continue to innovate but any new product can be quickly imitated. With digital revolution, the digital customer experience becomes a key in engaging with customers; meet the customer needs and wants which will lead to customer satisfaction and their loyalty and thus the banking profitability. The paper identified if there is a gap between customer expectations and actual service perception using digital banking services through the bank electronic channels that leads to customer dissatisfaction and declined digital customer experience problem in Saudi Arabia banks, and figure out the factors influencing this gap, and then recommend solution to close this gap. Keywords Digitalization; Digitization, Digital Transformation; DigitizeTheBank, Customer Experience; Customer Journey; Customer Satisfaction; Customer Expectation; DX; DCX; e-Banking; electronic channels; IoT; SMS; Branch; Big Data; VOC; customer centric; multi ch
Constacyclic Codes over Group Ring (Zq[v])/G

Recently, codes over some special ﬁnite rings especially chain rings have been studied. More recently, codes over ﬁnite non-chain rings have been also considered. Study on codes over such rings or rings in general is motivated by the existence of some special maps called Gray maps whose images give codes over ﬁelds. Quantum error-correcting (QEC) codes play a crucial role in protecting quantum information. The construction of quantum codes via classical codes over 2 F was ﬁrst introduced by Calderbank and Shor [4] and Steane [13] in 1996. This method, known as CSS construction, has received a lot of attention and it has allowed to ﬁnd many good quantum stabilizer codes. Later, construction of quantum codes over larger alphabets from classical linear codes over q F has shown by Ketkar et al. in [10]. One direction of the main research in quantum error correction codes is constructing quantum codes that have large minimum distances [9] for a given size and length. In [14], based on classical quaternary constacyclic linear codes, some parameters for quantum codes are obtained. In [8, 9], respectively based on classical negacyclic and constacyclic linear codes some parameters for quantum MDS codes are presented. In this work, we determine self-dual and self-orthogonal codes arising from constacyclic codes over the group ring(Zq[v]/G
Penerapan Dan Implementasi Sistem Informasi Perpustakaan Berbasis Web Di Perpustakaan Smk Modellink Kabupaten Sorong

Information technology is very responsible in the development of the library world. The role of technology is a computerized information system so as to improve performance to be more optimal. The increase in books and borrowing systems requires better, complete and factual management systems and services. This study aims to build a web-based information system at Modellink Vocational School in Sorong Regency that can be accessed online. The web-based library information system is built using Open Source Software (OSS) web devices using the Circular Library Management System (SLiMS) that supports AJAK (Asynchronous Javaskrip and XML) technology and can be run on Windows or Linux Operating Systems with PHP and MySQL RDBMS. Development of a web-based library information system using the Waterfall Method according to Pressman (2010). The results of this study proved to have been designed Web-based Library Management Information System Application at Modellink Vocational School in Sorong Regency which can be accessed online or offline that produces information about effective and efficient grouping management that makes features of loan transactions, returns, collection reservations, rules flexible lending, information and fines, making membership card membership, inventory management inventory (inventory), reports and statistics, issue management, management of multimedia documents and digital documents such as pdf. Detailed book descriptions are available in XLM (Extensible Markup Language) format for web service needs.
An automated parasite infection diagnostic system via open-source microscopy and deep learning (Conference Presentation)

We report the development of a cost-effective, automated parasite diagnostic system that does not require special sample preparation or a trained user. It is composed of a cost-effective, portable microscope that can automatically auto-focus and scan over the size of an entire McMaster chamber (100 mm2) and capture high resolution (~1 µm) bright field images without need for user intervention. Fecal samples prepared using the McMaster flotation method were imaged, with the imaging region comprising the entire McMaster chamber. A convolutional neural network (CNN) automatically segments and analyzes the images to robustly separate eggs from background debris. The performance of the CNN is high despite the challenging, unbalanced nature of the images, where >95% of images contain no eggs and thus the potential for false-positives is high. Simple post-processing of the CNN output yields both egg species and egg counts. The system was validated by comparing hand counts with automated counts of samples containing eggs from ascarid, strongyle, and Trichuris nematodes, along with Eimeria oocysts. The system shows excellent performance, even on challenging Eimeria parasites whose small size is similar to fecal debris. The R2 values between hand and automated counts are >0.95 for both Eimeria and nematode parasites. Further, the diagnostic accuracy of our system for recommending antibiotic treatment is 100% for nematode parasites and 96% for Eimeria. As a further demonstration of utility, the system was used to conveniently quantify drug response over time, showing residual disease due to antibiotic resistance after 2 weeks.
Detection of online spread of terrorism using web data mining

Terrorist growth has increased in certain parts of the world. Terrorist groups use Facebook, WhatsApp, messages to spread their information on the social network. It is essential to detect terrorism and prevent its spreading before a certain time. The basic idea of this project is to reduce or stop spreading of terrorism and to remove all these accounts. The terrorists are spreading their terrorism activities using the internet by speech, text, videos. Terrorist groups are utilizing the internet as a medium to convince the innocent people to take part in terrorist activities by infuriating people through web pages that inspire disenchanted individuals to take part in a terrorist organization. This needs a lot of human effort to implement this project that will collect the information and find the terrorist groups. To reduce the human effort, we implement the system which detects terrorist groups in social-media
PENGARUH PENERAPAN METODE POSTER COMMENT TERHADAP PRESTASI BELAJAR SISWA DALAM MATA PELAJARAN PEMBIAKAN TANAMAN PADA KELAS X AGRIBISNIS TANAMAN DAN HOLTIKULTURA (AG) DI SMK NEGERI 4 GOWA

The purpose of this class action research was to determine the effect of Poster Comment method on the learning achievement of the X AG class of 4 gowa State Vocational High Schools. This type of research is classroom action research conducted in two cycles. In the first cycle there were two meetings and in the second cycle there were two meetings. The research subjects were all students of class X AG as many as 30 students. Data analysis techniques use quantitative and qualitative data. Based on the results of the study, it can be concluded that the use of Poster Comment method can improve the learning outcomes of class X AG student of State Vocational School 4 Gowa. Improvement of student learning achievement is measured from cycle one evaluation test and cycle two.
The problem of university crisis in modern postindustrial society

The article highlights the main problems of modern post-industrial University education as an element of society and culture. Modern definitions of the University concepts are given, its increasing role in the formation of human capital in a society of high production and consumption is defined. The most dominant problems and ways to solve them are identified, namely: the topical issues of the learning process, the problems of the quality of education and commercialization of universities, the problems of unity and inseparability of education and culture.
Hebbian learning approaches based on general inner products and distance measures in non-Euclidean spaces

The topic of this thesis is to define a unified and generalized scheme for Hebbian approaches in non-Euclidean spaces for unsupervised and supervised learning. This can be realized in different ways. One possibility is the replacement of the inner product by a semi-inner product (SIP). A SIP relaxes the strict properties of an inner product but preserves the linear aspect in the first argument. Thus, these SIPs are natural equivalents of inner products generating Banach spaces instead of Hilbert spaces for inner products. In this work SIPs for Banach spaces are considered for unsupervised Hebbian like learning approaches. Further, the learning scheme of the supervised Learning Vector Quantization (LVQ) network, which is originally designed for applications in Euclidean data space, can be interpreted under specific circumstances as a Hebbian like learning, too. It is shown that, non-Euclidean metrics applied in LVQ can improve the performance of classification learning compared to Euclidean variants. The previously addressed Hebbian learning methods are vectorial approaches. However, if the data space is a vector space of matrices equipped with a respective matrix norm, then matrix approaches for Hebbian like learning methods become of interest. The extension of these methods in non-Euclidean spaces of matrices to process matrix data is the last main point of this thesis.
Comparison of the Influence of Different Normalization Methods on Tweet Sentiment Analysis in the Serbian language

Given the growing need to quickly process texts and extract information from the data for various purposes, correct normalization that will contribute to better and faster processing is of great importance. The paper presents the comparison of different methods of short text (tweet) normalization.  The comparison is illustrated by the example of text sentiment analysis.  The results of an application of different normalizations are presented, taking into account time complexity and sentiment algorithm classification accuracy. It has been shown that using cutting to n-gram normalization, better or similar results are obtained compared to language-dependent normalizations. Including the time complexity, it is concluded that the application of this language-independent normalization gives optimal results in the classification of short informal texts.
Improving Students’ Reading Comprehension By Using Think-Aloud Strategy

The problems of this research is the students are difficult to find the information from the text. The objective of this class action research are: (1) to know how far Think-aloud strategy can improve the students’ reading comprehension and; (2) to know how the process of teaching reading by using Think-Aloud Strategy at eleventh grade of SMK Kartikatama Metro in academic year 2017/2018. The method of this research is clasroom action research that consist of two cycles. The subject of this research is the students of Accounting Class eleventh grade of SMK Kartikatama Metro that consist of 30 students. The research instruments in this research are observation, interview sheets, and test. The result of the data analysis in this research are pre-test until post-test 2 that the average of pre-test was 60.93. Then, the implementation of think-aloud strategy in teaching, there is an increase of 3.65 become 64.58. Then, in the cycle 2 the average of students’ score is 80.17. Based on the teaching and learning activities, pre-test until post-test 2 are increased. From the cycle 2, It is about 80 % of the students can achieve the minimum passing criteria (KKM), so this research is success. The conclusion is the implementation of think-aloud strategy can improve students' reading comprehension.
Adapting RGB Pose Estimation to New Domains

Many multi-modal human computer interaction (HCI) systems interact with users in real-time by estimating the user’s pose. Generally, they estimate human poses using depth sensors such as the Microsoft Kinect. For multi-modal HCI interfaces to gain traction in the real world, however, it would be better for pose estimation to be based on data from RGB cameras, which are more common and less expensive than depth sensors. This has motivated research into pose estimation from RGB images. Convolutional Neural Networks (CNNs) represent the state-of-the-art in this literature, for example [1], [2], [9], [13], [14], and [15]. These systems estimate 2D human poses from RGB images. A problem with current CNN-based pose estimators is that they require large amounts of labeled data for training. If the goal is to train an RGB pose estimator for a new domain, the cost of collecting and more importantly labeling data can be prohibitive. A common solution is to train on publicly available pose data sets, but then the trained system is not tailored to the domain. We propose using RGB+D sensors to collect domain-specific data in the lab, and then training the RGB pose estimator using skeletons automatically extracted from the RGB+D data. This paper presents a case study of adapting the RMPE pose estimation network [2] to the domain of the DARPA Communicating with Computers (CWC) program [3], as represented by the EGGNOG data set [8]. We chose RMPE because it predicts both joint locations and Part Affinity Fields (PAFs) in real-time. Our adaptation of RMPE trained on automatically-labeled data outperforms the original RMPE on the EGGNOG data set.
PEMEROLEHAN BAHASA PADA ANAK USIA TIGA TAHUN

The first three years of a child‟s life is the golden age for a child‟s growth and development. Therefore, this age range became interesting to research the stage of achievement of what works performed by three years old child in terms of language acquisition. The subject of observation, Azra 3 years old with focus on the subject of language development in terms of phonological, syntax, semantics. The reserach found the children three years old mastering the overall sound of the vocal but some sounds diphtongs. In the consonant sounds there are still barries to the sound /r/ and /s/. In terms of syntax, the achievement of children in forming a sentence like: declarative, imperative, interrogative, and complex sentences have resembled an adult sentence, although there are some mistakes that are generally still acceptable. Finally , in terms of semantics subject still have difficulty in understanding the description of time .
Empathic Teaching: Promoting Social Justice in the Contemporary Classroom [Hardback]

Empathic Teaching: Promoting Social Justice in the Contemporary Classroom is written for those who are committed to employing social justice practices in the classroom. The intent is to educate the next generation to value tolerance and to have respect and empathy for others in society. While this tome will largely focus on understanding the role that equity should play in P-12 education, it will do so with an acute awareness that there are myriad factors that influence student engagement and the motivation to learn. Although some of the subjects under consideration have been written about elsewhere broadly, this tome will offer a unique contribution by examining each from a social equity perspective. As schools move to ensure a more inclusive and well-rounded student body, this book will be a substantial asset to anyone interested in advancing a social justice agenda.
Analysis of Attack Techniques on Cloud Based Data Deduplication Techniques

Data in the cloud is increasing rapidly.This huge amount of data is stored in various data centers around the world.Data deduplication allows lossless compression by removing the duplicate data.So, these data centers are able to utilize the storage efficiently by removing the redundant data.Attacks in the cloud computing infrastructure are not new, but attacks based on the deduplication feature in the cloud computing is relatively new and has made its urge nowadays.Attacks on deduplication features in the cloud environment can happen in several ways and can give away sensitive information.Though, deduplication feature facilitates efficient storage usage and bandwidth utilization, there are some drawbacks of this feature.In this paper, data deduplication features are closely examined.The behavior of data deduplication depending on its various parameters are explained and analyzed in this paper.
Metode Multi-Criteria Iterative Forward Search Untuk Penjadwalan Ujian dan Pengawas Ujian

Setting examination schedules to support learning evaluation is crucial.The ideal scheduling for this exam must be able to allocate all related components in the implementation of the test within a predetermined time span.The components of the implementation of an examination in a university include the departments in the faculty, a number of courses and participants, the room used, the time of execution, and the lecturer serving as supervisor.The arrangement of each component of the implementation of the exam needs to be carried out appropriately so there is no collision of the schedule between the participants, the schedule, the room used, and the supervisor in charge.The purpose of this study is to produce an ideal exam scheduling and examination supervisor.The study was conducted by applying the Multi-Criteria Iterative Forward Search from the Academic Information System (SIAKAD) data at the Faculty of Science and Technology, Unisnu Jepara.This research has resulted in a system that is able to create an examination schedule and supervisory schedule that accommodates all factors without conflict, well tested, and applied.
An NC Algorithm for Sorting Real Numbers in O(nlogn/√loglogn) Operations

We apply the recent important results of serial sorting of real numbers in O(n√logn) time to the design of a parallel algorithm for sorting real numbers in O(log1+n) time and O(nlogn/√loglogn) operations. This is the first NC algorithm known to take o(nlogn) operations for sorting real numbers.
Teori Grup Pada Algoritma DES Dan Transformasi Wavelet Diskrit Dalam Program Aplikasi Keamanan Citra Digital

Chryptography or Chriptology plays an important role in building data and information security. Chryptography aims to not read unauthorized people, so information can be safely maintained. Some research about Chryptography and algorithms related to data security have been done by practitioner of informatics and mathematic, one of which is DES algorithms and wavelet transform. DES algorithm is symmetrical standart algorithm which is widely used and is still considered safe to answer th challenges of the rapid development of information technology.This paper have discussed about application of Algebra in DES algorithms and discrete Wavelet Transform On Digital Image Security Application, i.e. XOR operation, permutation, and permutation group or siklik group which is used in DES algorithms on digital image security application. Then, as Group it found (x+b)-group in discrete wavelet transform on digital image security application