Reviewerly/exHarmony huggingface dataset:
THE ROLE OF MODERN TECHNOLOGY IN COMUNICATION OF BROKERS AND AGENTS WITH THE INSUREDS

Th anks to today’s digital age, insurance is the one industry that has particularly benefi ted from the advancements in technology. Every customer an insurance broker or agent serves has a diff erent communication want or need. Some customers crave Улога савремене технологије у општењу посредника и заступника са осигураницима 34 personal attention and want to be able to speak with their insurance agents or brokers. Others simply want easy access to information and a way to deliver information that is not stressful or disruptive. For that reason, insurance brokers or agents should use modern technology to off er multiple communication channels. Th is can include websites, mobile devices, social media, remote communication and business process automation as it is pointed out in this article. More people are accessing the Internet on mobile devices than on desktop computers. Insurance agents and brokers should make sure their websites are compatible with most (if not all) mobile devices. Another solution is to create a mobile app to make it easy for consumers to access their sites on the go. Social media for insurance agents and brokers has challenges. However, social media is now critical to the insurance business. Th e rewards they can reap on social media far outweigh the obstacles. Insurance sales and consultations have always been about connection. Brokers and agents make a connection with clients. Th ey discuss catastrophic situations, potential life problems and issues of daily living, making connections in real life. Th e world now requires those connections to be maintained online, especially during the coronavirus crisis. Remote communication is a way of communicating with others online. Meetings, information, and training materials are shared over the Internet. Advanced insurance brokers and agents create virtual teams. Th ey icommunicate and collaborate online and not in a shared offi ce space. Business process automation is the technology-enabled automation of complex business i.e. insurance processes utilized by agents and brokers. It can streamline an insurance business for simplicity, achieve digital transformation, increase service quality to the insureds, improve service delivery or contain costs. Insurance brokers and agents should spend more time interacting with potential customers. Th is includes answering questions and informing them of the important benefi ts of the insurance off ered. Th ey should turn to in-offi ce soft ware that helps them automate these workfl ows.
Penerapan Pendekatan Kontekstual dalam Pembelajaran Keterampilan Menulis Puisi pada Siswa Kelas X SMA PGRI 4 Kota Bogor

This research aimed are to find out Contextual approach in Learning writing poetry and to find out the difficulties on students of X grade SMA PGRI 4 Bogor in writing poetry. Experiment method is used in this research. Data collection are test, questionnaire and observation. Students of X grade SMA PGRI 4 Bogor are population of this research. The sample of this research are experiment and controll class. Experiment treatment is X-2 grade IPA and Controll treatment is and X-1 IPA 2 . To get the data is obtained through Cluster random sampling. The first hyphothesis is implementation of Contextual Teaching and Learning (CTL) which increases writing poetry on students of X grade SMA PGRI 4 Bogor. It can proved based on the students’result of pretest and postest in experiment treatment is used Contextual Teaching and Learning (CTL) that is their improvement. Hyphotesis is students of X grade SMA PGRI 4 Bogor have barrier in writing poetry that is proved. Based on the result of students’ questionnare, they get barrier in writing poetry that is proved based on the 58,33% percentage, they difficult to choose words around 66,67%, then they difficult to choose vocabulary 66,67%, they use the proper and good words 66,67%, they conveys their feeling and idea to write poetry around 62,50%. Therefore, we concluded that Contextual Teaching and Learning (CTL) improves students to write poetry . Either they write poetry or they get barrier to write poetry.
Salvatore Sciarrino’s music at the Beethoven Festival in Bonn: actualization of the classical heritage in conteporary art projects

Problem statement. Contemporary art space creates special conditions for the functioning of the classical musical heritage. The principle of the classics, which results in the formation of certain ideas about the criteria of the “reference” work and the ways of interaction with it undergoes a radical transformation. The turn of the XX and XXI centuries became a time of experiments, including experimental dialogues of the contemporary artists with the classical artistic artifacts. The relevance of the study is due to the growing scientific interest in the specifics of the implementation of contemporary art projects. The scientific novelty of the article is connected with the attempt to analytically comprehend the process of actualization of classical musical works in the conditions of the modern artistic environment. Theoretical Background. In the context of our study, the views of P. Sloterdijk (1986) on the autonomy impossibility of the classical text and the study of U. Eco (1986), focused on the dynamism of the artistic universe of the postmodern era and the multiplicity of its possible interpretations, are recognized as the most essential. Objectives. The purpose of this study is to reveal the specifics of the actualization of classical heritage in contemporary art projects (based on “Quando ci risvegliamo” by S. Sciarrino, presented at the Beethoven Festival in Bonn, 2015). Results and Discussion. The specifics of creative rethinking of L. van Beethoven’s works, done by contemporary European composers (S. Sciarrino, H. Dufourt, V. Tarnopolsky, B. Lang, E. Poppe) during the European cycle of the Beethoven Festival (2015–2019) are analyzed. The content of the multi-layered work “Quando ci risvegliamo” by S. Sciarrino’s is revealed as it is caused by the allusions to Fantasia for piano, soloists, choir and orchestra Op. 80 by L. van Beethoven and the symbolic drama “N&amp;#229;r vi d&amp;#248;de v&amp;#229;gner” (“When We Dead Awaken”) by H. Ibsen. The interaction between the texts takes place on a structural, symbolic and semantic levels. The space of silence on the imaginary border of sleep and awakening, modeled by S. Sciarrino in “Quando ci risvegliamo”, builds cross-cultural connotations, appealing at the same time to the work of the German composer and the Norwegian playwright. Conclusions. The conclusion on the actualization of the classical text in the conditions of the modern art environment at the expense of employment of other classical texts is made. It is noted that the appropriate level of cultural training and experience in perception of artistic texts, expected from the hypothetical recipients, should allow them to perceive the cultural and artistic connotations of the new work, which are included in the hypertext of postmodernism.
Analyzing Task Scheduling Algorithms and Load Balancing Approach to Enhance the Performance of Cloud Computing

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Pelatihan Dan Pendampingan Sistem Informasi Manajemen Di Era New Normal

Bali has a charm nature, unique culture that captivated the hearts of foreign tourists and domestic to visit. Since the pandemic covid-19 struck the world, economic growth in Bali the year 2020 has decreased, because one of the economic incomes of the business sector tourism. Efforts The government Bali restore the economy, turn on the micro, small and medium Enterprises (SMES). Peken Facebook is the SMES take the opportunities businesses trading through online networks and social media that continues to innovate using digital technology in the pandemic covid-19. Based on observation and interview found a weakness, the absence of application of Management Information System (SIM) the better. The purpose for apply SIM in the running of the operational business Peken Facebook so the quality of services increased as well as customer satisfaction achieved. Methods the activities of socialization, provides training and the practice of direct application of SIM and mentoring. The results of the activity show the high enthusiasm of the participants, Peken Facebook apply SIM in the running of their business operations to support service activities to meet the needs of the consumer. Conclusion, the service is done to increase the quality of human resources and partnerships, understand the concept of SIM as well as can give the satisfaction of consumers. Advice, Peken Facebook expected can apply the SIM properly, perform the evaluation in accordance with the development of market conditions so that it can create, innovate, following the development of better technology, particularly in terms of the provision of excellent service to the consumer.
A Comparative Analysis of Four Distinct Types of Searching Algorithms in Data Structure

Basically searching algorithms are used to search or find one or more than one element from a data set. Apparently there are a lot of searching algorithms. But here our research intends to demonstrate an overview of comparison between four different types of searching algorithms. We have tried to cover some part of binary search, linear search, hybrid search, and jump search. This research renders a detailed comparison view of four distinct searching algorithms.
Feasibility on accurate measurement of non-uniform strain field through contact methods

When straight material filaments do not remain straight after deformation, the strain varies spatially. These spatially varying strain fields arise because of (1) non-uniform distribution of boundary traction, (2) presence of residual stress in the reference configuration, (3) the body being inhomogeneous. The strain measured using devices such as extensometer and strain gauge assumes that the strain is uniform over the gauge length, irrespective of the strains actual variation. Here the accuracy of the strain estimated using contact strain measurement techniques is investigated by assuming that the uniaxial strain (not stress) varies periodically along the measurement axis. A tight bound for the error in the measured strain is obtained and verified through numerical simulation. This study’s significant finding is that for gauge length of strain measurement about two times the periodicity of the strain variation, the measured strain’s value would be repeatable but with a significant error. Thus, one has to be cautious about the magnitude of the estimated non-uniform strain.
SANDI: Story-and-Images Alignment

The Internet contains a multitude of social media posts and other of stories where text is interspersed with images. In these contexts, images are not simply used for general illustration, but are judiciously placed in certain spots of a story for multimodal descriptions and narration. In this work we analyze the problem of text-image alignment, and present SANDI, a methodology for automatically selecting images from an image collection and aligning them with text paragraphs of a story. SANDI combines visual tags, user-provided tags and background knowledge, and uses an Integer Linear Program to compute alignments that are semantically meaningful. Experiments show that SANDI can select and align images with texts with high quality of semantic fit.
Implementing AMETTA (Active, Joyful, and Unstressed) in Increasing Learning Activity and Outcomes

This research aims to analyze the learning model's practice and its effect on increasing student activity and learning outcomes in listening subjects. This study employed quasi-experimental research with a non-equivalent control group design. The data were gained using observation and tests. It is analyzed by reflection and statistical test of SPPS. The results show that the application of the AMETTA learning model effectively develops student learning activities and outcomes. The result of hypothesis testing with sig. (2-tailed) was 0.033 (˂ 0.05) It indicates that Ho is rejected. Thus, there is a significant difference between the average student learning outcomes in the experimental and control classes. In other words, the application of AMETTA learning model has a significant effect on students’ learning outcomes.
Towards Human-Centered Summarization: A Case Study on Financial News

Recent Deep Learning (DL) summarization models greatly outperform traditional summarization methodologies, generating high-quality summaries. Despite their success, there are still important open issues, such as the limited engagement and trust of users in the whole process. In order to overcome these issues, we reconsider the task of summarization from a human-centered perspective. We propose to integrate a user interface with an underlying DL model, instead of tackling summarization as an isolated task from the end user. We present a novel system, where the user can actively participate in the whole summarization process. We also enable the user to gather insights into the causative factors that drive the model’s behavior, exploiting the self-attention mechanism. We focus on the financial domain, in order to demonstrate the efficiency of generic DL models for domain-specific applications. Our work takes a first step towards a model-interface co-design approach, where DL models evolve along user needs, paving the way towards human-computer text summarization interfaces.
Selection of Malay Language Reading Material Based on Readability Factors

In this paper the author discuss the methods that can applied to select reading material that is appropriate to the reading ability of students. The old assumption that books or materials that written for a certain level is appropriate for all students in that particular level, needs to be changed. This is because students who isin a certain level have different reading abilities. Therefore, this paper will introduce the understanding of readability factors as one way of selecting appropriate reading material for students. The level of readability for reading materialsare influenced by a variety of factors, including the reader, environment and reading material. This article focuses on reading material factors such as clear font size and style, illustration and colour, vocabulary and sentence structure. Further, this article will present text difficulty analysis through the analysis of vocabularies. This paper conclude that vocabulary factor should not be overlooked and teachers must understand this because reading materials can be difficult when vocabulary that appear in the reading material does not fit to the level of the reader.
Penerapan Face Recognition pada Aplikasi Akademik Online

In the era of big data, the biometric identification process is growing very fast and is increasingly being implemented in many applications. Face recognition technology utilizes artificial intelligence (AI) to recognize faces that are already stored in the database. In this research, it is proposed to design an online academic login system at the National University using real time face recognition used OpenCV with the Local Binary Pattern Histogram algorithm and the Haar Cassade Classification method. The system will detect, recognize and compare faces with the stored face database. The image used is 480 x 680 pixels with a .jpg extension in the form of an RGB image which will be converted into a Grayscale image., to make it easier to calculate the histogram value of each face that will be recognized. With a modeling system like this it is hope to make it easy for user to log into online academics.Keywords:Face Recognition, Haar Cascade Clasifier, Local Binary Pattern Histogram, Online Akademic, OpenCV.
Analyzing the Domain Robustness of Pretrained Language Models, Layer by Layer

The robustness of pretrained language models(PLMs) is generally measured using performance drops on two or more domains. However, we do not yet understand the inherent robustness achieved by contributions from different layers of a PLM. We systematically analyze the robustness of these representations layer by layer from two perspectives. First, we measure the robustness of representations by using domain divergence between two domains. We find that i) Domain variance increases from the lower to the upper layers for vanilla PLMs; ii) Models continuously pretrained on domain-specific data (DAPT)(Gururangan et al., 2020) exhibit more variance than their pretrained PLM counterparts; and that iii) Distilled models (e.g., DistilBERT) also show greater domain variance. Second, we investigate the robustness of representations by analyzing the encoded syntactic and semantic information using diagnostic probes. We find that similar layers have similar amounts of linguistic information for data from an unseen domain.
Optical homogeneity measurement of parallel plates using nonuniform fast Fourier transform based on low-rank approximation and Taylor expansion

When the optical homogeneity of parallel plates is measured using wavelength phase shifting interferometers, the nonlinearity of phase shifts caused by nonlinear wavelength tuning results in spectrum aliasing, and thus the optical homogeneity cannot be obtained accurately. We propose a nonuniform fast Fourier transform algorithm based on low-rank approximation and Taylor expansion (LRTE-NUFFT) to solve the problem. The principle of the LRTE-NUFFT method is introduced and compared with the FFT method and the nonuniform fast Fourier transform algorithm based on fast Gauss gridding (FGG-NUFFT) method proposed earlier through simulations and experiments. The results show that LRTE-NUFFT can improve the accuracy of the optical homogeneity measurement of parallel plates compared with the FFT method, and it can also improve the computational efficiency compared with the FGG-NUFFT method.
Chroma Key Enhance Students’ Verbal Participation During Form One English Language Lesson

Technology in the ESL classrooms is not something new.Using Chroma Key helps in making lesson more interactive, enjoyable and interesting.With the combination of physical and virtual technology, Chroma Keyorfrequently known as GreenScreen,creates a platformformeaningful learning. This study reveals how the use of Chroma Keyempowersa class of Form One, lower secondary school students to accomplish tasks and provides a comfortable environment to enhance students’ verbal participationsduring ESL lesson in Malaysia.
Software and hardware infrastructure of a terrestrial autonomous platform with the elements of artificial intelligence.

Due to modern microcomputers and platforms based on microprocessors such as, for example, Raspberry Pi, Orange Pi, Nano Pi, Rock Pi, Banana Pi, Asus Tinker Board – the development of prototypes of em-bedded systems is possible in a «design» mode. The software part is implemented on the basis of operat-ing systems and standard technologies based on well-known programming languages such as C / C++, Python, C#, Java, etc. In such case the control channel for the embedded system can be either imple-mented via a web service separated by a communication channel or controlled independently. It is im-portant to understand that creating an embedded system on a standard platform is much more expensive than buying a ready-made mass-produced device with the same functionality. Therefore, it makes sense to use platforms like the Raspberry Pi mainly for individual artificial devices. If it is necessary to build a project of embedded systems and there is a problem with choosing a hardware platform for the client side, then currently there is a wide range of boards and solutions for building an efficient and inexpen-sive system using ready-made modules. The number of expansion cards and various sensors, video cam-eras, internet connection via Ethernet, Wi-Fi and Bluetooth provides a wide range of opportunities for building almost any solution based on this component base. The foundation can be made within a small budget, with minimal time spent, using large blocks and ready-made libraries for programming embed-ded systems. This article presents the results of research and development work on the creation of a software and hardware infrastructure of a terrestrial platform with the elements of artificial intelligence. Based on the actual results of the research, a deployment diagram and a component diagram of such an infrastructure have been constructed.
Fine-tuning Distributional Semantic Models for Closely-Related Languages.

In this paper we compare the performance of three models: SGNS (skip-gram negative sampling) and augmented versions of SVD (singular value decomposition) and PPMI (Positive Pointwise Mutual Information) on a word similarity task. We particularly focus on the role of hyperparameter tuning for Hindi based on recommendations made in previous work (on English). Our results show that there are language specific preferences for these hyperparameters. We extend the best settings for Hindi to a set of related languages: Punjabi, Gujarati and Marathi with favourable results. We also find that a suitably tuned SVD model outperforms SGNS for most of our languages and is also more robust in a low-resource setting.
On the Strengths of Cross-Attention in Pretrained Transformers for Machine Translation.

We study the power of cross-attention in the Transformer architecture within the context of machine translation. In transfer learning experiments, where we fine-tune a translation model on a dataset with one new language, we find that, apart from the new language's embeddings, only the cross-attention parameters need to be fine-tuned to obtain competitive BLEU performance. We provide insights into why this is the case and further find that limiting fine-tuning in this manner yields cross-lingually aligned type embeddings. The implications of this finding include a mitigation of catastrophic forgetting in the network and the potential for zero-shot translation.
BERT-based Multi-Task Model for Country and Province Level MSA and Dialectal Arabic Identification

Dialect and standard language identification are crucial tasks for many Arabic natural language processing applications. In this paper, we present our deep learning-based system, submitted to the second NADI shared task for country-level and province-level identification of Modern Standard Arabic (MSA) and Dialectal Arabic (DA). The system is based on an end-to-end deep Multi-Task Learning (MTL) model to tackle both country-level and province-level MSA/DA identification. The latter MTL model consists of a shared Bidirectional Encoder Representation Transformers (BERT) encoder, two task-specific attention layers, and two classifiers. Our key idea is to leverage both the task-discriminative and the inter-task shared features for country and province MSA/DA identification. The obtained results show that our MTL model outperforms single-task models on most subtasks.