Reviewerly/exHarmony huggingface dataset:
Priority Analysis of Right Remedies of Basic Living Recipients in Korea

Through an active administration approach, the Local Living Security Commission (LLSC) has provided relief to protect the poor strata and reinforce the distribution of entitlements. However, the absence of a system to monitor operational performance makes it difficult to manage it efficiently. The purpose of this study is to find ways to strengthen and efficiently operate the functions of the LLSC through priority analysis of its operation. To this end, the analytic hierarchy process (AHP) was conducted based on the results of the focus group interview to derive priorities for the operation of the LLSC. The variables used in the AHP analysis included regional conditions, operational performance, organizational method, and network. The result of the analysis revealed, first, that the performance of the committee has increased due to a joint evaluation or verification survey conducted at the end of each year, second, that the creation of a budget for the organization and the operation of an independent LLSC is necessary, and third, that operational performance is the most important, followed by organizational method, network, and regional conditions. Therefore, a system for monitoring performance should be established to improve the operation performance of the LLSC. Additionally, it is necessary to establish an independent LLSC and secure the budget for each city and county. It should be possible to provide feedback on operations through regular priority analysis.
A Chinese Text Synthesis Method Based on Word Order Rules

Chinese language processing is a basic subject in Natural Language Processing (NLP). The analysis of Chinese sentences is a difficult point and a research focus in this field. We propose a method for Chinese text analysis and synthesis based on the word part-of-speech(POS) and the priority of the word order rules. Experiment results show that the proposed method is effective for language synthesis.
Automatic Classification of Community Question Answer (CQA) for Non Factoid Queries

Owing to the steep increase in the Internet population, the content over the web is increasing exponentially so as Community Question Answer (CQA) have acquired very huge amount of questions and answers. In this article, a machine learning algorithms are utilized for Question Classification (QC) and Answer Classification (AC). We identify the category of the question posted and further map with the corresponding question. Similarly for the answers posted by the multiple user will be processed for category mapping. Here the result shows the effective classifier that can be chosen to perform the mapping task for both Question classifier as well as answer classifier. Here the results shows that, for Question Classification (QA), Linear Support Vector Classification (LSVC) is found to be best classifier and Multinomial Logistic Regression (MLR) is most suitable for Answer Classification (AC). Using the probability of overall possible outcomes of a particular answer will give a best answer. Experiments results shows that our method outperforms efficiently.
Il “concepito”: questo sconosciuto...

The “conceived” does not enjoy a clear legal status yet. In theory, human life deserves protection in every single step of its development: before-and-after birth and near-to-death. Practically, the condition of the ‘conceived’ ought to be ‘balanced’ with other constitutional relevant individual or general interests. While the evaluation of statute no. 194/1978, notwithstanding its flaws, is overall positive, many doubts and questions arise from the amazing genetic techniques known as CRISPR-Cas9, whose developments for the future generations have still to be certified.
Technological Education, Training and Process Identity

The paper presents the results of the analysis of technological education, namely the identification of educational technology and the technological process. It was found that most major technology creators transform both their ideas and their techniques into modern technological operations as well as educational technologies. The authors propose that the training process may be regarded as technological in nature and the one that embraces the same methods of analysis (including activity approaches). In other words, the analysis of the educational process is identical to the analysis of technological process. In methodological terms, the closest to that step sequence is project-based learning. The conclusion is reached by drawing on the analysis of training processes in general and on the analysis of operational training in particular including the step-by-step performance of certain technological operations.
THE LEARNING OF PRODUCING SHORT-STORY TEXT USING PROBLEM-BASED METHODS FOR HIGH SCHOOL STUDENTS

This research was conducted using descriptive methods. Where researchers will describe the work of students to get more detailed results. Before the research was conducted, the pretest was first held to find out more about where the students' ability was about producing short text. After that learning is done by applying the problem-based method, and ends with the posttest as a method of proving that effectiveness. The results showed that after learning to produce short text using this problem method, the ability of students to produce short stories increased. This is evidenced by the achievement of learning objectives and improved student learning outcomes. The increase can be seen from the results of the comparison of the average pretest is 56,5 and the average postest score is 69.2. Thus the posttest average is higher than the average pretest.
Sentence Generation from IMU-based Human Whole-Body Motions in Daily Life Behaviors

This paper presents a probabilistic approach to-ward integrating human whole-body motions with natural language. Human whole-body motions in daily life are recorded by inertial measurement units (IMU) and subsequently encoded into motion symbols. Sentences are manually attached to the human motion primitives for their annotation. Two aspects of semantics and syntactics are represented by probabilistic graphical models. One probabilistic model trains the linking of motion symbols to words, and the other model represents sentence structure as word sequences. These two models are useful toward translating human whole-body motions into descriptions, where multiple words are associated from the human motions by the first model, and the second model searches for syntactically consistent sentences consisting of the associated words. The proposed approach was tested on a large dataset of human whole-body motions and sentences to annotate these motions. The linking of human motions to natural language enables robots to understand observations of human behavior as sentences.
Discussion, Conclusions and Future Work

This chapter contains discussion on results of the research and future work that could be conducted to improve functionality, optimize design and facilitate industrial deployment of the robotic system for pipeline inspection.
Fostering Readers: Addressing the Knowledge Gap for Serving Beginning Readers

"How do we support children who have aged out of our 0–5 storytimes?"With the introduction of great resources like Every Child Ready to Read and Babies Need Words Every Day, this question popped up more and more in electronic mailing lists, social-media groups, and in-person chats. The truth is, library staff all over the map are doing some really great things for emerging readers in kindergarten and beyond. This question says more about youth library staff’s desire for the confidence that research-based activities can equip us with than our actual ability to work with this age group.
A Socio-pragmatics Study: Flouting of Conversational Maxims Found in “Bence” Traditional Market, Kediri

The study focuses on the flouting of conversational maxims in one of the traditional markets in Kediri. This study focuses on the types of flouted maxims, and the situations where the flouted maxims cause misunderstanding between the sellers and the buyers in the trade of interaction.&#x0D; This research is conducted by using a descriptive qualitative approach. The data are utterances between sellers and buyers. The theory which the writer used is based on the theory of Cooperative Principles, proposed by Grice (1975), which establishes four maxims, those are the maxim of quality, the maxim of quantity, the maxim of relation and maxim of manner. The data is collected by recording the conversation in the trade transaction. The data is also collected by noting the conversation and transcript it. &#x0D; The finding shows that there are many flouted maxims found in interaction practices between the seller and buyer. The writer’s analysis show that all kinds of maxims are flouted mostly buy the seller. Those are maxim of quantity, maxima of quality, maxims of relevance and maxim of manner. Thus, it may happen because between the seller and the buyer do not fulfil the rules of cooperative principles. The writer concludes there are some condition which make the participants in the trade interaction have to flout the maxims. Due to the fact that the conversation still run well without any misunderstanding.
Correlated Matrix Factorization for Recommendation with Implicit Feedback

The implicit feedback primarily recommendation problem once solely the user history is offered however there aren't any ratings—is a far tougher task than the express feedback based recommendation problem, thanks to the inherent uncertainty of the interpretation of such user feedbacks. Recently, implicit feedback drawback is being received additional attention, as application oriented analysis gets additional engaging at intervals the sphere. This paper focuses on a typical matrix factorisation methodology for the implicit drawback and investigates if recommendation performance is improved by applicable data format of the feature vectors before coaching. we tend to gift a general data format framework that preserves the similarity between entities (users/items) once making the initial feature vectors, wherever similarity is outlined mistreatment e.g. context or data. We tend to demonstrate however the planned data format framework is in addition to radio frequency algorithms. We tend to experiment with numerous similarity functions, totally different context and data primarily based similarity ideas. The analysis is performed on 2 implicit variants of the MovieLens 10M dataset and 4 world implicit databases. We tend to show that the data format considerably improves the performance of the radio frequency algorithms by most ranking measures.
TriDepth: Triangular Patch-based Deep Depth Prediction

We propose a novel and efficient representation for single-view depth estimation using Convolutional Neural Networks (CNNs). Point-cloud is generally used for CNN-based 3D scene reconstruction; however it has some drawbacks: (1) it is redundant as a representation for planar surfaces, and (2) no spatial relationships between points are available (e.g, texture and surface). As a more efficient representation, we introduce a triangular-patch-cloud, which represents the surface of the 3D structure using a set of triangular patches, and propose a CNN framework for its 3D structure estimation. In our framework, we create it by separating all the faces in a 2D mesh, which are determined adaptively from the input image, and estimate depths and normals of all the faces. Using a common RGBD-dataset, we show that our representation has a better or comparable performance than the existing point-cloud-based methods, although it has much less parameters.
The Effect of Internal Audit on Accounting Information Technology in the Public Joint Stock Pharmaceutical Industries in Jordan

This study aims to find out the effect of internal audit in public joint stock pharmaceutical industries sector of technology. This study found that there is a statistically significant effect of the internal audit on information technology of public joint stock pharmaceutical industries sector. There is also a statistically significant effect of the internal audit on the efficiency of reliance on information of public joint stock pharmaceutical industries sector. One of the most important recommendations of the researcher was to oblige all sectors to activate the role of internal audit in each sector.
Paper Minds: Literature and the Ecology of Consciousness. by Jonathan Kramnick

Jonathan Kramnick’s Paper Minds meditates on how literary forms give shape to experience and what they tell us about our ‘transaction’ (p. 5) with lived environments. These connected essays defending literary value and method are unapologetic close readings of literature’s trans-historical affinities and elegant take-downs of interdisciplinarity for its own sake. They model how embodied perception, the written line, and the physical world intersect. Kramnick uses the term ‘ecology’ to indicate this interchange between mind and matter. He draws on psychology, philosophy, and cognitive and literary studies to broach thinking and writing as active ‘skilled coping’ (p. 12) and to stress that singular definitions of form and consciousness are insufficient. Paper Minds reminds us that openness to uncertainty is integral to insightful scholarship. The book consists of three parts. In ‘On Method and the Disciplines’ (Part I), Kramnick’s discussion of reductive interdisciplinarity leads into his and Anahid Nersessian’s essay suggesting...
The Pathology of Iran's Position in Global Doing Business Ranking According to General Policies

The World Bank annually ratings "Doing Business" in terms of improving the business environment of 190 countries, surveying private sector activists in each country, indicating ease of starting, maintaining and expanding business. The overall policies of the system, such as employment general policies, general policies of national production, support for the Iranian labor and capital, and Sixth Development Plan General Policies have emphasized the improvement of business conditions and the promotion of Iran's position. In this regard, this paper, by documentary method and based on World Bank's 2020 Doing Business Report, Iran's position in each of its sub-indices and components is compared with the first world countries and region in the same sub-index. Based on the results of the research, it was found that the major problem of Iran is related to the time and the number of stages of obtaining business licenses and the legal force of business rights. Based on the results of the research ، the proposed strategies are presented in two areas: reduction of administrative bureaucracy and legal changes.
Interjection Bah! in Batak Toba: A natural semantic metalanguage approach

Interjection is the word used to show spontaneous expression. Batak language has a specific emotive interjection Bah! which is different from other interjections in the language. The objectives of this study are to find the meanings of interjection Bah! and to classify the elements of feelings of this interjection. This is a descriptive qualitative study employing the semantic explication method of the Natural Semantic Metalanguage approach. The data was collected from the interjection Bah! in a Batak Toba short story entitled Mangongkal Holi. The data were obtained by the attentive observation method and tapping technique. The methods used for data analysis were the distribution and contextual method. The results of this study showed that there are five meanings of the interjection Bah! They are astonishment, disappointment, confusion, surprise, and amazement. Meanwhile, those meanings express two elements of feelings, which are the positive feeling element (i.e. surprise and amazement), and the negative feeling element (i.e. astonishment, disappointment, and confusion). The revelation of the various meanings of Bah! is expected to provide richer understanding on its use in communication, and to further avoid miscommunication between different ethnics in Indonesia which each has their own mother tongue.
Incorporating Temporal Information for Recommendation in Heterogeneous Information Network

Heterogeneous information network is a better representation of various types of data, which has been successively applied to many fields. It provides a promising way to deal with data sparsity problem and improves the quality of recommendation. But current HIN-based recommendations ignore the time attributes on the relationships and fail to capture the dynamic changes of users' preference. In this paper, we use the temporal information to enhance the recommendation quality in HIN. Firstly, we propose the concepts of time-weighted HIN and extend the relevance measurement of time-weighted meta-path by designing a time deviation matrix. Then, SVD matrix factorization is applied to generate the latent features of each meta-path. To better assemble recommendations from different meta-paths, we propose a new weight learning approach called complementary combination (CC). Experiments on Movielens100K dataset illustrate the improvement of our work.
LIBRARY AS AN OPTIMAL MODEL OF INTERACTION WITH USERS IN THE CONDITIONS OF THE DIGITAL ECONOMY

The experience of the Regional Universal Scientific Library of Pskov as part of the ecosystem of the regional digital economy is presented. The essence of the problem is to create a new library digital model for to implement the national project «Culture». For Pskov specialists, digitalization is a catalyst for the development of library innovations. It brings about many opportunities. In particular, understanding how to use digitalization tools to increase readers’ activities and involvement, how to develop library specialists in the digital environment and how to attract investments for SMART projects implementation. The author dwells on such problems as an optimal portfolio of digital library projects’ development and implementation, which consists of digitizing book rarities, including them in the electronic full-text library «Pskoviana» and the National Electronic Library; organization of a free accessible online service for continuous informing and consulting both specialists and the people at large using the official library website and information resources; motivation and facilitation of assistance to Pskovians in mastering key competencies of the digital economy; formation and promotion of the library website as a digital third place digital. The author describes in detail the scenario for moving to the digital economy, developed in 2018 and including five directions: information and telecommunication infrastructure; information security; digital supervision and elimination of information and digital illiteracy of users; monitoring the operational readiness of various groups and categories of the Pskov region population for life and work in the digital economy environment; library staff for the digital economy. Specialists have formed a portfolio of digital projects for the near future and built a system for monitoring the economic and social effectiveness of projects, which has showed that among the library users the level of involvement in the consumption of digital information and online communications has grown; a digital information-enlightenment and intellectualleisure ecosystem has been created. A new social reality has developed, based on wide access to former exclusive goods and values.
PENGEMBANGAN GAMEEDUKASI TAJWID MENGGUNAKAN ADOBE FLASH CS6 PADA MATERI AHKAMUL HURUF KELAS IV SEKOLAH DASAR

The main problem of this research is the learning of Al-Quran education in Elementary Schools which only uses conventional media, and the lack of varied use of media. This results in a lack of interest and interaction of students in following the learning process. The purpose of this research is to produce a valid and practical learning media. This research uses a development research method that is a process or steps to develop a new product or improve existing products, which can be accounted for. The research development design and procedures used are 4-D models, namely define, design, develop and disseminate. This research did not carry out the disseminate stage. The research instrument used questionnaire validation sheets and response questionnaires. Based on the results of research that has been done, categorized games are very valid with a percentage value of 93.75% and practical with an index value of 92%. It can be concluded that this game can be used as a learning medium for Al-Quran Education and help students understand the material of the letters ahkamul.
Edge-Tailored Perception: Fast Inferencing in-the-Edge with Efficient Model Distribution.

The rise of deep neural networks (DNNs) is inspiring new studies in myriad of edge use cases with robots, autonomous agents, and Internet-of-things (IoT) devices. However, in-the-edge inferencing of DNNs is still a severe challenge mainly because of the contradiction between the inherent intensive resource requirements and the tight resource availability in several edge domains. Further, as communication is costly, taking advantage of other available edge devices is not an effective solution in edge domains. Therefore, to benefit from available compute resources with low communication overhead, we propose new edge-tailored perception (ETP) models that consist of several almost-independent and narrow branches. ETP models offer close-to-minimum communication overheads with better distribution opportunities while significantly reducing memory and computation footprints, all with a trivial accuracy loss for not accuracy-critical tasks. To show the benefits, we deploy ETP models on two real systems, Raspberry Pis and edge-level PYNQ FPGAs. Additionally, we share our insights about tailoring a systolic-based architecture for edge computing with FPGA implementations. ETP models created based on LeNet, CifarNet, VGG-S/16, AlexNet, and ResNets and trained on MNIST, CIFAR10/100, Flower102, and ImageNet, achieve a maximum and average speedups of 56x and 7x, compared to originals. ETP is an addition to existing single-device optimizations for embedded devices by enabling the exploitation of multiple devices. As an example, we show applying pruning and quantization on ETP models improves the average speedup to 33x.
Artificial photonic neural networks (Conference Presentation)

Software-implementation of brain-inspired computing approaches underlie many important modern-day computational tasks. Yet, traditional computing architectures physically separate the core computing functions of memory and processing. I will present an all-optical approach to overcome these restrictions by developing photonic spiking neurons interconnected via an integrated photonics network to photonic synapses. I will present our results in scaling to multi-element circuits and report on their optical performance in pattern recognition and data storage. Photonic implementations give access to the speed, bandwidth and power improvements inherent to optical systems, which will be attractive for the direct processing of data in the optical domain.
Applications in syntax analysis: natural languages

Syntactic analysis of natural languages is a subfield of natural language processing (NLP) that is often claimed to be a “corner stone” of the area, a necessary base for any advanced language processing and real understanding. we describe the syntax analysis of programming languages by using classical language models context -free grammars and pushdown automata. In the present chapter, however, we sketch the syntax analysis of natural languages based upon alternative grammatical models namely scattered context grammars.we have illustrated how to transform and generate grammatical sentences in English by using transformational scattered context grammars, which represent a very natural linguistic apparatus straightforwardly based on scattered context grammars. However, from a more general perspective, we can apply these grammars basically in any area of science that formalizes its results by strings containing some scattered context dependencies.