Reviewerly/exHarmony huggingface dataset:
A Self-adaptive Differential Evolution with Fragment Insertion for the Protein Structure Prediction Problem.

This work presents four hybrid methods based on the Self-adaptive Differential Evolution algorithm with fragment insertion applied to the protein structure prediction problem. The protein representation is the backbone torsion angles with side chain centroid coordinates. The fragment insertion is made by the Monte Carlo algorithm. The hybrid methods were compared with recent and compatible methods from the literature, where two proposed approaches achieved competitive results. The results have shown that using parameter control and fragment insertion greatly improves the results of the prediction when compared to fragment-less methods or without parameter control. Furthermore, an extra analysis was conducted using GDT-TS and TM-Score metrics to better understand the results obtained.
Klasifikasi Penentuan Penerima Program Keluarga Harapan (PKH) Menggunakan Algoritma Support Vector Machine (Svm) Pada Kantor Dinas Sosial Lombok Timur

The Family of Hope Program (PKH) is a program of giving cash to Very Poor Households (RTSM) based on established terms and conditions. Where PKH was implemented in Indonesia in 2007, but in East Lombok PKH was only implemented in 2011. However, judging from the data of PKH recipient members, there are still many RTSM who do not get the PKH assistance. This situation identified the data collection method and the determination of priorities that were not yet on target. From these problems, it is necessary to utilize data mining techniques using the support vector machine (SVM) algorithm in determining PKH recipients. After testing 4 times using different K-Fold Validation on the cross validation operator. K-Fold Validation functions to divide the amount of training data and testing data on the data being tested. Then the accuracy results that have been tested are 95.41%. DOI : 10.29408/jit.v3i1.1802
Lo stato di eccezione nell’ordinamento italiano. Riflessioni a partire dalle misure di contenimento dell’emergenza epidemiologica da Covid-19

This article explores some aspects of the pandemic emergency and aims to analyse the legal basis of the lockdown. It focuses on the definition of the “state of exception”, in order to evaluate its function as a key concept in public law discourse.
QMULibGuides: IGHD Overseas Partners - Open Access Resources: Home

A guide for the IGHD international projects partners to open access scientific literature resources available to them.
Implementation of Service Based Chatbot Using Deep Learning

A conversational agent (chatbot) is a software application which provides communication environment for conversation between machine and humans using natural language. The conversation is to be modeled to make it understandable to the machine and also it is an important task in (AI). In the modern digital era the dependency on computer is increasing day by day. One of the challenging tasks that everybody is looking is how to make a machine conversional with the user. Artificial Intelligence helping the developers to make a digital machine more intelligent and it should behave like a human being in understating the user queries and responding to the queries. The chatbot plays the crucial role in conversion with the user. Chatbot is a piece of software which will run on a computer. Normally chatbots are used for understanding the senetences given by the user and provide responses that are relevant to the user sentence that are already defined. In the past, constructing chatbot architectures have relied on rules specified by hand written and predefined templates or simple statistical approaches. With the rise of machine learning, deep learning and neural networks these models were quickly replaced by end-to-end trainable neural networks. Siri by Apple, Cortana by Microsoft, Google Assistant, and Alexa by Amazon are some of the most popular conversational agents today. They can assist user to get directions, check the scores of sports games and pick the phone number in your address book and call the people. But these chatbots give responses to the user from all the fields included when the people are searching for a particular field. So we are going to develop a chatbot for a service based so that it can give accurate results that the user wants and avoid confusion for the user.
LibGuides: CSUMB Common Read Book: Related Readings at CSUMB

This resource guide is for the CSUMB 2019 Common Read Book, The Best We Could Do by Thi Bui.
Status quo and countermeasure analysis of ICU nurses' implementation of airbag pressure monitoring in artificial airway

ObjectiveTo investigate the execution rate of airbag pressure monitoring of artificial airway by ICU nurses, and analyze the countermeasures to improve the execution rate of airbag pressure monitoring.MethodsFrom May to June 2017, 15 patients who were admitted to the ICU of this hospital with retained artificial airway and mechanical ventilation time greater than 24 hours were randomly selected.The 418 times of airbag pressure monitoring in 15 patients during mechanical ventilation were recorded, and the implementation of airbag pressure monitoring in nurses at different time points and with different seniority was compared, and the influence of nurses' teaching on airbag pressure monitoring was analyzed.ResultsTotal execution rate of airbag pressure monitoring was 45.93%.The comparison of airbag pressure monitoring implementation rates at different time points within 24 hours showed statistically significant differences (P<0.05). The execution rate in the afternoon was higher than that in the morning, and pre-night shift was higher than that of post-night shift, the difference was statistically significant (P<0.05). The execution rate of nurses within 3 years was higher than that of nurses over 3 years, and the difference was statistically significant(P<0.05). The execution rate of nurses with teaching was higher than that of nurses without teaching, the difference was statistically significant(P<0.05).ConclusionsThe execution performance of airbag pressure monitoring among ICU nurses is not optimistic.It is necessary to improve their execution performance from training, changing the work flow of nursing, setting an example or improving the nurses' subjective initiative, improving monitoring method, etc.Key words: ICU nurses; Artificial airway; Airbag pressure monitoring; Execution rate
Balancing expressiveness and inexpressiveness in view design

We study the design of data publishing mechanisms that allow a collection of autonomous distributed datasources to collaborate to support queries. A common mechanism for data publishing is via views: functions that expose derived data to users, usually specified as declarative queries. Our autonomy assumption is that the views must be on individual sources, but with the intention of supporting integrated queries. In deciding what data to expose to users, two considerations must be balanced. The views must be sufficiently expressive to support queries that users want to ask -- the utility of the publishing mechanism. But there may also be some expressiveness restriction. Here we consider two restrictions, a minimal information requirement, saying that the views should reveal as little as possible while supporting the utility query, and a non-disclosure requirement, formalizing the need to prevent external users from computing information that data owners do not want revealed. We investigate the problem of designing views that satisfy both an expressiveness and an inexpressiveness requirement, for views in a restricted declarative language (conjunctive queries), and for arbitrary views.
어린이집 원장의 초임보육교사 채용에 대한 인식과 선발과정에 관한 연구

Objective: The purpose of this study is to explore daycare-center director’s perceptons of recruitment and to understand how hire beginning teachers.Methods: One hundred twenty-five directors of daycare-centers in Seoul, Incheon, and Gyeonggi-do Province answered a questionnaire that was developed by researchers. The results were analyzed by frequency analysis, descriptive statistics and multiple response analysis through SPSS 18.0. Furthermore, 17 of the directors that participated in the study were given individual interviews by qualitative methods for research.Results: First, 56.8% of the directors felt difficulty to employ beginning teachers because of ‘lack of information about them’ and ‘uncertainty of practicecapability.’ On the other hand, other directors of daycare-centers said that they hire them for ‘high acceptance’ and ‘operational efficiency of the daycare-center.’ Second, the main way to recruit teachers for daycare-centers is open recruitment, and through recommendations of acquaintances or through colleges in relevant fields. Professional talent and personal characteristics were important selection criteria for recruitment, and daycare-center directors used interviews, r?sum?s, cover-letters, and demo classes for the hiring process. Primarily, most directors select candidates through r?sum?s and cover-letters, and the final selection is completed by conducting interviews.Conclusion/Implications: In conclusion, this study can be useful to prepare beginning teachers for employment and for educating applicants.
ENAM KEBIASAAN STRATEGIS UNTUK MENINGKATKAN KEMAMPUAN PENULIS PEMULA: PERSPEKTIF TEORI DAN PRAKTIK

For novice writers, especially for first-year students in English education study programs. Writing activities are not easy. Not only collide with psychological constraints, they are often faced with technical problems. This article tries to uncover some of the common obstacles faced by beginning writers and strategic steps to overcome these obstacles. The ideas offered in this paper are extracted from the results of the literature review combined with the author's experience.
Application and evaluation of micro-lectures teaching system of rehabilitation medicine

ObjectiveTo explore the influence of rehabilitation medicine micro-course teaching system on teaching and learning.MethodsUsing experimental control method. From February to July 2018, a total of 312 students majoring in clinical medicine in grade 2015 of Guangzhou University of Chinese Medicine were selected as subjects. According to the order of student number, the random serial number was generated. The odd number of serial number was the experimental group (156 students), and the odd number of ordinal number was the control group (156 students). The experimental group exposed to the rehabilitation medicine micro-course teaching system under the guidance of teachers, and the control group used the traditional teaching method. At the end of teaching, two groups joined theoretical test and practice test. After the test, students were analyzed from the final test results, the learning files and feedback evaluation of the system.ResultsThe theoretical test scores of the students in the experimental group were (88.49 ±3.15), while the control group were(87.23 ±6.49). There was no significant difference in theoretical test scores between the two groups(Z=-0.68, P=0.431). The operational score of the students in the experimental group (84.64±4.58) was higher than that in the control group (73.55±6.27), and the difference was statistically significant (Z=2.65, P<0.01). The total scores of the students in the experimental group(86.54±3.62)were higher than that of the control group(79.92±5.94). The difference was statistically significant(Z=2.05, P=0.041). The teaching resources of learning archives analysis showed that the video time in the experimental group accounted for 51.6% of the total learning time. When the video time was more than 10 minutes, the students appeared jump video click learning.ConclusionsUsing the use of micro-course teaching system of rehabilitation medicine can improve the examination results of students' rehabilitation medicine course and help to realize individualized teaching and learning. The teaching system can feedback the situation of learners.Key words: Rehabilitation medicine; Micro-lectures; Teaching system; Evaluation
A Novel Sequential Rate Distortion Function to Compute Partially Observable Markov Processes with MSE Distortion

We develop a new sequential rate distortion function to compute lower bounds on the average length of all causal prefix free codes for partially observable multivariate Markov processes with mean-squared error distortion constraint. Our information measure is characterized by a variant of causally conditioned directed information and it is utilized in various applications examples. First, it is used to optimally characterize a finite dimensional optimization problem for partially observable multivariate Gauss-Markov processes and to obtain the optimal linear policies that achieve the solution of this problem. Under the assumption that all matrices commute by pairs, we show that our problem can be cast as a convex optimization problem and achieves its lower rates. We also derive sufficient conditions which ensure that our assumption holds. Then, we compute the optimization problem by solving the KKT conditions and deriving a non-trivial reverse-waterfilling algorithm that we also implement. If our assumption is not met, then, one can still use it to derive sub-optimal waterfilling solutions on the obtained finite dimensional optimization problem. For scalar-valued Gauss-Markov processes with additional observations noise, we derive a new closed form solution and we compared it with the analytical solution obtained for scalar-valued Gauss-Markov processes to infer about the rate loss due to having the additional observations noise. For partially observable time-invariant Markov processes (without observations noise) driven by an additive i.i.d. non-Gaussian system's noise process, we recover using an alternative approach and thus strengthening a recent result by Kostina and Hassibi in [1, Theorem 9] whereas for time-invariant parallel and spatially identically distributed Markov processes driven by additive non-Gaussian noise process we also derive new analytical lower bounds.
An Artificial Intelligent of Princess Mandalika Legend: A New Strategy to Sustain the Resort of Mandalika-Lombok

A qualitative research is focused on a new architecture concept of the MandalikaTourist Region of Lombok. As an Infrastructure Project to rapidly a one of the TenNational tourism of Indonesia’s priority. According a phenomenological researchwithin multidiscipline actors was found an uniqueness of the Sasak local legend,named a story of the Princess Mandalika. She is a myth of the Lombok Land. Untilnow, the annually festival to remind her legend was held on February. To remind herthe videos, performing art, dance, and sculpture was created. Behind theinfrastructure itself, especially to enrich the resort region an artificial intelligent ofarchitecture may create as a part to sustain the spirit of the legend. An AugmentedReality (AR) may created in the surround of the district area. The Augmented Reality(AR) is a visual communication graphic design related the Princess Story through theadded images on the real world. Visitors my need a ‘smart glasses’ within the threegeneral characteristics; a). The combination of real environment with virtual objects,b). An Interactive display, c). A Display in 3D. By a Visual Prototyping AugmentedReality as images can manipulation the Princess Mandalika present on the regionwithin the Sasak Architecture background. So, by exploiting the legend the foreigntourists more enjoyed about the locale culture of Indonesia. In architecture is a partof the architecture-event.
MP-SPDZ: A Versatile Framework for Multi-Party Computation.

Multi-Protocol SPDZ (MP-SPDZ) is a fork of SPDZ-2 (Keller et al., CCS '13), an implementation of the multi-party computation (MPC) protocol called SPDZ (Damgard et al., Crypto '12). MP-SPDZ extends SPDZ-2 to 30 MPC protocol variants, all of which can be used with the same high-level programming interface based on Python. This considerably simplifies comparing the cost of different protocols and security models. The protocols cover all commonly used security models (honest/dishonest majority and semi-honest/malicious corruption) as well as computation of binary and arithmetic circuits (the latter modulo primes and powers of two). The underlying primitives employed include secret sharing, oblivious transfer, homomorphic encryption, and garbled circuits. The breadth of implemented protocols coupled with an accessible high-level interface makes it suitable to benchmark the cost of computation in various security models for researchers both with and without a background in secure computation This paper aims to outline the variety of protocols implemented and the design choices made in the development of MP-SPDZ as well as the capabilities of the programming interface.
Flexible Prior Elicitation via the Prior Predictive Distribution.

The prior distribution for the unknown model parameters plays a crucial role in the process of statistical inference based on Bayesian methods. However, specifying suitable priors is often difficult even when detailed prior knowledge is available in principle. The challenge is to express quantitative information in the form of a probability distribution. Prior elicitation addresses this question by extracting subjective information from an expert and transforming it into a valid prior. Most existing methods, however, require information to be provided on the unobservable parameters, whose effect on the data generating process is often complicated and hard to understand. We propose an alternative approach that only requires knowledge about the observable outcomes - knowledge which is often much easier for experts to provide. Building upon a principled statistical framework, our approach utilizes the prior predictive distribution implied by the model to automatically transform experts judgements about plausible outcome values to suitable priors on the parameters. We also provide computational strategies to perform inference and guidelines to facilitate practical use.
Algorithms for detection and recognition of local regions on images

The paper considers general approaches to image processing, analysis of visual data and computer vision. The main methods for detecting features and edges associated with these approaches are presented. A brief description is also given of modern edge detection and classification algorithms suitable for isolating and characterizing local objects (for example, a brain tumor, etc.).
Interactive activities supported with ICT in preschool education

This thesis deals with interactive activities with the support of the ICT at nursery schools. Furthermore, it reflects the topic of the digital literacy of the pre-school children. In the beginning of the theoretical part, I describe pre-school period and education. Secondly I continue with the chapter focused on pre-school children and ICT. Also, there is mentioned development of the digital competence and the description of the possibilities how to develop digital literacy of the pre-school children. The next part of the theoretical contain describes some ICT occurrences at nursery schools. It focuses on one particular kind of ICT: the touchable boards, because those are the main focus of the whole thesis. In the conclusion of the theoretical part you can find a variety of software which we can use for preparing interactive activities on the touchable boards or a buyable software.In the practical part of the thesis, there is a quantitative research of the unstructured observation. The observation itself took place in one chosen class of the Pilsen nursery school. There are photography, evaluation and the results according to Educational Programme for pre-school. The activities are divided into those created in the Activelnspire programme and the activities created with Aktivni skolicka programme: Colourful stones. In the result of the practical part, there are the outcomes of the research, evaluation of the programme and some information, which were gained during the practical work and them can be beneficial for further work with the devices. The most important aim of this thesis was to test model activities on the touchable board at nursery school and to gain more knowledge about possibilities of the mentioned device, its advantages and disadvantages, its suitability and in general to observe and write up the information for further work with the device at nursery schools.
UJI EFEKTIFITAS KAREBATA PADA PEMBELAJARAN BANGUN DATAR KELAS III DI SD 58 BARANA DITINJAU DARI AKTIVITAS SISWA

There's a problem facing a 58th grade teacher in implementing the 2013 curriculum especially in developing a learning media, it so essential for the innovation of the media learning to teach mathematics materials in particular classroom wake up III. Based on the results of observation the data that KAREVATA practices at the first meeting of 89.130% students is described as very active in learning and at the second meeting of 99.573% students was categorically very active in the learning. Therefore, in view of students activities KAREBATA was very effective to apply.
Application of Fuzzy Time Series-Markov Chain Method in Forecasting Data of Exchange Rate Riyal-Rupiah

Abstract Currency rates are one of the important indicators in the context of an economics country. The value of a country’s currency always increases and decreases in value against another country’s currency at any time. In this research, we make a model of dynamical currency rates data among Riyals and Rupiah. The data are obtained from the official website of Bank Indonesia. The aim research is to predict the currency rate between Riyal to Rupiah in the future time with the Markov Chain Fuzzy-Time Series method. The results of this research are data processing in the form of error value of the forecast used AFER and MEA methods. Those are 0.827% and Rp32.96 rupiahs respectively. The forecast value for the next 10 days are Rp3,779; p3,774; Rp.3,774; Rp3,779; Rp3,764; Rp3,760; Rp3,763; Rp3,797; Rp3,777 and Rp3,784.
Open Knowledge Graph of Historical Heritages for Korean Religions

The Knowledge Graphs (KGs) as the emerging artificial intelligence (AI) paradigm play a crucial role in knowledge representing and sharing to achieve intelligent knowledge services. This paper addresses a new Linked Open Data (LOD) development method that can realize KGs of the diverse domains from the practical perspectives. The proposed approach is based on two types of separation of concerns for the effective development of LOD data sets：conceptual layer separation between schema and instances, and view separation between LOD management system and user interface. In order to mediate separated concerns, a LOD Interface Sheet (LIS) is implemented to create a domain-specific LOD development environment. The paper implements the proposed method that can generate the domain-specific LOD development system providing the necessary functionalities for LOD management as well as KG realization. This paper also presents the development of an open knowledge graph of historical heritages for Korean religions to demonstrate the capability of the implemented i-Manager and the effectiveness of KGs in scholarly knowledge management.