Reviewerly/exHarmony huggingface dataset:
Co-located and Orchestrated Network Fabric (CONF): An Automated Cloud Virtual Infrastructure for Social Network Applications

Cloud environments can provide virtualized, elastic, controllable and high-quality on-demand infrastructure services for supporting complex distributed applications. However, existing IaaS (Infrastructure-as-a-Service) solutions mainly focus on the automated integration or deployment of generic applications; they lack flexible infrastructure planning and provisioning solutions and do not have rich support for the high service quality and trustworthiness required by social network applications. This paper introduces an automated cloud virtual infrastructure solution for social network applications, called Co-located and Orchestrated Network Fabric (CONF), which was conducted in a recently funded EU H2020 project ARTICONF. CONF aims to improve the existing infrastructure support in the DevOps lifecycle of social network applications to optimize QoS performance metrics as well as ensure fast recovery in the presence of faults or performance drops.
Anomaly Detection in Crowded Scenes Based on Group Motion Features

Event detection in crowded scenes is a challenging task for Computer Vision. In this study, based on group motion features, we propose an approach for crowded scene anomaly detection and localization. According to the motion trajectory of numerous pedestrians, both distance and relative speed between trajectories can be extracted, and the pedestrian groups can be recognized via their spatial relationship. Anomaly events in crowded scenes can be detected based on variations of group numbers and speed. To demonstrate the effectiveness of the approach, a quantitative experimental evaluation has been conducted on multiple, publicly available video sequences.
How to Construct an Index System to Evaluate the Undergraduate Thesis Quality—An Empirical Research of Economics and Management Major in an Applied University

The purpose of this study is to construct a scientific and reasonable quality evaluation system of undergraduate thesis in an Applied University and improve the quality of undergraduate thesis in an Applied University. MATLAB is used to get the results by dealing with the data obtained through structured questionnaire survey from a sample of 185 undergraduates and 20 instructors majoring in Investment and Management Science and 10 relevant experts. Quality Evaluation System is directly and positively associated with the quality of undergraduate thesis in an Applied University. Analytic Hierarchy Process is helpful for establishing a scientific and reasonable quality evaluation system in that it provides a better work for the situation where it is difficult to measure the evaluation target directly and accurately. Successful implementations of Analytic Hierarchy Process support the implementation of establishing a scientific and reasonable quality evaluation system of undergraduate thesis leading to improved quality of undergraduate thesis in an Applied University.The study of this thesis has a good reference value for scientifically determining the weight of the quality evaluation indicator of graduation, and provides ideas for improving the scientific and effectiveness of undergraduate thesis quality evaluation.
Design Anthropology On the Fly: Performative Spontaneity in Commercial Ethnographic Research

This chapter addresses the value of ethnographic approaches for facilitating and responding to the spontaneous, emergent potentialities. It illustrates interactions with one another and the other stakeholders revealed constant tensions between structure and spontaneity and between the need to produce business-appropriate insights and anthropological commitments to recognize and work with messy data. Accounts of ethnographic work for design and business purposes have described how research roles and activities are commonly delineated according to sequential and structured phases of work: first ethnographers or ethnographic teams conduct ethnographic research, and then designers or design teams turn research data, insights and explanatory frameworks into concepts and business decisions. Even the most deliberately experimental and open-ended modes of corporate ethnographic work can prevent the realization of potentiality.
Contents of Dialogues with 'Him'

The following contents are the result of, as at the 30th September 2018, 19 dialogues for a total of around 22 hours, with an Entity referred to as “He”/“Him” channelled by N.R. while in an OBE induced by Luciano Pederzoli (LP) by way of hypnotic techniques. This procedure is fully described in “Guide to OBE induction”. A distinctive feature of this technique is that, apart from allowing contact with a non-physical Entity by people who have never experienced it before, it also allows direct dialogue with the channelled entity, establishing actual interviews about subjects of interest to the interviewer and collaborators. Contact with the entity referred to as “He”/“Him” is described on page 3. The contents of these various dialogues have been grouped into subjects for ease of understanding and are not in chronological order. It is possible that they may also be updated, if these experiences continue further. As a cautionary note, although the channeller, interviewer, and other author of this introduction have little doubt that the contents reproduced herein originate from a real non-physical Entity, we should bear in mind that they could be a product of unknown mental processes of the channeller and/or the interviewer. We therefore suggest assessing them based on their informational value, rather than taking them as absolute truths. One certainty however, due to the other channellings carried out for a total of 36 hours with different channellers, is the perfect repeatability of the phenomenon.
Construction of the continuous nursing need index system based on discharge readiness for patients with spinal cord injury

ObjectiveTo construct the continuous nursing need index system based on discharge readiness for patients with spinal cord injury so as to guide the clinical nursing practice.MethodsFrom January 2017 to July 2018, this study selected 115 spinal cord injury inpatients of Spine Surgery Department at a ClassⅢ Grade A hospital in Qingdao as subjects by convenience sampling. The Readiness for Hospital Discharge Scale (RHDS) was used to investigate those patients. According to the investigation results, this study primarily built the continuous nursing need index system for spinal cord injury patients. Delphi method was used to select 25 experts for two rounds of consultation so as to establish the final the continuous nursing need index system for spinal cord injury patients.ResultsAmong 115 spinal cord injury patients, the total score and item average score of RHDS were (60.39±22.12) points and (5.27±2.75) points respectively. Among two rounds of consultation, the authoritative coefficients of experts were 0.78 and 0.81 respectively, and the coordination coefficients were 0.343 and 0.423. In the second round of consultation, the variation coefficients ranged from 0.09 to 0.18. The final the continuous nursing need index system for spinal cord injury patients included 5 first-level indexes and 33 second-level indexes.ConclusionsThe continuous nursing need index system for spinal cord injury patients has a high level of authoritative coefficients and is scientific practical which can provide a basis for discharge health instruction in spinal cord injury patients and promote the safe transition in hospital-community-family as well as comprehensive rehabilitation.Key words: Spinal cord injuries; Continuous nursing; Discharge readiness; Nursing needs; Delphi method
Glowworm swarm optimization, Optimization, Swarm intelligence, Clustering

This paper reviews glowworm swarm optimization algorithm (GSO), which is a meta-heuristic swarm intelligence algorithm.The GSO algorithm is applied for solving optimization problems.Shortcoming of the GSO algorithm has been identified with the introduction and discussion of the improvement taken place in recent years.Adaptive step size and new movement rules have been widely used in the improvement of GSO algorithm.The application of GSO including clustering techniques is also presented.Very promising GSO clustering versions use MapReduce framework to improve the computational efficiency when the clustered data set is large and thereby reducing the time complexity.
RETRACTED: A compensating total variation image denoising model combining L<sub>1</sub> and L<sub>2</sub> norm

To overcome the “staircase effect” while preserving the structural information such as image edges and textures quickly and effectively, we propose a compensating total variation image denoising model combining L1 and L2 norm. A new compensating regular term is designed, which can perform anisotropic and isotropic diffusion in image denoising, thus making up for insufficient diffusion in the total variation model. The algorithm first uses local standard deviation to distinguish neighborhood types. Then, the anisotropic diffusion based on L1 norm plays the role of edge protection in the strong edge region. The anisotropic and the isotropic diffusion simultaneously exist in the smooth region, so that the weak textures can be protected while overcoming the “staircase effect” effectively. The simulation experiments show that this method can effectively improve the peak signal-to-noise ratio and obtain the higher structural similarity index and the shorter running time.
Developing a Web Application to Ensure the Authenticated Election Process using Block Chain Security

Developing a web based application to ensure that the voting process takes place without any type of  type of malpractice and also safety to the employees who are involved in this challenging task. As we know the India’s population 1,368,737,513 [14].  in the 2019 and in order to maintain the county and its  resources  in  the  appropriate  way  the  Indian   constitution  has  the   election  system.   India  is  under democratic system which is the rule of the people, for the people and by the people.[12]. Hence there is a election commission which organizes the election process by which people select their representatives in the  state  level  and  nation  level  as  well.  Earlier  people  used  to  vote  by  ballot  paper  but  now  a  days Electronic Voting Machines (EVM) are available for voting purpose[12].  This EVM  system creates lot of discrepancy  by  which  it  leads  to  variety  of  the  disputes  by  the  opposition  and  also  by  the  people sometimes due  to the  machines technical issues and sometimes software related issues of  the machines. This  is  the  very  big  drawback  which  was  raised  during  2019  election  period.  In  this  article  we  have developed the web based application using the block chain which is highly safe and secure to hack or  to do  any  type  of  malpractice  by  which  ensuring  that  the  election  process  can  happen  in  an  authorised method also that leads to the less expensive.   World’s second highest expenses   occurred in India 2019 – election Process [11].    By implementing the model of block chain for voting purpose can save the huge volume   of   expenses   which   occurs   for   the   election   process.
A Ranking Based Approach in Security Alert for Handling Sensitive Data Organization

An organization undoubtedly wants to preserve and retain data stored in an organization's computers.On the other hand, this data is necessary for daily work processes.Users within the organization's perimeter (e.g., employees, subcontractors, or partners) perform various actions on this data (e.g., query, report, and search) and may be exposed to sensitive information embodied within the data they access.In an effort to determine the extent of damage to an organization that a user can cause using the information obtained, the concept of a ranking based approach in security alert for handling sensitive data organization is introduced.The score measure is tailored for tabular data sets (e.g., result sets of relational database queries) and cannot be applied to non-tabular data such as intellectual property, business plans, etc.By assigning a score that represents the sensitivity level of the data that a user is exposed to, the weight can determine the extent of damage to the organization if the data is misused.Using this information, the organization can then take appropriate steps to prevent or minimize the damage.
Writing Tips of English Descriptive Essay Text in Prayatna High School Medan

English is not certainly unfamiliar for us and it is often found on all occasions. And for students in school and students of university, English is also not a foreign thing in their academic activities, regardless of whether they are students or students majoring in English or not. Besides the students, English is also usually found by workers and also general people. Therefore, sufficient expertise in mastering English is indeed needed enough thus later we are not bothered with assignments or jobs that require us in mastering English, especially essay writing activities. The resolution of this problem, the teaching method was carried out at Prayatna Senior High School Medan. The aim was to train and equip students with skills in writing English Descriptive Essay Text. Thus, the Prayatna Senior High School students could master English especially in writing. The audience target of this service is the students of Prayatna Senior High School Medan. The dedicated of this activity was held on January 25, 2018 at Prayatna Senior High School, with 25 participants participating in the students of Prayatna Senior High School Medan. From the result of the evaluation, the results and benefits of this service activity include increasing the skills of high school students in English, especially in writing English Descriptive Essay Text.
ValueNet: A Neural Text-to-SQL Architecture Incorporating Values

Building natural language interfaces for databases has been a long-standing challenge for several decades. The major advantage of these so-called text-to-SQL systems is that end-users can query complex databases without the need to know SQL or the underlying database schema. Due to significant advancements in machine learning, the recent focus of research has been on neural networks to tackle this challenge on complex datasets like Spider. Several recent text-to-SQL systems achieve promising results on this dataset. However, none of them extracts and incorporates values from the user questions for generating SQL statements. Thus, the practical use of these systems in a real-world scenario has not been sufficiently demonstrated yet. In this paper we propose ValueNet light and ValueNet -- the first end-to-end text-to-SQL system incorporating values on the challenging Spider dataset. The main idea of our approach is to use not only metadata information about the underlying database but also information on the base data as input for our neural network architecture. In particular, we propose a novel architecture sketch to extract values from a user question and come up with possible value candidates which are not explicitly mentioned in the question. We then use a neural model based on an encoder-decoder architecture to synthesize the SQL query. Finally, we evaluate our model on the Spider challenge using the Execution Accuracy metric, a more difficult metric than used by most participants of the challenge. Our experimental evaluation demonstrates that ValueNet light and ValueNet reach state-of-the-art results of 64% and 60% accuracy, respectively, for translating from text to SQL, even when applying this more difficult metric than used by previous work.
Preparation of the Future Pedagogue-Psychologist for Innovative Activities in the Entrepreneurial Educational Environment of the University

The article discusses the problem of preparing students - future pedagogues-psychologists for innovative and educational activities in the entrepreneurial  educational environment of non-state schools and training centers for further education. It is emphasized that an entrepreneurial university creates new conditions and opportunities for training personnel capable of performing their basic professional functions with a focus on innovative entrepreneurial activity in educational organizations. It is noted that today the training of school psychologists should be aimed at developing entrepreneurial qualities, on the one hand, and at the psychological and pedagogical support of innovative educational, entrepreneurial activity at school, in training centers. In Kazakhstan, the number of private comprehensive schools is increasing, and training centers for further education have already firmly entered the market of educational services. State comprehensive schools, traditionally “far” from entrepreneurial activity, already noticeably feel the influence of market relations, especially in connection with innovations in education, in particular with the transition to per capita financing. The study examines the approaches and methods of preparing future school psychologists for the psychological and pedagogical support of innovative and educational entrepreneurial activities in organizations of general and additional general education. Using the methods of scientific and pedagogical research, the possibilities of an entrepreneurial university in the formation of the readiness of future pedagogues-psychologists to perform professional functions in an entrepreneurial innovative and educational environment are analyzed. The experience of the work of school psychologists in the psychological and pedagogical support of innovative and educational entrepreneurial activities is analyzed, the modeling of which reflects the content and preparation process of students - future pedagogues-psychologists.
Wavelet-Based Reversible Transform Encoding

Wavelet-based reversible transform encoding for image encoding, mainly Haar wavelet, is considered for various treatments in the entire span of the chapter. Basic details of Haar wavelet computations with 2 x 2 mask are given importance with information flow analysis for image encoding and authentication. Multilevel wavelet transformation has also been discussed. One-dimensional and two-dimensional examples for wavelet decomposition with inverse computation are given in detail. A complete encoding and decoding algorithm of color image authentication using Haar wavelet is given with results and analysis. Applications of wavelet are given at end of the chapter.
Statistical and Computational Aspects of Learning with Complex Structure

The recent explosion of data that is routinely collected has led scientists to contemplate more and more sophisticated structural assumptions. Understanding how to harness and exploit such structure is key to improving the prediction accuracy of various statistical procedures. The ultimate goal of this line of research is to develop a set of tools that leverage underlying complex structures to pool information across observations and ultimately improve statistical accuracy as well as computational efficiency of the deployed methods. The workshop focused on recent developments in regression and matrix estimation under various complex constraints such as physical, computational, privacy, sparsity or robustness. Optimal-transport based techniques for geometric data analysis were also a main topic of the workshop.
La “circoscritta (e puntellata) area” di incostituzionalità dell’art. 580 c.p. fra self-restraint della Corte costituzionale e perdurante inerzia del legislatore

With the decision on the “Cappato case” the Constitutional Court did not create the right to medically assisted suicide, which, moreover, the constitutional order does not contemplate, but only identified a “circumscribed area” of unconstitutionality of art. 580 of the Italian Criminal Code, supporting it with regulatory and procedural props. In this way, the Court demonstrated its self-restraint respectful of Parliament’s discretion and underlined the persistence of the need for legislative intervention in such a sensitive matter.
Anxiety Confronts Practice Exam Reviewed from Optimism, Emotional Intelligence, and Social Support on Student of STIKES

Anxiety if is  not handled properly will adversely affect even physical problems that will interfere with productivity and decline in academic ability and learning results. The research aimed to know the relation between optimism with anxiety facing the test, the relationship between emotional intelligence and anxiety facing tests and social support with anxiety facing tests at STIKES Aisyah Pringsewu Lampung. Samples were taken using random sampling techniques with a total of 150 students. The Data collected were  used  A (1) The anxiety scale facing test, (2) The scale of optimism, (3) The scale of emotional intelligence, and (4) The scale of social support. Analysis of data by using product moment analysis, partial correlation and double regression with the help of computer. The results of this study  were :  (1) there was a very significant negative relationship between optimism with anxiety facing tests (R =-. 171, p =. 037, and rX1y =-. 0031, p =. 040), (2) there was a very significant negative relationship between emotional intelligence and anxiety confronted Tests (R =-. 213, p =. 009, and rX2y =-. 0612, p =. 015), (3) there was a very significant negative relationship between social support with anxiety facing tests (R =-. 234, p =. 004, and rX2y =.-1162, p =. 006). (4) There was a relationship between optimism, emotional intelligence and social support with the anxiety of facing tests (F = 3,050, p =. 031). Optimism, emotional intelligence, social support jointly had a negative relationship with anxieties facing practice exams and significant relation to a significant level 5% , with an effective contribution of 5.9%. Training programs relating to the enhancement of optimism, emotional intelligence, and social support can be developed by involving students and other related parties.
Reinforcement Learning Based Outdoor Navigation System for Mobile Robots

This paper presents a navigation system for mobile robots in outdoor environments and the preliminary robot implementation results. Objectives of the proposed navigation system include path generation on the map (2D binary image) and path following of the robot to reach the goal location. In our method there is no waypoint in the generated paths and the map. The A-Star search algorithm is employed to plan paths on the map, and the q-learning is used to train the robot to follow the generated paths. The difference between the robot positions and A-star generated random paths is used to evaluate the performance of the proposed method. Preliminary simulation results revealed the potentials of the cooperation between reinforcement learning-based algorithms and conventional path planning algorithms for robot navigation.