Reviewerly/exHarmony huggingface dataset:
The Double Edge Sword Based Distributed Executor Service

Scalability is one of the most important quality attribute of softwareintensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload.In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems.TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime.In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers.Existing DTPSs are overloaded either due to an inappropriate TPS optimization strategy at backend servers or improper load balancing scheme that cannot quickly recover an overload.Consequently, the performance of software-intensive system is suffered.Thus, in this paper, we propose a new DTPS that follows the collaborative round robin load balancing that has the effect of a double-edge sword.On the one hand, it effectively performs the load balancing (in case of overload situation) among available TPSs by a fast overload recovery procedure that decelerates the load on the overloaded TPSs up to their capacities and shifts the remaining load towards other gracefully running TPSs.And on the other hand, its robust load deceleration technique which is applied to an overloaded TPS sets an appropriate upper bound of thread pool size, because the pool size in each TPS is kept equal to the request rate on it, hence dynamically optimizes TPS.We evaluated the results of the proposed system against state of the art DTPSs by a clientserver based simulator and found that our system outperformed by sustaining smaller response times.
OL-MAM-JENet: A Novel Joint Extraction of Entities and Relations Network with On-LSTM and Multi-head Self-attention Mechanism

Joint extraction of entities and relations has been touted as an effective approach to detect entities and relations by using a single model. However, it is still a challenge on how to identify overlapping relational triplets. In this paper, we propose a novel network model, termed OL-MAM-JENet, which is powered by On-LSTM and Multi-head Self-attention Mechanism to capture hidden dependency relation for triplets detection. The network consists of a sharing parameter module, an entity detection module and a relation recognition module. Specifically, the sharing parameter module obtains the direct dependency relation between words through On-LSTM. The entity detection module adopts Conditional Random Field (CRF) algorithm, while the relation recognition module leverages Bi-LSTM and multi-head self-attention mechanism. The entity detection module adopts entity label to communicate features with the relation recognition module. Experimental results demonstrate that the proposed model outperforms other baselines models. Moreover, OL-MAM-JENet can achieve good performance under different circumstances, such as different relation types and different numbers of relations.
The complication of cyber manhunt: How cyber manhunt further complicated the ethical conflict between breaching the confidentiality and endangering the society in face of the COVID-19 pandemic (Preprint)

<sec> <title>UNSTRUCTURED</title> While health care and public health workers are working on measures to mitigate the COVID-19 pandemic, there is an unprecedentedly large number of people spending much more time indoors, and relying heavily on the Internet as their lifeline. What has been overlooked is the influence of the increasing online activities on public health issues. In this article, we pointed out how a large-scale online activity called cyber manhunt may threaten to offset the efficacy of contact tracing investigation, a public health intervention considered highly effective in limiting further transmission in the early stage of a highly contagious disease outbreak such as the COVID-19 pandemic. In the first section, we presented a case to show how personal information obtained from contact investigation and disclosed in part on the media provoked a vehement cyber manhunt. We then discussed the possible reasons why netizens collaborate to reveal anonymized personal information about contact investigation, and specify, from the perspective of public health and public health ethics, four problems of cyber manhunt, including the lack of legitimate public health goals, the concerns about privacy breach, the impact of misinformation, and social inequality. Based on our analysis, we concluded that more moral weight may be given to protecting one's confidentiality, especially in an era with the rapid advance of digital and information technologies. </sec>
Formation Of Skills Of Research Activity Among Junior Students

The article examines the analysis of factors influencing the formation of research skills among junior university students. Research work involves the most complete and effective development of the intellectual and creative abilities of students, aimed at training highly qualified personnel for various fields of activity. The purpose of this work is to identify and state the factors that make it possible to fully reveal the scientific potential of gifted students for possible subsequent postgraduate studies and replenishment of scientific and pedagogical personnel of the university, as well as for the use of the acquired research skills in practical activities in production. The research is based on a systematic approach to the problem, using methods of modeling, analysis, comparison and generalization. The conclusions obtained as a result of work on this topic are based on the authors' long-term practice in this area of activity with students of various specialties. Among the numerous factors of the all-round development of future specialists and the realization of their scientific potential, the authors highlight the following: continuity of research experience; motivational component; competence and interest of the scientific leadership; independence; technical equipment. The use of these factors in work with junior students will ensure the intensification of research work, increase its effectiveness and bring a qualitative indicator of the training of specialists to a new level.
Computational and Artificial Intelligence Approaches to Indirectness

This chapter illustrates how computational models of ISA disambiguation have been improved and eventually applied to human-like robots in daily interactions, taking into account contextual parameters such as uncertainty about a speaker's intentions, hierarchical status and politeness expectations.
Intelligent Network Traffic Control Based on Deep Reinforcement Learning

This paper studies the problems of load balancing and flow control in data center network, and analyzes several common flow control schemes in data center intelligent network and their existing problems. On this basis, the network traffic control problem is modeled with the goal of deep reinforcement learning strategy optimization, and an intelligent network traffic control method based on deep reinforcement learning is proposed. At the same time, for the flow control order problem in deep reinforcement learning algorithm, a flow scheduling priority algorithm is proposed innovatively. According to the decision output, the corresponding flow control and control are carried out, so as to realize the load balance of the network. Finally, experiments show, the network traffic bandwidth loss rate of the proposed intelligent network traffic control method is low. Under the condition of random 60 traffic density, the average bisection bandwidth obtained by the proposed intelligent network traffic control method is 4.0mbps and the control error rate is 2.25%. The intelligent network traffic control method based on deep reinforcement learning has high practicability in the practical application process, and fully meets the research requirements.
Epilogue: Reflecting on Free Speech in the Time of Covid-19

This chapter deals with how the Covid-19 pandemic can inform our understanding of free speech. I argue that the latest experience of the pandemic has demonstrated that the free flow of information is significant and this significance stems from free speech’s quality of being a requirement of the right to equal autonomy and the right of individuals to share the political power. The fact that we are equally autonomous individuals requires us to freely hear, read and listen to all possible information and opinions on the subject of Covid-19. In other words, only under the conditions of free speech, can we develop our own authentic opinions on the subject without imposition from the authorities. Second, the silencing and censoring attempts of whistleblowers by some authorities in different countries have demonstrated that it is important to criticize and monitor the state authorities’ activities and that the right to democratic protest is a primary right that cannot be suspended even during a pandemic. Lastly, I investigate how hate speech has escalated during the pandemic and what type of speech we should tolerate, also given the overflow of fake news and information. I contend that speech that is deliberately manipulative and speech that lacks a valid scientific basis and, at the same time, that calls for violence against a group of people cannot be tolerated. I add that we have less reason to be tolerant of hate speech than any type of fake information since hate speech involves hate, exclusion and even sometimes a call for violence.
Cataloging Electronic Serials

There are unique issues involved when cataloging electronic journals. The workshop leaders presented examples of online journals to illustrate problems associated with bibliographic description, transcription of the 856 field, and access points that are useful for e-serials. Additionally, the workshop leaders examined CONSER’s one-record approach to cataloging digital reproductions. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-342-9678. E-mail address: getinfo@haworth.com]
Conditional Bisimilarity for Reactive Systems

Reactive systems \`a la Leifer and Milner, an abstract categorical framework for rewriting, provide a suitable framework for deriving bisimulation congruences. This is done by synthesizing interactions with the environment in order to obtain a compositional semantics. We enrich the notion of reactive systems by conditions on two levels: first, as in earlier work, we consider rules enriched with application conditions and second, we investigate the notion of conditional bisimilarity. Conditional bisimilarity allows us to say that two system states are bisimilar provided that the environment satisfies a given condition. We present several equivalent definitions of conditional bisimilarity, including one that is useful for concrete proofs and that employs an up-to-context technique, and we compare with related behavioural equivalences. We consider examples based on DPO graph rewriting, an instantiation of reactive systems.
Elastic Akka Cluster with Websockets

In this paper we will discuss an automated cost-effective solution to induce elasticity in a system dealing with the persistence of websocket connection. We are going to make use of the concept of Akka Clustering to ensure there is no single point of failure making the system resilient. The system is deployed using automation to the AWS cloud where we will make use of Cloudwatch and Lambda functions to scale up or down the cluster as traditional methods to scaling based on memory and CPU utilization will not suffice. The elastic nature of the system will make it flexible to deal with variable loads in terms of connected clients and scale based on the number of connected clients. The use of AWS auto-scaling will also ensure the system is highly available.
Fusion of Watermarking and Steganography for Protecting Image Ownership

The use of digital images has become very common because of the rapid increase of the internet over time. Moving digital images over the internet is easy, but keeping ownership is complex, and serious issues have emerged. Forgery, fraud, and pirating of this content are rising. Different techniques used to protect images, like watermarking and steganography, but these methods are not enough toprotect. So, providing new techniques is essential for protecting image ownership. We have proposed a fusion method of steganography and watermarking in this work. First, the secret message is encoded within the original image using the LSB technique to obtain the stego image. Secondly, the watermarking process is applied on the stego image using text watermarking or image watermarking to provide stego-watermarked-image. The proposed fusion watermarking and steganography method is very useful for protecting image ownership over insecure communication channels. An attacker cannot get the desired watermarked image from the stego-watermarked-image without knowing the secret message hiding inside it using the LSB technique. The proposed method is efficient, simple and secure; it provides significant protection for image ownership.
Konsep Wabi-Sabi Yang Diterapkan Dengan Teknik Sulam Dan Shibori Pada Busana Outerwear

The creation of a work with the title "The concept of Wabi-Sabi applied with embroidery and shibori techniques in Outerwear Clothing" is the embodiment of individual ideas or thoughts to achieve inner satisfaction which is processed according to the abilities of the author. This work has character and aesthetic value, using balanced ideas, concepts, and techniques. The creation of the work uses the Japanese concept of wabi-sabi which is applied to outerwear inspired by kimono. Approach methods in the creation of works are aesthetic, ergonomic, and semiotic approaches. There are three creation methods used to search data according to the theme raised, namely data collection, data analysis, design, and embodiment. The technique of embodiment of the work applies shibori and embroidery techniques. The works resulting from this creation are four works of art, each of which has its own uniqueness and characteristics in terms of motifs, colors and pieces of clothing. It is hoped that in making this work useful for art connoisseurs and the community. And can contribute and creative discourse about culture and fashion.
Full Issue

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 58, Issue 2 p. I-I Full Issue Full Issue First published: 08 April 2021 https://doi.org/10.1111/j.1467-6346.2021.09953.xAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Volume58, Issue2April 2021Pages I-I RelatedInformation
Efficacy of Spectral Doppler Indices in Predicting Malignancy in BI-RADS 3 Breast Lesions: A Prospective Cohort Study

Introduction: Breast Imaging, Reporting and Data System (BI-RADS) is an effective tool for management of patients with breast pathologies. While the BI-RADS 1 (negative) and BI- RADS 2 (benign) categories patients are advised for routine mammography screening. BI-RADS 4 (suspicious abnormality) and BI-RADS 5 (highly suggestive of malignancy) categories patients are recommended for tissue diagnosis, BI-RADS 3 category patients are managed with follow-up examinations. But upto 2% of BI-RADS 3 lesions are proved to be malignant on follow-up examinations and tissue diagnosis. Aim: To evaluate the efficacy of spectral Doppler indices in predicting malignancy in BI-RADS 3 category breast lesions. Materials and Methods: A prospective cohort study was conducted in the Department of Radiology, Katuri Medical College, Guntur, Andra Pradesh, India from July 2019 to February 2021. Study was conducted on 292 BI-RADS 3 lesions from 257 patients to evaluate the efficacy of spectral Doppler indices in differentiating malignant BI-RADS 3 lesions from benign ones. All the breast masses were evaluated with spectral doppler and the resistive and pulsatility indices were compared with histopathology findings of the suspicious lesions detected in follow-up examinations. Statistical analysis was performed using Statistical Package for the Social Sciences (SPSS) 2017 version 25, and the quantitative data was expressed in mean and standard deviation. Results: The patients recruited in the study were in age range of 27-80 years, and the mean age of the patients was 46±15 years (mean±SD). Follow-up examinations and tissue diagnosis of suspicious lesions revealed 8 out of 292 BI-RADS breast masses to be malignant. On spectral Doppler analysis, high resistivity and pulsatility indices are predictive of malignancy. A resistive index of more than 0.6 as a sign of malignancy proved to have a sensitivity of 87.5% and specificity of 85.5% and more than 0.8 as a sign of malignancy has a sensitivity of 25% and specificity of 95%. A pulsatility index of more than 0.9 as a sign of malignancy has a sensitivity of 87.5% and specificity of 87% and more than 1.6 as a sign of malignancy has a sensitivity of 37.5% and specificity of 96%. Conclusion: Spectral doppler is reliable in the prediction of malignancy of BI-RADS 3 breast masses.
PENERAPAN PEMBELAJARANMODEL JIGSAW UNTUK MENINGKATKAN KEAKTIFAN BELAJAR SISWA KELAS V SD NEGERI 2 KARANGSARI PADA TEMA 1 SUB TEMA 3

Student activeness in the learning process is very important to acquire knowledge and skills. Based on the results of observations made by researchers during thematic learning in class V SD Negeri 2 Karangsari on Saturday, January 4, 2020, the results of student activity and learning outcomes were still low. This can be seen from the activeness indicators: 1) students who are included in the active category are 5 students (30%), 2) students who are quite active are 3 students (20%),3) students who are in the less active category are 8 students (50%). This research was conducted to determine how the application of the Jigsaw model increases student activity. The activity observed is mental activity which includes responding to, remembering and solving problems. The research subjects were 16 grade V SD Negeri 2 Karangsari students. Student activeness is said to increase ≥75% of students reach the active and very active category, it is expected that the results of the implementation of teacher and student activities are at least 85%. The results showed that the average activity of students in the first cycle was 65% and the second cycle was 91% on average. The results of observations of the implementation of the activities of teachers and students in cycle I 79% and cycle II 93%, based on the data, the application of the Jigsaw model of learning can increase learning activeness in theme 1 sub theme 3.
Stark using Word Cloud

(Please read carefully abstract of the template). STARK (Simultaneous Tracking and Ranking) is a web application which comes handy with Telecommunication companies for knowing their product’s major faults and most frequently appearing comments using a Big Data methodology called the Word Cloud. A Word cloud (tag cloud or weighted list in visual design) is a visual representation of text data, typically used to depict keyword metadata (tags) on websites, or to visualize free form text. The Word Cloud is an algorithm commonly used in big data to bring an image of words with varying font size based on their number of occurrences in a text. Tags are usually single words, and the importance of each tag is shown with font size or color. This format is useful for quickly perceiving the most prominent terms and for locating a term alphabetically to determine its relative prominence. When used as website navigation aids, the terms are hyperlinked to items associated with the tag. Thus, the web application wisely employees the Word Cloud algorithm to form the word cloud image based on the comments and faults provided by the users of the web application.
Distributed Periodic Steady State Kalman Filter

In this paper a distributed implementation for the periodic steady state Kalman filter is proposed. The distributed algorithm has parallel structure and can be implemented using processors in parallel without idle time. The number of processors is equal to the model period. The resulting speedup is also derived. The Finite Impulse Response (FIR) form of the periodic steady state Kalman filter is derived.
PENGEMBANGAN BLOG PEMBELAJARAN MATEMATIKA PADA MATERI PECAHAN DI SEKOLAH MENENGAH PERTAMA

This study aims to develop a product for developing a mathematics learning blog on material in junior high school. The research method used in this research is the research and development method. Research and development are the process of developing a new product or improving an existing product. The data collection tools include a material expert validation questionnaire, a media expert validation questionnaire, and a student response questionnaire. From the results of material expert validation, an average score of 75 was obtained with a good category, the results of media expert validation obtained an average score of 75 with a good category, then the response questionnaire was obtained, namely a positive response with a percentage of 96.18% and a negative response with a percentage of 3.82 %. Based on the data obtained, it can be obtained that the blog development product is as expected and in accordance with the needs and curriculum. The responses that have been submitted to students get a very good response.
RESOURCE MANAGEMENT IN PRIVATE MULTI-SERVICE CLOUD ENVIRONMENTS

The JINR cloud infrastructure hosts a number of cloud services to facilitate scientific workflows of individual researchers and research groups. Although batch processing systems are still the major compute power consumers of the cloud, new auxiliary cloud services and tools are being adopted by researchers and are gradually changing the landscape of the cloud environment. While such services, in general, are not so demanding in terms of computational capacity, they can have spikes of demand and can dynamically scale to keep the service availability at a reasonable level. Moreover, these services may need to compete for resources due to the limited capacity of the underlying infrastructure. This paper discusses how resource distribution can be managed in such a dynamic environment with the help of a cloud meta-scheduler.
Improved Random Forest Method for Mental Health Education

There are serious hidden dangers in the mental health of contemporary higher vocational colleges. In order to solve this situation, an improved random forest method for mental health education is proposed. According to the psychological characteristics of higher vocational colleges, this paper briefly introduces the mental health status of Higher Vocational Colleges in school. Message entropy is a concept in message theory. As the leading organization of vocational education, colleges and universities have absolute responsibility for cultural psychology teaching. Put forward corresponding effective methods for mental health education in higher vocational colleges.