Reviewerly/exHarmony huggingface dataset:
Increasingly Complex Techno-Digital Realities in the Dynamics of Scientific Discourse

The article analyzes how factors of accelerating and complicating development of science and technology lead to changes in people's living conditions and, consequently, scientific discourse.The stage of industrial modernization was dominated by monodisciplinary knowledge with pronounced boundaries, which was rather functional for analyzing the realities of specific spheres of human life under the conditions of relatively slow development of the social and natural worlds.Scientists sought to identify "solid" technological, social, and economic correlations, to substantiate "universal" laws of socium and nature in the context of the mechanical picture of the world.However, the acceleration and increasing complexity of the development of science and technology have contributed to start the transition from monodisciplinary to interdisciplinary knowledge.The state of affairs changed significantly in the period of 'reflexive modernization' (Beck, Giddens, Lash), which was expressed in scientific 'turns' -qualitative changes in the production of knowledge in the form of permanently complicating scientific discourse.The 'turns' implied a different methodology of cognition, the rejection of "solid" correlations and "universal" laws, the transition to the interpretation of "liquid" realities (Bauman), the reflexion concerning the "runaway world" (Giddens).The post-modernization, the becoming of 'digital society' mark a radically different trend in the systems of knowledge production and the transition to a post-disciplinary scientific discourse.The main factors of this discourse are: the increasing complexity of acceleration; the formation of a unique socio-technonatural reality, which possesses the qualities of a complex system and develops non-linearly; the complication of risks in the transition from a "risk society" to a "world risk society" (Beck); "new" catastrophes of a " liquid" nature in the form of side effects of pragmatic human activity; the emergence of global cosmopolitanism as a supranational reality; the birth of complex forms of metamorphosis development; the formation of "post-humanism" and the appearance of new approaches to the essence of humanism.However, in the emerging post-disciplinary discourse the limits to knowing in the form of diminution of the intrinsic value of social beings and living entities are still preserved.That is why the author argues for a humanistic turn in all sciences and for postdisciplinarity with a humanistic pivot.
Monitoring of Rainfall Level Ombrometer Observatory (Obs) Type using Android Sharp GP2Y0A41SK0F Sensor

Measurements of rainfall carried out are generally automatic, but how many parties have carried out research using automatic rain gauge instruments.The rainfall level data obtained can be used to detect flooding so that it reduces the occurrence of natural disasters earlier.The principle works are when rain falls the water is collected and the height will be detected.The Sharp GP2Y0A41SK0F sensor will be read on Arduino Uno and pass through the signal conditioning circuit and then forwarded to the Water Pump to pump water so that the water comes out of the tube and the data will be stored.ESP8266, the Wi-Fi module will send data to Android.Measurements are made when the water is full the value of max 53.2 means heavy rain.After the data is obtained, then look for the standard error of the measurement tool for 7 days.The design of the model builds a tool using a funnel with a diameter of 14 cm and a height of 26 cm.Based on the calculation of the design that has been made the measuring instrument developed is able to measure rainfall up to 26000 mm rain height.
Need Analysis on Developing Essay Teaching Material base on Brainwriting Strategy

This research is an analysis of the needs of students and lecturers to determine the basis to be used in developing a product in the form of teaching essays in English. Analysis of this need is a step or procedure that must be done in research and development. This research was conducted at an English Education Program at STKIP Kusuma Negara Jakarta. One of the motivation of researcher to conduct this research is the existence of information on the ability of most students in writing English essays that are still below the average and one reason is because the English essay writing material used is less interesting and difficult to understand, so students not interested in studying thoroughly. With this, researcher was inspired to develop teaching material models for writing essays in English. One of the procedures carried out in developing the teaching material is needs analysis. Based on the needs analysis, the researcher found the characteristics of teaching materials in writing English essays needed by students and lecturers, these characteristics are almost similar to the characteristics of brainwriting learning strategies. Thus a brainwriting strategy will be integrated into the preparation of English essay writing teaching material.
An Investigation into Requirement of Mobile App for Apartment Residents

High-rise residential buildings, such as apartments, flats, and condominiums, are places of shelter for humans, just like any other types of houses. In a high-rise residential block, the building management plays a vital role in keeping the place pristine and habitable for its residents. Research shows that effective communication and harmonious relationship between the building management and the residents are crucial in maintaining a high-rise residential building. A solution needs to be proposed to alleviate this challenge. Traditionally, the mode of information dissemination and communication between the residents and the building management is done manually using information boards and feedback forms. However, their effectiveness, reliability and reachability are questionable. With the increasing adoption of mobile devices and cloud computing in today’s scenario, the application of mobile technologies such as mobile applications has become viable as a solution to many real-world problems. This research studies how information about the happenings around the high-rise residential area is conveyed to the residents that is deemed as an essential part of the communication between the building management and the residents. This study aims to improve overall communication efficiency between the residents and the management parties of high-rise residential buildings by introducing a mobile app for apartment residents. Two data collection methods - observation and questionnaire - were used in this study and inspections were carried out in this research. Representations were made to investigate how the residents of a high-rise building receive information about happenings around the apartment complex and how the building management and residents committee communicate to share the information. The questionnaire survey was distributed to Facebook groups of high-rise residential buildings, particularly those staying in Sri Bahagia Court and Angkasa Condominium, as well as UCSI University network. Based on the results collected from participants, most of the communication was through physical noticeboard or online social media platforms such as Facebook. Hence, this research investigates the requirement of a mobile app and proposes the development of a mobile app for apartment residents (MyAPT), which addresses the problems of information sharing and further improves communication among the residents and management of high-rise buildings.
Model Aggregation Method for Data Parallelism in Distributed Real-Time Machine Learning of Smart Sensing Equipment

In distributed real-time machine learning of smart sensing equipment, training speed and training accuracy are two hard-to-choose trade-off performance measures directly influenced by the design of distributed machine learning algorithms.And it will influence effort of smart sensing equipment directly.We take the model aggregation method of distributed machine learning as a starting point.Due to the loss of accuracy caused by the direct averaging of the parameter average method, we developed the loss function weight reorder stochastic gradient descent method (LR-SGD).LR-SGD uses the loss function value to determine the weight of the work nodes when aggregating the model parameters, and it improves the performance of the parameter average method for nonconvex problems.As shown in the experiment results, our algorithm can improve the training accuracy by a maximum of approximately 0.57% for the Bulk Synchronous Parallel (BSP) model and approximately 6.30% for the Stale Synchronous Parallel (SSP) model.
Analysis of the Quality Problem of Scientific School in the Higher Russian Technical Education by the Graduates and Professors of MSTU “STANKIN”

Higher education reforms can give Russian higher technical schools significant advantages, but at the same time they hide serious dangers. As a result of these reforms, the modern higher technical school in Russia is facing many problems. Firstly, the quality problem: technical education in Russia has always been at a fairly high level, due to its integrity and fundamental nature, so the feasibility of reforms often raises questions. Secondly, the organizational problem: the natural process for higher education in the modernization of education and the consolidation of knowledge in itself is quite complicated. The combination of the modernization process and reform is causing considerable resistance and questions, since it seems insufficiently thought out. Thirdly, the problem of training a creative engineer for the society of the future does not find a solution, because the process of training a specialist is becoming more and more mechanistic. Previously, engineering students within five and a half years had the opportunity to join the scientific community, thanks to the presence of individual work and direct communication with scientists of different generations. Modern communication between professor and student is largely carried out through the electronic environment, so they are more fragmented and mosaic. The lack of real practice in enterprises leads to the fact that students do not receive a live request from production for their creativity. In such conditions, the training of creative technicians is very difficult. It is advisable to reform higher technical education in the light of these problems, so that in the final, Russian education will benefit from them, while maintaining its identity.
[Application and Research of Digital Twin Technology in Safety and Health Monitoring of the Elderly in Community].

In this paper, through the research of digital twin technology, combined with the application of vision sensor, artificial intelligence chip and deep learning algorithm technology, the real-time monitoring and alarm system of elderly fall and abnormal posture based on digital twin technology is developed. The system collects the data of the posture and behavior of the elderly, and then presents them in the cloud by digital mapping after the calculation and analysis of artificial intelligence chip. Once the safety threshold is deviated, the alarm can be activated to avoid or mitigate the injury caused by the fall of the elderly. Through product validation and trial operation of Tianbao Nursing Home in Hongkou District of Shanghai, the user can set alarm thresholds in different time periods and regions, thus achieving the preset purpose of the product.
The Needs of Islamic Digital Resources in Polytechnic Brunei Darussalam: A Preliminary Study

The aim of this study is to identify and analyze the potential usage of Islamic Digital Resources in Polytechnic Brunei Darussalam.This research focus on identifying certain aspects which are (1) types of mobile device used; (2) learning activities that often used in mobile devices; (3) types of social media application favors by student; (4) determining most preferred method of teaching, and; (5) potential use of Islamic Digital Resources.The study uses quantitative approach through survey instrument (questionnaire) that involves 50 students.The data is analyzed using descriptive statistic (percentage frequency distribution and min).Findings show that the potential to create Islamic Digital Resources in Polytechnic is promising.This is based on the compatibility of mobile devices own by students, the familiarity in doing learning activities in mobile devices and willingness to learn through digital.The conclusion is Islamic Digital Resources in Polytechnic is suitable to be developed and applied in teaching and learning.At the end of the study, a few issues regarding the usage of Islamic Digital Resources has been discussed.
The State of Agile Software Development in the Czech Republic: Preliminary Findings Indicate the Dominance of “Abridged” Scrum

This paper presents preliminary results from a survey focused on the state of agile method adoption in the Czech Republic. To this end, an initial survey sample (N = 120) was analyzed. Scrum is the most frequently used agile software development method, reported by 46.7% of respondents as the agile method of choice. However, the results indicate that Scrum seems to be introduced through cherry-picking of those practices that are quite easy to implement. Specifically, the only widely-spread Scrum practice is the maintenance of Product backlog. To the contrary, the teams are rarely cross-functional and the Scrum master role frequently absents. This suggests that in many organizations, Scrum might be invoked due to being a valuable "brand name", rather than due to professionals' subscribing to core Scrum values and assumptions. Our results contribute to the body of empirical knowledge on the state of agile software development initiatives. Our findings confirm the theoretical proposition that in the real world, the implementation of software development methods is often patchy and rarely done "by the book".
Semantic SPA Framework for situational Student-Project Allocation in Education

Web 3.0 technologies have redefined the way classical problems in education are solved.The classical problems are constrained by interoperability challenges that can be addressed using semantic technologies.Student-project allocation (SPA) is one such classical problem in education, whose solution lies in finding a stable matching between student-project pairs.Although many methods exist to solve the SPA problem, recent developments in higher education, such as globalisation, has triggered interoperability challenge because of diversity in student and expert availability across disciplines, campuses, and universities.The author proposes the semantic SPA framework that addresses the interoperability challenge, by leveraging the existing semantic investments made by the educational institutions.The framework standardises the SPA data elements formally using semantic Web concepts, proposes reference ontology for the situational SPA problem, and adopts a semantic Web service approach, using OWL-S, for development.The OWL-S specification enables the automatic discovery, composition, and invocation of the Web services by educational Institutions or semantic agents on the Web, for situational SPA scenarios.
Waste Flooding: A Phishing Retaliation Tool

Phishing is a well known attack technique that is still a growing threat in the security area. The Internet popularity and the always connected users increased phishing possibilities by giving attackers new instruments and allowing closer contact to their focus. By applying social engineering methods, phishing thrives on misinformation and because of this, current main phishing response methods focus only on educating users or blocking phishing attempts, without any response to derail the already implemented attacks. These conditions may leave targeted users unprotected, as any leaked information can not be tracked to determine which person suffered from phishing and compromised data that can not be saved or easily detected. In this paper, we present, analyse and evaluate a new response tool that aims to furtively retaliate these attacks by automatic detecting phishing forms and using them to clutter phishing databases with useless information and conceal user data. The evaluation shows that the tool may be useful as a detection-resistant solution and gives a fair response to phishing attempts by flooding the phishing databases.
Anomaly Detection of Vehicle Data Based on LOF Algorithm

The official vehicle audit is an important issue in the government management, and it is very difficult to detect the potential doubts data in the collected data of official vehicles since most of them are unlabeled data.In this paper, a combination of DBSACN and Local Outlier Factor (LOF) algorithm is proposed for the official vehicle anomaly behavior detection by detecting the abnormal use data of the official vehicle under the same conditions.The detected data is regarded as a doubt data and submitted to the audit department for verification.Since the discrete features of the data set are too much and could not conform to the input type of the algorithm, the features are coded by One-Hot encoding, and a series of operations such as data cleaning and feature calculation are performed, and then compared with DBSCAN, LOF, and isolation forest anomaly detection algorithms.The experimental results show that the proposed algorithm outperforms the isolation forest, LOF and other machine learning algorithms in the anomaly detection of unmarked official vehicle data.
A counterexample regarding “New study on neural networks: The essential order of approximation”

The paper “New study on neural networks: the essential order of approximation” by Jianjun Wang and Zongben Xu, which appeared in Neural Networks 23 (2010), deals with upper and lower estimates for the error of best approximation with sums of nearly exponential type activation functions in terms of moduli of smoothness. In particular, the presented lower bound is astonishingly good. However, the proof is incorrect and the bound is wrong.
Ensuring the Confidentiality of Nuclear Information at Cloud Using Modular Encryption Standard

Lifeblood of every organization is its confidential information. The accentuation on cybersecurity has expanded considerably in the course of the last few years because of the expanded number in attacks at the individual and organization and even at the state level. One specific zone of consideration is the assurance of the security of nuclear information. This may relate to both Instrumentation and Control (I&amp;C) and Information Technology (IT). The present security measures are insufficient for nuclear information because of their lack of identification, classification, and securing measures (because of their multifaceted nature). With the increasing trends of data storage and management with the assistance of cloud, data confidentiality threats are immensely increasing. As there is no such safeguard that can make our systems a hundred percent secure, the best approach is to provide security at distinct layers. The basic purpose of layered security is to have the benefit that if one layer fails or compromised, the other layer compensates or maintains that confidentiality with the access control in the owner’s hand. In this paper, we have proposed a multilevel approach with protection-based computing by using Modular Encryption Standard (MES). We proposed a cloud framework as well to further enhance its security by utilizing a multicloud and modular approach. By performing simulations, the obtained results depicted that our proposed scheme works efficiently than other commonly used schemes.
MEMO: A Deep Network for Flexible Combination of Episodic Memories

Recent research developing neural network architectures with external memory have often used the benchmark bAbI question and answering dataset which provides a challenging number of tasks requiring reasoning. Here we employed a classic associative inference task from the human neuroscience literature in order to more carefully probe the reasoning capacity of existing memory-augmented architectures. This task is thought to capture the essence of reasoning -- the appreciation of distant relationships among elements distributed across multiple facts or memories. Surprisingly, we found that current architectures struggle to reason over long distance associations. Similar results were obtained on a more complex task involving finding the shortest path between nodes in a path. We therefore developed a novel architecture, MEMO, endowed with the capacity to reason over longer distances. This was accomplished with the addition of two novel components. First, it introduces a separation between memories/facts stored in external memory and the items that comprise these facts in external memory. Second, it makes use of an adaptive retrieval mechanism, allowing a variable number of ‘memory hops’ before the answer is produced. MEMO is capable of solving our novel reasoning tasks, as well as all 20 tasks in bAbI.
FAKE REVIEWS DETECTION BASED ON BOTH THE REVIEW AND THE REVIEWER FEATURES UNDER BELIEF FUNCTION THEORY

The online reviews play an increasingly spreading role in consumer purchasing decisions and they are also considered as one of the most powerful source of information for companies.Due to this attraction, manufacturers and retailers rely on spammers to promote their own products and demote the competitors' one by posting fake reviews.Therefore, it is essential to detect deceptive reviews in order to ensure customers confidence and to maintain companies' fair competition.To tackle this problem, we propose a new approach able to spot spam reviews relying both on the rating reviews and the different spammers' indicators under the belief function framework.This method treats uncertainty in the given reviews also in the reviewers' information to take into account each reviewer spamicity when making decision.Experiments are conducted on two real-world review data-sets from Yelp.com with filtered (spam) and recommended (non-spam) reviews to demonstrate our method the effectiveness.
Use of an Ontological Model to Assess the Relevance of Scientific Production

Several institutions do scientific publications, which are used to know the academic and technological level of a teacher, a research group and the institution. In this article, the use of an ontological model is proposed for the representation of the relevance of the scientific production of the most important public university in the southeastern of Mexico. The architecture of the system is presented considering the information gathering from repositories of digital resources, the storage of the data in a document-oriented database and in an ontological one to later represent through SPARQL queries some relevant information about scientific production. The presented results allow to observe the behavior of the scientific production in the analyzed institution and through statistics and graphic representations it is easier to make the decisions corresponding to the production. The shown SPARQL queries are the active researchers, the multidisciplinary publications, the quartiles of citations and the researchers who work in collaboration with other ones that are attached to the same institution. It is intended to establish rules and restricted classes in the ontology to facilitate the representation of the problem and infer instances through an ontological reasoner.