Reviewerly/exHarmony huggingface dataset:
Comparative analysis of IoT device security

Internet of things is one of the latest technology in today’s era, IoT devices are increasing day by day and become a part of our life. Sometimes we even didn’t know that we are using and surrounded by such technolgy. Smart devices like smart phone, tablets and any wearables are the example of IoT technology. These all are IoT devices and there are many more. As we all are in 2020 and facing the pandemic we all are become more connected with IoT devices to be safe. In this way the number of IoT devices per person will increase so much rapidly and several new innovations either of hardware or software take place. But the Internet of Things (IoT) devices are becoming more popular, the security measures are not upto the mark, and several issues will come in knowledge at different time on different devices. So we have to think about the security and privacy of user and should make it correct. We should learn from the past issues and try to fix them accordingly. To overcome the issues of IoT devices we can have to ways, one is to use ECC which will enchance the security in IoT device and another possible solution can be Blockchain. In this paper we will discuss about ECC and blockchain technology both and try to find a comparitive study.
User involvement into the information system design process based on the use of architectural schemes

One of the problems in the field of design and development of information systems remains the problem of transition between models of the subject area and models of the information system. To solve this problem, the concept of involving the end user (domain expert) in the development process is currently being applied. It is assumed that the end user is the main source of knowledge about the subject area, while he has practically no knowledge about the system. On the other hand, the development team has an opposite relationship between domain knowledge and system knowledge. The article discusses in detail the existing models of involving the end user in the process of developing information systems. On the basis of the identified shortcomings, a new model is proposed that does not require additional user knowledge when describing models of the system (the system itself) and allows the user to describe his professional activities in a unified form and in natural language. The article also shows the application of this model, on one of the aspects (development of data transformation logic).
Secure Blockchain with the Internet of Things(S-BIoT) for Modern World Applications

Remote-driven devices are on a high rise in the modern world, leading to data flooding across the Internet. Such devices include electronic and non-electronics one's that are all controlled through a remote, and the data is recorded via sensors that can be analysed at a later point of time to trace the log of all operations. At instances, there may arise a need to enable multiple authorized users to gain access to the log records to identify suspicious activities carried out by intruders who attack confidential data to derive commercial benefit out of it. This situation may arise in various applications like smart home, smart agriculture, smart wearable's, smart automobiles, etc. Hence, there is a need to strengthen the security aspects to overcome the unprecedented loss of confidential information. Towards this end, the proposed work aims to serve the purpose of the integration of the decentralized property of blockchain with data capturing aspects of IoT across a heterogeneous environment in a secure way. Various real-time scenarios are presented in this work to enable the researchers to gain a thorough understanding of the direction of integrating multiple technologies safely and securely. In addition, a broad set of challenges and solutions to overcome the same are also presented to address the real-time security issues in the aforementioned areas.
Proposal of heterogeneous data integration method sediment disaster sensor data and Geospatial statistical data

Data integration method between sensor data and geographical data is important for optimal disaster prevention planning. In this paper, an integration method between underground soil state sensing data and sediment disaster warning information is considered. First, the inference of unknown parameter is formulated using a likelihood function based on Bayes’ theorem. Here, the likelihood function is contained the sensor data rich logic function. Furthermore, the estimators are obtained by an above likelihood function. Moreover, the fundamental operation verification is conducted using the artificial generated data. As the result, basic operation of proposed data integration method is confirmed owing to calculation the estimation value and the posterior probabilistic distribution. In addition, the observation noise and the nonlinear characteristics of sensor are considered.
Recognising spatially and geochemically anomalous arc magmatism (SGAM) and implications for plate tectonic reconstructions

&amp;lt;p&amp;gt;Subduction zones generate volcanic arcs, but there are many examples where magmatism in convergent plate boundaries occurs in unexpected locations relative to the subducting slab. These magmas are commonly also geochemically anomalous relative to the composition of neighbouring typical subduction-related rocks. The origin of such Spatially and Geochemically Anomalous arc Magmatism (SGAM) may correspond to local variations in subduction parameters, the presence of crustal and lithospheric heterogeneities, or the potential contribution of melts generated by slab tearing and slab edge effects. Using the Holocene volcanoes in South America as a case study, we investigated spatial and geochemical patterns of volcanism along the Andean volcanic belt. Based on a series of geochemical indices, we developed a scoring system for the composition of volcanic rocks, with the lowest and highest scores indicating &amp;amp;#8216;typical&amp;amp;#8217; and &amp;amp;#8216;anomalous&amp;amp;#8217; arc melting processes, respectively. The results show that a number of Holocene volcanoes in South America can be unambiguously defined as SGAM. Volcanism in these localities may correspond to disruptions in the geometry of the subducting slab, or to areas affected by mantle flow in the proximity of the slab edge. To test the potential applicability of this method for plate tectonic reconstructions, we calculated geochemical anomaly scores for whole-rock analyses of volcanic rocks from other convergent boundary settings. The results show that high geochemical anomaly scores are obtained in areas where slab tearing has been documented or postulated, such as in Mount Etna (Sicily). The occurrence of anomalous magmatic rocks in older convergent plate boundary settings (e.g., Neogene rocks from the Gibraltar area) corroborates plate tectonic reconstructions that incorporated processes such as subduction segmentation, slab tearing, and the development of asthenospheric windows. Accordingly, we suggest that the recognition of SGAM from other modern and ancient arc settings may inform on similar types of processes, even in cases where the three-dimensional slab structure is no longer detectable.&amp;lt;/p&amp;gt;
A method for the automatic extraction of keywords in legislative documents using statistical, semantic, and clustering relationships

Using smart methods for the automatic generation of keywords in legislative documents has  attracted the attention of many researchers over the past few decades. With the increasing  evelopment of legislative documents and the large volume of unstructured texts, the need for rapid  access to these documents has become more significant. Extracting the keywords in legislative documents will accel-erate the legislative process and reduce costs. Nowadays, many methods are presented dynamically for generating keywords. The present study attempted to extract more meaningful keywords from texts by using the thesaurus, which has a structured system to improve the  classification of legislative documents. In this method, the semantic relationships in the thesaurus and document clustering were used and the statistical features of different words were calculated to extract some words as keywords. After pre-processing the texts, first the keywords in the text were selected using statisti-cal methods. Then, the phrases derived from the keywords were extracted using semantic terms in the thesaurus. After that, a numerical weight was assigned to each word to determine the relative importance of the words and indicate the effect of the word in relation to the text and compared to other words. Finally, the final keywords were selected using the relationships in the thesaurus and clustering methods. In order to evaluate this method, the tested text was compared to educational texts and the similarity between them was used. The results of testing various texts and subjects indicated the high accuracy of the proposed method. The data from the Parliament of Iran and the Deputy for Presidential Laws were used to evaluate the proposed model. This model could provide a very high accuracy and performance in these two bases in comparison to other methods.
NetRL: Task-aware Network Denoising via Deep Reinforcement Learning

Network data in real-world is error-prone, which results in inaccurate results when performing network analysis or modeling such as node classification and link prediction on these flawed networks. In this paper, we target at reconstructing a reliable network from a flawed network, named as network enhancement. Specifically, network enhancement aims to both detect the noisy links which are observed in the network but should not exist in the real world, and predict the missing links that indeed exist in the real world yet being unobserved in the network. Different from existing works that calculate a unified score to measure the above two kinds of links, we propose E-Net, an end-to-end graph neural network model, to leverage the mutual influence of the two tasks to achieve both the goals more effectively. Because on one hand, detecting noisy links can benefit the performance of predicting missing links; and on the other hand, predicting missing links can provide indirect supervision for detecting noisy links when the labels of the noisy links are unavailable. The experimental results on several datasets show that the proposed model obtains significant improvement for predicting missing links and detecting noisy links.
Digital Evidence and the Authenticity to Prove It

Modern communications tools have facilitated financial dealings by easing quick transactions. The current technological means of communication have led to a new type of proof technique called digital evidence. The digital guide has become vital because of its accessibility to everyone. It has provided ease and speed of transactions. It has necessitated resolving its authenticity in civil evidence for financial transactions between individuals through social media. Besides, it is essential to realize the extent of their use in modern civil proofs. The study aims to explain the digital evidence concept. It has listed the digital evidence characteristics, highlighted the legality of the digital evidence presence, and clarified digital evidence's authenticity in civil evidence before the court. Furthermore, it has explained digital evidence forms and described the legal document for the digital proof. After reviewing the digital guide's concepts and the law's position, it has been concluded that the Evidence Department has expanded in the Saudi legislator's view for all logical and convincing evidence. It has incorporated digital proofs and relied upon in some cases pending in its court. Digital evidence has been reflected as the contemporary means of civil proof before the Saudi courts. It is suggested to illuminate the public about the worth of digital evidence. It may require the contribution of media to educate the community regarding the importance of digital evidence.
Teaching Reform and Practice of Higher Vocational English Course under the New Situation

With the continuous development of society, people’s living standards gradually improve. In this new situation, higher requirements are put forward for the English level of higher vocational students. We need to change the traditional teaching mode and the teacher centered teaching mode. In the new situation of higher vocational English teaching, students and teachers are required to take the initiative to cooperate, and teachers, as the guide of teaching, students as the practitioners of learning, the two roles should be integrated, so as to make higher vocational English teaching more efficient under the new situation. This paper first analyzes the necessity of higher vocational English teaching reform, analyzes the current situation of teaching, and finally discusses the teaching reform and practice.
Natural Language Processing Bots in the field of Digital Humanities

My presentation deals with applications of Language Technology for digitization and dissemination of fragile literary material. I focus on my experience working with Special Collections at the SFU Library as part of the SpokenWeb project. While dealing with metadata entry from collections of thousands of poetry readings from tapes stored in the SFU archives, I developed a bot to traverse through the metadata ingestion system in order to make batch edits. My presentation deals with improvements I made to this bot, specifically involving improvements to the Python code and Bash scripts to facilitate large volumes of data, usage of NLP word prediction techniques to fill in gaps in areas with missing data and supervised learning to automate the data entry process. Besides this, I also include considerations of more experimental applications of the field of Computational Linguistics such as lip reading and sentiment analysis. I base this on my experience programming chatbots (with wit.ai) and working with Keras implementations of LipNet as an alternative to text-to-speech in environments with lots of background noise. I believe that these technologies may have a drastic impact on a world that is getting more and more digital every day including accessibility for the deaf, automated language generation and leaps in global connectivity through improvements to translation technology. Through my presentation, I hope to offer a well rounded view into the interdisciplinary field of Computational Linguistics using my own experience as a case study.
Tecnologías del Aprendizaje y el Conocimiento: uso de las Redes Sociales en la Educación Universitaria de Ecuador.

This article is a preview of an ongoing research whose purpose is to generate a theoretical interpretative construct about learning technologies and communication focused on the use of social networks in university education in Ecuador. It is located in the interpretive paradigm under the approach of hermeneutics. The in-depth interview was used to collect information from five selected teachers from the Higher Polytechnic School of Chimborazo, Faculty of Computer Science and Electronics, Graphic Design career. Among the conclusions highlight the university efforts to improve the capacities available to the educational management of social networks, as appropriate tools for research, content feedback and integration of collaborative knowledge.
Penggunaan Internet Sebagai Media Komunikasi Dalam Proses Pelaksanaan Aktivitas Belajar Mahasiswa Di Universitas Dharmawangsa

This study aims to determine the use of the internet and its obstacles as a medium of learning communication in the implementation of learning activities by lecturers to students at Dharmawangsa University. This study uses a qualitative approach, with descriptive methods. The research was conducted at the Dharmawangsa University. The research informants consisted of 6 permanent lecturers and 6 students from 6 faculties. Data collection using interview techniques. The results showed that during the covid 19 period, with online lectures, lecturers and students used learning media provided by Dharmawangsa University in the form of a google classroom with limited facilities that could only convey written materials. To be able to interact directly in the form of oral and video lecturers using Whatsapp media. The obstacles faced by lecturers were problems with the internet network which was sometimes unstable and internet quota, which was also experienced by students. The conclusion of the research on the lecture process using internet media as a medium of learning communication has been able to fulfill online lectures according to the set schedule, it's just that there are still many weaknesses faced in terms of providing internet media facilities so that the lecture process does not run optimally.
Application of Swarm-Based Feature Selection and Extreme Learning Machines in Lung Cancer Risk Prediction

Lung cancer risk prediction models help in identifying high-risk individuals for early CT screening tests. These predictive models can play a pivotal role in healthcare by decreasing lung cancer's mortality rate and saving many lives. Although many predictive models have been developed that use various features, no specific guidelines have been provided regarding the crucial features in lung cancer risk prediction. This study proposes novel risk prediction models using bio-inspired swarm-based techniques for feature selection and extreme learning machines for classification. The proposed models are applied on a public dataset consisting of 1000 patient records and 23 variables, including sociodemographic factors, smoking status, and lung cancer clinical symptoms. The models, validated using 10-fold cross-validation, achieve an AUC score in the range of 0.985 to 0.989, accuracy in the range of 0.986 to 0.99 and F-Measure in range of 0.98 to 0.985. The study also identifies smoking habits, exposure to air pollution, occupational hazards and some clinical symptoms as the most commonly selected lung cancer risk prediction features. The study concludes that the developed lung cancer risk prediction models can be successfully applied for early screening, diagnosis and treatment of high-risk individuals.
Scientometric Analysis of Vikalpa: The Journal for Decision Makers (2008-2017)

This study aims to present a scientometric analysis of the journal titled vikalpa: the journal for decision makers” for the period from 2008 to 2017. The present study was conducted with an aim to provide a summary of research activity in the current journal and characterize its most important aspects. The analysis covers mainly the year wise distribution of articles, category wise classification of papers, authorship patterns of papers, the degree of collaboration, most prolific contributions of papers, institution-wise distribution of contributions and geographical distribution of papers of the journal. The analysis showed that 325 papers were published in the journal of vikalpa: the journal for decision makers” for the period from 2008 to 2017. The maximum number of publication was recorded in 2014 (39 articles, 12.00%) while the minimum was in the year 2017 (21 articles, 6.46%). The authorship pattern was studied to determine the percentage of single and multiple authorship. It is observed from the study that a single author 114(35.08%) paper occupied the 2nd rank. Two author paper 132(40.62%) occupied in 1st rank. Three author paper 41 (12.62 %) occupied in 3rd rank and more than three author paper 38(11.69%) occupied in 4th rank. The study exposes that during 2008-17 the highest proportion of papers were by single authors 114 followed by papers with two authors 211, and more than three authors 325. Among the ten years of the study period, the highest degree of collaboration occurred in the year of 2012. The growth rate is 0.72 in 2008 and which decreased up to 0.07 in 2017. The mean relative growth rate for the periods of 2008 to 2017 the relative growth rate of 0.223. This study period resulted that the mean doubling time for total output 4.088 years. It is observed from the study that the highest number of contributors is belonging to India with 270 articles out of 325 total articles published and its percentage is 83.08 %.
Eclecticism Philosophical Viewpoint of Education: A Teaching Music Philosophy

This analytical essay paper presented the idea of synthesizing the best of several different styles or systems as called eclecticism. Further, it described the eclecticism philosophical viewpoint of education as a teaching music philosophy. The philosophical study of music has many connections with philosophical questions in metaphysics and aesthetics. In this connection, there are three basic philosophical viewpoints in dealing systematically and deeply with the fundamental intellectual issues of life and education; these are not, of course, all-inclusive, such as rationalism, empiricism, and pragmatism. Philosophical viewpoints are examined in relation to four aspects of teaching: curriculum and content, methods of instruction, evaluation, and the roles of teachers and students, to find out the practical effects of these viewpoints on what happens in music classes at a glance. In conclusion, there are different methods and techniques in the teaching of music but there is no definite approach that can be considered the best. There is no standard best procedure for teaching music. Any method, even your own invention, so long as the desired mental effect is produced, is acceptable because, in the teaching of music, reading notes can be syllables, numbers, and letters. The reason for considering philosophical matters or viewpoints is, teachers can do a much better job of understanding fundamental issues and applying them in their teaching, the benefit of the thinking of some of the great philosophical minds - therefore the philosophical viewpoints have devoted their considerable abilities to dealing systematically and deeply with the fundamental intellectual issues of life and education.
Panviz 2.0: AI-driven visual analytics to adapt to the novel challenges of COVID-19

The ongoing and evolving COVID-19 pandemic has resulted in tremendous negative effects on people's daily lives. It is critical for decision makers such as health care officials and governors to foresee potential impacts and make timely decisions. We present PanViz 2.0, a visual analytics application that combines an epidemic model and AI-driven analytics to infer the best-fit parameters to enable the adaptation to ongoing pandemics at multiple spatial aggregations (nation wide, state level, and county level). Our experiments for predicting the fatality cases in each county of the state of Oklahoma demonstrate the flexibility of our application in adapting to various scenarios and regions. © 2021 IEEE Computer Society. All rights reserved.
Geographic Information System Of Land Mapping Certification Of Rice Seeds In Bpsb, Subang Regency

This study aims to analyze the development of a geographic information system for mapping land certification for rice seeds at the Subang District's seed supervision and certification center based on (web gis). The geographic information system for mapping the land for certification of rice seeds at the BPSB (Seed Monitoring and Certification Agency) of Subang Regency is closely related to spatial data. The design or modeling of this system uses a modeling language, namely (Unified Modeling Language), and in its development using a method approach (Rational Unified Process) to determine the system structure's needs. Where the results of this analysis will be a system that will be developed, namely a geographic information system for mapping the land for certification of rice seeds at the Subang District's seed supervision and certification center is expected to simplify and improve performance at BPSB Subang Regency in managing land data so that it has more information value.