Reviewerly/exHarmony huggingface dataset:
Assessing Arguments with Schemes and Fallacies

We present a logical framework allowing us to express assessment of facts (is it proven?) and arguments (is it sound?) together with a proof system to answer these questions. Our motivation is to clarify the notion of validity in the context of logic-based arguments along different aspects (such as the formulas used and the inference scheme). Originality lies in the possibility for the user to design their own argument schemes. We show that classical inference obtains when arguments are based on classical schemes (e.g. Hilbert axioms). We go beyond classical logic by distinguishing “proven” formulas from “uncontroversial” ones (whose negation is not proven). Hence a formal definition of a fallacious argument: it uses controversial formulas or schemes recognized as illicit. We express some rational arguments and fallacies in the form of schemes.
Characterization of Activated Carbon from Industrial Solid Waste Agar with a Different Activator Concentrations

Production of seaweed processing generates a huge amount of waste, either waste solid or liquid waste. For solid waste contains a lot of organic carbon derived from cellulose or hemicellulose. Therefore, the solid waste that has the potential as a raw material of activated carbon. This study aims to determine the characteristics of the activated carbon produced from solid waste agar and determine the optimal concentration of activator that produced the best characteristics of the activated carbon. The treatment used is a different activator concentration which is designed using completely randomized design (CRD) with five treatments and four replications. The results showed the five treatments are significant differences in the characteristics of the ash and pure active carbon content. This study shows that the manufacture of activated carbon industrial solid waste agar with a different activator concentration influence on the characteristics of the active carbon with ash content parameter and pure active carbon content. The concentration of activator that can provide the highest value of pure activated carbon is in P5 with a concentration of 6 M. Based on this study are advised to do further research on how to lower the ash content of the activated carbon from solid waste agar.
Structuring Tenses of English by Islamic Higher Education Students: A Case Study at Universitas Sains Alqur’an

The aims of this study are to reveal errors in structuring tenses and to find out errors of surface structures committed by Islamic Higher Education Students of Universitas Sains Alqur’an, Wonosobo. Subject of the study is 28 students of Islamic Relegion Education Study Program of Tarbiyah Sciences and Teacher Training Faculty of Universitas Sains Alqur’an, Wonosobo in the first semester of the 2018/2019 Academic Year. Data collecting was conducted through written work instruments. In analyzing the data, the writer reads the data sources, indentifies the errors, classifies them, and especially for tense errors, the writer adds the step of data analysis, namely calculating the errors to find the percentage. The results convey that with regard to tense aspects, the student errors involve simple present 13,54%, present progressive 30,2%, present perfect 28,64%, and present perfect progressive tense 27,6%. Then, with regard to surface structures, the factors of errors committed are omission, addition, misformation, and misordering.
The Character Values of Hard Work in the Novels of Leila S. Chudori

Literary works are a media that has an important role in building character. One of the literary works is novels. A novel contributes the thoughts and ideas of the author through the language that aims to provide benefits to the readers. This study aimed to describe the character values of hard work in the novels of Leila S. Chudori. This was a qualitative research using descriptive qualitative method and content analysis. The data in this research were from the novels of Leila S. Chudori. The research results showed that the character values of hard work of the character were found through the implied words, phrases, and sentences in the novels of Leila S. Chudori. The character values of hard work in the novels could be seen from how the character was persistent to achieve the goals, and able to find solutions for every problem. The characters of hard work reflected from the character could provide a value or message for the readers of the novels of Leila S. Chudori. The characters of hard work found in the two novels were: (1)unyielding attitude, (2) willingness to try, (3) living a life with positive thinking, and (4) character of struggling for life.
Reference-Based Sequence Classification

Sequence classification is an important data mining task in many real-world applications. Over the past few decades, many sequence classification methods have been proposed from different aspects. In particular, the pattern-based method is one of the most important and widely studied sequence classification methods in the literature. In this paper, we present a reference-based sequence classification framework, which can unify existing pattern-based sequence classification methods under the same umbrella. More importantly, this framework can be used as a general platform for developing new sequence classification algorithms. By utilizing this framework as a tool, we propose new sequence classification algorithms that are quite different from existing solutions. Experimental results show that new methods developed under the proposed framework are capable of achieving comparable classification accuracy to those state-of-the-art sequence classification algorithms.
Automated Collagen Segmentation from Masson’s Trichrome Stained Images—Preliminary Results

We propose a new algorithm for automated collagen segmentation from Masson’s trichrome stained images with two steps: color transfer from a known, optimum-stained image, followed by k-means clustering. The algorithm’s output is scored by two proficient pathologists. Results show a good segmentation output (~60%) and strong agreement on pathologist’s opinion on a good segmentation (Cohen’s kappa = 0.8063).
Arbitrary Style Transfer of Facial Image Based on Feed-Forward Network and Its Application in Aesthetic QR Code

QR code has become essential in daily-life because of the popularity of mobile devices. The visual effect of a conventional QR code is not ideal. Consequently, many good aesthetic algorithms have been proposed. However, both the decoding rate and visual effect of a QR code cannot be guaranteed simultaneously when facial image serves as the background. We propose an arbitrary style transfer of facial image based on feed-forward network as a preprocessing algorithm for an aesthetic QR code. The deep characteristics of content image and style image are unified in the same layer of convolutional neural networks in our style transfer network. Styles are changed. The result of style transfer is restricted with semantic segmentation result, color uniform regularization of facial image and repeating restriction similarity constraints. Experimental results show that both the decoding rate and visual effect of a QR code are guaranteed when our method is used in background preprocessing.
Influence of Supply Chain Management on Universities Development: An Outward Glance

This study is devoted to assessing the supply chain management impact on universities promotion and efficiency in international and Russian universities' ratings on their development. The peculiarity of the study is that it considers both universities participating in the competitive recovery program and presented in international rankings, as well as those that do not participate therein. The paper analyzes the rating indicators, the development strategy and the positioning of four Russian universities: Kazan (Volga Region) Federal University (KFU), National Research University Higher School of Economics (HSE), M.T. Kalashnikov Izhevsk State Technical University (IzhSTU) and G.R. Derzhavin Tambov State University (TSU). The research revealed the positive effects of the promotion in the university rankings on their development, among which the following can be distinguished: the formation of a competitive environment within the university, the definition of a specific strategic goal, the attraction of more qualified personnel to the university, including from the international academic market, etc. Negative consequences were revealed too, such as: increase in the workload on teachers, and as a result, reduced attention to the organization of the educational process, higher risk of losing the quality of scientific research, as a result of increasing the number of publications, ineffective spending of the university funds.
Implementation of Six-axis Inertial Measurement Unit on a Stretchable Platform Using �gCut-and-Paste�h Method for Biomedical Applications

Wearable devices that can process and transmit signals from the human body have the potential to provide valuable biometric data for mobile health (mHealth) and human-machine interface (HMI).Among recent advancements in flexible and stretchable electronics, epidermal electronic devices have shown major breakthroughs in wearable device research fields.Epidermal systems, such as tattoo-and patch-type stretchable systems, have conformity to the human skin, which can be deformed with the skin without detachment for fracture.In this paper, the implementation of a six-axis inertial measurement unit (IMU) on a stretchable platform for applications in wearable electronics is presented.The proposed device is implemented using circuit elements on a patchlike substrate to collect accurate data from the human body.To achieve flexible and stretchable characteristics of the device, a serpentine interconnection is adopted between the circuit elements.Instead of a microfabrication process, a low-cost, dry, and freeform "cut-and-paste" method that uses a thin metal sheet and a cutting tool to fabricate complex serpentine interconnections is used to fabricate the substrate.The performance characteristics of the IMU using the proposed method are demonstrated for future application in highly accurate biosensors.
Research and Application of Clothing Recommendation System Combining Explicit Data and Implicit Data

Apparel recommendation algorithms are widely used to solve the problem of clothing information overload and satisfying users' personalized wear requirements. The recommendation algorithm usually adopts a single data type. This paper proposes a recommendation algorithm that combines user explicit data with implicit data. Explicit data in this article uses users preference color, style data, implicit data uses user purchase records, browsing record data, calculated by two data types and feature vectors, obtain user-score high-dimensional matrix, PCA dimensionality reduction for high-dimensional matrix to obtain user scoring feature matrix use the optimized Pearson user similarity algorithm to get a list of recommendations after the Top-N sorting algorithm. The experimental results show that the F1 value of Explicit CF is 0.284, and the F1 value of Implicit CF is 0.265. The F1 value of the proposed algorithm proposed in this paper is 0.321.
THEMATIC PROGRESSION IN RECOUNT TEXT WRITTEN BY THE EIGHT GRADE STUDENTS

This study was about the theme, rheme and thematic progression of students‟ recount text of the eight grade at SMP RK Budi Mulia Pematangsiantar. The aim of this study were (1) to investigate thematic progression pattern used (2) to find out the reason why the students used thematic progression in the way they did. This study was conducted by using descriptive qualitative method. The data in this study were clauses of students‟ recount text. The instrument of collecting data was elicitation technique and interview. The data were analyzed by using interactive model technique of Miles, Huberman and Saldana (2014). The result of this study were the following, (1) There were two patterns of thematic progression used in students‟ recount text, they were Theme Reteration/Constant Theme Pattern (TR/CTP), and Zig-zag/Linear Theme Pattern (Zig-zag/LTP). (2) The reason in use of thematic progression by students, they were: (a) the student‟s lack of knowledge about use of the thematic progression, (b) they also less interested in writing, (c) the students got resources from reading material and (d) the students got resources from english teacher‟s explanation.Keywords: Theme, Rheme, Thematic Progression, Recount Text
IMRPOVING STUDENTS’ READING COMPREHENSION THROUGH RECIPROCAL TEACHING STRATEGY ON NARRATIVE TEXT

This study is a CAR. The objective of this study is improve reading comprehension through reciprocal teaching strategy for the ninth grade student. The researcher answered 2 problem questions of research 1) can the use of reciprocal teaching strategy improve the students’ reading comprehension in the 9th grade of MTs At-Taqwa Cihampelas? 2) How far does the use of reciprocal teaching strategy improve the 9th of MTs AT-Taqwa? Design of the research was CAR. It was conducted in 2 cycles. The teacher analyzed the students’ reading comprehension in each cycle. The results showed that (1) the use of reciprocal teaching strategy can enhance students reading comprehension step by step from cycle 1 and 2. It is proved with the students score, the mean score pretest in cycle I 52.57 and the mean of the posttest in cycle I 63.14.The mean of the post-test in cycle II 71.71.the last cycle means score was categorized as good. The improvements in students understanding indicates that reciprocal teaching strategy is effective and applicable when deals with the students’ problem in reading narrative text.Keywords: Reciprocal teaching, reading comprehension, narrative text.
Human factor in software requirements engineering: Preliminary review of qualitative empirical studies

Software requirements engineering is a field insoftware engineering that highly depends on human factor sinceit includes knowledge and skills from domain of softwareengineering and from the domain of problem where software willbe used, but also from both organizational and social sciencesaspects. Therefore, researching human factor is very importantfor understanding industrial practice and identifyingimprovement directions. Deeper understanding of human factorinfluence on software requirements engineering practice assumesthe use of qualitative research methods. This paper presents apreliminary review of literature that investigates human factor insoftware requirements engineering by using qualitative researchmethods. The presented study contributes to the research field bypresenting a clearly defined process of preliminary literaturereview, and as a pilot study, it will be used for planning detailedand systematic literature review.
INNOVATIVE MOBILE LEARNING: A SCAN OF THE LITERATURE

This paper summarises findings from an initial study completed as the first phase of the Erasmus+ KA2 research project: Designing and Evaluating Innovative Mobile Pedagogies (DEIMP).The purpose of the scoping study was to inform the design and development of a multi-purpose mobile app that will support educators and pre-service teachers in designing and evaluating creative and innovative mobile learning episodes for their students.This first component of the DEIMP study involved the conduct of a Systematic Literature Review to identify innovative and effective practices in m-Learning.A set of 57 articles were identified as reporting on innovative mobile practices and these were further assessed for their level of innovation.The study showed that innovation lies on a continuum from sustaining innovation to disruptive innovation and that disruptive innovation is infrequent.
IMAGE COMPRESSION BY USING WALSH AND FRAMELET TRANSFORM

In this paper, Framelet and Walsh transform are proposed for transformation, and then using arithmetic coding for compress an image. The goal is to achieve higher compression ratio by applying two levels Framelet transform (FLT), and then apply 2D Walsh-Hadamard transform (WHT) on each 8x8 block of the low frequency sub-band, while all other sub-bands are ignored. Experimental results show that the proposed algorithm gets best possible solution for tradeoff between compression ratio (size of image) and quality of compressed image, Peak Signal to Noise Ratio (PSNR). The simulation was carried using MATLAB software package version 2014. In this work, experiments were carried out on the gray scale and colored images
EARTHQUAKE RISK ASSESSMENT IN SIKKIM THROUGH GEOSPATIAL TECHNIQUES

A hazard turns into disaster when the risk or vulnerability of an area is very high.To prevent a disaster from taking further toll on the economy and lives of the population in a particular area it is necessary that we build a risk map of the whole area and then plan the area's livelihood accordingly, this not only increases the coping capacity of the people but also strengthens its economy.Sikkim is an area which is plagued by disasters and there is utmost need that we map the risk zones of the state for various disasters for example earthquake.Remote sensing and GIS serves as a very important platform for analysing the risk and vulnerability of any hazard.
SISTEM PAKAR UNTUK MENGIDENTIFIKASI PENYAKIT MATA DENGAN METODE CERTAINTY FACTOR

Eye disease today is no longer a rare disease suffered by humans. Many symptoms encountered makes people become confused if the types of eye diseases from which they suffer. Type of eye disease that often affects people of Indonesia according to the Ministry of Health is conjunctivitis, Pterygium, Cataract and Glaucoma. It's no secret if in a meeting with the ophthalmologist will cost not less. Expert systems are computer-based systems that use knowledge, facts and reasoning techniques in solving problems that normally can only be solved by an expert in the field. Forward chaining inference engine used in this study to chronicling the symptoms are inconclusive, then the certainty factor method so that we can determine what percentage of the disease in the suffering of patients through the results of the count in the method. Application web-based expert system created to provide information to people with eye disease illness is entered in accordance with the symptoms.
Machine vs Non-Machine Learning Approaches to Cloud Security Solutions: A Survey

Cloud computing is a trending paradigm that provides both physical and logical computational resources as services over the Internet.The basic advantages of the cloud are, a reduction of IT organization's infrastructure cost, flexibility to access and use the services.Regardless of its advantages, it has raised several security concerns such as data availability, data privacy, data location, authentication, authorization, access control, network security, web security, and virtual machine security etc. which may potentially hamper its growth.In recent years, the expansion of several types of dynamic threats such as data breaches, account hijacking, insecure interfaces, advanced persistent threats, shared technology vulnerabilities, and distributed denial of service attacks target the cloud to disrupt cloud services and can compromise security.To tackle several security issues, solutions can be provided through a set of control based technologies such as next generation firewalls, cryptography techniques, intrusion detection systems, software defined networks, machine learning techniques etc.In this paper, we focus on comparative analysis of several cloud security issues through machine learning and non-machine learning approaches.Some open challenges for further research have also been suggested.
Usability Guidelines for an Online Image Database

There are currently no existing guidelines for optimizing user experience in online image databases. Here we use established usability design principles to develop a set of 50 recommendations for improving database organization, navigability, and search functionality. We conduct a resource audit of commercial and non-profit image galleries and evaluate them upon our criteria. Our findings are summarized within a basic wireframe to be used as reference for prospective image databases in the future.
Topological Modifications through Boolean Compositions on Algerbraic Level Sets Constructed from B-rep Models

Sports equipment design is a young and evolving engineering discipline focused on the best simultaneous optimization of user and product as a system.In motorsports, in particular, the final performance during a race depends on many parameters related to the vehicle, circuit, weather, and tyres and the personal feelings of every single driver.Top teams in high-tech categories can invest huge amounts of money in developing simulators, but such economic commitment is not sustainable for all those teams that operate in minor but very popular categories, such as karts or mini-motorcycles.In these fields, the most common design approach is trial and error on physical prototypes.Such an approach leads to high costs, long optimization times, poor innovation, and inefficient management of the design knowledge.The present paper proposes a driver centred methodology for the design of an innovative mini racing motorcycle frame.It consists of two main phases: the drivers' feelings translation into engineering requirements and constraints, and the exploration of the design solution space.Expected effects of the application of the proposed methodology are an overall increase in the degree of innovation, time compression, and cost reduction during the development process, with a significant impact on the competitiveness of small racing teams in minor categories.
Prediction of the chrome distribution in subarctic Noyabrsk using co-kriging, generalized regression neural network, multilayer perceptron, and hybrid technics

Combination of geostatistical interpolation (kriging) and machine learning (artificial neural networks, ANN) methods leads to an increase in the accuracy of forecasting. The paper considers the application of residual kriging of an artificial neural network to predicting the spatial contamination of the surface soil layer with chromium (Cr). We reviewed and compared two neural networks: the generalized regression neural network (GRNN) and multilayer perceptron (MLP), as well as the combined method: multilayer perceptron residual kriging (MLPRK). The study is based on the results of the screening of the surface soil layer in the subarctic Noyabrsk, Russia. The models are developed based on computer modeling with minimization of the RMSE. The MLPRK model showed the best prognostic accuracy.
A Logistics Information System Model of Agricultural Product Based on Cloud Computing

Cloud computing technology can play an important role in the various links of agricultural products logistics system, and provide strong technical support for the development of logistics management. The system architecture of agricultural product logistics information system based on cloud computing is drawn in the paper, which include the base layer, service layer, interface layer and user layer. From the perspective of the system functions, the agricultural product logistics information system based on cloud computing is designed to contain six subsystems of the planting management subsystem, process management subsystem, storage management subsystem, transportation management subsystem, order processing subsystem, consumer query subsystem. It has the features of with the help of the RFID technology, cloud computing technology and data mining technology. We decompose the index evaluation system of the agricultural product logistics information system into twelve scheme layers, and use the analytic hierarchy process to determine the weight of the evaluation indexes of each layer.