Reviewerly/exHarmony huggingface dataset:
American Philosophy in Translation

MetaphilosophyVolume 51, Issue 4 p. 611-617 Book Review American Philosophy in Translation Sami Pihlström, Corresponding Author Sami Pihlström sami.pihlstrom@helsinki.fi Faculty of Theology P.O. Box 4 (Vuorikatu 3) FI-00014 University of Helsinki Finland sami.pihlstrom@helsinki.fiSearch for more papers by this author Sami Pihlström, Corresponding Author Sami Pihlström sami.pihlstrom@helsinki.fi Faculty of Theology P.O. Box 4 (Vuorikatu 3) FI-00014 University of Helsinki Finland sami.pihlstrom@helsinki.fiSearch for more papers by this author First published: 21 July 2020 https://doi.org/10.1111/meta.12441Read the full textAboutPDF 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 Volume51, Issue4July 2020Pages 611-617 RelatedInformation
Modeling and Resource Classification Lateritic Nickel Deposits on a Heterogeneous Block in The Haul-Sagu Area using Estimation and Simulation Geostatistical Method

Abstract Deposits modeling is a very important thing in the exploration field, especially in estimating reserves. This research was conducted to model the geometry of lateritic nickel ore deposition on heterogeneous blocks using the geostatistical estimation method Ordinary kriging (OK) and simulation methods namely, Sequential Gaussian Simulation (SGS) then the distribution of laterite zonation was carried out to calculate the resource and mineral resource classification based on estimation data and simulation. The estimation results using the OK method have an average value of Ni higher than the average Ni grade from the SGS simulation results. Analysis of the calculation of total tonnage of resources from the estimated OK data shows the total amount of measured tonnage of 5,875 tons is far lower than the amount of resource tonnage from the SGS simulation data which displays the total amount of tonnage measured 189,766 tons. However the average grade of Ni from measured OK Resources is 1.49% higher, compared to the average Ni grades from measured resources of SGS 1.33%. with a difference of 0.16% Ni grades. The opposite occurs when the average Fe grade of the measured OK resource is lower 24.15% compared to the average Fe grade of the Measured resource of SGS 32.81% with a very large difference in Fe grade of 8.66%.
Assessing writing performance in TOEFL-iBT

Abstract This study aims to determine the linguistic and discoursal differences in essays produced by Iranian test-takers of TOEFL-iBT in response to integrated and independent writing tasks. A sample of 40 essays, written by 20 Iranian test-takers of scored integrated and independent writing tasks, was compared and analyzed in terms of the four latent constructs of text easability (fourteen variables), cohesion (nine variables), lexical sophistication (nineteen variables), and syntactic complexity (six variables), using the Coh-Metrix 3.0 program. Results indicate differences in the linguistic and discoursal features of integrated and independent writing tasks. The findings reveal that the scores on writing tasks of EFL test-takers can be anchored empirically through the analysis of some discourse qualities like cohesion. Independent tasks contain more connectives and particles so they can result in better discourse structure organization and the generation of more cohesive devices. Stakeholders of the test should verify test constructs in terms of particular contexts like EFL and communicative views of language proficiency. Consequently, the findings contribute to the ongoing validity argument on TOEFL-iBT writing tasks for designing and interpreting scoring schemes for the writing component of the test.
An Analysis Method of Multi Round Interactive Semantics for Power Enterprises Based on Solr Engine

The user experience is the foundation for many enterprises to settle down. One of the key points to improve the user experience is to solve the user’s problems immediately and at any time. Therefore, more and more enterprises have added online customer service and other modules in the service software to respond to customer needs at any time. On the other hand, enterprises must find a balance between improving customer experience and controlling human cost. Automatic response system can achieve zero cost and 24-hour duty, which is limited to most enterprises. However, there are some problems in traditional methods, such as single guessing information, low guessing probability and poor user experience. The purpose of this paper is to provide a multi round interactive semantic analysis method based on Solr engine, which can effectively solve the above-mentioned core problems: single guessing information, low guessing probability and poor user experience. The purpose of this paper is to provide a Solr engine based multi round interactive semantic analysis method for power enterprises. In addition to effectively solving the above core problems, it can also improve the accuracy of the semantic analysis results, so that the user consultation module can get a better user experience, use the multi round interactive semantic analysis method, and output the analysis results of user emotion dimension.
APPLICATION DEVELOPMENT OF VEHICLE COUNTING AND CLASSIFICATION USING YOLOV2

Abstract In this research, we going to introduce a method named You Only Look Once v2 (YOLOv2) for vehicle detection and vehicle classification. The vehicle is going to classify is divided by 4 there are car, motorcycle, truck, and bus. The result of classified data it can provide data for Intelligent Transportation System (ITS) to engineering the traffic road to reduce the number of traffic jam in the big city. With this method we can receive higher accuracy and performance than another method proposed before. By using data consist of 21198 objects for training, from all that data there is consist of 8936 cars, 462 buses, 1681 trucks, and 10119 motorcycles. Then from all that data we can created some weight that took for 10 hours for training so that we can receive mean Average Precision (mAP) for 60.63 % mAP and higher performance detection with frame rate 20 up to 35 frame per seconds which is almost equal to real-time.
Augmented Reality Technology Key Technologies Research

Human-computer interaction technology has been gradually transferred from computer-centered to user-centered and virtual and real interaction in augmented reality technology is a prominent manifestation. Augmented reality technology is a new technology developed on the basis of virtual reality technology and a new development of virtual reality technology. Augmented reality emphasizes the seamless integration of real world information and virtual world information with real-time interaction. In recent years, with the rapid development of computer graphics and computer vision technology, augmented reality based on computer vision technology has shown great advantages, not only simple equipment, low cost, and can effectively ensure the application of augmented reality real-time, accurate requirements. This paper introduces a series of methods in the interaction of augmented reality technology from four aspects: 3d registration, interactive technology, system development platform and virtual object modeling. This paper mainly introduces several common methods in visual based 3d registration technology and augmented reality interactive system, and finally introduces TARToolKit development platform.
Augmented Data Prediction Efficiency for Wireless Sensor Network Application by AI-ML Technology

Practical wireless sensor network (WSN) demands cutting-edge artificial intelligence (AI) technology like deep learning (DL), which is the subset of AI paradigm to impart intelligence to end devices or nodes. Innovation of AI in WSN aids the enhanced connected world of internet of things (IoT). AI is an evolving area of intelligent learning methodologies by computers via machine learning algorithms (MLA). This chapter entirely deals with the implementation of AI technologies in the areas of advanced machine learning, language recognition using natural language processing (NLP), and image recognition through live example of machine learning. MLA are constructed to predict optimized output by giving training dataset inputs. In image recognition, an outcome model utilizing the existing reference model to predict DL-based AI prediction. Complex DL AI services is achieved by Bluemix sole power-driven Watson studio and Watson Assistant Service. Application programming interface keys are designated to connect Watson and Node Red Starter (NRS) to provide the web interface.
Exploring Social Media User Emotions And Emoticons Use Among Malaysia Universities

Abstract Expressing emotions through Twitter has been the norm to social media users especially university students. Emoticons has been used in their Tweet to represents their emotions to current issue. Emolyzer has been used to extract the Tweet of five active Malaysia universities community Twitter account which are USM, UTM, UKM, UiTM and UUM. With a variety of emoticons, people find it interesting as there are so many emoticons to symbolize different emotions. Different social media may differ in emoticons used, so the observation of frequently used emoticons in Twitter is a must. These emoticons are then categorized into happy, sad, annoying, angry and surprise. As a result, each different sentiment between these five universities can be compared. The study shows that USM has the highest percentage of happy while UiTM has the highest percentage of sad. This finding can be used to guide universities social media administrator to strategize in content strategy in social media.
Explainable and unexpectable recommendations using relational learning on multiple domains

In this research, we combine relational learning with multi-domain to develop a formal framework for a recommendation system. The design of our framework aims at: (i) constructing general rules for recommendations, (ii) providing suggested items with clear and understandable explanations, (iii) delivering a broad range of recommendations including novel and unexpected items. We use relational learning to find all possible relations, including novel relations, and to form the general rules for recommendations. Each rule is represented in relational logic, a formal language, associating with probability. The rules are used to suggest the items, in any domain, to the user whose preferences or other properties satisfy the conditions of the rule. The information described by the rule serves as an explanation for the suggested item. It states clearly why the items are chosen for the users. The explanation is in if-then logical format which is unambiguous, less redundant and more concise compared to a natural language used in other explanation recommendation systems. The explanation itself can help persuade the user to try out the suggested items, and the associated probability can drive the user to make a decision easier and faster with more confidence. Incorporating information or knowledge from multiple domains allows us to broaden our search space and provides us with more opportunities to discover items which are previously unseen or surprised to a user resulting in a wide range of recommendations. The experiment results show that our proposed algorithm is very promising. Although the quality of recommendations provided by our framework is moderate, our framework does produce interesting recommendations not found in the primitive single-domain based system and with simple and understandable explanations.
Designing the QuickCash Payment System prototype by using cash withdrawal services through minimarket as an alternative solution for secure money transfer from bank customers to non-bank customers

Abstract In this era wich has many electronic payment facilities, it is noted that the need for cash in Indonesia is still high and bank customers are still relatively small. This shows that Indonesians need money transfer services from bank customers to non-bank customers. As an alternative to meeting these needs, Alhothaily, et al. put forward a QuickCash payment system that allows bank customers to transfer money to non-bank customers. Therefore, in this study, the prototype design of the QuickCash payment system was made to facilitate the transfer of money. According to Alhothaily, et al. QuickCash payment system is a payment system that makes it easy for users to transfer money. To prove this statement, the prototype design of the QuickCash payment system was built using the SSDLC methodology and tested the QuickCash payment system prototype by collecting data using a questionnaire. Based on the test results with a significance level of 5%, all respondents agreed that the QuickCash payment system made it easy for users to make money transfers.
Prediction Method of Basketball Players’ Shooting Rate Based on Quantum Search Algorithm

The traditional basketball players’ shooting rate prediction algorithm adopts quantum algorithm, which is easy to cause information divergence and fall into local extremum when dealing with the statistical data of large scale basketball players’ shooting rate, the accuracy of prediction of shooting rate of basketball players is not high. An adaptive learning based quantum evolutionary search (QEP) algorithm is proposed to predict the shooting rate of basketball players. The statistical data regression model of basketball players’ shooting rate is constructed, and the statistical characteristic sequence analysis of basketball players’ shooting rate is carried out. The quantum optimization algorithm is used to compare whether the frequency fluctuation in the information flow is the same or not in the statistical regression analysis of shooting hit rate, the same one is merged, and the quantum search algorithm is designed based on the fuzzy C-means clustering algorithm. Based on the adaptive learning quantum evolutionary search algorithm, the statistical data of basketball players’ shooting rate are projected into the high-dimensional phase space, and the real-time prediction optimization of the basketball players’ shooting rate is carried out. The simulation results show that the algorithm has higher accuracy and less error in predicting the shooting rate of basketball players, and it has a better application value in basketball training.
Image clustering using genetic algorithm with tournament selection and uniform crossover

Abstract This study aims to test genetic algorithm with tournament selection and uniform crossover for clustering complicated images. Genetic algorithm can be used for searching the optimum centroid for clustering images. Images that used in this study is beach images, city images, traditional market images, and garden images. Based on the research result genetic algorithm with tournament selection and uniform crossover can be used for clustering images but there is some outlier in formed cluster. Based on trial the best parameters for image clustering with genetic algorithm with tournament selection and uniform crossover is population=200, iteration=200, and number of cluster=2. Fitness value on genetic algorithm is increase when population and iteration value are higher. The result of this study can be used as a reference in the development of images clustering.
Efficient Context-aware File System Approach

With the rapid development of science and technology, wireless networks are now widely used throughout the world. Given the requirement to improve the usability of computers, a context-aware file system has been rendered as an important research topic. Enhanced methods must be proposed to improve the accuracy of user authority in such systems. In this study, we introduce a combined approach involving the historical and physical user contexts to gain the contextual information for the file system. We proposed a role-based access control (RBAC) based on context awareness model, which is an extension of the traditional RBAC model, to implement context awareness in the users' permission for the file system. Using the context constraints, the file system can control the access of the user to protect the file system from damages caused by hackers. Results showed that the proposed method is more accurate than traditional ones because it can control the user access through context awareness.
DESIGN AND IMPLEMENTATION OF WECHAT APPLETS AIRCRAFT BATTLE

With the rise and development of WeChat applets, their convenient features are very popular with users, making their number of users develop rapidly. With the emergence of small games in WeChat applets, more and more non-game players are also attracted. This article is about a classic flight shooting game " Airplane Wars" developed by WeChat developer tools and JavaScript language. It mainly uses canvas drawing and sprite wizard to detect collisions and other functions. It can realize smooth human-computer interaction and animation rendering. It has rich game elements and high playability.
Concept design for adjustable motorcycle handlebar

Abstract Transportation in this modern era became one part of human’s daily lives. It helps people travel from one place to another. As a part of technology, transportation technology keeps on developing everyday, increasing the capability of human’s physical limits. This article was conducted as an attempt to create a design concept of an adjustable motorcycle handlebar. Design process is done by initially searching for customer feedback through survey, then selecting materials used in the concept, adjusting the specifications of the concepts and creating a 3D model of the designs. The design of the adjustable handlebar of the motorcycle is created by using Aluminium Alloy 7075 as the primary material, and uses a railing design to grant parallel movement to the handlebar. Results of the concept designing process includes the 3D model of an adjustable handlebar, in which concept could be used in further design processes.
On multivariate polynomials with many roots over a finite grid

In this paper, we consider roots of multivariate polynomials over a finite grid. When given information on the leading monomial with respect to a fixed monomial ordering, the footprint bound [Footprints or generalized Bezout’s theorem, IEEE Trans. Inform. Theory 46(2) (2000) 635–641, On (or in) Dick Blahut’s ‘footprint’, Codes[Formula: see text] Curves Signals (1998) 3–9] provides us with an upper bound on the number of roots, and this bound is sharp in that it can always be attained by trivial polynomials being a constant times a product of an appropriate combination of terms consisting of a variable minus a constant. In contrast to the one variable case, there are multivariate polynomials attaining the footprint bound being not of the above form. This even includes irreducible polynomials. The purpose of the paper is to determine a large class of polynomials for which only the mentioned trivial polynomials can attain the bound, implying that to search for other polynomials with the maximal number of roots one must look outside this class.
Shape Classification Using Randomized Neural Network Descriptors Extracted from the Fourier Spectrum

The study of shape objects, in special, its description and recognition is a field of intense research in computer vision. This paper presents a novel approach for shape descriptor based on two methods: the randomized neural network (RNN), which has a single hidden neuron layer and a training algorithm much faster than the traditional backpropagation approach, and the Fourier transform, a traditional signal analysis tool that enables us to decompose a signal into its frequencies. By combining these methods, we are able to compute a robust shape signature, which is capable of recognizing very different types of images, from occluded shapes to large sets of images under affine transformations. We compared the proposed approach with several shape analysis methods. The results indicate that our proposed approach can be successfully applied in different shape analysis problems.
Seamless Long-Tail and Big Data Access via the EarthCube Brokering Cyberinfrastructure BALTO

Earth and Space Science Open Archive PosterOpen AccessYou are viewing the latest version by default [v1]Seamless Long-Tail and Big Data Access via the EarthCube Brokering Cyberinfrastructure BALTOAuthors D. Sarah Stamps iD James Gallagher iD Scott Peckham iD Anne Sheehan Nathan Potter Kodi Neumiller iD Emmanuel Njinju iD Maria Stoica Zachary Easton Daniel Fuka David Fulker iDSee all authors D. Sarah StampsiDCorresponding Author• Submitting AuthorVirginia TechiDhttps://orcid.org/0000-0002-3531-1752view email addressThe email was not providedcopy email addressJames GallagheriDOPeNDAPiDhttps://orcid.org/0000-0002-0311-202Xview email addressThe email was not providedcopy email addressScott PeckhamiDUniversity of Colorado BoulderiDhttps://orcid.org/0000-0002-1373-2396view email addressThe email was not providedcopy email addressAnne SheehanUniversity of Colorado Boulderview email addressThe email was not providedcopy email addressNathan PotterOPeNDAPview email addressThe email was not providedcopy email addressKodi NeumilleriDOPeNDAPiDhttps://orcid.org/0000-0003-4486-1825view email addressThe email was not providedcopy email addressEmmanuel NjinjuiDVirginia TechiDhttps://orcid.org/0000-0002-3406-5641view email addressThe email was not providedcopy email addressMaria StoicaUniversity of Colorado Boulderview email addressThe email was not providedcopy email addressZachary EastonVirginia Techview email addressThe email was not providedcopy email addressDaniel FukaVirginia Techview email addressThe email was not providedcopy email addressDavid FulkeriDOPeNDAPiDhttps://orcid.org/0000-0001-8791-1306view email addressThe email was not providedcopy email address
Establishment of an application for photographs’ quality detection based on sharpness and light intensity

Abstract Along with the booming of digital photography, camera users grow significantly, especially the users of digital single-lens reflex (DSLR) camera. There are many new users who apply their DSLR cameras for the first time and have little knowledge how to use them. That’s why an application is needed to guide a novice user so that he/she could get better understanding about photography. We have an idea to create such a guidance application that can provide evaluation and suggestion about the quality of user’s photographs. Thus, users can easily develop the ability of photography. Overall, the level of accuracy of this application in identifying deficiencies in the pictures taken is about 75%. This level of accuracy is calculated from errors that occur in detecting both sharpness of the pictures and light intensity (exposure) of the pictures, or any one of them. The errors in detecting the conditions of pictures, occur in some pictures. Hence, it needs further development of methods to improve the accuracy in all conditions of pictures taken. Best accuracy is necessary so that the proper suggestion is given by the application in accordance with the actual condition of the picture.
Discussion of the Higher Vocational English Teaching in the Informatization Digital Network

Since entering the new era, informational teaching has become more and more important. In order to promote English teaching in higher vocational colleges, higher vocational colleges should make full use of multimedia technology and internet information technology to improve the quality of English teaching. This paper discusses the development of English informatization digital network teaching in higher vocational colleges, and discusses the methods of English informatization teaching in higher vocational colleges, aiming to provide some reference for further improving the informatization teaching of higher vocational English.