Reviewerly/exHarmony huggingface dataset:
The Impact of Human Capital on Economic Growth: Evidence from Selected Asian Countries

The aim of this paper is to find out the role of human capital in economic growth of selected Asian countries namely Pakistan, India, Bangladesh and Sri Lanka. It is based on time series data for the period 19712013. Ordinary Least Squares (OLS) and Cointegration have been used as analytical techniques for this purpose. The results obtained through Ordinary least Squares show that human capital in form of education affects economic growth in all selected countries except India. The relationship is positive and statistically significant. Moreover, physical capital is another significant determinant of economic growth in the study area. When education is replaced by health as human capital, the OLS results demonstrate a little change showing human capital a significant determinant of economic growth but physical capital in case of India becomes insignificant. In order to avoid the doubt of spurious regression, stationarity was checked by using the Augmented Dickey-Fuller (ADF) test and long-run relationship was analyzed by conducting Johansen Cointegration Test. The Cointegration test results confirmed the existence of long run relationship in human capital (education) and economic growth in Pakistan and Bangladesh. Moreover, there is long run association between human capital in form of health and economic growth in Pakistan, India and Bangladesh. It is therefore concluded that human capital in form of health and education is an important determinant of GDP per capita in most of selected countries. It is, therefore suggested to focus on health and education to reap the economies of sustained economic growth.
Geostatistical Modeling of Electrical Resistivity Tomography for Imaging Porphyry Cu Mineralization in Takht-e-Gonbad Deposit, Iran

This work presents the application of a geostatistical-based modeling approach for building up electrical properties acquired from a geophysical electrical tomography survey deployed for the purpose of porphyry Cu exploration at the Takht-e-Gonbad deposit, in the central domain of Iran. Electrical data were inverted in 2D along several profiles across the main favorable zones of Cu-bearing mineralization to image electrical resistivity and chargeability properties. Upon tight spatial correlation of these geophysical properties and Cu mineralization (i.e. Cu grade), electrical models were constructed in 3D through geostatistical interpolation of 2D inverted data to provide insights into the geometry of probable ore mineralization. Anomalous geophysical zone that was coincident simultaneously with higher values of electrical chargeability and resistivity, was in accordance with the main body of high Cu grades generated from exploratory drillings. It reveals that the porphyry-type Cu mineralization system in this area has strong geophysical footprints controlled mainly by rock types and alterations. Note that these physical models supply valuable pieces of information for designing the layout of further exploratory drillings, constructing geological characteristics, separating non-mineralized form mineralized zones, and resource modeling.
Randomly generated node-state-update procedure for dipole-coupled magnetic reservoir computing with voltage control of the magnetism

We demonstrate reservoir computing using a dipole-coupled magnetic-dot array by simulations with a macro-spin model at 0 K. The magnetic moment of the dot is used for the node state of the reservoir. We perform short-term-memory (STM) and parity check (PC) tasks to evaluate the performance of the reservoir. Binary information was written to the input magnetic dots as a direction of the magnetic moment. A voltage-induced magnetic-anisotropy change was used to update the node state. We investigated the STM capacity (STMC) and PC capacity (PCC) dependence on the number of magnetic dots by means of randomly generated node-update procedures. As a result, the STMC and PCC are strongly dependent on the node-state update procedure.
Variability Features in Building Approaches for Context-Aware Mobile Applications

The growth of mobile applications has been exponential in the last couple of years and it has come with technological advances, such as embedded sensors in mobile devices. This brings out greater challenges in the development of context-aware mobile applications, according to the demands of the current market. Currently, there are building approaches for this kind of applications, but these do not have flexibility in the generated applications. Until now, there is not a unified solution for this kind of applications, so, this is an open research area. This paper presents a taxonomy of variability concepts (Relevance, Combination, Precision and Accuracy’s Margins, Configuration Type, and Execution Type) to be taken into account when designing building approaches for context-aware mobile application. When these approaches are designed from scratch considering these variability concepts, this allows generating a wide variety of applications. The contribution of our taxonomy is to help the designer to identify the potential variability points in order to obtain more flexible approaches. The aim is to generate a discussion in relation to the variability concepts of the proposed taxonomy, this provides guidelines to be able to achieve variability in this kind of approaches. We hope this will enrich the discussion in relation to this kind of approaches in order to the unification of features that should be handled by these building approaches to obtain variability.
VideoWhiz: Non-Linear Interactive Overviews for Recipe Videos

With millions of recipe videos increasingly available online, viewers often face the challenge of browsing through these videos and deciding among different styles of recipe demonstrations and instructions. Although state-of-the-art video summarization techniques using linear presentation formats have been shown to be effective in domains such as surveillance, sports or lecture videos, recipe videos are often more complex and may require a different summarization approach. We first investigated how viewers navigate recipe videos and what information they look for when seeking quick overviews of such videos. Based on our findings, we designed VideoWhiz, a novel interactive video summarization tool that provides a non-linear overview design allowing easy access to the key stages or milestones within the recipe and inter-milestone relationships. VideoWhiz uses a combination of computer vision techniques and an annotation workflow to generate these interactive overviews. Our evaluation showed that viewers found VideoWhiz to be effective and useful in providing quick overviews of recipe videos. We discuss the potential for future work to investigate non-linear overviews for other types of instructional videos and to explore more powerful representations for video summarization.
CATCHA: When Cats Track Your Movements Online

Any website can record its users’ mouse interactions within that site, an emerging practice used to learn about users’ regions of interests usually for personalization purposes. However, the dark side of such recording is that it is oblivious to the users as no permissions are solicited from the users prior to recording (unlike other resources like webcam or microphone). Since mouse dynamics may be correlated with users’ behavioral patterns, any website with nefarious intentions (“cat”) could thus try to surreptitiously infer such patterns, thereby compromising users’ privacy and making them prone to targeted attacks. In this paper, we show how users’ personal information, specifically their demographic characteristics, could leak in the face of such mouse movement eavesdropping. As a concrete case study along this line, we present CATCHA, a mouse analytic attack system that gleans potentially sensitive demographic attributes—age group, gender, and educational background—based on mouse interactions with a game CAPTCHA system (a simple drag-and-drop animated object game to tell humans and machines apart). CATCHA ’s algorithmic design follows the machine learning approach that predicts unknown demographic attributes based on a total of 64 mouse dynamics features extracted from within the CAPTCHA game, capturing users’ innate cognitive abilities and behavioral patterns. Based on a comprehensive data set of mouse movements with respect to a simple game CAPTCHA collected in an online environment, we show that CATCHA can identify the users’ demographics attributes with a high probability (almost all attributes with more than 85%), significantly better than random guessing (50%) and in a very short span of interaction time (about 14 s). We also provide a thorough statistical analysis and interpretation of differentiating features across the demographics attributes that make users susceptible to the CATCHA attack. Finally, we discuss potential extensions to our attack using other user interaction paradigms (e.g., other types of CAPTCHAs or typical web browsing interactions, and under longitudinal settings), and provide potential mitigation strategies to curb the impact of mouse movement eavesdropping.
Prototype of Automatic Braking System on Car Model Using Fuzzy Logic

Car braking system is a very important part of car safety. The effectiveness of conventional braking systems is strongly influenced by the ability and experience of the driver. Car accidents can be avoided if the correct amount of brake pressure is applied at the right time. Therefore it is necessary to use automatic braking system that can anticipate accidents. In this automatic braking system, controlling fuzzy logic is needed to determine the percentage value of the brake that will be performed. The inputs on the fuzzy logic are the speed of the car when moving and the distance between the car and the obstacles in front of it. There are 28 rules used in this controlling fuzzy logic. The rules contain comparisons between the speed of the car when moving and the distance between the car and the obstacles in front of it, the resulting the percentage value of the brake that matches the condition of the moving car. The design of this automatic braking system is made in the form of a prototype car using Arduino Uno R3 as the processor. By using fuzzy logic with 28 rules, the system is capable to stop the car even when it runs at low speed or high speed, with a braking distance about 10cm to 5cm.
Video action recognition based on improved 3D convolutional network and sparse representation classification

In view of the problem that the typical convolutional neural networks fail to model actions at their full temporal extent, a novel video action recognition algorithm, which is based on improved 3D Convolutional Network (iC3D) architecture with K-means keyframes extraction and sparse representation classification (SRC), is proposed in this study. During the feature extraction process, the K-means keyframes extraction is constrained to reduce redundant information generated by continuous video frames and increase the temporal acceptance region. Meanwhile, to improve the noise immunity, sparse coding and its reconstruction errors are used for classification. The proposed method has 96.5% recognition accuracy on the typical video action classification dataset UCF101 that outperforms other competing methods. In addition, we built a wild test dataset to verify the generalization performance of the proposed model.
Solving interdisciplinary tasks: the challenge and the ways to surmount it

Abstract The paper outlines the first steps on the path to identification and systematization of the types of purposeful activity tasks and to the ways to solve them. The authors have been developing a non-traditional interdisciplinary approach and apply it here to the concept of a task as such. This research area shows a good promise, since it enables the development of a framework for a holistic objective interdisciplinary picture of knowledge in any scientific field. The result of the work is the classification of object types and their characteristics, as well as the classification of the latter in the aspect of their relationship to objective reality. This result points out key directions to the systematization of objects, their related task types, and solution methods.
Conceptualizing Factors that Influence South African Students’ Intention to Choose Mobile Devices as Tools for Learning

South African students use mobile devices as information access and interaction tools in their daily lives but seldom use them for learning. The question is why online students minimally choose to use mobile devices for learning despite empirical case study evidence that supports m-learning. To get an answer to this question, this study investigated the factors that influence students’ intention to choose to use mobile devices for learning. The study adopted the Procedure for Conceptual Framework Analysis to carry a literature analysis of selected South African m-learning case studies, ICT policies, educational ICT policies, and grey ICT reports. The result of this study is a proposed conceptual framework that categorizes factors that influence students’ intention to choose to use mobile devices for learning into Country Mobile Phone Environment Factors, Educational Institution Factors, Educator Factors and Student Factors. The categories are valuable for they inform strategic planning and implementation of mobile learning services whilst ensuring the needed cooperation with students at educational institutions.
Salient Points Driven Pedestrian Group Retrieval

Groups are the primary constituent units of crowd and the study on groups can help us better understand the collective phenomena in public area. In this paper, collection of stable individuals with some social relationship in public area, called group, is selected as the research object, and a novel task of pedestrian group retrieval is introduced. Different from the individual person matching, groups often show high aggregation due to their inherent characteristics, individuals in the group are more occluded. Therefore, the performance of individual person based detection and matching will be affected. At the same time, group matching also needs to handle difficulties like variations in the shape and ordering of people within the group. We then design a salient points driven framework for pedestrian group retrieval across non-overlapping cameras. The work focuses on the problems of overall appearance characteristics extraction of a deformable pedestrian collection and matching of groups at varying scales. Experiments on Pedestrian-Groups dataset demonstrate the effectiveness of our proposed framework for Pedestrian Group retrieval.
THE INDONESIAN EFL STUDENTS’ ATTITUDES TOWARD THEIR L1-ACCENTED ENGLISH

In an international communication context, English becomes an International language , commonly known as English as an International Language (EIL). EIL sees various English accents equally because intelligibility, being able to deliver message clearly to listeners, is the main goal in a communication. Therefore, Indonesian EFL (English as a foreign language) students need to focus their English mastery on intelligibility over native-likeness accent when learning English. However, whether or not the students concentrate their English learning more on intelligibility is still unknown yet. To identify which aspects EFL students focus on, the research examined Indonesian EFL students’ attitudes toward their L1-accented English. The main aim is to enhance their awareness that intelligibility is the key component in an English communication. Also, English teachers hopefully discuss the intelligibility in their teaching. Thus, the targeted learning results, particularly related to speaking skills development, are more reachable so the students are more encouraged to develop their English. The study involved 46 students (14 males and 32 females) from University of Muhammadiyah Malang (UMM), East Java. The implemented instrument as a data collection is a questionnaire. The collected data were organized and then analyzed to find out EFL students’ attitudes perceiving their Indonesian-accented English. The researcher figured out that EFL students had less positive attitude towards their own English accent. That perception might be caused by their low linguistic awareness, excessive exposure to the Internet (YouTube, International news) made by native speakers of English. The result of data analysis will be elaborated to interweave the investigation outcomes with classroom context so the outcomes could be implemented in classroom instruction. Keywords: Accent, Intelligibility, EIL and attitude.
Transformation PLM-Systems into the Cyber-Physical Systems for the Information Provision for Enterprise Management

The article proposes a concept of transforming the existing Product Lifecycle Management System (PLM-System) into a Cyber-Physical System for the production and management of an enterprise (in an extended meaning of this term). The concept is based on the study of interaction of product development systems with decision making about the feasibility of transferring relevant processes into an automated digitalization mode. When implementing transformation of a PLM-System into a Cyber-Physical System, it is necessary to investigate the business-processes of the enterprise by developing appropriate models briefly described in the paper. Such transformation, based on introduction of emerging technologies, can be used as the basis for creating a cyber-physical system for managing the entire process lifecycle of the enterprise from a job order and organization of production process to product delivery and support.
La scrittura argomentativa nei manuali di scrittura per il triennio delle scuole superiori

The present paper analyses the way handbooks of writing for the triennium of upper-secondary schools approach argumentative writing. The objective of the analysis is to verify whether currently-used handbooks propose appropriate methodologies, based on efficient and up-to-date linguistic theories.
Panduan Lingkungan Ruang Kelas Berorientasi Multiple Intelegences di Sekolah Dasar

&lt;p&gt;&lt;strong&gt;Abstract:&lt;/strong&gt; The research and development was carried out in class V SDN Sukabumi 2 Probolinggo city and SDN Purutrejo 2 Pasuruan city had the aim of producing a multi-intelligence oriented classroom environment guide product. The research method with Borg &amp;amp; Gall as its model was modified into: (1) information gathering, (2) planning, (3) product development, (4) expert validation, (5) field trials, (6) final products. The results of the study are validation of learning technology experts score 88.3% valid criteria. Validation of linguists score 81.6% valid criteria. Field validation scores 78.5% valid criteria. Conclusion product guide for thematic classroom environment oriented multiple intelligences has a high level of validity, readability, and applicability so that this product matches the theoretical foundation and can be applied in elementary schools. Suggestions for disseminating products to improve the quality of local education.&lt;/p&gt;&lt;strong&gt;Abstrak: &lt;/strong&gt;Penelitian dan pengembangan dilakukan di kelas V SDN Sukabumi 2 kota Probolinggo dan SDN Purutrejo 2 kota Pasuruan mempunyai tujuan menghasilkan produk panduan lingkungan ruang kelas berorientasi multiple intelegences. Metode penelitian dengan Borg &amp;amp; Gall sebagai modelnya yang dimodifikasi menjadi: (1) pengumpulan informasi, (2) perencanaan, (3) pengembangan produk, (4) validasi ahli, (5) uji coba lapangan, (6) produk akhir. Hasil penelitian yaitu validasi ahli teknologi pembelajaran skor 88,3% kriteria valid. Validasi ahli bahasa skor 81,6% kriteria valid. Validasi lapangan skor 78,5% kriteria valid. Kesimpulan produk panduan lingkungan ruang kelas berorientasi &lt;em&gt;multiple intelegences&lt;/em&gt; mempunyai tingkat validitas, keterbacaan dan keterterapan tinggi sehingga produk ini sesuai landasan teoritik dan dapat diterapkan di sekolah dasar. Saran dilakukan penyebarluasan produk untuk meningkatkan kualitias pendidikan setempat.
Communication signal classification and recognition method based on GA-LSSVM classifier

Abstract In order to recognize signals more efficiently and accurately, this paper proposes a method of communication signal classification and recognition based on GA-LSSVM classifier. Firstly, GA algorithm is used to optimize the penalty factor and kernel function parameters of the two main parameters in the model of support vector machine classifier. By constructing a GA-LSSVM classifier for wireless communication signals, combining with the characteristic parameters of modulated signals, the signals are identified and simulated under different SNR conditions, and the analysis and verification are carried out. The performance of GA-LSSVM classifier is studied. The simulation results show that GA-LSSVM classifier has better recognition and classification performance than other classifiers in different SNR environments, and more than 90% accuracy can be achieved when SNR is greater than 0 dB.
Learning from the Individuals and the Crowd in Robotics and Mobile Devices

Service robots at homes or works are expected to upload data that can be used by companies to fix the controllers and improve robot behaviours. Nevertheless, this is a delicate issue that concerns data privacy. Instead, we propose an iterative process of local learning (in the robots) and global consensus (in the cloud) that still preserves the benefits of learning from the crowd but when models instead of data are uploaded to a server. This strategy is also valid for mobile phones or other devices. In fact, in order to work with a heterogeneous community of users, we have applied our strategy in a real problem with mobile phones: walking recognition. We achieved very high performances without the need of massive amounts of centralized data.
Quantum photonics: feature introduction

Photons, the individual quanta of the light field, are what the science of quantum photonics is dedicatedly investigating. The manipulation and coherent control of photons in quantum photonics enables the exploration of various quantum phenomena of high fundamental interest. In the meantime, due to the fast speed and a lack of the interaction with the environment, photons are now regarded as a promising platform for the emerging quantum information processing (QIP) studies. Therefore, there is a growing number of works on quantum computing, quantum communication, and quantum metrology that are solidly based on the techniques of quantum photonics.
Research on American Contemporary Art Review Based on Sentiment Analysis Technology

This paper attempts to use emotional analysis technology to analyze contemporary art criticism. We have collected about 5000 articles from eight journals over the past 60 years. For each article, SnowNLP and TextBlob are used for emotional analysis from three levels: the topic of the article, the abstract and all the sentences in the full text. The abstract is generated by TextRank technology. We calculated the probability density distribution of emotions at three levels for all articles in each year, and found that the proportion of negative emotions was much higher than that of positive ones. We compared the distribution of emotional probability density between different years and found no significant difference. We also conducted an emotional trend analysis of art reviews, and found that thematic emotions began to develop in a positive direction after 2000, while the emotions of abstracts and full-text sentences have basically been developing in a negative direction. The median of all years is lower than the average.