Miracle-dz/UniFAR-FTUs huggingface dataset:
Problems around Accessing Information in Rural Communities

Poverty is known to be a rural phenomenon regardless of developments taking place. Rural communities of underdeveloped countries are regarded to be living in those parts of the country that lack almost all kinds of services and basic needs even worse. Information society should be maintained because information has a significant impact in ensuring development in communities but this is not the case in rural areas because of information poverty caused by lack of means to access it. The study addresses the problems to access information in rural communities. This research explores the problems to access information through ICTs such as computer and Internet in rural communities and proposes guidelines on how to ensure proper access to information for rural residents. Rural communities and the government will benefit a lot from the success of this research. Government is the one that ensures that every citizen has the means to access information in order to bridge the gap of information poverty and digital divide.
KOREAN PROSODIC STRUCTURE AND FOCUS

There seems to be some relation between meaning and intonation. In particular, that the semantic notion of focus can determine prosodic phrasing is by now well documented. In this paper, the effects of focus on prosodic phrasing, f0, and duration are investigated paying attention not only to the target of focus but also to those constituents that are outside the domain of focus. We find that the constituents preceding and following the focused word tend to be dephrased. Dephrasing does not always cover up to the intonational phrase boundary. Syntactic constituency also plays a role in prosodic phrasing. It was shown that dephrasing caused by focus is a main factor determining f0 and durational difference between focused and neutral sentences.
Context Disclosure as a Source of Player Motivation in Human Computation Games

Human computation games (HCGs) enables players to perform real-world tasks as a by-product of playing them. Since these tasks typically require domain knowledge, game designers map them onto simpler ones that non-experts can tackle. In many HCGs, most details on how the game mechanics abstract the task are left undisclosed, leaving players oblivious to how they are truly contributing. One outstanding question is whether revealing such details can promote player motivation. This paper presents a study carried out on Amazon’s Mechanical Turk (AMT) workers using the MATCHMAKERS HCG. The study examined the impact of context disclosure at four levels of granularity: from zero context, the task’s significance, the description of the task, to how the task is accomplished through game mechanics. Based on the study’s findings, AMT Workers were most motivated when receiving the task’s description. This work aims to provide insights into how context can be used to better motivate HCG players. CCS CONCEPTS • Human-centered computing ~ Empirical studies in HCI Author
Educational performance of children from interethnic relationships in Denmark

As inter-ethnic partnerships become increasingly common in Denmark; this study closely examines the effect of these marriages in terms of children’s human capital formation. The aim of this paper is to study the effect of parental ethnic background on educational outcomes in terms of grades from final examinations in the core subjects Danish and Mathematics. This paper uses rich register data, where families are linked together and in order to control for shared factors at the family level, cousin fixed effects are applied. This study is a significant contribution to Scandinavian migration literature since it provides new insights into human capital formation across immigrant generations. Results show a clear gradient of educational performance across immigrant generations. Having one native -and one immigrant parent is more beneficial as compared to having two immigrant parents. Results are less clear when it comes to the importance of the gender of the non-native parent; however parental country of origin seems to be of importance for the educational performance of children from interethnic relationships in Denmark.
Rural tourism and its sociocultural impact on the residents of Casacay , El Oro , Ecuador Turismo rural y su impacto sociocultural en los residentes de Casacay

The lack of tourism services in some areas of the country could be explained by the scant attention paid by the competent bodies that must propose and create promotion and entrepreneurship programs in the rural communities to improve tourism services. The central problem of the limited tourism development in Casacay, El Oro, Ecuador, can be addressed with adequate training, taking advantage of the offer presented in this tourist resort and stimulating the entrepreneurial tourism vision in this area. In this study, field work was undertaken relating to the type of tourism and the perspective that the local residents have of the sociocultural impact this can entail. According to the initial diagnosis, the tourists who arrive in the area are seeking sport activities, handicrafts and memories they can gain from their visit, considering the Casacay river to be the major attraction in the area. The residents are at ease with tourism and are very used to it. Nevertheless, the tourism resource has not been sufficiently exploited to drive sustainable local development that can improve the sector and the quality of life of the residents of Casacay.
The Perfect Match : 3 D Point Cloud Matching with Smoothed Densities Supplementary material Zan Gojcic Caifa

This section provides a detailed explanation of the evaluation metric adopted from [2] and used for all evaluation experiments throughout the paper. Consider two point cloud fragments P and Q, which have more than 30% overlap under ground-truth alignment. Furthermore, let all such pairs form a set of fragment pairs F = {(P,Q)}. For each fragment pair the set of correspondences obtained in the feature space is then defined as
Gender Identification from Facial Images using Local Texture Based Features

With the advancement of biometric identification systems, there is a need to automate tasks such as gender classification so that personal identification can be done with minimal human intervention. Identifying the gender of a subject from his/her facial image poses an interesting research problem for the Machine Learning and Computer Vision community. This report presents gender classification from facial images by extracting texture-based LBP features. Instance-based (kNearest Neighbor), statistical (Support Vector Machines) and connectionist (Neural Networks) learning algorithms have further been applied to the features and a comparitive analysis of the results has been presented. Keywords—Local Binary Patterns, Gender classification, Support Vector Machines, k-Nearest Neighbors, Neural Networks
A Competent Situation of Responsive Intrusion Detection System for Secure Portable Devices

Our point is to talk about various issues in versatile processing, for example, dangers of working cell phones, the issue of keeping up sufficient power in a portable system, cell phone programming dependability, connection mindful and system mindful portable figuring, and cell phone execution. Since the versatile environment includes numerous programming and equipment parts and advancements, it is essential to address numerous pertinent issues. Subsequently, for each of these issues, where proper, we build up a quantitative way to making suggestions for cell phone change. We utilize crude disappointment information reported as a part of the writing to add to a few quantitative appraisals of portable system unwavering quality, in view of sorts of disappointments and reactions to the disappointments. In different cases, for example, setting mindfulness versatile figuring, where there gives off an impression of being no quantitative information relating unwavering quality and execution to the connection of the portable environment. [1]
A Critical Assessment of Scientific and Political Dimensions of the Issue of Community Forests Inventory in Nepal : A Policy Discussion Note

A recently enforced forest inventory directive has been a contentious issue in Nepal's community forestry. This note explores the science and politics that lie behind this issue. It is argued that properly addressing this issue necessitates adopting a scientific approach for resource inventory that is compatible with local knowledge system, while at the same time achieving the desirable level of precision, and separating 'service' from 'regulatory functions' of Department of Forest (DOF).
SHREC 2019 - Monocular Image Based 3D Model Retrieval

Monocular image based 3D object retrieval is a novel and challenging research topic in the ﬁeld of 3D object retrieval. Given a RGB image captured in real world, it aims to search for relevant 3D objects from a dataset. To advance this promising research, we organize this SHREC track and build the ﬁrst monocular image based 3D object retrieval benchmark by collecting 2D images from ImageNet and 3D objects from popular 3D datasets such as NTU, PSB, ModelNet40 and ShapeNet. The benchmark contains classiﬁed 21,000 2D images and 7,690 3D objects of 21 categories. This track attracted 9 groups from 4 countries and the submission of 20 runs. To have a comprehensive comparison, 7 commonly-used retrieval performance metrics have been used to evaluate their retrieval performance. The evaluation results show that the supervised cross domain learning get the superior retrieval performance (Best NN is 97.4 %) by bridging the domain gap with label information. However, there is still a big challenge for unsupervised cross domain learning (Best NN is 61.2%), which is more practical for the real application. Although we provided both view images and OBJ ﬁle for each 3D model, all the participants use the view images to represent the 3D model. One of the interesting work in the future is directly using the 3D information and 2D RGB information to solve the task of monocular Image based 3D model retrieval.
Dengan Pendekatan Extended The Unified Theory of Acceptance and Use of Technology

Technological advances in wireless communications has increased the number of users of mobile devices, it also has accelerated the growth of mobile commerce. Rapidly growing mobile commerce business and increasing consumers to make payments using mobile devices more and strengthen the role of mobile payment as an important application to make payments in this business. Mobile payment now received more attention from consumers in making payments to the merchants as an alternative to using cash or credit cards. The use of mobile payment services provide practicality, convenience, speed and provide comfort in transacting anytime and anywhere. This study aims to determine the factors that influence the intention to use of mobile payment services based on the identification of factors in Extended The Unified Theory of Acceptance and Use of Technology (UTAUT2) model. This study developed a model of the proposed merger UTAUT2 models with perceived risk constructs. The research model was tested using the 165 respondents of the online survey in Indonesia. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results of this study indicate facilitating conditions and price value has an influence on the intention to use mobile payment. Keywords-Mobile payment, UTAUT2, Perceived Risk, PLS-SEM Intisari— Kemajuan teknologi dalam dunia komunikasi nirkabel telah meningkatkan jumlah pengguna perangkat mobile, hal ini juga telah mempercepat pertumbuhan mobile commerce. Tumbuh pesatnya bisnis mobile commerce dan semakin tingginya konsumen melakukan pembayaran dengan menggunakan perangkat mobile semakin menguatkan peran mobile payment sebagai aplikasi penting untuk melakukan pembayaran pada bisnis ini. Mobile payment sekarang ini mendapat perhatian lebih dari konsumen dalam melakukan pembayaran pada merchant sebagai alternatif dari menggunakan uang tunai atau kartu kredit. Penggunaan layanan mobile payment memberikan kepraktisan, kemudahan, kecepatan serta memberikan kenyamanan dalam bertransaksi kapan dan dimana saja. Tujuan dari penelitian ini adalah untuk mengetahui faktor-faktor yang mempengaruhi niat menggunakan layanan mobile payment berdasarkan identifikasi faktorfaktor pada model Extended The Unified Theory of Acceptance and Use of Technology (UTAUT2). Penelitian ini mengembangkan model dengan mengusulkan penggabungan model UTAUT2 dengan construct perceived risk. Model penelitian ini diuji menggunakan 165 tanggapan responden dari survei online di wilayah Indonesia. Data dianalisis menggunakan Partial Least Squares Structural Equation Modeling (PLS-SEM). Hasil penelitian ini menunjukkan facilitating conditions, dan price value memiliki pengaruh terhadap niat menggunakan mobile payment. Kata Kunci-Mobile payment, UTAUT2, Perceived
European Conference on Fracture 2-5 September , 2008 , Brno , Czech Republic Fatigue Fracture and Damage of Engineering Polymers

Abstract. Polymers are very interesting as structural materials in future. The high specific strength is attractive for the reduction of the mechanical systems. We carried out the fatigue tests on the several kinds of polymers to investigate the fracture behavior and the degradation process in the fatigue life. The tested polymers were ABS, PET and PEEK. The fatigue facture was evaluated in the inert and ambient atmosphere and fracture surface was observed through the SEM. The polymers were insensitive to the humidity. The whole fatigue tests were conducted in the condition, where the temperature increase was suppressed within 1 K. The fracture surfaces showed the characteristic features. The dimple patter was observed for the fatigue ruptured PET. The fatigue degradation was evaluated by the measurement of the change in the density and viscoelastic properties. The reduction in the density was observed for PET before the macroscopic fracture. The voids would be generated interior of the specimen and induce the fatigue crack nucleation. Furthermore, the viscoelastic properties changed prior to the fracture. The reduction in fatigue strength can be associated with the increase of the relaxation time. It would suggest that the change of the microstructure would take place during the cyclic loading. The cyclic applied stress would produce the radicals through the breaking of the molecular chains. Then new chemical reaction would bring more complex molecules, which could increase the relaxation time. The increment is proportional to the degradation of the fatigue strength.
Terrain Type Classification Based on Sound

The autonomous mobility of mobile robots has great contribution to human beings exploring hazardous terrains. The motivation of this thesis is to detect different types of terrains traversed by a robot based on acoustic data from the robot-terrain interaction thereby helping to make the mobile robots more autonomous. The acoustic data was collected using a microphone mounted on our robot. Then, these recorded datasets were used to train classifiers so as to distinguish different terrain types from one another. Different acoustic features and classifiers were investigated, such as Mel-frequency cepstral coefficient and Gamma-tone frequency cepstral coefficient for the feature extraction, and Gaussian mixture model and Feed forward neural network for the classification. We analyze the system’s performance by comparing our proposed techniques with some other features surveyed from distinct related works. Thus, we demonstrate the effectiveness of our approach using five different terrain classes which are trained using real data sets gathered from different ground surfaces. The experimental result indicates the average accuracy obtained is approximately 93.6% and it is enhanced to 95.2% with an increase in audio duration. In real applications, it is better to decrease the detection time and our system still has satisfactory performance using human-like terrain labeling even for smaller audio duration. These are very promising results which show that acoustics is an interesting domain that needs to be extensively explored to improve the autonomy of tracked robots.
Supplementary Materials for N A TTACK : Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks

• ADV-TRAIN & THERM-ADV. Madry et al. (2018) proposed a defense using adversarial training (ADV-TRAIN). Specially, the training procedure alternates between seeking an “optimal” adversarial example for each input by projected gradient descent (PGD) and minimizing the classification loss under the PGD attack. Furthermore, Athalye et al. (2018) find that the adversarial robust training (Madry et al., 2018) can significantly improve the defense strength of THERM (THERM-ADV). Compared with ADV-TRAIN, the adversarial examples are produced by the logit-space projected gradient ascent in the training.
Modelling of Graph Databases

Comparing graph databases with traditional, e.g., relational databases, some important database features are often missing there. Particularly, a graph database schema including integrity constraints is mostly not explicitly de ned, also a conceptual modelling is not used. It is hard to check a consistency of the graph database, because almost no integrity constraints are de ned or only their very simple representatives can be speci ed. In the paper, we discuss these issues and present current possibilities and challenges in graph database modelling. We focus also on integrity constraints modelling and propose functional dependencies between entity types, which reminds modelling functional dependencies known from relational databases. We show a number of examples of often cited GDBMSs and their approach to database schemas and ICs speci cation. Also a conceptual level of a graph database design is considered. We propose a su cient conceptual model based on a binary variant of the E-R model and show its relationship to a graph database model, i.e. a mapping conceptual schemas to database schemas. An alternative based on the conceptual functions called attributes is presented.
A Comparison of Oversampling Effects on Imbalanced Topic Classification of Korean Texts

A Comparison of Oversampling Effects on Imbalanced Topic Classification of Korean Texts Yirey Suh Program in Cognitive Science The Graduate School Seoul National University Imbalanced data is a widely-acknowledged problem in supervised learning classification tasks. Oversampling is one way to overcome the problem and there are many methods of oversampling that have been discovered. While researches on the effect of oversampling on other languages have been widely conducted, studies comparing oversampling methods on Korean texts are scarce. This study compares the effect of oversampling methods on the task of classifying Korean internet news articles. This study finds that support vector machines (SVM) and logistic regression reacted with stability and performed best when paired with borderline-SMOTE2 in imbalanced conditions.
A REVIEW ON FINGERPRINT ORIENTATION ESTIMATION METHODS

As a global feature of fingerprint, orientation fie ld plays important roles in most of image preproces sing methods used in automatic fingerprint identification system (AFIS). Many algorithms have been proposed for or ientation field estimation. This paper reviews the advantages and disadvantages of existing fingerprint orientation e stimation methods. Issues on possible directions of further developmen t have been presented.
Research on Image Display and Processing of 3 D Data Scenes

This paper explores graphic image display and processing for 3-D data visualization, and includes the most commonly encountered techniques in practice. Volume rendering is an important class visualization technology and, compared with the geometric surface extraction method of visualizing data from the field, it does not generate intermediate geometric elements, but goes directly to the data overall synthesis. Thus, different content can be displayed simultaneously in one image, to make it convenient for people to carry out comprehensive and integrated field data analysis and research. More obscure weaknesses of imaging volume rendering method are its slow speed and difficulties to express image information. This paper proposes some effective ways to develop volume rendering technology to better visualize and improve people's ability to analyze and understand the data.
Using a self‐organizing map to predict invasive species: sensitivity to data errors and a comparison with expert opinion

Summary 1. Predicting which species are more likely to invade a region presents significant difficulties to researchers and government agencies. Methods for estimating the risk of establishment are often qualitative and rely on consultation with experts and stakeholders. The inherent subjectivity of this process can lead to ambiguities in any estimate of a species’ risk of establishment. 2. Using global presence ⁄ absence data of insect crop pests employed a self-organizing map (SOM) to categorize regions based on similarities in species assemblages. This technique enabled them to generate a list of species and rank them based on an index of the risk of establishment. However, the sensitivity of this risk list to errors in the presence ⁄ absence data has never been tested. 3. We evaluated the sensitivity of the SOM method by altering the original presence ⁄ absence data by increasing amounts and compared estimates of risk with those generated by a national coordinating body (Plant Health Australia) utilizing expert stakeholder opinion. 4. The risk list was unaffected by alterations of up to 20% of data over all regions. The error rate we detected in the data was within these limits. 5. Comparison with the expert stakeholder methodology revealed significant differences in the estimates of establishment risk. Further analysis of the Australian data revealed that a number of regions with strong trade links to Australia supported species assemblages similar to those in Australia, suggesting they are possible sources of pest species with high probability of establishment. 6. Synthesis and applications. This analysis confirms that the SOM methodology is a robust tool in the quantification of risk of establishment. In addition, SOMs can deliver a level of objectivity, which can complement current consultative processes employed by many biosecurity agencies around the world, providing a better overall assessment of invasion risk. This assessment can inform research and development funding decisions and incursion management plans for both government and host industries. While SOMs are utilized in this work for the prioritization of pest insects they can potentially be applied to any taxa (pest or native) or at any scale in which the data are available.