Reviewerly/exHarmony huggingface dataset:
On the Use of Emojis to Train Emotion Classifiers

Nowadays, the automatic detection of emotions is employed by many applications in different fields like security informatics, e-learning, humor detection, targeted advertising, etc. Many of these applications focus on social media and treat this problem as a classification problem, which requires preparing training data. The typical method for annotating the training data by human experts is considered time consuming, labor intensive and sometimes prone to error. Moreover, such an approach is not easily extensible to new domains/languages since such extensions require annotating new training data. In this study, we propose a distant supervised learning approach where the training sentences are automatically annotated based on the emojis they have. Such training data would be very cheap to produce compared with the manually created training data, thus, much larger training data can be easily obtained. On the other hand, this training data would naturally have lower quality as it may contain some errors in the annotation. Nonetheless, we experimentally show that training classifiers on cheap, large and possibly erroneous data annotated using this approach leads to more accurate results compared with training the same classifiers on the more expensive, much smaller and error-free manually annotated training data. Our experiments are conducted on an in-house dataset of emotional Arabic tweets and the classifiers we consider are: Support Vector Machine (SVM), Multinomial Naive Bayes (MNB) and Random Forest (RF). In addition to experimenting with single classifiers, we also consider using an ensemble of classifiers. The results show that using an automatically annotated training data (that is only one order of magnitude larger than the manually annotated one) gives better results in almost all settings considered.
A comparative study for two newly developed estimators for the slope in the functional EIV linear model

Two estimators were recently developed for the slope of a line in the functional EIV model. Both are unbiased, up to order $\sigma ^4$, where $\sigma$ is the error standard deviation. One estimator was constructed as a function of the maximum likelihood estimator (MLE). Therefore, it was called the Adjusted MLE (AMLE). The second estimator was constructed using a completely different approach. Although both the estimators are unbiased, up to the order $\sigma ^4$, the latter estimator is much more accurate than the AMLE. We study these two estimators more rigorously here, and we show why one estimator outperforms the other one.
Enso: A general-purpose virtual machine

In this paper we introduce Enso, a virtual machine designed to be used as general-purpose state transition function in blockchains. This design allows the blockchain application logic to be coded into the state, instead of into the state transition function, making it much more flexible and easier to modify. A byproduct is reducing the frequency of forks, concerted or not.
Profitable Double-Spending Attacks

Our aim in this paper is to investigate the profitability of double-spending (DS) attacks that manipulate an a priori mined transaction in a blockchain. It was well understood that a successful DS attack is established when the proportion of computing power an attacker possesses is higher than that the honest network does. What is not yet well understood is how threatening a DS attack with less than 50% computing power used can be. Namely, DS attacks at any proportion can be of a threat as long as the chance to making a good profit exists. Profit is obtained when the revenue from making a successful DS attack is greater than the cost of carrying out one. We have developed a novel probability theory for calculating a finite time attack probability. This can be used to size up attack resources needed to obtain the profit. The results enable us to derive a sufficient and necessary condition on the value of a transaction targeted by a DS attack. Our result is quite surprising: we theoretically show that DS attacks at any proportion of computing power can be made profitable. Given one's transaction size, the results can also be used to assess the risk of a DS attack. An example of the attack resources is provided for the BitcoinCash network.
STEFANN: Scene Text Editor using Font Adaptive Neural Network

Textual information in a captured scene plays an important role in scene interpretation and decision making. Though there exist methods that can successfully detect and interpret complex text regions present in a scene, to the best of our knowledge, there is no significant prior work that aims to modify the textual information in an image. The ability to edit text directly on images has several advantages including error correction, text restoration and image reusability. In this paper, we propose a method to modify text in an image at character-level. We approach the problem in two stages. At first, the unobserved character (target) is generated from an observed character (source) being modified. We propose two different neural network architectures - (a) FANnet to achieve structural consistency with source font and (b) Colornet to preserve source color. Next, we replace the source character with the generated character maintaining both geometric and visual consistency with neighboring characters. Our method works as a unified platform for modifying text in images. We present the effectiveness of our method on COCO-Text and ICDAR datasets both qualitatively and quantitatively.
IMPLEMENTASI ALGORITMA FLOYD WARSHALL PADA APLIKASI PENGADUAN MASYARAKAT BERBASIS ANDROID

Public complaints are complaints from the public, Government Agencies or other parties verbally or in writing containing information, complaints, dissatisfaction or irregularities in the performance of the National Police that require further handling and settlement. In conducting complaints, the community usually uses short messages (sms) or telephone so that the community must have a personal contact number of the police member who can be contacted. To make it easier for the public to make complaints, a complaint application is needed to find out the policeman to be contacted. Application that will be developed based on preliminary research that took place at Kuningan Police Station. Mobile-based applications that are needed a lot in searching for police and the location of traffic accidents and providing a description of pastoral events. The application that is created only shows the location of the accident in Kuningan Regency. In finding the nearest route, it will be displayed in the form of maps. The police can choose directions from the details of the complaint, then the system will display the results in the form of a route on maps. In this application there is also a service to find out the location of the community by using GPS technology. And the author uses the Floyd Warshall algorithm to determine the nearest police station and determine the route from the location of the police station to the scene. As well as in storing data in this application the author uses MySQL or phpMyAdmin as a web server in storing event data and police data, notifications and reports concerned with the complaint application. And in the development of this application is based on client-server.Keywords: Floyd Warshall Algorithm, GPS, Kuningan Regency, Mobile, MySQL, Police station, phpMyAdmin, Web Server, Community
Interrelation of Enthusiasm for Work and Professional Burning Out at Teachers of Engineering Higher Education Institution

The teacher of the higher school needs to create a training environment now. It assumes not only knowledge of a subject, but an opportunity to build up the personal relationship with students. It is possible under a condition when in educational process participants feel satisfaction, but not a stress. But professional burning out also is also characteristic of teachers. It leads to a negative side of activity. It is possible to prevent development of burning out, if constantly to hold the training seminars on development of the emotional sphere and development of positive motivation of professional and pedagogical activity with teachers.
Using Test Technologies In The Conditions Of Informatization Of Higher Education

This paper studies development and introduction of testing technologies to encourage individual learning and cognitive activities of students in the conditionsof computerization of education. The authors described a possibility to develop new ways of using information and communication technologies provided by different packages of application software. The paper presents a possibility and ways of applying the acrotex package to develop interactive training materials. The authors describe how to use testing materials for efficient individual work of students. The authors have developed a set of original electronic learning and teaching materials, containing forming tests. Developed materials allow university teachers to apply an individual approach to training, and monitor a progress of learning quickly and impartially.
Analysis of Cryptographic Protocol by Dynamic Epistemic Logic

The security of the cryptographic protocols has always been important to ensure proper implementation of a protocol. To assure protocol security, a number of works for analysis and verification of cryptographic protocols have emerged in the literature. In this paper, with dynamic epistemic logic, we propose a model approach to analyze a cryptographic protocol. In order to capture the security properties of the protocol, we present the update of the epistemic states based on the epistemic actions. The epistemic actions lead to changes in the knowledge set of the agents participating in the protocol. We model this execution process of the specific example of the cryptographic protocol using the Kripke models and the transition between states. The result of analysis demonstrates that this cryptographic protocol conforms to the security requirements.
Detect Malware in Portable Document Format Files (PDF) Using Support Vector Machine and Random Decision Forest

Portable Document Format is a very powerful type of file to spread malware because it is needed by many people, this makes PDF malware not to be taken lightly. PDF files that have been embedded with malware can be Javascript, URL access, media that has been infected with malware, etc. With a variety of preventive measures can help to spread, for example in this study using the classification method between dangerous files or not. Two classification methods that have the highest accuracy value based on previous research are Support Vector Machine and Random Forest. There are 500 datasets consisting of 2 classes, namely malicious and not malicius and 21 malicius PDF features as material for the classification process. Based on the calculation of Confusion Matrix as a comparison of the results of the classification of the two methods, the results show that the Random Forest method has better results than Support Vector Machine even though its value is still not perfect.
Based on "the Belt and Road" Exploration of Higher Vocational Education Internationalization

Under the brand-new pattern of â€œOne Belt, One Roadâ€ construction and strengthening innovation and opening cooperation, higher vocational education has been officially incorporated into the â€œDouble First-Classâ€ initiative construction plan, making the â€œBelt and Roadâ€ service an inevitable trend and important way for the development of vocational education in China. The Hanzhong Vocational and Technical College takes the opportunity of international cooperation and development, starting with the development needs of the current era background, combining the practical experience of the college's international education cooperation and exchange project, actively exploring the advantages of multi-specialized skills education and regional service, and improving vocational education. The quality of education for internationalization, high-tech and high-skilled personnel training has achieved certain results and is worthy of exchange and promotion.
The overview analysis of the movie Sense and Sensibility

Movies have been everybody�s favorite across all ages. Some movies are not suitable for certain ages and the parents� assistance is needed during the watching movie process so that they can show the morals conceived in the movie. This study tries to shed lights on the elements contained in �a movie entitled �Sense and Sensibility�, �a movie made based on a novel by Jane Austen. This study was carried out in qualitative approach using visual feature analysis technique. The object of this study was the movie with the duration of 140 minutes. The data obtained were then classified based on its elements such as realism, local color, narratives, and symbolism. The result portrayed that the realism given in this movie is the condition of a noble family who had lost all of their wealth and life had been becoming crude. The local color depicts the social status in the mid-eighteenth century. The story was narrated in the linear plot and finally, the symbolism in this movie exposed much about the calming and melancholic nature of Devonshire.
Resolving Conflicts for Lower-Bounded Clustering

This paper considers the effect of non-metric distances for lower-bounded clustering, i.e., the problem of computing a partition for a given set of objects with pairwise distance, such that each set has a certain minimum cardinality (as required for anonymisation or balanced facility location problems). We discuss lower-bounded clustering with the objective to minimise the maximum radius or diameter of the clusters. For these problems there exists a 2-approximation but only if the pairwise distance on the objects satisfies the triangle inequality, without this property no polynomial-time constant factor approximation is possible, unless P=NP. We try to resolve or at least soften this effect of non-metric distances by devising particular strategies to deal with violations of the triangle inequality (conflicts). With parameterised algorithmics, we find that if the number of such conflicts is not too large, constant factor approximations can still be computed efficiently.In particular, we introduce parameterised approximations with respect to not just the number of conflicts but also for the vertex cover number of the conflict graph (graph induced by conflicts). Interestingly, we salvage the approximation ratio of 2 for diameter while for radius it is only possible to show a ratio of 3. For the parameter vertex cover number of the conflict graph this worsening in ratio is shown to be unavoidable, unless FPT=W[2]. We further discuss improvements for diameter by choosing the (induced) P_3-cover number of the conflict graph as parameter and complement these by showing that, unless FPT=W[1], there exists no constant factor parameterised approximation with respect to the parameter split vertex deletion set.
Parallel Processing of Morphological Pattern Spectrum for a Massive-Parallel Memory-Embedded SIMD Matrix Processor MX-1

The use of digital images has become quite widespread in legal, medical, and private contexts. However, anyone can easily edit or manipulate any digital image on a computer. In addition, the digital image are familiar to us with the population smartphone or mobile device. The morphological pattern spectrum is a mathematical method to describe size distributions of structuring element in an image. This algorithm is possible to execute effective image processing and has a lot of repeated calculation. Thus, conventional embedded processors low-throughput per power consumption for morphological pattern spectrum processing. A Massive-Parallel Memory-Embedded SIMD (Single Instruction Multiple Data) Matrix Processor (MX-1), which is based on C language processing, has been developed for effective parallel processing to satisfy with required specification on the digital convergence. The MX-1 consists of two SRAMs and 2-bit processing elements. The MX-1 can execute fast morphological pattern spectrum processing by parallel operation. Thus, throughput per power consumption of MX-1 is up to about 22 times than conventional parallel processor. And throughput per CMOS process-based power consumption of MX-1 is up to about 22 times than conventional parallel processor. The MX-1 performance for morphological pattern spectrum processing becomes effective solution for mobile devices on the digital convergence era.
Quantifying error contributions of computational steps, algorithms and hyperparameter choices in image classification pipelines

Data science relies on pipelines that are organized in the form of interdependent computational steps. Each step consists of various candidate algorithms that maybe used for performing a particular function. Each algorithm consists of several hyperparameters. Algorithms and hyperparameters must be optimized as a whole to produce the best performance. Typical machine learning pipelines typically consist of complex algorithms in each of the steps. Not only is the selection process combinatorial, but it is also important to interpret and understand the pipelines. We propose a method to quantify the importance of different layers in the pipeline, by computing an error contribution relative to an agnostic choice of algorithms in that layer. We demonstrate our methodology on image classification pipelines. The agnostic methodology quantifies the error contributions from the computational steps, algorithms and hyperparameters in the image classification pipeline. We show that algorithm selection and hyper-parameter optimization methods can be used to quantify the error contribution and that random search is able to quantify the contribution more accurately than Bayesian optimization. This methodology can be used by domain experts to understand machine learning and data analysis pipelines in terms of their individual components, which can help in prioritizing different components of the pipeline.
Online Reading Resources Among EFL Students: Do They Promote Reading Habit?

The aim of this study are to describe the EFL learners’ reading habit, the factors influence of reading habit, and the impact of the use Online Reading Resources on promoting students’ reading habit. 156 EFL learners FKIP- Islamic University of Riau involved as participants who read by using online reading resources. The study employed questionnaire, reading log, and interview intensively to collect the data. The results of analysis data from instruments were used in this study reflected that the use of online reading resources as a source of reading material has changed the reading habits of the learners, from conventional reading cultures into integrated the new technologies in reading process. There were 75% students already have got reading habit. It was significant increase than before. Besides that, online reading resources also provided positive changes for students who have low motivation in reading to be a fun reading activity. Supporting of teacher, parents, and environment help the learners establish their reading habit. The significant reason of learners get the reading habit was to complete the task. The result implies that the learners expected to read more and intensively to get the greatly reading habit. In conclusion, online reading resources are helpful to work the task, to get much information, and to improve learners’ knowledge in reading.
Distributed Variational Bayesian Algorithms for Extended Object Tracking

This paper is concerned with the problem of distributed extended object tracking, which aims to collaboratively estimate the state and extension of an object by a network of nodes. In traditional tracking applications, most approaches consider an object as a point source of measurements due to limited sensor resolution capabilities. Recently, some studies consider the extended objects, which are spatially structured, i.e., multiple resolution cells are occupied by an object. In this setting, multiple measurements are generated by each object per time step. In this paper, we present a Bayesian model for extended object tracking problem in a sensor network. In this model, the object extension is represented by a symmetric positive definite random matrix, and we assume that the measurement noise exists but is unknown. Using this Bayesian model, we first propose a novel centralized algorithm for extended object tracking based on variational Bayesian methods. Then, we extend it to the distributed scenario based on the alternating direction method of multipliers (ADMM) technique. The proposed algorithms can simultaneously estimate the extended object state (the kinematic state and extension) and the measurement noise covariance. Simulations on both extended object tracking and group target tracking are given to verify the effectiveness of the proposed model and algorithms.
Analysis of the (μ/μI,λ)-CSA-ES with Repair by Projection Applied to a Conically Constrained Problem

Theoretical analyses of evolution strategies are indispensable for gaining a deep understanding of their inner workings. For constrained problems, rather simple problems are of interest in the current research. This work presents a theoretical analysis of a multi-recombinative evolution strategy with cumulative step size adaptation applied to a conically constrained linear optimization problem. The state of the strategy is modeled by random variables and a stochastic iterative mapping is introduced. For the analytical treatment, fluctuations are neglected and the mean value iterative system is considered. Non-linear difference equations are derived based on one-generation progress rates. Based on that, expressions for the steady state of the mean value iterative system are derived. By comparison with real algorithm runs, it is shown that for the considered assumptions, the theoretical derivations are able to predict the dynamics and the steady state values of the real runs.
Magnetic Three-dimensional Pose Control System for Micro Robots in the Human Head

Micro robots are devices that have the ability to revolutionize the area of medicine. These devices work without cables, move easily in aqueous environments, and have the ability to be controlled in different ways, allowing them to access very small places. Currently, three-dimensional electromagnetic actuating systems have been proposed for the movement of micro robots by means of arrangements of Helmholtz and Maxwell coils with various functionalities but with high energy consumption. The present investigation proposes a system of coils of Helmholtz and Maxwell with analysis of the currents used to move the micro robot, complementing with the simulation of movement of the micro robot in the subarachnoid region of the human brain by means of Unity. In this way, it is planned to take a first step to know the design of a real system so that in the future, microrobots can reach difficult areas such as the subarachnoid region.