Reviewerly/exHarmony huggingface dataset:
LINGUISTIC LANDSCAPE ON CAMPUS IN PONOROGO (A CASE STUDY OF SIGNS IN PONOROGO UNIVERSITIES)

This research aims to: (1) describe the types of linguistic landscape are used in Universities Ponorogo, (2) know purposes of the signs posted in Ponorogo Universities, (3) know the factors that Ponorogo Universities used that sign. This research design was qualitative research of case study. The researcher used observation and interview as the data collection technique. There are eight universities in Ponorogo, those are Universitas Darussalam Gontor, Universitas Merdeka, Institut Agama Islam Negeri Ponorogo, Unmuh Ponorogo, Akper Ponorogo, Insuri Ponorogo, and Akafarma Ponorogo, however, and only three universities gave permission for the researcher to conduct this research. The findings of observations, six of the eight campuses in Ponorogo have tried to display a sign that has finally become a special feature of the campus. This research concludes most of them still use the Indonesian language. While, campus managed to convey the purpose of the sign installation to the viewer. In other word, the sign viewer understands the purpose of each sign that is installed by giving opinions and implementing them in daily life.
Automatic Term Extraction from Turkish to English Medical Corpus

This study aims to evaluate the state-of-the-art automatic and semi-automatic term extraction from a domain-specific bilingual corpus in Turkish -English language pair.Three different tools (a computerassisted translation tool, a web-based corpus analysis toolkit, and a desktop corpus analysis tool) are used for extracting Turkish cardiology single-word and multi-word candidate terms with different parameters, and the results are compared in terms of number of candidate term counts.It has been observed that each tool responds to different needs of translators and comes with a limited number of customization options.It is concluded that while monolingual term extraction is useful for translators and terminologists, there is still no tool providing bilingual candidate term extraction for Turkish -English language pair.
Intrinsically Motivated Hierarchical Policy Learning in Multiobjective Markov Decision Processes

The multiobjective Markov decision processes (MOMDPs) are sequential decision-making problems that involve multiple conflicting reward functions that cannot be optimized simultaneously without a compromise. This type of problem cannot be solved by a single optimal policy as in the conventional case. Alternatively, multiobjective reinforcement learning (RL) methods evolve a coverage set of optimal policies that can satisfy all possible preferences in solving the problem. However, many of these methods cannot generalize their coverage sets to work in the nonstationary environments. In these environments, the parameters of the state transition and reward distribution vary over time. This limitation results in significant performance degradation for the evolved policy sets. In order to overcome this limitation, there is a need to learn a generic skillset that can bootstrap the evolution of the policy coverage set for each shift in the environment dynamics, therefore, it can facilitate a continuous learning process. In this article, intrinsically motivated RL (IMRL) has been successfully deployed to evolve generic skillsets for learning hierarchical policy to solve the MOMDPs. We propose a novel dual-phase IMRL method to address this limitation. In the first phase, a generic set of skills is learned, while in the second phase, this set is used to bootstrap policy coverage sets for each shift in the environment dynamics. We show experimentally that the proposed method significantly outperforms the state-of-the-art multiobjective reinforcement methods on a dynamic robotics environment.
English-Ethiopian Languages Statistical Machine Translation

In this paper, we describe an attempt towards the development of parallel corpora for English and Ethiopian Languages, such as Amharic, Tigrigna, Afan-Oromo, Wolaytta and Ge’ez. The corpora are used for conducting bi-directional SMT experiments. The BLEU scores of the bi-directional SMT systems show a promising result. The morphological richness of the Ethiopian languages has a great impact on the performance of SMT especially when the targets are Ethiopian languages.
An OpenPose Based Method to Detect Texting while Walking

A method was proposed to detect so called “texting while walking” from positions of human body 25 keypoints estimated by the OpenPose for a person in a video scene. The method was based on the fact that movements of human joints had some spatial correlation structures. Walking behaviors with or without using a smartphone were separated by the difference between the correlation structures. We evaluated the difference using a canonical correlation analysis applied to two covariance matrices calculated from pose vectors for both walking behaviors, respectively. The canonical score well separated the texting while walking from the normal one. The proposed method was successfully applied to actual video scenes for three persons’ three types of walking behaviors.
Use of a Group Text Messaging Application to Teach Developmental Milestones on a Pediatric Clerkship

Students on their pediatric clerkship learned developmental milestones in a nontraditional format. Brief videos in a group text message allowed for short teaching moments and enhanced student engagement.
Lexical Phenomenon in Linguistics Theories

Lexical is study of vocabulary and its meanings in one language or in a number of languages. Vocabulary is concerned mainly with derivation of words, structures, moral, syntactic connotations, idiomatic expressions, synonyms, and multiplicity of meanings. This research aimed to describe the lexical phenomenon in linguistic theories. The methodology used in this research was qualitative research method with the type of library research. The results of the research were the lexical theory is carried out in a number of procedures necessary to accomplish the lexicon of the language, acoustically, and not neglected widely.
A novel solar irradiance forecast model using complex network analysis and classification modeling

The output power of solar photovoltaic (PV) plant is mainly determined by the received solar irradiance of the solar PV panels. Therefore, for step wise PV power forecast methods, the accuracy of solar irradiance forecast is very important. However, the diversity of irradiance fluctuation patterns brings great challenges to PV power predictions and limits the application of existing forecast models. In this paper, a novel solar irradiance forecast model of ultra-short-term time scale is proposed, which using complex network analysis to identify the irradiance and classification modeling to realize classified forecast of irradiance. Firstly, 4 irradiance fluctuation patterns are defined according to the local historical irradiance data, then 4 BP neural networks (BPNN) are built and trained respectively using these data of different fluctuation patterns. Secondly, each four-hour irradiance series is transformed into complex network based on weighted horizontal visibility algorithm (WHVG), then three complex network features are extracted to analysis not only the time series characteristics but also the network topology of irradiance data sequence. Thirdly, the support vector machine (SVM) is used to identify the irradiance fluctuation pattern with complex network features, and the corresponding BPNN is applied to forecast the future irradiance. The accuracy of irradiance pattern identification and the subsequent classified ultra-short-term irradiance forecast are verified by simulation with two-years actual irradiance data in Mississippi, US.
Gesture Controlled Robotic Arm

In many applications of controlling robotic gadget it becomes quite hard and complicated when there comes the part of controlling it with remote or many different switches. Mostly in military application, industrial robotics, construction vehicle in civil engineering side, medical application for surgery. Sometimes the operator may get confused in the switches and buttons itself, so as a new concept is introduced to control the machine with the movement of hand which will simultaneously control the movement of robot. In my project I am using this concept to control the robot through the movements of our hands and also the movement of our 'fingers'. I have combined the two robot types that is a robot car and a robotic arm to make one single multipurpose robot. My project is a concept introducing robot and its uses. By making more advancement in it i.e. by changing the end effector it can be used in military appliances like bomb diffusing robot. The sensors can also be used to make wheel chair for patients who can't walk.
CrowdLED: Towards Crowd-Empowered and Privacy-Preserving Data Sharing Using Smart Contracts

In this research paper, we explore how Blockchain technologies and Smart Contracts can be used to fairly reward users for the data they share with advertising networks without compromising anonymity and user privacy. The novelty of using Blockchains alongside such systems is to understand and investigate how a proper and fair exchange of data can ensure that participating users can be kept secure and eliminate aggressive data collection by ad libraries; libraries that are embedded inside the code of smart-phones and web applications for monetization. There are a lot of privacy issues regarding mobile and online advertising: Advertising networks mostly rely on data collection, similar to a crowd-sensing system, but in most cases, neither consent has been granted by the user for the data collection nor a reward has been given to the user as compensation. Making a comparison between the problems identified in mobile and online advertising and the positives of the approach of using Blockchain, we propose “CrowdLED”, a holistic system to address the security and privacy issues discussed throughout the paper.
Inference for Linear Conditional Moment Inequalities

We consider inference based on linear conditional moment inequalities, which arise in a wide variety of economic applications, including many structural models. We show that linear conditional structure greatly simplifies confidence set construction, allowing for computationally tractable projection inference in settings with nuisance parameters. Next, we derive least favorable critical values that avoid conservativeness due to projection. Finally, we introduce a conditional inference approach which ensures a strong form of insensitivity to slack moments, as well as a hybrid technique which combines the least favorable and conditional methods. Our conditional and hybrid approaches are new even in settings without nuisance parameters. We find good performance in simulations based on Wollmann (2018), especially for the hybrid approach.
Pre-Service EFL Teachers’ Perception of Edmodo Use as a Complementary Learning Tool

Various recent studies have shown that the use of Information and Communication Technology to provide online learning as a complementary tool for encouraging andempowering independent learning and innovative teaching is becoming an essential part of education in the 21st century. One of the widely used online learning sites employedto complement English classes is Edmodo. However, the number of studies focusing on the use of Edmodo as a complementary tool for learning in EFL teacher education classes is still limited. This study focuses on the perception of pre-service EFL teachers of Edmodo use as a complementary learning tool. Employed a mixed method research designed, quantitative and qualitative data were collected from 54 students of theEnglish Education Department of Universitas Kristen Indonesia Jakarta. The finding revealed that the majority of the participants were ready to use Edmodo as acomplementary learning tool in the English classroom, considered the use of Edmodo is a beneficial learning tool to supplement traditional face-to-face classroom settings, and had a positive view on their experiences in using Edmodo.
CAREER MANAGEMENT OF MANAGERIAL PERSONNEL OF EDUCATIONAL ORGANIZATION: MODERN PROBLEMS AND POSSIBLE SOLUTIONS

The article has been devoted to the ongoing research of a system of development of managerial personnel of educational organization. The results of the analysis of modern problems and the search for possible solutions to improve the management of the career of managerial personnel of educational organization have been presented. The essence and content of career management of managerial personnel of educational organization have been clarified; a set of problems, caused by the lack of a systematic approach to career management of managerial personnel of educational organizations has been substantiated; possible solutions to improve career management of managerial personnel of educational organization have been offered.
Cognitive target detection based on Bayesian approach in radar

Cognitive radar (CR), which uses a closed-loop feedback perception-action cycle system, aims to develop a higher level of intelligence. In this study, the authors develop an efficient Bayesian approach to target detection in CR. The approach, which uses the Neyman-Pearson criterion with priori probability, can improve the target detection effectively. The recursive form of computing priori probability is also discussed. Numerical simulations illustrate that the proposed target detector can improve the performance of detection with the usage of priori probability, which can be computed recursively using the previous measurements.
Airframe Sealing Automation Using Snake-robot

The work described herein have had the objective of carrying out a technical-economic feasibility study of a snake-robot for sealant application in an aircraft fuselage.The execution of the project brought knowledge related to the design and development of robots, constrained Cartesian trajectory generation, optimization methods for inverse kinematics computation, collaborative robotics and 3D simulations besides experiments related to aircraft components and application of sealants in the fuselage.Concerning the technical feasibility of the project, the solution proposed proved to be an adequate solution for the proposed task.The sealant application trajectories in fillets (union of two plates of the fuselage) and fasteners were tested, being all well executed by the robot in a virtual environment, without collisions and without relevant complications.All the trajectories used for the evaluation were taken from the test framework provided by Saab and respecting the process specifications described for this task.Economical evaluation of ROM (Rough Order of Magnitude) gives a result showing fairly good pay-back time although the potentials would be even better with a lower cost.A list of commercial components for the manufacturing of the snake robot was specified, such as: motors, reducers, vision system, components for programming and controlling the robot (drivers, software and robot interface with the user) etc.It is important to mention that, despite the design of the robot drivers, the CAD model developed here needs further detailing for fabrication purposes.Structural analysis must be carried out in the structure and, after any changes are made, evaluations and corrections must be done.A study about the dimension and mass reductions of an existing sealant dispenser was carried out, where the cartridge and the sealant application valve were chosen to be coupled directly to the robotic arm.In general, all activities were executed according to the proposed schedule.The project presented a very high potential and could be applied not only to the aeronautical industry (which was the main objective of the present work), but also to other fields of the industry.Therefore, a continuation of this project is highly recommended, such that the proposed snake robot can be manufactured and physically tested.
Epistemic Logic Programs: A Different World View.

Epistemic Logic Programs (ELPs), an extension of Answer Set Programming (ASP) with epistemic operators, have received renewed attention from the research community in recent years. Classically, evaluating an ELP yields a set of world views, with each being a set of answer sets. In this paper, we propose an alternative definition of world views that represents them as three-valued assignments, where each atom can be either always true, always false, or neither. Based on several examples, we show that this definition is natural and intuitive. We also investigate relevant computational properties of these new semantics, and explore how other notions, like strong equivalence, are affected.
Completeness and Incompleteness of Synchronous Kleene Algebra

Synchronous Kleene algebra (SKA), an extension of Kleene algebra (KA), was proposed by Prisacariu as a tool for reasoning about programs that may execute synchronously, i.e., in lock-step. We provide a countermodel witnessing that the axioms of SKA are incomplete w.r.t. its language semantics, by exploiting a lack of interaction between the synchronous product operator and the Kleene star. We then propose an alternative set of axioms for SKA, based on Salomaa’s axiomatisation of regular languages, and show that these provide a sound and complete characterisation w.r.t. the original language semantics.
Novelty circular neighboring technique using reactive fault tolerance method

The availability of the data in a distributed system can be increase by implementing fault tolerance mechanism in the system. Reactive method in fault tolerance mechanism deals with restarting the failed services, placing redundant copies of data in multiple nodes across network, in other words data replication and migrating the data for recovery. Even if the idea of data replication is solid, the challenge is to choose the right replication technique that able to provide better data availability as well as consistency that involves read and write operations on the redundant copies. Circular Neighboring Replication (CNR) technique exploits neighboring policy in replicating the data items in the system performs well with regards to lower copies needed to maintain the system availability at the highest. In a performance analysis with existing techniques, results show that CNR improves system availability by average 37% by offering only two replicas needed to maintain data availability and consistency. The study demonstrates the possibility of the proposed technique and the potential of deploying in larger and complex environment.
Facing the full model selection problem in high volume datasets employing intelligent proxy models

Full model selection is a technique to improve the accuracy of machine learning algorithms through the search of the most appropriate combination on each dataset of feature selection, data preparation, a learning algorithm and the adjustment of its hyper-parameters. This paradigm has been widely st udied in datasets of moderate size, but poorly explored in high volume datasets. One of the main reasons is the high search space and an elevated number of fitness evaluations of candidate models. In order to overcome this obstacle, the use of proxy models or surrogate functions has been proposed in the literature. In this work, we propose the use of the full model selection paradigm to construct proxy models. Such proxy models were employed to assist in the search of models in high volume datasets in order to reduce the number of fitness evaluations and to guide the search. The obtained results, show a performance without significant differences in comparison to the complete search algorithm, using just the third part of the expensive fitness evaluations.
Preference Dynamics and Behavioral Traits in Fashion Domain

Users preferences evolve over the time. This socalled dynamics is a serious challenge which is widely researched in several domains. In these domains, users are usually active for a long period of time and they tend to interact with a wide range of items. To make it more complicated, users preferences are likely to evolve only in some aspects while others remain untouched. In this paper we present an analysis of user behavior dynamics in a fashion e-shop. We identified four typical user behaviors, i.e., classes. Moreover, we explored typical user behavior before and after the purchase. As a result, such knowledge can improve various tasks dealing with short-term dynamics, mainly in session-based recommender systems.
Identification of fixations, saccades and smooth pursuits based on segmentation and clustering

Accurate automated eye movement classification is a key technique in the field of eye tracking, and the identification effects are largely influenced by the noise and imprecision of an eye tracker, and the characteristics of eye movements. In this paper, we propose a novel segmentation and clusteri ng-based identification algorithm (I-SC) to effectively recognize fixations, saccades and smooth pursuits in eye tracking. In the proposed algorithm, firstly we employ the velocity feature in the recorded eye data to identify the saccade segments, and then the standard deviation of the dispersion is used to divide the remaining data into segments. Finally, in each segment we define the average direct distance feature and adopt the method of clustering by fast search and find of density peaks (CFSFDP) to classify fixations and smooth pursuits. To demonstrate its effectiveness and robustness, the proposed I-SC algorithm is evaluated with the eye tracking dataset sampled from 11 participants by a commercial eye tracker. The experimental results show that the proposed mechanism can achieve up to an accuracy of 96.0% and a recall of 87.6%, which is a considerably better performance than both the Velocity and Dispersion Threshold Identification (I-VDT) algorithm and the Convolutional Neural Networks (CNN) algorithm. With our mechanism, accurate classification can be achieved even with the noise and imprecision of data from eye trackers.
Quantum query-to-communication simulation needs a logarithmic overhead

Buhrman, Cleve and Wigderson (STOC'98) observed that for every Boolean function f : { -1, 1}n → {-1, 1} and • : {-1, 1}2 → {-1, 1} the two-party bounded-error quantum communication complexity of (f ο •) is O(Q(f) log n), where Q(f) is the bounded-error quantum query complexity of f. Note that the bounded-error randomized communication complexity of (f ο •) is bounded by O(R(f)), where R(f) denotes the bounded-error randomized query complexity of f. Thus, the BCW simulation has an extra O(log n) factor appearing that is absent in classical simulation. A natural question is if this factor can be avoided. Razborov (IZV MATH'03) showed that the bounded-error quantum communication complexity of Set-Disjointness is Ω([MATH HERE]). The BCW simulation yields an upper bound of O([MATH HERE] log n). Hoyer and de Wolf (STACS'02) showed that this can be reduced to clog*n for some constant c, and subsequently Aaronson and Ambainis (FOCS'03) showed that this factor can be made a constant. That is, the quantum communication complexity of the Set-Disjointness function (which is NORn ο ∧) is O(Q(NORn)).Perhaps somewhat surprisingly, we show that when • = ⊕, then the extra log n factor in the BCW simulation is unavoidable. In other words, we exhibit a total function F : {-1, 1}n → {-1, 1} such that Qcc(F ο ⊕) = Θ(Q(F) log n).To the best of our knowledge, it was not even known prior to this work whether there existed a total function F and 2-bit function •, such that Qcc(F ο •) = ω(Q(F)).