Reviewerly/exHarmony huggingface dataset:
Turkish lexicon expansion by using finite state automata

Turkish is an agglutinative language with rich morphology. A Turkish verb can have thousands of different word forms. Therefore, sparsity becomes an issue in many Turkish natural language processing (NLP) applications. This article presents a model for Turkish lexicon expansion. We aimed to expand the lexicon by using a morphological segmentation system by reversing the segmentation task into a generation task. Our model uses finite-state automata (FSA) to incorporate orthographic features and morphotactic rules. We extracted orthographic features by capturing phonological operations that are applied to words whenever a suffix is added. Each FSA state corresponds to either a stem or a suffix category. Stems are clustered based on their parts-of-speech (i.e. noun, verb, or adjective) and suffixes are clustered based on their allomorphic features. We generated approximately 1 million word forms by using only a few thousand Turkish stems with an accuracy of 82.36%, which will help to reduce the out-of-vocabulary size in other NLP applications. Although our experiments are performed on Turkish language, the same model is also applicable to other agglutinative languages such as Hungarian and Finnish.
Potential Usage of Mobile Learning via Short Messaging System (SMS) For Enhancing Islamic Knowledge of Adult Learners

The study was to explore the potential usage of mobile learning via SMS for enhancing Islamic knowledge that focusing on the topic of waqf.The study used questionnaire survey data gathered from 80 adult learners in Universiti Sains Malaysia, Pulau Pinang.The application of short messaging system (SMS) in this study based on Adult Learning Theory, Andragogy.There were four illustrations of andragogical model used in this study.The method used was the Solomon Four Group Design and questionnaire based on waqf knowledge.The adult learners were divided into four groups which were two experimental groups and two control groups.The involvements of the adult learners were voluntary and randomly assign for each group.Study participants distributed into 20 each group.The experimental group received SMS and the control group did not receive SMS. Pre-and post-assessment was used to measure the level of achievement.Data were analysed using SPSS.The pre-and post-assessment results were analysed with two-way ANOVA analysis and descriptive analysis.The results showed that the usage of mobile learning via SMS is potential for enhancing the level of adult learners' achievement on waqf knowledge as indicated in the significantly improved marks for post assessment in the experimental group.Majority of students in the experimental groups agreed that the use of SMS increased their interest and ability to remember the contents.Therefore, the study suggests that the usage of mobile learning via SMS can be utilised and has potential as one of the tools in delivering of Islamic knowledge to the public.
A Short History of Imaginary Numbers

This paper is discussing how and where imaginary numbers came to be and how their extension to our classic number line helped mathematics to grow even faster. We talk about the beginning of imaginary numbers and the set of rules that come with them. We show how an error that occurred in an equation started the discovery of these. These numbers also help us achieve a better perspective towards the parabolas we see every day. At the end, you can see how these new numbers found the perfect place on the number line and fit in well with different categories we all know.
Algorithms for Merging Probabilistic Knowledge Bases

There is an increasing need to develop appropriate techniques for merging probabilistic knowledge bases (PKB) in knowledge-based systems. To deal with merging problems, several approaches have been put forward. However, in the proposed models, the representation of the merged probabilistic knowledge base is not similar to the representation of original knowledge bases. The drawback of the solutions is that probabilistic constraints on the set of input knowledge bases must have the same structure and there is no algorithm for implementing the merging process. In this paper, we proposed two algorithms for merging probabilistic knowledge bases represented by various structures. To this aim, the method of constraint deduction is investigated, a set of mean merging operators is proposed and several desirable logical properties are presented and discussed. These are the basis for building algorithms. The complexity of algorithms as well as related propositions are also analysised and discussed.
Smart Line Judgement System: A Novel Technology in Vol-leyball Arbitration

&lt;p class="BodyText1"&gt;Within previous decade, sensitivity to arbitration systems in sports such as soccer, tennis and volleyball has been sharply increased and technicians turned to new technologies to fulfill the demands for a reliable judgement. The main purpose of this study was to address a new method in judgement of presence of ball in the volleyball field in the shortest possible time by manipulation of lines surrounded the field and the ball layer’s structure. A carbon semi- conducting fabric layer designed ball was thrown to the printed circuit board (PCB), which have replaced the surrounded field lines. The ball was thrown in six different angles of 15, 30, 45, 60, 75, and 90 degrees and with 20 and 40 m.s-1 speed. As soon as the semiconducting ball hits the PCB lines, the LED, which embedded under the PCB, turns on and announce the presence of the ball in the field. In 20 m.s-1 speed, the PCB detected 97.1% of ball presence in the field per 1500 trials six angles. Almost similar, in 40 m.s-1 speed, the accuracy of PCB in hit detection was 97.6% per 1500 trails. Additionally, regardless of ball speed, the more perpendicular the ball hit the PCB line, the accurate detection was made. The smart line judgment system could be a reliable, efficient, and affordable technology that provide referees with an accurate decision and athletes with a faster game flow. &lt;/p&gt;
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures and values of learning parameters are determined through cross-validation, and test datasets unseen in the cross-validation are used to evaluate the performance of the DMLP trained using the three-stage learning algorithm. Experimental results show that the proposed method is effective in combating overfitting in training deep neural networks.
Multi-indicators Brain Storm Optimization Algorithm for Multi-objective Optimization Problems

The brains storming optimization (BSO) is a novel swarm intelligence algorithm, which is inspired from the intelligence of the human brainstorming process. In BSO, the convergent operation and divergent operation are implemented to drive the evolution of individuals towards a global optimal region in the single-objective space. In order to extend BSO to resolve multi-objective optimization problems, this paper presents a multi-objective brainstorming algorithm based on multiple indicators, called MIBSO. In MIBSO, the two indicators are used to measure the dispersion and convergence degrees of the obtained solutions, respectively. Experimental results show the effectiveness and efficiency of the proposed algorithm.
Enhanced Shadow Retargeting with Light-Source Estimation Using Flat Fresnel Lenses

Shadow-retargeting maps depict the appearance of real shadows to virtual shadows given corresponding deformation of scene geometry, such that appearance is seamlessly maintained. By performing virtual shadow reconstruction from unoccluded real-shadow samples observed in the camera frame, this method efficiently recovers deformed shadow appearance. In this manuscript, we introduce a light-estimation approach that enables light-source detection using flat Fresnel lenses that allow this method to work without a set of pre-established conditions. We extend the adeptness of this approach by handling scenarios with multiple receiver surfaces and a non-grounded occluder with high accuracy. Results are presented on a range of objects, deformations, and illumination conditions in real-time Augmented Reality (AR) on a mobile device. We demonstrate the practical application of the method in generating otherwise laborious in-betweening frames for 3D printed stop-motion animation.
Knowledge, beliefs and sources of information of HIV among students of a Tertiary Institution in Nigeria

Two out of three new HIV infections occurring globally each day occurs in sub-Saharan African in which Nigeria belongs.Its prevention however, is based on the knowledge of its transmission in which people are predisposed to.Unfortunately, the school environment has a high risk for the infection because of its vulnerability to high sexual risk behaviours which increases likelihood of HIV transmission.This study aimed at assessing the knowledge, beliefs and sources of information of HIV among students in the study area.The cross-sectional survey was conducted at an off-campus student community in Ilorin, north-central Nigeria.Primary data was collected through administration of structured questionnaire to 292 participants selected through multistage non-probability sampling method.Result revealed that, (84.2%) of the participants have the knowledge that a healthy looking person can have HIV, (88.7%) are knowledgeable of the fact that, HIV virus weakens the immune system of an infected person while, (82.2%) know that HIV can be transmitted through unprotected sex.A total of (81.2%) of the participants identified fever as the symptom of HIV while (77.7%) identified safe sex as preventive measure.The highest source of information of HIV in the study is the media, (68.2%) getting informed via health talk, followed closely by television (66.4%).On participants' beliefs on HIV, (63.7%) strongly disagree that HIV is a myth while (36.6%) strongly agree that HIV can be cured with prayers.Statistical significant relationship (where p value <0.05) was found between the age of participants and knowledge of HIV, between all the sources of information and knowledge of HIV while only school, health talk and television were found to be significantly related with beliefs of participants.The study concluded that participants have high knowledge of HIV although froth with misconceptions that stems from the belief held about the disease.
Error Bounds for the Normal Approximation to the Length of a Ewens Partition

Let $$K(=K_{n,\theta })$$ be a positive integer-valued random variable with a distribution given by $$\mathrm{P}(K = x) = \bar{s}(n,x) \theta ^x/(\theta )_n$$ $$(x=1,\ldots ,n) $$ , where $$\theta $$ is a positive value, n is a positive integer, $$(\theta )_n=\theta (\theta +1)\cdots (\theta +n-1)$$ , and $$\bar{s}(n,x)$$ is the coefficient of $$\theta ^x$$ in $$(\theta )_n$$ for $$x=1,\ldots ,n$$ . This formula describes the distribution of the length of a Ewens partition, which is a standard model of random partitions. As n tends to infinity, K asymptotically follows a normal distribution. Moreover, as n and $$\theta $$ simultaneously tend to infinity, if $$n^2/\theta \rightarrow \infty $$ , K also asymptotically follows a normal distribution. This study provides error bounds for the normal approximation. The results show that the decay rate of the error varies with asymptotic regimes.
Visual Attention in Virtual Reality Settings: An Abstract

Virtual reality, VR, is challenging marketers to understand both brand interaction and the customer experience at the point of sale. In order to test the usefulness of VR in retailing, research must address how the customer’s visual attention in a VR setting affects his/her behavior. There are two main drivers for this research. First, there has been an enormous growth in recent years in the use of neurophysiological methods to measure visual attention. At the store level, previous works show that attention to products measured through eye tracking influences consumer decision. Second, VR is being increasingly adopted by brands, but research is lacking into comparisons between VR formats. We aim to compare visual attention during two consecutive tasks related to shopping behaviors in a VR retail environment. Thus, we integrate neurophysiological measurement of attention and VR. Our research goals are to compare visual attention and time spent looking at products and to measure the sense of presence evoked by the VR experience. To do so, a virtual representation of a set of supermarket shelves was created. The procedure consisted of a single-factor experiment of 2 VR immersive formats: a desktop monitor and virtual reality head-mounted display glasses. Participants were randomly assigned to one of the two formats. Data were gathered from 100 participants exposed to one of the two scenarios: using head-mounted display glasses, HTC Vive, with Tobii Pro VR eye tracking integrated directly into the glasses, and Tobii TX 300 for tracking visual attention through the monitor. Participants completed two consecutive tasks: a search for a given brand and a search for any brand in a given category. The data were complemented by a questionnaire to measure sense of presence and recall of stimuli. Our findings suggest that sense of presence is high in both VR scenarios, which shows that participants perceive a high level of realism; visual attention given to products through a desktop monitor and head-mounted glasses was not significantly different but varies by task, with more time spent on the two tasks when wearing the HTC Vive glasses than with the monitor. References Available Upon Request
Manifestos do movimento de acesso aberto: Análise de Domínio a partir de periódicos brasileiros

The informational volume in digital format has increased during the last decades causing the researchers to worry about the access to these documents. This study analyses the Open Access Movement domain through the manifests produced by this movement. It discusses about the definitions related to scientific journalism, open access, the main statements that guided the policies of the movement as well as what they represent. We used two approaches of Domain Analysis with methodological tools to obtain the research results together with information on recovered manifests in the Base de Dados Referenciais de Artigos de Periodicos em Ciencia da Informacao (BRAPCI). The study identifies the lack of production of scientific articles on the subject and identifies the need of more productions on the subject. It presents – as a reflection – the significance of the Initiative in relation to the elaboration of guiding documents which serve as the basis for the establishment of policies that direct institutions to provide free access to information of all scientific productions.
Evolution of Format Preserving Encryption on IoT Devices: FF1+

The Internet of Things (IoT) is a network of interconnected low-power sensing devices designed to interact and communicate with each other.To avoid compromising user privacy, it is necessary to encrypt these channels.We introduce Format Preserving Encryption (FPE), a modern cryptosystem that allows full customization of the ciphertext, while offering comparable security to AES.To gauge the performance of FPE, we compare the NIST-approved FF1 algorithm against several symmetric and asymmetric encryption schemes on a Raspberry Pi 3.While suitable for small plaintexts, FF1 breaks down for longer character strings.We propose a modified algorithm, FF1+, that implements dynamic round selection and key scheduling.Significant performance improvements are observed in our results, thus demonstrating FF1+ as a viable cryptosystem for IoT devices.
OPTIMASI CITRA DICOM DENGAN MENGGUNAKAN APLIKASI PADA SMARTPHONE ANDROID

&lt;p class="AbstractEnglish"&gt;&lt;strong&gt;Abstract:&lt;/strong&gt; A radiographic image is generated from a mapping of attenuation of the X-ray beam that passed through a material. Over the past few years, as computer acquisition technology has grown, conventional diagnostic medical imaging modalities have increasingly been replaced by digital imagery. Computed radiography (CR) is one of radiographic image acquisition using computers. CR images could be either .jpg files or DICOM files. We exposed some wrenches which diameter of 5.68 mm; 3.99 mm and 3.2 mm as well as a bottle and a circular cork. We use Siemens mobile x-ray to expose the objects and DroidRender 3D DICOM Viewer as the DICOM viewer. We got two images which are .jpg file and DICOM file respectively. We adjust WW and WL parameters in order to optimize the image of the DICOM file. The results are WW = 2833 and WC = 2170.&lt;/p&gt;&lt;p class="KeywordsEngish"&gt;&lt;strong&gt;Abstrak:&lt;/strong&gt; Citra medis yang dihasilkan oleh sistem radiografi pada dasarnya adalah pemetaan dari berkas sinar-X yang diteruskan yang dinyatakan melalui hukum penurunan intensitas sinar-X. Selama beberapa tahun terakhir, dengan semakin berkembangnya teknologi akuisisi komputer, modalitas pencitraan medis diagnostik konvensional semakin digantikan oleh citra digital. &lt;em&gt;Computed radiography &lt;/em&gt;(CR) merupakan salah satu teknologi akuisisi komputer pengolah citra radiografi. Hasil citra radiografi pada CR dapat berbentuk file .jpg ataupun DICOM. Untuk membaca file DICOM harus digunakan DICOM &lt;em&gt;viewer &lt;/em&gt;yang dapat diunduh secara gratis dari internet. Pada penelitian ini, obyek-obyek yang dipapari sinar-X yaitu kunci inggris dengan tebal diameter 5,68 mm; 3,99 mm dan 3,2 mm serta botol dan gabus berbentuk lingkaran. Pesawat sinar-X yang digunakan adalah &lt;em&gt;mobile x-ray&lt;/em&gt; bermerk Siemens. Aplikasi DICOM &lt;em&gt;viewer &lt;/em&gt;yang digunakan adalah DroidRender 3D DICOM Viewer. Dari hasil eksperimen, pengaturan WW dan WC pada aplikasi untuk dapat menampilkan gabus secara optimal diperoleh pada nilai WW = 2833 dan WC = 2170.&lt;/p&gt;
FORMATION OF SKILLS TO INSTALL REASONAL RELATIONSHIPS OF TEACHERS IN THE STUDY OF ECOLOGICAL MATERIAL IN SCHOOL BIOLOGY

УДК 37.01:
A Novel Privacy Preserving Search Technique for Stego Data in Untrusted Cloud

We propose the first privacy preserving search technique for stego health data in untrusted cloud in this paper.The Cloud computing is a popular technology to the healthcare providers for outsourcing health data due to flexibility and cost effectiveness.However, outsourcing health data to the cloud introduces serious privacy issues to the patient.For example, dishonest personnel of the cloud provider may disclose patient sensitive information to business organizations for some financial benefits.Using steganography, patient sensitive information is hidden within health data for privacy preservation.As a result, stego health data is generated.To the best of our knowledge, no method exists for searching a particular stego data without disclosing any information to the cloud.We propose a framework for privacy preserving search over stego health data.We systematically describe each component of the proposed framework.We conduct several experiments to evaluate the performance of the framework.
Preparing for Blockchain Technology in the Energy Industry: How Energy Sector Leaders Can Make Informed Decisions During the Blockchain Adoption Process

This research was motivated by the lack of literature about the constructs influencing the decision to adopt blockchain technology.This paper contributes to the knowledge by integrating common adoption and diffusion theories with a 2017 framework for blockchain adoption.This paper brings together competing adoption models with different sets of technology acceptance determinants and proposes a new model to identify constructs (i.e., ease of understanding, perceived usefulness, the perceived ease of use, knowledge acquisition, self-efficacy, and the novelty and complexity of the new technology application) as essential determinants of blockchain technology adoption at individual and organizational levels.The study offers a new model and research agenda to help executives and managers prepare for blockchain adoption and make informed decisions to speed up the adoption process.This research is focused on energy companies, which are known to be slow to adopt new technologies.
Chinese Medical Question Answer Matching with Stack-CNN

Question and answer matching in Chinese medical science is a challenging problem, which requires an effective text semantic representation. In recent years, deep learning has achieved brilliant achievements in natural language processing field, which is utilized to capture various semantic features. In this paper, we propose a neural network, i.e., stack-CNN, to address question answer matching, which stacks multiple convolutional neural networks to capture the high-level semantic information from the low-level n-gram features. Substantial experiments on a real-world dataset show that our proposed model significantly outperforms a variety of strong baselines.
ENGLISH FOR TEP LEARNING MEDIA BASED VI-LEARN TO TRAIN VERBAL COMMUNICATION SKILLS OF CHEMISTRY STUDENT

Learning can not only be done in the classroom with direct face-to-face activities but can now be done with the help of IT, for example with learned learning. Although learning with vi-learn or e-learn cannot indeed replace overall face-to-face learning in the classroom. The world of education cannot be separated from technological advances such as this study because sometimes in carrying out classroom learning there are obstacles that cannot be avoided. These obstacles can be administrative in nature such as national holidays which coincide with the schedule of courses and cannot be replaced on another day due to limited space and insufficient time. In this study, learning tools for the English for TEP-based learning program have been developed to learn the verbal communication skills of students majoring in chemistry. From the data from the validation results, it can be concluded that learning devices consisting of enrichment modules and worksheets are feasible to be used in learning lessons. Likewise, from the response data, students showed a positive response from students in using enrichment modules and worksheets.