Reviewerly/exHarmony huggingface dataset:
Deep context interaction network based on attention mechanism for click-through rate prediction

Click-through rate (CTR) prediction, which aims to predict the probability of a user clicking on an ad, is a critical task in online advertising systems. The problem is very challenging since(1) an effective prediction relies on high-order combinatorial features, and(2)the relationship to auxiliary ads that may impact the CTR. In this paper, we propose Deep Context Interaction Network on Attention Mechanism(DCIN-Attention) to process feature interaction and context at the same time. The context includes other ads in the current search page, historically clicked and unclicked ads of the user. Specifically, we use the attention mechanism to learn the interactions between the target ad and each type of auxiliary ad. The residual network is used to model the feature interactions in the low-dimensional space, and with the multi-head self-attention neural network, high-order feature interactions can be modeled. Experimental results on Avito dataset show that DCIN outperform several existing methods for CTR prediction.
IMPLEMENTASI METODE ADAPTIVE TYPE-2 FUZZY DAN HISTOGRAM EQUALIZATION UNTUK MEREDUKSI NOISE SALT AND PEPPER PADA CITRA BERTIPE GRAYSCALE

Along with technological developments, images play a very important role as a form of information with the convenience offered in terms of retrieval, processing and storage. Digital image can have a defect (noise) / the main disturbance is salt & pepper type noise which causes the image to experience a decrease in quality. Therefore, it is necessary to improve the quality of digital images (Image enhancement) to improve image quality. The method that can be used to improve image quality (Image Enhancement) is Adaptive Typee-2 Fuzzy. This method will be applied to images containing impulse noise (salt & pepper). This filter consists of two steps, in the first step the pixels are categorized as good or bad. In the second step the pixels that were categorized as bad in the previous step will go through the filter stage. This method is applied to grayscale images to find out how accurate the method is. Based on the discussion, it is found that this method is effective in reducing noise in grayscale-type photographic images, as evidenced by the small value of the Mean Square Error (MSE) and the large value of the resulting Peak Signal to Noise Ratio (PSNR). The average MSE value of the adaptive type-2 fuzzy method is 0.006497218 and the average PSNR value is 24.242225. This method is also better when compared to linear filter methods, for example the Median Filter. The average MSE value of the median filter method is 0.061200481 and the average PSNR value is 17.4459775. The histogram equalization method is applied to the output of the filtering, which is a process that changes the distribution of the grayscale value in an image so that it becomes uniform (uniform). This method is proven to be effective in increasing the distribution of grayscale values so that the output image looks brighter and the details are more visible.
병사 일과이후 휴대전화 사용에 따른 IPTV 이용 『사이버·보안기강 교육』 개선연구

Despite its advantages, several hindrance factors of military disciplines have been recognized, followed by the allowance of the use of Smart-phones after work hours such as soldiers accessing gambling sites, pornographies, and violating security safety-codes. in this article, we show utilizing IPTVs equipped in the squad rooms for security education instead of holding a muster, appears to satisfy more than 90% of the soldiers. This observation provides a foundation that adopting IPTVs and Smart-phones. Which are physically readily accessible to soldiers, is taking on a significant and efficient role as an educational method. We also propose guidelines for an institutional, technical, and methodical utilizing the ‘Push-function’ in security training programs for Smart-phones with an integrated management system for mobile devices being developed henceforth.
Penerapan Metode Haversine Pada Sistem Informasi Geografis Pencarian Lokasi Laundry Terdekat di Kota Makassar

Laundry service is a laundry service for washing dirty clothes to dry and ready to use, in the sense that the clothes that were originally brought to the laundry service are dirty and when they are received back by consumers who use the laundry service the clothes are ready to be used again, clean, neat and ironed. , where the tariff determination is based on the type of laundry service, the number of kilograms and the number of clothes in the laundry The purpose of this study is to provide recommendations for the location of the laundry service closest to the user's position and provide directions to the location of the laundry so as to minimize time and cost labor. The method used in this research is the Haversine Formula to calculate the distance between two points on the earth based on the length of a straight line between two points without ignoring the curvature of the earth, by applying this technology in a GIS system users can find out their position to a certain location even though they still ignore the relief. real earth The result of this research is the formation of a search application that can help the local community in finding the closest laundry from their location
A novel secure biomedical data aggregation using fully homomorphic encryption in WSN

A new method of secure data aggregation for decimal data having integer as well as fractional part using homomorphic encryption is described. The proposed homomorphic encryption provides addition, subtraction, multiplication, division and averaging operations in the cipher domain for both positive and negative numbers. The scheme uses integer matrices in finite field Zp as encryption and decryption keys. An embedded Digital signature along with data provides data integrity and authentication by signature verification at the receiving end. The proposed scheme is immune to chosen plaintext and chosen ciphertext attacks. In the case of homomorphic multiplication, the ciphertext expansion ratio grows linearly with the data size. The computational complexity of the proposed method for multiplication and division is relatively less by 22.87% compared to Brakerski and Vaikantanathan method when the size of the plaintext data is ten decimal digits.
Linear Congruential Pseudorandom Numbered Hybrid Crypto-System with Genetic Algorithms

While using networks that may be in any form more and more problems related to securityrises within the network as well as outside the network. To resolve the security problems network security is the science that facilitatesto safeguard the resources and the quality of the network and data. At different workstations filters and firewalls are used in protecting the resources. But while the data is in transmission security services are needed to protect. These services are to be altered frequently to prevent from attacks. In developing such system, this work uses linear congruential pseudorandom number with multiple genetic algorithms. In small business applications these types of hybrid systems can be used to prevent from hackers.
COVID-19 X DIABETES: Como os Pacientes Diabéticos se Relacionam com a Doença causada pelo Novo Coronavírus

No fim de 2019, na China, foi relatado o primeiro caso da doenca causada pelo novo coronavirus, o SARS-CoV-2, posteriormente, denominada como COVID-19. Com sua rapida disseminacao, grande numero de novos casos e mortes, rapidamente foi considerada uma pandemia. Diante disso, cientistas do mundo todo se voltaram para a pesquisa do virus, da doenca causada por ele e de fatores de riscos associados a doenca. Com isso, doencas cronicas, como a diabetes foi apontada como uma relevante comorbidade ligada a casos severos e letais da doenca, o que se torna preocupante devido ao grande numero de pessoas acometidas com a doenca espalhadas pelo mundo. Este trabalho tem o objetivo de elucidar como os pacientes diabeticos se relacionam com a COVID-19. Para isso, foram utilizados como fontes de dados: artigos, revistas e enderecos eletronicos disponiveis nas bases: Scielo, Pubmed, Google academico e pesquisa direta no Google. No entanto, apesar da diabetes ser uma doenca ja conhecida, a COVID-19 ainda esta em estudo, sendo necessaria atualizacoes constantes para compreendermos como virus e doenca se relacionam. Sendo assim, os profissionais podem atuar de forma adequada e os pacientes receberao o melhor tratamento possivel.AbstractIn late 2019, in China, the first case of the disease caused by the new coronavirus, SARS-CoV-2, later named as COVID-19, was reported. With its rapid spread, large number of new cases and deaths, it was quickly considered a pandemic. Therefore, scientists around the world have turned to research the virus, the disease caused by it and risk factors associated with the disease. With this, chronic diseases such as diabetes were identified as a relevant comorbidity linked to severe and lethal cases of the disease, which is worrying due to the large number of people affected by the disease spread around the world. This work aims to elucidate how diabetic patients relate to COVID-19. For this, the following data sources were used: articles, magazines and electronic addresses available in the following databases: Scielo, Pubmed, Academic Google and direct Google search. However, despite diabetes being a known disease, COVID-19 is still under study, and constant updates are needed to understand how viruses and disease are related. Therefore, professionals can act properly and patients will receive the best possible treatment.
Error Analysis in Students’ Writing Composition

To recognize the students’ difficulties, this research analyzes errors in Students’ writing composition of Passive Voice. This study of error (error analysis) is part of an investigation of the process of English language learning. This research is to find the types of error analysis in students’ writing composition and to find the most dominant types of error analysis in students’ writing composition of passive voice. This research is qualitatively accomplished to look into errors in the second language acquisition. This research focused on the qualitative research by using document analysis to collect empirical data from the students’ writing. This method is applied to get the accurate data collection. The object of the research is students’ writing composition randomly taken from sixteen ESP students of Strata 1 – Arabic Department of STAI Ali bin Abi Thalib Surabaya. The researcher investigates more details by using surface strategy taxonomy to get the result of this error analysis. It is limited on the students’ passive sentences error in writing composition consisting of four error types: omission, addition, misformation, and misordering. Finally, after identifying the entire data and analyzing the research findings, it can be summarized that the types of passive voice errors produced by the students are (1) omission that occurred 24 times or 51,06% of all, (2) addition that occurred 15 times or 31,96% of all, (3) misordering that occurred 5 times or 10,64% of all, and (4) misformation that occurred 3 times or 6,38% of all. According to the research findings, the most dominant type of passive voice error is omission.
PROFESSIONAL PREPARATION OF TEACHERS IN THE USA FROM THE PERSPECTIVE OF PROFESSIONALISM AND COMPETENCE

The relevance of the study is in the fact that modern school and university teachers are limited by the frameworks of one discipline and thus their professional growth is only limited by the gradual recitation of the provisions of one or another subject in the senior school not allowing them developing interdisciplinary courses. The authors of the paper consider the problem much deeper and define that the teachers’ opportunity to increase their professional knowledge is based on the provision of the necessary preparation of teachers in order to not only let them teach their own discipline but also to let them implement the interdisciplinary approach. The novelty of the paper is in the fact that it does not say that the teacher should give several courses and thus have the idea of the structure of some or other discipline. For the authors of the paper, the main component is the need in the preparation of the senior school teacher of both technical and humanitarian disciplines, which allows precisely demonstrating the interdisciplinary connections in the process of education. The paper reveals the parameters of such qualification and presents the model that allows assessing the extent teachers may apply the obtained knowledge in practice. The implementation of the paper’s provision in the field of the pedagogical practice is seen by the authors in the development of the programs of the professional preparation of teachers in the process of their work and further improvement of their professional knowledge.
Investigating Deep Neural Structures and their Interpretability in the Domain of Voice Conversion

Generative Adversarial Networks (GANs) are machine learning networks based around creating synthetic data. Voice Conversion (VC) is a subset of voice translation that involves translating the paralinguistic features of a source speaker to a target speaker while preserving the linguistic information. The aim of non-parallel conditional GANs for VC is to translate an acoustic speech feature sequence from one domain to another without the use of paired data. In the study reported here, we investigated the interpretability of state-of-the-art implementations of non-parallel GANs in the domain of VC. We show that the learned representations in the repeating layers of a particular GAN architecture remain close to their original random initialised parameters, demonstrating that it is the number of repeating layers that is more responsible for the quality of the output. We also analysed the learned representations of a model trained on one particular dataset when used during transfer learning on another dataset. This also showed high levels of similarity in the repeating layers. Together, these results provide new insight into how the learned representations of deep generative networks change during learning and the importance of the number of layers, which would help build better GAN-based speech conversion models.
LibGuides: WSDOT Library: Exam Preparation

Links to resources useful to employees of the Washington State Department of Transportation and beyond.
Cuidados de enfermagem podológicos promotores de conforto ao idoso: uma revisão integrativa

Introduction: Podiatry care refers to the care of the extremities of the lower limbs and feet, namely in the assessment of the person's feet, hygiene and interventions that address problems with the maintenance or recovery of minor nail and foot problems. They involve a set of non-invasive interventions that protect the health of the feet and that should be a focus of nurses' attention / intervention.  Aim: Identify in the scientific literature the changes that occur in the feet of the elderly and know the nursing care podiatric that promotes comfort to the elderly.  Materials and Methods: This is an integrative review of the literature carried out during february 2020, scientific databases consulted: CINAHL; MEDLINE Cochrane and Mediclatina, in the sample period from January 2009 to December 2019.   Results: Of the 27 articles found, 5 were selected, that evidenced the alterations that occur in the feet of the elderly and the podological nursing care These, should be, in addition to being comforting, evaluate and identify problems, avoid disabilities and complications, rehabilitate sensory disabilities and promote functional independence, self-care and self-esteem, leading to a better quality of life for the elderly.  Conclusion: The prevalence of problems in elderly feet is a reality. We present the changes that occur in the feet of the elderly, as well as the nursing interventions that respond to the needs of the podiatrist and comfort.
MAgEC: Using Non-Homogeneous Ensemble Consensus for Predicting Drivers in Unexpected Mechanical Ventilation

We conduct exploratory analysis of a novel algorithm called Model Agnostic Effect Coefficients (MAgEC) for extracting clinical features of importance when assessing an individual patient's healthcare risks, alongside predicting the risk itself. Our approach uses a non-homogeneous consensus-based algorithm to assign importance to features, which differs from similar approaches, which are homogeneous (typically purely based on random forests). Using the MIMIC-III dataset, we apply our method on predicting drivers/causers of unexpected mechanical ventilation in a large cohort patient population. We validate the MAgEC method using two primary metrics: its accuracy in predicting mechanical ventilation and the similarity of the proposed feature importances to a competing algorithm (SHAP). We also more closely discuss MAgEC itself by examining the stability of our proposed feature importances under different perturbations and whether the non-homogeneity of the approach actually leads to feature importance diversity. The code to implement MAgEC is open-sourced on GitHub (https://github.com/gstef80/MAgEC).
Islamic Center Design with Islamic Architecture Design Approach

At the time of the Prophet, the mosque was a center for worship activities and economic activities, learning, socio-politics, etc. From this mosque environment, great figures in Islam were born who were not only strong in religion but also intellectually and mentally. However, the mosque has decreased in function now so that it is only a place of prayer. This phenomenon also occurs in the city of Medan, which is one of the largest cities in Indonesia, with the majority of the population being Muslim. Therefore, Medan often becomes the center of various activities, including Islamic religious activities in the area. Unfortunately, Medan does not yet have adequate facilities that can accommodate various Islamic religious activities, so it needs an activity center known as an Islamic center. The design of the Islamic center in the city of Medan solves design problems with an approach methodology ranging from literature studies, site surveys, and design concept analysis. This Islamic center applies a design concept by taking Islamic values ​​that are not indifferent to the surrounding environment so that elements of the local culture are still considered. It is hoped that this Islamic center will not only be able to become a center of activity, especially Islamic religious activities in Medan, but also an area of ​​learning about Islamic and local values ​​in its design
New Approach in Cryptography Using RC4 Protocol

RC4 protocol is most popular Cipher in Cryptography. In this topic to study of the efficient design of RC4 stream cipher, and proposing the efficient architecture for cipher. The concept of loop unrolling and pipeline combined to produce the 2 RC4 key stream bytes per clock cycle. The design is compared with the previous weeks and to check the how much cycles required for complete the individual KSA and PRGA modules and together the RC4 Stream Cipher. The Design is built using the XILINX 13.2 on Vertex ML605 Evaluation FPGA Board.
Sum of Costs Optimal Multi-Agent Path Finding with Continuous Time via Satisfiability Modulo Theories

Multi-agent path finding with continuous movements and time (denoted MAPF-R) is addressed. The task is to navigate agents that move smoothly between predefined positions to their individual goals so that they do not collide. Recently a novel solving approach for obtaining makespan optimal solutions called SMT-CCBS based on satisfiability modulo theories (SMT) has been introduced. We extend the approach further towards the sum-of-costs objective which is a more challenging case in the yes/no SMT environment due to more complex calculation of the objective.
Speeding Up Heuristic Function Synthesis via Extending the Formula Grammar

Heuristic search algorithms have long been used in video-game AI for unit navigation and planning. The quality of the solution they produce depends substantially on the quality of the heuristic function they use. Recent work automatically synthesized human-readable heuristic functions for a given pathfinding map. This enables tailoring a heuristic to the map but is expensive since each map requires an independent synthesis run. In this paper we propose and evaluate re-using elements of heuristics synthesized for one map in synthesizing heuristics for another map. We do so by adding parts of a synthesized heuristic back to the grammar that defines the space of heuristic functions for the synthesis.
Teaching Writing Recount Text by Using Cooperative Learning Type Team Assisted Individualization (TAI) Strategy

The objective of this study is to find out if there is a significant difference between the eighth-grade students of SMP Islam YPUI Banda Aceh who are taught writing recount text by using TAI strategy and those who are taught without using TAI strategy. This study was conducted by using quantitative approach and research design used was experimental study. The population of this study was all eight grade students of SMP Islam YPUI Banda Aceh. The total population is 60 students who are composed of two classes; VIII Male and VIII Female. Every class consisted of 30 students.While the samples of this study were the students who were taken from both classes. One class was as an experimental group and the other was as the control group. In this study, class VIII Female was taken as control group and class VIII Male was taken as experimental group.The data was analyzed by using t- test. Based on the result of the study, the writer found that there was a significant difference between the two groups. It can be proven from the result of this study where the result of post-test of the both group was 4.26, it was greater than t-table (2.00).Based on the result of the study, English teachers of SMP Islam YPUI Banda Aceh who teach writing skill especially recount texts are suggested to use TAI strategy in teaching and learning process because it can improve the students’ ability in mastering writing especially writing recount text.
Research on saliency prediction of GAN network based on residual structure

The structure of simple generated countermeasure network is optimized, whichis used to obtain visual saliency map more effectively through antagonistic case training, so as to reduce false positive and improve saliency. The network model still follows the traditional generation countermeasure network structure. In the first stage, it is composed of a generator built with residual structure. The weight of the model is calculated by the back-propagation of the binary cross entropy loss (BCE) of the down sampling version of saliency map, and the more effective saliency map is obtained by training. The prediction results are classified by the trained discriminator network between saliency map and truth graph. The experiment shows that the improved ability to generate predictive saliency map of generators in the countermeasure network can improve the performance of the whole network, and it is also ahead of other saliency map prediction models.