Reviewerly/exHarmony huggingface dataset:
DCSFN: Deep Cross-scale Fusion Network for Single Image Rain Removal

Rain removal is an important but challenging computer vision task as rain streaks can severely degrade the visibility of images that may make other visions or multimedia tasks fail to work. Previous works mainly focused on feature extraction and processing or neural network structure, while the current rain removal methods can already achieve remarkable results, training based on single network structure without considering the cross-scale relationship may cause information drop-out. In this paper, we explore the cross-scale manner between networks and inner-scale fusion operation to solve the image rain removal task. Specifically, to learn features with different scales, we propose a multi-sub-networks structure, where these sub-networks are fused via a crossscale manner by Gate Recurrent Unit to inner-learn and make full use of information at different scales in these sub-networks. Further, we design an inner-scale connection block to utilize the multi-scale information and features fusion way between different scales to improve rain representation ability and we introduce the dense block with skip connection to inner-connect these blocks. Experimental results on both synthetic and real-world datasets have demonstrated the superiority of our proposed method, which outperforms over the state-of-the-art methods. The source code will be available at https://supercong94.wixsite.com/supercong94.
These 4-year colleges offer free tuition — but there's a catch

With the student loan debt up to $1.6 trillion as of Q1 2019, according to Federal Reserve data, here are three colleges that offer free tuition as long as you work for it.
IMPLEMENTASI TEKNOLOGI MIXED REALITY SEBAGAI INOVASI STRATEGI PEMBELAJARAN SISTEM PEMBANGKIT TENAGA LISTRIK ENERGI BARU TERBARUKAN

Abstract: In an era that is completely digital, Information and Communication Technology (ICT) is very influential in many aspects of life, not to mention in the field of education, especially in universities. Along with the existence of an independent campus policy from the ministry of education, many universities are trying to harmonize appropriate learning methods. This can support the needs of superior human resources from higher education, so that the existence of ICT-based learning methods that present reality in a learning atmosphere is very important to design an appropriate visualization strategy. One of the ICTs that presents reality in a learning atmosphere that can be applied to the education sector is Mixed Reality (MR), which is a combination of Virtual Reality and Augmented Reality. This research will be conducted using research and development methods, where data collection will be carried out first and the selection of learning materials and end with the implementation and dissimilation. The benefits of applying this learning method are expected to create a learning environment that is closer to reality and establishes student independence in learning. The output of this research is the creation of MR-based learning materials at SMK TI Muhammadiyah Cikampek.
Sentiment Perception in Articulation

Emotion is quite prevalent aspect in daily life. Every individual has a inequity levels of anxiety in the finding the concealed emotion present in a speech or talk. So we had decided to procreate a new methodology in which every emotion which is present in a speech can be detected. The system we developed can detect any emotion with a great extent of efficiency. Any type of emotion will be detected using Machine learning algorithms in a effective way. We will utilize Multi-Layer Perceptron in the initial stage and then we will compare this with working model of Convolution Neural Networks. We want to develop an Artificial Intelligence perception system which leads to detection of emotion in any articulation
FIELDS OF IMPLEMENTATION OF THE TEACHER'S EDUCATIONAL FUNCTIONS

The present work seeks to answer which are the appropriate tools for an effective organization for carrying out a creative learning process In the aggregate of complex social and pedagogical functions performed by the teacher, the education of adolescents occupies the largest share. This is where the teacher spends most efforts, in which his qualities of a teacher and educator stand out most clearly. Through his activity in the learning process, the teacher is the one who mostly contributes to the development of the students, integrates them into the rich cognitive experience of mankind, prepares them for inclusion in the various fields of social and economic life.
Pattern Analysis Through Edge for the Reduction of Artifact of Decompressed Image in DCT Domain

In this paper, we present a simple and effective approach for measurement of blocking artifact with optimal 2-D step function. First, a simple edge detection technique is designed for the measurement of blocking artifacts. Based on the visibility of blocking artifact in the edge image, optimal 2-D step function is chosen. In frequency domain, blocking artifact reduction algorithm is designed to extract all the parameters needed to detect the presence of blocking artifacts and replace optimal step function with ramp function by changing the coefficient of first row of horizontal blocks with the coefficient of shifted block. The proposed technique is experimented on various standard benchmark images and found to have improvement in the perceptual quality of the JPEG compressed images after removal of blocking artifact with the proposed method.
The (Un)identification of Continuous-Action Rational Inattention Decision Models

In this paper, we discuss some properties of optimal consideration set in binary state continuous-action rational inattention decision problems.First, we show that it is the form of the utility function that determines the form of posterior distribution, i.e. whether it is a binary distribution or a triple or quadruple distribution, etc. Besides, we will also show that the posterior distribution may not be resulted after information acquisition in some circumstances.Second, we show that the optimal consideration set is essentially the optimal action strategies.Therefore, without further conditions, the rational inattention decision model is unidentifiable.Third, in order to identify the rational inattention decision model, we introduce another condition to the model.The discrete actions after information acquisition that satisfy the endogenously-determined probability (optimal action strategies) should satisfy the properties of probabilities, and therefore the discrete actions should also follow an exogenous probability distribution.This idea is tested by an example with quadratic utility function.Through this example, we find that under this condition, the optimal consideration set can be identified.The elements in the optimal consideration set, or equivalently the discrete signals after information acquisition, exhibit a curve or curves.
Students Difficulties in Determining Case in Sentence

The objectives of this research were to find out the students difficulties in determining types of case and to investigate the reasons why the students had difficulties in determining case. This was a qualitative descriptive research. The subject of this research was the sixth semester students of English Department in IAIN Langsa that consist of 30 students. Documentation, questionnaire and interview were the instruments in collecting the data. Based on the data, the students felt difficult in determining types of case such as accusative, locative, nominative, possessive, agentive, and ablative. It can be seen from the mistakes made by students through documentation and supported by the results obtained from questionnaire and interview. Then, there were several reasons why the students had difficulties in determining case. They were: 1) Many types of case given by a lecturer made the students difficult to remember them. 2) The students were confused with the types of case because a noun phrase can have more than one type. 3) The students felt difficult to distinguish between accusative and dative case. 4) The students did not master English grammar well.
Spelling Checker using Algorithm Damerau Levenshtein Distance and Cosine Similarity

Writing is an embodiment of the author's ideas that are to be conveyed to others. A writer often experiences typos in typing the script, so that it can influence the meaning of the text. Therefore, a system is needed to detect word errors. In this study, checking is done by using the Dictionary Lookup method and giving the candidate words using the Damerau Levenshtein Distance algorithm. Candidates will then determine the ranking by breaking the word into Bigram form and calculating the similarity value using the Cosine Similarity algorithm. The test results based on the data used yield different Mean Reciprocal Rank (MRR) values for each type of error. The type of error deletion produces an MRR value of 88.89%, the type of insertion error produces an MRR value of 97.78%, the type of substitution error produces an MRR value of 88.89%, the type of transposition error produces an MRR value of 89%
Pentingnya Pengukuran Pupil Distance (PD) Secara Tepat Untuk Menjaga Akurasi Distance Vitror (DV) Kacamata

Pupil Distance (PD) is measured in millimetres and even a slight variation can cause a number of vision and eye health problems due to inacurately fitting of Distance Vitror (DV). PD must be paralel to DV, therefore PD measurements must be committed throughtly. It requires comprehensive knowledge and technical skill. With the popularity of buying glasses online, a number of websites have come up with do-it-yourself measurements or apps that will take this measurement for you. The problem is that these are not scientifically accurate measurements and are not being performed by professionals. There is a large margin of error and buyers could end up with glasses that hurt their vision—not correct it.This research is aimed to show ideal procedure that must be committed in producing glasses to avoid inacurate PD measurement. The researcher uses library aprroach to gain related data and informations, then discuss the problem and solution in descriptive approach.
Comparing Weak Admissibility Semantics to their Dung-style Counterparts (Extended Abstract)

Semantics based on weak admissibility were recently introduced to overcome a problem with self-defeating arguments that has not been solved for more than 25 years. The recursive definition of weak admissibility mainly relies on the notion of a reduct regarding a set E which only contains arguments which are neither in E, nor attacked by E. At first glance the reduct seems to be tailored for the weaker versions of Dung-style semantics only. In this paper we show that standard Dung semantics can be naturally reformulated using the reduct revealing that this concept is already implicit. We further identify a new abstract principle for semantics, so-called modularization describing how to obtain further extensions given an initial one. Its importance for the study of abstract argumentation semantics is shown by its ability to alternatively characterize classical and non-classical semantics.
SELM: Siamese extreme learning machine with application to face biometrics

Extreme learning machine (ELM) is a powerful classification method and is very competitive among existing classification methods. It is speedy at training. Nevertheless, it cannot perform face verification tasks properly because face verification tasks require the comparison of facial images of two individuals simultaneously and decide whether the two faces identify the same person. The ELM structure was not designed to feed two input data streams simultaneously. Thus, in 2-input scenarios, ELM methods are typically applied using concatenated inputs. However, this setup consumes two times more computational resources, and it is not optimized for recognition tasks where learning a separable distance metric is critical. For these reasons, we propose and develop a Siamese extreme learning machine (SELM). SELM was designed to be fed with two data streams in parallel simultaneously. It utilizes a dual-stream Siamese condition in the extra Siamese layer to transform the data before passing it to the hidden layer. Moreover, we propose a Gender-Ethnicity-dependent triplet feature exclusively trained on various specific demographic groups. This feature enables learning and extracting useful facial features of each group. Experiments were conducted to evaluate and compare the performances of SELM, ELM, and deep convolutional neural network (DCNN). The experimental results showed that the proposed feature could perform correct classification at 97.87% accuracy and 99.45% area under the curve (AUC). They also showed that using SELM in conjunction with the proposed feature provided 98.31% accuracy and 99.72% AUC. SELM outperformed the robust performances over the well-known DCNN and ELM methods.
Hasil Cek Similarity: A Corpus-Based Analysis Of English CoreModal Verbs And Their Counterparts InIndonesian

This paper examines the core modal verbs in English and their counterparts in Indonesian. It reveals the plausible modality c ategoriesdominant among English and Indonesian speakers, identifying the most salient modality categories. The English core modal verbs being investigatedare equivalent to can, could, will, would, shall, should, may, might, and must, which have been selected due to their wide us e in formal and non-formalcontexts. The analysis indicates the frequency of modal verb usage in English and Indonesian sentence constructions. It provides a contrastive analysisusing quantitative and qualitative approaches. Data was collected from several corpora: ARCHER and COCA for English language data and MCP andWortschatz for Indonesian language data. Data was analysed quantitatively by applying the normalised frequency method and qualitatively by employingthe translational identity method. The analysis shows that core modal verbs expressing volition and prediction are most frequently found in English, withthe modal verb will being the most frequently used modal verb and its preterite form occupies the third position. As with English, Indonesian alsoconsiders the expression of volition and prediction salient because it most frequently uses the modality expression akan. The modal verbs can and couldare also used intensively by English speakers, showing that speakers consider the concepts of possibility and permission prominent, as well asprediction and volition. The contrastive analysis shows that, among English and Indonesian speakers, prediction and volition are important notionalstates in terms of modality expression.Index Terms: corpus, corpus-based analysis, English, Indonesian, modal verbs
Reasoning about Iteration and Recursion Uniformly based on Big-step Semantics

A reliable technique for deductive program verification should be proven sound with respect to the semantics of the programming language. For each different language, the construction of a separate soundness proof is often a laborious undertaking. In language-independent program verification, common aspects of computer programs are addressed to enable sound reasoning for all languages. In this work, we propose a solution for the sound reasoning about iteration and recursion based on the big-step operational semantics of any programming language. We give inductive proofs on the soundness and relative completeness of our reasoning technique. We illustrate the technique at simplified programming languages of the imperative and functional paradigms, with diverse features. We also mechanism all formal results in the Coq proof assistant.
Pemetaan digital kedalaman tanah Kota Banjarmasin

Digital mapping (also called digital cartography) is the process that forms data sets that are compiled and formatted into digital images. The main function of this technology is to produce maps that provide an accurate representation of a particular area, detailing the main roads and other points of interest. This technology also makes it possible to calculate distances from one place to another. In the area of Banjarmasin City, a lot of data has been obtained well based on sondir data or SPT data. But for now, there is no information that summarizes the depth of hard soil in the city of Banjarmasin, especially in the form of digital maps. Therefore, it is necessary to create a digital map concept that can be used as a reference for the initial foundation work in the field. The result of this study is a map of the depth of hard soil in the city of Banjarmasin with the help of GIS software. From the results of recapitulation of soil depth data based on sondir data obtained a depth distribution of hard soil in the city of Banjarmasin from 28 m to 42.4 m. For points that are not covered, a linear interpolation method is used. This depth varies in each sub-district, between 30-40 m in North Banjarmasin, 36-42.4 m in West Banjarmasin, South Banjarmasin, and Central Banjarmasin, and 28-40 m in East Banjarmasin.
Pose-Guided Feature Learning with Knowledge Distillation for Occluded Person Re-Identification

Occluded person re-identification (ReID) aims to match person images with occlusion. It is fundamentally challenging because of the serious occlusion which aggravates the misalignment problem between images. At the cost of incorporating a pose estimator, many works introduce pose information to alleviate the misalignment in both training and testing. To achieve high accuracy while preserving low inference complexity, we propose a network named Pose-Guided Feature Learning with Knowledge Distillation (PGFL-KD), where the pose information is exploited to regularize the learning of semantics aligned features but is discarded in testing. PGFL-KD consists of a main branch (MB), and two pose-guided branches, \ieno, a foreground-enhanced branch (FEB), and a body part semantics aligned branch (SAB). The FEB intends to emphasise the features of visible body parts while excluding the interference of obstructions and background (\ieno, foreground feature alignment). The SAB encourages different channel groups to focus on different body parts to have body part semantics aligned representation. To get rid of the dependency on pose information when testing, we regularize the MB to learn the merits of the FEB and SAB through knowledge distillation and interaction-based training. Extensive experiments on occluded, partial, and holistic ReID tasks show the effectiveness of our proposed network.
A Generalizable Model-and-Data Driven Approach for Open-Set RFF Authentication

Radio-frequency fingerprints~(RFFs) are promising solutions for realizing low-cost physical layer authentication. Machine learning-based methods have been proposed for RFF extraction and discrimination. However, most existing methods are designed for the closed-set scenario where the set of devices is remains unchanged. These methods can not be generalized to the RFF discrimination of unknown devices. To enable the discrimination of RFF from both known and unknown devices, we propose a new end-to-end deep learning framework for extracting RFFs from raw received signals. The proposed framework comprises a novel preprocessing module, called neural synchronization~(NS), which incorporates the data-driven learning with signal processing priors as an inductive bias from communication-model based processing. Compared to traditional carrier synchronization techniques, which are static, this module estimates offsets by two learnable deep neural networks jointly trained by the RFF extractor. Additionally, a hypersphere representation is proposed to further improve the discrimination of RFF. Theoretical analysis shows that such a data-and-model framework can better optimize the mutual information between device identity and the RFF, which naturally leads to better performance. Experimental results verify that the proposed RFF significantly outperforms purely data-driven DNN-design and existing handcrafted RFF methods in terms of both discrimination and network generalizability.
A Sign Language Based ATM Accessing System for Visually Impaired

The blind population often face difficulties in accessing ATMs to withdraw money which forces them to visit bank. This often cause inconvenience to them. Though Braille inscribed keypads are provided to easier their use, usually impaired who might be braille- illiterate fail to use these systems. But what if people don’t know to insert a card? The friend accompanying him might get to know the password or someone else can come to know of his pin number. A stranger might try to help the blind win the trust and rob him. Hence, as an alternative a sign language based accessing system is proposed in this project.
Students' perception of the acquisition of competence in digital content creation with gamification

Teacher training in Digital Teaching Competence (DTC) should be facilitated through innovative approaches such as gamma-mapping. In this study, it is verified through a questionnaire how gamification affects the interest and perception of learning technology in a master's degree in distance education, and if there are differences according to variables, such as gender and age, in the acquisition of the Digital Content Creation dimension of the DCC. The results show an improvement in the perception of knowledge after the experience. We found differences in terms of previous knowledge in the creation of videos and programming, and in terms of previous interest in the use of the POI and content enrichment. These results allow us to conclude that the experience facilitates the perception of the acquisition of the skills studied and allows us to make proposals for improvement.
국방환경 변화에 따른 대민지원 개념 및 추진방향에 관한 연구

The defense environment is changing, due to the reduced in military personnel and shortened military service period in the era of low birthrate and aging population, as well as the issue of guaranteeing the human rights of soldiers.Military Aid to Civil Authorities can be divided into two categories. First, “Military Assistance to Civil Authorities” systematically supports civilian to carry out military mission in various kinds of disasters. and Second, there is “Civil Affairs Service Activities” which soldiers can voluntarily participate in peacetime.By examining the laws, systems, organizations and support cases related to Military Aid to Civil Authorities of Korean and foreign troops, same implications are suggested.In addition, Military Aid to Civil Authorities should be distinguished from fatigue duty. The scope should be devided as clearly as possible whether the military aids are available or not so that the soldiers can be faithful to their original duties.
Fast Monocular Hand Pose Estimation on Embedded Systems

Hand pose estimation is a fundamental task in many human-robot interaction-related applications. However, previous approaches suffer from unsatisfying hand landmark predictions in real-world scenes and high computation burden. This paper proposes a fast and accurate framework for hand pose estimation, dubbed as "FastHand". Using a lightweight encoder-decoder network architecture, FastHand fulfills the requirements of practical applications running on embedded devices. The encoder consists of deep layers with a small number of parameters, while the decoder makes use of spatial location information to obtain more accurate results. The evaluation took place on two publicly available datasets demonstrating the improved performance of the proposed pipeline compared to other state-of-the-art approaches. FastHand offers high accuracy scores while reaching a speed of 25 frames per second on an NVIDIA Jetson TX2 graphics processing unit.