Reviewerly/exHarmony huggingface dataset:
Distributed Multi Cloud Storage System to Improve Data Security with Hybrid Encryption

Data security of cloud storage is one of the major concerns right now. Usually, cloud storage providers store user data in a single location to achieve better maintainability. Beside some advantages, this approach has drawbacks also. The government of the country can legally order the cloud storage provider to let them access their stored data and in such situation, a user who is from another part of the world can not stop the provider. In a system it is very likely to have system vulnerability and the hacker is going to take its advantages as soon as he discovers it. The storage design approach described in this paper aimed to reduce the unauthorized access to end-user data. Our goal is to design a storage system which is a combination of some major cloud storage service providers. Our experimental results indicate that proposed approach provided the end user better control on his data in cloud storage with minimum cost and performance effect. Our system ensures user data privacy from anyone including government or cloud service provider itself.
Bahan Ajar Tema Daerah Tempat Tinggalku Berbasis Kearifan Lokal

&lt;div align="center"&gt;&lt;table width="645" border="1" cellspacing="0" cellpadding="0"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td valign="top" width="439"&gt;&lt;pre&gt;&lt;strong&gt;Abstract:&lt;/strong&gt; This study aims to produce products in the form of teaching materials on the theme of the area where My live based on local wisdom. This product consists of teacher books and student books. The product was developed with reference to the Dick &amp;amp; Carey development model. This study uses a type of quantitative data. The feasibility of the product is tested through validation test, attractiveness test, practicality test, and effectiveness test. The results of the tests that have been carried out, the product is declared to have met the criteria and requirements used in the field as a supporting book. &lt;/pre&gt;&lt;p&gt;&lt;strong&gt;Abstrak:&lt;/strong&gt;&lt;strong&gt; &lt;/strong&gt;Penelitian ini bertujuan untuk menghasilkan produk berupa bahan ajar tema daerah tempat tinggalku berbasis kearifan lokal. Produk ini terdiri atas buku guru dan buku siswa. Produk dikembangkan dengan mengacu pada model pengembangan Dick &amp;amp; Carey. Penelitian ini menggunakan jenis data kuantitatif. Kelayakan produk diujikan melalui uji validasi, uji kemenarikan, uji kepraktisan, dan uji keefektivan. Hasil dari pengujian yang telah dilakukan, produk dinyatakan telah memenuhi kriteria dan persyaratan digunakan di lapangan sebagai buku penunjang.&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;/div&gt;
Configurable Hardware Accelerator Architecture for a Takagi-Sugeno Fuzzy Controller

In this paper, we present a parametric hardware accelerator for Takagi-Sugeno fuzzy controllers. The architecture consists of an application specific weighting function computation block, generic control output computation unit, and a programmable register file based interface. The proposed hardware design methodology is applied to a two degree of freedom robot arm controller. FPGA implementation results indicate that the hardware TS fuzzy controller supports throughputs up to 1.5 Msamples/sec, with maximum working frequencies of around 150 MHz.
Amplify Your Impact: The Insta-Story: A New Frontier for Marking and Engagement at the Sonoma State University Library

This month’s author, Catherine Fonseca from Sonoma State University Library, shares some innovative and fun ideas on how libraries can use the Instagram Stories feature to engage with their audience in multiple ways. We guarantee you will find a tidbit you can use in your own library.—Editor
Exposure Bracketing Techniques for Camera Document Image Enhancement

Capturing document images using digital cameras in uneven lighting conditions is challenging, leading to poorly captured images, which hinders the processing that follows, such as Optical Character Recognition (OCR). In this paper, we propose the use of exposure bracketing techniques to solve this problem. Instead of capturing one image, we used several images that were captured with different exposure settings and used the exposure bracketing technique to generate a high-quality image that incorporates useful information from each image. We found that this technique can enhance image quality and provides an effective way of improving OCR accuracy. Our contributions in this paper are two-fold: (1) a preprocessing chain that uses exposure bracketing techniques for document images is discussed, and an automatic registration method is proposed to find the geometric disparity between multiple document images, which lays the foundation for exposure bracketing; (2) several representative exposure bracketing algorithms are incorporated in the processing chain and their performances are evaluated and compared.
IMPLEMENTATION OF DIGITAL SIGNATURE FOR RESEARCH PAPER LEGALIZATION, AUTHENTICATION AND RATIFICATION CASE STUDY: TRAINING CENTER FOR NATIONAL CYBER AND CRYPTO AGENCY

At The Training Center for The National Cyber and Crypto Agency, at the end of every course programs, the students are given a task to write scientific papers. Then those papers must be ratified by the seminar committee using their wet signatures as a sign of ratification of documents. But the drawback of using wet signatures is that often difficult to get committee signatures as they are not always in the office. To overcome this problem, we'll discuss the uses of digital signature for student's papers ratification. This research begins by describing a digital signature and how it can replace a wet signature. Then we present the design of a scheme for implementing a digital signature that can be applied for papers authentication and ratification. Retrieval of the research data is done through in-depth observations in the process of ratifying student's scientific papers at The Training Center for The National Cyber and Crypto Agency. The result of this study is the application of digital signatures as a substitute solution for wet signatures on student’s scientific papers ratification.
A New Transformed Stochastic Shortest Path with Dead Ends and Energy Constraint

We consider Stochastic Shortest Path (SSP) Markov Decision Processes (MDPs) with dead ends and energy constraint.The objective is to find an optimal policy that maximizes the probability of reaching the target and minimizes the expected cost if the energy is sufficient.Firstly, we present a new Transformed SSP MDP that guarantees the convergence of the classical iterative algorithms and addresses the problem of energy-reachability.Secondly, we propose a topological algorithm based on a decomposition of the state space into some levels.In each level, a restricted SSP MDP is constructed and solved; the combined solution gives an admissible heuristic solution used as an initial point in the Pre-Gauss-Seidel Value Iteration (PGSVI) algorithm.Finally, an example of robot navigation in hexagonal grid's environment will be presented to show the advantages of the TSSP MDP and the performance of the proposed topological solver.
The Effect of Scaffolding toward Students’ Writing Procedure Text

The purpose of this study was to determine whether scaffolding can have a significant effect on students' ability to write procedure texts. In this study, the sample used is the students of grade XI SMA Muhammadiyah 25 Setiabudi Pamulang. The sample was from the class XI IPA 1 as the experimental class and XI IPA 2 as the control class. Each of them consists of 36 students. The writer used purposive sampling technique in determining the number of samples from the existing population. The method used was quantitative and the design used was quasi-experimental study. The instrument in this study was a written test. To ensure the reliability of the instrument, the writer uses a rubric in the assessment called analytic scoring adopted from John Anderson to assess student writing in pre-test and post-test. The findings of this study were the mean score of pre-test of experimental class students was 56.47 and the mean score of the student's post-test was 76.14. In contrast, the students’ pre-test mean score of the controlled class was 63.25 and the mean score for the post-test was 66.72. The significant effect was shown by the students’ post-test mean score of the experimental class which was treated by scaffolding technique was greater than the post-test mean score of the controlled which was not treated by scaffolding technique. The result of the statistical hypothesis test found that on significance level 0.000 &lt; 0.005. Thus the H0 (Null Hypothesis) was rejected and the H1 (Alternative Hypothesis) was accepted. It proved that the application of scaffolding technique is effective towards the students’ skill in writing procedure text.
Research on Digital Resources Integration Model in Cloud Computing Environment

This article analyzed the present situation of digital resources integration, expounded the content and methods of the digital resources integration, focused on related digital resources integration theory for cloud computing environment, combined with the characteristics of cloud computing, and proposed the application and improvement of the digital resources integration based on cloud computing technology.
Superposition of Dual Image Fusion with Improved Dehazing Methods for high Visibility of Underwater Image

Limited visibility is one of the problem in underwater imagery. As the images captured in deep blue or green ocean, the visibility becomes restricted as the color spectrum is filtered or absorbed by the water medium. This results the objects to be hardly seen and differentiated from the background. The propose method which is called integrated dehazed image fusion (IDF) superimposes two main steps in improving the visibility of the object in deep underwater image. At the beginning, the modified homomorphic filtering is applied to the input image to improve the homogeneous illumination of the image between the background and foreground. Dehazing process is then implemented with integrated of contrast boosting mechanism, followed by dual image fusion technique. Finally, the image is applied with specific local histogram enhancement with adaptive mechanism to improve the local contrast of the image. Implementation of dehazing process improves the effect of homogeneity in the output image which prevent the image from having imbalance color between fore-and background. Superposition with contrast enhancement improves the overall contrast quality of the image. Qualitatively, the output image has better contrast and visibility compare to the current state-of-the-art methods, beside the improvement of overall image color.
Question Answering Systems Approaches and Challenges

Question answering (QA) systems permit the user to ask a question using natural language, and the system provides a concise and correct answer.QA systems can be implemented for different types of datasets, structured or unstructured.In this paper, some of the recent studies will be reviewed and the limitations will be discussed.Consequently, the current issues are analyzed with the proposed solutions.
Kinematic real-time trajectory planning with state and input constraints for the example of highly automated driving

The real-time generation of kinematic trajectories w.r.t. state and input constraints is discussed for the stabilization of the lateral, longitudinal and vertical motion of objects such as (automated) vehicles in the Frenet frame. The goal is to exploit the property of differential flatness in order to achieve optimal trajectories as well as a flexible and selectable prioritization-based constraints satisfaction. This aim is subject to the absence of an online optimization and a low complexity of the planner’s architecture. With regard to practical application, a discrete-time implementation of the planner is presented and benchmarked with two modern MPC approaches in terms of optimality and CPU-time consumption by means of simulation studies.
Combining convolutional neural networks and slantlet transform for an effective image retrieval scheme

&lt;p&gt;In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN), Convolutional Neural Network - Slanlet Transform (CNN-SLT) model uses Slanlet Transform (SLT). The CBIR system was therefore inspected and the outcomes benchmarked. The results clearly illustrate that generally, the recommended technique outdid the rest with accuracy of 89 percent out of the three datasets that were applied in our experiments. This remarkable performance clearly illustrated that the CNN-SLT method worked well for all three datasets, where the previous phase (CNN) and the successive phase (CNN-SLT) harmoniously worked together.&lt;/p&gt;
A Proposal Model Based on Blockchain Technology to Support Traceability of Colombian Scholar Feeding Program (PAE)

Given the development of Blockchain technology and its advantages of immutability and traceability to provide traceability in the control and management of transactions the present work exposes a model based on Blockchain technology to support traceability and control of the resources of the Colombian Scholar Feeding Program PAE (in Spanish Programa de Alimentación Escolar – PAE). This proposal tries to promote a technological approach to face corruption linked with this kind of programs; providing PAE with tools that could reduce the risk to lost resources or facilitate the identification of the people responsible of corruption cases. The steps of the proposed model are described providing their advantages and limitations.
Code Overload

I spend much of my time analyzing code. In most cases that code was written by someone else, but it could just as easily have been written by an evil earlier version of me from many years ago. Today, any nontrivial code base is typically hundreds of thousands of lines of code, and for large companies it often reaches into the megamillions. This makes the code-review process feel like you're exploring caves with myriads of little passages leading nowhere in particular.
Dyadic Interference Leads to Area of Uncertainty During Face-to-Face Cooperative Interception Task

People generally coordinate their action to be more efficient. However, in some cases, interference between them occur, resulting in an inefficient collaboration. For example, if two volleyball players collide while performing a serve reception, they can both miss the ball. The main goal of this study is to explore the way two persons regulate their actions when performing a cooperative task of ball interception, and how interference between them may occur. Starting face to face, twenty-four participants (twelve teams of two) had to physically intercept balls moving down from the roof to the floor of a virtual room. To this end, they controlled a virtual paddle attached to their hand moving along the anterior-posterior axis. No communication was allowed between participants so they had to focus on visual cues to decide if they should perform the interception or leave the partner do it. Participants were immersed in a stereoscopic virtual reality setup that allows the control of the situation and the visual stimuli they perceived, such as ball trajectories and the information available on the partner's motion. Results globally showed participants were often able to intercept balls without collision by dividing the interception space in two equivalent parts. However, an area of uncertainty (where many trials were not intercepted) appeared in the center of the scene, highlighting the presence of interference between participants. The width of this area increased when the situation became more complex (facing a real partner and not a stationary one) and when less information was available (only the paddle and not the partner's avatar). Moreover, participants initiated their interception later when real partner was present and often interpreted balls starting above them as balls they should intercept, even when these balls were \textit{in fine} intercepted by their partner. Overall, results showed that team coordination here emerges from between-participants interactions and that interference between them depends on task complexity (uncertainty on partner's action and visual information available)
Transaction credit in the unstructured crowd transaction network

Purpose Current models of transaction credit in the e-commerce network face many problems, such as the one-sided measurement, low accuracy and insufficient anti-aggression solutions. This paper aims to address these problems by studying the transaction credit problem in the crowd transaction network. Design/methodology/approach This study divides the transaction credit into two parts, direct transaction credit and recommended transaction credit, and it proposes a model based on the crowd transaction network. The direct transaction credit comprehensively includes various factors influencing the transaction credit, including transaction evaluation, transaction time, transaction status, transaction amount and transaction times. The recommendation transaction credit introduces two types of recommendation nodes and constructs the recommendation credibility for each type. This paper also proposes a “buyer + circle of friends” method to store and update the transaction credit data. Findings The simulation results show that this model is superior with high accuracy and anti-aggression. Originality/value The direct transaction credit improves the accuracy of the transaction credit data. The recommendation transaction credit strengthens the anti-aggression of the transaction credit data. In addition, the “buyer + circle of friends” method fully uses the computing of the storage ability of the internet, and it also solves the failure problem of using a single node.
Klasifikasi Kecerdasan Majemuk pada Anak Berdasarkan Posting Aktivitas di Media Sosial Menggunakan SentiStrength dan Spearman's Rank Correlation Coefficient

Intelligence are things related to intelligence, intellectual action, and perfect development of the mind. Every human being has the right to develop himself based on intelligence. A child who is good at playing violin shouldn't let himself feel like he is stupid because he is unable to complete his mathematical tasks. Therefore, the author wants to create a system for determining children's talent based on multiple intelligence as measured by the tendency of posts about their daily activities on social media by using the Sentistrength and Spearman's Correlation Coefficient methods. The purpose of this research is to create a social media application called Juicer, which is able to determine one's talent according to multiple intelligence theory based on data in the form of user posts about their daily activities. Users input their daily activities and opinions about the activities that he is currently undergoing. The system will analyze the data entered a negative or positive opinion. Then determine whether the data entered are musical-rhythmic, visual-spatial, verbal-linguistic, logical-mathematical, bodily-kinesthetic, interpersonal, intrapersonal, naturalistic, and / or spiritual-type using lexicon-based sentiment analysis with the Sentistrength method. After a long period of time, the system will sort the data that has been stored. After the data is classified, user intelligence types will be found based on multiple intelligence theory, as a result of this study. The result of the correlation between intelligence type data obtained through the system compared to intelligence type data obtained through the manual method is 80%, and the deviation value is 0.09.
Moth-flame glowworm swarm optimisation

One of the drawbacks of glowworm swarm optimisation (GSO) is its premature convergence, which leaves it often ineffective for solving complex practical problems. This paper proposes a new hybrid metaheuristic algorithm, that is, moth-flame glowworm swarm optimisation (MFGSO). The main idea of the h ybrid algorithm is to combine the exploration ability in moth-flame optimisation (MFO) with the exploitation ability in GSO. Performance evaluations are conducted on benchmarking test functions in comparison with the basic GSO and other metaheuristic algorithms. The results show that MFGSO outperforms the basic GSO and other metaheuristic algorithms on most test functions in terms of local optima avoidance and convergence speed.
Understanding Failure Mode Effect Analysis Data Using Interactive Visual Analytics

Providing actionable insights through interactive visual analytics is essential to effective decision making. Yet, many complex systems engineering (SE) domains still lack such tools. Design reviews are often still based on static snapshots of data, without any dynamic interaction, data curation, and view creation capabilities to answer salient analysis questions. In this study, we report on a tool called DataHawk that helps answer common questions associated with one prominent SE context, namely failure mode and effect analysis (FMEA). The tool provides powerful exploration capabilities that enable system engineers, designers, and managers to probe FMEA data from multiple starting points, build questions dynamically, and find triangulated answers using multiple views rapidly. Field results are illustrated through a usage scenario from the automotive industry and show that the tool demonstrates the needed versatility, scalability, and effectiveness for real-world engineering data.
Exact Takagi-Sugeno descriptor models of recurrent high-order neural networks for control applications

This work presents an exact Takagi-Sugeno descriptor model of a recurrent high-order neural network arising from identification of a nonlinear plant. The proposed rearrangement allows exploiting the nonlinear characteristics of the neural model for $$\mathcal H_\infty $$-optimal controller design whose conditions are expressed as linear matrix inequalities. Simulation and real-time results are presented that illustrate the advantages of the proposal.