Reviewerly/exHarmony huggingface dataset:
One-Point Cellulose Adsorbents for Water Purification

The protection of our environment from pollution by various industrial wastewater discharges is of great importance that each Industry treats its effluent to meet acceptable limit/design means to reclaim water from industrial effluents for re-use. The study aimed at reclaiming water from wastewater by assessing the performance of two cellulose adsorbents using the fixed-bed column method to treat pharmaceutical/metal wastewater. The study was carried out by determining the physico-chemical and microbiological parameters of wastewater quality before and after treatment using fixed-bed column. Effluent samples were collected and analyzed according to standard methods.&#x0D; The range of percentage reduction in pollution load with respect to treatment time: 30, 120, 360 and 1440 min was 45-52%, 55-64%, 31-43, 25- 45%, 41- 44%, 55-73%, 48- 51%, 48-54%, 56-71% 13-31%, 45-52%, 47-67% from the metal effluent using nanocellulose adsorbent while 14-24%, 18-23%, 4-10%, 28-46%, 16-20%, 24-42%, 14-32%, 42-57%, 32-52%, 36-47%, 37-56%, 8-53% from the pharmaceutical effluent using oxidized cellulose adsorbent for colour, turbidity, conductivity, total hardness, Nitrite, Phosphate, Ammonia, Biochemical Oxygen Demand, Chemical Oxygen Demand, total solids, total suspended solids and total dissolved solids respectively. Up to 99.9 % was achieved by the adsorbents in the removal of biological contaminants. The study concluded that the celluloses adsorbents showed promising potentials as one-point adsorbent that can be used for water reclamation from wastewater by its ability to remediate both physico-chemical and bacteriological contaminants.
A Programmable Artificial Neural Network Coprocessor for Handwritten Digit Recognition

This paper proposes the hardware architecture of an artificial neural network coprocessor that its structure can be programmable. The number of neurons in each layer of a feedforward network can be set by writing configuration registers. The processing unit with four MACs and the sigmoid calculation engine are connected in eight pipeline stages to enhance the processing speed. The application of handwritten digit recognition from the MNIST database was performed to verify the performance of proposed architecture. The design was developed with Verilog HDL and implemented on the Xilinx Artix-7 XC7A35T FPGA. The experimental results revealed that the speed of back-propagation learning and validation process can be up to 47 times faster than computation on ARM Cortex-A4 CPU, while the recognition rate is still the same.
Efficient Information Reconciliation for Energy-Time Entanglement Quantum Key Distribution

Graph based codes such as low density parity check (LDPC) codes have been shown promising for the information reconciliation phase in quantum key distribution (QKD). However, existing graph coding schemes have not fully utilized the properties of the QKD channel. In this work, we first investigate the channel statistics for discrete variable (DV) QKD based on energy-time entangled photons. We then establish a so-called balanced modulation scheme that is promising for this channel. Based on the modulation, we propose a joint local-global graph coding scheme that is expected to achieve good error-correction performance.
Developing a User-Centred Communication Pad for Cognitive and Physical Impaired People

It is always challenging for people with disabilities, particularly having speech inhibition to communicate. In this research article, we explored the case study of the resident at the neurological centre, having a complication in conveying messages due to physical and speech paralysis. For making effective communication, we have developed a user-centred communication pad where the resident needs to swipe a finger on the pad with printed alphabets and digits (we called it communication pad). A camera placed over the communication pad detects the finger movement of the resident and extract the message to display on the computer screen or the tablet. Our tracking method is robust and can track the fingers even in varying illumination conditions. This paper also covers the main steps of design methods with various design prototypes and its user feedback. Result analysis of different design modules and user experience evaluation shows that our designed system has provided independence and convenience to the resident in conveying a message successfully.
Using Machine Learning Method to Identify for Frog Classification

This paper presents the application of machine learning (ML) method to do frog classification. Bioacoustic features are filtered with respect of Mel-scale frequency cepstral coefficient (MFCC) algorithm. The raw data is collected from real frog sounds by using a digital signal processing technique. For classification and identification of frog, we can adopt the neural network (NN) of ML algorithm. Experimental results are carried out for bioacoustic features four frogs. The effectiveness of the proposed system on the bioacoustic features is identified by using the general NN scheme. Implementation results on CPU and GPU processors can be discussed.
EFFICIENCY OF TEACHING ENGLISH MONOLOGUE PRODUCTION TO FUTURE MECHANICAL ENGINEERS BY MEANS OF PODCASTING

The purpose of the given article is to prove the efficiency of teaching ESP monologue production to students majoring in mechanical engineering by means of podcasting. The efficiency of the methodology devised was verified in the process of an experiment conducted at the Institute of Mechanical Engineering, Igor Sikorsky Kyiv Polytechnic Institute in the academic year 2018 – 2019, from September to December. Three experimental groups, thirty-four students in total, studying in their final year of Bachelor’s studies, participated in the methodological experiment. The main stages of any methodological experiment that comprise its “nucleus” are: pre-experimental assessment; experimental teaching and post-experimental assessment. The obtained results of the pre-experimental assessment indicated an insufficient level of the participants’ communicative competence formation in monologue production, thus proving the significance of developing new teaching methodologies for the future mechanical engineers. The experimental teaching lasted for 28 hours and took place in three experimental groups on the basis of the suggested set of tasks. The set of tasks inferred implementation of information and communication technology and was performed both in class and out of class. Working out-of-class, students performed tasks on the podcasting terminal, arranged by the experimenter on the Internet on a special educational platform called Canvas. The purpose of the post-experimental assessment was to evaluate the participants’ communicative competence formation in monologue production after the experimental teaching, thus, verifying the efficiency of the methodology devised. The methodological experiment performed and the data processed by methods of mathematical statistics with its further qualitative and quantitative analysis have confirmed that the process of teaching ESP monologue production to future mechanical engineers is effective on condition that the set of tasks that envisages podcasting implementation is used.
Promoting Social Learning in Soil Water and Nutrients Management Using Farmer—Friendly Monitoring Technology

Soil water management is typically by trial and error among smallholder farmers. Social learning in the use of farmer—friendly soil-water and nutrients monitoring tools were promoted in Malawi to improve productivity. A simple tool (chameleon) which was designed to fit the mental model of African farmers and to give an output that is linked to action was deployed to 198 farmers in nine irrigation schemes. Chameleon illustrates information on soil moisture status by colours—blue, green and red colours representing adequate moisture, moderate and dry soil status, respectively. The use of colours and not numbers promoted inclusiveness across illiterate and all gender categories. Farmers participated in sensors’ installation, soil moisture measurement, data visualization and learning by doing to get insights from their participation. The chameleon was combined with an on-line communication and learning system to improve water management at scheme level. The results indicated that: (1) the tool gave farmers new frames of reference; (2) it improved farmers on time, labour and water saving by reducing irrigation intervals; (3) it gave farmers new reference of experience to change their irrigation traditions; (4) it also reduced conflict for water in irrigation schemes between users apart from improving water productivity. Use of these tools made a rigor that make scientists easily communicate science to lay farmer and initiated the movement of farmers who know how to manage water. Social learning in sensor technology helped to increase farmers’ resilience to climate change and shaping the science of the future.
Designing Courier Service (Jastip) Application by using Spark-based Big Data technology

Jastip is an informal service that offers assistance to people in need or want to buy something but cannot go to the desired place to buy themselves for various reasons.Those who offer help will give you a service value for each item offered for them to buy.This phenomenon is a new business model that has the potential to be developed.Based on this phenomenon, it is necessary to design an application that can accommodate the phenomenon of Jastip.This application will design as a mobile application using Spark based Big Data technology.StealDeal is an online service application through a mobile application that provides discount product recommendations on websites that exist in Japan.In this application object design service only issues a test object design using a large data processing method in the system architecture design.Focus point of this design is the architectural design.
An Extensible Framework for Interactive Real-Time Visualizations of Large-Scale Heterogeneous Multimedia Information from Online Sources

This work presents the user-centered design and development of a generic and extensible visualization framework that can be re-used in various scenarios in order to communicate large–scale heterogeneous multimedia information obtained from social media and Web sources, through user-friendly interactive visualizations in real-time. Using the particular framework as a basis, two Web-based dashboards demonstrating the visual analytics components of our framework have been developed. Additionally, three indicative use case scenarios where these dashboards can be employed are described. Finally, preliminary user feedback and improvements are discussed, and directions for further development are proposed on the basis of the findings.
Hybrid Elephant Herding Optimization Approach for Cloud Computing Load Scheduling

Cloud computing is rather important distributing computing paradigm and in general refers to the common pool of configurable resources that is accessed on-demand. Resources are dynamically scalable and metered with the basic aim to provide reliable and quality services to the end-users. Load scheduling has a great impact on the overall performance of the cloud system, and at the same time it is one of the most challenging problems in this domain. In this paper, we propose implementation of the hybridized elephant herding optimization applied to load scheduling problem in cloud computing. The algorithm is using CloudSim framework, and comparison with different metaheuristics, adapted and tested under same experimental conditions, for this type of problem was performed. Moreover, we compared proposed hybridized elephant herding optimization with its original version in order to evaluate its improvements in performance over the original version. Obtained empirical results prove the robustness and quality of approach that we propose in this paper.
Uncorrected Least-Squares Temporal Difference with Lambda-Return

Temporal difference, TD(λ), learning is a foundation of reinforcement learning and also of interest in its own right for the tasks of prediction. Recently, true online TD(λ) has been shown to closely approximate the “forward view” at every step, while conventional TD(λ) does this only at the end of an episode. We re-examine least-squares temporal difference, LSTD(λ), which has been derived from conventional TD(λ). We design Uncorrected LSTD(λ) in such a way that, when λ = 1, Uncorrected LSTD(1) is equivalent to the least-squares method for the linear regression of Monte Carlo (MC) return at every step, while conventional LSTD(1) has this equivalence only at the end of an episode, since the MC return is corrected to be unbiased. We prove that Uncorrected LSTD(λ) can have smaller variance than conventional LSTD(λ), and this allows Uncorrected LSTD(λ) to sometimes outperform conventional LSTD(λ) in practice. When λ = 0, however, Uncorrected LSTD(0) is not equivalent to LSTD. We thus also propose Mixed LSTD(λ), which % mixes the two LSTD(λ)s in a way that it matches conventional LSTD(λ) at λ = 0 and Uncorrected LSTD(λ) at λ = 1. In numerical experiments, we study how the three LSTD(λ)s behave under limited training data.
Genetic Algorithm and Software Tools for Solving Optimization Problems in Intelligent Robotics

This paper concentrates on application of genetic algorithm in area of intelligent robotics. It raises the following issues: what optimization problems are faced in robotics, how they can be solved and how genetic algorithm can be useful in this area. The first section explains the role, kinds and examples of optimization problems in field of robotics and what solutions they can have. The second section of the paper covers the basic concepts of genetic algorithm, the steps it performs, and its possibilities. The third section contains an overview and a comparison of existing software implementations of genetic algorithm. This section also presents the system that we have developed for solving optimization problems with genetic algorithm and describes its main features and capabilities, gives a list of configuration parameters that user is allowed to change, and demonstrates its graphical interface for manipulating different types of objects that are managed by genetic algorithm.
Perancangan Sistem Restorasi Citra Dengan Metode Image Inpainting

Image Inpainting method is a technique of modifying images without being detected. The purpose of this application is starting from the restoration of damaged paintings and photography to removing or replacing certain objects. Image inpainting is one method of image restoration for confronting images that are slightly damaged such as scratched or streaked where filling the area will be restored based on information around the area so that the restoration is carried out completely in that area. Image restoration is often used in improving image quality where in this image restoration focuses on repairing damaged images, either during the digitization process or due to intentional or accidental processes. Keywords: Image Restoration, Inpainting Method, design
Represented Value Function Approach for Large Scale Multi Agent Reinforcement Learning

In this paper, we consider the problem of large scale multi agent reinforcement learning. Firstly, we studied the representation problem of the pairwise value function to reduce the complexity of the interactions among agents. Secondly, we adopt a l2-norm trick to ensure the trivial term of the approximated value function is bounded. Thirdly, experimental results on battle game demonstrate the effectiveness of the proposed approach.
Upaya Meningkatkan Kemampuan Membaca Permulaan Kelas 1 SD/MI dengan Metode Iqro di Madrasah Ibtidaiyah Al Hikmah Purwodadi Belitang Mulya OKU Timur

One of the goals is to provide early reading learning for elementary / MI children in the lower classes, namely classes 1, 2 and 3. The learning process especially reads at MI Al-Hikmah Purwodadi, who still uses the manual method by spelling with letters that students already know making students a little confused because they don't really understand the letters of the alphabet. Most of the students of Al-Hikmah Purwodadi were mostly recited at the TPA so that the students understood the hijaiyah letters more than the letters of the alphabet. Many students face difficulties in reading the beginning because of the background of students who are not from kindergarten graduates. As a solution to provide convenience for students who read the beginning and for MI Al-Hikmah Purwodadi teachers to simplify the learning process by using motivational and interesting methods and media to learn to read the beginning. In this service the method used is the iqra method. The results and benefits of service are increasing reading interest in MI Al Hikmah Purwodadi students, increasing knowledge and understanding of 1st grade students of MI Al-Hikmah Purwodadi in reading, increasing reading skills in class 1 MI Al-Hikmah Purwodadi.&#x0D; &#x0D; Keywords: Reading Beginning, Iqra Method
A GUI-driven prototype for synthesizing self-adaptation decision

The ability to ensure an optimal decision is significant for self-adaptive systems especially when dealing with uncertainty. For this reason, a synthesis-driven approach can be used to capture and synthesize a decision that aims to satisfy the multi-objective properties. Assessing the quality of the synthesis-driven approach is challenging, since it involves a set of activities from modeling, simulating, and analyzing the outcomes. This paper presents the design and implementation of a graphical user interface (GUI)-based prototype for assessing synthesis outcome and performance of an adaptation decision. The prototype is designed and developed based on the component-based development approach that is able to integrate the existing and related libraries from PRISM-games model checker for the synthesis engine, JFreeChart libraries for the chart presentation, and Java Universal Network/Graph Framework libraries for the graph visualization. This paper also presents the implementation of the proposed prototype based on the cloud application deployment scenario to illustrate its applicability. This work contributes to provide a fundamental work towards automated synthesis for self-adaptive systems.
Fast Global Motion Estimation on Android-based Software-defined Satellite

Recently, although advanced satellite can collect massive image data, the efficiency of information extraction is still lacking due to low-quality and redundancy of data, and limited transmission bandwidth worsens this situation. As the result, researchers start to focus on software-defined satellite. Through directly deploying image processing applications on a space-based computing platform, satellite's capabilities can be flexibly changed, expanded or enhanced. Under such a trend, this paper proposes a global motion estimation system which attempts to reduce data redundancy in satellite videos. Our work consists of two stages: first, adaptively feature matching and optical flow are combined to estimate global motion. Following this, we give the transform formula between homography matrices in different resolution images, thus algorithm can be faster executed at a smaller search space. The proposed system runs on the Android platform, which is easy to be programmed, ported and updated. It is validated on the newest software-defined satellite TianZhi-1, and shows outstanding results under real experimental environment.
THEATRALIZATION AS A PEDAGOGICAL TECHNIQUE OF FOREIGN LANGUAGES TEACHING

The article suggests examining efficiency of use of staging as a pedagogical technique in the course of foreign language studies, which has been used at the Business Foreign Languages and Translation Department of the National Technical University "Kharkiv Polytechnic Institute". The findings of our research are based on the analysis of experience of the teaching staff and students. The article shows that theatrical activity of the students of the specialty "Translation" is a mandatory element of the educational process. The focus is given to description of formation of partnerships between teachers and students. The Theatre of English Miniatures is described as an innovative pedagogical method. The authors emphasize that the Theatre of English Miniatures is an efficient technique for modelling the foreign language environment. It is concluded that this form of extracurricular activity makes it possible to successfully develop creative abilities, imagination, activity and independence. Staging and dramatization contribute to development of thinking, development of methods of joint creativity and intellectual tension, involve experiments, a flexible and harmonious conjunction of the individual, group and team activities, independent and focused on teaching. Staging is described as an innovative approach to studying as one of the most democratic types of pedagogy and art, which enables solving plenty of current problems of modern pedagogy and psychology related to: artistic training and education; formation of aesthetic taste; moral education; development of communicative qualities of the individual; training of the will, development of memory, imagination, initiative, fancy, language (monologue and dialogue); creating a positive emotional state; stress relief; solving conflicting situations through the game. The Theatre of English Miniatures is considered as one of the potential strategies for overcoming communicative difficulties in the course of the foreign language learning. Dramatization while learning the foreign language promotes creation of a situation of communication in the foreign language that is close to the real life circumstances and pushes students to solving the problems that arise within the bounds of such situation.
The Application of Gaze Heat Maps in Impression Evaluation

Eye trackers have gradually been applied in research including in the Kansei Engineering field. Furthermore the semantic differential (SD) method can obtain users’ Kansei from different aspects through the semantics of different words. As for facade, because it contains too many components, the components’ effect on Kansei is difficult to analyze using only evaluation scores. In this paper, an eye tracker was utilized in the facade evaluation process to analyze whether evaluation words would have an effect on gaze. Subjects were divided into four groups, three of which were given different evaluation words, and the fourth group was not given any evaluation word. The differences in heat maps were quantified and compared. While using evaluation words in the Kansei evaluation experience, the heat maps were more similar than those without using any evaluation word, indicating that the logic of the evaluation task, the Kansei evaluation words, and individual preference all had an effect on gaze position.
Evaluation of Half Gaussian Filter Rotation for Edge Detection

In image processing, contours can be extracted by linear convolution of the image with first-order derivative filters. The oriented half Gaussian filters are directed in all desired directions to analyze the images. Thus, they are useful for detecting contours or extracting precise orientations. The process of filter orientation requires the application of a rotation technique in a two-dimensional discrete domain of different scientific strategies: interpolation (which can modify image information) or discrete geometry (without modification of the image values). In this paper, different methods of discrete rotating the half Gaussian filter are compared and evaluated to detect contours in synthetic and real images. Results are qualitatively and quantitatively compared, validating which rotation technique is most beneficial for edge detection.