Reviewerly/exHarmony huggingface dataset:
Continuous-Time Systems for Solving 0-1 Integer Linear Programming Feasibility Problems

The 0-1 integer linear programming feasibility problem is an important NP-complete problem. This paper proposes a continuous-time dynamical system for solving that problem without getting trapped in non-solution local minima. First, the problem is transformed to an easier form in linear time. Then, we propose an "impulse algorithm" to escape from local traps and show its performance is better than randomization for escaping traps. Second, we present the time-to-solution distribution of the impulse algorithm and compare it with exhaustive search to see its advantages. Third, we show that the fractional size of the basin of attraction of the global minimum is significantly larger than $2^{-N}$, the corresponding discrete probability for exhaustive search. Finally, we conduct a case study to show that the location of the basin is independent of different dimensions. These findings reveal a better way to solve the 0-1 integer linear programming feasibility problem continuously and show that its cost could be less than discrete methods in average cases.
A New Watermarking Method Based on Analytical Clifford Fourier Mellin Transform

Here, we intend to introduce a new Fourier Transform. The well-known Analytical Fourier Mellin Transform (AFMT) will be defined on Clifford Algebra in order to process colored images. The proposed Fourier Transform is called Clifford Analytical Fourier Mellin Transform (CAFMT). Its magnitude, same as AFMT modulus, is invariant against planar similarities, not only on gray level images but also on colored images. Using ACFMT magnitude, we propose a robust watermarking technique in the frequency domain.
Analysis of Relationship between Aerobic Physical Activity and Life Satisfaction of Short Stature

This study was conducted to grasp the relationship between the practice rate of physical activity, the amount of aerobic physical activity and life satisfaction of short stature, and analyzed global physical activity questionnaire(GPAQ) and life satisfaction for 24 adult disabled people with short stature, a rare intractable disease. The results are as follows: METmin/week of men was 1512.50±1055.81 and that of women was 1890.00±2111.93 and the practice rate of men
THE ROLE OF CAREER ENRICHMENT IN ACHIEVING ORGANIZATIONAL LEARNING FIELD STUDY IN A SAMPLE OF INDUSTRIAL COMPANIES AT DHOFAR GOVERNORATE

This quantitative study aims to discuss the role of functional enrichment in achieving organizational learning in a sample of human resources staff working in four industrial companies in Dhofar Governorate.The problem lies in the information collected by the researcher; there is a gap between the functional enrichment and organizational learning variables in these companies: Salalah Pasta Company, Salalah Mills Company, Oman Oils Company and Raysut Cement Company.The researcher used the analytical descriptive method, which is based on the study of the phenomenon as it is, and expressed in quantity and quality.The study population consists of (600) employees of these industrial companies.A random sample of (100) employees was selected.The researcher designed a questionnaire of (40) paragraphs; (19) paragraph to measure the enrichment of functional and (21) paragraph to measure organizational learning.The study found the following results: There is a relationship of positive correlation with statistical significance at the level of (0.01) between the importance of tasks and organizational learning.A statistically significant relationship of correlation was found at the level of statistical significance (0.01) between independence of tasks and organizational learning.One of the recommendations was to give the employee an opportunity to participate in decisions related to the functions in which he participated in order to increase the level of creativity of the employee in the performance of his work.
Peningkatkan Hasil Belajar Siswa pada Mata Pelajaran IPS dengan Menggunakan Metode Cooperative Integrated Reading and Composition (CIRC) di Kelas III MI NW Taman Pagesangan Mataram

The aim of this study was to know the improvement of students learning outcomes in Social Studies subject using Cooperative Integrated Reading and Composition (CIRC) method in Class III of MI NW Taman Pagesangan Mataram. The research method used was Classroom Action Research. This research was carried out in MI NW Taman Pagesangan and used 23 students as subjects of the research. Instruments of data collection used observation sheet, test, and documentation. Data analysis technique used descriptive qualitative and quantitative analysis technique by using the completeness test formula. The result of this study indicated that the application of Cooperative Integrated Reading and Composition method could improve Social Studies learning outcomes in class III of MI NW Taman Pagesangan. This was in accordance with the results of tests that had showed improvement on students learning outcomes from the first cycle test to the second cycle test. The students’ average test score of the first cycle was 80 and the students’ average test score of the second cycle test increased to 85. The completeness Classical score also experienced an increase from cycle I to cycle II, from 82.60% up to 91.30%.
TEACHING ENGLISH TO ADULT STUDENTS AT MANAGEMENT RESEARCH AND EDUCATION (LP2M) EL-RAHMA EDUCATION CENTER PALEMBANG

The Objectives of the study are to describe the system used in Teaching English as a foreign language at LP2M El-Rahma Education Center Palembang, whether or not it is relevant with the principles of the procedure for the development of instructional system and to find out whether the system is suitable to the adult student’s needs or not. A descriptive method was used in this research, becauase the writer described the data as they are. The subject of the study is the population of the second semester students of LP2M El-Rahma Education Center Palembang in the academic year 2006/2007, there are 180 students from the population 40 students are taken as the sample randomly. The data are obtained through documentation, interview to the English instructors who taught at LP2M El-Rahma Education Center Palembang . Observation and Questionaire given to the students. The data are analyzed by means of percentage . Based on the results of the data analysis, the writer found that the system used in TEFL at LP2M El- Rahma Education Center Palembang was relevannt to the system of teaching and the system applied was not suitable to the students’ needs. they needed to learn English computer science in the term of writing grammatically, speaking with public either science textbooks espeacially which are written in English.
Uncertainty-Aware Data Aggregation for Deep Imitation Learning

Estimating statistical uncertainties allows autonomous agents to communicate their confidence during task execution and is important for applications in safety-critical domains such as autonomous driving. In this work, we present the uncertainty-aware imitation learning (UAIL) algorithm for improving end-to-end control systems via data aggregation. UAIL applies Monte Carlo Dropout to estimate uncertainty in the control output of end-to-end systems, using states where it is uncertain to selectively acquire new training data. In contrast to prior data aggregation algorithms that force human experts to visit sub-optimal states at random, UAIL can anticipate its own mistakes and switch control to the expert in order to prevent visiting a series of sub-optimal states. Our experimental results from simulated driving tasks demonstrate that our proposed uncertainty estimation method can be leveraged to reliably predict infractions. Our analysis shows that UAIL outperforms existing data aggregation algorithms on a series of benchmark tasks.
SITProMP: A simplistic approach towards managing IT projects

Simplistic IT Project Management Practice (SITProMP) is a generic framework towards IT Project Management or ITPM. ITPM is somewhat different than Project Management in other fields. There exists several principles, methodologies and approaches for managing projects. SITProMP considers existing approaches towards PM and presents a simplistic principle-based framework for ITPM. SITProMP offers agility and proposes to manage IT projects through any suitable methodology, tools or approaches towards PM that may fit in. SITProMP complements all existing approaches and principles for ITPM; and can encapsulate all existing tools and technologies for ITPM. Though primary focus of SITProMP is on IT projects, it can be adapted to projects in any other fields, and thus customizable. The foundation for SITProMP is the existing knowledge bases in PM.
Implicit Filter Sparsification In Convolutional Neural Networks

We show implicit filter level sparsity manifests in convolutional neural networks (CNNs) which employ Batch Normalization and ReLU activation, and are trained with adaptive gradient descent techniques and L2 regularization or weight decay. Through an extensive empirical study (Mehta et al., 2019) we hypothesize the mechanism behind the sparsification process, and find surprising links to certain filter sparsification heuristics proposed in literature. Emergence of, and the subsequent pruning of selective features is observed to be one of the contributing mechanisms, leading to feature sparsity at par or better than certain explicit sparsification / pruning approaches. In this workshop article we summarize our findings, and point out corollaries of selective-featurepenalization which could also be employed as heuristics for filter pruning
Analysing the tor web with high performance graph algorithms

The exploration and analysis of Web graphs has flourished in the recent past, producing a large number of relevant and interesting research results. However, the unique characteristics of the Tor network demand for specific algorithms to explore and analyze it. Tor is an anonymity network that allows offering and accessing various Internet resources while guaranteeing a high degree of provider and user anonymity. So far the attention of the research community has focused on assessing the security of the Tor infrastructure. Most research work on the Tor network aimed at discovering protocol vulnerabilities to de-anonymize users and services, while little or no information is available about the topology of the Tor Web graph or the relationship between pages' content and topological structure. With our work we aim at addressing such lack of information. We describe the topology of the Tor Web graph measuring both global and local properties by means of well-known metrics that require due to the size of the network, high performance algorithms. We consider three different snapshots obtained by extensively crawling Tor three times over a 5 months time frame. Finally we present a correlation analysis of pages' semantics and topology, discussing novel insights about the Tor Web organization and its content. Our findings show that the Tor graph presents some of the characteristics of social and surface web graphs, along with a few unique peculiarities.
SPLINE-Net: Sparse Photometric Stereo through Lighting Interpolation and Normal Estimation Networks

This paper solves the Sparse Photometric stereo through Lighting Interpolation and Normal Estimation using a generative Network (SPLINE-Net). SPLINE-Net contains a lighting interpolation network to generate dense lighting observations given a sparse set of lights as inputs followed by a normal estimation network to estimate surface normals. Both networks are jointly constrained by the proposed symmetric and asymmetric loss functions to enforce isotropic constrain and perform outlier rejection of global illumination effects. SPLINE-Net is verified to outperform existing methods for photometric stereo of general BRDFs by using only ten images of different lights instead of using nearly one hundred images.
The Effectiveness of Group Work Technique in Improving the Students’ Speaking Skill a Survey at Second Semester Students of English in Academic Years 2017-2018

This study is intended to find out the effectiveness of group work technique in improving the students speaking : a survey at second semester student of English department of FPBS university of Mataram in academic years 20017-200, there are 48 students taken and are divided in two groups namely : experimental group and control group. D class was treated as experimental group and was taught by using group-work technique and E class was treated as control group and were taught by using individual work technique. The data was collected base on the result of pre-test and post-test, which was given after the student of two groups were given treatment, after gaining the data from the research, the writer process the score of the two group, the total of the mean score from the experimental group is 58 and the control group is 50,5. After the computation of the mean score we continues to calculate the standard deviation of the two groups and the standard deviation score from the experimental group is 198,96 and from the control group si 123,34 and the analyzed the significance of the mean score and the deviation score used a t-test formula and the value of the t-test is 2,953 where the writer checking on the t-table at 5 and 1 level of significance. After the statistical analysis of the date obtained, finally, the writer concludes that, that of use group work technique is effective in improving the student speaking skill.
Simultaneous Semi-supervised Segmentation of Category-Independent Objects from a Collection of Images

This work is about simultaneous segmentation of different foreground objects from a collection of images with heterogeneous contents. Our idea is to propagate the segmentation information between images in order to detect foreground objects in all these images simultaneously, under the hypothesis of using categorized or uncategorized images, rather than resorting to image co-segmentation that forces the use of similar categorized images. In fact, given an input image, the objective is to integrate seamlessly other images in the general foreground model, in order to benefit the segmentation of the foreground objects in this image. Indeed, the proposed method aggregates general information, on foregrounds as well as on backgrounds, from a collection of images. To this end, the method is based on an energy minimization function. The linear dependence of the foreground histograms is firstly estimated to optimize the proposed energy function. Then, an iterative optimization of each image permits to remarkably optimize the final segmentation result for all images composing the input collection. Extensive experiments demonstrate that the suggested method allows full-object segmentation of the foreground from a collection of images composed of different classes of objects. Indeed, the validation of the accuracy on four challenging datasets (iCoseg, Oxford Flowers, Caltech101 and Berkeley) shows that the proposed method compares favorably with the state-of-the-art of foreground object segmentation from a collection of images. Besides, it has the challenging ability to deal accurately with uncategorized objects.
Automatic construction of lexical typological questionnaires

Questionnaires constitute a crucial tool in linguistic typology and language description. By nature, a Questionnaire is both an instrument and a result of typological work: its purpose is to help the study of a particular phenomenon cross-linguistically or in a particular language, but the creation of a Questionnaire is in turn based on the analysis of cross-linguistic data. We attempt to alleviate linguists’ work by constructing lexical Questionnaires automatically prior to any manual analysis. A convenient Questionnaire format for revealing fine-grained semantic distinctions includes pairings of words with diagnostic contexts that trigger different lexicalizations across languages. Our method to construct this type of a Questionnaire relies on distributional vector representations of words and phrases which serve as input to a clustering algorithm. As an output, our system produces a compact prototype Questionnaire for cross-linguistic exploration of contextual equivalents of lexical items, with groups of three homogeneous contexts illustrating each usage. We provide examples of automatically generated Questionnaires based on 100 frequent adjectives of Russian, including veselyj ‘funny’, ploxoj ‘bad’, dobryj ‘kind’, bystryj ‘quick’, ogromnyj ‘huge’, krasnyj ‘red’, byvsij ‘former’ etc. Quantitative and qualitative evaluation of the Questionnaires confirms the viability of our method.
Some Directions of Building Petrophysical Generalizationsin a Modern Interior

Summary Petrophysics and log interpretation are considered from the standpoint of knowledge engineering.Separate the problems that are significant with this approach. As an illustration, an example ofbuilding FZI using cluster regression is given.
Lexical reduction in German SMS communication

This article intends to tackle the problem of lexical reduction realisation in German SMS communication.In line with the recent events, whereby the transfer of information seems to take centre stage in society, there has been an increased usage of short forms and short texts commonly referred to as SMS messages.SMS message is a modern electronic-written form of speech interaction.In the research carried out 10 % of the researched texts contained lexical reduction.This includes graphical and lexical abbreviations, acronyms, letter-digital shortenings and syncope.The findings also highlighted that there was substantive usage of graphically shortened meaningful units accepted in literary German.Moreover, the studies found out that a peculiar feature of abbreviation in German texts of SMS messages is shortening of separate words, as well as complete word combinations, and sentences that are actualized in conversational speech.Another feature that came to the limelight is letter-digital shortenings whereby a digit is used in place of the word or word part parts of the word are laterally represented in private German SMS communication.As a result of the informatization of society syncope, namely syncope and apocope, have become productive means of word-formation.Thus, shortening of proper names, names of organizations, establishments, countries and cities have become part and parcel of German SMS communication.Aphaeresis, however, is rarely encountered in German SMS communication.
Treatment of sewage waste water using an agricultural waste corn cobs

Corncobs are agricultural wastes obtain in maize cultivation. It is less utilized part of the maize plant. Due to rigidity and their porous structure they can be used as an absorbent. Corncobs are available in large quantity, it may be burnt or given as food for animals. But if corncobs are burnt it causes air pollution which we already saw what happen in Delhi (Capital of India) and if corncobs are given as food to animals, they also not take it as it contains hemicellulose content in it and acts as an obstructing agent in the elementary canal of the animals. So, it is a good idea to use corncobs agricultural waste to treat wastewater. Sometimes they are thrown away but naturally, they take too much time to biodegrade. In this treatment no need of chemicals and electricity. The wastewater can be treated naturally using corn cobs as an absorbent. As corn cobs are cheap, this is more economical treatment. It is also easy and simple to operate. So, it can be adopted in villages also.
Parallelized Synchronous Multi-agent Deep Reinforcement Learning with Experience Replay Memory

In the field of deep reinforcement learning, reusing training data from different time-steps by introducing the Experience Replay Memory (ERM) can significantly reduce non-stationarity and decorrelate updates. However, in Multi-Agent Deep Reinforcement Learning (MA-DRL), in particular, the independent Q-Learning problems, it may introduce obsolete experiences to the training process, which inevitalbiy leads that the policy network takes more training times to converge. In this paper, we propose an approach which can exploit parallelization in resource-rich environments (e.g., cloud) to generate decorrelated training data instead of purely relying on ERM in MA-DRL. We enhance the synchronous method, a parallel method originally proposed for single-agent DRL, to the multi-agent environment. And to avoid the drawback of synchronous method, we combine it with ERM together and apply the improved method to lenient deep reinforcement learning. As a result, our algorithm, the lenient ERM-helped synchronous n-step deep Q-network (LESnDQN), takes the advantage of both ERM and parallelization. The LESnDQN algorithm has been tested in an extended variation of the coordinated multi-agent object transportation problem. The results show that LESnDQN takes less training episodes and computation time to converge than the state-of-the-art algorithm with similar parameter settings.
Generation and Detection of Down-converted Photon Pairs at 2.080 µm

We report the generation and coincidence-to-accidental ratio characterization of a pulsed spontaneous parametric down-conversion photon pair source at 2.080 µm, as a basis for free-space quantum communication in an atmospheric window with low solar background.
Hyper Spectral Prevalent News Customization System With Sentimental Analysis

Broad communications sources, specifically the news media, have traditionally informed us of daily events.News customization play an important role in news media.Extracting knowledge of certain incident from different online portals into a single online portal.The news media introduces expertly verified events or occasions ,while web based life displays the interests of the group of onlookers in these regions.Users can see the multiple news website news in a single portal.The online news media shows the verified news only.Repetition of news is avoided.Users can share the valuable information from online news media to online social media.Online user generated reviews become an inevitable part of decision making process.Natural language processing technologies is used for online reviews.Analyzing the overall sentiment expressed in a whole piece of text or in the form of like or dislike.
Integration of Geophysical Methods and Space Research in the Search for Deposits in the Miass District

Summary Research problem is assessment of a possibility of application of the analysis of satellite images for increase in effectiveness of prospecting geological works. Studying of geological information showed that the explored territory is located near gold fields. Carrying out geological mapping confirmed availability of rocks, the characteristic of places in which there are good chances to find gold ores. Presumably gold mineralization can be carried to type gold sulphidic quartz. Geophysical works included magnetic survey, GPR data acquisition, geoelectric survey, radiometrics. Data of field geophysical works were processed by means of the specialized software. Geophysical anomalies were allocated by geostatistical methods. The analysis of satellite images was carried out in the QGIS software. Selection of geological lineaments and specification of structural and geological borders was one of results of the analysis. The complex analysis of images geological objects and geophysical anomalies was carried out on the basis of the regression analysis and allowed to estimate the nature and prospects of geophysical anomalies.