Reviewerly/exHarmony huggingface dataset:
Underwater image restoration based on improved dark channel prior

Underwater image restoration has attracted the attention of many experts due to the demand of underwater rescue, archaeology, resource exploration et al. Water scattering and absorption hinder the linear propagation of light in water, resulting the image degradation. The degraded image visibility can be improved by the image restoration method. Many image restoration methods have been proposed by the experts for underwater images restoration. The dark channel prior method is a classical method for image dehazing, and it also can be used for underwater image restoration. However, the underwater image restored by this method still has the color distortion problem due to the water absorption, and the less visibility due to the inaccuracy transmission estimation. To overcome this problems, we propose an image restoration method based on improved dark channel prior to repair the image degraded by underwater scattering media. The quadtree decomposition is used to find the high intensity region for waterlight estimation. The transmission is estimated by the improved dark channel prior. The underwater degraded image can be restored by our proposed method without color distortion. This method will be helpful to the underwater rescue and resource exploration et al.
THE USE OF KWL (KNOW, WANT TO KNOW, LEARNED) STRATEGY TO IMPROVE STUDENTS’ READING COMPREHENSION ON ACADEMIC READING

The aim of this research is to discover a significant difference of reading comprehension between the students who are taught by using KWL Strategy and students who are taught by using the DRTA (Direct, Reading, Thinking, Action) method in the first semester of English Education Department at UIN Alauddin. This research was conducted at State Islamic University of Makassar (UIN Alauddin). In the research, the population was the students in the first semester. The number of population were 97 students. Technically, 20 students were grabbed in experimental class and 20 students were grabbed in controlled class. So, total sample was 40 students. Quasi-experimental method was applied in this research with two group pre-test and post-test design. The instrument used to collect data was academic vocabulary test. The findings showed that the first semester students of UIN Alauddin had very poor classification score on pre-test with the mean score 20,5. After giving treatment, the students achieved good improvement, they got fairly good classification score with the mean score 67,5. It was proved by the result with degree of freedom (df)= 38 indicated that the t-test value of the students’ academic vocabulary (4,46) was higher than t -table value (2,024). The implication revealed that there was a significant improvement in the students’ reading comprehension on academic reading by giving KWL Strategy.
USEFUL PYTHON LIBRARIES FOR CREATING IDS SOFTWARE

Abstract: This paper represents all possibilities of Python programming language for detecting intrusion attacks whose purpose is to penetrate secured network or secured computer. Reading this paper we are going to see Python libraries that we can use for monitoring network traffic and eventually use them for making IDS software (Intrusion detection system). After preview of libraries with those capabilities we are going to represent a simple example of IDS software solution so readers can see how mentioned libraries can be used for that kind of software.
Pengaruh Model Blended Learning Terhadap Prestasi Mahasiswa Ditinjau dari Locus of Control

The aim of this study was to analyze the effect of the blended learning model on student achievement in the Faculty of Economics and Business, Jenderal Soedirman University in terms of locus of control using web media. The approach used in this research is quantitative research. Data collection method is done through pretest and posttest to find out student achievement, while for locus of control ability is measured by questionnaire. The collected data is then tested with normality, homogeneity, and anova tests as well as the t test for pretest and posttest, while for the activeness data is tested by regression test and independent sample t-test. The result of analysis shows data is normal and homogent with significantion estimate of 0,05 that 0, 510 for experiment class and 0,108 for control class. To Anova test for estimate F 2.515 and significantion estimate of 0,001, and to Independent Sample Test the estimate for Sig .(2-taile d) that 0,01 &lt; 0,05 , then can be conclusion that there is different between student achievement and locus of control ability among experiment class team with control class team. Keywords : Blended Learning Model; Locus of Control; Learning Achievement. ABSTRAK Penelitian ini bertujuan untuk menganalisis pengaruh model blended learning terhadap prestasi belajar mahasiswa ditinjau dari locus of control di Fakultas Ekonomi Dan Bisnis, Universitas Jenderal Soedirman dengan media web. Penelitian ini menggunakan penelitian kuantitatif, untuk menggumpulkan data untuk prestasi belajar menggunakan pretest dan posttes t, sedangkan untuk kemampuan locus of control menggunakan kuesioner. Data yang diperoleh lalu di ujikan dengan uji normalitas, homogenitas , dan anova serta uji t untuk pretest dan posttest , sedangkan untuk data keaktifan di uji dengan uji regresi dan uji independent sampel t-test . Hasil analisis menunjukkan bahwa data berdistribusi normal dan homogen dengan nilai signifikansi sebesar 0,05 yaitu 0,510 untuk kelas eksperimen dan 0,108 untuk kelas kontrol. Untuk uji anova didapatkan nilai nilai F 2.515 dan nilai signifikansi sebesar 0,001, dan untuk nilai Uji Independent Sample T-Test diperoleh nilai Sig.(2-tailed ) sebesar 0,01&lt;0,05, maka sesuai dasar pengambilan keputusan dalam Uji Independent Sampel T-Tes t, maka dapat disimpulkan bahwa terdapat perbedaan antara prestasi belajar dan kemampuan locus of contol antara kelompok kelas eksperimen dengan kelompok kelas kontrol. Kata kunci : Model Blended Learning; Locus of Control; Prestasi Belajar.
Introduction to Special Issue on Source Code Analysis and Manipulation

In this paper, we study the market-oriented online bi-objective service scheduling problem for pleasingly parallel jobs with variable resources in cloud environments, from the perspective of SaaS (Software-as-as-Service) providers who provide job-execution services. The main process of scheduling SaaS services in clouds is: a SaaS provider purchases cloud instances from IaaS providers to schedule end users’ jobs and charges users accordingly. This problem has several particular features, such as the job-oriented end users, the pleasingly parallel jobs with soft deadline constraints, the online settings, and the variable numbers of resources. For maximizing both the revenue and the user satisfaction rate, we design an online algorithm for SaaS providers to optimally purchase IaaS instances and schedule pleasingly parallel jobs. The proposed algorithm can achieve competitive objectives in polynomial run-time. The theoretical analysis and simulations based on real-world Google job traces as well as synthetic datasets validate the effectiveness and efficiency of our algorithm.
Russian Book and Press in Creating the Emigrant Community in the 20th Century

The article discusses the history of book publishing in the Russian emigration in the 20th century, which arose in foreign countries after 1917. Books and periodicals in exile had their own development path, unlike the Soviet one. The article gives a brief description of book publishing in Russian, examines the activities of libraries and publishing centers in preserving the cultural heritage of pre-revolutionary Russia. Particular attention is paid to the organizational function of the book, which was embodied in cultural and educational events, book projects and publishing series aimed at reproducing among immigrants cultural images and literary works that demonstrate the idea of Russian culture and homeland to the younger generation, which most of these were aimed at projects. The paper analyzes genre-thematic areas in book publishing, which are mainly reflected in memoir prose and press of political organizations.
Monitoring of the Development Potential of Educational Services in General Secondary Education Institutions

The article considers the results of scientific research on the problem of monitoring the quality of educational services, as well as analyzes and summarizes the important parameters of such monitoring. The activities of educational institution have many components and aspects. Proposed to develop integrated indicators of the quality of educational services, which would combine many factors of educational activities and reflect the central goal of the educational process − the development of the child's personality. The author writes that comprehensive personal development is the main goal of educational activities, so such an integral criteria for the quality of educational services can be the development potential of the educational process in educational institutions. The article considers the system of students’ skills, abilities, personal and mental qualities, which provide an opportunity to successfully acquire the necessary school knowledge and skills. They are considered as indicators and manifestations of effective developmental effect of the educational process on the student's personality. They characterize the development potential of educational services. Described the following types of universal learning activities: cognitive (ability to learn, logical thinking, etc.), communicative (social competence, ability to communicate, etc.), regulatory (goal setting, planning, etc.), personal (provide value-semantic and moral-ethical orientations of students ). Criteria and levels for assessing the development potential of educational services were presented.
Analysis of the Harm of Electromagnetic Wave Pollution and its Protection Strategies

As we all know, in the photoelectric information age, electromagnetic wave is closely related to our life. Not only sunlight, wireless remote control, wireless communication, etc. can produce electromagnetic wave radiation, but also many home appliances used in our daily life also need to use electromagnetic wave. It can be said that the earth is covered with electromagnetic waves. But at present, the majority of people still lack the understanding of the harm of electromagnetic wave radiation. If the protection is improper, it may cause electromagnetic wave pollution and cause serious harm to the human body and even the environment. In this paper, the harm of electromagnetic wave is briefly described, and some protection strategies against electromagnetic pollution are put forward on this basis.
Data Visualisation Prototypes for Problem Definition in the Design of Accessible Transport Solutions

Public transport is a challenging environment for both passenger and operator. The operation of large networks carries expectation of timely delivery of passenger-oriented services. With numerous stakeholders such as government, private industry, and the general public the expectation around the primary concept of mobility within transport networks often differs. This chapter examines how data visualisation has been engaged to better understand an enduring mobility challenge of Australian metropolitan rail networks, the universally accepted accessibility issue widely known as ‘the gap’. With increasing global requirements for disability compliance and anti-discrimination within public transport, data visualisation is applied within a broader design project. Engaged at the problem-definition stage this data-driven approach provides investigators greater insight and visual transparency towards understanding the impact this issue has on mobility for all users of public transport.
3D LiDAR and Color Camera Data Fusion

3D LiDAR sensor and 2D color camera provide complementary information of a scene. It is essential to fuse both types of data to obtain a holistic representation of the real-world scene. In this paper, we present a method to fuse the data captured by rigidly mounted LiDAR and camera. We first cocalibrate the LiDAR and camera with a calibration target. We then establish 3D-2D correspondences and fuse the LiDAR and camera data through geometric transformations. Experimental results demonstrate that our method is able to fuse the 3D LiDAR point cloud with the 2D color image efficiently and accurately. Our method is also fast and can be used in autonomous driving applications.
Comparative Reflections on COVID-19 Responses: Drafting, Powers, and Interpretation

Abstract This article examines comparatively approaches in Hong Kong and English law on powers created by the use of subordinate legislations to combat the COVID-19 pandemic from the perspectives of legislative drafting and statutory interpretation. These powers, being wide and flexible in nature, pose a tension between two competing concerns. On the one hand, they enable law enforcement officers to be able to deal with the unique challenges posed by a public health crisis. On the other hand, they pose the potential to restrict fundamental human rights disproportionately. This article will proceed in three parts. First, the article will analyse the responsibilities of drafters in drafting subordinate legislations and the techniques therein; the discussion will be contextualized within a need for urgent public health responses to combat the pandemic. Second, the powers conferred upon law enforcement officers and restrictions on individual liberty under Hong Kong law and English law will be analysed. Third, approaches to interpreting the relevant legislations under the two jurisdictions will be examined. It will be argued that despite the need to confer wide and flexible powers to the executive to combat the pandemic, specificity of language and precision in articulating these powers remain of cardinal and overarching importance.
MEASURING STRATEGIES FOR KNOWLEDGE MANAGEMENT AND ORGANIZATIONAL PERFORMANCE IN LIBYAN TRANSPORTATION INDUSTRY: STRUCTURAL EQUATION MODELLING

The purpose of this research is to measure the strategies for knowledge management and organisational performance in Libya using an approach to structural equation modelling (SEM). The research method of this analysis is a quantitative method only, where the total sample size is assumed to be 453 using simple random sampling. The structural model for this analysis showed the relationships between the variables. The results show that the framework of knowledge management is significantly related to the strategy of knowledge management, while knowledge management practise is significantly related to the strategy of knowledge management. However, the framework of knowledge management was found not to be very positively linked to organisational performance. Unexpectedly, in terms of significantly related to organisational performance, knowledge management activity has also not been considered relevant. Knowledge management approach, on the other hand, is positively linked to organisational performance and to the reciprocal relationship between the system of knowledge management and the practise of knowledge management. By offering an empirically validated model that could be used to forecast organisational performance as a whole, this study has added to established knowledge.JEL: L10; L25; L91 Article visualizations:
Information and Innovative Technologies in Distance Learning in Higher Education Institutions of Ukraine

The article considers the possible development of information and innovative technologies for use in distance learning in higher educational institutions of Ukraine. The main advantages and disadvantages of distance learning in higher education institutions of Ukraine are identified. The main existing forms and technologies of distance learning and their characteristics are considered and analyzed. Based on the analysis and research, the application of levels of organization of the distance education process is proposed. in higher education institutions of Ukraine in the period of global constraints, as an example of a pandemic. Positive and negative qualities of distance education development in Ukraine are determined.
Image-Building of Public Library from Readers’ Perspective: A Case Study on the Northern Haidian Library

Organization image management is regarded as an effective way for libraries to rebuild their public images through their own endeavors and interactions with the public. However, the previous studies usually explore the issue from the perspective of library staff, yet seldom from the perspective of readers. This article examined reader’s needs for library service, and set up a model of readers’ hierarchy of needs. We also explored a method to build a positive image for libraries from the perspective of readers’ demands, and set up the model of Image-building for public libraries. We hoped to provide a new approach to learn readers’ needs for library, as well as a new sight on library image construction.
Insulator Orientation Detection Based on Deep Learning

In order to solve the problem of inaccurate location in insulator target detection, this paper proposes an insulator orientation recognition algorithm based on deep learning. By adding angle information to the axis alignment detection frame, it can effectively solve the problem that conventional deep learning algorithm can not accurately locate the target. First, the angular rotation parameters are introduced into the axially aligned rectangular detection frame to form a directional detection frame. Then the parameter offset is added as the fifth parameter to the loss function for iterative regression. At the same time, in order to improve the detection accuracy, Adam algorithm is used to replace Stochastic Gradient Descent (SGD) to optimize the loss function. Finally, the insulator directional detection model can be obtained. The experimental results show that the orientation detection frame with rotation angle can effectively locate the insulator target accurately.
Dhwani: Sound Generation from Google Drive Images Controlled with Hand Gestures

Dhwani is a project focusing on sound generation from a given image using the content or background of the picture. Audio production from images can have much utilization, especially in reliving the past moment or for exploring the places without even visiting them. With the use of waving hand gesture, the user can open an image and can listen to the sound generated from one photograph at a time. The use of waving hand gesture for accessing the next or previous image has been incorporated into the project for improvizing the user’s experience. There is a use of folder linked to Google Drive on which the processing has been performed. So, the user gets an advantage of directly using the images stored on the Google Cloud saving time and hustle to transfer the pictures. Using deep learning, object tracking and computer vision, Dhwani is providing the users with a prominent innovation that comes bundled with high-level user experience.
A supervised technique for drill-core mineral mapping using Hyperspectral data

&amp;lt;p&amp;gt;Drilling is a key task in exploration campaigns to characterize mineral deposits at depth. Drillcores&amp;lt;br&amp;gt;are first logged in the field by a geologist and with regards to, e.g., mineral assemblages,&amp;lt;br&amp;gt;alteration patterns, and structural features. The core-logging information is then used to&amp;lt;br&amp;gt;locate and target the important ore accumulations and select representative samples that are&amp;lt;br&amp;gt;further analyzed by laboratory measurements (e.g., Scanning Electron Microscopy (SEM), Xray&amp;lt;br&amp;gt;diffraction (XRD), X-ray Fluorescence (XRF)). However, core-logging is a laborious task and&amp;lt;br&amp;gt;subject to the expertise of the geologist.&amp;lt;br&amp;gt;Hyperspectral imaging is a non-invasive and non-destructive technique that is increasingly&amp;lt;br&amp;gt;being used to support the geologist in the analysis of drill-core samples. Nonetheless, the&amp;lt;br&amp;gt;benefit and impact of using hyperspectral data depend on the applied methods. With this in&amp;lt;br&amp;gt;mind, machine learning techniques, which have been applied in different research fields,&amp;lt;br&amp;gt;provide useful tools for an advance and more automatic analysis of the data. Lately, machine&amp;lt;br&amp;gt;learning frameworks are also being implemented for mapping minerals in drill-core&amp;lt;br&amp;gt;hyperspectral data.&amp;lt;br&amp;gt;In this context, this work follows an approach to map minerals on drill-core hyperspectral data&amp;lt;br&amp;gt;using supervised machine learning techniques, in which SEM data, integrated with the mineral&amp;lt;br&amp;gt;liberation analysis (MLA) software, are used in training a classifier. More specifically, the highresolution&amp;lt;br&amp;gt;mineralogical data obtained by SEM-MLA analysis is resampled and co-registered&amp;lt;br&amp;gt;to the hyperspectral data to generate a training set. Due to the large difference in spatial&amp;lt;br&amp;gt;resolution between the SEM-MLA and hyperspectral images, a pre-labeling strategy is&amp;lt;br&amp;gt;required to link these two images at the hyperspectral data spatial resolution. In this study,&amp;lt;br&amp;gt;we use the SEM-MLA image to compute the abundances of minerals for each hyperspectral&amp;lt;br&amp;gt;pixel in the corresponding SEM-MLA region. We then use the abundances as features in a&amp;lt;br&amp;gt;clustering procedure to generate the training labels. In the final step, the generated training&amp;lt;br&amp;gt;set is fed into a supervised classification technique for the mineral mapping over a large area&amp;lt;br&amp;gt;of a drill-core. The experiments are carried out on a visible to near-infrared (VNIR) and shortwave&amp;lt;br&amp;gt;infrared (SWIR) hyperspectral data set and based on preliminary tests the mineral&amp;lt;br&amp;gt;mapping task improves significantly.&amp;lt;/p&amp;gt;
A new venture to image encryption using combined chaotic system and integer wavelet transforms

In this digital era, securing multimedia information is receiving its due concern apart from securing textual data. Securing the image by utilising integer wavelet transform is the chief curiosity of the proposed work. This research work is envisioned to explore the use of reversible integer wavelet transforms (IWTs) for designing robust image encryption algorithm. The proposed exploration comforts to seal the gap in the space in between image encryption and the existing robust IWT. Ten different IWT namely Haar, 5/3, 2/6, 9/7-M, 2/10, 5/11-C, 5/11-A, 6/14, 13/7-T, 13/7-C are used for the analysis. Four keys utilised for image scrambling and image diffusion are generated with the help of the proposed combined chaotic system. Image scrambling is performed only on the approximation coefficients to get full image scrambling and bit XOR is used for image diffusion. This proposed method provides NPCR value as 99.6246%, UACI value as 33.5829, entropy value as 7.997 and very less correlation values. Simulation results prove that image encryption technique can be designed with various integer wavelet transforms.
Clause-level Analysis High-value Reviews based on Sentiment

Today, huge numbers of reviews are posted on the internet. Online shoppers often refer to reviews written about the products. A review has a star rating that represents what other people think about the product. However, the star rating is not always appropriate for evaluating the product. High-value reviews that affect the users' willingness to buy are independent of the number of stars in ratings. High-value reviews are those from which people find useful information those regarded as good reviews. As described in this paper, we investigated the relation between high-value reviews and the sentiment (positive/negative/neutral) of their clauses based on four hypotheses. We extract characteristics of high-value reviews based on our results. Furthermore, we propose a classification method that classifies clause level sentiment from reviews.