Reviewerly/exHarmony huggingface dataset:
The Business Logistics Security Research on Web Application

Abstract The rich functions of web applications have played an important role in the rapid development of the Internet. Different web applications have different functions. Compared with traditional XSS vulnerabilities, SQL injection vulnerabilities, and command execution vulnerabilities, the security issues involved in different server functions of Web applications vary widely, which leads to the absence of general solutions for specific security vulnerabilities in business logic process. After analyzing the security of the business logic process, it can be found that when the various security points of the business logic process are used by the attacker, and the behaviour of the attacker does not have any obvious difference from the normal user, which leads to the inability to achieve effective protection by directly using various types of scripts. Therefore, it is of practical significance to research a penetration detection idea of a logical vulnerability.
The Lita Guide to No- or Low-Cost Technology Tools for Libraries

"The Lita Guide to No- or Low-Cost Technology Tools for Libraries." Medical Reference Services Quarterly, 38(4), pp. 411–412
DCA: Diversified Co-Attention towards Informative Live Video Commenting

We focus on the task of Automatic Live Video Commenting (ALVC), which aims to generate real-time video comments with both video frames and other viewers' comments as inputs. A major challenge in this task is how to properly leverage the rich and diverse information carried by video and text. In this paper, we aim to collect diversified information from video and text for informative comment generation. To achieve this, we propose a Diversified Co-Attention (DCA) model for this task. Our model builds bidirectional interactions between video frames and surrounding comments from multiple perspectives via metric learning, to collect a diversified and informative context for comment generation. We also propose an effective parameter orthogonalization technique to avoid excessive overlap of information learned from different perspectives. Results show that our approach outperforms existing methods in the ALVC task, achieving new state-of-the-art results.
Identification of Rhetorical Roles of Sentences in Indian Legal Judgments

Automatically understanding the rhetorical roles of sentences in a legal case judgement is an important problem to solve, since it can help in several downstream tasks like summarization of legal judgments, legal search, and so on. The task is challenging since legal case documents are usually not well-structured, and these rhetorical roles may be subjective (as evident from variation of opinions between legal experts). In this paper, we address this task for judgments from the Supreme Court of India. We label sentences in 50 documents using multiple human annotators, and perform an extensive analysis of the human-assigned labels. We also attempt automatic identification of the rhetorical roles of sentences. While prior approaches towards this task used Conditional Random Fields over manually handcrafted features, we explore the use of deep neural models which do not require hand-crafting of features. Experiments show that neural models perform much better in this task than baseline methods which use handcrafted features.
LibGuides: Book Trailers Tips and Tools: Overview

This guide is meant to provide librarians with assistance on what apps, websites and computer programs are available to students who would like to create their own book trailers.
Integrative Methods in Teaching and Learning History in Malaysia

The objective of this study is to examine the effectiveness of Integrative Teaching Methods in teaching and learning History. Interviews and observation were implemented to review the student's perspective on integrative methods. The effectiveness of Integrative methods is reviewed from the perspective of students. The study found that students’ response was very positive. They are happy and keen to involve in activities organized through multiple sources and methods. In addition, respondents show appreciation on integration of various races, especially when they respond to the question on the Implementation of Integrative Value (INI) and Highlighting the Talent and Potential Students (MPB), because these methods highlight the elements of unity that can be seen from a clear and practical class demonstrations. Furthermore, findings from the observation reveal that MPB method makes students more active, interested, having equal opportunity, creating good learning environment and establishing an appreciation to national values. Similar reaction is also found in the application of UKP. The implication of this study is that the use of Integrative Methods could transformed the way to teach and to learn History, making it more interesting, intriguing and encouraging as well as creating a student- oriented learning. In future, this may facilitate the element of unity and national integration to be incorporated into every students’ curriculum.
Special Issue on “Algorithm Engineering: Towards Practically Efficient Solutions to Combinatorial Problems”

The purpose of this special issue of Algorithms was to attract papers presenting original research in the area of algorithm engineering. In particular, submissions concerning the design, analysis, implementation, tuning, and experimental evaluation of discrete algorithms and data structures, and/or addressing methodological issues and standards in algorithmic experimentation were encouraged. Papers dealing with advanced models of computing, including memory hierarchies, cloud architectures, and parallel processing were also welcome. In this regard, we solicited contributions from all most prominent areas of applied algorithmic research, which include but are not limited to graphs, databases, computational geometry, big data, networking, combinatorial aspects of scientific computing, and computational problems in the natural sciences or engineering.
A Combined Preemptive SJF and Preemptive Priority Algorithm to Enhance CPU Utilization

A computer system performs its tasks by executing processes.In a CPU multiplexed system multiple processes can execute concurrently by switching among them.For handling the processes CPU scheduling techniques are used, through which the CPU utilization can be enhanced.There are several CPU scheduling algorithms for deciding which of the processes in the ready queue is to be allocated in the CPU.The existing algorithms have some problems that may lead to huge average waiting time or starvation.The SJF results the minimum average waiting time, but it also introduces starvation for bigger processes.The priority scheduling works on the basis of priority assigned to each process results waiting time that is greater than SJF.Sometimes it is required to apply an algorithm which will give attention to both of these algorithms.The proposed algorithm will work as a bridge between SJF and priority on the basis of their arrival.
Irreversible splitting of light

Quantum OpticsPrisms and dielectric beam splitters tend to be unitary and reversible optical elements, with the quantum properties of the photons largely irrelevant. Kurtscheid et al. introduce a method of irreversibly, but coherently, populating a split state with photons by thermalizing the photons into a low-energy ground state by repeated absorption-emission interaction with a fluorescent dye within a double-dimple optical cavity. Generation of such a coherent split state could be used as a precursor step to the quasi-continuous creation of many-body entangled states of light, which could be useful in applications in quantum communication, computing, and simulation.Science , this issue p. [894][1] [1]: /lookup/doi/10.1126/science.aay1334
Implementasi Metode Fuzzy Tsukamoto Pada Pertimbangan Peningkatan Insentif Karyawan Perusahaan Cabang PT Pinus Merah Abadi

PT Pinus Merah Abadi is a distributor company in Indonesia. They engaged in selling snacks such as snacks and wafers with Nabati brand. They expends incentives for their employees every month. The expending of incentive depends on pre-determined terms or targets each month with specified terms and targets and intense competition from other employees. However, in the calculation process of incentives is managed manually using the criteria by the Personnel General Affair. Then the data from the manual calculation are sent to the head office. Sometimes the results of the decision are too rigid. The research method used is descriptive qualitative. The results of the study show results that have the effect of incentives with all achievements between incentives towards employee achievement performance simultaneously. The amount of incentives depends on the ruled given. The income difference for each criterion for each employee will cause a difference in income.
Exposing Islamic Character Values at English for Islamic Studies (EIS) Class

This descriptive qualitative research aims to describe the selection and usage of English for Islamic studies material based on Islamic character values. It was conducted at English for Islamic studies class followed by the students of Akhwal As Syakhsiyyah Department, IAIN Pontianak. The results showed that the lecturer chose internet authentic material regarding Islamic character values, and he administered an online readability test to gain a reading passage that fits students' abilities. According to interviews with several students, after reading and discussing passages containing Islamic character values, students felt that such reading materials were beneficial information, and they attempted to behave according to Islamic characters mentioned in the reading passages.
Methods of contextual learning in Russia and in the United States

The educational system reform hat has been taking place in Russia in recent years is aimed at giving students an opportunity to get education of high quality and become highly qualified specialists. Contextual learning is a topical educational approach which contributes to the formation of professionally significant competences of students of a higher education institution and allows carrying out a step-by-step transformation of educational activities into professional ones. Pedagogues in Russia and abroad as well are engaged in the problem of effective implementation of contextual learning at a higher education institution. We have reviewed the works on the development and implementation of this educational approach, published by authors in English. The article presents the results of the analysis of Russian and foreign literature on contextual learning. Special attention is paidto teaching methods offered within the framework of this educational approach in Russia and in the United States.
Application of Reinforcement Learning for 5G Scheduling Parameter Optimization

RF Network parametric optimization requires a wealth of experience and knowledge to achieve the optimal balance between coverage, capacity, system efficiency and customer experience from the telecom sites serving the users. With 5G, the complications of Air interface scheduling have increased due to the usage of massive MIMO, beamforming and introduction of higher modulation schemes with varying numerologies. In this work, we tune a machine learning model to "learn" the best combination of parameters for a given traffic profile using Cross Entropy Method Reinforcement Learning and compare these with RF Subject Matter Expert "SME" recommendations. This work is aimed towards automatic parameter tuning and feature optimization by acting as a Self Organizing Network module
Lexical Bundles in Chemical Engineering Research Articles: Focusing on Structures and Functions

This paper aims to investigate the frequency, structures and functions of lexical bundles in chemical engineering. For this purpose, a million word-sized corpus was built by drawing from published research articles (Chemical Engineering Research Articles Corpus, CERAC). This specialized corpus, CERAC was compared with a similar size of a general corpus, BNC Baby with respect to frequency. CERAC was analyzed within the framework of Biber et al. (1999) for a structural analysis and within the framework of Hyland (2008) and Cortes (2004) for a functional analysis. Results revealed a considerable difference in frequency between CERAC and BNC Baby. And the distribution of structural patterns of lexical bundles in CERAC was shown in order of VP ＞ PP ＞ NP. As for the functional analysis, lexical bundles in research-oriented text occurred the most frequently and participant-oriented text the least. Also, a strong connection was found between some functional categories and structural patterns as suggested by Hyland (2008). The list of lexical bundles presented in Appendix may be utilized as an educational material in the chemical engineering discipline.
Two-weight codes over the integers modulo a prime power

Let $p$ be a prime number. Irreducible cyclic codes of length $p^2-1$ and dimension $2$ over the integers modulo $p^h$ are shown to have exactly two nonzero Hamming weights. The construction uses the Galois ring of characteristic $p^h$ and order $p^{2h}.$ When the check polynomial is primitive, the code meets the Griesmer bound of (Shiromoto, Storme) (2012). By puncturing some projective codes are constructed. Those in length $p+1$ meet a Singleton-like bound of (Shiromoto , 2000). An infinite family of strongly regular graphs is constructed as coset graphs of the duals of these projective codes. A common cover of all these graphs, for fixed $p$, is provided by considering the Hensel lifting of these cyclic codes over the $p$-adic numbers.
Database Watermarking Algorithm Based on Difference Expansion

Database watermarking technology is an important means to protect database information security. Firstly, the key components of the database are divided into several sub-groups by using the key hash function. Then, the size of the Pearson correlation coefficient is used in the sub-group to be selected the attribute column to be embedded in the watermark, and then the threshold is set by the differential expansion algorithm to determine the final embedded watermark. The pair of attributes, embedding in the virtual watermark repeatedly in the position that satisfies the condition. By setting the threshold, the embedding amount of the watermark is reduced, and the robustness of the watermark is improved. The loss of the original data of the database is guaranteed, and the watermark and the watermark extraction rate are better when attacked. When the attack ratio is low, the data recovery effect is better.
PENGARUH STRATEGI POW+TREE TERHADAP KEMAMPUAN MENULIS PARAGRAF

POW+TREE Strategy helps students write and develop ideas easily. However, not all of the students were able to write text types. The objective of this research to find out whether there is a significant effect of POW+TREE Strategy towards students’ writing ability of the students at SDN 169 Pekanbaru. This research was experimental research which had two classes experimental class and control class. This research focused on writing the next paragraph. The researcher applied the POW+TREE Strategy in the experimental class. While in control class the researcher did not apply the strategy. Further, the researchers gave two tests for the students, pre and post-test. Then, the researchers gave pretest before giving the treatment. And then, the researchers gave post-test after applied the treatment in the experimental class. The result of students’ score in the control class was, the researchers got a mean score of pre-test was 46.17. While, in post-test, the researcher got a mean score was 60.67. However, the researcher got the students’ mean score in the experimental class was 49.5. After the researchers applied the POW+TREE Strategy, the mean score of students become 65.50. Thus, there was an increase in students score after using the strategy. Based on the researchers’ analysis by using SPSS 22.0 program by using Kolmogorov-Smirnov, the researchers got a significant test was 0.05. it was same as the standard significant. In brief, there was a significant effect of POW+TREE Strategy towards students’ writing ability of the students at SDN 169 Pekanbaru.
A trial study on a mixture of Acridine and Giemsa stains and modified Quantitative Buffy Coat for detection of malaria parasites

Microscopy after Geimsa staining remains the gold standard technique for detection of malaria parasites while Acridine is a common fluorescent stain that enhances the visibility of parasites.Combination of both stains could further enhance the performance of microscopy technique.The aim of this study was to investigate the efficacy of staining with mixture of Acridine and Giemsa and modified Quantitative Buffy Coat technique in detection of plasmodium parasites.Five hundred and seventy (570) volunteered students attending the Kwara State University Health Center Malete with history malaria fever and tested positive for malaria parasite were re-examined with the two methods being investigated.Two millilitres of the blood sample from each subject was collected into EDTA container and mixed properly.Thick smears were made in duplicate from each sample and properly labeled, stained by Giemsa and Acridine-Giemsa techniques and examined under x100 objective of the microscope while the remaining blood samples were also tested by Modified QBC.The study assessed the Sensitivity, Specificity, Positive Predictive Value and Negative Predictive Value of both techniques with respect to Giemsa microscopy as a gold standard.Findings from the investigation showed that modified QBC and Acredine-Giemsa techniques recorded sensitivity of 100% and 99.7% respectively.Concentrated Acridine-Giemsa stain recorded higher specificity (90.7%) than modified QBC with 82.5% using Geimsa staining as a gold standard.The Positive Predictive Value (PPV) for Modified QBC and Acredine-Giemsa techniques were 96.8% and 96.5% respectively whereas the Negative Predictive Value (NPV) for both methods were 100% and 98.7% respectively.In conclusion, the finding depicts a keen competition between Acridine-Giemsa staining method and Modified QBC technique for detection of malaria parasites and there was no significant difference in the efficacy of both methods with respect to detection of malaria parasite.
ManiGAN: Text-Guided Image Manipulation

The goal of our paper is to semantically edit parts of an image matching a given text that describes desired attributes (e.g., texture, colour, and background), while preserving other contents that are irrelevant to the text. To achieve this, we propose a novel generative adversarial network (ManiGAN), which contains two key components: text-image affine combination module (ACM) and detail correction module (DCM). The ACM selects image regions relevant to the given text and then correlates the regions with corresponding semantic words for effective manipulation. Meanwhile, it encodes original image features to help reconstruct text-irrelevant contents. The DCM rectifies mismatched attributes and completes missing contents of the synthetic image. Finally, we suggest a new metric for evaluating image manipulation results, in terms of both the generation of new attributes and the reconstruction of text-irrelevant contents. Extensive experiments on the CUB and COCO datasets demonstrate the superior performance of the proposed method. Code is available at https://github.com/mrlibw/ManiGAN.
Single Image Reflection Removal through Cascaded Refinement

We address the problem of removing undesirable reflections from a single image captured through a glass surface, which is an ill-posed, challenging but practically important problem for photo enhancement. Inspired by iterative structure reduction for hidden community detection in social networks, we propose an Iterative Boost Convolutional LSTM Network (IBCLN) that enables cascaded prediction for reflection removal. IBCLN is a cascaded network that iteratively refines the estimates of transmission and reflection layers in a manner that they can boost the prediction quality to each other, and information across steps of the cascade is transferred using an LSTM. The intuition is that the transmission is the strong, dominant structure while the reflection is the weak, hidden structure. They are complementary to each other in a single image and thus a better estimate and reduction on one side from the original image leads to a more accurate estimate on the other side. To facilitate training over multiple cascade steps, we employ LSTM to address the vanishing gradient problem, and propose residual reconstruction loss as further training guidance. Besides, we create a dataset of real-world images with reflection and ground-truth transmission layers to mitigate the problem of insufficient data. Comprehensive experiments demonstrate that the proposed method can effectively remove reflections in real and synthetic images compared with state-of-the-art reflection removal methods.
Zero-shot Cross-lingual Dialogue Systems with Transferable Latent Variables

Despite the surging demands for multilingual task-oriented dialog systems (e.g., Alexa, Google Home), there has been less research done in multilingual or cross-lingual scenarios. Hence, we propose a zero-shot adaptation of task-oriented dialogue system to low-resource languages. To tackle this challenge, we first use a set of very few parallel word pairs to refine the aligned cross-lingual word-level representations. We then employ a latent variable model to cope with the variance of similar sentences across different languages, which is induced by imperfect cross-lingual alignments and inherent differences in languages. Finally, the experimental results show that even though we utilize much less external resources, our model achieves better adaptation performance for natural language understanding task (i.e., the intent detection and slot filling) compared to the current state-of-the-art model in the zero-shot scenario.
Robust and Accurate Global Motion Estimation Using the Student-t Distribution

Pixel-based Global Motion Estimation (GME) has always struggled to simultaneously reject outliers, avoid local minima and run quickly. There are many robust cost functions that perform well in terms of rejecting outliers, but they can yield unstable results during long image sequences as a result of their inability to adjust to changes in image content. In this letter, we propose a parameterised student-t cost function that can interpolate between two cost functions that are amongst the most widely in image registration problems, the L2 norm and the Cauchy-Lorentzian function. We also propose a parameter estimation method that helps to find the best parameters for the proposed cost function. Experiments prove that the proposed approach can estimate global motion accurately relative to the existing cost functions without demanding a higher computational cost.
Neural Network Processing Neural Networks: An efficient way to learn higher order functions

Functions are rich in meaning and can be interpreted in a variety of ways. Neural networks were proven to be capable of approximating a large class of functions[1]. In this paper, we propose a new class of neural networks called "Neural Network Processing Neural Networks" (NNPNNs), which inputs neural networks and numerical values, instead of just numerical values. Thus enabling neural networks to represent and process rich structures.