Reviewerly/exHarmony huggingface dataset:
Design and Application of Railway Intelligent Big Data Information Network Platform

Integrating the independent information resources and management instructions of railway passenger station functional departments, intermediate stations, and production workshops into a unified system platform.The internal information of the platform is highly efficient and secure.Vertically, the infrastructure and application systems achieve unified and standardized management.Horizontally, Data sharing and system interconnection and interaction among various departments.This article describes the development background, design goals, network structure, overall design, and function implementation of the system platform, and then builds a unified big data network information platform to achieve smart office, resource sharing, scientific decision-making, and improve the railway intelligent transportation system.Level of decision support and control in various business areas.
Aggregate And Fill Source Study Of West Qurna And Adjacent Area, Southern Iraq

The area of west Qurna oil fields is a low topography and represent a part of the marshes dried.The top layer of soil is composed of cohesive fragile with compression is very low.The thickness of its is about 1m, rich in organic matter.This soil is not suitable to establishing pads for oil wells, up appropriately and establish a road network connecting these wells with each other and with the main roads in the region.The soil sections were tested visually.The coordinates and photographs of mentioned sections were took using GPS and digital camera respectively.Improved raw satellite image were used which captured by Landsat in April 5 th , 2003 covering "path 166 raw 39" .ERDAS and ARC GIS, software version ninth were used to preparation the satellite image for serves the purpose of the study, produced the land cover land use digital map, and to locate the visited sites on this map.It has been confirmed that the Onsite of west Qurna area is empty from any source of aggregate, because the sections of the soil is:-From top to 12m deep is silt clay, marely clay and organic clay.From 12m to 17m is silt sand.From 17m to 20m is sand.Deeper than 20m is sand stone.The water table is about 6m.In the other hand the granular sand cover a very wide area of the southern part of study area (Offsite) which adjacent to west Qurna area.Another part covered with new sediments of the Gypcrete alluvial fan.The percentage of the sand increased as the gravels decrease from south-west to north-east.The gravels have different size, the smaller is granule, and the bigger like cobble as maximum.There are about 30 out crops utilized as aggregate quarries for construction.They are about 5-12 m deep.Their sediments are layer type.Sometimes, the sediments lens type are parallel or semi parallel, positioned among other layers.Lithological column consist of number of consecutive sediment cycles of basin cross plane bedding become gradually more fine as it directs upward.The thickness of the sediment cycles is about (5-2m).The ground water level locates at depth more than 15m.
Clustering

This chapter moves readers from the analysis of one or two texts to a larger corpus. Machine clustering is introduced in the context of an authorship attribution problem, and we reuse some functions developed in previous chapters.
Geochemistry of layered kyanite-bearing eclogites from the Roberts Victor mine, South Africa

Kyanite-bearing eclogites and grospydites are often members of kimberlitic xenolith suites.Although generally non-diamondiferous, some rare diamondiferous grospydites and kyanite eclogites have been described from the Udachnaya kimberlite pipe in Siberia (Ponomarenko et al., 1975).Heterogeneous kyanite eclogites and grospydites often show bands of modally different eclogite, typically with sharp compositional variation between the layers of different mineralogy (Hatton, 1978).These sharp interfaces also show up in the composition of the garnets across the layers, and were among the reasons to propose a process of liquid immiscibility for the genesis of these rocks (e.g.Hatton and Gurney, 1977).Other research groups proposed that the layers could be remnants of premetamorphic primary differences (Jacob and Jagoutz, 1995).This was based mainly on the following facts: (1) the studied layered eclogite belongs to the 2.7 Ga old suite of eclogites at Roberts Victor of subducted origin (Jagoutz et al., 1984), and (2) the bulk composition of kyanite eclogites is anorthositic.Thus, kyanite eclogite could have been an anorthositic cumulate within the Archean oceanic crust.Lappin and Dawson (1975) proposed a cumulate origin for the kyanite eclogites of Roberts Victor from an evolved high P-magma at 1400-1500°C, 26-28 kbar followed by stages of partial melting and chemical exchange with the ascending kimberlitic magma.We have studied several non-diamondiferous layered kyanite eclogites from the Roberts Victor Mine in terms of major and trace elements as well as oxygen isotopes.Major elements were measured at the University at Frankfurt, Germany, on a Jeol JXA 8900 microprobe using WDS, trace element concentrations were measured in situ by Laser Ablation ICP-MS at the Memorial University in St. John's, Newfoundland.
Dual Shot Face Detecting using Deep Learning

In the paper, we have used a deep learning technique to identify dual faces i.e. nothing but detecting dual shot faces. As the data is emerging day by day with high dimensionality, recognizing dual faces is a major problem. So wasting time on identifying images is like fiddling around. In order to save time and get absolute accuracy we have implemented a fast preprocessing technique named as Convolutional Neural Network (CNN) along with feature extraction technique which is used to knob the relevant features to detect and identify images/faces. By performing this robust method, our intention is to detect dual images in an efficient way. This technique results in decreased feature cardinality and preserves unique efficiency of the data. The experiment is performed on extensive well liked face detecting benchmark datasets, Wider Face and FDDB. CNN with FE demonstrates the results with superiority and the accuracy was in-depth analyzed by CNN classifier.
Clustering of Digital Images using Shape Features with SOM

In these days people are interested in using digital images. So the size of image databases is increasing rapidly. It leads retrieval problem of images from large databases. Machine learning algorithms are applying in recent research to simplify the task of image retrieval and make it automatic. Thus the concept of content based image retrieval system came into existence. In this system the images are extracted based on similar content. Content means features of the images and it is formed by feature extraction of the images in databases. Contents can be edges, color, shape, gradient, orientation, histogram gradient etc. These contents are clustered into various groups of similar feature vectors. So for any input image the selected feature is searched for and image is retrieved from the database. This reduces the time complexity. There have been many algorithms for implementing the content based image retrieval system. In this research work we propose a novel paradigm where in shape features are extracted from the database images and are used to train the self-organizing map to cluster the shape features. These clusters are then used for image retrieval.
PSO with Robust Disturbance Rejection Controller for Maneuvering Control the Altitude of UAV

In this research article, particle swarm optimization (PSO) algorithm with variable weights and robust disturbance rejection (RDR) controller used to control the height of unmanned aerial vehicle (UAV).To solve the problem of controller parameters and robustness in obtaining a set of optimal solutions for the attitude control movements of the quadrotor UAV.The algorithm designed in this article is mainly composed of two parts; the first one in accordance with the iterative process, the distance of swarm particles with the variable weight of the dynamic change in the particle size of the global optimum set the coefficient to control its impact on the degree of inertial weight.The global optimal value of the result shows that the optimization algorithm is effective to adjust the parameters of the designed controller, which in result guarantee the quality in the control of the UAV and improve the design efficiency.
A Robust Technique to Remove Fog from Single Image

Images captured in foggy/hazy environment suffers from poor visibility due to the increase of whiteness and low contrast. It affects vision applications used in object identification, surveillance, tracking and target setting. In this paper, a robust technique for removing fog from single image and enhance the visibility is proposed to satisfy vision applications. Proposed technique is simple and uses mean filter for image smoothing. Computer vision techniques are used to reconstruct image and contrast enhancement. Experiments on different foggy images shows the power of proposed technique.
Securely solving privacy preserving minimum spanning tree algorithms in semi-honest model

Yao introduced secure 2PC for the so-called millionaire's problem. It is about two millionaires Alice and Bob, interested to determine who is wealthier without revealing their values. Goldreich generalised the secure 2PC and formalised the MPC. Suppose two telephone companies wish to merge to provide better services to end users. Each company has a cost function for connecting any pair of houses. They want to connect every house with minimum cost in merged company. Before merging both companies want to know whether merging will benefit them or not without revealing cost function. Based on the MPC paradigm, we propose new algorithms for privacy-preserving computation of MST. We also investigate how to solve the classical MST problem with the help of ABB operations. We propose two more algorithms for solving MST in semi-honest model with secure ABB in the secretly shared data environment. Our protocols offer perfect security against semi-honest adversaries.
Automated Localization and Segmentation of Mononuclear Cell Aggregates in Kidney Histological Images Using Deep Learning

high performance in image segmentation tasks [6,7], in which each pixel of an image is assigned a discrete class.By assigning each image pixel a discrete class label, the image can be segmented into distinct regions of interest.The use of CNNs have thus recently gained traction in biomedical segmentation [6] and digital pathology tasks, such as the detection and localization of breast cancer and its metastases in lymph nodes [8][9][10].Based on such successful applications, a number of DL-based approaches have been approved for clinical use in the USA and other countries and are already contributing to higher precision and efficiency in many domains of diagnostics and treatment, such as diabetes care, oncology, cardiology, and radiology to name a few [11].DL has been successfully applied for several routine nephrologyrelated evaluation procedures [12][13][14], which promises to improve speed
Enterprise Level Smart Cloud Power Management System Model Based on Internet of Things and Big Data Technology

The existing energy management platform problem description, cloud computing, big data analysis, the meaning of the Internet of things technology are analyzed, with the Internet of things industry, cloud computing platform, big data analysis, suggestions for the construction of energy management platform based on reverse optimization control.The corresponding system is developed.Practical operation shows that the system provides users with reasonable energy efficiency strategies, effectively improves energy efficiency and brings specific economic benefits.
Research on cross culture teaching in College English teaching based on the concept of "Internet +"

With the rapid development of Internet, it is imperative to build a new teaching mode from "Internet +".Therefore, cross-cultural English teaching is not only an innovative way of English teaching, but also an important breakthrough in the reform of College English teaching.In order to effectively avoid the phenomenon of Chinned, teachers need to actively and correctly guide students to truly master the language of English and to use it correctly.Therefore, it is necessary to actively promote and use cross-cultural English teaching model in the process of College English teaching.This paper makes an in-depth study on the intercultural teaching mode of College English, and analyses the existing problems, and puts forward relevant improvement strategies.With the development of society, the development of all walks of life is supported by the Internet.To varying degrees, it is also affected by the Internet, which is also true in College English teaching.The appearance of "Internet +" has broken the monopoly of traditional educational resources in the region, and the dissemination of knowledge and information has broken through the restrictions of region and school.Students can get the resources they want no matter where they are, which opens up a new way to transfer knowledge.Under the influence of "Internet +", many teaching practice innovations have sprung up.With the rapid development of science and technology, the "Internet +" mode will become an important direction of future teaching development.
A Robust Blind Image Forensic-Detection Method Based On Fuzzy Technique

Blind forensic-investigation in a digital image is a new research direction in image security. It aims to discover the altered image content without any embedded security scheme. Block and key point based methods are the two dispensation options in blind image forensic investigation. Both the techniques exhibit the best performance to reveal the tampered image. The success of these methods is limited due to computational complexity and detection accuracy against various image distortions and geometric transformation operations. This article introduces different blind image tampering methods and introduces a robust image forensic investigation method to determine the copy-move tampered image by means of fuzzy logic approach. Empirical outcomes facilitate that the projected scheme effectively classifies copy-move type of forensic images as well as blurred tampered image. Overall detection accuracy of this method is high over the existing methods.
Problems of Internal Auditing in the Educational Sector (A Field study at the private university in Erbil – Iraq)

Internal auditing is an important part of internal control.The auditing function is carried out by the staffs working within the unit who are assisted by the administration to assist them in finalizing the control processes that they cannot complete themselves, The Search problem Weak scientific and practical efficiency of internal auditing, Requires study There are significant differences between the problem of scientific and practical efficiency of the internal auditor and the problem of the location in the organizational structure and independence, In the end, the researcher conducting the most important results The results of the field survey conducted by the researcher from AL-Mustansiriya University and its colleges, which provided departments and divisions for internal auditing, showed that there is a clear shortage in the number of internal auditors working in those departments and divisions and insufficient to cover audits.The number of internal auditors is not matched with the number of internal auditors required.In some colleges, auditing functions are usually conducted by a single examiner.
Structured programming

This chapter introduces the concepts of structured programming and explains how those concepts can be used in assembly programming. Loops and if-then-else structures are described and demonstrated. Next, the AArch64 function call conventions are explained. It explains and demonstrates how the stack is used for passing arguments, temporary storage, and automatic variables. The chapter also explains how to perform recursion in Assembly Language, and ends by showing how to access the fields in a C and how to access data in an array.
Introducing Identity

Abstract The best-known syntactic account of the logical constants is inferentialism . Following Wittgenstein’s thought that meaning is use, inferentialists argue that meanings of expressions are given by introduction and elimination rules. This is especially plausible for the logical constants, where standard presentations divide inference rules in just this way. But not just any rules will do, as we’ve learnt from Prior’s famous example of tonk , and the usual extra constraint is harmony . Where does this leave identity? It’s usually taken as a logical constant but it doesn’t seem harmonious: standardly, the introduction rule (reflexivity) only concerns a subset of the formulas canvassed by the elimination rule (Leibniz’s law). In response, Read [5, 8] and Klev [3] amend the standard approach. We argue that both attempts fail, in part because of a misconception regarding inferentialism and identity that we aim to identify and clear up.
Portraying Privacy Leakage of Public WiFi Systems for Users on Travel Spam Detection in Social Bookmarking System

In this paper, we depicts spam revelation, in perspective of the examination of posts, in social bookmarking districts. For consistent acknowledgment of spam posts, we propose a name estimation plot and a specific evaluation procedure for picking marks. The label estimation scores each tag. In the particular evaluation, the label scores in perspective of the utilization repeat and the degree of spammers are estimated and the thoughts of white tag and dim tag are introduced. Using these thoughts, names are proficiently arranged into the names demolishing the execution of spam revelation, the names pleasing in getting spammers, and the marks which should achieve a discipline. Finally, we propose semantic components to moreover upgrade the spam distinguishing proof
Research on Smart Physical Bookstores and Digital Reading Based on Word2vec Technology and Text Clustering

With the impact of the epidemic situation, many physical bookstores have launched online crowdfunding to save the nation, and the operation of physical bookstores is not easily known to the public. In addition to online crowdfunding and government support, how can physical bookstores get out of the predicament and develop in the context of the Internet era is a problem that physical bookstores have to think about. To solve this problem, we need to consider the needs of consumers for physical bookstores. In this paper, we take the perception of Zhihu users on physical bookstores as experimental data, remove irrelevant data, and take sentences as a unit to deeply analyze consumer comments, extract keywords in sentences through word2vec technology. At the same time, we compare the accuracy of word2vec keyword extraction with TF-IDF keyword extraction. The accuracy of word2vec is much higher than TF-IDF. In this paper, word2vec method is selected for keyword extraction and clustering. In order to analyze and summarize the needs of consumers for physical bookstores, to help physical bookstores get rid of difficulties and move forward.
Peningkatan Hasil Belajar Ilmu Pengetahuan Alam Peserta Didik Melalui Media Model Dengan Metode Inkuiri Di Kelas V SD Negeri 04 Payakumbuh Tahun 2019/2020

This study aims to improve student learning outcomes in class VC SD Negeri 04 Payakumbuh through a media model using the inquiry method. This type of research is classroom action research (CAR). The subjects of this study were all VC class students of SD Negeri 04 Payakumbuh in the 2019/2020 school year, totaling 35 people. The data obtained comes from student data, teachers, and documentation. The data collection procedure used observation instruments, field notes, tests, and documentation. The results showed that the media model with the inquiry method could improve student learning outcomes in science subjects for class VC SD Negeri 04 Payakumbuh. This is evidenced by the average value from the initial conditions of 62, in the first cycle it rose to 68.57, in the second cycle it became 76.28 and in the third cycle it reached 84.
Build Rust

Build Rust Zach Savich (bio) You ever think it's time to start thinkingabout changing your life, that dog you can't kick? A quick thought. Quickis what it cut to. Fireflies in summer hail. I had a theory about the exactly-obvious.Most art fails from being over- or under-obvious. The student said she wantedher work to be about abrasion, but she hardly abraded anything. The chisel itselfshould fray. The hand should. The eye, encountering it. You don't need moreexplanation than that. So I started cultivating rust. 20% population loss in the pasteighteen years. I moved here. Dense canopy fireflies rose up early in, mistaking dusk.Let rust be what we make. It is. As sourdough employs ambient yeast, tastingof local air. Rust Belt. Built rust. "Build soil," writes Robert Frost. "Turnthe farm in upon itself / Until it can contain itself no more." Time authors it. Youspeed its rustic flush with hydrogen peroxide, vinegar, and salt. "An Elemental Rust,"says Dickinson. I grew it on the inside of a can. A rustling effect. A chandelier.A .22. Its cartridges. A bit of window screen patching a screen. Then removed it from steel platesexactingly and set it places it won't grow. Driftwood, mirrors.A contact lens. I held, with rusted gloves, the rusted wooden handle of a pristine axe.The meaning is I wanted to see it. I trusted that. I dream of increasing the metallic qualitiesof flowers—I'm adding iron to the water, watering the peonies—and spraying the blossoms [End Page 109] with my solution. I dream the rust-pollen will pass to bees. I dream of sprayingthe bees. [End Page 110] Zach Savich Zach Savich's latest books are the poetry collection Daybed (Black Ocean, 2018) and the memoir Diving Makes the Water Deep (Rescue, 2016). He directs the BFA Program in Creative Writing at the University of the Arts in Philadelphia and co-edits Rescue Press's Open Prose Series. Copyright © 2020 Pleiades and Pleiades Press
A Message from the New Editor-in-Chief

As a promising way for establishing secret keys, physical layer key generation has been broadly studied, which typically extracts secret keys with wireless channel characteristics. The existing schemes proved that temporal channel variations, channel reciprocity and spatial de-correlation of wireless channel greatly affected the performance of physical layer key generation. In this paper, the application of collision entropy (Rényi’s quadratic entropy) for improving physical layer key generation is discussed. Specifically, after collecting sufficient channel measurements, a channel measurement evaluation mechanism based on collision entropy is implemented to determine the adequacy of these measurements. Consequently, some consecutive measurements with smaller collision entropies are dropped and the reserved measurements are applied as input of the following process. Based on the evaluation mechanism, an adaptive and efficient key generation scheme is proposed. The proposed scheme consists of five components: channel probing, the evaluation mechanism, the adaptive quantization, information reconciliation and privacy amplification. To validate this scheme, several experiments in real environments are conducted. Different from the existing schemes, the received signal strength (RSS) measurements derived by heterogeneous devices are used as channel measurements. The results show that: (1) compared with homogeneous devices, RSS sequences of heterogeneous devices have more discrepancies and these discrepancies make key generation more challenging; (2) the proposed evaluation mechanism can effectively reduce bit mismatch rate and enhance the efficiency of information reconciliation; (3) compared with other schemes, the proposed key generation scheme can efficiently generate shared secret keys between heterogeneous transceivers in real environments.