Reviewerly/exHarmony huggingface dataset:
WEAPONS IN WARFARE AND HUNTING WITH SPECIAL REFERENCE TO ROCK PAINTINGS OF EARLY IRON AGE IN TAMIL NADU

The provenance of rock paintings in Tamil Nadu had started from Mesolithic. It was developing in the Neolithic period. The paintings had reached into the zenith of its position during the period of early Iron Age, which means the images have depicted in different aspects. In which the scenes of warfare and hunting have depicted as a major role in the rock paintings of early Iron Age particularly in Tamil Nadu. The humans have shown with different weapons in the warfare and hunting. The images have depicted on the shelter, boulder and even in the dolmen, which are locating accessible and inaccessible places. The paintings have found in the mount, hillock and plain land, where the isolated boulders have located. The images have prominently found on the mount and hillock. The paintings have drawn on the granite variety of the rock. The images have depicted in red ochre and white kaolin, in which the majority of the images have depicted in white kaolin.
THE INFLUENCE OF READING HABITSAND READING STRATEGIES ON STUDENTS’ READING COMPREHENSION ATJUNIOR HIGH SCHOOL 1 IN THE DISTRICT OFBENAI-KUANSING

The purpose of this study was to the influence reading habits and reading strategies on students reading comprehension at junior high school 1 in the district Benai-Kuansing.There were three questions contained in this study.Firstly,Is there any significant influence of reading habit on students’ reading comprehension in junior high school 1 Benai.Secondly, Is there any significant influence of reading strategies on students’ reading comprehension in junior high school 1 Benai.Thirdly, Is there any significant influence of reading habit and reading strategies on students’ reading comprehension in junior high school 1 Benai.This study used quantitative explanatory research. The subjects in this study are 70 students of the second grade students. Data collection techniques in this study used questionnaires and tests. The questionnaires in this study related to students' reading habits and students' reading strategies, while the tests related to student reading comprehension. The data obtained were analyzed using descriptive statistics, classic assumption tests, multiple regression tests and hypothesis testing.The results of this study indicate that, student reading habits (X1) have significant results of 0,685. Student reading strategies (X2) have significant results of 0.379. And student reading comprehension (Y) has a significance result of 0.818. Therefore, the researcher concludes that there is a positive and significant contribution of student reading habits and student reading strategies on student reading comprehension. Keywords:Reading Habit, Reading Strategies, Reading Comprehension.
The Spirit of Thoreau in the Age of Trident

Henry David Thoreau went to jail in 1842 rather than pay a poll tax whose revenues were used, in part, to pay for US President James K. Polk’s colonialist war against Mexico. That long ago, Thoreau insisted that a citizen had a civic responsibility to oppose an unjust war: “The soldier is applauded who refuses to serve in an unjust war by those who do not refuse to sustain the unjust government which makes the war.” His more general counsel was to “let your life be a counter friction to stop the machine. What I have to do is to see, at any rate, that I do not lend myself to the wrong which I condemn.”
An Iterative Information System Design Process Towards Sustainability

While bringing business and computer science into an improved alignment using the theoretical foundations of information and computation is one of the main aims of information science, improved design knowledge from other interdisciplinary research fields like human-computer interaction (HCI) could advance different information system (IS) design thinking and processes. Since structuring the IS design process for a sustainable result is challenging, a HCI viewpoint and focus on IS design could be beneficial due to the multi and interdisciplinary nature of HCI. In this paper an iterative design process for sustainable IS design conceptualized from HCI is proposed. The resulting design process highlighted the role of HCI in building knowledge in information science. This was achieved by showing the influence of different design choices on user behavior and in that way contributing towards generating reusable designs in different phases of the sustainable IS design process.
Increasing the Vocational Action Competences of Rail Traffic Controllers by Creating a Virtual Learning Environment for Trainees

In Germany railway operations underlie a vast number of complex rules and regulations. Therefore rail traffic controllers, who are responsible for save and hitch-free railway operations, need a profound knowledge and action competencies to consider the regulations in everyday work. Before being able to work as rail traffic controllers, they have passed an apprenticeship of three years. In addition, because of local characteristics of tracks and infrastructure, a rail traffic controller needs an instruction phase for a couple of months, just to be able to work at one single signal box. To cope with the high demands of the job, a virtual learning environment for trainees was created to increase their vocational action competences, to enhance their knowledge and to ease the passage to job. A prototype of the software was created using a usability engineering approach. A strong collaboration with rail traffic controllers and potential users ensured the usability of the system. The final concept and prototype of the learning environment will be presented in this paper. It consists of three different learning sections and one test section, where trainees can check their knowledge.
Use of Secure Repository for Passwordless Handshake to Enhance the Authentication

In this paper we presented an innovative thought to provide better security for authentication procedure. In this procedure user’s password is restricted to transmit over the network, still provides the same security for authentication services. To accomplish this we have used smart card which adopts the Kerberos Protocol and a secure password repository. As the smart card system allows restricted access, it provides a secure place to keep credentials safe. Without revealing the secrets to public an authentication system may perform its scope by referencing to them through identifiers. This promotes the credibility of the mechanism while at the same time it achieves to reduce the overhead of the authentication systems due to the complex encryptions procedures.
Privacy Preserving Public Auditing in Cloud: Literature Review

Cloud computing has given a bloom to the technical world by providing various services. Data storage is the essential factor for the users who are having or working with lots and lots of data. Cloud data storage becomes the only way to store and maintain the large data, which can be accessed from anywhere and anytime. The open nature of cloud computing leads to some security issues. With respect to the cloud data storage, the Cloud Service Provider (CSP) has to provide security for the data outsourced. Data owner will be concerned on the data correctness after outsourcing into the cloud. To verify the data correctness, ensuring the state of data at the cloud data storage is needed, which is performed with the help of a Trusted Third Party Auditor (TTPA). Data owner can also perform the verification task, but it leads to computation cost and communication costs in huge amount. This survey gives a brief on public auditing schemes to explore what are all the system models designed by various researchers.
Daily Time Series Estimation of Global Horizontal Solar Radiation from Artificial Neural Networks

Obtaining a complete and efficient database is necessary for the sizing of photovoltaic systems. Despite the existence of the unit-level radiometric chain, the acquisition of data from different radiation components has problems, and thus gaps in the radiometric database. Thus, good sizing is possible only if the measurements are available continuously in space and time. The purpose of our work is to use the insolation basis for the estimation of the global daily radiation at the URERMS research unit (latitude 27.87, longitude −0.272) using neuronal techniques, demonstrating the efficiency of using neural networks as a global solar irradiation modeling tool.
Upcoming meetings

Artificial OrgansVolume 43, Issue 10 p. 1045-1045 UPCOMING MEETINGS Upcoming meetings First published: 13 October 2019 https://doi.org/10.1111/aor.13555Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume43, Issue10October 2019Pages 1045-1045 RelatedInformation
4D – Distracted Driver Detection Device

This paper describes an inexpensive distracted driver detection device built using a Raspberry PI3, a video camera, and python code. Distracted and drowsy driving are two of the leading causes of automobile accidents in the United States, and this inexpensive standalone can help prevent those deaths. live video feed of the driver’s face is read in and through the facial landmark detector within DLIB, the co-ordinates of the eyes and mouth are extracted in real time. The ratio of the distance between the eyelids in the vertical direction to the horizontal direction defined as Eye Open Ratio is used to evaluate if the eye is open or closed and a similar ratio on the mouth(Mouth Open Ratio) is used to identify if it is open or closed. By looking at the eye and mouth open ratio for several consecutive frames, it is determined with &gt;95% accuracy whether the driver is drowsy, distracted, or yawning. If any of these behaviors are noted, the device will prompt an audible warning to encourage the driver to focus on the road. The prototype was tested under a variety of lighting conditions from dark to bright light and on different subjects with and without glasses. This test data was used to determine the threshold for when the eye or mouth is determines open or closed. Additionally, the prototype’s settings are customizable for a primary driver to further improve the accuracy. The device connects to a smart phone and sends information with the time stamp of the distracted driver incident. This device can be used to prevent distracted or drowsy driving-related deaths, and is an inexpensive attachment that can easily be fitted into a preexisting vehicle.
Multi hidden layer extreme learning machine optimised with batch intrinsic plasticity

Extreme learning machine (ELM) is a novel learning algorithm where the training is restricted to the output weights to achieve a fast learning speed. However, ELM tends to require more neurons in the hidden layer and sometimes leads to ill-condition problem due to random selection of input weights and hidden biases. To address these problems, we propose a multi hidden layer extreme learning machine optimised with batch intrinsic plasticity (BIP) scheme. The proposed algorithm has a deep structure and thus learns features more efficiently. The combination of BIP scheme helps to achieve better generalisation ability. Comparisons with some state-of-the-art ELM algorithms on both regression and classification problems have verified the performance and effectiveness of our proposed algorithm.
Dangerous Speech

This chapter is concerned with dangerous speech. Dangerous speech is any form of expression that is likely to cause others to commit or condone acts of violence against some group of people. Not all dangerous speech is dehumanizing speech, however. People often incite or justify violence against a group without encouraging an audience to think of their targets as nonhumans. But this chapter shows that dehumanizing speech is an especially dangerous kind of speech, because of its power to elicit extreme forms of violence. This form of speech dehumanizes indirectly, by causing others to adopt dehumanizing attitudes. The producer of the speech may or may not even share these attitudes.
Background

Strings are present in many applications of Computer Science and details on their definitions and notation may vary depending on the context of the application. In this chapter we define basic notation used throughout the book and we present fundamental data structures for string processing.
Fuzzy Clustering

Fuzzy clustering methods produce a soft partition of units. Unlike standard methods, each unit is assigned to a cluster according to a membership degree that takes value in the interval [0, 1]. Starting from the most known algorithm, the Fuzzy k-Means, in the last decades, several variants have been proposed. By relaxing the unit-sum constraints of the membership degrees, we move from the fuzzy to the possibilistic approach. In this case, the membership degrees are better identified as typicality degrees. In this chapter, fuzzy and possibilistic clustering methods will be first briefly introduced from a theoretical point of view, and after their application to benchmark case studies will be presented.
Pleuger celebrates 90-year history

German company, Pleuger Industries, is an international supplier of submersible motor pumps, thrusters and plunger pumps with headquarters in Hamburg. It recently celebrated its 90th anniversary and reflected on its tradition of manufacturing industrial submersible motor pump aggregates.
Dexterous Trashbot

Waste segregation involves assembling a wide range of waste in an unsorted way by utilizing manual work. Segregation of this waste is exceptionally repetitive, tedious and wasteful. There is a requirement for a framework, which robotizes the procedure of waste isolation, with the goal that the junk transfer can be executed effectively and productively. In the proposed solution, the framework utilizes deep learning approach, use of CNNs, which combines with robotics to classify wastes into categories like plastic, paper, cardboard, glass and metal. Garbage segregation is accomplished using classifying images and picking the object using a robotic arm. The problem of manual picking of garbage which is hazardous to human health is avoided using the Dexterous Trashbot. ResNet and Vgg architectures were used for transfer learning and gave better results than a custom CNN model for image classification. Real-time images captured are classified by making a HTTP request to the deployed model. The garbage is segregated into respective category by picking the selected object using robotic arm. The solution proposed discourages the hazardous manual picking of garbage. Segregation of dry waste could be done in real-time. Dexterous Trashbot has the ability to segregate garbage easily without any human intervention.
Design and implementation of a wirelessly controlled object carrying hexacopter

Unmanned aerial vehicle (UAV) is becoming the future of remote operation, monitoring and delivery system. For a UAV, remote operation requires a versatile control system that can maintain its position without disturbing the task at hand. This paper introduces a hexacopter which is able to pick and place an object by using a robotic arm, while it is flying. The arm is used to grip an object firmly and carry it to the desired destination. It maintains its position on air accurately while performing the pick and place operation. This UAV is able to withstand windflaw to maintain its position. This project can be used for rescuing, transportation of products, first aid supply etcetera.
Software Reusability of Object-Oriented Systems using Data Mining Techniques

Due to fast advancement in software industry, there was a demand to cut down time and efforts during process of software development. While designing product and services it is very essential to assure quality of product in order to strengthen market value of the product. To accomplish both quality as well as productivity objectives, it is suggested to go for software reuse. Reusability is an essential measure that can be used to improve overall software quality with lesser cost and efforts. This paper gives insights into various literature studies related to software reusability of Object-oriented software using data mining techniques. In this paper even comparative analysis of various techniques related to prediction and enhancement of reusability of Object-Oriented software systems has been done. This would help to get better understanding of need of reusability enhancement of Object-Oriented systems using data mining techniques
Assorted Model of Sentiment using Mapreduce Framework

Social networking sites platforms, such as Facebook and Twitter, are being broadly used by community to share their feelings on different matters. Consequently, social networking site becomes an admirable and major open source for collecting public opinion. To perform sentiment analysis on such huge data, computational assorted models of single node are ineffective. Two ways to grip data that are big ,either by using super computers or by using parallel processing or by distributed processing. Where it is costly to use super computer, most models of parallel processing such as MPI, are difficult to implement and scaling, MapReduce is one of the parallel processing models that is highly scalable, tolerant to fault, and easy for using, in this research paper, we have proposed assorted model of sentiment analysis for twitter using MapReduce Framework. mapreduce based naïve bayes training algorithm was proposed for this purpose. Only single mapreduce job is executed for this algorithm which makes it different from earlier previous work. Training model is deployed to to classify million of tweets of twitter computers are costly, most parallel programming models, such as MPI, are difficult to use and scale. MapReduce is one of the parallel programming models that is highly scalable, fault tolerant and easy to use. This paper proposes a scalable framework for sentiment analysis of Twitter using MapReduce model. For this purpose a MapReduce based Na¨ıve Bayes training algorithm is proposed, this algorithm uses only one MapReduce job which makes it different from previous works. The trained model is deployed to classify millions of tweets. Accuracy and Scalabilty of our propsed model is well compared to previous models.
Implementation of Reversible Data Hiding Innovations for Image Encoding

Since many years, the protection of multimedia system knowledge is turning into vital. The protection of this multimedia system knowledge are often finished cryptographic or knowledge activity innovations. Recent reversible knowledge activity ways are planned with high capability, however these ways aren't applicable on encrypted pictures. Information is that the currency of democracy, safety of identical throughout transfer and storage has become a challenge within the field of information communication. Digital pictures are utilized in virtually each space of the life. The appearance of digital pictures has brought loads of accomplish varied scientific areas, however conjointly several new threads are opened. One among the most issues with digital knowledge and pictures is unauthorized replication and use. One among the foremost economical solutions to the current ever-growing drawback is steganographic. The cynosure of this paper is that the changed cryptographic and decipherment of pictures victimization changed Reversible Search innovation (R_S_A) and its later application on a picture file. The planned innovationic rule higher accuracy came compared to existing methodology retrieval of the first picture by applying decipherment mechanisms. At the end, Associate in an efficient approach is establish for keep the picture secure.
Reviews

Geophysics and Geosequestration, edited by Thomas L. Davis, Martin Landr⊘, and Malcolm Wilson, ISBN 978-1-107-13749-3, 2019, Cambridge University Press, 388 p. Geological Carbon Storage: Subsurface Seals and Caprock Integrity, edited by Stéphanie Vialle, Jonathan Ajo-Franklin, and J. William Carey, ISBN 978-1-119-11864-0, 2018, American Geophysical Union and Wiley, 364 p. Introduction to Deep Learning, by Eugene Charniak, ISBN 978-0-262-03951-2, 2019, MIT Press, 192 p. Foundations of Machine Learning, second edition, by Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar, ISBN 978-0-262-03940-6, 2018, MIT Press, 504 p. Seismic Ambient Noise, edited by Nori Nakata, Lucia Gualtieri, and Andreas Fichtner, ISBN 978-1-108-41708-2, 2019, Cambridge University Press, 370 p.
Web Superintendence

Over the past two decades, the internet has exponentially expanded to every part of the world. It has made every single individual as its either consumer or even a producer. And with the evolution of different social networking sites, it has even made individuals upload their personal content over the internet. This personal information compromises information ranging from even the smallest detail ranging from his birthdate to even the place he is traveling to. Uploading personal information over the internet has leveraged various opportunities, it could either be business intelligence or even for the purpose of overseeing a person with antisocial behavior.
Clustering Validation

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning.
Clustering Related behaviour of Users by the Use of Partitioning and parallel Transaction Reduction Algorithm

Fast improvement of data in relationship in the present universe of business trades, wide data getting ready is a primary issue of Information Technology. By and large, an Apriori figuring is extensively used to find the relentless thing sets from database. Later drawback of the Apriori count is overpowered by various estimations yet those are in like manner inefficient to find visit thing sets from far reaching database with less time and with amazing profitability. From this time forward another structure is proposed which contains facilitated passed on and parallel preparing thought. The examinations are directed to discover visit thing sets on proposed and existing calculations by applying diverse least help on various size of database. With expanded dataset, Apriori and Transaction decrease calculation gives horrible showing when contrasted with Partitioning and Parallel Transaction Reduction Algorithm(PPTRA). The actualized calculation demonstrates the better outcome as far as time intricacy and furthermore handle enormous database with more productivity