Reviewerly/exHarmony huggingface dataset:
Improved RRT Algorithm for Field Environment Tends to Smooth Path

RRT algorithm is a widely used method for path planning. The 3D path planning of mobile robots in the field environment tends to be flat. An improved RRT algorithm is proposed. In view of the particularity of the field environment, considering the limitation of the maximum turning angle and the maximum pitch angle of the mobile robot, a new node acceptance criterion is proposed. The acceptance criteria of the new node takes into account the changes in the altitude of the field terrain, the flatness of the path, and the mobility constraints of the mobile robot itself. Simulation results show the effectiveness of the improved method. Under the premise of avoiding mountains, valleys and rugged terrain, the required planning path can be generated to ensure the safety of the mobile robot.
Implementation of SVM+PSO Model in Monolingual and Cross Lingual Information Retrieval Ranking

Now a day's many research works are going on in the field of Information Retrieval Ranking.Retrieval and Ranking of information from the huge database of internet world is become a most useful and interesting task.Machine learning plays the major role now days.In this paper we have worked for monolingual and cross lingual information retrieval ranking in which the retrieval of document within the same language and retrieval of document in different language has been done.We take English language for monolingual IR ranking and for cross lingual we take Hindi queries and get documents in English.
New colour appearance scales under high dynamic range conditions

New colour appearance scales close to daily experience and image quality enhancement are highly desired including whiteness, blackness, vividness and depth.This article describes a new experiment to accumulate the data under HDR (high dynamic range) conditions.The data were then used to test the performance of different colour appearance scales such as CIELAB and CAM16-UCS plus the recent extension by Berns' Vab*, Dab*.The results showed those Berns' scales gave a reasonable performance.However, it was found no scale is capable of predicting colour appearance data covering a wide dynamic range.New scales were developed based on the absolute scales of brightness and colourfulness of CAM16-UCS and gave accurate predictions to the data.
The Journey towards the Love for Reading: From the Lens of English Enthusiasts

This study described the lived experiences of the English enthusiasts at the University of Cebu – Main Campus. The study used Interpretative Phenomenological Analysis (IPA) through 15 BSED English Majors interviews. The analysis of data generated six themes “Actually, I am not really fond of reading books, but I’ve learned to enjoy reading love storybooks. They are very entertaining.” (Gaining Interest and Love for Reading), “The challenges that I encountered in my journey towards acquiring the love of reading are the unfamiliar words. Whenever I encountered those words, I usually pause and find their meanings.” (Dealing with Unfamiliar Words) “I addressed the challenges in positive ways. These only urge me to love reading more.” (Context and Comprehension Challenges) “I simply love reading because I can use my imagination. When I read, I feel like I’m the main character of the story.” (Attitude towards Reading) “In reading, you will experience things you haven’t experienced yet. You choose an author and a genre first before you read. In that way your interest and love of reading will be sustained but exploring is more fun.” (Personal Book Choice) “In reading, actually you discover yourself more, especially if you read different genres of books. My journey towards reading is self-discovery.” (Realizations through Reading). The study attempts to explain the different factors involved in the love of reading. These are gaining interest and love of reading, dealing with unfamiliar words, context and comprehension challenges, attitude towards reading, personal book choice, and realizations through reading. The English enthusiasts encountered some difficulties in reading various texts, passages, and other English classics. However, their enduring interest, love, and passion for reading transcend all forms of reading complexities. In contrast, some students may lack interest and motivation in reading. They tend to be superficial readers, or they just read when they are told to do so. Reading for them is dull and boring. Thus, the English enthusiasts may share their lived reading experiences with those reluctant and passive readers, and they may become more interested and motivated to read beyond the parameters of academic requirements.
Cyber Security and Information Security

To understand the differences between terms like cyber security and information security is important because many banking regulatory bodies like Reserve bank of India, Hong Kong Monetary Authority, Monetary Authority of Singapore, etc. have asked banks to have separate cyber security AIS security policies. These two words “Cyber Security” and “Information Security” are generally used as synonyms in security terminology, and create a lot of confusion among security professionals. We are discussing with some InfoSec professionals about the same and found out that some of them think that cyber security is subset of information security while others think the opposite. So, to clear this confusion, we decided to research on the same and write a blog.
Foreword

Illicit trade in fake goods is a major challenge in an innovation-driven global economy. It has a negative impact on the sales and profits of affected firms, as well as broader adverse effects on the economy as well as public health, safety and security. Organised criminal groups are seen as playing an increasingly important role in these activities, using profits from counterfeiting and piracy operations to fund other illegal activities. Counterfeiters operate swiftly in the globalized economy, misusing free trade zones, taking advantage of many legitimate trade facilitation mechanisms and thriving in economies with weak governance standards.
Online Literary Text Usage on the Studentsâ€™ Reading Comprehension

Recently, the upcoming era, namely industry revolution 4.0 becomes trend topic and big issues. It has many roles in aspects of life. It can be recognized in teaching and learning process also. English practitioners, both teachers and students, should involve and master technology to improve their English capability or skills as the consequently. The research plays technology as a message of industry revolution 4.0 to encounter English teaching problem. The objective of the research is to find the effect of online literary text usage on the studentsâ€™ reading comprehension. The research methodology is using experiment with a factorial design. Data collection is obtained by examining reading comprehension test. One paired sample t-test acts to analyze the data. The number of sample is 40 students of 50 population number at Islamic studies program Sekolah Tinggi Agama Islam academic year 2017/2018. Random sampling works as technique of taking the sample. Data calculation and analysis shows that Asymp. Sig. (2-tailed) =0.000 less than Asymp. Sig. (2-tailed) &lt; 0.05 explaining that H0 is rejected. It means that there is a significant effect of online literary text on the studentsâ€™ reading comprehension. Seeing the research result, it is suggested to English practitioners, both teachers and students, keep in touch online literary text to improve the studentsâ€™ reading comprehension
Data Transformation Techniques for Academic Datasets

Data mining is a real-world procedure of discovering useful patterns from heterogeneous datasets. All most all industry uses data mining in their day to day activities. To build an effective mining model, a series of development steps are to be followed. It starts with discovering the business problem and ends with communicating the results. In this development life cycle, the most important step is data preparation or data preprocessing. Data preprocessing is converting raw data into data understandable by the machine. Data normalization is a phase in data preprocessing where the data values are scaled to 0 and 1. Right normalization of the datasets leads to improved mining results. In this paper, academic data of students is taken. The dataset is normalization using six normalization technique. Multi Layer Perceptron classifier is applied to normalized dataset and results are obtained. Results of this study reveal the best normalization technique which can be used for normalizing academic datasets. Finally, in a line, the goal of this work is to discover the best normalization technique which produces better mining result when applied to academic datasets.
Traditional Dimensionality Reduction Techniques using Deep Learning

From the analysis of big data, dimensionality reduction techniques play a significant role in various fields where the data is huge with multiple columns or classes. Data with high dimensions contains thousands of features where many of these features contain useful information. Along with this there contains a lot of redundant or irrelevant features which reduce the quality, performance of data and decrease the efficiency in computation. Procedures which are done mathematically for reducing dimensions are known as dimensionality reduction techniques. The main aim of the Dimensionality Reduction algorithms such as Principal Component Analysis (PCA), Random Projection (RP) and Non Negative Matrix Factorization (NMF) is used to decrease the inappropriate information from the data and moreover the features and attributes taken from these algorithms were not able to characterize data as different divisions. This paper gives a review about the traditional methods used in Machine algorithm for reducing the dimension and proposes a view, how deep learning can be used for dimensionality reduction.
Sistem Informasi Geografis Peternakan Ayam Pada Kabupaten Jembrana Berbasis Website

This thesis proposal discusses the difficulties of chicken buyers to get information on chicken farms in Jembrana Bali, and the limited information obtained, currently complete information on farm layout in Jembrana Regency, only exists at the Jembrana District Animal Husbandry Service, then chicken breeders are also it is still difficult to provide information about their layout due to the limited means of adequate information in each village. So a chicken farm geographic information system was created with the aim of helping chicken buyers, livestock raisers and the Chicken Farming Service to get information on chicken breeding in Jembrana Regency more easily.Keywords— livestock, chicken, GIS, Website, Jembrana
Knowledge Management Processes for B-Schools

This study, explores the intentions of institutions of Indian B-Schools academicians towards knowledge management and knowledge management processes. The use of knowledge management is recognized as an institutional capacity and tends towards growth. A review is conducted based on knowledge management treated as strategic and tactical plan. A pilot study is carried out and the findings are presented in the paper. The pilot study is based on the responses to the questionnaire prepared on the basis of literature. A closer link has to be brought in between the knowledge management and knowledge management processes as it helps our future managers and also provide them the skills they require throughout their life. It is felt that there should be a stronger requirement for change and responses from universities to address them and close the gap. There could be the knowledge management and its practices contributing to the performance of B-Schools and overall development of the institution.
Exploration of System Performance of Quantum Cryptography in Network Security

Cryptography NetworkSecurity was a conception to secure the datatransmission and the network of the wireless networks. For the datatransmission the major feature isdata Security on independent network. In a network authorization of access of thedata was maintained by the NetworkSecurity, here the network administrator controls the entire process. The users will login by the ID, Password and some other authenticating information to access in to the network to perform their authentication. The NetworkSecurity protects different kinds of both private and public networks, computer networks and daily transactions in the business and in the communications and in government and other sectors. Public access and private access are the different varieties of Networks in the system. In this paper the cryptography NetworkSecurity by Ciphers are defined. In this cryptography algorithm is used.
HADEM-MACS: a hybrid approach for detection and extraction of objects in movement by multimedia autonomous computer systems

Nowadays, we assist in the multiplication of applications that need to exactly identify objects crossing a field watched by cameras. Multimedia information thus becomes an inescapable medium for the validation of applications such as identification, localisation and object tracking. This gives rise to many processing methods that, after collecting multimedia data (images, videos), continue with a pre-processing in order to reduce noise, finally it finishes with processing in order to extract objects, more precisely the form of object that capture our domain of interest. The first stage consists of detecting objects in movement in the scene. This detection passes through a background modelling. Model based on mixture of Gaussian is commonly used and it is classified in the categories of parametric approaches. However, many other approaches exist today in literature each of them having its advantages and drawbacks. We present in this paper a hybrid approach of movement detection which combines an improved version of mixture of Gaussian with a neural network-based approach.
Model of Project-Based Learning Platform

The implementation of the Project BasedLearning (PBL) in education facing a number of problems anddifficulties, prompting teachers to avoid its use and rely ontraditional methods of training. The article examines the role ofICT in PBL, the benefits of PBL and its main problems in itsimplementation. A conceptual model of a PBL platform ineducation is proposed to guide and assist the teacher inplanning, implementing and presenting project results. The roleof the teacher is leading and involves preparing, presenting aproject, motivating students, managing the process throughcontinuous communication and facilitating.
Conclusion

Abstract We answer the broader question of whether Timmer’s framework is relevant to development in Africa today drawing on findings from the chapters presented in this volume. We conclude with policy recommendations for sparking a youth-inclusive transformation given today’s challenges. First, providing incentives for young farmers to adopt improved agricultural technologies is key to enhancing productivity growth in the agricultural sector. Second, employment policies need to be restructured to focus on the RNFE and the informal sector. Third, improvements in rural access to finance and savings promotion are necessary to enable enterprises to expand and create more jobs for youth. Fourth, government investments in infrastructure and education are essential to increase market access to farmers and entrepreneurs and improve the quality of the labour force to attract additional investments from foreign and domestic firms.
Sequential Estimation of Feed Forward Networks for Small Embedded Hardware

Deterministic Finite Automata (DFA) and Non-Deterministic Automata (NFA) Systems require an input and lead to an output after stage traversals and based on the pathway so chosen leads to the either the acceptance or rejection of a language. Considering compilers, the compiler works first to understand the lexical correctness of the input and to do so follows steps to check for the validity of the same. If the input is of a valid form then the input is accepted else a suitable corresponding error is thrown. When considering a feed forward neural network, we see a pattern of an input being taken and passed to a hidden layer, which further may either pass to another hidden layer (making it a deep network) or lead it to an output layer. Neural networks find application in classification problems, regression analysis and recognition paradigms. On naïve speculation, a correlation can be made on similarities between finite automata and feed forward networks.
LINGUA LOMBARDA?

The paper deals with the vivid concept of â€˜lingua lombardaâ€™ (often in between higher and lower cultures) as it is can be traced in a wide range of authors, from the first centuries to Dante, from Manzoni to 20th- and 21st-centuries scholars. It is in Italian dialectal areas where it is especially clear the cultural and methodological connection between (micro-)history and (micro-)geography for the long linguistic history of Italy. On the steps of a willing and yet perfectible regional law, scholars and academics (and the very Crusca too) should take actions in favour of these documentary and oral testimonies of â€˜local varietiesâ€™ in order to avoid their disappearance; they are an immaterial and now endangered treasure which was able, over the centuries, to give voice to so many â€˜vili e meccaniciâ€™. One important step in this direction could be a new (historically and geographically oriented) reading of the AIS maps.
Formation of Technological Competence in Students: Essence and Content

This article reveals the essence and content of formation of technological competence in students.
Sistem Pakar dalam Mengidentifikasi Minat Vokasi Menggunakan Metode Certainty Factor dan Forward Chaining

Developing an expert system application in providing an overview of the interests of students to help decision making interests in the vocational field so that they are right on target in choosing a major. In this study, using the Certainty Factor method and the Fordward Chaining method where this expert system can help experts identify vocational interests based on the characteristics of vocational interest in students. The personality types used to determine the type of vocational interest are Tangible, Thinking, Flexible, and Entrepreneur. The results of system calculations with expert decisions are worth 80% of the 4 test data, so a good level of accuracy is obtained. The resulting expert system can help students quickly provide an overview of vocational interest in making department decisions in continuing higher education, can carry out online consultations, document files, and can be used as a consultation portal for students.
Convolutional and Long Short-term Memory Neural Network for Earthquake Detection

Earthquake detection is a foundation and critical work link in the study of seismology.Traditional detection algorithms have the disadvantages of low detection sensitivity, low computational efficiency, and poor general applicability.In this paper, we develop a novel earthquake detection method based on convolutional neural network (CNN) and long short-term memory network (LSTM).It extracts the high-level features in the seismic signal and learns the time-frequency characteristics of the main phase by recording the three component data on a single station.We train the network using 4932 waveform windows (2236 positive windows and 2696 negative windows) recorded in Wenchuan, China, with a window size of 30s.Using the trained model to test a continuous waveform for one day, compared to the long-short window energy ratio method (STA/LTA), all manually selected seismic events were successfully detected.To explore the impact of different window sizes and LSTM layers on the detection results, we use a larger dataset (derived from Oklahoma, USA) for network training.The test results show that our method not only has a good generalization ability for cataloging events, but also detects micro-seismic events that are not included in the catalog.The detection accuracy of cataloging events reaches 100%.Our results indicate that this method has fast, efficient and scalable superior performance in earthquake detection.
Multi-Level Credit Card Fraud Detection

Fraud detection in credit card transactions is one of the major requirements of the current business scenario due to the huge amount of losses associated with the domain. This work presents a multi-level model that can provide highly effective fraud detection in credit card transactions. The model is based on the amount for which the transaction is committed. The proposed MLFD model identifies the nature of the transaction and depending on the significance level of the transaction, the appropriate learning model is selected. Experiments were performed with the standard benchmark data and comparisons were performed with existing model in literature. Results shows that the proposed model exhibits high performance compared to the existing model.
Semantic expansion of search queries

One of the major challenges in Web search pertains to the correct interpretation of users' intent. Query Expansion is one of the well-known approaches for determining the intent of the user by addressing the vocabulary mismatch problem. A limitation of the current query expansion approaches is that the relations between the query words and the expanded words is limited. In this thesis, we capture users' intent through query expansion. We build on earlier work in the area by adopting a pseudo-relevance feedback approach; however, we advance the state of the art by proposing an approach for feature learning within the process of query expansion. In our work, we specifically consider the Wikipedia corpus as the feedback collection space and identify the best features within this context for term selection in two supervised and unsupervised models. We compare our work with state of the art query expansion techniques, the results of which show promising robustness and improved precision.
Engrossing Prosecution of Code Smells Type Identification and Rectification using Machine Learning AdaBoost Classifier

Software code smells are the structural features which reside in a software source code. Code smell detection is an established method to discover the problems in source code and reorganize the inner structure of object-oriented software for improving the quality of such software, particularly in terms of maintainability, reusability and cost minimization. The developer identified where the code smell is identified and rectified within a system is a major challenging issue. The various code smell detection technique has been designed but it failed to classify the code type and minimum rectification cost. In order to perform classification with minimum cost, an efficient technique called Machine Learning Ada-Boost Classifier (MLABC) technique is introduced. The MLABC technique improves the software quality by identifying and rectifying the different types of software code smell in source code. Initially, MLABC technique uses decision tree as base classifier to identify the code smell type. The decision tree is used to classify the code smell type based on the certain rule. After that, the base classifiers are combined to make a strong classifier using adaboost machine learning technique. The output of strong classifier is used to identify the code smell type. Finally, the code smell type rectification is performed by applying the refactoring technique where the code smell is identified with minimum cost and space complexity. Experimental results shows that the proposed MLABC technique improves the software code quality in terms of code smell type identification accuracy, false positive rate, code smell type rectification cost and space complexity with the source code.