Reviewerly/exHarmony huggingface dataset:
SITIRAN SKRIPSI MAHASISWA PRODI DESAIN KOMUNIKASI VISUAL BIDANG PERANCANGAN MEDIA UNIVERSITAS NEGERI MALANG

ABSTRAK Dalam penelitian yang dilakukan tidak akan terlepas dari referensi literatur yang mutakhir. Penelitian ini dilakukan untuk mengkaji penggunaan literatur pada skripsi mahasiswa Desain Komunikasi Visual Universitas Negeri Malang periode kelulusan tahun 2015-2017. Tujuan dari penelitian ini untuk mengetahui karakteristik jenis literatur, keterbaruan literatur yang dilihat dari keusangan literatur dan sejauh mana subjek mempengaruhi suatu penelitian. Pada penelitian ini menggunakan metode analisis kuantitatif deskriptif dengan menggunakan purposive sampling. Analisis kajian bibliometrika berupa analisis sitiran, analisis paro hidup. Pedoman analisis subyek menggunakan pedoman Tajuk Subjek Perpustakaan Nasional Republik Indonesia 2011 untuk mengetahui subjek verbal. Total sitiran pada penelitian ini 709 sitiran, dengan 562 sitiran (86, 48%) Bahasa Indonesia dan 88 sitiran (13,52%) Bahasa Inggris. Jenis literatur 502 judul buku (77,23%) yang paling banyak disitir. Nilai keusangan literatur yang disitir adalah 5 tahun atau di bawah tahun 2012 adalah titik keusangan literatur. Sedangkan subyek terbanyak adalah Periklanan, 120 kali subjek (13,94%). Kata kunci : analisis sitiran, keusangan literatur, analisis subjek, skripsi ABSTRACT In the research carried out it will not be separated from the reference of current literature. This research was conducted to examine the use of literature in the thesis of Visual Communication Design students at the State University of Malang in the 2015-2017 graduation period. The purpose of this study is to study the characteristics of the type of literature, the readiness of literature that is read from the obsolescence of literature and which subjects influence research. In this research using quantitative descriptive analysis method and using purposive sampling. Analysis of bibliometric studies consists of citation analysis, half-life analysis. The guideline for subject analysis used the National Library of the Republic of Indonesia Subject Subject Guide 2011 for subjects of verbal lessons. Total citations in this study were 709 citations, with 562 citations (86, 48%) in Indonesian and 88 citations (13.52%) in English. The type of literature 502 book titles (77.23%) are the most cited. The value of obsolescence of the cited literature is 5 years or below 2012 is the point of obsolescence of literature. While the most subjects were Advertising, 120 times the subject (13.94%). Key word : analysis of citation, literature obsolescence, analysis of subject 1 1 1 1 MicrosoftInternetExplorer4 0 2 DocumentNotSpecified 7.8 磅 Normal 0
Permeability: Catalyst for Connection, Creation and Innovation

Project briefing for the Coalition for Networked Information (CNI) Spring Meeting April, 2019 in St Louis, Missouri
Applicering och utvärdering av en konsekvensanalysmetod för beroenden

Dependencies between critical infrastructures are often complex by nature, which makes it hard to assess both their criticality and their impact level. These are the overarching reasons behind the development of a newly proposed KE-method at Lund University (at CenCIP) in cooperation with the Swedish Civil Contingencies Agency (MSB) in 2018/19. The purpose of the method is to map, analyze and visualize direct and indirect consequences due to floods, but aiming to be applicable for other sorts of threats and hazards. Since the KE-method has not earlier been fully tested, we apply it for Karlshamns municipality in order to enable identification of possible improvements and determine the applicability of the method. To obtain this, an evaluation method for impact assessment methods had to be developed. Hopefully this developed evaluation method will be applicable also for other types of similar methods. The evaluation determined that there is room for some adequate improvements for the KE-method. These were increased practical support together with some suggestion of more detailed structural improvements. It is finally concluded in this thesis that the KEmethod is a well-functioning dependency impact assessment method which is applicable in a Swedish municipality since it is considered to be both relevant and user-friendly. (Less)
DESIGN AND IMPLEMENTATION OF “PRESENT BLOCK CIPHER ALGORITHM”

Due to the vast development of information technology, it is very necessary to protect the sensitive information via encryption and decryption which is becoming more and more important in daily life. Cryptographic operation in devices which use little memory and a low power processor causes system overhead. Thereby implementing cryptographic operation is necessary nowadays. Today increases any wireless communication security is crucial during data transmission. for encryption and decryption of data we use “PRESENT BLOCK CIPHER ALGORITHM “algorithm to enhance the security in FPGA by creating a module dedicated for encrypting the data transmitted by FPGA. Once the connection is established between two machines then the encrypted message is sent from the transmitter to receiver and output is observed. The algorithm “PRESENT” is a block cipher lightweight algorithm of reduced size and execution It uses substitution and permutation blocks of only 4 bits also the key size is small as compared to other algorithms. It uses a block size of 64 bits and the key size is 80 bits or 128 bits. In total, the number of rounds for a PRESENT block cipher is 31.The project presents a security which can be used by ATM, Smart TV ,WiFi, smart phone. Now days security is very important so we design present algorithm.The project presents a security which can be PRESENT is a block cipher algorithm lightweight type highly used since it has easy implementation in both hardware and software . Its implementation in hardware can be done in some of the smallest FPGA's on the market.
The Similarities and Differences to English Independent Study in the University and Public Libraries: Comparative Study Between Indonesia and Japan

This current study was conducted to observe how libraries in Japan and Indonesia are similar and different in regards to supporting Eng-lish Independent Study (EIS); the investigation was done in both public and university libraries in Chiba and Kyoto (Japan) and Malang (Indonesia). To arrive at the findings, comparative study was conducted by doing site visits to the libraries in Japan and Indonesia; the data collection was done through interview, observation and visitor survey. This study revealed that some indirect supports to EIS activi-ties are detected such as through the availability of physical and digital English collections accessible both online and offline. The simi-larities found in the investigated libraries covered the unavailability of special English section, the integrated arrangement of English resources along with other resources, challenges in detecting various EIS activities, procurement planning without special attention to English resources, and the same types of collections. The differences of the investigated libraries in both countries were in terms of the arrangement of collections, the procurement of collections, the number of EIS materials—which was relatively higher for Japanese li-braries, and the accessibility of collections. The study was ended by proposing some suggestions for better support of EIS in libraries, such as by considering English based material procurement, establishing special EIS section or giving special tag to EIS collection, and integrating better ICT systems.
LibGuides: Unleash Inner Genius: Computers

Geniuses keep journals…we’re ALL geniuses we just need to get organized! Find here tips, tools, and techniques to track and build upon your curiosity, learning, and ideas. Whatever your interest, whatever your talent, the library supports it.
Study on gesture recognition based on IIDTW algorithm

When the length of sampling data sequence is too large, the method of gesture recognition based on traditional Dynamic Time Warping (DTW) algorithm will lead to too long calculation time, and the accuracy of recognition result is not high.Support vector machine (SVM) has some shortcomings in precision, Edit Distance on Real Sequences(EDR) algorithm does not guarantee that noise suppression will not suppress effective data.A new method based on Improved Interpolation Dynamic Time Warping (IIDTW)algorithm is proposed to improve the efficiency of gesture recognition and the accuracy of gesture recognition.The results show that the computational efficiency of IIDTW algorithm is more than twice that of SVM-DTW algorithm, the error acceptance rate is FAR reduced by 0.01%, and the error rejection rate FRR is reduced by 0.5%.Gesture recognition based on IIDTW algorithm can achieve better recognition status.If it is applied to unlock mobile phone, it is expected to become a new generation of unlock mode.
Getting Started with Play 2

After reading the introductory section on Play 2, you should now have an idea of the capabilities of Play Framework and how it can accelerate Java web development. This chapter is about
A new era of Information Technology with Quantum Computing

The basics of quantum computing are explained based on quantum mechanics superposition and entanglement effects. The technological characteristics of the quantum computers currently available are described, as well as the programming environment qiskit. The foreseeable fields of application of quantum computing are then reviewed.
Howto setup Python in Pop!_OS 19.10 or Ubuntu

A new OS, another two hours wasted. Pop!_OS 19.10 comes with Python3.7rc5, which is nice but my project requires 3.6 just now. As you know
PENGEMBANGAN MODEL BAHAN AJAR BAHASA INGGRIS BERBASIS PENDEKATAN WHOLE LANGUAGE UNTUK KELAS III SEKOLAH DASAR

This Research and Development aimed to produce English teaching materials for elementary school 3rd grade student. The study involved third-grader students of SDN Penjaringan 03 with total of 32 students. This study used Rowntree development models combined with Martin Tessmer models. This study passed expert review stage, one-to-one evaluation, small group evaluation, and field test. Expert reviews involved of English study expert, media expert, and instructional design expert showed the average percentage for this stage was 95,5%. The average percentage results for small group was 94%, while the average percentage result for field test was 90%. The conclusion for this study shows that the product of English Teaching Materials Model Development Based on Whole Language Approach for Elementary School 3rd Grade achieved very good criteria.
Республика Корея: опыт и задачи цифровой трансформации

The article describes the digital transformation of the Korean economy in the framework of the fourth industrial revolution. The essence of the reform is to promote an ecosystem of innovative growth based on digital transformation, digitalization of social infrastructure, industry and enterprises, as well as responding to anticipated social changes. The reform strategy provides, in particular, a significant expansion of the practice of creating smart factories and ensuring the development of the human potential necessary for this.
A NOVEL APPROACH FOR ENTITY EXTRACTION IN CODE MIXED DATA

In the field of Natural Language Processing (NLP), Named Entity Recognition (NER) is one of the major task. The main challenge in this extraction is to extract Entities that lies in the inadequate information available in a tweet. There has been plenty of work done on this domain of entity extraction but it was mainly focused on popular languages such as English. In general extraction of entities from an informal text makes it difficult and for data that is written in two or more languages (code-mixed) makes it more difficult. In this paper the author has proposed the Machine Learning algorithms like Decision tree, and Conditional Random Field (CRF) with efficiencies of 60% and 76% respectively. The dataset was collected from FIRE-2016.
Detection of weak signals in weakly structured data masses

This paper is related to a project aiming at discovering weak signals from different streams of information, possibly sent by whistleblowers in a platform as GlobalLeaks. The study presented in this paper tackles the particular problem of clustering topics at multi-levels from multiple documents, and then extracting meaningful descriptors, such as weighted lists of words for document representations in a multi-dimensions space. In this context, we present a novel idea which combines Latent Dirichlet Allocation and Word2Vec (providing a consistency metric regarding the partitioned topics) as potential method for limiting the “a priori” number of cluster k usually needed in classical partitioning approaches. We proposed 2 implementations of this idea, respectively able to : (1) finding the best k for LDA in terms of topic consistency ; (2) gathering the optimal clusters from different levels of clustering. We also proposed a non-traditional visualization approach based on a multi-agents system which combines both dimension reduction and interactivity.
Renyi divergence and non-deterministic subsampling in Rigid Image Registration

The successful application and reported robustness of Mutual Information both in rigid and nonrigid image registration over the last decades gave rise to an ongoing research on other information based similarity metrics emanating from Renyi Divergence. To the best of our knowledge however, this is the first paper studying the effects of Renyi parameter in combination with a subsampling factor in image registration accuracy. To this end, a series of experiments are presented with respect to the effect of Renyi's parameter and the subsampling factor in registration accuracy. Our results show that the increase of the Renyi parameter and the percentage of the pixels used leads, on average, to the reduction of the registration error.
Study IV: Noreland trio

Stimulated by Daniel Noreland's Numerical Techniques for Acoustic Modelling and Design of Brass Wind Instruments.
A Moral Consensus Mechanism for Autonomous Driving: Towards a Law-compliant Basis of Logic Programming

Research into autonomous vehicles is making progress. While implementation is progressing through machine learning and efficient sensor technology, one key challenge remains dealing with moral disputes. In general, traffic requires for moral decisions that might even decide on the life or death of participants. While people make intuitive decisions in accidents, a decision of an autonomous vehicle is made already at the programming stage. Thus, a concrete handling for implementation is needed. Due to a lack of legislation, this is still missing and prevents car manufacturers from a practical solution. The paper at hand addresses this problem by presenting a consensus mechanism, combining moral convictions, legislation, and programming guidelines. Based on a study of dilemma situations, moral principles of the ‘correct action’ of autonomous vehicles are derived. Of four principles, we confirm one, reject two, and propose one for further research investigation to form a basis for jurisdictions.
Do you hear what I hear? Audiation and the Compositional Process

When Igor Stravinsky was asked if he hears music when he composes, he replied it’s sometimes more a question of knowing how it sounds. Alternatively, John Cage commented ‘I don’t hear music when I write it. I write in order to hear something I haven’t yet heard. My writing is almost characterised by having something unusual in the notation. The notation is about something that is not familiar.’These comments by two leading 20th Century composers would seem to undermine the notion that music is initially ‘heard’ and subsequently transcribed, potentially challenging the popular view of the compositional process. Of course, both these composers employed significantly different compositional strategies. However, in each case there is arguably some kind of apprehension of sound in the mind of the composer to be translated through notation into performance. What is the relationship, therefore, between what is heard and what is written, and how much could notation be said to mediate this process? Further, what is the nature of what is heard and to what degree is this auditory musical image informed by its own possibility in notation, by a habit of thought? Can we imagine a music that can’t be notated, for example? If so how would we write it? Can notation itself create a useful distance between what is heard and how a score becomes manifest, with a view to finding new forms of expression?The dialogue between the auditory and what is notated is clearly more complex than at first appears. The 20th Century saw a decline in a common musical language and an increase in the diversity of compositional techniques and new forms of generative processes/notational strategies, often raising doubt as to the role of audiation in the creative discourse. However, the use of such compositional processes can often lead to the discovery of new musical potential and material, beyond what might in the conventional sense be said to have an audiative origin, but which is nevertheless defined by an internal musical ear - an analytical audiative process. This paper examines these issues in relation to my own work as a composer, which seeks to explore the complex relationships obtaining between what might be said to exist in the mind of a composer - an initial apprehension of sound, and the development of meaningful compositional strategies aimed at capturing the reality of an auditory musical image through notation.
EXPONENTIAL STABILITY OF HOPFIELD-TYPE DELAY IMPULSIVE DISCRETE NEURAL NETWORKS AND COMPUTER SIMULATION

A discrete Hopfield-type neural network with constant delays, instan-taneous switching topologies at certain times and time variable connection weights isstudied. Some criteria for exponential stability are derived. The obtained results areillustrated on an example with different activation functions such as tanh, Swish, andthe error function. The example is computer realized by coding the correspondingalgorithms for calculating the values of the solution for each step.
Detection of spam review on mobile app stores, evaluation of helpfulness of user reviews and extraction of quality aspects using machine learning techniques

As mobile devices have overtaken fixed Internet access, mobile applications and distribution platforms have gained in importance. App stores enable users to search and purchase mobile applications and then to give feedback in the form of reviews and ratings. A review might contain critical information about user experience, feature requests and bug reports. User reviews are valuable not only to developers and software organizations interested in learning the opinion of their customers but also to prospective users who would like to find out what others think about an app.Even though some surveys have inventoried techniques and methods in opinion mining and sentiment analysis, no systematic literature review (SLR) study had yet reported on mobile app store opinion mining and spam review detection problems. Mining opinions from app store reviews requires pre-processing at the text and content levels, including filtering-out nonopinionated content and evaluating trustworthiness and genuineness of the reviews. In addition, the relevance of the extracted features are not cross-validated with main software engineering concepts.This research project first conducted a systematic literature review (SLR) on the evaluation of mobile app store opinion mining studies. Next, to fill the identified gaps in the literature, we used a novel convolutional neural network to learn document representation for deceptive spam review detection by characterizing an app store review dataset which includes truthful and spam reviews for the first time in the literature. Our experiments reported that our neural network based method achieved 82.5% accuracy, while a baseline Support Vector Machine (SVM) classification model reached only 70% accuracy despite leveraging various feature combinations.We next compared four classification models to assess app store user review helpfulness and proposed a predictive model which makes use of review meta-data along with structural and lexical features for helpfulness prediction.In the last part of this research study, we constructed an annotated app store review dataset for the aspect extraction task, based on ISO 25010 - Systems and software Product Quality Requirements and Evaluation standard and two deep neural network models: Bi-directional Long-Short Term Memory and Conditional Random Field (Bi-LSTM+CRF) and Deep Convolutional Neural Networks and Conditional Random Field (CNN+CRF) for aspect extraction from app store user reviews. Both models achieved nearly 80% F1 score (the weighted average of precision and recall which takes both false positives and false negatives into account) in exact aspect matching and 86% F1 score in partial aspect matching.
Exploring the Impact on the Consumer decision Making Proess: The Application of Virtual reality Technoloy in Tourism

The following thesis has been written with the aim of identifying if virtualreality could potentially have an impact on consumer behavior in tourism.Answering this question could have an impact on the application of thetechnology as a marketing tool. Due to the fact that there is limitedknowledge available on this topic so far, the research is considered to beexploratory. To gain first insights into the reactions of consumers whenbeing exposed to the technology, their reactions were evaluated using aqualitative approach.This thesis is consisting of four parts. Firstly, the relevance of the topic willbe discussed. The following, theoretical part is dealing with tourism,consumer behavior and virtual reality technology. Thereafter the empiricalpart is establishing hypotheses in a first stage to later rank and evaluatethese hypotheses further. To conclude the thesis, the paper will bepresenting conclusions and a future outlook.After the lecture of the thesis you will learn what potential implications theusage of virtual reality technology can have when being used as amarketing tool in tourism. This knowledge of potential implications can laythe foundation for further research and shows the predominantconsiderations that should be made when dealing with the topic of virtualreality in tourism marketing.
LibGuides: Working Remotely: COVID-19 Latest Publications

MCW Libraries will continue to provide high quality services and resources where ever you may be.
Electric Guitarists and the Digital Age : A study on guitar player’s thoughts and attitudes towards tube amplifiers and high tech amp simulators

Tube amplifiers were used extensively in rock music since the 1960’s and through those years, digital alternatives to the tube amplifier were also being developed. Today, a plethora of high quality ...
Recommendation Analysis of Candidates for Student Union Leadership Based on Data Mining Techniques

Recommender systems are ever-trending research that can be applied in various domains. Voting for the preferred candidates has to be an issue in a student union environment. A Candidate recommendation system for student union leadership provides the means to students especially the freshers with their preferred student union leaders selection process with a good number of leadership attributes. In this paper, we proposed a recommender system that understands what the information seeker needs and through simple interface generates recommendations for him/her accordingly which provides information to the information seeker to vote for the preferred candidates into the student union leadership.