Reviewerly/exHarmony huggingface dataset:
Case Based Construal using Minimal Features to Decipher Ambiguityin Punjabi Language

A minimal feature set is taken in order to find the closest context of the given ambiguous word by using case based construal model. The model proposed in this paper uses case-based reasoning to sort out the similar cases with vectors of size two (bigram), three (trigram) and four (n-gram) using Euclidean similarity function. These cases are then subjected to three different classifiers, namely - Bayes, k-Nearest Neighbor, and Decision Tree, to decipher the ambiguity.Vectorization eases the process of disambiguation as compared to when full sentences are processed. The similarity function helps to find similar cases of the given ambiguous word whereas the three classifiers helps in finding the right context of the given ambiguous word. Upon experimentation, Decision Tree classifier has achieved an accuracy of 84.88% using pre-bigram vectors.
Performance Evaluation of Apache Storm With Writing Scripts

With the exponential growth of stream data emanating from a variety of sources, today, big data presents a new era in data exploration and usage. The understanding of the performance of real-time stream data processing technologies has become a key pre-requisite while considering any deployment. Although many technologies for stream data analytics exist, little is known about the impact of writing scripts on their performance. Using a MapReduce programming model on a pseudo cluster, we conduct a word count, experimental evaluation of Apache Storm using five writing scripts; English, Arabic, Hindi, Chinese and Japanese. We define our word count as the number of time a word is written in a body of text. Static and structured data made up of 300 English sentences is translated into the scripts under study and loaded into Apache Storm. The results show that Apache Storm analyzes, English, Arabic and Hindi script sentences with ease as compared to those written in Chinese and Japanese script. Apache Storm also executes and distinguishes individual words and performs a word count on English, Arabic and Hindi sentences faster than those written in Chinese and Japanese. However, in terms of processing, the reverse is true, sentences written in Chinese and Japanese are processed faster than those written in English, Arabic and Hindi scripts.
Integration and use of an AR display in a maritime helicopter simulator

Operating a helicopter in off-shore wind parks in DVE from clouds or fog can endanger crew and material due to the presence of unseen obstacles. Utilizing on-board sensors like Lidar or radar one can sense and record obstacles that could be potentially dangerous. One major challenge is then to display the resulting raw sensor data in a way that the crew, especially the pilot can make use of without distracting them from their actual task. Augmented and mixed reality applications are thought to play an important role here. By displaying the data in a see-through helmet mounted display (HMD) the pilot can be made aware of obstacles that are currently obscured by degraded visual conditions or even parts of the own helicopter. This can be accomplished in one HMD. No attention sharing between the outside view and a headdown instrument is necessary. DLR is continuously aiming at testing and evaluating both flight-proof and consumer grade HMDs. One particular widely known system is the Microsoft HoloLens. DLR will integrate this low-cost HMD into their test helicopter ACT/FHS. For this, as a first step a Microsoft HoloLens was integrated into DLR's simulator AVES. In this paper the integration process is detailed. The simulation capabilities are described, especially for conformal, open-loop Lidar sensor data. Furthermore, first concepts of the display format are shown, and strengths and drawbacks of the HoloLens in a cockpit environment are discussed.
A Novel Near Lossless Image Compression Method

A novel near lossless image compression method is proposed in this paper. In the proposed method, a redundant representation of the image is firstly obtained by pixel level shifting and then partitioned into image blocks with the same size. Next, the image blocks are classified into smooth image blocks and non-smooth image blocks. For the smooth image blocks, improved block coding which includes mean residual error is utilized for pixel rectangles with the same pixel value in each to remove the redundancy. Lastly, the whole image is scanned by efficient image scanning that only one pixel is scanned for each pixel rectangle and then compressed by Huffman coding. Simulation results indicate that the proposed method has good performance compared with traditional lossless/near lossless image compression methods.
Multiuser optical information authentication using photon counting in spiral phase transform domain

In the present time, the substantial advances in communication technology have prompted many challenges including secure transmission of sensitive information. Optical techniques have also been studied extensively for information security and validation. In this paper, we present a new optical information authentication techniques using photon counting in spiral phase transform (SPT) domain. SPT is used for the optical propagation. For SPT, a modified spiral phase function is utilized which defines the order of the transform. In the encryption process, an asymmetric approach is used, in which, first the input image is combined with the random phase mask and Fresnel propagated with a distance, d to get the intermediated image. Further, the polar decomposition (PD) is applied to the intermediate image which will give a rotational matrix and two symmetric matrices. The symmetric matrices can be used for authenticating the original information and serve as the private keys. The final encrypted image is obtained by performing the SPT of a particular order on the rotational matrix after PD. The encrypted image is made sparse by randomly retaining few pixels using photon counting approach. For authentication, the nonlinear correlation approach is studied, which offer better correlation peaks with fewer sparse-based complex samples. The numerical simulation results have been presented in support of the validity and effectiveness of the proposed technique. The proposed method deals with the optical encryption, authentication and also overcomes the limitations of data storage issue.
Western Name Authority File: A Pilot Regional Name Authority Project

The prospect of authority control in digital libraries creates unique challenges. Digital library systems and software often do not support integrated authority control, which can create issues in consistency for personal and corporate names representation in descriptive metadata. Standard practice for library metadata is to use existing controlled vocabularies such as the Library of Congress Name Authority File, but what can be done if the personal names and corporate bodies in local or regional digital collections are not represented in the Library of Congress? As digital collection managers look towards providing metadata for regional and statewide shared repository systems and national digital collection aggregators like the Digital Public Library of America (DPLA), issues in digital collection authority control are magnified. This article explores the process in creating a shared regional authority file of personal names and corporate bodies existing in digital collection metadata records in several institutions throughout the Western United States. Steps in the process included reviewing data models, metadata collection, metadata deduplication and wrangling, vocabulary reconciliation, and data enhancement. Details on the process in making the Western Name Authority File accessible to the public and assessing project outcomes are included.
Describing Sequential Association Patterns from Longitudinal Microarray Data Sets in Humans

DNA microarray technology provides a powerful vehicle for exploring biological processes on a genomic scale. Machine-learning approaches such as association rule mining (ARM) have been proven very effective in extracting biologically relevant associations among different genes. Despite of the usefulness of ARM, time relations among associated genes cannot be modeled with a standard ARM approach, though temporal information is critical for the understanding of regulatory mechanisms in biological processes. Sequential rule mining (SRM) methods have been proposed for mining temporal relations in temporal data instead. Although successful, existing SRM applications on temporal microarray data have been exclusively designed for in vitro experiments in yeast and none extension to in vivo data sets has been proposed to date. Contrary to what happen with in vitro experiments, when dealing with microarray data derived from humans or animals the "subject variability" is the main issue to address, so that databases include multiple sequences instead of a single one. A wide variety of SRM approaches could be used to handle with these particularities. In this study, we propose an adaptation of the particular SRM method "CMRules" to extract sequential association rules from temporal gene expression data derived from humans. In addition to the data mining process, we further propose the validation of extracted rules through the integration of results along with external resources of biological knowledge (functional and pathway annotation databases). The employed data set consists on temporal gene expression data collected in three different time points during the course of a dietary intervention in 57 subjects with obesity (data set available with identifier GSE77962 in the Gene Expression Omnibus repository). Published by Vink [1], the original clinical trial investigated the effects on weight loss of two different dietary interventions (a low-calorie diet or a very low-calorie diet). In conclusion, the proposed method demonstrated a good ability to extract sequential association rules with further biological relevance within the context of obesity. Thus, the application of this method could be successfully extended to other longitudinal microarray data sets derived from humans.
Flight Chair

In future, emergency services will increasingly use technology to assist emergency service dispatchers and call taker with information during an emergency situation. One example could be the use of drones for surveying an emergency situation and providing contextual knowledge to emergency service call takers and first responders. The challenge is that drones can be difficult for users to maneuver in order to see specific items. In this paper, we explore the idea of a drone being controlled by an emergency call taker using embodied interaction on a tangible chair. The interactive chair, called Flight Chair, allows call takers to perform hands-free control of a drone through body movements on the chair. These include tilting and turning of one's body
The Academy of Sciences Library – 300 years serving the readers

The article presents a paper delivered at the International Conference of the Russian Academy of Sciences Library (BAN) on November 23, 2018. The purpose of the paper is to capture the image of the BAN and its reader at key moments of their life over three centuries with method of portraying. The author gives three portraits of the BAN and its readers. The first portrait (1718– 1917) shows birth and formation of the library as a national and academic book depository. It emphasizes influence of the authorities in strengthening international relations with libraries in Western Europe. It notes the active role of readers in its development. The second portrait (1917– 1991) is devoted to the BAN as the basis for the development of the Russian science that occupied an honored place in the world and gained respect for the works of its readers. The ideology of the BAN was focused on their scientific interests. The article characterizes the role of the library in the years of the Great Patriotic War, the new readership and the specificity of readers' requests. It provides information about the readers of the BAN in the postwar years. It considers the activities of the library and its readers in eliminating the consequences of the February 1988 fire. The third portrait (1991–2018) characterizes the BAN and its readers in modern conditions. Attention is paid to the fact that the library carefully preserves the traditions and continues to remain a unique book depository not only to the national, but also tothe world science and culture.
A Secure Reversible Data Hiding Scheme for Digital Images using Random Grid Visual Secret Sharing

A secure data hiding scheme based on visual secret sharing and histogram shifting is proposed. Visual secret sharing is used to encrypt the secret image before hiding it into the host image. Encryption is performed by dividing secret image into n shares. Out of these shares, n-1 are embedded in the host image, and one is stored as a secret key share with Trusting Authority. At the receiver side, the k out of these n-1 shares are extracted from the image. The complete secret data can be revealed only when the key share would be superimposed with the k retrieved shares. Random grid technique along with XOR operation has been used to create shares, resulting in no pixel expansion and maximum contrast for the extracted image. The shares have been embedded in the cover image by using the concept of histogram shifting.
Relation between Transit Oriented Development (TOD) and the effect of electromagnetic field with fengshui on residential planning

The concept of Transit Oriented Development (TOD) began to emerge, this has resulted in the design of buildings that cross railways and roads. The method used is the analysis of TOD theories, electromagnetic fields and fengshui to see the relation between the three things and the planning of residential buildings on it: 1) What is the relation between TOD and electromagnetic fields; 2) How does the Electromagnetic field relate to fengshui; 3) What is the connection between TOD and fengshui. Understanding these three links will result in residential planning that provides optimal benefits for residents. The conclusion is: Electromagnetic fields that occur as a result of the movement of transport vehicles, especially transportation related to the rail, cause unstable electromagnetic fields that can hinder the occupants from growing optimally, so structuring TOD with good and true fengshui will provide higher benefits for its inhabitants. The ease of transportation due to the meetings from various modes of transportation at that point causes the people who live in TOD to have a shorter travel time for their travel activities, by getting "more" time, of course the level of productivity can be higher so that as a result, the level of welfare will be well. After knowing the danger of unstable (氣) qi due to the influence of electromagnetic fields that occur due to rail or road trajectories, hopefully TOD stakeholders can arrange their properties properly and correctly so that users can enjoy good fengshui and display optimal life performance for the sake of a more prosperous Indonesia.
Smart Information Systems in Cybersecurity

This report provides an overview of the current implementation of SIS in the field of cybersecurity. It also identifies the positive and negative aspects of using SIS in cybersecurity, including ethical issues which could arise while using SIS in this area. One company working in the industry of telecommunications (Company A) is analysed in this report. Further specific ethical issues that arise when using SIS technologies in Company A are critically evaluated. Finally, conclusions are drawn on the case study and areas for improvement are suggested.
Explanations in Artificial Intelligence Decision Making

The opacity of AI systems' decision making has led to calls to modify these systems so they can provide explanations for their decisions. This chapter contains a discussion of what these explanations should address and what their nature should be to meet the concerns that have been raised and to prove satisfactory to users. More specifically, the chapter briefly reviews the typical forms of AI decision-making that are currently used to make real-world decisions affecting people's lives. Based on concerns about AI decision making expressed in the literature and the media, the chapter follows with principles that the systems should respect and corresponding requirements for explanations to respect those principles. A mapping between those explanation requirements and the types of explanations generated by AI decision making systems reveals the strengths and shortcomings of the explanations generated by those systems.
A coarse-grained password model with memorable unit-based recurrent neural networks

Passwords will continue to be the most prevalent form of authentication in the foreseeable future. But passwords often consist of some common segments which are easy to be predicted and attacked. Lots of methods have been proposed to describe password construction by regarding passwords as sequences of characters or segments. They are mainly based on statistical language models, for example Markov models and Probabilistic Context-Free Grammars. Recently, some researchers show that character-level recurrent neural networks can often outperform the previous methods. However, passwords usually consist of coarse-grained memorable units rather than fine-grained random characters. In this paper, we propose a memorable unit-based recurrent neural networks to model password construction. We first split passwords into memorable units (i.e., segments) with seven kinds of patterns and further split non-semantic pure letter and digit units into shorter units. Then, we build a unit-level recurrent neural network to predict the next unit with previous context units. Experiment results demonstrate that our coarse-grained unit-level model can reduce the search space during generating password guesses, which means our model obtains higher efficiency than the fine-grained character-level model.
Dataset retrieval system based on automation of data preparation with dataset description model

Summary Data preparation is the most effortful task in the process of statistical learning. Many studies related to data mining are performed without data preparation by assuming that qualified datasets are already prepared. It may hide useful patterns of data, which can result in poor performance and incorrect learning. Automation of data preparation can solve these problems. For automation of data preparation, a few issues should be considered, such as flexible expression of requirements according to the purpose of the learning model, accessibility to data sources, and performance degradation due to automation. In this paper, we propose a dataset description model that can express the requirements for data processing and dataset retrieval system based on automated data preparation. The proposed system makes it possible to provide good quality datasets for statistical learning applications using data preparation methods such as data acquisition, refinement, and organization. In the experiment, we demonstrate that the proposed system doesn't have performance loss as compared to the existing manual systems. Moreover, the quality of the datasets are also improved by using the proposed system.
Evaluation of Skeletonization Methods for Document Images with Rotation States

Images skeletonization is an important process for many applications of pattern recognition. Currently, lot of skeletonization methods have been proposed to dealwith usual skeletonization challenges such as nosy contour, topology preserving, and two-pixel thinness problems. Unfortunately, no one among them focused in producinga fix skeleton with different rotation states. This paper presents an evaluation of set of recent and well-knownskeletonization methods for binary document images to deal with the rotation challenge. We implemented and tested the Bataineh, Abu-Ain, Huang, and K3M methods overdocument images with several rotations. The DIBCO2010, H_DIBCO2010_GT benchmark dataset with benchmark measurements are used to evaluate the performance of the involved methods. The experiments showed a various results based on the adopted measurements.
Chapter 5. Classification of nominal compounds containing mimetics

In Japanese, some nominal compounds have mimetic components (Nominal Compounds with Mimetics (NCMs)) (e.g., zaazaa-buri [mimetic(the sound of heavy rain)-a fall(from the sky)] ‘a downpour’). This paper examines how mimetics participate in word-formation of nominal compounds, applying Construction Morphology. Examination of representative NCMs indicates: (i) NCMs are mostly right-headed, although some are double-headed, and (ii) mimetics combine with the types of nouns that combine with non-mimetic components. Given this, the paper proposes NCMs are part of the inheritance hierarchy for nominal compounds; specifically, their top node diverges according to the head position, building on Booij (2010: 7). The hierarchy consists of different constructional schemas, such as <[x i-hada] nk ↔ [hada ‘skin’ with attribute SEMi]k>, wherein the variable x can be replaced by a mimetic, as in gasagasa-hada ‘rough skin’, or a non-mimetic, as in yawa-hada ‘soft skin’. The paper argues that mimetics are an integral part of nominal compound word formation, enriching lexical varieties of nominal compounds. The Construction Morphology representational system proves useful to indicate where NCMs appear in the word network.
Technical objects' ecological efficiency indicators control

Traditional automatic control systems do not solve the task of limiting the harmful effects of technical objects on the environment. The problem is to increase the effectiveness of means of its protection against the harmful effects of industry. Relevant is the use of indicators of environmental performance of technical objects as controlled parameters. A new approach to the control of technical objects is proposed. As the main control parameter it proposed to adopt the level of their ecological efficiency. Complicating circumstances of solving the problem is the insufficient knowledge of the factors of harmful effects on objects of living nature, their intensity, interrelation, mechanism, strength, and dynamics of exposure. Improving the economic efficiency of technical objects leads to an increase in their ecological efficiency. The solution to the problem is facilitated by the fact that traditional ACS should be left in action, adding to them an ecological efficiency control component. Heat-powerengineering has a large impact on the environment through emissions and discharges of harmful substances and heat. To give to ASC the functions of controlling the ecological efficiency of the boiler (for SOy emission), it is necessary to apply an additional, new control loop - regulator of SOy concentration in furnace gases. An urgent task in the use of direct control of the ecological efficiency of boiler-furnace systems is the development and production of physical quantity sensors, reflecting the level of aggressiveness of the source of hazard, working in real time. Direct control of indicators of ecological efficiency is much easier in other branches of industry, in particular, in its food branch, where objects do not have a large-scale complex negative impact on the environment.