Reviewerly/exHarmony huggingface dataset:
In-plane deformation gradient measurement using common-path spatial phase shift shearography

The spatial phase shifting digital speckle pattern shearing interferometry (DSPSI) system has been widely used to determine map of deformation. In this paper a common-path DSPSI setup is introduced for in-plane strain measurement under dynamic loading, using two laser beams with different wavelengths that symmetrically illuminate the test object, and a single detector. The simplicity, stability and efficiency of the arrangement are provided using a glass plate as a shearing device which is capable of tuning the sensitivity continuously. The phase is recovered from a single frame by the Fourier method. In this setup the spatial carrier frequencies can be adjusted independent of the lateral shearing amount. Ultimately, the desired field of view can easily be achieved by simple imaging optics. To validate the feasibility and the flexibility of our technique, the proposed setup is used to evaluate the strain map of an aluminum plate which is deformed under dynamic stress in its plane. Experimental results are presented and discussed.
Visual Analysis of Bird Moving Patterns

In spite of recent advances in data analysis techniques, exploration of complex, unstructured spatial-temporal data could still be difficult. An interactive approach, with human in the analysis loop, represents a valuable add on to automatic analysis methods. We describe an interactive visual analysis method to exploration of complex spatio-temporal data sets. The proposed approach is illustrated using a publicly available data set, a collection of bird locations recorded over an extended period of time. In order to explore and comprehend complex patterns in bird movements over time, we provide two new views, the centroids scatter plot view and the distance plot view. Successful analysis of the birds data indicates the usefulness of the newly proposed approach for other spatio-temporal data of a similar structure.
Entity emotion mining in social media environment

Summary With the thriving of the social media (eg, Sina Microblog and Twitter), the public is keen on expressing their opinions or views on entities as celebrities and products. Emotion mining on social media can be applied in diverse areas, such as helping government or organizations understand people's attitudes so as to make right decisions for business services or political campaigns. One kind of the mainstream approaches for emotion mining are based on topic models, while most of these existing approaches aim at analyzing entire sentiments for the whole Microblog, rather than explicitly assigning the relevant sentiments to the specific entities. In addition, topic model is mainly based on the bag‐of‐words model but ignores the semantic relations of entity‐word in the modeling process, which brings low accuracy and poor interpretability to the sentiment analysis. To overcome the aforementioned difficulties, an Entity Sentiment Topic Model (ESTM) is proposed, which carries out entity‐dependent sentiment analysis. To improve the accuracy of sentiment analysis and enhance the interpretability of the results, ESTM is integrated with relations of entity‐word and a six‐dimensional emotion lexicon as weakly supervised information. Experiments have shown promising results on sentiment classification accuracy, interpretability, and quality of coherent topics for entities.
Model Answer Generation for Word-Type Questions in Elementary Mathematics

There are several categories of word-type questions at elementary level Mathematics. These include addition, subtraction, multiplication, division and ratio. Addition and subtraction problems can be further divided based on their textual information. Those types are change type (join-separate type), compare type, and whole-part type. This paper presents a set of ensemble classifiers to automatically generate model answers for these three types of addition and subtraction problems. Currently, questions with one unknown variable are considered. In addition to the existing data sets, a new data set is created for the training and the evaluation purpose. Our results outperform the existing statistical approaches.
Fuel Level Indication and Mileage Calculator Using Iot

Digital technologies shape our everyday lives for calculating everything. In this paper we proposed to implement a digital way to view fuel target in a vehicle. The simple aspect of this work is to check whether the fuel filled in the vehicle is appropriate to the given price or not, as for the first two pumps the tank is filled with fuel with air and then for the rest of the pumps, tank is filled with fuel. The level of the fuel is calculated with the help of float sensor. When people are moving in the highways or in the hills, they don't know how long will that vehicle will travel. So, we are embedding the mileage calculation with the level detection. With the help of the distance which is displayed in the LCD, the person can aware about how far that vehicle will move further.
Evaluating the Quality of Emergency Reporting Mobile Application on Usage Service Decision

Abstract Emergency Reporting Mobile Application is an android-based application that was built to provide convenience to the public in reporting emergency conditions. This application is divided into 2 end-user applications, there are the sender application and the receiver application. The sender application pages consist of the registration page for new users, pattern lock as security, and the preferred service page. The receiver application pages consist of the login page, inbox page, history page and profile of main service office page. The application has been developed and an assessment of the quality of the application is needed to improve the use of the application. Therefore, this study aims to evaluate applications on the sender side. The evaluations of the analysis result are needed as recommendations for future application development. The evaluation of the application use usability instruments which consist of components of effectiveness, efficiency and user satisfaction. The research was conducted by distributing the SUS (System Usability Scale) questionnaire to 20 respondents and each statement was given a weight based on the Likert scale. The results showed that the application was in the excellent category and could be accepted by the community.
E-Commerce Security by Quantum Digital Signature-Based Group Key Management

The Internet development is high over the past decades and there is a lot of cloud computing technology is used in business and other purposes. This leads to the major tread to the security in the cloud and secure communication is much required. Quantum Key Distribution (QKD) is one of the most common methods used to provide better encryption. The main focus of this research is that provide secure communication from the group keying. The Quantum Digital Signature-based Group Key management (QDSGKM) combines QKD with the Fibonacci, Lucas, and Fibonacci–Lucas matrices, which provides the quantum digital signature checks. This method gives the technique to verify the integration of information received by the participants, to authenticate the identity of the participants, and to improve the verification of the signing verification. The experimental result shows that the proposed system provides the security with less delay when compared to the QKD system.
Mitigating the insider threat of remote administrators in clouds through maintenance task assignments

Today’s cloud providers strive to attract customers with better services and less downtime in a highly competitive market. The need for minimizing the operational cost unavoidably leads cloud providers to rely on third party remote administrators for fulfilling regular maintenance tasks. In such a scenario, the lack of trust in those third party remote administrators paired with the extra privileges granted to them to complete the maintenance tasks usually implies undesirable security threats. A dishonest remote administrator, or an attacker armed with the stolen credential of a remote administrator, can pose severe insider threats to both the cloud provider and its tenants. In this paper, we take the first step towards understanding and mitigating such insider threats of remote administrators in clouds. Specifically, we first model the maintenance task assignments and their corresponding security impact due to privilege escalation. We then mitigate such impact through optimizing the task assignments with respect to given constraints. Finally, the simulation results demonstrate the effectiveness of our solution in various scenarios.
Large-Aperture Real-Time Compensated Collimating Wavefront Error Detection Method

This paper proposes a real-time compensated pentaprism scanning wavefront detection method to achieve real-time compensation for scanning errors occurring during prism movement along a guide rail. The method is based on existing pentaprism scanning wavefront detection technology and it is realized by applying self-collimation-based three-dimensional error compensation. Using theoretical and data analyses of a detection experiment, the reliability of the optimized pentaprism scanning detection method is verified, thus effectively ensuring the reasonable estimation of the interferometry surface measurement uncertainty.
Self-Explanatory Capabilities in Intelligent Decision Support Systems in Resource Management

Self-explanations in decision support systems need to be presented in parallel with considering and understanding the outcomes of advice from the expert system. This advice can realise benefits such as increased user acceptance and confidence in the adoption of the improved system. There are numerous categories of explanation, including the following. In order for an expert system to reach a conclusion, there needs to be: (1) justification and a record of the inferential steps; (2) an explicit knowledge of the underlying argument, or (3) explanation of the rationale behind each inferential measure taken by the expert system. This recommendation will result in more persuasive justification and lead to satisfaction, and acceptance of advice. For this reason, it is proposed to announce a discourse semantics approach to an Intelligent Decision Support System framework by the inclusion of a discourse layer. In this paper, the discourse semantics layer approach will be demonstrated to show the mechanism of how a fuzzy logic based expert system utilises justification techniques for advice offered in the problem of control and resource management.
A Method for Constructing a Clone Code Case Library Based on Bugs

Code clone is a quite common behavior in the software development process, but improper clone operations may generate bugs or make potential Bugs multiply. This paper proposes a method for constructing a ”clone code case library” based on bugs. The research takes the clone code of continuous multi-version software as the analysis object, and carries out four key steps of “clonel detection”, “clone code evolution tracking”, “clone code associated with Bugs”, “build and visualize clone code Bug library ”. The case base will provide scientific basis and practical value for the reuse, reconstruction and evolution management of clone code, and provide targeted clone maintenance suggestions for different users.
How to Exploit Prior Knowledge in Industrial 3D-Metrology

The goal of every measurement is to obtain new information about the specimen - preferably with as little effort as possible. We will discuss different ways of exploiting prior knowledge to accomplish this goal in industrial environments.
Difficulty-weighted learning: A novel curriculum-like approach based on difficult examples for neural network training

Curriculum learning, in which training examples gradually proceed from easy to difficulty, has been applied to various tasks and demonstrated better performance than other machine learning approaches. However, identifying the difficulty level in advance often requires domain knowledge and is a time-consuming process. We dynamically decide the difficulty of examples based on outputs from neural networks during training and propose a loss function to promote training with difficult examples. Experimental results verify that the proposed method improves the generalization ability across several datasets.
Evaluating the Efficiency of Energy-scape software

Recently, researchers were focusing on integrating renewable energy (RE) within urban environment instead of integrating renewables with buildings due to the large occupies of urban areas. Urban areas have a great potential in generating sufficient amount of energy that could satisfy the needs of urban neighborhoods. Energy-scape elements are sustainable elements that integrates RE devices with landscape elements. This research focuses on analyzing the importance and efficiency of Energy-scape software through a qualitative method. The efficiency of Energy-scape web-based application will be tested using qualitative method and a site survey. The research concludes that Energy-scape software application is an effective tool for landscape designers in using Energy-scape elements, it identifies the optimum type and location of Energy-scape elements within their projects, and it calculates the impact of using Energy-scape elements in term of energy-savings and carbon emission (CO2) reduction.
A Virtual Counselor for Genetic Risk Communication

A pedagogical embodied conversational agent that plays the role of a genetic counselor is being developed to improve individuals’ comprehension of genetic risks related to hereditary cancers. Genetic risk communication is increasingly important for disease prevention and treatment, yet many individuals lack the basic health literacy and numeracy required to understand this information. The virtual genetic counselor will address the challenges in communicating complex genetic risks by dynamically adapting its teaching strategies to an individual’s knowledge state.
Development of an illumination module for stroboscopic phase-shift interferometry on MEMS devices

The proper functionality of microelectromechanical systems (MEMS) is governed by characterisation methods reliant on optical metrology. Static characterisation methods like interferometry are well established. The standard dynamic characterisation method is Laser Doppler Vibrometry (LDV), which can be used for areal measurements by merging data from pointwise measurements. However, the increasing complexity of MEMS structures is raising the demand for more efficient spatial dynamic analyses. Phase-shifting interferometry (PSI) is state of the art in high-resolution topography acquisition techniques. By equipping interferometers with a stroboscopic illumination source, it is possible to perform dynamic analyses of periodically oscillating samples by synchronising the illumination flashes to the sample motion. Although this is a known approach, interferometers with this technology embedded are scarce and restricted to lower bandwidths. This paper introduces an external standalone stroboscopic illumination module, which can be installed onto the interferometer objective through optical fibres. Firstly, fast-switching power-LEDs were selected as illumination sources. Optical pulse length as short as 15 ns was realized, leading to a bandwidth of some tens of MHz. Micromirror arrays (MMAs) developed at the Fraunhofer IPMS were used as test samples to prove the concept. For MMAs switched at 2 kHz, overshoot and oscillation frequency were determined. The main advantage of the stroboscopic interferometric method is in recording thousands of points simultaneously, in contrast to the LDV. This is equivalent to a performance increase in the order of tens or even hundreds of times.
Integrating Multi-agent Simulations into Enterprise Application Landscapes

To cope with increasingly complex business, political, and economic environments, agent-based simulations (ABS) have been proposed for modeling complex systems such as human societies, transport systems, and markets. ABS enable experts to assess the influence of exogenous parameters (e.g., climate changes or stock market prices), as well as the impact of policies and their long-term consequences. Despite some successes, the use of ABS is hindered by a set of interrelated factors. First, ABS are mainly created and used by researchers and experts in academia and specialized consulting firms. Second, the results of ABS are typically not automatically integrated into the corresponding business process. Instead, the integration is undertaken by human users who are responsible for adjusting the implemented policy to take into account the results of the ABS. These limitations are exacerbated when the results of the ABS affect multi-party agreements (e.g., contracts) since this requires all involved actors to agree on the validity of the simulation, on how and when to take its results into account, and on how to split the losses/gains caused by these changes. To address these challenges, this paper explores the integration of ABS into enterprise application landscapes. In particular, we present an architecture that integrates ABS into cross-organizational enterprise resource planning (ERP) processes. As part of this, we propose a multi-agent systems simulator for the Hyperledger blockchain and describe an example supply chain management scenario type to illustrate the approach.
Towards Semantic Integration of Heterogeneous Data Based on the Ontologies Modeling

The integration of the heterogeneous data is a major problem encountered today by the users of the Web. A typical integration scenario is that two heterogeneous systems A and B are built for different business purposes for different users at different times by different software developers using different information models. The two systems often have heterogeneous semantics, data structures and business rules are different. It involves in particular the differences between systems infrastructures, the conceptual schematizations of the data and its meanings. Indeed, the ontology specifies its systems of knowledge representation. It allows the modeling of knowledge in an explicit and formal way by concepts and relations between these concepts. The semantic integration comes after syntactic integration and the mechanisms of translation connection. In this paper, we proceeded to a semantic integration of the heterogeneous data based on the management of the heterogeneousness and the semantic ontology of the knowledge.
Extrinsic calibration of a 3D sensor based on an array projector and a single camera

We previously presented a technique calibrating a Multi-Aperture Array Projector (MAAP) for performing high-speed three-dimensional (3D) surface topology measurements with structured illumination. The MAAP achieves projection rates up to 3 kHz by projecting a sequence of aperiodic sinusoidal fringes through several distinct projecting aperture channels such that up to 330 3D measurements per second could be achieved. This rapid switching between several projecting channels overcomes the projection limit of conventional off-the-shelf single aperture Digital Light Processing (DLP) or Liquid Crystal on Silicon (LCoS) technologies that typically have projection rates on the order of 100 Hz. The proposed MAAP calibration technique re-enabled photogrammetric 3D measurements to be made using a single CCD or CMOS camera where a stereo-camera setup used to be required for triangulation. The focus to reduce a stereo-configuration to a single camera system opens possibilities to decrease cost as well as form factor of such a high-speed metrology system utilizing an MAAP. For such a photogrammetric optical metrology system, intrinsic camera calibration and extrinsic setup calibration are vital to obtain high measurement performance. With the pinhole camera model assumption, intrinsic calibration is typically carried out using the standard Zhang method. However, there is currently no such standard technique that can comprehensively perform the required extrinsic calibration. In this study, the main sources of measurement error arising from extrinsic calibration of the proposed technique are discussed and investigated. Several different extrinsic calibration techniques are proposed and the resulting measurement performance evaluated.
Is It Worth It? Implementation of Electronic Lab Notebook Software Among the STEM Community at an American University in the UAE

Scientists and engineers have been recording the results of their scientific findings and studies via lab notebooks for hundreds of years to lay out protocols and track their progress.Most of this recording of protocols and progress has been done via paper lab notebooks.With the popularity of the internet, many have been turning to electronic means to record their study data, though this does not imply that paper lab notebooks have been completely abandoned.In the beginning, many were making use of tools not necessarily created for the sole use in laboratories, such as Microsoft Word, Evernote, Google Docs, or other means of recording notes online and/or via a computer.However, there proved to be a market for products used especially by those doing research on scientific fields and thus the electronic lab notebook was born.New York University Abu Dhabi has a growing faculty specializing in STEM fields.