Miracle-dz/UniFAR-FTUs huggingface dataset:
DEVELOPMENT AND USABILITY TESTING OF A STUDENT MOBILE APPLICATION FOR THE AIChE CONCEPT WAREHOUSE

Incorporating user feedback is imperative for the adoption and continued usage of educational innovations in the classroom. We report on the development of an Android-based student mobile application, a user-suggested improvement for the AIChE Concept Warehouse. An Apple-based mobile application is also in development. Our intent is to share the applications’ development and improvement process in the hopes that other innovators can benefit from the lessons learned through our experience. The AIChE Concept Warehouse was developed with the intent of fostering a community of learning within chemical engineering. The Concept Warehouse is a web-enabled database infrastructure that is designed to promote concept-based instruction through the use of concept questions. These concept questions are used in core curriculum courses like Material/Energy Balances, Thermo-dynamics, Transport Phenomena, Kinetics and Reactor Design, and Materials Science. Availability of high quality concept questions can lower the barrier for faculty to use concept-based instruction and assessment. This software allows the instructor to engage students and evaluate student learning in real-time. The instructor is then able to adjust the pace of lecture in response to student understanding. The Concept Warehouse also allows for reflective assessments such as “the muddiest point. ” The student mobile application was developed to make it easier for students to submit answers and written explanations to these assessments using mobile devices. Originally, students could submit their answers to conceptual questions using clickers, mobile browsers on smartphones, and laptops. Input via smartphones, however, proved cumbersome because it depended on the quality of the student’s mobile browser and utilized the full-size webpage interface. The improved mobile student interface facilitates participation by making responses via smartphone more user-friendly. After the development of the application, we conducted initial usability tests with students who had previously used the web-based options for answer submission. In order to gauge usability, we collected usage statistics from student responses to a usability survey. Survey responses were used to identify student likes and dislikes as well as to compare different available options for answer submission. These results will be used to improve the design of the current application as well as guide our design decisions for the development of the iOS version of the student app.
Affective Design of Automotive Center Fascia Display: Focused on Regional Preference

○cc This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Objective: This study is primarily aimed at examining regional affections to automotive center fascia displays.
55 / 2010 Hedging with CO 2 allowances : the ECX market

We investigate and empirically estimate optimal hedge ratios, for the rst time, in the EU ETS carbon market. Minimum variance hedge ratios are conditionally estimated with multivariate GARCH models, and unconditionally by OLS and the naïve strategy for the European Climate Exchange (ECX) market in the period 2005-2009. Also, utility gains are considered in order to take into account risk-return considerations. Empirical results indicate that dynamic hedging provides superior gains (in reducing the variance portfolio) compared to those obtained from static hedging, when adjustment costs are not taken into account. Moreover, results improve when the leptokurtic characteristics of the data are into consideration through distributions. Results are always compared in and out of sample, suggesting also that utility gains increase with investors increased preference over risk. Keywords: CO2 Emission Allowances; Dynamic Hedging; Futures Prices; Risk Management; Spot Prices JEL classi cation: C32, G19, G32, Q54 *This paper was prepared for and presented at the Energy & Finance Conference, October 6 to 8, 2010, which took place in Essen, Germany. We thank the useful comments.
How important are mangroves and seagrass beds for coral-reef fish? The nursery hypothesis tested on an island scale

There has been much controversy over the degree to which mangroves and seagrass beds function as nursery habitats for the juveniles of fish species that live on coral reefs as adults. In previous studies we have shown that the juveniles of at least 17 Caribbean reef-fish species are highly associated with bays containing mangroves and sea- grass beds as nurseries, and that juveniles of these species are absent in bays lacking such habitats. In this study we there- fore hypothesised that on islands lacking these bay nursery habitats, adults of these fish species will be absent or show low densities on the coral reef. Densities of the 17 species were compared between the reefs of Caribbean islands with and without mangroves and seagrass beds. On reefs of islands lacking these habitats, complete absence or low den- sities were observed for 11 of the 17 species, several of which are of commercial importance to fisheries. This finding sug- gests a very important nursery function of such habitats and implies that the densities of several fish species on coral reefs are a function of the presence of nearby bays containing man- groves and seagrass beds as nurseries. The results indicate that degradation or loss of these habitats could have signifi- cant impacts on reef-fish stocks in the Caribbean.
Mobile-assisted Language Learning (MALL) for ESL Learners: A Review of Affordances and Constraints

Nowadays, mobile technology is changing the landscape of language learning and is seen as the next frontier being researched for its potential in enhancing the teaching and learning of English language. The portability of mobile devices is believed to bring new methods that can shape learning styles and pedagogies which could become more personalised and allow learners to learn on the move; thus, enhance English language teaching and learning. This creates the potential for significant change in the teaching and learning of English as Second Language (ESL). Taking mobile learning as the setting within which developments in Mobile-assisted Language Learning (MALL) may be understood, this paper offers reflections on what Mobile-assisted Language Learning (MALL) has potentially offered and the constraints that might be faced by the English as Second Language (ESL) learners when using MALL. Above all, it was a challenging issue to cover learning tasks by using a mobile device particularly in learning English as Second Language (ESL). Nevertheless, mobile devices which are popular among students are motivational tools to be used in education as well as various learning activities. This was proven by many researchers who have shown the positive outcomes. Hence, we should admit that mobile devices are finding their way into classrooms in the student’s pockets, and we have to ensure that educational practice can include this mobile technology in effective and productive ways particularly for English as Second Language (ESL) learning.
Investigating Enhancement Mode Gallium Nitride Power FETs in High Voltage, High Frequency Soft Switching Converters

An increased attention has been detected to develop smaller and lighter high voltage power converters in the range of 50V to 400V domain. The main applications for these converters are mainly focused for Power over Ethernet (PoE), LED lighting and AC adapters. This work will discuss a study of using enhancement mode gallium nitride switches to form a 50V quasi-square-wave zero-voltage-switching buck converter running at 2-6 MHz under full load. The designed converter achieved 83% efficiency converting 50V input voltage to 12.2V at 9W load.
Scalable Robust Voltage Control of DC Microgrids With Uncertain Constant Power Loads

Constant power loads (CPLs) impose instability issues in DC microgrids due to their negative impedance characteristics. This paper studies the problem of voltage control design of DC microgrids with CPLs. It is assumed that the power of CPLs is uncertain and belongs to a given interval leading to an infinite number of equilibrium points of the system. We develop a polytope model for DC microgrids with uncertain CPLs. Using this model, a robust two-degree-of-freedom feedback-feedforward voltage control framework is then proposed. The voltage controller is obtained by a solution of a set of linear matrix inequalities. The voltage control design strategy for each distributed generation (DG) unit is scalable and independent of the other DGs. The effectiveness of the proposed control approach is evaluated through simulation studies in MATLAB/SimPowerSystems toolbox.
A Robust RGB-D SLAM System With Points and Lines for Low Texture Indoor Environments

High-performance 6D pose estimation and dense 3D mapping with an RGB-D camera has recently attracted substantial research attention since this type of camera can simultaneously capture RGB and depth information. However, there is an unresolved problem in estimating pose and generating highly accurate 3D maps from challenging indoor scenes. This paper presents a real-time simultaneous localization and mapping (SLAM) system based on the RGB-D camera for indoor mobile robots. Our contributions are fourfold. First, we propose a complete high-accuracy SLAM system based on a combination of information from points and lines, which differs from most solutions that rely on only point features. Second, we propose a novel pose solver to handle point and line correspondences, in which a line-based inliers refinement (LBIR) algorithm is proposed to remove outliers. Third, we construct a unified optimization model to concurrently minimize point and line reprojection errors, and extend it to the bundle adjustment (BA) method. Fourth, extensive experiments demonstrate the robustness, accuracy, and real-time performance of the proposed system on public TUM datasets and real world scenes. The empirical results show that the proposed system achieves a comparable or better performance than state-of-the-art methods. Notably, our system can operate in nearly texture-less scenes, while other methods are prone to failure.
Social Networking Service for Helping Each Other in the Neighborhoods

This research focuses on the use of Social Network Services among the elderly people in Japan, as a solution that could help to bridge the digital divide in that country. It proposes the creation of a Social Network Service for neighborhoods, in which the relationship among the young and the old is promoted. Existing design and usability guidelines for senior citizens and culture-related issues are highly taken into consideration. User-centered design method is applied to tailor the tool for testing. This paper hopes to bring new insights about how elderly people use Social Network Services in Japan and the usability challenges that they face when trying to use it. Keywords— Social Network Service; Elderly People; Usability; Japan.
Unpacking Entrepreneurial Intensity and Individual Ambidexterity in Small Project-Based Enterprises: A New Perspective for the TV Drama Industry

The purpose of this paper is to show that individual ambidexterity affects performance in small project-based enterprises. This is consistent with a recent and prominent stream of research that investigates the characteristics of workers as antecedents of ambidexterity behaviors and their effect on performance. We also analyze the role of entrepreneurial intensity as an important context issue that hampers this relationship. We test our hypotheses in the context of Italian television drama series productions, which are small project-based enterprises, by analyzing the careers of 1736 project entrepreneurs who had been working in the industry from 1996 to 2010. Our results suggest that for project entrepreneurs, high diversity in work experiences positively affects the project performance. Moreover, we demonstrate that the industry tenure of project entrepreneurs lessens the main relationship, by reducing the positive effect of entrepreneurial intensity and limiting benefits of ambidextrous behaviors. Our findings allow us to add insights to the entrepreneurship research and individual level ambidexterity theory. First, we contribute to this stream of research by analyzing how the diversity of work experiences at the individual level affects project performance. In doing so, we overcome the prior literature, which limited analysis only to the project portfolio level. Second, we develop a framework that investigates the argument regarding whether and under what circumstances does individual level ambidexterity improve project performance.
Unsupervised Classification of Images: A Review

Unsupervised image classification is the process by which each image in a dataset is identified to be a member of one of the inherent categories present in the image collection without the use of labelled training samples. Unsupervised categorisation of images relies on unsupervised machine learning algorithms for its implementation. This paper identifies clustering algorithms and dimension reduction algorithms as the two main classes of unsupervised machine learning algorithms needed in unsupervised image categorisation, and then reviews how these algorithms are used in some notable implementation of unsupervised image classification algorithms.
Voltage Stability Index Calculation by Hybrid State Estimation based on Multi Objective Optimal Phasor Measurement Unit Placement

Operation of a power system close to the voltage stability limit due to increasing of load demand and limited power sources may result in disastrous economic loss with voltage collapse of the entire power system. A system operator has to understand how far the system is from the critical boundary of the voltage collapse. This paper investigated the influence of State Estimation (SE) in the calculation of the Critical Boundary Index (CBI) as a voltage stability index. For SE, Hybrid State Estimation (HSE), including the measurement set of both Remote Terminal Unit (RTU) in Supervisory Control and Data Acquisition (SCADA) and Phasor Measurement Unit (PMU), is employed. Concurrently, the CBI is estimated using voltage phasor estimated by HSE based on optimal PMU location, which is selected from a Pareto optimal front obtained by the Non-dominated Sorting Genetic Algorithm II (NSGA-II). As a result of CBI estimation, HSE using PMU is relatively accurate in voltage stability index estimation compared to SCADA SE, which uses the RTU alone. However, when a mixed measurement condition in some lines affects the CBI estimation, it is suggested that it may be necessary to discard PMU measurements in some cases.
Empirical characterisation of the indoor multi‐user MIMO channel in the 3.5 GHz band

This study presents an analysis of the capabilities of using multi-user multiple input multiple output (MU-MIMO) in indoor environments at the 3–4 GHz band through an empirical characterisation of the MU-MIMO channel, obtaining a statistical description of the degree to which this specific multi-user channel verifies the condition of ‘favourable propagation’. Different metrics have been considered to measure the degree of orthogonality between the channels, such as the orthogonality coefficient or the condition number. In addition, in order to obtain a direct measure of the goodness of the channel in terms of the achievable spectral efficiency, the capacity of the channel has been calculated for different numbers of users and base station antennas and compared with theoretical i.i. d. Rayleigh channels.
Manifold Sparse Auto-Encoder for Machine Fault Diagnosis

Although the use of deep learning algorithms to find effective features for fault diagnosis has somewhat enhanced of fault classification accuracy, the lack of guidelines and the parameters such as layers of the deep learning architecture and dimension of each hidden-level has limited further improvement. Based on manifold mapping eigenvalues, an optimized deep learning model, called manifold sparse auto-encoder (MSAE) neural network, is constructed to diagnose the machine faults. Two main contributions of this paper can be summarized as (1) every encoding and decoding process is taken as a module to decline the vanishing gradient problem, and (2) the dimension of each hidden layer is determined by the manifold mapping eigenvalues of hidden neurones, whereas the layers of the deep learning architecture are determined by the clustering distribution of features. Gearbox datasets demonstrated that the proposed MSAE can extract better discriminative high-level features and has higher accuracy in machinery fault diagnosis compared with other machine learning methods.
Effectiveness Assessment of a Nanocrystalline Sleeve Ferrite Core Compared with Ceramic Cores for Reducing Conducted EMI

The interconnection of different electronic devices or systems through cables is becoming more difficult due to the hard restrictions related to electromagnetic compatibility (EMC) in order to comply with requirements. Therefore, the use of EMC components is a good solution to manage the problems associated with the filtering of electromagnetic interference (EMI) in cables and to pass the compliance test. In this sense, sleeve ferrite cores become a very interesting solution since they can be set around a wire and, hence, they provide an effective solution against EMI without having to redesign the electronic circuit. This contribution is focused on the characterization of the performance of a sleeve ferrite core based on a novel nanocrystalline (NC) novel material for EMI suppression and comparing it to the most conventional ceramic ferrite cores such as MnZn and NiZn. The research highlights the suitability of an NC novel component in terms of its magnetic properties to reduce EMI within the conducted emissions range. This range is generally defined by the International Special Committee on Radio Interference (CISPR) test standards frequency band that covers from 150 kHz up to 30 MHz (108 MHz in the case of CISPR 25). First, this study presents a description of the main parameters that define the behavior of NC and ceramic cores and, secondly, by analyzing the data obtained from experimental procedures, it is possible to directly determine the insertion loss parameter. Hence, this characterization procedure is used to obtain the performance of NC material compared to the conventional sleeve ferrite core compositions employed to filter the interferences in this problematic frequency range. As can be deduced from the results obtained, an NC sleeve ferrite core provides the best performance in terms of EMI filtering within a significant frequency range between 100 kHz and 100 MHz.
Estado de la investigación en energía en Colombia: una mirada desde los grupos de investigación

En este artículo se presenta el estado de la investigación en Colombia en temas de energía, a partir de la revisión, la sistematización y el análisis de los resultados de los grupos de investigación. La información se obtuvo desde la plataforma Scienti de Colciencias, de una muestra de grupos de investigación que declaran tener líneas de interés en energía. Se tuvieron en cuenta tres categorías para el análisis de la información: ubicación geográfica de los grupos y su clasificación, intereses investigativos determinados desde las líneas de investigación propuestas, y producción científica de los grupos. Se encontró que el 75 % de los grupos se ubica en cuatro de los 32 departamentos del país y que el 90 % pertenece a instituciones de educación superior. Hay diversidad en cuanto a los intereses investigativos y se destacan cuatro líneas principales: energía y potencia, gestión energética, hidrocarburos y energías renovables. La producción científica está centrada básicamente en artículos científicos, libros y desarrollo de proyectos; en cuanto a patentes, los resultados son escasos. En relación con energías renovables, la producción científica empezó a surgir a partir de 1999 y ha experimentado un crecimiento con tendencia lineal. Se logró identificar que si bien hay una investigación establecida en temas de energía desde las instituciones de educación superior y algunas empresas del sector energético, los avances relacionados con energías renovables son aún incipientes; hay un camino por recorrer, el cual se ha ido abonando con las nuevas reglamentaciones que se han dado en el país.
An Enhance Apporach to Mitigate the Impact of Black Hole and Gray Hole Attacks in AODV Routing Protocol

Wireless network has become more and more popular during the past decades. A Mobile AdHoc Network (MANET) is integrating of mobile nodes, in which the packets are forwarded without any centralized network authority. The devices are connected via wireless medium. Due to this characteristic security is high risk because packets are easily trapped in the network. There is no pledge of attack free communication due to heterogeneity in the network. AdHoc on Demand Vector (AODV) is a reactive routing protocol in MANET. This is a typical MANET protocol so in this protocol malicious node tries to attack on this protocol. The operation of AODV is loop-free, and by avoiding the "counting to infinity" difficulty offers quick junction when the ad hoc network topology changes. In this paper, propose a friend-ship value based detection algorithm which aims to detect malicious nodes. We have proposed a approach for securing AODV against black hole attack as well as gray whole attack. This approach also prevents and detects black hole/gray hole node or malicious node in the network. The propose algorithm identifies malicious node as well as improve the performance parameter using NS-2.35 simulator.
Multiprocessor Scheduling Problem by Wading across Stream Algorithm

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). Multiprocessor Scheduling Problem by Wading across Stream Algorithm Shang Gao a* and Yong Liu b 1 School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China; Artificial Intelligence of Key Laboratory of Sichuan Province, Zigong 643000, China. Gao_shang@just.edu. cn susergzn@163.com Abstract. The Wading across Stream Algorithm (WSA) act a solution as a start point, then search several solutions randomly near the start point, and find the best solution of these solutions. This best solution is to take as next start point, and then search several solutions randomly near this start point, and so on. For solving the Multiprocessor Scheduling problem, two methods to selected the initial solution as start solution were given. In order to search neighborhood trial solution, four strategies are put forward. It is proved that Wading across Stream Algorithm is a simple and effective algorithm.