Miracle-dz/UniFAR-FTUs huggingface dataset:
Multivariate Time Series Data Prediction Based on ATT-LSTM Network

Deep learning models have been widely used in prediction problems in various scenarios and have shown excellent prediction effects. As a deep learning model, the long short-term memory neural network (LSTM) is potent in predicting time series data. However, with the advancement of technology, data collection has become more accessible, and multivariate time series data have emerged. Multivariate time series data are often characterized by a large amount of data, tight timeline, and many related sequences. Especially in real data sets, the change rules of many sequences will be affected by the changes of other sequences. The interacting factors data, mutation information, and other issues seriously impact the prediction accuracy of deep learning models when predicting this type of data. On the other hand, we can also extract the mutual influence information between different sequences and simultaneously use the extracted information as part of the model input to make the prediction results more accurate. Therefore, we propose an ATT-LSTM model. The network applies the attention mechanism (attention) to the LSTM to filter the mutual influence information in the data when predicting the multivariate time series data, which makes up for the poor ability of the network to process data. Weaknesses have greatly improved the accuracy of the network in predicting multivariate time series data. To evaluate the model’s accuracy, we compare the ATT-LSTM model with the other six models on two real multivariate time series data sets based on two evaluation indicators: Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The experimental results show that the model has an excellent performance improvement compared with the other six models, proving the model’s effectiveness in predicting multivariate time series data.
Biologically Inspired, Anisoptropic Flexible Wing for Optimal Flapping Flight

Abstract : A multidisciplinary program involving collaboration between eight researchers at three universities to address fundamental aspects of flapping wing micro aerial vehicles (MAV) is described. The overall goal of the program was to develop the fundamental scientific foundation necessary to enable the design of agile, autonomous flapping-wing MAVs for operation in an urban environment. Significant accomplishments include: a) Developed and validated high- and low-fidelity computational tools for analysis and design of flapping wing MAVs; b) Developed and used measurement techniques to determine the relation between wing kinematics, geometry, and anisotropic structural flexibility; c) Conducted coordinated experimental and computational modeling to determine the roles of aerodynamic loading, wing inertia, and structural flexibility and elasticity; and d) Developed surrogate tools for flapping wing MAV design and optimization. Detailed research accomplishments have been documented in 83 archival publications, 11 Ph.D. Dissertations and 5 Master Thesis. Several archival publications are in collaboration with colleagues at AFRL.
Effects of glucose on growth and health-promoting compounds in sunflower (Helianthus annuus L.) sprouts

Plant products with high potential health benefits have been consumed continuously (Rouphael et al., 2018). Edible sprouts have been consumed as a dietary food due to their high nutritional quality (Martinez-Villaluenga et al., 2010; Ebert et al., 2017). Based on this evidence, research interests have focused on strategies to increase the content of beneficial bioactive compounds in sprouts without breeding or genetic manipulation. A basic and efficient method is to use a plant stress response system. Environmental stresses, such as chemical stress, salt stresses and osmotic stress, have been reported to exert a valuable effect on the secondary metabolites content in many sprouts (Guo et al., 2011a; 2011b; 2014; Mendoza-Sánchez et al., 2016). Abstract Article Info AGRICULTURE AND NATURAL RESOURCES
Strategic Positioning: Key Point of Business Transformation —Revelation of Xiangeqing’s Transition

Explicit strategic positioning is the most important factor to motivate the development of an enterprise. Based on the specific condition for an enterprise, a unique strategy could be one competitive advantage for it. Furthermore, for the enterprises who want to change their traditional operating styles, a strategy that follows up with current environment is necessary. This essay tries to discuss the importance of specific and renewable strategic positioning based on the failed transformation of Xiangeqing and provide some suggestions for the main problems.
Given that the Paris Agreement is unlikely to prevent dangerous climate overshoot, an alternative risk management strategy is urgently needed

Because the 2015 Paris Agreement will not prevent dangerous climate change, there is an urgent need to develop an alternative mitigation strategy. Even if all national commitments are met and technological breakthroughs accelerate the transition to emission-free technologies, the 2°C target will still be overshot due to systemic inertia from existing greenhouse gases, warming oceans, and the decades required to replace existing infrastructure. Compounding risks are: (a) Most policy-makers greatly underestimate the scale, severity and duration of climate change, and the non-linear impacts of lags, feedbacks and tipping points; (b) Although all IPCC mitigation scenarios require the large-scale deployment of climate geoengineering, many methods may not be politically and/or technologically feasible; (c) While most scenarios assume climate overshoot will occur before safe climates are re-established, many human and environmental systems cannot adapt to higher temperatures. Temperatures likely to cause catastrophic and/or irreversible damage pose unacceptable risks.
Starting Out: The Quality of Working Life of Young Workers in the Retail and Hospitality Industries in Australia

In the 1990s workers in Australia were increasingly subjected to negative work pressures. Irregular work patterns, work intensification, and the transformation of the notion of career, often in the name of ‘flexibility’, were increasingly common. This period was also characterised by scant regard for the quality of working life of young people in entry-level employment, which is often portrayed as a transition stage prior to their admission into the full-time core workforce. This paper explores the experiences of twenty-two young people at the beginning of their careers, in the hospitality and retail industries, with reference to three quality of working life (QWL) elements: hours flexibility, work-life balance and career potential. Qualitative evidence reveals a variety of experiences but, on balance, suggests a negative quality of working life and limited commitment to their current industry. In conclusion, the paper suggests that these industries must pay more attention to QWL issues in order to attract and retain quality staff.
Theoretical Appraisal of Sustainability Metrics and Empirical Application to an Irish City-region to Assess Current and Future Sustainability

The purpose of this paper is to appraise a myriad of sustainability measurement methodologies, using a number of criteria, including strengths and weaknesses, data requirements, outputs and applicability at various spatial and temporal scales. The main criterion was the ability to measure and monitor sustainability of a sub-national settlement and to facilitate scenario building in order to assess the likelihood of current policy measures achieving sustainability in the selected city-region. The methods that were selected and empirically applied to the case-study, i.e. the Limerick city-region are urban metabolism, carbon and ecological footprinting and trend to target assessment. The aim of the research is to develop the optimal policy mix, which will help guide the city-region along a more sustainable trajectory and highlight trends in critical indicators and sectors, commonalities, feedback loops and leverage points in the policy-making process.
Workload-Based Capacity for Air Traffic Management

The charter of FAA is to promote the safe, orderly, and expeditious use of the National Airspace System (NAS). To ensure that traffic flow is safe and efficient, FAA needs to know the expected traffic demand on the sector and the sector's capacity to accommodate that demand. When sector capacity is inadequate to meet the demand, congestion occurs. To ensure that safety is not compromised, FAA often takes action to reduce demand or increase capacity to avoid congestion. The MITRE Corporation's Center for Advanced Aviation System Development developed a time-on-task workload model to assess capacity and congestion in en route NAS sectors. A metric was developed and used along with the workload generated by the model and a workload threshold to estimate sector capacity. The metric, as constructed, enabled equitable comparison of capacity of different sectors, regardless of size. A field and lab evaluation of the workload model was used to quantify the model's task coverage and to calibrate its parameter values. The workload model was used to generate workload, capacity, and congestion profiles for selected en route sectors during good weather and during convective weather. The data used to generate the profiles can be used for various air traffic management applications.
Systematic identification of applications for a cluster of femto-satellites

Embracing reduced requirements and leveraging commercial technology has led to a fast growing small satellite industry. Although most interest in small satellites has hovered around the micro satellites through to the picosatellites, academic interest now extends up to the sub 100 g range of satellites as well. Femto-satellites with a mass range between 10 g and 100 g could in the future be mass produced and hundreds to thousands of femto-satellites can be deployed as a cluster to enhance, for example, the situational awareness of the Earth’s environment. Femto-satellite is seen to form the next class of miniature satellites which will exploit spacecraft engineering, swarm science and mission design to realize exciting new space missions. Consequently, there has been considerable research interest in the sub 100 g range of satellites and the advantage of distributed satellites in space. However, most of the research work has been limited to a bottom-up approach to realize an individual femto-satellite with as much functionality as possible, without sufficient attention to the realization of an application using these distributed femto-satellites in space. This has resulted in an ambiguous top tier of space applications whose realization with a cluster of femto-satellites is arguable. The paper outlines the different realizations of distributed systems in space and identifies the most suitable candidate for femto-satellites. The aim is to map the user requirements for applications to the scaled capability of a cluster of femto-satellites, thereby aiding to systematically identify potential applications for femto-clusters. The principal challenge is that there exists no simple means to scale the capability of an individual femto-satellite to the capability of a distributed cluster of femto satellites. Scaling certain capabilities is not straightforward. For example, when we consider a user requirement such as orbit control, the inherent virtue of a distributed system may obviate the need for orbit control in individual satellites for some scenario and may not in other cases. These functionalities are carefully considered to develop a qualitative approach that will enable the scaling of individual satellite capability to the overall capability of a cluster of satellites.
Design and Analysis of Lean Production Planning and Control System for NPF Company

Some of the important factors that are highly considered in NPF are; production processes, waste reeducation and optimization of raw materials. These concerns can be addressed through advance planning and scheduling and thoughtful programming for production, which reflects the goals, taking into account the different alternatives and the limited resources. On this basis the problem was formulated specifically, the problem specifically, taken into account the particular circumstances of NPF Company, special data was collected to configure a model for the planning and control of production processes. Implementation and analysis of all of that depended on brainstorming with the engineers of NPF, and then the marketing studies for finished productswere analyzed. We concluded after all to the study forecasts the future of the company products; based on the results an aggregate plan is designed. Then a production plans for all levels of planning and control of the proposed production quantities of all products are presented.
AHS road-to-vehicle communication system

Advanced cruise-assist highway system (AHS) has established itself as the system in the total integrated transportation system (ITS) concept of Japan providing services aimed at improvement of road traffic safety, increase in transport efficiency, and alleviation of environmental problems. Realization of AHS services requires road-to-vehicle communication (RVC) for sensors installed on the side of roads to communicate road transport data to the vehicle in motion. This type of communication demands that the system has distinctive features not realized by existing dedicated short-range communication (DSRC) and public mobile communication. This paper defines the requirements for AHS road-to-vehicle communication and for the data communication system involved and presents the concept of the AHS data communication system.
Grid Voltage Regulation with MMC-HVDC System

This paper presents an operation of the modular multilevel converter-high voltage direct current (MMC-HVDC) system as a Statcom to support the grid voltage. The advantage of the MMCHVDC system is that it can control the active and reactive powers independently. The proposed control scheme will be designed by combining this performance and the control method of the Statcom. The grid voltage is regulated by the control of the reactive power, meanwhile the active power is controlled according to its applications. The simulation results based on the PSCAD/EMTDC simulation program will evaluate the effectiveness of the control scheme.
ADACS-an automated system for part finishing

This paper describes an automated finishing system called the advanced deburring and chamfering system (ADACS). ADACS uses the real-time control system (RCS), a hierarchical controller architecture that was developed at the National Institute of Standards and Technology. ADACS uses a graphical user interface that prompts an operator to specify chamfering edges and cutting parameters for the part. Given the operator-designated chamfering edges, ADACS uses this edge information to extract features-such as inside corner-to generate a finishing process plan. ADACS interprets the finishing plan to generate motion trajectories that are tightly coupled to the tooling control. Because of the inaccuracies in robotic position control, ADACS uses active force control in the tool to compensate for any small position errors along the finishing path. A prototype ADACS has successfully processed aerospace test parts. <<ETX>>
Patient Representation Learning From Heterogeneous Data Sources and Knowledge Graphs Using Deep Collective Matrix Factorization: Evaluation Study

Background Patient representation learning aims to learn features, also called representations, from input sources automatically, often in an unsupervised manner, for use in predictive models. This obviates the need for cumbersome, time- and resource-intensive manual feature engineering, especially from unstructured data such as text, images, or graphs. Most previous techniques have used neural network–based autoencoders to learn patient representations, primarily from clinical notes in electronic medical records (EMRs). Knowledge graphs (KGs), with clinical entities as nodes and their relations as edges, can be extracted automatically from biomedical literature and provide complementary information to EMR data that have been found to provide valuable predictive signals. Objective This study aims to evaluate the efficacy of collective matrix factorization (CMF), both the classical variant and a recent neural architecture called deep CMF (DCMF), in integrating heterogeneous data sources from EMR and KG to obtain patient representations for clinical decision support tasks. Methods Using a recent formulation for obtaining graph representations through matrix factorization within the context of CMF, we infused auxiliary information during patient representation learning. We also extended the DCMF architecture to create a task-specific end-to-end model that learns to simultaneously find effective patient representations and predictions. We compared the efficacy of such a model to that of first learning unsupervised representations and then independently learning a predictive model. We evaluated patient representation learning using CMF-based methods and autoencoders for 2 clinical decision support tasks on a large EMR data set. Results Our experiments show that DCMF provides a seamless way for integrating multiple sources of data to obtain patient representations, both in unsupervised and supervised settings. Its performance in single-source settings is comparable with that of previous autoencoder-based representation learning methods. When DCMF is used to obtain representations from a combination of EMR and KG, where most previous autoencoder-based methods cannot be used directly, its performance is superior to that of previous nonneural methods for CMF. Infusing information from KGs into patient representations using DCMF was found to improve downstream predictive performance. Conclusions Our experiments indicate that DCMF is a versatile model that can be used to obtain representations from single and multiple data sources and combine information from EMR data and KGs. Furthermore, DCMF can be used to learn representations in both supervised and unsupervised settings. Thus, DCMF offers an effective way of integrating heterogeneous data sources and infusing auxiliary knowledge into patient representations.
Practices of parallel media: using mobile devices when watching television

We have been studying how people use mobile phones and laptops while watching television. Our results show that these are not necessarily used to access content that is related to what is being watched. However, this is not to say devices are being used in isolation from their surrounds; their use is interwoven with watching television and with interacting with other people. We suggest that designing for ‘the connected home’ is more than an integration project, and should take account of the social fabric of domestic life.
Instrumentation and data fusion architecture for systems control

Sensors selection and data fusion is of key importance for control of complex mechanical systems with vibrating flexible structures. This paper presents a systematic approach, based on the theory of hyperstability, for the design of an instrumentation and data fusion architecture which enables the robust control of complex systems. Earlier results are generalized and previous restrictions on sensors are relaxed to broaden the practical applicability of the proposed method.
Analisa Kinerja Sistem Deteksi Terdistribusi Pada Jaringan Sensor Nirkabel

Pada sistem deteksi terdistribusi jaringan sensor nirkabel, sejumlah sensor disebar dalam suatu daerah tertentu untuk mendeteksi suatu target. Sensor mengumpulkan data dan membuat keputusan sementara berdasarkan data yang diperoleh. Keputusan sementara dari sensor dikirimkan ke pusat pengolahan data yang disebut fusion center. Fusion center membuat keputusan final hipotesa yang mendekati benar berdasarkan data yang dikirimkan sensor. Kinerja dari system dapat dilihat dari parameter yang dinamakan probabilitas deteksi system dan probabilitas false alarm. Disini akan dievaluasi parameter-parameter tersebut untuk berbagai macam kondisi jaringan sensor nirkabel. Kata kunci : deteksi terdistribusi , jaringan sensor nirkabel, fusion center, probabilitas deteksi, probabilitas false alarm
Real Time Model Predictive Control in JModelica.org

In this thesis a framework for real-time model predictive control has been developed for JModelica.org, which is an open-source platform for simulation and analysis of dynamical systems. Model predictive control (MPC) is an advanced optimizationbased control method that uses a model of the process being controlled to optimize control. The framework was tested on three different processes, real and simulated, and its performance was compared with that of an linear-quadratic regulator (LQR), which is a simpler type of controller that uses multiplication with a pre-calculated matrix to calculate the control signal from the state vector. The MPC controller was found to perform as well as or better than the LQR controller in all cases, with the main improvements being seen in the MPC controller’s ability to handle process constraints or when far from the LQR controller’s linearization point; however, the LQR controller was much faster in calculating the control signal. This also served as a first test of using JModelica.org to perform MPC on real processes, and although it performed well on the two it was tested on, further work will be needed if the MPC framework should be able to handle processes that are much faster or more complex.
Arbeidsforhold i gods og turbil

Abstract in Norwegian I denne rapporten har vi sett pa arbeidsforholdene innenfor gods- og turbilbransjen. Det er bred enighet bade pa arbeidsgiver- og arbeidstakersiden om at den landbaserte transportnaeringen er stilt overfor en rekke utfordringer som folge av okt internasjonal konkurranse de siste tiarene. Det er ogsa en gjennomgaende bekymring blant aktorene i bade turbil- og godsbransjen for hvilke konsekvenser lavtlonnskonkurransen har for sjaforenes arbeidsforhold. Nar det gjelder forhold knyttet til useriositet, er det saeregne utfordringer i gods- og turbilbransjen i forhold til tilsvarende problematikk i andre bransjer som uteliv, renhold og bygg og anlegg. Mobilitet er et grunnleggende trekk ved transportbransjen og gjor at tiltak som kanskje virker i andre bransjer, ikke vil ha samme effekt innenfor transport, spesielt ikke i de segmentene som er grensekryssende og derfor vanskelige a regulere. (Less)
Ultrahigh-speed personal wireless communications in 60 GHz using picocell zones and high-gain direct beams

This paper describes a simple and low cost transceiver for indoor wireless LAN system to be operated in 60 GHz for ultra-high speed data (e.g. 156 Mbps) transmission, along with design of system parameters such as frequency selection, radio link parameters featuring very low RF power of 10 mW suitable to MMIC performances and high gain antennas. Without using route diversity and adaptive delay equalizers making up for shadowing and multipath reflection of RF signals, new layout of hub and user stations and line-of-sight transmission scheme are adopted. In addition, partially applied radio absorber helps effectively to reduce the undesired co-channel interference signal to the neglectful level, which system is named minimum delay spread (MDS0 local area network (LAN). This paper also presents the idea of effective applying absorber on ceiling which is derived from simulation and some useful measured data of absorbing construction materials, and presents main features of developed MMIC chip set workable in 60 GHz.