Miracle-dz/UniFAR-FTUs huggingface dataset:
Fundamentals of Mass Conservative System Simulation in Fluid Power

This article illustrates the development of a dynamic system simulation tool for fluid power on basis of mass flows. The goal is to increase the predictability and efficiency of system simulation tools in fluid power. State of the art simulation tools make use of simplified differential equations. Especially in closed systems or long-term simulations, the volume flow based approach leads to significant variations of simulation results as balancing of flow parameters and its integrations to potentials lead to a violation of the equation of continuity. However, with a mass flow and energy conservative approach we obtain a clear and physically correct model implemented in the simulation tool DSHplus. The new basis of calculation enables further implementation of thermo-hydraulic and multi-phase flow models such as cavitation or particle transport into the concentrated parametric system simulation. © 2009 ASME
Training a neural network with conjugate gradient methods

This study investigates the use of several variants of conjugate gradient (CG) optimisation and line search methods to accelerate the convergence of an MLP neural network learning two medical signal classification problems. Much of the previous work has been done with artificial problems which have little relevance to real world problems and results on real world problems have been variable. The effectiveness of CG compared to standard backpropagation (BP) depended on the degree to which the learning task required finding a global minimum. If learning was stopped when the training set had been learned to an acceptable degree of error tolerance (the typical pattern classification problem), standard BP was faster than CG and did not display the convergence difficulties usually attributed to it. If learning required finding a global minimum (as in function minimisation or function estimation tasks), CG methods were faster but performance was very much dependent on careful selection of 'tuning' parameters and line search. This requirement for meta-optimisation was more difficult for CG than for BP because of the larger number of parameters.
Structure and Physical Properties of the Layered Pnictide-Oxides: (SrF)2Ti2Pn2O (Pn: As, Sb) and (SmO)2Ti2Sb2O.

The title compounds are prepared by solid state reactions using SrPn (Pn: As, Sb), SrF2, Sm2O3, TiO2, and Ti as starting materials (1000—1150 °C, 50 h) and characterized by powder XRD, resistivity, susceptibility, Hall coefficient, thermoelectric power, and heat capacity measurements.
Coastal adaptation to sea level rise along the Nile delta, Egypt

Global warming and climate change processes are expected to raise sea levels. This paper represents a contribution to the efforts of investigating the impact of sea level rise (SLR) on the Nile delta coastal zone and identifies anticipatory and adaptation measures that may be appropriate today in spite of current SLR uncertainties. SLR was calculated by applying the quadratic equation for 10-year intervals using 1980 as the base year. Despite large variation between SLR predictions, the results indicated that SLR is accelerating, with estimated value for the present (21st) century in the order of 0.6 m, although with a margin of as much as ±0.4 m. Local land subsidence in the Nile delta would exacerbate the impacts of rising seas. It was estimated that with a 1.0m SLR, about 4500 square kilometers representing 19% of the delta area will be submerged and that 6.1 million people will be affected. These potential impacts of SLR would be serious but manageable if appropriate actions are taken. The following adaptation measures to the impact of SLR in the Nile delta coastal zone were identified: maintaining and building coastal protection structures, restoration of sand dunes along the shore, preserving existing wetlands, setting regulations to control development in vulnerable areas, change of land use, relocation of infrastructures in the landward side, and development of comprehensive monitoring and early warning systems.
Toward Unsupervised Activity Discovery Using Multi-Dimensional Motif Detection in Time Series

This paper addresses the problem of activity and event discovery in multi dimensional time series data by proposing a novel method for locating multi dimensional motifs in time series. While recent work has been done in finding single dimensional and multi dimensional motifs in time series, we address motifs in general case, where the elements of multi dimensional motifs have temporal, length, and frequency variations. The proposed method is validated by synthetic data, and empirical evaluation has been done on several wearable systems that are used by real subjects.
Emission inventory of semi-volatile and intermediate-volatility organic compounds and their effects on secondary organic aerosol over the Pearl River Delta region

Abstract. Semi-volatile and intermediate-volatility organic compounds (S–IVOCs) are considered critical precursors of secondary organic aerosol (SOA), which is an important component of fine particulate matter (PM2.5). However, knowledge of the contributions of S–IVOCs to SOA is still lacking in the Pearl River Delta (PRD) region, southern China. Therefore, in this study, an emission inventory of S–IVOCs in the PRD region was developed for the first time for the year 2010. The S–IVOC emissions were calculated based on a parameterization method involving the emission factors of POA (primary organic aerosol), emission ratios of S–IVOCs to POA, and domestic activity data. The total emissions of S–IVOCs were estimated to be 323.4 Gg, with major emissions from central cities in the PRD, i.e., Guangzhou, Foshan, and Shenzhen. On-road mobile sources and industries were the two major contributors of S–IVOC emissions, with contributions of ∼42 % and ∼35 %, respectively. Furthermore, uncertainties of the emission inventory were evaluated through Monte Carlo simulation. The uncertainties ranged from −79 % to 229 %, which could be mainly attributed to mass fractions of OC (organic carbon) to PM2.5 from on-road mobile emissions and emission ratios of IVOCs ∕ POA. The developed S–IVOC emission inventory was further incorporated into the Weather Research and Forecasting with Chemistry (WRF-Chem) model with a volatility basis-set (VBS) approach to improve the performance of SOA simulation and to evaluate the influence of S–IVOCs on SOA formation at a receptor site (Wan Qing Sha (WQS) site) in the PRD. The following results could be obtained. (1) The model could resolve about 34 % on average of observed SOA concentrations at WQS after considering the emissions of S–IVOCs, and 18 %–77 % with the uncertainties of the S–IVOC emission inventory considered. (2) The simulated SOA over the PRD region was increased by 161 % with the input of S–IVOC emissions, and it could be decreased to 126 % after the reaction coefficient of S–IVOCs with OH radical was improved. (3) Among all anthropogenic sources of S–IVOCs, industrial emission was the most significant contributor of S–IVOCs for SOA formation, followed by on-road mobile, dust, biomass burning, residential, and off-road mobile emissions. Overall, this study firstly quantified emissions of S–IVOCs and evaluated their roles in SOA formation over the PRD, which contributes towards significantly improving SOA simulation and better understanding of SOA formation mechanisms in the PRD and other regions in China.
The ICCS Code: A New Development for an Old Problem.

Abstract CPHA has developed a new classification system for hospital services, the ICCS (International Classification of Clinical Services). The codes are designed to organize hospital billing data so it is more accessible and useful for both clinical and financial applications. This coding structure has been adopted by over 100 hospitals in the United States since the beginning of 1987. The paper describes the underlying principles and the development process of the ICCS code.
Capturing high‐level structure of naturally occurring, extended explanations using bottom‐up strategies

This paper notes some structural features of naturally occurring, extended explanations and argues that current generation methodologies are inadequate for determining high‐level structure. We then present a computational model for generating high‐level structure, which is based on the hypothesis that high‐level structure is distinct from text structure at lower levels and is determined by the material to be conveyed rather than by independent, recursive text structuring devices. We propose that high‐level structure can be determined by bottom‐up processes that attempt to satisfy speaker, listener, and compositional goals, after which top‐down strategies can be used to organize the material about the selected framework.
Targeted fully homomorphic encryption based on a Double Decryption Algorithm for polynomials

Several public-key encryption schemes used to solve the problem of ciphertext data processing on the fly are discussed. A new targeted fully homomorphic encryption scheme based on the discrete logarithm problem is presented. Public-key encryption cryptosystems are classified to examine homomorphic encryption. Without employing techniques proposed by Gentry such as somewhat homomorphic and bootstrapping techniques, or relinearization technique proposed by Brakerski et al., a new method called ”Double Decryption Algorithm” is employed in our cryptography to satisfy a fully or targeted fully homomorphic property. Inspired by ElGamal and BGN cryptography, we obtain the desired fully homomorphic property by selecting a new group and adding an extra component to the ciphertext. Proof of semantic security is also demonstrated.
The impact of MP3 and the future of digital entertainment products

MP3, or MPEG Layer 3 Audio, is a format for compressing digital audio developed by the Motion Picture Experts Group, a standards organization that has developed a number of digital standards for video and audio. MP3 has become a very popular format for storing music digitally. Fueled by the explosive growth of the Internet, MP3 has become the most popular format for music files, both legal and illegal (unauthorized digital copies of copyrighted works).
Traffic Information and Learning in Day-to-Day Route Choice

The aim of the research is to gain insight into the impact of traffic information on day-to-day route choice. The effects of both en-route information and ex-post information are studied. Special attention is given to three other important aspects in day-to-day route choice: learning from experience and information, habits and the effect of uncertainty / reliability. A large experiment was set up and a discrete choice model for panel data was estimated on the resulting data. Conclusions:  The more elaborate traffic information that was provided, the higher the travel time savings that were realized.  Travellers chose less reliable routes more often when they were provided with traffic information.  Whereas travellers who did not receive en-route traffic information based their expected travel time mainly on the most recent experience, travellers with en-route information used more previous experiences.  The role of past choices (used to model implicit learning and habit formation) compared to the role of the expected travel time (used to model explicit learning) was found to be relatively large in the route choice process.
Unrelated parallel machine scheduling with job splitting

Scheduling jobs on unrelated parallel machines is an activity that is very much a part of industrial scheduling. We report a methodology for minimizing the total weighted tardiness of all jobs intended to be processed on unrelated parallel machines in the presence of dynamic job releases and dynamic machine availability. More importantly, the mixed (binary) integer linear programming model formulated for the problem incorporates a couple of “hard” operational constraints to ensure that just-in-time manufacturing practices are followed by controlling the work-in-process and/or finished goods inventories generated by split jobs mandated by a tight due date, a high priority, and/or a high workload. Four different methods based on simple and composite dispatching rules are used to identify an initial solution, which is then used by the tabu-search-based heuristic solution algorithm to ultimately find the best solution. Incorporating the various tabu search features led to the development of six different heuristics that were tested on eight small problem instances to compare the quality of their solutions to the optimal solutions. The results show that the proposed heuristics are capable of obtaining solutions of good quality in a remarkably short computation time with the best performer among them recording a percentage deviation of only 1.18%. A factorial experiment based on a split-plot design is performed to test the performance of the heuristics on problem structures, ranging from nine jobs and three machines to 60 jobs and 15 machines. The results show that the newly developed composite dispatching heuristic, referred to as the modified apparent tardiness cost, is capable of obtaining initial solutions that significantly accelerate the tabu-search-based heuristics to attain the best solution. The use of a long-term memory function is proven to be advantageous in solving all problem structures. In addition, the variable tabu list size is preferred for solving the small problem structure, while the fixed tabu list size is preferred as the problem size grows from small to medium and then large.
Automatic Extraction of Cause-Effect Information from Newspaper Text Without Knowledge-based Inferencing

This study investigated how effectively cause-effect information can be extracted from newspaper text using a simple computational method (i.e. without knowledge-based inferencing and without full parsing of sentences). An automatic method was developed for identifying and extracting cause-effect information in Wall Street Journal text using linguistic clues and pattern matching. The set of linguistic patterns used for identifying causal relationships was based on a thorough review of the literature and on an analysis of sample sentences from the Wall Street Journal. The cause-effect information extracted using the method was compared with that identified by two human judges. The program successfully extracted ∼68% of the causal relationships identified by both judges (the intersection of the two sets of causal relationships identified by the judges). Of the instances that the computer program identified as causal relationships, ∼25% were identified by both judges, and 64% were identified by at least one of the judges. Problems encountered are discussed
A monolithic transformer coupled 5-W silicon power amplifier with 59% PAE at 0.9 GHz

This paper presents the circuit design and application of a monolithically integrated silicon radio-frequency power amplifier for 0.8-1 GHz. The chip is fabricated in a 25-GHz-f/sub T/ silicon bipolar production technology (Siemens B6HF). A maximum output power of 5 W and maximum efficiency of 59% is achieved. The chip is operating from 2.5 to 4.5 V. The linear gain is 36 dB. The balanced two-stage circuit design is based fundamentally on three on-chip transformers. The driver stage and the output stage are connected in common-emitter configuration. The input signal can be applied balanced or single-ended if one input terminal is grounded. One transformer at the input acts as balun as well as input matching network. Two transformers acts as interstage matching network.
Electronic learning in Slovenia

The presence or expansion of internet-based e-learning is one of the characteristics of the information society by which we can estimate the level of its development. We have witnessed many changes in Slovenia in the last decade and are interested in what is happening in the e-learning arena, especially as the internet is rather successfully penetrating Slovenian society.
Wireless propagation in urban environments: Modeling and experimental verification

Wireless communication systems play an important role in our society not only for voice transmission but also for data communications. New applications are constantly being developed and they usually result in a demand for higher transfer data rates. Therefore the design of reliable communication systems must be made with advanced engineering tools that account for the complex environment where communications take place so that higher data rates can be guaranteed. To achieve these data rates, one of the tasks that need to be accomplished is the proper characterization of the communication channel. In order to obtain a characterization of the communication channel, one must be able to describe the propagation of electromagnetic waves in the environment under consideration. At the beginning of radio communications, one of the main concerns was propagation past large obstacles, such as hills or mountain ridges, and around the earth. Diffraction is the mechanism that explains the propagation around obstacles. In order to take advantage of the classical solution for the problem of diffraction past a half plane, many earlier works have assimilated large obstacles to knife edges. Later, propagation problems have been successfully studied with a simplification of the wave equation that leads to the parabolicequation method. These different methods are described in, among other works,[1], [2], [3],[4], [5], [6],[7]. In this presentation, using ray-tracing methods, we examine the efforts that have been taken by our research group in order to provide effective models to characterize the propagation of electromagnetic fields inside urban environments. We first describe our polygonal line simulator for the analysis of electromagnetic wave propagation in a vertical plane. We then discuss its accuracy by showing the results of measurements that were taken in the frequencydomain and in the time-domain. Next the polygonal line simulator is compared with the methods of Hata , Zhang and COST-231. Then a general method to address propagation in a horizontal 2D environment is explained. Finally, we present a new 3D propagation method that is currently under development within our research group.
A personalized query expansion approach using context

When humans communicate, queries made by one human do not completely describe the requirements of the human most of the times. Still the other human involved in the communication can understand the messages better, if they share the same context and therefore know the preferences of each other. Similar to human communication, if an automated system could keep or capture the contextual information related to a user and the query, then it could use this information to process the query, resulting more useful answers. This paper is based on a research related to these factors, understanding user request better by identifying domain and task of user query and expanding user query using contextual information such as domain, user and task-specific preferences. The main steps required for this query expansion, and a domain identification algorithm to identify the query domains were proposed in the research. Sets of rules that could be used to identify the tasks and the relevant user preferences are defined in this paper. The algorithm and the rules sets were implemented and the results of the evaluation are also presented in the paper.
Programming the Connection Machine

The Connection Machine architecture provides a massive number of simple processors that execute synchronously. A language called SC is presented which makes it easy to write parallel programs for the Connection Machine. SC is an enhancement of C; it adds a few data types and primitives to develop parallel programs. The primitives introduced by SC are derived from the UNITY, a parallel-programming theory and notation. The SC primitives support the data-parallel programming style, where a processor is assumed to be assigned to each data element. However, SC programs do not adhere to a synchronous execution model and allow MIMD (multiple-instruction, multiple-data-stream) parallelism to be expressed. A preliminary description of the SC primitives and their implementation is provided. <<ETX>>
Evaluating professional development

Foreword - Dennis Sparks Acknowledgments About the Author Introduction 1. What Is Professional Development? 2. What Is Evaluation? 3. Practical Guidelines for Evaluating Professional Development 4. Level 1: Participants' Reactions 5. Level 2: Participants' Learning 6. Level 3: Organization Support and Change 7. Level 4: Participants' Use of New Knowledge and Skills 8. Level 5: Student Learning Outcomes 9. Presenting Evaluation Results References Author Index Subject Index
Target Recognition and Features ExtractionBased on ROI and SIFT Descriptors

This paper presents a target recognition method based on SIFT features matching and image ROI technology for vision system of assembly robots. In order to accelerate target recognition method, color histogram is used to detect the region of interest in images, then SIFT algorithm is employed in the ROI to extract the features. Thereby, the image Gaussian pyramid structure is simplified and the computation cost is reduced significantly. The experimental results show that this method can quickly recognize the objects without the loss of robustness and accuracy, and can provide necessary visual feedback information for assembly robots in approaching and operating task.
Rendered virtual view image objective quality assessment

The research on rendered virtual view image (RVVI) objective quality assessment is important for integrated imaging system and image quality assessment (IQA). Traditional IQA algorithms cannot be applied directly on the system receiver-side due to interview displacement and the absence of original reference. This study proposed a block-based neighbor reference (NbR) IQA framework for RVVI IQA. Neighbor views used for rendering are employed for quality assessment in the proposed framework. A symphonious factor handling noise and interview displacement is defined and applied to evaluate the contribution of the obtained quality index in each block pair. A three-stage experiment scheme is also presented to testify the proposed framework and evaluate its homogeneity performance when comparing to full reference IQA. Experimental results show the proposed framework is useful in RVVI objective quality assessment at system receiver-side and benchmarking different rendering algorithms.
Quality assessment in the blog space

Purpose – The purpose of this paper is the presentation of a new method for blog quality assessment. The method uses the temporal sequence of link creation events between blogs as an implicit source for the collective tacit knowledge of blog authors about blog quality.Design/methodology/approach – The blog data are processed by the novel method for the assessment of blog quality. The results are compared to Google Page Rank with respect to the Gold Standard, the BlogRazzi Bookmark Rank.Findings – The method is similar or better than Google Page Rank with respect to the chosen Gold Standard.Originality/value – The major contribution of this paper is the introduction of a novel method for blog quality assessment. Even though its superiority to other and more established methods cannot be proven in the context of this limited study, it enriches the toolset available for blog quality assessment and may become important for a deeper understanding of organizational learning.