Miracle-dz/UniFAR-FTUs huggingface dataset:
Building bridges: Linking diverse classification schemes as part of a technology change project

Unifying diverse content silos requires not simply bringing together assets, but also the metadata used to manage those assets. Often, as part of technology change projects, different Knowledge Organization Systems (KOSs), such as taxonomies and ontologies, need to be related. This may involve brokering agreements between different organizational or departmental cultures. Much work on developing metadata crosswalks has been at the heading or label level, but semantic analysis also needs to be undertaken when mapping diverse KOSs and, in practice, often needs to balance preservation of local or specialized terminology with accessibility for general users. This article, based on a presentation given at the second biennial conference of the UK chapter of the International Society for Knowledge Organization (ISKO UK), describes a BBC project to bring together Archive and Production workspaces in which various metadata and KOS integration issues were encountered.
Life Cycle Cost Analysis and Carbon Credit Earned by Hybrid PV/T Solar Water Heater for Delhi Climatic Conditions

In this communication, a study has been carried out to evaluate the life cycle cost analysis and carbon credit earned by hybrid PV/T solar water heater. The study has been based on thermal, electrical and exergy output of water heater. The solar water heater is installed at Solar Energy Park, IIT Delhi. The annual energy and exergy gain have been evaluated by considering four types of weather conditions (A, B, C and D Type) of New Delhi and considering a case that the hot water is withdrawal two times in the afternoon and two times in the evening in a day. This paper gives the total carbon credit earned by hybrid PV/T water heater as per norms of Kyoto Protocol for Delhi climatic conditions. We have found that (i) the cost/kWh is higher in case of exergy when compared with cost/kWh on the basis of thermal energy (ii) if this type of system is installed at 10% of the total residential houses in Delhi then the total carbon credit earned by PV/T water heater annually in terms of thermal energy is Rs. 105.6 cores and in terms of exergy is Rs. 10.2 cores respectively. The thermal energy has wider applications in the hu- man's life. It can be generally utilized in the form of either low grade (low temperature) or high grade (high tempera- ture). The temperature profiles of the photovoltaic (PV) module in a non-steady state condition with respect to time have studied (1). The overall electrical efficiency of the PV module can be increased by increasing the packing factor (PF) and reducing the temperature of the PV module by us- ing the thermal energy associated with the PV module (2, 3). The carrier of thermal energy associated with the PV module may be either air or water. Once thermal energy withdrawal is integrated with the photovoltaic (PV) module, it is referred as hybrid PV/T system. Photovoltaic-thermal (PV/T) technology refers to the integration of a PV module and conventional solar thermal collector in a single piece of equipment. The rationale behind the hybrid concept is that a solar cell converts solar radiation to electrical energy with peak efficiency in the range of 9- 12%, depending on specific solar-cell type and thermal en- ergy through water heating. More than 80% of the solar ra- diation falling on photovoltaic (PV) cells is not converted to electricity, but either reflected or converted to thermal en- ergy. In view of this, hybrid photovoltaic and thermal (PV/T) collectors are introduced to simultaneously generate electric- ity and thermal power (4). The PV/T water heating system, two types of combi-
Massively parallel optical interconnect for long data stream convolution

Convolution of long sequences of data is often needed for various sensing, signal processing, and pattern recognition applications. In this paper, massively parallel opto-electronic interconnect schemes are proposed to solve the problem of real-time convolution of long (104 - 106) data systems. Based on the Chinese remainder theorem, a 1D data sequence of length N (N equals r1r2, where r1 and r2 are mutually prime to each other) may be permuted into a 2D array of a size r1 by r2. A convolution of the two 1D data sequences each of N points is therefore converted into a convolution of the two corresponding 2D arrays each of a size r1 X r2. A standard 2D optical image convolver sandwiched between an input and an output opto-electronic data permutation devices (interconnect networks) can thus perform the required convolution. Two video rate opto- electronic data permutation schemes which are based on: (1) the use of a modified cathode ray tube (CRT) and (2) a combination of a standard CRT and an optical geometric transformer, respectively, are described. The permuted 2D data are subject to a standard free-space optical convolution before a 2D to 1D inverse permutation to generate the final 1D convolution result. Computer simulation for the entire three-stage algorithm and their results are discussed. Technical problems and fundamental limitations of the proposed schemes are also discussed.
Research on K-means clustering algorithm and its implementation

K-means algorithm is a kind of clustering analysis based on partition algorithm, it through constant iteration to clustering, when algorithm converges to an end conditions, and the output iterative process termination clustering results. Because its algorithm is simple, and easy to realize thoughts of large-scale data clustering, so k-means algorithm has become one of the most commonly used one of the clustering algorithm. K-means algorithm can find about clustering error local optimal solution, be applied in many clustering on the question of the rapid iteration algorithm. In this paper, we deeply research and analysis of the K-means clustering algorithm in the cluster analysis and analysis of its advantages and disadvantage, finally, we implement the K-means and do an experiment for application. Keywords; K-means; Clustering center; Data mining; algorithm.
Diagnostic analysis of vibration signals using adaptive digital filtering techniques

Signal enhancement techniques are described using recently developed digital adaptive filtering equipment. Adaptive filtering concepts are not new; however, as a result of recent advances in microprocessor-based electronics, hardware has been developed that has stable characteristics and of a size exceeding 1000th order. Selected data processing examples are presented illustrating spectral line enhancement, adaptive noise cancellation, and transfer function estimation in the presence of corrupting noise.
Adaptive Automation of a Dynamic Control Task Based on Secondary Task Workload Measurement

Adaptive automation (AA) has been proposed as a method for regulating human workload and abating out-of-the-loop performance problems in complex systems control. The majority of AA or adaptive manual control studies, to this point, have facilitated control allocations using either preprogrammed schemes based on desired system performance, comparisons of human performance with established goals, or psychophysical variable monitoring to represent workload levels and determine appropriate control allocations for moderating workload. This study further explored the psychophysical assessment approach by using a secondary task measure of workload to facilitate control allocations in a complex primary task. An experiment was conducted in which participants performed a secondary gauge-monitoring task along with a simulated radar monitoring and target elimination task. Differences in single-secondary task performance and performance observed while also functioning in the primary task were used to direct operator-m.
A 1 V, 8 GHz CMOS integrated phase shifted transmitter for wideband and varying envelope communication systems

A novel fully integrated phase shifted (PS) transmitter is presented in this paper. The PS transmitter employs switching power amplifiers, operates without mixers and provides an intermodulation distortion free output spectrum making it a suitable choice for mobile communication systems. The RF blocks of the PS transmitter include a local oscillator, phase shifters, switching class F power amplifiers and wideband output combiners. The PS transmitter is implemented in a standard 0.18 /spl mu/m CMOS technology, with 1 level of polysilicon and 6 levels of metallization, and occupies an area of 5000/spl times/1000 /spl mu/m/sup 2/. It operates from a 1 V supply and provides 35 dBc adjacent channel power ratio for output bandwidths up to 50 MHz at 8 GHz. The combined class F PAs in the PS transmitter provide 20 dBm output power with a 38% power added efficiency.
Trade-Off between Bandwidth and Number of Array Elements in the Performance Enhancement of Passive Fathometer

Improved signal to noise ratio (SNR) and resolution of the ambient noise cross-correlation function (NCF) between two points help in the estimation of bottom profile of the ocean. One of the main requirements of the improvement of the SNR and resolution is collection of a large amount of data. These large amounts of data can be achieved by recording a large bandwidth ambient noise or using an array of hydrophones. This paper evaluates the performance of the array processing and compares it to the large bandwidth technique in terms of SNR and resolution of NCF. It is shown that the large bandwidth technique gives better SNR and resolution compared to the array processing technique under certain conditions. The outcome of this article finds application in the enhanced estimation of the passive fathometer.
Sequential distributed detection for multisensor data

A sequential detection algorithm is formulated for a distributed detection scheme. The data are obtained from m distant sensors. The jth sensor produces a finite-valued output u/sub j/, which is transmitted to the central detector. Data are obtained until one of two thresholds is crossed and then a decision is made. The authors analyze the performance of this distributed sequential detection scheme, and they consider the optimization of the local processors, at the front end of the sensors. <<ETX>>
R‐learning with multiple state‐action value tables

We propose a method to improve the performance of R‐learning, a reinforcement learning algorithm, by using multiple state‐action value tables. Unlike Q‐ or Sarsa learning, R‐learning learns a policy to maximize undiscounted rewards. Multiple state‐action value tables cause substantial explorations as needed and make R‐learning work well. Efficiency of the proposed method is verified through experiments in a simulated environment. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 159(3): 34– 47, 2007; Published online in Wiley InterScience (www.interscience. wiley.com). DOI 10.1002/eej.20473
The value of productivity: human-capital versus friction-cost method

Many cost-of-illness studies have investigated the impact of rheumatoid arthritis on productivity, invariably concluding that productivity costs are high. Different methods exist to value productivity. The human-capital method takes the patient’s perspective and counts any hour not worked as an hour lost. By contrast, the friction-cost method takes the employer’s perspective, and only counts as lost those hours not worked until another employee takes over the patient’s work. Both methods can produce widely different results. Productivity costs have the potential to compensate for the costs of expensive biological agents, but only in early-onset disease when patients still have jobs and if productivity is given full weight by using the human-capital method. If productivity is given less weight by excluding productivity costs or by using the friction-cost method, then currently, biological agents are probably too expensive.
Estudio evolutivo de la investigación española con células madre.: Visualización e identificación de las principales líneas de investigación

Using visualization techniques based on social networks, this study aims to analyze stem cell research in Spain, as reflected in the Science Citation Index ( SCI ) database between 1997 and 2010 , divided into three sub-periods. The selected unit of analysis was the KeyWords Plus descriptors ( KW+ ), the unit of measurement was their co-occurrence , and the Pajek and VOSviewer tools were used to generate and display the social networks. The results show two complementary images of research: the static structure, distinguishing between clinical and basic research, and the evolutionary dynamic, analysing both the most established and the emerging lines. The main contribution of this work is to present a methodology for the visualization and detection of the main r esearch lines over time, demonstrating its applicability and its predictability in scientific and geographic domains.
Distributed average consensus control in networks of agents using outdated states

Time delays are commonly considered as a negative factor in the literature on consensus problems of multi-agent systems. This, however, is not always the fact. Here, the authors propose some consensus protocols for multi-agent systems with a fixed undirected communication topology. Different from the common consensus protocols for multi-agent systems, which uses the current states only, the protocols proposed here use both current states and outdated states. It is shown that the use of the outdated information can accelerate the consensus if the consensus protocols are chosen properly. Simulation examples are given to illustrate the effectiveness of the proposed algorithms.
Research on Uncertainty of Video Content Retrieval Based on Semantic

Nowadays, video media data is already facilitates generation, transmission, storage and circulation on the global scale. Video data is geometrically fast as the rate of growth, the video data processing and analysis have lagged behind the pace of development in the growth of data, resulting in large amounts of data is wasted. Therefore, it becomes an urgent need for efficient retrieval of video data content. In this paper, firstly, starting from the color feature, the color space of digital mapping and semantic color space conversion technology is proposed according to the problem of Semantic concepts for video does not match with the perceived characteristics. And then we realize the mapping from the low-level features to high-level semantic. Finally, semantic rules of uncertainty reasoning based on cloud model established to complete video content retrieval.
Electromagnetic Transmission through Apertures of Arbitrary Shape in a Conducting Screen

In this paper, the general problem of electromagnetic coupling between two dissimilar regions, both open at infinity, via an aperture of arbitrary shape is considered. The aperture is assumed to be located in a conducting screen of infinitesimal thickness. The analysis is based on the “generalised network formulation” for aperture problems. Field equivalence principle is first used to divide the problem into two parts. Next, boundary conditions are invoked to obtain a magnetic field integral equation (MFIE) which is then solved using the method of moments (MOM). Triangular patches, with appropriately defined basis functions, are used to model the arbitrarily shaped aperture. This leads to a matrix equation whose solution requires the evaluation of integrals with bounded and unbounded kernels over a triangular domain. Representative results are given for rectangular, circular, elliptic, diamond-shaped, cross-shaped and H-shaped apertures.
Robust Self-Localization in Industrial Environments Based on 3D Ceiling Structures

This video introduces a new perceptual model for Monte Carlo Localization (MCL). In our approach a 3D laser scanner is used to observe the ceiling. The MCL matches ceiling structures like beams, columns, air condition and lightning installation against a world model containing line and point features. Thus the localization is not effected by clutter or any kind of dynamic obstacles on the ground level. Different experiments show that our system can be used to localize robustly in factory buildings and halls. Experimental results include a 5 day run of an autonomous fork lift truck at a logistics fair in Hannover.
61.3: Stereoscopic 3D Content Depth Tuning Guided by Human Visual Models

We present a new approach for tuning stereoscopic 3D content based on viewers' comfort and preferences. 2D image disparities are computed by a block matching based estimation algorithm. Human visual comfort models are applied to analyze the image disparities and guide the depth tuning (shifting/scaling) algorithms in order to generate new stereo views with desired and comfortable depth perception. Real‐life image results are shown to demonstrate the effectiveness of our approach.
Comparison of Surface Roughness of Ceramics after Polishing with Different Intraoral Polishing Systems using Profilometer and SEM

Purpose: To evaluate the effects of the different available intraoral ceramic polishing systems on the surface roughness of the latest ceramic materials. Methods: Eighty ceramic discs (5mmx2mm) were prepared from 2 ceramic materials (VM9 and e.max) using stainless steel mold. The discs were then randomly divided into 4 subgroups for each material (n=10). A Fine diamond bur was used to remove the glaze layer on one side of the disc (the other side serving as a control), and the samples were then polished by one of the 4 polishing systems (Sof-lex discs, Optrafine, EVE, and Jazz). Surface roughness was measured quantitatively by Profilometer and qualitatively by SEM. Three roughness readings were taken for each sample before being polished, after removal of the glaze layer, and after being polished. Results: The mean Ra value for the glazed surface (control) was (Ra=0.557). The lowest mean Ra value was recorded for the Sof-lex polishing system with the e.max material (Ra=0.195). The highest mean Ra value was recorded for the Jazz polishing system with the VM9 material. There was no statistically significant difference between Optrafine and EVE with VM9 and Sof-lex, Optrafine and EVE with e.max. Conclusion: The use of ceramic polishing kits was effective in reducing surface roughness. The polished ceramic samples were as smooth as their controls. Therefore, any needed adjustment to the ceramic restoration can be achieved by the use of a ceramic polishing kit, without the need for glazing.
Intrathecal Clonidine as Adjuvant for Labor Analgesia, Spinal Anesthesia, and Postoperative Analgesia in Caesarean Section

Spinal adjuvants drugs are use to enhance analgesia and anesthesia in several clinical scenarios. Clonidine has been used in anesthesia since 1982 to reduce needs of anesthetics, to provide cardiovascular stability, for anxiolysis, for sedation, and to treat pain. Although its spinal use in obstetrics patients still controversial, there is sufficient information to consider spinal clonidine as a safe adjuvant to enhance spinal labour analgesia and to improve spinal anesthesia for caesarean section, and also to augment spinal postoperative anesthesia after surgical delivery. Using recommended doses, the usual side effects of subarachnoid clonidine are moderate hypotension, non harm fetal arrhythmias, and moderate mother sedation.
Image Matching Application Based on Modified SURF Algorithm

The key technique to increase the accuracy of electronic marking is the technique of image matching, namely to match two doubtfully duplicate images. Currently there are few technologies aiming for features on test paper images with high performance on matching accuracy. The research is based on SURF algorithm and specific to the features of test paper images. Thus the research is to put forward the modified algorithm with constraints among feature spots of orientation angles on their geometrical positions, including differential constraints on critical points from approximate blank test papers with less individual features at the same time. After processing and analyzing 2,000 test paper gathered from one actual examination, the results show that the modified detection algorithm has 100% false rejection rate and 100% accuracy when it is used to detect the test paper matching.
Speaker-independent speech-driven facial animation using a hierarchical model

We present a system capable of producing video-realistic videos of a speaker given audio only. The audio input signal requires no phonetic labelling and is speaker independent. The system requires only a small training set of video to achieve convincing realistic facial synthesis. The system learns the natural mouth and face dynamics of a speaker to allow new facial poses, unseen in the training video, to be synthesised. To achieve this we have developed a novel approach which utilises a hierarchical and nonlinear PCA model which couples speech and appearance. We show that the model is capable of synthesising videos of a speaker using new audio segments from both previously heard and unheard speakers. The model is highly compact making it suitable for a wide range of real-time applications in multimedia and telecommunications using standard hardware.
Automatic Image Categorization using MPEG-7 Description

We propose an automatic image categorization technique for content-based image filtering and retrieval system. In this paper, category-feature database for image categorization is constructed on human visual perception. Query images are automatically classified into predefined categories by content-based description using MPEG-7. Similarity distances at each category are measured using multiple MPEG-7 descriptors. In this paper, a matching technique for combining multiple similarity distances is proposed. The proposed method takes into account the categorization performance of single descriptor at each category. To evaluate the proposed method, it is applied to a great number of query images randomly collected from the Internet and other image databases.
A Novel Iterated Multi-step Prediction Method of Traffic Flow ⋆

Multi-step prediction of traffic flow is very useful for dynamic navigation systems and intelligent transportation systems. A general iterative multi-step prediction is normally based on an iterative use of some one-step prediction and it usually results in error accumulation. To obtain a better method of iterative multi-step prediction and its availability, firstly based on Kalman filtering model and support vector machine model, a new combination model is designed for one-step prediction; and then a method of iterated multi-step prediction combined with the use of historical similar sequence is presented. The use of historical similar sequence in the method can significantly reduce its error accumulation. Experiment results show that its maximum prediction error growth rate within 12-step predictions (about an hour with 5 minutes as a time-interval) does not exceed 5% for the whole day and its relative error is maintained at less than 10% in peak hours.
Feature interaction detection

The feature interaction problem is a major obstacle to the rigid deployment of telecommunications features. For a feature to function correctly, its logic and assumptions must be checked against those of other existing features to detect potential interaction problems. Innovations in the detection of feature interactions, are described, including techniques generically applicable to detection of feature interactions in other domains, as well as those specifically developed for telephone networks. These techniques have been implemented in a software system called FIDO whose architecture, functionality, and operation are described. <<ETX>>