Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel orthogonal momentum-type particle swarm optimization applied to solve large parameter optimization problems

This study proposes an orthogonal momentum-type particle swarm optimization (PSO) that finds good solutions to global optimization problems using a delta momentum rule to update the flying velocity of particles and incorporating a fractional factorial design (FFD) via several factorial experiments to determine the best position of particles. The novel combination of the momentum-type PSO and FFD is termed as the momentum-type PSO with FFD herein. The momentum-type PSO modifies the velocity-updating equation of the original Kennedy and Eberhart PSO, and the FFD incorporates classical orthogonal arrays into a velocity-updating equation for analyzing the best factor associated with cognitive learning and social learning terms. Twelve widely used large parameter optimization problems were used to evaluate the performance of the proposed PSO with the original PSO, momentum-type PSO, and original PSO with FFD. Experimental results reveal that the proposed momentum-type PSO with an FFD algorithm efficiently solves large parameter optimization problems.
E-Commerce Collaborative Filtering Algorithm Research Based on Cloud Computing

With the continuous development of online shopping, a day will generate tens of thousands of consumer records. E-commerce sites want to recommend the consumers that they may be interested in the products by analyzing the consumer historical consumption data. However massive consumer records led to recommendation speed getting slow by using the traditional personalized recommendation algorithm. By researching on the collaborative filtering algorithm based on ALS and the MapReduce parallel programming model, we explore parallelization of collaborative filtering algorithm based on ALS. The experimental results show that the algorithm in this paper can improve the computing efficiency.
当代语义理论指南 = The Handbook of Contemporary Semantic Theory

Notes on Contributors. Preface. Introduction. Part I: Formal Semantics in Linguistics: . 1. The Development of Formal Semantics in Linguistic Theory: Barbara H. Partee. Part II: Generalized Quantifier Theory:. 2. The Semantics of Determiners: Edward L. Keenan. 3. The Role of Situations in Generalized Quantifiers: Robin Cooper. Part III: The Interface Between Syntax and Semantics:. 4. The Syntax/ Semantics Interface in Categorial Grammar: Pauline Jacobson. 5. Anaphora and Identity: Robert Fiengo and Robert May. 6. The Interpretation of Ellipsis: Shalom Lappin. Part IV: Anaphora, Discourse and Modality:. 7. Coreference and Modality: Jeroen Groenendijk, Martin Stokhof and Frank Veltman. 8. Anaphora in Intensional Contexts:: Craige Roberts. 9. Quantification, Quantificational Domains and Dynamic Logic: Jean Mark Gawron. Part V: Focus, Presupposition and Negation:. 10. Focus: Mats Rooth. 11. Presupposition and Implicature: Laurence R. Horn. 12. Negation and Polarity Items: William A. Ladusaw. Part VI: Tense:. 13. Tense and Modality: Murvet Enc. Part VII: Questions:. 14. The Semantics of Questions: James Higginbotham. 15. Interrogatives: Questions, Facts and Dialogue: Jonathan Ginzburg. Part VIII: Plurals:. 16. Plurality: Fred Landman. Part IX: Computational Semantics:. 17. Computational Semantics - Linguistics and Processing: John Nerbonne. Part X: Lexical Semantics:. 18. Lexical Semantics and Syntactic Structure: Beth Levin and Malka Rappaport Hovav. Part XI: Semantics and Related Domains: . 19. Semantics and Logic: Gila Y. Sher. 20. Semantics and Cognition: Ray Jackendoff. 21. Semantics, Pragmatics, and Natural-Language Interpretation: Ruth M. Kempson. 22. Semantics in Linguistics and Philosophy: An Intentionalist Perspective: Jerrold J. Katz. References. Index.
A microphone array with adaptive post-filtering for noise reduction in reverberant rooms

The author presents a self-adapting noise reduction system which is based on a four-microphone array combined with an adaptive postfiltering scheme. Noise reduction is achieved by utilizing the directivity gain of the array and by reducing the residual noise through postfiltering of the received microphone signals. The postfiltering scheme depends on a Wiener filter estimating the desired speech signal and is computed from short-term measurements of the autocorrelation and cross-correlation functions of the microphone signals. The noise reduction system has been tested experimentally in a typical office room. The system produces an enhanced speech signal with barely noticeable residual noise if the input SNR is greater than 0 dB. The received noise power-measured in the absence of the speech signal-can be reduced by 28 dB. <<ETX>>
A Statistical Analysis of Mathematical Measures for Linear Simplification

The implementation of automated cartography has resulted in the digitization of linear data and the development of simplification algorithms for generalizing these data. Some algorithms, such as the nth point and random point methods are simple in both practice and operation. Others, such as polynomial reconstruction, appear to be conceptually overly complex and computationally time consuming. This study presents a method for the evaluation of simplification algorithms. Thirty mathematical measures are developed for this purpose, including both single attribute measurements, which may be applied to a single line, and measures of displacement for evaluating differences between a line and its simplification. These measures are used to compare thirty-one unsimplified naturally-occurring lines with two simplifications of each. Using principal components analysis, correlation matrices, and cartographic judgment, the thirty measures are reduced to six by eliminating statistical redundancy. The resulting six mea.
Computer Assisted Instruction at Stanford

has been conducting a program of research and development in computer assisted instruction. For a review of the early work in CAI conducted a t Stan-ford University, see Chapter 1 of Suppes, Jerman and Brian (1968). Currently, both tutorial and drill-and-practice programs are in operation in the areas of elementary mathematics, logic and algebra , spelling, beginning reading, and elementary Russian a t the college level. A brief description of the programs now in operation in each area follows. The logic and algebra program is a three-year sequence. Last year, 195 students completed the first year of the sequence, and two students completed both the first and second years. Students who completed the first year are continuing with the second-year course this year. Others are beginning the first and third year. The student terminal is a teletype machine located in the school building. Each teletype terminal is cynected by telephone line t s a computer complex on the Stanford compus. Figure 1 shows the system configuration and lists the number of terminals for Kentucky, Mississippi, Tennessee, San Francisco, and Ravenswood, California. Logic and algebra lessons are given a t all locations except Thrs article is part of the current serles on leading centers of activity in computer assisted instruction. 22 Ravenswood, San Francisco, and a few local schools. This is the only program aimed mainly at very bright students and is offered as a supplement or enrichment to the regular mathematics program beginning at grade 5. In September, 1967, 30 students at Stanford University enrolled in a course of computer-based elementary Russian for credit. The control class received regular classroom instruction, attended the language laboratory, and submitted written homework assignments. In the computer-based class, regular classroom instruction was eliminated and work a t Model-35 teletypes with Cyrillic keyboard and audiotapes with earphones was substituted. Students received instruction at the computer-based terminals for a period of 50 minutes per day, five days a week, throughout the entire academiG year. At the end of the first year, the computer-based students performed at a statistically significantly higher level. Perhaps equally as important as the superior performance was a smaller drop-out rate for the computer-based section than for the regularly taught sections of the course. The first-year program has been revised and a second-year course written. Both are now in operation , with 41 first-year and 19 second-year students enrolled. During the 1967-68 school …
Test environment for image synthesis of a single pixel camera

Compressed sensing as an imaging method has become very popular among scientists and is becoming more and more popular among hardware manufacturers. There are many hardware variants of single-pixel compressed sensing based camera and there are many algorithms of sparse signal approximations. This fact makes it appear more and more applications of compressive imaging. Recently, many algorithms for signal reconstruction have been developed, however, all of them need many parameters to be properly set before using. Setting proper parameters is crucial for preparing a real model of the single pixel camera as well as for fast and efficient image synthesis. Because of high complexity of image recovery algorithms, image synthesis process needs to be optimized. Optimization of signal acquisition and processing parameters can be achieved running various camera simulations. In the paper we present the integrated test environment for image synthesis of the single pixel camera and the test results of simulations run with various configurations and parameters values. We used two combined adaptive methods for image reconstruction - the Newton method and the conjugate gradient method. Test environment allows to run two kinds of tests. The first test type is simulation of various parameters of acquired signal e.g. bit resolution. Image geometric transformation like rotation is the second type of tests. Simulation results include quality parameters values of MSE, PSNR and SSIM and image reconstruction time. Integrated test environment can be used during the process of hardware selection as well as during camera tests with real signals.
Adaptive fuzzy gain scheduling for load frequency control

An adaptive fuzzy gain scheduling scheme for conventional PI and optimal load frequency controllers has been proposed. A Sugeno type fuzzy inference system is used in the proposed controller. The Sugeno type fuzzy inference system is extremely well suited to the task of smoothly interpolating linear gains across the input space when a very nonlinear system moves around in its operating space. The proposed adaptive controller requires much less training patterns than a neural net based adaptive scheme does and hence avoiding excessive training time. Results of simulation show that the proposed adaptive fuzzy controller offers better performance than fixed gain controllers at different operating conditions.
Digital image quality measurements by objective and subjective methods from series of parametrically degraded images

Many digital image applications like digitization of cultural heritage for preservation purposes operate with compressed files in one or more image observing steps. For this kind of applications JPEG compression is one of the most widely used. Compression level, final file size and quality loss are parameters that must be managed optimally. Although this loss can be monitored by means of objective image quality measurements, the real challenge is to know how it can be related with the perceived image quality by observers. A pictorial image has been degraded by two different procedures. The first, applying different levels of low pass filtering by convolving the image with progressively broad Gauss kernels. The second, saving the original file to a series of JPEG compression levels. In both cases, the objective image quality measurement is done by analysis of the image power spectrum. In order to obtain a measure of the perceived image quality, both series of degraded images are displayed on a computer screen organized in random pairs. The observers are compelled to choose the best image of each pair. Finally, a ranking is established applying Thurstone scaling method. Results obtained by both measurements are compared between them and with other objective measurement method as the Slanted Edge Test.
An Approach for Finding Saliency Regions in 3D Images and Videos

-Multimedia processing applications need newly improved techniques for satisfying the new demands in the modern era. 3D multimedia applications are the new trend in the society. The main difference between the 3D and the 2D images is the depth. In addition to the color, luminance and texture , the depth factor is the major feature of stereoscopic display. So, the saliency detection models for 2D display cannot be used for stereoscopic visuals. In this paper, a simple approach is proposed for both stereoscopic images and videos. Features like color, luminance, texture and depth are extracted from the original image and convert to YCbCr color space and also from the discrete cosine transform coefficients of the feature’s. Then, a Gaussian model of the spatial distance between image patches a gradient filter is used for calculating the depth map. From that the feature map is constructed and all the feature map are combined to produce the final saliency map for 3D images and videos.
A Combined Method for Chinese Micro-Blogging Topic Tracking

To the problem of Chinese micro-blogging topic tracking, a method combined LDA model and Bagging of ensemble learning was proposed. The method firstly used the LDA hidden topic modeling, effectively solved the issue that the dataset’s sparsity of the short text, then made the C4.5 decision tree as a weak classifier, through examples resampling to obtain multiple training set, compounding the training sets according to the voting rule, and ultimately getting the similarity of the micro-blogging topic. Experiments show that, compared with the model based on single vector model, classical TF-IDF and the tracking method of C.45Bagging similarity computing, this method have a better performance on precision, recall ratio and F1 value.
A method for the registration of multiview range images acquired in forest areas using a terrestrial laser scanner

Terrestrial laser scanning can provide high-resolution, three-dimensional (3D) surveys of forest canopy surfaces. Applications that aim to build 3D forest scenes or to make plot-level or canopy-level assessments may ultimately require co-registration of range images from multiple viewpoints. Numerous challenges are reported in the co-registration of range images. A method for the registration of multiview range images acquired in forest areas using an inclinometer together with the positions of tree trunks and ground surface information is proposed in this study. Two of the six transformation parameters needed for co-registration were measured by an inclinometer. Another three transformation parameters were determined using the central positions of corresponding trunks in the two range images being registered. The last transformation parameter was determined by the fitness of ground surfaces in the two range images. A vertical filtering method is proposed for the extraction of trunk points. Similar triangles composed of trunks in the two range images were used to find corresponding trunks. Since the overlap of range images acquired at a station and that between stations was different, the registration process was divided into two stages. The range images acquired by prone scanners were first matched with the one acquired by a standing scanner at the same station. Then the range images acquired by standing scanners were used for the registration between stations. The results in our test site showed that an average registration accuracy of 0.74 cm with standard deviation (SD) of 0.23 cm within each station and an average accuracy of 3.0 cm with SD of 1.5 cm between stations were achieved.
Efficient decoding of binary shortened cyclic fire code

Channel coding adds redundant bits to the original information bits in order to detect and correct possible errors occurring during transmission. In GSM (global system for mobile communications), we use both block coding and convolutional coding for error control. One of the channel coding schemes is CS-1 (see ETSI EN 300 909 v8.5.1, 1999), which employs shortened the cyclic fire code for burst error correction. We propose an efficient way of decoding the shortened binary cyclic fire code. The proposed scheme takes 224 clock cycles for syndrome computation and another 224 clock cycles for error trapping and correction. This decoding method is much less complex than conventional schemes and slightly less complex compared to the recently patented algorithm (Ramesh et al, "Shortened Fire code. Error-Trapping Decoding Method and Apparatus", US Patent 5,936,978). The proposed decoding scheme is applicable also to any binary shortened cyclic code.
Sensitive Attributes based Privacy Preserving in Data Mining using k-anonymity

Data mining is the process of extracting interesting patterns or knowledge from huge amount of data. In recent years, there has been a tremendous growth in the amount of personal data that can be collected and analyzed by the organizations. Organizations such as credit card companies, real estate companies and hospitals collect and hold large volumes of data for their research purposes. E. g. National Institute of health. When these organizations publish data containing a lot of sensitive information. The importance of sharing data for research and knowledge discovery has been well-recognized. However, sharing data that contains sensitive personal information, such as insurance data, medical record, etc across organization boundaries can raise serious privacy concerns. There is a need to preserve the privacy of the individuals in data set . K-anonymity is one of the easy and efficient techniques to achieve privacy in many data publishing applications. In k-anonymity, all tuples of releasing database are generalized to make it anonymize which lead to data utility reduction and more information loss of publishing table. Sensitive attribute based anonymity method is very useful in preserving the privacy of individuals in organization's publication of data. It reduces information loss to the researchers by providing sensitive levels. This method also avoids Homogeneity attack and Background attacks.
Diabetes mellitus: fatores associados à prevalência em idosos, medidas e práticas de controle e uso dos serviços de saúde em São Paulo, Brasil

This study analyzes factors associated with diabetes prevalence according to demographic and socioeconomic variables, health status, and lifestyle among 872 elderly living in the city of Sao Paulo, Brazil, in addition to health services utilization and control measures and practices. Reported diabetes prevalence among the elderly was 17.9%, a higher rate than in the adult population. The highest diabetes rates in elderly individuals were associated with: bad or very bad self-rated health, never having consumed alcohol or having stopped drinking, widowhood, and at least one hospitalization in the previous 12 months, independently of age. Among the elderly, 69.9% routinely sought out health services due to their diabetes, and 96.1% received treatment at the services they turned to. There is a lack of information, knowledge, and use of control measures for diabetes among the elderly. Health policies focusing on professional training and family orientation are needed to promote lifestyle changes among the elderly.
An automatic geometric precision correction system based on hierarchical registration for HJ-1 A/B CCD images

On 6 September 2008, two optical satellites, HJ-1 A and B (HJ-1 A/B), were successfully launched from China. However, the system geometric correction products of the HJ-1 A/B charge-coupled device (HJ-1 images) have low geometric precision and need to be corrected. The HJ-1 images have a large aspect angle, a wide swath width, and a large image size. Furthermore, the local geometric distortions are too complex in one scene. Given these characteristics of HJ-1 images, geometric correction is still a challenging work. This article proposes an automatic geometric precision correction system (GPCS) based on the automatic registration between HJ-1 images and Landsat Thematic Mapper images. First, the coarse image matching method based on geometric-restricted scale-invariant feature transform (SIFT) is used to determine the coarse global transformation between the HJ-1 image and the reference image. Second, inspired by the hierarchical method of non-rigid registration for medical images, a hierarchical image matching approach is proposed based on the combination of SIFT feature points and template matching. This approach decomposes a matching problem of a whole image into numerous matching problems of image blocks and can overcome the impact of local distortions in HJ-1 images. Hierarchical random sample consensus (RANSAC) based on digital elevation model (H-RANSAC) is used to remove incorrect control points. Third, an HJ-1 image is rectified using a triangulated irregular network. Finally, the automatic evaluation method based on automatic image matching between the corrected HJ-1 image and the reference image is adopted to evaluate the geometric precision. On the one hand, experiments on eight HJ-1 images demonstrate the efficiency and accuracy of the different steps of GPCS. On the other hand, experiments on 1000 HJ-1 images also demonstrated the robustness, accuracy, and suitability for batch processing.
Light trees: optical multicasting for improved performance in wavelength routed networks

We introduce the concept of a light-tree in a wavelength-routed optical network. A light-tree is a point-to-multipoint generalization of a lightpath. A lightpath is a point-to-point all-optical wavelength channel connecting a transmitter at a source node to a receiver at a destination node. Lightpath communication can significantly reduce the number of hops (or lightpaths) a packet has to traverse; and this reduction can, in turn, significantly improve the network's throughput. We extend the lightpath concept by incorporating an optical multicasting capability at the routing nodes in order to increase the logical connectivity of the network and further decrease its hop distance. We refer to such a point-to-multipoint extension as a light-tree. Light-trees can not only provide improved performance for unicast traffic, but they naturally can better support multicast traffic and broadcast traffic. In this study, we shall concentrate on the application and advantages of light-trees to unicast and broadcast traffic. We formulate the light-tree-based virtual topology design problem as an optimization problem with one of two possible objective functions: for a given traffic matrix, (i) minimize the network-wide average packet hop distance, or (ii) minimize the total number of transceivers in the network. We demonstrate that an optimum light-tree-based virtual topology has clear advantages over an optimum lightpath-based virtual topology with respect to the above two objectives.
ADAM: A Practical Approach for Detecting Network Anomalies Using PCA

Anomalies are abnormal behaviors that can arise in any network. This paper presents a practical statistical approach for anomaly detection, analyzing various network related parameters. Our approach ADAM (Anomaly Detection and Analysis Measures), initially uses two parameters i.e. average available bandwidth (ABW) and average round-trip time (AvgRTT). We analyze samples of these two parameters by collecting randomly changing values of these parameters periodically from various remote locations around the world. Our proposed algorithm performs rigorous statistical calculations on these samples. Passing collected data to PCA (Principal Component Analysis) algorithm, which performs separation of link traffic into disjoint normal and anomalous subspaces. We compared our anomaly detection approach with the existing commercial and open-source tools that requires behavior-based and signatures-based detection respectively.