Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Face Recognition Using GABOR Filter And Different Self Organizing Maps Neural Networks

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given. The next stage is the classification stage, and consists of self-organizi ng map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20 people with six images for each person and a measure of the time differences between the methods is given. Keyword: Self-Organizing Map, Gabor filter.
Online dialog: What if you build it and they don't come?

In 1995 we built an online dialog capability to supplement student class-time discussion of course topics in a senior undergraduate-graduate course in Global Change. We naively thought this would promote deeper learning. The resulting discussion could most accurately be described as superficial remarks spiced with personal agendas, religious fervor, cutesy comments, and an occasional spark of academic interest. We quickly realized we needed a different means of explicitly emphasizing use of critical thinking skills and social interaction to enhance learning. We provide herein a chronology of our experiences toward achieving what we believe to be an improved, although certainly not perfect, method for engaging students in substantive online dialog on global change issues. Global Change is a 1-semester, 3 credit course offered over 15 weeks as a regular on-campus course or (starting Spring 2003) as a distance education course. The 15-week semester is divided into 3 equal length “blocks” with approximately 15 learning units (e.g., lectures under the former system) in each block. Instructor evaluation and student self assessment is done at the end of each block. Typically there are students from about 20 different disciplines in each class, which provides a rich mixture of perspectives on global change issues. The course went online in 1995 with both content and student discussion. Course content for the present implementation is freely available on the internet at http://www.meteor. iastate.edu/gccourse but the dialog is managed from within student online portfolios that are password protected. The growing course content and annual addition of archived student dialog allows for a rapidly expanding database of learning materials for global change issues. We first reported on initiation of this online course at this conference in 1996 (Takle and Taber, 1996) and have described attributes of the course in various conferences and papers (e.g., Takle et al, 1998, 2000, 2002; Sorensen and Takle, 2001a, b, 2002).
HIV-1 Vpu is a potent transcriptional suppressor of NF-κB-elicited antiviral immune responses

Many viral pathogens target innate sensing cascades and/or cellular transcription factors to suppress antiviral immune responses. Here, we show that the accessory viral protein U (Vpu) of HIV-1 exerts broad immunosuppressive effects by inhibiting activation of the transcription factor NF-κB. Global transcriptional profiling of infected CD4 +T cells revealed that vpu-deficient HIV-1 strains induce substantially stronger immune responses than the respective wild type viruses. Gene set enrichment analyses and cytokine arrays showed that Vpu suppresses the expression of NF-κB targets including interferons and restriction factors. Mutational analyses demonstrated that this immunosuppressive activity of Vpu is independent of its ability to counteract the restriction factor and innate sensor tetherin. However, Vpu-mediated inhibition of immune activation required an arginine residue in the cytoplasmic domain that is critical for blocking NF-κB signaling downstream of tetherin. In summary, our findings demonstrate that HIV-1 Vpu potently suppresses NF-κB-elicited antiviral immune responses at the transcriptional level.
A Design on the Communication Protocol for Data Collection of the IOT Based on Cold Chain System

This paper designed and analyzed the communication protocol for the data communication between the IOT device and the middleware server of the IOT based Cold Chain Monitoring System. In this regard, we have referenced the CoAP Protocol Model of IETF CoRE WG, and analyzed and designed the process status flow, data flow and frame format of the IOT device (IOTD) and the middleware server. In order to test the effectiveness of the proposed Cold Chain Communication Protocol, we have produced the Zigbee, Bluetooth and wifi module mounted gateway and the temperature, humidity sensor. After sending the temperature data from the IOTD to the middleware server, we analyzed the received data from the middleware server. As the result, we were able to interpretate the data sent from the IOTD, and identify that in using these data the cold chain data such as the temperature, humidity, and battery remains data can be collected in real time.
Are our Educational Technology Systems Secure

The use of information and communication technology is an essential part of any contemporary higher-level educational system. Web applications that are accessed via web browsers over a network such as Internet or intranet are dominant in almost all education systems, such as universities, training, and research institutions. In particular, web based systems are used as informative or interactive web pages. Since these web pages contain critical information, securing educational systems is as important as securing any banking system. It has been noticed that some academic institutions have not fully secured their web pages against some class of vulnerabilities. In this empirical study, we elaborate these vulnerabilities and show their existence in the web sites of one of the academic institutions and describe the tools, techniques and results of our experiments.
Regularised Anisotropic Nonlinear Diffusion for Rendering Refraction in Volume Graphics

Rendering refraction in volume graphics requires smoothly distributed normals to synthesise good quality visual representations. Such refractive visualisation is more susceptible to noise in the data than visualisations that do not involve refraction. In this paper, we addresses the need for improving the continuity of voxel gradients in discretely sampled volume datasets using nonlinear diffusion methods, which was originally developed for image denoising. We consider the necessity for minimising unnecessary geometrical distortion, detail the functional speci(cid:2)cation of a volumetric (cid:2)lter for regularised anisotropic nonlinear diffusion (R-ANLD), discuss the further improvements of the (cid:2)lter, and compare the ef(cid:2)cacy of the (cid:2)lter with an anisotropic nonlinear diffusion (ANLD) (cid:2)lter as well as a Gaussian (cid:2)lter and a linear diffusion (cid:2)lter. Our results indicate that it is possible to make signi(cid:2)cant improvements in image quality in refractive rendering without excessive distortion.
A Parallel Space Saving Algorithm For Frequent Items and the Riemann – Hurwitz zeta distribution

A parallel version of the Space Saving algorithm to solve the k– majority problem is presented. The algorithm determines in parallel frequent items, i.e., those whose multiplicity is greater than a given threshold, and is therefore useful for iceberg queries and many other different contexts. We apply our algorithm to the detection of frequent items in a stream of data whose probability distribution function is a Riemann–Hurwitz or Zipf–Mandelbrot distribution.
Eine umfassende Constraint-Dependenz-Grammatik des Deutschen

The Hamburg implementation of the Weighted Constraint Dependency Grammar formalism (WCDG) includes an example grammar with comprehensive coverage for written German. This manual is the annotation guideline that was used to define the goals of the grammar and to create the Hamburg Dependency Treebank also published in the course of this project.
Cephalopod assemblages caught by trawling along the Iberian Peninsula mediterranean coast

The cephalopod fauna collected in five MEDITS-ES trawl surveys carried out on the Iberian Mediterranean coast was analysed. Hauls, which were carried out in spring between 1994 and 1998, numbered 480. A total of 34 cephalopod species, grouped in 11 families, was found at depths of between 25 and 786 m. Species and samples assemblages were analysed with the Bray-Curtis similarity index. From the physical parameters studied (depth, temperature and bottom type) only depth showed a positive correlation with cephalopod distribution. Three main cephalopod communities were defined: the shelf community ( 480 m) and a group of cephalopods which were widely distributed more abundantly on the lower continental shelf-upper slope (150-480 m). SIMPER analysis revealed that Loligo (Alloteuthis) media was the main indicator species of the shelf group, Eledone cirrhosa was the indicator species of the lower shelf upper slope group and Todarodes sagittatus of the middle slope community. The 150-480 m stratum was considered a transitional zone, representing an overlapping region for shelf and slope faunas.
UNCERTAINTY VISUALIZATION TESTING

The issue of spatial data quality and representation of uncertainty related to it has again attracted attention in relation to the INSPIRE Directive. Therefore, a number of approaches and methods of uncertainty visualization has been developed based for example on Bertin’s theory of graphic variables and combining both static and dynamic elements of visualization. Despite partial achievements and existing conceptual approaches to uncertainty visualisation, relatively little is known about specific influence of certain visualization on end users, especially on their ability to use the given visualization in an effective and unambiguous way. The presented paper describes the process of test development for selected methods of cartographic visualization of both positional and thematic uncertainty. The web-based testing application MuTeP was used enabling parallel testing of heterogeneous user groups, automatic recording of test results, and semiautomatic processing for final evaluation.
From ‘fearing’ to ‘empowering’ climate refugees: Governing climate-induced migration in the name of resilience

The concept of resilience was born and grew up in the environmental sciences during the 1970s. After migrating into many other disciplines, resilience is now ‘coming home’ to the politics of the environment in the name of security. The field of climate change induced migration is investigated as a paradigmatic case of environmental security. On a theoretical level, resilience is studied as a governmentality; that is, as advanced liberal government which governs through contingency. On an empirical level, a brief genealogy of environmental migration is presented with a focus on the latest discursive shift towards resilience. It is demonstrated that climate change induced migration was once represented as a pathology to be prevented and, more recently, as an issue of refugee rights. However, the shift towards resilience has reframed the debate. Climate change-induced migration is now presented as a rational strategy of adaptation to unavoidable levels of climate change and the relocation of millions of people is rendered acceptable and rational. The most drastic policy implication of this shift is that the space of the political is eliminated. Climate change is presented as a matter of fact rather than as a social problem that could still be tackled by significant emission reductions and lifestyle changes by residents in the major developed economies.
Comparative transcriptome analysis of mammary epithelial cells at different stages of lactation reveals wide differences in gene expression and pathways regulating milk synthesis between Jersey and Kashmiri cattle

Jersey and Kashmiri cattle are important dairy breeds that contribute significantly to the total milk production of the Indian northern state of Jammu and Kashmir. The Kashmiri cattle germplasm has been extensively diluted through crossbreeding with Jersey cattle with the goal of enhancing its milk production ability. However, crossbred animals are prone to diseases resulting to unsustainable milk production. This study aimed to provide a comprehensive transcriptome profile of mammary gland epithelial cells at different stages of lactation and to find key differences in genes and pathways regulating milk traits between Jersey and Kashmiri cattle. Mammary epithelial cells (MEC) isolated from milk obtained from six lactating cows (three Jersey and three Kashmiri cattle) on day 15 (D15), D90 and D250 in milk, representing early, mid and late lactation, respectively were used. RNA isolated from MEC was subjected to next-generation RNA sequencing and bioinformatics processing. Casein and whey protein genes were found to be highly expressed throughout the lactation stages in both breeds. Largest differences in differentially expressed genes (DEG) were between D15 vs D90 (1,805 genes) in Kashmiri cattle and, D15 vs D250 (3,392 genes) in Jersey cattle. A total of 1,103, 1,356 and 1,397 genes were differentially expressed between Kashmiri and Jersey cattle on D15, D90 and D250, respectively. Antioxidant genes like RPLPO and RPS28 were highly expressed in Kashmiri cattle. Differentially expressed genes in both Kashmiri and Jersey were enriched for multicellular organismal process, receptor activity, catalytic activity, signal transducer activity, macromolecular complex and developmental process gene ontology terms. Whereas, biological regulation, endopeptidase activity and response to stimulus were enriched in Kashmiri cattle and, reproduction and immune system process were enriched in Jersey cattle. Most of the pathways responsible for regulation of milk production like JAK-STAT, p38 MAPK pathway, PI3 kinase pathway were enriched by DEG in Jersey cattle only. Although Kashmiri has poor milk production efficiency, the present study suggests possible physicochemical and antioxidant properties of Kashmiri cattle milk that needs to be further explored.
Identification and Classification of Jinhua Ham by Electronic Nose

An electronic nose(E-nose) was developed to distinguish different grades of Jinhua hams through detecting the aroma of three types of Jinhua ham samples to obtain the response value respectively.Then the data was analyzed by using Principal Component Analysis(PCA),Linear Discriminant Analysis(LDA) and Partial Least Squares(PLS). LDA was used for identification,PCA for dimensionality reduction and PLS for prediction.Results showed that electronic nose can distinguish different grades of Jinhua hams.The method was confirmed in prediction of Jinhua hams with different grades.The research will provide an important scientific knowledge to improve and perfect the national standard of Jinhua hams in future.
Research and Application of Grain Pests Detection and Classification Technology

This paper presents the technique of the detection and classification of stored-product pest and provides the hardware composition ofthe detection system. With reference to the first order gray histogram of pest images and their graphic target zones, a new technique and method areprovided to extract the mathematical and statistic feature, texture feature and geometrical configuration features of the pests are acquired. Asexperiments demonstrates, this digital image processing technique can reveal a range of reliable eigenvalue and effectively increase the efficiency ofidentification. This technique has become a new vehicle to the classification and identification of stored-product pest.
Feature compensation algorithm based on vector Taylor series for speaker recognition

A feature compensation algorithm based on vector Taylor series(VTS) is applied to the speaker recognition system.The approximate closed-form solution of the channel variance is derived,and a joint rapid estimation framework for convolution noise and additive noise is proposed.The mean and variance of convolution noise and additive noise can be estimated from the mismatch speech to compensate the environment mismatch without any other prior information about the mismatch environment.The experimental results show that the compensation of the channel variance maximally reduces the error rate by 3.24%,which improve the system performance in the wireless environment with large channel variations.Compared with feature mapping algorithm and cepstrum mean subtraction algorithm based on the linear distortion model,the proposed algorithm decreases the system error rate by 49.65%and 68.06%at maximum in the wireless environment with additional noise,respectively,especially for the mismatch environment of large channel variations.
A Sorting Algorithm Based on Selection Sort Strategy

This paper discusses an improved algorithm based on selection sorting,which employs stacks to remember previous compared information.This algorithm takes half of the original time in mass records.As for a small quantity of records,this algorithm is the best on the whole among all the sorting algorithms based on comparison and shift.Moreover,it is sensitive to the ordered degree of the original sort.When the original sort is comparatively in order,the speed is relatively high.The result shows that this sorting algorithm is quite fit for a small quantity of sorting,portion sorting,comparatively ordered sequence sorting and the combination with quick sort algorithms.
Multiphase Voltage Regulator Modules with Magnetic Integration to Power Microprocessors

(ABSTRACT) Advances in very large scale integration (VLSI) technologies impose challenges for voltage regulator modules (VRM) to deliver high-quality power to modern microprocessors. As an enabling technology, multiphase converters have become the standard practice in VRM industry. The primary objectives of this dissertation are to develop advanced topologies and innovative integrated magnetics for high-efficiency, high-power-density and fast-transient VRMs. The optimization of multiphase VRMs has also been addressed. Today's multiphase VRMs are almost universally based on the buck topology. With increased input voltage and decreased output voltage, the multiphase buck converter suffers from a very small duty cycle and cannot achieve a desirable efficiency. The multiphase tapped-inductor buck converter is one of the simplest topologies with a decent duty cycle. However, the leakage inductance of its tapped inductors causes a severe voltage spike problem. An improved topology, named the multiphase coupled-buck converter, is proposed. This innovative topology enables the use of a larger duty cycle ii with clamped device voltage and recovered leakage energy. Under the same transient responses, the multiphase coupled-buck converter has a significantly better efficiency than the multiphase buck converter. By integrating all the magnetic components into a single core, in which the windings are wound around the center leg and the air gaps are placed on the two outer legs, it is possible for multiphase VRMs to further improve efficiency and cut the size and cost. Unfortunately, this structure suffers from an undesirable core structure and huge leakage inductance. An improved integrated magnetic structure is proposed to overcome these limitations. All the windings are wound around the two outer legs and the air gap is placed on the center leg. The improved structure also features the flux ripple cancellation in the center leg and strongly reverse-coupled inductors. Both core loss and winding loss are reduced. The steady-state current ripples can be reduced without compromising the transient responses. The overall efficiency of the converter is improved. The input inductor can also be integrated in the improved integrated magnetic structure. Currently, selecting the appropriate number of channels for multiphase VRMs is still an empirical trial-and-error process. This dissertation proposes a methodology for determining the right number of channels for the optimal multiphase design. The problem formulation and general method for the optimization are proposed. Two examples are performed step by step to demonstrate the proposed optimization methodology. Both are focused on typical VRM 9.0 designs for the latest Pentium …
RFID dynamic positioning method

A novel proximity method-RFID dynamic positioning method was presented,using a moving radio frequency identification(RFID) reader to accurately position the target based on reference tag arrays.The major advantage of the method was that through reading tags without any measurement data,e.g.,the time of arrival(TOA) or the received signal strength indication(RSSI),it improved the accuracy of positioning target based on reference tags and a moving reader.The algorithm was simple but useful.Based on the performance of the prototype system,it demonstrated that the proposed system could accurately position in one of the smallest reference tag cell(within dozens of centimeters) and could be deployed easily with low cost,thus has potential application in RFID warehouse management.
Application of compressed sensing theory in image processing

Traditional Shannon sampling method leads to a large amount of image data,and massive data processing brings a great pressure to bear on the post-processing of image information.Compressed Sensing(CS) theory which can overcome the problem mentioned above is researched in this paper.It can reconstruct a large amount data by sampling small quantity data,and breakthroughs the restriction of Shannon sampling theory.This paper reviews the theory and key technique of CS,and introduces the application and development of CS in imaging system,image fusion,target recognition and tracking.It points out that the CS theory is an effective data processing,and more extensive applications will be come true with the development of the theory.
Visualization of Cascading Failures in Power Grids

This paper introduces a new visualization platform for investigating cascading failures in power grids. The proposed visualization platform could let people “watch” the cascading behavior under different initial triggers, and help them understand how a failure propagates from one or more local substations to the whole power grid. In this study, the ArcMap is adopted to take charge of visualizing a power grid network and the user interface. All scripts to support this platform, e.g. constructing a power grid network and simulating cascading failures, are written in Python, a popular industrial computer language. The power grid around Bay Area is used to test the proposed visualization platform and investigate the single node (i.e. substation) failure cases. The proposed visualization platform successfully demonstrated how the failure of a node can propagate in the power grid and cause large-scale power outage.
Research on Image De-noising Algorithm

This article discusses the characteristics of digital image noise and its mathematical model,and on this basis to discuss various denoising methods,mainly airspace de-noising method and frequency-domain de-noising method,there are now compared the number of heat new methods,such as mathematical morphology,neural networks.At the same time,this article also discusses the advantages and disadvantages of each method have been studied at home and abroad.At last,give the latest research results and development prospects of de-noising algorithm.