Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallelization of a Transient Method of Lines Navier–Stokes Code

Parallel implementation of a serial code, namely method of lines (MOL) solution for momentum equations (MOLS4ME), previously developed for the solution of transient Navier–Stokes equations for incompressible separated internal flows in regular and complex geometries, is described. *E-mail: ceme@metu.edu. tr The serial code was parallelized by using a domain decomposition strategy with overlapped boundary at the interfaces for information exchange between the sub-domains. A parallel virtual machine (PVM) and dual-processor personal computer (PC) connected over a switch are employed as the message passing software and the parallel computing platform, respectively. Performance of the parallelization strategy was first tested on a transient 1-D laminar pipe flow problem for MOL, explicit and implicit finite difference methods. Assessment of the performance of the parallel code (PARMOLS4ME) was then tested by applying it to two test cases; (i) laminar pipe flow with sudden expansion and (ii) turbulent flow in a gas turbine combustor simulator (GTCS) and comparing the results of serial and parallel codes. Comparisons show that the flow fields predicted by parallel codes agree well with those of serial codes at considerably lower execution times. Effects of load balancing are also investigated and it is seen that the load balancing has a significant effect on the execution time of the parallel code.
An improved power system stability criterion with multiple time delays

Since there exist significant time delays in the data of phasor measurement unit (PMU) and wide-area measurement system (WAMS), to evaluate their impact is very important for power system online stability assessment and controller design in the wide-area environment. In this paper, we use Lyapunov stability theory and linear matrix inequality (LMI) method to analyze the impact of time delays on power system stability. An improved delay-dependent stability criterion for power system stability analysis with multiple time delays is presented. Based on Lyapunov-Krasovskii theory, a proper Lyapunov functional is firstly constructed. And, in deduction of its derivative function along the system trajectory, some necessary slack variables are introduced so as to reduce the method conservativeness. Then the derivative function is expressed as a set of linear matrix inequalities, which can be easily solved with LMI toolboxes in Matlab or Scilab. Finally, a typical two-dimension time-delayed system and WSCC 3-generator-9-bus system with two time delays are employed to validate the method effectiveness. It is revealed that the presented method is correct, effective and with less conservativeness. Work of this paper is helpful for power system stability assessment and control with considering time delays under wide-area environment.
INTERACTIONS AMONG SCOLYTID BARK BEETLES , THEIR ASSOCIATED FUNGI , AND LIVE HOST CONIFERS

Scolytid bark beetles that colonize living conifers are frequently associated with specific fungi that are carried in specialized structures or on the body surface. These fungi are introduced into the tree during the attack process. The continuing association suggests that there is mutual benefit to the fitness of both beetles and fungi. The fungal species may benefit from the association with the beetles by transport to new host trees. Beetle species may benefit from the association with fungi by feeding on the fungi, or by the fungi contributing to the death of the host trees through mycelial penetration of host tissue, toxin release, interactions with preformed and induced conifer defenses, or the combined action of both beetles and fungi during colonization. Extensive research has been directed towards characterizing the interactions of beetle-fungal complexes with live host conifers and determining the ecological advantages for maintaining the associations. However, differences among systems and how species interact under different population and environmental conditions make it difficult to generalize about the importance of the separate biological components in successful host
Study on the Thermal Aging Characteristics and Bond Breaking Process of Oil-paper Insulation in Power Transformer

The degradation of transformer oil-paper insulation is decided by the chemical and physical processes in oil-paper insulation. The thermal aging plays the main role in the electrical and thermal degradation. In order to study aging mechanism of oil-paper insulation, accelerated thermal aging experiments in laboratory were performed. Four types of oil paper compounds, which are composed by regular transformer paper and thermal upgraded transformer paper and naphthenic mineral oil, BIOTEMP vegetable oil, were thermally aged for 1500 to 9500 hours at 90degC, 110degC, 130degC, respectively. The degree of polymerization (DP) and concentration of furfural dissolved in oil were measured at sampling period. The variation law of DP and furfural content in oil, the influence on aging rate caused by different kinds of oil and paper, and the linear relationship between furfural and DP were all investigated. Furthermore, bond breaking mechanism of cellulose during thermal aging was discussed based on Material studio 4.0 software.These instructions give you basic guidelines for preparing papers for conference proceedings.
Evaluation of narrow band speech codecs for Ubiquitous Speech Collection and Analysis Systems

With wireless acoustic sensor network extending to the services like surveillance of sensitive areas, such as Line of Control, or unmanned terrains, interest in robust, narrowband and low bit rate speech codecs is increasing. This has resulted in a need for evaluation of such codecs. This work investigates the different factors like bit rate, algorithmic delay, implementation, and more importantly robustness of codec's perceptual quality to noise. These factors play a vital role in choosing a speech codec and evaluating its performance. This work examines the selected narrow band speech codecs using ITU-T (International Telecommunication Union) recommendation P.862 tool. This study can also help to choose a speech codec in myriad applications like Wireless Acoustic Sensor Networks, Cellular Telephony, VoIP, Underwater Acoustic Monitoring and many other applications where bandwidth plays a vital role and data compression is inevitable.
Microfluidically Reconfigured Wideband Frequency-Tunable Liquid-Metal Monopole Antenna

A microfluidically reconfigured wideband frequency-tunable liquid-metal monopole antenna is presented. The antenna operation relies on continuous moving of the liquid-metal volume over the capacitively coupled microstrip line feed network with a micropump unit. To maximize the capacitive coupling at the feed point, the antenna is realized by bonding microfluidic channel molds prepared in polydimethylsiloxane (PDMS) polymer with 1-mil-thick liquid crystal polymer (LCP) substrate. The concept is demonstrated through the design and experimentation of a 4:1 frequency-tunable monopole antenna that operates from 1.29 to 5.17 GHz. The presented monopole antenna can also be utilized as an element to form wideband frequency-tunable high-gain antenna apertures without necessitating any additional micropump units. This is accomplished by resorting to strategically meandered or interconnected microfluidic channels. This concept is demonstrated through the design and experimentation of a 4 × 1 microfluidically controlled monopole array capable of providing 2:1 frequency tuning range from 2.5 to 5 GHz.
Survey of Classifier Systems for Intrusion Detection System

This paper describes design for intrusion detection that combines anomaly detection with misuse detection. The proposed method includes an ensemble feature selecting classifier and a data mining classifier. The former consists of four classifiers using different sets of features and each of them employs a machine learning algorithm named fuzzy belief k-NN classification algorithm. The latter applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The outputs of ensemble feature selecting classifier and data mining classifier are then fused together to get the final decision. The experimental results indicate that approach effectively generates a more accurate intrusion detection model on detecting both normal usages and malicious activities.
A Comparative Study of FIR Filters Using Vedic and Booths Algorithm

In this paper step by step procedure for the construction of a high speed FIR filter is developed based on the concept of Vedic mathematics as well as modified Booth Wallace technique. MAC units made with both these techniques give comparative results. The objective of this paper is to find the better technique suited to the application of MAC as a filter.
Association of Antineuronal Antibody Levels with Cognitive Impairment in Older Cuban Adults

INTRODUCTION Alzheimer disease is the main cause of dementia associated with aging in Cuba and the world. Development of methods for early diagnosis is vital to increasing intervention effectiveness and improving patient quality of life. Recent studies have shown associations between alterations in serum levels of antineuronal antibodies and Alzheimer disease pathology. However, the specifi c relationship between such antineuronal antibodies and Alzheimer pathogenesis remains unclear because of the great variety of antibodies identifi ed and their heterogeneity among patients and nondemented controls. OBJECTIVE Assess the association between serum levels of antibodies against neuronal antigens (total brain protein, aldolase and amyloid beta protein) and cognitive performance in older Cuban adults. METHODS A cross-sectional pilot study was conducted of adults aged ≥65 years living in Havana’s Playa Municipality and Artemisa Province (southwest of Havana). A sociodemographic and risk factor questionnaire was administered, neuropsychological assessment conducted, and physical and neurological examinations performed. A relative or caregiver was also interviewed. Laboratory tests included: complete blood count, glycemia, lipid panel, and apolipoprotein E genotype. Of 143 individuals studied, 33 were cognitively normal, 52 had mild cognitive impairment, and 58, probable Alzheimer disease. Serum antibody levels were determined by ELISA and compared using covariance analysis with a signifi cance level of 0.05. ELISA specifi city, sensitivity and predictive value were assessed by analyzing their respective diagnostic performance curves. RESULTS Patients with probable Alzheimer disease performed least well on the mini mental state examination (cognitively normal 28.8, SD 1.2; mild cognitive impairment 27.4, SD 2.2; probable Alzheimer disease 12.9, SD 6.5; ANOVA p <0.001). The percentage of Apo E4 carriers was seven times greater in the group with probable Alzheimer disease than in the cognitively normal group. Among the antibodies studied, only those against amyloid beta peptide had levels signifi cantly higher in the Alzheimer disease group than in the cognitively normal group (p = 0.007) and the group with mild cognitive impairment (p = 0.002). CONCLUSIONS Results support the presence of an autoimmune component in Alzheimer disease and suggest that serum anti–amyloid-beta could be used for its diagnosis.
Vision sharing for new service development

The integration of technologies and customer value is a key issue for technology-based companies to achieve service innovation. We are developing a methodology for service concept creation focusing on customer value exploration to address this issue. Our primary goal is to deploy our methodology (process, methods, tools, and examples) to business planning sites in our company. By taking an action research approach consisting of four steps, observation (involved in pilot projects), conceptualization, modeling, and deployment, we have clarified the basic concept of our methodology and designed a process for service concept creation: (1) sharing a vision of new services, (2) exploring customer value, and (3) creating a service concept consisting of target users (Who), customer value (What), and key technologies (How). In this paper, we discuss the issues to solve in the early stage of developing new services and illustrate our vision sharing workshop, which is characterized by the following: (1) an interaction technique for empathetic understanding through storytelling and active listening, (2) a visualization technique for sharing clarified vision, (3) a feedback technique for deep understanding. By applying the workshop to our pilot projects, we demonstrated its feasibility and effectiveness.
On-line Visual Measurement and Inspection of Weld Bead Using Structured Light

The inspection of weld seam is important for high quality of welding. This paper deals with the issue of visual measurement and inspection of weld bead and defect detection in multilayer welding. An inspection system based on laser structured light vision has been developed for weld bead profile monitoring, measuring and defect detection with scale calibration. Image processing and extraction algorithms of the laser profiles and feature points are presented. Then dimensional parameters are measured and weld defects are detected in the process of multilayer welding. Experiments were conducted with our visual inspection system using structured light.
CONSTRUCTION AND FIRST MAGNETIC FIELD TEST OF A SUPERCONDUCTING TRANSVERSAL GRADIENT UNDULATOR FOR THE LASER WAKEFIELD ACCELERATOR IN JENA

A superconducting transversal gradient undulator (TGU), tailored to the particular beam properties of the laser wakefield accelerator (LWFA) at the University of Jena, has been designed and constructed at KIT. This undulator in combination with a specialized beam transport line will be employed to produce undulator radiation with natural bandwidth despite the relatively large energy spread of the electrons (ΔE/E0 ∼ 10 %) produced by the LWFA. The fabrication of this undulator and first results of the magnetic field measurement are discussed in this paper.
Neural network-based adaptive control for induction motors

Neural network-based adaptive control scheme is developed to address the tracking problem of an induction motor (DVI) based on a modified version of field oriented control (FOC). In this paper, conventional PI controller is applied to regulate the speed and torque in the synchronous rotating coordinates. However, PI is simple but sensitive to parameter variations. Taking advantage of this fact, we aim to develop an adaptive control methodology that provides strong robustness to parameters variations, unmodelled dynamics and disturbance rejection. The obtained controller is then augmented by an online single hidden layer neural network (SHL NN) that is used to adaptively compensate for the partially known dynamics and unknown or varying system parameters. The network weights are adapted using a Lyapunov-based design. The effectiveness of the proposed controller is demonstrated through computer simulation.
Pivotal Events in Graduate Teacher Preparation for a Faculty Career.

Research I institutions produce the faculty for the majority of colleges and universities in the United States and the faculty for an increasing number of developing nations. The tremendous investment in­ stitutions of higher education make in graduate edu­ cation, in the search for outstanding faculty and in the undergraduate teaching environment make it im­ perative to support the successful development of graduate students as instructors in the undergraduate classroom. In addition, the strength of a research uni­ versity is found in the wealth of human capital. The best and brightest young scholars make up the gradu­ ate student cohort. They are a tremendous source of intellectual inspiration for undergraduates and con­ stitute a renewable resource for the future of higher education. This paper details a longitudinal study of a cohort of outstanding graduate students and their teaching experiences as they prepared for and moved into faculty roles. The researcher identified the piv­ otal events in the graduate experience which contrib­ ute to the successful preparation of teacher scholars. Pivotal events are those experiences which shape a graduate student's and new faculty's· professional development and allow them to be knowledgeable and successful participants in the academic culture of their institution. The rationale for this study is to identify and support the institutional enabling fac­ tors which contribute positive experiences while re­ ducing the events which seem to detract from the development of a professional approach to the schol­ arship of teaching.
IMM-UKF Versus Frequency Analysis [Past and Present]

In this article, we consider the degradation in the DAT loops performance caused by a gradual increase in backlash of the valve actuator (valve leakage) and several disturbances that occur in the process. The objective of this study is to develop automated strategies for fault detection, diagnosis, and isolation (FDDI) based on frequency and spectral analysis of the system response and an interactive multiple model (IMM) based on the unscented Kalman filter (UKF) estimation technique to the problem of FDDI of the valve actuator failures in DAT loops of the HVAC systems. The performance of the IMM-UKF is compared with that obtained by using the frequency analysis (FA). Both techniques are HVAC model driven-based, and the simulations results reveal the superiority of the IMM-UKF algorithm concerning its accuracy and robustness to the changes in the system structure parameters. The FDDI based on the IMM algorithm is implemented in a simulation environment, and the fault diagnosis results are presented for a several fault scenarios in terms of mode probabilities and active fault index.
Natural Disasters and Macroeconomic Performance: The Role of Residential Investment

Recent empirical research has shown that income per capita in the aftermath of natural disasters is not necessarily lower than before the event. In many cases, income is not significantly affected and surprisingly, can even respond positively to natural disasters. Here, we propose a simple theory based on the neoclassical growth model that explains these observations. Specifically, we show that GDP is driven above its pre-shock level when natural disasters destroy predominantly residential housing (or other durable goods). Disasters destroying mainly productive capital, in contrast, are predicted to reduce GDP. Insignificant responses of GDP can be expected when disasters destroy about equally residential structures and productive capital. We also show that disasters, irrespective of whether their impact on GDP is positive, negative, or insignificant, entail considerable losses of aggregate welfare.
Considerations for Secondary Prevention of Nutritional Deficiencies in High-Risk Groups in High-Income Countries

Surveys in high-income countries show that inadequacies and deficiencies can be common for some nutrients, particularly in vulnerable subgroups of the population. Inadequate intakes, high requirements for rapid growth and development, or age- or disease-related impairments in nutrient intake, digestion, absorption, or increased nutrient losses can lead to micronutrient deficiencies. The consequent subclinical conditions are difficult to recognize if not screened for and often go unnoticed. Nutrient deficiencies can be persistent despite primary nutrition interventions that are aimed at improving dietary intakes. Secondary prevention that targets groups at high risk of inadequacy or deficiency, such as in the primary care setting, can be a useful complementary approach to address persistent nutritional gaps. However, this strategy is often underestimated and overlooked as potentially cost-effective means to prevent future health care costs and to improve the health and quality of life of individuals. In this paper, the authors discuss key appraisal criteria to consider when evaluating the benefits and disadvantages of a secondary prevention of nutrient deficiencies through screening.
Compact wideband band-pass filter using regular hexagon ring resonator

A compact wide-band microstrip band-pass filter with sharp-rejection is proposed and discussed in this paper. This band-pass filter includes a regular hexagon ring resonator and two tuning stubs. Because the regular hexagon ring resonator and two tuning stubs are used, this filter not only features good band-pass filtering property, but also has two sharp stop-bands. In order to verify this new band-pass filter circuit structure and its corresponding design theory, a proposed band-pass filter using common microstrip technology are designed, simulated and measured. The measured results show excellent agreement with the simulated results. The proposed band-pass filter has compact size, low insertion loss, sharp-rejection and simple structure. Furthermore, the measured results of the fabricated microstrip band-pass filter show that the return loss is below 15 dB in the pass-band and less than 1 dB in the stop-band.
The intelligent methods for teaching quality comprehensive assessment

One of the important methods implied into teaching management is the comprehensive assessment of the teaching quality. Currently, this has been held based on weighted sum of those indexes among index system, which can not efficiently make use of the information dependency between historical information and indexes. In solving this dilemma, hierarchical naive Bayesian network was created, which can more efficiently utilize the dependency information between historical information and indexes when the three-class indexes can be either discrete or successive. In doing so, not only can comprehensive assessment of teaching quality realized, but also the quantitative analysis for the index contribution can be reached.
License Plate Detection Based on Rectangular Features and Multilevel Thresholding

Rapid advancement of technology in artificial intelligence and computer science knowledge and then feel the need to search and secure automated systems are because of the appearance of intelligent systems based on image processing and spread this knowledge. One of these intelligent systems is license plate recognition (LPR) system. LPR plays an important role in intelligent transportation system; however, plate region extraction is the key step before the final recognition. In this paper, an effective license plate extraction algorithm is proposed based on geometrical features and multilevel thresholding to identify and segment the license plate from the image. Experimental results show that the technique achieved promising accuracy.
Inhomogeneity Image Segmentation with Optimal Spatial Scale

A novel local region-based active contour model is proposed to segment medical images with intensity inhomogeneities and various noises. The contribution of the proposed work is twofold. First, the anisotropy of evolution contours is exploited to characterize the local classification information around each pixel. Integrating it with local gray intensity information, the new model stabilizes the active contours in all evolving processes. Second, under the constraint of maximum absolute error of parameter estimation, the optimal spatial scales are automatically selected for the local segmentation models. It is demonstrated from the experiments that our algorithm achieves faster and more robust results than several same-type methods.