Miracle-dz/UniFAR-FTUs huggingface dataset:
Lean Manufacturing Systems in Small and Medium Enterprises: A Framework for Lean Tools Integration

Existing lean tools are mainly dedicated to make-to- stock industries. In this paper, lean tools for make-to-order (MTO) industries are presented. The successful implementation of lean manufacturing reduces costs, improves quality, and guarantees reliability. Unfortunately, lean principles cannot be applied directly to many small and medium enterprises (SMEs) within MTO product environments. Thus, the main objective of this work is to propose a framework for integrating suitable lean tools for SMEs. The lean kit comprises the fuzzy stochastic analytic hierarchy process, value network mapping, and Cobacabana. In addition, the integrated definition for function modeling (version IDEF0) is exploited for exploring a company's activities before applying a performance improvement tool. Each tool plays a different role that aids in determining the appropriate content for implementing lean manufacturing within SMEs.
Frequency domain identification of linear time invariant systems under non-standard conditions

This paper presents a frequency domain identification method for parametric transfer function models of linear time invariant systems that takes into account the non-zero initial condition and/or the transient effects in the response of the system when excited by periodic or time limited signals. The method is useful for systems with large settling times where it takes too much time to wait measuring at the start of the experiment until the system reaches steady state. In the special case of free decay experiments the presented technique is a frequency domain version of fitting damped sinusoids embedded in noise. The theory is illustrated by simulations and a real measurement example.
FOREIGN DIRECT INVESTMENTS, TRADE OPENNESS AND CO2 EMISSIONS RELATIONSHIP: THE CASE OF 1995-2019 EU COUNTRIES

Foreign direct investments (FDI), which are very important in the economic development of countries, prefer regions with free trade. Since the share of international trade in the world economy is constantly increasing, trade openness and foreign direct investments have become more important for countries. However, the increase in trade and FDI entries can have negative effects on the environment. Although many different variables are included in the literature as determinants of carbon emission, foreign direct investments are mostly taken as an explanatory variable with the effect of the economic globalization process. The aim of this paper is to analyze the relationship between FDI, trade openness and CO2 emission for the 1995-2019 period in 24 EU countries. The relationship between variables was estimated by applying panel AMG estimator and Emirmahmutoglu and Kose causality tests to series with cross-sectional dependency. Empirical results for the overall panel show that there is unidirectional causality from carbon emission to trade openness and FDI. There is a directional causality from FDI to trade openness for the general panel has been determined. When analyzed on a country basis, there is unidirectional causality from carbon emission to trade openness for Bulgaria, Italy, Latvia, Poland, Portugal and Slovenia. Likewise, for Austria, Denmark, Estonia, Finland, France, Germany, Poland, Portugal, Spain and Switzerland, there is unidirectional causality from carbon emission to FDI. In addition, when analyzed on a country basis, there is a one-way causality relationship from foreign direct investments to trade openness for Bulgaria, Italia, Latvia, Poland, Portugal and Slovenia. For Bulgaria, Finland and Germany, there is a one-way causality from trade openness to foreign direct investment. The importance of this study derives from the emphasis on the need for environmentally protective FDIs to reduce carbon emissions.
UHF Radio Frequency Propagation Model for Akure Metropolis

During radio frequency propagation, an interaction between waves and environment attenuates the signal level. It causes path loss and finally limits coverage area. Empirical models are employed in network planning, most especially for conducting feasibility studies. This research work embraces two empirical models: Friis and Okumura-Hata and are used to predict broadcast signal strength for Akure, Ondo State, Nigeria. Measurement results of signal strength in UHF band taken in the three routes of Akure were compared with the predicted results using the empirical models. However, in this research paper, a modified Okumura-Hata model was developed and can be used for radio communication system design in Akure metropolis.
Investigation of the double peak in the visible-light range of radiative divertor emission profiles on the EAST tokamak

The double-peaked emission profile has been identified by tomographic reconstruction from the signals of the tangentially viewing visible-light imaging system on EAST. In the upper-single-null discharge with neon seeding, two light emission peaks are located near the X-point and in the high-field-side (HFS) scrape-off layer (SOL) on the poloidal cross-section while the outer divertor target is still attached. The double-peaked emission phenomenon has not been reported for other tokamaks. In particular, the existence of the emission peak near the X-point under the attached condition is unexpected because it is usually an indication of X-point multifaceted asymmetric radiation from the edge under the detached condition. Therefore, it is of fundamental importance for the divertor physics to make clear the mechanism of the double-peaked emission phenomenon. The computational simulations with SOLPS-ITER and DIVIMP are performed in this work. The simulated results show the contribution of W impurity to the double-peaked emission profile is negligible with the upper tungsten divertor. Considering the existence of a lower carbon divertor in EAST, the influence of the possible deposition of the carbon on the upper divertor is further investigated. The simulating CIII (465 nm) and CII (514 nm) emissions, which make a significant contribution to the visible-light emission in channel B (blue) and G (green), respectively, are found to be similar tothe experimental results. The emission peak near the X-point is related to the carbon deposited on the dome, while that in the HFS SOL is contributed by the carbon on the inner baffle. The ionization source of the carbon impurity and the net force pointing to the X-point are analyzed to understand the concentration of the carbon impurity near the X-point, which in turn causes the emission peak.
Content validity index: development of learning model for basic skills of basketball passing

Physical education teachers are required to be creative in carrying out learning, especially if there are problems with sports facilities and infrastructure in schools. The learning model must be adaptive, especially to the limited facilities and infrastructure of physical education. In addition, the implementation of physical education learning, most of which still uses the drill method, cannot be used in physical education learning, especially if the facilities and infrastructure owned are limited, because it will create boredom in students because of the time waiting for their turn to do motion tasks. This article aims to determine the value of the content validity index (CVI) from development research to create a learning model for the basic skills of basketball passing for students which are expected to be a solution to the problems. The learning model that will be developed later is a learning model using traditional play and sports approaches. CVI was developed by education experts and has been widely used in sharing research to determine the validity of the content. Three experts consisting of education, basketball, and learning experts were asked to evaluate the development of a learning model for basic basketball passing skills. The results of expert validation on the development of a learning model of basketball passing basic skills obtained i-CVI was 0.867 and the average proportion of items considered relevant in the three experts was 0.8; 0.8; and 0.93. The conclusion of this study is the production of products that are declared valid and can be continued at the trial stage using learning materials for traditional games of Orekan, bentengan games, and cat and mouse games. The implementation of this research is expected to be used by teachers in learning so that it is expected to improve basketball learning outcomes, especially the passing skills.
Study and Design of the Appropriate High-Performance Computing System for Beamline Data Analysis Application at Iranian Light Source Facility (ILSF)

Data analysis is a very important step in doing experiments at light sources, where multiple application and software packages are used for this purpose. In this paper we have reviewed some software packages that are used for data analysis and design at Iranian Light Source Facility then according to their processing needs, after taking in mind different HPC scenarios a suitable architecture for deployment of the ILSF HPC is presented. The proposed architecture is a cluster of 64 computing nodes connected through Ethernet and InfiniBand network running a Linux operating system with support of MPI parallel environment.
Isthmic Spondylolisthesis is Associated with Less Revisions for Adjacent Segment Disease After Lumbar Spine Fusion Than Degenerative Spinal Conditions

Elective lumbar spine fusions (LSFs) were prospectively followed-up for an average 9.7 years. The incidence of revisions for adjacent segment disease (ASD) was determined among patients with isthmic spondylolisthesis (IS) and degenerative lumbar spine disorders (DLSD). The incidence was 4.8% among patients with IS, while it was 20.5% among patients with degenerative disorders. Study Design. Prospective, follow-up study. Objective. We aim to compare the rate of revisions for ASD after LSF surgery between patients with IS and DLSD. Summary of Background Data. ASD is a major reason for late reoperations after LSF surgery. Several risk factors are linked to the progression of ASD, but the understanding of the underlying mechanisms is imperfect. If IS infrequently becomes complicated with ASD, it would emphasize the role of the ongoing degenerative process in spine in the development of ASD. Methods. 365 consecutive patients that underwent elective LSF surgery were followed up for an average of 9.7 years. Surgical indications were classified into 1) IS (n = 64), 2) DLSD (spinal stenosis with or without spondylolisthesis) (n = 222), and 3) other reasons (deformities, postoperative conditions after decompression surgery, posttraumatic conditions) (n = 79). All spinal reoperations were collected from hospital records. Rates of revisions for ASD were determined using Kaplan–Meier methods. Results. Altogether, 65 (17.8%) patients were reoperated for ASD. The incidences of revisions for ASD in subgroups were 1) 4.8% (95% CI: 1.6%–22.1%); 2) 20.5% (95% CI: 15.6%–26.7%); 3) 20.6% (95% CI: 12.9%–31.9%). After adjusting the groups by age, sex, fusion length, and the level of the caudal end of fusion, when comparing with IS group, the other groups had significantly higher hazard ratios (HR) for the revision for ASD [2) HR (95% CI) 3.92 (1.10–13.96), P = 0.035], [3) HR (95% CI) of 4.27 (1.11–15.54), P = 0.036]. Conclusion. Among patients with IS, the incidence of revisions for ASD was less than a 4th of that with DLSD. Efforts to prevent the acceleration of the degenerative process at the adjacent level of fusion are most important with DLSD. Level of Evidence: 3
MNN-XSS: Modular Neural Network Based Approach for XSS Attack Detection

: The rapid growth and uptake of network-based communication technologies have made cybersecurity a significant challenge as the number of cyber-attacks is also increasing. A number of detection systems are used in an attempt to detect known attacks using signatures in network traffic. In recent years, researchers have used different machine learning methods to detect network attacks without relying on those signatures. The methods generally have a high false-positive rate which is not adequate for an industry-ready intrusion detection product. In this study, we propose and implement a new method that relies on a modular deep neural network for reducing the false positive rate in the XSS attack detection system. Experiments were performed using a dataset consists of 1000 malicious and 10000 benign sample. The model uses 50 features selected by using Pearson correlation method and will be used in the detection and preventions of XSS attacks. The results obtained from the experiments depict improvement in the detection accuracy as high as 99.96% compared to other approaches. Bayes, J48 and bagging for the classification of malicious and benign code. The features extracted from the user-input context were used along with some basic features partic-ularly related to input, output, validation, and sanitization routines. Experimental results show that an accuracy of 92.6% was achieved using bagging. Shar et al. [18] proposed a predication model for detection on XSS vulnerabilities based on machine learning classification and clustering techniques. Hybrid attributes extracted using static and dynamic analysis were used for code for vulnerability prediction. The experiment was performed on six applications, and results show that an average of 90% recall and 85% precision was obtained. The downside of the approach is that it has huge performance overheads and high false positive rate. A study by Fang et al. [19] presented an approach for detecting XSS using deep learning. In this study the features were extracted from XSS payload. They used Long Short-Term Memory (LSTM) recurrent neural network for detection. Experimental results show that precision of 99.5% was achieved. The downside of this approach is that it has a high time complexity. A study by Stokes et al. [20] proposed and implemented a deep recurrent neural for the detection of malicious JavaScript’s. A hybrid of static and dynamic analysis was used. The presented model is highly complex, and the results produced are not convincing. Experimental results show that the applied LaMP model achieved a 65.9% true positive rate, and the best CPoLS model obtained 45.3% true positive rate, with 1.0% as a false positive rate.
Free revealing in open innovation: A comparison of different models and their benefits for companies

In open innovation processes, free-revealing of information has proliferated in the wake of distributed electronic communication systems. Many scholars have coined a multitude of concepts to explain this free-revealing phenomenon and to develop models of organising innovation based on it. These models are partly overlapping, partly exclusive, and partly encompassing. In an extensive literature review, we identify five such concepts and research streams: collective invention, user innovation networks, commons-based peer production, crowdsourcing and open-source innovation. We compare and contrast these models along several dimensions. We present an integrative perspective on the five models and derive implications for research and practice.
A robust digital current control method for active power filters

A robust digital current control strategy for active power filters using voltage-source converters is presented. The proposed control system is designed and implemented in the form of internal model control structure and takes the presence of computational time-delay into account. As a result, it provides an effectively overshoot-free reference-to-output response. The stability of the closed-loop system has much lower sensitivity with respect to parameter uncertainties compared to the case when a conventional predictive controller is used. The experimental results obtained from a DSP-based single-phase experimental active power filter are also reported.
Simulation Investigations of the Effect of a Supporting Structure Defect on the Dynamic State of the Rotor Supported on Slide Bearings

The present article reports an attempt to assess the effect of the defect having the form of supporting structure fracture on the dynamic state of the rotor supported on slide bearings. The investigations were conducted on an experimentally verified numerical model of a selected large-dimension rotating machine. Within the framework of the investigations, selected cases of a defect localised in the region of one of bearing supports were analysed. The applied method of calculations comprised two basic stages. The first stage consisted in determining complex flexibility characteristics of the supporting structure at the rotor foundation place. In the second stage the obtained flexibility characteristics, after transformation to real matrices of stiffness, damping, and apparent masses, were used for determining parameters of rotor motion. As a result of the calculations, characteristics were obtained that provide opportunities for assessing the effects of the examined defects on rotor vibrations within a wide range of rotational speeds.Copyright © 2007 by ASME
Probabilistic power flow with correlated wind sources

A probabilistic power flow model that takes into account spatially correlated power sources and loads is proposed. It is particularly appropriate to assess the impact of intermittent generators such as wind power ones on a power network. The proposed model is solved using an extended point estimate method that accounts for dependencies among the input random variables (i.e. loads and power sources). The proposed probabilistic power flow model is illustrated through 24-bus and 118-bus case studies. Finally, conclusions are duly drawn.
Improving understanding of climate change dynamics using interactive simulations

Global climate change is one of the most complex problems that human kind will face during the 21st century. Long delays in changing greenhouse gas emissions and in the response of the climate to anthropogenic forcing mean action to limit the risks of “dangerous interference with the climate system” must begin now, before further impacts of climate change are observed. However, research shows even well educated adults do not understand the time delays and other basic stock and flow dynamics of the climate, resulting in widespread belief that action to limit emissions can be delayed. Poor intuitive understanding of the dynamic structure of climate change has important consequences for building public support for mitigation policies. We introduce an interactive simulation designed to improve people’s understanding of climate change dynamics and influence their attitude towards mitigation action. We report results of an experiment using the simulator in an interactive workshop with highly educated adults. Results show a positive shift in participant opinion about the urgency of emissions reductions and improved performance on tasks involving stocks and flows in the context of climate change. Thesis Supervisor: John D. Sterman Tile: Jay W. Forrester Professor of Management, Director, MIT System Dynamics Group This Page Intentionally Left Blank To my shooting star, she shines above to guide me and within to inspire me. This Page Intentionally Left Blank -
Direct nonlinear power MESFET parameter extraction and consistent modeling

A novel method is developed which permits a direct nonlinear FET parameter extraction of the gate source capacitor and diode, the drain current generator, and the avalanche breakdown characteristics from large-signal waveform measurements. Differences between the DC and RF characteristics of the drain current generator and the breakdown characteristics are observed and interpreted. The measured FET output power and phase spectra are compared with simulated results for different RF models of the nonlinear drain current generator. The proposed method is a valuable instrument for the analysis of the existing high-frequency FET nonlinearities and can be used to improve large-signal FET models. <<ETX>>
Knowledge Management Success in an Engineering Firm

Does engineering organizations knowledge use organizations and engineers knowledge workers? This paper says positively and discusses the need for knowledge management in engineering organizations. Unfortunately, the knowledge management literature does not provide much guidance on how to measure the success or benefits of doing knowledge management in an engineering or other knowledge using organization. This paper discusses research that proposes a definition of knowledge management success and dimensions and measures that organizations can use to value knowledge management success. A case study of a nuclear utility engineering organization is used to illustrate how these dimensions and measures can be used to demonstrate the success of a knowledge management
Context-Assisted Fast Face Detection

In this paper, we propose a novel algorithm for fast face detection in camera video. By extending the task of face detection from solely relying on visual data of camera sensor to cooperatively analyzing synchronized information of multiple sensors, we greatly reduce the time cost of face detection. Specifically, when subjects wearing motion sensors move around in the field of view (FOV) of a camera, motion status estimated from the wearable sensors helps to decide when is the good time to start face detection, and thus save large amount of work previously spent on filtering out faceless frames. To test the technical feasibility and efficiency of the proposed method, we conducted extensive experiments and compared it with state-of-the-art algorithms. Results indicate that the proposed algorithm achieves significant improvements in terms of time cost.
Building a One-Dimensional Teacher: Technocratic Transformations in Teacher Education Policy Discourses

Abstract In the context of neoliberal reforms, teacher education policy discourses have shifted away from social justice imperatives toward technocratic approaches. I examine these shifts by applying the tools of critical policy and discourse analysis to accreditation standards and other policy texts of the last decade. Using Marcuse’s theory of one-dimensional subjects, I analyze how teacher education policy discourses position teachers as agents of social control whose work is to preserve the status quo and to legitimize the current structures of domination. This positioning is accomplished through the technocratization of teacher knowledge and depoliticization of diversity and equity in teacher preparation. The significance of this analysis lies in establishing connections between the technocratization of teaching pursued by the recent wave of teacher education policy discourses and the maintenance of inequality that teacher education redesign is expected to support.
Making the Cut and Winning a Golf Putting Championship: The Role of Approach-Avoidance Achievement Goals

Golf is a global game enjoyed yearly by tens of millions. Effective ways to improve golf performance, especially putting, the club used the most, is of value to all golfers. Hence, the purpose of the present prospective study was to further the knowledge of the impact of approach-avoidance achievement goals on golf putting performance. Participants (N = 175) from university run golf courses participated in a two-round qualifying putting tournament with 81 participants making the cut to the championship round. Achievement goals, at the dispositional level, from Elliot and McGregor’s (2001) 2 × 2 framework (i.e., mastery-approach, masteryavoidance, performance-approach, and performance avoidance) were collected 5 weeks before the tournament, and then, at the contextual level, minutes before each round. Results indicated that those who made the cut line had significantly greater endorsement of the mastery-approach goal and lower endorsement of the performance-avoidance goal compared with those who missed the.