Miracle-dz/UniFAR-FTUs huggingface dataset:
A concurrent function deployment-based and concurrent engineering-based product development method for original design manufacturing companies

In order to launch products earlier while balancing limited company resources, outsourcing is becoming more and more of a necessary alternative. Currently, original design manufacturing (ODM) is a convenient and potentially cost-effective production option, where outsourced suppliers (i.e. ODM companies) are contracted to handle product design and manufacturing. For ODM companies, procuring ODM business will increase sales and boost revenue. This paper presents a product development method based on concurrent function deployment and concurrent engineering to assist ODM companies in generating detailed proposals and in carrying out product development. With this method, ODM companies can engage in and effectively complete ODM projects, and, most importantly, meet customer's requirements: high quality, low cost and time-to-market. Three liquid-crystal-display television design and manufacturing companies in Taiwan will be investigated to formulate this method. An example is shown in this paper in order to present its application in a real-life setting.
Adaptive Neural Network Output Feedback Control of Uncertain Underactuated Systems With Actuated and Unactuated State Constraints

Underactuated systems are widely applied in industry, construction, manufacturing, etc., and the complex working environment puts forward higher demands for safety and transient performance. Hence, it is necessary to consider how to simultaneously ensure actuated and unactuated motion constraints by fewer control inputs, especially when systems suffer from model uncertainties, unavailable velocities, etc. Unfortunately, it is still a significant challenge to overcome in real applications and theoretical analysis. Additionally, most existing studies merely consider the specific control objects and few general methods are applicable to a class of underactuated systems. To this end, we design a new adaptive output-feedback controller for a class of uncertain underactuated systems. Compared with existing methods only handling actuated constraints, an important merit of this article is that by introducing the elaborately designed coupling term composed of actuated and unactuated constraints together, all state variables are kept within the preset time-variant ranges and converge to their desired values. Furthermore, a new Lyapunov function candidate is utilized to provide a theoretical guarantee. As far as we know, without the need of exact model knowledge and velocity feedback, this article provides the first solution to achieve accurate motion control and state constraints for both actuated and unactuated variables, which is meaningful both theoretically and practically. Meanwhile, the asymptotic stability of the equilibrium point for the closed-loop system is proven by utilizing Lyapunov techniques and Barbalat’s lemma. For verification, the presented controller is applied to underactuated overhead and rotary cranes, respectively, together with detailed theoretical analysis and experimental validations.
An intelligent maximum power extraction algorithm for inverter-based variable speed wind turbine systems

This paper focuses on the development of maximum wind power extraction algorithms for inverter-based variable speed wind power generation systems. A review of existing maximum wind power extraction algorithms is presented in this paper, based on which an intelligent maximum power extraction algorithm is developed by the authors to improve the system performance and to facilitate the control implementation. As an integral part of the max-power extraction algorithm, advanced hill-climb searching method has been developed to take into account the wind turbine inertia. The intelligent memory method with an on-line training process is described in this paper. The developed maximum wind power extraction algorithm has the capability of providing initial power demand based on error driven control, searching for the maximum wind turbine power at variable wind speeds, constructing an intelligent memory, and applying the intelligent memory data to control the inverter for maximum wind power extraction, without the need for either knowledge of wind turbine characteristics or the measurements of mechanical quantities such as wind speed and turbine rotor speed. System simulation results and test results have confirmed the functionality and performance of this method.
Exploring the Causes of Plagiarism among Post Graduate Research Students-A Phenomenological Case Study Approach

The phenomenological case study aimed to unearth the reasons that influence university students to plagiarize assignments.67 participants were selected for semi-structured interviews, from the Faculty of Education of a public university, located in Karachi, Pakistan. The obtained data were analyzed through thematic analysis. Findings uncovered that most participants lacked a deep understanding of different types of academic plagiarism and practical skills to evade it. Prevalent sources of information for preparing assignments included websites, research papers, e-books, and project reports, without verifying quality. The most common reasons that have influenced research students to plagiarize assignments included weak language and academic writing skills, easy access to online resources, conventional assignments, inadequate digital literacy, short time-frame, and challenge to balance personal, professional, and academic life. Thus, plagiarism is a conscious act coupled with indirect pressures. It is recommended to promote the culture of academic honesty among learners. In this regard, courses on preventing plagiarism, digital literacy, academic reading, and research writing should be integrated as a pre-requisite for a postgraduate research degree. It is also proposed to help learners embrace conscious networking skills and ownership of learning. Furthermore, contextual information literacy and plagiarism frameworks should be introduced.
Developing a Textile Design Recommendation System According to Consumers' Sensibilities

Abstract Analysis of customers' sensibilities and preferences is an important strategy in a market that is becoming increasingly more customer oriented. The authors propose the Textile Design Recommendation System (TDRS) as an effective tool for focusing on customers' needs in the textile industry. The authors have developed a user interface tool that can suggest textile designs according to the users' needs. Collaborative filtering was adopted to search a textile design, and the performance of TDRS was tested according to three algorithms. This system may allow textile merchandisers to meet a consumer's needs more exactly and easily.
A Novel Framework for Texture-Modified Diets is Associated with ADL Improvement in Older Adult Patients

Aims: To test our hypothesis that swallowing capacity evaluated at admission is associated with poorly improving Activities of Daily Living (ADL) in older adult inpatients and that they must be target of earlier nutritional intervention including nutritional counseling conducted by registered dietitians. Methods: Recruited subjects were consecutive all inpatients aged ≥ 65 years old admitted to a single hospital met without exclusion criteria. After dividing included subjects by with the International Dysphagia Diet Standardization Initiative Functional Diet Scale (IDDSI-FDS) score <7 (low) vs. ≥ 7 (high) at admission, all collected data was compared to draw which patients must be target of intensive nutritional intervention to achieve relevant outcome. Results: 95 patients out of 167 were included with lowvs. high-IDDSI score (n=24 vs. 71, respectively). FOIS and IDDSI score in low-group showed significantly smaller ADL change measured by differences between Barthel Index (BI) between admission and discharge compared with in high-group (0 vs. 15, respectively: p=0.004), instead nutritional management added with parenteral nutrition. The logistic regression analysis showed that odds ratio of IDDSI-FDS for BI improvement was 2.061 (95% CI: 1.124-3.777: p=0.019). Conclusion: The IDDSI score seems have an association of swallowing dysfunction followed by smaller BI improvement in older adult patient's ≥ 65 years old who must be target of intensive nutritional intervention to prevent poor outcome.
Operating control strategies and dimensioning of photovoltaic powered reverse osmosis desalination plants without batteries

Small photovoltaic reverse osmosis systems (PV-RO) without batteries are not driven constantly at their operating point, but are tracked to the solar power offered. Because of this intermittent and dynamic operation, high requirements for the operating control strategies must be satisfied. A PV-RO system has been modelled in the Dymola simulation environment. This system minimizes the specific energy consumption (SEC) and accordingly distributes the incoming PV power to the different pumps in the PV-RO system. The operating control strategy also accounts for the requirements stipulated by the membrane producer. To obtain the required amount of permeate every day of the year, a tool has been developed especially for dimensioning the PV generator for the PV-RO system under the local boundary conditions.
Numerical Investigations of the Effects of Sidewall Compression and Relaminarization in 3D Scramjet Inlet

This paper presents the numerical simulations and performance analysis of a 3D scramjet inlet with focus on the effects of sidewall compression and relaminarization. A well-validated �finite volume flow solver was used to simulate a scramjet inlet with a double ramp configuration for outer compression and varying degrees of sidewall compression. The computed wall pressure and heat transfer in the symmetry plane are in close agreement with the measurements and numerical results indicate that sidewall compression alters the inlet performance significantly. The effects of relaminarization over the expansion corner prior to the interior part of the inlet is isolated and studied in both experiment and simulation.
Compact model for ballistic MOSFET-like carbon nanotube field-effect transistors

In this work, a compact model for MOSFET-like ballistic carbon nanotube field-effect transistors (CNFETs) is presented. The model is based on calculating the charge and surface potential on the top of the barrier between source and drain using closed-form analytical formulae. The formula for the surface potential is obtained by merging two simplified expressions obtained in two extreme cases (very low and very high gate bias). Two fitting parameters are introduced whose values are extracted by best fitting model results with numerically calculated ones. The model has a continuous derivative and thus it is SPICE-compatible. Accuracy of the model is compared to previous analytical model presented in the literature with numerical results taken as a reference. Proposed model proves to give less relative error over a wide range of gate biases, and for a drain bias up to 0.5 V. In addition, the model enables the calculation of quantum and gate capacitance analytically reproducing the negative capacitance behaviour known in CNFETs.
The Role of Authentic Leadership in Shaping Performance Feedback Reactions: The Mediating Role of Trust in Leader

In this study we attempted to explore the effect of authentic leadership on followers’ feedback reactions in the performance appraisal context using trust in leader as the mediating variable. We collected data from a sample of 183 employees working in the information technology sector of Pakistan using a self-administered questionnaire, employing a cross-sectional study design with convenience sampling technique. The study provided empirical evidence about the effect of authentic leadership on performance feedback reactions and the associated mediating mechanism. It drew on authentic leadership theory and investigated why such a leadership style was important in making the performance appraisal process successful and effective. As hypothesized, authentic leadership significantly predicted perceived feedback accuracy and utility (two feedback reactions in performance appraisal). Our findings confirmed that there was a significant mediating effect of trust in leaders between authentic leadership and performance feedback reactions. The inferences drawn based on the results suggested that raters’ authenticity in performance appraisal context creates a trusting situation and leads to ratees’ perception of feedback accuracy and utility.
Adaptive cooperative communications with multiple antennas

Although multiple-input multiple-output antenna transmission is advantageous on orthogonal frequency division multiple access system, it may not be possible that practical systems have more than two antennas because of its size and cost. Therefore, cooperative communication has been recently studied as a way to solve this problem in a wireless environment. However, if cooperative communication system selects relay in a bad channel environment between source and relay, the relay has a bad effect on the bit error ratio performance. Thus, selective relay technique is proposed in this paper. The proposed system can select the best relay which has the best SNR between source and relay among the candidates. The proposed system also easily finds the best relay with low complexity.
The Impact of Perceived of Cyber Fraud, Ease of Use and Risk Perception on the Behavior of Using E-Commerce Systems in Indonesia

This study aims to examine the factors that influence interest in the use of e-commerce by using the Technology Acceptance Model (TAM) model developed by Davis (1989). This study uses survey methods in data collection. The sample of this research is the Jakarta, Bogor, Depok, Bekasi and Tangerang (Jabodetabek area) communities in Indonesia. A total of 180 respondents who have used e-commerce are processed using multiple linear regression. The results of the analysis for this model show that e-commerce usage behavior is positively influenced by ease of use and risk perception. While the perception of fraud in cyberspace is proven to have a negative effect on the interest in using e-commerce.
Analysis of Asymmetrical Deformation of Surface and Oblique Pipeline Caused by Shield Tunneling along Curved Section

The deformation of existing pipelines caused by the tunneling of a shield machine along curved sections has not been sufficiently researched, and a corresponding theoretical prediction formula is lacking. This paper derives a prediction formula for the deformation of an existing pipeline caused by shield machine tunneling along a curved section. Further, a finite difference model (FDM) corresponding to an actual project is built. Finally, the deformation of the surface and existing pipelines caused by shield machine tunneling along the curved section is analyzed. The research results show that the results of theoretical prediction, FDM calculation, and field monitoring data are consistent. In addition, the deformation of the surface and the existing pipeline are asymmetrically distributed when the shield machine tunnels along the curve section instead of symmetrically distributed (for straight line segment). When the pipeline is perpendicular to the tunnel axis, the maximum deformation position of the existing pipeline deviates from the tunnel axis by about 0.5 times the tunnel radius. In addition, as the angle β between the pipeline axis and the tunnel axis increases, the maximum deformation position of the pipeline gradually approaches the tunnel axis.
Aggregate Planning Tools for Make-or-Buy Decisions: An Industrial Engineering Suggestion

A routine managerial accounting problem is the make-or-buy decision: to make a needed industrial subcomponent/material in-house, or to outsource/buy/purchase such items, but too often, the decision is treated as a one- time cost consideration problem without taking into account often the advantages of long-term production capacities of the "making" company. This paper proposes an evaluative tool that utilizes the Aggregate Planning Transportation model problem from the applied mathematics field of Operations research, that will enable production planners or small business managers to take long-term perspectives on cost minimization on the make-or-buy decision. Operations Research (or Management Science) has been a source for applied mathematical tools in the practice of Industrial Engineering. The paper suggests that the transportation problem only takes the variable costs considerations for producing a subcomponent in-house, but does not consider the fixed costs concerns that the Assignment problem can solve. Total costs for a planning horizon of more than one-period would be the objective of this evaluation tool. Numerical examples would be provided as to show the relative combinations of production demand that would best utilize this aggregate planning model. This should provide a human-centric computational tool that only requires a basic business graduate's academic training in management science.
Freeway Network Simulation and Dynamic Traffic Assignment with METANET Tools

Traffic flow simulation and user-optimal dynamic traffic assignment (DTA) in complex freeway networks are considered. For the DTA calculation, feedback laws of the bang-bang, proportional, proportional plus integer (PI) types, and iterative algorithms that use Frank–Wolfe or PI updating formulas are investigated. Recently, METANET, a macroscopic simulation program for freeway networks, was extended to include generic feedback DTA calculation, whereas METANETDTA, a new METANET derivative, which uses iterative DTA calculation, was developed. Respective program structures and DTA functions are described. Simulation results demonstrate the DTA functions of extended METANET and METANET-DTA.
Two multistate outbreaks of a reoccurring Shiga toxin-producing Escherichia coli strain associated with romaine lettuce: USA, 2018–2019

Abstract Leafy green vegetables are a common source of Shiga toxin-producing Escherichia coli O157:H7 (STEC O157) foodborne illness outbreaks. Ruminant animals, primarily cattle, are the major reservoir of STEC O157. Epidemiological, traceback and field investigations were conducted to identify potential outbreak sources. Product and environmental samples were tested for STEC. A reoccurring strain of STEC O157 caused two multistate outbreaks linked to romaine lettuce in 2018 and 2019, resulting in 234 illnesses in 33 states. Over 80% of patients interviewed consumed romaine lettuce before illness. The romaine lettuce was sourced from two California growing regions: Santa Maria and Salinas Valley in 2018 and Salinas Valley in 2019. The outbreak strain was isolated from environmental samples collected at sites >90 miles apart across growing regions, as well as from romaine-containing products in 2019. Although the definitive route of romaine contamination was undetermined, use of a contaminated agricultural water reservoir in 2018 and contamination from cattle grazing on adjacent land in 2019 were suspected as possible factors. Preventing lettuce contamination from growth to consumption is imperative to preventing illness. These outbreaks highlight the need to further understand mechanisms of romaine contamination, including the role of environmental or animal reservoirs for STEC O157.
Change Detection of Olive Trees Distribution using Semi-Automated Object Based Image Classification

Geographic object-based image analysis (GEOBIA) is a remote sensing technique that characterize image pixels into objects based on spectral, temporal, and spatial characteristics. It is a useful technique for land use classification and change detection. In this study, a land use and land cover classification and change detection was caried out at Oum Zessar watershed in the Medenine governorate of Tunisia to estimate the changes in olive trees distribution using high resolution satellite images of 2005 and 2013 and the geographic object-based image analysis technique (GEOBIA). Eight different vegetation indices (VIs) were used to enhance the classification process. The multi-resolution segmentation algorithm was selected as the main segmentation algorithm through the entire classification process. Results showed that Normalized Difference Vegetation Index (NDVI), Normalized Near Infrared (NNIR) and Ratio Vegetation Index (RVI) had high significance to be used for the recognition of the different objects and classes. In addition, results showed that olive tree canopy increased by almost 60% from 39 ha to 62 ha in the study area during the period from 2005 to 2013. In addition, analysis of the classification results showed that the number of the trees objects increased by 22.7 % from the year 2005 to 2013. This study showed the potential of Geographic objectbased image analysis” (GEOBIA) technique in classifying land use in general and in detecting olive trees objects specifically.
High-Resolution Gridded Livestock Projection for Western China Based on Machine Learning

Accurate high-resolution gridded livestock distribution data are of great significance for the rational utilization of grassland resources, environmental impact assessment, and the sustainable development of animal husbandry. Traditional livestock distribution data are collected at the administrative unit level, which does not provide a sufficiently detailed geographical description of livestock distribution. In this study, we proposed a scheme by integrating high-resolution gridded geographic data and livestock statistics through machine learning regression models to spatially disaggregate the livestock statistics data into 1 km × 1 km spatial resolution. Three machine learning models, including support vector machine (SVM), random forest (RF), and deep neural network (DNN), were constructed to represent the complex nonlinear relationship between various environmental factors (e.g., land use practice, topography, climate, and socioeconomic factors) and livestock density. By applying the proposed method, we generated a set of 1 km × 1 km spatial distribution maps of cattle and sheep for western China from 2000 to 2015 at five-year intervals. Our projected cattle and sheep distribution maps reveal the spatial heterogeneity structures and change trend of livestock distribution at the grid level from 2000 to 2015. Compared with the traditional census livestock density, the gridded livestock distribution based on DNN has the highest accuracy, with the determinant coefficient (R2) of 0.75, root mean square error (RMSE) of 9.82 heads/km2 for cattle, and the R2 of 0.73, RMSE of 31.38 heads/km2 for sheep. The accuracy of the RF is slightly lower than the DNN but higher than the SVM. The projection accuracy of the three machine learning models is superior to those of the published Gridded Livestock of the World (GLW) datasets. Consequently, deep learning has the potential to be an effective tool for high-resolution gridded livestock projection by combining geographic and census data.