Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimized Design of PMSM With Hybrid-Type Permanent Magnet for Improving Performance and Reliability

This paper proposes an optimized design of permanent magnet (PM) synchronous motor (PMSM) using hybrid-type PM for improving the output characteristics and reliability. Here, the hybrid-type PM is defined as using both neodymium PM (Nd-PM) and ferrite PM (Fe-PM) in a rotor. First, a basic design of PMSM is conducted by considering the magnetic equivalent circuit and applying the magnetic characteristic of Fe-PM changed by the reversed flux of Nd-PM. For optimizing the motor using hybrid-type PM, parallel configuration of reluctance factors is helpful for increasing the output characteristics, and it is analyzed by using a finite element method (FEM). In addition, by using an algorithm, an optimized design is suggested for obtaining maximum torque. The performances of target and proposed motors are compared through FEM. Next, the irreversible demagnetization of each motor is analyzed at high and low temperature, and the demagnetization phenomenon of two-type motors is compared for verifying the reliability of the proposed motor. Finally, prototypes of reference and proposed models are developed for evaluating the enhanced performance through comparison between the two motors.
Alignment of Business Strategy and it Strategy: A Case Study of A Fortune 50 Financial Services Company

In recent years, information technology (IT) has become a critical tool for the execution of business strategy and a driver of business strategy. The alignment of business strategy and IT strategy has emerged as a critical issue for organizations. Using a case study approach, this research study identifies the reasons why alignment gaps exist between business strategy and IT strategy and suggests methods which can be used to minimize those strategy alignment gaps. Senior executives at a large Fortune 50 financial services company were interviewed in order to examine whether alignment gaps between business strategy and IT strategy existed at this organization, the reasons why the strategy alignment gaps exist, and how the strategy alignment gaps could be minimized. The results suggest that improving the business strategy and vision, and communication of the business strategy and vision has the greatest potential for improving the alignment of business strategy and IT strategy. The degree of alignment between various business areas was found to have a major impact on the alignment of business strategy and IT strategy. Two effective methods of aligning IT strategy and business strategy were identified: (i) developing a robust, business architecture, and, (ii) establishing a separate, centralized IT department.
DCT-based Least-Squares Predictive Model for Hourly AQI Fluctuation Forecasting

Recently the issue of air quality has become a global public health concern. As air pollution has been reported as the largest single environmental health risk in the world, analysis and prediction of air quality is increasingly important. Normally, either statistical models or CTM (“deterministic chemistry-transport”) models are used for forecasting air PM (“particulate matter”) levels. Actually, hourly air quality fluctuation is also one time-series. Compared with commonly used deterministic photochemical air quality models, data-driven or time-series-based modeling is simpler and can also perform well even be more accurate. In this study, a called DCT(“discrete cosine transform”)-based least-squares predictive model is proposed for forecasting hourly AQI (“air quality index”) from time-series analysis or data-driven modeling perspective. The proposed DCT-based predictive method is implemented in combination with the least-squares method to compute the called least-squares-optimum DCT coefficients for forecast modeling on the basis of finite hourly AQI observations. The proposed method yields one good result of average 93.24% predictive accuracy in forecast experiments at five monitoring stations in Xiangtan of China. Experimental results and analysis of performance comparisons of the proposed DCT-based least-squares predictive model with the classical BP-ANN model, the Fourier-series-based least-squares predictive model and the ARIMA model indicate that for the same tasks of forecasting hourly AQI fluctuations, the proposed DCT-based predictive model outperforms the former two competitive models and performs slightly better than or comparable to the ARIMA model. It is indicated that the hourly AQI fluctuations can be well forecasted by the proposed DCT-based least-squares predictive model with using about 12-term least-squares-optimum DCT coefficients.
Design and Simulation of a 12 Gb/s Transceiver With 8-Tap FFE, Offset-Compensated Samplers and Fully Adaptive 1-Tap Speculative/3-Tap DFE and Sampling Phase for MIPI A-PHY Applications

This brief presents a fully adaptive high-speed serial interface designed in 28-nm planar CMOS technology for future mobile industry processor interface (MIPI)-compliant automotive microcontrollers operating at 12 Gb/s over long-reach channels. The transmitter has a voltage-mode driver and operates at full rate featuring an 8-tap feed-forward equalizer with tap programmability of 1/16. The transmitter’s output impedance tuning is performed through activation of different driver replicas. The half-rate receiver features an analog front-end which comprises a variable-gain amplifier and a continuous-time linear equalizer. The subsequent decision-feedback equalizer (DFE) has three programmable taps, the first of which is loop-unrolled to relax timing constraints. Another amplifier is embedded in the DFE’s summing node. We employ transistor-level simulations to assess the capability of the interface to optimally adapt to realistic channels: the DFE taps and the data sampling phase are automatically adapted by means of a behavioural implementation of an least mean squares algorithm based on information gathered through error sampling. Such an interface was simulated on channels representing likely MIPI A-PHY to-be-defined specifications featuring up to 33 dB loss at 6 GHz.
The founding of a southern elephant seal colony

The only large mainland colony of southern elephant seals (Mirounga leonina) is on PenValdat 42 ◦ S, in Argentine Patagonia. Censuses of pups have been carried out regularly there since 1970, and the population grew five-fold by 2010. Here we use Bayesian modeling tools to make rigorous estimates of the rate of population growth, r, and to estimate survival and recruitment parameters that couldaccountforthegrowth,incorporatingobservationerroracrossdifferentcensus methods. In the 1970s, r = 8%/yr, but has slowed to <1%/yr over the past decade. Using explicit demographic models, we established that the high growth of the 1970s was consistent with adult and juvenile survival at the upper end of published values (0.87/yr adult female survival; 0.40 juvenile survivorship to age four); the decline in the rate of population growth from 1970 to 2010 can be described by density-dependent reductions in adult and juvenile survival that fall well within published variation. Extrapolating empirical models of population growth rate backwards illustrates that the population could have been an established colony, with 100 pups born per year, between 1915 and 1945, consistent with qualitative observations prior to 1950. We conclude that the Vald´ es colony was founded by a few immigrants early in the 20th century and has been growing mostly by internal recruitment, with unknown density-dependent processes causing a reduction in growth and stabilization at 15,000-16,000 pups born.
Accurate Classification for Automatic Vehicle-Type Recognition Based on Ensemble Classifiers

In this paper, a real-world problem of the vehicle-type classification for automatic toll collection (ATC) is considered. This problem is very challenging because any loss of accuracy even of the order of 1% quickly turns into a significant economic loss. To deal with such a problem, many companies currently use optical sensors (OSs) and human observers to correct the classification errors. Herein, a novel vehicle classification method is proposed. It consists in regularizing the problem using one camera to obtain vehicle class probabilities using a set of convolutional neural networks (CNNs) and, then, uses the Gradient boosting-based classifier to fuse the continuous class probabilities with the discrete class labels obtained from the OS. The method is evaluated on a real-world dataset collected from the toll collection points of the VINCI Autoroutes French network. The results show that it performs significantly better than the existing ATC system and, hence, will vastly reduce the workload of human operators.
Who Uses Ride-Hailing Services in the United States?

Over the past few years, ride-hailing services have rapidly gained in popularity and grown extensively in the United States (U.S.). Using data from the 2017 National Household Travel Survey, this paper investigates the socio-demographic and land use factors that affect the adoption and frequency of use of ride-hailing services in the U.S.A. First, a comprehensive literature review is carried out to identify the gaps in the literature. Next, a detailed descriptive analysis is conducted to understand the key socio-demographic characteristics of the ride-hailing service users. Finally, an ordered logit (ORL) model is estimated to investigate the socio-demographic and land use factors that affect the adoption and frequency of use of ride-hailing services. Results suggest that racial differences exist in the adoption and frequency of use. Specifically, African American individuals are less likely than others to adopt and frequently use these services. People who work full time but with flexible schedules are more likely than other workers and non-workers to adopt and frequently use these services. The tendency to adopt and frequently use these services is higher among individuals in insufficient vehicle households (i.e., households with more workers than vehicles) than other individuals. The presence of children, elderly persons, or both, in the household is likely to have a negative effect on the adoption and frequency of use. Further, these services appear to have a complementary effect on public transit, indicating that collaboration efforts between transit agencies and ride-hailing service providers may help develop an integrated transportation system.
Comparison between rule- and optimization-based workload control concepts: a simulation optimization approach

An important goal of Production Planning and Control systems is to achieve short and predictable flow times, especially where high flexibility in meeting customer demand is required, while maintaining high output and due-date performance. One approach to this problem is the workload control (WLC) concept. Within WLC research two directions have been developed, largely separately, over time: Rule based and optimisation-based models. If a company intends to introduce an order release concept based on WLC it first has to decide which of these two approaches should be applied. Therefore, this paper compares two of the most widely used and considered best performing periodic order release models out of both streams: the LUMS (rule based) and the clearing function model (optimisation based). The parameters of both approaches are set using simulation optimisation. The performance is compared using a simulation study of a hypothetical job shop in a rolling horizon setting. The results show that the optimisation model outperforms the rule-based mechanism in all instances with stochastic demand (exponential inter-arrival times), but is outperformed in aggregate cost of backorders and inventory holding and balancing measures by the LUMS approach for scenarios with high utilisation and seasonal demand.
FAKTOR-FAKTOR YANG MEMPENGARUHI PENGGUNAAN E_FILLING PADA WAJIB PAJAK ORANG PRIBADI DI JAKARTA BARAT

The purpose of the research is to examine whether perceived usefulness, perceived ease of use, complexity, security and privacy, attitude toward using, readiness technology taxpayers information and voluntariness of using have significant effect on the e-filing use. Th isresearch conducted on individual taxpayers located in West Jakarta. Total respondents were used as samples are as many as 100 people . This research uses SPSS version 23 software ( Statistical Product and Service Solution 2 3 ) and Microsoft Excel inthe processing of research data. The results of this research show that perceived ease of use, complexity, security and privacy, readiness technology taxpayers information and voluntariness of using have a significant effect on the e-filing use, while attitude toward using don’t have a significant effect on e-filing use. Key word s : Perceived Usefulness, Perceived Ease of Use, Complexity, Security and Privacy, Voluntariness, Readiness Technology Taxpayers Information, Tax General Knowledge, E-Filing Use
A Review on Swarm Intelligence Based Routing Approaches

The principles of bio-inspired or swarm intelligence algorithms can be effectively used to achieve optimal solutions in routing for complex and dynamic wireless sensor networks or body area networks. As the name indicates, it is a field that is inspired by natural living beings like ants, bees, fishes, etc. Studies have proved that the routing protocols based on such bio-inspired methods perform better in terms of energy efficiency, reliability, adaptivity, scalability, and robustness. The general classification of routing protocols is classical-based and swarm-based routing protocols, where both the protocols were specifically categorized as data-centric, location-aware, hierarchical and network flow, and QoS aware protocols. In this paper, an evocative taxonomy and comparison of various swarm-based routing algorithms are presented. A brief discussion about the sensor network design and the major factors that influence the routing is also discussed. The comparative analysis of the selected swarm-based protocols is also done with respect to routing characteristics like query based, route selection, energy efficiency, and path selection. From the review, it is observed that the selection of a routing protocol is application dependent. This paper will be helpful to the researchers as a reference on bio-inspired algorithms for new protocol designs and also for the proper selection of routing protocols according to the type of applications.
Avoiding Starvation in Tribocontact Through Active Lubricant Transport in Laser Textured Surfaces

Laser texturing is a viable tool to enhance the tribological performance of surfaces. Especially textures created with Direct Laser Interference Patterning (DLIP) show outstanding improvement in terms of reduction of coefficient of friction (COF) as well as the extension of oil film lifetime. However, since DLIP textures have a limited depth, they can be quickly damaged, especially within the tribocontact area, where wear occurs. This study aims at elucidating the fluid dynamical behavior of the lubricant in the surroundings of the tribocontact where channel-like surface textures are left after the abrasion wear inside the tribocontact area. In a first step, numerical investigations of lubricant wetting phenomena are performed applying OpenFOAM®. The results show that narrow channels (width of 10 μ m ) allow higher spreading than wide channels (width of 30 μ m ). In a second step, fluid transport inside DLIP textures is investigated experimentally. The results show an anisotropic spreading with the spreading velocity dependent on the period and depth of the laser textures. A mechanism is introduced for how lubricant can be transported out of the channels into the tribocontact. The main conclusion of this study is that active lubricant transport in laser textured surfaces can avoid starvation in the tribocontact.
Influence of attention on speech-rhythm evoked potentials: first steps towards an auditory brain-computer interface driven by speech

A brain-computer interface (BCI) uses neuronal responses to control external systems. The majority of BCI systems are based on visual stimuli, only few apply auditory input. Because auditory-based BCI do not rely on visual skills or mobility of the body, they could be an alternative for visually or physically disabled people. This study investigates the performance of an auditory paradigm using two competing streams of repeatedly presented speech syllables. The streams had different repetition rates of 2.3 and 3.1 Hz. Our auditory BCI approach uses the auditory steady-state response (ASSR) to automatically detect which stream a listener selectively attends to. In a single trial classification ten healthy volunteers achieved an accuracy significantly above chance of 61% and an information transfer-rate (ITR) of 0.2 bit min−1. The use of the average over six random trials improved the average classification accuracy to 79% while keeping the ITR comparable. In conclusion it is possible to classify ASSR evoked from streams of spoken syllables. For a real life application it is necessary to improve the performance of this auditory BCI, but it is a step towards the long term goal of using BCI on natural speech features and eventually controlling the processing of hearing devices.
Steady Flow of a Cement Slurry

Understanidng the rheological behavior of cement slurries is important in cement and petroleum industries. In this paper, we study the fully developed flow of a cement slurry inside a wellbore. The slurry is modeled as a non-linear fluid, where a constitutive relation for the viscous stress tensor based on a modified form of the second grade (Rivlin–Ericksen) fluid is used;we also propose a diffusion flux vector for the concentration of particles. The one-dimensional forms of the governing equations and the boundary conditions are made dimensionless and solved numerically. A parametric study is performed to present the effect of various dimensionless numbers on the velocity and the volume fraction profiles.
SUBSTITUTION OF TRADITIONAL CONCENTRATES WITH GREWIA OPPOSITIFOLIA LEAVES IN SHEEP

An experiment was conducted in a 4 x 4 Latin Square Design, involving four cross bred wethers (F1, Kag hani x Rembouilet) of 50 kg + 2 kg body weight, four diets and four feeding peri ods. The diets were chopped sorghum hay as basal di et (diet A), basal diet with cottonseed cake (diet B), basal diet with maize oil cake (diet C) and basal diet with Grewia oppositifolia leaves (diet D). The wethers were kept in individual metabolic crate s. The experiment was conducted at NWFP, Agricultural University Dairy Farm Malakandair and was lasted for sixty days consisting four feeding periods. Each period was consis ted of ten days adaptation followed by five days data collection. The crude pr otein contents were highest (26.04%) in cottonseed cake followed by G. oppositifolia leaves (17.25%), maize oil cake (16.21%) and was l owest in the basal diet (4.77%). Supplements affect the intake of basal diet; the higher total dry matter intake (TDM I) of the basal diet was recorded with diets C and B followed by diet D. No difference (P>0.05) in the dry matter and organic m atter digestibility were observed among the four di ets. The nitrogen digestibility of the basal diet was significantly l ower than that containing leaves (P<0.05). Based on the present findings, it has undoubtedly confirmed that G. oppositifolia leaves, the cheapest among the purchasable sources of N in the country, has improved the utilization of basal diet through incr eased total dry matter intake and nitrogen digestib ility. Therefore, it is concluded that G. oppositifolia leaves can successfully replace the traditional pr otein supplements in sheep.
Industrial Revolution 4.0 and Education

The purpose of this paper is to discuss what happen to education system in the era of Industrial revolution 4.0 (IR 4.0). Information management is the most challenging issue faced by any organisations in developing countries. Everybody has an excessive number of wellsprings of leisure activity. Our brains are always being rewired because of diminished capacities to focus. What we realize among our education won't keep going for the whole career as the technologies is speeding up. Indeed, even schools are not extremely supportive in picking profession way. The fourth Industrial Revolution (IR 4.0) has changed the landscape of educational innovation. IR 4.0 is controlled by artificial intelligence and digital physical frameworks that make human-machine interface more universal. Quick revolution in innovation has delivered another model of education for the future ─ Education 4.0. To prepare graduates for future life and work achieved by IR 4.0 where more smart robots will supplant people in certain activity divisions, education should harness on pertinent information and abilities that couldn't be replaced by robots. Innovation interruption that produces Education 4.0 that focuses on educational development and skill has made future learning more customized, hyper, intelligent, portable, worldwide and virtual. Past the 21st century abilities, advanced skill and development, for example, Artificial Intelligence (AI), huge information and examination, distributed computing and portable arrangement, online networking, the Internet of Things (IoT), Virtual Reality (VR) and Augmented Reality (AR) with computerized pleasures are in a general sense changing the flow of education and instructional advances landscape into new type of computerized teaching method and smart classroom. IR 4.0 that detonated exponentially has rambled the future learning into wonderland. Sci-fi moves toward becoming science certainty ─ where creative energy knows no bound; and virtual and augmented reality is crawling into smart classroom. Self-sufficient and intelligent robots, rambles, vehicles and classrooms are joys of the day. As cutting edge educators, we have to investigate new and creative approaches to utilizing educational innovation to upgrade future learning. In this regards, this introduction hypothesizes the requirement for instructors to re-examine their old originations of instructing and learning and upgrade their understudies' learning encounters so they meet the requirements of Education 4.0.
The knowledge management of micro-firms in the crowd: key challenges for successful operations*

Abstract Crowdfunding platforms are increasingly being used by small and micro-firms to fund the development and initial promotion of their new products. The transition from a crowdfunding campaign to the subsequent operational phase is critical to successfully fulfil the expectations of the backers who supported the micro-firm and expect to receive the new product. This paper analyzes the main challenges that must be faced by micro-firms during this transition, adopting the perspective of knowledge management theory. Based on an exploratory case study analysis, the paper highlights the particularities of these knowledge management challenges in terms of knowledge diversity, dependence and novelty. Asymmetry, dispersion, synchronization, a lack of a common understanding and backer lock-in are the main knowledge-based challenges for the operations of micro-firms that use crowdfunding. Various theoretical and practical implications of the findings are offered.