Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Fault Diagnosis Expert System of CNC Machine Tool Based on Expert Knowledge

CNC machine tools play a pivotal role in the manufacturing field. Due to the complexity and diversity of faults, experienced engineers who can quickly locate the cause of faults are rather scarce. This paper takes expert knowledge in the field of fault diagnosis as the research object and proposes an ontology-based knowledge expression structure to improve fault retrieval efficiency and fault diagnosis accuracy; then applies the SimRank algorithm to calculate the similarity between fault phenomena and fault causes in the case base to guide the work of maintenance engineers. Finally, this paper introduces the diagnosis process of machine tool fault diagnosis expert system with Siemens 808d CNC system as a case study.
InP/AlGaAs Based CSDG MOSFET With Au/Pt Gate Materials for High Frequency/Hybrid Applications

Aluminium Gallium Arsenide (A1xGa1-xAs- Arbitrary Alloy) is a material used in the latest high-frequency devices for the advantages of the lesser band-gap and also optimal electron mobility coefficient. The value of resistance between the source and drain in the A1xGa1-xAs material is lesser than other material that makes the Indium Phosphide (InP) material most suitable to grow contacts on the Aluminium Gallium Arsenide (AIGaAs). These materials will have a very low thermal budget as it is mainly based on the ion implantation model for designing. Re-grown contacts like drain and source have serious issues such as higher parasitic capacitances, which need utmost care while designing the MOSFET. The velocity of the electrons in the proposed model had considerably increased than the conventional MOSFETs by 14.63 % in the Au-Pt pair and 11.90 % in the Au-Au pair. The devices with the capability of higher electron mobility can be used in high-frequency device fabrication. This proposed work shows better performance in terms of electron mobility, conduction band profile, and transconductance. Hence it can be used in radio frequency applications and high precision equipment.
The dynamics of employee relations. 3rd ed.

The Dynamics of Employee Relations provides a critical assessment of employee relations within contemporary organizations. Written in a lively and readable style, The Dynamics of Employee Relations captures the essence of working reality within a variety of working environments. The third edition has been updated to include insights into the latest developments in the field and contains new case studies to illustrate the nature of employee relations at the turn of the century. A must read for all undergraduate, postgraduate and MBA students studying employee relations and a valuable resource for anyone engaged in grappling with the challenges presented by employee relations in contemporary workplaces. Also available is a companion website with extra features to accompany the text, please take a look by clicking below - http://www.palgrave. com/business/blytonandturnbull/index.asp
Development of Remotely Configurable Range Timing Display System

In a Test Range, network configuration plan is decided on the basis type and trajectory of missile to be tested. This paper presents the development of Range timing display system with the facility of configuring its network credentials remotely from a central location. The paper explains the scheme which consists of client software and management software. Client software is dumped over Raspberry pi board to be placed at remote stations and management software to be placed at single central location for controlling all the time display devices. The comparison of performance of new device with conventional device is also discussed.
The influence of dietary protein and energy levels on the performance, meat bone ratio and meat chemical composition of SenSi-1 Agrinak chicken

<p class="Default"><span lang="EN-US">Sensi-1 Agrinak is a strain of the improved native chickens for meat production in Indonesia. The objective of </span><span lang="IN">this</span><span lang="EN-US"> study was to investigate influence of different dietary energy and protein levels on </span><span lang="IN">p</span><span lang="EN-US">erformance, meat bone ratio</span><span lang="IN">,</span><span lang="EN-US"> and meat chemical composition of Sensi-1 Agrinak chicken, reared until 10 weeks of age. Two hundred and sixteen of unsexed day old chickens (DOC) of Sensi-1 Agrinak were subjected to six experimental rations differed in dietary crude protein (CP) content,. </span><span lang="IN">Namely:</span><span lang="EN-US"> 21;19; and 17 % and dietary metabolizable energy (ME) (2800 and 3000 kcal/kg). Each treatment combination was replicated four times and fed from day old to 10 weeks old. In each treatment combination there were nine unsexed-DOCs. The parameters observed were performance (i.e. live weight, feed intake, viability, FCR), economic index (European Production Efficiency Factor/EPEF), meat bone ratio, and meat chemical composition. </span><span lang="IN">R</span><span lang="EN-US">esult showed that </span><span lang="EN-US">increas</span><span lang="IN">ed</span><span lang="EN-US"> of dietary CP level increased live weight and EPEF (p<0.05). Sensi-1 Agrinak chicken had the best FCR (2.59), when fed diet containing 21% CP and 3000 kcal/kg. Increas</span><span lang="IN">ed</span><span lang="EN-US"> dietary CP level increased the meat-bone ratio of breast, thighs, and drumsticks. Meanwhile, increas</span><span lang="IN">ed</span><span lang="EN-US"> levels of dietary CP and ME did not affect (p>0.05) meat chemical composition. It </span><span lang="IN">is</span><span lang="EN-US"> concluded that optimal dietary levels of crude protein and energy for unsexed Sensi-1 Agrinak chicken up to 10 weeks of age were 21% CP and 3000 kcal/kg. </span></p>
Power Consumption Characteristic of low power Wireless Transceivers

Wireless transceivers are typically the most power-hungry component in wireless sensor nodes. A closer investigation into the power consumption behavior of these components can lead to the optimization of wireless sensor networks or IoT systems. In this paper, we present an analytical method based on the energy efficiency Figure of Merit (FoM) to estimate the power consumption characteristics of a typical MOSFET-based wireless transceiver. We show that the best energy efficiency can be achieved in a radio transceiver when the energy consumed in the receiving mode is approximately equal to the energy consumed during transmission.
A comparison of decision-feedback equalizers for a 9600 bit/s modem

When a digital data signal is received over a linear channel that distorts the signal, the resulting intersymbol-interference can be removed, or at least greatly reduced, by means of a decision-feedback equalizer. A conventional equalizer is adjusted adaptively to minimize the mean-square error in the equalized signal, where the error is caused partly by intersymbol interference and partly by noise. Alternatively, the equalizer may be adjusted adaptively to minimize the noise in the equalized signal, subject to the accurate equalization of the channel. The latter equalizer is usually easier to adjust close to its ideal setting, for both timeinvariant and time-varying channels.The paper compares the tolerances to additive white Gaussian noise of the two equalizers, for the particular application of digital data transmission at 9600 bit/s over telephone circuits. Theoretical analysis is used to compare the equalizers, first for the case where there is a very high signal/noise ratio, and then for the case where the channel introduces pure phase distortion. Computer-simulation tests over models of six different telephone circuits are used to compare the equalizers for more general situations where the signal/noise ratio is not very high and where there is amplitude distortion in the received signal.
EEG-Based Emotion Recognition Using Genetic Algorithm Optimized Multi-Layer Perceptron

Emotion Recognition is an important problem within Affective Computing and Human Computer Interaction. In recent years, various machine learning models have provided significant progress in the field of emotion recognition. This paper proposes a framework for EEG-based emotion recognition using Multi Layer Perceptron (MLP). Power Spectral Density features were used for quantifying the emotions in terms of valence-arousal scale and MLP is used for classification. Genetic algorithm is used to optimize the architecture of MLP. The proposed model identifies a. two classes of emotions viz. Low/High Valence with an average accuracy of 91.10% and Low/High Arousal with an average accuracy of 91.02%, b. four classes of emotions viz. High Valence-Low Arousal (HVLA), High Valence-High Arousal (HVHA), Low Valence-Low Arousal (LVLA) and Low Valence-High Arousal (HVHA) with 83.52% accuracy. The reported results are better compared to existing results in the literature.
Predicting the Health Impacts of Commuting Using EEG Signal Based on Intelligent Approach

Commuting to work is an everyday activity for many which can have a significant effect on our health. Commuting on regular basis can be a cause of chronic stress which is linked to poor mental health, high blood pressure, heart rate, and exhaustion. This research investigates the neurophysiological and psychological impact of commuting in real-time, by analyzing brain waves and applying machine learning. The participants were healthy volunteers with mean age of 30 years. Portable electroencephalogram (EEG) data were acquired as a measure of stress level. EEG data were acquired from each participant using non-invasive NeuroSky MindWave headset for 5 continuous activities during their commute to work. This approach allowed effects to be measured during and following the period of commuting. The results indicate that whether the duration of commute was low or large, when participants were in a calm or relaxed state the bio-signal alpha band exceeded beta band whereas beta band was higher than alpha band when participants were stressed due to their commute. Very promising results have been achieved with an accuracy of 97.5% using Feed-forward neural network. This work focuses on the development of an intelligent model that helps to predict the impact of commuting on participants. In addition, the result obtained from the Positive and Negative Affect Schedule also suggests that participants experience a considerable rise in stress after their commute. For modelling of cognitive and semantic processes underlying social behavior, the most of the recent research projects are still based on individuals, while our research focuses on approaches addressing groups as a complete cohort. This study recorded the experience of commuters with a special focus on the use and limitation of emerging computing technologies in telehealth sensors.
Dietary supplementation of dairy cows with a docosahexaenoic acid-rich thraustochytrid, Aurantiochytrium limacinum: effects on milk quality, fatty acid composition and cheese making properties

Polyunsaturated fatty acids (PUFA) are considered essential for general health and wellbeing (Gómez Candela et al., 2011), and may also play a role in limiting the effects of a number of chronic diseases (Ruxton et al., 2014). Omega-3 (n-3) and omega-6 (n-6) PUFA are both required to maintain good health; however, in many western countries n-3 fatty acid (FA) intake is below recommended levels, while n-6 PUFA intake is often considerably above recommended levels (Simopoulos, 2008). To address the lack of n-3 PUFA available in the food chain, dietary supplementation of intensively farmed animals with microalgae has been successfully used to increase the n-3 PUFA content in animal products (Moran et al., 2018a,b,c; 2019). For ruminants, the alteration of unsaturated fatty acids to form saturated fatty acids by ruminal microbes, via the processes of lipolysis and biohydroABSTRACT. The aim of this study was to evaluate the effect of heterotrophically grown docosahexaenoic acid (DHA)-rich thraustochytrid Aurantiochytrium limacinum (AURA) added to dairy cow diet on milk fatty acid profile and milk cheese making properties. The secondary aim was to investigate the effect of pelleting on DHA transfer from diet to milk. Thirty six lactating dairy cows were blocked by parity, number of days in milk and by milk production and randomly assigned to 1 of 3 diets: AURA (150 g/cow/day) with protein concentrate in pelleted or meal form, and control group – protein concentrate in pelleted form without AURA. Milk samples from each cow were taken on days 0, 28, 56 and 84. Dietary supplementation for 84 days resulted in the successful enrichment of milk with DHA, at a level of 4.47 and 6.37 mg/100 ml milk for the groups supplemented with AURA in a pelleted and meal form, respectively. As less DHA was detected in the pelleted concentrate (470 vs 570 mg/kg), and subsequently in the milk of the groups fed these pellets, the process of pelleting may have resulted in a loss of DHA from the feed. Dietary supplementation with AURA improved milk quality: increased DHA content and lowered n-6:n-3 ratio. With no differences observed for the cheese making properties of milk from cows fed supplemented or control diets, it can be stated that milk obtained from cows fed diet enriched with DHA-rich thraustochytrid Aurantiochytrium limacinum at a dose 150 g/cow/day (which gives about 24 g DHA/cow/day) can be suitable for cheese production. Received: 18 January 2018 Revised: 24 January 2019 Accepted: 11 March 2019
Reliability methods applied to The IEEE Gold Book Standard Network

Several key reliability indices for industrial and commercial customers are a knowledge of the reliability and the frequency and duration of load point interruptions within their electrical power system networks at their facilities. A reliable equipment data source is key to an accurate analysis. Data sources, such as The IEEE Gold Book provide the user with the necessary data parameters to evaluate the reliability of industrial and commercial power system network configurations. An accurate understanding of component reliability and maintenance actions will provide the necessary availability indices for a reliability analysis approach. This paper discusses The IEEE Bold Book Standard Network and three reliability models: spreadsheet reliability model; GO software tool; and minimal cut-set reliability analysis methodology.
A Compact U-Shaped Antenna with Bandwidth Enhancement for Ultra- Wideband Communication

A compact coplanar waveguide (CPW) fed printed monopole antenna having dimension 36×22×0.8 mm3 is designed and evaluated for ultra-wideband (UWB) communication applications. A bending is introduced into the modified U -shaped radiator at the lower ends of the radiating patch and in the adjacent edges of the coplanar ground plane for bandwidth enhancement. Antenna performances are demonstrated from its reflection coefficient (S11), radiation patterns, gain, and radiation efficiency. This designed antenna is providing a broad impedance bandwidth ranging from 3-12.4 GHz highlighting 122% improvement. The antenna exhibits omni-directional radiation pattern with a gain variation between 1.4-4.8 dBi which is invariable and an average radiation efficiency of 90% in its impedance band. The experimental outcome shows good enough achievement which is also compatible with the simulated one.
Isolation , characterisation and genome assembly of Barnettozyma botsteinii sp . nov . and novel strains of Kurtzmaniella quercitrusa isolated from the intestinal tract of the termite Macrotermes

14 Bioconversion of hemicelluloses into simpler sugars leads to production of a significant amount of 15 pentose sugars, such as D-xylose. However, efficient utilization of pentoses by conventional yeast 16 production strains remains challenging. Wild yeast strains can provide new industrially relevant 17 characteristics and efficiently utilize pentose sugars. To explore this strategy, we isolated gut18 residing yeasts from the termite Macrotermes bellicosus collected in Comoé National Park, Côte 19 d ́Ivoire. The yeasts were classified through their ITS/LSU sequence, their genomes were 20 sequenced and annotated. We identified a novel yeast species, which we name Barnettozyma 21 botsteinii sp. nov. 1118 T (MycoBank: 833563, CBS 16679 T and IBT 710) and two new strains of 22 Kurtzmaniella quercitrusa: var. comoensis (CBS 16678, IBT 709) and var. filamentosus (CBS 23 16680, IBT 711). The two K. quercitrusa strains grow 15% faster on synthetic glucose medium 24 than Saccharomyces cerevisiae CEN.PK T in acidic conditions (pH = 3.2) and both strains grow on 25 D-xylose as the sole carbon source at a rate of 0.35 h -1 . At neutral pH, the yeast form of K. 26 quercitrusa var. filamentosus, but not var. comoensis, switched to filamentous growth in a carbon 27 source dependent manner. Their genomes are 11.0-13.2 Mb in size and contain between 4888 and 28 5475 predicted genes. Together with closely related species, we did not find any relationship 29 between gene content and ability to grow on xylose. Besides its metabolism, K. quercitrusa var. 30 filamentosus also has a large potential as a production organism, because of its capacity to grow at 31 low pH and to undergo a dimorphic shift. 32 D ow naded rom http/academ ic.p.com /g3journal/advance-a.1093/g3journal/jkab342/6377786 by Fculty of ife Scnces Lrary user on 04 O cber 2021
Design and fabrication of the degradation level monitoring sensor for power transformer insulating oil

This paper presented the method to detect the degradation level of insulation oil for transformer. Degradation of insulation oil for transformer is due to both mechanical and chemical deterioration. Metallic particle and organic material such as a dust are known as the main reason of mechanical deterioration. According to degradation and oxidation of insulation oil for the time of transformer operation, total acid number (TAN) will be increased, sludge will be appeared, and finally conductivity will be decreased. Designed sensor, which is an inter-digit capacitive type, was fabricated by using MEMS technology. Size of sensor is 9 mm (length) x 7 mm (width) x 1 mm (thickness). From the tested result, when the oil is aged, the capacitance increases and the impedance decreases. And the result shows the good proportionality with time.
Provenance-integrated parameter selection and optimization in numerical simulations

Simulations based on partial differential equations (PDEs) are used in a large variety of scenarios, that each come with varying requirements, e.g., in terms of runtime or accuracy. Different numerical approaches to approximate exact solutions exist, that typically contain a multitude of parameters that can be tailored to the problem at hand. We explore how high-level provenance, i.e., provenance that is expensive to capture in a single simulation, can be used to optimize such parameters in future simulations for sufﬁciently similar problems. Our experiments on one of the key building blocks of PDE simulations underline the potential of this approach.
Fundamental Scaling Laws of Covert DDoS Attacks

The Internet has become an indispensable commodity in the last several years. This achievement was parallel to the growth of sophistication that home networks have undergone, nowadays hosting a variety of devices such as PCs, tablets, mobile phones and specialized apparatus such as smart thermostats and other Internet of things (IoT) devices. While these devices offer users an array of services and conveniences, they come at the cost of increasing the attack surface of the home network.Because of the vulnerabilities of such devices, they have been increasingly used as the source of Distributed Denial-of-Service (DDoS) attacks.
Changes in Toyota Motors’ operations management

A key driver behind Toyota Motors’ rise to prominence has been the Toyota Production System (TPS). This pillar of the firm's competitive strength was developed over several decades. As of the late 1980s, various changes were introduced into the TPS. Some of these, such as line segmentation, the use of inter-segment buffers and high-tech automation, have been portrayed as breaks with TPS foundations. With virtually no exception published accounts on these changes stop with the situation in the mid-1990s. Based on general literature and three factory visits, this article aims to provide an update on the situation in April 2001.
Modulus Increase with Magnetic Field in Ferromagnetic Shape Memory Ni–Mn–Ga

Ferromagnetic shape memory Ni–Mn–Ga has been shown to exhibit deformations of up to 9.5% when driven with quasistatic fields. This article is focused on the use of Ni–Mn–Ga as the active element in a dynamic transducer consisting of a solenoid and a low-reluctance, closed magnetic path. Despite the absence of a restoring force in this configuration, we have shown in prior studies recoverable compressible strains of 1/4 4100 m, which are attributable to internal bias stresses built in the material during manufacture. In this study, we experimentally establish the presence of a modulus defect in Ni50Mn28.7Ga21. 3, whereby the elastic modulus increases as much as 255% upon increasing the applied magnetic field from zero to 380 kA/m DC. Experimental measurements are conducted under both mechanical and magnetic excitation, and analyzed in combination with vibratory models for the system. While in our experiments the attractive magnetic forces between the transducer poles may contribute to the total modulus increase, the presence of a modulus change associated with the Ni–Mn–Ga element is substantiated. Dynamic Ni–Mn–Ga transducers offer an attractive mechanism for electrical tuning of the modulus, with potential application in active vibration absorption problems.
Some Infrared (IR) Applications In Combustion Technology

Infrared technology finds many applications in the field of combustion, ranging from pollution monitoring, through military systems, to the control of industrial furnaces and boilers. This review of some selected concepts highlights the interaction between the diagnostic role of infrared measurements and the current status of mathematical modelling of combustion systems. The link between measurement and computing has also evolved to the point where a digital processor is becoming an inherent part of many new instruments. This point is illustrated by reference to the diffraction particle size meter, fire detection and alarm systems, and furnace control. In the future, as fuels become scarce and expensive, and micro-electronics become more available and inexpensive, it is certain that infra-red devices will find increasing application in smaller industries and the home.
Smart structure state monitoring system using OFS array and NN processing

Embedded optical fiber sensing (OFS) array, signal processing neural network (NN), and embedded micro actuators are three key techniques for optical fiber smart structures. On the basis of the former two techniques, a smart structure state monitoring system is described. The microbending OFS array configured with many rows and columns of fibers laid perpendicular to each other, and the NN signal processing based on the outgoing light intensity pattern is suggested. The actual series experiments on smart skins, gypsum members, and reinforced concrete members, in which the OFS array is embedded, are given and analyzed in detail. The experimental results show the effectiveness of the OFS array and NN signal processing method proposed by the authors. The system can monitor inner states of the structures, such as strains or stresses or cracks, and has potential applications in areas of space aeronautics, ship and civil engineering, etc.