Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of RFID Adoption among Logistics Service Providers in Malaysia: A Discriminant Analysis

This paper studies the determinant factors that influence the adoption of Radio Frequency Identification (RFID) by Logistics Service Providers (LSPs) in Malaysia. The influencing factors include costs of the technology, perceived risks of technology, organisational readiness, the size of the organisation, customer and competitor pressures and government support. To provide insight into these factors, this study employed a questionnaire survey. The data are obtained from 68 logistics companies. The results provided evidence that the adoption of technological innovations is influenced significantly by technological, organisational and environmental characteristics and that adopting new technologies will increase supply chain performance for the logistics industry in Malaysia.
Olive Cake and Fibrolytic Enzymes Inclusion in Ewes’ Diets and its Effect on Blood Values and Reproductive Performance

| Enhancing the productive performance of ruminant by improving nutrients metabolism get much attention. The aim of the current study was to investigate the effect of feeding olive cake either treated or untreated with fibrolytic enzymes on the reproductive performance and some blood parameters in ewes . Forty-eight multiparous lactating Barki ewes at second to third season of lactation (42±3 kg of live body weight) were equally and randomly allotted to four dietary groups. Control group (G1) was fed on 60 % concentrate feed mixture (CFM), 40 % green maize, first group (G2) as control with replacing 30% of CFM with olive cake, second group (G3) as control with replacing 30% of CFM with olive cake silage and third groups (G4) as control with replacing 30% of CFM with olive cake silage treated with fibrolytic enzyme. The results indicated no significant change were noted between control and other groups in blood serum total protein, Albumin, Tri-glycerides, glucose, ALT and urea. G1 significantly increased (p<0.05) T3 as compared with G1, while G4 recorded the highest value for progesterone as compared with other treatments. Amongst the four groups, G2, G3, G4 improved lambing rate, prolificacy rate, fertility%, female ratio, litter weight as compared with G1, while, the highest stillbirth being in G1. It could be concluded that inclusion of olive cake silage either treated or untreated with fibrolytic enzyme could improve the reproductive performance of ewes. and enzymes inclusion in ewes’ diets and its effect on blood values and reproductive performance.
Dependence of Thermal Shock Crack on Specimen Width for Ceramic Materials

Knowledge of size effect of thermal shock properties of ceramics is a prerequisite in engineering applications. In the present study, the size effect of the cracking in the ceramic materials subjected to water quenching has been experimentally conducted. Based on the Rizk model, the equivalent specimen width of the elastic strip with cracks is introduced and modified to describe the effect of cracks on the deformation of the elastic strip underwater quenching. It is found that the simulation obtained from the proposed modified model is in good agreement with the experimental results. And the reasons for the size effect of crack depth and crack growth into the compressive region are well analyzed by theoretical results. The proposed model is expected to provide a powerful tool to characterize and predict the size effect on thermal shock crack of ceramic materials.
Classifying shoulder implants in X-ray images using Big data techniques

This research work focuses on optimal solution for the image detection and segmentation. The prosthesis may – a few or numerous years after it was embedded – come needing fix or substitution. In a portion of these cases, the maker and the model of the prosthesis might be obscure to the patients and their essential consideration specialists, for instance when the medical procedure was led in another nation where the patient has presently no admittance to the records. The highest accuracy value is 81.68% which is while applying the=7k=6 and the lowest accuracy value is 65.6% when apply the k=7. The highest precision value is 81.68% while applying the k=1 and very lowest precision value is 73.69% lies on k=2 and k=9.The highest recall value is 83.69% which is produced by while applying the parameter k=6, the lowest recall value is 65.76% while applying the parameter k=9. The K=10 model takes more time to build the model is while applying the k=10 and very low time consumption model is k=8. Another conceivable instance of not knowing the specific producer and model could be expected uncertainty in clinical records or clinical images.
The impact of inflation on the unemployment rate in Egypt: a VAR approach

Unemployment and inflation are among the most critical phenomena facing both developed and developing countries due to their harmful social, economic, and political effects. The Egyptian monetary policy’s main objective is to maintain a low inflation rate in the medium run to keep the confidence and a high rate of investment and economic growth. At the same time, economists argue that targeting a low-rate of inflation may increase unemployment. Although the classical Philips curve indicates a trade-off between inflation and unemployment, several empirical studies have argued that the relationship between inflation and unemployment depends on the shocks’ source and lagged responses. The main objective of this paper is to examine the relationship between inflation and Egypt’s unemployment rate. We used time-series data from 1980 to 2019, where a vector autoregressive (VAR) model and the Impulse response function tool (IRF) were employed. The results show that inflation has a positive relationship with GDP while negatively affecting the unemployment rate.
Green synthesis route for WS2 nanosheets using water intercalation

The exfoliation of layered materials has attracted a lot of attention in recent times. In this report, we have exfoliated WS2 in deionized water (without using any chemical solvents, surfactants, etc) using the thermal coefficient mismatch between WS2 and H2O along with other anomalous properties of water, such as the formation of five-, six- and seven-ring structures while freezing. Two different green synthesis routes have been proposed for WS2 exfoliation. We call them the ‘hard’ and ‘soft’ quenching methods. The nanosheets were investigated using different characterization tools and we found the exfoliation of the bulk into <4 layers with an average lateral dimension of 200 nm. The exfoliation method is unique in the sense of producing pristine nanosheets due to the absence of any organic solvents, which are difficult to remove.
Factors Influencing Business IT Alignment

Business IT alignment has consistently been ranked at the top of the most important topics from the perspective of business executives. Over the years, many models and IT management frameworks have been proposed to address this issue. The purpose of this study was to develop comprehensive understanding of business IT alignment phenomena based on live experiences of IT leaders working in FMCG companies based in the UK. To achieve the goal of the study, a descriptive phenomenological method was employed. Live experiences of eleven participants from FMCG companies were used as the primary source of data. Phenomenological analysis of the data obtained from interviews revealed twenty-two sub-themes grouped into four main themes. Four main themes identified during the study are: leading topics, IT trends, IT management frameworks influencing business IT alignment and future improvement. The leading topics theme gathers current most important areas being discussed between senior IT and business leaders. The IT trend’s theme points to all technological trends that draw the attention of companies. In particular, three categories were discovered: technologies to automate and optimize, digital technologies, and disruptive technologies. The IT management framework theme tackles all frameworks contributing to business IT alignment. The logical chain of sequence could be observed due to speed of changes and customers moving to online channels (leading topics), and because digital technologies are spreading (IT trends) supported by organizational changes (IT management frameworks). The last theme aggregates recommendations for improvement in business IT alignment based on participants’ suggestions.
Boundary-layer flow and heat transfer of cross fluid over a stretching sheet

The current study is a pioneering work in presenting the boundary-layer equations for the 2-D flow and heat transfer of the Cross fluid over a linearly stretching sheet. The system of PDE is turned down into highly non-linear ODE by applying suitable similarity transformations. The stretching sheet solutions are presented via. a numerical technique namely the shooting method and graphs are constructed. The impact of the emerging parameters namely the power-law index, n, the local Weissenberg number, We, and the Prandtl number on the velocity and temperature fields are investigated through graphs. The numerical values of the local skin friction coefficient and the local Nusselt number are also presented in tabular form. Additionally, the graphs are sketched for the local skin friction coefficient and the local Nusselt number. It is observed that with growing values of the local Weissenberg number the velocity profiles exhibited a decreasing trend while opposite behavior is seen for the temperature field. Further, comparisons are made with previously available literature for some limiting cases and an excellent agreement is achieved.
Serum concentration of endocan, fetuin-A, and endothelin
in plaque psoriasis – coincidence or fate? A preliminary study

Introduction. Psoriasis vulgaris is one of the most common dermatoses. Increased prevalence of metabolic abnormalities coexisting with psoriasis vulgaris is caused by systemic inflammation. One feature of inflammation is endothelial dysfunction, which appears to be responsible for these comorbidities. In recent years several markers of endothelial dysfunction have been implicated in the pathogenesis of psoriasis vulgaris, from which endocan, fetuin-A, and endothelin-1 seem most reliable. Objective. To determine whether endocan, fetuin-A, and endothelin-1 could serve as biomarkers of psoriasis vulgaris, and their relationship with the disease severity and metabolic abnormalities observed in psoriasis vulgaris. Material and methods. The study group consisted of 60 patients with psoriasis and 28 patients with non-psoriatic skin diseases, who served as controls. Psoriasis Area and Severity Index and Body Surface Area were assessed. Waist circumference, body mass index, blood pressure, fasting glucose, lipid profile and serum endothelin-1, fetuin-A, and endocan levels were determined in both groups. Results. There were no significant differences in blood pressure, waist circumference, concentration of total cholesterol, low-density lipoprotein, high-density-lipoprotein, and endothelin-1 between the groups. The body mass index, endocan, triglycerides, and fasting glucose were significantly higher in patients with psoriasis compared to the control group, while the concentration of fetuin-A was significantly higher in the control group. Conclusions. The results obtained in the study indicate a possible role of fetuin-A and endocan in the pathogenesis of psoriasis and its metabolic comorbidities.
Control of the Wave Energy Converter ISWEC in Simulation

The control of a Wave Energy Converter is a key fac tor for its power extraction capabilities. This work is focused on the control of the ISWEC (Inerti al Sea Wave Energy Converter), a wave energy conver ter that uses its gyroscopic properties to extract sea wave energy. In this work, the model of the device is presented as well as the control technique currently used. Th ree control strategies are developed with the objective of improving the amount of energy extracted by the device. Fractional Control, Internal Model Control and Feed back Linearization control are implemented resortin g o MATLAB and Simulink. Irregular waves are considered and the performance of these control strategies is evaluated and compared to the currently in use Prop orti nal Derivative controller. The simulations performed in this work show that th e use of these controllers leads to similar power extraction. However, the use of Internal Model Cont r l or Feedback Linearization control is advantageo us as these controllers have less parameters to tune once deployed in the real environment.
Application and Dynamic Simulation of Improved Genetic Algorithm in Production Workshop Scheduling

From the point of view of combining theories with practice, in order to better realize the effective management of production workshop scheduling and thus improve the competitiveness of manufacturing enterprises in the market, this study focuses on the simulation of production workshop scheduling based on genetic algorithm. Firstly, the study analyses the concept and characteristics of production workshop scheduling, and then proposes the objective function and scheduling rules of production workshop scheduling; the study also introduces the genetic algorithm to combine the scheduling rules, which are regarded as the genetic gene to realize the optimization of the production scheduling through the simulation calculation; in addition, in order to satisfy the dynamic production environment of manufacturing enterprises, the study put forward a dynamic scheduling model; finally, the dynamic simulation of the production workshop scheduling system is realized through the mixed programming of Matlab and VC. The simulation results show that the dynamic model can reduce the scheduling times and improve the stability of dynamic scheduling, and has a positive guiding significance for the production workshop scheduling of manufacturing enterprises. (Received, processed and accepted by the Chinese Representative Office.)
500 kW Forced Air-Cooled Silicon Carbide (SiC) Three-Phase DC/AC Converter With a Power Density of 1.246 MW/m3 and Efficiency >98.5%

There is a continuous demand for high-power, high-efficiency, and high-density converters in various existing and emerging applications such as large motor drives, electric vehicles, more electric aircraft, and utility applications. Compared with conventional silicon (Si) insulated gate bipolar transistors (IGBTs), silicon carbide (SiC) MOSFETs can have lower switching loss and higher frequency operation capabilities, which enables higher efficiency and higher power density at the converter level. Meanwhile, to achieve a high power rating such as 500 kW, how to extend the current capabilities of existing SiC power modules, the choice of parallel schemes, the selection of passive components, cooling and mechanical structure design pose clear challenges in maximizing the system power density and efficiency. This article presents a comprehensive design of the world-first air-cooled 500 kW SiC dc/ac three-phase converter, which achieves a record-high power density of 1.246 MW/m3 (1.246 kW/L) and an efficiency over 98.5%. The converter has been tested in the experiment to the full power rating, which provides benchmark results for high power SiC converters and their applications.
Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation

Supervised depth estimation has achieved high accuracy due to the advanced deep network architectures. Since the groundtruth depth labels are hard to obtain, recent methods try to learn depth estimation networks in an unsupervised way by exploring unsupervised cues, which are effective but less reliable than true labels. An emerging way to resolve this dilemma is to transfer knowledge from synthetic images with ground truth depth via domain adaptation techniques. However, these approaches overlook specific geometric structure of the natural images in the target domain (i.e., real data), which is important for high-performing depth prediction. Motivated by the observation, we propose a geometry-aware symmetric domain adaptation framework (GASDA) to explore the labels in the synthetic data and epipolar geometry in the real data jointly. Moreover, by training two image style translators and depth estimators symmetrically in an end-to-end network, our model achieves better image style transfer and generates high-quality depth maps. The experimental results demonstrate the effectiveness of our proposed method and comparable performance against the state-of-the-art.
Digital Transformation of Incumbent Firms: A Business Model Innovation Perspective

The literature argues that a real digital transformation of firms requires holistic changes of the business model. Despite knowledge about this ambitious goal, understanding of how digital business model transformation can be achieved is still very limited. In this article, we explore how firms achieve digital business model transformation. We apply a case study design to investigate how incumbents have changed their respective business model dimensions during digital transformation. Our findings center on interview data and complementary archival records from 15 cases. We present a framework for digital business model transformation along the dimensions of value proposition, value creation, and value capture. Our results emphasize the importance of a preparatory phase in which the strategic course is set. Furthermore, our findings demonstrate that transforming a company's business model is most effective when a single person, namely the Chief Digital Officer, is responsible. Our findings contribute to the business model literature, by providing a more holistic view on how business model innovation can be utilized during digital transformation.
Comparison of models for the simulation of landslide generated Tsunamis

In this paper, we analyze the relevance of the use of the shallow water model and the Boussinesq model to simulate tsunamis generated by a landslide. In a first part, we determine if the two models are able to reproduce waves generated by a landslide. Each model has drawbacks but it seems that it is possible to use them together to improve the simulations. In a second part we try to recover the landslide displacement from the generated wave. This problem is formulated as a minimization problem and we limit the number of parameters to determine assuming that the bottom can be well described by an empirical law.
EFFNet: Enhanced Feature Foreground Network for Video Smoke Source Prediction and Detection

Smoke detection in video is a challenging task because of the irregular shape of smoke, its complex motion state, which is affected by temperature, wind and other external factors, and background disturbances. Pixel-based foreground modeling method is a crucial step in many smoke detection systems and can be applied to efficiently focus on a certain object or a specific region to detect movements or anomalies. In video analysis, it is a natural idea to move the focus from the pixel-level foreground to the feature-level foreground. In this paper, the feature foreground is generated by the middle layer of a convolutional neural network (CNN) to guide the temporal modeling process for smoke objects. A novel temporal module called the Feature Foreground Module (FFM) is proposed to boost learning of a smoke temporal representation. Consider the problem of smoke analysis in video, we present a novel unifying approach, named an enhanced feature foreground network (EFFNet), that performs both smoke source prediction and detection. Efficient branch networks are designed in EFFNet, to predict the source mask and bounding boxes of smoke plumes in video. To the best of our knowledge, this is the first paper to study the source of smoke using deep learning methods. Finally, experiments on a realistic smoke dataset and a public dataset show that EFFNet method performs much better than do previous state-of-the-art methods.
Research on distributed wind farm reactive power optimization method considering voltage quality

To solve the voltage fluctuation problem caused by distributed wind power connected to distribution network, a reactive power optimal dispatching method for coordinated control of distributed wind power and regional power grid considering uncertainty is proposed. Firstly, the influence of wind power access on the voltage quality of distribution network is analyzed, and the control idea of optimal operation is determined. Secondly, aiming at the problem of reactive power coordination optimization after wind power is connected to distribution network, a reactive power optimization model considering economy and power quality is established. The model is solved by introducing uniformly distributed initial harmony database and improved harmony search algorithm of variable dimension and voice database, and the results are compared with those of particle swarm optimization algorithm. Finally, the control strategy of reactive power optimization in distribution network is obtained. The test results show that the proposed optimization model and algorithm can achieve maximum wind energy absorption on the basis of satisfying the relevant constraints, especially ensuring the voltage quality of distribution network nodes.
A fast, very-high-energy γ-ray flare from BL Lacertae during a period of multi-wavelength activity in June 2015

The mechanisms producing fast variability of the γ-ray emission in active galactic nuclei (AGNs) are under debate. The MAGIC telescopes detected a fast, very-high-energy (VHE, E > 100 GeV) γ-ray flare from BL Lacertae on 2015 June 15. The flare had a maximum flux of (1.5 ± 0.3) × 10−10 photons cm−2 s−1 and halving time of 26 ± 8 min. The MAGIC observations were triggered by a high state in the optical and high-energy (HE, E > 100 MeV) γ-ray bands. In this paper we present the MAGIC VHE γ-ray data together with multi-wavelength data from radio, optical, X-rays, and HE γ rays from 2015 May 1 to July 31. Well-sampled multi-wavelength data allow us to study the variability in detail and compare it to the other epochs when fast, VHE γ-ray flares have been detected from this source. Interestingly, we find that the behaviour in radio, optical, X-rays, and HE γ-rays is very similar to two other observed VHE γ-ray flares. In particular, also during this flare there was an indication of rotation of the optical polarization angle and of activity at the 43 GHz core. These repeating patterns indicate a connection between the three events. We also test modelling of the spectral energy distribution based on constraints from the light curves and VLBA observations, with two different geometrical setups of two-zone inverse Compton models. In addition we model the γ-ray data with the star-jet interaction model. We find that all of the tested emission models are compatible with the fast VHE γ-ray flare, but all have some tension with the multi-wavelength observations.
A META-HEURISTIC MULTI-OBJECTIVE FUZZY SIMPLEX-GENETIC ALGORITHM FOR CREDIT RATING PREDICTION OF BANKS CUSTOMERS

This study examines a multi-objective fuzzy simplex-genetic algorithm which was developed to predict bank legal customers financial performance. Prediction performance of the model was examined based on its ability to accurately identify credit default. Using available data from KESHVARZI bank over 2001-2006, debt ratio, operational ratio, and return on equity are selected as descriptive variables, and on the other side dependent variable was considered as a dummy variable. To training and validating the model, data were divided in to model (in-sample) and test (out-of-sample) sets. After running the algorithm, besides the sensitivity and specificity ratios, the key variable was specified.