Miracle-dz/UniFAR-FTUs huggingface dataset:
TQM Role in Achieving Student Satisfaction in Higher Education Institutions

This paper examines the dimensions of Total Quality Management (TQM) and their role in achieving student satisfaction. The study reviewed the relevant literature belonging to TQM, in addition to analyzing the literature over the years related to TQM in general in Jordan. This study analyzed the relationship between TQM dimensions (tangibility, assurance and responsiveness) and student satisfaction in higher education in Jordan. The sample was selected from different universities in Jordan by using questionnaire method to collect the data. Multiple linear regression was conducted to test the hypotheses as well descriptive analysis and reliability test to validate the instrument of the study. The study showed that the student satisfaction was significantly related to tangibility and assurance dimensions, whereas the responsiveness dimension was insignificant. The study concluded that TQM and its execution in higher education institutions in Jordan need to develop and add new methods and approaches to maintain its reputation.
Self-localization of mobile robot with single camera in corridor environment

This paper presents a single vision-based self-localization method in an corridor environment. The authors use the Hough transform for finding parallel lines and vertical lines. Relative distance from mobile robot to the cross points is calculated by using the cross points as feature points. Mapping an environment map to the feature points is performed by self-localization in a searching window. Experimental results show the efficiency of the proposed method in a corridor environment.
Prototyping and infrastructuring in design for social innovation

During the past five years design has been recognised as a powerful innovation driver. Design methods and tools have also been applied in new fields. One of them is social innovation, which is aimed at developing new ideas and solutions in response to social needs. While different initiatives have demonstrated how design can be a powerful approach in social innovation, especially when it comes to systemic thinking, prototyping and visualising, some concerns have been raised regarding the limitations of applying design in this field. Through a specific case, this paper will discuss and suggest some approaches and concepts related to design for social innovation. Coming from a participatory design tradition, we focus on the idea of infrastructuring as a way to approach social innovation that differs from project-based design. The activities that are carried out are aimed at building long-term relationships with stakeholders in order to create networks from which design opportunities can emerge. We also discuss the role of prototyping as a way to explore opportunities but we also highlight dilemmas.
Inrush current control for equipment powered by UPSs

With the present-day widespread use of uninterruptible power supplies (UPS) in power equipment, inrush becomes a major concern since most UPSs have a limited ability to furnish high peak-current demands. The author discusses inrush current in general and presents, both conceptually and in block-diagram form, a proposal for circuitry that manages and eliminates the inductive inrush current concerns. It is established that the most important factor in identifying the influence on the UPS of a power supply connected to the UPS is the crest factor of the applied load. To control the inrush current, the preferred approach for a capacitive load is to switch a current-limited resistor temporarily into the circuit, while for an inductive load, a well-chosen critical turn-on angle of the connecting device is the most effective method. <<ETX>>
60 GHz compact low noise amplifier in 65 nm CMOS

A single-ended low noise amplifier in 65 nm CMOS for applications at 60 GHz is presented. Its measured gain and noise figure at the centre frequency of 57 GHz are 19.1 dB and 5.5 dB, respectively, and it provides wideband matching. Transistors in the design have an asymmetrically fingered layout which reduces parasitic capacitances while simultaneously allowing for higher channel current densities.
Investigating the Validity of the Ogive Aggregation Method, Including the use of Rasch Analysis, for the Sentence Completion Test and the STAGES Model

This project assesses psychometric aspects of the STAGES sentence completion test (SCT) using data from 740 scored surveys, and some of the analysis applies to all variations of the SCT for ego development (meaning making maturity). The goals of this research project include: (1) to apply item response theory (IRT) and Rasch analysis to determine item-level psychometric properties of the SCT that were previously unaddressed in SCT research; and (2) to further investigate suspected problems with the ogive cutoff method for aggregating item scores in the SCT and propose alternatives. The psychometric analysis includes: within-test item normality, item standard deviations, test length analysis, factor analysis, characteristics of and correlations among each item, overall test strength, and construct levels discrimination. A range of issues with the standard ogive cutoff method are described, and a new item aggregation method is then proposed.
HearCom: hearing in the communication society

A group of 28 research partners joined the EU-funded project HearCom with the overall aim to improve hearing communication. One of the main achievements has been the provision of advanced hearing screening tests by telephone and Internet. Next to that it was aimed to harmonize hearing diagnostic tests for European languages. For this the concept of an Auditory Profile was defined on which a number of diagnostic hearing tests were developed in several languages. As hearing problems are also a result of adverse acoustical circumstances such as for room acoustics and telecom systems, these effects have been studied, modelled and evaluated for hearing impaired persons. In the area of rehabilitation a large scale comparison study was performed on signal enhancement techniques for hearing devices. Both objective and subjective benefits were found for specific listening conditions in relation to a chosen signal processing method. As modern technology may assist on hearing and communication it was studied how the use of automatic speech transcription or the use of handheld communication devices may help people with hearing problems. It is shown that communication benefits can be obtained, but that the benefit is limited in practice as processing power of today's handheld devices is still insufficient. An overview is given on the HearCom portal with sections for screening diagnostics, hearing information for the public and professionals, and a new HearCompanion service that provides step-by-step support for the hearing rehabilitation process. © S. Hirzel Verlag.
Comparação das resistências ao embutimento paralelo às fibras de madeiras de pínus oocarpa, cumaru e pínus taeda

A norma brasileira NBR 7190 (ABNT, 1997) estabelece as diretrizes para a determinacao da resistencia da madeira ao embutimento com pinos metalicos por meio de ensaios laboratoriais ou, na ausencia deles, disponibiliza equacoes que permitem estimar a resistencia da madeira ao embutimento. A referida norma admite ainda que na direcao paralela as fibras da madeira a resistencia a compressao seja igual a resistencia ao embutimento. O objetivo deste trabalho consistiu em analisar as resistencias de embutimento e de compressao, ambos na direcao paralela as fibras, utilizando madeiras das especies pinus oocarpa (Pinus oocarpa Shiede), cumaru (Dipterix odorata) e pinus taeda (Pinus taeda L.). Para comparacao das resistencias foi utilizado o teste estatistico de hipotese conhecido como Teste T. Os resultados da analise estatistica revelaram a nao equivalencia entre os valores de resistencia apenas para as madeiras de pinus oocarpa, evidenciando, assim, a importância da determinacao da resistencia da madeira ao embutimento atraves de ensaios laboratoriais normalizados.
Attendance Management System Using Face Recognition Method

When it comes to classroom management, the attendance check is a critical component. Time-consuming, particularly when it comes to open meetings, is checking attendance by calling names or by handing around a sign-in sheet to make it easier to commit fraud. An implementation of a real-time attendance check is described in this article in great detail facial recognition system and its outcomes. The system must be able to identify a student’s face in order for it to work first snap a photograph of the pupil and save it in a database as a reference for future use. During the event, there were students may be identified by using the webcam, which captures photos of their faces auto-detects faces and selects students with names that are most likely to match, and lastly, depending on the facial recognition findings, an excel file will be updated to reflect attendance. To identify faces in webcam footage, the system uses a pre-trained Haar Cascade model. As a result, a 128-bit FaceNet has been generated by training it to minimise the triplet loss. The dimensions of the facial picture. When two facial pictures have similar encodings If the two facial pictures are from the same student or different. Use of the system as part of a class, and the outcomes have been extremely positive. There has been a poll done to find out more about There are both advantages and disadvantages to using a college attendance system.
Maximum Hybrid Entropy Assessment of Equipment Failure Probability Caused by Voltage Sags

In order to depict the complex uncertainty involved in evaluation of equipment sensitivity to voltage sags, the voltage tolerance level of sensitive equipment is characterized by interval data, a evaluation model is proposed to derive interval probabilities of equipment operation status. Hybrid entropy is used to measure the uncertainty of randomness and fuzziness. Then, the interval result is transformed into point-valued probability based on maximum hybrid entropy model. By the help of personal computers, the proposed model is finally verified in a test distribution system.
A Hybrid Multiprocessor Scheduler for Soft Real-Time System with Processor Affinity Concept

Now a days numerous real-time OS like QNX, VxWorks, LynxOS and real-time extension of Linux practicing the processor affinity concept to schedule the real-time tasks and it offers more flexible approach instead of traditional approaches defined in the literature. Limiting the migration may reduce the context switch overhead and improve the cache performance but it largely influence on other parameters which are most important for the any real-time operating system. It degrades overall performance by decreasing the schedulability of tasks, increase the deadline miss ratio. This paper presents the problem in existing processor affinity based approach which confines the schedulability of the tasks and designed a novel processor affinity based algorithm to enhance the schedulability of the tasks and decreases the average deadline miss ratio by providing the flexible migration policy with the priority reassignment mechanism.
Factors influencing the use of Deep Learning for Medicinal Plants Recognition

Medicinal plants are very essential in maintaining the physical and mental health of human beings. For providing better treatment, Identification and classification of medicinal plants is essential. In this research paper, main objective is to create a medicinal plant identification system using Deep Learning concept. This system identifies and classifies the medicinal plant species with high accuracy. In this system, five different Indian medicinal plant species namely Pungai, Jamun (Naval), Jatropha curcas, kuppaimeni and Basil are used for identification and classification. The dataset contains 58,280 images, includes approximately 10,000 images for each species. The leaf texture, shape, color, physiological or morphological as the features set for leaf identification. The CNN architecture is used to train the collected dataset and develop the system with high accuracy. As result of this model, 96.67% success rate in finding the corresponding medicinal plant. This model is advisable to use as early detection tool for finding the medicinal plant because of its best success rate
Tradeoff studies in multiobjective insensitive design of airplane control systems

The latest results of an ongoing study of computer-aided design of airplane control systems are given. Constrained minimization algorithms are used, with the design objectives in the constraint vector. The concept of Pareto optimiality is briefly reviewed. It is shown how an experienced designer can use it to find designs which are well-balanced in all objectives. Then the problem of finding designs which are insensitive to uncertainty in system parameters are discussed, introducing a probabilistic vector definition of sensitivity which is consistent with the deterministic Pareto optimal problem. Insensitivity is important in any practical design, but it is particularly important in the design of feedback control systems, since it is considered to be the most important distinctive property of feedback control. Methods of tradeoff between deterministic and stochastic-insensitive (SI) design are described, and tradeoff design results are presented for the example of the a Shuttle lateral stability augmentation system. This example is used because careful studies have been made of the uncertainty in Shuttle aerodynamics. Finally, since accurate statistics of uncertain parameters are usually not available, the effects of crude statistical models on SI designs are examined.
An Efficient Interconnection System for Neural NOC Using Fault Tolerant Routing Method

Large scale Neural Network (NN) accelerators typically have multiple processing nodes that can be implemented as a multi-core chip, and can be organized on a network of chips (noise) corresponding to neurons with heavy traffic. Portions of several NoC-based NN chip-to-chip interconnect networks are linked to further enhance overall nerve amplification capacity. Large volumes of multicast on-chip or cross-chip can further complicate the construction of a cross-link network and create a NN barrier of device capacity and resources. In this paper, this refer to inter-chip and inter-chip communication strategies known as neuron connection for NN accelerators. Interconnect for powerful fault-tolerant routing system neural NoC is implemented in this paper. This recommends crossbar arbitration placement, virtual interrupts, and path-based parallelization strategies in terms of intra-chip communications for the virtual channel routing resulting in higher NoC output at lower hardware costs. A lightweight NoC compatible chip-to-chip interconnection scheme is proposed regarding to inter-chip communication for multicast-based data traffic to enable efficient interconnection for NoC-based NN chips. Moreover, the proposed methods will be tested with four Field Programmable Gate Arrays (FPGAs) on four hard-wired deep neural network (DNN) chips. From the experimental results it can be illustrate that a high throguput can obtained effectively by the proposed interconnection network in handling thedata traffic and low DNN through advanced links.
Stabilizing a multimachine power system via decentralized feedback linearizing excitation control

A new controller for the generator excitation system is described that uses a combination of feedback linearizing and the observation decoupled state space. This creates a controller that can be realistically implemented using only local measurements, and whose performance is consistent with respect to changes in network configuration, loading and power transfer conditions. The control differs in this respect from linear constant-gain controllers such as power system stabilizers, whose characteristics can vary significantly with changes in operating conditions. The design is well-suited to a multimachine setting, in that it is not based on an infinite-bus approximation. Simulations were performed on a 38-bus reduced modelof the Northeast Power Coordinating Council system and benchmarked against simulations in which automatic voltage regulators with power system stabilizers were substituted in place of the nonlinear controls. >
Click Fraud Detection Approaches to analyze the Ad Clicks Performed by Malicious Code

Mobile PR is an important component of the mobile app ecosystem. A major threat to this ecosystem’s long-term health is click fraud, which involves clicking on ads while infected with malware or using an automated bot to do it for you. The methods used to identify click fraud now focus on looking at server requests. Although these methods have the potential to produce huge numbers of false negatives, they may easily be avoided if clicks are hidden behind proxies or distributed globally. AdSherlock is a customer-side (inside the app) efficient and deployable click fraud detection system for mobile applications that we provide in this work. AdSherlock separates the computationally expensive click request identification procedures into an offline and online approach. AdSherlock uses URL (Uniform Resource Locator) tokenization in the Offline phase to create accurate and probabilistic patterns. These models are used to identify click requests online, and an ad request tree model is used to detect click fraud after that. In order to develop and evaluate the AdSherlock prototype, we utilise actual applications. It injects the online detector directly into an executable software package using binary instrumentation technology (BIT). The findings show that AdSherlock outperforms current state-of-the-art methods for detecting click fraud with little false positives. Advertisement requests identification, mobile advertising fraud detection are some of the keywords used in this article.
Biotechnology methods to produce planting material of the genus Rubus L.

The work is devoted to improving clonal micropropagation methods of the genus Rubus representatives. When cultivating R. arcticus L. cultivars, the optimal concentration of 6-benzylaminopurine (6-BAP) was 0.3 mg L−1. Significant effect of FeEDTA concentration in the nutrient medium on multiplication of R. idaeus L. cultivars was established. The interaction of auxin type and plant genotype was revealed during rooting of blackberry cultivars and raspberry-blackberry hybrids. The nutrient medium supplemented with 0.5 mg L-1 indoleacetic acid contributed to the highest percentage of rhizogenesis in R. arcticus representatives (82%). The optimal growth regulator for conservation of raspberry explants was 6-BAP at a concentration of 0.3 mg L-1. One of the most representative in vitro collections of Rubus cultivars has been created.
Different improvement designs of conventional comparator

Comparators play a significant role in the semiconductor industry and have become indispensable in the design of ADC. The delay and energy consumption are two important indicators of the comparator. Many designs have been made to reduce the delay and energy consumption, such as separated gata-biasing cross-coupled transistors for a new latching stage, and pMOS is used to replace nMOS in comparators. This paper analyzes the working principle of the proposed comparators designed for different needs reported on different papers. It compares their simulation results about key data such as delay and energy consumption.
Analysis and implementation of realtime stock prediction using reinforcement frameworks

Real time stock prediction is interesting research topic due to the risk involved with volatile scenarios. Modelling of the stocks by reducing the overestimation in ANN model, due to rapid fluctuations in the market guide fund managers risky decisions while building stock portfolio. This paper builds real time framework for stock prediction using deep reinforcement learning to buy, sell or hold the stocks. This paper models the transformed stock tick data and technical indicators using Transformed Deep-Q Learning. Our framework is cost reduced and transaction time optimized to get real time stock prediction using GPU and Memory containers. Stock predictor is architected using GRPC based clean architecture which has the benefits of easy updates, addition of new services with reduced integration costs. Data archive features of the cloud will give benefit of reduced cost of the new stock predictor framework.
Study of the Effect of Process Induced Uncertainties on the Performance of a Micro-Comb Resonator

This paper presents a modeling technique based on the integration in the classic deterministic simulation methods of probabilistic computational techniques such as uncertainty analysis and sensitivity analysis. As study case, it is presented a micro-comb resonator that is actuated electrostatically to vibrate in the plane parallel to the substrate. A deterministic Finite Element coupled electromechanical analysis is performed to evaluate the mode shapes and the corresponding eigenfrequencies of the mobile mass and afterwards a Monte Carlo simulation is used to determine the dispersion of the eigenfrequency of the mode shape of interest in function of the variations of the input parameters. The scatter of the results is analyzed and then it is presented a sensitivity analysis for establishing which of the input parameters have more influence on the variability of the microresonators performance.
Meridional Migration of Diurnal Heavy Rainfall during Extreme Events over Java and Surrounding Waters and Its Relation to Madden Julian Oscillation

In this study, meridional migration characteristic of diurnal heavy rainfall (DHR) over Java and surrounding waters and its relation to Madden Julian Oscillation (MJO) during extreme events was investigated. The rainfall data was the Climate Prediction Centre Morphing (CMORPH) V1.0 in the December-January-February (DJF) wet season of the 1998-2019 period. The thresholds of extreme events were based on the 95% percentile of daily rainfall area average of mountainous area (MA), northern plain area (NPA), northern waters (NW), southern plain area (SPA), and southern waters (SW) that were based on Global Land One-kilometer Base Elevation (GLOBE) Digital Elevation Model. We analyzed meridional migration of DHR through composite and the Hovmoller diagram. To get the MJO signal, we used the Wheeler-Kiladis wavenumber-frequency domain to filter outgoing longwave radiation (OLR). The results showed that DHR was stationary over the mountains, migrated to the Java Sea (The Indian Ocean), and was stationary over the Java Sea (Indian Ocean) in conjuction with migration from Java to the waters when extreme events occur over MA, NPA (SPA), and NW (SW), respectively. Based on a comparison of MJO-OLR during extreme events period of MA, NPA, SPA, NW, and SW, it seems that MJO had a stronger impact on the DHR of NW and SW than the others, but it must be examined based on significant test in the further study.
A Lower Energy-Aware-Based Routing Protocol Oriented to Internet of Things

As energy of reader in Internet of things is limited, we can only decrease energy overhead of protocol and balance energy consumption among readers to extend the network lifetime as much as possible. Combining with characteristics of Internet of things and requirements of low-energy, energy-aware-based routing protocol was selected for wireless networking of readers. Three methods dealing with how to decrease the energy and how to prolong the wireless network’s life expectancy are proposed in this paper. They are power mode switch based on power control, data mining technique as well as indefinite prolonged transmission. Based on these low-energy measures, improved energy-aware-based routing protocol was designed and performance was simulated for analysis. Simulation results show that improved protocol is superior to original one in aspects of total energy cost and network lifetime.