Miracle-dz/UniFAR-FTUs huggingface dataset:
Iterative learning control for dual stroke actuator systems

This paper presents a dual iterative learning control strategy for a dual stroke actuator system in the lithography scanner. The motion control strategy is employed, in which the trajectory of a short stroke stage is followed by one of a long stroke stage. A short stroke stage is used for improving the system response performance while a long stroke stage is introduced for the purpose of long motion stroke of the system. Combining the dynamic model of the system, the coupling effects between two actuators are analyzed, and the system model is simplified. This model is used for the design of a dual iterative learning control strategy and decoupling controllers. As a result, the heavy proportion of the recurrent coupling force on the long stroke stage is eliminated by the decoupling feedforward action from the output of the short stroke stage in the scanning process. The rest of the coupling force is removed by the first iterative learning control between two subsystems. The impact on the short stroke stage from the long stroke stage is weakened, and the short stroke stage is then designed independently by the two degree of freedom control strategy combining feedback control with the second iterative learning control. The convergence of the iterative learning control system is shown, and the effectiveness of the combined method is verified by a simulated wafer stage.
INVITED PAPER Tangible Bits: Beyond Pixels

Tangible user interfaces (TUIs) provide physical form to digital information and computation, facilitating the direct manipulation of bits. Our goal in TUI development is to empower collaboration, learning, and design by using digital technology and at the same time taking advantage of human abilities to grasp and manipulate physical objects and materials. This paper discusses a model of TUI, key properties, genres, applications, and summarizes the contributions made by the Tangible Media Group and other researchers since the publication of the first Tangible Bits paper at CHI 1997. http://tangible.media. mit.edu/ Author Keywords
DETERMINING THE CRISIS MANAGEMENT STRATEGIES APPLIED BY HOTEL MANAGERS DURING THE OUTBREAK OF CORONAVIRUS (COVID-19)

The aim of this research is to determine the crisis management strategies that city hotel managers applied during the Covid-19 pandemic period. The data for the research were collected from the managers in Eskisehir, which is popular with city tourism. Findings may contribute to the literature by offering crisis management strategies that can be guiding for managers of other city hotels. Semi-structured interview questions as a part of qualitative method were used to collect the data. The interviews were held with 13 hotel managers between 25th September and 21th October 2020. Thematic analysis was used and three main themes and nine sub-themes were revealed. The findings showed that hotel managers felt the negative effects of the crisis in the hotels where they worked. Despite the fact that hotel managers were caught unprepared for the coronavirus (Covid-19) crisis, they managed to control the crisis process well with their knowledge, skills and experience. Managers adopted a reactive approach since there was no similar crisis situation before and made the necessary efforts to overcome the crisis. Suggestions were presented to researchers for future studies on the subject and to practitioners in the tourism sector on the development of crisis management strategies.
Computing on Vertices in Data Mining

The main challenges in data mining are related to large, multi-dimensional data sets. There is a need to develop algorithms that are precise and efficient enough to deal with big data problems. The Simplex algorithm from linear programming can be seen as an example of a successful big data problem solving tool. According to the fundamental theorem of linear programming the solution of the optimization problem can found in one of the vertices in the parameter space. The basis exchange algorithms also search for the optimal solution among finite number of the vertices in the parameter space. Basis exchange algorithms enable the design of complex layers of classifiers or predictive models based on a small number of multivariate data vectors.
Strategies to Improve Job Satisfaction of U.S. Technical Personnel

ABSTRACTAs organizations downsize to improve profitability, move to empower employees, and emphasize building quality into the work process, technical personnel are becoming increasingly critical to fulfilling the company missions. It is important for these organizations to implement strategies that minimize job dissatisfaction and improve job satisfaction for these employees to enthusiastically carry out their roles. This study developed a causal model relating technical orientation with job satisfaction of technical and managerial personnel. A survey was conducted and 139 responses were obtained from professionals in highly technical U.S. organizations. Despite the enormous exodus of managers from some of the country's biggest technical firms, this study confirmed that employees perceive that they have to move to management to obtain higher status, thereby reducing job dissatisfaction. Advancement in their careers was essential for them to derive job satisfaction. Employees also perceived that progressi.
The Role of Religiosity, Ethnicity and Gender Identification in Individual’s Moral Judgments; The Mediation Effect of Self-transcendence

Most recently, corporate financial scandals, and unethical behaviour cast doubt on investors and raised public concern globally. It is due to the weak corporate governance structure and low ethic awareness amongst the people. The purpose of this research is therefore to justify the factors that influence an individual’s moral judgement. This study also seeks to provide practical recommendations to corporations and different associations. As such, to evaluate the proposed hypotheses, 300 self-administered questionnaires were distributed in five universities in Malaysia using a non-probability sampling approach. As a result, the findings demonstrate that ethnicity has the highest impact on self-transcendence and moral judgement, followed by religiosity and gender identification (gender difference). The contribution of this research is to evaluate the relationships between religiosity, ethnicity, and gender identification towards moral judgement with the intervention of mediating variable (self-transcendence). In essence, ethical values and moral obligations should be highlighted in corporations, and these values should be practised and embraced into the organisational culture. Thus, organisational decision-makers should highly emphasise the role of ethicality and morality in corporations because ethical competence aligns with an employee’s responsibility as a whole.
Low RCS microstrip antenna using polarisation‐dependent frequency selective surface

A low radar cross-section (RCS) microstrip antenna is proposed. A polarisation-dependent frequency selective surface (PDFSS) structure is designed and used as the antenna ground. By properly etching the unit cells of the PDFSS with different orientations on the ground of the microstrip antenna, the RCS has been reduced in the angular range of −90 ° ≤ θ ≤ +90° in both the xoz-plane and the yoz-plane under the φ-polarised incident wave. The ‘Γ’ shape slots between the unit cells with different orientations are used to reduce their mutual coupling.
Clustering based opcode graph generation for malware variant detection

Malwares are the key means leveraged by threat actors in the cyber space for their attacks. There is a large array of commercial solutions in the market and significant scientific research to tackle the challenge of the detection and defense against malwares. At the same time, attackers also advance their capabilities in creating polymorphic and metamorphic malwares to make it increasingly challenging for existing solutions. To tackle this issue, we propose a methodology to perform malware detection and family attribution. The proposed methodology first performs the extraction of opcodes from malwares in each family and constructs their respective opcode graphs. We explore the use of clustering algorithms on the opcode graphs to detect clusters of malwares within the same malware family. Such clusters can be seen as belonging to different sub-family groups. Opcode graph signatures are built from each detected cluster. Hence, for each malware family, a group of signatures is generated to represent the family. These signatures are used to classify an unknown sample as benign or belonging to one the malware families. We evaluate our methodology by performing experiments on a dataset consisting of both benign files and malware samples belonging to a number of different malware families and comparing the results to existing approach.
Adaptive Fault-tolerant H∞ Control via State Feedback for Linear Systems against Actuator Faults

This paper studies the problem of adaptive fault- tolerant H∞ controller design for linear time-invariant systems. New indirect adaptive fault-tolerant controller design methods via state feedback are presented for actuator fault compen- sations. Based on the on-line estimation of eventual faults, the adaptive fault-tolerant controller parameters are updated automatically to compensate the fault effect on system. A notion of adaptive H∞ performance index is proposed to describe the disturbance attenuation performances of closed-loop systems. The designs are developed in the framework of linear matrix inequality (LMI) approach, which can guaranteed the asymp- totic stability and adaptive H∞ performances of closed-loop systems even in the case of actuator faults. The effectiveness of the proposed design is illustrated via a decoupled longitudinal model of an F-18 aircraft.
Who Rides and who Pays

A comprehensive benefit–cost assessment of motorcycle use is offered, along with the characteristics, behaviors, and attitudes of motorcycle riders. U.S. motorcyclists are at high risk of crashing, with rates 24 times higher than those of passenger car and light-duty truck drivers per mile traveled. However, motorcycles require only one-quarter the parking space of a car and can reduce congestion by doubling network capacity (in vehicles per hour). Most motorcycles have high fuel economy, but low seating capacities render them little or no better than most cars and some light-duty trucks (assuming average vehicle occupancies) when compared in terms of fuel consumption per rider (or vehicle occupant) mile traveled. Motorcycles emit fewer grams of many polluting emissions but more volatile organic compounds and carbon monoxide than most cars if a catalytic converter is not installed. Noise impacts are a serious issue, with an inconsistent patchwork of regulations applied across states and localities. Results of a survey of current and former U.S. motorcyclists indicate that most respondents ride motorcycles for recreational purposes and ride in groups, but about one-half also ride for more mandatory (less discretionary) purposes and about 40% also ride solo. Fewer than one-third of respondents have formal motorcycle training, and helmet use is lowest among current riders who do not own a motorcycle. Engine size appears to be rising, and respondents support policies that combat operating a vehicle under the influence (e.g., ignition interlock devices for offenders). Regression models illuminate key factors and marginal effects on motorcycle riding and ownership rates.
Design and analysis of a 3.1–10.6 GHz Ultra-Wideband Low Noise Amplifier in 0.13μm CMOS

In this paper, a new low complexity ultra-wideband (UWB) 3-10.6 GHz low noise amplifier (LNA) is designed which is consisted of three stages. To overcome the input stage constraints such as broadband impedance matching and high gain while keeping low-power consumption, the combination of the current reuse and reactive feedback technique are applied as the first stage. The second and third stages are common source amplifier with an inductive peaking technique to achieve high flat gain and wide -3 dB bandwidth simultaneously. Analytical formulae are derived for describing the input impedance, gain, and noise figure. The LNA is designed in the standard 0.13 µm CMOS technology which provides 17 dB power gain while consuming 15 mW from a 1-V voltage supply. The average noise figure is 5.5 dB and the simulated input-referred IP3 (IIP3) is - 7.7 dBm. The input return loss (S11) and output return loss (S22) are less than -10 dB and -25 dB, respectively. The reverse isolation (S12) is better than -54.52 dB.
Optimizing current control performance in double winding asynchronous motors in large power inverter drives

The operation of AC drives in applications requiring high overload capability imposes hard working conditions on the electronic switching devices. The use of induction motors with two stator windings, fed by two inverter modules, allows large power rating in variable speed drives for high performance applications. This paper shows the structure and the main features of a field-oriented control for a double winding motor, fed by two GTO inverters. The operational results of an 850 kW drive, working as a melt pump in a polyethylene plant, are reported in order to describe the obtained performances.
Vadose zone moisture measurement through steel casing evaluation

Westinghouse Hanford Company has initiated investigation into the use of a standard moisture gauge for measurement of in-formation moisture content from cased wells. The presence of air in the borehole does not destroy the instrument response, in fact, the response is very sensitive to formation moisture from steel-cased boreholes. Calibration of the prototype instrument configuration and some experimental characterization for various borehole constructions have been performed and reported. Recommendations for future study are also provided.
A novel control system for automatically locking a diode laser frequency to a selected gas absorption line

A novel control system has been developed for avoiding manual operation during traditional frequency locking. The control system uses a computer with a commercial data acquisition card. This accomplishes the whole operation of frequency locking, including generating ramp, searching locking point, engaging a proportional-integral-differential (PID) regulator at the proper time and outputting PID compensation signal. Moreover, a new method has also been employed to make the novel control system accurately identify the locking points of all absorption lines within the scanning range, so that the laser frequency can be automatically firmly brought onto any selected absorption line centre without any adjusting time. The operation of the system, the ability to identify absorption lines and the performance of the frequency locking were discussed in detail. Successful tests were made with two different lasers: external cavity diode lasers and distributed feedback diode lasers.
APPROVAL PREDICTION FROM IMPROVEMENT REQUESTS BASED ON SENTIMENT ANALYSIS

: Even after delivering the product by implementing all the features as per customers requirements, the improvement or enhancement requests are frequently proposed by the users. For a product if more numbers of stakeholders are there, then the improvement requests are more in number and also frequency of receiving requests is high. Though the received requests are high in number, all are not suitable to implement. It is very time consuming for a developer to manually go through each and every request and to differentiate them between implementable and un-implementable requests. So, to overcome this problem, sentiment-based analysis can be used to predict the most likely requests which will be approved for implementation. This approach makes the software applications competent in the market by helping in implementing the features at a rapid rate and thus meeting the deadlines. In this approach, the first step is to pre-process improvement requests using natural language pre-processing techniques. Second is to calculate the sentiment of each improvement request by identifying the words having positive and negative sentiments in the summary attribute of the data collected. Third is to train the machine learning based classifier to predict whether a given improvement request would be approved. The proposed approach is evaluated with the sample history data from real software applications by using the algorithms SVM (Support Vector Machine), Naïve Bayes, Logistic Regression and Random Forest. A comparison among these algorithms is done to decide on the best algorithm for the kind of the data considered
Demand risk and contractual abandonment : a real op ons analysis of the BR-381 / 262 / MG / ES highways concession

Recebido: 12 de junho de 2020 Aceito para publicação: 12 de outubro de 2020 Publicado: 20 de dezembro de 2021 Editor de área: Antônio Nélson Rodrigues da Silva ABSTRACT This ar1cle assesses the rela1onship between demand risk and contractual abandonment of highway concessions according to recent changes in Brazilian regula1on. Contractual abandonment is an existent tacit managerial flexibility in contracts of this type and can add value to the project since the concessionaire, according to the law, must be compensated for the investments made, regardless of the termina1on origin. The real op1ons theory was applied to model the abandonment op1on of the BR-381-262/MG/ES highway concession. Based on the expected cash flow for the project, currently in the bidding process, and historical data on demand risk for similar projects, the binomial model was applied to price the op1on. Under those condi1ons, it was found that the op1on adds substan1al value to the project, about R$ 2.6 billion. This work contributes to a be=er understanding of the rela1onships among uncertain1es, the abandonment of the project and the added value. It is important to have prior knowledge on the issue of contractual abandonment in order to define op1mal levels of incen1ves and indemni1es for provision purposes.
Determinant Factors of Intellectual Capital for Improving Public Sector Innovation: An Empirical Study from Indonesia

The aim of the study is to explore the impact of intellectual capital and knowledge management on public sector innovation and also role knowledge management as the mediator variable. The study applied a descriptive quantitative method and by using a simple random sampling approach to 200 civil workers in Indonesian government entities. The data was gathered using an online questionnaire technique and analyzed using the AMOS program for structural equation modeling (SEM). According to the findings of the research, intellectual capital has a substantial influence on knowledge management. As a result, intellectual capital and knowledge management have a significant impact on public sector innovation, with knowledge management serving as a mediator between intellectual capital and public sector innovation. Besides that, the findings of this study suggest that organizations can increase innovation by choosing the right intellectual capital and utilizing good knowledge management. This work addresses a vacuum in the literature on applying knowledge management in the public sector, and so adds substantially to the theoretical progress of the area. Moreover, this is the first study to test the mediating role of knowledge management in the relationship between intellectual capital and innovation in the public sector of a developed country.
The Relationship between Dynamic Capabilities, Marketing Capabilities, and Environmental Turbulence: An Empirical Study from China

This study proposes a model and attempts to illustrate the relationship between the frequency of dynamic capability utilization and marketing capabilities, and how market, technology, and competitor turbulence may affect these relationships. The findings suggest that in a highly turbulent environment, frequent use of sensing and integration capabilities may cause certain changes in the impact of marketing capabilities, and in a highly competitive environment, marketing capabilities are positively correlated with company performance. The sample consists of 212 enterprises of China with a three-year vertical data span. The partial least square program Smart-PLS was used for data analysis. The careful management of dynamic capabilities (i.e., relational, sensory, and inclusive) is required to address environmental conditions to achieve capacity alignment and ultimately enhance performance. Our findings demonstrate that relationship capabilities are valuable to the organization and might even help improve its sensing and integrating capabilities. In a highly competitive environment, marketing capabilities contribute the most to company performance. The more frequent the environmental turbulence, the higher the impact of integration capabilities on marketing capabilities. This situation necessitates the organization’s usage of dynamic capabilities to modify its marketing approach effectively between stable and turbulent environments.
The Effect of Economic Openness on Multifactor Productivity: Empirical Evidence from Selected Asian Countries*

Variation in demand, natural resource availability, and technological advancement within a country are the main reasons for necessitating export and import activities between nations. Accordingly, this paper aims to analyze the effect of economic openness on Multifactor Productivity (MFP) in selected Asian countries (Vietnam, Thailand, The Philippines, Indonesia, Cambodia, China, Japan, Malaysia, South Korea, and Singapore) based on data for the period 1990–2018. The analysis conducted in the study employed the panel ARDL approach based on the estimation by Pooled Mean Group (PMG), Mean Group (MG), and Dynamic Fixed Effect (DFE). The Hausman test conducted indicates that the PMG estimation is better than that of MG and DFE since it has a higher variability value than the significance value. The results revealed that economic openness is able to elicit significant and positive effects on short-term and longterm MFP growth. In addition, the study established that other variable, such as the number of schooling years, are also able to produce a positive and significant effect on MFP growth in the long term. Since economic openness can impact MFP growth, every country should thus increase its export activities through more capital and worker inputs that will stimulate greater production.
A passivity-based multilevel active rectifier with adaptive compensation for traction applications

The control of a single-phase multilevel H-bridge rectifier suitable for traction applications is considered. Such a converter often presents instability problems making difficult its design and uncertain its behavior. In this paper the use of a passivity-based controller is experimentally investigated. Such a controller achieves stability, unity power factor, good balancing between the two DC links, and satisfactory behavior even in the presence of load changes. A right choice of the damping parameters allows the fulfilling of system requirements in terms of DC-link voltage error and grid current distortion.