Input Method Research Articles

Study of Classroom Discourse of English-Major Interns from the Perspective of Functional Linguistics

Based on the qualitative analysis of classroom discourse of English-major interns, this study investigates the characteristics and causes of classroom discourse of English-major interns in underdeveloped areas in western China from the perspective of functional linguistics, and endeavors to explore the reasons for these characteristics from social context. The results show that the classroom discourse of English-major interns has the following three characteristics: 1) code-switching is common; 2) the types of clauses are mainly imperative sentences, declarative sentences with rising intonation; 3) teachers talk a lot and dominate the conversational turn. Code-switching reflects the shortage of target language input and outdated teaching methods in English class; and the second characteristic just echoes with existing research; teacher’s dominance over conversational turn indicates interns’ imitation of their instructors’ teaching mode, hoping to construct their teacher identity. This paper puts forward relevant suggestions to the above-mentioned problems, including adopting a research-guided teaching in elementary education, reinforcing the supervision of college internship instructors, diversifying the way interns constructing their teacher identities.

Pengembangan Aplikasi E-Commerce Menggunakan Metode Web Information System Development Methodology (Studi Kasus: Jaks Store.Id)

The jaks_store.id shop is a shop that sells various kinds of adventure tools such as camping tents, flysheets, sleeping bags, etc. this store was founded in 2020 at the beginning of covid-19 this jaks_store.id store already uses internet media, namely Instagram and Whatsapp with a total of 40 products, even though it has used Instagram and Whatsapp media, marketing is still not optimal and also the jaks_store.id store in processing data product and sales data still use manual input methods so that errors often occur in terms of inputting data both from inputting product data and from product sales results. Therefore, jaks_store.id requires an E-Commerce website-based sales facility or service to make it easier for stores to process product data and also add up product sales results so that there are no errors in inputting products back and also with this E-commerce customers can also facilitated in terms of transacting online. In its development using the WSDM method and also using the PHP programming language and using MySQL and UML (Unified Modeling Language) including use case diagrams, activity diagrams and class diagrams. With the development of this system, it is hoped that it can help this jaks_store.id store in managing products so that there are no errors in inputting goods.

AR 플랫폼을 위한 인터랙션 선정법 및 적용 사례 소개

AR technology is an essential technology to provide closer interaction with users in the metaverse and digital twin environments. Representative interaction methods for displaying content on the AR platform include image recognition, QR code recognition, NFC tag recognition, GPS signal, and Beacon recognition. In applying these various input methods, it is common for most developers to select and develop an input method empirically. In this paper, we examine the advantages and disadvantages of these input methods and implementation methods to reduce trial and error in the initial development of AR applications. In addition, we studies are presented to help find suitable AR interactions cases.

Pemakaian Metode ASME PTC 4.1 Pada Evaluasi Performa (Efisiensi) Boiler Pulverized Firing di Pembangkit Listrik Tenaga Uap (PLTU)

The rankine cycle is widely used for thermal generators that use steam as a turbine driver in power generation plant. There are 4 main equipments in power plant with rankine cycle system that is: Boiler, Turbine, Condenser and Feed pump. Boiler is a tool to heat water up to steam with high temperature and pressure. Then steam goes into the turbine to drive the generator. The steam coming out of the turbine is cooled inside the condenser to be changed into liquid again. Condenser coolers are widely used in steam power plants is sea water, but some are using river water. Water becomes a working fluid in the rankine cycle and undergoes closed cycle (close loop cycle) meaning continuously water at the end of the cycle process re-entry to the early process cycle. There are several methods to calculate boiler efficiency by direct method (input method) and heat loss method (energy balanced method). The calculation by the direct method by dividing the resulting steam energy divided by the fuel energy coming into the boiler. While the calculation of boiler efficiency with heat loss method is the fuel energy that enter the boiler reduced by losses that occur in the boiler. ASME PTC 4.1 method can be used to calculate boiler efficiency at large boiler capacity, so PTC 4.1 method is often used to evaluate boiler in power plant. The ASME PTC 4.1 method is recommended for the calculation of heat-loss methods in the boiler and is often performed to review the efficiency according to the design as a benchmark.

On dynamic response and damage evaluation of bridge piers under far-field explosion loads

This paper aims to investigate of the dynamic response and damage mechanism of typical bridge piers under far-field explosions numerically and develop a feasible scheme for rapid damage evaluation of bridge piers. An ANSYS-AUTODYN-based explicit finite element formulation is introduced in which the dynamic input method of blast waves is developed using subroutines. The tests of drop hammer impact and far-field explosion are referenced to verify the reliability of the formulation and the mesh scale applicable to beam-column members is determined. Based on the validated formulation, the refined fluid–solid coupling models of typical single-column and double-column piers are established to explore their far-field blast responses. The effects of input parameters (i.e., the strength and angle of the blast wave,) on the pier response are analyzed. It is demonstrated that bending damage occurs in bridge piers is similar to that of cantilever beam under different strength loads, while the damage of double-column pier members under the constant displacement increases with the increase of the blast wave angle. By incorporating the crack distribution, quantitative assessing criterion and P-I diagram, a damage evaluating scheme is proposed and the damage regularities of piers under far-field blast loads are acquired. The present work can serve as a valuable reference for blast-resistant design and damage assessment of bridge piers under far-field blast loads.

Java Script Powered Web Based Speech to Text Converter

Java script-powered web-based speech-to-text converter interface is used to access speech recognition, which involves the use of the Web Speech API, which allows web developers to incorporate speech recognition and synthesis capabilities into their web applications. The Web Speech API offers a selection of APIs for recording audio input, identifying speech, and speech to text conversion. We have developed a speech-to-text input method for use with web platforms. The system is provided as a JavaScript with dynamic HTML files, and CSS. Users can use voice commands to create content and articles instead of typing. Speech recognition entails listening to speech through a device's microphone and having a speech recognition service check proper grammar for any sentence or word phrases and use as a translator from one language to other. A result (or series of results) is returned as a text string when a word or phrase is correctly identified, and subsequent actions can be started as a result. The quality of the audio input, background noise, and language support are some of the variables that affect how accurately speech-to-text recognition performed using JavaScript. However, the technology has improved significantly over the years and can provide accurate and reliable results for many use cases. Typically, the device's built-in default speech recognition system—which is present in the majority of contemporary operating systems and may be used to provide voice commands—will be utilized for speech recognition. Think about Dictation on mac OS, Siri on iOS, Cortana on Windows 10, Android Speech, etc.

Gesture Vocabularies for Hand Gestures for Controlling Air Conditioners in Home and Vehicle Environments

With the growing prevalence of modern technologies as part of everyday life, mid-air gestures have become a promising input method in the field of human–computer interaction. This paper analyses the gestures of actual users to define a preliminary gesture vocabulary for home air conditioning (AC) systems and suggests a gesture vocabulary for controlling the AC that applies to both home and vehicle environments. In this study, a user elicitation experiment was conducted. A total of 36 participants were filmed while employing their preferred hand gestures to manipulate a home air conditioning system. Comparisons were drawn between our proposed gesture vocabulary (HomeG) and a previously proposed gesture vocabulary which was designed to identify the preferred hand gestures for in-vehicle air conditioners. The findings indicate that HomeG successfully identifies and describes the employed gestures in detail. To gain a gesture taxonomy that is suitable for manipulating the AC at home and in a vehicle, some modifications were applied to HomeG based on suggestions from other studies. The modified gesture vocabulary (CrossG) can identify the gestures of our study, although CrossG has a less detailed gesture pattern. Our results will help designers to understand user preferences and behaviour prior to designing and implementing a gesture-based user interface.

A Comparative Review of Sentimental Analysis Using Machine Learning and Deep Learning Approaches

The sentiment data provides vital information about the feedback of the user’s opinion, attitude and emotions. The business of product development and digital marketing teams entirely depends upon the outcome of these sentiments and they apply various Data Mining techniques, Machine Learning and Deep Learning approaches to analyse the depth of the dataset. The Sentiment Analysis provides the automatic data mining of reviews, comments, opinions and suggestions, received from various input methods, including text, audio notes, images and emoticons, through Natural Language Processing. The analysis assists in the classification of reviewer feedback in terms of positive, negative and neutral categories. In this study, the opinions shared by individuals over various social networking sites in the case of any big event, the release of any new product or show and political events were analysed. Machine Learning and Deep Learning techniques are discussed and used dominantly to illustrate the outcome of opinions and events. The accurate analysis of vast information shared by individuals free of cost and without any influence can provide vital information for organisations and management authorities. This review analyses various techniques in the field of Aspect-Based Sentiment Analysis along with their features and research scopes and thus, it helps researchers to focus on more precise works in the future. Among the machine learning algorithms, Random Forest performed much better as compared to other methods, and among the Deep Learning approaches, Multichannel CNN outperformed with the highest accuracy of 96.23%. The paper includes the comparative study of multiple Machine Learning and Deep Learning techniques for the evaluation of sentiment data and concludes with the challenges and scope of Sentiment Analysis.

Extended harmonic input method for response spectrum determination of vehicle–bridge systems

The calculation of response power spectral densities (PSDs) from the excitation PSDs of vehicle–bridge (VB) systems is crucial for the safety evaluation of operating vehicles, bridge fatigue analysis, and vibration control optimization. However, calculations using the available methods result in considerable computational errors when applied to evaluate the response PSDs of VB systems. Hence, an extended harmonic input method (HIM) is proposed to compute the time-varying response spectrum in VB systems. First, the unique characteristics of VB systems that may cause the inapplicability of conventional methods are systematically analyzed. Subsequently, an extended version of the HIM is mathematically established to calculate the time-varying response spectrum of VB systems via the representation of inputs and decomposition of responses. Finally, a numerical example of an actual high-speed railway bridge subjected to track irregularities or seismic excitations is presented to illustrate the efficacy of the novel method.

Conservation and divergence of canonical and non-canonical imprinting in murids

BackgroundGenomic imprinting affects gene expression in a parent-of-origin manner and has a profound impact on complex traits including growth and behavior. While the rat is widely used to model human pathophysiology, few imprinted genes have been identified in this murid. To systematically identify imprinted genes and genomic imprints in the rat, we use low input methods for genome-wide analyses of gene expression and DNA methylation to profile embryonic and extraembryonic tissues at allele-specific resolution.ResultsWe identify 14 and 26 imprinted genes in these tissues, respectively, with 10 of these genes imprinted in both tissues. Comparative analyses with mouse reveal that orthologous imprinted gene expression and associated canonical DNA methylation imprints are conserved in the embryo proper of the Muridae family. However, only 3 paternally expressed imprinted genes are conserved in the extraembryonic tissue of murids, all of which are associated with non-canonical H3K27me3 imprints. The discovery of 8 novel non-canonical imprinted genes unique to the rat is consistent with more rapid evolution of extraembryonic imprinting. Meta-analysis of novel imprinted genes reveals multiple mechanisms by which species-specific imprinted expression may be established, including H3K27me3 deposition in the oocyte, the appearance of ZFP57 binding motifs, and the insertion of endogenous retroviral promoters.ConclusionsIn summary, we provide an expanded list of imprinted loci in the rat, reveal the extent of conservation of imprinted gene expression, and identify potential mechanisms responsible for the evolution of species-specific imprinting.

Magnetic/conductive/elastic multi-material 3D-printed self-powered sensing gloves for underwater/smoke environmental Human-Computer Interaction

Current Human-Computer Interaction (HCI) devices allow interactive communications between the users’ gestures and the computers. However, extreme environments beyond atmosphere, such as underwater or smoke, will greatly interrupt the normal operation of existing HCI devices. Here we demonstrated the fabrication of 3D-printed self-powered sensing gloves that can be used for underwater/smoke environmental HCI. A home-made multi-extrusion-head manipulator, which can simultaneously print three kinds of functional inks including magnetic, conductive and elastic materials, has been developed to generate the self-powered sensing gloves. The magnetic part was printed on the polymeric thumb region while four liquid metal coils were printed on the other four fingers, yielding the self-powered gesture recognition by clicking the fingers or nine-key input method keys of alphabetic typing. Our work offers a design of self-powered sensing glove for gesture recognition and therefore provides a pathway to realize HCI in extreme environments.

THE EVALUATION OF ENHANCING CHARACTER EDUCATION PROGRAM

This research aims to find efforts and strategies to improve the character education strengthening program by producing recommendations for the continuation of the next character education strengthening program. This research uses the Context, Input, Process, and Product (CIPP) method with the samples in this research are Lecturers, Rector/Director of Higher Education and Higher Education Officials of the Ministry of Education and Culture related to the Character Education Strengthening Program at Buddhist Universities in Banten. The results of character education strengthening program at the Buddhist Colleges in Banten takes the form of outputs and outcomes in order to form graduates of Buddhist Colleges with national character. Based on the results of the CIPP analysis, in the Context component, the character education strengthening program at Buddhist Colleges in Banten includes aspects of requirements analysis, the objectives, targets and policies getting "Good" evaluation results, in the Input component which includes aspects of resources, organization and infrastructure after going through the evaluation getting a range of "Good", the Process component of the character education strengthening program at Buddhist Colleges in Banten includes work procedures, activity schedules and implementation processes, based on the results of the evaluation getting "Adequate", the Product component which includes Output and Outcomes based on the results of the evaluation getting "Adequate." The assessment of the effectiveness of the character education strengthening program in the scope of education in general, is quite effective because this character education strengthening program refers to the priority of certain values that will be the focus of learning, understanding, understanding, and practice in order for character education to change the behavior, way of thinking, and way of acting of the entire Indonesian nation to be better and have integrity.

EVALUATION OF THE INCLUSION PROGRAM AT THE INCLUSIVE SENIOR HIGH SCHOOLS IN BOGOR, WEST JAVA

Education for children with special needs needs to be planned, implemented, monitored and evaluated based on quality standards. Therefore, it is required a successful strategy of providing learning and tutorials to develop progress in autistic children. The purpose of this evaluation research is to describe the results of an assessment of the inclusion program at Inclusive Senior High Schools in Bogor in order to improve and develop the inclusion program which has been implemented since 2010. Method of this research is qualitative with descriptive research type uses the Context, Input, Process, and Product (CIPP) method. Informants were determined using a purposive sampling technique in this study, who were Educators at Inclusive High Schools in Bogor Regency. While data collection techniques are carried out by observation, in-depth interviews with informants, and the use of written documents. Then to ensure the validity of the data in this study a triangulation technique was used. Furthermore, data analysis technique is using data reduction, data presentation and conclusion making. The results obtained from this research indicated that the process of implementing the Inclusion Program at Inclusive Senior High Schools in Bogor, West Java, has been implemented based on good procedures. This is because of the four effectiveness indicators indicate that the program is implementing well in the context, input, and process components, while in the product component the average is "adequate." It means that the output and outcomes components have not fulfilled the CIPP method for the Senior High School Inclusion Program in Bogor.

Single-sided gate-wrap-around CNTFET SRAM cell for utilization in reliable IoT-based platforms

This paper proposes a novel design of an 11-transistor SRAM bit-cell with a single-ended structure and memory mini-array with the bit-interleaving architecture support using the gate-diffusion input (GDI) method based on the gate-wrap-around (GWA) CNTFETs technology. The cell core of the suggested design is composed of a robust cross-coupled structure of two asymmetric inverters based on circuit-level methodologies. The proposed bit-cell scheme exhibits significant features such as improved write-ability, read data stability, and reduced leakage/short-circuit power due to the asymmetric write-assist method and inverter gates with stacked transistors, respectively. The simulation analysis has been done based on criteria such as static noise margins (SNMs), power-delay product (PDP), and the electrical quality/yield-based figure of merits (FoMs) in write/hold/read operation cycles. The suggested SRAM bit-cell demonstrates the best results with an average of 9.36 %, 48.53 %, and 22.82 %, respectively, for FoMs against other SRAM bit-cell schemes. The Monte-Carlo simulations in the 16-nm node show better results for the proposed bit-cell in the energy and failure probability per operation cycles than similar designs, with the best performance on average of 27 % and 8 %, respectively.Finally, to investigate the effectiveness of the suggested memory cell in the real application domain, an on-chip scaled power supply memory architecture for storing digital data based on quick response (QR) code using the proposed hardware algorithm is evaluated. Our results certify that the suggested memory array configuration in comprehensive FoMs based on quality and hardware efficiency metrics shows better results than the counterpart memory architecture.

Analysis of the operation of the electrical current supply scheme to two cables of a multilayer wire rope

Purpose. Regular inspection of cables on cable-stayed bridges is key to ensuring the safety of people's lives. However, the detection signals are usually complicated by the interwoven structures of the ropes, which cause the rope defect signal and the strand signal to be mixed. To ensure the working capacity of the wire rope, it is necessary to regularly check the integrity of the cables. Research methodology. Analytical methods of observations and mathematical and statistical data processing are used in the work; system analysis when developing criteria for assessing the actual technical condition of wire ropes; the method of mathematical modeling in the development of prognostic models of cable breaks. Research results. The paper analyzes the cable rope control system when changing the parameters of the lengths of the electric current applied to two cables, and shows the nature of the distribution when the number of the damaged cable is changed to another. The obtained results demonstrate the necessity of using this method of input, because the system clearly works in different cases. Scientific novelty. The automatic cable break detection system with the function of determining the place of damage allows in automatic mode during the operation of a lifting machine equipped with a flat rubber rope to monitor the technical condition of the cables vulcanized in a rubber shell and to stop the machine in the event of a break of any cable. The change in the electric voltage between the ends of the twisted cable depends on the length of the rope as follows: with a rope length of 10 m - the potential difference does not exceed 7V, and at 100 m - 106, at 300 m - 1015 proportionally depends on the square root and the product of the electrical resistance of the cable and the specific conductivity of rubber layers of rope. Practical value. The introduction of an automatic control system will make it possible to quickly make decisions aimed at eliminating damage to flat single-layer and cable-stayed multi-layer ropes, stop the "development" of damage, reduce time spent on restoring the working condition of the lifting machine, and most importantly - increase its reliability and safety of operation.

A novel time representation input based on deep learning for ECG classification

Electrocardiogram (ECG) is an important tool used to analyze abnormal heart activity and assess heart health, especially in remote cardiac health monitoring. Although deep learning has achieved significant results in automatic ECG classification, how to combine the characteristics of ECG physiological signals to construct inputs or features with differentiation is still a key point of classification. To this end, a novel representation input method with temporal characteristics was proposed in this paper. At first, the temporal characteristic of ECG signals was extracted and transformed into a time representation input with the original input. Subsequently, the deep learning network combining Convolutional Neural Network and Long Short-Term Memory was employed for feature extraction. Simultaneous attention mechanism was used to focus on feature differences. The proposed method was validated in the classification of five classes of heartbeats (Normal heartbeat, Left bundle branch block heartbeat, Right bundle branch block heartbeat, Atrial Premature Contraction, Premature ventricular contraction), achieving a higher average accuracy, precision, sensitivity, and specificity of 98.95%, 97.07%, 96.54%, and 99.33% respectively in the MIT-BIH arrhythmia database. The results show that our method is able to combine the periodic characteristics of ECG to construct a better temporal representation input than traditional feature fusion. This method can provide a new way to classify similar physiological signals with periodic characteristics.

Interactive Quantum Chemistry Enabled by Machine Learning, Graphical Processing Units, and Cloud Computing.

Modern quantum chemistry algorithms are increasingly able to accurately predict molecular properties that are useful for chemists in research and education. Despite this progress, performing such calculations is currently unattainable to the wider chemistry community, as they often require domain expertise, computer programming skills, and powerful computer hardware. In this review, we outline methods to eliminate these barriers using cutting-edge technologies. We discuss the ingredients needed to create accessible platforms that can compute quantum chemistry properties in real time, including graphical processing units-accelerated quantum chemistry in the cloud, artificial intelligence-driven natural molecule input methods, and extended reality visualization. We end by highlighting a series of exciting applications that assemble these components to create uniquely interactive platforms for computing and visualizing spectra, 3D structures, molecular orbitals, and many other chemical properties. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 74 is April 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

COMPARATIVE EFFICIENCY MEASUREMENT OF THE SELECTED GARMENTS FACTORIES IN BANGLADESH: AN APPLICATION OF DATA ENVELOPMENT ANALYSIS (DEA)

Readymade garments sector is the largest export earning sectors in Bangladesh. The efficiency of that sector is needed to compete and survive in the competitive global market. For the purpose of identifying the inputs and output variables which are deriving the efficiency of garments factories in Bangladesh, five garment factories have been selected purposively on the basis of availability of data as a sample size. Pearson coefficient correlation has been used to find out significant input variables related with output variable of sales revenue indicating the result that only cost of material and labour has significant impact among four input variables. From the method of CRS input oriented DEA, it is estimated that two garments factory are efficient relative to the(Fawellient factory of the rest three. If it is possible to reduce the excessive used of inputs (percentages) cost of material and labour then rest three inefficient factories would be capable as like as efficient two.

Koopman-Operator-Based Robust Data-Driven Control for Wheeled Mobile Robots

The Koopman operator theory offers a way to construct explicit control-oriented high-dimensional linear dynamical models for the original nonlinear systems, solely using the input–output data of the dynamical system. The modeling accuracy of the Koopman model largely depends on the basis functions (lifting functions), dimensionality, and data quality. However, there has not been a systematic way to solve the problems mentioned above. In this article, a Koopman-operator-based robust data-driven control framework is proposed for wheeled mobile robots, via incorporating tools from control theory, to solve the problem of modeling errors of the Koopman model. By employing an extended state observer, the modeling errors of the Koopman model, including unknown external disturbances, are online estimated and compensated in the control signal in real time. Then, sliding-mode control is used to synthesize the controller. Importantly, the method of virtual control input is proposed, to cope with the model errors arising from the rotational motion of all the mobile robots. Besides, stability analysis is conducted, and the optimal dimensionality of the Koopman model is experimentally selected. Finally, experimental tests on an omnidirectional mobile robot are carried out to verify the effectiveness of the proposed control scheme, in terms of tracking performance and robustness.

Input-Output Equations and Identifiability of Linear ODE Models

Structural identifiability is a property of a differential model with parameters that allows for the parameters to be determined from the model equations in the absence of noise. The method of input–output (IO) equations is one method for verifying structural identifiability. This method stands out in its importance because the additional insights it provides can be used to analyze and improve models. However, its complete theoretical grounds and applicability are still to be established. A subtlety and key for this method to work correctly is knowing whether the coefficients of these equations are identifiable. In this article, to address this, we prove identifiability of the coefficients of IO equations for types of differential models that often appear in practice, such as linear models with one output and linear compartment models in which, from each compartment, one can reach either a leak or an input. This shows that checking identifiability via IO equations for these models is legitimate, and as we prove, that the field of identifiable functions is generated by the coefficients of the IO equations. Finally, we exploit a connection between IO equations and the transfer function matrix to show that, for a linear compartment model with an input and strongly connected graph, the field of all identifiable functions is generated by the coefficients of the transfer function matrix even if the initial conditions are generic.