Words Per Minute Research Articles

Predictions of electricity consumption in a campus building using occupant rates and weather elements with sensitivity analysis: Artificial neural network vs. linear regression

This study compares building electric energy prediction approaches that use a traditional statistical method (linear regression) and artificial neural network (ANN) algorithms. We investigate how significantly occupancy rates and local environmental conditions, such as temperature, humidity ratio, solar radiation, cloud type, and wind speed, impact the actual electric energy consumption of a campus building for both working and non-working days. To analyze the degree of impact of each input data type element, an impact value factor was applied to these data sets. The results illustrate that the ANN modeling was more accurate and stable than the linear regression method in predicting the electricity consumption for working days. By impact factor analysis for working days, occupancy rates were found to strongly dominate the electricity consumption in the building, while temperature and humidity also affected the results. However, there were no accuracy differences between the two models in predicting electricity consumption on non-working days because different data type elements had similar impact on the non-working day results. The two models—linear regression and ANN with a Levenberg–Marquardt Back Propagation (LM-BP) algorithm—were able to meet the long-term and real-time hourly prediction requirements for electricity consumption of an actual building based on occupancy rates and local environmental conditions. The analysis of the input element changes on a macroscopic scale is helpful in predicting how each element influences electric energy consumption in buildings with numerical impact factor. The proposed ANN method with LM-BP algorithm can be used as a reliable approach, compared with the linear regression modeling, for predicting the electricity consumption of a building.

How Do Proficient and Less Proficient Students Differ in Their Composition Processes?

ABSTRACT We evaluate how higher- vs. lower-scoring middle-school students differ in their composition processes when writing persuasive essays from source materials. We examined differences on four individual process features–time taken before beginning to write, typing speed, total time spent, and number of words started. Next, we examined differences for four aggregated process measures: fluency, local editing, macro editing, and interstitial pausing (suspending text entry at locations associated with planning). Results showed that higher vs. lower scoring students were most consistently differentiated by total time, number of words started, and fluency. These differences persisted across two persuasive subgenres and two proficiency criteria, essay score and English language arts total-test score. The study’s findings give a more complete picture of how the processes employed by more- and less-successful students differ, which contributes to cognitive writing theory and may have eventual implications for education policy and instructional practice.

Near mean motion resonance of terrestrial planet pair induced by giant planet: application to Kepler-68 system

ABSTRACT In this work, we investigate configuration formation of two inner terrestrial planets near mean motion resonance (MMR) induced by the perturbation of a distant gas giant for the Kepler-68 system, by conducting thousands of numerical simulations. The results show that the formation of terrestrial planets is relevant to the speed of type I migration, the mass of planets, and the existence of giant planet. The mass and eccentricity of the giant planet may play a crucial role in shaping the final configuration of the system. The inner planet pair can be trapped in 5:3 or 7:4 MMRs if the giant planet revolves the central star with an eccentric orbit, which is similar to the observed configuration of Kepler-68. Moreover, we find that the eccentricity of the middle planet can be excited to roughly 0.2 if the giant planet is more massive than 5 MJ; otherwise, the terrestrial planets are inclined to remain in near-circular orbits. Our study may provide a likely formation scenario for the planetary systems that harbour several terrestrial planets near MMRs inside and one gas giant exterior to them.

Improving Energy Expenditure Estimation through Activity Classification and Walking Speed Estimation Using a Smartwatch.

Energy expenditure (EE) estimation is an important factor in tracking personal activity and preventing chronic diseases, such as obesity and diabetes. The challenge is to provide accurate EE estimations in free-living environment through portable and unobtrusive devices. In this paper, we present an experimental study to estimate energy expenditure during sitting, standing and treadmill walking using a smartwatch. We introduce a novel methodology, which aims to improve the EE estimation by first separating sedentary (sitting and standing) and non-sedentary (walking) activities, followed by estimating the walking speeds and then calculating the energy expenditure using advanced machine learning based regression models. Ten young adults participated in the experimental trials. Our results showed that combining activity type and walking speed information with the acceleration counts substantially improved the accuracy of regression models for estimating EE. On average, the activity-based models provided 7% better EE estimation than the traditional acceleration-based models.

Effects of a sit-stand-walk intervention on musculoskeletal discomfort, productivity, and perceived physical and mental fatigue, for computer-based work

The effects of a sit-stand-walk intervention to reduce musculoskeletal discomfort, attenuate perceived physical and mental fatigue, and increase physical activity without adversely affecting productivity was investigated for computer-based work. A between-participants design was used with 80 participants randomly assigned to one of five work conditions (sit-stand, stand-sit, sitting, standing and sit-stand-walk) to perform a 60-min computer-based typing transcription task. Musculoskeletal discomfort, and perceived physical and mental fatigue were reported through surveys; productivity was measured by typing speed and typing errors. For the sit-stand-walk intervention musculoskeletal discomfort was significantly less compared to sitting or standing for the hour; perceived physical fatigue was significantly less compared to standing for the hour. There were no benefits or differences among the work conditions in terms of perceived mental fatigue and productivity. By combining postural variability of sit-stand workstations with intermittent light-intensity physical activity enabled by active breaks, the sit-stand-walk intervention demonstrates a beneficial and viable alternative to sedentary office work.

Personalized Query Auto-Completion for Large-Scale POI Search at Baidu Maps

Query auto-completion (QAC) is a featured function that has been widely adopted by many sub-domains of search. It can dramatically reduce the number of typed characters and avoid spelling mistakes. These merits of QAC are highlighted to improve user satisfaction, especially when users intend to type in a query on mobile devices. In this article, we will present our industrial solution to the personalized QAC for the point of interest (POI) search at Baidu Maps, a well-known Web mapping service on mobiles in China. The industrial solution makes a good tradeoff between the offline effectiveness of a novel neural learning model that we devised for feature generation and the online efficiency of an off-the-shelf learning to rank (LTR) approach for the real-time suggestion. Besides some practical lessons from how a real-world QAC system is built and deployed in Baidu Maps to facilitate a large number of users in searching tens of millions of POIs, we mainly explore two specific features for the personalized QAC function of the POI search engine: the spatial-temporal characteristics of POIs and the historically queried POIs of individual users . We leverage the large-volume POI search logs in Baidu Maps to conduct offline evaluations of our personalized QAC model measured by multiple metrics, including Mean Reciprocal Rank (MRR), Success Rate (SR), and normalized Discounted Cumulative Gain (nDCG). Extensive experimental results demonstrate that the personalized model enhanced by the proposed features can achieve substantial improvements (i.e., +3.29% MRR, +3.78% SR@1, +5.17% SR@3, +1.96% SR@5, and +3.62% nDCG@5). After deploying this upgraded model into the POI search engine at Baidu Maps for A/B testing online, we observe that some other critical indicators, such as the average number of keystrokes and the average typing speed at keystrokes in a QAC session, which are also related to user satisfaction, decrease as well by 1.37% and 1.69%, respectively. So the conclusion is that the two kinds of features contributed by us are quite helpful in personalized mapping services for industrial practice.

Influence of virtual keyboard design and usage posture on typing performance and muscle activity during tablet interaction

This study aimed to determine the effects of virtual keyboard designs and postures on task performance and muscle activity during tablet use. Eighteen healthy adults were randomly assigned to one of three postures (DESK, LAP, BED) to complete six sessions of 60-minute typing on a tablet with three virtual keyboards (STD, WIDE, SPLIT) twice in an experimental laboratory. Keystroke dynamics and muscle activity of the forearm and neck-shoulder regions were measured by electromyography. The split virtual keyboard was found to be associated with faster typing speed (SPLIT vs STD, p = .015; SPLIT vs WIDE, p < .001) and decreased muscle activity of extensor digitorum communis (SPLIT vs STD, p = .021). Lap posture was associated with faster typing speed (p = .018) and higher forearm muscle activity (p < .05). Typing performance decreased (p < .001) with elevated neck extensor muscle activity (p = .042) when the task duration prolonged. The split virtual keyboard showed potential to improve tablet ergonomics under various postures. Practitioner Summary: Tablets have become widely used for a variety of tasks and have gradually expanded into the realm of mobile productivity and education. Adequate designs of virtual keyboards for tablets show the potential for increased task performance and decreased muscle activity pertinent to typing activity and posture constraints imposed by non-traditional work positions. Abbreviations: WPM: words per minute; IKI: inter-key press interval; EMG: electromyography; EDC: extensor digitorum communis; FDS: flexor digitorum superficialis; CES: cervical erector spinae; UT: upper trapezius; EA: electrical activity; MVC: maximum voluntary contraction; APDF: amplitude probability distribution function

CO2 absorption into aqueous diethanolamine solution with nano heavy metal oxide particles using stirrer bubble column: Hydrodynamics and mass transfer

Abstract In this research, the TiO2, ZnO, and ZrO2 nanofluids based on the DEA solution were provided exploiting the ultrasonic dispersion system to investigate the impact of the nano-particles on the CO2 absorption in a continuously stirred bubble column. The nano-particle concentration was determined in the range 0.01−0.10 wt%,. Bubble size distribution along column axis measurements was carried out using the high-speed digital camera. The influences of several factors such as CO2 partial pressure, solid loading, nanoparticle type, and stirring speed on the hydrodynamic characteristics and CO2 absorption performance were examined in detail. The presence of nanoparticles increased the gas holdup and interfacial area up to optimum value and then had a negligible effect. The stirrer speed increased the gas holdup and interfacial area up to optimum value and then decreased. Furthermore, the results showed that the adding nanoparticles in the range of 0.01−0.1 wt% increased CO2 absorption efficiency between 25.2–43.8% and the optimum value of nanoparticles can be an effective key parameter at the absorption phenomena into a dilute amine solution. Also, it was determined that at optimum stirrer speed, the removal efficiency of ZnO, TiO2, and ZrO2 nanofluids was caused an increase of about 12.1 % 8.0 %, and 13.3 %, respectively.

К выбору типа и частоты вращения мешалки для эффективного перемешивания флокулянтов в воде

К выбору типа и частоты вращения мешалки для эффективного перемешивания флокулянтов в воде

Effects of mood and aging on keystroke dynamics metadata and their diurnal patterns in a large open-science sample: A BiAffect iOS study.

Ubiquitous technologies can be leveraged to construct ecologically relevant metrics that complement traditional psychological assessments. This study aims to determine the feasibility of smartphone-derived real-world keyboard metadata to serve as digital biomarkers of mood. BiAffect, a real-world observation study based on a freely available iPhone app, allowed the unobtrusive collection of typing metadata through a custom virtual keyboard that replaces the default keyboard. User demographics and self-reports for depression severity (Patient Health Questionnaire-8) were also collected. Using >14 million keypresses from 250 users who reported demographic information and a subset of 147 users who additionally completed at least 1 Patient Health Questionnaire, we employed hierarchical growth curve mixed-effects models to capture the effects of mood, demographics, and time of day on keyboard metadata. We analyzed 86541 typing sessions associated with a total of 543 Patient Health Questionnaires. Results showed that more severe depression relates to more variable typing speed (P < .001), shorter session duration (P < .001), and lower accuracy (P < .05). Additionally, typing speed and variability exhibit a diurnal pattern, being fastest and least variable at midday. Older users exhibit slower and more variable typing, as well as more pronounced slowing in the evening. The effects of aging and time of day did not impact the relationship of mood to typing variables and were recapitulated in the 250-user group. Keystroke dynamics, unobtrusively collected in the real world, are significantly associated with mood despite diurnal patterns and effects of age, and thus could serve as a foundation for constructing digital biomarkers.

Modeling dynamic responses of a cross-river road shield tunnel under stochastic vehicle loads

Vehicle-induced dynamic loads are far more complex than those induced by trains because of their stochastic nature. In this study, we developed the stochastic dynamic vehicle load model and addressed a series of loading scenarios for a large road shield tunnel across the Yangtze River of China. The range analysis results show that, given the three factors influencing the dynamic responses of the tunnel, the pavement roughness plays a more important role than the vehicle type and running speed. The finite element model analysis shows that stress concentration occurs around the corbels fixed to the tunnel haunches; the stress amplitude of the soil responses, ranked in the descending order, is at the tunnel sides, under the tunnel bottom and above the tunnel, respectively. Under the stochastic vehicle loads, the amplitudes of the displacement of the road shield tunnel and the maximal settlement of the surrounding soils are basically one-tenth of those of the subway tunnel; the surrounding soil stress amplitude of the road shield tunnel is about one-third of that of the subway shield tunnel; while the structural stress amplitude of the road shield tunnel, focused around the corbels, are about 4 times of that of the subway shield tunnel. Those insights can be referred by the practitioners, especially those of the cross-river combined road-and-subway shield tunnels.

Evaluation of performances of different types of spray nozzles in site-specific pesticide spraying

In recent years, site-specific spraying methods, which are capable of combining the image processing technologies with electronic and information technologies, have been started to be used in the weed control and target-oriented spraying. In this study, in addition to the site-specific spraying in laboratory conditions; a mobile spraying system, which can also perform broadcast application as a reference method, was set up. The spraying performance of the mobile system was tested for three different nozzle types (standard flat fan nozzle, cone nozzle, air induction nozzle) and at speeds of 0.48, 0.60, 0.72 and 0.84 km h-1. The mobile system was operated as both broadcast and site-specific for each nozzle type and travel speed. Three artificial weed samples were used at 75 cm intervals as sampling surfaces on the movement of the mobile system in the spraying operations; filter papers (FP) and water-sensitive papers (WSP) were placed behind them on the bars. While deposition values were measured with the filter papers, water-sensitive papers were used to measure the coverage rates. The spray distribution of the site-specific method in comparison with the reference method was investigated. According to the results, site-specific spraying applications did not cause any negative impact on depositions and coverage rates. The nearest results compared with the broadcast spraying were obtained with the air induction nozzle type at a speed of 0.48 km h-1 with a 60.5% deposition amount and 95.9% coverage rate.

A Novel Approach for Vehicle Type Classification and Speed Prediction Using Deep Learning

In Vehicles automation system, Classification and speed detection has become an important research challenge in road safety and intelligent transportation system. Many systems like pattern recognition, image processing and machine learning technologies have overcome numerous hindrances to accomplish this goal. In this paper, we demonstrate a speed detection system and vehicle type classification founded on deep learning technique. Moreover, we built up Modular Neural Network (MNN) architecture, advancement algorithm and its parameters are acquired by training dataset. This integrated part of a system will enhance to finding in automation detection and traffic flow management system.

The Influence of Nozzle Type and Application Speed on Sicklepod Control with Cadre and Butyrac

Sicklepod, also colloquially known as coffeeweed, is one of the most common and troublesome weeds in Georgia peanut production systems. Spray chamber/greenhouse studies were conducted to evaluate the effects of application speed (8 and 12 MPH), nozzle type (XR, TTI, and AIXR), and herbicide treatment on sicklepod control. Earn 0.5 CEUs in Integrated Pest Management by reading the article and taking the quiz at www.certifiedcropadviser.org/education/classroom/classes/804.

Development of railway track condition monitoring from multi-train in-service vehicles

A cab-based track monitoring system has been developed which makes use of the existing on-board GSM-R cab radio present in the majority of trains operating in the UK. With the addition of a low-cost sensor, type, location and severity of the track defects are reported using the system. The system improves safety and network performance by efficiently directing maintenance crews to the location of defects, minimising time spent on maintenance and inspection. Initially, vehicle dynamic simulation was used to test the feasibility of the system for defect monitoring and to develop compensation factors for vehicle type and operating speed. Novel on-board signal processing techniques are also presented through comparison of vibration response from sites with known defects and outputs from Network Rail’s (NR) New Measurement Train (NMT). Good agreement was reported for track faults in relation to vertical and lateral alignment and dip faults. Statistically, good agreement has been demonstrated, suggesting that the data acquired could be used to provide an indication of track quality thereby improving network performance, reducing rough ride and leading to improved passenger comfort. Improvements in the measured and statistical correlation are anticipated through the use, of multi-train / multi-journey and machine learning methods.

Effects of Motor Mental Imagery Training on Tennis Service Performance during the Ramadan Fasting: a Randomized, Controlled Trial.

The objective of the present study is to analyze the effects of motor mental imagery training on tennis service performance among tennis athletes who fast during Ramadan. Participants were 38 young male tennis players, randomly divided into two groups: Imaging Training (IMG, n = 18) and control group (CG, n = 20). The CG has watched videos on the history of the Olympic Games, while IMG has followed a training program in motor imagery. The performance of the tennis service was obtained by the product between accuracy and speed of typing (accuracy × average speed of all shots (km/h)). The effect of group/time interaction (p < 0.01) was identified for all performance indicators (accuracy, running speed and performance (speed × precision)), with improvement only in IMG (p = 0.01). The results showed that motor imagery training could be an effective strategy for mitigating/counteracting the negative effects of Ramadan on the tennis service performance.

MP83-19 HYGIENIC KEYBOARDS - DESIGNED TO REDUCE INFECTIONS, BUT AT WHAT PRICE?

You have accessJournal of UrologyGeneral & Epidemiological Trends & Socioeconomics: Quality Improvement & Patient Safety IV (MP83)1 Apr 2020MP83-19 HYGIENIC KEYBOARDS - DESIGNED TO REDUCE INFECTIONS, BUT AT WHAT PRICE? Phillip Stokes, Zahabiya Campwala, John Smith, Jeremy Brown, Arthur Goyne, Akin S. Amasyali, Ruth Belay*, Daniel Baldwin, Mohammad Hajiha, Muhannad Alsyouf, and D. Duane Baldwin Phillip StokesPhillip Stokes More articles by this author , Zahabiya CampwalaZahabiya Campwala More articles by this author , John SmithJohn Smith More articles by this author , Jeremy BrownJeremy Brown More articles by this author , Arthur GoyneArthur Goyne More articles by this author , Akin S. AmasyaliAkin S. Amasyali More articles by this author , Ruth Belay*Ruth Belay* More articles by this author , Daniel BaldwinDaniel Baldwin More articles by this author , Mohammad HajihaMohammad Hajiha More articles by this author , Muhannad AlsyoufMuhannad Alsyouf More articles by this author , and D. Duane BaldwinD. Duane Baldwin More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000975.018AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Currently, hospitals are under pressure to reduce hospital-acquired infections. One technique suggested to reduce infection is the use of a novel flat computer keyboard, which are easier to sterilize. In an attempt to reduce infections, our institution replaced all conventional keyboards with a flat “hygienic” keyboard covered by silicone. Although these keyboards are easily cleaned, lack of tactile feedback from conventional keys appeared to make typing more difficult and may increase the potential for errors. Medical errors cost $20 billion and kill 100 thousand people a year in the U.S. The purpose of this study is to compare accuracy, speed and error correction rates between a “hygienic” flat and conventional keyboard. METHODS: A prospective randomized study including 40 participants (physicians, nurses and medical students) was conducted in the perioperative setting. Subjects performed practice and recorded typing tests on the conventional and flat keyboard using a randomized, crossover design. Results were recorded as words per minute (WPM), accuracy, and error correction rates. Accuracy was determined by the number of incorrectly typed characters. The clinical impact of the two different keyboard types was determined by measuring the number of typed words for every patient admitted to the urology service for 30 days. The data for word count, accuracy and speed were compared between a conventional and “hygienic” keyboard when employed for a 1 year period. RESULTS: Subjects typed significantly faster using the conventional keyboard (58 WPM) compared to the flat keyboard (50 WPM; p<0.001). In addition accuracy was significantly higher using the conventional (94.5% vs. 90%; p=0.0236) compared to the flat keyboard. The percent error correction was similar (52% vs 52%; p=0.31). During the one month study period, the urology service typed an average of 526 (43-9480) words for 67 patients with a total of 35,245 words. Applying word and error rates to a one-year period, using the conventional keyboard would save 17.7 hours and 19,032 less errors compared to the flat “hygienic” keyboard. CONCLUSIONS: The optimal solution for reducing infection transmission would not compromise speed or accuracy. This study demonstrates that any potential benefit from reduced infection seen with the flat keyboard comes at the price of a 16% reduction in typing speed and 5% greater error rate. Source of Funding: None © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e1263-e1263 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Phillip Stokes More articles by this author Zahabiya Campwala More articles by this author John Smith More articles by this author Jeremy Brown More articles by this author Arthur Goyne More articles by this author Akin S. Amasyali More articles by this author Ruth Belay* More articles by this author Daniel Baldwin More articles by this author Mohammad Hajiha More articles by this author Muhannad Alsyouf More articles by this author D. Duane Baldwin More articles by this author Expand All Advertisement PDF downloadLoading ...

Brain computer interface based smart keyboard using neurosky mindwave headset

In the last decade, numerous researches in the field of ‎ electro-encephalo-graphy (EEG) and brain-computer-interface ‎‎ (BCI) have been accomplished. BCI has been developed to aid ‎ disabled/partially disabled people to efficiently communicate ‎ with the community. This paper presents a control tool using ‎ the Neurosky Mindwave headset, which detects brainwaves ‎‎ (voluntary blinks and attention) to form a brain-computer ‎ interface (BCI) by receiving the system signals from the frontal lobe. This paper proposed an alternative computer input device ‎ for those disabled people (who are physically challenged) ‎ rather than the conventional one. The work suggested to use ‎ two virtual keyboard designs. The conducted experiment ‎ revealed a significant result in developing user printing skills ‎ on PCs. Encouraging results (1.55-1.8 word per minute ‎‎ (WPM)) were obtained in this research in comparison to other ‎ studies.

Combined scaled manhattan distance and mean of horner’s rules for keystroke dynamic authentication

Account security was determined by how well the security techniques applied by the system were used. There had been many security methods that guaranteed the security of their accounts, one of which was Keystroke Dynamic Authentication. Keystroke Dynamic Authentication was an authentication technique that utilized the typing habits of a person as a security measurement tool for the user account. From several research, the average use in the Keystroke Dynamic Authentication classification is not suitable, because a user's typing speed will change over time, maybe faster or slower depending on certain conditions. So, in this research, we proposed a combination of the Scaled Manhattan Distance method and the Mean of Horner's Rules as a classification method between the user and attacker against the Keystroke Dynamic Authentication. The reason for using Mean of Horner’s Rules can adapt to changes in values over time and based on the results can improve the accuracy of the previous method.

A Review on Feature Extraction in Keystroke Dynamics

Feature extraction is an important process before an analysis of a data is carry out. Different behaviour of a user while using the keyboard is a feature that need to be identified in the Keystroke Dynamics (KD) study. Example are the difference between typing time between letters, typing speed and the force of a person pressing the keyboard. Past studies related to feature extraction for KD have been described in this paper. Various features that have been used are listed and the results of the study are compared. The results of this writing are expected to help new researchers in the process of evaluating KD.