User Feels Research Articles

Lighting Features Affecting the Well-Being of Able-Bodied People and People with Physical Disabilities in the Park in the Evening: An Integrated and Sustainable Approach to Lighting Urban Green Areas

This study focuses on the analysis of lighting in night conditions to explain what lighting in parks should look like and how parks should be lit from the point of view of people’s perceptions. It addresses the impact of the lighting configuration of urban parks on preference, safety, mystery, legibility, and contact with the environment. The feelings of wheelchair users and able-bodied people were measured. The respondents assessed park landscapes presented in visualisations that varied in terms of lighting features and spatial contexts. This research showed, inter alios, that the participants rated evenly lit spaces more highly than those featuring spot lighting. In unevenly lit spaces, the lighting of the surroundings turned out to be crucial import for able-bodied people, while for the disabled respondents, a combination of lighting of the surroundings and of paths was significant. For evenly lit spaces, path lighting is less important for disabled people than for those without disabilities. These insights can help researchers to look at lighting solutions in a more human-centered way and take into account the environment in which they are used. This allows the design of night lighting in parks to be socially sustainable and promotes access to urban green spaces for all citizens. The study emphasises that the provision of sustainable lighting in parks should take into account different social groups, making light a common good.

Acoustic and vibrations measurments in an autonomous shuttle bus

In response to the ADEME's call for Autonomous Road Vehicle Experimentation projects, a consortium was created to propose the SAM project about Safety and Acceptability of Autonomous Driving and Mobility. It was composed of industrial and research teams, associated with local partners. SAM is a national project involving large-scale trials of autonomous driving and mobility on open roads. The assessments covered several topics, including environmental impacts, focusing on air pollution, noise and the life cycle of components. Cerema proposed a methodology to characterize acoustic and vibration levels for autonomous driving in the specific site near Paris. The tests consisted in instrumenting the interiors of an automated shuttle and a conventional car to determine the user's feelings. The vehicles were driven in a quiet area and in a high traffic area. The results displayed by Cerema are based on statistical studies on 20 vehicle passages for each experiment. The indicators were characterized for the entire route and by homogeneous sections. In fluid navigation situation, the measurements showed that the acoustic and vibration impacts are minimal. However, the tests have highlighted the effects of the lack of anticipation of an automated shuttle during specific events requiring rapid braking.

THE DIGITAL GATEAWAY TO EMPLOYMENT: INSIGHTS INTO ONLINE JOB PORTAL USAGE

Abstract – The feelings of WEB users have a great benefits for students , colleges and companies. It is necessary to structure well the unstructured data from various placement platforms for proper and meaningful analyses. For the classification of multilingual data, the analysis of feelings has recognized significant information od student and companies. This is called the Job Portal that may be used to maintain the visible connection between company and colleges and companies and student through the mediator Admin. To solve the problem of old job portal this introduced that it has minimum manual work for minimum error and other problems. These architectures may be used Java based languages. In this research variuos data, we had started this project to give more and opportunities for student placement. Key Words: project, job, management, system, application, online software, deployment, security.

DIGITAL RECRUITMENT REVOLUTION: EVALUATING THE EFFECTIVENESS OF ONLINE JOB PORTALS

Abstract – The feelings of WEB users have a great benefits for students , colleges and companies. It is necessary to structure well the unstructured data from various placement platforms for proper and meaningful analyses. For the classification of multilingual data, the analysis of feelings has recognized significant information od student and companies. This is called the Job Portal that may be used to maintain the visible connection between company and colleges and companies and student through the mediator Admin. To solve the problem of old job portal this introduced that it has minimum manual work for minimum error and other problems. These architectures may be used Java based languages. In this research variuos data, we had started this project to give more and opportunities for student placement. Key Words: project, job, management, system, application, online software, deployment, security.

Technical Blog

A blog is an online repository of experience, knowledge, and data that users post and share with other users in the form of text, video, or image files. Any experience, understanding, or knowledge that the user feels like sharing with other blog community members in order to disseminate information and other materials can be found on a blog website. He or she is free to publish anything they like, but they also have to abide by some regulations around disciplinary content that shouldn't be made obvious to other members of the community. Here "Build A Healthy and Interactive Community which will be on Benefit for Everyone" is our most essential motto. This project is an all-inclusive web portal offering a vast array of technical information topros, amateurs, and students alike. Using simple navigation and interactive tools, users can study articles, tutorials, and debates spanning a variety of technical subjects. Users may create, edit, and share insights with the help of content management systems, and strong user authentication and role-based access guarantee secure interactions. Thanks to robust search features and a lively community-driven environment, users can easily locate and engage with pertinent material. Using efficient moderating tools, administrators uphold the integrity of the platform, promoting a secure and cooperative atmosphere. With scalability, performance, and security as our top priorities, our TechBlog initiative aims to stimulate learning, make information sharing easier, and encourage creativity in the tech community

1125 Use of a Pillow Designed to Help Users Feel Cool Improves Objective Sleep Quality and Perceived Sleep

1125 Use of a Pillow Designed to Help Users Feel Cool Improves Objective Sleep Quality and Perceived Sleep

Taking the pulse about contact tracing apps on Twitter

AbstractSocial media allow citizens to express their opinions on all aspects of life and society, and this trend has been enhanced during the COVID-19 crisis, when more “traditional” ways of opinion expression were not possible. To get the feeling of Twitter users’ opinions on topics of importance we analysed tweets and combined them with relevant news, thus allowing for potential event detection. We showcase the prototypical framework that we have developed with our findings about European COVID-19 mobile contact tracing apps in tweets posted between 09/07/2020 and 10/07/2021. We obtained both high-level results (for example, trending twitter activity, sentiment polarisation of important hashtags, etc.) and more specific ones (such as, the spatial distribution of tweets regarding a specific app), which indicate that our approach can be applied in the future to get useful insights on topics of public interest that result in active discussions on social media platforms.

Analysis of The Influence of Attitude Toward Digital Products and Perception of Technology Benefits on Intention to Purchase Digital Products

This study examines how attitudes toward smartwatches and their consequences for behavioral intention to use are influenced by perceived utility, perceived ease of use, and subcultural appeal. Researchers will employ a descriptive research design type of study. Questionnaires were distributed to collect data using convenience and non-probability sampling. This study's population consists of smartwatch wearers. In this study, convenience sampling is combined with a non-probability sampling strategy. The structural equation model method will be used to examine the data in this study. Several conclusions were drawn from this study's data processing and analysis results. First, their mobility positively impacts the perceived ease of use of smartwatches. Perceived usefulness is positively affected by perceived simplicity of usage. Third, attitudes regarding smartwatches are positively impacted by perceived utility. Fourth, perceptions regarding smartwatches are positively affected by subcultural appeal. Fifth, behavioral intention to use is positively impacted by perceived usefulness, meaning that consumers are more likely to continue using a smartwatch if they believe it to be beneficial. Lastly, a user's attitude about their wristwatch positively impacts their behavioral intention to use it. This means that the more positively a user feels about their smartwatch, the more likely they will use it going forward.

Exploring Control Authority Preferences in Robotic Arm Assistance for Power Wheelchair Users.

This paper uses mixed methods to explore the preliminary design of control authority preferences for an Assistive Robotic Manipulator (ARM). To familiarize users with an intelligent robotic arm, we perform two kitchen task iterations: one with user-initiated software autonomy (predefined autonomous actions) and one with manual control. Then, we introduce a third scenario, enabling users to choose between manual control and system delegation throughout the task. Results showed that, while manually switching modes and controlling the arm via joystick had a higher mental workload, participants still preferred full joystick control. Thematic analysis indicates manual control offered greater freedom and sense of accomplishment. Participants reacted positively to the idea of an interactive assistive system. Users did not want to ask the system to only assist, by taking over for certain actions, but also asked for situational feedback (e.g., 'How close am I (the gripper)?', 'Is the lid centered over the jug?'). This speaks to a future assistive system that ensures the user feels like they drive the system for the entirety of the task and provides action collaboration in addition to more granular situational awareness feedback.

An Exploration of Factors Influencing Oversharing on Facebook Groups

Social media usage is extremely prevalent and so is the oversharing of personal information online. This paper aims to examine the factors that influence information disclosure on Facebook and how participation in groups may affect sharing behaviors. Groups can provide a more intimate and supportive environment, which may lead to excessive information sharing. An online survey was conducted on Amazon’s Mechanical Turk platform with 373 accepted responses from self-reported Facebook users. The data was analyzed to determine which demographic and personality factors are correlated with oversharing behaviors on user profiles and within Facebook groups. This work has implications for understanding how individuals seek support online and what information they feel comfortable disclosing. Oversharing may increase user feelings of social support but also may make users vulnerable to cyberbullying and social engineering attacks.

Optimized RMDL with Transfer Learning for Sentiment Classification in the MapReduce Framework

A core task in sentiment analysis is sentiment categorization, and it is crucial to understand user feelings based on their remarks in social media or product evaluations. Due to ambiguous phrases, refusal words, and other factors, categorizing sentiment presents several challenging issues. The objective of this research is to develop a hybrid optimization-based deep learning model and MapReduce framework-based sentiment categorization approach. The review document is taken from a dataset and used in this case with the MapReduce methodology. MapReduce is a software framework and programming model for analyzing massive volumes of data that consists of two phases, mapper and reducer. BERT tokenization and aspect term extraction are executed in the mapper phase, whereas sentiment analysis is performed in the reducer stage utilizing random multimodal deep learning (RMDL) with transfer learning and AlexNet and ResNet 50 as pre-trained models. In addition, the exponential coot political algorithm (ECPA) is offered as an optimization algorithm for weight optimization in RMDL. The ECPA is obtained by combining the exponential weighted moving average model (EWMA) with the coot algorithm, as well as a political optimizer (PO). The proposed ECPA_RMDL model has acquired 90.9% precision, 89.7% recall, and 89.9% f-measure.

Analyzing and computing humans by means of the brain using Brain-Computer Interfaces - understanding the user - previous evidence, self-relevance and the user's self-concept as potential superordinate human factors of relevance.

Brain-computer interfaces (BCIs) are well-known instances of how technology can convert a user's brain activity taken from non-invasive electroencephalography (EEG) into computer commands for the purpose of computer-assisted communication and interaction. However, not all users are attaining the accuracy required to use a BCI consistently, despite advancements in technology. Accordingly, previous research suggests that human factors could be responsible for the variance in BCI performance among users. Therefore, the user's internal mental states and traits including motivation, affect or cognition, personality traits, or the user's satisfaction, beliefs or trust in the technology have been investigated. Going a step further, this manuscript aims to discuss which human factors could be potential superordinate factors that influence BCI performance, implicitly, explicitly as well as inter- and intraindividually. Based on the results of previous studies that used comparable protocols to examine the motivational, affective, cognitive state or personality traits of healthy and vulnerable EEG-BCI users within and across well-investigated BCIs (P300-BCIs or SMR-BCIs, respectively), it is proposed that the self-relevance of tasks and stimuli and the user's self-concept provide a huge potential for BCI applications. As potential key human factors self-relevance and the user's self-concept (self-referential knowledge and beliefs about one's self) guide information processing and modulate the user's motivation, attention, or feelings of ownership, agency, and autonomy. Changes in the self-relevance of tasks and stimuli as well as self-referential processing related to one's self (self-concept) trigger changes in neurophysiological activity in specific brain networks relevant to BCI. Accordingly, concrete examples will be provided to discuss how past and future research could incorporate self-relevance and the user's self-concept in the BCI setting - including paradigms, user instructions, and training sessions.

PENERAPAN UI/UX PADA E-COMMERCE BATIK JAMBI DUO SERANGKAI BERBASIS WEB (STUDI KASUS GERAI BATIK JAMBI DUO SERANGKAI)

User experience is a science that studies how to design and change a user's feelings, perceptions and behavior towards a display, service and performance of a product, system or service. User experience (UX) assesses how satisfied and comfortable a person is with a product, system and service. The user interface is one of the factors that determines the increase in traffic on a website. Because users interact with programming logic through the user interface. And the design of the user interface itself is very important considering that the more effective and efficient a design is, the more comfortable the user will be to linger on the website. The user interface is one of the most important factors in building a website. E-commerce is a dynamic set of application technologies and business processes that connect companies, consumers and certain communities through electronic transactions and trading of goods, services and information that is carried out electronically. The UI/UX on the Batik Duo Serangkai Jambi e-commerce website is to provide a solution to enhance the transparent postage feature, display popular products, increase information about product color and size, and create a visual experience that spoils the eyes for customers.

The Author’s Methodology of Forecasting Election Results on the Basis of Big Data

Internet mass media provides their readers with an opportunity to express their opinions on topics (comments) being published. For this purpose each article inserted in the Internet is connected with certain means of communication. These comments are taken seriously by mass media as they contain valuable information that helps find out feelings of Internet users. Social networks generate a vast amount of unstructured data due to their use by thousands of users. Therefore, our research aims at substantiation and use of machine learning (artificial intellect) approach in order to analyze users’ feelings through comments on YouTube dealing with press-conferences given by nominated candidates. Obtained results show feasibility of the approach. The author proposes other ways of its modernization.

Design and Implementation the Prayer Reminder Application using KISS Principle based on User Centered Design

The five daily prayers are an obligation of worship for Muslims in the world. Prayers have a predetermined time schedule according to the teachings of the Prophet Muhammad SAW and have different schedules according to each region. As Muslims, it is obligatory to pray five times a day. However, there are a lot of start-up company which forgot about the employee need such as praying. One of them is called byPulsa Start-up company which wants anticipates delays in praying. Because of this reason, the Ceo at byPulsa need an application to remind the employee about praying. So, this company wants to improve the additional feature into its application and develop its application more less interaction and efficient. So, this research aims to develop the previous application into an application that can remind employees to pray. In this research, Kiss Principle Method and User Centered Design were used to this application to make it more efficient and usable for user. The results show that the user feels more satisfied with the application because it has prayer schedule feature based on user's position. The CSAT score from evaluation has score 80% which higher than previous application. This application can help and guide users in exploring their religion by following online studies and using features such as prayer beads, Islamic book recommendations, even Islamic podcasts. As well as the Kiss principle method used here, it functions to make it easier for users to interact with the application.

EXAMINING SOFTWARE QUALITY CONCEPT: BUSINESS ANALYSIS PERSPECTIVE

Software quality is a critical aspect of software development that significantly impacts business performance and customer satisfaction. However, defining software quality can be challenging, as different sources provide various definitions and perspectives. The article presents a literature review of software quality, acknowledging an ongoing debate over the years regarding the definition of software quality and the methods used for its assessment. Among all the different ideas about software quality, the article highlights key concepts that are crucial in understanding software quality: meeting requirements, satisfying users, using software features, and spotting defects. The article also checks out international standards like ISO/IEC 25010:2011 and ISO/IEC 5055:2021, introducing terms such as "Quality in use" and "Structural Quality." Unveiling a tripartite perspective elucidated in international standards—internal quality, external quality, and quality in use - the article underscores the intricate interplay between subjectivity and objectivity. The subjective dimension, influenced by user perception and contextual factors, is juxtaposed with more objective criteria such as conformance to requirements and the absence of defects. The standards provide helpful perspectives, but the human side of things, like user feelings and specific contexts, makes finding a universal definition tricky. The pivotal role of business analysis and requirements engineering in ensuring software quality is underscored. Business requirements, stakeholder needs, and the quality of functional and non-functional requirements emerge as integral components. The article argues that software quality is intricately tied to the quality of its requirements, presenting a dual perspective: compliance with quality criteria and alignment with stakeholders' expectations and business goals. Practical software quality assessment is built upon the foundational understanding of contextual nuances, user needs, and operational conditions, all discerned through business analysis.

Data mining twitter for COVID-19 sentiments concerning college online education

In the last decade there has been a large increase in corporate and public reliance on social media for information, rather than on the traditional news and information sources such as print and broadcast media. People freely express their views, moods, activities, likes/dislikes on social media about diverse topics. Rather than surveys and other structured data gathering methods, text data mining is now commonly used by businesses to go through their unstructured text in the form of emails, blogs, tweets, likes, etc. to find out how their customers feel about their company and their products/services. This paper reports upon a study using Twitter (recently renamed to “X”) data to determine if meaningful and actionable information could be gained from such social media data in regard to pandemic issues and how that information compares to a traditional survey. In early 2020, the COVID-19 pandemic hit and forced colleges to move classes to an online format. While there is considerable literature in regard to using social media to communicate geo-political issues and in particular pandemics, there is not a study using social media to explore public sentiment in regard to COVID’s forcing online education upon the public. In this study, text data mining was used to gain some insight into the feeling of Twitter users in regard to the effect of COVID-19 and the switch to online education in colleges. This study found that Twitter data mining did produce actionable information similar to the traditional survey, and the study is important since its results may influence organizations to explore the use of Twitter (and possibly other social media) to obtain people’s sentiments instead of (or in addition to) traditional surveys and other traditional means of gathering such information. This paper demonstrates both the process of text data mining social media and its application to current real-world issues.

A Conceptual Aquila Merged Arithmetic Optimization (AIAO) Integrated Auto-Encoder Based Long Short Term Memory (AUE-LSTM) For Sentiment Analysis

Sentiment analysis is a branch of analysis that uses disorganized written language to infer the opinions and emotions of people's critiques and attitudes toward entities and its features. In order to produce acceptable results, the majority of sentiment analysis models that employ supervised learning algorithms require a large amount of labeled information during the training stage. This is typically costly and results in significant labor expenses when used in practical applications. In this study, an intelligent and unique sentiment prediction system is developed for accurately classifying the positive, negative, and neutral comments from the social media dataset. Data preprocessing, which entails noise reduction, tokenization, standardization, normalization, stop word removal, and stemming, is done to ensure that the data is of a high enough quality for efficient sentiment prediction and analysis. The preprocessed data is then used to extract a mix of features, including hash tagging, Bag of Words (BoW), and Parts of Speech (PoS). Consequently, in order to choose the best features and speed up the classifier, a new hybrid optimization method called Aquila merged Arithmetic Optimization (AIAO) is used. Furthermore, an Auto-Encoder based Long Short Term Memory (AuE-LSTM), an innovative and clever ensemble learning technique, is used to precisely anticipate and classify user feelings based on the chosen data. This study uses a variety of open source social media datasets to evaluate the performance of the suggested AIAO integrated AuE-LSTM model.

NATURAL LIGHT INTENSITY AND VISUAL COMFORT THROUGH ADJUSTING THE HEIGHT OF THE CURTAIN OPENING

The type of activity, room area, and light intensity influence the visual comfort level of room users. In educational buildings, visual comfort influences the level of performance during the teaching and learning process of students. Students of the Bachelor of Architecture Study Program, FTSP, Trisakti University, use the Studio on the 6th floor (C.608-609) with 85% curtained glass window walls on the North and West, and 10% uncurtained bouvenlight windows on the South. It is estimated that the availability of natural light sources with such capacity is sufficient for the Studio learning process, but in fact users still turn on artificial lighting when working during the day. The hope is that by using curtained windows, students can regulate natural lighting needs to reduce the use of artificial lighting. Until this research was conducted, it was not known how high curtains met visual comfort standards. This research aims to create contour simulation of room’s natural light intensity C.608-609 using dialux kw06-288 software, in relation to adjust of curtains on windows with heights of 30 cm, 60 cm, 90 cm and 120 cm, and their impact on the user's feelings of visual comfort or discomfort. The results show that the distribution of natural light entering the room is not even and varied. According to SNI 03-6575-2001, the light intensity for a studio is 500-750 lux, but the measurement results show that at a curtain opening height of 120 cm, the light reach to the room with the furthest depth of 16.8m is not reached, so to achieve visual comfort the assistance of artificial lighting is needed, especially in the east-south of studio. Meanwhile, the area around the light source causes glare. Keywords: Light Intensity, Visual Comfort, Curtain Opening Height

ANALISIS KOMPARATIF UX DESIGN PADA PLATFORM EDUKASI ONLINE

User experience is the result of what the user feels and thinks when using a product or service, and makes the user experience subjective, therefore the user experience (user experience) can be tested in conjunction with other tests to get an objective assessment of the user when can be done directly with the product. This study will discuss the user experience using the User Experience Questionnaire and Focus Group Discussion methods. The process to be carried out is by using the Brainly and Quora applications obtained from the UEQ and FGD test questionnaires through interviews and data interviews from questionnaires. Based on the results of this study, the results of the analysis and comparisons with UEQ and FGD were obtained. The first test objectively used direct testing to respondents using the UEQ questionnaire which has 6 scales, namely: attractiveness, efficiency, perspective, dependability, stimulation and novelty, which are given to 11 respondents. Second, subjective testing using Focus Group Discussion for perceptions and more detailed user problems with interviews. From the second test conducted, it can be denied that the Brainly application is superior to Quora.