Reviewerly/exHarmony huggingface dataset:
Advancements and Future Directions in Human Activity Recognition

Abstract: Activity recognition deals with the automation of recognizing various activities by identifying the subject and its interactions with the environment. Human activity recognition deals with identifying different activities like sitting, walking, laying moving, running, jogging, various hand movements, posture and behavior prediction and recognition. Activity recognition deals with the automation of recognizing various activities by identifying the subject and its interactions with the environment. The wide variety of environments are incorporated with Human Activity Recognition. It assists with the vast variety of problems related to people, living, lifestyle, security, monitoring, which may or may not be related to computer science.
Semantic-Aware Superpixel for Weakly Supervised Semantic Segmentation

Weakly-supervised semantic segmentation aims to train a semantic segmentation network using weak labels. Among weak labels, image-level label has been the most popular choice due to its simplicity. However, since image-level labels lack accurate object region information, additional modules such as saliency detector have been exploited in weakly supervised semantic segmentation, which requires pixel-level label for training. In this paper, we explore a self-supervised vision transformer to mitigate the heavy efforts on generation of pixel-level annotations. By exploiting the features obtained from self-supervised vision transformer, our superpixel discovery method finds out the semantic-aware superpixels based on the feature similarity in an unsupervised manner. Once we obtain the superpixels, we train the semantic segmentation network using superpixel-guided seeded region growing method. Despite its simplicity, our approach achieves the competitive result with the state-of-the-arts on PASCAL VOC 2012 and MS-COCO 2014 semantic segmentation datasets for weakly supervised semantic segmentation. Our code is available at https://github.com/st17kim/semantic-aware-superpixel.
Causal Intervention for Human Trajectory Prediction with Cross Attention Mechanism

Human trajectory Prediction (HTP) in complex social environments plays a crucial and fundamental role in artificial intelligence systems. Conventional methods make use of both history behaviors and social interactions to forecast future trajectories. However, we demonstrate that the social environment is a confounder that misleads the model to learn spurious correlations between history and future trajectories. To end this, we first formulate the social environment, history and future trajectory variables into a structural causal model to analyze the causalities among them. Based on causal intervention rather than conventional likelihood, we propose a Social Environment ADjustment (SEAD) method, to remove the confounding effect of the social environment. The core of our method is implemented by a Social Cross Attention (SCA) module, which is universal, simple and effective. Our method has consistent improvements on ETH-UCY datasets with three baseline models and achieves competitive performances with existing methods.
Uncertainty-Aware Image Captioning

It is well believed that the higher uncertainty in a word of the caption, the more inter-correlated context information is required to determine it. However, current image captioning methods usually consider the generation of all words in a sentence sequentially and equally. In this paper, we propose an uncertainty-aware image captioning framework, which parallelly and iteratively operates insertion of discontinuous candidate words between existing words from easy to difficult until converged. We hypothesize that high-uncertainty words in a sentence need more prior information to make a correct decision and should be produced at a later stage. The resulting non-autoregressive hierarchy makes the caption generation explainable and intuitive. Specifically, we utilize an image-conditioned bag-of-word model to measure the word uncertainty and apply a dynamic programming algorithm to construct the training pairs. During inference, we devise an uncertainty-adaptive parallel beam search technique that yields an empirically logarithmic time complexity. Extensive experiments on the MS COCO benchmark reveal that our approach outperforms the strong baseline and related methods on both captioning quality as well as decoding speed.
Age and Gender Identification Using Neural Networks

Face recognition is still very challenging and complex problem. This problem can be credited as large intra-personal variations and large inter personal similarity. Facial recognition is the application of biometric breakthroughs that can observe or verify a person by observing and examining designs based on the individual's shape. Despite the increased interest in other applications, face recognition is still mostly utilized for well-being. Generally, advancements in face recognition are worthwhile since they may have a wide range of legal applications and commercial uses.
Billiards Optimization with Modified Deep Learning for Fault Detection in Wireless Sensor Network

Wireless Sensor Networks (WSNs) gather data in physical environments, which is some type.These ubiquitous sensors face several challenges responsible for corrupting them (mostly sensor failure and intrusions in external agents).WSNs were disposed to error, and effectual fault detection techniques are utilized for detecting faults from WSNs in a timely approach.Machine learning (ML) was extremely utilized for detecting faults in WSNs.Therefore, this study proposes a billiards optimization algorithm with modified deep learning for fault detection (BIOMDL-FD) in WSN.The BIOMDL-FD technique mainly concentrates on identifying sensor faults to enhance network efficiency.To do so, the presented BIOMDL-FD technique uses the attention-based bidirectional long short-term memory (ABLSTM) method for fault detection.In the ABLSTM model, the attention mechanism enables us to learn the relationships between the inputs and modify the probability to give more attention to essential features.At the same time, the BIO algorithm is employed for optimal hyperparameter tuning of the ABLSTM model, which is stimulated by billiard games, showing the novelty of the work.Experimental analyses are made to affirm the enhanced fault detection outcomes of the BIOMDL-FD technique.Detailed simulation results demonstrate the improvement of the BIOMDL-FD technique over other models with a maximum classification accuracy of 99.37%.
DEVELOPMENT OF PROTOTYPE AUTOMATED EGG INCUBATOR WITH INTERNET-OF-THINGS (IoT) APPLICATION

Incubation is a technology that provides an opportunity for farmers to produce chicks from eggs without the need for the mother hen.It is one of the fastest ways of transforming eggs into chicks.To meet the high demand that the poultry industry is facing, the need to maximize poultry production should be addressed.Hence, this research study aimed to develop and test a digital egg incubator that can autonomously incubate eggs while allowing a user to remotely monitor the egg incubation and hatching process in a mobile app using Internet-of-Things (IoT) technology.The innovation of a prototype autonomous egg incubator with-internet of things application was developed overarching the objectives to determine the production yield of the prototype automated egg incubator, determine the efficiency of the prototype automated egg incubator in terms of the number of eggs hatched, humidity, temperature, and egg turning, evaluate the prototype automated egg incubator embedded system using the ISO-IEC 25010 system product quality evaluation, and determine its acceptability o in terms of its usability, functionality, and performance.Henceforth, the field testing and experimentation data of this study showed that the device garnered 100% efficiency score in terms of maintaining temperature, humidity, and CO2 (ventilation), as well as managing the egg-turning mechanism.In addition, the IoT Egg Incubator and Hatching device's average output of 94% efficiency in egg hatching with a production yield of 0.94 further supports the claim.Furthermore, the conducted ISO-IEC 25010 System Product Quality Evaluation for the proposed device indicated that the evaluating panel of IT experts found the embedded system to be excellent in terms of functional suitability, performance efficiency, usability, and reliability.Moreover, the Acceptability Evaluation in terms of its usability, functionality, and performance was very acceptable and indeed useful and functional, and it can incubate and hatch poultry eggs adequately.
Information Technology and Entrepreneurship Success in Bayelsa State, Nigeria: Small and Medium Enterprises (SMEs) Perspective

The paper examined relationship between information technology and entrepreneurship success in Bayelsa State. Specifically, the study is to examine the relationship between information technology and SMEs success in Bayelsa State, and the challenges of adopting information technology for entrepreneurship success in Bayelsa State. This paper adopted the quantitative research approach and adopting cross-sectional survey design which involve multiple SMEs in Bayelsa State. Population for this study consist of fifty (50) entrepreneurs in Bayelsa state. A self-designed questionnaire was modified and adopted as the instrument of primary data collection, which was previously used by Olusegun (2015), with an overall reliability coefficient of 0.64 for all question items in the Likert-5 response scale instrument. Data collected was analyzed adopting descriptive analysis for the socio-economic data and Pearson Moment Correlational Coefficient as the inferential analysis. The result shows that there is an empirical link between information technology and SMEs success in Bayelsa State, and there are visible challenges in adopting information technology for entrepreneurship success in Bayelsa State. In Conclusion, the use of information technology to small business operations has had a significant positive influence on entrepreneurial practices from the viewpoints of SMEs in Bayelsa State, Nigeria. The paper recommended that the government need to provide entrepreneurs sufficient funding so that they may employ modern technologies in their small businesses, which will help them expand.
PENYULUHAN BENTUK KESALAHAN BERBAHASA SKRIPSI BAGI MAHASISWA PRODI PENDIDIKAN BAHASA DAN SASTRA INDONESIA

Based on the results of language error analysis research, students' ability to apply linguistic rules when writing academics is still lacking. There are patterns and types of errors that are common and always occur when students write their thesis. Therefore, in order to produce quality scientific writing in terms of substance as well as grammar, it is necessary to conduct counseling on the forms of language errors in theses. Thus, the thesis language errors can be minimized. Counseling is carried out in the form of lectures, case studies, focus group discussions, and demonstrations. In particular, the extension method adopts the stages of text learning with slight modifications. The stages in question, namely building context, providing models, finding errors, and evaluating errors. This counseling activity contributed to the improvement of participants' ability to do self-editing of their own writing for the better. In addition, the participants better understood the relationship between linguistic theory and language errors, making it easier for them to analyze and identify language errors. In the end, this counseling activity contributed directly to improving the quality of student scientific writing, especially in terms of writing. This increase in quality is also in line with the increase in the quality of graduates and the learning outcomes of graduates.
Unlocking the Secret of Language Learning Strategies: Improving Year 4 ESL Pupils’ Writing Skills

English is widely acknowledged as Malaysia's second language and learners' proficiency in the language is strongly influenced by their learning preferences, needs, and styles, as well as their cultural backgrounds and experiences.This study aims to investigate the general usage as well as most preferred and least preferred language learning strategies (LLS) in improving language skills particularly writing skills among Year 4 ESL pupils in a Malaysian primary school.This qualitative research targeted the population of primary school ESL learners and used a survey design research approach.The sample in this study was Year 4 ESL pupils in an urban school in Selangor, Malaysia, selected using purposive sampling technique.A questionnaire from Strategy Inventory for Language Learning (SILL) was adapted as the data collection instrument.Descriptive statistics was used to analyse the data obtained and the findings showed the common, the most preferred as well as the least preferred LLS used by Year 4 ESL pupils in a Malaysian primary school to improve their writing skills.The importance of using a plethora of LLS in teaching writing skills to ESL learners was also highlighted in this study.The implications of the study suggest the awareness among teachers of the LLS used by their students in improving their writing skills to better tailor their teaching to suit their students' needs.Overall, this study is expected to be significant in providing insights into the effective LLS while guiding Malaysian ESL teachers in enhancing learners' writing skills.
FACIAL MORPHOMETRIC STUDY OF ADULT HAUSA MALE TAXI AND TRICYCLE DRIVERS IN KANO, NIGERIA

Human faces contain several cues, for example, identity, emotional expression, age, gender, ethnicity, attractiveness, personality traits, and many more. The aim of this study was to determine the facial parameters in the population of Hausa Male taxi and tricycle drivers in Kano, Nigeria and to compare them with those determined in earlier studies in different populations. Four hundred (402) subjects were selected from the two association in Kano state, Tsaya da Kafarka Taxi Drivers Association and Tricycle Operators Association Kano (TOAKAN), using random sampling methods, with the age range of the participants between 18-50 years and Those with facial deformities or craniofacial trauma, surgery, and congenital facial abnormalities were excluded from the study. Photographic methods were used to capture the face. The data were expressed as mean ± SD, frequency, and percentages. It was observed that facial height (tr_gn) was higher in the facial vertical dimensions than the rest with the mean value of 190.59 ±17.60mm, while the lower face width (go1_go2) was higher in the horizontal facial dimensions than the rest, with the mean value of 115.92±11.86mm. The right eye length (ex1_en1) was slightly lower (30.07±3.80mm) than the left (30.27±3.81mm). In conclusion, the present study has established the baseline data of facial dimensions of Hausa Male taxi and tricycle drivers in Kano, Nigeria.
Strategic Planning Practices and Performance of Micro-Finance Industry in Rwanda: A Case of Study of Jali Finance Ltd

This study explored effect of strategic planning practices on performance of micro-finance industry in Rwanda. The study used a descriptive study design with a correction regression size effect with both qualitative and quantitative approaches. The study targeted 300 employees of Jali Finance Ltd and the sample size was 171 employees to be sampled utilizing purposive and simple random sampling techniques from various departments if the organization under this study with the right information. Information from primary source was gathered using questionnaire and interviews. Data collected was coded, analyzed, and presented utilizing graphs, tables, frequencies which was done using SPSS version 25.0. Correlation and regression analysis of the study variable was done. The results showed that entire strategic planning process was statistically affecting achievement of goals/ objectives (B=0.569, p-value=.000). The findings indicated regression coefficients for employee satisfaction rate. It felt that feedback during strategic planning was statistically significant to employee satisfaction rate (B=.450, p-value=0.000). Results shown that entire strategic planning process, and following the right procedures is statistically affecting employee satisfaction rate (B=0.280, p-value=.001). The second research objective demonstrated that Jali Finance Ltd provides resources with a strong agreement with 54.4%, however, only 40.8% strongly accepted management deploys resources on time to support the strategic formulation and execution. Deploying resources on time was significantly correlated with achievement of goals/ objectives (b=0.395, p-value=0.006). Thus, knowledge on risks was significantly affecting achievement of goals/ objectives increase (b=0.866, p-value=0.000). The study suggests Jali Finance Ltd prioritize improving the skills and dedication of its staff, recognizing their value as the company's most asset. Effective leadership and enhanced communication channels are recommended to foster information flow and feedback among all employees. Keywords: Strategic Planning Practices, Performance of Micro-Finance Industry, Jali Finance Ltd, Rwanda
Design an aerobics teaching resource management platform based on computer system

This study takes the design and application of aerobics teaching platform under the background of "Internet +" as the research object, uses the method of literature, interview, observation and logical analysis to design the teaching platform of aerobics, and explains how to apply the platform in detail.Based on the analysis of the importance of the design and application of the aerobics teaching platform, the advantages and necessity of using the platform for learning are expounded, so as to design the teaching platform for aerobics.Through the design and application of calisthenics teaching platform, we can enrich the learning content of calisthenics, expand the learning scope of students, change the learning form of students, improve the drawbacks of traditional calisthenics teaching and optimize the implementation process of calisthenics teaching.It makes calisthenics teaching more systematic, improves students' autonomous learning ability, cultivates students' innovation ability and improves students' learning effect, and provides certain theoretical and practical basis for the future innovation and development of calisthenics teaching, and provides reference for the future integration and innovation of "Internet +" and physical education curriculum.
How the Use of Software Visual Feature Affects Students' Ability to Stay Connected in Online Design Education

COVID-19 threatens higher education's sustainability.Online courses lack connectivity and engagement, two key elements of design education.Design online education has less research than STEM fields.This study used emoticons to improve design students' connectivity and engagement in online environment.91 Chinese design students were analyzed in a quasi-experiment.They tested emoticons in three different teaching situations.The data analysis found a positive correlation between online emoticon use and design students' connectivity and engagement.Students who used many personified emoticons felt more connected and engaged.increased connectivity and engagement.We suggested the development of online teaching software as well as online design instruction in order to strengthen the long-term viability of design education.
Descriptive statistical analysis, mean analysis and model construction of the current situation of innovation and entrepreneurship education in applied undergraduate colleges

Through the investigation of some applied undergraduate colleges in Shandong Province, the basic statistical analysis and mean value analysis of the survey data are carried out.On this basis, the innovation and entrepreneurship education model is constructed from six aspects: individual variables of students, school organization management system, the impact of teachers, government influence, degree of enterprise involvement, talent training program and curriculum system construction.
Emotional Design Elements of Virtual Exhibition -Focusing on Revolutionary Theme

The emotional design of virtual museum is an important factor to improve the quality of visitors.By deconstructing and recreating the theme of "Revolution Education", the designer aims to improve the emotional sensitivity and cognitive experience of visitors.The virtual red museum is a space for emotional research.It plays a variety of roles that enrich human emotions.As a comfortable space, it spreads a wide range of revolution culture for visitors.Based on Donald Norman's emotional design, this study analyzed the elements of emotional design, including The Memorial Hall of The Victims in Nanjing Massacre by Japanese Invades and The Exhibition of Evidences of Crime Committed by Unit 731 of The Japanese Imperial Army.Its unique characteristics of performance layer, behavior layer and reflection layer are stable factors that make visitors of these two public facilities have emotional resonance.In order to improve the emotional satisfaction of visitors in the "Revolution Education" theme exhibition hall, it is necessary to stimulate their interest and try various new expressions.
A study on the subject Teaching knowledge Level of middle school Mathematics Teachers integrating technology

Teachers with good content knowledge, effective teaching strategies and integrated technology play a crucial role in the learning effect of students.Based on the modified Questionnaire of Pre-service Teachers' Teaching and Technical Knowledge, the data results were processed by Matlab and Excel software to analyze the subject teaching knowledge level of 53 in-service mathematics teachers with integrated technology.It is found that in-service mathematics teachers have good subject and teaching knowledge, but weak technical knowledge, good subject teaching knowledge and teaching knowledge of integrated technology, and need to improve the subject knowledge of integrated technology, teachers have a good level of subject teaching knowledge of integrated technology, but there is room for improvement.
Research on English Vocabulary Learning Platform Based on Personalized Recommendation

In the mobile learning environment, it is necessary to consider how to mine learners' personalized vocabulary needs and recommend appropriate vocabulary resources according to the characteristics of resources and learners.This is of practical significance for improving learners' vocabulary learning efficiency.Based on the classification time perception method and vector space model representation, this paper constructs the learner dynamic interest model.This model can represent learners' personalized features more accurately and improve the accuracy of word recommendation.Combined with the collaborative filtering recommendation based on learners' dynamic interests, it can recommend vocabulary resources for learners.Finally, through the questionnaire survey, the effectiveness of the system is tested from the aspect of the learning effect of the system.The data show that the system can improve the user's learning effect to a certain extent.
Construction of Piano Accompaniment Teaching Platform in Colleges and Universities under Big Data

At present, with the high development of computer music technology, more and more computer music technology into the field of music education, teaching concepts.Computer music technology has exerted a profound influence on the further development of music in the new era, no matter from the means of creation, sound carrier or music aesthetics.Especially in the process of impromptu accompaniment training has played an incomparable role.