Reviewerly/exHarmony huggingface dataset:
Android Application for Online Fertilizer Selling and Accounting

Authors:
raw_author_name: None Ansari S
raw_affiliation_string: SND College of Engineering and Research center, Yeola, India

Abstract: The "Android Application for Online Fertilizer Selling and Accounting" aims to streamline the process of buying and selling fertilizers through a user-friendly mobile application. This comprehensive platform facilitates a secure and convenient marketplace for users, integrating essential features for both buyers and sellers. The application encompasses user authentication, a detailed product catalog, efficient shopping cart functionality, secure checkout and payment options, order tracking, and dedicated interfaces for sellers to manage their products and orders. For buyers, the application provides an intuitive interface to explore a diverse catalog of fertilizers, categorized for easy navigation. Users can securely authenticate, add products to their cart, and complete transactions using various payment methods. The order tracking feature ensures transparency and keeps users informed about the status of their purchases. The application also maintains an order history for reference. Sellers benefit from a dedicated management interface, allowing them to efficiently update and manage their fertilizer inventory. The platform ensures accurate accounting through the integration of invoicing features, generating detailed invoices for each transaction. This streamlines the selling process and helps sellers keep track of their sales and revenue. By combining the convenience of online shopping with robust accounting functionalities, the Android application for online fertilizer selling and accounting seeks to enhance the overall experience for users in the agricultural sector. The goal is to foster a reliable and efficient marketplace that meets the needs of both buyers and sellers in the fertilizer industry.
Wearable IoT System for Hand Function Assessment Based on EMG Signals

Authors:
raw_author_name: Qun Wu
raw_affiliation_string: School of Art·Design, Zhejiang Sci-Tech University, Hangzhou 310018, China; Zhejiang Fashion Design and Manufacturing Collaborative Innovation Center, Hangzhou 310018, China

Abstract: Evaluating hand function presents a significant challenge in the realm of remote rehabilitation, particularly when highlighting the need for comfort and practicality in wearable devices. This research introduces an innovative wearable device-based Internet of Things (IoT) system, specifically designed for the assessment of hand function, with a focus on a wearable wristband. The system, enhanced by cloud technology, offers comprehensive solutions for remote health management and therapeutic services. Firstly, it uses electromyography (EMG) signals from the arm to assess hand function. By employing sophisticated classification and regression models, this system can automatically identify user gestures and accurately measure grip strength. Additionally, the integration of additional sensor data ensures that the system fulfills essential criteria for hand function assessment. Leaving conventional grip strength classification methods, this study explored four distinct regression models to accurately represent the grip strength curve. The findings reveal that the Random Forest Regression (RFR) model is the most effective, achieving an R2 score of 0.9563 on the test data. This significant outcome not only confirms the practicality of the wearable wristband, which relies on EMG signals, but also underscores the potential of the IoT system in assessing hand function.
Reimagining STEM Education in South Africa: Leveraging Indigenous Knowledge Systems Through the M-Know Model for Curriculum Enhancement

Authors:
raw_author_name: Dagogo Legg-Jack
raw_affiliation_string: Directorate of Learning and Teaching Development, Walter Sisulu University, Nelson Mandela Drive, Mthatha, Eastern Cape, South Africa

Abstract: This conceptual paper investigates the integration of indigenous knowledge systems (IKS) into South African Science, Technology, Engineering, and Mathematics (STEM) education, exploring its conceptions, historical roots, significance, and the challenges and benefits associated with such integration. The objective was to understand the role of IKS in enriching STEM education and its potential contributions to global scientific knowledge. A culturally sensitive research approach was employed, with criteria set for selecting relevant literature on IKS and STEM. The results highlighted the profound historical significance of IKS in South Africa and its potential in bridging cultural gaps in education. Pedagogical innovations rooted in indigenous practices were identified as key to revitalising the STEM learning experience. However, challenges such as educational barriers, policy constraints, and institutional norms were also noted. Thus, the Multiple-ways of knowing (M-Know) model is proposed to demonstrate the possibility of using an integrated approach for the inclusion of IKS and enhancement of the STEM higher education school curriculum in South Africa. The model negotiates for a synergic or integrated arrangement between formal STEM curriculum and IKS in terms of using IKS to interrogate, complement, and consolidate the contents and pedagogy of Westernised STEM education in higher education.
Evaluating The Effectiveness of Information and Communication Technologies (Icts) in Fire Response in Disaster Management in Batam, Indonesia

Authors:
raw_author_name: Sakir Sakir
raw_affiliation_string: Department of International Program of Government Affairs and Administration, Universitas Muhammadiyah

Abstract: This research aims to evaluate the utilization of Information and Communication Technologies (ICTs) in the context of fire response for disaster management in Batam, Indonesia, spanning the years 2018 to 2023. Employing a mixed-methods approach involving surveys and case studies, the study investigates strategies and provides recommendations for health adaptation actions during climate-related disasters. The research assesses the effectiveness of ICTs in disaster risk management, with a specific focus on evaluating the role of the Disaster Management Act in Indonesia. The findings reveal that ICT-based early warning systems, enhanced communication networks, and efficient data management significantly contribute to improving Batam's preparedness and response to disasters. Despite these positive outcomes, the study identifies challenges, including issues related to equitable technology access, infrastructure limitations in remote areas, and privacy concerns that warrant attention. This study presents valuable quantitative insights into the effectiveness of ICTs in disaster management in Batam, Indonesia. It emphasizes the importance of addressing the identified challenges for a more robust disaster mitigation framework. The results have significant implications for policymakers and practitioners, underscoring the need for targeted interventions to overcome barriers and ensure the effective integration of ICTs in disaster response and management practices in Indonesia.
Arsenic geochemical species modeling, prediction, and bioavailability in groundwaters of the Oban Massif, southeastern Nigeria

Authors:
raw_author_name: Azubuike S. Ekwere
raw_affiliation_string: Department of Geology, University of Calabar, Calabar, Nigeria

Abstract: To ascertain the distribution patterns, source identification, chemical speciation, and bioavailability of arsenic in basement aquifers, 64 groundwater samples were analyzed using hydrochemical and geochemical modeling. It was determined that important ion geochemistry, hydrogeochemical facies, and basic hydrogeochemical parameters are interdependent. Arsenic (As) concentrations varied from 0.001 mg/l to 0.03 mg/l, with a mean of 0.007 mg/l. The results of 4.68% of samples were higher than the allowable level of 0.01 mg/l, i.e., groundwater arsenic levels are not dangerous. Significant ion concentrations decreased from dry to rainy seasons suggesting that ionic concentrations generated by silicate weathering in aquifers became diluted. Abundance trends in metal concentration during the dry and rainy seasons were Fe &gt; Mn &gt; Zn &gt; Ni &gt; Cu &gt; As &gt; Pb &gt; Cd and Fe &gt; Zn &gt; Mn &gt; Ni &gt; Pb &gt; Cu &gt; As &gt; Cd, respectively. Of the two hydrochemical facies discovered, the predominant one was the main alkaline-earth-bicarbonate facies [Ca-(Mg)-HCO3] typical of basement terrains, suggesting the fundamental stage of groundwater evolution. Plots of ionic ratios, metal loads, and principal component analyses showed that ionic concentrations are controlled by geology. Geochemical modeling revealed the presence of aqueous arsenic species, which are the less dangerous arsenates at unsaturated levels and do not currently pose a concern.
Design of an Efficient &amp; Secure Steganographic Model using Modified LSB &amp; Encryption Process

Authors:
raw_author_name: Ajit Singh
raw_affiliation_string: Department of Computer Science and Engineering, Bhagat Phool Singh Mahila Vidyalaya, India

Abstract: This paper introduces a novel steganographic model for robust multimodal data security, seamlessly integrating a modified Least Significant Bit (LSB) technique with encryption, making it applicable to diverse data types such as images, audio, video, and text. Overcoming challenges posed by existing complex models and communication delays, our approach employs a modified LSB technique to encode similar sized data samples, followed by dynamic bioinspired elliptic curve cryptography (BECC) utilizing a Mayfly Optimization (MO) Model. This adaptive strategy optimizes curve types and prime key sets, significantly enhancing data security while minimizing delays and complexities across diverse data sizes. The proposed model achieves an 8.3% reduction in encryption and steganographic process delays, while simultaneously maintaining superior Peak Signal to Noise Ratio (PSNR) and lower Mean Squared Error (MSE) levels compared to existing methods when applied to the same data samples. This highlights its effectiveness in securing dynamic datasets without compromising efficiency.
Analysis and Comparison of 3D Printed Soft Pneumatic Actuator Configurations for Swaying Lateral Motion of Planar Objects

Authors:
raw_author_name: None Herianto
raw_affiliation_string: Universitas Gadjah Mada

Abstract: Soft pneumatic actuators (SPAs) offer unique possibilities in robotics and automation due to their compliance and versatility. Unlike conventional actuators that can move either revolute or prismatic, SPAs can produce complex motions, especially when configured in combinations. This paper systematically investigated the performance of four distinct SPA configurations (Types 1-4) concerning the task of moving a planar square object and swaying it laterally to the right and left. These configurations are analyzed for their ability to achieve desired movements and orientations. Type 4, involving two SPAs, emerges as the most effective configuration, successfully navigating the challenges posed by the desired task. In contrast, Type 2, consisting of four SPAs, encounters difficulties in executing the task attributed to increased inertia, which was similar as type 3. Types 1, while not precisely meeting the primary task, reveal distinctive movements - left-right motion without orientation change. This study contributes valuable insights into the complex dynamics of SPAs, offering considerations for optimal design and performance. The outcomes could be developed in the future in soft actuator applications, especially those involving configurations based on specific needs.
Analisis kemampuan literasi numerasi mahasiswa pada implementasi program kampus mengajar

Authors:
raw_author_name: Muhammad Ridlo Yuwono
raw_affiliation_string: Universitas Widya Dharma
raw_author_name: Ana Setyandari
raw_affiliation_string: Universitas Widya Dharma

Abstract: The aim of this research is obtain a profile of the numeracy literacy abilities of students who have participated in the Teaching Campus program through analysis of the problem solving. This type of research is a case study. The subjects of this research were alumni of the Class 3 Teaching Campus at Widya Dharma University. Research data collection uses test methods and interview methods. The research instruments are the main instrument (researcher) and auxiliary instrument (numeracy literacy test). This research uses triangulation techniques to obtain valid data. The results of this research are (1) in text type questions students mention important information, do not formulate the problem, do not write down strategies, solve the problem correctly, check again without alternative solutions; (2) on text and image type questions, students mention important information and formulate problems, convey strategies, implement strategies with wrong image patterns, recheck answers; and (3) on text and table type questions, students mention important information and formulate the problem briefly, do not convey strategies, solve problems by paying attention to tables, and are less careful in analyzing text and table.
Term Standardisation With LDA Model To Detect Service Disruption Events Using English And Manglish Tweets

Authors:
raw_author_name: Maizatul Akmar Ismail
raw_affiliation_string: Universiti Malaya, Malaysia
raw_author_name: Tasnim M.A. Zayet
raw_affiliation_string: Universiti Malaya, Malaysia
raw_author_name: Kasturi Dewi Varathan
raw_affiliation_string: Universiti Malaya, Malaysia
raw_author_name: Rafidah MD Noor
raw_affiliation_string: Universiti Malaya, Malaysia

Abstract: Rapid transit is one of Malaysia's most important transportation modes, where commuters use public transportation to travel. Any disruption in the rapid transit service affects their daily routines. Therefore, detecting such service disruption has become fundamental. In this study, the disruption in Malaysia's rapid transit service was assessed using English and Manglish (a combination of English and Malay) tweets through Latent Dirichlet Allocation (LDA). The gathered tweets were classified into event and non-event tweets and LDA was applied to the event tweets. Manglish event tweets were pre-processed using the proposed term standardisation technique. As a result, LDA has proved its efficiency in topic detection for both English and Manglish tweets with better performance for Manglish tweets; The best event detection rate of the LDA_English model was at the likelihood of 80% while the best detection rate of the LDA_Manglish model was at a likelihood of 60%.
Enhancing Fixation and Pursuit: Optimizing Field of View and Number of Targets for Selection Performance in Virtual Reality

Authors:
raw_author_name: Xiaojiao Chen
raw_affiliation_string: College of Computer Science and Technology, Zhejiang University, Hangzhou, PR China; Laboratory of Art and Archaeology Image, Zhejiang University, Hangzhou, PR China
raw_author_name: Yonghao Chen
raw_affiliation_string: College of Computer Science and Technology, Zhejiang University, Hangzhou, PR China; Laboratory of Art and Archaeology Image, Zhejiang University, Hangzhou, PR China
raw_author_name: Tengyu Huang
raw_affiliation_string: Laboratory of Art and Archaeology Image, Zhejiang University, Hangzhou, PR China
raw_author_name: Qinghua Liu
raw_affiliation_string: College of Computer Science and Technology, Zhejiang University, Hangzhou, PR China; Laboratory of Art and Archaeology Image, Zhejiang University, Hangzhou, PR China
raw_author_name: Jinpeng Yang
raw_affiliation_string: Laboratory of Art and Archaeology Image, Zhejiang University, Hangzhou, PR China
raw_author_name: Wenru Qi
raw_affiliation_string: Laboratory of Art and Archaeology Image, Zhejiang University, Hangzhou, PR China

Abstract: Gaze interaction in virtual reality (VR) offers promising advantages in speed and hands-free operation. However, selecting a suitable selection mechanism in VR interfaces with different visual encodings remains a challenge. This research compares two visual input techniques and explores specific visual elements, including field of view (FOV), design style, and number of targets, with the goal of alleviating these problems. The pilot study identifies two search stages, and it also demonstrates a significant effect of FOV on search time. In the formal experiment, a gaze-based trigger experiment is employed to examine the selection performance of fixation and smooth pursuit. The results reveal that optimizing FOV and number of targets improves the triggering efficiency. Furthermore, fixation outperforms pursuit in terms of triggering time and accuracy under the same conditions, while cognitive load during triggering process remains relatively similar. These findings are expected to propose design recommendations to enhance fixation and pursuit within VR interfaces.
Energy and Performance Centric Resource Allocation Framework in Virtual Machine Consolidation Using Reinforcement Learning Approach

Authors:
raw_author_name: Madala Guru Brahmam
raw_affiliation_string: School of Computer Science Engineering &amp; Information Systems, Vellore Institute of Technology, Vellore, India
raw_author_name: Vijay Anand R
raw_affiliation_string: School of Computer Science Engineering &amp; Information Systems, Vellore Institute of Technology, Vellore, India

Abstract: Abstract:: Virtual machines are used to reduce cloud platform application performance, management costs, and access irregularities. Virtual machines are frequently vulnerable to delays, overburdening workloads, and other obstacles while consolidating and migrating servers. To significantly disperse loads among virtual machines, dynamic consolidation techniques are implemented to control energy dissipation, monitor overloading, and address underloading problems. Background:: The process of consolidation involves more calculations and resources in order to transfer services between virtual machines, provided that Service Level Agreements are observed. Methods:: The suggested approach promotes the use of cutting-edge architecture to combine virtual machines, and, therefore, strike a balance between performance and energy requirements. The main design considerations for the suggested Dynamic Weightage algorithm, which includes the clustering approach in relation to reinforcement learning approaches, are overall resource needs and Performance to Power Ratio (PPR). A cluster of ideal virtual machines is created, and resources are distributed according to performance and energy requirements. Virtual machine resource requests are converted into a matching relationship factor, which represents the individual hosts while taking PPR into account. The overall workload associated with virtual machine consolidation is also provided by these estimations. It is noted that there is little energy trade-off and that performance is maintained at a nominal level across the cluster. The architecture is put into practice throughout offline platforms, which are dispersed ecosystems that allow for increased system performance and scaling. Results:: The CloudSim simulator is used to validate the system using datasets that are obtained from PlanetLab. According to the data, energy saving has produced yields of up to 47% and promising quality of service attributes. Conclusion:: The validation of the system is performed using the CloudSim simulator with datasets from PlanetLab. The results indicate significant energy conservation, up to 47%, along with promising quality of service parameters. The proposed architecture is compared with other state-of-the-art algorithms for distributed architectures and heterogeneous environments, showcasing its efficiency. The conclusion emphasizes the prioritization of VM consolidation and energy efficiency in the proposed architecture, which has been tested on a Proliant G7- based data center using a variety of hosts. Notably, the CloudSim Toolkit is highlighted as outperforming OpenStack-based techniques in simulation results.
Interpretable Software Defect Prediction from Project Effort and Static Code Metrics

Authors:
raw_author_name: Luiz Fernando Capretz
raw_affiliation_string: Department of Electrical and Computer Engineering, Western University, London, ON N6A 3K7, Canada

Abstract: Software defect prediction models enable test managers to predict defect-prone modules and assist with delivering quality products. A test manager would be willing to identify the attributes that can influence defect prediction and should be able to trust the model outcomes. The objective of this research is to create software defect prediction models with a focus on interpretability. Additionally, it aims to investigate the impact of size, complexity, and other source code metrics on the prediction of software defects. This research also assesses the reliability of cross-project defect prediction. Well-known machine learning techniques, such as support vector machines, k-nearest neighbors, random forest classifiers, and artificial neural networks, were applied to publicly available PROMISE datasets. The interpretability of this approach was demonstrated by SHapley Additive exPlanations (SHAP) and local interpretable model-agnostic explanations (LIME) techniques. The developed interpretable software defect prediction models showed reliability on independent and cross-project data. Finally, the results demonstrate that static code metrics can contribute to the defect prediction models, and the inclusion of explainability assists in establishing trust in the developed models.
The Role and Responsibilities of Academic Leaders in Effectuating Quality, Impact, and Excellence by Innovation in Higher Education

Authors:
raw_author_name: Yang Li
raw_affiliation_string: Nanjing Normal University, Jiangsu-Nanjing 210023

Abstract: &lt;p&gt;Innovation is critical for higher education in the 21st century. It can improve teaching and learning, increase research quality and impact, solve social problems, and bring more funding and collaboration. It can also boost the happiness and creativity of staff and students, who can follow their interests, try new things, and work with different people. But innovation is not simple. It requires a positive and supportive culture, a clear and shared vision, a strong and effective leadership, and a regular and systematic evaluation. This seeks to review the existing research on innovation in higher education, analyze and discuss how academic leaders can encourage and enable innovation in higher education, and to further provide some helpful and evidence-based suggestions for academic leaders and practitioners who want to innovate in higher education.&lt;/p&gt;