Reviewerly/exHarmony huggingface dataset:
Design and Implementation of Hybrid Cloud Device-as-a-Service

Traditional Cloud Device-as-a-Service (DaaS) model for providing Virtual Desktop Infrastructure (VDI) and Virtual Mobile Infrastructure (VMI) services are being provided using each independent systems because of difference of its system features. To provide VDI and VMI service simultaneously, a clouds service providers have to build each server infrastructures that cost twice. In this paper, we propose a cost effective heterogeneous DaaS structure capable of offering VDI and VMI services simultaneously on a single cloud platform. Additionally, it presents a technique to distribute CPU loads, used for rendering and encoding, by leveraging low-cost general-purpose GPUs on cloud servers that will enable a host machine to function more efficiently by operating more guest machines, owing to elimination of CPU loads. In this paper, we introduce in detail our proposed scheme and discuss its originality; moreover, we present performance estimation results.
Comparing Human Object Learning with Deep Neural Networks

One challenge in machine learning is that networks readily forget previously learned information as they encounter new information. For example, a network pre-trained with ImageNet can acquire useful features for classification tasks. However, training it with more images from other sources to further improve its performance or perform new tasks will lead to catastrophic forgetting of the previously learned tasks. This study examined whether this type of catastrophic forgetting is universal for human and machine category learning by testing them under exactly the same conditions. Human participants and a pre-trained convolutional neural network (CNN) learned some images of novel objects called greebles under mixed-batch, by-category, and full-set conditions. In the mixed-batch condition, they learned the training images by batches, with each block being a mixture of greebles from different classes. In the by-category condition, each block had most greebles from the same class. The full-set condition presents all images in one block. Human participants learned classification by judging/guessing class labels and receiving feedback. The CNN model was trained with exactly the same images and conditions with the same number of iterations. After learning, they were both tested on the learned greebles, novel greebles with the same viewpoint, and novel greebles with a different viewpoint. Performances are evaluated by classification accuracy during testing. Our results showed that humans do not have catastrophic forgetting like CNNs. There were no significant effects of the learning scheme or testing item type. In contrast, the CNN showed significant impairments in the by-category condition (catastrophic forgetting) and in novel objects and novel viewpoints. This study indicates that humans, compared with machines, might have different mechanisms in object category learning to avoid catastrophic forgetting, providing potential directions for continual learning in neural networks.
The cost of forming statistical summary representations across multiple spatial scales

The visual system can extract a statistical summary representation (SSR) of a group of similar objects (Ariely 2001). We can form SSRs across multiple feature dimensions for a group of objects (Chong & Treisman, 2005), across multiple feature dimensions across multiple groups of objects (Emmanouil & Treisman, 2008), and across multiple sensory modalities (Albrecht et al., 2013). The current experiments are the first to study the properties of SSRs across multiple spatial scales. The stimuli consist of three large rectangles constructed by spatially arranging multiple small rectangles. All the small rectangles within a large rectangle have the same orientation. Participants estimate the average orientation of either the large rectangles (global level or low spatial frequency) or the small rectangles (local level or high spatial frequency). In Experiment 1, we use a cueing paradigm to demonstrate the cost in forming statistical summary representations across multiple spatial scales. Many models (Parkes et al. 2001; Baek & Chong, 2019) assume that properties of individual items must be computed before creating an SSR of the group. If so, it is important to show that there is an SSR formation cost in Experiment 1 above and beyond the cost of representing the individual items. In Experiment 2, we address this question with stimuli consisting of a single large rectangle constructed from several small rectangles. Participants estimated the orientation of either the large rectangle or the small rectangles. There was a cost involved in the formation of a single item hierarchical representation. Comparing the results from the two experiments revealed that there is an additional cost in the formation of hierarchical SSRs after the hierarchical single item representations are formed.
Restricting the Distribution of Visual Attention Reduces Cybersickness

It has been suggested that the allocation of visual attention could influence cybersickness (i.e. motion sickness in virtual reality), but this has not been experimentally tested. Wei et al. (2018) found a negative correlation between self-reported motion sickness susceptibility and attention to the periphery during vection. Based on this finding, they proposed that reallocating more attention to the peripheral visual field could reduce cybersickness. On the other hand, previous studies have demonstrated that restricting the field-of-view (FOV) decreases cybersickness, suggesting that limiting the attention to peripheral motion cues would reduce cybersickness. We tested these possibilities experimentally by encouraging attention to the central or peripheral visual field during VR exposure. We also measured attention to the visual periphery during vection and self-reported motion sickness susceptibility to replicate Wei et al. (2018). Two preregistered experiments were conducted. In Experiment 1, we used task-relevant cues to manipulate visual attention. Visual cues were provided in either the central or peripheral visual field during virtual navigation. We found no difference in cybersickness across conditions. However, it is possible that the task-relevant cues had only transient effects and did not manipulate sustained attention. In Experiment 2, sustained attention to the visual center or periphery was manipulated with a dot-probe task during passive VR exposure. We found that subjects experienced greater cybersickness in the condition that required sustained attention to the periphery. In both experiments, we did not observe any correlation between baseline attention allocation tendency during vection and self-reported motion sickness susceptibility. Our results demonstrate that maintaining a narrow distribution of visual attention can be an effective intervention for cybersickness. We suggest that visual attention reallocation and FOV restriction reduce cybersickness in the same way, by limiting the processing of peripheral motion signals.
Syntactic structures of Turkish research article titles in medicine and engineering

The title is of vital importance to research articles as it summarizes the content in several words and grabs the attention of readers. When selecting articles pertinent to their research, the prevalence of online publication leads readers to use online search engines like Google Scholar, which generally displays the first few words of a title, making the title highly important. This study aimed to investigate some key features, such as length, style, syntactic structure and punctuation marks of titles in Turkish research articles in medicine and engineering. To this end, we selected 1,200 titles in four leading journals publishing research articles in these disciplines. As a tool to collect data, document analysis was used in the study to analyze such features of titles and in analyzing the data, descriptive analysis technique was used. The study revealed that both medicine and engineering have almost the equivalent title length. Titles in both disciplines are dominated by single-unit ones and both single-unit and compound titles are predominated by nominal group construction. The results also suggested some disciplinary differences: Compound titles were more common in medicine than in engineering. Medical titles appear to have used more varied syntactic structures in forming titles. Moreover, medical titles have shown a high degree of complexity in terms of punctuation usage. The differences might be attributed to disciplinary practices set out in these two fields. The results of the present study will provide novice writers with ample opportunity to construct their titles as best they can while maintaining their effort to build and enhance their academic writing skills.
Establishing Cross-Curricular Connections Through Python Programming in Computer Modeling Education

In the present paper, the possibilities of making cross-curricular connections through Python programming in computer modeling education are explored. For this purpose, sample projects are systematized according to the study subjects – mathematics, history, geography, human and nature. Their designation is to contribute to the consolidation of certain knowledge and skills, both in terms of Python programming and in the relevant other subject. Concrete implemented projects are represented, different variants of them are discussed, and their accessibility is ensured for their future reuse for educational purposes. As a result, they could be directly used to apply a project-based teaching approach in learning relevant topics from the study material.
Towards a Risk-Based Continuous Auditing-Based Certification for Machine Learning

Abstract Machine learning systems have gained widespread adoption across various industries. This includes highly regulated ones that need to match certain quality requirements based on a given risk exposure. The MLOps paradigm, following a similar approach to DevOps, promises major improvements in quality and speed, with a focus on deploying ML models at a fast pace with high quality on an automated basis. However, traditional point-in-time certifications with manual audits are inadequate for MLOps setups due to frequent changes to the ML system. To overcome this challenge, we propose Continuous Audit-Based Certification (CABC), which uses automated audits to issue or revoke certificates based on an automated assessment of artifacts from the MLOps lifecycle. Our approach utilizes artifacts from the MLOps lifecycle for quality measurements based on standards such as ISO 25012. We propose a risk-based measurement selection, an audit API for standardized retrieval of data for measurement, a tamper-proof data collection process, and an architecture for separation of duties in the certification process. CABC aims to improve efficiency, enhance trust in the ML system, and support highly regulated industries in achieving their quality goals.
Application of The Haversine Method In The Android-Based Donation Search Application

Used goods that we no longer use will only fill the room which if we leave it will be damaged and have no use value because it consumes time. If given to someone else, the goods may still be useful and can help their lives the problem is how we find people who need our goods and vice versa. For this reason, a system is needed that can help facilitate and bring the two parties together. The effort made to make it easier for the recipient to contribute in taking the donated goods is to use the haversine method so that the recipient can consider the distance between them and the donated item. The haversine formula is an equation that uses latitude and longitude to find the distance between the two different points. By using the haversine formula, the output is the distance from the location of the party receiving the donation (current location) to the donor. Therefore, the author wants to create and design an android-based application so that it can reach many people and can make it easier for donors to donate their goods or for the recipient of donations in looking for items that have been donated.
Design a Web-based Education Development Contribution Payment Application at SDIT Tahfidz Bintangku

Improving services to facilitate the management and monitoring of billing and payment of SPP (Education Development Contribution) in educational institutions must get serious attention because the quality of educational institutions is greatly influenced by the availability of adequate payment management. The research method used in application development uses the waterfall method. The application developed is web-based using the Laravel 9 framework with a combination of design with boostrap so that it is more responsive and uses the Mysql database. The results of the developed application are able to assist the treasurer and student guardians in managing, provide convenience for students and parents in making payments online, reduce the need to queue at physical payment counters, save time and energy, make it easier for treasurers and parents to track payment history, can verify transactions that have been made and ensure that no payment transactions are left behind, make it easier for schools to manage financial recording processes and payment processing to be more organized and controlled quickly.
Distributed Multi-agent Target Search and Tracking With Gaussian Process and Reinforcement Learning

Deploying multiple robots for target search and tracking has many practical applications, yet the challenge of planning over unknown or partially known targets remains difficult to address. With recent advances in deep learning, intelligent control techniques such as reinforcement learning have enabled agents to learn autonomously from environment interactions with little to no prior knowledge. Such methods can address the exploration-exploitation tradeoff of planning over unknown targets in a data-driven manner, streamlining the decision-making pipeline with end-to-end training. In this paper, we propose a multi-agent reinforcement learning technique (MARL) with target map building based on distributed Gaussian process (GP). We leverage the distributed GP to encode belief over the target locations in a scalable manner and incorporate it into centralized training with decentralized execution MARL framework to efficiently plan over unknown targets. We evaluate the performance and transferability of the trained policy in simulation and demonstrate the method on a swarm of micro unmanned aerial vehicles with hardware experiments.
LITERASI INFORMASI KESEHATAN PADA FENOMENA DIAGNOSIS MANDIRI COVID-19 MELALUI SUMBERDAYA ONLINE

This phenomenon of self diagnose through online resources in the era of the covid-19 pandemic is something that is dangerous in the diagnosis process. Information literacy about health plays an important role in the process of self-diagnosis of this phenomenon. This study will discuss how the experience of health information literacy is for patients who self-diagnose through online resources in the era of the covid-19 pandemic. This study will use a qualitative method by integrating a phenomenological approach and the seven pillars of information literacy standards. The results of this study show that there are physical and psychological vulnerabilities, which have an impact on information neglect, the quality of health information that makes patients depressed, and corrective actions from expert informants and references.&#x0D; Keywords: health literacy information, online resources, phenomenology, self-diagnosis
Conference Report: Information Infrastructure of Social Science Research in India (IISSRI-2023), Salt Lake City, Kolkata, India, March 2023

An international conference on the Information Infrastructure of Social Science Research in India (IISSRI-2023) was organized by the Institute of Development Studies Kolkata (IDSK) in collaboration with the Indian Council for Social Science Research – Eastern Regional Centre (ICSSR-ERC) on 2-3 March 2023 in Salt Lake, Kolkata, India. The challenges and opportunities related to the information infrastructure in India were explored at this offline conference. Eminent academics, scholars, and information professionals from India and abroad participated in this conference. Read more...
Nation Building and International Financings – A Legal Perspective

This article explores the challenges and opportunities for nation building in Nigeria in the context of the immediate aftermath of the 2023 elections, the twilight of the inauguration of the new administration, led by Senator Bola Ahmed Tinubu and the urgent need to address the critical issues of infrastructure deficit, palpable poverty, and inadequate access to basic services.&#x0D; The article discusses the importance of international financing as a critical source of funding for sustainable development and highlights the importance of aligning national financing objectives with the United Nations' Sustainable Development Goals (SDGs). It emphasizes the need for clear development plans, coordination of risk mitigation mechanisms, cooperation of multilateral financial institutions and national and subnational committees and agencies, transparent legal and regulatory framework, as well as a robust judicial process, to attract international lenders and ensure effective deployment of financing towards the achievement of national development priorities.
A New, Underground Atlas of Subduction Zones

Submap merges graphic design with geodynamics, providing a fast, free, and user-friendly resource to map subduction zones.
Developing AKM-like English Reading Literacy for EFL Students

This study was conducted to develop AKM-like English reading literacy for EFL students and to reveal the different reading strategies. The researchers went through preliminary and formative stages using a development study design. The study generated valid, practical, and potentially AKM-like English reading literacy effects for EFL students. The product satisfies the criteria of validity, practicability, and effectiveness. The students were motivated, engaged, and challenged as the potential effect of the assessment. Most students had high critical reading skills in accessing, retrieving, interpreting, integrating, evaluating, and reflecting on the AKM-like English reading literacy test. The study also revealed that the students used a schemata theory in developing their critical reading ability. To improve students' critical reading literacy and introduce different reading comprehension techniques, EFL teachers should use appropriate types of texts to select students' contextualized world topics.
The Effect of Summarization Strategy on Reading Comprehension through Summary Writing Ability

This study was conducted to investigate the role of summarizing ability as mediator of the effect of summarization strategy on reading comprehension. The study employed a quasi-experimental pre-test and post-test control group design. It was carried out at Azezo Tseda kifleketema Atse Fasil Elementary School. Intact classes of 7th1 (n=54) and 7th2 (n=55) students participated as experimental and control groups, respectively. Students in the treatment and controle groups completed eight reading comprehension lessons using the summarization strategy and the conventional strategy respectively. From them, pre- and post-intervention data were obtained through tests. The data were analyzed through covariate-based structural equation modeling (CB-SEM) using SPSS AMOS v.20. Pretest datawere covariated and controlled. The statistical model showed that summarization strategy has a significant positive direct effect (β = 2.410, CR = 3.948, p&lt; .005) on summarizing ability; on the other hand, summarizing ability has no significant direct effect (β =.178, CR = 1.460, p =.108) on reading comprehension. The strategy also has no significant indirect effect on reading comprehension through summarizing ability (β =.430, p =.109). Therefore, summarizing ability has no mediation role in the relationship between summarization strategy and reading comprehension. Based on the findings, pedagogical and research implications and suggestions were discussed and indicated.
Audible Obstacle Warning System for Visually Impaired Person Based on Image Processing

To be able to do their daily activities, a visually impaired person needs a guidance device to help him/her walk including to avoid obstacles on their way to the destination. The quick and clear instruction is given to the user is the most challenging problem to be solved. The visually impaired person should have simple guidance about the obstruction in front of him/her. Most guidance devices use simple sounds to give the warning without information about which direction the user should go. In this paper, an obstacle warning system based on image processing methods was developed. A guidance device for visually impaired persons using a single-board computer based on an image-processing algorithm has been designed. The main sensor of the guidance device is a NoIR camera. The distance measurement approximation model was developed with errors up to 4.3%. The test found that the proposed system can detect obstruction in the form of a person, the device also detects the stairs. The best detection obtains when the object position is less than 300 cm in front of the user. The stair detection was carried out by using the Hough line transform method. The output of the system is the sound of direction that can be heard through the headset.
Physicochemical and microbial alterations in crude oil-contaminated soil samples

Environmental pollution is becoming an issue of concern due to its negative impact on the living and non-living components of the environment. Crude oil and its products are the major sources of environmental pollution that renders negative impact on the soil mineral components and microorganism. This study was thus carried out to determine the effect of crude oil on soil physicochemical properties, bacterial and fungal population. The experiment lasted for 42 days and the analysis were carried out at days 0, 14, 28 and 42 using standard protocols. Results obtained show significant changes (P ≤ 0.05) in hydrocarbons and other physicochemical parameters such as pH, nitrate, electrical conductivity, sodium ion, calcium ion, phosphate and magnesium ion, when the control was compared with crude oil contaminated soil. Also, soil bacterial and fungal count decreased significantly (P ≤ 0.05) with increasing concentrations of crude oil indicating its toxicity to soil microbial consortium. However, results also showed that hydrocarbon-degrading microorganisms strived at higher concentrations but insignificantly (P ≤ 0.05) in comparison with the control. Owing to the result obtained in this study, crude oil exploration should be properly managed to prevent spillages that negatively impact on the environment.