Reviewerly/exHarmony huggingface dataset:
Interaction Techniques with a Navigation Robot for the Visually Impaired

Robotic technology has long been seen as a potential mobility aid for the visually impaired, and the latest advancements in sensing and artificial intelligence have made it a reality. Before starting the project, we researched the capabilities of, and user interactions with guide dogs. We discovered that the rich haptic interaction with the "handle" allows users to comfortably follow a guide dog.
Business Value Assessment and IT Roadmap to Achieve e-Government Dimension of Smart Village using TOGAF ADM: A Case Study of Regency in Indonesia

An architectural business process in a company certainly needs an estimate related to assessing the owned business. Because by doing this assessment, of course, you can find out how good or how complex a project can be done or handled by an agency organization. Another thing that needs to be considered is how a regulation runs and can follow the development of the latest technology. Of course, in conducting this evaluation, it is hoped that it can provide pressure or reduction in terms of operational costs and increase investment so that the process or value presented will be proportional and even increase and have good quality. This study will present a result of the assessment with the value of the business value assessment (BVA) of the information technology project based on a case study of the development of the smart village concept in the e-government domain. The method used is expected to provide an output design in business architecture enterprise artefacts, data, applications, and technology architecture.
Review : Equation Study of Langmuir and Freundlich Isotherms on Adsorption of Heavy Metal Fe (II) with Zeolite and Activated Carbon from Biomass

Zeolite and activated carbon can be used as adsorbent of metal ion Fe(II). The activation of zeolite and activated carbon was carried out with various acid and alkaline solutions. The purpose of this literature review is to determine the equation of the Langmuir isotherm and the Freundlich isotherm on the absorption of an adsorbate, namely metal ion Fe (II) by natural and synthetic zeolites and activated carbon made from biomass sourced from the relevant literature. Determination of the appropriate adsorption isotherm pattern is done by entering the research data into the empirical formula of the Langmuir and Freundlich equations. The equation in Langmuir is 1/q = 1/qm.b . 1/Ce + 1/qm, where to determine the Langmuir isotherm equation it is necessary to find the values of 1/qm.b and 1/qm. The equation in Freundlich is 1/q = 1/qm.b . 1/Ce + 1/qm, where to determine the Freundlich isotherm equation it is necessary to find the value of log k and 1/n. The sought price can be obtained by graphing by plotting 1/q versus 1/Ce for Langmuir and log x/m versus log Ce for Freundlich. The largest maximum capacity of the Langmuir isotherm is 10.19 mg/g using a zeolite (synthetic) adsorbent. And the largest maximum capacity on the Freundlich isotherm is 182.9 mg/g using activated carbon as adsorbent (button mangrove stem biomass).&#x0D; AbstrakZeolit dan karbon aktif dapat dimanfaatkan sebagai adsorben ion logam Fe (II). Pengaktivasian zeolit dan karbon aktif dilakukan dengan berbagai larusan asam dan larutan basa. Tujuan dalam literature review ini adalah untuk mengetahui persamaan isoterm Langmuir dan isoterm Freundlich pada penyerapan suatu adsorbat yaitu ion logam Fe (II) oleh zeolit alam maupun sintetis dan karbon aktif yang terbuat dari biomassa yang bersumber pada literature yang relevan. Penentuan pola isoterm adsorpsi yang sesuai dilakukan dengan cara memasukkan data hasil penelitian ke dalam rumus empiris persamaan Langmuir dan Freundlich. Persamaan pada Langmuir yaitu 1/q = 1/qm.b . 1/Ce + 1/qm, dimana untuk menentukan persamaan isoterm Langmuir perlu dicari harga 1/qm.b dan 1/qm. Persamaan pada Freundlich yaitu 1/q = 1/qm.b . 1/Ce + 1/qm, dimana untuk menentukan persamaan isoterm Freundlich perlu dicari harga log k dan 1/n. Harga yang dicari dapat didapatkan dengan cara membuat grafik dengan mengeplotkan 1/q versus 1/Ce untuk Langmuir dan log x/m versus log Ce untuk Freundlich. Kapasitas maksimum terbesar pada isoterm Langmuir yaitu 10,19 mg/g dengan menggunakan adsorben zeolit (sintesis). Dan Kapasitas maksimum terbesar pada isoterm Freundlich yaitu 182,9 mg/g dengan menggunakan adsorben karbon aktif (biomassa batang bakau kancing).
Normalization effects on deep neural networks

We study the effect of normalization on the layers of deep neural networks of feed-forward type. A given layer $ i $ with $ N_{i} $ hidden units is allowed to be normalized by $ 1/N_{i}^{\gamma_{i}} $ with $ \gamma_{i}\in[1/2,1] $ and we study the effect of the choice of the $ \gamma_{i} $ on the statistical behavior of the neural network's output (such as variance) as well as on the test accuracy on the MNIST data set. We find that in terms of variance of the neural network's output and test accuracy the best choice is to choose the $ \gamma_{i} $'s to be equal to one, which is the mean-field scaling. We also find that this is particularly true for the outer layer, in that the neural network's behavior is more sensitive in the scaling of the outer layer as opposed to the scaling of the inner layers. The mechanism for the mathematical analysis is an asymptotic expansion for the neural network's output. An important practical consequence of the analysis is that it provides a systematic and mathematically informed way to choose the learning rate hyperparameters. Such a choice guarantees that the neural network behaves in a statistically robust way as the $ N_i $ grow to infinity.
A Review of the Challenges and Opportunities in Cloud Computing Services

Hardware, software, and networks are all shared resources in the context of cloud computing. The third-party cloud service provider (CSP) maintains the shared resources using environment. The third-party cloud service provider (CSP) maintains the shared resources. On-demand services are offered by cloud service providers in accordance with the needs of cloud users. Users of the cloud must pay for any services they use in the environment. This article discusses the challenges of the cloud and some of its opportunities in domains like education and healthcare.
An Analysis of Students’ Speaking Anxiety in EFL Classroom: A Mixed-Method Study

The study aims to investigate the students’ speaking anxiety levels, find the effect of anxiety, and identify the factors influencing students’ speaking participation. This study involved 62 students in the second semester of the English Education Department, UIN Syarif Hidayatullah Jakarta. This study employed a mixed-method design. To gather the data, a set of questionnaires was utilized based on the Foreign Language Speaking Anxiety Scale by (Horwitz et al., 1986) and an interview. The result of the FLCAS questionnaire classified the category of student anxiety. There were 8 students categorized as very anxious level, 29 students as anxious level, 23 students as mildly anxious level, and 2 students as relaxed level. Students with mildly anxious levels and very anxious levels were interviewed to probe richer data. Further, the study found the effect of students’ speaking anxiety on their speaking participation: considering the idea they want to express, refusing to ask or argue, and being hesitant to participate. This study also found several factors influencing students’ speaking participation, such as English proficiency level, students’ low self-esteem, afraid of making mistakes, lack of preparation, motivation, the method used, and lecturer's attitude
Adaptive quantum error mitigation using pulse-based inverse evolutions

Quantum Error Mitigation (QEM) enables the extraction of high-quality results from the presently-available noisy quantum computers. In this approach, the effect of the noise on observables of interest can be mitigated using multiple measurements without additional hardware overhead. Unfortunately, current QEM techniques are limited to weak noise or lack scalability. In this work, we introduce a QEM method termed `Adaptive KIK' that adapts to the noise level of the target device, and therefore, can handle moderate-to-strong noise. The implementation of the method is experimentally simple -- it does not involve any tomographic information or machine-learning stage, and the number of different quantum circuits to be implemented is independent of the size of the system. Furthermore, we have shown that it can be successfully integrated with randomized compiling for handling both incoherent as well as coherent noise. Our method handles spatially correlated and time-dependent noise which enables to run shots over the scale of days or more despite the fact that noise and calibrations change in time. Finally, we discuss and demonstrate why our results suggest that gate calibration protocols should be revised when using QEM. We demonstrate our findings in the IBM quantum computers and through numerical simulations.
Curvature-Sensitive Predictive Coding with Approximate Laplace Monte Carlo

Predictive coding (PC) accounts of perception now form one of the dominant computational theories of the brain, where they prescribe a general algorithm for inference and learning over hierarchical latent probabilistic models. Despite this, they have enjoyed little export to the broader field of machine learning, where comparative generative modelling techniques have flourished. In part, this has been due to the poor performance of models trained with PC when evaluated by both sample quality and marginal likelihood. By adopting the perspective of PC as a variational Bayes algorithm under the Laplace approximation, we identify the source of these deficits to lie in the exclusion of an associated Hessian term in the PC objective function, which would otherwise regularise the sharpness of the probability landscape and prevent over-certainty in the approximate posterior. To remedy this, we make three primary contributions: we begin by suggesting a simple Monte Carlo estimated evidence lower bound which relies on sampling from the Hessian-parameterised variational posterior. We then derive a novel block diagonal approximation to the full Hessian matrix that has lower memory requirements and favourable mathematical properties. Lastly, we present an algorithm that combines our method with standard PC to reduce memory complexity further. We evaluate models trained with our approach against the standard PC framework on image benchmark datasets. Our approach produces higher log-likelihoods and qualitatively better samples that more closely capture the diversity of the data-generating distribution.
SIGN RECOGNITION AND VOICE CONVERSION DEVICE FOR DUMB

At most of us are blessed with natural capability to see, hear and interact. Still, numerous people do not have this capability. Due to various reasons like birth scars, accidents, oral conditions, and environmental impacts the number of analogous people is swiftly adding in the recent times. Ultimate of the deaf and dumb use gesture and subscribe symbol for the communication. Subscribe language is the form of communication where shapes, arms or body, exposure and movement of hands, and facial expressions are completely combined. The communication gap between two persons is because of a dumb person uses sign language which is not comprehensible by a normal person. This design mainly focuses on removing the barricade of communication between the mute community and the people not familiar with the generality of sign language so that the dispatches that a dumb person is trying to bear is accessible to a person with no knowledge of sign language. The design of the device is predicated on bedded systems. Keywords Arduino, Dumb, Bedded systems, Gesture recognition, Speech recognition, Speech processing.
Quantum illumination using polarization-path entangled single photons for low reflectivity object detection in noisy background

Detecting object with low reflectivity embedded within a noisy background is a challenging task. Quantum correlations between pairs of quantum states of light, though are highly sensitive to background noise and losses, offer advantages over traditional illumination methods. Instead of using correlated photon pairs which are sensitive, we experimentally demonstrate the advantage of using heralded single-photons entangled in polarization and path degree of freedom for quantum illumination. In the study, the object of different reflectivity is placed along the path of the signal in a variable thermal background before taking the joint measurements and calculating the quantum correlations. We show the significant advantage of using non-interferometric measurements along the multiple paths for single photon to isolate the signal from the background noise and outperform in detecting and ranging the low reflectivity objects even when the signal-to-noise ratio is as low as 0.03. Decrease in visibility of polarization along the signal path also results in similar observations. This will have direct relevance to the development of single-photon based quantum LiDAR and quantum imaging.
The Impact of Cryptocurrency Volatility Dynamics on the Islamic Equity Market: The Case of Emerging Asia

This paper investigates the impact of the realized volatility of positive and negative intraday Bitcoin returns on the sensitivity of Shariah-compliant stocks’ orthogonalized returns. We identify the impact in different market states and find that Bitcoin’s upside volatility negatively affects the returns of Islamic equities. The paper contributes to uncovering the properties of a niche Islamic Emerging Asian equity market. The findings offer important implications for investors’ diversification strategies.
WIP: Practical Removal Attacks on LiDAR-based Object Detection in Autonomous Driving

LiDAR (Light Detection And Ranging) is an indispensable sensor for precise long-and wide-range 3D sensing, which directly benefited the recent rapid deployment of autonomous driving (AD).Meanwhile, such a safety-critical application strongly motivates its security research.A recent line of research demonstrates that one can manipulate the LiDAR point cloud and fool object detection by firing malicious lasers against LiDAR.However, these efforts evaluate only a specific LiDAR (VLP-16) and do not consider the state-of-the-art defense mechanisms in the recent LiDARs, so-called next-generation LiDARs.In this WIP work, we report our recent progress in the security analysis of the next-generation LiDARs.We identify a new type of LiDAR spoofing attack applicable to a much more general and recent set of LiDARs.We find that our attack can remove >72% of points in a 10×10 m 2 area and can remove real vehicles in the physical world.We also discuss our future plans.
Can You Tell Me the Time? Security Implications of the Server-Timing Header

Performing a remote timing attack typically entails the collection of many timing measurements in order to overcome noise due to network jitter.If an attacker can reduce the amount of jitter in their measurements, they can exploit timing leaks using fewer measurements.To reduce the amount of jitter, an attacker may use timing information that is made available by a server.In this paper, we exploit the use of the server-timing header, which was created for performance monitoring and in some cases exposes millisecond accurate information about server-side execution times.We show that the header is increasingly often used, with an uptick in adoption rates in recent months.The websites that use the header often host dynamic content of which the generation time can potentially leak sensitive information.Our new attack techniques, one of which collects the header timing values from an intermediate proxy, improve performance over standard attacks using roundtrip times.Experiments show that, overall, our new attacks (significantly) decrease the number of samples required to exploit timing leaks.The attack is especially effective against geographically distant servers.Coordinated Disclosure: We have disclosed our findings to the authors of the W3C Working Draft and have also contacted Shopify to warn them about the possible security risks of using the server-timing header. II. BACKGROUNDWhen timing attacks were introduced two and a half decades ago by Kocher in 1996, most of these attacks were aimed at exploiting cryptographic implementations to extract
MEMORIZATION STRATEGY DURING LEARNING PROCESS: STUDENTS' REVIEW

The purpose of this research is to determine about how the attitude of using the memorization strategy towards students' learning activities. This research using a quantitative methods. The sample of this research were 38 students from English Education in a private university. They consist of male and female sixth-semester students. The research instrument in the form of a questionnaire obtained through google form, then the data will be analyzed using SPSS to find out how students' attitudes towards the learning strategy of memorization. The results of this study indicate that the student's attitude towards the memorization learning strategy show a positive attittude, it can be seen from the results of the questionnaire that has been filled out by the participants. According to their responses, the memorization strategy also made it easier for them to absorb lesson information. These findings can be used by teachers or lecturers to apply the memorization strategy as an effective learning strategy for the students.
THE CORRELATION BETWEEN ANXIETY AND STUDENT GPA &amp; EPT SCORE DURING COVID 19 PANDEMIC

One of the problems and inhibitions of students’ learning development is anxiety. Students’ in Indonesia learn online from home in an effort to limit social restrictions during the pandemic covid-19. From this online learning, there is also anxiety felt by students’. The purpose of this study is to find out what are the anxieties felt by students’ in online learning during this pandemic that have an correlation with their last GPA score and EPT (English proficiency test) score. This research was designed using quantitative correlational study with independent variables. The data of this study was taken from English Education Students’ of Universitas Teknokrat Indonesia and the sample obtained in this study was 39 students’ who take Quantitative Research class. The instruments used in collecting the data are questionnaire and the last GPA EPT score. Statistical analysis of Pearson product-moment correlation and SPSS software was used to find the correlation between the variables. The result of this study showed that there were negative correlation between anxiety and students’ GPA and EPT scores. The correlation was 0.925, and the t-table was lower than the T-test. As a result, it is entirely possible to conclude that anxiety has a statistically significant impact on student achievement.
Analysis of the Influence of Part-Time Work on Student Learning Activities

Education is one of the necessities of life that every individual must have. One level of education is a college education. In tertiary institutions' learning process, students are inseparable from financial needs for learning needs and living standards. This need forces students to do part-time jobs. Part-time jobs are growing from time to time. Part-time work has both positive and negative effects on student development in the world of work. This study aims to analyze part-time jobs for students of the 2017 Geography Education Department, their relation to learning activities, and the factors that motivate students to work part-time. This study uses a quantitative approach with simple analytical techniques. The population in this study were all students of the 2017 class of the Geography Education Department, with a sample of 20 students. Data collection techniques using a questionnaire. The study results show a significant effect of part-time work and learning activities with a substantial value of 0.037 &lt;0.05. The main factor for students is working part-time because of the financial need for college needs and the standard of living. Part-time jobs done by students are online motorcycle taxi drivers, shopkeepers, salespeople, private tutors, and web programmers.Keywords: Part-Time, Student, Geography Education, Learning Activities
A meta-analysis of the effects of spherical video-based virtual reality on cognitive and non-cognitive learning outcomes

ABSTRACTABSTRACTRecent years have seen an increase number of studies on spherical video-based virtual reality (SVVR) in education.However, the impact of SVVR on learning performance remains unclear and cannot be simply generalized from traditional VR-based education. The purpose of this study was to examine the overall effects of SVVR on cognitive and non-cognitive learning outcomes and to explore a set of moderating variables in student, technology, pedagogy, and methodology aspects. The meta-analysis examined 33 studies from 31 articles that compare SVVR to other instructional conditions. All analyzed articles were published between 2018 and 2021, and were sourced from ERIC, the Web of Science, Scopus, and Google scholar. This resulted in 27 independent effect sizes on cognitive outcomes and 23 independent effect sizes on non-cognitive outcomes. Overall, we found SVVR had a low-medium and a medium effect on cognitive and non-cognitive learning outcomes, respectively. For cognitive learning outcomes, the effect sizes were significantly moderated by scaffolding type and learning duration. For non-cognitive learning outcomes, the effect sizes were significantly moderated by interaction functionality, learning duration, learner's stage, research setting, source of SVVR, and scaffolding type. A detailed discussion of the findings and implications for teaching and learning with SVVR were provided.KEYWORDS: Spherical video-based virtual realitymeta-analysiscognitivenon-cognitivevideo-based learningcomputer-generated virtual reality Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the National Natural Science Foundation of China [grant number 61977023].Notes on contributorsBian WuBian Wu is an associate professor in the Department of Education Information Technology at East China Normal University. His research interests include VR in education, STEM education, and learning analytics.Xinyu ChangXinyu Chang is a master student in the Department of Education Information Technology at East China Normal University. Her research interests include VR in education.Yiling HuYiling Hu is an associate professor in the Department of Education Information Technology at East China Normal University. Her research interests include problem-solving learning and learning analytics.