Reviewerly/exHarmony huggingface dataset:
All-photonic GKP-qubit repeater using analog-information-assisted multiplexed entanglement ranking

Long distance quantum communication will require the use of quantum repeaters to overcome the exponential attenuation of signal with distance. One class of such repeaters utilizes quantum error correction to overcome losses in the communication channel. Here we propose a novel strategy of using the bosonic Gottesman-Kitaev-Preskill (GKP) code in a two-way repeater architecture with multiplexing. The crucial feature of the GKP code that we make use of is the fact that GKP qubits easily admit deterministic two-qubit gates, hence allowing for multiplexing without the need for generating large cluster states as required in previous all-photonic architectures based on discrete-variable codes. Moreover, alleviating the need for such clique-clusters entails that we are no longer limited to extraction of at most one end-to-end entangled pair from a single protocol run. In fact, thanks to the availability of the analog information generated during the measurements of the GKP qubits, we can design better entanglement swapping procedures in which we connect links based on their estimated quality. This enables us to use all the multiplexed links so that large number of links from a single protocol run can contribute to the generation of the end-to-end entanglement. We find that our architecture allows for high-rate end-to-end entanglement generation and is resilient to imperfections arising from finite squeezing in the GKP state preparation and homodyne detection inefficiency. In particular we show that long-distance quantum communication over more than 1000 km is possible even with less than 13 dB of GKP squeezing. We also quantify the number of GKP qubits needed for the implementation of our scheme and find that for good hardware parameters our scheme requires around $10^3-10^4$ GKP qubits per repeater per protocol run.
Usability evaluation of online digital libraries of educational institutions

Advancement in technology bestowed people with numerous invaluable gadgets and devices. Mobile phone is one of the most distinguished products of modern technology. The researchers, software engineers and scientists have joint venture to explore the possibility of mobile phone technology. Their toiling efforts are being consumed in broadening the application and usability of mobile phone. Many applications have been programmed to assist the process of learning for the convenience of teachers and learners. In this research, we aim at evaluating the usability of Online Digital Libraries of different Pakistani Universities. Indeed, there are different ways to evaluate the usability of online library applications, such as interviews, card sort and Shneiderman’s Eight Golden Rules, and Heuristics Nielson 10 golden rules etc. To evaluate and enhance the usability of mobile app, we used Nielson 10 golden rules. These set of rules and guidelines provide right direction and allow us to identify major usability issues. We have found the main usability issues in the mobile App libraries; if they are fixed, they can become more effective for the users to search their required materials.
Hook, line, and sinker: the mechanics of fraud

Fraud is a crime that has been called "theatrical mugging" because it involves a wide range of psychological, societal, and economic principles as well as human nature, creativity, and a unique set of (criminal) skills and practices. Fraud is the wrongful or criminal deception for financial or personal gain. The components or elements of any fraud are the same, from Three Card Monte to embezzlement to large-scale criminal activities like Enron or the FIFA scandal. This chapter reviews the fundamentals of fraud (the hook, the line, the sinker, and the blow-off), some of the psychological aspects that make it a unique crime, and how modern digital life makes fraud easier. While there may still be a sucker born every minute, by understanding how cons work and their universal structure, whether at work, as work, or after work, it will be easier to detect even the better cons and stop them before they take their next victim.
Expressive architectures enhance interpretability of dynamics-based neural population models

Artificial neural networks that can recover latent dynamics from recorded neural activity may provide a powerful avenue for identifying and interpreting the dynamical motifs underlying biological computation. Given that neural variance alone does not uniquely determine a latent dynamical system, interpretable architectures should prioritize accurate and low-dimensional latent dynamics. In this work, we evaluated the performance of sequential autoencoders (SAEs) in recovering latent chaotic attractors from simulated neural datasets. We found that SAEs with widely-used recurrent neural network (RNN)-based dynamics were unable to infer accurate firing rates at the true latent state dimensionality, and that larger RNNs relied upon dynamical features not present in the data. On the other hand, SAEs with neural ordinary differential equation (NODE)-based dynamics inferred accurate rates at the true latent state dimensionality, while also recovering latent trajectories and fixed point structure. Ablations reveal that this is mainly because NODEs (1) allow use of higher-capacity multi-layer perceptrons (MLPs) to model the vector field and (2) predict the derivative rather than the next state. Decoupling the capacity of the dynamics model from its latent dimensionality enables NODEs to learn the requisite low-D dynamics where RNN cells fail. Additionally, the fact that the NODE predicts derivatives imposes a useful autoregressive prior on the latent states. The suboptimal interpretability of widely-used RNN based dynamics may motivate substitution for alternative architectures, such as NODE, that enable learning of accurate dynamics in low-dimensional latent spaces.
Distribution of Coronavirus Disease (Covid-19) in West Sumatra Province with Local Indicator of Spatial Association (LISA) Cluster Map

&lt;div&gt;&lt;table cellspacing="0" cellpadding="0" align="left"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td align="left" valign="top"&gt;&lt;p&gt;&lt;em&gt;The COVID-19 pandemic in West Sumatra Province indicates a greater number of cases and mortality. The spread of COVID-19 is related to the mobility of the population, so the potential for transmission between regions is difficult to control. This study aims to determine the local index used in evaluating the tendency for local spatial groupings and can show some form of spatial relationship. Spatial analysis were conducted on 2020 to analyze spatial distribution of Covid-19 in West Sumatera Province. Spatial relationship was assessed by Local Indicator of Spatial Association (LISA). Mapping can be done with the LISA cluster map. The data used is COVID-19 incidence data based on reports from district or city in West Sumatra Province in 4 June 2020. We used Open Geoda Software to analyze the spatial distribution. There is positive spatial autocorrelation and classification in hot spots, cold spots, and outliers in the spread of COVID-19 cases in West Sumatra Province. Hot spots were found in Padang City, Bukittinggi City, and Padang Panjang City. Cold spots also detected in several districts, that is &lt;/em&gt;&lt;em&gt;West Pasaman, Pasaman, Payakumbuh, Solok, Padang Pariaman, Pariaman, Sawahlunto, and Sijunjung. &lt;/em&gt;&lt;em&gt;The transmission of the COVID-19 case does not recognize regional boundaries, but the grouping of districts or cities based on regional vulnerability is important as part of local control efforts to allocate resources. Coordination and collaboration among local governments need to be strengthened in preventing transmission between regions and reducing the number of cases in vulnerable areas based on hot spots and cold spots from LISA cluster map. It’s necessary for intervention programs more focused and effectively.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt; &lt;/em&gt;&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;/div&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords: COVID-19, Mapping, Spatial, Vulnerability&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;
Defining Quality in Primary and Secondary Education

The purpose of this paper is to explore the conceptual content of the term &amp;lsquo;quality&amp;rsquo; in primary and secondary education through the content analysis of 32 scientific publications. The analysis of the qualitative data is based on the methodology of grounded theory, revealing 21 major dimensions of quality with a high frequency of occurrence that are divided into five broader categories. The first category, &amp;lsquo;learning environment,&amp;rsquo; includes psychosocial elements, physical elements, respect for diversity and collaboration, sharing, and team spirit. The second category, &amp;lsquo;learning content,&amp;rsquo; includes student-centred pedagogy, well-structured knowledge base, continuous curriculum improvement, interest in all students, and life skills. The third category, &amp;lsquo;processes,&amp;rsquo; includes teaching, learning, assessment, support, and supervision. The fourth category, &amp;lsquo;students,&amp;rsquo; includes involvement/participation, feedback, challenging learning activities, and improved learning outcomes. Finally, the fifth category, &amp;lsquo;teachers,&amp;rsquo; includes knowledge of educational context, content, curriculum, and pedagogy, pedagogical skills, emotional/management/reflection skills, and teacher professional development. According to the main findings, from the category &amp;lsquo;learning environment,&amp;rsquo; the dimension concerning the psychosocial elements prevails in the literature; from the category &amp;lsquo;learning content&amp;rsquo;, the dimension of student-centred pedagogy prevails; and from the category &amp;lsquo;processes&amp;rsquo;, three dimensions prevail: the first is related to support and supervision and the other two are related to teaching and assessment. From the wider category &amp;lsquo;students,&amp;rsquo; the dimension relating to improved learning outcomes prevails. Finally, in the category &amp;lsquo;teachers,&amp;rsquo; two dimensions prevail: the first concerns skills (emotional, management, reflection), and the second dimension concerns knowledge of the educational context, content, curriculum, and pedagogy.
Impact of service innovation and digital supply chain capability on risk protection in supporting online foods delivery

Purpose This study has aimed to investigate the impact of service innovation capabilities (SIC), supply chain digitalization capabilities (SDC) and customer risk protection (CRP) capabilities of GrabFood on customer satisfaction. GrabFood has been chosen as a case study because GrabPay is one of the Malaysian government's digital wallet partners, and GrabFood is one of the region's leading Online Food Delivery Service (OFDS) providers. Design/methodology/approach A total of 410 valid responses have been gathered from the GrabFood users for data analysis using the partial least square technique. Findings The findings reveal that SIC, SDC and CRP of GrabFood have a highly significant influence on customer satisfaction. CRP has been found to partially mediate the relationship between SIC and customer satisfaction and the relationship between SDC and customer satisfaction. Originality/value OFDS providers need to consider how to minimize the potential risk to be encountered by customers in delivering services that satisfy the customers. OFDS providers must identify the gap between their capabilities and customer perception and continuously improve their service quality to mitigate the gap.
Enhancement in Speaker Identification through Feature Fusion using Advanced Dilated Convolution Neural Network

There are various challenges in identifying the speakers accurately. The Extraction of discriminative features is a vital task for accurate identification in the speaker identification task. Nowadays, speaker identification is widely investigated using deep learning. The complex and noisy speech data affects the performance of Mel Frequency Cepstral Coefficients (MFCC); hence, MFCC fails to represent the speaker characteristics accurately. In this proposed work, a novel text-independent speaker identification system is developed to enhance the performance by fusion of Log-MelSpectrum and excitation features. The excitation information is obtained due to the vibration of vocal folds, and it is represented using Linear Prediction (LP) residual. The various types of features extracted from the excitation are residual phase, sharpness, Energy of Excitation (EoE), and Strength of Excitation (SoE). The extracted features were processed with the dilated convolution neural network (dilated CNN) to fulfill the identification task. The extensive evaluation showed that the fusion of excitation features gives better results than the existing methods. The accuracy reaches 94.12% for 11 complex classes and 91.34% for 80 speakers, and Equal Error Rate (EER) is reduced to 1.16% for the proposed model. The proposed model is tested with the Librispeech corpus using Matlab 2021b tool, outperforming the existing baseline models. The proposed model achieves an accuracy improvement of 1.34% compared to the baseline system.
The 3D Digital Documentation of Shaft K24 in Saqqara

In our contribution we discuss in detail the three-dimensional digital documentation strategy of the intact burial chambers of Shaft K24 of the recently discovered mummification workshop complex by the Saqqara Saite Tombs Project (SSTP). This 30 m deep shaft served as a communal burial site. In six tombs dug into the walls of the shaft at different depths, a large number of significant archaeological materials were found in situ. After an introduction to the project, we discuss the different 3D technologies, which we used to document the site and the excavation process, highlighting their advantages and disadvantages. Besides the technical description, a main focus of the paper will be the influence of 3D documentation on the research and conservation processes.
Next-Month Prediction of Hourly Solar Irradiance based on Long Short-Term Memory Network

Today, in parallel with the population growth and the advancement of technology, development concerns have started to arise in terms of country administrators. Therefore, alternative solutions to classical energy sources are sought. Renewable energy sources are one of the preferred energy sources today. The popularity of renewable energy sources, including solar energy, is increasing day by day. Solar energy has the potential and accessibility to spread faster than other renewable energy sources. Since Türkiye is located in a region with a high potential in terms of solar energy, which is generally called the sun belt, it is a right decision to prefer solar energy as an energy source in our region. In this study, time series prediction using Long Short-Term Memory (LSTM) Network method is used for short-term solar irradiance estimation. In order to demonstrate the success of the results, a comparison was made with the Artificial Neural Network (ANN) method. Finally, prediction results of solar irradiance were compared with statistical tests and error analyzes were given in numerically.
Impact of the COVID-19 pandemic on the nursing students' education in a public university in Colombia

To explore the impacts of the COVID-19 pandemic on nursing student education in one public university in Medellin, Colombia.This descriptive qualitative study used content analysis to address the following questions: (1) How has the COVID-19 pandemic impacted nursing education at the University of Antioquia? (2) What were the most important challenges experienced by nursing students? (3) What was most supportive for the students during the pandemic? and (4) What were the potential opportunities and lessons learned related to nursing education? Data were collected virtually through individual online interviews with 14 undergraduate nursing students and analysed using qualitative content analysis with constant comparisons.Four main categories of findings related to the experience of undergraduate nursing students during the COVID-19 pandemic were identified: (1) transitioning to online learning, (2) managing the digital world, (3) impacts on clinical training, and (4) work-related stressors. Key challenges included home environments that were not conducive to learning, reduced social interactions with peers and faculty, accessing technology required for online education and insufficient preparation for clinical practice. Family members and university-provided resources were important sources of student support. Whereas the pandemic limited opportunities for hands-on clinical training, the shift to online learning allowed for the development of skills related to informational technologies and telehealth.Undergraduate students at the University of Antioquia identified significant barriers to learning during the COVID-19 pandemic restrictions and transition to online learning, as well as new opportunities for the development of digital skills among both students and faculty.
Faktor-Faktor yang Mempengaruhi Hasil Belajar Geografi secara Daring: Studi Siswa SMA Negeri 1 Samaturu, Sulawesi Tenggara

This study aimed to determine the factors of online geography learning outcomes in class XI IIS SMAN 1 Samaturu. Learning outcomes' position was crucial and inseparable from the learning process. Learning outcomes can be used as an indicator of the success of the learning process. Low learning outcomes were a problem in the learning process, which is still developing, and solutions or factors that influence learning outcomes have yet to be found. This type of research uses quantitative descriptive. The subject of this study was students of class XI IIS, totalling 33 students. The technique used to collect data was a questionnaire. First, data analysis was carried out by giving student scores for each questionnaire item. Second, averaging student scores for all of these items, and third, determining student criteria. The results of this study obtained that the student's geography learning outcomes factor was the parental attention factor found in the indicators of giving awards, giving punishments, giving examples, giving guidance and helping difficulties and meeting students' learning needs. The last two indicators make a major contribution to low student learning outcomes.
Mobile Forensic Tools for Digital Crime Investigation: Comparison and Evaluation

The advancement of new technology is quickening.Because of the features and applications available on mobile devices, smartphones are gradually taking over the role of computers.One of them is a multi-platform instant messaging application with various features that can bring people together, but the negative aspect is that it is used to commit digital crimes.Digital evidence is required in the investigation of digital crimes, In order to obtain digital evidence, a set of forensic tools is required to carry out the forensic process of physical evidence.The goal of this research is to describe and contrast the forensic process.These tools are currently based on digital evidence obtained through the stages of the Digital Forensic Research Workshop.MEF, DB4S, OFD, and FMF are the forensic tools used in this study.According to the findings, FMF has the highest extraction capability for obtaining digital evidence, OFD has advantages in terms of data acquisition features, and MFE has advantages in identification, physical evidence preservation, and cloning.
Learning Model of Reading and Writing Literacy During the Covid-19 Pandemic in Kindergarten

This study aims to describe the learning model of reading and writing literacy during the Covid-19 pandemic at TK Tunas Ambulung Banjarbaru and TK Tunas Bangsa Banjarbaru. This study uses a qualitative approach with a multi-site method. Data collection through interviews, observation and documentation. The data is processed in the form of reduction, data presentation and conclusion. The results of the study illustrate that Kindergarten uses guidelines from the Ministry of Education and Culture, fun play activities at school and at home, creates a pleasant atmosphere and provides an environment rich in literacy at school and at home, increases the competency of school principals and teachers through webinars on the implementation of learning and improvement competence in school and inter-school learning communities, partnering with Community Health Centers and Regional Libraries in limited face-to-face meetings, and teachers and parents taking advantage of Kindergarten media around children's homes and around the school environment.
Missing value imputation Techniques: A Survey

Numerous of information is being accumulated and placed away every day. Big quantity of misplaced areas in a dataset might be a large problem confronted through analysts due to the fact it could cause numerous issues in quantitative investigates. To handle such misplaced values, numerous methods were proposed. This paper offers a review on different techniques available for imputation of unknown information, such as median imputation, hot (cold) deck imputation, regression imputation, expectation maximization, help vector device imputation, multivariate imputation using chained equation, SICE method, reinforcement programming, non-parametric iterative imputation algorithms, and multilayer perceptrons. This paper also explores a few satisfactory choices of methods to estimate missing values to be used by different researchers on this discipline of study. Furthermore, it aims to assist them to discern out what approach is commonly used now, the overview may additionally provide a view of every technique alongside its blessings and limitations to take into consideration of future studies on this area of study. It can be taking into account as baseline to solutions the question which techniques were used and that is the maximum popular.
Seasonal Optimum Tilt Angle of Solar Panels for 100 Cities in the World

Solar energy is the most abundant renewable energy source. This energy can be converted directly into electricity using solar panels. The fixed tilt solar panels are the most practical and the most widely installed throughout the world. Optimum tilt angle calculation has the advantage that it does not use expensive solar trackers. This research calculates the seasonal optimum tilt angle of solar panels for 17 cities in Iraq and 83 cities in 83 countries distributed around the world. Solar Panel Angle Calculator program was used in calculating the optimum tilt angles from vertical. The optimum tilt angle varies between 6° and 112° throughout the year. This angle for winter, spring/ autumn and summer seasons are found to be between 6° to 66°, 30° to 89° and 54° to 112°, respectively. All angles calculated from the calculator program are validated by comparing it with those obtained from equations. An excellent agreement was established. Cities which have approximately the same absolute values of the latitudes are have the same optimum tilt angles. Based on the results, adjusting angles four times a year is recommended. This work can serve as a guidance for installing solar panels.