Reviewerly/exHarmony huggingface dataset:
Recommendations for Ethical Usage of Facial Recognition Technology

This paper investigates the current state of Facial Recognition Technology (FRT) and the ethical concerns surrounding it discussed in literature. Based on these concerns, a code of ethics is developed to provide recommendations on how to use FRT ethically. The essence of this code is to protect the rights of citizens and to use FRT in a way that minimizes misuse and benefits all. Finally, a specific use case of FRT is introduced to demonstrate how the proposed code of ethics can be applied effectively to a real project. The findings are then summarized, and recommendations made going forward.
Penerapan Aplikasi Android E-Payment dan Pemesanan Layanan Pujasera

Pujasera or Multi-purpose Snack Center is an area where food and drinks are served or enjoyed by buyers which consist of many variations of sellers divided into outlets, booths, or stalls. In general, each of these outlets conducts transactions directly with buyers, both choosing orders, serving food, and paying. This raises several problems, including queue numbers that are no longer in order and table numbers that are not well-coordinated, and the occurrence of queues of buyers. The purpose of this study is to design an Android-based application with e-payment and ordering service features at the food court so that it is expected to minimize obstacles and errors that occur. The payment mechanism is also carried out virtually with the existence of e-payments to make it easier for buyers and store owners. The features provided start from the deposit and balance refunds, and other related services so that they don't have to queue and don't have to carry cash. This implemented system can provide convenience and comfort to buyers and store owners, the application works well and is integrated to facilitate ordering and payment services to be more transparent and more informative. The percentage of interpretation evaluation is categorized as very feasible, with the results of the evaluation of application users with an interpretation level of 90%.
Understanding Agile Practices for Job Satisfaction through Job Characteristics

Usage of Agile Practices draws the attention to the adoption of these agile methods because of their significant contributions to high software quality and job benefits. Therefore, the purpose of this research was to look at the role of job characteristics in mediating the relations between agile practices; project management (PM), and software development approaches (SDA) and job satisfaction. Sample was 486 professionals working in the companies incorporating agile practices, to whom an online survey was administered during period of September 2021 using the Google Forms platform. Findings affirmed the claims that agile PM and SDA practices made professionals more satisfied with their jobs and this impact has been found further mediated by job characteristics. Results indicated that job characteristics like job autonomy and feedback mediated the agile PM practices and job satisfaction. While agile SDA practices and job satisfaction were explained significantly by all job characteristics i.e., feedback, task significance, skill variety, autonomy, and task identity. This study offers insights into agile approaches in project management and software development. This research reveals beneficial aspects of agile practices that influence job satisfaction in work environment.
No-Reference Image Quality Assessment based on Quality Awareness Feature and Multi-task Training

in data augmentation-based methods.These methods directly research the data itself, augment the dataset by applying distortion to high-quality original images.RankIQA [14] designed a strategy to generate large-scale distorted images without laborious human labeling.According to the law that image quality decreases with increasing distortion levels, they synthetically generate ranked image pairs with different distortion levels from the Waterloo Exploration dataset [15].A Siamese network is pretrained using pairs of sorted images.Finally, they used a
Code of Ethics for Facial Recognition

Facial Recognition is a big part of surveillance and security in recent years. Along with any technology there are ethical issues that need to be considered when designing, creating, and using the system. This paper reviews the literature and their codes of ethics and ethical issues surrounding facial recognition to draw conclusions about the most important principles. Issues discussed include bias, collection of data, transparency, vulnerable population, security, and accountability. With these conclusions a code of ethics is introduced to improve or justify the current literature. Elaborations are made on each principle to justify the issue and inform specific ways to make the system ethical. This new code of ethics is then used to analyse the ethics around facial recognition in schools.
Memoryless quantum repeaters based on cavity-QED and coherent states

A quantum repeater scheme based on cavity-QED and quantum error correction of channel loss via rotation-symmetric bosonic codes (RSBC) is proposed to distribute atomic entangled states over long distances without memories and at high clock rates. In this scheme, controlled rotation gates, i.e., phase shifts of the propagating light modes conditioned upon the state of an atom placed in a cavity, provide a mechanism both for the entangled-state preparations and for the error syndrome identifications. The distributed entangled pairs can then be used for quantum key distribution (QKD). In order to assess the performance of this repeater protocol, an explicit instance of RSBC--multi-component cat codes are studied quantitatively. A numerical simulation shows that the total fidelity and the success probability for quantum communication over a long distance (such as 1000km) both can almost approach unity provided a small enough elementary distance between stations (smaller than 0.1km or 0.01km) and rather low local losses (up to 0.1%) are considered. Secret key rates can become correspondingly high, both per channel use, beating the repeaterless bound, and per second thanks to the relatively high clock rates of the memoryless scheme. It is predicted from these results that a larger elementary distance might also keep both the fidelity and the success probability close to unity if higher-loss codes are employed. Based upon the cavity-QED setting, this scheme can be realized at room temperature and at optical frequencies.
Is My Perspective Better Than Yours? Blockchain Interoperability with Views

&lt;p&gt;Distributed ledger technology (DLT) provides decentralized and tamper-resistant data storage, replicated among mutually untrusting participants. With the advancement of this technology, different privacy-preserving blockchains have been proposed, such as Corda, Hyperledger Fabric, and Digital Asset's Canton. These distributed ledgers only provide \emph{partial consistency}, which implies that participants can view the same ledger differently. &lt;/p&gt; &lt;p&gt;A \emph{view} represents the states of a blockchain available to a particular stakeholder. The combination of views forms an integrated view that represents a consistent global state shared by all participants. &lt;/p&gt; &lt;p&gt;This paper introduces BUNGEE (Blockchain UNifier view GEnErator), the first DLT view generator, to allow capturing DLT snapshots, constructing views, and performing arbitrary operations on those, such as integrating views. Creating and integrating views allows interesting applications, such as stakeholder-centric snapshots for audits, cross-chain analysis, blockchain migration, and data analytics.&lt;/p&gt;
Latents2Segments: Disentangling the Latent Space of Generative Models for Semantic Segmentation of Face Images

With the advent of an increasing number of Augmented and Virtual Reality applications that aim to perform meaningful and controlled style edits on images of human faces, the impetus for the task of parsing face images to produce accurate and fine-grained semantic segmentation maps is more than ever before. Few State of the Art (SOTA) methods which solve this problem, do so by incorporating priors with respect to facial structure or other face attributes such as expression and pose in their deep classifier architecture. Our endeavour in this work is to do away with the priors and complex pre-processing operations required by SOTA multi-class face segmentation models by reframing this operation as a downstream task post infusion of disentanglement with respect to facial semantic regions of interest (ROIs) in the latent space of a Generative Autoencoder model. We present results for our model's performance on the CelebAMask-HQ and HELEN datasets. The encoded latent space of our model achieves significantly higher disentanglement with respect to semantic ROIs than that of other SOTA works. Moreover, it achieves a 13% faster inference rate and comparable accuracy with respect to the publicly available SOTA for the downstream task of semantic segmentation of face images.
Characterizing disruptions in online gaming behavior following software patches

Multiplayer online games are ideal settings for studying the effects of technological disruptions on social behavior. Software patches to online games cause significant changes to the game's rules and require players to develop new strategies to cope with these disruptions. We surveyed players, analyzed the content of software patch notes, and analyzed changes to the character selection behaviors in more than 53 million matches of Dota 2 in the days before and after software patches over a 30-month period. We found that the severity of patches is correlated with the magnitude of behavioral changes following a patch. We discuss the opportunities of leveraging software patches to online games as a valuable but overlooked empirical instrument for measuring behavioral dynamics.
The Impact of Green Innovation on Environmental Sustainability

The current research aimed to show the relationship between green innovation and environmental sustainability as the study assumes that green innovation contributes to environmental sustainability, and to test the research hypotheses, the researcher distributed (300) questionnaires to employees of the Al-Zawraa challenge site and received (295) questionnaires of which were valid for analysis (275) questionnaires and the advanced statistical program SmartPlS was used The research reached a set of conclusions, the most important of which is that green innovation has a moral impact on environmental sustainability. Furthermore, the study has made a set of recommendations, the most important of which is for bodies and institutions and all stakeholders to push for the promotion of green innovations to advance environmental sustainability.
Facial Recognition Technology and Ethical Issues

Facial recognition technology (FRT) is being adopted across the world with little thought given to the ethical and sustainability issues it faces. FRT must address these challenges as soon as possible to avoid repercussions. The issues of data privacy, security controls, and accuracy are discussed in this paper. To address the issues, a code of ethics is created and applied to Apple’s Face ID. It is found that Apple has made much progress, but still needs further improvement in its transparency of AI training.
DenseHybrid: Hybrid Anomaly Detection for Dense Open-set Recognition

Anomaly detection can be conceived either through generative modelling of regular training data or by discriminating with respect to negative training data. These two approaches exhibit different failure modes. Consequently, hybrid algorithms present an attractive research goal. Unfortunately, dense anomaly detection requires translational equivariance and very large input resolutions. These requirements disqualify all previous hybrid approaches to the best of our knowledge. We therefore design a novel hybrid algorithm based on reinterpreting discriminative logits as a logarithm of the unnormalized joint distribution $\hat{p}(\mathbf{x}, \mathbf{y})$. Our model builds on a shared convolutional representation from which we recover three dense predictions: i) the closed-set class posterior $P(\mathbf{y}|\mathbf{x})$, ii) the dataset posterior $P(d_{in}|\mathbf{x})$, iii) unnormalized data likelihood $\hat{p}(\mathbf{x})$. The latter two predictions are trained both on the standard training data and on a generic negative dataset. We blend these two predictions into a hybrid anomaly score which allows dense open-set recognition on large natural images. We carefully design a custom loss for the data likelihood in order to avoid backpropagation through the untractable normalizing constant $Z(\theta)$. Experiments evaluate our contributions on standard dense anomaly detection benchmarks as well as in terms of open-mIoU - a novel metric for dense open-set performance. Our submissions achieve state-of-the-art performance despite neglectable computational overhead over the standard semantic segmentation baseline.
Neural Network Equalization for Asynchronous Multitrack Detection in TDMR

The advent of multiple readers in magnetic recording opens the possibility of replacing the current industry's single-track detection with the more promising multitrack detection architectures. We have proposed a first solution, a generalized partial-response maximum-likelihood (GPRML) architecture, that extends the conventional PRML paradigm to jointly detect multiple asynchronous tracks. In this paper, we propose to replace the conventional communication-theoretic multiple-input multiple-output equalizer in the GPRML architecture with a neural network equalizer for better adaption to the nonlinearity of the underlying channel. We evaluate the proposed equalization strategy on a realistic two-dimensional magnetic-recording channel, and find that the proposed equalizer outperforms the conventional linear equalizer, by a 35% reduction in the bit-error rate.
Some Features of Teaching a Foreign Language in an Economic University in Modern Conditions: Achievement Motivation

In the presented article, the author, in search of overcoming the negative trends that have arisen in the educational environment in our time, reducing the ability of students to concentrate on a particular topic for a long time and memorize, draws attention to the need to additionally motivate students in a foreign language class at a non-linguistic university when teaching economic specialties. The possibility of motivating students through achievement motivation is considered, which can contribute to the achievement of the goals set by the university and to the formation of the personality of the future specialist.
Minyak Zaitun Sebagai Pengganti xylene pada Prosesing Jaringan Histologis Untuk Pewarnaan Kulit dan Hepar Mencit dengan Hematoxylin Eosin: Sebuah Studi Perbandingan

Clearing results in histological processing can be affected due to tissue density and viscosity of the clearing agent. xylene is the most commonly used aromatic solvent for clearing agents and deparaffinizing agents in histopathology laboratories, but xylene is one of the most dangerous chemicals found in histology laboratories. Based on the dangers posed by xylene, a replacement material is needed. Several xylene substitutes such as reagents derived from limonene, aliphatic hydrocarbons, vegetable oils and mineral oils have been commercially developed, but the available xylene substitutes are still less effective, more expensive, and still as dangerous as xylene itself. Substitutes that are considered safer are from natural oils, one of which is olive oil which has similarities with xylene, namely in hydrocarbon and phenol compounds. This study used two types of tissue, namely skin and liver from mice (Mus musculus) which were cut into two parts; the first part uses xylene as and the other part uses olive oil as a clearing agent. The assessment of hematoxylin eosin staining results were determined based on the category of assessment of cell structure, such as the cell nucleus, cytoplasm, and color uniformity carried out by three readers and five fields of view for each microscopic slide at 40X magnification of the objective lens. Comparison of observations of the xylene group in skin and liver tissue 100% got a good score on the cell nucleus, cytoplasm, and color uniformity. (p=1,000). The olive oil group had a slight difference in color uniformity in liver tissue when compared to skin, but not statistically different (p=0.773). The comparison of the overall readings of the xylene and olive oil groups on skin and liver tissue also showed no statistically different (p=0.262). So it can be concluded that olive oil can be recommended as a substitute for xylene in the clearing process in histological tissue processing.
Working Memory and Language

Working memory (WM) is our limited-capacity storage and processing (memory) system that permeates essential facets of our cognitive life such as arithmetic calculation, logical thinking, decision-making, prospective planning, language comprehension, and production. Since the very inception of WM in the early 1960s (Miller et al., 1960), its role in language acquisition and processing has been extensively investigated both empirically and theoretically by researchers from diverse fields of psychology and linguistics, accumulating an increasingly huge body of literature (e.g., see Baddeley, 2003; Gathercole & Baddeley, 1993 for reviews of early studies). Notwithstanding, the field still lacks a comprehensive and updated profile of conceptualizing and implementing working memory in the broad domains of native and second language acquisition, processing, impairments, and training. In this chapter, we introduce a comprehensive handbook in which key areas of inquiry and practice in working memory and language are at the forefront and theoretical ingenuity and empirical robustness are integrated throughout.
PENGEMBANGAN KOMIK BERBASIS KARAKTER SEBAGAI BAHAN AJAR PADA MATERI DAMPAK PENCEMARAN LINGKUNGAN BAGI KEHIDUPAN

AbstractThe research aims to develop the character-based comic that possible to use learning material the research also aims to determinal the responses of students about the comic. The research from is Research and Develop(R&amp;D) which adopted from model of development of Kemp. The subjects of the research are the character-based comic learning materials that are tested to students of grade VII SMPIT AL MUMTAZ and are taked 18 students in every class who have high ability, medium ability and low ability. Data collection instruments in this research are the aligibility questionnaire and student response questionnaire. The result of data processing showed that the character-based comics have a very valid of worthiness of content (92.85%), presentation feasibility(92.5%), language feasibility (83.33%), graphic feasibility (91.66%) and media feasibility (97.5%). The result of student’s responses showed that the learning material has very high interpretasions with total score of 86.73%. Thus, character-based comic can be used as to support the learning process.
The Use of Storytelling in Teaching a Foreign Language in Universities

This article dwells on storytelling as a technique of teaching foreign languages, as well as its features, advantages, and provides information about the origin and development of this technique in the context of education development in general. The modern demand of society for constantly improving educational methods involves taking into account various factors and students’ needs. Storytelling is a universal technique suitable for any level and age of students, it develops critical thinking, improves teamwork skills, motivates students, helps improve intercultural communication skills, and also allows the teacher to explain complex material in an interesting and accessible way. Storytelling also creates conditions for students for the complex development of four types of activities: listening, speaking, reading, writing.
New Algorithms and Software for Significance Controlled Variable Selection

Stepwise regression algorithms have been widely used for a variety of applications and continue to be a fundamental tool in variable selection. Most functions available in statistical software packages deliver models that may contain insignificant predictors because of the criterion of the optimization at each step. Here we introduce an R package that provides the user with several measures of the prospective model at each step of the algorithm. These prospective models are checked with multiple testing p-value corrections such as Bonferroni and False Discovery Rate and hence the algorithm's final model includes only predictors that have their significance controlled by the choice of correction type and alpha level. Moreover, the steps forward or backward can have an entry or drop criterion that is a combination of the p-values of prospective models. We illustrate the functionality of the package with examples and simulations.
Approximate Analytical Solution of Unstable Ordinary Differential Equation Using Differential Evolution Algorithm

The application of evolutionary optimization algorithms in problem solving is currently gaining wide popularity. Use of Differential Evolution (DE) algorithm in obtaining analytically approximate solution of unstable second order initial value Ordinary Differential Equation (ODE) is presented in this work. The methodology involves solving an associated problem of optimization with con-strains to get an analytically approximate solution for the ODE under consider-ation. Three test cases were used to demonstrate the efficiency of our method. In comparison with other methods discussed in the literature, our method gave significant improvement on the accuracy of the obtained results.
Plan Execution for Multi-Agent Path Finding with Indoor Quadcopters

We study the planning and acting phase for the problem of multi-agent path finding (MAPF) in this paper. MAPF is a problem of navigating agents from their start positions to specified individual goal positions so that agents do not collide with each other. Specifically we focus on executing MAPF plans with a group of Crazyflies, small indoor quadcopters . We show how to modify the existing continuous time conflict-based search algorithm (CCBS) to produce plans that are suitable for execution with the quadcopters. The acting phase uses the the Loco positioning system to check if the plan is executed correctly. Our finding is that the CCBS algorithm allows for extensions that can produce safe plans for quadcopters, namely cylindrical protection zone around each quadcopter can be introduced at the planning level.
Data Openstreetmap Untuk Memetakan Aksesibilitas Spasial dan Jangkauan Pelayanan Dasar Pendidikan dan Kesehatan di Kota Semarang

Accessibility and range of services are important aspects in order to measure the government administration in providing basic services for its people. Network analysis is used to identify current services locations within the city of Semarang in order to increase the level of service facilities. The use of the OpenStreetMap database which is rich in spatial information is able to map in detail the coverage of basic services for education and healthcare in the city of Semarang. Therefore with the use of geographic information system technology, it can be a monitoring and evaluation tool that is appropriate for policy makers in formulating public policies.