Reviewerly/exHarmony huggingface dataset:
Using Machine Translation Error Identification to Improve Translation Students’ Post-Editing Skills

Attempts to investigate challenges facing translation students in post-editing remain limited in literature. This research investigates a common challenge observed during post-editing training using SDL Trados 2021 which is deciding whether to post-edit MT output or translate from scratch. Making such decisions by translation students may need more focused procedures and criteria to improve this decision-making capability. The current research suggests integrating MT error identification proposed by Daems J, Vandepitte S, Hartsuiker RJ and Macken L (2016) as a basic criterion to undertake post-editing process and tested its effects on improving their performance in post-editing process regarding decision making and time consumed. A quasi- experimental approach was adopted, and the experiment was applied on thirty (30) translation students at university level divided into a control group and an experimental group. A pre-test was given to both groups to identify both performance and time consumed in the post-editing process. MT error identification techniques and Statistical MT error types were introduced in a five-day workshop using a task-based approach to instruct the experimental group. The control group received traditional post-editing training with no focus on MT error types. A post-test was administered to both groups to test the improvement in post-editing skills. The findings showed the significant improvement in students’ post-editing skills. This research would contribute to enhancing translation training courses provided to cope with the continuous advancement in translation technologies and market needs.
Design of Sales Accounting Information System Using EMKM Accounting Standard

This study intends to design a sales accounting information system for UMKM Toko Utara Game. The purpose of this study is to design a sales information system with EMKM standards at Toko Utara Game that can be implemented as one of the human error risk management that might occur if the system is run conventionally and not computerized. The research method used in this study is a descriptive research method, in which the author analyzes and describes events that occur in the present with the intention of overcoming problems that occur at Toko Utara Game. The types of data used in this research are primary data and secondary data. Data collection techniques used in this study were interviews, observation and literature studies. The results of interviews and observations are used as primary data and the results of literature studies are used as secondary data. The system development methodology used in this study is the prototyping method with an object-oriented system design method using UML (Unified Modeling Language). The system design made in this study is a Use Case Diagram, an Activity Diagram, and uses an Entity Relationship Diagram (ERD). At the stage of creating the program code, researchers used the Java and MYSQL programming languages which were poured into the NetBeans IDE8.1 software using XAMPP as a web server. The result of this implementation is the design of a web-based sales application so that Toko Utara Game sales management can be computerized properly.
ReScan: A Middleware Framework for Realistic and Robust Black-box Web Application Scanning

Black-box web vulnerability scanners are invaluable for security researchers and practitioners.Despite recent approaches tackling some of the inherent limitations of scanners, many have not sufficiently evolved alongside web browsers and applications, and often lack the capabilities for handling the inherent challenges of navigating and interacting with modern web applications.Instead of building an alternative scanner that could naturally only incorporate a limited set of the wide range of vulnerability-finding capabilities offered by the multitude of existing scanners, in this paper we propose an entirely different strategy.We present ReScan, a scanner-agnostic middleware framework that transparently enhances scanners' capabilities by mediating their interaction with web applications in a realistic and robust manner, using an orchestrated, fully-fledged modern browser.In essence, our framework can be used in conjunction with any vulnerability scanner, thus allowing users to benefit from the capabilities of existing and future scanners.Our extensible and modular framework includes a collection of enhancement techniques that address limitations and obstacles commonly faced by state-ofthe-art scanners.Our experimental evaluation demonstrates that despite the considerable (and expected) overhead introduced by a fully-fledged browser, our framework significantly improves the code coverage achieved by popular scanners (168% on average), resulting in a 66% and 161% increase in the number of reflected and stored XSS vulnerabilities detected, respectively.
Trellis: Robust and Scalable Metadata-private Anonymous Broadcast

Trellis is a mix-net based anonymous broadcast system with cryptographic security guarantees.Trellis can be used to anonymously publish documents or communicate with other users, all while assuming full network surveillance.In Trellis, users send messages through a set of servers in successive rounds.The servers mix and post the messages to a public bulletin board, hiding which users sent which messages.Trellis hides all network-level metadata, remains robust to changing network conditions, guarantees availability to honest users, and scales with the number of mix servers.Trellis provides three to five orders of magnitude faster performance and better network robustness compared to Atom, the state-of-the-art anonymous broadcast system with a similar threat model.In achieving these guarantees, Trellis contributes: (1) a simpler theoretical mixing analysis for a routing mix network constructed with a fraction of malicious servers, (2) anonymous routing tokens for verifiable random paths, and (3) lightweight blame protocols built on top of onion routing to identify and eliminate malicious parties.We implement and evaluate Trellis in a networked deployment.With 64 servers located across four geographic regions, Trellis achieves a throughput of 220 bits per second with 100,000 users.With 128 servers, Trellis achieves a throughput of 320 bits per second.Trellis's throughput is only 100 to 1000× slower compared to Tor (which has 6,000 servers and 2M daily users) and is therefore potentially deployable at a smaller "enterprise" scale.Our implementation is open-source.
Breaking and Fixing Virtual Channels: Domino Attack and Donner

Payment channel networks (PCNs) mitigate the scalability issues of current decentralized cryptocurrencies.They allow for arbitrarily many payments between users connected through a path of intermediate payment channels, while requiring interacting with the blockchain only to open and close the channels.Unfortunately, PCNs are (i) tailored to payments, excluding more complex smart contract functionalities, such as the oracleenabling Discreet Log Contracts and (ii) their need for active participation from intermediaries may make payments unreliable, slower, expensive, and privacy-invasive.Virtual channels are among the most promising techniques to mitigate these issues, allowing two endpoints of a path to create a direct channel over the intermediaries without any interaction with the blockchain.After such a virtual channel is constructed, (i) the endpoints can use this direct channel for applications other than payments and (ii) the intermediaries are no longer involved in updates.In this work, we first introduce the Domino attack, a new DoS/griefing style attack that leverages virtual channels to destruct the PCN itself and is inherent to the design adopted by the existing Bitcoin-compatible virtual channels.We then demonstrate its severity by a quantitative analysis on a snapshot of the Lightning Network (LN), the most widely deployed PCN at present.We finally discuss other serious drawbacks of existing virtual channel designs, such as the support for only a single intermediary, a latency and blockchain overhead linear in the path length, or a non-constant storage overhead per user.We then present Donner, the first virtual channel construction that overcomes the shortcomings above, by relying on a novel design paradigm.We formally define and prove security and privacy properties in the Universal Composability framework.Our evaluation shows that Donner is efficient, reduces the onchain number of transactions for disputes from linear in the path length to a single one, which is the key to prevent Domino attacks, and reduces the storage overhead from logarithmic in the path length to constant.Donner is Bitcoin-compatible and can be easily integrated in the LN.
MiniPI: Minimizing Power Imbalance among Stakeholders for Quality Software Product

The role of requirements elicitation is crucial in the software requirement engineering process as the requirement engineer has to extract the accurate requirements from different stakeholders. However, the problem emerges when the requirement team could not prioritize the extracted requirements because the requirement’s nature may vary as different categories of stakeholders have their own perspectives. This ultimately produces a power imbalance among stakeholders. Therefore, minimizing the power imbalance of software requirements among different categories of stakeholders is fundamentally important for a quality software product. Although many contributions have been made to this subject in the past, there is still a research gap available for minimizing the power imbalance among stakeholders. In this paper, we present a novel approach for minimizing the effects of power imbalance by age-sampling among different categories of stakeholders into three groups and then by age-mapping the requirements. After gathering questionnaires from stakeholders, the concerned parties determine the attributes of the Kano model through the filled Kano’s questionnaires and afterward, the satisfaction index is calculated by taking the values of the relevant age group into account, which eventually minimizes the power imbalance among stakeholders. In order to verify our methodology, we have performed quantitative analysis by calculating index values and applied verified Kano’s satisfaction formula to calculate the overall satisfaction index which improves the quality level of a software product.
Recognize The Alphabet of Fingerspelling Using Statistical Classifiers to Facilitate Communication Between Hearing-Impaired Persons and Others

The predominant method of communication for hearing-impaired and deaf people is still sign language. It is a carefully constructed hand gesture language, and each motion denotes a certain meaning. The purpose of this paper is to create a system for Arabic Sign Language automatic translation. The proposed Arabic sign to Text System consists of five primary stages and serves as a translator for deaf and dumb persons and normal people to improve communication. This system depends on building a two datasets image features for Arabic sign language gestures alphabets from two resources: the Arabic Sign Language dictionary and gestures from different signers' humans. It also uses gesture recognition techniques, which lets the user interact with the outside world. Video and images capture, Video and images processing, Hand Signs construction, classification, and finally text transformation and interpretation. In this paper, we use a set of appropriate features in step hand sign construction and classification of based on different classification algorithms such as (KNN, MLP and C4.5) and compare these results to get better classifier. This system offers a novel technique of hand detection that detects and extracts hand gestures of Arabic Sign from Image or Video..
Blockchain Applications: The Impact of a Firm's Choice of Financial Accounting System on Nonprofessional Investor Judgment and Decision-Making

Blockchain technologies have the potential to revolutionize business processes and financial reporting. This study explores how blockchain implementation impacts nonprofessional investor perceptions of transparency and investment decision-making. We conduct an online experiment with 236 nonprofessional investor participants and find that type of financial accounting system differentially affects various antecedents of nonprofessional investor’s intentions to buy or sell shares in a firm. Specifically, when firms employ a traditional accounting system, perceived signal credibility affects perceived investment quality. When firms employ a blockchain-based accounting system, transparency and perceived asymmetries of information influence perceptions of firm trustworthiness, both directly and indirectly. In all cases, perceived investment quality and trustworthiness influence intentions to buy/sell shares. This study provides initial evidence about the potential impact of blockchain technology on nonprofessional investor decision-making.
Guilt Detection in Text: A Step Towards Understanding Complex Emotions

Abstract We introduce a novel Natural Language Processing (NLP) task called Guilt detection, focused on detecting guilt in text. We identify guilt as a complex and important emotion that has not been studied in NLP before, and we aim to provide a more fine-grained analysis of it. To address the lack of publicly available corpora for guilt detection, we create a dataset called VIC, which contains 4622 texts from three existing emotion detection datasets that we binarize into guilt and no-guilt classes. We experiment with traditional machine learning methods using bag-of-words and term frequency-inverse document frequency features, achieving a 72% f1 score with the highest-performing model. Our study provides a first step towards understanding guilt in text and opens the door for future research in this area.
Spectroscopic estimation of the photon number for superconducting Kerr parametric oscillators

Abstract Quantum annealing (QA) is a way to solve combinational optimization problems. Kerr nonlinear parametric oscillators (KPOs) are promising devices for implementing QA. When we solve the combinational optimization problems using KPOs, it is necessary to precisely control the photon number of the KPOs. Here, we propose a feasible method to estimate the photon number of the KPO. We consider coupling an ancillary qubit to the KPO and show that spectroscopic measurements on the ancillary qubit provide information on the photon number of the KPO.
AI-Powered Archaeology: Determining the Origin Culture of Various Ancient Artifacts Using Machine Learning

This paper attempts to determine the degree of accuracy to which we can originate and classify ancient artifacts using AI. It compares the performance of two CNN models (InceptionResNetV2, and a VGG-19) on a specially curated dataset of 55,000 ancient artifact images belonging to over 343 different cultures. The dataset consists of samples from different regions all over the world, and is built using the British Museum’s online collection of over 3 million artifact images. For training the CNNs, an NVIDIA RTX A6000 GPU was used on a cloud computing platform, achieving high accuracy for both models. Two trials were run for the InceptionResNetV2 model, which achieved a final validation accuracy of 65 percent for its best trial. The VGG-19 performed poorly on the dataset, only achieving a 12.95 percent validation accuracy. Afterwards, the models obtained from both InceptionResNetV2 trials were evaluated on a set of artifacts of unknown origin, coming up with surprising results and providing insight into how effective image recognition can be in the field of archaeology.
[Review] Criminology review of the crime of gambling case in Batam City

Along with the development of technology has an impact on all aspects of life. Technological developments also have an impact on gambling crimes, one of which is Gelper gambling or an electronic game arena located in Batam City. Although many gambling places have been closed by the police, until now there are still some spots. Gambling is an activity that is prohibited and regulated in Law no. 303 of the Criminal Code. Gambling is a game of luck or chance. Because in gambling cases, players don't need certain abilities to play. Therefore, if there are players who experience victory it is a factor of luck and not of ability. This study discusses the Criminological Review of gambling in the Batam City Police Legal area. The purpose of this study is to find out what factors are the causes of the spread of gambling on the game arena and what efforts are being made to overcome it. This research uses a qualitative descriptive method with a sociological juridical approach. With the aim of obtaining accurate information in accordance with the gambling phenomenon that occurs in society in Batam City. And also explained about the laws that apply to players and owners of gambling in Batam City. With the aim of obtaining accurate information in accordance with the gambling phenomenon that occurs in society in Batam City.
Error Model and Two-Phase Correction Method for Indirect Illumination

Phase shifting profilometry (PSP) has the advantages of high accuracy, spatial resolution, and anti-noise ability. However, in addition to random noise, indirect illumination, such as subsurface scattering, inter-reflection, and volume scattering, often occurs in the actual measurement environment, seriously affecting the system accuracy. In this paper, a sine series model (SSM) is proposed to simulate the error, which significantly simplifies the computational work. Based on the sine series model, a two-phase correction method (TPC) is proposed, where two phases with different frequencies are adopted to suppress the interference caused by indirect illumination and random noise. Moreover, by combining the multi-wavelength method to unwrap phase, TPC does not need to project additional patterns. Contrast experiments demonstrate that the proposed TPC method has the performance of reducing the error by 40.8%.
Hand-eye Calibration of Industrial Robots with 3D Cameras based on Dual Quaternions

In this paper, a hand-eye calibration method with the 3D depth camera is proposed. A set of 3D cube-shaped calibrators are designed, which facilitates the obtainment of the coordinates of the calibration points of these calibrators. Using the point-to-point correspondence between, a registration method is employed to calculate the pose transformation matrix of the object relative to the camera coordinate system under different camera. Constraint equations are formulated based on the positional transformation matrix, and then the hand-eye relation is solving by using dual quaternions and singular value decomposition. Experimental results show that the proposed method achieves higher accuracy, and the calibration process is more convenient for practical application.
3D Path Planning of Unmanned Aerial Vehicle Based on Improved Grey Wolf Optimization Algorithm

Aiming at the problem of unmanned aerial vehicle’s(UAV) path planning in complex battlefield environment, this paper proposes an improved grey wolf optimization algorithm (IGWO). UAV path planning is to plan the flight path from the starting point to the target point under the conditions of ensuring the best performance and satisfying different constraints. Based on the traditional GWO algorithm, this paper proposes two improvements: adjusting the decay form of the convergence factor, and re-updating the location according to weighted sum of ϕ, φ, χ. Furthermore, under the consideration of various constraints, a 3D path planning strategy for UAV based on IGWO is constructed to obtain the UAV path with the optimal comprehensive performance. Finally, the comparative simulations with three other algorithms are carried out. The simulation result shows that IGWO can be implemented for achieving optimal UAV path planning, and IGWO outperforms the other three optimization algorithms.
Analysis of connectivism as a tool for posthuman university classrooms

In the posthuman era, teaching and learning through technologies are becoming increasingly important, most especially in the university system. Connectivism, a theory of learning that emphasises the importance of connections between people and information, is one of the most influential educational philosophies driving today’s educational dynamism. In a posthuman world, where technology is constantly evolving and becoming more sophisticated, connectivism is argued to provide a framework for understanding how students learn and how can technology be used to facilitate learning. This study argues that connectivism is one of the ways in which classroom stakeholders can be made to prepare for the posthuman era. The study is located within the transformative paradigm to enable the researcher to tailor the argument toward transforming the university classrooms towards developing a new way of thinking about society's present social boundaries by pursuing truth within a postmodern framework. In the same vein, conceptual analysis was adopted to make sense of the argument since it helps to interoperate and dismantle complex and ambiguous concepts toward meaning-making. The analysis begins by presenting connectivism and its potential assumptions. The assumptions were juxtaposed with the posthuman agenda by arguing the relationship between posthumanism and connectivism and lastly, how it prepares classroom stakeholders for building students’ capacity ahead of the emerging interaction between human (students) and non-human (technologies). The study concludes that connectivism viewpoint is one of the unavoidable philosophies of the future.
Borderless Curriculum in the Post-Human Era: Reflections on the United States of America and South African Initial Teacher Pedagogical Practices

This paper interrogates the opportunities and challenges of a borderless curriculum as the alternative to reimagine a better future premised on initial teacher education. The paper comes against the background that curriculum projects remain nationalised, depriving learners and educators of an opportunity to learn from the best educational practices outside their borders. The paper is located in posthumanism, where a borderless curriculum through technology can be positioned to respond positively to human tragedies such as war, systematic racism, human trafficking and conflict. Borderless curriculum involves unlearning in order to learn by harvesting best practices across borders to reimagine a comprehensive initial teacher education that addresses the lived realities of the learners globally. The paper argues that the posthuman era provides a platform for nations to share knowledge in the virtual and blended space to deconstruct prejudices while evoking living and working together across curriculum and spaces to improve initial teacher education.