Reviewerly/exHarmony huggingface dataset:
Predictive modeling of PV solar power plant efficiency considering weather conditions: A comparative analysis of artificial neural networks and multiple linear regression

This study investigates the surface parameters and environmental factors affecting the energy production of a 500 kWp photovoltaic (PV) solar power plant in Igdir province. Using both the PV panel characteristics and the weather conditions specific to the power plant location, a total of 7 detailed features were included. The estimation of the power plant efficiency, a novel contribution not found in previous studies, is also a major focus. The performance evaluation of different models, including feed-forward neural networks and multiple linear regression, demonstrates the effectiveness of artificial neural networks in capturing the complex relationships between features and efficiency despite limited data availability. Principal Component Analysis (PCA) was used to reduce feature dimensions, showing that even with a reduced feature set, accurate efficiency prediction is still achievable. Prediction using PCA is one of the novelties of the paper. The effects of solar irradiation, module power, and module temperature on power plant efficiency are revealed. The results provide valuable insights for optimizing energy investments in the Igdir region and highlight the potential of artificial neural networks in energy forecasting, demonstrating their suitability for capturing complex patterns in solar power plant efficiency.
Short-Term Solar Irradiance Forecasting Using Deep Learning Techniques: A Comprehensive Case Study

Reliable estimation of solar irradiance is required for many solar energy applications such as photovoltaics, water heating, cooking, solar microgrids, etc. Deep Learning techniques have shown outstanding behaviour for analysing complex datasets efficiently with high accuracy. Multi-Layer Perceptron, Long-Short Term Memory, and Gated Recurrent Unit techniques are found to be the most competitive techniques in the literature for solar irradiance forecasting. Therefore, in this study, a comparative analysis of those models is carried out using eleven years of NASA satellite data for training and testing. The grid search technique is used to optimize the networks architectures to ensure the best performance of the models for forecasting daily global solar irradiance. The results show that all models have almost the same accuracy with a mean square error close to 0.017 kWh/m2/day. However, the speed of training and the complexity differ for each model. The MLP is found to be the most efficient model due to using a low number of parameters. The study is of importance for reliable solar irradiance forecasting for any location worldwide.
How to Wire a <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:mn>1000</mml:mn></mml:math> -Qubit Trapped-Ion Quantum Computer

One of the most formidable challenges of scaling up quantum computers is that of control-signal delivery. Today’s small-scale quantum computers typically connect each qubit to one or more separate external signal sources. This approach is not scalable due to the input/output (I/O) limitations of the qubit chip, necessitating the integration of control electronics. However, it is no small feat to shrink control electronics into a small package that is compatible with qubit-chip fabrication and operational constraints without sacrificing performance. This so-called “wiring challenge” is likely to impact the development of more powerful quantum computers even in the near term. In this paper, we address the wiring challenge of trapped-ion quantum computers. We describe a control architecture called WISE (Wiring using Integrated Switching Electronics), which significantly reduces the I/O requirements of ion-trap quantum computing chips without compromising performance. Our method relies on judiciously integrating simple switching electronics into the ion-trap chip—in a way that is compatible with its fabrication and operation constraints—while the complex electronics remain external. To demonstrate its power, we describe how the WISE architecture can be used to operate a fully connected 1000-qubit trapped-ion quantum computer using approximately 200 signal sources at a speed of approximately 40–2600 quantum gate layers per second.9 MoreReceived 28 May 2023Accepted 28 August 2023DOI:https://doi.org/10.1103/PRXQuantum.4.040313Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasAtom & ion trapping & guidingQuantum computationQuantum information processingPhysical SystemsIonsQuantum Information, Science & TechnologyAtomic, Molecular & Optical
RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation

Fengji Zhang, Bei Chen, Yue Zhang, Jacky Keung, Jin Liu, Daoguang Zan, Yi Mao, Jian-Guang Lou, Weizhu Chen. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. 2023.
A Framework for Developing Collaborative Training Environments for Assembling

Abstract 120th ASEE Annual Conference and Exposition Atlanta, Georgia, USA, June 23-26, 2013 A Framework for Developing Collaborative Training Environments for AssemblingAbstractState-of-the-art 3D video games can provide their users with a near-real experience from visual,audio and interactivity perspectives. Numerous efforts have been made to take advantage ofthese favorable characteristics for educational purposes. The majority of these projects focusedeither on the reconstruction of certain scenarios, for instance for fire, earthquake or floodemergency response training, driver or pilot training, medical training, or on the realisticsimulation of real environments, such as virtual museum tours and virtual architectural tours.However, only recently have attempts been made to develop virtual engineering trainingenvironments, since they require the assembly of different types of individual components intopotentially complex systems and involve interactions between multiple participants and modelsof physical devices.In this article, a framework for developing collaborative environments for mechanical assemblytraining based on a commercial computer game engine will be introduced. Such environmentsnot only maintain the feel of immersion of a 3D game, but also emphasize realistic physicaldevice management and control. In this context, the trainees are enabled to manage a largevariety of mechanical components, assemble them according to engineering requirements orpotentially disassemble them. Also, the instructors can monitor the entire assembly process andautomatically collect performance statistics. Therefore, such environments have the potential tobecome valuable workforce development tools that enable their users to acquire practical skillsfor assembling a variety of electro-mechanical systems for the purpose of manufacturing,maintenance and repair.
Library Collections and Distance Information: New Models of Collection Development for the 21st Century

Contemporary collection development policies must continue to be updated to reflect the actual practices and changes in the traditional building of local collections. They must also reflect the decisions that have been made to share collections through cooperative resource-sharing agreements, or to reveal the growing transconsortial pressure of coordinating or funding agencies towards managed information and instructional programs. Collection policies must recognize the evolving reliationships between physical and digital information sources, and the creation of truly new multimedia or compound information objects that include text, graphics, sound, video and multi-dimensional animation-hyperlinked on a global basis
Intentional and Performative Persuasion: The Linguistic Basis for Criminalizing the (Direct and Indirect) Encouragement of Terrorism

Abstract Article 5 of the Council of Europe Convention on the Prevention of Terrorism requires member states to criminalise ‘public provocation to commit a terrorist offence’. In the U.K., the realisation of this obligation is found in the ‘Encouragement of terrorism’ offence contained in section 1 of the Terrorism Act 2006. As well as fulfilling the U.K.’s treaty obligation, this offence was intended to stop the spread of violent extremist ideology. Although the compatibility of this offence with the right to freedom of expression enshrined in Article 10 of the European Convention on Human Rights has been queried, both the domestic courts and the European Court of Human Rights have held that it complies with Article 10’s demands. So, instead of taking Article 10 as its starting point, this article draws instead on work from the field of linguistics: namely, speech act theory (SAT). By using insights from SAT, and by examining some of the linguistic strategies that may be used to encourage acts of terrorism, the article seeks to advance the legal understanding of the concept of encouragement. In particular, the article draws out two features of encouragement that have important implications for the appropriate boundaries of the encouragement of terrorism offence -encouragement is intentional and it is performative - and argues that, as currently drafted, the offence does not reflect the nature of encouragement as an intentional activity. The article concludes by drawing out from its analysis a series of proposed amendments that together address the rights-based concerns about the offence whilst maintaining its effectiveness as a counterterrorism tool.
Innovations of Phishing Defense: The Mechanism, Measurement and Defense Strategies

Now-a-days, social engineering is considered to be one of the most overwhelming threats in the field of cyber security. Social engineers, who deceive people by using their personal appeal through cunning communication, do not rely on finding the vulnerabilities to break into the cyberspace as traditional hackers. Instead, they make shifty communication with the victims that often enable them to gain confidential information like their credentials to compromise cyber security. Phishing attack has become one of the most commonly used social engineering methods in daily life. Since the attacker does not rely on technical vulnerabilities, social engineering, especially phishing attacks cannot be tackled using cyber security tools like firewalls, IDSs (Intrusion Detection Systems), etc. What is more, the increased popularity of the social media has further complicated the problem by availing abundance of information that can be used against the victims. The objective of this paper is to propose a new framework that characterizes the behavior of the phishing attack, and a comprehensive model for describing awareness, measurement and defense of phishing based attacks. To be specific, we propose a hybrid multi-layer model using Natural Language Processing (NLP) techniques for defending against phishing attacks. The model enables a new prospect in detection of a potential attacker trying to manipulate the victim for revealing confidential information.
Benchmarks for Pathfinding in 3D Voxel Space

The problem of finding optimal paths in 3D space is computationally more complex than in a 2D plane. While a range of different approaches have been developed across different fields, there has been relatively little work studying the complexities and tradeoffs of implementations for path planning in 3D space. This paper describes the 3D path planning problem faced in the game Warframe. The solution used by industry was tuned for their own constraints, but little is known about the applicability of other approaches to solving this problem. Thus, the makers of this game have made their underlying planning data available for researchers to use. This paper describes this new data set which is publicly available for study and dissemination.
Efficient and Secure Identity-based Strong Key-Insulated Signature Scheme without Pairings

Public Key Cryptosystem (PKC) completely relies under the assumption that user’s private key is absolutely secure. Exposure of private key may lead to disastrous situations in the communication network. To diminish the damage of private key exposure in PKC, key-insulation mechanism was introduced. In key-insulated cryptosystems, a user can update his private key with the help of a physically secure device from time to time. Identity-based cryptosystem alleviates the heavy certificate management problems in traditional PKC. Recently, many Identity-based key insulated signature schemes have been proposed in literature; however, most of the Identity-based schemes are designed based on the expensive bilinear pairing operation over elliptic curves. Due to the heavy computational cost of a pairing, the pairing based schemes are less efficient in practice. In order to improve the computational and communicational efficiency and to resist the problem of private key exposure in Identity-based signature schemes, we present a pairing-free key insulated signature scheme in identity based setting. We show that this scheme is unforgeable and achieves strong key insulation property with secure key updates, under the hardness of the Elliptic Curve Discrete Logarithm Problem (ECDLP). The performance analysis shows that our scheme is more efficient than the existing schemes.
Ammonia sorption outgassing and cross contamination ability of Entegris FOUPs evaluation and its volatile acids comparison

A comparative study was carried out to evaluate the capacity of two Entegris Front Opening Unified Pod (FOUP) polymers, PC and EBMCNT, to be contaminated by NH3, and the ability of these FOUPs to transfer ammonia to Cr-coated wafers. The results are compared to those previously published for molecular acids (HF and HCl) ranking the contaminant affinity to polymer as NH3 < HCl < HF; and the ability to outgas is set as NH3 > HCl > HF. The high outgassing ammonia concentrations are not directly related to a large contamination transfer to wafers since each phenomenon is predominantly governed by the solubility or diffusivity parameter respectively. This study has shown that EBMCNT FOUP is the best FOUP polymer tested. Finally, it was proven that PC FOUPs are not suitable in high ammonia environments because the polymer has a chemical reaction with the ammonia, causing it to degrade.
Usage, Retention, and Abandonment of Agile Practices: A Survey and Interviews Results

Background: A number of Agile maturity models (AMMs) have been proposed to guide software organizations in their adoption of Agile practices. Typically the AMMs suggest that higher maturity levels ...
Intelligent Security and Privacy of Electronic Health Records Using Biometric Images

&lt;P&gt;Background: In the presence of Cloud Environment and the migration of Electronic Health Systems and records to the Cloud, patient privacy has become an emergent problem for healthcare institutions. Government bylaws, electronic health documentation, and innovative internet health services generate numerous security issues for healthcare conformity and information security groups. To deal with these issues, healthcare institutes must protect essential IT infrastructure from unauthorized use by insiders and hackers. The Cloud Computing archetype allows for EHealth methods that improve the features and functionality of systems on the cloud. On the other hand, sending patients’ medical information and records to the Cloud entails a number of risks in the protection and privacy of the health records during the communication process. &lt;/P&gt;&lt;P&gt; Aim: In this paper, a solution is proposed for the security of Electronic Health Records (EHRs) in cloud environment during the process of sending the data to the cloud. In addition, the proposed method uses biometric images that allow for unified patient identification across cloud-based EHRs and across medical institutions. &lt;/P&gt;&lt;P&gt; Method: To protect the privacy of patients’ information and streamline the migration process, a watermarking-based method is proposed for health care providers to ensure that patients’ data are only accessible to authorized personnel. Patients’ information, such as name, id, symptoms, diseases, and previous history, is secured in biometric images of patients as an encrypted watermark. Results: Quality and impeccability analysis and robustness were performed to test the proposed method. The PSNR values show that the proposed method produced excellent results. Conclusion: The robustness and impressibility of the proposed method were tested by subjecting the watermarked images to different simulated attacks. The watermarks were largely impermeable to varied and repeated attacks.&lt;/P&gt;
Can we overcome the n log n barrier for oblivious sorting

It is well-known that non-comparison-based techniques can allow us to sort n elements in o(n log n) time on a Random-Access Machine (RAM). On the other hand, it is a long-standing open question whether (non-comparison-based) circuits can sort n elements from the domain [1..2k] with o(kn log n) boolean gates. We consider weakened forms of this question: first, we consider a restricted class of sorting where the number of distinct keys is much smaller than the input length; and second, we explore Oblivious RAMs and probabilistic circuit families, i.e., computational models that are somewhat more powerful than circuits but much weaker than RAM. We show that Oblivious RAMs and probabilistic circuit families can sort o(log n)-bit keys in o(n log n) time or o(kn log n) circuit complexity. Our algorithms work in the indivisible model, i.e., not only can they sort an array of numerical keys --- if each key additionally carries an opaque ball, our algorithms can also move the balls into the correct order. We further show that in such an indivisible model, it is impossible to sort Ω(log n)-bit keys in o(n log n) time, and thus the o(log n)-bit-key assumption is necessary for overcoming the n log n barrier.Finally, after optimizing the IO efficiency, we show that even the 1-bit special case can solve open questions: our oblivious algorithms solve tight compaction and selection with optimal IO efficiency for the first time.
Learning Programmatically Structured Representations with Perceptor Gradients

We present the perceptor gradients algorithm -- a novel approach to learning symbolic representations based on the idea of decomposing an agent's policy into i) a perceptor network extracting symbols from raw observation data and ii) a task encoding program which maps the input symbols to output actions. We show that the proposed algorithm is able to learn representations that can be directly fed into a Linear-Quadratic Regulator (LQR) or a general purpose A* planner. Our experimental results confirm that the perceptor gradients algorithm is able to efficiently learn transferable symbolic representations as well as generate new observations according to a semantically meaningful specification.
Design and Development of a Low-Cost Wearable Glove to Track Forces Exerted by Workers in Car Assembly Lines

Wearables are gaining widespread use and technologies are making it possible to monitor human physical activity and behaviour as part of connected infrastructures. Many companies see wearables as an opportunity to enhance worker safety since they can monitor their workers’ activity in real life scenarios. One of the goals of this technology is to integrate existing electronic components, such as sensors or conductors, in order to create fully wearable systems. This integration is constrained not only by technical factors but also by user requirements and internal company standards. This paper considers such constraints and presents preliminary research for the design of a wearable glove as a new tool to track forces exerted by workers in car assembly lines. The objective of the glove is to measure forces and compare these to maximum forces already identified by the company. Thus, the main objectives are to: (1) integrate the components based on the requirements of the users and the context of application, and (2) provide a new tool that can be used “in situ” to track workers. This study was carried out in close collaboration with Volkswagen through a human-centred iterative design process. Thus, this paper presents the development of a wearable device glove based on a specific design methodology where both the human and technological aspects are considered.
Hierarchical Image Semantics Using Probabilistic Path Propagations for Biomedical Research

Image segmentation is an important subtask in biomedical research applications, such as estimating the position and shape of a tumor. Unfortunately, advanced image segmentation methods are not widely applied in research applications as they often miss features, such as uncertainty communication, and may lack an intuitive approach for the use of the underlying algorithm. To solve this problem, this paper fuses a fuzzy and a hierarchical segmentation approach together, thus providing a flexible multiclass segmentation method based on probabilistic path propagations. By utilizing this method, analysts and physicians can map their mental model of image components and their composition to higher level objects. The probabilistic segmentation of higher order components is propagated along the user-defined hierarchy to highlight the potential of improvement resulting in each level of hierarchy by providing an intuitive representation. The effectiveness of this approach is demonstrated by evaluating our segmentations of biomedical datasets, comparing it to the state-of-the-art segmentation approaches, and an extensive user study.
Visual Calibration for Multiview Laser Doppler Speed Sensing

We present a novel calibration method for a multi-view laser Doppler speed sensing (MLDSS) system. In contrast with the traditional method where only the laser geometry is independently calibrated, the proposed method simultaneously optimizes all the laser parameters and directly associates the parameters with a motion sensing model. By jointly considering the consistency among laser Doppler velocimetry, the laser geometry and a visual marker tracking system, the proposed calibration method further boosts the accuracy of MLDSS. We analyzed the factors influencing the precision, and quantitatively evaluated the efficiency of the proposed method on several data sets.
Counteracting the contemporaneous proliferation of digital forgeries and fake news

Fake news has been certainly the expression of the moment: from political round table discussions to newspapers to social and mainstream media. It is everywhere. With such an intense discussion and yet few effective ways to combat it, what can be done? Providing methods to fight back even the least harming hoax is a social responsibility. To look for authenticity in a wide sea of fake news, every detail is a lead. Image appearance and semantic content of text and images are some of the main properties, which can be analyzed to reveal even the slightest lie. In this vein, this work overviews some recent methods applicable to the verification of dubious content in text and images, and discusses how we can put them together as an option to curb away the proliferation of unverified and phony "facts". We briefly present the main idea behind each method, highlighting real situations where they can be applied and discussing expected results. Ultimately, we show how new research areas are working to seamlessly stitch together all these methods so as to provide a unified analysis and to establish the synchronization in space and time - the X-Coherence of heterogeneous sources of information documenting real-world events.