Reviewerly/exHarmony huggingface dataset:
Intra- and All-Day PV Power Forecasting Using Expansion PDE Models Composed of the L-Transform Components in Nodes of Step-by-Step Evolved Polynomial Binary-Nets

Photovoltaic (PV) power is one of the most important energy sources available in backcountry regions or developing southern countries with missing infrastructure. Intra- or all-day statistical models, using the latest environmental and power data records, can predict PV power for a plant-specific location and condition on time. Numerical Weather Prediction (NWP) systems are run every 6 h to produce free prognoses of local cloudiness with a considerable delay and usually not in operational quality. Differential binomial neural networks (D-BNN) are a novel neurocomputing technique that can model the characteristics of the weather. D-BNN decomposes the n-variable Partial Differential Equation (PDE), allowing a complex representation of the near-ground atmospheric dynamics, into a set of 2-input node sub-PDEs. These are converted and substituted using the Laplace transform formulations of Operation Calculus. D-BNN produces applicable PDE components, one by one using the selected binary nodes to extend its sum models. Historical spatial data are examined to pre-assess daily training samples for a specific inputs->output time shift used in forecasting the Clear Sky Index. Iterative 1–9 h and 24-h sequence PV power prediction models using machine learning (ML) and statistics are compared and evaluated. Daily modelling allows for sequence predictions of full PV power (PVP) cycles in operational quality. Reliable PV forecasting is required in load management in plant power supply and consumption.
A Preliminary Study of Neural Correspondence to Intuitive Binary Decision through Electroencephalography

The cognitive process of decision-making is complicated and has different dimensions. It can be intuitive that is evolutionary, faster, and automatic, or analytic that is slower and logical. The understanding of the neural function of decision making is important because, decision making is a task that is needed in every aspect of life; and understanding it will help to investigate other cognitive functions like trust, emotions, and other socio-behavioral constructs. Over the years, different studies have been conducted to understand decision-making from different aspects, e.g., cognitive, behavioral, psychological, and neurological. Yet, the general mechanism of decision-making is to be understood. Though several fMRI and EEG study has been conducted on decision making, most of them- as per our knowledge- are in very specific contexts, which cannot be necessarily interpreted for any other situation in general. In our study, we address this issue and aim to investigate intuitive decision-making from a comparatively general situation. We considered delving into a binary decision-making situation for this purpose. We have used the go/no-go paradigm to represent an intuitive binary decision-making situation. Participants are told to make a decision to go or to no-go based on the presented visual stimuli. Then the signal is collected as Electroencephalography data and analyzed in the time domain to observe the latency and amplitude to understand the signal characteristics. It is observed that the frontal region is active while performing the intuitive decision-making task of the go/no-go context. Also, significant variation of signals is found among individual participants.
Survey of Pedestrian Trajectory Prediction Techniques Using Surveillance Videos

AI and computer vision are making strides everyday with newer solutions to real-world problems and emerging challenges. An extremely important and useful application of computer vision is surveillance systems for security in open or closed spaces. With this research work, we investigate state-of-the-art works for forecasting pedestrian trajectory using videos. We present a comprehensive review of literature and compare the various techniques along with their pros and cons that have been used for this application.
Agile Principle 7: “Working Software Is the Primary Measure of Progress”

Delivering valuable software frequently is the name of the game. As with the word “valuable,” the word “progress” means different things to different people. Developers define working software as software that functions. Customers define working software as software that has value. Progress toward valuable software is the only progress that matters to your customer. Vignettes from leaders at Centene, UScellular, Nokia, Amazon, and Oracle illustrate the challenge of defining what working softwareWorking software is, and how to apply the definition of working software in measuring progress. The most effective, efficient, and productive way for developers and business owners to stay in synch on the development of the product is through demos. Demos properly conducted elicit the feedback from business owners that influence the next sprints. Developers need to listen to the feedback, evaluate the feedback, determine the disposition of the feedback, and communicate decisions with the business owners who provided that feedback. The feedback loop is the generativeGenerative aspect of the demoDemo process.
Conclusion

Leadership is a social construct. It is conjunction, processual, and generative. It is best practiced with a keen eye and a kind heart.
Blockchain Initiatives Dynamics Regarding The Sustainable Development Goals

Using a public and open database, we analyze the dynamics of blockchain trends in relation to the United Nations' Sustainable Development Goals (SDGs). While the use of blockchains is natural for SDGs related to cross-border payments or supply chain management for instance, some SDGs have received significantly less attention. We provide a deep analysis of the interplay between SDGs and assess the absolute and relative dynamics of the attention received by all SDGs. In terms of infrastructure, we show that the share of projects using a public blockchain has recently been increasing. Nonetheless, too many projects are not transparent about their underlying infrastructure. Overall, our research can be used by policy makers to design efficient blockchain policies toward the achievement of the United Nations' SDGs.
Agile Principle 4: “Businesspeople and Developers Must Work Together Daily Throughout the Project”

Delivering valuable software frequently is the name of the game. Businesspeople and developers must be aligned on the objectives of the project. And they must be aligned on the deliverables due at each stage of the project. Priorities and deliverables can change, and this makes daily connection and daily alignment that much more important. When businesspeople and developers work together daily—when they commit to generative dialogue and meaningful progress—they create the products and solutions that matter most to their customer. Vignettes from leaders at Oracle, UScellular, and Amazon illustrate these leadership challenges. To ensure the development team makes progress every day, you as the leader must connect the businesspeople with your developers. Your team must commit to generativeGenerative dialogue. This dialogue will help ensure that your team gains insight from the businesspeople. The questions your team asks in this dialogue help achieve clarity. The team reaches alignment. The teams jointly prioritize and reprioritize as customer needs evolve and as the marketplace evolves. With insight, clarity, alignment, and prioritization, the team is positioned to make meaningful progress toward delivering valuable software quickly.
Agile Principle 1: “Our Highest Priority Is to Satisfy the Customer Through Early and Continuous Delivery of Valuable Software”

Delivering valuable software frequently is the name of the game. Developers and customers have different definitions of what constitutes value. You learn what “value” means to your customer by bringing her together with your team. You accomplish this through dialogue. The dialogue generates clarity of requirements and a common understanding of the process. Developing software that satisfies the quality, speed, and value expectations of customers is what matters most. This is what customers want and need, and this is what they are paying you for, so this is what you as the leader must deliver. Leaders of agile software development teams know that this is far easier said than done. It involves dialogue, iterative development, risks, and failures. Vignettes from leaders at Nokia, UScellular, and Centene Corporation illustrate these leadership challenges and how to address them. It begins with dialogue. You as the leader bring your agile software development team together with the business owner to establish and execute a sustainable, repeatable process for prioritizing requirements, defining what will satisfy the customer and how the customer will use the software solution, and defining what the customer deems valuable. The objective of joining the teams and executing the process is to generate solutions. Leaders overcome challenges by implementing a repeatable and sustainable process for generating solutions. Teams must agree on what “valuable” means and what “continuous” means. Answers aren’t revealed. Rather, solutions are generated, and they’re generated through dialogue.
Agile Principle 3: “Deliver Working Software Frequently, from a Couple of Weeks to a Couple of Months, with a Preference to the Shorter Timescale”

Delivering valuable software frequently is the name of the game. Your customer wants and needs solutions as quickly as you can deliver them. Solutions delivered late are less valuable than solutions delivered early. Customers want and need you to create valuable opportunities for them today, not tomorrow. Customers want and need you to solve their costly problems today, not tomorrow. Vignettes from leaders at Oracle, Amazon, and Nokia illustrate the objective, the challenges, and solutions relative to this principle. The most effective way to satisfy customers with valuable software sooner rather than later is to bring them along on the journey through the process of software demonstrations, or demos. Demos provide the opportunity for developers and customers to learn together and to co-create. Honest feedback that serves the objective of the project is imperative to progress. Acknowledging all feedback is imperative to maintaining trust. Honest and constructive feedback that is addressed by the development team generates progress toward the goal of delivering working software frequently.
Agile Principle 2: “Welcome Changing Requirements, Even Late in Development. Agile Processes Harness Change for the Customer’s Competitive Advantage”

Delivering valuable software frequently is the name of the game. Requirements will change throughout the lifecycle of your project. Some changes you will be able to accommodate sooner and faster than other changes. Requirements can change for several reasons: new information, clearer understanding, changing market dynamics. Your development process must not only allow for change, but encourage and generate change, so that the product you deliver is valuable to your customer at the time you deliver it. Customers require what is valuable; customers don’t require what was valuable last year. Vignettes from leaders at Centene Corporation, Oracle, Amazon, and Nokia illustrate the objective, the challenges, and solutions relative to this principle. Leaders will experience changing requirements throughout the development process. To address these challenges, leaders establish a repeatable, sustainable process for generative dialogue with their customer. The leader ensures roles and responsibilities are clearly defined. The joint team—developers, business owners, testers—executes in an agile manner, which in turn allows for, accommodates, and even encourages changing requirements throughout the process. This iterative and conjunctiveConjunctive process generates products and solutions that enable the customer’s competitive advantage.
Using the Agile Manifesto as a Framework

The Manifesto for Agile Software Development, or as it’s commonly referred to, the Agile Manifesto, lays out the values and principles whose aim is to enable software development teams to work more efficiently and effectively in service of their customers. Think of the values as the guiding principles for agile software development and delivery. Then think of the principles as structuring and informing the practice of agile software development and delivery. The values emphasize the importance of individuals and their interactions. The values emphasize that making progress matters more than making something perfect. Collaboration matters. Responding to changes—in priorities, in needs, in requirements—matters. The principles are not rules, and they are not strictures. Instead, they are tenets that structure and inform the practice. The principles provide a framework, and they are ours and they are yours to apply in service of your team and in service of your customers.
Digital Identity and Authentication in the Blockchain Era

In the digital age, our identity is built on our sense of identity, which defines who we are in our families, communities, cultures, and the wider world. The phrase "Know Yourself" (KYS) describes who we are and how we want to be perceived. It covers a range of characteristics, including those related to language, culture, religion, education, character, and career. While these traits help to define our individual identities, in order for governments and institutions to effectively provide services in areas like education, healthcare, banking, employment, and travel, a broader definition of identity is required. As a result, ‘Know Your Customer’ (KYC) checks are required by regulatory agencies all over the world. These checks are designed to confirm a person's identification before allowing access to services or facilities, such as admission to universities, creating bank accounts, getting loans, receiving health care, getting mobile SIM cards, etc. Therefore, in this digital world, protecting our identities and valuing who we are as individuals should be our first priority. The use of digital identities is becoming more prevalent as paper-based identity verification becomes less common. A greater challenge in the digital age is setting up how to protect our personal information and ensure that we are dealing with the correct individual, which is thoroughly examined in this study.
Scheduling Coflows by Online Identification in Data Center Network

Recently, many scheduling schemes leverage coflows to improve the communication performance of jobs in distributed application frameworks deployed in data center networks, such as MapReduce and Spark. Most of them require application modification to obtain the coflow information such as the coflow ID. The latest work CODA suggests non-intrusively extracting coflow information via an identification method. However, the method depends on the historical traffic information, which may cause the identification accuracy to decrease a lot when traffic varies. To tackle the problem, we present SOCI for Scheduling coflows by the Online Coflow Identification. By observing that flows in a coflow typically communicate with a master process for starting and ending in the up-to-date distributed application frameworks, SOCI uses this characteristic for the online coflow identification. Given identification errors are inevitable, the coflow scheduler in SOCI adopts a Selectively Late Binding (SLB) mechanism, which associates the misclassified flows with coflows according to the estimation on the impact of this association on the average Coflow Completion Time (CCT). The trace-driven simulations show that SOCI can reduce CCT by up to <inline-formula><tex-math notation="LaTeX">$1.23\times$</tex-math></inline-formula> compared to CODA when the identification accuracy decreases and is comparable to schemes without coflow identification.
NoHammer: Preventing Row Hammer With Last-Level Cache Management

Row Hammer (RH) is a circuit-level phenomenon where repetitive activation of a DRAM row causes bit-flips in adjacent rows. Prior studies that rely on extra refreshes to mitigate RH vulnerability demonstrate that bit-flips can be prevented effectively. However, its implementation is challenging due to the significant performance degradation and energy overhead caused by the additional extra refresh for the RH mitigation. To overcome challenges, some studies propose techniques to mitigate the RH attack without relying on extra refresh. These techniques include delaying the activation of an aggressor row for a certain amount of time or swapping an aggressor row with another row to isolate it from victim rows. Although such techniques do not require extra refreshes to mitigate RH, the activation delaying technique may result in high-performance degradation in false-positive cases, and the swapping technique requires high storage overheads to track swap information. We propose <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NoHammer</monospace> , an efficient RH mitigation technique to prevent the bit-flips caused by the RH attack by utilizing Last-Level Cache (LLC) management. <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NoHammer</monospace> temporarily extends the associativity of the cache set that is being targeted by utilizing another cache set as the extended set and keeps the cache lines of aggressor rows on the extended set under the eviction-based RH attack. Along with the modification of the LLC replacement policy, <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NoHammer</monospace> ensures that the aggressor row's cache lines are not evicted from the LLC under the RH attack. In our evaluation, we demonstrate that <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NoHammer</monospace> gives 6% higher performance than a baseline without any RH mitigation technique by replacing excessive cache misses caused by the RH attack with LLC hits through sophisticated LLC management, while requiring 45% less storage than prior proposals.
Agile Principle 12: “At Regular Intervals, the Team Reflects on How to Become More Effective, Then Tunes and Adjusts Its Behavior Accordingly”

Delivering valuable software frequently is the name of the game. Teams can improve. They can be told what to do and how to do it. Or they can be trusted to engage in honest self-reflection. Honest self-reflection becomes the best and most effective means for the team finding and creating sustainable improvements in the way they operate. Vignettes from leaders at TDS Telecom, Oracle, and Calstate Management Group, Inc., and a reminder from Richard Feynman, illustrate the challenge and the importance of regular reflection. You as the leader must encourage but not require self-reflection among your team. Enable it without prescribing how they should do it. Self-reflection can lead to discovery, and discovery is the key to continuous improvement.
Agile Principle 10: “Simplicity—The Art of Maximizing the Amount of Work Not Done—Is Essential”

Delivering valuable software frequently is the name of the game. The notion of simplicity needs to be applied to requirements, documentation, and priorities but not to code reviews. Simplicity reduces waste from the system and sharpens the team’s focus on delivering what matters most and nothing more. Vignettes from leaders at Amazon and Nokia, and a reminder from Albert Einstein, illustrate the challenge and the importance of achieving simplicity.
Reconstruction Guided Meta-Learning for Few Shot Open Set Recognition

In many applications, we are constrained to learn classifiers from very limited data (few-shot classification). The task becomes even more challenging if it is also required to identify samples from unknown categories (open-set classification). Learning a good abstraction for a class with very few samples is extremely difficult, especially under open-set settings. As a result, open-set recognition has received limited attention in the few-shot setting. However, it is a critical task in many applications like environmental monitoring, where the number of labeled examples for each class is limited. Existing few-shot open-set recognition (FSOSR) methods rely on thresholding schemes, with some considering uniform probability for open-class samples. However, this approach is often inaccurate, especially for fine-grained categorization, and makes them highly sensitive to the choice of a threshold. To address these concerns, we propose Reconstructing Exemplar-based Few-shot Open-set ClaSsifier (ReFOCS). By using a novel exemplar reconstruction-based meta-learning strategy ReFOCS streamlines FSOSR eliminating the need for a carefully tuned threshold by learning to be self-aware of the openness of a sample. The exemplars, act as class representatives and can be either provided in the training dataset or estimated in the feature domain. By testing on a wide variety of datasets, we show ReFOCS to outperform multiple state-of-the-art methods.
AF<sup>2</sup>R Net: Adaptive Feature Fusion and Robust Network for Efficient and Precise Depth Completion

In order to acquire precise depth maps, depth completion is a fundamental method for autonomous vehicles and robotics. Recent methods mainly focus on fusing multi-model information from sparse depth maps and color images to recover dense depth maps. Previous researches have made remarkable contributions in predicting depth values, but how to better fuse multi-model features, and how to better restore details are still two main issues. Aiming at these two issues, we propose a fusion net composed of two-branch backbone and depth refinement module. The backbone aims to extract and combine the features of sparse depths and color images, in which we adopt the strategies of symmetric gated fusion and pixel-shuffle for cross-branch and branch-wise fusion respectively. Then, we designed a new module named dilation-pyramid convolution spatial propagation network (DP-CSPN) for depth refinement which enlarges the propagation neighborhoods and obtains more local affinities than CSPN. Finally, to better process details, we designed loss functions to achieve clearer edges as well as to be aware of tiny structures. Our method achieves the state-of-the-art (SoTA) performance in NYU-Depth-v2 Dataset and KITTI Depth Completion Dataset, and we got the achievement of top 5 in mobile intelligent photography and imaging (MIPI) challenge held by European Conference on Computer Vision (ECCV) 2022.