Miracle-dz/UniFAR-FTUs huggingface dataset:
The Capacity of Private Information Retrieval With Partially Known Private Side Information

We consider the problem of private information retrieval (PIR) of a single message out of <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> messages from <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> replicated and non-colluding databases where a cache-enabled user (retriever) of cache-size <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> possesses side information in the form of full messages that are partially known to the databases. In this model, the user and the databases engage in a two-phase scheme, namely, the prefetching phase where the user acquires side information and the retrieval phase where the user downloads desired information. In the prefetching phase, the user receives <inline-formula> <tex-math notation="LaTeX">$m_{n}$ </tex-math></inline-formula> full messages from the <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>th database, under the cache memory size constraint <inline-formula> <tex-math notation="LaTeX">$\sum _{n=1}^{N} m_{n} \leq M$ </tex-math></inline-formula>. In the retrieval phase, the user wishes to retrieve a message (which is not present in its memory) such that no individual database learns anything about the identity of the desired message. In addition, the identities of the side information messages that the user did not prefetch from a database must remain private against that database. Since the side information provided by each database in the prefetching phase is known by the providing database and the side information must be kept private against the remaining databases, we coin this model as <italic>partially known private side information</italic>. We characterize the capacity of the PIR with partially known private side information to be <inline-formula> <tex-math notation="LaTeX">$C=\left ({1+\frac {1}{N}+\cdots +\frac {1}{N^{K-M-1}}}\right)^{-1}=\frac {1-\frac {1}{N}}{1-\left({\frac {1}{N}}\right)^{K-M}}$ </tex-math></inline-formula>. Interestingly, this result is the same if none of the databases knows any of the prefetched side information, i.e., when the side information is obtained externally, a problem posed by Kadhe et al. and settled by Chen-Wang-Jafar recently. Thus, our result implies that there is no loss in using the same databases for both prefetching and retrieval phases.
Effect of Using Probabilistic Contingency Tables to Modify Forecast Predictions

The 45th Weather Squadron (45 WS) records daily rain and lightning probabilistic forecasts and the associated binary event outcomes. Subsequently, they evaluate forecast performance and determine necessary adjustments with an implemented verification process. For deterministic outcomes, weather forecast analysis typically utilizes a Tradition Contingency Table (TCT) for verification, however the 45 WS uses an alternative tool, the Probabilistic Contingency Table (PCT). Using the TCT for verification requires a threshold, typically at 50%, to dichotomize probabilistic forecasts. The PCT maintains the valuable information in probabilities and verifies the true forecasts being reported. Simulated forecasts and outcomes as well as 2015-2018 45 WS data were utilized to compare forecast performance metrics produced from the TCT and PCT to determine which verification tool better supports producing the greatest quality forecasts. Comparisons of frequency bias, reliability, and Brier Score (BS) computed from both dichotomized and continuous forecasts revealed misrepresentative performance metrics from the TCT as well as a loss of information necessary for verification. Exploration of the 45 WS data with a probabilistic verification process revealed a need to verify seasonally as well as slightly unreliable warm season lightning event forecasts.
A computational reward learning account of social media engagement

Social media has become a modern arena for human life, with billions of daily users worldwide. The intense popularity of social media is often attributed to a psychological need for social rewards (“likes”), portraying the online world as a Skinner Box for the modern human. Yet despite such portrayals, empirical evidence for social media engagement as reward-based behavior remains scant. Here, we apply a computational approach to directly test whether reward learning mechanisms contribute to social media behavior. We analyze over one million posts from over 4,000 individuals on multiple social media platforms, using computational models based on reinforcement learning theory. Our results consistently show that human behavior on social media conforms qualitatively and quantitatively to the principles of reward learning. Specifically, social media users spaced their posts to maximize the average rate of accrued social rewards, in a manner subject to both the effort cost of posting and the opportunity cost of inaction. Results further reveal meaningful individual difference profiles in social reward learning on social media. Finally, an online experiment (n = 176), mimicking key aspects of social media, verify that social rewards causally influence behavior as posited by our computational account. Together, these findings support a reward learning account of social media engagement and offer new insights into this emergent mode of modern human behavior
Channel Characteristics for Fixed and Portable DTV Reception in a Single Frequency Network

This paper presents the propagation channel characteristics of a digital TV Single Frequency Network (SFN) obtained in field measurements carried out with two synchronized transmitters. The measurements were performed at 31 reception points with both a directive reception antenna, typical of fixed reception, and an omnidirectional antenna, used for mobile reception. The characteristic parameters of the channel were obtained, including the average delay, the r.m.s. delay spread and the Rician K-factor. These parameters are important for the design of SFN systems. An empirical expression for the prediction of the r.m.s. delay spread as a function of the K factor and the distances to the transmission antennas was obtained.
Binaural Codebook-Based Speech Enhancement With Atomic Speech Presence Probability

In this work, we present a universal codebook-based speech enhancement framework that relies on a single codebook to encode both speech and noise components. The atomic speech presence probability (ASPP) is defined as the probability that a given codebook atom encodes speech at a given point in time. We develop ASPP estimators based on binaural cues including the interaural phase and level difference (IPD and ILD), the interaural coherence magnitude (ICM), as well as a combined version leveraging the full interaural transfer function (ITF). We evaluate the performance of the resulting ASPP-based speech enhancement algorithms on binaural mixtures of reverberant speech and real-world noise. The proposed approach improves both objective speech quality and intelligibility over a wide range of input SNR, as measured with PESQ and binaural STOI metrics, outperforming two binaural speech enhancement benchmark methods. We show that the proposed ITF-based ASPP approach achieves a good balance of the trade-off between binaural noise reduction and binaural cue preservation.
Mobility-Enabled Edge Server Selection for Multi-User Composite Services

In mobile edge computing, a set of edge servers is geographically deployed near the mobile users such that accessible computing capacities and services can be provided to users with low latency. Due to user’s mobility, one fundamental and critical problem in mobile edge computing is how to select edge servers for many mobile users so that the total waiting time is minimized. In this paper, we propose a multi-user waiting time computation model about composite services and show the resource contention of the edge server among mobile users. Then, we introduce a novel and optimal Multi-user Edge server Selection method based on Particle swarm optimization (MESP) in mobile edge computing, which selects edge servers for mobile uses in advance within polynomial time. Extensive simulations on a real-world data-trace show that the MESP algorithm can effectively reduce the total waiting time compared with traditional approaches.
Towards Understanding How Developers Comprehend Tests

Developers spend the majority of their time and effort on reading and comprehending source code. In order to improve this process of program comprehension for developers, a numerous amount of existing studies have looked into understanding how developers approach it and factors of influence. However, less is known in the field about how developers comprehend test code, an alternative form of source code, despite its widely acknowledged importance and benefits in both research and practise. In this paper, we perform a foundational study on understanding how developers comprehend tests by applying existing knowledge and work on program comprehension onto tests comprehension and looking at the influential factors. An online controlled experiment was conducted with 44 developers to measure three defined metrics of tests comprehensibility, namely the total time spent on reading a test suite, the ability to identify the overall purpose a test suite, and the ability to produce additional test cases to extend a test suite. The main findings of our study, with several implications for future research and real world, are that (i) prior knowledge of the software project decreases the total reading time, (ii) developers with more Java experience spend proportionally less time on the Arrange and Assert sections of test cases, (iii) experience with Java and prior knowledge of the software project positively influences the ability to produce additional test cases of certain categories, and (iv) the most influential factor towards understanding and extending a test suite is experience with using tests.
Classification of imagined spoken Word-Pairs using Convolutional Neural Networks

: Imagined speech is gaining traction as a communicative paradigm for brain-computer-interfaces (BCI), as a growing body of research indicates the potential for decoding speech processes directly from the brain. The development of this type of direct-speech BCI has primarily considered feature extraction and machine learning approaches typical to BCI decoding. Here, we consider the potential of deep learning as a possible alternative to traditional BCI methodologies in relation to imagined speech EEG decoding. Two different convolutional neural networks (CNN) were trained on multiple imagined speech word-pairs, and their performance compared to a baseline linear discriminant analysis (LDA) classifier trained using filterbank common spatial patterns (FBCSP) features. Classifiers were trained using nested cross-validation to enable hyper-parameter optimization. Results obtained showed that the CNNs outperformed the FBCSP with average accuracies of 62.37% and 60.88% vs. 57.80% (p<0.005).
Will Your Paper Get Promoted by a Citation? A Case Study of Citation Promoter in Computer Science Discipline

Reseachers have investigated numerous factors influencing citation counts of cited papers. One factor investigated has been the number of gained citations, as this could increase the visibility of cited papers and subsequently induce further citations. In this paper, aiming to identify a particular kind of citation that could trigger a rapid growth in the citation counts of cited papers, a concept of “citation promoter” was proposed. We defined citation promoters based on the annual citation rates of the cited papers and the co-citation counts received by the pair of cited and citing papers. The comparative results showed that papers would obtain a sharp rise in citation counts shortly after they were cited by citation promoters. Papers that received citation promoters at an early age outperformed other papers in long-term citation counts. In addition, we developed a classification model for predicting whether a citing paper would be a citation promoter for its cited paper. Since it was a class imbalanced problem (4 percent positive instances), and there was a lack of content and author features in our dataset, our preliminary models achieved moderate performance with an <inline-formula><tex-math notation="LaTeX">$F_1$</tex-math><alternatives><mml:math><mml:msub><mml:mi>F</mml:mi><mml:mn>1</mml:mn></mml:msub></mml:math><inline-graphic xlink:href="luo-ieq1-2861321.gif"/></alternatives></inline-formula> score slightly higher than 0.5, while the <inline-formula><tex-math notation="LaTeX">$F_1$</tex-math><alternatives><mml:math><mml:msub><mml:mi>F</mml:mi><mml:mn>1</mml:mn></mml:msub></mml:math><inline-graphic xlink:href="luo-ieq2-2861321.gif"/></alternatives></inline-formula> score obtained by random guessing was 0.07.
Novel hardware verification methods for FPGAs

ly generated during technology mapping and are later refined to concrete FPGA resources during placement. After placement, the endpoints of the TCONs are fixed to the specific signals-multiplexers to be traced and the router further refines the DUT by reserving the switches and wires to realize the connection between the subset of multiplexers and trace-buffers. During routing the tool flow has to route a large set of TCON-containing signals. These signals have more than one resource sharing possibility. They may share resources if they have the same source or if they are not active at the same time. Two TCONs, sgn1 and sgn2 with their connection conditions ⇣1 and ⇣2, are not active at the same time, if their connection conditions are not simultaneously true for every parameter value (n0 and n1). Thus, if sgn1 and sgn2 are not active simultaneously for each parameter p in a set of parameters P then 8(p) 2 (P ) ) ¬(⇣1(p) ^ ⇣2(p)) (3.1) The results of Equation 3.1 are reflected in Figure 3.3. Here, the tool has detected during technology mapping that the sgn0 and sgn2 that represent the gates NAND0 and NAND1 are not used at the same time, so they can share resources. Therefore, during debugging, the signal set will contain the sgn0 and not sgn2. This is defined by the Boolean function that uses as parameter inputs the multiplexers’ selection bits: n0, n1, . , nn. Hence, the tool will create a subset of signals that for each multiplexer-cluster are never used at the same time. IN-CIRCUIT DEBUGGING USING PARAMETERIZED CONFIGURATIONS 63
Turbo Message Passing-Based Receiver Design for Time-Varying OFDM Systems

In this paper, we study time-varying orthogonal frequency division multiplexing (OFDM) systems, and propose a joint channel-and-signal estimation receiver based on turbo message passing (TMP) to efficiently suppress inter-carrier interference (ICI). We establish a factor graph representation of the problem and divide the whole factor graph into two parts, one for channel estimation and the other for signal detection. For the first part, we use Gaussian message passing (GMP) for channel estimation; for the second part, a discrete state space (DSS) model is employed to describe the transition of signal states, and a forward-backward algorithm is adopted for message passing over the transition trellis in signal detection. The resulting algorithm is referred to as DSS-GMP. The complexity of DSS-GMP quickly becomes the bottleneck as the increase of the signal constellation size and the ICI width. To address this issue, we further develop a continuous-state-space (CSS) model based turbo message passing algorithm, where the messages of modulated signals are approximated as continuous Gaussian messages. Numerical results demonstrate that the TMP based scheme significantly outperforms the state-of-the-art schemes.
The psycholinguistics of the interaction approach

Second Language Acquisition (SLA) has been an independent research discipline since the late 1970s, and Sue Gass has been a leading figure throughout its evolution. The first issue of Studies in Second Language Acquisition was published in 1978. Sue’s PhD thesis ‘An investigation of syntactic transfer in adult second language acquisition’ was completed in 1979 and published as an article in Language Learning in the same year. ‘Second language acquisition: An introductory course’ (Gass & Selinker, 1994, 2001) is for many the standard introductory text. Sue has been associate editor of SSLA for longer than I can remember, an active member of the American Association for Applied Linguistics since its inception in 1977 (president in 1987), and is currently the president of the International Association for Applied Linguistics (AILA). Sue’s influence can be seen throughout the field. Yet for me, her most profound contribution is
The effect of task characteristics on enterprise resource planning system success with user characteristics and organizational characteristics as mediating variables

Enterprise Resource Planning(ERP) is an integrated system that provides a wide range of benefits for the company, but there are still many companies who have unsuccessfully implemented ERP system. This study aimed to analyze the effect of the task characteristic and the success of Enterprise Resource Planning (ERP) on the success of ERP, with the user characteristic and organizational characteristic as mediating variables. The data were collected by using a questionnaire distributed directly to users of Enterprise Resource Planning (ERP) in Indonesian companies listed in Indonesia Stock Exchange (ISE). The data were processed by using Partial Least Square (PLS). It was found that the suitability of the task significantly affects the success of an ERP system, either directly or mediated by the user variable characteristic and organizational characteristic. Task difficulty also significantly affects the success of an ERP system if mediated by the convenience variable (user characteristic). The success of the ERP system is determined by based tasks and task complexity through the system the user's convenience in using the information system.
Multi-Scale Convolutional Neural Network-Based Intra Prediction for Video Coding

In both H.264/AVC and HEVC, the angular prediction is adopted for intra coding, which only exploits the spatial correlation between the current block and its neighboring single line reference. This angular prediction can handle the main directional patterns well, however, lacks the ability to deal with other directions. In this paper, a multi-scale convolutional neural network based intra prediction is proposed to address this problem. Specifically, a predicted block is first generated by the angular prediction, then fed into the proposed network with its neighboring reconstructed <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula>-shape to generate a more accurate predicted block. On one hand, the <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula>-shape of multiple lines provides more reliable reconstructed pixels and more contextual information to get better prediction; on the other hand, the multi-scale feature extraction takes the advantage of the feature maps in different scales to further enhance the prediction. With this multi-scale structure, the <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula>-shape can be used to refine both left-above and right-bottom pixels in the predicted block during the convolution operation. Experimental results demonstrate that compared with HEVC reference software HM 16.9, the proposed intra prediction can achieve an average of 3.4% (up to 5.6%) bitrate saving with all intra configuration.
Becoming more systematic about flexible learning: beyond time and distance

Changes in higher education frequently involve the need for more flexibility in course design and delivery. Flexibility is a concept that can be operationalized in many ways. One approach to conceptualizing flexibility within courses is to distinguish planning-type flexibility, which the instructor can designate before the course begins and which needs to be managed when the course is offered, for interpersonal flexibility, which relates more to the dynamics of the course as it is experienced by the learners. Course management systems (CMSs) offer options that can support both of these sorts of flexibility, if instructors use the CMSs with a systematic frame of reference. The instructor faces challenges in managing both types of flexibility, but the experience at one institution shows that being systematic about flexibility choices and ways to support those choices in the institutional CMS can help in meeting these challenges.
What is the cost of disregarding market feedback in transmission expansion planning?

Under the current European market environment, transmission companies have to decide network expansion by maximizing social welfare. However, generation companies (GENCOs) decide their capacity expansion with the aim of maximizing their own profit. This process, in addition to the increasing penetration of renewable energy, storage and distributed generation, might represent a rupture between short and long-term signals. Therefore, this paper proposes a bi-level formulation for the generation and transmission coordination problem (GEPTEP). We consider a proactive framework in which a centralized TSO represents the upper level while the decentralized GENCOs, that trade in the market, represent the lower level. A case study is presented to evaluate different policy planning objectives. Additionally, the planning results of the bilevel framework (considering both perfect competition and Cournot oligopoly in the lower level) are compared with a traditional cost minimization framework.
Pair programming in middle school: variations in interactions and behaviors

ABSTRACT Background and Context: Pair programming is used in classrooms to promote learning and engage a more diverse group of students in computing fields, but little is known about what it looks like in middle school. Objective: The aim of this study was to examine how programming pairs were interacting and about what. Method: Video, audio, and screen capture data were collected and analyzed from 66 middle school students working in pairs to program a computer game in an after-school class. Findings: Less than half of pairs interaction time was about their game, and one third of their time was spent not interacting at all. Most behaviors were collaborative. There were few differences across demographic groups. Factors that significantly influenced interactions and behaviors included attitude toward collaboration and prior programming knowledge. Implications: We discuss how to use pair programming in the classroom, including how to pair students to promote productive interactions.