Miracle-dz/UniFAR-FTUs huggingface dataset:
Load Balancing With Minimal Deviation in Switch Memories

Traffic splitting is a required functionality in networks, for example for load balancing over multiple paths or among different servers. The capacities of the servers determine the partition by which traffic should be split. A recent approach implements traffic splitting within the ternary content addressable memory (TCAM), which is often available in switches. It is important to reduce the amount of memory allocated for this task since TCAMs are power consuming and are also required for other tasks such as classification and routing. Previous work showed how to compute the smallest prefix-matching TCAM necessary to implement a given partition exactly. In this paper we solve the more practical case, where at most <inline-formula> <tex-math notation="LaTeX">${n}$ </tex-math></inline-formula> prefix-matching TCAM rules are available, restricting the ability to implement exactly the desired partition. We consider the <inline-formula> <tex-math notation="LaTeX">$L_{1}$ </tex-math></inline-formula> distance between partitions, which is of interest when overloaded requests are simply dropped, and we want to minimize the total loss. We prove that the Niagara algorithm (Kang et al., 2015) can be used to find the closest partition in <inline-formula> <tex-math notation="LaTeX">$L_{1}$ </tex-math></inline-formula> to the desired partition, that can be realized with <inline-formula> <tex-math notation="LaTeX">${n}$ </tex-math></inline-formula> TCAM rules. Moreover, we prove it for arbitrary partitions, with (possibly) non-integer parts. We also include a short discussion on similarities and differences to previous work which studies the same problem but for <inline-formula> <tex-math notation="LaTeX">$L_{\infty }$ </tex-math></inline-formula> distances.
Spatial Distribution of the Gamma-ray Bursts and the Cosmological Principle

Abstract The Cosmological Principle claims that in the large scale average the visible parts of the universe are isotropic and homogeneous. In year 1998 the author, together with his two colleagues, discovered that the BATSE’s short gamma-ray bursts are not distributed isotropically on the sky. This first discovery was followed by other ones confirming both the existence of anisotropies in the angular distribution of bursts and the existence of huge Gpc structures in the spatial distribution. All this means that these anisotropies should reject the Cosmological Principle, because the large scale averaging hardly can be provided. This was claimed in year 2009. The aim of this contribution is to survey these publications since 1998 till today.
Local Computation Algorithms for Graphs of Non-Constant Degrees

In the model of local computation algorithms (LCAs), we aim to compute the queried part of the output by examining only a small (sublinear) portion of the input. Many recently developed LCAs on graph problems achieve time and space complexities with very low dependence on n, the number of vertices. Nonetheless, these complexities are generally at least exponential in d, the upper bound on the degree of the input graph. Instead, we consider the case where parameter d can be moderately dependent on n, and aim for complexities with quasi-polynomial dependence on d, while maintaining polylogarithmic dependence on n. In this thesis, we give randomized LCAs for computing maximal independent sets, maximal matchings, and approximate maximum matchings. Both time and space complexities of our LCAs on these problems are 2 0(log d)polylog(n), 2 0(log d)polylog(n) and 2 0(log3 d)polylog(n), respectively. Thesis Supervisor: Ronitt Rubinfeld Title: Professor of Electrical Engineering and Computer Science
Fine-Grained Retrieval Method of Textile Image

There are a large category of textile images that have the characteristics of high local feature repetition rate and complex background information. These types of images have significant intra-class differences and small inter-class differences, making it impossible to perform classification training. Making it difficult for existing methods to accurately retrieve textile images. To improve the retrieval accuracy of textile images, this paper defines multiple repeated local fine-grained features in textile images as textile image “feature components”, extracts multiple “feature components” from a textile image, and fuses the “feature components” to generate the definition of textile “fingerprints”. We propose an image retrieval method based on a pre-trained Mask R-CNN model to extract multiple “feature components” in the textile image, then extract the depth feature of the textile again through a convolution neural network, and fuse the extracted depth feature to obtain the “fingerprint” of the textile. The obtained “fingerprint” can effectively eliminate the interference of large area background and a large number of local repeated features in the textile image, and improve the efficiency of textile retrieval. A series of comparative experiments are carried out on textile image data sets with repeated features. The experimental results show that the proposed method is generally effective.
Managing Self-Presentation

Socially desirable responding (SDR) is usually treated as a “noise” in psychological research, to be con - trolled for by creating certain conditions for respondents. We tested a range of cues aimed to decrease/ increase SDR to be applied/avoided in selection or recruitment. To decrease it, we developed two novel procedures: one inspired by the bogus pipeline in which the respondents were induced to believe we can objectively record their sincerity (all three studies), and the other, inspired by the Bayesian Truth Serum (BTS) method, in which the respondents were rewarded points for sincerity (Study 3). To increase it, we exposed the respondents to descriptive group norms signaling socially desirable behaviors in their peers (Study 1 and Study 2). We measured SDR via overclaiming (Study 1 and Study 3), L and K scales from the MMPI (Study 1), and attitudes towards vulnerable groups (Study 2). Across all three studies, we decreased the SDR via newly developed procedures, but failed to increase it, indicating a “default” level of positive self-presentation. When we compared the two procedures for decreasing SDR (overclaiming indices), the one inspired by the bogus pipeline was more effective than the BTS-inspired one (Study 3).
Uncorrelated component analysis on manifold for statistical process monitoring

A novel process modeling approach referred to as locally invariant uncorrelated component analysis (LIUCA) is proposed for the purpose of statistical process monitoring. The contributions are as follows: (1) LIUCA intends to find a part‐based representation subspace in which two data points are close to each other, if they are close in the k‐nearest neighbor graph; (2) LIUCA can exploit the geometrical structure of the data space, which will improve the algorithm's modeling performance in real‐world applications; (3) LIUCA‐based multivariate statistical process monitoring scheme is proposed. (4) In contrast to traditional process modeling algorithm such as principal component analysis, LIUCA imposes no restriction on data distribution. In addition, both a multivariate numerical example and a hot galvanizing pickling waste liquor treatment process are taken to evaluate the feasibility of the proposed process monitoring scheme. Experiment results demonstrate the effectiveness of the proposed method.
M3D-C1 simulations of the plasma response to RMPs in NSTX-U single-null and snowflake divertor configurations

In this work, single- and two-fluid resistive magnetohydrodynamic calculations of the plasma response to n=3 magnetic perturbations in single-null (SN) and snowflake (SF) divertor configurations are compared with those based on the vacuum approach. The calculations are performed using the code M3D-C1 and are based on simulated NSTX-U plasmas. Significantly different plasma responses were found from these calculations, with the difference between the single- and two-fluid plasma responses being caused mainly by the different screening mechanism intrinsic to each of these models. Although different plasma responses were obtained from these different plasma models, no significant difference between the SN and SF plasma responses were found. However, due to their different equilibrium properties, magnetic perturbations cause the SF configuration to develop additional and longer magnetic lobes in the null-point region than the SN, regardless of the plasma model used. The intersection of these longer and additional lobes with the divertor plates are expected to cause more striations in the particle and heat flux target profiles. In addition, the results indicate that the size of the magnetic lobes, in both single-null and snowflake configurations, are more sensitive to resonant magnetic perturbations than to non-resonant magnetic perturbations.
The frequency and properties of young tidal dwarf galaxies in nearby groups

Abstract We present the results of a multi-wavelength investigation of the dwarf galaxy populations in three interacting galaxy groups: NGC 871/6/7, NGC 3166/9, NGC 4725/47. Using degree-scale Giant Metrewave Radio Telescope Hi mosaics and deep optical photometry from the Canada-France-Hawaii Telescope, we measured the Hi and stellar properties of the gas-rich low-mass group members to classify each one as a classical dwarf galaxy, a short-lived tidal knot or a tidal dwarf galaxy (TDG). Our observations detect several dwarf irregulars and various tidal knots. We identify four potentially long-lived tidal objects in the three groups, implying that TDGs are not readily produced. The tidal objects examined in this small survey also appear to have a wider variety of properties than TDGs formed in current simulations.
Construction of Series of Degenerate Representations for GSp(2) and PGL(n)

The relative trace formula is a tool for studying automorphic representations on symmetric spaces. In this work two relative trace formulas are studied: One for GSp(2) relative to a form of SO(4) and one for PGL(n) relative to GL(n− 1). The first trace formula is used to study the Saito-Kurokawa lifting of automorphic representations from PGL(2) to PGSp(2), thus characterising the image as the representations with a nonzero period for the special orthogonal group SO(4,E/F ) associated to a quadratic extension E of the base field F , and a nonzero Fourier coefficient for a generic character of the unipotent radical of the Siegel parabolic subgroup. The second trace formula is used to study the representations π of PGL(n) which have a nonzero linear form invariant under the Levi subgroup GL(n−1), and a certain nonvanishing degenerate Fourier coefficient, over local and global fields. The result is that these π are of the form I(1n−2, π ′), namely normalizedly induced from the parabolic subgroup of type (n− 2, 2), trivial representation on the GL(n− 2)-factor and cuspidal π′ on the PGL(2)-factor. The analysis of the formula is intricate our main achievement is rigorously establishing the convergence of the formula. New in this case is that none of the representations of PGL(n) involved are cuspidal, they rather occur in the continuous spectrum, but discretely in our formula.
Three-dimensional Simulations and Spacecraft Observations of Sub-ion Scale Turbulence in the Solar Wind: Influence of Landau Damping

Three-dimensional nonlinear finite Larmor radius (FLR)–Landau fluid simulations, which include some small-scale kinetic effects, are performed to explore the nature of the sub-ion scale turbulence in the solar wind and to investigate the role of Landau damping and FLR corrections. The resulting steady-state magnetic power spectrum in the dispersive range display exponents that vary within a range of values compatible with statistical results reported from in situ spacecraft measurements of solar wind turbulence as well as from gyrokinetic simulations. The spectral slopes are shown to depend on the strength of the nonlinear effects and on the scale at which turbulent fluctuations are driven in the simulations. The influence of Landau damping is addressed by comparison with simulations where the double-adiabatic closure is imposed. The role of FLR corrections is also analyzed. Comparison with in situ observations in the solar wind are performed to enlighten the influence of the fluctuations power at different scales on the spectral slopes in the sub-ion range. Using diagnosis of both magnetic compressibility and frequency-wavenumber spectra, it is shown that in spite of the evidence of the presence of fast-magnetosonic modes, the magnetic energy is mostly distributed around the kinetic Alfvén waves and the slow modes, in agreement with solar wind measurements. The observed large broadening about the linear dispersion relations may reflect the presence of coherent structures.
Linearized Calculations of Stationary Waves in the Atmosphere

The linearized response of the atmosphere to thermal and orographic stationary wave forcing is examined with a high resolution (1km vertical resolution, 1.5* latitude resolution) primitive equation model. It is found that the response to thermal forcing (but not orographic forcing) is sensitive to small changes in the basic distribution of wind and temperature. This suggests that anomalies in stationary waves can occur even without changes in forcing.
Examining the association between self-control and mental health among adolescents: The mediating role of resilience

Failure of self-control is one of the core characteristics of numerous mental health issues. The significance of self-control for mental health is well known, but studies investigating the association between self-control and mental health and the mechanisms underlying this association are quite limited, especially in adolescents. The current cross-sectional study aimed to test the mediating role of resilience in the relationship between self-control and mental health (i.e. psychological well-being and mental health problems) in adolescents. The sample comprised 405 high school students from a state school in one of the major cities of Turkey. Participants’ ages ranged from 13 to 18 years (Mage = 15.94, SD = 1.11), and 34.6% identified as male and 65.4% as female. Findings showed that self-control was positively correlated with psychological well-being and resilience but negatively correlated with mental disorders. Additionally, resilience mediated the association between self-control and mental health disorders as well as the association between self-control and psychological well-being. The study's results are discussed in the context of previous research, and implications for psychologists and mental health professionals working in schools are offered.
JURNAL SAINS DAN INFORMATIKA Research of Science and Informatic

URLs are very much on the network of computer systems. Moreover, nowadays all activities use an online system. Starting from social media, and marketplaces to group chat applications. An early prevention system from malicious URL attacks is needed to counteract the large number of URLs circulating in the online system. Previously, malicious URL detection based on Blacklisting and Heuristic URLs could not recognize the new type of malicious URL without first being analyzed. For this reason, a technique is needed to detect malicious URLs using machine learning. The lack of machine learning in the detection of malicious URLs is that it is not 100% able to detect malicious URLs precisely. This study will use an improved random forest approach with a random forest as a classifier to detect malicious URLs. Improved Random Forest is a Random Forest that is used using evaluator features and filter instances to improve the accuracy of ordinary random forests. This study concluded that both methods of improved random forest and ordinary random forest have an accuracy value above 99%.
Spectral- and spatial-based multi-focus image fusion method towards multi-layer nonwovens

In the microscopic imaging scenario where the object thickness exceeds the depth of field of the microscope, multi-focus image fusion (MFF) is an effective method to generate an all-in-focus image. However, for nonwoven fabric for which the captured image number is up to 100 or more, the existing methods often underperform in areas near the fiber edges, owing to image ghosting and noise accumulation caused by the platform moving. To address the above problem, this paper presents a method designed to fuse multi-layer micro-images based on the combination of spectral and spatial features of the images. Firstly, the spectral domain-based map is generated by decomposition and reconstruction of the high-frequency and low-frequency components of the images, aimed at obtaining the edge information. Simultaneously, the spatial domain-based fuse map is built through sharpness measurement, referring to visual perception. Finally, the two methods are combined via an optimized weight to obtain an all-in-focus fused image. Four groups of real-world data consisting of 100 multi-focus nonwoven images are utilized to verify the superiority of this method. The experimental results demonstrate that the proposed method can obtain satisfactory performance in terms of both human visual evaluation and objective evaluation compared with the image fusion framework based on the convolutional neural network, MFF, region-based image fusion algorithm and convolutional neural network state-of-the-art fusion methods.
The Effectiveness of Islamic Capital Market Securities in Supporting MSMEs Working Capital Financing

This study was undertaken to determine how effective Islamic Capital Market Securities, namely the issuance of subordinated sukuk and others sukuk in Islamic banking, are on the quantity of working capital financing distribution to MSMEs in Indonesia. By using monthly time series secondary data and multiple linear regression analysis techniques, it was found that the issuance of subordinated sukuk and others sukuk had a significant positive effect on increasing the quantity of working capital financing distribution to MSMEs. It can be concluded that the policy of Islamic banking to issue Islamic Capital Market Securities effectively supports the increase in the working capital of MSMEs.
Power Flow Modeling Using Fast Genetic Approach in Power Systems

OPF is an optimization problem, in which the effectiveness strives to minimize its generation costs while satisfying all its equality and inequality constraints, while the system is operating within its security limits. This paper proposes a Genetic Algorithm Optimal Power Flow (GAOPF) problem on the use of a genetic algorithm load flow. This approach overcomes the limitations of the conventional approaches in the modeling of non-convex cost functions, discrete control variables, and prohibited unit-operating zones. The paper concludes that the proposed scheme is effective for the real network situation in developing countries. straightforward manner. The optimal power flow can be analyzed by formulating the problem in a mathematical manner using some mathematical algorithm. Recent attempts of these mathematical programming approaches include the application of simulated annealing-type methods (7-8), and genetic algorithms (GAs) etc., (9-10). GAs is essentially search algorithm based on mechanics of nature and natural genetics (11). They combine solution evaluation with randomized, structured exchanges of information between solutions to obtain optimality. GAs is a robust method because restrictions on solution space are not made during the process. The power of GAs stem from its ability to exploit historical information structures from previous solution guesses in an attempt to increase performance of future solutions (12). This paper proposes a Genetic Algorithm Optimal Power Flow (GAOPF) problem on the use of a genetic algorithm load flow. This approach overcomes the limitations of the conventional approaches in the modeling of non-convex cost functions, discrete control variables, and prohibited unit-operating zones. However, they do not scale easily to larger problems, since the solution deteriorates with the increase of the chromosome length, i.e., the number of control variables The rest of the paper is organized as follows: Section 2 gives the basic model of UPFC system. Genetic algorithm optimal power flow is discussed in section 3. Results are shown in section 4 and conclusions are discussed in section 5.
Applications of ChatGPT and Large Language Models in Medicine and Health Care: Benefits and Pitfalls.

Background The use of large language models like ChatGPT is becoming increasingly popular in health care settings. These artificial intelligence models are trained on vast amounts of data and can be used for various tasks, such as language translation, summarization, and answering questions. Observations Large language models have the potential to revolutionize the industry by assisting medical professionals with administrative tasks, improving diagnostic accuracy, and engaging patients. However, pitfalls exist, such as its inability to distinguish between real and fake information and the need to comply with privacy, security, and transparency principles. Conclusions Careful consideration is needed to ensure the responsible and ethical use of large language models in medicine and health care. The development of [artificial intelligence] is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone. It will change the way people work, learn, travel, get health care, and communicate with each other. Bill Gates1.
Breakdown and quasi-DC phase of a nanosecond discharge: Comparison of optical emission spectroscopy measurements with numerical simulations

A nanosecond atmospheric pressure plasma jet operated in pure nitrogen is studied by spatially and temporally resolved optical emission spectroscopy complementing the companion paper (Kuhfeld et al 2023 Plasma Sources Sci. Technol. 32 084001), where the discharge is investigated by means of Particle-in-Cell/Monte Carlo collisions (PIC/MCC) simulations and fluid models. Two temporal phases of the evolution of the discharge are identified: a fast breakdown and a quasi-DC phase. It is shown that during the breakdown phase several ionization waves develop, while after the breakdown the discharge has a structure similar to DC glow discharges, in agreement with the modeling predictions. The results of the measurements of the spatial-temporal dynamics of the light emission are compared with the distribution of densities of the N2+(B2Σu+) and N2(C3Πu) states reconstructed from the PIC/MCC simulations. A good agreement is demonstrated.
Trends, Opportunities, and Challenges of Using WhatsApp in Learning: A Literature Review

WhatsApp is a widely used and widely used communication platform in education. The main objectives of this literature review are to identify the trends and challenges associated with using WhatsApp in education, explore the benefits and opportunities for students and teachers in using this platform for learning, and understand the challenges and limitations of using WhatsApp within the classroom setting. The literature was obtained through various databases using keywords related to WhatsApp and education. It is important for educators and administrators to be aware of the trends, opportunities, challenges, and opportunities associated with the using of WhatsApp. The increased usage of WhatsApp as a tool for communication and collaboration between students and teachers is one trend that has been identified in the research. The results of this literature review will contribute to the field of education and technology by highlighting the potential of WhatsApp as a tool for learning and providing insights on how it can be effectively integrated in classroom instruction. The article also discusses the need to consider privacy and security issues when using WhatsApp in education, and provides suggestions for further research.