Miracle-dz/UniFAR-FTUs huggingface dataset:
The variance of sums of arithmetic functions

Some of the fundamental problems in analytic number theory concern sums of arithmetic functions over short intervals. Such problems include the existence of primes in an interval, cancellation in Möbius sums and existence of squarefree integers in an interval. It is conjectured for many naturally occurring functions that their mean in short intervals is asymptotic to their mean in a full interval. Moreover, sums over short intervals are expected to enjoy squareroot cancellation, in the sense that the error term is at most the squareroot of the number of terms. Even under the Riemann Hypothesis, these problems are open for most functions. It is common and useful to introduce randomness into the problem, by picking a short interval at random. One can then study the sum of a arithmetic function over the random interval. Upper bounds on the variance of this random sum lead one to ‘almost-all’ versions of difficult conjectures. In this thesis we study the variance of sums of arithmetic functions in function fields. We use combinatorial, analytic and geometric tools to prove stronger results than known over the integers. Our four main results are 1. An asymptotic formula for the variance of squarefree polynomials over short intervals, going well beyond R. R. Hall’s 1982 work, and giving evidence to a recent conjecture of Keating and Rudnick. 2. A tight upper bound for the variance of factorization functions in short intervals. 3. An asymptotic formula for the variance of sums of two squares in short intervals, in the large-q limit. Our formula deviates from a naive probabilistic model and produces a prediction over the integers which agrees very well with numerical data. 4. A large-q asymptotic formula for the number of twin primes in a polynomial ring with an optimal error term.
A 2 . 2 ps 2-D Gated-Vernier Time-to-Digital Converter with Digital Calibration

This paper presents a 2-dimension (2-D) Vernier time-to-digital converter (TDC) which uses two 3-stage gated-ring-oscillators (GROs) in the X/Y Vernier branches. The already small Vernier quantization noise (~10.6ps) is improved by the 1-order noise shaping of the GRO. Moreover, since all delay differences between X phases and Y phases can be used (rather than only the diagonal line of the 1-dimension architecture), the intrinsic large latency time of the Vernier architecture is dramatically reduced. The TDC is implemented in a 65nm CMOS process and consumes 2.3mA from 1.0V. The measured total noise integrated over a bandwidth of 1.25 MHz yields an equivalent TDC resolution of 2.2ps, while the average latency time (within 2ns) is less than 1/6 of that in a standard Vernier TDC.
Systolic implementation for 2-D unitary ESPRIT

We discuss the systolic array implementation of 2-D unitary ESPRIT. By exploiting the idea of Unitary ESPRIT we modify the algorithm into totally real valued process, which can reduce the computational burden of each processor. An important issue in extending the 1-D systolic ESPRIT into its 2-D case is to achieve the simultaneous upper-triangularization of 3 compressed matrices which we call SGSD. For this aim we employ the Jacobi-type method incorporated with iterative shifted QR method to obtain an approximate decomposition. Finally a simulation result shows that the proposed algorithm can track the azimuth and elevation of moving sources.
Publicly Verifiable Vibrant Digital Medical Information Systems

As data processing advances, decentralized media has been widely recognized for its ability to store large amounts of data. By comparing a revisited content to a dispersed repository, a cloud provider may verify the document’s integrity without having to retrieve it. A reconsidered examining strategy is offered to lead the customer to reconsider the significant assessing task to third sector inspector, taking into consideration the important computing cost brought up by the checking process (TPA). TPA may be deterred by the primary revisited evaluating strategy, but the second plan gives the harmful organization the right of inspection over the readdressed data of users, which poses a significant risk to patient privacy. Human Emphasis for reconsidered inspection is presented in this work, which emphasizes that the service user can be overwhelmed by her own data. Based on user-centered design, our suggested methodology not only prevents patient’s data from leaking to TPA without depending on cryptographic algorithms, but can also avoid the use of additional free unpredictable supply that is impossible to fulfill on a daily basis. Also, we start to make our approach work with continuous changes. Our recommended scheme is both verifiably safe and essentially productive, as shown by the privacy analysis and test evaluations.
Robust optimal control of a nonlinear impulsive time-delay system for 1,3-PD fed-batch culture

In this paper, taking the feeding process as a form of impulsive and considering the time-delay in fermentation process. A robust model with the time-delay system as the control variable and the time-delay system as the constraint is established. In order to solve this optimal control problem, we have propose an particle swarm optimization method to solve problem. Numerical results show that 1,3-PD yield at the terminal time increases compared with the experimental result.
SELNN: Effective Crossover Features by Attention Mechanism and Logarithmic Conversion for CTR

With the continuous increase of web resources, information overload is becoming more and more serious. Getting the information that meets the needs of a large amount of data has become an urgent problem. One of the popular studies in click-through rate prediction is to construct feature interactions to improve prediction accuracy. Traditional models with low-order interactions cannot adequately represent the intersection information, and deep models with undifferentiated feature intersections lack relevance. In this paper, we propose a model called SELNN, which improves the accuracy of click-through rate prediction through attention mechanism and logarithmic conversion. On the one hand, improving attention mechanisms learns the importance of each feature itself. On the other hand, combining logarithmic conversion structure with feedforward neural networks to learn different orders of feature interactions. The experimental results indicated that the AUC values of SELNN on the Criteo and Movielens-1M datasets were 81.46% and 87.36%, respectively. SELNN effectively improves the prediction accuracy and reduces the number of parameters and computational effort.
Research on threat detection in cyber security based on machine learning

The volume of the data has been rocketed since the new information era arrives. How to protect information privacy and detect the threat whenever the intrusion happens has become a hot topic. In this essay, we are going to look into the latest machine learning techniques (including deep learning) which are applicable in intrusion detection, malware detection, and vulnerability detection. And the comparison between the traditional methods and novel methods will be demonstrated in detail. Specially, we would examine the whole experiment process of representative examples from recent research projects to give a better insight into how the models function and cooperate. In addition, some potential problems and improvements would be illustrated at the end of each section.
Evaluation of Earthquake-Damaged Concrete and Masonry Wall Buildings

Efforts at improving earthquake recovery policies have been hampered by a lack of criteria and standards for evaluating and repairing damaged buildings. The Applied Technology Council has developed a performance-based methodology for the evaluation of earthquake-damaged concrete wall buildings and masonry wall buildings, recently published as FEMA 306/307/308. The methodology provides a way to quantify damage in terms of loss of seismic performance capability. It also provides guidelines for remedial measures to restore or improve seismic performance capability. In this methodology, the expected future seismic performance of a building is evaluated in its pre-event, damaged, and repaired conditions. Following the nonlinear static analysis procedure, displacement demands and capacities of the structure are used as indices of seismic performance. Identifying the governing mechanism of nonlinear deformation and the behavior mode of a structure and its components is shown to be a necessary first step towards evaluating expected seismic performance, interpreting indications of damage, and assessing their significance. The methodology provides a technical resource for understanding how buildings respond seismically on both global and component levels, and gives a basis for formulating post-earthquake policies.
Magnetic Sensors and Magnetometers

Thin Film Magnetoresistive SensorsRecent Trends on Electromagnetic Environmental Effects for Aeronautics and Space ApplicationsMagnetic Sensors and Magnetometers, 2eOptimizing Nitrogen-vacancy Diamond Magnetic Sensors and Imagers for Broadband SensitivityHall Effect in Semiconductors and Magnetic SensorsTransducers ’01 Eurosensors XVNanomagnetismLow-Power and High-Sensitivity Magnetic Sensors and SystemsSmart Sensors for Industrial ApplicationsMagnetometersOptical MagnetometryMagnetic Actuators and SensorsMagnetic Field Sensing Using Micromechanical OscillatorsSQUID SensorsMake: SensorsMagnetic SensorsSolid State Magnetic SensorsAeronautics and AstronauticsMagnetic SensorsMagnetic Sensors and MagnetometersSensor Analysis for the Internet of ThingsHigh Sensitivity MagnetometersVector AC Stark Shift in 133Cs Atomic Magnetometers with Antirelaraxion Coated CellsThe MEMS Flux Concentrator: Potential Low-Cost, High-Sensitivity MagnetometerMEMS Lorentz Force MagnetometersHandbook of Magnetic MaterialsMagnetic Sensors and DevicesSmart Actuation and Sensing SystemsMagnetic Sensors for Biomedical ApplicationsGiant Magnetoresistance (GMR) SensorsModeling and Measurement Methods for Acoustic Waves and for Acoustic MicrodevicesHigh Sensitivity Magnetometers. Sensors and ApplicationsA Procedure for Calibrating Magnetic SensorsMagnetic Sensors and Magnetometers, Second EditionSensors, Magnetic SensorsElectrical Compliance and Safety Engineering Volume 2Human Behavior UnderstandingHall Effect Devices, Second EditionMagnetic Sensors and DevicesBasic Sensors in IOS
The influence of the duration of the “subjective day” under intermittent LED lighting on the daily rhythm of oviposition and the productivity of hens

Lighting is the key factor affecting oviposition time. The oviposition time is directly related to ovulation, which occurs 5 hours after reaching the peak concentration of luteinizing hormone in the blood, which depends on the lighting regime. This paper studies the impact of the “subjective day” duration under intermittent LED lighting on the daily rhythm of oviposition and the productivity of hens of the productive flocks of cross SP-789. The “subjective day” lasted 16 hours per day for group 1, 15 h for group 2, 14 h for group 3 and 13 h for group 4. It was established that the shorter the duration of the “subjective day”, the earlier the hens begin and finish laying. So, in groups 1, 2, 3, and 4, hens began laying eggs at 4 a.m., 3 a.m., 2 a.m., and 1 a.m. and ended at 6 p.m. , 4 p.m. , 4 p.m. , and 3 p.m. with an average time of laying eggs of 8.67; 7.36; 5.36 and 5.27 h, respectively. In groups 1, 2, 3, and 4 the livability of hens, weight of eggs, egg production and yield of egg weight per the initial laying hen, feed consumption for 10 eggs and 1 kg of egg weight were 98.0, 97.0, 99.0, 99.0%; 60.0, 59.9, 60.4, 59.7 g; 123.9, 124.1, 130.3, 126.1 pcs, 7.48, 7.47, 7.97, 7.63 kg; 1.37, 1.36, 1.32, 1.36, and 2.28, 2.26, 2.18, 2.26 kg, respectively.
False News Recognition Using Machine Learning

In these modern times where internet has become widely popular and used by almost everyone, anyone can share or upload articles without any credibility. False news refers to articles that are published with the intent of deliberately misleading readers. In the recent times false news on internet has become more and it has become a major problem as it is difficult to differentiate between the real and the false news. False news and false posts have become more prevalent on social media sites such as Face book and Twitter. From these platforms the news will be spread like wild fire without any authenticity. It can be used to sway election outcomes against certain candidates, can be used for click baiting purposes, and can be used to earn revenue by misleading the users. In this paper we will use natural language processing techniques like bag of words and TD-IDF and machine learning concepts of classification algorithms like SVM and passive aggressive classifier to train our machine to differentiate false news from real news and we will compare the accuracy of methods used to find accurate model.
Comparative analysis of dynamic state recognition between permutation entropy and weighted permutation entropy

Permutation entropy (PE) and weighted permutation entropy (WPE) are indexes of the complex system. In this paper, the nonlinear sequence of two chaotic states is simulated by Logistic mapping, and the effectiveness of the PE and WPE algorithms in chaotic state recognition is compared and analyzed with different sliding step sizes. The results show that the value of WPE changes more obviously than PE in different chaotic states, and the recognition effect of WPE is better than PE in dynamic states, which can provide theoretical support for further analyzing the complexity characteristics of actual data.
Profitability Analysis of Poultry Egg Production in Bauchi Local Government Area of Bauchi State, Nigeria

The study, profitability analysis of poultry egg production in Bauchi Local Government Area ( LGA) of Bauchi State was conducted to examine the profitability of poultry egg production based on the different scale of production found in the study area. The study used all the 37 farm units of poultry egg production in the area. Farm budgeting technique and profitability indices were used to analyze the profitability of the small, medium and large scale poultry production and the result was found to be ₦0.26, ₦ 0.28 and ₦ 0.30 respectively. ANOVA and LSD tests confirmed that though the figures from the profitability indices were close, but are statistically different. Although egg production was found to be profitable, it was recommended that the scale of production be increased. ________________________________________________________________________________________
Measurement and Analysis of Ocean Current using High- Frequency (HF) Radar Observation in the Bali Strait

High-Frequency (HF) Radar is an instrument using radio waves to measure ocean currents and waves remotely. This technology has many advantages, including has unprecedented spatial and temporal resolution, can operate in any weather condition, and is not dangerous for the environment. However, HF Radar's research is still limited in Indonesia. This research aimed to analyze the tidal and residual current in the Bali Strait in July 2020. Radial velocity from two HF Radar sites is combined to obtain the total currents. Current data from HF Radar were compared with Acoustic Doppler Current Profiler (ADCP) data to investigate its accuracy. Surface current data were analyzed using harmonic analysis to separate tidal and residual currents. Comparison between HF Radar and ADCP data are in good agreement for meridional current with a very high correlation of 0.813 and a small RMSE value of 0.22 m/s. Harmonic analysis shows that the dominant currents are tidal currents. The current direction was northward (southward) at flood (ebb), with maximum northward (southward) velocities are 2.17 m/s (2.97 m/s), respectively. The residual current has a random pattern, slightly faster northward than southward, and has similar spectral with the wind.
Choice Experiment: The Benefits of Living Heritage Conservation in Melaka City, Malaysia

Melaka living heritage is a unique living testimony to the multi-cultural heritage and tradition of Asia from the past with great national and international significance, recognised by UNESCO as World Heritage Site in year 2008. Despite the great opportunities for conserving the living heritage in Melaka, the city is currently facing threats of high traffic, excessive depletion of the natural environment in the city. This is due to underestimation on the non-market values of living heritage in development decisions. The aim of this study is to estimate the economic benefit of living heritage in Melaka city as the results would be able to provide insight to the value of this unique heritage to the society. The method employed is Choice Experiment (CE). The payment vehicle opted in this study is via accommodation, where a fixed heritage charge per night was included in the total accommodation bill in Melaka. In CE, four attributes of non-market value of the city were defined; living heritage, natural environment, crowded recreational activities and heritage charge value. A total of 502 respondents were interviewed in person, using random stratified sampling method. The attribute for crowded recreational activities in the city provides the highest probability for the respondents for this study to pay for an improvement level. While living heritage attribute has a negative probability of the respondents to pay for a higher level of this attribute. The results of valuation can help to convince the government and other decision makers to allocate more resources for conservation. Quantifying the major benefits provided by living heritage can provide invaluable support to the conservation efforts and the WTP results could encourage policy-makers to set priorities to ensure that the living heritage would be conserved in proper manner.
The Influence of Noise in the Super-Resolution Reconstruction of Structured Illumination Microscopy

As one of the mainstream super-resolution imaging technologies, structured illumination microscopy (SIM) is popular for its fast imaging speed and simple optical path structure. Spectrum separation is a key step in the reconstruction of super-resolution images. However, in the process of imaging, the unavoidable noise will seriously affect the accuracy of frequency spectrum separation. This paper carries out a simulation study on the influence of noise in the process of frequency spectrum separation. The results show that although noise can cause distortion of low-frequency information in frequency spectrum separation results, it has little influence on high-frequency information. Therefore, a super-resolution image reconstruction method is proposed to effectively suppress the influence of noise. Both simulation and experimental results are shown the method can suppress the influence of noise without losing the details of super-resolution.
A Survey on Security of the Hadoop Framework in the Environment of Bigdata

The world is becoming increasingly digital at the moment. Every day, a significant amount of data is generated by everyone who uses the internet nowadays. The data are critical for carrying out day-to-day operations, as well as assisting corporate management in achieving their objectives and making the best judgments possible based on the information gathered. BigData is the process of merging many hardware and software solutions to deal with extremely huge amounts of data that surpass storage capability. It’s possible that large amounts of data will be generated. Hadoop systems are used in a variety of areas, including healthcare, finance, and government. insurance, and social media, in order to provide a quick and cost-effective big data solution. The Apache Hadoop is a framework for storing and processing data, managing, and distributing large amounts of information over a large number of server nodes. Here are some solutions that work on top of the Apache Hadoop stack to guarantee data security. To get a complete picture of the problem, we decided to conduct an investigation into existing security solutions for Apache Hadoop security in sensitive data which is stored on a huge data platform employing distributed computing on a cluster of commodity devices. The goal of this paper is to provide knowledge of security and Big Data issues.
Continuous central venous

D. L. Bredle Department of Kinesiology, University of Wisconsin–Eau Claire, Eau Claire, Wis. , USA Abstract Objective: To compare the course of continuously measured mixed and central venous O2 saturations in high-risk patients and to evaluate the impact of various factors that might interfere with reflection spectrophotometry. Design and setting: Prospective, descriptive study in the interdisciplinary ICU of a university hospital. Patients: 32 critically ill patients with triple-lumen central vein catheters, including 29 patients requiring pulmonary artery catheterization. Interventions: The accuracy of fiberoptic measurements was assessed by comparison to reference co-oximeter results at regular intervals. We examined the effect on measurement accuracy of physiological variables including hematocrit, hemoglobin, pH, temperature, and the administration of various solutions via central venous catheter. Continuous parallel measurements of SvO2 and ScvO2 were performed in patients with each type of catheters over a total observation time of 1097 h. Results: ScvO2 values were more accurate and stable than in vitro oximeter measurements (r=0.96 from 150 samples, mean difference 0.15%, average drift 0.10%/day) and was not significantly affected by synchronous infusion therapy or by changes in hematocrit, hemoglobin, pH, or temperature. ScvO2 values closely paralleled SvO2, whether measured in vitro (r=0.88 from 150 samples) or in vivo (r=0.81 from 395,128 samples) but averaged about 7€4 saturation percentage higher. ScvO2 changed in parallel in 90% of the 1,498 instances in which SvO2 changed more than 5% (over an average of 43 min). Conclusions: Continuous fiberoptic measurement of central vein O2 saturation has potential to be a reliable and convenient tool which could rapidly warn of acute change in the oxygen supply/demand ratio of critically ill patients.
An Active "Cold" Noise Source

An active circuit which behaves like a "cold" noise source is described. The circuit which uses a gallium arsenide FET is given the name COLFET. The appropriate theory is developed and practical circuits described using the circuit. Equivalent noise temperatures of less than 50 K have been measured for a 50-omega source at 1400 MHz.
An Analysis of How Social Media Impacts Financial Markets

In this paper, I examine how social media affects cryptocurrencies and more traditional stocks. I use data on Twitter posts in combination with daily stock prices to estimate the causal effect of a tweet on stock and coin prices. To do this, I use a difference-indifference regression with index funds as my control group, which allows me to capture general market trends that coins and stocks would follow if not for intervention. I find that tweets have a significant impact on cryptocurrencies that last up to three days after the post. The increase in coin prices is driven by tweets from Tyler Winklevoss and tweets about Tezos and Ethereum specifically. Meanwhile, Twitter posts have no impact on more traditional stocks. These results suggest that social media can provide the public with valuable information in real time for fast moving and volatile crypto assets, while their effects on more stable and institutionalized traditional stocks are more muted.