Miracle-dz/UniFAR-FTUs huggingface dataset:
OFDM System Location Determination with 4-element Antenna Array Using Frequency Domain Matrix Pencil (FDMP) Method

A 3D location determination method using only four elements antenna is proposed for OFDM systems which are commonly used in the 4G. A group of frequencies is received from the transmitter (on mobile phone) or returned signals (Radar). The Matrix Pencil method is used to identify the length of each path. Depending on the geometrical distribution of the four elements, the phase shifts are determined for each path. Knowing the phase shift between the elements helps to flnd the Direction of Arrival (DOA) for each path. Small dipole antennas are used in the numerical examples to clarify this location determination method in the presence of complex noise in the OFDM systems. As known the OFDM is a multi-carrier technique that has recently received considerable attention for high speed wireless communication. Most WLAN systems currently use the IEEE802.11b standard, which provides a maximum data rate of 11Mbps. Newer WLAN standards such as IEEE802.11a and HiperLAN are based on OFDM technology and provide a much higher data rate of 54Mbps. However systems of the near future will require WLANs with data rates of greater than 100Mbps, and so there is a need to further improve the spectral e-ciency and data capacity of OFDM systems in WLAN applications. For cellular mobile applications, we will see in the near future a complete convergence of mobile phone technology, computing, Internet access, and potentially many improved multimedia applications such as high quality video and audio. In fact, some may argue that this convergence has already largely occurred, with the advent of being able to send and receive data using a notebook computer and a mobile phone. The use of frequency diversity, within the framework of narrowband signals for identiflcation of multipaths can be used for distance determination. Based on this technique, DOA and location determination using only four elements are achieved. The procedure depends on sending a group of narrowband tones and sub-carriers from the mobile set to the base station then using the MP method (1{4) for distance determination. This procedure is applied to four small dipole antennas to get the location determination in the OFDM.
Anomaly detection in Multivariate Temporal Data for Vessels Anomaly detection in Multivariate Temporal Data for Vessels

The growing number of deployed data mining systems leverage the interest in temporal data anomaly detection. From cyber-security or finance to heart-diseases detection, unexpected data often incorporate critical information that must be analysed. Data anomalies have long been studied from an univariate perspective where only one data dimension changes over time. Few works have been dedicated to multivariate anomaly detection. In this work we provide a comprehensive and structured analysis of the main definitions, state-of-art methods and approaches focusing multivariate temporal data anomaly detection. Our research focus on dealing with variable length data series with millions of samples and multiple feature categories, either static or dynamic, real or categorical valued. We describe a case-study in the maritime domain investigating the unusual spatio-temporal behaviour of commercial vessels and experiment over two open datasets and one got from the MARISA H2020 Project 1 .
The Impact of Freedom on Fertility Transition:

Demographers have worked for decades to identify the conditions common to the final stages of the demographic transition. The most widely respected theoretical explanations of fertility decline focus on couples’ decisions about their family size, decisions presumed to be driven by distal factors in society that are usually socioeconomic in nature. The theoretical explanations generally overlook the many barriers preventing women from having fertility regulation methods and the information they need to manage whether or when to have a child. Many of these barriers are often ignored by policy makers, even though from the consumer perspective they may be virtually insurmountable. This paper suggests that an opportunity model, which could also be viewed as an adjustment to existing theory, may provide a plausible explanation for the timing and pace of fertility decline. It proposes that what is often viewed as latent desire by women to control their fertility, ascribed to those women who used contraception or desired a smaller family size in the absence of the normally expected distal factors, may be simply a shift in the results of their implicit cost-benefit analyses. Women’s success in managing their childbearing appears to be largely dependent on their opportunities. In recognizing women’s rational reasoning based on the information they have available, from a policy perspective it is important to ensure that the barriers to the correct information and the technologies they need are reduced, as called for in ICPD. With this perspective, we can see that average family size can decline, and often has declined, by purely voluntary means, within a human rights framework. Introduction “A theory is a good theory,” writes Stephen Hawking,“ if it satisfies two requirements. It must accurately describe a large class of observations on the basis of a model that contains only a few arbitrary elements, and it must make definite predictions about the results of future observations. ” (Hawking, 1988)(page 9). Classic and economic theoretical explanations of the demographic transition neither predicted nor explained the below replacement level fertility now found in Russia, parts of Europe or Japan. The classic and economic theories do not explain the fall in Iran’s total fertility rate (TFR) from 5.2 to 2 in the 12 years between 1988 and 2000 (Vahidnia, 2007, Tarmann, 2005), or Addis Ababa’s decline in TFR to 1.6 while the whole of Ethiopia remained at a TFR of
Mobile-based Cattle Infectious Disease Prediction System

: It is not easy to notice the infectious disease that can spread among the herd of animals, such as cattle, sheep, etc without daily care and diagnosis. However, it is expensive to give daily care in detail by human to them due to large number of animals and expensive costs of veterinary. This paper presents a novel prediction algorithm for diagnosing cattle’s infectious disease with mobile based information system. It mainly uses Naïve Bayes classifiers to classify the level of risk affected to cattle by observing six baseline syndrome patterns of animal health such as body weight, ambulatory lameness, decreased feed intake/milk production, respiratory, skin/ocular/mammary and gastrointestinal signs. The system firstly uploads the abnormal information detected from cattle to our mobile based system. It then analyzes them using Naïve Bayes classification algorithm to know what kind of diseases currently affect to them and give suggestion the method of cure for earlier protection to them. The paper then performs the experiments with the cattle baseline patterns surveyed from different five livestock area in Myanmar. The results show that our prediction algorithm produces accurate results (95.6% for almost each 600 data patterns obtained, from each area, about 3000 in total) and could help those who are thriving in need of human veterinary to analyze their cattle’s health conditions.
Preparation of Hybrid Sol-Gel Materials Based on Living Cells of Microorganisms and Their Application in Nanotechnology

Microorganism-cell-based biohybrid materials have attracted considerable attention over the last several decades. They are applied in a broad spectrum of areas, such as nanotechnologies, environmental biotechnology, biomedicine, synthetic chemistry, and bioelectronics. Sol-gel technology allows us to obtain a wide range of high-purity materials from nanopowders to thin-film coatings with high efficiency and low cost, which makes it one of the preferred techniques for creating organic-inorganic matrices for biocomponent immobilization. This review focuses on the synthesis and application of hybrid sol-gel materials obtained by encapsulation of microorganism cells in an inorganic matrix based on silicon, aluminum, and transition metals. The type of immobilized cells, precursors used, types of nanomaterials obtained, and their practical applications were analyzed in detail. In addition, techniques for increasing the microorganism effective time of functioning and the possibility of using sol-gel hybrid materials in catalysis are discussed.
Relational analysis of Emotion and Performance

: A number of factors are important in daily life for consideration of ‘Stress of Study’. Main factors giving Stress is an increase in competition. In research, we are imposing a new approach of stress detection and classification for students during the examination period. We used MFCC (Mel-frequency cepstral coefficients) for feature extraction and SVM (Support vector Machine) classifier for better performance. In this system three types of corpus have been tested and classified. Support Vector Machine combines with the Rule base approach with Energy and Fundamental Frequency rules. Indian Dataset is created by 50 students, including male and female both. Testing of corpus proved that Native area, Nationality and living place effects on speech frequencies. At the end of result analysis, we can see that Indians normal speech frequency is nearby equal to the Mongolian angry frequency. Accuracy of system achieved more than 90% for depressive stress and aggressive stress. The result proved that in the examination period performance of students increases in exited and decreases in a depressive state. This research addresses the impact of stress on the student performance during the examination period.
Design Optimization of a Cross-Flow Air Turbine for an Oscillating Water Column Wave Energy Converter

A cross-flow air turbine, which is a self-rectifying, air-driven turbine, was designed and proposed for the power take-off (PTO) system of an oscillating water column (OWC) wave energy converter (WEC). To predict the complicated non-linear behavior of the air turbine in the OWC, numerical and experimental investigations were accomplished. The geometries of the nozzle and the rotor of the turbine were optimized under steady-flow conditions, and the performance analysis of the model in bi-directional flows was conducted by commercial computational fluid dynamics (CFD) code ANSYS CFX. Experimentation on the full-scale turbine was then undertaken in a cylindrical-type wave simulator that generated reciprocating air flows, to validate the numerical model. The optimized model had a peak cycle-averaged efficiency of 0.611, which is 1.7% larger than that of the reference model, and a significantly improved band width with an increase in flow coefficients. Under reciprocating-flow conditions, the optimized model had a more improved operating range with high efficiency compared to the performance derived from the steady-flow analysis, but the peak cycle-averaged efficiency was decreased by 4.3%. The numerical model was well matched to the experimental results with an averaged difference of 3.5%. The proposed optimal design having structural simplicity with high performance can be a good option to efficiently generate electricity.
Preoperative Neurosurgical Planning

Knowledge of the location of nerve tracts during the surgical preoperative planning stage and during the surgery itself may help neurosurgeons limit the risk of causing neurological deficits affecting the patient’s essential abilities. Development of MRI techniques has helped profoundly with in vivo visualization of the brain’s anatomy, enabling to obtain images within minutes. Different methodologies are relied upon to identify anatomical or functional details and to determine the movement of water molecules, thus allowing to track nerve fibers. However, precise determination of their location continues to be a labor-intensive task that requires the participation of highly-trained medical experts. With the development of computational methods, machine learning and artificial intelligence, many approaches have been proposed to automate and streamline that process, consequently facilitating image-based diagnostics. This paper reviews these methods focusing on their potential use in neurosurgery for better planning and intraoperative
DEVELOPMENT OF A SIMPLE SOURCE – REFERENCED CURRENT VOLTAGE MODEL

: for Low Power CMOS Analog Design the requirements of modeling MOS Devices are both very demanding and stringent. For low power the devices operate at low voltage and low current. The operating regions of the devices pertain to strong, moderate and weak inversion modes with its characteristics device physics and model parameters. From simulation viewpoint the major concern of model development has been the continuity of current and model parameters in the transition region of these modes of operation. For a compact model for analog design these issues have to be addressed along with the effects of scaling down to submicron level. The paper discuss briefly the study of development of a simple source –referenced current voltage model, Review of two and three terminal MOS capacitor (Definition of Strong, Moderate and Weak Inversion, Threshold Voltage, Capacitance-Voltage Characteristics), and Criteria for compact MOSFET model with reference to Low Power Analog Design.
Physical, structural, optical and gamma-ray shielding properties of Na2O-CdO-Bi2O3-B2O3 glasses

Research on materials for radiation protection has burgeoned in the last decades. This increase is related to the widespread of using this type of ionizing radiation worldwide. Thus, for example, in 2019, there are more than 448 nuclear power plants in the world.1 The ionizing radiation has enough energy to penetrate and release electrons from specific composition.2 In the human tissue, low risk can be predicted if the released ions recombine and probability of healing is extremely high. The greatest concern is not the immediate effect of radiation, but the long-term effects that may take years to develop (such as leukemia, with its 10-year incubation period). 3 The radiation protection is a concept that shows the possibility of prevent deterministic effects and minimize stochastic effects of exposure to ionizing radiation.4 For a long time, concretes and lead were the standard choice for radiation shielding, but both show undesirable properties. For instance, concrete Received: 1 July 2020 | Revised: 21 September 2020 | Accepted: 8 October 2020 DOI: 10.1111/ijag.15859
Hypoactive Sexual Desire Disorder among Menopausal Women in Moroccan and Factors Influencing It

Introduction: Various factors can influence the sexual desire of postmenopausal women, which affects the quality of their life; mental well-being associated risk factors for Female problem of sexual desire in post-menopausal women with Muslim culture from health center of morocco. Methods: This cross-sectional study investigated 125 women (35 and 50 years and more) from September 2018 to September 2019 in the settat city of morocco. The questionnaire used in this study has included several demographic, socio-economic, diabetes, medications and stress. To do this statistical analysis, we used a IBM SPSS Statistics software, Chicago Illinois, version 21. Results: The average age of the women in this study was average 50 ± 4, 35 years. The results of the linear regression factors such a low socioeconomic level (p < 0.001), diabetes (97.2%, p <0.001), medication (100%, p< 0.001), stress (98%, p <0.0001), a Exercising (100%, p < 0.048). ); First traumatic sexual intercourse (77.8%; p = 0.002) marriage age at age 25 and over (100%; p = 0.001) significantly affected sexual desire. Multivariate analysis showed that the odds of Hypoactive Sexual Desire Disorder were significantly increased with older age (odds ratio, OR = 1, 07), low and moderate socioeconomic level (OR = 1.20), presence of Diabetic (OR = 1.22). Conclusion: It can be concluded from the findings of this study that several factors affecting the Hypoactive Sexual Desire Disorder age, low socioeconomic level, diabetes, medications. It is necessary to devote more careful attention to Hypoactive Sexual Desire Disorder in menopausal.
A Novel Time-to-Digital Converter Based on Low-Jitter Phase-Locked Loop

ABSTRACT This paper presents a novel multi-levels time-to-digital converter (TDC) suitable for array architecture for the photon time-of-flight (TOF) measurement. A simple method was applied to solve the initial phase time mismatch caused by random occurrence of the TOF start signal. A low-jitter phase-locked loop (PLL) is adopted to provide excellent clocks to the TDC. The proposed PLL–TDC has a good differential nonlinearity (DNL) (±0.4 LSB) and integral nonlinearity (INL) (±0.5 LSB) due to the low-jitter clock and elimination of initial phase time mismatch. The circuit of the low-jitter PLL was implemented in TSMC 0.35 µm standard complementary metal oxide semiconductor (CMOS) process with 3.3 V supply voltage. The measured result of the low-jitter PLL and the simulated result of the TDC show the proposed 14-bit TDC can realize 1.0 ns time resolution and 16 µs maximum range with 125 MHz centre frequency. Under this given frequency, the time interval error (TIE) jitter is 7.8 ps(rms).
Optimales Design und Scheduling einer Smart City Optimal Design and Scheduling of a Smart City Under Uncertain Renewable Energy Generation

Increasing the share of renewable energy while maintaining a high degree of self-suﬃciency is a major challenge within energy system design for cities. This work uses a two-stage stochastic program, formulated as a mixed integer linear program to optimise the energy system of a city under additional constrains of self suﬃciency. Multiple uncertainties have to be addressed during optimal design of energy systems. Energy production from solar and wind power as well as energy demand are considered uncertain. A tech-nique aggregating historical data into typical periods is used for scenario generation. Using a case study of a city in western Germany, the eﬀects of either using typical days or typical weeks during scenario generation and diﬀerent self-suﬃciency enforcing strategies and levels on the resulting optimal design were examined. Longer typical periods seem to increase the ﬂexibility in the operating schedule regarding storage components. With more aggressive strategies and higher levels of self-suﬃciency, we observe a displacement of varying and uncertain energy sources by stable and deterministic ones.
Guiding Lens-based Exploration using Annotation Graphs

We introduce a novel approach for guiding users in the exploration of annotated 2D models using interactive visualization lenses. Information on the interesting areas of the model is encoded in an annotation graph generated at authoring time. Each graph node contains an annotation, in the form of a visual markup of the area of interest, as well as the optimal lens parameters that should be used to explore the annotated area and a scalar representing the annotation importance. Graph edges are used, instead, to represent preferred ordering relations in the presentation of annotations. A scalar associated to each edge determines the strength of this prescription. At run-time, the graph is exploited to assist users in their navigation by determining the next best annotation in the database and moving the lens towards it when the user releases interactive control. The selection is based on the current view and lens parameters, the graph content and structure, and the navigation history. This approach supports the seamless blending of an automatic tour of the data with interactive lens-based exploration. The approach is tested and discussed in the context of the exploration of multi-layer relightable models.
Motivated Risk Assessments

How do people assess risks associated with a hedonic but dangerous activity? I conduct a longitudinal field experiment (N=434) exploiting the conditions of the COVID-19 pandemic to investigate whether monetary incentives induce people to motivate their risk assessments. Each participant receives a café voucher with a random value: treated participants receive a 10EUR voucher, and the control group a 1.50EUR voucher. The results show that subjects who receive a high incentive not only visit cafés more often but also reduce their risk assessment relative to subjects with a low incentive. Importantly, the assessment updating happens in anticipation of the visit, suggesting that it justifies a risky activity. This finding is inconsistent with the standard notion of Bayesian updating but consistent with motivated reasoning. It is robust to different risk measures (incentivized and non-incentivized) and does not lend support for alternative explanations, such as visits at less busy times or additional information acquisition. The data further suggests that the formation of motivated risk assessments is supported by selective recall of previous assessments. Treated subjects systematically underestimate former assessments relative to subejects in the control group. JEL codes: C93, D03, D91
On the Variations of Shunt Characterization Technique of Decoupling Transmission Line for Millimeter-Wave CMOS Applications

Decoupling transmission line (TL) is a low characteristic impedance TL that is used for isolating DC and RF signals in millimeter-wave CMOS circuits. Low characteristic impedance makes the direct measurements difficult for characterization. A shunt characterization method is presented for the characterization. In this method, the S-parameters are calculated directly. Nevertheless, the results might change according to calculation procedure. In this work, variations on shunt characterization method are investigated and their effects on millimeter-wave CMOS amplifier simulation accuracy are introduced. Keyword CMOS, decoupling transmission line, metal-insulator-metal, shunt characterization, mm-wave, variations
Explore, Edit, Guess: Understanding Novice Programmers' Use of CodeBlocks for Regression Experiments

Machine Learning (ML) suites, while readily available for practical use, are not easily usable. There are several publicly available packaged software and console libraries that are available as well. However, novice programmers tend to avoid these ML suites due to the abstractions with pre-existing tools. Users who know how these models work have limited programming experience and therefore struggle with making practical use of these ML suites. To address this, we present TREX: A Toolbox for Regression Experiments which uses code-blocks. It provides a sandbox environment so novices can freely use and experiment with models and bridge how these models and code work altogether. First, we developed a prototype following an iterative approach, focusing on linear regression tasks. Across several software iterations, multiple usability tests involving at least 33 respondents participated. Second, we observed how they went through their ML tasks and inquired into their pains and struggles in writing code. Lastly, we analysed these findings and provided recommendations for the future design of interactive ML tools.