Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating Bayes Factors for Linear Models with Random Slopes on Continuous Predictors

Using mixed-effects models and Bayesian statistics has been advocated by statisticians in recent years. Mixed-effects models allow researchers to adequately account for the structure in the data. Bayesian statistics – in contrast to frequentist statistics – can state the evidence in favor of or against an effect of interest. For frequentist statistical methods, it is known that mixed models can lead to serious over-estimation of evidence in favor of an effect (i.e., inflated Type-I error rate) when models fail to include individual differences in the effect sizes of predictors ("random slopes") that are actually present in the data. Here, we show through simulation that the same problem exists for Bayesian mixed models. Yet, at present there is no easy-to-use application that allows for the estimation of Bayes Factors for mixed models with random slopes on continuous predictors. Here, we close this gap by introducing a new R package called BayesRS. We tested its functionality in four simulation studies. They show that BayesRS offers a reliable and valid tool to compute Bayes Factors. BayesRS also allows users to account for correlations between random effects. In a fifth simulation study we show, however, that doing so leads to slight underestimation of the evidence in favor of an actually present effect. We only recommend modeling correlations between random effects when they are of primary interest and when sample size is large enough. BayesRS is available under https://CRAN.R-project.org/package=BayesRS. BAYES FACTORS FOR LINEAR MIXED-EFFECTS MODELS 3
Sub-optimal Ultra-wide Band Receivers

Ultra-wide Band (UWB) has sparked a lot of interest lately from the industry and academia. The growing capacity of the wireless industry is requires a new communication system that satisfies the high data rate which does not interfere with existing RF systems. UWB promises to be this new technology. UWB also promises low power, low cost and flexibility. The UWB Channel opens up a huge new wireless channel with Giga Hertz Capacities as well as the highest spatial capacities measured in bits per hertz per square meter. When properly implemented UWB channel can share spectrum with traditional radio systems without causing harmful interference. In this thesis we studied and compared several reduced complexity sub-optimal Ultra-Wide Band receivers. These receivers include auto correlation receiver, the square value detector and the absolute value detector are studied. We consider OOK and PPM modulation schemes. We examine these schemes and the receivers on Gaussian and UWB indoor channels. We compare the performance with
Does the gamma-ray signal from the central Milky Way indicate Sommerfeld enhancement of dark matter annihilation?

Recently, some studies showed that the GeV gamma-ray excess signal from the central Milky Way can be explained by the annihilation of ∼ 40 GeV dark matter through the bb̄ channel. Based on the morphology of the gamma-ray flux, the best-fit inner slope of the dark matter density profile is γ = 1.26. However, recent analyses of the Milky Way dark matter profile favor γ = 0.6 – 0.8. In this article, we show that the GeV gamma-ray excess can also be explained by the Sommerfeld-enhanced dark matter annihilation through the bb̄ channel with γ = 0.85 – 1.05. We constrain the parameters of the Sommerfeld-enhanced annihilation by using data from Fermi-LAT. We also show that the predicted gamma-ray fluxes emitted from dwarf galaxies generally satisfy recent upper limits on gamma-ray fluxes detected by Fermi-LAT.
DISCOVERY OF FIVE CANDIDATE ANALOGS FOR η CARINAE IN NEARBY GALAXIES

The late-stage evolution of very massive stars such as η Carinae may be dominated by episodic mass ejections that may later lead to Type II superluminous supernova (SLSN-II; e.g., SN 2006gy). However, as long as η Car is one of a kind, it is nearly impossible to quantitatively evaluate these possibilities. Here, we announce the discovery of five objects in the nearby (∼4–8 Mpc) massive star-forming galaxies M51, M83, M101, and NGC 6946 that have optical through mid-infrared (mid-IR) photometric properties consistent with the hitherto unique η Car. The Spitzer mid-IR spectral energy distributions of these Lbol ≃ 3–8 × 106 L⊙ objects rise steeply in the 3.6–8 μm bands and then turn over between 8 and 24 μm, indicating the presence of warm (∼400–600 K) circumstellar dust. Their optical counterparts in HST images are ∼1.5–2 dex fainter than their mid-IR peaks and require the presence of ∼5–10 M⊙ of obscuring material. Our finding implies that the rate of η Car–like events is a fraction f = 0.094 (0.040 < f < 0.21 at 90% confidence) of the core-collapse supernova (ccSN) rate. If there is only one eruption mechanism and Type II superluminous supernovae are due to ccSNe occurring inside these dense shells, then the ejection mechanism is likely associated with the onset of carbon burning (∼103–104 years), which is also consistent with the apparent ages of massive Galactic shells.
Is ventricular deformation affine

Recent advances in cardiac diffusion tensor imaging (DTI) have enabled robust imaging of the in vivo heart [1]. This allows to non-invasively assess myofiber and myosheet orientations, which has been a long-standing bottleneck of patient-specific cardiac modeling [2]. Thanks to efficient sequence design, in vivo DTI has even been performed in patients [3] and at multiple cardiac phases [4]. In this study, we analyze dual phase cardiac DTI data of normal humans to investigate the affinity of ventricular deformation. The angulation data is compared to predictions based on myofiber transportation by macroscopic deformation, to quantify the potential relative sliding between myofibers.
Denial of Service Attack on Protocols for Smart Grid Communications

In this work, a denial of service (DoS) attack known as the clogging attack has been performed on three different modern protocols for smart grid (SG) communications. The first protocol provides authentication between smart meters (SM) and a security and authentication server (SAS). The second protocol facilitates secure and private communications between electric vehicles (EV) and the smart grid. The third protocol is a secure and efficient key distribution protocol for the smart grid. The protocols differ in either their applications (authentication, key distribution), or their ways of communications (usage of encryption, hashes, timestamps etc.). But they are similar in their purpose of design (for the smart grid) and their usage of computationally intensive mathematical operations (modular exponentiation, ECC) to implement security. Solutions to protect these protocols against this attack are then illustrated along with identifying the causes behind the occurrence of this vulnerability in SG communication protocols in general.
Adaptive Bands Z-Test-Statistics in Futures Markets: A New Technical Analysis Indicator

This paper presents a study of technical analysis trading rules that generate abnormal returns for futures prices. It reports abnormal returns above that of the passive buyand-hold policy for FKLI, FCPO, Soybean Oil Futures, Soybean Futures and Corn Futures for year 2008 tested. This research devises a new technical analysis indicator, Adaptive Bands Z-Test-Statistics, using adaptive standard deviation. One of the most baffling issues that confronts market technicians for decades is the critical definition of when the market is trending and when it is ranging. Applying a trending algorithm trading system to a ranging market will result in whipsaws (false entry signals) that yield losses. To avoid some of these false entry whipsaws, this paper proposes to variate some technical analysis tools to suit the different market conditions. This research attempts to variate lagging technical indicators like moving average and standard deviation to trade with less whipsaws in ranging market and yet capture the new trends early. In a ranging market, longer moving averages and corresponding standard deviations are used to avoid some of the whipsaws. In a trending market, shorter moving * Senior Lecturer, School of Accounting, Faculty of Economic and Management, Univerisiti Kebangsaan Malaysia, Bangi 43600 Selangor Darul Ehsan, Malaysia; palilrizal@gmail.com Mohd Rizal Palil ISSN 0975-3311 20 averages and corresponding standard deviations are used to gain early entry and exit. This paper presents a study of algorithm professional trading systems using some futures contracts to find high abnormal profits, in excess of the benchmark buy-andhold policy's returns. The ultimate result of this research is a new adaptive technical indicator, Adaptive Bands ZTest-Statistics (ABZ). Using daily data, this research investigates the profitability of ABZ and other algorithm trading systems on futures contracts from 15 December 1995 to 31 December 2008. Test results for ABZ indicate abnormal profits in excess of the benchmark buy-andhold policy's return for all the contracts tested. In 2008, for FKLI, ABZ reports a profit of +463 index points against a buy-and-hold return of -562 index points.
Identifying and prioritizing critical factors for promoting the implementation and usage of big data in healthcare

Big data is expected to provide many benefits to healthcare organizations through cost reduction, disease prediction, and patient care improvement. Big data in healthcare at a nascent stage faces many challenges in satisfying expectations. This study investigates factors for promoting the implementation and usage of big data in healthcare in Korea, using an analytical hierarchy process (AHP). We established a research framework that considers four domains and 15 factors. We collected data by a survey of experts engaged in big data and healthcare IT. The results show that data and organization have greater impacts than technology and support domains. Organizational analytics capability, data quality, data privacy and security, organizational application capability, data standardization, and data experts are the most important factors for promoting the implementation and usage of big data in healthcare. The study presents the implications in terms of the policies and ecosystem for countries, including Korea, which intend to activate big data in healthcare.
PROSPECT OF ORGANIC SUGARCANE CULTIVATION FOR JUICE AND JAGGERY(GUR):A LIVELIHOOD FOR FARMERS OF INDIAN SUNDARBAN DELTA.

Goutam Mahata. Assistant Botanist, Sugarcane Research Station, Bethuadahari, Nadia, Department of Agriculture, Govt. of West Bengal-741126, India. Manuscript Info Abstract . Manuscript History Received: 04 March 2019 Final Accepted: 06 April 2019 Published: May 2019
Implementation of Anomaly Detection on a Time-series Temperature Data set

Aldrig har det varit lika aktuellt med hallbar teknologi som idag. Behovet av battre miljopaverkan inom alla omraden har snabbt okat och energikonsumtionen ar ett av dem. En enkel losning for automatisk kontroll av energikonsumtionen i smarta hem ar genom mjukvara. Med dagens IoT teknologi och maskinlarningsmodeller utvecklas den mjukvarubaserade hallbara livsstilen allt mer. For att kontrollera ett hushalls energikonsumption maste plotsligt avvikande beteenden detekteras och regleras for att undvika onodig konsumption. Detta examensarbete anvander en tidsserie av temperaturdata for att implementera detektering av anomalier. Fyra modeller implementerades och testades; en linjar regressionsmodell, Pandas EWM funktion, en EWMA modell och en PEWMA modell. Varje modell testades genom att anvanda dataset fran nio olika lagenheter, fran samma tidsperiod. Darefter bedomdes varje modell med avseende pa Precision, Recall och F-measure, men aven en ytterligare bedomning gjordes for linjar regression med R^2-score. Resultaten visar att baserat pa noggrannheten hos varje modell overtraffade PEWMA de ovriga modellerna. EWMA modeller var nagot battre an den linjara regressionsmodellen, foljt av Pandas egna EWM modell.
LIDAL (Light Ion Detector for ALTEA): a compact Time-Of-Flight detector for radiation risk assessment in space

Manned space missions towards Moon and Mars planned in the next decades require a reliable radiation risk assessment considering the long time exposure of astronauts (up to years) to different radiation fields. The radiation environment inside a human space habitat, generated by the interaction of the Galactic Cosmic Rays and occasionally of Solar Particle Events with the spacecraft hull, is peculiar due to its composition (ions from Hydrogen to Iron, knock out neutrons) and the large kinetic energy range of the particles. For this reason the risk assessment approach used for astronauts in space is quite different from the one used on Earth. In this approach the risk for astronauts is evaluated calculating factors which score the risk in function of physical characteristics of the single particle, like the quality factor Q (related to the radiation ionizing power) or the squared ratio between the charge (Z) and velocity (β) of the particle (Z2/β2). LIDAL-ALTEA (Light Ion Detector for ALTEA - Anomalous Long Term Effects on Astronauts) is an experimental apparatus which will allow to evaluate for the first time in the field the Z2/β2 risk factor of the single detected particle on-board the International Space Station. The LIDAL system is a Time-Of-Flight detector designed to work paired to three Silicon Detector Units of the ALTEA, which will measure the deposited energy of the passing particle. The velocity of the particle (β), calculated from the Time-Of-Flight measurement performed by LIDAL, allows to evaluate the particle electric charge once related to the deposited energy measured by ALTEA. A first LIDAL prototype has been developed by the University of Rome “Tor Vergata” and tested at TIFPA (Trento Insistute for Fundamental Physics Applications) proton beam line, in order to evaluate the timing performances of the detector. Results are briefly presented and the current status of the apparatus production is discussed in view of the launch scheduled for 2019.
Petri Nets Model of Implicit Data and Control in Program Code

To describe the implicit data and the implicit control in program code,CNets,one extension of Petri nets,is applied.By data view nets and control view nets,data and control of the program code are modeled.Based on the CNets specification,interactions between data flow and control flow,relations among data,operations,and resources are also captured respectively.Meanwhile,mapping rules from CNets specification to Petri nets are presented.According to the rules,from CNets specification,properties of the program are analysized through Petri nets techniques without a running a program.
Filtering in Gaussian Linear Systems With Fuzzy Switches

This paper presents recent results on conditionally Gaussian observed Markov switching models by incorporating fuzzy switches in the model, instead of hard ones. This kind of generalization is of interest for applications involving continuous switching regimes, such as tracking an object using cameras in intermittent sunlight and shadow conditions. The filter developed hereby is recursive, optimal, and exact, up to an approximation of integrals according to some fuzzy measures. Experiences on simulated and on real data—dealing with outdoor air temperature and power consumption of a building—confirm the accuracy and effectiveness of the proposed filter compared with the hard filter with “crisp” switches.
Survey and analysis on Task scheduling in Cloud environment

Objectives: In cloud environment many scheduling algorithms are available to achieve the quality of service, but the scalability of task execution increases, scheduling becomes more complex. So there is a need for better scheduling. This paper deals with the survey of dynamic scheduling, different classification and scheduling algorithms currently used in cloud providers. Analysis: This paper focuses on a comparative study of static and dynamic task scheduling currently used and various researchers work on dynamic task scheduling for many applications. Findings: Scheduling methods/techniques used by various cloud service providers, advantages and limitations of each method are discussed. Scheduling algorithms in cloud setup in each paper is analyzed. Application: Analyzing task scheduling in cloud environment, uniform standard can be applied for all cloud providers. Online scheduling and dynamic scheduling can be further improved
On nilpotent interval matrices

In this paper, we give a necessary and sufficient condition for the powers of an interval matrix to be nilpotent. We show an interval matrix $it{bf{A}}$ is nilpotent if and only if $ rho(mathscr{B})=0 $, where $mathop{mathscr{B}} $ is a point matrix, introduced by Mayer (Linear Algebra Appl. 58 (1984) 201-216), constructed by the $ (*) $ property. We observed that the spectral radius, determinant, and trace of a nilpotent interval matrix equal zero but in general its converse is not true. Some properties of nonnegative nilpotent interval matrices are derived. We also show that an irreducible interval matrix $bf{A}$ is nilpotent if and only if $ | bf{A} | $ is nilpotent.
Psip Cases Version 1.3 7.08.2018 19 Pages) on Some Specific Cases of Psi Phenomena (Not Proved to be Frauds Until Present) with Possible Electrogravitational Explanations and Transdisciplinary Implications

The Merriam-Webster dictionary defines PSI phenomena (PSIP) as: “the aggregate of parapsychological functions of the mind including extrasensory perception [telepathy, clairvoyance], precognition, and psychokinesis”. Parapsychology (which is considered pseudoscience by the majority of mainstream scientists [including academics], with articles published only in a relatively small number of niche journals) also investigates other paranormal and psychic phenomena like: near-death experiences, reincarnation, apparitional experiences and other paranormal claims. This paper brings in discussion some specific cases of PSI phenomena (which weren’t proved yet to be frauds) with possible explanations and implications in physics, biology and the theories of information and human consciousness. If proved (with no doubt) to be authentic, PSI phenomena may have huge implications in the evolution (and unification) of physics, biology and spirituality (including religious currents): this unification (built on synapse-like bridges of knowledge and informational integration) is the constant purpose of interdisciplinarity and transdisciplinarity.
Camera calibration of a near-parallel imaging system based on magnification rate

Abstract. Microscopes are now widely used in the field of three-dimensional measurements for their high magnification and changeable physical focal length. However, the small depth of focus restricts the camera from taking clear images with apparent tilts. To set the camera in focus, the calibration board should be near-parallel to the imaging plane. As a result, the traditional calibration methods are not practical for a normal lens, which requires multiple views of the calibration board. For this, a method in which a digital camera with a microscope is calibrated precisely under the near-parallel condition is proposed. In this method, the magnification rate of the imaging system, which is equal to the rate of image distance to object distance, is calculated precisely and utilized to calculate camera parameters. Due to the invariance of the magnification rate, the parameters calculated by this method are accurate and stable. In addition, to solve the problem that the physical focal length cannot be calibrated by one image, the magnification method is adopted to measure it. Finally, the stability and accuracy are evaluated by simulations and experiments.
Overview of the data security and privacy-preserving of mobile cloud services

Compared with the traditional cloud services,the mobile cloud services have the characteristics of the mobile interconnected,flexible end-user applications and convenient data access.However,the rich applications of mobile cloud services bring more security and privacy-leaking problems.The basic concepts,applications and security issues of mobile cloud services were shaded light on,and then describes the architecture of security and privacy-preserving was described,some key technologies were studied in this domain,mainly focusing on the research progress of the security protocols and authentication,access control,integrity verification,mobile trusted computing and the privacy-preserving based on encryption,anonymous and confusion,and the advantages and disadvantages were pointed out respectively.Finally,some future research direction were given at the end.
MOOC TO GO

Massive Open Online Courses (MOOCs) have been one of the major trend topics of the last years within the e-learning community. Many companies, such as Coursera, edX and Udacity, launched MOOCs offering a broad range of topics. In this paper, the authors will take a look at the mobile support of different MOOC providers. Use cases and benefits of mobile access to a MOOC platform—both online and offline—will be shown. Finally, openSAP’s solution to address this task will be demonstrated. In this context, key technical decisions, which can serve as a blueprint for other MOOC providers will be discussed.
PENERAPAN METODE K-MEANS CLUSTERING DALAM PENGELOMPOKAN DATA PENUMPANG DAN KAPAL ANGKUTAN LAUT DI INDONESIA

Abstrak Transportasi laut merupakan sistem transportasi yang memberikan kontribusi sangat besar bagi pembangunan nasional, baik sebagai penunjang pertumbuhan ekonomi dan berbagai sektor pembangunan lainnya. Kebutuhan akan jasa angkutan laut semakin lama semakin meningkat, baik jumlahnya maupun macamnya. Usahausaha dalam pembangunan sarana transportasi laut yang dilakukan sampai saat ini adalah merupakan cerminan dalam mengatasi peningkatan kebutuhan, maka dari itu dibutuhkan pengelompokan data untuk meninjau laju pertumbuhan jumlah angkutan laut di setiap provinsi di Indonesia. Clustering sudah banyak diterapkan dalam berbagai bidang, salah satunya metode yang sering digukanan yaitu K-Means Clustering. Metode K-Means Clustering cukup efektif untuk diterapkan dalam proses pengklasifikasian karakteristik terhadap objek penelitian. Algoritma K-Means juga tidak terpengaruh terhadap urutan objek yang digunakan dan juga pusat cluster ditentukan secara acak dari salah satu objek pada permulaan perhitungan. Sistem yang akan dibangun dalam penelitian ini adalah sebuah sistem dengan fungsi utama untuk melakukan pengelompokan penumpang dan kapal angkutan laut di Indonesia dan menampilkan hasil dari pengelompokan data tersebut yang diharapkan dapat mempermudah instansi terkait dalam meninjau pertumbuhan transportasi laut. Kata kunci : Clustering, K-Means, Angkutan Laut. Abstract Sea transportation is a transportation system that contributes greatly to national development, both as a supporter and stimulator of economic growth and various other development sectors. The need for sea transportation services is increasing, both in number and in kind. Efforts in the development of sea transportation facilities carried out to date are a reflection of overcoming increasing demand, therefore it is necessary to group data to review the rate of growth in the number of sea transportation in each province in Indonesia. Clustering has been widely applied in various fields, one of which is the method often used, namely KMeans Cluster Analysis. The K-Means Cluster Analysis method is quite effective to be applied in the process of classifying characteristics of research objects. The K-Means algorithm is also not affected by the order of objects used and also the cluster center is determined randomly from one object at the beginning of the calculation. The system to be built in this study is a system with the main function of grouping passengers and ships on sea transport in Indonesia and displaying the results of the data groupings which are expected to facilitate related agencies in reviewing the growth of sea transportation. Keywords: Clustering, K-Means, Sea Transport