Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermoelectric Properties of the XCoSb (X: Ti,Zr,Hf) Half‐Heusler alloys

We investigate the thermoelectric properties of the half‐Heusler alloys XCoSb (X: Ti,Zr,Hf) by solving Boltzmann transport equations and discuss them in terms of the electronic band structure. The rigid band approximation is employed to address the effects of doping. While many half‐Heuser alloys show excellent thermoelectric performance, the materials under study are special by supporting both n‐ and p‐doping. We identify the reasons for this balanced thermoelectric transport and explain why experimentally p‐doping is superior to n‐doping. We also determine the spectrum of phonon mean free paths to guide grain refinement methods to enhance the thermoelectric figure of merit.
Extraction of Tongue Crack Based on Gray Level and Texture

Tongue diagnosis is one of the most important content of Traditional Chinese Medicine (TCM). While the tongue crack is an important index of tongue diagnosis, there are just a few existing researches of tongue crack extraction and the results of them are unsatisfactory. This paper proposes a new algorithm for tongue crack extraction based on crack’s grayscale and texture in the tongue image. The method analyses and handles the tongue image’s luminance component in HSV color space. Firstly, we use the morphological opening closing reconstruction to eliminate small texture and noise of tongue images. Then we use Bot-hat transform and Otsu adaptive threshold segmentation to extract tongue cracks. Finally, we use correlation and entropy of grayscale symbiotic matrix to screen extracted tongue cracks and realize automatic extraction of tongue cracks. The result has shown that the method can extract tongue cracks with high accuracy and lay a good foundation for subsequent analysis of the crack.
Interference Model to Calculate the Lepton Masses

In this paper, we extend the original idea of de Broglie matter-waves into a special physical interaction form which has been abbreviated as mass interference. We postulated that all elementary particles could form a two-particle quantum state containing two standing matter-waves. The estimable mass of the particles is the result of this standing matter-wave interference. For the practical use of the newly introduced mass interference interaction model, we have created a generalized form of the quantized harmonic oscillator known from Quantum Mechanics. Utilizing this new theory, we are presenting two successful calculation methods for the theoretical determination of the lepton masses. This new simple theory has been strengthened by the direct presence of the physical relation between the leptons and the neutrons, which has long been recognized.
Penerapan Metode Rapid Application Development (RAD) untuk Digitalisasi UKM Industri Busana Muslim

Digitalisasi Usaha Kecil Menengah (UKM) saat ini tengah berkembang dengan pesat. Salah satu caranya melalui sistem penjualan online yang dilakukan di beberapa usaha penjualan atau pertokoan. Risti Boutique adalah salah satu toko busana muslim untuk pria dan wanita yang berlokasi di Kota Samarinda. Risti Boutique menjual berbagai macam busana muslim dari berbagai usia menggunakan sistem penjualan secara langsung datang pada toko, dengan tata kelola penjualan menggunakan catatan manual pada buku. Sejalan dengan itu maka sistem informasi penjualan diperlukan untuk melakukan efisiensi dalam penjualan dan pendataan barang dari toko. Penelitian ini bertujuan untuk melakukan transformasi sistem penjualan dari Risti Boutique yang sebelumnya dilakukan hanya secara offline menjadi online menggunakan Content Management System (CMS) Prestashop pada pembuatannya. Pengembangan sistem informasi menerapkan metode Rapid Application Development (RAD) yang memiliki tingkat kedinamisan yang tinggi dalam membangun sebuah sistem. Penelitian ini menghasilkan sistem informasi penjualan untuk manajemen pengelolaan toko Risti Boutique yang mampu mendokumentasikan segala hal terkait penjualan untuk membantu pihak took dalam memasarkan produk dan mengembangkan usahanya.
Value based marketing: Examining the role of leadership support in promoting neuromarketing

Abstract Neuromarketing is a branch in the field of commercial marketing communication. Neuromarketing closely relates to neuropsychology and market research for studying the cognitive thinking process of customers and their responses to the marketing stimuli. Presently no study has investigated the moderating role of firm leadership support in promoting neuromarketing applications in their firm. However, there is a huge interest among researchers and industry practitioners to understand this phenomenon and how leadership support can sponsor and invest in neuromarketing related programs in their marketing departments. Against this background, the objective of this study is to examine the role of firm leadership support in promoting neuromarketing and the consequences of it. With the help of marketing theories and literature, a theoretical model has been developed. Later, the model is validated using the CB-SEM technique using 372 responses from employees in marketing departments of various firms. The study finds that there is a significant and positive impact of neuromarketing on customer loyalty, improving business value, and marketing performance of the firms, which in turn significantly impacts the competitive advantage of the firms. The study also finds that leadership support plays an important role in promoting neuromarketing related applications in the firms.
The Havriliak–Negami and Jurlewicz–Weron–Stanislavsky relaxation models revisited: memory functions based study

We provide a review of theoretical results concerning the Havriliak–Negami (HN) and the Jurlewicz–Weron–Stanislavsky (JWS) dielectric relaxation models. We derive explicit forms of functions characterizing relaxation phenomena in the time domain—the relaxation, response and probability distribution functions. We also explain how to construct and solve relevant evolution equations within these models. These equations are usually solved by using the Schwinger parametrization and the integral transforms. Instead, in this work we replace it by the powerful Efros theorem. That allows one to relate physically admissible solutions to the memory-dependent evolution equations with phenomenologically known spectral functions and, from the other side, with the subordination mechanism emerging from a stochastic analysis of processes underpinning considered relaxation phenomena. Our approach is based on a systematic analysis of the memory-dependent evolution equations. It exploits methods of integral transforms, operational calculus and special functions theory with the completely monotone and Bernstein functions. Merging analytic and stochastic methods enables us to give a complete classification of the standard functions used to describe the large class of the relaxation phenomena and to explain their properties.
Adaptive Dynamic Programming for Decentralized Stabilization of Uncertain Nonlinear Large-Scale Systems With Mismatched Interconnections

This paper presents a novel decentralized control strategy for a class of uncertain nonlinear large-scale systems with mismatched interconnections. First, it is shown that the decentralized controller for the overall system can be represented by an array of optimal control policies of auxiliary subsystems. Then, within the framework of adaptive dynamic programming, a simultaneous policy iteration (SPI) algorithm is developed to solve the Hamilton–Jacobi–Bellman equations associated with auxiliary subsystem optimal control policies. The convergence of the SPI algorithm is guaranteed by an equivalence relationship. To implement the present SPI algorithm, actor and critic neural networks are applied to approximate the optimal control policies and the optimal value functions, respectively. Meanwhile, both the least squares method and the Monte Carlo integration technique are employed to derive the unknown weight parameters. Furthermore, by using Lyapunov’s direct method, the overall system with the obtained decentralized controller is proved to be asymptotically stable. Finally, the effectiveness of the proposed decentralized control scheme is illustrated via simulations for nonlinear plants and unstable power systems.
Image Super-resolution Reconstruction Algorithm Based on Self-Similarity and Compressive Sensing

Traditional super-resolution reconstruction algorithm based on sparse representation can present a good visual effect, but it is time-consuming and largely dependents on the training databases. A new image super-resolution algorithm based on self-similarity and compressive sensing is proposed. Firstly, the input low resolution image is rotated to increase the diversity of the training databases for self-similarity learning and the medium-frequency (MF) patches are exploited to predict more high-frequency (HF) details based on the self-similarity theory, instead of using the low-frequency (LF) patches. In this way, we can obtain the initial high-resolution image and regard it as the only training sample database. Then, sparse reconstruction process is carried out by adopting the K-SVD dictionary learning combined with the compressive sensing (CS) theory. Finally, to preserve sharper edges, the non-local means and iterative back projection algorithm are applied to optimize the reconstructed high-resolution image. During the process of search and match in self-similarity reconstruction, the Fast Library for Approximate Nearest Neighbors (FLANN) is used to replace the Approximate Nearest Neighbors (ANN). Experimental results validate the effectiveness of this method and show that the proposed algorithm can perform better both visually and quantitatively.
Methamphetamine (Mkpuru-Mmiri) prevalence in Southeastern Nigeria: Exploring peoples' perception of public flogging as a control measure

This study investigated the peoples' perception of public flogging as a control measure for methamphetamine (Mkpuru-Mmiri) use among youth in Southeastern Nigeria. The study adopted mixed methods. The questionnaire comprised (12) items administered to a sample size of 1055 through the online mediated platform – Google Forms, while the qualitative data were collected from (12) participants via face-to-face interviews. The quantitative data were processed using SPSS version 20.0 and displayed in descriptive statistics. The hypothesis was tested using the Mann-Whitney U test. The NVivo 10 software was used to analyze the qualitative data thematically. The study revealed that the practice seems to have been accepted as a social control measure for drug misuse in Southeast Nigeria. In addition, the hypotheses stipulate that educational level influenced the acceptability of public flogging as a methamphetamine deterrent with human rights concerns. The study concludes that preventing methamphetamine misuse can be accomplished by creating job opportunities for young people and rehabilitating users.
‘I've probably risk assessed this myself’: Choice, control and participant co‐regulation in a disability individualised funding scheme

Co-production is an intrinsic component of disability individualised funding schemes such as Australia's National Disability Insurance Scheme (NDIS). In this paper, we argue that an under-explored facet of co-production is the role that users of these services play in co-regulation. We draw on data collected in a qualitative study exploring participants' use of providers who are not registered with the NDIS regulator, the Quality and Safeguards Commission. Employing Steiner et al.'s (2023) 5Ws framework, we focus particularly on the dimensions of what, why and where to understand the conditions underpinning client co-regulation of quality and safety in the NDIS. We also explore the various types of activities participants engage in to co-produce their NDIS services, highlighting activities designed to improve the quality and safety of services delivered by unregistered providers.
Towards a Holistic Approach to Inverter-Fed Machine Design: FEM-Based PDIV Prediction of Complete Windings

The Schumann inception criterion was used to predict the partial discharge inception voltage (PDIV) of insulation models representing both wire wound and form wound (hairpin) low voltage machines. It was found that the fitting parameter <inline-formula> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> (the logarithm of the critical number of electrons that define the transition from Townsend to streamer discharge) is almost independent of material parameters when dealing with a given type of insulation (e.g., turn-to-turn using round conductors or flat conductors). These numbers can be fed to software for finite element analysis to provide a worst-case estimate of the PDIV.
Runge kutta to precise the detection of lesion for magnetic resonance imaging (MRI) image

In this paper, we translate non linear model to linear one and used numerical analysis: “Runge kutta4 (RK4)” is mathematical solutions to study the approximation’s solutions of ordinary differential equations, then pass to the statistical study for multiple regression to applied anova technique and with it, we extract the place of the lesion on medical image MRI by two ways: Distribution of gaussien curve (hypothesis test of ho) and directly on the pathologic image. The logicial applied here is Matlab. Key words: Runge kutta, linear regression, anova.
Parameter Searching in Attractor Algorithm for Community Detection —an Application in Pathway Enrichment Analysis

Generally, it was challenging to identify various complicated network structures in the real world, e.g., the dynamic network in social media. Given the underlying relationships among them was unveiled, it was efficient to achieve the goal of the knowledge curation and inference. As an existed community detection algorithm, Attractor built a successful dynamic system by representing the dynamic distance updating rules among relevant nodes through time changes, and it eventually partitioned nodes into different communities. Though Attractor was good at large-scale data handling and low time complexity, there was still room for improvement. By modifying its main iteration formulas and better controlling the iteration-related parameters, we achieved a better convergence rate for dynamic distance updating. Moreover, the scope of λ parameter was tested intensively so as to find the best cutoff of the parameter setting. In the last section, the modified Attractor algorithm was applied to the gene enrichment, and the results were compared accordingly.
A 1.2GHz Frequency Range, 153.4 dBc/Hz FoM, low Phase Noise, Current Starved Multi-Path Ring VCO

This article describes the design of a low power, low phase noise, multi-Path ring VCO (MPRVCO) in 90nm CMOS process. The proposed oscillator achieves a tuning range of 1.2GHz operating at 1.65 GHz center frequency, with reduced phase noise of -87.3dBc/Hz at 1MHz offset. The proposed MPRVCO achieves a FoM of 153.4dBc/Hz, consuming 0.657mW power at 1.65GHz frequency. The proposed VCO utilizes Current starving technique for frequency variation. Sub-threshold transistor is used to obtain monotonic and linear frequency tuning characteristics. The proposed VCO is one of the very few Current Starved ring VCOs capable of producing such low phase noise in 90nm CMOS process while operating in GHz frequency range
Comparison of numerical advection schemes in two-dimensional turbulence simulation

Abstract The influence of numerical approximations on statistical characteristics of modelled two-dimensional turbulence sustained by a stochastic external forcing is studied. The ability of various finite-difference and semi-Lagrangian schemes to reproduce reliably the dual energy and enstrophy cascades for coarse spatial resolution is tested. It is also studied how the requirement of preserving invariants inherent to a two-dimensional ideal fluid is important relative to numerical schemes. The results of calculations with high spatial resolution were taken as a reference solution. The choice of studied schemes was motivated by their use in atmosphere and ocean numerical models, in particular, in the Institute of Numerical Mathematics climate model (INMCM) and semi-Lagrangian absolute vorticity (SLAV) model of medium-range weather forecast. The importance of conservation laws for integral vorticity and enstrophy is revealed in the numerical experiments with a small-scale external forcing.
Prediction of Stock Prices Using Capital Asset Pricing Model in Nigerian Stock Market

The main intention of this study is to use the accounting data using CAPM to determine the stock prices/returns for the Nigerian capital market. In this study, the independent variable is the prediction of the stock prices and the dependent variable is stock prices in the market. The proxy that is used in this study to measure the dependent variable is CAPM in Nigerian Market. The most important and interesting phenomenon to investors is the analysis from financial market pertaining to stock returns. The research method employed is quantitative which is unlike qualitative as a way of assessing the stock price. The study mainly aims at assessing the correlation of beta factors and the predictability of stock returns from Nigerian firms listed on the stock exchange. In order to boost the beta estimates and mitigate statistical problems resulted from incorrect measurement, the securities were combined into portfolios. In conclusion the study employs ordinary least squares (OLS) regression technique and obtained beta value which is positive and found conclusive evidence for using CAPM and is thus consistent with Nigerian stock market prices. The CAPM has implications for asset pricing since it shows how to calculate the requisite rate of return to assess the value of the stock prices with any given amount of systematic risk (beta) and since the beta is positive hence the policy makers and investors in the Nigerian stock market would make better informed decisions.
Transductive Inference and Semi-Supervised Learning

This chapter contains sections titled: Problem Settings, Problem of Generalization in Inductive and Transductive Inference, Structure of the VC Bounds and Transductive Inference, The Symmetrization Lemma and Transductive Inference, Bounds for Transductive Inference, The Structural Risk Minimization Principle for Induction and Transduction, Combinatorics in Transductive Inference, Measures of the Size of Equivalence Classes, Algorithms for Inductive and Transductive SVMs, Semi-Supervised Learning, Conclusion: Transductive Inference and the New Problems of Inference, Beyond Transduction: Selective Inference
Steganalysis of StegoStorage system

Abstract The aim of this contribution is to detect the presence of messages in JPEG images that were stored in the files using sequential embedding into the least significant bits of DCT coefficients. The Stegostorage system was used for embedding. For testing purposes, we set this system to the full capacity of cover files as the worst case from the view of security. For steganalysis, we used and implemented a process of calibration of JPEG images, which makes it possible to investigate a histogram from steganographic images which are similar to the histogram of the original images without secret information. Also, Pearson’s Chi- -square test of goodness of fit was implemented, whose results indicate detectability of the presence of hidden messages through images in the two databases, the first database containing 1000 JPEG images and the second one containing 450 JPEG images. An interesting result is that after saving messages into the images and compressing the JPEG once more, the detectability decreased in this case by almost half. Moreover, this contribution provides a framework for further testing by calculating the minimum square error (the weighted stego analysis), which also indicates detectability in both databases, and after embedding the messages into images and re-compressing them with different quantization matrix, the detectability is only slightly reduced. Therefore, we consider this method an appropriate one for further testing and utilizing it when embedding into the LSB randomly, without filling the full capacity of the carrier file.
Realisierung einer Shared Production

In diesem Beitrag wird ein Ansatz für die Umsetzung der Shared Production basierend auf Konzepten der Plattform Industrie 4.0 und Gaia-X vorgestellt. Das Ziel der Shared Production ist der Aufbau eines Fertigungsnetzwerkes mit einer automatisierten Einbindung von externen Produktionskapazitäten. Dies ermöglicht die Ad-hoc-Erstellung von Lieferketten über StandortbeziehungsweiseFabrik- und Unternehmensgrenzen hinweg. Die Verteilung und Abwicklung von Aufträgen und deren Bearbeitung werden so deutlich effizienter. In diesem Beitrag wird gezeigt, wie Gaia-X, die Industrie-4.0-Sprache und die Verwaltungsschale miteinander kombiniert werden können, um die Shared Production mit herstellerübergreifenden und interoperablen Technologien zu verbinden.In diesem Beitrag wird ein Ansatz für die Umsetzung der Shared Production basierend auf Konzepten der Plattform Industrie 4.0 und Gaia-X vorgestellt. Das Ziel der Shared Production ist der Aufbau eines Fertigungsnetzwerkes mit einer automatisierten Einbindung von externen Produktionskapazitäten. Dies ermöglicht die Ad-hoc- Erstellung von Lieferketten über Standortbeziehungsweise Fabrik- und Unternehmensgrenzen hinweg. Die Verteilung und Abwicklung von Aufträgen und deren Bearbeitung werden so deutlich effizienter. In diesem Beitrag wird gezeigt, wie Gaia-X, die Industrie-4.0-Sprache und die Verwaltungsschale miteinander kombiniert werden können, um die Shared Production mit herstellerübergreifenden und interoperablen Technologien zu verbinden.
Search for Microscopic Black Holes in Multi-Jet Final-States using Multiple Single-Jet Triggers with ATLAS Detector with 8 TeV Proton-Proton Collisions at the Large Hadron Collider

Higher dimensional microscopic black holes may be produced in particle accelerators at high energies which will emit a high multiplicity of Standard Model (SM) particles via thermal decay. This thesis documents a search for higher dimensional microscopic black holes in multi-jet final-states using six single-jet triggers with the ATLAS detector with 8 TeV proton-proton collisions at the Large Hadron Collider. The ATLAS 2012 data corresponds to a total integrated luminosity of 20.3 fb−1. The background topology in this search consists of all multi-jet final-states from all SM processes. Quantum Chromodynamics (QCD) processes contribute maximally to the SM multi-jet final-states and dominate this background topology. The invariant mass (M) and scalar sum of transverse momenta of all jets (HT ) in events are used as analysis variables. The M and HT distributions for ATLAS data are consistent with QCD predictions of two well known hadronization models (PYTHIA8 and HERWIG++) for each single-jet trigger. Counting experiments are performed to set model-independent upper limits (at 95% confidence level) on the production cross section times acceptance times efficiency of new physics in multi-jet events. The model-independent upper limit on the production cross section times acceptance times efficiency is 0.15 fb−1 for the threshold mass Mth > 4.5 TeV. Model-dependent production cross section limits (at 95% confidence level) are also calculated versus Mth and fundamental Planck mass MD for non-rotating and rotating black holes for two, four and six large extra dimensions.
Sugli estremi dei momenti delle funzioni di ripartizione doppia

© Scuola Normale Superiore, Pisa, 1956, tous droits réservés. L’accès aux archives de la revue « Annali della Scuola Normale Superiore di Pisa, Classe di Scienze » (http://www.sns.it/it/edizioni/riviste/annaliscienze/) implique l’accord avec les conditions générales d’utilisation (http://www.numdam.org/conditions). Toute utilisation commerciale ou impression systématique est constitutive d’une infraction pénale. Toute copie ou impression de ce fichier doit contenir la présente mention de copyright.