Miracle-dz/UniFAR-FTUs huggingface dataset:
Improve Energy Consumption Model for Cloud Data Centers using PSO Algorithm

—The growth of cloud computing has resulted in uneconomic energy consumption, which has negatively impacted the environment through the generation of carbon emissions. This project proposes a distributed Locust-inspired scheduling algorithm to reduce cloud computing consumed energy (LACE). It schedules and optimizes the allocation of virtual machines (VMs) based on behavior derived from locusts. LACE distributes scheduling among servers; each server is responsible for allocating and migrating its VMs. Hence, the scheduling load is distributed between servers rather than being centralized in one component. LACE was thoroughly evaluated by comparing it with long-standing VM scheduling algorithms: dynamic voltage–frequency scaling (DVFS),energy-aware scheduling using the workload-aware consolidation technique, and the static threshold with minimum utilization policy. In addition, this project proposes a resource provisioning and scheduling strategy for scientific workflows on Infrastructure as a Service (IaaS) and Platform as services clouds (PaaS). This project presents an algorithm based on the Superior Element Multitude Optimization (SEMO), which aims to minimize the overall workflow execution cost while meeting deadline constraints. The main scope of the project is used to analyze best available resource in the cloud environment depends upon the total execution time and total execution cost which is compare between one process to another process. If the provider satisfies the time least time, then the process becomes to termination.
Multi Band Spectral Subtraction for Speech Enhancement with Different Frequency Spacing Methods and their Effect on Objective Quality Measures

This paper mainly studies Multi Band Spectral Subtraction (MBSS) for speech enhancement based on the spectrum representation in the frequency domain with three different scales(linear, log, mel) and their effect on performance measures in presence of additive nonstationary noise at different ranges of input SNR. Since speech is non-stationary signal, noise distribution is nonuniform i.e few frequency components are affected severely than others. A common method to restore the original speech in presence of noise is speech enhancement by suppressing the back ground noise. Multi Band Spectral Subtraction is one among the speech enhancement techniques which performs spectral subtraction by dividing noisy speech spectrum into uniformly spaced non over lapping frequency bands and spectral over subtraction is performed in each band separately. The performance of this method is evaluated in terms of objective measures such as Cepstrum distance, Log Likelihood Ratio, Weighted Spectral Slope distance, segmental SNR and Perceptual Evaluation of Speech Quality.
Deep Spatial–Temporal 3D Convolutional Neural Networks for Traffic Data Forecasting

Reliable traffic prediction is critical to improve safety, stability, and efficiency of intelligent transportation systems. However, traffic prediction is a very challenging problem because traffic data are a typical type of spatio-temporal data, which simultaneously shows correlation and heterogeneity both in space and time. Most existing works can only capture the partial properties of traffic data and even assume that the effect of correlation on traffic prediction is globally invariable, resulting in inadequate modeling and unsatisfactory prediction performance. In this paper, we propose a novel end-to-end deep learning model, called ST-3DNet, for traffic raster data prediction. ST-3DNet introduces 3D convolutions to automatically capture the correlations of traffic data in both spatial and temporal dimensions. A novel recalibration (Rc) block is proposed to explicitly quantify the difference of the contributions of the correlations in space. Considering two kinds of temporal properties of traffic data, i.e., local patterns and long-term patterns, ST-3DNet employs two components consisting of 3D convolutions and Rc blocks to, respectively, model the two kinds of patterns and then aggregates them together in a weighted way for the final prediction. The experiments on several real-world traffic datasets, viz., traffic congestion data and crowd flows data, demonstrate that our ST-3DNet outperforms the state-of-the-art baselines.
Time Series Analysis to Predict End-to-End Quality of Wireless Community Networks

Community Networks have been around us for decades being initially deployed in the USA and Europe. They were designed by individuals to provide open and free “do it yourself” Internet access to other individuals in the same community and geographic area. In recent years, they have evolved as a viable solution to provide Internet access in developing countries and rural areas. Their social impact is measurable, as the community is provided with the right and opportunity of communication. Community networks combine wired and wireless links, and the nature of the wireless medium is unreliable. This poses several challenges to the routing protocol. For instance, Link-State routing protocols deal with End-to-End Quality tracking to select paths that maximize the delivery rate and minimize traffic congestion. In this work, we focused on End-to-End Quality prediction by means of time-series analysis to foresee which paths are more likely to change their quality. We show that it is possible to accurately predict End-to-End Quality with a small Mean Absolute Error in the routing layer of large-scale, distributed, and decentralized networks. In particular, we analyzed the path ETX behavior and properties to better identify the best prediction algorithm. We also analyzed the End-to-End Quality prediction accuracy some steps ahead in the future, as well as its dependency on the hour of the day. Besides, we quantified the computational cost of the prediction. Finally, we evaluated the impact of the usage for routing of our approach versus a simplified OLSR (ETX + Dijkstra) on an overloaded network.
Human motion detection and notification system

Video surveillance has become an important tool for organizations for maintaining its security and safety applications. This science has been evolving ever since. These systems are very important and find its applications finance, banks, and home. Traditional video surveillance will typically succeed close distance observance. Digital surveillance systems are replacing analog cameras which use coaxial cable for cost and performance reasons. The motion detector can capture any object moving in its surrounding area and continuously monitor the area for any changes. Security is a primary concern, and CCTV or security guards can be expensive. In this age of technology, we can use much cheaper alternatives for security monitoring. Automated Video Surveillance System has been developed to detect the motion in a live video stream environment. The System proposed is a software module that can be used in with any kind of camera or computer system. With this, any unlawful intrusion can be detected and notified. Motion Detection continuously scans a particular area for any presence of motion. It makes use of advance image processing and video processing for this purpose. The system acquires the video footage and does a real-time frame by frame analysis. Every frame is processed to find the details about the surrounding. This detail is then used to add details to the video footage through video processing.
PENGARUH INTERVENSI EDUKASI BERBASIS THEORY OF PLANNED BEHAVIOR DALAM MENINGKATKAN KEPATUHAN PASIEN TUBERKULOSIS

Pendahuluan: Perilaku kepatuhan pasien tuberkulosis menjadi faktor yang paling krusial dalam upaya mencapai kesembuhan. Penelitian ini bertujuan untuk mengetahui pengaruh intervensi edukasi berbasis Theory of Planned Behavior (TPB) dalam meningkatkan kepatuhan pasien TB. Metode: Quasyexperiment studi dilakukan pada 64 pasien TB di poli paru RSUD dr. Darsono Pacitan dengan teknik purposive sampling. Penelitian ini dilakukan dengan memberikan intervensi edukasi berbasis TPB pada kelompok perlakuan selama 2 bulan. Uji statistik yang digunakan adalah independent t test, paired t test, mannwhithney, wilcoxon test, chi square dan multivariate test. Hasil: Terdapat perbedaan nilai mean yang bermakna di antara kelompok perlakuan dan kontrol pada variabel attitude toward behavioral (ATB), subjective norm (SN), percieved behavior control (PBC), intention, kepatuhan minum obat, pencegahan penularan dan kepatuhan nutrisi. Kesimpulan: Intervensi edukasi berbasis Theory of Planned Behavior terbukti mempunyai pengaruh dalam meningkatkan ATB, SN, PBC, intention, kepatuhan minum obat, pencegahan penularan dan kepatuhan nutrisi pada pasien tuberkulosis.
Real-time MRI: recent advances using radial FLASH.

Recent advances in real-time MRI result in high-quality images with acquisition times of only approximately 30 ms. The technique employs a fast low-angle shot sequence with proton density, T1 or T2/T1 contrast and radial data encoding for motion robustness. High temporal resolution is achieved by an up to 20-fold undersampling of the radial data. An iterative reconstruction algorithm estimates the image as the solution of a nonlinear inverse problem and ensures image fidelity by temporal regularization, which exploits the temporal continuity of successive frames during dynamic imaging. Preliminary real-time examinations at a field strength of 3T range from joint dynamics, speaking and swallowing to the 3D localization of objects in space. In particular, real-time MRI largely facilitates assessments of cardiovascular function and quantitative blood flow. Taken together, advanced real-time MRI methods allow for hitherto inaccessible studies, lead to more robust and shorter examinations, improve patient comf.
Usability Guidelines for an Online Image Database

There are currently no existing guidelines for optimizing user experience in online image databases. Here we use established usability design principles to develop a set of 50 recommendations for improving database organization, navigability, and search functionality. We conduct a resource audit of commercial and non-profit image galleries and evaluate them upon our criteria. Our findings are summarized within a basic wireframe to be used as reference for prospective image databases in the future
New species of the genus Tritogenia Kinberg, 1867 from southern Africa (Oligochaeta: Microchaetidae)

Eighteen new species of Tritogenia are descriptionbed and illustrated: alveata, annetteae, ataxia, curiosa, diversa, douglasi, herbana, insolita, koilia, liversagei, lunata, miniseta, monosticha, ngelensis, palusicola, silvicola, soleata, tumeri. All known species are arranged into four species-groups based on the position of spermathecal pores: the grisea group with spermathecal pores in one intersegmental furrow (including provisionally the poorly known species benhami (Michaelson, 1900)); the sulcata group with spermathecal pores in two intersegmental furrows; the mucosa species-group with spermathecal pores in three intersegmental furrows; and the zuluensis group with spermathecal pores in more than three intersegmental furrows. Keys are provided to the genera of Microchaetidae, to the newly proposed species-groups, and to the species of Tritogenia.
Decadal- to centennial-scale climate changes over the last 2000 yr recorded from varved sediments of Lake Kusai, northern Qinghai-Tibetan Plateau

Abstract High-resolution climate archives of the Late Holocene are essential in the study of paleoclimatic dynamics and for understanding the importance of natural and anthropogenic influences on past and future climate changes. Here, we present well-dated X-ray fluorescence scanning records retrieved from a varved sediment core from Lake Kusai. These records show the decadal- to centennial-scale paleoclimatic variability of the northern Qinghai-Tibetan Plateau over the last 2000 yr. Ca is mainly related to the precipitation of authigenic carbonates and is a proxy for temperature changes. The Ca record of Lake Kusai is well-correlated with the variations and periodicities of solar activity. Therefore, solar output can be suggested as being the predominant forcing mechanism of decadal- to centennial-scale temperature fluctuations over the last 2000 yr. The evolution of effective moisture was inferred from the log-ratios of Rb/Sr, which demonstrated synchronous changes with the typical Indian summer monsoon record from Dongge Cave. These results indicate that the decadal- to centennial-scale effective moisture evolution of the northern Qinghai-Tibetan Plateau is mainly influenced by the Indian summer monsoon. Additionally, we have not found the evident periodicities of solar activity in our effective moisture record over the last 2000 yr.
Decentralized Droop Control in DC Microgrids Based on a Frequency Injection Approach

Power sharing control among grid forming dc sources employing a conventional voltage droop approach meets inaccurate load sharing and unacceptable voltage regulation performance. Thereby, communication-based secondary and supervisory controllers have been presented to overcome the aforementioned issues. Furthermore, with the aim of eliminating communication system, frequency-based droop approaches have been introduced for low-voltage dc grids where the frequency of the superimposed ac signal onto the dc voltage is proportional to the output power. However, in reality, dc grid structures can be applied to medium and high voltage applications with different X/R ratios. This paper generalizes the frequency-based droop scheme for dc microgrids with different low, medium, and high X/R ratios. Obtained simulation and experiment results demonstrate the effectiveness of the proposed control method.
IDENTIFICATION OF A POPULATION OF X-RAY-EMITTING MASSIVE STARS IN THE GALACTIC PLANE

We present X-ray, infrared, optical, and radio observations of four previously unidentified Galactic plane X-ray sources: AX J163252–4746, AX J184738–0156, AX J144701–5919, and AX J144547–5931. Detection of each source with the Chandra X-ray Observatory has provided sub-arcsecond localizations, which we use to identify bright infrared counterparts to all four objects. Infrared and optical spectroscopy of these counterparts demonstrate that all four X-ray sources are extremely massive stars, with spectral classifications: Ofpe/WN9 (AX J163252–4746), WN7 (AX J184738–0156 = WR121a), WN7–8h (AX J144701–5919), and OIf+ (AX J144547–5931). AX J163252–4746 and AX J184738–0156 are both luminous, hard, X-ray emitters with strong Fe xxv emission lines in their X-ray spectra at ∼6.7 keV. The multi-wavelength properties of AX J163252–4746 and AX J184738–0156 are not consistent with isolated massive stars or accretion onto a compact companion; we conclude that their X-ray emission is most likely generated in a colliding-wind binary (CWB) system. For both AX J144701–5919 and AX J144547–5931, the X-ray emission is an order of magnitude less luminous and with a softer spectrum. These properties are consistent with a CWB interpretation for these two sources also, but other mechanisms for the generation of X-rays cannot be excluded. There are many other as yet unidentified X-ray sources in the Galactic plane, with X-ray properties similar to those seen for AX J163252–4746, AX J184738–0156, AX J144701–5919, and AX J144547–5931. This may indicate a substantial population of X-ray-emitting massive stars and CWBs in the Milky Way.
QUALIDADE DE MUDAS DE BATATA-DOCE OBTIDAS EM DIFERENTES RECIPIENTES

O plantio da batata-doce ocorre por meio do uso de material vegetativo e a produção de mini ramas é uma alternativa de aumento na produtividade. Objetivou-se com esse trabalho avaliar a qualidade de mudas de batata-doce obtidas em diferentes tipos de recipientes. O experimento foi realizado em ambiente protegido, em delineamento inteiramente casualizado, em esquema fatorial 5 x 3, sendo cinco genótipos de batata-doce (Duda, Princesa, BDFMI#04, BDFMI#16 e BDFMI#106) e três tipos de recipientes (bandejas de poliestireno com 128 células de 40 cm³ cada; copos descartáveis de 200 cm³ de capacidade e tubetes com capacidade de 115 cm³), com quatro repetições. Foram avaliadas as seguintes características nas mudas de batata-doce: número de folhas, massa seca das folhas, massa seca da parte aérea, massa seca das raízes, relação entre a massa seca da parte aérea com a massa seca das raízes e índice de qualidade de Dickson. O recipiente copo descartável, sendo o de maior volume, favoreceu uma melhor expressão dos resultados dos genótipos para a maioria das características analisadas. À medida que o volume do recipiente foi aumentando, os genótipos conseguiram apresentar resultados mais satisfatórios em relação à produção de mudas.
Interstellar Extinction in the Vicinity of the Galactic Center

We present J (1.2 μm), H (1.6 μm), K′ (2.11 μm), and Brγ (2.166 μm) images from four large regions within the central 40 pc of the Galaxy. Localized variations in the extinction, as determined by observations of the stellar population, are examined using the median H-K′ color as a function of position within each region. As the value of the derived extinction from the stars is dependent upon the intrinsic magnitude of the assumed stellar type, the J-H versus H-K′ diagrams are first used to investigate the distribution of stellar types in the four regions. We find that there is a distinct OB population, contrary to earlier assumptions, with the ratio of K and M giants and supergiants to OB stars approximately twice that of the solar neighborhood. Although on the scale of ~1' fluctuations in the extinction are on the order of AV ~ 2, throughout the entire region the extinction varies from AV ≳ 25 to AV ≲ 40. We also examine whether there is any variation in the extinction and stellar number density relative to the unusual radio features in these regions and do not find a significant correlation. Spectral imaging in Brγ 2.166 μm emission shows a strong morphological correspondence between the 6 cm radio images and the diffuse Brγ emission. By comparing the theoretical Brγ flux derived from the radio flux using recombination theory with our measured Brγ flux, we obtain a second, independent, estimate of the extinction. We compare the two data sets and find that the extinction as derived from the stars is consistently greater, sometimes by a factor of 2, than the value of the extinction derived from the Brγ images. The derived extinction in various regions, however, is insufficient for any of these regions to be located behind the molecular clouds as previously observed in the Galactic center, consistent with the theory that the observed radio emission is produced on the foreground surface of these clouds.
A sound analysis/synthesis system based on a deterministic plus stochastic decomposition

When generating musical sound on a digital computer, it is important to have a good model whose parameters provide a rich source of meaningful sound transformations. Three basic model types are used widely today for musical sound generation: instrument models, spectrum models, and abstract models. Instrument models attempt to parameterize a sound at its source, such as a violin, clarinet, or vocal tract. Spectrum models attempt to parameterize a sound at the basilar membrane of the ear, discarding whatever in{ormation the ear seems to discard in the spectrum. Abstract models, such as FM, attempt to provide musically useful parameters in an abstract formula. This paper addresses the second category of synthesis technique: spectrum modeling. It describes a technique called specftal modeling synthesis {SMSl, that models time-varying spectra as (l ) a collection of sinusoids controlled through time by piecewise linear amplitude and frequency envelopes lthe deterministic part), and (2) a time-varying filtered noise component (the stociasticpartl. The analysis procedure first extracts the sinusoidal trajectories by tracking peaks in a sequence of short-time Fourier transforms. These peaks are then removed by spectral subtraction. The remaining "noise floor" is then modeled as white noise through a timevarying filter. A piecewise linear approximation to
A proteomics-based systems genetics approach reveals environment-specific loci modulating protein co-expression and drought-related traits in maize

The evolution of maize yields under drought is of particular concern in the context of climate change and human population growth. To better understand the mechanisms associated with the genetic polymorphisms underlying the variations of traits related to drought tolerance, we used a systems genetics approach integrating high-throughput phenotypic, proteomics and genomics data acquired on 254 maize hybrids grown under two watering conditions. We show that water deficit, even mild, induced a strong proteome remodeling and a reprogramming of the genetic control of the abundance of many proteins. We identify close co-localizations between QTLs and pQTLs, thus highlighting environment-specific pleiotropic loci associated to the co-expression of drought-responsive proteins and to the variations of phenotypic traits. These findings bring several lines of evidence supporting candidate genes at many loci and provide novel insight into the molecular mechanisms of drought tolerance.
A 10.4-Gb/s 1-Tap Decision Feedback Equalizer With Different Pull-Up and Pull-Down Tap Weights for Asymmetric Memory Interfaces

In asymmetric memory systems, the pull-up and pull-down data from the channel can have different amounts of inter-symbol interference (ISI), so they cannot be fully corrected by an equalizer which uses a single tap weight. We introduce a receiver-side single-ended 1-tap asymmetric decision-feedback equalizer (DFE) with a weight selection multiplexer, which allows the application of a different weight to each direction of data value transition. Implemented in a 55-nm CMOS technology, our DFE compensated for asymmetric ISI in a 10.4-Gb/s signal from a channel with an insertion loss of −8.3 dB, leading to a 50% wider horizontal margin at a bit-error-rate of 10−12 than symmetric correction. The energy efficiency is 0.16 pJ/bit.
Blockchain-Based Soybean Traceability in Agricultural Supply Chain

The globalized production and the distribution of agriculture production bring a renewed focus on the safety, quality, and the validation of several important criteria in agriculture and food supply chains. The growing number of issues related to food safety and contamination risks has established an immense need for effective traceability solution that acts as an essential quality management tool ensuring adequate safety of products in the agricultural supply chain. Blockchain is a disruptive technology that can provide an innovative solution for product traceability in agriculture and food supply chains. Today’s agricultural supply chains are complex ecosystem involving several stakeholders making it cumbersome to validate several important criteria such as country of origin, stages in crop development, conformance to quality standards, and monitor yields. In this paper, we propose an approach that leverages the Ethereum blockchain and smart contracts efficiently perform business transactions for soybean tracking and traceability across the agricultural supply chain. Our proposed solution eliminates the need for a trusted centralized authority, intermediaries and provides transactions records, enhancing efficiency and safety with high integrity, reliability, and security. The proposed solution focuses on the utilization of smart contracts to govern and control all interactions and transactions among all the participants involved within the supply chain ecosystem. All transactions are recorded and stored in the blockchain’s immutable ledger with links to a decentralized file system (IPFS) and thus providing to all a high level of transparency and traceability into the supply chain ecosystem in a secure, trusted, reliable, and efficient manner.