Miracle-dz/UniFAR-FTUs huggingface dataset:
Video Signal Transmission In 3D MIMO Encoded 4 X 2 mmWave Wireless Communication System

In this paper, robustness and effectiveness of 3D MIMO space-time block coding scheme have been evaluated in 3D MIMO encoded 4 x 2 mmWave wireless communication system on video signal transmission. The simulated system utilizes two channel coding schemes such as such as Repeat and Accumulate(RA),(3,2) single parity code(SPC) and 2-D Median filtering for noise reduction Based on the simulation result with MATLAB, it is quite noticeable that the simulated system is highly robust in retrieving video signal under mmWave MIMO fading channel in QAM digital modulation and Repeat and Accumulate channel coding scheme. Keywords—3D MIMO code, Channel coding ,2D Median filtering, Bit Error rate (BER), AWGN and mmWave MIMO channel
Effect of salty fog on flashover characteristics of OCS composite insulators

To study the flashover characteristics of the fog water in saline-alkali areas for high-speed railway OSC insulators, the spatial distributions of both the potential and electric field of soiled insulators in the presence of salty fog are analyzed using COMSOL Multiphysics, a multi-physics coupling software. Furthermore, to analyze the effect of the contamination of insulators due to salty fog water , a saline solution is used for staining an insulator sample by using the solid coating method. In an artificial climate chamber, the salty fog environment is simulated, and the flashover voltage for different salty fog water conductivities and surface staining are obtained. The salt-density correction coefficient K is also proposed. It provides a strong basis for the selection of railway insulators in saline-alkali areas. The results show that the salty fog water changes the original surface equivalent salt density, ρESDD, by wetting the existing fouling layer on the surface of the insulator, so that the original surface contamination layer becomes equivalent to Kρ ESDD ; the smaller is the value of ρESDD of the insulator surface, the larger is the value of K; the surface of the same insulator is dirty, and as the concentration of salty fog-water increases, K also increases.
Sense-Share: A Framework for Resilient Collaborative Service Performance Monitoring

Modern large-scale networked services, such as video streaming, are typically deployed at multiple locations in the network to provide redundancy and load balancing. Different techniques are used to provide performance monitoring information so that client nodes can select the best service instance. One of them is collaborative sensing, where clients share measurement results on the observed service performance to build a common ground of knowledge with low overhead. Clients can then use this common ground to select the most suitable service provider. However, collaborative algorithms are susceptible to false measurements sent by malfunctioning or malicious nodes, which decreases the accuracy of the performance sensing process. We propose Sense-Share, a simple light-weight and resilient collaborative sensing framework based on the similarity of the client nodes’ perception of service performance. Our experimental evaluation in different topologies shows that service performance sensing using Sense-Share achieves, on average, 94% similarity to non-collaborative brute force performance sensing, tolerating faulty nodes. Furthermore, our approach effectively distributes the service monitoring requests over the service nodes and exploits direct inter-node communication to share measurements, resulting in reduced monitoring overhead.
Orchestrating End-to-end Slices in 5G Networks

5G networks are characterized by massive device connectivity, supporting a wide range of novel applications with their diverse Quality of Service (QoS) requirements. This poses a challenge since 5G as one-fits-all technology has to simultaneously address all these requirements. Network slicing has been proposed to cope with this challenge, calling for efficient slicing and slice placement strategies in order to ensure that the slice requirements (e.g., latency, data rate) are met, while the network resources are utilized in the most optimal manner. In this paper, we compare different end-to-end (E2E) slice placement strategies by formulating and solving a Mixed Integer Linear Programming (MILP) slice placement problem and study their trade-offs. E2E slice requests are modelled as Service Functions Chains (SFC), in which each core network and radio access network component is represented as a Virtual Network Function (VNF). Based on the analysis of the results, we then propose a slice placement heuristic algorithm whose objective is to minimize the number of VNF migrations in the network and their impact onto the slices while, at the same time, optimizing the network utilization and making sure that the QoS requirements of the considered slice requests are satisfied. The results of the simulations demonstrate the efficiency of the proposed algorithm.
The Experience of Implementation of AMI System in Mashhad: The Green Project of FAHAM

Implementation of Advanced Metering Infrastructure (AMI) system is an essential step for smart grid. This paper aims to present the experience of practical implementation of AMI system in Mashhad Electric Distribution Company (MEEDC). Technical, environmental and social benefits of project are reviewed and a comprehensive Data monitoring system is proposed for efficient management of distribution network. Finally, the ability of proposed system in power quality improvement, distribution loss calculation, renewable resources integration and demand response program is presented.
A systematic review of studies examining effectiveness of therapeutic communities

Purpose – The purpose of this paper is to systematically review quantitative research since 2000 on the effectiveness of residential therapeutic communities (TCs) for the treatment of substance-use disorders with reference to substance-use, crime, mental health and social engagement outcomes. Design/methodology/approach – A systematic search with broad inclusion criteria resulted in the review of 11 studies. The studies investigated community-based TCs, as well as TCs modified for prisoners, prisoners transitioning to community living and TCs for individuals with co-occurring substance-use and mental health issues. Findings – Results were analysed by comparing the findings of the studies under investigation, of which three studies investigated within-subjects outcomes, four compared TC treatment with a no-treatment control condition and four compared TC treatment with another treatment condition. Conclusion: consistent with previous systematic reviews of TCs, outcomes varied across studies but indicated T.
Energy Supply Chain – Sourced by bio-power and bioethanol

The present work deals with the development of a model that optimizes a supply chain of bioethanol and bio-power. The growing concern about environmental issues has led the society to seek for solutions in order to replace fossil fuels. Part of this research is focused in the transport sector since it is a major contributor to the high emission levels of greenhouse gases. To reverse the situation two hypotheses are proposed: integrate a new the type of fuel consumed in the existent vehicles or introduce new type of vehicles in the market. Regarding the first hypothesis, bioethanol is currently the most exploited proposal and it has the greatest potential for expansion. The other solution involves the development of the market for electric cars. Considering the two presented solutions, a linear programming model was implemented, based on the works of Zamboni et al. [2] and Giarola et al. [3]. The referred model is built to understand what the best economical solution to produce energy from bio-products is: production of bioethanol or bio-power generation. Bioethanol production is performed by the Dry Grain Process (DGP) technology and bio-power is generated using the gasification and combustion. Taking into account the different technologies, results are promising regarding the implementation of a biomass combustion system. In a situation to encourage clean energy production, the production of electricity using combustion is the most profitable situation, followed by the production of bioethanol by DGP and finally by gasification. Analyzing a situation of selling the electricity produced without tax benefits, indications favor the production of bioethanol.
The nuts and bolts of Jamkesmas - Indonesia's government-financed health coverage program for the poor and near-poor

This case study describes and assesses Jamkesmas, Indonesia's government-financed health coverage program for the poor and near-poor. It provides a detailed description of the scope, depth, and breadth of coverage provided under Jamkesmas, and highlights ways in which the program interacts with the rest of Indonesia's health system. It also summarizes and discusses evidence on whether Jamkesmas is attaining its stated objectives of removing financial barriers and improving access to health care by the poor and near-poor, what could be improved, and what lessons can be learned from the experience of Jamkesmas that could help inform Indonesia's quest for universal coverage. The primary theme underlying the study is that supply-side constraints and supply-side subsidies have not been leveraged to increase the effectiveness of the Jamkesmas program. There are significant geographic deficiencies in the availability and quality of the basic benefits package, especially for those living in relatively remote and rural locations of the country, and this limits the effective availability of benefits for many Jamkesmas beneficiaries. The remainder of the case study is organized as follows. Section two provides general background and information on health system outcomes in Indonesia. Section three is an overview of health care financing and delivery. Section four describes the institutional architecture of Jamkesmas. Section five highlights the process of targeting, identification, and enrolment of beneficiaries under the program. Section six focuses on the role of public financing. Section seven outlines the basic benefits package. Section eight provides an overview of the information environment of Jamkesmas. Section nine discusses the special theme of supply-side constraints and supply-side subsidies that dilute the effectiveness of the Jamkesmas program. Section ten discusses the pending agenda around some of the architectural and operational features of Jamkesmas in the context of universal coverage.
Steering Traffic via Recurrent Neural Networks in Challenged Edge Scenarios

With edge computing, it is possible to offload computationally intensive tasks to closer and more powerful servers, passing through an edge network. This practice aims to reduce both response time and energy consumption of data-intensive applications, crucial constraints in mobile and IoT devices. In challenged networked scenarios, such as those deployed by first responders after a natural or human-made disaster, it is particularly challenging to achieve high levels of throughput due to scarce network conditions.In this paper, we present an algorithm for traffic management that takes advantage of a deep learning model to implement the forwarding mechanism during task offloading in these challenging scenarios. In particular, our work explores if and when it is worth using deep learning on a switch to route traffic generated by microservices and offloading requests. Our approach differs from classical ones in the design: we do not train centralized routing decisions. Instead, we let each router learn how to adapt to a lossy path without coordination, by merely using signals from standard performance-unaware protocols such as OSPF. Our results, obtained with a prototype and with simulations are encouraging, and uncover a few surprising results.
Chaotic and regular dynamics in the three-site Bose-Hubbard model

We analyze the energy spectrum of the three-site Bose-Hubbard model. It is shown that this spectrum is a mixture of the regular and irregular spectra associated with the regular and chaotic components of the classical Bose-Hubbard model. We find relative volumes of these components by using the pseudoclassical approach. Substituting these values in the Berry-Robnik distribution for the level spacing statistics we obtain good agreement with the numerical data.
AWSD: Adaptive Weighted Spatiotemporal Distillation for Video Representation

We propose an Adaptive Weighted Spatiotemporal Distillation (AWSD) technique for video representation by encoding the appearance and dynamics of the videos into a single RGB image map. This is obtained by adaptively dividing the videos into small segments and comparing two consecutive segments. This allows using pre-trained models on still images for video classification while successfully capturing the spatiotemporal variations in the videos. The adaptive segment selection enables effective encoding of the essential discriminative information of untrimmed videos. Based on Gaussian Scale Mixture, we compute the weights by extracting the mutual information between two consecutive segments. Unlike pooling-based methods, our AWSD gives more importance to the frames that characterize actions or events thanks to its adaptive segment length selection. We conducted extensive experimental analysis to evaluate the effectiveness of our proposed method and compared our results against those of recent state-of-the-art methods on four benchmark datatsets, including UCF101, HMDB51, ActivityNet v1.3, and Maryland. The obtained results on these benchmark datatsets showed that our method significantly outperforms earlier works and sets the new state-of-the-art performance in video classification. Code is available at the project webpage: https://mohammadt68.github. io/AWSD/
Electron Microscopic Studies in Escherichia Coli on Mode of Action of Sodium Benzoate and Potassium Sorbate

Traditionally food antimicrobials was utilized to extent the lag phase or inhibit the growth of microorganisms; however, it has been demonstrated that exposure to antimicrobials such as sodium benzoate and potassium sorbate in sublethal concentrations, and gradually increasing the dose, allowed the adaptation of microorganisms of interest in food, such as E. coli, exhibiting induced resistance by unknown mechanisms. Therefore, the objective of this study was to identify the ultrastructural changes in viable cells of E. coli adapted to high concentrations (7000 ppm) of these antimicrobials, using transmission electron microscopy (TEM). After treatment with potassium sorbate, E. coli presented important morphological changes such as the separation of the cell membrane from the cytoplasm and cell wall, the appearance of a remarkable electronic light at the center of cells containing condensed deoxyribonucleic acid (DNA) molecules, as well as the appearance of small dense granules of electrons. Therefores, potassium sorbate induced more severe shape structural changes, presence of unusual structures and loss of integrity compared to viable cells adapted to sodium benzoate.
Look Ahead Distributed Planning For Application Management In Cloud

In this paper, we propose and implement a distributed autonomic manager to maintain service level agreements (SLA) for each application’ scenario. The proposed autonomic manager seeks to support SLAs by configuring bandwidth ratios for each application scenario using overlay network before provisioning more computing resources. The most important aspect of the proposed autonomic manager is scalability which allows us to deal with geographically distributed cloud-based applications and large volume of computation. This can be useful in look ahead optimization and when using complex models, such as machine learning. Through experiments on Amazon AWS cloud, we demonstrate the elasticity of the autonomic manager.
Inter-container Communication Aware Container Placement in Fog Computing

In recent years, fog computing has increasingly become popular with the advent of Internet of Things (IoT) applications characterized by strict Quality of Service (QoS) requirements. To deploy applications, applications are typically decomposed into services then embedded with fog nodes. However, an overlooked aspect in container placement strategies is the heterogeneous inter-container network communication technologies and their impact on application performances in fog networks. We propose and evaluate in this paper, a near optimal genetic algorithm based container placement strategy that takes into account Remote Direct Memory Access as well host and overlay mode for inter-container communication to ensure application response time requirements.
efining an inverse dispersion method to quantify gas sources on olling terrain

This paper analyses a trace gas dispersion experiment with multiple point sources and line-averaging laser gas detectors on gently rolling terrain. The objective of the experiment was to establish how well emission rate can be inferred by “inverse dispersion” (ID), using a Lagrangian stochastic wind transport model (WindTrax) that (strictly) is appropriate only in horizontally-homogeneous winds. Measured mean wind speeds at fixed height above ground revealed spatial variation of order ±10% over the site. However the results of the inversion to estimate source strength Q from the concentration field suggest that the unwanted impact of the terrain is adequately compensated by representing detector light paths as curves, approximating their true height above ground. Under that treatment the mean and standard deviation of the ratio QIDM/Q of inferred to true source strength, over an ensemble of 96 fifteen minute intervals, were respectively 〈QIDM/Q〉=1.04 and Q|Q = 0.15, with little distinction between outcomes under unstable and stable stratification. We also used the measurements to study the influence (on the accuracy of retrieved source strength) of discretionary elements of inverse dispersion procedure: data quality criteria; optimal placement of detectors relative to the source(s); and the impact of alternative spatial representations of the source, supposing one had but partial information in that regard. Because the sources were always rather close to the downwind detector, the quality of the inversions was less sensitive to extremes of stratification than has been reported for other trials. Inversions that treated the actual point sources as an aggregate area source proved acceptable, provided this was placed at or near the height of the (true) point sources. An idealized distribution of elevated point sources can also be satisfactory, but bad inversions may result if placement of the token sources is biased in the cross-plot direction relative to the actual source(s). © 2016 Elsevier B.V. All rights reserved.
Environmental controls and anthropogenic impacts on deep-sea sponge grounds in the Faroe-Shetland Channel, NE Atlantic: the importance of considering spatial scale to distinguish drivers of change

Determining the scale of anthropogenic impacts is critical in order to understand ecosystem effects of human activities, within the context of changes caused by natural environmental variability. We applied spatial eigenfunction analysis to disentangle effects of anthropogenic drivers from environmental factors on species assembly in the Faroe-Shetland Channel (FSC), in the northeast Atlantic. We found that the species assembly considered here was structured at both small and large spatial scales. Specifically, substrate types, distance to oil wells and pipelines, the presence of objects and demersal fishing (both static and mobile) appeared significant in explaining large spatial scale species assembly structures. Conversely, temperature and variance in temperature shaped the species community across smaller spatial scales. Mobile scavenger species were found in areas impacted by demersal fishing. Oil and gas structures seemed to provide a habitat for a range of species including the commercially important fishes Molva sp. and Sebastes sp. These results demonstrate how the benthic ecosystem in the FSC has been shaped by multiple human activities, at both small and large spatial scales. Only by sampling datasets covering several sites, like in this study, can the effects of anthropogenic activities be separated from natural environmental controls.
Skin Detection applied to Multi-racial Images Skin detection based on mixture of color spaces

A skin detection methodology based on color skin clusters is proposed. The paper shows that, by adequately mixing color spaces, it is possible to segment the human skin, even if the images are collected from many different sources. Experimental results have shown the efficiency of the methodology in skin detection from different ethnics. KeywordsSkin, Segmentation, Color Space, rgb, HSV, TSL.
Quantum Computing and Shor’s Algorithm

This paper covers the basic aspects of the mathematical formalism of quantum mechanics in general and quantum computing in particular, underscoring the differences between quantum computing and classical computing. This paper culminates in a discussion of Shor’s algorithm, a quantum computational algorithm for factoring composite numbers that runs in polynomial time, making it faster than any known classical algorithm for factorization. This paper serves as a survey of Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer by Peter Shor[3].
A Key Management Scheme for Heterogeneous Wireless Sensor Networks

Abstract. A key management strategy is presented for heterogeneous wireless sensor networks. The wireless sensor networks have some sensor nodes that are more powerful than other nodes. Both ordinary nodes and heterogeneous nodes are evenly distributed respectively in a sensing area that is divided into a number of same equilateral hexagons. The pairwise keys between nodes are established through utilizing the concept of the overlap key sharing and the random key pre-distribution scheme. Analysis demonstrates that the connectivity and security of wireless sensor networks have been improved obviously with some heterogeneous nodes.
DEVELOPMENT AND EVALUATION OF WEBSITE TO CHECK INSTRUCTIONAL DESIGN BASED ON THE ARCS MOTIVATION MODEL

Website that contained motivational design strategies for various instructional setting, including face-to-face lectures and self-paced learning materials, were designed and developed to help lecturers/designers improve their instruction based on the result of user reaction questionnaire. The Website has capabilities of collecting questionnaire data, analyzing them, and suggesting weak areas, based on Keller’s ARCS motivational design model. Strategies to improve instruction are then suggested by retrieving from motivational strategy database that are suitable for a given instructional setting (teaching mode, target audience, characteristics of learning objectives, etc.). Formative evaluation studies were conducted to revise the Website for usability and practical effects, where the lecturers/designers worked through the Website to come up with a set of their own motivational enhancement strategies by referring to the weak areas the system analyzed and the motivational strategies the system proposed.