Miracle-dz/UniFAR-FTUs huggingface dataset:
IoT Device Onboarding, Monitoring, and Management

Deep learning models can achieve more accuracy sometimes that exceed human-level performance. It is crucial for safety-critical applications such as driverless cars, aerospace, defence, medical research, and industrial automation. Most of the deep learning methods mimic the neural network. It has many hidden layers and creates patterns for decision making and it is a subset of machine learning that performs end-to-end learning and has the capability to learn unsupervised data and also provides very flexible, learnable framework for representing the visual and linguistic information. Deep learning has greatly changed the way and computing devices processes human-centric content such as speech, image recognition, and natural language processing. Deep learning plays a major role in IoT-related services. The amalgamation of deep learning to the IoT environment makes the complex sensing and recognition tasks easier. It helps to automatically identify patterns and detect anomalies that are generated by IoT devices. This chapter discusses the impact of deep learning in the IoT environment.
Impact of Organic, Inorganic and Integrated Nutrient Management Practices On Carbon Pool and Nutrient Availability of Perennial, Annual and Seasonal Crops Grown Innagpur District

Soils are the largest carbon reservoirs of the terrestrial carbon cycle. Soil, if managed properly, can serve as a sink for atmospheric carbon dioxide (Jha et al., 2012). The global soil carbon (C) pool of 2500 gigatons (Gt) includes about 1550 Gt of soil organic carbon (SOC) and 950 Gt of soil inorganic carbon (SIC). The soil C pool is 3.3 times the size of the atmospheric pool (760 Gt) and 4.5 times the size of the biotic pool (560 Gt). The SOC pool represents a dynamic equilibrium of gains and losses. Conversion of natural to agricultural ecosystems cause depletion of the SOC pool by as much as 60% in soils of International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 10 Number 01 (2021) Journal homepage: http://www.ijcmas. com
Forecasting Framework Using Hybrid Modeling and Support Vector Regression

Time series forecasting for financial market has increasingly attracted the interests of investors and academic researchers. In recent years, some hybrid models have been constructed to improve the predictions since some methods cannot extract useful information from stock time series with noise to conduct prediction. In this research, a prediction framework is proposed to forecast the stock market behavior using the methods of wavelet coherence, multiscale decomposition and support vector regression (SVR). First, a combined method is applied to the raw data and remove noise to get useful information. Then, a SVR model is applied to improve the prediction performance of multidimensional nonlinear data. Furthermore, the comparison experiments were performed with both Shanghai Composite Index and Dow Jones Index to examine the effectiveness of the framework. The results indicate that the proposed framework performs better than other advanced models.
Multiferroic ground states in free standing perovskite-based nanodots: a density functional theory study

We use density functional theory to investigate the possibility of polar and multiferroic states in free-standing, perovskite-based nanodots at the atomic limit of miniaturization: single unit cells with terminations which allow centro-symmetry. We consider both A-O and B-O2 terminations for three families of nanodots: (i) A = Ba with B = Ti, Zr, and Hf; (ii) A = Ca and Sr with B = Ti; and (iii) A = Na and K with B = Nb. We find all A–O terminated dots to be non-polar and to exhibit cubic symmetry (except for K8NbO6), regardless of the presence of ferroelectricity in the bulk. In contrast, all the B–O2 terminated nanodots considered relax to a non-cubic ground state. Rather surprisingly, all of these structures exhibit polar ground states (except NaNb8O12). We propose a new structural parameter, the cluster tolerance factor (CTF), to determine whether a particular chemistry will result in a polar ground state nanodot, analogous to the Goldschmidt factor for bulk ferroelectrics. In addition, we find that all A–O terminated (except Ca8TiO6) and all polar B–O2 terminated nanodots are magnetic, where none show magnetism in the bulk. As with bulk systems, multiferroicity in the B–O2 terminated dots originates from separation between spin density in peripheral B atoms and polarity primarily caused by the off-center central A atom. Our findings stress that surface termination plays a crucial role in determining whether ferroelectricity is completely suppressed in perovskite-based materials at their limit of miniaturization.
Theoretical Investigation Of Coverage Effects Of CO Adsorption On Cu(100) Surface

This work investigates the CO adsorption on the metallic Cu(100) surface using periodic DFT computations. CO adsorption was studied at varying coverages from 1/16 ML to 1/1 ML for a combination of adsorption positions (4-fold, bridge and top). The results showed that adsorption energies are coverage dependent, however, not enough to identify the adsorption site and coverage. However, C-O stretching frequencies are almost unique for studied coverage and adsorption positions. CO adsorption energy changes between -250 kJ/mol to +21 kJ/mol; similarly, the vibrations’ range in the 1702 cm to 2110 cm interval, within the studied coverage and adsorption positions. Nevertheless, under the saturation coverage (θCO ≈ 0.55ML) the preferable adsorption site is the on-top position identified with a C-O stretching frequency around ~2100 cm and with ~117 kJ/mol adsorption energy.
Legislativa pro oblast nanolátek se zaměřením na fulleren a jeho deriváty

Diplomova prace se zabýva nanomaterialy a to předevsim fullerenem a jeho derivaty. Uvod prace je věnovan nanostruktuře fullerenu, jeho výskytu v přirodě, výrobě a zpracovani. Nasleduje souhrn vlastnosti týkajici se fullerenu, ktere jsou obsaženy jak v bezpecnostnim listu, tak v přistupných literarnich nebo elektronických zdrojich. Zpracovan je i přehled platne legislativy v EU a USA týkajici se nanomaterialů. V prakticke casti diplomove prace je věnovana pozornost termicke analýze, fytotoxicitě a stalosti fullerenu i jeho bromderivatu vůci UV zařeni, ktere je potřebne znat z hlediska posouzeni nebezpecnosti. Pro posouzeni fytotoxicity byly použity dva testy - test semichronicke toxicity se semeny Sinapis alba a test inhibice růstu kořene rostlin.
An Overview of Own Tracking Wireless Sensors with GSM-GPS Features

Wireless Sensors (WS) mobility and pause time have a major impact directly influencing the energy consumption. Lifetime of a WS Network (WSN) depends directly on the energy consumption, thus, the hardware and software components must be optimized for energy management. This study aims to combine a compact hardware architecture with a smart energy management efficiency in order to increase ratio Lifetime/Energy Consumption, to improve the operating time on a portable tracking system with GPS/GSM/GPRS features and own power. In this paper we present the evolution of own WS tracking architecture with GPS/GSM/GPRS features, basic criterion being the lifetime combined with low power consumption. Concern was focused on hardware and software areas: Large number of physical components led to reconsideration of hardware architecture, while for software, we focused on algorithms able to reduce the number of bits in transmitted data packets, which help to reduce energy consumption. The results and conclusions show that the goal was achieved.
Kinetic and thermodynamic study for the removal of cadmium (II) ions from aqueous media by Aucoumea klaineana sawdust

In this study, the biosorption by Aucoumea klaineana sawdust (AS) of cadmium(II) ions, from aqueous media was investigated under various operating conditions in a batch process. The influence of operating conditions such as initial concentration, ionic strength, initial pH solution, temperature, biosorbent dose, and biosorbent particle size on cadmium(II) ions removal by biosorption on AS is discussed. It was found that the equilibrium time at initial concentrations from 25 to 150 mg/L, was from 10 to 30 min, respectively. Pseudo-first-order, pseudo-second-order and Elovich models were used to fit the experimental data. The obtained results indicate that the biosorption system obeyed a pseudo-second-order kinetics model (r ≥ 0.987). In addition, thermodynamic parameters such as ΔG°, ΔH°, and ΔS° were calculated. The thermodynamic study of biosorption isotherm indicated that the biosorption of cadmium(II) ions is spontaneous (ΔG° < 0) and endothermic (ΔH° > 0) process.
Spectrophotometric determination of Zn(II), Cd(II), Hg(II), Fe(II), Co(II), Ni(II) and Cu(II) with 2-(4,6-dimethyl-2-pyrmidylazo )-1-naphthol-4-sulphonate, sodium salt

A newly synthesized water-soluble heterocyclic azo dye, 2-(4,6-dimethyl-2-pyrimidylazo)-1-naphthol-4-sulphonate sodium salt reacts with zinc, cadmium, mercury, iron, cobalt, nickel and copper to give highly sensitive colour reactions which can be monitored spectrophotometrically. Optical constants for the metal complexes have been determined.
A Random Walk Model for Spatial Galaxy Distribution

A new statistical model of spatial distribution of observed galaxies is described. Statistical correlations are involved by means of Markov chain ensembles, whose parameters are extracted from the observable power spectrum by adopting of the Uchaikin–Zolotarev ansatz. Markov chain trajectories with the Lévy–Feldheim distributed step lengths form the set of nodes imitating the positions of galaxy. The model plausibly reproduces the two-point correlation functions, cell-count data and some other important properties. It can effectively be used in the post-processing of astronomical data for cosmological studies.
Sustainability in ASEAN: The Roles of Financial Development towards Climate Change

As we know, nowadays financial sector is waking up the climate change. Therefore, the aim and novelty of the paper is to show the link between energy efficiency, sustainable economic growth, population and financial development in ASEAN 5 countries. Panel data analysis was employed and results shows that factors such as financial development, economic growth, population and renewable energy found to be important factors in influencing climate change in this study. Based on the results, increasing financial development, more energy use, high population and increasing economic growth will generate more CO2 emissions and cause climate change. Thus, there are several policies suggested to balance the relationship between financial development and the carbon emission levels and these policy implications should be considered and carried out by government and policy makers in order to improve the environmental quality in ASEAN countries. In conclusion, in the 5 ASEAN countries, financial growth plays an important role in waking up the issues of climate change. Many past literatures focused the impacts of renewable energy consumption, population, economic growth and foreign direct investment on climate change. Thus, this study narrows the gap that exists in literature.by focusing on financial development which able to foster vigorous economic growth especially in ASEAN countries. Overall, results from the fixed effect estimates show that financial development is significant factor and has a positive contribution towards climate change. This study contributes to existing literature by examining the link between energy efficiency, sustainable economic growth, population and financial development in ASEAN 5 countries.
Bacterial diversity and lipid biomarkers in sea ice and sinking particulate organic material during the melt season in the Canadian Arctic

The estimation of important carbon fluxes in a changing Arctic environment remains a challenge, one that could benefit from the development of biomarkers that distinguish between sympagic (ice-associated) and pelagic organic material. Products of 10S-DOX-like lipoxygenase and fatty acid cis-trans isomerase (CTI) activity of bacteria attached to sympagic particulate organic matter (POM) were proposed previously as potential biomarkers of the contribution of sympagic biota to carbon fluxes to the seafloor. To date, neither the bacteria involved in such enzymatic activities nor the detection of these potential biomarkers at their presumed source (i.e., sea ice) has been investigated. Here, we determined and compared the diversity of prokaryotic communities (based on operational taxonomic units) attached to sea ice POM and under-ice sinking particles during an early stage of ice melt (brine drainage) in Baffin Bay (Canadian Arctic). Based on a time series of biodiversity analyses and the quantification of lipid tracers of these two bacterial enzymatic activities, we suggest that CTI-active bacteria, exposed to hypersaline stress, are attached to algal POM just above bottom sea ice and released into the water column following brine drainage. In contrast, bacteria attached to sinking particles and exhibiting 10S-DOX-like lipoxygenase activity are suggested to come from the bottommost layer of sea ice, where they may play a role in the detoxification of algae-produce free fatty acids. These results provide a refined view of the potential use of products of CTI activity as specific biomarkers of sympagic organic matter.
Thermodynamic Calculation of the Mg - Cu Phase Diagram

The thermodynamic and phase equilibrium data of the binary Mg-Cu system were assessed thermodynamically to yield two descriptions. In the first description, the liquid and the (Cu) phase were treated as substitutional solutions and the two intermetallic phases, Mg 2 Cu and MgCu 2 , as stoichiometric phases. In the second description, MgCu 2 was then to be a Wagner-Schottky type phase, taking into consideration the range of homogeneity of this phase at high temperatures. The model parameter values for the various phases for the two descriptions are essentially the same and the calculated liquidus curves and the invariant temperatures are also the same. In view of the assumption of a stoichiometric phase for MgCu 2 in the first description, the calculated composition for the phase is fixed at 66.7 at. % Cu
Kronik böbrek hastalığı olan hastalarda oksidatif stress düzeyi

Amac: Bu calismada kronik bobrek hastaligi olan hastalarda dinamik tiyol/disulfid dengesinin arastirilmasi amaclandi. Gerec ve Yontem: Calismaya evre 1-5 (non diyaliz) 150 ( 57 erkek, 93 kadin) kronik bobrek hastasi ve (76 ( 30 erkek, 46 kadin ) saglikli kontrol grubu alindi. Kan tiyol/disulfid dengesi yeni gelistirilen otomatik ve kalorimetrik bir yontemle olculdu. Bulgular: Tum populasyonun serum thiol duzeyi ortalamasi 320.8±57.8 µmol/L , total thiol duzeyi ortalamasi 352.0±61.5 µmol/L , ortalama disulfid duzeyi 15.6±5.3 µmol/L idi. Kronik bobrek hastalarinda ortalama serum thiol ( p <0.001), total thiol ( p <0.001) ve disulfid duzeyleri ( p <0.001) kontrol grubuna kiyasla anlamli olarak daha dusuktu. Kronik bobrek hastalari ve kontrol grubu arasinda disulfid/thiol, disulfid/total tihol ve thiol /total thiol oranlari acisindan olarak anlamli farklilik saptanmadi. Sonuc: Calisamizda hem tiyol hem disulfid duzeyinde azalma olmasi Kronik bobrek hastalarin da serum tiyol dusuklugunun sadece tiyol gruplarinin disulfide cevrimine degil, vucuttaki total tiyol rezervinin azalmasina da bagli oldugunu gostermektedir. Bu nedenle kronik bobrek hastaliginda tiyol rezervini attirmaya yonelik nutrisyonel destek saglanmasi onerilebilir.
Big-Parallel-ETL: New ETL for Multidimensional NoSQL Graph Oriented Data

The quantitative explosion of digital data derived from social networks, smart devices, IoT sensors, etc is eventuated by the Big Data concept considered as a very important aspect in the performance improvement of traditional decision-making systems since it reveals serious challenges to be addressed. Therefore, the main purpose of this research paper is the integration of NoSQL Graph-oriented Data into Data Warehouse to deal with Big Data challenges especially with the absence of similar approaches to the best of our knowledge. In this paper, we propose a new approach called Big-Parallel-ETL that aims to adapt the classical ETL process (Extract-Transform-Load) with Big Data technologies to accelerate data handling based on the famous MapReduce concept characterized by its efficient parallel processing feature. Our solution proposes a set of detailed Algorithms based on several rules able to conceive rapidly and efficiently the target multidimensional structure (dimensions and facts) from the NoSQL Graph oriented database.
Reliability-Aware Multipath Routing of Time-Triggered Traffic in Time-Sensitive Networks

With the development of industrial networks, the demands for strict timing requirements and high reliability in transmission become more essential, which promote the establishment of a Time-Sensitive Network (TSN). TSN is a set of standards with the intention of extending Ethernet for safety-critical and real-time applications. In general, frame replication is used to achieve fault-tolerance, while the increased load has a negative effect on the schedule synthesis phase. It is necessary to consider schedulability and reliability jointly. In this paper, a heuristic-based routing method is proposed to achieve fault tolerance by spatial redundancy for TSNs containing unreliable links. A cost function is presented to evaluate each routing set, and a heuristic algorithm is applied to find the solution with higher schedulability. Compared to the shortest path routing, our method can improve the reliability and the success rate of no-wait scheduling by 5–15% depending on the scale of topology.
Comparison between attendance system implemented through haar cascade classifier and face recognition library

Face detection and face recognition are the most widely used features of machine learning(ML) and deep learning(DL). These features are slowly gaining popularity in fields like surveillance through CCTV cameras, mobile phone security (biometric locks), etc. This paper presents a college attendance system based on the above mentioned feature which automatically marks the attendance of the students through the live feed by the CCTV cameras in the classroom. This system saves time, works more efficiently, then manually marking the attendance by the roll call. System was built with the haar cascade features, open CV and face recognition library. These are discussed in the proposed paper. We have presented a comparison between the two models discussed and concluded that haar cascade features work more efficiently than the inbuilt face recognition library for the college attendance system.
Economic policy uncertainty: are there regional and country correlations?

ABSTRACT This study examines the correlation of economic policy uncertainty (EPU) across countries and regions. Using correlation analysis, the findings reveal that some countries have a positive EPU correlation while other countries have a negative EPU correlation. The economic policy uncertainty index is positively correlated and jointly significant for EU member-countries. There is evidence of cross-regional positive correlation. Also, the EPU correlations are significant for Europe, non-EU countries and the region of the Americas during the global financial crisis, which suggest that financial crises are a contributory factor that drives the correlation of economic policy uncertainty in certain regions.
Factors affecting financial management: Case study of educational manager training and fostering public institutions

The research focuses deeply on and evaluates the factors affecting financial management of educational managers training and fostering institutions in Ho Chi Minh City, Vietnam. This is a very specific model for countries in transition economies as in Vietnam, a country is in the process of comprehensive renovation, restructuring public service delivery institutions, increasing the assignment of self-responsibility to institutions, reducing financial pressure on the State budget. Using qualitative and quantitative research methods together with techniques, i.e., testing reliability scales with Cronbach's alpha coefficients, exploratory factor analysis EFA, CFA and linear model SEM, the study investigated 500 samples in 07 educational institutions in Ho Chi Minh City, Vietnam. The findings revealed six (06) factors, which are internal control system, technology infrastructure, top managers’ commitment, cash management and budget system, organizational responsibility, affected the financial reporting system, and meanwhile, the financial reporting system has a positive impact on the financial management. Based on this result, the study has proposed implications for improving financial management in educational managers training and fostering institutions in Ho Chi Minh City, Vietnam.
A Comparison of Land Use Classifications in Urbanized Areas in Selected European Countries

The real estate cadastre is the primary source of information on land use. It re‐ cords information related to the division of land into types based on the actual way of land use or development. The distinguished types of land use depend on many geographical factors, as well as historical and economic conditions. The study presents a comparison of the detail of land use classification regis‐ tered in the real estate cadastre in areas functionally related to the urban areas of 9 European countries: Austria, Bulgaria, the Czech Republic, Estonia, Spain, Lithuania, Luxembourg, Germany and Poland. The research concerned the determination of the degree to which the classifica‐ tion of land use in urbanized areas is detailed, whether the studied European countries are characterized by the same number of distinguished classes of ob‐ jects at different levels of detail, and what percentage are the distinguished classes of land use objects in urbanized areas in relation to all of the distin‐ guished classes of objects land use at different levels of detail of classification. The study used legal acts regulating land use issues which have been made available in national languages by government institutions.
Manager Overconfidence and Cost Stickiness

China market economy is in a new period of structural deceleration. Factors, such as fierce external competition and the advancement of the globalization process have put Chinese companies under enormous development pressure. Cost management is very important for improving the utilization rate of resources, the core competitiveness of an enterprise, and achieving the net profit target set by the enterprise. The basis study of cost management is the cost form. After the stickiness of costs is proposed, it has been widely concerned by academia and practice. Managers are the decision-makers of business activities and internal information disclosure. The current shareholding structure of the Chinese government’s macro-control has formed an “insider control” phenomenon, which highlights the importance of managers. Overconfidence of the managers can strongly impact on the manager’s decision-making. Based on this, it is of great significance to study the influence of managers’ overconfidence on the cost stickiness. This paper uses the data of Shanghai and Shenzhen A shares manufacturing companies from 2014 to 2018 to verify the existence of cost stickiness, and then studies the influence of managers’ overconfidence on the cost stickiness. The study found that there is a phenomenon of cost stickiness in listed companies in China’s manufacturing industry. More over, managers’ overconfidence can aggravate the problem of cost stickiness of enterprises. The innovation of the research is as following. Firstly, it enriches the research perspective of the sticky motivation of costs. Secondly, the study extends the research of managers’ overconfidence to the field of cost decision-making.