Miracle-dz/UniFAR-FTUs huggingface dataset:
Proposed Approach to Apply Green Balanced Scorecard at Iraqi Environment

Using Information Technology (IT) in preparing a Balanced Score Card (BSC) may increase the levels of environmental pollution. For the purpose of mitigating the harmful emissions resulted from using the bad techniques, it is necessary to invent a BSC dealing with the Green Information Technology (GIT) perspective. The Green Balanced Scorecard (GBSC) helps the organization to fulfill the profitable aims without harming the environment in these days or in the future. The GBSC evaluation measures the performance of the organization from four axes aiming at achieving the essential functions as well as the sustainability of the green environment. This study gives a model of GBSC which reduces the consequences against the environment. However, depending on the traditional card will increase, in turn, the polluting emissions. The study suggests that GBSC should rely on the main drivers of GIT. In addition to the optional driver (sustainability), by modifying the axes of the traditional BSC in away suits the Iraqi environment. Generally, the proposed approach GBSC in this paper services the environment - friendly organizations in fulfilling the aims of profits without harming the environment; therefore, the sustainability in the Iraqi environment is achievable.
SAM-The Smart Adaptable Management Jacket

People were feeling uncomfortable due to change in temperature day by day. The sudden change in environmental conditions may leads to major health issues. The proposed paper enables us to sense both body temperature, environmental conditions and controls the temperature either manually or automatically. The main components of the paper are Arduino Uno interfaced with a temperature sensor, an LCD display, Peltier module, Bluetooth module, Relay module and Rechargeable battery. The overall operation is to measure the temperature of the body and environmental conditions that displays on LCD module and mobile screen through Bluetooth module. The heater and cooler in turn will help user to provide either warming or chilling effects inside the jacket. This jacket acts as a guard and helps people to work comfortable irrespective of the weather conditions against the temperature variations.
Interphase Boundary Layer-Dominated Strain Mechanisms in Cu + Implanted Zr-Nb Nanoscale Multilayers

Sputter-deposited Zr/Nb nanoscale metallic multilayers with a periodicity of 27 (thin) and 96 nm (thick) were subjected to Cu+ implantation with low and high fluences and then studied using various experimental techniques in combination with DFT calculations. After Cu+ implantation, the thinner multilayer exhibited a tensile strain along c-axis in Nb layers and a compressive strain in Zr layers, while the thicker multilayer showed a compressive strain in both layers. The strain is higher in the thin multilayer and even further pronounced for high fluence. We developed a mathematical method for the fundamental understanding of the deformation mechanisms in metallic multilayers subjected to radiation damage. In the model, the cumulative strain within a layer is described as the combination of two contributions coming from the interfacial region and the inner region of the layers. The semi-analytical model predicts that the interfacial strain is dominant and extends over a certain region around the interface. Predictions are well supported by ab-initio calculations which show that in the vicinity of the interface and in the Zr side, vacancy and interstitials (low energy barriers) exhibit high mobility compared to the Nb side, thus resulting in a high recombination rate. As a consequence, less strain occurs in the Zr side of the interface compared to the Nb side. The density and distribution of various types of defects along the ion profile (low and high damaged regions) are obtained by combining DFT results and the predictions of the model.
Overview on Open Source Machine Learning Platforms-TensorFlow

Deep learning is a part of artificial intelligence utilizing deep neural network architectures that have essentially progressed to the cutting edge in PC vision, speech recognition, characteristic language preparation, and different spaces. In November 2015, Google delivered TensorFlow, an open-source deep-learning programming library for characterizing, preparing, and conveying machine-learning models. In this paper, we audit Tensor Flow and put it in current deep learning ideas and programming. We discuss its essential computational standards and appropriated execution model, its programming interface, and visualization toolbox. We, at that point, contrast Tensor Flow with elective libraries, for example, Theano, Torch, or Caffe on a subjective just as a quantitative premise. Lastly, remark on watched use-instances of TensorFlow in the scholarly community and industry
Generalized Autoregressive Dirichlet Multinomial Models: Definition and Stability

The need for a dynamic framework in discrete time for multicategory choice processes is examined. A state-space model to describe the evolution of a Dirichlet-Multinomial multicategory choice system with strong temporal correlation is developed, forecasting formulæ are derived and the conditions for long term stability in the mean are developed. A first order undifferenced process (AR = 1,MA = 1) is constructed for the controlling parameters of a Dirichlet-Multinomial distribution from which choice counts are drawn. This process is suitable to model the results of public opinion and consumer surveys where there is an expectation that preferences will drift over time without violating the distributional assumptions of the counting process itself. The constructed process thus possesses a structure analogous to the General Linear Model when used to model binary decisions but is extended to a richer distributional family.
SAR Image Classification Using Machine Learning

In today's existence, satellite imaging plays an important role in identifying landscape features on the surface of the earth. Sophisticated sensors record the apparent hue and the other spectrums in high-resolution images. Satellite imaging is interpreted and analysed for advanced remote sensing applications including meteorology, oceanography, fisheries, agriculture, conservation of habitats, forestry, landscape, geology, mapping, regional planning, education, intelligence and wars. Digital image processing has become a challenge with the accelerated development of these emerging application domains. The photographs collected by the satellite were interpreted and analysed In order to recognised the exact objects on the earth surface that provide a lot of geographical detail, interpretation and analysis have been performed on the satellite images. Classifying objects on images is actually a major field of study in the processing of pictures. It can thus be used in different applications in real time. Recent classification works on the objects present in satellite images are based on assembly processes, a mixture of one or more classification systems. For image improvement, precise segmentation and classification of input images, new methods are proposed. A new algorithm is applied in order to increase the contrast and denounce the input image resulting in a very high quality output image at the integrated stages of the work "Integrated wavelet-based Satellite Image Enhancement (IWSE)".
A Comparative Survey on Different Caching Mechanisms in Named Data Networking (NDN) Architecture

The Named Data Networking (NDN) is the forthcoming internet architecture which is developed and tested as an alternative to the standard IP architecture. It is acquired from Information Centric Networking (ICN). The data accessing depends on the name of the data content so that it is not depended on any particular server or location. Each router in the network stores particular data as cache based on different policies like Least Frequently Used (LFU), Universal Caching (UC), First in First out (FIFO), Least Recently Used (LRU), and etc., Caching process in NDN is the main function, where the availability of data to the user is based on getting and storing the appropriate required data in the storage area. So that it must be available whenever the user request for it. Due to this function, it is the major area to be concerned and researched in the NDN architecture. This survey is done on several caching strategies, their algorithm, caching types, their advantages and issues.Based on the survey work, various cache methods are compared depend on different criteria. Different challenges in their works are analyzed, and a proposal based on these works is given at the end of this paper.
A Two-Dimensional Simulation of Ultrasonic Wave Propagation in Concrete Using Finite Element Method

Due to the propagation and interaction characteristics in materials of the ultrasonic wave, it is widely used in the different fields such as medical, mechanical, and construction engineering, specially to detect cracks and defects in concrete construction, and to identify characteristics of concrete material as well. Understanding the propagation and interaction characteristics of the ultrasound wave in isotropic and anisotropy elastic materials plays a very important role. The paper presents a method for a two-dimensional simulation of ultrasonic wave propagation in concrete structure treating as homogenous, isotropic and anisotropic elastic media. A mathematical model of wave propagation using dynamic equilibrium equations in concrete structures with inclusions, steel reinforcements and cracks, is introduced. Then, numerical simulation is mentioned based on finite element method. The results of simulation show two-dimensional images of wave propagation inside concrete structures, as well as displacements, stresses and strains at specific points in the material according to space and time. The simulations are made for different cases of concrete structures with inclusions, steel reinforcements and open cracks.
Studies of Routing Protocol under Responsive and Un-responsive flow in MANET

Mobile nodes that can communicate with each other using wireless links without utilizing any fixed based station infrastructure and centralized management, known as Mobile ad-hoc network (MANET). There are many developments in MANET regarding the protocols of different layer. All the layers of MANET are keeping certain responsibility; out of all the layers; here the focus point on routing protocol of network layer. Quality-of-Service (QoS) metrics analyzed the performance of MANET; that metric includes throughput, packet drop, delay, residual energy, packet delivery ratio (PDR). That’s why, here, the analysis happens over the responsive and un-responsive protocol which are of transport layer. The analysis takes care of the routing protocols like AODV, DSDV, DSR and DSR with responsive flow (TCP) and unresponsive flow (UDP). The results and graphs are collected using through network simulator (NS-2) and gnuplot.
Cocrystallization of Loratadine With Succinic Acid Using Neat Grinding Method

Cocrystal of loratadine (L) was produced using succinic acid (SA), in order to improve the poor aqueous solubility profile. This was prepared in molar ratio of 1:1 (CC1) and 1:2 (CC2), applying the neat grinding method, therefore, the physicochemical properties and in vitro dissolution of both were characterized in free CO2 aquadest. The thermogram DSC of CC1 exhibited single endothermic peak at 116.8°C, two peaks were seen in CC2, at 90.2 and 152.2°C, and L had one, at 137.5°C. In addition, the results of XRPD showed a new peak at 2θ 21.93° and 21.88°, respectively, while C=O and –OH band shifts were identified in the FTIR spectra of both preparations. SEM photomicrographs revealed particle size reduction without habit alteration, while physicochemical characterization confirmed the incomplete cocrystal formation of loratadine with succinic acid, which promotes efficiency dissolution (DE15), in contrast with loratadine.
Adaptive Speech Spectrogram Approximation for Enhancement of Speech Signal

The process of speech enhancement tends to decrease the noise with keeping undistorted speech signal amplitude. There are several benefits of speech processing systems which comes with the some challenges. In this paper, we proposed adaptive speech spectrogram approximation (ASSA) technique that used to tackle the de-noising and dereverberation in a single channel speech signal. The model is processed using sparse representation prototype in order to perform the de-noising process, where it remove the noise that present in speech signal more thoroughly.Where matrix factorization and SIFT is used to model the speech signal spectrogram, a time-varying filter is used to minimalize the noise more effectively.The noise adaptive model is implemented via iterative updating parameters in order to approximate the lower reverberant speech signal in a SIFT domain.Afterwards, the proposed ASSA technique compute the variation in estimated speech signal in order to decrease the noise components and to predict the final speech magnitude. In order to evaluate the performance of proposed system it is compared with state-of-art techniques using some performance metrics.
A Web Based Solution to Detect Rice Leaf Blast Disease using Convolutional Neural Network

In the time of advancement, different enterprises are moving from manual to automated courses of action of various issues in the hand. While these frameworks have not simply extended the capability, they moreover have condensed the cost, time and work hours required to get an ensured excellence. In agriculture, paddy is one of the real harvests packaging substantial measure of fields moreover, serving the sustenance necessities. One of the crucial infections of paddy is leaf blast. The thought behind the work is to assemble a Convolutional Neural Network model and train it utilizing a collection of leaf blast pictures and group into various dimensions of infection so as to recommend appropriate solution to the farmers. A web based application is the proposed product of the work and the farmers can input the pictures of leaf blast and get seriousness of the malady and the solution for it.
Insights into the Cracking Mechanism Affecting a Structural Aluminum Alloy Processed by Laser Powder Bed Fusion

Structural Aluminum alloy- 6061 (Al-0.8Si-1.2Mg %wt) is frequently reported to becrack sensitive during laser powder bed fusion (L-PBF). The lack of in-depthunderstanding of the root causes of hot cracking is an impediment for designing partsfor safety-critical applications. In the present work, the ambiguity on crackingmechanism is resolved and is identified as solidification cracking. Cracking is found tooccur only along columnar grain boundaries having a large misorientation, θ &gt; 15°. This is attributed to the coalescence undercooling that lowers the dendrite coalescencetemperature. Our findings using the Rappaz-Drezet-Gremaud (RDG) criterion andRosenthal calculations show that the existence of stable liquid films is linked tomisorientation, causing a sudden increase in pressure drop leading to cracking. In thiswork, hot cracking sensitivity (HCS) maps are developed using the RDG criterion underconditions typical of L-PBF to investigate:the effect of the processing conditions, the melting parameters (laser power andscanning speed) on the thermal gradient (G) and solidification Velocity (v) inferred fromthermal simulations, on the hot tearing sensitivity. This led us to an understanding ofthe required G and v, and therefore the required laser power and speed to decreasethe cracking susceptibility and propose improvements to process the 6061 Al-alloyusing L-PBF relying on the developed HCS maps.the effect of addition of alloying elements such as Si and Mg, on the crackingsensitivity. This can be further used as guidelines to suggest chemical compositionmodifications of 6061 Al-alloy to improve its processability by L-PBF.
Harmonics Analysis of Cycloconverter Excited Induction Motor

A great deal of interest has been generated in the use of cycloconverter at low speed drives especially in high power application. In this paper we developed and discuss SIMULINK model of three phase to three phase cycloconverter controlled induction motor with LC filter circuit. LC filter circuit designed to reduce harmonics from cycloconverter controlled output voltage. The simulation result shows effects of filter circuit and discusses the magnitude of different harmonics order, DC component and total harmonics distortion on output voltage of cycloconverter before using filter circuit and after using filter circuit with different value of LC filter circuit.
A Comparative Study and Tribological Analysis of IC Engine Using Alternative Fuel

The ever-growing demand for fossil fuel and its scarcity at the same time made researchers dig more on the development of alternative fuels. Alternative fuels can be ethanol, methanol, naphtha, oils derived from vegetables or from animal fats, etc. In this review paper, a comparative study is attempted to see the effect of alternative fuel derived from Karanja on performance, emissions and tribological study including ferrography test, wear analysis, lubricating oil analysis, atomic absorption spectroscopy, surface roughness, etc on CI engine by different authors with respect to standard diesel. The biofuels can be directly injected into the IC engine without any engine modification. Improvement in BTE and BSFC/BSEC with the use of Karanja with less emissions except for NOx. Improvement in the properties of the alternative fuel is done by the use of additives. The tribological analysis is done in the long run of engines. Less wear is observed with Karanja biodiesel but increased in the case of 20% blend. A table is formed showing comparative study on performance, emissions and wear analysis of CI engine run with alternative fuel derived from Karanja compared to standard diesel.
Analyzing the Cost Efficiency Using Attribute Based Encryption on Medical Blockchain Platform

Blockchain technologies have been supporting Healthcare systems in improving the experience of the user in using the complete system cost effectively. This paper provides a focus on the various perspectives of blockchain applications and the various modifying issues with its regarding solutions. There are many challenges in administration of the electronic health records (EHR) in the method of enabling manifold doctors who have admittance to the patient’s entire history record of the patients healthcare data. Blockchain will be able to manage integrated records, serves incase of data security, cost efficiency and privacy and also ensuring an effective solution for the healthcare system challenges ensuring a trustworthy transactions. It contributes in providing results using an attribute based encryption in implementation of blockchain maintaining the Health records in health systems.
Quanto-Geometric Tensors and Operators on Unified Quantum-Relativistic Background

Physicists have long realized that the idea of holding one theory for the treatment of physical dynamics in the microcosm and one other for the dynamics taking place at larger scale physical structures is simply untenable, moreover if both families of theories are completely opaque to one another. Despite the proliferation of gauge theories, we are still unable to explain the continuum of Nature as revealed before us and it may be time to realize that the bridging notion of quantum-gravity is just ill-founded and non-falsifiable as framed. There will be no Grand Unification if we do not endeavor to elucidate the origin of the most important traits of the continuum, which is the plethora of fundamental physical constants that make up the continuum of Nature, those which we have arrived at by pure empiricism for the most part. In this work, I lay down a conceptual framework dubbed Quanto-Geometry that addresses the ontological Nature of space and the quantum-scalar along with their correlation throughout the continuum, the pivotal Tensors and Operators acting on the continuum, culminating with the stellar derivation of the most seminal constant of Nature in this Universal Arena, the Speed of Light (c).
TSD-TSR: Traffic Sign Detection Using Various Technique Based on Different Condition

This paper to present a great role of traffic sign detection and recognition is one of the fields of transportation systems. Traffic sign based on three types such as color based detection, shape based detection and text extraction. The recognition is including the hog feature and segmentation feature. This paper presents an efficient method for traffic sign detection in natural scene of traffic sign images. The image recognition techniques use the machine learning techniques feature extraction which is not only time consuming but also very complex. The result to improve the algorithms and make them more and efficient.
Energy-Efficient Routing Protocols for Wireless Sensor Networks - Overview

Wireless Networks are getting mainstream because of the idea of "3 any"- any individual, anyplace and whenever. Technological headways in wireless correspondence cleared the path to the advancement of minuscule ease, low-power and multifunctional sensor nodes in wireless sensor networks. The organization layer manages routing issues in sensor networks. Since radio transmission and gathering devours enormous measure of vitality, power is a significant factor to be researched on. Vitality preservation is, in this way, a vital issue in wireless sensor networks. Progressing research includes planning routing conventions that require less vitality during correspondence along these lines expanding the networks lifetime. For the more significant part of the applications, a substitution of vitality is excessively costly. A vitality reaping wireless sensor networks utilize nodes that can gather vitality from the condition. This paper gives an overview of vitality effective routing. In any WSN application estimated information is assembled at customary spans and the equivalent is sent to the Base station (BS) by utilizing neighbouring nodes. By shaping bunches of nodes in the WSN, the deliberate information from the nodes can be collected, and the collected worth can be sent towards the BS rather than sending each estimation esteem and subsequently diminishing vitality devoured by the nodes. By receiving progressive routing conventions, it is conceivable to lessen vitality utilization extensively.
A General Criterion for Predicting the Activation of 〈c a〉 Dislocations in Magnesium Alloys

The presence of alloying elements in magnesium (Mg) can activate pyramidal ⟨c + a⟩ slip systems and thereby improve the plasticity of Mg at room temperature. Several criteria for evaluating the activation of dislocations have been developed, but these often contradict experimental observations. Here, based on a synergistic effect stemming from both leading and trailing partial dislocations, we propose a more general and robust criterion - defined hereafter as "multiple energy barrier" (MEB) criterion - to predict the effect of alloying elements on the activation of ⟨c + a⟩ dislocations. Based on this proposed new criterion, we find that the addition of rare earths, Li, Ca, and Sn significantly lowers at least one energy barrier in pure Mg, and ultimately promotes the activation of the pyramidal I and/or pyramidal II slip systems. The reduced energy barriers are mainly attributed to the local lattice distortions and charge redistribution induced by alloying atoms. These findings provide important insight into the influence of alloying on the activation of ⟨c + a⟩ dislocations, and may ultimately facilitate the development of a framework to design high-plasticity Mg alloys.