Miracle-dz/UniFAR-FTUs huggingface dataset:
Advancing Energy Storage Technology through Hybridization of Supercapacitors and Batteries: A Review on the Contribution of Carbon-Based Nanomaterials

Fast depletion of fossil fuel and other non-renewable energy resources with their negative environmental impact have raised the quest for eco-friendly and sustainable energy resources. Sustainable energy resources such as solar and wind energy are periodical. Therefore, such energy resources can only be effectively utilized with advanced energy storage technology. Currently, various energy storage technologies such as batteries and supercapacitors are available with various energy storage properties. For instance, batteries are characterized with high energy and low power density. On the other hand, supercapacitors are low energy and high power density devices. The high power density of supercapacitors results to their faster charging and discharging capability compared to batteries. While batteries can accommodate higher energy compared to supercapacitors. Therefore, to obtain single energy storage material/device with both high energy and power density is a challenge in the energy storage sector. However, various efforts have been made to address this challenge through combinations of various materials or devices. For instance, carbon-based nanomaterials such as graphene and carbon nanotubes have been extensively studied in design of supercapacitors for high energy storage density. While supercapacitors and batteries have been hybridized on the effort to obtain energy storage device with both high energy and power density for advanced energy storage technology. Therefore, this review looks into the contribution of carbon-based nanomaterials in improving energy storage density of supercapacitors and their hybridization with batteries as the way forward to obtain energy storage materials/devices with both high energy and power density for advanced energy storage technology.
Transfer Learning Adaptive Facial Attractiveness Assessment

Recent advances in Computer Vision and Artificial Intelligence have brought the opportunity to automate facial attractiveness evaluation. A range of studies have been addressed to the task and have achieved reasonable prediction accuracy. However, most of these methods work well only on photos with restrictions on expression, posture, illumination, but not on real-world face photos. This work is aimed to improve the attractiveness assessment state-of-the-art in both cases. To this end, an approach that employs transfer learning methodology as well as shallow machine learning was proposed for highly accurate facial attractiveness prediction. Specifically, a Convolutional Neural Network (CNN), Facenet, originally designed and pre-trained for the face recognition task is utilized. High-level facial features were extracted by using the network and then fed into Support Vector Regression in order to predict facial attractiveness. Extensive experiments conducted on widely used facial beauty datasets Gray and SCUT-FBP5500 demonstrated that the proposed method outperformed other attractiveness prediction approaches. The experimental results also confirmed the effectiveness of the method in both constrained and unconstrained environment.
Effective Deagglomeration in Biosynthesized Nanoparticles: A Mini Review

Materials with nanoscale particle size have different properties from its bulk phase, which allows for wider application of the material. There are various methods to synthesize nanoparticles, namely physical, chemical, and biological method. Nowadays, nanoparticle synthesis method is focused on biological method because of its advantages, such as environmentally friendly, relatively simple procedures, and lower production costs. Biosynthesis by co-precipitation method using extracts from biological agents is considered the most efficient among other biological methods. Biochemical compound in the extract have a dual role in synthesis, they act as a reducing agent which reduces metal salt to metal ion, and as a capping agent which stabilizes the nanoparticle. Biosynthesis has been shown to result in nanoparticles as good as physical and chemical method. However, several studies report that the synthesized nanoparticles have low stability regardless of the presence of their capping agent, resulting in agglomeration of nanoparticles, which reduces its efficiency. Until now, studies on particle deagglomeration especially during nanoparticle biosynthesis have not been widely carried out. This mini review will explain the phenomenon of agglomeration during biosynthesis. Moreover, deagglomeration treatment using physical and chemical approaches will be examined. Each approach is considered to be able to deagglomerate nanoparticles well, and the combination of the two is projected to be able to provide better results.
Cadmium Removal with Mutant Brevibacillus Agri C15 Cdr Entrapped in Calcium Alginate Gel: a New Process

With large-scale mining and industrial use of cadmium (Cd), contamination with this metal increased steadily, concerns due to its toxicity and potential damage to the environment and human health have led to the introduction of legislation that regulates acceptable environmental concentrations in different contexts. Therefore, many treatment methods for water and soils have been developed to limit the concentration of Cd in the environment and comply with regulations. In this study, a small laboratory bench-scale column reactor was constructed, optimised, and used to evaluate the removal of Cd from artificial groundwater (AGW) with mutant Brevibacillus agri C15 CdR and its wild type B. agri C15 entrapped in calcium alginate beads at different Cd concentrations. The morphological properties of the beads were studied by scanning electron microscopy (SEM), and energy-dispersive X-ray (EDX) spectroscopy and the location of Cd adsorbed in the beads was detected using a dithizone histochemical method. The experimental results showed that the mutant had significantly higher removal rates than its wild type B. agri C15 (9 and 5 nmol per day per gram of biomass, respectively) due to the presence of the Cd-dithizone complexes on the bead containing the mutant, compared with the less presence of these complexes on the beads containing the wild type. In conclusion, a new process was developed that achieved higher Cd removal rate from AGW by the mutant B. agri C15 CdR. In addition, an alternative detection method of Cd (Cd-dithizone complexes) was introduced that showed that Cd was distributed throughout the Cd-loaded beads.
A comparative study of sound sources separation by independent component analysis and binaural model

Humans’ auditory system can separate mixed sounds based on their sources easily. However, mimicking this ability by computer algorithm is not an easy task. Some approaches have been developed, particularly based on the statistical approach and binaural modeling. From statistical methods, independent component analysis (ICA) grows fast to mimics sound separation and localization by human auditory processing. On the other side, mathematical modeling to model binaural hearing has been built block by block. This paper is a comparative study of both approaches, a statistical method represented by FastICA and binaural modeling represented by the frequency domain binaural model. The task is to mimic how to binaural processing works to separate sound sources. The result of the comparison was given by the perceptual evaluation of speech quality (PESQ) and Itakura-Saito (IS) distortion measurement. PESQ scores ICA method obtains better performance than the binaural model while, in contrast, IS scores the binaural model better than ICA.
Role of toll like receptor-9 (1237 T/C) gene polymorphism in patients with type 2 diabetes and diabetic foot ulcer

This study aimed to evaluate whether (1237 T/C) polymorphism is related with diabetic foot ulcer in type-2 diabetes mellitus of Iraqi patients in Najaf city. Diabetic foot ulcer (DFU) is one of the most prevalent and serious diabetic complications. DFU accounts for about 15% of the diabetic population. It is commonly associated with the increased diabetic morbidities and mortalities. The type 2 diabetes is recognized by aberrations of glucose, lipid and protein metabolism. It is increasingly appreciated that wound healing defect seen in diabetic patients is attributed to the altered protein and lipid metabolism. This study involved (180) subjects, between them, 60 were patients as group one suffering from type 2 diabetes and 60 were patient suffering from type 2 diabetes and foot ulcer as group two. In addition, 60 healthy group three as control subjects. Polymerase chain analysis was used for detection of TLR-9 genotypes followed by restriction analysis. We observed no significance differences in the distribution of the genotypes and alleles of (1237 T/C) polymorphism among the study groups.
Artificial Intelligence based Temporal Material Identification for Improving Qulaity of Service in Communication

The artificial intelligence based learning model helps in identifying temporal material by processing linguistic terms that express time duration in code mixed data. The data available on social media contents are written in mixed script format and from this content temporal material content identification is a challenging task. The retrieval of temporal information and its corresponding time duration expression terms can be identified using artificial intelligence technique based neural learning model. The temporal retrieval and its time duration representation are widely used to present the opinions over the social media. The work described in the paper gives the comparative view of different techniques used in the area of transliteration. The rule framed approach is presented which accepts the roman form text as input and as per the defined rules the system is developed to give the temporal details words available in the sentence. The evaluation measures used here to validate the hypothesis is based on statistical measures along with HLSTM learning model. Further the result is validated using the voting technique that can choose appropriate Temporal label which are not identifies by the learning model. The applied neural learning approach increases the precision value.
Multi-Antenna Selection for Double Spatial Modulation

In this paper, to exploit the spatial domain of transmit antennas (TAs) for the transmit diversity gain in the double spatial modulation (DSM) system, a new scheme of multi-antenna selection for DSM (MAS-DSM) is designed. In the MAS-DSM system, the number of TAs are grouped into n groups, each of which corresponds to an sub-system of DSM. More specifically, a transmitted spatial vector is constructed by two spatial vectors (SVs). For the achievability of transmit diversity gain, one of the two SVs is obtained by using n antenna index (AI) vectors to modulate a data symbol, another of them is obtained by multiplying with a rotation angle after another n AI vectors to modulate another data symbol. Finally, the spectral efficiency and the average bit error ratio (BER) are analyzed. Simulation results by using Monte Carlo demonstrate that the proposed MAS-DSM system has better BER performance compared with the conventional spatial modulation schemes in wireless communication network.
Influence of Subgrade Splicing Mode and Width on Differential Settlement of Pavement Subgrade

In order to study the influence of subgrade splicing mode and width on differential settlement, the large-scale finite element analysis software ANSYS is used to establish the subgrade settlement model, in which the parameters are determined according to the actual subgrade width, widening mode and engineering geological conditions of the widening project of Anxin expressway. The influence of unilateral widening and bilateral widening on the settlement of widened subgrade, the maximum differential settlement on the top of widened subgrade and the influence on horizontal displacement of widened subgrade are systematically evaluated. The results show that for unilateral and bilateral widening, with the increase of widening width, the settlement of the middle line of the old road gradually increases, and the double side widening can make the weight of the widened embankment distribute to both sides of the old subgrade, which greatly improves the settlement coordination of the old and new Subgrade, and is beneficial to the stress of the pavement structure.
MQTT based Time-Series Anomaly Detection System for Smart Grid

Developing smart grid system is a crucial thing and relies heavily on modern technology. Powered by cloud computing and artificial intelligence, electrical grid can make a generational leap towards a more efficient and smart future. Meanwhile, machine learning can get great result in fields like anomaly detection and load forecasting, However, power grid equipment is usually quite underpowered, can’t perform deep learning algorithm locally. In this paper, we proposed a new stream processing architecture based on MQTT protocol, therefore time-series anomaly detection algorithms running on the cloud. Allowing any anomaly event can be detected fast and accurately.
Advanced Hyperchoatic Image Encryption Technic with DNA Sequence

As the development of computer usage increases the need for security also increases as it had changed from entertainment based to high confidential files maintaining medium. So, there was a great improvement in the field of cryptography for data transfer and these are basically text and so they are more simple to process when compared to higher level of files like image and vide. This lead to the need for encryption methods for fast and secure techniques to avoid quality and quantity of high speed encrypted data files. There are lots of highly secure cryptographic methods but they need to be compatible with image for processing. So the project goes along with a technic called hyper chaotic encryption technique with DNA sequence for hybrid image cryptography.
Research on the Application of Computer Technology in Software Technology Talents Training System in Higher Vocational Colleges

With the advent of the information age, the demand for computer professionals such as network maintenance engineers, security engineers, development and operation engineers has gradually increased, and computer software has become one of the hottest industries at present and in the future. As an important part of the education system, higher vocational colleges are constantly training and transporting computer software technology professionals needed by the society, and exploring the application of efficient talent training mode has become one of the key tasks of higher vocational colleges in the future. While enterprises generally reflect that college graduates can’t meet their own needs, colleges and universities are suffering from being unable to know the real needs of enterprises, and lack of specific training templates and inspection standards, resulting in the disconnection between software talent training and demand. In this paper, the analytic hierarchy process (AHP) is used to analyze the established evaluation index system of software technology specialty in higher vocational colleges, and to explore the effective strategies to strengthen the application of efficient talent training mode of software technology specialty in higher vocational colleges.
Security Aware High Scalable paradigm for Data Deduplication in Big Data cloud computing Environments

The challenge of data deduplication has piqued the interest of the research community in order to provide effective and efficient solutions for cloud data centres to remove bottlenecks caused by duplicate data on the exponential growth of outsourced data. An Imminent challenge is the presence of high redundant existence in the storage memory of the cloud environment. Traditional algorithm has been employed to mitigate the data duplication in the cloud environment but it is a daunting task since it requires an effective solution to manage the duplication in the application basis to eliminate the privacy violation on sensitive data. In order to tackle above mentioned issues, a new paradigm named as Security Aware High Scalable has been proposed on large scale computing data centres. Proposed method employed to secure the data Deduplication process using access control mechanism on data of the privileged authorities. Outsourced data will be in the form of encrypted files. Access control mechanism is provided to the secure authorities to conduct the data deduplication on the data that was outsourced. Access Control Mechanism is employed using encryption techniques. It uses randomised encryption that is convergent and stable distribution of ownership party keys to enable the cloud service provider to handle outsourced access to data even though control changes on a regular basis This prevents data from being leaked not just to to those who have had their rights removed who previously owned the data, but even to a degree trustworthy yet suspect server for cloud storage. Furthermore, the proposed technique protects integrity of data from attacks based on label inconsistencies. As a measure, the proposed technique has been modified that enhances security. The efficiency review reveals that the proposed system is nearly as successful as the existing ones, with just a small increase in computational overhead.
Quantification of Ca, K, Mg, Zn and Fe elements in grape leaves from different regions of Iraq by atomic absorption spectroscopy

Grapes grow in various regions of Iraq, regions have been selected Baqubah, Al Khalesah, Nasiriyah and Sulaymaniyah, to determine the Ca, K, Mg, Zn, and Fe concentrations in their leaves for its nutritional importance using atomic absorption spectroscopy (A.A.S.). Two procedures were used for sample preparation (one of their new) and their accuracy data was evaluated, no significant differences at 97% level of confidence were found by comparison the dataset results for two methods. It has been found that Ca, K, Mg, Zn and Fe metal ion concentration are in the range of (806.9 – 2815.2), (7092.2 – 11058.7), (3708.7 – 5434.8), (17.2 – 30.8) and (114.8 – 3083) μg. g-1, respectively and follow the order K>>Mg>Ca>>Fe>Zn. However, the metal contents in vine leaves from Al Khalesah and Baqubah were relatively high in comparing to those of Sulaymaniyah and Nasiriyah. Fe metal content significantly differs from region to region and the highest concentration was found in grape leaves from Baqubah region (2890.9 – 3083.0 μg.g–1), Nasiriyah (2314.8 - 2331.3 μg.g–1), Al Khalesah (205.7 – 237.2 μg.g–1), while the lowest from Sulaymaniyah (110.9 – 114.8 μg.g-1). Thus, through the variation in the concentration of trophic metals in grape leaves from one region to another and their lack of similarity, irregularity, and incongruence, it can be concluded that the different concentration of elements depends on the quality of the soil, the irrigation water, and the climate and atmosphere (The nature of environment).
Acoustic performance of an additive manufactured lattice structure

In this paper, a new type of fibreless, bulk, sound absorber is studied. The acoustic material is an additive manufactured lattice structure constituted by a mesh of pins generated by uniform spatial translation of a regular hexagonal prismatic open cell. The material presents remarkable advantages of metal foams: it is “green”, since no deteriorating, air polluting fibres are used; it is thermally and mechanically resistant, thus fire retardant, self-supporting and impact resistant. Compared to fibrous acoustic materials, it has low moisture absorption although the weight is higher. In addition to these properties, this additive manufactured material is provided with regular open cells whose geometry can be precisely controlled according to the desired performance. Moreover, the acoustical behaviour can be well modelled by simulating the air-solid thermo-viscous interaction within one single cell. The high, broad band sound absorption is a major result of the large viscous losses occurring in the flow which oscillates within the small hexagonal apertures. This lattice, referred to as honeycomb skeleton absorber (HAS), is a multifunctional material which can be used in a variety of structural applications where the sound levels must be controlled and/or a certain thermal resistance/insulation is required (for instance car floors).
Characteristic of semi refined and refined carrageenan flours used in the making of biofilm (bioplastic)

The physical, microbiological, and thermal properties of the raw material, semi refined and refined carrageenan derived from Eucheuma cottonii, were performed in purpose of preliminary research for biofilms (bioplastics) production. The physical properties i.e. particle size, pH, water content, gel strength and viscosity were tested. Meanwhile, the microbiological analysis were performed for the Total Plate Count, mold, and yeast. The thermal properties were performed using Differential Scanning Calorimetry (DSC). The results showed that the Semi Refined Carrageenan (SRC) and Refined Carrageenan (RC) flour have respectively a 60 and 80 mesh of particle size, an 8 and 7 of pH, a 7.9 and 8 % of the moisture content, a 560 and 1140 g / cm2 of gel strength, and an 80 and 35 mPa·s of viscosity. The overall results of the microbiological tested showed that the SRC and RC were recognized as safe to be used for food application in accordance to the regulation, and the thermal analysis showed that the melting points of SRC and RC flour were respectively 168°C and 175°C.
X-Ray AGB Stars in the 4XMM-DR9 Catalog: Further Evidence for Companions

Single AGB stars are not normally expected to be X-ray emitters due to the lack of a corona capable of powering a hot plasma. Therefore, the detection of X-ray emission in AGB stars by the ROSAT, Chandra, and XMM-Newton observatories has been interpreted as evidence for binarity. The number of X-ray-emitting AGB stars is, however, very small, and statistically sound conclusions shall be considered tentative. In this paper we aim at increasing the number of X-ray-emitting AGB stars and at providing a consistent analysis of their X-ray emission to be compared to their UV and optical properties. The XMM-Newton 4XMM-DR9 catalog has been searched for X-ray counterparts of various types of AGB stars: nearby (i.e., listed in Hipparcos), mass-losing, and S- and C-types. Seventeen X-ray counterparts of AGB stars have been found in the 4XMM-DR9. Nine of them have pointed XMM-Newton observations, whereas eight are genuine serendipitous discoveries. Together with the AGB stars detected by ROSAT, this increases the number of X-ray AGB stars to 26. Most of their X-ray spectra can be fit by the emission from an optically thin single-temperature thermal plasma with temperatures typically larger than 107 K. There is no obvious correlation between the X-ray and bolometric luminosity of these stars, but the X-ray luminosity generally increases with the amount of far-UV excess. The high temperature of some X-ray-emitting plasma in AGB stars and the correlation of their X-ray luminosity with the far-UV emission supports the origin of this X-ray emission from accretion disks around unseen companions.