BC₃ Sheet Functionalized with Lithium‐Rich Species Emerging as a Reversible Hydrogen Storage Material

Hussain, Tanveer,Chakraborty, Sudip,Kang, T. W.,Johansson, Bö,rje,Ahuja, Rajeev WILEY‐VCH Verlag 2015 ChemPhysChem Vol.16 No.3

<P>The decoration of a BC3 monolayer with the polylithiated molecules CLi4 and OLi2 has been extensively investigated to study the hydrogen-storage efficiency of the materials by first principles electronic structure calculations. The binding energies of both lithiated species with the BC3 substrate are much higher than their respective cohesive energies, which confirms the stability of the doped systems. A significant positive charge on the Li atom in each of the dopants facilitates the adsorption of multiple H-2 molecules under the influence of electrostatic and van der Waals interactions. We observe a high H-2-storage capacity of 11.88 and 8.70 wt% for the BC3-CLi4 and BC3-OLi2 systems, respectively, making them promising candidates as efficient energy-storage systems.</P>

Emotion Recognition of Low Resource (Sindhi) Language Using Machine Learning

Ahmed, Tanveer,Memon, Sajjad Ali,Hussain, Saqib,Tanwani, Amer,Sadat, Ahmed International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.8

One of the most active areas of research in the field of affective computing and signal processing is emotion recognition. This paper proposes emotion recognition of low-resource (Sindhi) language. This work's uniqueness is that it examines the emotions of languages for which there is currently no publicly accessible dataset. The proposed effort has provided a dataset named MAVDESS (Mehran Audio-Visual Dataset Mehran Audio-Visual Database of Emotional Speech in Sindhi) for the academic community of a significant Sindhi language that is mainly spoken in Pakistan; however, no generic data for such languages is accessible in machine learning except few. Furthermore, the analysis of various emotions of Sindhi language in MAVDESS has been carried out to annotate the emotions using line features such as pitch, volume, and base, as well as toolkits such as OpenSmile, Scikit-Learn, and some important classification schemes such as LR, SVC, DT, and KNN, which will be further classified and computed to the machine via Python language for training a machine. Meanwhile, the dataset can be accessed in future via https://doi.org/10.5281/zenodo.5213073.

이상행동 및 행동 인식 모델 학습 및 테스트를 위한 시스템 UI 설계에 대한 연구

이수민,권찬민,Tanveer Hussain,Samee Ullah Khan,Waseem Ullah,Noman Khan,Zulfiqar Ahmad Khan,이미영,백성욱 한국차세대컴퓨팅학회 2021 한국차세대컴퓨팅학회 학술대회 Vol.2021 No.05

인공지능을 활용한 사업이 활발히 진행되면서 범죄 예방 및 안전분야와 관련하여 이상행동 및 행동 인식에 대한 연구와 관심이 높아지고 있다. 하지만 딥러닝 등 인공지능 모델을 생성하는 것은 전문 지식이 없는 경우 많은 어려움이 따른다. 본 논문에서는 사용자가 편리하게 딥러닝 모델을 생성할 수 있도록 데이터셋을 제공하고 이상행동 및 행동 인식 기술을 API화하여 인터페이스에서 호출하는 방식을 사용하는 사용자 친화적인 모델 학습 및 테스트를 위한 시스템 UI를 제안하였다. 본 논문에서 제안한 시스템은 딥러닝에 대한 사전 지식이 없는 사용자가 편리하게 딥러닝 모델을 생성할 수 있을 것으로 기대된다.

Reversible hydrogen storage properties of defect-engineered _{C 4} N nanosheets under ambient conditions

Alhameedi, Khidhir,Hussain, Tanveer,Bae, Hyeonhu,Jayatilaka, Dylan,Lee, Hoonkyung,Karton, Amir Elsevier 2019 Carbon Vol.152 No.-

<P><B>Abstract</B></P> <P>Inspired by the promise of hydrogen (H<SUB>2</SUB>) as a clean alternate to the existing energy sources, we have employed spin-polarized density functional theory calculations on a recently designed two-dimensional <SUB> C 4 </SUB> N monolayer as a promising <SUB> H 2 </SUB> storage material. By means of first principles DFT calculations, we have comprehensively studied the geometric and electronic properties of pristine, defected and metal-doped <SUB> C 4 </SUB> N nanosheets and further explored their <SUB> H 2 </SUB> storage properties. We found that light metal dopants such as Li, Na, K, Mg, and Ca bind strongly to defects on a <SUB> C 4 </SUB> N nanosheet with binding energies of 3–4 eV per dopant. These binding energies are sufficiently strong to surpass metal clustering. Thermal stability of the metal-doped <SUB> C 4 </SUB> N nanosheets has been further verified by means of ab initio molecular dynamics simulations. The bonding nature of the metal dopants with the <SUB> C 4 </SUB> N nanosheet has been studied through Bader analysis and Roby-Gould methods and the electronic properties were studied through density of states. We found that each dopant in the metal-doped <SUB> C 4 </SUB> N nanosheet can bind up to five <SUB> H 2 </SUB> molecules with adsorption energies ranging between 0.15 and 0.60 eV/ <SUB> H 2 </SUB> , which results in optimal <SUB> H 2 </SUB> storage capacities. Finally, we employed thermodynamic analysis to investigate the <SUB> H 2 </SUB> adsorption/desorption mechanism under practical operating conditions.</P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Dual Modality-based Animals Species Recognition using Deep learning Techniques

Min Je Kim,Tanveer Hussain,Waseem Ullah,Hikmat Yar,Mi Young Lee,Muhammad Sajjad,Sung Wook Baik 한국차세대컴퓨팅학회 2022 한국차세대컴퓨팅학회 학술대회 Vol.2022 No.10

The analysis, recognition and perception of behavior has usually been a crucial task for researchers. The goal of this paper is to address the problem to recognize animal species, which has numerous applications in zoology, ecology, biology, and entertainment. Researchers used different machine learning approach for animal species recognition, however the researchers mostly used image data for this purpose and ignore the importance of audio data. In this work, our focus is to process multi modality (image and voice) dataset for animal species recognition. We proposed two different networks for animals’ audio and visual representation to recongize animals’ species. First network for animals’ audios classification that extract MFCC features, and these features is passed from four VGG style blocks while the second network extract visual features from images to classify according to their species. The experimental results demonstrated the effectiveness of the proposed model of achieved better performance in terms of classification accuracies.

Customer Activity Recognition System using Image Processing

Waqas, Maria,Nasir, Mauizah,Samdani, Adeel Hussain,Naz, Habiba,Tanveer, Maheen International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.9

The technological advancement in computer vision has made system like grab-and-go grocery a reality. Now all the shoppers have to do now is to walk in grab the items and go out without having to wait in the long queues. This paper presents an intelligent retail environment system that is capable of monitoring and tracking customer's activity during shopping based on their interaction with the shelf. It aims to develop a system that is low cost, easy to mount and exhibit adequate performance in real environment.

Sequence variation of necdin gene in Bovidae

( Sunday O. Peters ),( Marcos De Donato ),( Tanveer Hussain ),( Hectorina Rodulfo ),( Masroor E. Babar ),( Ikhide G. Imumorin ) 한국축산학회(구 한국동물자원과학회) 2018 한국축산학회지 Vol.60 No.12

Background: Necdin (NDN), a member of the melanoma antigen family showing imprinted pattern of expression, has been implicated as causing Prader-Willi symptoms, and known to participate in cellular growth, cellular migration and differentiation. The region where NDN is located has been associated to QTLs affecting reproduction and early growth in cattle, but location and functional analysis of the molecular mechanisms have not been established. Methods: Here we report the sequence variation of the entire coding sequence from 72 samples of cattle, yak, buffalo, goat and sheep, and discuss its variation in Bovidae. Median-joining network analysis was used to analyze the variation found in the species. Synonymous and non-synonymous substitution rates were determined for the analysis of all the polymorphic sites. Phylogenetic analysis were carried out among the species of Bovidae to reconstruct their relationships. Results: From the phylogenetic analysis with the consensus sequences of the studied Bovidae species, we found that only 11 of the 26 nucleotide changes that differentiate them produced amino acid changes. All the SNPs found in the cattle breeds were novel and showed similar percentages of nucleotides with non-synonymous substitutions at the Nterminal, MHD and C-terminal (12.3, 12.8 and 12.5%, respectively), and were much higher than the percentage of synonymous substitutions (2.5, 2.6 and 4.9%, respectively). Three mutations in cattle and one in sheep, detected in heterozygous individuals were predicted to be deleterious. Additionally, the analysis of the biochemical characteristics in the most common form of the proteins in each species show very little difference in molecular weight, pI, net charge, instability index, aliphatic index and GRAVY (Table 4) in the Bovidae species, except for sheep, which had a higher molecular weight, instability index and GRAVY. Conclusions: There is sufficient variation in this gene within and among the studied species, and because NDN carry key functions in the organism, it can have effects in economically important traits in the production of these species. NDN sequence is phylogenetically informative in this group, thus we propose this gene as a phylogenetic marker to study the evolution and conservation in Bovidae.

데이터 주석 및 모델 성능 향상을 위한 능동적 학습 접근

Hikmat Yar,Samee Ullah Khan,Tanveer Hussain,Min Je Kim,Mi Young Lee,Sung Wook Baik 한국차세대컴퓨팅학회 2022 한국차세대컴퓨팅학회 학술대회 Vol.2022 No.05

Deep learning models achieved a lot of success due to the availability of labeled training data. In contrast, labeling a huge amount of data by a human is a time-consuming and expensive solution. Active Learning (AL) efficiently addresses the issue of labeled data collection at a low cost by picking the most useful samples from a large number of unlabeled datasets However, current AL techniques largely depend on regular human involvement to annotate the most uncertain/informative samples in the collection. Therefore, a novel AL-based framework is proposed comprised of proxy and active models to reduce the manual labeling costs. In the proxy model, VGG-16 is trained on chunks of labeled data that later act as an annotator decision. On the other hand, in the active model, unlabeled is passed to Inception-V3 using the sampling strategy. The uncorrected predicted samples are then forwarded to the proxy model for annotation and considered those data have a high confidence score. The empirical results verify that our proposed model is the best in terms of annotation and accuracy.

Development of UV Protective, Superhydrophobic and Antibacterial Textiles Using ZnO and TiO2 Nanoparticles

Muhammad Zaman Khan,Vijay Baheti,Munir Ashraf,Tanveer Hussain,Azam Ali,Amjed Javid,Abdur Rehman 한국섬유공학회 2018 Fibers and polymers Vol.19 No.8

In this research work, multifunctional cotton fabric comprising of UV protection, superhydrophobicity and antibacterial activity has been developed using facile pad-dry-cure method. In the first step, the concentration of repellent chemical has been optimized. Then, formulations containing nanoparticles of ZnO or TiO2 along with optimized concentration of repellent chemical and organic-inorganic binder have been applied to cotton fabric followed by the evaluation of functional properties. The surface morphology and elemental composition of treated fabric has been characterized through SEM and EDX, respectively. The treated samples have shown promising UV protection, superhydrophobicity and antibacterial properties durable upto 20 washing cycles.

Stable Ferroelectric Behavior of Nb-Modified Bi0.5K0.5TiO3-Bi(Mg0.5Ti0.5)O3 Lead-Free Relaxor Ferroelectric Ceramics

Zaman, Arif,Malik, Rizwan Ahmed,Maqbool, Adnan,Hussain, Ali,Ahmed, Tanveer,Song, Tae Kwon,Kim, Won-Jeong,Kim, Myong-Ho Minerals, Metals & Materials Society and the Insti 2018 Journal of electronic materials Vol.47 No.3

<P>Crystal structure, dielectric, ferroelectric, piezoelectric, and electric field-induced strain properties of lead-free Nb-modified 0.96Bi(0.5)K(0.5)TiO(3)-0.04Bi(Mg0.5Ti0.5)O-3 (BKT-BMT) piezoelectric ceramics were investigated. Crystal structure analysis showed a gradual phase transition from tetragonal to pseudocubic phase with increasing Nb content. The optimal piezoelectric property of small-signal d (33) was enhanced up to similar to 68 pC/N with a lower coercive field (E (c)) of similar to 22 kV/cm and an improved remnant polarization (P (r)) of similar to 13 mu C/cm(2) for x = 0.020. A relaxor-like behavior with a frequency-dependent Curie temperature T (m) was observed, and a high T (m) around 320A degrees C was obtained in the investigated system. This study suggests that the ferroelectric properties of BKT-BMT was significantly improved by means of Nb substitution. The possible shift of depolarization temperature T (d) toward high temperature T (m) may have triggered the spontaneous relaxor to ferroelectric phase transition with long-range ferroelectric order without any traces of a nonergodic relaxor state in contradiction with Bi0.5Na0.5TiO3-based systems. The possible enhancement in ferroelectric and piezoelectric properties near the critical composition x = 0.020 may be attributed to the increased anharmonicity of lattice vibrations which may facilitate the observed phase transition from a low-symmetry tetragonal to a high-symmetry cubic phase with a decrease in the lattice anisotropy of an undoped sample. This highly flexible (at a unit cell level) narrow compositional range triggers the enhancement of d (33) and P (r) values.</P>