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Muhammad Ijaz Ahmad,Muhammad Umair Ijaz,Ijaz ul Haq,Chunbao Li 한국축산식품학회 2020 한국축산식품학회지 Vol.40 No.1
Various processing methods have a great impact on the physiochemical and nutritional properties of meat that are of health concern. Hence, the postmortem processing of meat by different methods is likely to intensify the potential effects on protein oxidation. The influence of meat protein oxidation on the modulation of the systemic redox status and underlying mechanism is well known. However, the effects of processed meat proteins isolated from different sources on gut microbiota, oxidative stress biomarkers, and metabolomic markers associated with metabolic syndromes are of growing interest. The application of advanced methodological approaches based on OMICS, and mass spectrometric technologies has enabled to better understand the molecular basis of the effect of processed meat oxidation on human health and the aging process. Animal studies indicate the involvement of dietary proteins isolated from different sources on health disorders, which emphasizes the impact of processed meat protein on the richness of bacterial taxa such as (Mucispirillum, Oscillibacter), accompanied by increased expression of lipogenic genes. This review explores the most recent evidences on meat processing techniques, meat protein oxidation, underlying mechanisms, and their potential effects on nutritional value, gut microbiota composition and possible implications on human health.
Optimal Resolution Selection to Run Pre-Trained Deep Learning Models on Tiny Images
Ijaz Ahmad,Seokjoo Shin 한국차세대컴퓨팅학회 2021 한국차세대컴퓨팅학회 학술대회 Vol.2021 No.05
The performance of a deep learning model significantly improves on challenging datasets when using transfer learning. However, the pre-trained networks have certain constraints in terms of their architecture. For example, the available pre-trained models are trained for a specific input size. Therefore, require resizing the input images of different sizes. When training a model from scratch, higher resolution image offers better performance. However, our study has shown that this is not true when using pre-trained models. We have compared the pre-trained MobileNetV2 performance on CIFAR10 and CIFAR100 datasets. The pre-trained weights of MobileNetV2 are available for image resolutions of 92x92, 128x128, 160x160, 192x192 and 224x224. The performance of the model is evaluated in terms of classification accuracy. Our analysis have shown that for image resolution of 160x160, the pre-trained model has achieved better classification accuracy.
A Pixel-based Encryption Method for Privacy-Preserving Deep Learning Models
Ijaz Ahmad,Seokjoo Shin 한국통신학회 2022 한국통신학회 학술대회논문집 Vol.2022 No.2
In the recent years, pixel-based perceptual algorithms have been successfully applied for privacy-preserving deep learning (DL) based applications. However, their security has been broken in subsequent works by demonstrating a chosen-plaintext attack. In this paper, we propose an efficient pixel-based perceptual encryption method. The method provides a necessary level of security while preserving the intrinsic properties of the original image. Thereby, can enable deep learning (DL) applications in the encryption domain. The method is substitution based where pixel values are XORed with a sequence (as opposed to a single value used in the existing methods) generated by a chaotic map. We have used logistic maps for their low computational requirements. In addition, to compensate for any inefficiency because of the logistic maps, we use a second key to shuffle the sequence. We have compared the proposed method in terms of encryption efficiency and classification accuracy of the DL models on them. We have validated the proposed method with CIFAR datasets. The analysis shows that when classification is performed on the cipher images, the model preserves accuracy of the existing methods while provides better security.
( Ijaz Ahmad ),( Muhammad Fiaz ),( Muhammad Nauman Manzoor ),( Tanveer Ahmad ),( Muhammad Yaqoob ),( Ik Hwan Jo ) 한국동물자원과학회(구 한국축산학회) 2013 한국축산학회지 Vol.55 No.6
Male cattle calves(n=24), 9-12 months age, with an average body weight of 120±20kg were fed total mixed rations(TMR) for 120 days to determine their growth performance. Animals were divided into four groups(six of each breed): Crossbred (Friesian×Sahiwal), Dhanni, Lohani, and Cholistani. The data obtained were analyzed using analysis of variance techniques under a completely randomized design. The average daily gain(ADG), feed efficiency(FE), and dressing percentage ranged from 639-892g/d, 0.105-0.155kg/kg, and 51.2-51.5%, respectively, in the different breeds. The ADG and FE did not differ between the Crossbred, Dhanni, and Lohani breeds, but these values were lower in Cholistani calves(P<0.05). The dressing percentage was similar in all breeds. The highest increase in body height was observed in Dhanni calves, but heart girth was obviously higher in Lohani calves. The feed cost per kg gain was higher for Cholistani calves but similar among Crossbred, Dhanni, and Lohani calves(P>0.05). In conclusion, Dhanni, Lohani, and Crossbred calves possess the promising potential for beef production under the rainfed(Barani) conditions of the Punjab.