Zippering and Intermeshing: Novel Phase Diagrams for Interfaces and Films

New surface and layering phase diagrams are proposed based on generalized sine-Gordon models with and without a substrate potential. In particular, we find that the preroughening transition can be driven first order, explaining “zipper” features in heat capacity data for argon and krypton on graphite substrates. For different parameters, we predict the existence of a novel variant of den Nijs' disordered flat phase with spontaneously broken particle-hole symmetry and continuously varying surface height with an accompanying intermeshing layering phase diagram. The restricted solid-on-solid model displays zippering for sufficiently large second neighbor coupling

Layering transitions, disordered flat phases, reconstruction, and roughening

We study in light of recent ellipsometry, vapor pressure isotherm and specific-heat measurements on the thermodynamics of adsorbed thin films on graphite, the connection between the layering phase diagrams of thin films on periodic substrates and the thermodynamics of the solid-vapor interface of a semi-infinite crystal. The latter is the limit of the former when the film becomes infinitely thick, and we are interested in connecting this limiting behavior to the thermodynamics of films of finite thickness. We argue that the concepts of surface roughening, preroughening, and reconstruction provide a quantitatively useful framework within which to discuss this connection. Through general renormalization-group arguments and, in more detail, through a self-consistent mean-field treatment that explicitly accounts for all relevant phases, we show that the same types of interactions that lead to these different surface phases lead also to the reentrant layering transitions seen in the recent experiments. By appropriate tuning of the mean-field parameters we can semiquantitatively reconstruct all the observed experimental phase diagrams. It turns out that certain experimental phase diagrams with “zippers” require that the preroughening transition become first order. Our renormalization-group arguments predict such behavior in certain parameter ranges. In addition, for different parameters we predict the existence of an, as yet unobserved, θ disordered flat phase with spontaneously broken particle-hole symmetry and continuously varying surface height with an accompanying intermeshing layering phase diagram. The underlying lattice in the experiments is triangular, and this actually enhances the stability of the disordered flat phase and the corresponding reentrant layering transitions in the films

Vector Linear Error Correcting Index Codes and Discrete Polymatroids

The connection between index coding and matroid theory have been well studied in the recent past. El Rouayheb et al. established a connection between multi linear representation of matroids and wireless index coding. Muralidharan and Rajan showed that a vector linear solution to an index coding problem exists if and only if there exists a representable discrete polymatroid satisfying certain conditions. Recently index coding with erroneous transmission was considered by Dau et al.. Error correcting index codes in which all receivers are able to correct a fixed number of errors was studied. In this paper we consider a more general scenario in which each receiver is able to correct a desired number of errors, calling such index codes differential error correcting index codes. We show that vector linear differential error correcting index code exists if and only if there exists a representable discrete polymatroid satisfying certain conditionsComment: arXiv admin note: substantial text overlap with arXiv:1501.0506

Optimal Error Correcting Delivery Scheme for Coded Caching with Symmetric Batch Prefetching

Coded caching is used to reduce network congestion during peak hours. A single server is connected to a set of users through a bottleneck link, which generally is assumed to be error-free. During non-peak hours, all the users have full access to the files and they fill their local cache with portions of the files available. During delivery phase, each user requests a file and the server delivers coded transmissions to meet the demands taking into consideration their cache contents. In this paper we assume that the shared link is error prone. A new delivery scheme is required to meet the demands of each user even after receiving finite number of transmissions in error. We characterize the minimum average rate and minimum peak rate for this problem. We find closed form expressions of these rates for a particular caching scheme namely \textit{symmetric batch prefetching}. We also propose an optimal error correcting delivery scheme for coded caching problem with symmetric batch prefetching.Comment: 9 pages and 4 figure

Hypervolume Sen Task Scheduilng and Multi Objective Deep Auto Encoder based Resource Allocation in Cloud

Cloud Computing (CC) environment has restructured the Information Age by empowering on demand dispensing of resources on a pay-per-use base. Resource Scheduling and allocation is an approach of ascertaining schedule on which tasks should be carried out. Owing to the heterogeneity nature of resources, scheduling of resources in CC environment is considered as an intricate task. Allocating best resource for a cloud request remains a complicated task and the issue of identifying the best resource – task pair according to user requirements is considered as an optimization issue. Therefore the main objective of the Cloud Server remains in scheduling the tasks and allocating the resources in an optimal manner. In this work an optimized task scheduled resource allocation model is designed to effectively address  large numbers of task request arriving from cloud users, while maintaining enhanced Quality of Service (QoS). The cloud user task requests are mapped in an optimal manner to cloud resources. The optimization process is carried out using the proposed Multi-objective Auto-encoder Deep Neural Network-based (MA-DNN) method which is a combination of Sen’s Multi-objective functions and Auto-encoder Deep Neural Network model. First tasks scheduling is performed by applying Hypervolume-based Sen’s Multi-objective programming model. With this, multi-objective optimization (i.e., optimization of cost and time during the scheduling of tasks) is performed by means of Hypervolume-based Sen’s Multi-objective programming. Second, Auto-encoder Deep Neural Network-based Resource allocation is performed with the scheduled tasks that in turn allocate the resources by utilizing Jensen–Shannon divergence function. The Jensen–Shannon divergence function has the advantage of minimizing the energy consumption that only with higher divergence results, mapping is performed, therefore improving the energy consumption to a greater extent. Finally, mapping tasks with the corresponding resources using Kronecker Delta function improves the makespan significantly. To show the efficiency of Multi-objective Auto-encoder Deep Neural Network-based (MA-DNN) cloud time scheduling and optimization between tasks and resources in the CC environment, we also perform thorough experiments on the basis of realistic traces derived from Personal Cloud Datasets. The experimental results show that compared with RAA-PI-NSGAII and DRL, MA-DNN not only significantly accelerates the task scheduling efficiency, task scheduling time but also reduces the energy usage and makespan considerably

Optimized Screening of Glaucoma using Fundus Images and Deep Learning

Diabetic retinopathy, glaucoma, and age-related macular degeneration are among the leading causes of global visual loss. Early detection and diagnosis of these conditions are crucial to reduce vision loss and improve patient outcomes. In recent years, deep learning algorithms have shown great potential in automating the diagnosis and categorization of eye disorders using medical photos. For this purpose, the ResNet-50 architecture is employed in a deep learning-based strategy. The approach involves fine-tuning a pre-trained ResNet-50 model using over 5,000 retinal pictures from the ODIR dataset, covering ten different ocular diseases. To enhance the model's generalization performance and avoid overfitting, various data augmentation techniques are applied to the training data. The model successfully detects glaucoma-related ocular illnesses, including cataract, diabetic retinopathy, and healthy eyes. Performance evaluation using metrics like accuracy, precision, recall, and F1-score shows that the model achieved 92.60% accuracy, 93.54% precision, 91.60% recall, and an F1-score of 91.68%. These results indicate that the proposed strategy outperforms many state-of-the-art approaches in the detection and categorization of eye disorders. This success underscores the potential of deep learning-based methods in automated ocular illness identification, facilitating early diagnosis and timely treatment to ultimately improve patient outcomes

PCR-based sex determination of cetaceans and dugong from the Indian seas

A sex-determination technique based on PCR amplifi- cation of genomic DNA extracted from the skin tissue has been standardized in cetaceans and dugong sam-pled from the Indian seas. A Y-chromosome-specific region (SRY or Sex-determining Y-chromosome gene) of 210–224 bp size in the genome has been amplified (only in males) using specific PCR primers. A fragment of the ZFX/ZFY (zinc finger protein genes located both on the X and Y chromosomes respectively) re-gion in the size range 442–445 bp is also amplified (in both sexes) using another pair of primers simultaneously as positive controls for confirmation of sex. Molecular sexing was standardized in spinner dolphin (Stenella longirostris), bridled dolphin (Stenella attenuata), bottlenose dolphin (Tursiops aduncus), Indo-Pacific humpbacked dolphin (Sousa chinensis), Risso’s dolphin (Grampus griseus), finless porpoise (Neopho-caena phocaenoides), sperm whale (Physeter macro-cephalus), blue whale (Balaenoptera musculus), Bryde’s whale (Balaenoptera edeni) and dugong (Dugong du-gon), which are all vulnerable/endangered species pro- tected under the Indian Wildlife Act

Optimization of Piezo-fibre Composite with IDE Embedded in a Multilayer Glass Fibre Composite

AbstractThis paper deals with studying the effect of positioning and number of PFC with IDE (PFC-W14) embedded in a multilayer glass fibre composite for energy harvesting. Vacuum Bagging process is used to fabricate eight Multi- layered composite with PFC-W14 embedded inside the specimen at different locations and numbers. The PFC-W14 is positioned at different layers of the composite and number of PFC-W14 is varied in order to study various cases of strain acting on composite. Vibration test for different frequencies were conducted on these eight specimen using electro-dynamic shaker. The generated energy is directly proportional to the strain or voltage generated along the perpendicular axis of the direction of the strain applied, which is collected by the Integrated Digitated Electrodes. The max frequency of vibration at which max voltage is generated by each specimen is observed for different locations and numbers. The results of this study are presented with an eye toward obtaining guidelines for design of useful energy harvesting structures

Multi-access Coded Caching with Decentralized Prefetching

An extension of coded caching referred to as multi-access coded caching where each user can access multiple caches and each cache can serve multiple users is considered in this paper. Most of the literature in multi-access coded caching focuses on cyclic wrap-around cache access where each user is allowed to access an exclusive set of consecutive caches only. In this paper, a more general framework of multi-access caching problem is considered in which each user is allowed to randomly connect to a specific number of caches and multiple users can access the same set of caches. For the proposed system model considering decentralized prefetching, a new delivery scheme is proposed and an expression for per user delivery rate is obtained. A lower bound on the delivery rate is derived using techniques from index coding. The proposed scheme is shown to be optimal among all the linear schemes under certain conditions. An improved delivery rate and a lower bound for the decentralized multi-access coded caching scheme with cyclic wrap-around cache access can be obtained as a special case. By giving specific values to certain parameters, the results of decentralized shared caching scheme and of conventional decentralized caching scheme can be recovered.Comment: 26 pages, 6 figures, 6 tables, Submitted to IEEE Transactions on Communication