MOBILE PHONES OF HEALTH CARE PROFESSIONALS: A POTENTIAL THREAT TO INFECTION CONTROL IN A TERTIARY CARE HOSPITAL

Background: Nosocomial infections are a major problem in both developed and developing countries. Among various reasons for the increase in the rate of nosocomial infections, the role of mobile phones used by Health Care Professionals (HCPs), is analyzed in this study. Aims and Objectives: To screen the surfaces of mobile phones of HCPs for pathogenic and nonpathogenic bacteria and to compare it with the control group. To study the significance of mobile phones of HCPs acting as vehicles for transmitting nosocomial infections. Materials and Methods: 200 HCPs (Doctors, nurses, medical students, and technicians) 50 other than HCPs mobile phone surfaces are swabbed with sterile swabs soaked in sterile saline and inoculated onto Blood agar and Mac Conkey agar and incubated for 48 hours. The organisms are identified by the colony morphology and characteristic biochemical reactions. Control group (50) comprised of general public and arts and science students. A questionnaire related to their habit of using the cell phones was also filled up by both the test group and the control group. Results: The pathogenic bacteria isolated from study group are Staphylococcus aureus, which is predominant, followed by E. coli, Klebsiella, Pseudomonas aeruginosa andProteus mirabilis. The non- pathogenic bacteria isolated are Micrococci, Coagulase Negative Staphylococci, Diphtheroids, Neisseria catarrahlis, Aerobic spore bearers, and Candida albicans. The prevalence of Pathogenic bacteria and Non Pathogenic bacteria are higher in HCPs samples when compared with the control group. KEY WORDS: Nosocomial infections; Mobile phones; Health care professionals

MOBILE PHONES OF HEALTH CARE PROFESSIONALS: A POTENTIAL THREAT TO INFECTION CONTROL IN A TERTIARY CARE HOSPITAL

Background: Nosocomial infections are a major problem in both developed and developing countries. Among various reasons for the increase in the rate of nosocomial infections, the role of mobile phones used by Health Care Professionals (HCPs), is analyzed in this study. Aims and Objectives: To screen the surfaces of mobile phones of HCPs for pathogenic and nonpathogenic bacteria and to compare it with the control group. To study the significance of mobile phones of HCPs acting as vehicles for transmitting nosocomial infections. Materials and Methods: 200 HCPs (Doctors, nurses, medical students, and technicians) 50 other than HCPs mobile phone surfaces are swabbed with sterile swabs soaked in sterile saline and inoculated onto Blood agar and Mac Conkey agar and incubated for 48 hours. The organisms are identified by the colony morphology and characteristic biochemical reactions. Control group (50) comprised of general public and arts and science students. A questionnaire related to their habit of using the cell phones was also filled up by both the test group and the control group. Results: The pathogenic bacteria isolated from study group are Staphylococcus aureus, which is predominant, followed by E. coli, Klebsiella, Pseudomonas aeruginosa andProteus mirabilis. The non- pathogenic bacteria isolated are Micrococci, Coagulase Negative Staphylococci, Diphtheroids, Neisseria catarrahlis, Aerobic spore bearers, and Candida albicans. The prevalence of Pathogenic bacteria and Non Pathogenic bacteria are higher in HCPs samples when compared with the control group. KEY WORDS: Nosocomial infections; Mobile phones; Health care professionals

Wavelet Based Image Coding Schemes : A Recent Survey

A variety of new and powerful algorithms have been developed for image compression over the years. Among them the wavelet-based image compression schemes have gained much popularity due to their overlapping nature which reduces the blocking artifacts that are common phenomena in JPEG compression and multiresolution character which leads to superior energy compaction with high quality reconstructed images. This paper provides a detailed survey on some of the popular wavelet coding techniques such as the Embedded Zerotree Wavelet (EZW) coding, Set Partitioning in Hierarchical Tree (SPIHT) coding, the Set Partitioned Embedded Block (SPECK) Coder, and the Embedded Block Coding with Optimized Truncation (EBCOT) algorithm. Other wavelet-based coding techniques like the Wavelet Difference Reduction (WDR) and the Adaptive Scanned Wavelet Difference Reduction (ASWDR) algorithms, the Space Frequency Quantization (SFQ) algorithm, the Embedded Predictive Wavelet Image Coder (EPWIC), Compression with Reversible Embedded Wavelet (CREW), the Stack-Run (SR) coding and the recent Geometric Wavelet (GW) coding are also discussed. Based on the review, recommendations and discussions are presented for algorithm development and implementation.Comment: 18 pages, 7 figures, journa

CLIP goes 3D: Leveraging Prompt Tuning for Language Grounded 3D Recognition

Vision-Language models like CLIP have been widely adopted for various tasks due to their impressive zero-shot capabilities. However, CLIP is not suitable for extracting 3D geometric features as it was trained on only images and text by natural language supervision. We work on addressing this limitation and propose a new framework termed CG3D (CLIP Goes 3D) where a 3D encoder is learned to exhibit zero-shot capabilities. CG3D is trained using triplets of pointclouds, corresponding rendered 2D images, and texts using natural language supervision. To align the features in a multimodal embedding space, we utilize contrastive loss on 3D features obtained from the 3D encoder, as well as visual and text features extracted from CLIP. We note that the natural images used to train CLIP and the rendered 2D images in CG3D have a distribution shift. Attempting to train the visual and text encoder to account for this shift results in catastrophic forgetting and a notable decrease in performance. To solve this, we employ prompt tuning and introduce trainable parameters in the input space to shift CLIP towards the 3D pre-training dataset utilized in CG3D. We extensively test our pre-trained CG3D framework and demonstrate its impressive capabilities in zero-shot, open scene understanding, and retrieval tasks. Further, it also serves as strong starting weights for fine-tuning in downstream 3D recognition tasks.Comment: Website: https://jeya-maria-jose.github.io/cg3d-web

TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions

Removing adverse weather conditions like rain, fog, and snow from images is an important problem in many applications. Most methods proposed in the literature have been designed to deal with just removing one type of degradation. Recently, a CNN-based method using neural architecture search (All-in-One) was proposed to remove all the weather conditions at once. However, it has a large number of parameters as it uses multiple encoders to cater to each weather removal task and still has scope for improvement in its performance. In this work, we focus on developing an efficient solution for the all adverse weather removal problem. To this end, we propose TransWeather, a transformer-based end-to-end model with just a single encoder and a decoder that can restore an image degraded by any weather condition. Specifically, we utilize a novel transformer encoder using intra-patch transformer blocks to enhance attention inside the patches to effectively remove smaller weather degradations. We also introduce a transformer decoder with learnable weather type embeddings to adjust to the weather degradation at hand. TransWeather achieves improvements across multiple test datasets over both All-in-One network as well as methods fine-tuned for specific tasks. TransWeather is also validated on real world test images and found to be more effective than previous methods. Implementation code can be accessed at https://github.com/jeya-maria-jose/TransWeather .Comment: CVPR 202

Adaptive scheduled partitioning technique for reliable emergency message broadcasting in VANET for intelligent transportation systems

This paper aims to enable accurate and reliable emergency message broadcast in Vehicular Ad hoc Network (VANET). The VANET is the most common topology used in Intelligent Transportation Systems (ITS), where changes in standard topology due to the mobility of nodes create challenges in broadcasting the emergency message and efficient data delivery in both highway and urban scenarios. The main problems in urban scenarios are channel contention, message redundancy and road structure. To obtain information, broadcast protocols for VANET typically use beacon messages, which are distributed among the vehicles. When multiple vehicles transmit messages at the same time, a broadcast storm occurs and vehicles experience message delivery failure. To address this problem, Adaptive Scheduled Partitioning and Broadcasting Technique (ASPBT) for emergency message broadcast and beacon retransmissions for message reliability were proposed. This protocol dynamically modifies several partitions and beacon periodicity to reduce the number of retransmissions. Later, the partition size is determined by estimating the network transmission density of each partition schedule via the Black Widow Optimization (BWO) algorithm is proposed. The simulation is carried out with different network densities at the vehicle speed of 110 km/h, a direct path length of 12 km under a four-way direction path and performance analysis was performed