A Low Cost Two-Tier Architecture Model For High Availability Clusters Application Load Balancing

This article proposes a design and implementation of a low cost two-tier architecture model for high availability cluster combined with load-balancing and shared storage technology to achieve desired scale of three-tier architecture for application load balancing e.g. web servers. The research work proposes a design that physically omits Network File System (NFS) server nodes and implements NFS server functionalities within the cluster nodes, through Red Hat Cluster Suite (RHCS) with High Availability (HA) proxy load balancing technologies. In order to achieve a low-cost implementation in terms of investment in hardware and computing solutions, the proposed architecture will be beneficial. This system intends to provide steady service despite any system components fails due to uncertainly such as network system, storage and applications.Comment: Load balancing, high availability cluster, web server cluster

Dimensional Analysis and Variational Formulation of Diffuse Optical Tomography (DOT) Model

Diffuse Optical Tomography (DOT) is an emerging modality for soft tissue imaging with medical applications including breast cancer detection. DOT has many benefits, including its use of non ionizing radiation and its ability to produce high contrast images. However, it is well known that DOT image reconstruction is unstable and has low resolution. DOT uses near infra-red light waves to probe inside a body; for example, DOT can be used to measure the changes in the amount of oxygen in tissues, which can detect early stages of cancer in soft tissues such as the breast and brain. In this thesis, we perform dimensional analysis to obtain a dimensionless form of the ODE for the 1-d DOT model and the PDE for the 2-d DOT model. We later solve the 1-d cases using the finite element method (FEM) in MATLAB. We investigate whether the inverse problem using the dimensionless scaled forward DOT model will improve the ill-posedness of the image reconstruction problem in the 1-d case. We solve the inverse problem for DOT image reconstruction by reformulating the inverse problem as a variationally constrained non-linear optimization problem and compare solving the optimization problem for specific cases of the 1-d DOT model with Newton\u27s iteration versus the traditional Gauss-Newton method. We observe the effects of different regularization parameters and step lengths on the reconstructions for Newton\u27s iteration. We also observe the effect of moving the inclusion away from the boundary during image reconstruction. Using the optimally derived regularization parameter from the noise-free data, we reconstructed the parameter space by adding different levels of noise to the synthetic data. Based on our simulations in 1-d, we conclude that the scaled inverse problem is still ill-posed but that the variational approach provides a better reconstruction than the Gauss-Newton method

Effects of water stress on Alnus glutinosa populations across the species distribution range

Mestrado em Gestão da Floresta e dos Recursos Naturais no Mediterrâneo (MedFor) - Instituto Superior de AgronomiaAlnus glutinosa (Black alder) is paramount species in the riparian ecosystem for supporting ecosystem functioning and the services it provides. This species is declining in an alarming rate which is a prominent threat to devastate native priority forests across Europe, so understanding population responses to environmental change is key for its proper management. In this study, we characterized vegetative phenology and investigated morphological, structural and physiological responses to imposed drought across five populations from countries ranging the species distribution limits (Sweden, Italy, Spain, Portugal, and Morocco). First, we registered 5 stages of budburst of the 120 seedlings of alder (24 by population) in open space. Then, we established a greenhouse experiment where we imposed progressive (Field capacity-FC, 75%FC, 50%FC and 25%FC) water stress (17.06.2019 to 01.08.2019) on 40 seedlings (S), keeping 40 at field capacity, as control until the end of experiment (CE). During 45 days, we performed physiological and morphological measurement at different percentages of FC to compare treatments and populations. Destructive harvest was performed on 40 seedlings (from the total 120) at the onset of the experiment (CO), and then, at the end of the experiment control (CE) and stress (S) seedlings were also destroyed to analyze the structural and functional responses of alder among CE, S and CO and also to compare the variations among populations. We found significant differences among populations on the number of days to reach each phenological stage where northern populations displayed delayed budburst than the southern. As a result of imposed drought, growth and development of A. glutinosa was generally reduced under water restrictions compared to control plants, yet none of the parameters reflected severe plant stress. Conversely, we observed that several of the studied parameters were significantly different among the studied populations likely reflecting intraspecific diversity and environmental conditionsN/

AI Modeling Approaches for Detecting, Characterizing, and Predicting Brief Daily Behaviors such as Toothbrushing using Wrist Trackers.

Continuous advancements in wrist-worn sensors have opened up exciting possibilities for real-time monitoring of individuals\u27 daily behaviors, with the aim of promoting healthier, more organized, and efficient lives. Understanding the duration of specific daily behaviors has become of interest to individuals seeking to optimize their lifestyles. However, there is still a research gap when it comes to monitoring short-duration behaviors that have a significant impact on health using wrist-worn inertial sensors in natural environments. These behaviors often involve repetitive micro-events that last only a few seconds or even microseconds, making their detection and analysis challenging. Furthermore, these micro-events are often surrounded by non-repetitive boundary events, further complicating the identification process. Effective detection and timely intervention during these short-duration behaviors are crucial for designing personalized interventions that can positively impact individuals\u27 lifestyles. To address these challenges, this dissertation introduces three models: mORAL, mTeeth, and Brushing Prompt. These models leverage wrist-worn inertial sensors to accurately infer short-duration behaviors, identify repetitive micro-behaviors, and provide timely interventions related to oral hygiene. The dissertation\u27s contributions extend beyond the development of these models. Firstly, precise and detailed labels for each brief and micro-repetitive behavior are acquired to train and validate the models effectively. This involved meticulous marking of the exact start and end times of each event, including any intervening pauses, at a second-level granularity. A comprehensive scientific research study was conducted to collect such data from participants in their free-living natural environments. Secondly, a solution is proposed to address the issue of sensor placement variability. Given the different positions of the sensor within a wristband and variations in wristband placement on the wrist, the model needs to determine the relative configuration of the inertial sensor accurately. Accurately determining the relative positioning of the inertial sensor with respect to the wrist is crucial for the model to determine the orientation of the hand. Additionally, time synchronization errors between sensor data and associated video, despite both being collected on the same smartphone, are addressed through the development of an algorithm that tightly synchronizes the two data sources without relying on an explicit anchor event. Furthermore, an event-based approach is introduced to identify candidate segments of data for applying machine learning models, outperforming the traditional fixed window-based approach. These candidate segments enable reliable detection of brief daily behaviors in a computationally efficient manner suitable for real-time. The dissertation also presents a computationally lightweight method for identifying anchor events using wrist-worn inertial sensors. Anchor events play a vital role in assigning unambiguous labels in a fixed-length window-based approach to data segmentation and effectively demarcating transitions between micro-repetitive events. Significant features are extracted, and explainable machine learning models are developed to ensure reliable detection of brief daily and micro-repetitive behaviors. Lastly, the dissertation addresses the crucial factor of the opportune moment for intervention during brief daily behaviors using wrist-worn inertial sensors. By leveraging these sensors, users can receive timely and personalized interventions to enhance their performance and improve their lifestyles. Overall, this dissertation makes substantial contributions to the field of real-time monitoring of short-duration behaviors. It tackles various technical challenges, provides innovative solutions, and demonstrates the potential for wrist-worn sensors to facilitate effective interventions and promote healthier behaviors. By advancing our understanding of these behaviors and optimizing intervention strategies, this research has the potential to significantly impact individuals\u27 well-being and contribute to the development of personalized health solutions

Role of India in Rohingya Crisis

Almost 7,000,00 Rohingya Muslims have left Burma's Rakhine State since late August 2017 to escape the military's extensive campaign of collective action. Mass murders, sexual violence, and unrestrained consumption are only a few of the barbaric acts committed by Burmese security forces. These crimes are against humanity. Aung Sang Suu Kyi's government received criticism from both Western and Islamic countries, while Asian giant India supported Myanmar's initiatives. Given their long-term geo-legislative problems and geo-financial elements of South and Southeast Asian objectives, India too has significant stakes in Myanmar. Myanmar is a crucial essential ally in India's efforts to strengthen trade, speculation, and other forms of financial engagement with ASEAN since it is the only ASEAN nation with whom India has both land and sea borders. India's gateway to Southeast Asia is Myanmar, which explains why India has been so tactful in its stance toward the Rohingya problem. Alongside that, the Rakhine state is a crucial connection for India's hydrocarbon and exchange objectives; India has been taking a stab at linking upper East Indian states to Sittwe port. This study further reveals how India pursues its strategic goals by delivering developmental aid in Rakhine and some little help to the displaced people in Bangladesh while concluding arrangements to effectively repatriate the couple of thousand Rohingyas from the nation

EVALUATION OF MUNICIPAL SERVICES IN SELECTED WARDS OF DHAKA CITY CORPORATION: CITIZEN’S PERSPECTIVE

Dhaka city is the home of more than five million and is one of the most densely populated cities of the world. Dhaka City Corporation is responsible for providing various services to its citizen with its limited resources. ‘Citizen Report Card’ is one of the new methods to measure the performance of civic services provided by urban government. This study used this method to measure the performance of waste management, mosquito control and certification service offered by Dhaka City Corporation in some selected wards of Dhaka City. The performance of each of these services is ranked using The Urban Governance Indicator value. The study concluded that citizen of Dhaka ranked the waste management and certification service as fair while mosquito control service was identified as poor. The paper ended with a discussion on possible improvement of quality of services.Dhaka City Corporation, Citizen Report Card, Municipal Services, The Urban Governance Initiative Index (TUGI).

D-π-D chromophores based on dithieno[3,2-b:2′,3'-d]thiophene (DTT) : potential application in the fabrication of solar cell

In this work, four stable dithieno[3,2-b:2′,3'-d]thiophene-based π-extended molecules were designed and synthesized via a Pd-catalysed Sonogashira coupling reaction. The structures of these symmetrical compounds, including dithieno[3,2-b:2′,3'-d]thiophene (DTT) as the π-center and various donor (D) groups, were determined on the basis of NMR spectral data, elemental analysis, and X-ray crystallography. The photo-physical properties of the DTT-based derivatives 2 were fully investigated in both solution and solid state. The notable optical features of their solid-state powders showed significant red-shift in comparison with the luminescence of their dilute dichloromethane solutions. These results combined with the theoretical calculations indicate that they are promising candidates for the several applications in electronic and optoelectronic devices, as well as organic dyes for solar cells