An investigation into the impact of reservoir management Kerala floods 2018: A case study of the Kakki reservoir

The coastal state of Kerala, India experienced unprecedented levels of rainfall and flooding in August 2018, resulting in huge life and property loss. Since then the impact reservoir management may have had on the severity of the 2018 Kerala floods has been in question. This study presents a novel approach to developing a reservoir model using HECHMS and HEC-ResSim models, combined with satellite remote sensing data. In order to establish a link between flood severity and reservoir management, a model of the Kakki reservoir in southern Kerala was created. Simulations were carried out for six long term, two short term, and two immediate run cases. It was found that all cases except the immediate simulation run resulted in a reduced peak flow. The long simulation run, which altered the guide curve after the heavy rainfall occurring on 14th August 2018, while constraining the outflow, was found to produce the greatest reduction in peak outflow. The significant peak outflow reduction achieved suggests that improved reservoir management could have reduced the severity of the 2018 floods

A Case for Using The Balanced Scorecard Framework at Project Stage-Gates

IT project management is plagued by its inability to stop projects that ultimately fail. This persistent problem results in the loss of scarce resources and IT departments unable to generate full value for money invested. There is considerable evidence to suggest that information asymmetry is a significant contributor to this waste. The Balanced Scorecard is a framework that has been widely employed in business as a tool to translate the organizational vision into workable business plans and a framework for effective communication amongst stakeholders. Stage-gates are a widely-used method in new product development and they are gradually making inroads into software project governance. Using a model based on Balanced Scorecard and Stage-gates, this study proposes how their use in IT project governance can mitigate the effects of information asymmetry and thereby increase the likelihood of terminating an uneconomical project quickly

Performance and Security Enhancement of AODV Protocol under Black Hole Attack

As in the convention of the wireless there are two types of wireless networks namely with base station (cell phone technology) and adhoc networks without base station. As adhoc networks play an important role in military based applications as centralized base station cannot be placed. So, the adhoc networks came into existence. As in the conventional adhoc networks the routing protocols are AODV. The AODV is based on IEEE802.11 the AODV uses destination based routing. As AODV cannot withstand blackhole attack. So the SAODV came into existence. In this paper we will present multihop adhoc networks and then the security for AODV is discussed. DOI: 10.17762/ijritcc2321-8169.15024

Bone marrow transplantation alters the tremor phenotype in the murine model of globoid-cell leukodystrophy

Tremor is a prominent phenotype of the twitcher mouse, an authentic genetic model of Globoid-Cell Leukodystrophy (GLD, Krabbe’s disease). In the current study, the tremor was quantified using a force-plate actometer designed to accommodate low-weight mice. The actometer records the force oscillations caused by a mouse’s movements, and the rhythmic structure of the force variations can be revealed. Results showed that twitcher mice had significantly increased power across a broad band of higher frequencies compared to wildtype mice. Bone marrow transplantation (BMT), the only available therapy for GLD, worsened the tremor in the twitcher mice and induced a measureable alteration of movement phenotype in the wildtype mice. These data highlight the damaging effects of conditioning radiation and BMT in the neonatal period. The behavioral methodology used herein provides a quantitative approach for assessing the efficacy of potential therapeutic interventions for Krabbe’s disease

Breaking the Iron Triangle: The Impact of Information Sufficiency on Project Portfolio Decisions

IT project governance is plagued by an inability to stop projects that ultimately fail, resulting in the loss of scarce resourcesand IT departments unable to generate full value for money invested. This study investigates the impact of the measurementinformation framework on information sufficiency, a key factor in reaching effective decisions. Specifically, this researchaddresses the question “Does a Balanced Scorecard (BSC) measurement information framework provide higher informationsufficiency and greater decision making efficacy than the traditional Quality-Cost-Schedule approach in a project governancecontext?” This question is addressed using a randomized counterbalanced experimental design. Results were encouragingwith significant support for two of the three hypotheses positing improved outcomes from use of the Balanced Scorecardframework

Spectroscopic and Structural Properties of Yb3+-Doped and Undoped 2D-Mos2 Thin Films for Optoelectronic and Photonic Device Applications

Molybdenum disulphide (MoS 2 ) has layered structure and is classed as a transition metal-disulphide (TMD) material. Recently it has drawn significant attention for exploring optoelectronic and photonic properties on sub-nanometre scale, with a potential for accessing quantum interactions [1]. The electronic structure and stoichiometry of TMDs make them distinguishable from the metallic graphene, as the TMDs depict a clear bandgap, as in compound semiconductors [2], which is quite attractive for device engineering and applications in photovoltaic, energy storage, and bandgap engineered light-sources [3]. In this research, the fabrication of undoped and Yb 3+ -ion doped MoS 2 nanometre (nm)-scale thin films are discussed using femto-second pulsed laser deposition (fs-PLD) and the structural and spectroscopic properties of fs-PLD are compared with liquid-phase epitaxy grown undoped MoS 2 films. Such a comparative analysis may offer materials fabrication platform in future for engineering optoelectronic and photonic devices on silica glass and silicon platforms

Sodium-Glucose Cotransporter-2 Inhibitor Use is Associated with a Reduced Risk of Heart Failure Hospitalization in Patients with Heart Failure with Preserved Ejection Fraction and Type 2 Diabetes Mellitus: A Real-World Study on a Diverse Urban Population

Background: Limited evidence-based therapies exist for the management of heart failure with preserved ejection fraction (HFpEF). Sodium-glucose cotransporter-2 inhibitor (SGLT2i) use in patients with systolic heart failure (HFrEF) and type-2-diabetes mellitus (T2DM) is associated with improved cardiovascular (CV) and renal outcomes. Objective: We sought to examine whether there is an association of SGLT2i use with improved CV outcomes in patients with HFpEF. Patients and methods: We conducted a single-center, retrospective review of patients with HFpEF and T2DM. The cohort was divided into two groups based on prescription of a SGLT2i or sitagliptin. The primary outcome was heart failure hospitalization (HFH); secondary outcomes were all-cause hospitalization and acute kidney injury (AKI). Results: After propensity score matching, there were 250 patients (89 in the SGLT2i group, 161 in the sitagliptin group), with a mean follow-up of 295 days. Univariate Cox regression analysis showed that the SGLT2i group had a reduced risk of HFH versus the sitagliptin group (hazard ratio (HR) 0.13; 95% confidence interval (CI) (0.05–0.36); p \u3c 0.001). The SGLT2i group had a decreased risk of all-cause hospitalization (HR 0.48; 95% CI (0.33–0.70); p \u3c 0.001) and SGLT2i had a lower risk of AKI (HR 0.39; 95% CI (0.20–0.74); p = 0.004). Conclusions: The use of SGLT2is is associated with a reduced incidence of HFH and AKI in patients with HFpEF and T2DM

Learned Monocular Depth Priors in Visual-Inertial Initialization

Visual-inertial odometry (VIO) is the pose estimation backbone for most AR/VR and autonomous robotic systems today, in both academia and industry. However, these systems are highly sensitive to the initialization of key parameters such as sensor biases, gravity direction, and metric scale. In practical scenarios where high-parallax or variable acceleration assumptions are rarely met (e.g. hovering aerial robot, smartphone AR user not gesticulating with phone), classical visual-inertial initialization formulations often become ill-conditioned and/or fail to meaningfully converge. In this paper we target visual-inertial initialization specifically for these low-excitation scenarios critical to in-the-wild usage. We propose to circumvent the limitations of classical visual-inertial structure-from-motion (SfM) initialization by incorporating a new learning-based measurement as a higher-level input. We leverage learned monocular depth images (mono-depth) to constrain the relative depth of features, and upgrade the mono-depth to metric scale by jointly optimizing for its scale and shift. Our experiments show a significant improvement in problem conditioning compared to a classical formulation for visual-inertial initialization, and demonstrate significant accuracy and robustness improvements relative to the state-of-the-art on public benchmarks, particularly under motion-restricted scenarios. We further extend this improvement to implementation within an existing odometry system to illustrate the impact of our improved initialization method on resulting tracking trajectories

MTG: Mapless Trajectory Generator with Traversability Coverage for Outdoor Navigation

We present a novel learning-based trajectory generation algorithm for outdoor robot navigation. Our goal is to compute collision-free paths that also satisfy the environment-specific traversability constraints. Our approach is designed for global planning using limited onboard robot perception in mapless environments, while ensuring comprehensive coverage of all traversable directions. Our formulation uses a Conditional Variational Autoencoder (CVAE) generative model that is enhanced with traversability constraints and an optimization formulation used for the coverage. We highlight the benefits of our approach over state-of-the-art trajectory generation approaches and demonstrate its performance in challenging and large outdoor environments, including around buildings, across intersections, along trails, and off-road terrain, using a Clearpath Husky and a Boston Dynamics Spot robot. In practice, our approach results in a 6% improvement in coverage of traversable areas and an 89% reduction in trajectory portions residing in non-traversable regions. Our video is here: https: //youtu.be/OT0q4ccGHt