Optimal Hierarchical Layouts for Cache-Oblivious Search Trees

This paper proposes a general framework for generating cache-oblivious layouts for binary search trees. A cache-oblivious layout attempts to minimize cache misses on any hierarchical memory, independent of the number of memory levels and attributes at each level such as cache size, line size, and replacement policy. Recursively partitioning a tree into contiguous subtrees and prescribing an ordering amongst the subtrees, Hierarchical Layouts generalize many commonly used layouts for trees such as in-order, pre-order and breadth-first. They also generalize the various flavors of the van Emde Boas layout, which have previously been used as cache-oblivious layouts. Hierarchical Layouts thus unify all previous attempts at deriving layouts for search trees. The paper then derives a new locality measure (the Weighted Edge Product) that mimics the probability of cache misses at multiple levels, and shows that layouts that reduce this measure perform better. We analyze the various degrees of freedom in the construction of Hierarchical Layouts, and investigate the relative effect of each of these decisions in the construction of cache-oblivious layouts. Optimizing the Weighted Edge Product for complete binary search trees, we introduce the MinWEP layout, and show that it outperforms previously used cache-oblivious layouts by almost 20%.Comment: Extended version with proofs added to the appendi

Analysis of Process Parameters of Fused Deposition Modeling (FDM) Technique

Fused deposition modeling (FDM) is one of the RP technique in which a plastic filament is melted in the extruder of the 3D printer and deposited on the build platform of the 3D printer to form the object layer by layer. Part quality and mechanical properties of the FDM fabricated parts extensively depends on process variable parameters such as layer thickness, raster angle, part orientation, raster width, air gap. Hence, selection and optimization of FDM process parameters is vital. The aim and objective of this article is to study and determine the influence of these parameters on processed part through the research work carried out so far. A number of optimization techniques and designs of experiments for the determination of optimum process parameter have been studied

A Stochastic Program for Black Start Allocation

The fast and secure restoration of the power system after an extended blackout highly depends on the location of Black Start (BS) resources. In contrast to most generators, BS units have the ability to start without being connected to an already energized power grid. Selecting a unit to provide BS services is associated with costly technical upgrades, continuous testing, and compensation for the services, and once a unit is selected as BS it is expected to provide that service for several years. For these reasons, the selection process to allocate new BS units is very important and currently handled by experts in the field. Building on the existing literature for power system restoration and black start allocation, we formulate an optimization problem aimed at allocating BS units optimally in the power grid. While restoration plans are usually examined under the assumption of a total blackout, in reality most blackouts are partial, leaving parts of the grid energized and certain elements damaged. In order to account for these cases during the selection process, we formulate a two-stage stochastic program that optimizes the allocation of BS resources over a number of outage scenarios. We use a scenario decomposition algorithm to solve the resulting optimization problem to near-optimality in a high performance computing environment. We conduct numerical experiments using the proposed model and decomposition method on the IEEE-39

A prospective study of the bacteriological profile and risk factors of infection after internal fixation of close fractures of long bones

Background: Infection in implant related procedures is dreaded due to difficulty in getting rid of it. Disappointment to patients and surgeons, drainage of health care and patients’ resources is significant. Causes and risk factors are many related to host, environment and procedure. The bacteriological profile and antibiotic sensitivity have been changing trend with emerging resistance to many drugs.Methods: A prospective observational study of 941 patients with operative fixation of long bone closed fractures. The details of the procedure, host characteristics were noted. Followed up in ward post operatively and after discharge to identify the cases of surgical site infection. Once identified they were evaluated with X-rays and lab parameters. Wound swabs or pus samples taken to find out the organisms and cultured to find the sensitivity.Results: 116 patients (86 males and 30 females) developed SSI (incidence 12.42%). Plate fixation (18.20% infection rate), operative time >1 and half hours (15.73% rate), fracture femur (16.66% rate), ORIF (14.38% rate), age >60 yrs were some of the risk factors. Co-morbidities like anaemia, diabetes, liver disease, lung disease, immunosuppressive drugs, hypertension, smoking, alcoholics had significant association with SSI. Staphylococcus aureus was the most common organism. Gram positive showed highest sensitivity to linezolid, vancomycin and tetracycline. Gram negative showed highest sensitivity to colistin and tigecycline.Conclusions: Infection rate should be less than 1% and hence risk factors encompassing preoperative, intraoperative and postoperative period are to be controlled. Probably the first study from north east india showing the burden of orthopaedic SSI

Scheduling with Setup Costs and Monotone Penalties

We consider single processor preemptive scheduling with job-dependent setup times. In this model, a job-dependent setup time is incurred when a job is started for the first time, and each time it is restarted after preemption. This model is a common generalization of preemptive scheduling, and actually of non-preemptive scheduling as well. The objective is to minimize the sum of any general non-negative, non-decreasing cost functions of the completion times of the jobs -- this generalizes objectives of minimizing weighted flow time, flow-time squared, tardiness or the number of tardy jobs among many others. Our main result is a randomized polynomial time O(1)-speed O(1)-approximation algorithm for this problem. Without speedup, no polynomial time finite multiplicative approximation is possible unless P=NP. We extend the approach of Bansal et al. (FOCS 2007) of rounding a linear programming relaxation which accounts for costs incurred due to the non-preemptive nature of the schedule. A key new idea used in the rounding is that a point in the intersection polytope of two matroids can be decomposed as a convex combination of incidence vectors of sets that are independent in both matroids. In fact, we use this for the intersection of a partition matroid and a laminar matroid, in which case the decomposition can be found efficiently using network flows. Our approach gives a randomized polynomial time offline O(1)-speed O(1)-approximation algorithm for the broadcast scheduling problem with general cost functions as well

Pycnodysostosis with recurrent long bone fractures

Pycnodysostosis is a rare autosomal recessive sclerosing bone disorder characterized by generalized diffuse osteosclerosis. Patients usually have a large head with separated sutures, open fontanels, aplasia of frontal sinuses, obtuse mandibular gonial angle and acroosteolysis of distal phalanges and multiple long bone fractures. We report this case of a 30-year-old female with repeated multiple long bone fractures and other clinico-radiological pathognomonic features of pycnodysostosis

Optimization of Turning Process Parameters for Their Effect on En 8 Material Work piece Hardness by Using Taguchi Parametric Optimization Method

A common method to manufacture parts to a specific dimension involves the removal of excess material by machining operation with the help of cutting tool. Turning process is the one of the methods to remove material from cylindrical and non-cylindrical parts. In this work the relation between change in hardness caused on the material surface due the turning operation with respect to different machining parameters like spindle speed, feed and depth of cut have been investigated. Taguchi method has been used to plan the experiments and EN 8 metal selected as a work piece and coated carbide tool as a tool material in this work and hardness after turning has been measured on Rockwell scale. The obtained experimental data has been analyzed using signal to noise and. The main effects have been calculated and percentage contribution of various process parameters affecting hardness also determined

Mutation-based Fault Localization of Deep Neural Networks

Deep neural networks (DNNs) are susceptible to bugs, just like other types of software systems. A significant uptick in using DNN, and its applications in wide-ranging areas, including safety-critical systems, warrant extensive research on software engineering tools for improving the reliability of DNN-based systems. One such tool that has gained significant attention in the recent years is DNN fault localization. This paper revisits mutation-based fault localization in the context of DNN models and proposes a novel technique, named deepmufl, applicable to a wide range of DNN models. We have implemented deepmufl and have evaluated its effectiveness using 109 bugs obtained from StackOverflow. Our results show that deepmufl detects 53/109 of the bugs by ranking the buggy layer in top-1 position, outperforming state-of-the-art static and dynamic DNN fault localization systems that are also designed to target the class of bugs supported by deepmufl. Moreover, we observed that we can halve the fault localization time for a pre-trained model using mutation selection, yet losing only 7.55% of the bugs localized in top-1 position.Comment: 38th IEEE/ACM International Conference on Automated Software Engineering (ASE 2023

Conservation Agriculture for Food Security and Climate Resilience in Nepal

Achieving the sustainable development goals of the United Nations requires innovations in agriculture and development of climate-smart and economically feasible approaches for smallholder farmers in developing countries. Historical climate data of Nepal, which include 116 yr since 1901, has shown an increasing trend for average temperature by 0.016 ˚C yr–1 whereas precipitation has shown a decreasing trend by 0.137 mm yr–1. Such weather trends could enhance glacier melt associated flooding, and delayed monsoon rainfalls negatively impacting the agricultural production. The Nepalese government is promoting conservation agriculture (CA) through development of low-cost technologies that can be used effectively in difficult terrains. Such techniques include crop diversification, crop rotation, cover crops, and minimum tillage; all of which can reduce soil degradation. In addition, increasing crop residue retention can result in greater C sequestration and crop yield and reductions in greenhouse gas emissions. However, there is still lack of consensus on the merits of CA in the context of smallholder farming systems in Nepal. This paper reviews existing literature and provides an overview of farming practices in Nepal, highlights near-term challenges associated with climate change and food security, and discusses the role of CA as a climate-smart strategy to minimize soil degradation and improve food security