Placement Policy Research Articles

Distributed storage placement policy for minimizing frequency deviations: A combinatorial optimization approach based on enhanced cross-entropy method

The paper addresses the well-known challenge of allocating storage units within the grid to minimize frequency deviations during transients. The current research is mainly motivated by a sequence of recent works that focus on location of inertia and storage units, considering the limitations of the transmission network, and its spatial effects. One possible drawback of these algorithms is their numerical complexity. To address this gap, this paper studies the storage distribution problem using the general framework of combinatorial optimization, and proposes algorithms to solve it. Among them, one solution is based on exhaustive search, while the others strongly rely on the cross-entropy method. We show that the latter is especially suitable for this application, since it can efficiently solve high-dimensional combinatorial optimization problems. Since the CE method may converge to sub-optimal solutions if the number of storage units increases significantly, this paper also proposes an enhanced CE method which solves the distribution problem considering the assumption that the locations of potential transients are known. In this regard, a key result is that the enhanced CE method convergences faster to the optimal solution and significantly reduces the number of computations.

Socioeconomically equitable public defibrillator placement using mathematical optimization

BackgroundMathematical optimization can be used to place automated external defibrillators (AEDs) in locations that maximize coverage of out-of-hospital cardiac arrests (OHCAs). We sought to determine whether optimization can improve alignment between AED locations and OHCA counts across levels of socioeconomic deprivation. MethodsAll suspected OHCAs and registered AEDs in Scotland between Jan. 2011 and Sept. 2017 were included and mapped to a corresponding socioeconomic deprivation level using the Scottish Index of Multiple Deprivation (SIMD). We used mathematical optimization to determine optimal locations for placing 10%, 25%, 50%, and 100% additional AEDs, as well as locations for relocating existing AEDs. For each AED placement policy, we examined the impact on AED distribution and OHCA “coverage” (suspected OHCA occurring within 100 m of AED) with respect to SIMD quintiles. ResultsWe identified 49,432 suspected OHCAs and 1532 AEDs. The distribution of existing AED locations across SIMD quintiles significantly differed from the distribution of suspected OHCAs (P < 0.001). Optimization-guided AED placement increased coverage of suspected OHCAs compared to existing AED locations (all P < 0.001). Optimization resulted in more AED placements and increased OHCA coverage in areas of greater socioeconomic deprivation, such that resulting distributions across SIMD quintiles matched the shape of the OHCA count distribution. Optimally relocating existing AEDs achieved similar OHCA coverage levels to that of doubling the number of total AEDs. ConclusionsMathematical optimization results in AED locations and suspected OHCA coverage that more closely resembles the suspected OHCA distribution and results in more equitable coverage across levels of socioeconomic deprivation.

What Factors Determine the Success or Failure of ‘Cross-Border’ Career Development of Chinese Retired Olympic Champions? A Qualitative Comparative Analysis

In recent years, advanced professional athletes’ career development after retirement has become an issue in which society is increasingly interested. However, there are very few theoretical studies exploring the relevant factors influencing the nature of athletes’ transition. Based on 80 Chinese Olympic champions who have retired and pursued cross-border careers (i.e. careers outside the sphere of their own competitive sport) for more than five years, this study uses qualitative comparative analysis (QCA) to analyze five factors, including gender, psychological capital, human capital, individual social influence of winning sport event and ‘cross-border distance’. This study shows that: first, the higher the level of psychological capital, human capital, sport event influence and the smaller cross-border distance, the greater the possibility that retired Olympic champions will succeed in cross-border career development. Second, when levels of human capital and sport event influence are not sufficiently high, athletes’ psychological capital plays a decisive role in successful cross-border career development. Third, athletes’ level of psychological capital and the level of influence of their sport event are ‘bottlenecks’ which restrict cross-border career success. These results have theoretical and practical value for optimizing placement policy for retired athletes, and guiding the career planning of both competing and retired elite athletes. Supplemental data for this article is available online at https://doi.org/10.1080/09523367.2021.1953993 .

Admission to the Regular Ward is Safe Following Uncomplicated Craniosynostosis Surgery: A Retrospective Study

Background: At our craniofacial center patients are routinely admitted to a regular ward, or floor, rather an intensive care unit (ICU) after uncomplicated craniosynostosis surgery. In this study, we review the safety of our postoperative placement policy, examining the rate of transfer from floor to ICU. Methods: The charts of patients who underwent craniosynostosis surgery from 2009 through 2017 at a single children’s hospital were reviewed. Postoperative hospital courses were characterized as preoperatively-planned ICU admission, perioperatively-planned ICU admission, or primary floor admission. The primary outcome was transfer from floor to ICU. Secondary outcomes included duration of hospitalization. Results: Chart review yielded 420 patients. Three hundred sixty-eight (88%) were admitted directly to the floor and 52 (12.0%) directly to an ICU. Of patients admitted to the floor, 2 (0.5%) were transferred to an ICU. Twenty-four patients with syndromic and 20 patients with multisutural craniosynostosis were admitted to the floor. Only 1 patient from each group (the same patient; 4.2% and 5.0%, respectively), was transferred to an ICU. Thirty-two ICU admissions were preoperatively planned and 20 were perioperatively planned. Reasons for preoperatively planned ICU admission included significant comorbidities and type of surgery. Reasons for perioperatively planned ICU admissions included significant intraoperative adverse events, excessive blood loss, and failure of clearance from the post-anesthesia care unit (PACU). Patients admitted to the ICU had a statistically significant longer mean length of hospitalization (4.8 days vs 2.7 days) than did patients admitted to the floor. Conclusions: Most postoperative craniosynostosis surgery patients—including patients with syndromic and/or multisutural synostosis—are managed safely on the floor at our center. Some patients still need postoperative ICU admission, but are easily identified preoperatively, intraoperatively, or in the PACU. Our findings should be applicable to other large craniofacial centers.

'We're both here to do a job and that's all that matters': Cisgender correctional officer recruit reflections within an unsettled correctional prison culture.

Reflecting on new trans prisoner placement policies within Canadian federal prisons, in light of recent changes instigated under the Canadian Liberal Trudeau government, we provide knowledge from cisgender correctional officer (CO) recruits regarding these policy changes and underscore their views of working with officers who identify as transgender. Canada's new policies recognize the presence of trans prisoners and create new protocols accordingly, simultaneously challenging some of the foundational tenets of the carceral system. While overwhelming support exists from cisgender recruits for their trans colleagues, support among a relative minority of COs is contingent upon notions like safety and security grounded in a dominantly cisgender prison culture; a culture we situate within the wider context of an unsettled correctional prison culture.

Dependability in fog computing: Challenges and solutions

The tremendous increase in IoT devices and the amount of data they produced is very expensive to be processed at cloud data centers. Therefore, fog computing was introduced in 2012 by Cisco as a decentralized computing environment that is considered to be more efficient in handling such a plethora in the number of requests. Fog computing is a distributed computing paradigm that focuses on bringing data processing at the network peripheral to reduce response time and increase the quality of service. Dependability challenges of such distributed and heterogeneous computing environments are considered in this paper. Because fog computing is a new computing paradigm, several studies have been presented to tackle its challenges and issues. However, dependability in specific did not receive much attention. In the paper, we explore several solutions to increase dependability in fog computing such as fault tolerance techniques, placement policies, middleware, and data management mechanisms aiming to help system designers choose the most appropriate solution.

POS-668 BARRIERS AND OPPORTUNITIES TO INCREASE PD INCIDENCE AND PREVALENCE: LESSONS FROM A EUROPEAN SURVEY

Peritoneal Dialysis (PD) remains underutilized despite the fact that outcomes have been demonstrated to be equal to hemodialysis (HD). Several barriers for PD growth have been identified, such as late referral, economic incentives, lack of training facilities or PD catheter placement issues. However, the potential interaction between all these mediators has not been explored, and they might be intertwined. The EuroPD™Future Leadership group* therefore performed a pan-European survey to identify potential barriers to growth of PD programs by exploring PD and home HD related practices and organizational aspects at centre level. In this abstract, we focus on the association between PD catheter placement policy, urgent (unplanned) start and education policy*EuroPD™FutureLeadership includes also Bechade C France; de Laforcade L France; Eden G Germany; Martin H,Germany; Steubl D,Germany; Wojtaszek E,Poland; Altabas K,Slovenia; Pajek J,Slovenia; Ros S,Spain; Vega A,Spain; Burkhalter F,Suisse; Allen J,UK; Corbett Richard,UK; Lambie M,UK An electronic survey was send to the contacts of EuroPD™ and to the members of regional societies of the members of the EuroPD Future Leadership initiative. In the survey, a virtual case vignette of a 48 year old woman not previously known to your unit who arrives at the emergency department with established end stage kidney disease was presented (late referral/unplanned start). We used chi-square tests and (ordinal) logistic regression to assess associations between modality choices for this case vignette and PD related practices, and also with % incident and prevalent patients on PD. We received 628 responses (317 academic, 243 non academic non private, 68 private; 67 with less than 50, 125 with 50-100, 243 with 100-220 and 193 with more than 200 patients). For the unplanned start case vignette, 32.6, 32.2 and 35.2% indicated they would start urgent PD, urgent HD or urgent HD with the plan to educate patient on PD at a later time respectively. Only 2 out of 3 respondents indicated that it was (very) likely this patient would receive education on PD in the unplanned setting. Urgent placement of a PD catheter (<48hours) was only possible in 32.4% of centres. In univariate analysis, choice for urgent start PD was associated with presence of a dedicated PD team, presence of a structured PD education program, the likelihood of an unplanned patient to receive education on PD, and having good relations with the PD access placement team, but not with centre size, %PD incidence or prevalence, financial issues, or the possibility to have a PD catheter placed within 48 hours. In a general linear mixed model, inclination to start PD in the case-vignette on unplanned start was only associated with presence of a dedicated PD team and the likelihood that the patient will receive education on homebased therapies. Percentage PD incidence and prevalence were only associated with presence of good education for both planned as for unplanned patients, and with a good relationship with the PD access team. Absence of a dedicated PD team seems to be the common denominator of already identified barriers to PD growth such as unplanned start and PD access placement issues. If we intend to grow PD programs, we will need to establish enthusiastic PD teams with good collaborations with dedicated PD catheter placement teams.

Mobile-edge computing-based delay minimization controller placement in SDN-IoV

Internet of Vehicles (IoV) plays a fundamental role in the rapid development of intelligent transportation systems and smart cities by the way of facilitating data access. However, traditional routing protocols-based data forwarding cannot guarantee reliable services for low-latency applications in IoV. Motivated by the promising technologies of Software-defined networking (SDN) and Mobile-edge computing, this paper aims at enhancing the performance of IoV with the assistance of these two. Specifically, we first propose a three-layer hierarchy control framework for SDN-IoV based on the MEC. Under this framework, we investigate a controller placement problem with the objective of minimizing the delay between the switch and the controller. Then, we propose a Louvain algorithm-based controller placement policy to obtain the optimal location of controllers subject to load balance index and buffer size. Further, we put forward a controller replacement policy to adapt to the dynamic topology of IoV. Numerical results show that the proposed methods achieve a better performance than two baselines, in terms of the delay and load balance index.

Demystifying the Placement Policies of the NVIDIA GPU Thread Block Scheduler for Concurrent Kernels

In this work, we empirically derive the scheduler's behavior under concurrent workloads for NVIDIA's Pascal, Volta, and Turing microarchitectures. In contrast to past studies that suggest the scheduler uses a round-robin policy to assign thread blocks to streaming multiprocessors (SMs), we instead find that the scheduler chooses the next SM based on the SM's local resource availability. We show how this scheduling policy can lead to significant, and seemingly counter-intuitive, performance degradation; for example, a decrease of one thread per block resulted in a 3.58X increase in execution time for one kernel in our experiments. We hope that our work will be useful for improving the accuracy of GPU simulators and aid in the development of novel scheduling algorithms.

Immigrant Political Representation and Local Ethnic Concentration: Evidence from a Swedish Refugee Placement Program

AbstractThis study leverages population registry data from Sweden to examine whether immigrants who live in areas with a high concentration of ethnic minorities are more or less likely to be nominated for political office. It exploits a refugee placement program in place in Sweden during the late 1980s and early 1990s that restricted refugees' opportunities to freely choose their place of residence. The article presents evidence that immigrants who live in areas with a high ethnic density are less likely to be nominated for political office. The findings have important implications for local integration policies as well as refugee placement policies, as many countries consider local context when resettling refugees.

An approach towards development of new linear regression prediction model for reduced energy consumption and SLA violation in the domain of green cloud computing

With the increase of mega-cities, the demand for Smart Cities is overgrowing. The mega-cities can be smarter through the Cloud of Things (CoT). Efficient energy consumption in Smart Cities has a massive impact on the environment. But, computational power is increasing rapidly in the cloud computing environment. Enormous energy consumption (EC) and Service Level Agreement violation (SLAV) becomes a key concern. The Virtual Machine (VM) consolidation approach can significantly reduce EC, SLA violation (SLAV), and increase resource utilization. However, dynamic VM consolidation may produce performance degradation of Physical Machines (PMs) and SLAV. Therefore, it becomes essential to find a trade-off between EC and SLAV. Herein, a novel New Linear Regression(NLR) prediction model, host overload/underload, and VM placement policy have been proposed to reduce EC and SLAV. The NLR model’s primary intention is to take that the model goes through a straight line and a mean point. Future CPU utilization is predicted based on the proposed NLR model. Evaluation of proposed algorithms has been accomplished by extending CloudSim Simulator. The experiment shows that proposed algorithms reduced EC and SLAV in cloud data centers and can be used to construct a smart and sustainable environment for Smart Cities.

A two-phase virtual machine placement policy for data-intensive applications in cloud

Cloud computing and big data are two technologies whose combination can yield many benefits and challenges. One of the most significant challenges is the traffic produced by data-intensive jobs within a data center. A possible way to manage the produced traffic is optimizing the placement of virtual machines (VM) on hosts. However, placing VMs compactly to reduce the communication cost can negatively impact on other aspects such as host utilization and load balancing. In this paper, we aim to make a balance between optimizing the host utilization and the communication cost while considering load balancing. We investigate the VM placement problem by modeling it as the minimum weight K-vertex-connected induced subgraph. We prove the NP-Hardness of the problem and propose a novel two-phase strategy for placing VMs on hosts. At first phase, in order to balance traffic and workload among racks, we rank all racks using a fuzzy inference system and select the best ones based on a linear programming model. At second phase, we introduce a novel greedy algorithm to assign each VM to a host regarding a proposed communication cost metric. We evaluate our approach using CloudSim simulator whose results show our two-phase strategy is able to make a balance between host utilization and network traffic. It keeps more than 80 percent of the traffic rack local while reduces the average network link saturation to almost 40 percent with a low variance. Besides, the number of used hosts increase linearly by increasing the number of VMs which leads to a higher host utilization.

Historical data based approach for straggler avoidance in a heterogeneous Hadoop cluster

Cloud computing has emerged as a new way of sharing resources. MapReduce has become the de facto standard for cloud computing, which helps for data-intensive computation in parallel. Hadoop is an open-source framework that allows the implementation of MapReduce on the cluster of commodity hardware. An environment with different generations of commodity hardware (node) raises heterogeneity in the Hadoop environment. Today heterogeneity has become common in industries as well as in research centers. Hadoop’s current implementation assumes that nodes in the environment are homogeneous and distribute the workload evenly among these nodes. This homogeneity assumption creates a load imbalance among the nodes in the heterogeneous Hadoop environment, which furthers leads to stragglers. Stragglers are the nodes that are available in the environment, but their performance is abysmal. The paper proposed a Historical data based data placement (HDBDP) policy to balance the workload among heterogeneous nodes based on their computing capabilities to improve the Map tasks data locality and to reduce the job turnaround time in the heterogeneous Hadoop environment. The approach introduces an agent to measures the node computing capabilities using the job history information. It also helps NameNode to decide the block counts for each node in the environment. The proposed policy’s performance is evaluated on Hadoop’s most popular benchmark, i.e., HiBench benchmark suite. Finally, compared to the Hadoop’s default data placement policy and different policies, the proposed HDBDP policy minimizes the job turnaround time for several workloads by an average of 14–26%. Also, it improves the Map tasks data locality by nearly 27% in a heterogeneous Hadoop environment.

A MARL Approach for Optimizing Positions of VANET Aerial Base-Stations on a Sparse Highway

A Vehicular Ad-Hoc Network (VANET) helps vehicles send and receive environmental and traffic information, making it a crucial component towards fully autonomous roads. For VANETs to serve their purpose, there has to be sufficient coverage, even in less populated areas. Moreover, a lot of the safety information is time-sensitive; excessive delay in data transfer can increase the risk of fatal accidents. Unmanned Aerial Vehicles (UAVs) can be used as mobile base-stations to fill in gaps of coverage. The placement of these UAVs is crucial towards how well the system performs. We are particularly interested in the placement of mobile base-stations for a rural highway with sparse traffic, as it represents the worst-case scenario for vehicular communication. Instead of heuristic or linear programming methods for optimal placement, we use multi-agent reinforcement learning (MARL). The main benefit of MARL is that it allows the agents to learn model-free through experience. We propose a variation of the traditional Deep Independent Q-Learning. The modifications include an observation function augmented with information directly shared between neighbouring agents as well a shared policy scheme. We also implement a custom sparse highway simulator that is used for training and testing our algorithm. Our testing shows that the proposed MARL algorithm is able to learn the placement policies that produce the maximum rewards for different scenarios while adapting to the dynamic road densities along the service area. Our experiments show that our model is scalable, allowing the number of agents to increase without any modifications to the code. Finally, we show that our model can be generalized as the algorithm can be directly used and performs equally as well on an industry standard simulator. Future experiments can be performed to improve the realism and complexity of the highway models and adapting the algorithm to real-world scenarios.

Instituting of Kindergarten Gifted Education Program in the Philippines

This study assessed the institution of kindergarten gifted education program in the Philippines. It specifically focused on implementation of the following areas: (1) establishment of gifted education program, (2) selection policies, and (3) placement prerequisites for kinder pupils as gifted and talented. Descriptive survey method was applied with data collection procedures through interviews and documentation. Instruments comprised checklists, and questionnaires. The participants were principals, teachers and parents of gifted and talented kindergarten pupils of public schools with recognized gifted education program. Statistical tools include frequency count, percentage, weighted mean, and rating scale of four-point ranking system with descriptive interpretations. Findings show that principals, teachers and parents equally noted a “very evident” perception level on program establishment. Participants respectively viewed the execution of teacher hiring and selection policies as “very evident”. As a separate group, however, they only perceived the compliance to selection and placement policies on an “evident” degree. Findings imply a positive affirmation of participants for program initialization. However, each participant-group still perceived the necessity for advanced and apposite educational practices to improve the founding practices of Kindergarten gifted education program. It is recommended that parallel investigation be done to appraise other gifted education services.

Application and Storage-Aware Data Placement and Job Scheduling for Hadoop Clusters

As one of the most popular frameworks for large-scale analytics processing, Hadoop is facing two challenges: both applications and storage devices become heterogeneous. However, existing data placement and job scheduling schemes pay little attention to such heterogeneity of either application I/O requirements or I/O device capability, thus can greatly degrade system efficiencies. In this paper, we propose ASPS, an Application and Storage-aware data Placement and job Scheduling approach for Hadoop clusters. The idea is to place application data and schedule application tasks considering both application I/O requirements and storage device characteristics. Specifically, ASPS first introduces novel metrics to quantify I/O requirements of applications. Then, based on the quantification, ASPS places data of different applications to the preferred storage devices. Finally, ASPS tries to launch jobs with high I/O requirements on the nodes with the same type of faster devices to improve system efficiency. We have implemented ASPS in Hadoop framework. Experimental results show that ASPS can reduce the completion time of a single application by up to 36% and the average completion time of six concurrent applications by 27%, compared to existing data placement policies and job scheduling approaches.

Text Summarization as a Multi-objective Optimization Task: Applying Harmony Search to Extractive Multi-Document Summarization

Abstract Today, automated extractive text summarization is one of the most common techniques for organizing information. In extractive summarization, the most appropriate sentences are selected from the text and build a representative summary. Therefore, probing for the best sentences is a fundamental task. This paper has coped with extractive summarization as a multi-objective optimization problem and proposed a language-independent, semantic-aware approach that applies the harmony search algorithm to generate appropriate multi-document summaries. It learns the objective function from an extra set of reference summaries and then generates the best summaries according to the trained function. The system also performs some supplementary activities for better achievements. It expands the sentences by using an inventive approach that aims at tuning conceptual densities in the sentences towards important topics. Furthermore, we introduced an innovative clustering method for identifying important topics and reducing redundancies. A sentence placement policy based on the Hamiltonian shortest path was introduced for producing readable summaries. The experiments were conducted on DUC2002, DUC2006 and DUC2007 datasets. Experimental results showed that the proposed framework could assist the summarization process and yield better performance. Also, it was able to generally outperform other cited summarizer systems.

To, Through, and beyond Higher Education: A Literature Review of Multilingual Immigrant Students’ Community College Transitions

ABSTRACT Amidst the growing diverse student population, community colleges are enrolling an increasing number of adult immigrant-background students. However, recent research trends tend to focus on students who enter community colleges from the U.S. K-12 system (Generation 1.5 learners), leaving a significant gap in the research and a lack of cohesion in terminology regarding adult immigrant students who enter into postsecondary education from another path. The objective of this systematic review of the literature is to synthesize research on the transition of adult-arrival immigrants (referred to as Generation 1 learners) from adult ESL to credit-level courses at the community college. Researchers conducted a database search and identified 91 research studies, technical reports, and doctoral dissertations relevant to the transition of Generation 1 Learners through ES(O)L, developmental education, and credit-level courses. Following a thematic analysis of the relevant literature, researchers identified the components of popular models for facilitating Generation 1 transitions, as well as the various placement and assessment policies, and professional development opportunities provided by institutions. Additionally, trends for methodologies and theoretical frameworks used in recent research suggest future directions for study that focus on large-scale or longitudinal research, as well as inter-institutional perspectives. Further analysis of these themes will provide guidance for practitioners and administrators who seek to provide assistance to Generation 1 Learners as they transition through the community college.

Traffic-Aware Erasure-Coded Archival Schemes for In-Memory Stores

Redundancy schemes are introduced to in-memory stores to provide fault tolerance. To achieve good trade-off between access performance and memory efficiency, it is appropriate to adopt replication and erasure coding to keep popular and unpopular data, respectively. Within such a hybrid-redundancy in-memory store, an issue of redundancy transition from replication to erasure coding (a.k.a., erasure-coded archival) should be addressed for unpopular in-memory datasets, since caching workloads exhibit long-tail distributions and most in-memory data are unpopular. If data replicas are distributed across nodes in randomly-selected racks, then subsequent data-block-replica retrieval for erasure-coded archival will create cross-rack traffic, and final parity-block relocation will cause extra cross-rack communications. In this article, we propose an encoding-oriented replica placement policy - ERP - by incorporating an interleaved declustering mechanism. We design two traffic-aware erasure-coded archival schemes -TEA-TL and TEA-SL - for ERP-powered in-memory stores by taking into account temporal locality and spatial locality, respectively. With ERP in place, both TEA-TL and TEA-SL schemes embrace the following three salient features: (i) they alleviate cross-rack traffic raised by retrieving required data-block replicas; (ii) they improve rack-level load balancing by distributing replicas via load-aware primary-rack-selection approach; and (iii) they mitigate block-relocation operations launched to sustain rack-level and node-level fault-tolerance. We conduct quantitative performance evaluations using the YCSB benchmark. The empirical results show that both TEA-TL and TEA-SL schemes not only bring forth lower cross-rack traffic than the four candidate encoding schemes, but also exhibit superb archival-throughput and rack-level-balancing performance. In particular, within a group of comparative tests using the baseline configurations, TEA-TL and TEA-SL accelerate archival throughput by at least 36.3 and 70.8 percent, respectively; both TEA-TL and TEA-SL schemes improve rack-level load-balancing by a factor of more than 1.45x relative to the four candidate encoding schemes.

Major lower extremity amputations in a developing country: 10-Year experience at a tertiary medical center

Lower extremity amputation (LEA) is a major surgical procedure with a high risk of significant morbidity and mortality. The objective of this study was to describe mortality and functionality outcomes following this procedure in a developing country. This is a retrospective study of all patients undergoing LEA for non-traumatic etiology between 2007 and 2017. Medical records were used to retrieve demographics, comorbidities, and perioperative complications of identified patients. Patients were contacted to follow-up on their medical, postoperative care, and ambulatory status. Mortality and postoperative functionality rates were analyzed. The study included 78 patients. Median follow-up duration was 24 months. Hypertension (81%) and diabetes (79%) were the most common comorbidities. Mortality rates at 30 days, 1, and 5 years were 10.3, 29.2, and 65.5%, respectively. Mortality was significantly associated with age > 70 at amputation (p = 0.042), hypertension (p = 0.003), chronic kidney disease (p = 0.031), and perioperative sepsis (p = 0.01). Only 1.6% of patients were discharged into a specialized care center, and only 27% of patients were ambulatory postoperatively, although 90.5% were fitted with a prosthesis. Survival following major amputation in a developing country is currently comparable to more developed regions of the world. Major discrepancy seems to exist in ambulatory status following the procedure. Discharge placement policies should be properly set, and rehabilitation centers funding should be increased. Awareness may also be warranted to educate patients and families about the value and positive impact of rehabilitation centers.