31 research outputs found
A Transcendental Phenomenological Study of Happiness as Experienced by the Sadhus
No full textHuman happiness has been a widely debated topic for the past 2,500 years within the various philosophical and religious traditions. However, happiness itself remained an elusive concept within the context of recent empirical happiness research. This qualitative phenomenological study aimed to understand the phenomenon of happiness from the perspective of sadhus, holy ascetics of India, who renounce all their material possessions and worldly desires for the discovery of true happiness or moksha (Sanskrit: freedom from all sufferings). Using Husserl’s transcendental phenomenological method, the study selected 20 sadhus for in-depth interviews. The sadhus reported their happiness as ananda (Sanskrit: happiness), far higher than normal levels of happiness that ordinary people experience. Inductive thematic data analysis found that happiness is every human being’s most fundamental unchanging true nature, and one must discover it within, not in the external world. According to the sadhus, happiness has an animate nature, meaning it is a living construct with no shape, form, size, or other qualities, but happiness is conscious or “the knower.” The sadhus also described human happiness as infinite, all-pervasive, beyond, and distinct from the human mind. They described happiness as none other than Divine, their source of continuous care and protection. The study found sadhus are very happy people and have no sense of fear. They attributed their happiness to five critical factors: (a) Guru, a spiritual teacher, (b) self-knowledge, (c) serving others, (d) practicing yoga and meditation, and (e) renunciation and living a simple life. From the perspective of sadhus, this study found everyone has access to immense happiness which can be discovered within through virtuous actions and secular practices like yoga and meditations or mindfulness-based meditations
Application of MIMO system for telemetry, tracking command and monitoring subsystem to control the satellite
No full text
Railroad decision support tools for track maintenance
No full textThe North American rail system requires billions of dollars annually to be maintained in proper working order. Therefore, it is critical that maintenance is performed on the right components, at the right time, and in the right location. Application of decision support tools that use objective analysis methods can result in more efficient and effective maintenance plans. This requires quantifying both direct costs associated with the performance of maintenance and the indirect costs of train delay, disruption risk, and equipment routing. To thoroughly assess these costs, an integrated approach is needed that incorporates degradation modeling, project selection, and maintenance scheduling for the entire track structure. Planning track maintenance in this way allows for the effects of changing maintenance timing to be seen explicitly through the disruption risk while considering equipment and other constraints. Managers can then combine the output from the decision support tools with their practical experience to account for location- or situation-specific characteristics that are not easily quantifiable.
This dissertation presents new methods for determining the indirect costs associated with both planned and unplanned disruptions. Train delay cost models were developed that consider train operating characteristics such as terminal dwell and trainset configurations. These costs were combined with a train delay calculator adapted from the highway domain to determine the operational impact to trains during both disrupted and recovery operations. Degradation models were also developed or modified to estimate unplanned disruption risk for slow orders and acute disruptions such as rail breaks and derailments. Combined, these new methods allow for the costs of unplanned disruptions to be estimated and accounted for when planning track maintenance.
A maintenance plan costing model was developed that incorporates the direct and indirect costs associated with a proposed maintenance plan. The model determines the complete cost of the plan based on capital maintenance timing, level of maintenance aggregation, and detour use. Incorporation of maintenance aggregation allows for the efficiencies of performing multiple maintenance activities simultaneously on long work windows to be explicitly considered. Alternative maintenance plans that adjust a base schedule to use maintenance aggregation can be compared to determine if the reduced direct and delay costs outweigh the additional indirect costs. Since the best way to modify a plan to reduce costs is not always obvious and can be tedious to determine manually, an optimization model was developed and solved using simulated annealing. While optimality is not guaranteed when using simulated annealing, it was shown to provide lower cost maintenance plans.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-12-01The student, Alexander Lovett, accepted the attached license on 2017-10-11 at 05:58.The student, Alexander Lovett, submitted this Dissertation for approval on 2017-10-11 at 06:17.This Dissertation was approved for publication on 2017-10-13 at 08:58.DSpace SAF Submission Ingestion Package generated from Vireo submission #11257 on 2018-03-13 at 09:54:18Made available in DSpace on 2018-03-13T15:20:50Z (GMT). No. of bitstreams: 4
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Previous issue date: 2017-10-13Embargo set by: Seth Robbins for item 105124
Lift date: 2020-03-13T15:21:19Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 105124
Lift date: 2020-03-13T15:25:40Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 105124
Lift date: 2020-03-13T15:28:52Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Only Restriction Lifted for Item 105124 on 2020-03-14T09:15:12Z
