Optimizing Lead Time in Fall Detection for a Planar Bipedal Robot

For legged robots to operate in complex terrains, they must be robust to the disturbances and uncertainties they encounter. This paper contributes to enhancing robustness through the design of fall detection/prediction algorithms that will provide sufficient lead time for corrective motions to be taken. Falls can be caused by abrupt (fast-acting), incipient (slow-acting), or intermittent (non-continuous) faults. Early fall detection is a challenging task due to the masking effects of controllers (through their disturbance attenuation actions), the inverse relationship between lead time and false positive rates, and the temporal behavior of the faults/underlying factors. In this paper, we propose a fall detection algorithm that is capable of detecting both incipient and abrupt faults while maximizing lead time and meeting desired thresholds on the false positive and negative rates

Fall Prediction for Bipedal Robots: The Standing Phase

This paper presents a novel approach to fall prediction for bipedal robots, specifically targeting the detection of potential falls while standing caused by abrupt, incipient, and intermittent faults. Leveraging a 1D convolutional neural network (CNN), our method aims to maximize lead time for fall prediction while minimizing false positive rates. The proposed algorithm uniquely integrates the detection of various fault types and estimates the lead time for potential falls. Our contributions include the development of an algorithm capable of detecting abrupt, incipient, and intermittent faults in full-sized robots, its implementation using both simulation and hardware data for a humanoid robot, and a method for estimating lead time. Evaluation metrics, including false positive rate, lead time, and response time, demonstrate the efficacy of our approach. Particularly, our model achieves impressive lead times and response times across different fault scenarios with a false positive rate of 0. The findings of this study hold significant implications for enhancing the safety and reliability of bipedal robotic systems.Comment: Submitted to ICRA 2024. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Local Participation in Community Forest Associations: A Case Study of Sururu and Eburu Forests, Kenya

Participation of local communities in the management and utilization of state-owned forest resources has become widely recognized in contrast to centralised forms of forest governance. This paper examined the extent of inclusiveness and household participation in community forest associations (CFAs) adjacent to Sururu and Eburu forests in Kenya. The probit model was used to assess the socio-economic factors determining participation in the CFAs. The study established that gender (P<0.05), group membership (P<0.0001), ownership of tree nursery (P<0.0001), wealth status (P<0.0001), percentage share of wage income (P<0.05), and farm size allocated to trees (P<0.05) significantly influenced CFA participation. However, because of high opportunity participation costs some poor (68%) and rich (65%) households did not participate in CFA activities. Since households participated in CFAs to derive livelihood gains, unclear participation benefits offered little incentive to get involved. Thus participation in CFA activities remained low. Therefore, Kenya Forest Service should review participation guidelines to enable effective CFA input in decision making on forest issues. Keywords: Community; inclusiveness; household; participation; user groups; participatory forest managemen

The Effect of Alternative Investments on the Financial Performance of Pension Funds in Kenya

Abstract Purpose - This research focused on the effects of alternative investments on the financial performance of pension schemes in Kenya. Methodology - This research was descriptive and Secondary data covering a period of 5 years, 2012-2016, and comprised a population of 442 segregated pension schemes and from which a sample of 90 schemes was selected using stratified sampling technique. Only data from 385 schemes was available. The remaining 57 schemes did not qualify for sampling due to incomplete data, data received did not pass sense checks and also responses to queries were not received on time. The data was obtained from the Retirement Benefit Authority and the Actuaries Survey from Alexander Forbes Consulting. Diagnostic tests carried out were tests for normality, multicollinearity and autocorrelation. They were used to test for data fitness before any further analysis. The study also employed the use of a linear multiple regression model to analyze the effect of alternative investments on the financial performance of pension funds in Kenya. The tests of significance used in the study were the t-test, F-statistic, the R-square and Adjusted R-square. Findings - From the findings, most pension schemes had the largest allocation in fixed income and government securities and quoted equity, with the least allocation in private equity and venture capital and real estate investment trusts. The R-square test indicated that 10.6% of the variations in the return on investments were due to the weights of the asset classes indicating that the weights of the asset classes are one among many factors which contribute to the returns of the pension funds. The regression coefficients yielded a positive relationship between this alternative asset classes and return on investments except private equity and venture capital. Implications - Fund managers and Trustees should therefore deliberate about this alternative asset classes which boost the growth of assets under management as well as increase retirees earnings

FARMER-PREFERRED LEARNING METHODS AND UTILISED TEACHING APPROACHES BY EGERTON UNIVERSITY, KENYA

Universities are centres of frontier knowledge and skills, with the capacity to transform communities,when appropriately and adequately transmitted to users. The aim of this paper was to compare farmer-preferred learning methods and those utilised in teaching during Egerton University\u2019s outreach activities, with a view to drawing useful insights for more effective community future engagements. A cross sectional survey was conducted in 2017, using researcher-administered questionnaires, on a sample of 84 farmers purposefully selected from communities where Egerton University implemented extension outreach programmes. Key informant interviews and focus group discussions were also conducted for community leaders and extension officers in the selected Wards, to supplement data collection. Results showed that the decision to participate in the outreach activities implemented by Egerton University was personal, with nearly all the respondents (99%) citing acquisition of new knowledge and skills as the major reason. Demonstrations were the most preferred and utilised methods (90 and 92%, respectively); while the use of group discussions were preferred by 51% of the respondents and utilised in 86% of the outreach activities. Results also showed significant relations for demonstration (\u3c72 = 17.21, P<.001), touring university model farms (\u3c72 = 68.11, P<.001) and use of training videos (\u3c72 = 40.98, P<.001) between farmer-preferred learning methods and utilised teaching methods. This explains the popularity of demonstrations as a teaching and learning method of Egerton University in connecting theoretical and scientific aspects, to practice. Learner centred teaching methods, with the capacity to facilitate collaborative or cooperative learning, should be enhanced.Les universit\ue9s sont des centres de connaissances et de comp\ue9tences, capables de transformer les communaut\ue9s lorsqu\u2019elles sont transmises de mani\ue8re appropri\ue9e et ad\ue9quate aux utilisateurs. L\u2018objectif de cette \ue9tude \ue9tait de comparer les m\ue9thodes d\u2019apprentissage privil\ue9gi\ue9es par les agriculteurs et celles utilis\ue9es dans l\u2019enseignement pendant les activit\ue9s de sensibilisation de l\u2019Universit\ue9 d\u2019Egerton, en vue de tirer des enseignements utiles pour des engagements futurs plus efficaces dans la communaut\ue9. Une enqu\ueate transversale a \ue9t\ue9 men\ue9e en 2017, \ue0 l\u2019aide de questionnaires administr\ue9s par des chercheurs, sur un \ue9chantillon de 84 agriculteurs d\ue9lib\ue9r\ue9ment s\ue9lectionn\ue9s dans les communaut\ue9s o\uf9 l\u2019Universit\ue9 d\u2019Egerton a mis en oeuvre des programmes de vulgarisation. Des entretiens avec des informateurs principaux et des discussions de groupe ont \ue9galement \ue9t\ue9 men\ue9s \ue0 l\u2019intention des dirigeants communautaires et des agents de vulgarisation des quartiers s\ue9lectionn\ue9s, afin de compl\ue9ter la collecte de donn\ue9es. Les r\ue9sultats ont montr\ue9 que la d\ue9cision de participer aux activit\ue9s de sensibilisation mises en oeuvre par l\u2019Universit\ue9 d\u2019Egerton \ue9tait personnelle, presque tous les r\ue9pondants (99%) citant l\u2019acquisition de nouvelles connaissances et comp\ue9tences comme principale raison. Les d\ue9monstrations \ue9taient les m\ue9thodes les plus pr\ue9f\ue9r\ue9es et utilis\ue9es (90 et 92%, respectivement); tandis que le recours aux discussions de groupe a \ue9t\ue9 pr\ue9f\ue9r\ue9 par 51% des r\ue9pondants et utilis\ue9 dans 86% des activit\ue9s de sensibilisation. Les r\ue9sultats ont \ue9galement montr\ue9 des relations significatives pour la d\ue9monstration (c2 = 17,21, P <0,001), les fermes mod\ue8les universitaires en tourn\ue9e (c2 = 68,11, P <0,001) et l\u2019utilisation de vid\ue9os de formation (c2 = 40,98, P <0,001) entre les m\ue9thodes d\u2019apprentissage privil\ue9gi\ue9es par les agriculteurs et les m\ue9thodes d\u2019enseignement utilis\ue9es. Cela explique la popularit\ue9 des d\ue9monstrations en tant que m\ue9thode d\u2019enseignement et d\u2019apprentissage de l\u2019Universit\ue9 d\u2019Egerton pour relier les aspects th\ue9oriques et scientifiques \ue0 la pratique. Les m\ue9thodes d\u2019enseignement centr\ue9es sur l\u2019apprenant, avec la capacit\ue9 de faciliter l\u2019apprentissage collaboratif ou coop\ue9ratif, devraient \ueatre am\ue9lior\ue9es

Feedback Control of an Exoskeleton for Paraplegics: Toward Robustly Stable Hands-free Dynamic Walking

This manuscript presents control of a high-DOF fully actuated lower-limb exoskeleton for paraplegic individuals. The key novelty is the ability for the user to walk without the use of crutches or other external means of stabilization. We harness the power of modern optimization techniques and supervised machine learning to develop a smooth feedback control policy that provides robust velocity regulation and perturbation rejection. Preliminary evaluation of the stability and robustness of the proposed approach is demonstrated through the Gazebo simulation environment. In addition, preliminary experimental results with (complete) paraplegic individuals are included for the previous version of the controller.Comment: Submitted to IEEE Control System Magazine. This version addresses reviewers' concerns about the robustness of the algorithm and the motivation for using such exoskeleton

Impact of Drought on the Spatial Pattern of Transmission of Sehistosoma haematobium in Coastal Kenya

We analyzed temporal changes in spatial patterns of active Schistosoma haematobium infection in different age groups and associated them with ponds infested with Bulinus snails. A major drought between 2001 and 2009 resulted in drying of ponds that were known sources of infection, and we detected very few or no snails in ponds that were infested in the past. The household-level spatial pattern of infection for children of various age groups in 2009 was contrasted with historical data from 2000. The significant local clustering of high- and low-infection levels among school-aged children that occurred in 2000 was absent in 2009. We attribute the disappearance of significant clustering around historical transmission hot spots to a decade-long drought in our study area. The implications of extreme weather and climate conditions on risk and transmission of S. haematobium and their relevance to control strategies are discussed. Copyright © 2011 by The American Society of Tropical Medicine and Hygiene

Assessing the Influence of Accounting Outsourcing on Financial Performance of Small and Medium Enterprises in Thika Subcounty, Kenya

Globally, small and medium sized enterprises (SMEs) have been found to significantly contribute to the gross domestic product (GDP) in developing nations as well as to employment. In Kenya, the SMEs have the potential of raising many citizens to the mainstream economy. Although the SMEs contribute toward economic development as well as to employment in Kenya, their financial performance is still wanting, which is evidenced by the high collapse rate of SMEs. This research project assessed the influence of accounting outsourcing (AO) on financial performance of SMEs. The study used a descriptive design, and the number of SMEs that formed the population of study was 8605 in Thika subcounty. The sample size was therefore 368 SMEs, which were sampled using stratified and simple random sampling. The study adopted a questionnaire to collect data, and the Cronbach alpha coefficient was employed for testing of reliability. Descriptive and inferential statistics were used in analyzing the collected data with the assistance of statistical packages of social science (SPSS) version 23. The relationship between influences of AO and its effect on financial performance of SMEs were established through a simple regression model. The results of this study showed a significant positive association between the explanatory variables and the financial performance of SMEs. The study concludes that influences of AO have significant influence on SMEs financial performance. The study recommended that managers and owners of SMEs should seek service from qualified accountants as this may increase the quality of financial records and may improve their SMEs financial performance

Impact of soil acidity and liming on soybean (Glycine max) nodulation and nitrogen fixation in Kenyan soils

Open Access Article; Published online: 22 Oct 2020There is a wide application of rhizobia inoculants to legume crops in Africa, irrespective of the soil acidity, though the latter limits the effectiveness of inoculants. Two trials were conducted in a controlled environment to determine suitable soil pH and impact of liming on soybean nodulation and nitrogen fixation to inform proper application of the rhizobia-inoculant technology on acid soils. In the first trial; soil, variety and inoculation had significant influence (p < 0.05) on weighed nodule effectiveness (WNE) and N fixation. Strongly acidic soils recorded low WNE and N fixation. In the second trial, WNE and N fixation significantly increased with co-application of lime and inoculation (p < 0.05). The results showed that soybean inoculation is effective in increasing nodulation and N fixation in moderate acidic soils, contrarily to strongly acidic soils. Interestingly, co-application of lime and inoculation has potential of increasing nodulation and N fixation in strongly acidic soils. The WNE is recommended as a robust formula to report nodule effectiveness, compared to the current percentage method