Complementary Knowledge Research Articles

Evidential combination of augmented multi-source of information based on domain adaptation

In the applications of domain adaptation (DA), there may exist multiple source domains, and each source domain usually provides some auxiliary information for object classification. The combination of such complementary knowledge from different source domains is helpful for improving the accuracy. We propose an evidential combination of augmented multi-source of information (ECAMI) method. The information sources are augmented at first by merging several randomly selected source domains to generate extra auxiliary information. We can obtain one piece of classification result with the assistance of each information source based on DA. Then these multiple classification results are combined by belief functions theory, which is expert at dealing with the uncertain information. Nevertheless, the classification results derived from different information sources may have different weights. The optimal weights are calculated by minimizing an given error criteria defined by the distance between the combination result and the ground truth using some training data. For each object, the augmented information sources will produce multiple classification results that will be discounted by the learnt weights under the belief functions framework. Then the combination of these discounted results is employed to make the final class decision. The effectiveness of ECAMI is evaluated with respect to some related methods based on several real data sets, and the experimental results show that ECAMI can significantly improve the classification accuracy.

Process of the integration of patient advisors in oncology: Patient advisors' views.

54 Background: Since 2017, in Quebec (Canada), a research project is focusing on the feasibility, the processes, and the contribution of integrating patients who have already had cancer experiences (named patient advisors (PA)) in the oncology clinical team. In fact, the trained PA meet patients in health care settings in addition to the other health professionals in order to improve health care and partnership between professionals and patients. This presentation communicates the PA’s perception of their contribution and the factors influencing implementation of these programs in 4 establishments. Methods: Between April and May 2020, semi-structured virtual interviews lasting about 60 minutes were conducted on 12 patient advisors involved since 2017 in the elaboration of these support programs. The interviews were recorded and transcribed completely. The data analysis was done with content analysis using the QDA Miner 5.0 software, applying the qualitative analysis quality standards. Results: First of all, the 12 PAs have reported that the accompaniment of 67 patients have allowed them to share their experiential knowledge not only related to living with the illness but also about healthcare organization and the anticipation of treatments. They also highlighted their capacity to share situations that can be improved by healthcare professionals (example: wait times for exams; patients’ difficulty in understanding their illness, etc). However, they also highlighted 4 factors which limit the implementation: 1) organizational (the unclear and changing nature of the breast cancer consultation schedule, difficulty of access to consultation rooms and unsuitable schedules for the PA’s reality.; 2) leadership (lack of clinicians promoting the intervention; managers’ low involvement; lack of clarity of roles); 3) human (work overload and employee turnover); 4) PA’s status (lack of compensation and of recognition). Also, to optimize their integration, the PA’s suggest to work on a lasting bond of trust with the professionals, the creation of a status recognized by health establishments, the recognition of their role by the clinical team, to give them access to physical spaces, and an openness of the teams to their complementary knowledge. Conclusions: These first results suggest the importance during the implementation of such programs of working proactively with the PAs and the professionals on organization, leadership, resources, and status factors to allow the people dealing with cancer to benefit from experiential knowledge of other patients within their clinical team.

The role of bipartite structure in R&D collaboration networks

AbstractA great number of real-world networks are, in fact, one-mode projections of bipartite networks comprised of two different types of nodes. In the case of interactions between institutions engaging in collaboration for technological innovation, the underlying network is bipartite with institutions (agents) linked to the patents they have filed (artefacts), while the projection is the co-patenting network. Since projected network properties are highly affected by the underlying bipartite structure a lack of understanding of the bipartite network has consequences for the information that might be drawn from the one-mode co-patenting network. Here, we create an empirical bipartite network using data from 2.7 million patents recorded by the European Patent Office. We project this network onto the agents (institutions) and look at properties of both the bipartite and projected networks that may play a role in knowledge sharing and collaboration. We compare these empirical properties to those of synthetic bipartite networks and their projections. We show that understanding the bipartite network topology is critical for understanding the potential flow of technological knowledge. Properties of the bipartite structure, such as degree distributions and small cycles, affect the topology of the one-mode projected network—specifically degree and clustering distributions, and degree assortativity. We propose new network-based metrics as a way to quantify how collaborative agents are in the collaboration network. We find that several large corporations are the most collaborative agents in the network; however, such organizations tend to have a low diversity of collaborators. In contrast, the most prolific institutions tend to collaborate relatively little but with a diverse set of collaborators. This indicates that they concentrate the knowledge of their core technical research while seeking specific complementary knowledge via collaboration with smaller institutions.

Contrastive Adaptation Network for Single- and Multi-Source Domain Adaptation.

Unsupervised domain adaptation (UDA) makes predictions for the target domain data while manual annotations are only available in the source domain. Previous methods minimize the domain discrepancy neglecting the class information, which may lead to misalignment and poor generalization performance. To tackle this issue, this paper proposes contrastive adaptation network (CAN) that optimizes a new metric named Contrastive Domain Discrepancy explicitly modeling the intra-class domain discrepancy and the inter-class domain discrepancy. To optimize CAN, two technical issues need to be addressed: 1) the target labels are not available; and 2) the conventional mini-batch sampling is imbalanced. Thus we design an alternating update strategy to optimize both the target label estimations and the feature representations. Moreover, we develop class-aware sampling to enable more efficient and effective training. Our framework can be generally applied to the single-source and multi-source domain adaptation scenarios. In particular, to deal with multiple source domain data, we propose: 1) multi-source clustering ensemble which exploits the complementary knowledge of distinct source domains to make more accurate and robust target label estimations; and 2) boundary-sensitive alignment to make the decision boundary better fitted to the target. Experiments are conducted on three real-world benchmarks (i.e., Office-31 and VisDA-2017 for the single-source scenario, DomainNet for the multi-source scenario). All the results demonstrate that our CAN performs favorably against the state-of-the-art methods. Ablation studies also verify the effectiveness of each key component of our proposed system.

“It’s not just hacking for the sake of it”: a qualitative study of health innovators’ views on patient-driven open innovations, quality and safety

BackgroundOpen do-it-yourself (DIY) health innovations raise new dilemmas for patient-oriented and service-oriented scholars and healthcare providers. Our study aimed to generate practical insights into quality and safety issues to patient...

Flux flow instability as a probe for quasiparticle energy relaxation time in Fe-chalcogenides

In this work, we aim to demonstrate the potential of the flux flow instability (FFI) tool as a probe for the evaluation of the quasiparticle energy relaxation time τ ϵ in iron-based superconductors (IBS). The knowledge of this microscopic parameter, its temperature dependence and the magnetic field influence, turns particularly useful to implement IBS materials in photon detection applications, as well as to get information on the gap symmetry or its anisotropy. Here, we focus on Fe(Se,Te) thin films that both from structural and magnetic properties show the simpler behaviour, thus it can be a reference test for any more complex IBS. By current-voltage characterizations and resistance measurements, we investigate the FFI features in the presence of an external applied magnetic field as a function of the angular dependence between the crystal structure of the film and the orientation of the field. We describe the observed experimental characteristics of FFI within the intrinsic electronic mechanism of Larkin-Ovchinnikov model. In this way, we are able to give a quantitative estimate of τ ϵ in Fe(Se,Te) that can be compared with evaluation from other techniques such as pump and probe measurements. Thus, the angular measurements of FFI in high magnetic fields are a viable route to the possible mechanisms of quasiparticle relaxation and to the complementary knowledge on its anisotropy.

Evolving healthcare; nurses’ attitudes towards complementary therapies

Abstract Background Integration of complementary therapies alongside conventional medical treatment is common and affects health behaviour and outcomes. Nurses frequently interact with patients and their attitudes to these therapies may play a significant role in decision-making. This mixed-method study investigated nurses' attitudes and behaviour towards complementary therapies. Methods A sequential exploratory design was utilised. Qualitative data were collected via interviews with nurses working in primary and tertiary settings, in all states of Australia. Interview data underwent thematic analysis. Findings from the interviews informed the development of a questionnaire, which was used to conduct a national online survey. Survey data were descriptively analysed using frequency distributions and percentages. Results Nineteen nurses were interviewed and 614 responded to the survey. Themes that emerged from the qualitative data were; Promoting safe care, Seeking complementary therapies knowledge; Supporting holistic health care and Integrating complementary therapies in practice. Survey responses revealed most nurses (77.5%) discussed complementary therapies with patients. More than one half (55.5%) would 'sometimes' recommend complementary therapies and 12.0% would 'almost always/always' do so. The majority (91.8%) believed nurses should have some understanding of complementary therapies. There was a lack of agreement regarding integration of these therapies into nursing practice. Conclusions Nurses were generally supportive of patients' interest in complementary therapies and want basic education about these therapies. Key messages Nurses working in Australia often engage with patients about complementary therapies. Increasing nurses’ complementary therapy knowledge is likely to promote informed decision-making and improve patient safety.

Effects of Nutrition Education on Improving Knowledge and Practice of Complementary Feeding of Mothers with 6- to 23-Month-Old Children in Daycare Centers in Hawassa Town, Southern Ethiopia: An Institution-Based Randomized Control Trial.

Undernutrition and hidden hunger threaten the survival, growth, and development of children, young people, economies, and nations. Inappropriate complementary feeding practice due to poor maternal knowledge and awareness in combination with low income and infectious disease is the contributing factor for child undernutrition. Hence, this study was aimed at determining the effect of nutrition education on improving the knowledge and practice of complementary feeding of the mothers with 6- to 23-month old children in daycare centers of Hawassa Town, Southern Ethiopia. An institution-based randomized control trial design was employed. Daycare centers were randomly allocated for the intervention group and the control group. Among the total daycare centers in the town, five were assigned to receive nutrition education and the rest five for the control group (CG). The simple random sampling technique used to select individual participants from each daycare center. Two hundred (200) mother-child pairs (100 for each group) were recruited. Sociodemographic and economic variables were collected by the structured questionnaire. Knowledge of appropriate complementary feeding was assessed by seven knowledge questions. Appropriate complementary feeding practice was assessed by adapting Alive and Thrive Infant and Young Child Feeding (IYCF) practice guidelines. Nutrition education was given for four consecutive months by using Alive and Thrive IYCF guidelines. Data were analyzed by the SPSS software program version 20. The chi-squared test was used to test the significant differences in the proportion of good knowledge and good practice of complementary feeding and good dietary diversity between two groups. The independent t test was used to test the significant differences in mean dietary diversity between two groups. At 95% confidence interval, p < 0.05 was considered statistically significant. The results revealed that the proportion of mothers with good knowledge of appropriate complementary feeding was increased from 59% at pretest to 96% at posttest and the appropriate complementary feeding practice was improved from 54% at pretest to 86% at posttest in IG. There was no change in the knowledge and practice of complementary feeding practice in CG after four months. The proportion of mothers with good complementary knowledge was 54% both at pretest and at posttest and good complementary feeding practice was 51% and 52% at pre- and posttest in CG, respectively. There was no significant difference (p > 0.05) on complementary feeding knowledge and practice between two groups at pretest, while the difference was highly significant (p < 0.05) at the posttest. In conclusion, providing nutrition education improved the appropriate complementary feeding knowledge and practice of mothers. In recommendation, government and other partners working on sustainable child nutrition reduction should focus on the nutrition education to improve the knowledge and appropriate complementary feeding practice including daycare centers.

ON THE JOINT EXPLOITATION OF OPTICAL AND SAR SATELLITE IMAGERY FOR GRASSLAND MONITORING

Abstract. Time series of optical and Synthetic Aperture RADAR (SAR) images provide complementary knowledge about the cover and use of the Earth surface since they exhibit information of distinct physical nature. They have proved to be particularly relevant for monitoring large areas with high temporal dynamics and related to significant ecosystem services. Grasslands are such crucial surfaces, both in terms of economic and environmental issues and the automatic and frequent monitoring of their agricultural practices is required for many purposes. To address this problem, the deep-based SenDVI framework is presented. SenDVI proposes an object-based methodology to estimate NDVI values from Sentinel-1 SAR observations and contextual knowledge (weather, terrain). Values are regressed every 6 days for compliance with monitoring purposes. Very satisfactory results are obtained with this low-level multimodal fusion strategy (R2 = 0.84 on a Sentinel-2 tile). Finer analysis is however required to fully assess the relevance of each modality (Sentinel-1, Sentinel-2, weather, terrain) and feature sets and to propose the simplest conceivable framework. Results show that not all features are necessary and can be discarded while others have a mandatory contribution to the regression task. Moreover, experiments prove that accuracy can be improved by not saturating the network with non-essential information (among contextual knowledge in particular). This allows to move towards more operational solution.

Buyer-Supplier Networks and Innovation: The Role of Shared Technological Knowledge

Supplier networks are an important source technological knowledge spillovers. We analyze the role of shared technological knowledge between buyers and their supplier networks on the former’s innovation performance. Using a panel data of buyer-supplier relationships and the patenting activity of the respective firms, we address the following research questions: What moderating role does shared technology between a buyer and its supplier network play on the relationship between technology diversity of a buyer’s supplier network and buyer’s innovation performance? What moderating role does shared technology between a buyer and its supplier network play on the relationship between geographic proximity of the buyer from its supplier network and buyer’s innovation performance? What moderating role does shared technology between buyer and its supplier network play on the relationship between buyer’s diversification level and its innovation performance? We show that the level of shared technological knowledge, representing complementary or similar knowledge, can be significant in strengthening or weakening the associations between different characteristics of supply chain partners and innovation performance.

Prospective primary school teachers’ competence for analysing the difficulties in solving proportionality problem

In this paper, we describe the design, implementation and results of a formative intervention, meant to develop prospective primary school teachers’ competence in the analysis of the difficulties emerging in the resolution of proportionality tasks. Solving problems by different methods, identifying the knowledge put at stake in each problem and taking this information into account to recognize the difficulties that pupils may encounter in solving the problems using each strategy are essential aspects of the epistemic and cognitive facets of didactic-mathematical knowledge. The experience has been carried out with a sample of 88 prospective primary school teachers during the third year of their studies, by applying a didactic model that includes work in teams, institutionalization, and assessment of the individual learning achieved. To analyse the participants’ responses, we used some theoretical and methodological tools of the onto-semiotic approach in mathematics education. The identification of pupils’ potential difficulties in addressing problem-solving, based on the objects involved in the mathematical activity, was a challenging task for prospective teachers. The difficulties most frequently identified by the prospective teachers were those concerned with understanding the statement requirements, or the problem-situations context, and the mathematical procedures involved in the resolution of the task. They did not discriminate the difficulties according to the resolution strategies. Time constraints conditioned the degree of learning achieved. We conclude that it is necessary that teacher education programs consider this type of didactical analysis and should be articulated with situations focused on developing other complementary knowledge and competencies.

Snapshot of rare, exotic and overlooked fish species in the Italian seas: A citizen science survey

Italy, at the center of the Mediterranean Sea, hosts a high diversity of fishes, but to a certain extent, this richness remains hidden or poorly known because of rare, cryptic or recently introduced species, that are hardly to detect with the traditional sampling approaches. In this study, we gained complementary knowledge, engaging Italian sea users, especially fishers and underwater photographers, to share their observations. Results obtained during 2019 provided 124 new records distributed in 40 species. Most of these records are related to native-rare and native-thermophilic fishes (~95%), while few observations (~5%) concern non-indigenous taxa. Records of thermophilic species were reported from the Tyrrhenian Sea and the Ionian Sea, while alien species were mostly reported from the southernmost coasts of Italy. Our findings highlight the potential of participatory actions and emphasize the value of a close collaboration between researchers and sea-lovers for monitoring marine biodiversity on large spatial scales.

A Secure Federated Transfer Learning Framework

Machine learning relies on the availability of vast amounts of data for training. However, in reality, data are mostly scattered across different organizations and cannot be easily integrated due to many legal and practical constraints. To address this important challenge in the field of machine learning, we introduce a new technique and framework, known as federated transfer learning (FTL), to improve statistical modeling under a data federation. FTL allows knowledge to be shared without compromising user privacy and enables complementary knowledge to be transferred across domains in a data federation, thereby enabling a target-domain party to build flexible and effective models by leveraging rich labels from a source domain. This framework requires minimal modifications to the existing model structure and provides the same level of accuracy as the nonprivacy-preserving transfer learning. It is flexible and can be effectively adapted to various secure multiparty machine learning tasks.

USE OF AN INDIGENOUS LEARNING BUNDLE IN AN ENGINEERING PROJECT COURSE

In response to the Calls to Action of the Truth and Reconciliation Commission of Canada a range of Collaborative Indigenous Learning Bundles have been introduced at a Canadian university to provide ways for Indigenous knowledge to be incorporated into courses across the university. One of the first courses in the engineering faculty to use the Indigenous Environment Relations Bundle was a third year project course for the BEng Electrical Engineering program. The use of the bundle, through the learning management system, was part of the lecture series and was used in a class discussion with an optional reflection. The objective was to provide complementary Indigenous knowledge to the discussion of the environmental impact of engineering. A first year introductory engineering course used the First Peoples: A Brief Overview. The response of the students in both courses was respectful and produced thoughtful discussions. Those that undertook the optional reflection produced insightful and often personal thoughts on a particular place. The use of the bundles shows that Indigenous matters and information from knowledge keepers can be integrated into engineering courses.

The Design and Impact of an Interprofessional Education Event Among Pharmacy and Nursing Students in Palliative Care-RnRx.

Nearly all reports of interprofessional education (IPE) in palliative care have excluded pharmacy students. This article describes an IPE event between pharmacy and nursing students and assesses its impact on IPE competencies. Second-year nursing students and third-year pharmacy students participated in an evening-long event, focused on a married couple who each require palliative care-one for end-of-life planning and one for chronic disease progression. The impact of the event was assessed using the Interprofessional Collaborative Competency Attainment Scale (ICCAS) and qualitative feedback. Two hundred nine (96.7%) completed the ICCAS, and 16 of the 20 statements of the ICCAS showed large positive effect sizes (Cohen d ≥ 0.8), with the remaining 4 showing moderate positive effect sizes (Cohen d ≥ 0.5). The greatest effect sizes were related to improved awareness of complementary skillsets and knowledge between the professions. Addressing team conflict and including the patient/family in decision-making showed the least improvement. While ongoing interactions are ideal for the development of skills related to conflict and team development, this article demonstrates that even a 1-time activity can have an impact on students' interprofessional care competence.

RETRACTED: Allocation of control right between the participants of building information modeling–integrated project delivery project from the perspective of knowledge sharing

The emergence of building information modeling technology has facilitated promotion and application of integrated project delivery mode, while reasonable allocation of control right is the key to dealing with opportunistic behavior during the knowledge sharing process of the building information modeling–integrated project delivery project. Replicator dynamics model from the perspective of knowledge sharing was established by means of evolutionary game, to analyze the evolutionarily stability strategy for allocation of control right between the owners and the professional technology companies. The research showed that, when the knowledge sharing benefit from innovation was more than the supervision cost for struggling for control right, two stably revolutionary strategies existed in the game system, namely contingent control and joint control; and the stably revolutionary status was under the influence of knowledge synergy coefficient, proportion of complementary knowledge, knowledge stock, degree of knowledge sharing, probability that the estimated operation status of the project was favorable, supervision cost, success probability of the project, etc. The research results provided a theoretical reference for the owners and the professional technology companies of building information modeling–integrated project delivery project in deciding whether to struggle for control right or not according to the observed information and the final benefit level.

(Invited) Investigations of Interaction and Molecular Structure of Additives on the Copper Electrodeposited Layer By Combination of Cyclic Voltammetry with Time-of-Flight Secondary-Ion Mass Spectrometry (TOF-SIMS)

Appropriate additives, such as polyethylene glycol, play the essential role of metal deposition suppressors and are required to control the fabrication process of copper electrodepositionon micro and nanoscale devices. Moreover, brighteners, accelerators and levellers are involved in adjusting of functional properties of the electroplating bath influencing roughness and waviness of deposited copper layer. Our recent studies [1] show that TOF-SIMS measurements under static regime can be conducted successfully for the identification of additives such as PEG, SPS, and Cl, accumulated on the copper electrodeposited layer.Especially, evaluation of molecular structure of the large molecules such as polyethylene glycol is very challenging and out of range for techniques such as SERS, widely applied for in situ studies under copper electrodeposition regime. On the other hand, traditional mass spectroscopy such as electrospray mass spectrometry are oriented on evaluation of composition of electroplating bath. Recently, we have developed a new approach for evaluation of additives on the copper layer by combination of cyclic voltammetry (CV) with TOF-SIMS. To determine the molecular structure of polyethylene glycol and its interaction with chloride and acceleratorson the copper electrodeposited layer CV experiment was conductedwhile a nitinol wire as a working electrode was withdrawn at constant speed from a copper electroplating bath. In that way applied potential during CV corresponds to position of the wire withdrawn from the electroplating bath. This approach allows to evaluate of distribution of chemical species in a function of the applied potential by ex situ TOF-SIMS measurements. Moreover,the thickness of the copper layer was controlled by laser scan micrometer. In the presence of brightener and leveler, the roughness was evaluated by atomic force microscopy in a function of length of wire. In that fashion, CV experiment combined with a molecular analysis, thickness and roughness of copper layer measurements bring complementary knowledge to comprehensively understand the processes occurring on the copper surface. This will have an application for the real-world samples in a wide range of thickness copper layer, applied potential and concentration of additives and copper sulfate.[1] R. Mroczka, R. Łopucki, G. Żukociński, Molecular analysis of additives and impurities accumulated on copper electrodeposited layer by time-of-flight secondary ion mass spectrometry, Applied Surface Science 463 (2019) 412–426

Combination of Classifiers With Different Frames of Discernment Based on Belief Functions

Classifier fusion remains an effective method to improve classification performance. In applications, the classifiers learnt using different attributes may work with various frames of discernment (FoD) of classification. There generally exist more or less complementary knowledge among these classifiers. However, how to efficiently combine such classifiers under different FoD is a challenging problem. In this article, we propose a new method for classifier fusion with different FoD based on the belief functions, which allow to well represent and deal with uncertain information. The credal transformation rules are developed to map the various FoD into a common one. It allows to transfer the probability (or mass of belief) of one class in the given FoD not only to several singleton classes but also to the metaclasses (i.e., disjunction of several classes) and the ignorance in other chosen FoD according to a transformation matrix, which is estimated based on the training (pairwise) data by minimizing a certain error criteria. Thus, we can well characterize the uncertainty and imprecision during the transformation of FoD. After that, the outputs of different classifiers represented by basic belief assignments (BBAs) can be transformed to a common FoD. Then, the well-known Dempster's rule is employed to combine these transformed BBA to obtain final classification result under the chosen FoD. Several real data sets are used in the experiment to evaluate the performance of the proposed method. Our experimental results show that this new method can efficiently improve the classification accuracy with respect to other related methods.

Use and management of tamarind (Tamarindus indica L., Fabaceae) local morphotypes by communities in Tigray, Northern Ethiopia

ABSTRACTThe population structure, phenotypic differences and ethnobotanical knowledge of tamarind (Tamarindus indica L., Fabaceae) were studied in Kunama- and Tigrigna-speaking communities in the Tigray Regional State of Ethiopia. A vegetation survey on 902 plots of 400 m2 each was conducted along riparian forests and farmlands. Seed and pod morphology of sweet and sour morphotypes was compared based on 6 pods/tree from 20 trees. Thirty-two key informants and 256 randomly selected general informants were interviewed about the use and management of tamarind. Tree densities differed significantly among sociocultural groups and land use. Relatively more trees (6.0–17.5 individuals per hectare) were found in riparian forests as compared to farmland (4.0–7.8). Stem diameter class distribution has a bell-shape, indicating a regeneration problem. Morphological characteristics (pod length, pod width, pod weight, seed weight, pulp weight, and the number of seeds per pod) differed significantly between sour and sweet tamarind morphotypes (p < .05). Interviews identified seven use categories of tamarind, including human and veterinary medicines and five food types, with a greater number of uses mentioned within Kunama communities. Results can be used to support the sustainable use of tamarind in riparian forests and on farms, including conservation of varietal diversity based on the complementary knowledge of both communities.

Evaluation of complementary feeding knowledge and behavior of mothers with children between four-twenty four months

Aim: Complementary feeding is important for growth in infancy. In this study, we aimed to determine the knowledge of complementary feeding of mothers who take their children to our hospital and to evaluate the effects of mother’s and baby’s characteristics on complementary feeding. Material and Method: Between December 2018 and February 2019, 259 mothers who admitted to our hospital were included in the study. Mothers’ knowledge and behavior about complementary feeding were questioned. Results: The mean age of 259 mothers was 28.71 ± 5.09 years old. 94 (36.3%) of the participants introduced complementary feeding before six months. The mean time to introduce complementary feeding was 5.67 ± 0.84 months. Complementary feeding was introduced with 48.6% yoghurt, 17.8% fruit puree and 17% soup. The most frequent reason for early onset was the weight gain of the baby and the decrease in breast milk. A significant difference was found between the monthly income of the family, smoking and working of the mother, and early initiation of complementary feeding. The use of feeding bottles and/or pacifiers was also associated with early onset of complementary feeding. Conclusion: Mothers’ time to introduce complementary feeding varies. Mothers should be given more education about complementary feeding for healthy development of babies.