Men’s Knowledge, Attitudes and Perceptions on Family Planning in Tourourou Village, Gogui Rural Commune, Nioro Circle, Kayes Region of Mali

Introduction: The involvement of men in reproductive health programmes and more specifically in family planning has always been of concern to the various development actors at both national and international levels. Objective: To study the births, ideas and opinions of men on Family Planning in the village of Tourourou. Material and Methods: This was a prospective cross-sectional, descriptive and analytic study from February 1 to July 31, 2020 in the village of TOUROUROU on the Knowledge, Attitudes and Perceptions of Men on Family Planning. We included in our study, all men residing in TOUROUROU whose age is between 14 and 99 years, who agreed to participate in the study. Results: Our study involved 200 men. The 25 - 29 age group was the most represented with 25.5%. The Soninke had represented 41%. In our study, 97.5% of men had heard of family planning, 62% had spontaneously cited at least one modern contraceptive method, and the pill ranked first with 64.5%. Radio and friends were the most frequent sources of information with 57.5% and 54.5% respectively. Birth spacing was the most cited family planning goal by men in 43.5% of cases. Men supported the practice of family planning in 50.5% of cases. Conclusion: In the village of Tourourou men play a crucial role in decision-making concerning the health of the couple and the family, their effective involvement in Reproductive Health especially in Family Planning will contribute enormously to the improvement of the health of the family.

Path Planning for Intelligent Robots Based on Deep Q-learning With Experience Replay and Heuristic Knowledge

Path planning and obstacle avoidance are two challenging problems in the study of intelligent robots. In this paper, we develop a new method to alleviate these problems based on deep Q-learning with experience replay and heuristic knowledge. In this method, a neural network has been used to resolve the "curse of dimensionality" issue of the Q-table in reinforcement learning. When a robot is walking in an unknown environment, it collects experience data which is used for training a neural network;such a process is called experience replay.Heuristic knowledge helps the robot avoid blind exploration and provides more effective data for training the neural network. The simulation results show that in comparison with the existing methods, our method can converge to an optimal action strategy with less time and can explore a path in an unknown environment with fewer steps and larger average reward.

Family Planning Knowledge and Practices among Reproductive Age Women in Widou Thiengoly, Louga Region, Senegal

Family planning is an effective intervention to improve the health of the mother, newborn and child. It was introduced in Senegal in the 1960s. Significant disparities were noted between urban and rural areas. This research aimed at measuring family planning methods knowledge and practices among reproductive age women (RAW) in the village of Widou Thiengoly, Louga region, Senegal. A descriptive and analytical cross-sectional study was carried out from 12 to 20 August 2016 and involved 150 RAW with an average age of 29.34 years. They were mostly married (98%), with a fertility rate of 3.22 children/woman. 67.3% of RAW knew at least one FP method and the contraceptive prevalence was 40.7%. Birth spacing is the main reason or utilization for more than half of users, while for non-users, more than half were ignorant of FP. Knowledge and practices of contraception were not related to the age of WCA, or the number of children. Fears or experiences of side effects were barriers to initiation and continuous use of FP methods, hence the importance of focusing awareness campaigns on alleviating fears about side effects.

Improving the Patient Discharge Planning Process through Knowledge Management by Using the Internet of Things

The UK National Health Service (NHS) is faced with problems of managing patient discharge and preventing the problems that result from it such as frequent readmissions, delayed discharge, long waiting lists, bed blocking and other such consequences. The problem is exacerbated by the growth in size, complexity and the number of chronic diseases in the NHS. In addition, there is an increase in demand for high quality care, processes and planning. Effective Discharge Planning (DP) requires practitioners to have appropriate, patient personalised and updated knowledge in order to be able to make informed and holistic decisions about a patients’ discharge. This paper examines the role of Knowledge Management (KM) in both sharing knowledge and using tacit knowledge to create appropriate patient discharge pathways. The paper details the factors resulting in inadequate DP, and demonstrates the use of Internet of Things (IoT) and Machine2Machine (M2M) as candidate technologies and possible solutions which can help reduce the problem. The use of devices that a patient can take home and devices which are perused in the hospital generate information, which can serve useful when presented to the right person at the right time, thus harvesting knowledge. The knowledge when fed back can support practitioners in making holistic decisions with regards to a patients’ discharge.

Analysis on the Causes of Existing Problems of Professional Knowledge of Western Rural Teachers Under the Urban and Rural Educational Planning Background

This paper adopts the self-designed questionnaire to make investigations and interviews with the rural middle and primary school teachers in Chengdu and Chongqing districts about the professional development problems of western rural teachers, and refers to the educational literature materials in western rural areas. Through a comprehensive analysis, it is known that the professional knowledge status of western rural teachers is worrying, and the reason is mainly caused by the location, policy, economy, society, continuing education and teachers＇ own factors.

Dosimetric Effects Due to Inter-Observer Variability of Organ Contouring When Utilizing a Knowledge-Based Planning System for Prostate Cancer

Purpose: Radiotherapy is a widely accepted standard of care for early-stage prostate cancer, and it is believed that the plan quality and treatment outcome are associated with contour accuracy of both the target and organs-at-risk (OAR). The purposes of this study are to 1) assess geometric and dosimetric uncertainties due to inter-observer contour variabilities and 2) evaluate the effectiveness of geometric indicators to predict target dosimetry in prostate radiotherapy. Methods: Twenty prostate patients were selected for this retrospective study. Five experienced clinicians created unique structure sets containing prostate, seminal vesicles, bladder, and rectum for each patient. A fully automated script and knowledge-based planning routine were utilized to create standardized and unbiased plans that could be used to evaluate changes in isodose distributions due to inter-observer variability in structure segmentation. Plans were created on a “gold-standard” structure set, as well as on each of the user-defined structure sets. Results: Inter-observer variability of contours during structure segmentation was very low for clearly defined organs such as the bladder but increased for organs without well-defined borders (prostate, seminal vesicles, and rectum). For plans generated with the user-defined structure sets, strong/moderate correlations were observed between the geometric indicators for target structure agreement and target coverage for both low-risk and intermediate-risk patient groups, while OAR indicators showed no correlation to final dosimetry. Conclusions: Target delineation is crucial in order to maintain adequate dosimetric coverage regardless of the associated inter-observer uncertainties in OAR contours that had a limited impact upon final dosimetry.

GNN-based temporal knowledge reasoning for UAV mission planning systems

Unmanned aerial vehicles(UAVs)are increasingly applied in various mission scenarios for their versatility,scalability and cost-effectiveness.In UAV mission planning systems(UMPSs),an efficient mission planning strategy is essential to meet the requirements of UAV missions.However,rapidly changing environments and unforeseen threats pose challenges to UMPSs,making efficient mission planning difficult.To address these challenges,knowledge graph technology can be utilized to manage the complex relations and constraints among UAVs,missions,and environments.This paper investigates knowledge graph application in UMPSs,exploring its modeling,representation,and storage concepts and methodologies.Subsequently,the construction of a specialized knowledge graph for UMPS is detailed.Furthermore,the paper delves into knowledge reasoning within UMPSs,emphasizing its significance in timely updates in the dynamic environment.A graph neural network(GNN)-based approach is proposed for knowledge reasoning,leveraging GNNs to capture structural information and accurately predict missing entities or relations in the knowledge graph.For relation reasoning,path information is also incorporated to improve the accuracy of inference.To account for the temporal dynamics of the environment in UMPS,the influence of timestamps is captured through the attention mechanism.The effectiveness and applicability of the proposed knowledge reasoning method are verified via simulations.

Knowledge Representation and Semantic Inference of Process Based on Ontology and Semantic Web Rule Language

The process inference cannot be achieved effectively by the traditional expert system,while the ontology and semantic technology could provide better solution to the knowledge acquisition and intelligent inference of expert system.The application mode of ontology and semantic technology on the process parameters recommendation are mainly investigated.Firstly,the content about ontology,semantic web rule language(SWRL)rules and the relative inference engine are introduced.Then,the inference method about process based on ontology technology and the SWRL rule is proposed.The construction method of process ontology base and the writing criterion of SWRL rule are described later.Finally,the results of inference are obtained.The mode raised could offer the reference to the construction of process knowledge base as well as the expert system's reusable process rule library.

Framework of Digital Machining Process Planning Platform for Cylinder Body Part

Digital factory technology is an advanced manufacturing technology served as to establish a bridge between the process of product development and manufacturing.In terms of application for digital factory technology in machining,especially in machining of a complicated part such as a cylinder body part,a concept of digital process planning and its framework are proposed.Its components including machining domain knowledge model,machining knowledge base,machining resource base and process planning system are studied.A machining knowledge model in tree form and an object-driven knowledge reasoning mechanism are used for machining knowledge base.The process planning system is a user interface that leads a planner to finish the planning process.A case about a cylinder head part is given to demonstrate how the platform works.The framework of digital process planning is the foundation of some intelligent CAPP systems and helps to production line planning.

Women’s Attitudes and Knowledge towards the Use of Contraceptive Methods

Background: Contraceptive use reduces the need for abortion by preventing unwanted pregnancies, and the causes of maternal death worldwide. Contraceptive use helps women to plan their pregnancies and contributes for population growth. This study aims to analyze the attitudes and knowledge of the women attending Van Norma Clinic for the use of contraceptive methods. Methods: A cross-sectional study was used to analyze the information. A convenience sampling method has been used to select the 100 women who attended Van Norman Clinic in Family planning service in the period of the study of four months (April to July, 2020). A self-administered questionnaire with four parameters addressing importance of using contraceptive methods, the factors affecting the women’s attitudes for not using contraceptive methods, types of contraceptive methods currently used, advantages and disadvantages of using contraceptive methods was used to collect data. Results: Research findings show that the majority of respondents knew the importance of using contraceptive methods like preventing unwanted pregnancies (97%), spacing pregnancies (96%), planning pregnancies (92%), and getting well (70%). Two factors affecting women for not using contraceptive methods had been identified such as religion (73%) and fear (70%). In addition, the women attending Van Norman Clinic prefer using implants (99%) and injectable (99%). It is clear that women do not know the consequences related to the nonuse of contraceptive methods. Some recommendations have been made to the health care facilities, parents, women themselves, churches’ leaders and government in general. Conclusion: Factors which influence women’s attitudes for not using contraceptive methods were notified in our study such as religion (73.0%) and fear (70.0%) which was explained by the fact that in Burundi most people are catholic which is the most religion prohibiting the use of contraceptive methods. However, the participants’ knowledge was significantly good as their score was more than 50% for all variables.

Research on Framework of Digital Process Planning Platform

Digital factory technology is a research focus in academe and industry,which is an advanced manufacturing tech- nology that is proposed to bridge product development and manufacturing.For applying digital factory technology in machining domain,a concept of digital process planning and its framework are suggested,its components including machining domain knowledge model,machining knowledge base,machining resource base and process planning system are studied.The framework of digital process planning is of value for implementing digital factory technology in machining industry.

MULTI-AGENT COMPUTER AIDED ASSEMBLY PROCESS PLANNING SYSTEM FOR SHIP HULL

A multi agent computer aided assembly process planning system (MCAAPP) for ship hull is presented. The system includes system framework, global facilitator, the macro agent structure, agent communication language, agent oriented programming language, knowledge representation and reasoning strategy. The system can produce the technological file and technological quota, which can satisfy the production needs of factory.

An Intelligent Master Model of Computer Aided Process Planning for Large Complicated Stampings

Process planning for large complicated stampings is more complicated, illegible and multiform than that for common stampings. In this paper, an intelligent master model of computer aided process planning （CAPP） for large complicated stampings has been developed based on knowledge based engineering （KBE） and feature technology. This innovative model consists of knowledge base （KB）, process control structure （PCS）, process information model （PIM）, multidisciplinary design optimization （MDO）, model link environment （MLE） and simulation engine （SE）, to realize process planning, optimization, simulation and management integrated to complete intelligent CAPP system. In this model, KBE provides knowledge base, open architecture and knowledge reuse ability to deal with the multi-domain and multi-expression of process knowledge, and forms an integrated environment. With PIM, all the knowledge consisting of objects, constraints, cxtmricncc and decision-makings is carried by object-oriented method dynamically for knowledge-reasoning. PCS makes dynamical knowledge modified and updated timely and accordingly. MLE provides scv. cral methods to make CAPP sysmm associated and integrated. SE provides a programmable mechanism to interpret simulation course and result. Meanwhile, collaborative optimization, one method of MDO, is imported to deal with the optimization distributed for multiple purposes. All these make CAPP sysmm integrated and open to other systems, such as dic design and manufacturing system.

Males as Partners in Family Planning Service Uptake in Ghana: A Descriptive Cross-Sectional Survey

Background: Family planning is an efficient and effective intervention that results in quick benefits for the whole family socio-economically. Differences exist in the rate of contraceptive use between male and female and male involvement of service uptake in Ghana. The objective of this study was to explore male direct involvement and or support to their partners in family planning service uptake. Methods: The study used a descriptive cross-sectional survey to sample 384 men of reproductive age (18 - 45 year) using cluster sampling to enlist participants from within the Suame Magazine light Industrial area in the Ashanti Region of Ghana. Data was analyzed descriptively using SPSS version 16. Results: Men showed very high knowledge (90%) about what constitutes Family Planning, with moderate level of involvement both active and passive involvement (56%) though only a few (38.9%) were presently adopting or using modern contraceptive. The study rather found only 14% (55) males were willing to be solely responsible and actively involved in Family Planning service. Family Planning services did not adequately meet the needs of men with the services centers remaining unavailable in the study area. Conclusion: The extent of male involvement in family planning programmes is marginally above average. Males showed appreciable knowledge of family planning options though misconceptions continued to exist. A more couple-oriented approach to family planning is needed including recruiting males as family planning providers, offering more family planning counseling for couples, and promoting female-oriented methods with men and vice versa.

Toward a Multi-Dimensional Ontology Model for Urban Planning

In the recent past years, the major challenge facing scientists and researchers in the field of knowledge engineering is classifying and sharing geographic data with both computer and human. Ontology is one of the most important classification schemes that aim to make data machine-interpretable. In the literature, all ontology based models developed in the field of urban planning have some limits. First, they describe the nature of each parcel of the soil while ignoring other important components of urban planning such as services, infrastructure … Secondly, these ontologies are developed according to legislation and regulations of the zone studied so they can’t be used by some urban territories that have specific urban law such as Moroccan country. This paper presents a new multi-dimensional ontology model called LUP specifically developed to overcome this flaw. The main goal is to provide semantic land use descriptions according to four dimensions: zoning, services, infrastructure and easement and to define all LUP concepts within the Moroccan urban law. We illustrate the use of our proposed model with a case study by mapping a land use planning document within the area of Ainchock municipality of Casablanca city according to our model concepts.

Qualitative Assessment of Knowledge, Attitude, and Practice of Contraceptives among Women Attending Postnatal Care in a Health Facility in Jos, Plateau State, Nigeria

Background: Contraceptive acceptance and utilization in society has been a huge challenge for communities in developing countries. There is a need to support the increase in the utilization of contraception and family planning services. In all this, good knowledge and practice of contraception services will enable women to select the best methods. The study seeks to qualitatively assess the knowledge, attitude, and practice of contraceptive use among women attending postnatal care in a health facility in Jos, Plateau State, Nigeria. Methods: This qualitative study was conducted in Bingham University Teaching Hospital, Jos, Plateau State in September 2019. This study utilized Focus Group Discussions among 36 women recruited using the purposive sampling technique. There were four (4) sessions involving nine (9) women per session. Findings: Of the 36 women, a majority (88.9%) had positive perception regarding contraception, all agreed that contraception and family planning is beneficial to families and communities. A majority felt that communities are yet to accept contraception. Most (83.3%) of the women had good knowledge of contraception. Three-quarters (77.8%) of the women have used contraception in the past, and about half (41.7%) are using it currently. Attitude towards adoption of contraceptives after current pregnancy was generally good. About half (52.7%) of the participants stated they required spousal approval before they adopt a method of contraception. Conclusion: There is a need for health agencies, development partners, and government to continue the health education, community sensitization, and support towards making contraception and family planning commodities available and accessible.

Autonomous planning system based on temporal constraint satisfaction

In order to realize spacecraft autonomy activity duration and complex temporal relations must be taken into consideration. In the space mission planning system, the traditional planners are unable to describe this knowledge, so an object-oriented temporal knowledge representation method is proposed to model every activity as an object to describe the activity's duration, start-time, end-time and the temporal relations with other activities. The layered planning agent architecture is then designed for spacecraft autonomous operation, and the functions of every component are given. A planning algorithm based on the temporal constraint satisfaction is built in detail using this knowledge representation and system architecture. The prototype of Deep Space Mission Autonomous Planning System is implemented. The results show that with the object-oriented temporal knowledge description method, the space mission planning system can be used to describe simultaneous activities, resource and temporal constraints, and produce a complete plan for exploration mission quickly under complex constraints.

On the Decision Structures and Knowledge Discovery for ANP Modeling

This paper proposes an integrative framework for network-structured analytic network process (ANP) modeling. The underlying rationales include: 1) creating the measuring items for the complex decision problems;2) applying factor analysis to reduce the complex measuring items into fewer constructs;3) employing Bayesian network classifier technique to discover the causal directions among constructs;4) using partial least squares path modeling to test the causal relationships among the items-constructs. The proposed framework is implemented for knowledge discovery to a case of high-tech companies’ enterprise resource planning (ERP) benefits and satisfaction in Hsinchu Science Park,Taiwan. The results show that the proposed framework for ANP modeling can reach a satisfactory level of convergent reliability and validity. Based on the findings, pragmatic implications to the ERP venders are discussed. This study has shed new light on the long neglected, yet critical, issue on decision structures and knowledge discovery for ANP modeling.

The Global Educational Environment Within Global Management of Knowledge

The previous studies have outlined the major theoretical perspectives that have been developed within the global education of planning development. They have explored the application of these perspectives to the central substantive theme emerging from global educational analysis of planning organisation and behaviour, that is, the process of managerial control. This study focuses upon the global educational environment within global management of knowledge and substantive parameters set by the previous studies. It carries out this task in a number of respects. First, it reviews the various explanations that have been offered for the historical development of modern planning--both as a unique organisational form and as a distinctive educational worldview. Second, it considers various conceptions of managerial work that have evolved within educational analysis since the inception of the corporate system enters into global education societies during the early years of the 21st century. Third, it assesses the implications of empirical research on the three major levels of planning that haw： crystallised within contemporary corporate hierarchies. These are made up by the elite group of staffs and senior lecturers, and the middle strata of line workers, who are the superintendents of production. A concluding section evaluates the general contribution educational analysis has made to our understanding of the nature of managerial work.

Consumer Knowledge, Brand Image, Openness to Experience and Involvement: A Case in Cosmetic Consumption

The study adopted the theory of planned behavior (TPB) as research model to inspect what factors would influence consumers to purchase cosmetics by adding brand image, involvement, consumer knowledge and openness to experience to the model. A 7-point Likert scale questionnaire was designed to measure TPB items and totally 400 valid respondents were collected online. The results show that among the above, only “perceived behavioral control” has positive influence on intention of purchasing cosmetics. Neither attitude nor subjective norm has significant influence on purchasing intention. In addition, brand image and involvement have no significant influence on purchasing intention but consumer knowledge and openness to experience were found to have positive influence on purchasing intention.