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Properly allocating an organization's activities within a building is vital to reducing the relational complexity arising from process–environment interactions. Multiple relationships are mapped, and certain interferences are only identified after these have been processed. The method/software employed for this task is Mapping Activity Environment Allocation (MAEA). However, data input and interpretation of results depend on the usability conditions of the organization's agents. This paper presents MAEA's usability test results.

Test sessions and interviews were carried out with seven agents registered at a University Hospital. Participants were instructed to think aloud during its use, and immediately afterward, responded to semi-structured interviews. Test sessions were audio recorded and screen captured.

Participants found the software easy to use and pointed out valuable implications for professional and academic use. In addition to relationship, priority and parallelism data, customized visualizations were created, including organizational charts, flowcharts and activity flow routes on the floor plan.

MAEA's simplicity allows non-designers to conduct evidence-based assessments and decisions. It allows designers to test their proposals during the programming and outline proposal stages.

A more detailed definition of design requirements from the beginning increases the conditions to successfully achieve project goals.

The ability to map the allocation of activity-spaces in the pre-design phase of building architecture allows for early identification of interactions, aiding in the development of more robust project requirements during programming.

Purpose: Preserving a country’s culture is crucial for its sustainability. Handicraft is a key draw for tourism destinations; it protects any civilisation’s indigenous knowledge and culture by managing the historical, economic, and ecological ecosystems and perfectly aligns with sustainable development. It has a significant role in creating employment, especially in rural regions and is an essential contributor to the export economy, mainly in developing nations. The study focuses on the skills required and existing gaps in the handicraft industry, its development and prospects by considering women and their role in preserving and embodying the traditional art of making handicrafts.

Approach: A framework has been developed for mapping and analysing the skills required in the handicraft sector using econometric modelling; an enormous number of skills have been crowdsourced from the respondents, and machine learning techniques have been used.

Findings: The findings of the study revealed that employment in this area is dependent not only on general or specialised skills but also on complex matrix skills ranging from punctuality to working in unclean and unsafe environments, along with a set of personal qualities, such as taking initiatives and specific skills, for example polishing and colour coding.

Implications: The skills mapping technique utilised in this study is applicable globally, particularly for women indulged in casual work in developing nations’ handicrafts industry. The sustainable development goals, tourism, and handicrafts are all interconnected. The research includes understanding skills mapping, which provides insights into efficient job matching by incorporating preferences and studying the demand side of casual working by women in the handicraft sector from a skills perspective.

The warp-knitted fully-formed shorts are one kind of fully-formed garments knitted by a double-needle bar machine, which is widely used in the medical field. Because of its distinctive forming method, designers are unable to grasp the final effect of the product accurately during the design process. The purpose of this paper is to clarify a visible 3D simulation method in the design process along with the knitting method and structure characteristics, which is reflected in the final product effect.

This study introduces a simulation process for warp-knitted fully-formed fabric from an input 3D surface model group. Stitch mesh models are established according to the garment structure and the triangle index of the garment model that swchape-controlling points belong to is calculated. The garment model group includes a 2D plate and a 3D model, between which there is a space coordinate transformation relationship. The study makes use of the 3D tubes to connect the coordinate points in order and render the tubes in real yarn colors. The effects of two parameters, radial segment and tubular segment, are analyzed and decided to obtain a fine surface within a reasonable rendering time.

A stereoscopic simulation process from flat fabric to 3D product is realized using computer graphics technology. The warp-knitted fully-formed short is shown during the design process within a short time by setting the rendering parameters of tubular segments (ts = 125) and radial segments (rs = 6).

Visual simulation for the shorts provides a time-saving and resource-saving method for structure design and parameter modification before knitting. There is no need to knit samples repeatedly to satisfy demand, which indicates that it is a saver of time and resources.

The purpose of the research was to, first, investigate if the use of maps as instructional resources will boost scholarly performance and, second, examine if gender can moderate the effect of map usage on scholarly performance.

The study was a quasi-experimental pre-test and post-test. A sample of 260 JSS II Students from 8 schools were selected through the purposive sampling technique. A Social Studies Scholarly Performance Test (SSSPT) with a reliability index of 0.79 was the instrument for data collection. The students were assigned into two groups: control and experimental. Both groups were pre-tested taught for a timeline of six weeks and thereafter post-tested.

The study reported a significant increase in the scholarly performance of students taught with maps; a significant difference occurred in the scholarly performance of both groups and gender did not moderate the effect of maps.

The social studies teachers used for the study did not have previous knowledge or map skills; this could have affected the outcome. Secondly, the treatment took place for just six weeks, and the time allotted for social studies in the school timetable was used. This may not have given the students enough time to master map interpretation.

A major implication of the study is that results will show that maps can promote the scholarly performance of students in social studies. Secondly, the fact that gender did not moderate the effect of maps suggests that maps are gender-friendly.

The results of the study, if implemented, would make social studies teachers to become inventive and resourceful in the use of maps as instructional resources for junior secondary students' scholarly performance in social studies without taking gender into consideration.

This study is a product of the researcher’s doctoral thesis; therefore, it is original and has value. The results are the product of a painstaking study carried out by the author for a period of three years on the effect of instructional resources on social studies students’ scholarly performance. Maps were one of the instructional resources studied for the award of a Ph.D. degree.

With the rise in wine consumption, accurate wine price forecasts have significantly impacted restaurant and hotel purchasing decisions and inventory management. This study aims to develop a precise and effective wine price point and interval forecasting model.

The proposed forecast model uses an improved hybrid kernel extreme learning machine with an attention mechanism and a multi-objective swarm intelligent optimization algorithm to produce more accurate price estimates. To the best of the authors’ knowledge, this is the first attempt at applying artificial intelligence techniques to improve wine price prediction. Additionally, an effective method for predicting price intervals was constructed by leveraging the characteristics of the error distribution. This approach facilitates quantifying the uncertainty of wine price fluctuations, thus rendering decision-making by relevant practitioners more reliable and controllable.

The empirical findings indicated that the proposed forecast model provides accurate wine price predictions and reliable uncertainty analysis results. Compared with the benchmark models, the proposed model exhibited superiority in both one-step- and multi-step-ahead forecasts. Meanwhile, the model provides new evidence from artificial intelligence to explain wine prices and understand their driving factors.

This study is a pioneering attempt to evaluate the applicability and effectiveness of advanced artificial intelligence techniques in wine price forecasts. The proposed forecast model not only provides useful options for wine price forecasting but also introduces an innovative addition to existing forecasting research methods and literature.

This paper aims to propose a new linear parameter varying (LPV) controller for the robot tracking control problem. Using the identification of the robot dynamics in different work space points about modeling trajectory based on the least square of error algorithm, an LPV model for the robotic arm is extracted.

Parameter set mapping based on parameter component analysis results in a reduced polytopic LPV model that reduces the complexity of the implementation. An approximation of the required torque is computed based on the reduced LPV models. The state-feedback gain of each zone is computed by solving some linear matrix inequalities (LMIs) to sufficiently decrease the time derivative of a Lyapunov function. A novel smoothing method is used for the proposed controller to switch properly in the borders of the zones.

The polytopic set of the resulting gains creates the smooth switching polytopic LPV (SS-LPV) controller which is applied to the trajectory tracking problem of the six-degree-of-freedom PUMA 560 robotic arm. A sufficient condition ensures that the proposed controller stabilizes the polytopic LPV system against the torque estimation error.

Smoothing of the switching LPV controller is performed by defining some tolerances and creating some quasi-zones in the borders of the main zones leading to the compressed main zones. The proposed torque estimation is not a model-based technique; so the model variation and other disturbances cannot destroy the performance of the suggested controller. The proposed control scheme does not have any considerable computational load, because the control gains are obtained offline by solving some LMIs, and the torque computation is done online by a simple polytopic-based equation.

In this paper, a new SS-LPV controller is addressed for the trajectory tracking problem of robotic arms. Robot workspace is zoned into some main zones in such a way that the number of models in each zone is almost equal. Data obtained from the modeling trajectory is used to design the state-feedback control gain.

To solve the obstacle detection problem in robot autonomous obstacle negotiation, this paper aims to propose an obstacle detection system based on elevation maps for three types of obstacles: positive obstacles, negative obstacles and trench obstacles.

The system framework includes mapping, ground segmentation, obstacle clustering and obstacle recognition. The positive obstacle detection is realized by calculating its minimum rectangle bounding boxes, which includes convex hull calculation, minimum area rectangle calculation and bounding box generation. The detection of negative obstacles and trench obstacles is implemented on the basis of information absence in the map, including obstacles discovery method and type confirmation method.

The obstacle detection system has been thoroughly tested in various environments. In the outdoor experiment, with an average speed of 22.2 ms, the system successfully detected obstacles with a 95% success rate, indicating the effectiveness of the detection algorithm. Moreover, the system’s error range for obstacle detection falls between 4% and 6.6%, meeting the necessary requirements for obstacle negotiation in the next stage.

This paper studies how to solve the obstacle detection problem when the robot obstacle negotiation.

This article explores the applicability of participatory action research (PAR) on two levels: on the one hand, as a participatory evaluation method for community engagement and community development; on the other hand, as a tool to link ex ante and ex-post evaluation that situated at various stages of the policy cycle.

Through a practice-based case study of the community engagement process of Valletta Design Cluster, this paper aims to illustrate how PAR can offer collaborative and continuous evaluation by facilitating social action through a practical, situative, context-bounded, responsive and transformative framework.

The study explores how PAR can contribute to cultural sustainability by linking community development with participatory evaluation, and it offers new perspectives on the applicability of PAR as a tool to link ex ante and ex-post evaluation, situated at various stages of the policy cycle.

Although based on a single case, the paper demonstrates that the method has the potential to be applied in various contexts, as it helps to foster local ownership and to develop future cultural strategies, thus providing a base for cultural sustainability.

The novelty of this study is to link evaluation – a majorly top-down and ex ante approach – with participatory planning. PAR-E offers a continuous participatory framework for the whole European Capitals of Culture (ECoC) cycle, as well as serving as a tool for empowerment and community development.

This paper aims to identify and prioritize the needs of coworking members. The authors focus on maintaining the existing members rather than attracting new ones.

The authors use two phases and multiple methods. The first phase focuses on a qualitative approach using observations and interviews to uncover and formulate the members’ needs. The second phase focuses on prioritizing the needs using a quantitative approach.

The authors discovered 19 member needs from the coworking spaces. Based on an online survey, the authors classified those needs into three main Kano model’s categories.

The resulting member needs and their strategic priorities provide a useful basis for coworking providers to direct their improvement efforts towards achieving greater member satisfaction.

This study aims to realize efficient, fast and safe robot search task, the belief criteria decision-making approach is proposed to solve the object search task with an uncertain location.

The study formulates the robot search task as a partially observable Markov decision process, uses the semantic information to evaluate the belief state and designs the belief criteria decision-making approach. A cost function considering a trade-off among belief state, path length and movement effort is modelled to select the next best location in path planning.

The semantic information is successfully modelled and propagated, which can represent the belief of finding object. The belief criteria decision-making (BCDM) approach is evaluated in both Gazebo simulation platform and physical experiments. Compared to greedy, uniform and random methods, the performance index of path length and execution time is superior by BCDM approach.

The prior knowledge of robot working environment, especially semantic information, can be used for path planning to achieve efficient task execution in path length and execution time. The modelling and updating of environment information can lead a promising research topic to realize a more intelligent decision-making method for object search task.