Designing Method Research Articles

Use of Design Thinking in Service Product Innovation Cabut Kost

The condition of the Covid-19 pandemic in Indonesia to date has had an impact on all business actors, therefore all actors from various business fields need to make a breakthrough or innovation in order to be able to compete and stay afloat. The problem now is that all must be required to provide appropriate problem solving and be able to be implemented properly in responding to all perceived obstacles and challenges. One of the methods that can be used and provide solutions to current conditions is design thinking. Design thinking is a discipline that uses designer sensibilities and methods to match people's needs with what is technologically feasible and what is feasible according to a business strategy can be transformed into customer value and market opportunities, by analyzing five stages which include empathize, define, ideate, prototypes and tests. The purpose of writing this article is to explain the use of design thinking in the Logistics Service business of Cabut Kost with a qualitative descriptive method with the aim of providing a description or summary of a situation or phenomenon that is currently happening by using scientific procedures to answer actual problems. The results obtained are that the application of design thinking can be used as a reference method for Cabut Kost in developing the business that is being undertaken. As far as the analysis is concerned, design thinking can be a method for developing a strategy to build a brand name for Cabut Kost.

Integrating ergonomics data and emotional scale to analyze people's emotional attachment to different landscape features in the Wudaokou Urban Park

Against the background of urban renewal, the landscape transformation of urban public space into urban parks has become an effective way of improving environmental quality and creating an emotional attachment for people. Meanwhile, existing studies have seldom adopted experimental methods to scientifically reveal the effect of different landscape features on emotional experience. Using a portable eye movement tracker, wearable wireless physiological sensor, and emotional attachment scale, this study collects participants’ ergonomics data, and their degree and dimension of emotional attachment while experiencing different landscape features in Wudaokou Park in Beijing, China. The data were analyzed with the help of ErgoLab platform and IBM SPSS software. The results indicate that the artificial and natural landscape features and their specific characteristics have different effects on eye movement index, heart rate variability, skin conductance level, and attachment degree and dimension. The design of Wudaokou Park was proven to significantly promote emotional attachment. Natural features play an important role, among which the use of wild plants and gazebos—showing the texture and structural logic of bamboo materials—stand out. The research not only expands the practical scope of ergonomics instruments and improves the rationality of the emotional attachment scale, but also provides emotion-oriented design methods for urban researchers and designers to improve the emotional experience in urban parks in the future.

Transmit beampattern design for joint radar-communications system with circulating code array

A new transmit beampattern design method is proposed for the joint radar-communications (JRC) systems with circulating code array. Each array element of the designed JRC system transmits the same basic waveform with different starting time, multiple beams towards the radar targets and the communication receivers are formed. For circulating code array, there is a certain relationship between the spectrum band of the transmitted signal and the coverage of the synthesized beampattern. By implementing spectrum planning according to the desired beampattern, flexible beampattern synthesis can be realized. Phase modulation term is attached to the phase of the transmitted signal in the corresponding communication spectrum band, and it is used to carry communication information. Unlike previous works, benefiting from the use of circulating coed array, multiple wide beams and narrow beams can be synthesized simultaneously in this paper without solving optimization problems. The effectiveness of the designed method is validated by numerical results.

Probabilistic landscape of seizure semiology localizing values.

Semiology describes the evolution of symptoms and signs during epileptic seizures and contributes to the evaluation of individuals with focal drug-resistant epilepsy for curative resection. Semiology varies in complexity from elementary sensorimotor seizures arising from primary cortex to complex behaviours and automatisms emerging from distributed cerebral networks. Detailed semiology interpreted by expert epileptologists may point towards the likely site of seizure onset, but this process is subjective. No study has captured the variances in semiological localizing values in a data-driven manner to allow objective and probabilistic determinations of implicated networks and nodes. We curated an open data set from the epilepsy literature, in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, linking semiology to hierarchical brain localizations. A total of 11 230 data points were collected from 4643 patients across 309 articles, labelled using ground truths (postoperative seizure-freedom, concordance of imaging and neurophysiology, and/or invasive EEG) and a designation method that distinguished between semiologies arising from a predefined cortical region and descriptions of neuroanatomical localizations responsible for generating a particular semiology. This allowed us to mitigate temporal lobe publication bias by filtering studies that preselected patients based on prior knowledge of their seizure foci. Using this data set, we describe the probabilistic landscape of semiological localizing values as forest plots at the resolution of seven major brain regions: temporal, frontal, cingulate, parietal, occipital, insula, and hypothalamus, and five temporal subregions. We evaluated the intrinsic value of any one semiology over all other ictal manifestations. For example, epigastric auras implicated the temporal lobe with 83% probability when not accounting for the publication bias that favoured temporal lobe epilepsies. Unbiased results for a prior distribution of cortical localizations revised the prevalence of temporal lobe epilepsies from 66% to 44%. Therefore, knowledge about the presence of epigastric auras updates localization to the temporal lobe with an odds ratio (OR) of 2.4 [CI95% (1.9, 2.9); and specifically, mesial temporal structures OR: 2.8 (2.3, 2.9)], attesting the value of epigastric auras. As a further example, although head version is thought to implicate the frontal lobes, it did not add localizing value compared with the prior distribution of cortical localizations [OR: 0.9 (0.7, 1.2)]. Objectification of the localizing values of the 12 most common semiologies provides a complementary view of brain dysfunction to that of lesion-deficit mappings, as instead of linking brain regions to phenotypic-deficits, semiological phenotypes are linked back to brain sources. This work enables coupling of seizure propagation with ictal manifestations, and clinical support algorithms for localizing seizure phenotypes.

A Nonlinear Vibration Compensation Method for Engineering Forging Hydraulic Press Using Tabu Search Algorithm

The research on the nonlinear vibration compensation method in the field of forging hydraulic press is still in the blank stage. This paper studies the nonlinear vibration compensation problem of forging hydraulic press under the action of a kind of nonlinear external system and realizes the increase of a kind of nonlinear vibration in the nonlinear system of a hydraulic press. This paper proposes two methods to solve the nonlinear relationship. One is to concatenate an inverse function of a nonlinear relationship and synthesize it to obtain a linear relationship. While another is to acknowledge its nonlinear relationship and determine its output based on its nonlinear relationship. Furthermore, this paper chooses the tabu search algorithm to solve the compensation problem of nonlinear vibration and improves its search neighborhood to solve the problem of vibration range selection, analyses the vibration reinforcement calculation, and describes the specific steps of applying the tabu search algorithm. Finally, MATLAB is used to simulate and validate the designed method. The simulation results show that the method can suppress nonlinear vibration and the corresponding compensation effectiveness, proving the design method’s rationality.

Fuzzy Sliding Mode Control for Microbial Fuel Cells

The microbial fuel cells (MFCs) are a kind of green energy with good prospects, which provides an effective solution to the problem of unsustainable development of energy today. Aiming at the problem that MFCs are susceptible to various external disturbances, a sliding mode (SM) controller for MFCs is designed in this paper. The controller can effectively reduce the influence of external disturbance on voltage output and improve the practicability of microbial fuel cells (MFC). At the same time, aiming at the chattering problem of the basic SM control, a fuzzy sliding mode (FSM) control method is proposed by combining the fuzzy logic theory and the SM control. The design method of FSM controller is given by using Lyapunov theory. The method can adaptively adjust the parameters according to the difference between the actual value of the substrate concentration and the set value. The controller can reduce the system input chattering and the influence of external disturbances on the system output. Simulation results show that compared with SM control and backstepping control, the designed method has smaller steady-state error and overshoot.

The interaction of clothing design factors: how to attract consumers' visual attention and enhance emotional experience

PurposeThis paper aims to study consumers’ visual attention and emotional experience with clothing design factors and their combinations from the perspective of cognition and emotion and propose an interaction phenomenon to evaluate the combined effect of clothing factors to better guide online clothing design and sales.Design/methodology/approachAn eye movement physiology experiment was conducted, 33 participants screened by questionnaires were invited for this experiment. Hypotheses of visual attention were verified by the FIRST_FIXATION_TIME indicator, DWELL_TIME indicator and FIXATION_COUNT indicator. Hypotheses of emotional experience were verified by the PUPIL_SIZE indicator.FindingsFirst, on the product list page, it is better to use only the three factors of clothing and a small number of stimulating factors. Second, when the stimulus is consistent with the cognitive task performed by the consumer, the efficiency of the task and the consumer's user experience will be improved. Third, the positive interaction phenomenon of clothing design factors and their combinations could significantly attract consumers' visual attention and improve their emotional experience.Research limitations/implicationsThis work argues consumer interest and emotional experience with online clothing can be expressed through eye movement physiological indicators, and the concept of interaction was proposed to evaluate the design and display of online clothing.Originality/valueThis paper conducted interaction research on online clothing design factors and their combinations from the perspective of cognition and emotion, which provided an objective quantitative method for online clothing designers and online clothing retailers.

Classifying High Strength Concrete Mix Design Methods Using Decision Trees.

Concrete mix design methods are used to determine proportions of concrete ingredients needed for certain workability and strength. Each mix design method operates under certain assumptions and suggests slightly different proportions. It is of great importance that site/construction engineers know the method by which the mix was designed. However, it can be difficult to know the designing method based solely on mix proportions. Hence, in this work, a decision trees model was used to classify high strength concrete mix design methods based on their produced concrete mix proportions. It was found that the trained decision tree model is capable of classifying mix design methods with high accuracy. Further, based on dimensionality reduction methods, the amount of cement in a concrete mix was found to be the paramount predictor of the used mix design method. In this work, a novel high-accuracy model for determining a mix design method based only on mix proportion is proposed.

A gain‐tuning method for almost disturbance decoupling problems of nonlinear systems with zero dynamics

AbstractIn this paper, a gain‐tuning method for almost disturbance decoupling problems of nonlinear systems with zero dynamics is developed. Firstly, a linear subsystem is formed by linearizing the nonlinear system. Then, a linear matrix inequality can be formed for the linear subsystem. After that, a linear state‐feedback controller can be obtained by solving the linear matrix inequality. A nonlinear state‐feedback controller can be obtained for the original nonlinear system by using backstepping design method. Another linear state‐feedback controller can be derived by linearizing the nonlinear state‐feedback controller. Finally, the backstepping gains can be solved by equating the two linear controllers. The detailed derivations of the method are provided. Some comparisons with the existing techniques are discussed. Moreover, the designed method is verified by simulations and some comparisons are made accordingly.

Finite-Time Bound Synchronization of the New Chaotic System With Energy Consumption Estimation

As chaotic systems are widely used in many fields, the study of them is becoming more and more in-depth. This paper first presents a new single-equilibrium chaotic system which is only three terms, and some fundamental dynamical feature of the new chaotic system are discussed, such as equilibria, dissipativity, Poincaré diagram, bifurcation graph, etc. Secondly, a new finite-time controllers is designed by using Lyapunov stability theory, and it can be used for bound synchronization of the general chaotic systems. In contrast to the current finite time controller of the chaotic system, the designed controller in this paper does not contain exponential term, it can be simple and eliminate the chattering phenomenon during synchronizationis, which may be easier to implement in practical application. In addition, under the finite time controller, the bound of control energy consumption of the chaotic system is estimated. Finally, the finite-time controllers for the new chaotic system are advanced using the design method of finite-time controller of the general chaotic system, and the result of numerical simulation is given to check its validity by the designed method.

Structural form-finding of bending components in buildings by using parametric tools and principal stress lines

This paper aims to provide an efficient and straightforward structural form-finding method for designers to extrapolate component forms during the conceptual stage. The core idea is to optimize the classical method of structural form-finding based on principal stress lines by using parametric tools. The traditional operating process of this method relies excessively on the designer's engineering experience and lacks precision. Meanwhile, the current optimization work for this method is overly complicated for architects, and limitations in component type and final result exist. Therefore, to facilitate an architect's conceptual work, the optimization metrics of the method in this paper are set as simplicity, practicality, freedom, and rapid feedback. For that reason, this paper optimizes the method from three aspects: modeling strategy for continuum structures, classification processing of data by using the k-nearest neighbor algorithm, and topological form-finding process based on stress lines. Eventually, it allows architects to create structural texture with formal aesthetics and modify it in real time on the basis of structural analysis results. This paper also explores a comprehensive application strategy with internal force analysis diagramming to form-finding. The finite element analysis tool Karamba3D verifies the structural performance of the form-finding method. The performance is compared with that of the conventional form, and the comparison results show the practicality and potential of the strategy in this paper.

Nanomembrane folding origami: Geometry control and micro-machine applications

Three-dimensional (3D) microstructures have important applications in a wide range of engineering fields. A strategy of nanomembrane folding origami with microdroplet-guided intercalation and strain engineering to construct complex 3D microstructures for micro-machine applications is proposed in the present investigation. The results showed that nanomembranes were released by the microdroplet intercalation and subsequently fold up as creases, or remain flat as facets, depending on the strain design configurations. The 3D geometry can be controlled by the crease design and by an externally applied magnetic field. Moreover, this folding strategy is used to construct magnetic micro-mirror arrays, magnetic micro-robots, and a twin-jet motor platform, showing potential micro-machine applications in optical micro-devices and robotics. This strategy offers a simple, precise, and designable method of folding 3D microstructures for fundamental research and practical applications.

Development of a real-time RT-PCR assay for the detection of pan-human parechoviruses

BackgroundParechoviruses (PeV-As), which constitute a new genus within the family Picornaviridae, have been associated with numerous localized outbreaks of serious diseases, such as coryza, pneumonia, maculopapular exanthem, and conjunctivitis. However, to the best of our knowledge, only a few laboratories worldwide conduct tests for the identification of this group of viruses. Therefore, in this study, we aimed to develop and validate a real-time RT-PCR assay for the identification of PeV-As.MethodsTo design and validate a real-time PCR primer–probe targeting the 5′-UTR region of PeV-As, the 5′-UTR sequences of PeV-As available in GenBank were aligned using the MUSCLE algorithm in MEGA v7.0. Thereafter, the highly conserved 5′-UTR region was selected, and its primer–probe sequence was designed using Primer Premier v5.0. This primer–probe sequence was then evaluated for specificity, sensitivity, and repeatability, and for its validation, it was tested using fecal samples from 728 healthy children living in Beijing (China).ResultsThe PeV-A real-time RT-PCR assay detected only the RNA-positive standards of PeV-A genotypes (1–8, 14, 17, and 18), whereas 72 serotypes of non-PeV-A EV viruses were undetected. In addition, the VP1 region of these 11 PeV-A genotypes that tested positive were amplified using the primers designed in this study. Typing results indicated that eight, one, and two strains of the 11 were PeV-A1, PeV-A4, and PeV-A6, respectively. We also determined and presented the genetic characterization and phylogenetic analyses results corresponding to these 11 VP1 region sequences. Furthermore, real-time RT-PCR assay showed good sensitivity with LOD of 102 copies/μL. Positive results in eight parallel experiments at each concentration gradient from 107 copies/μL to 102 copies/μL, indicating good repeatability.ConclusionOur findings suggested that the real-time RT-PCR assay developed in this study can be applied for routine PeV-A identification. We detected PeV-A1, 4 and 6 genotypes in the 728 faecal samples using this method. Additionally, we believe that our results will serve as a foundation for further studies on PeV-As and facilitate the expansion of the gene sequence information available in GenBank.

The impact of rainfall distribution methods on streamflow throughout multiple elevations in the Rocky Mountains using the APEX model-Price River watershed, Utah.

The hydrology of mountainous watersheds in the western United States is significantly influenced by snow year-round. It is widely known that topography affects precipitation; however, the knowledge of how watershed rainfall designation methods affect streamflow is not well understood for high-relief areas. The objectives of this study were to assess the predictive capability of the Agricultural Policy/Environmental eXtender (APEX) model to simulate streamflow in a snowmelt-dominated watershed with high spatial rainfall variability through (a) allocating weather stations to sub-basins based on a conventional Thiessen polygon method (CM) or a rainfall-elevation-based input (RE) and using an areal average Parameter-Elevation Regression on Independent Slopes Model (PRISM) rainfall designation and (b) improving the snowmelt processes in the Price River watershed, Utah. The updated APEX model with snowmelt parameters significantly improved spring flood simulation. The RE was the most robust method in snowmelt and seasonal streamflow simulations compared with the CM and PRISM rainfall designations. Adapting the APEX model to simulate snow-dominant complex terrains will provide crucial water quantity and quality predictions for reliable environmental and watershed management assessment.

A novel design approach and ergonomic evaluation of Class I compression legging

PurposeThe conception of a compression garment that applies a desired interface pressure level has been a great challenge for therapists and compression garment manufacturers even today. The purpose of this study is to develop a new method for designing a compression legging that exerts Class I interface pressure to the lower limb.Design/methodology/approachThis research presents a new method for the design of Class I compression garment. It consists of theoretically calculating the circumferences of the Class I compression legging based on the reduction factors. To assess the effectiveness of the method, we used both objective and subjective evaluations. For the objective evaluation, we have developed a measuring device to measure Class I legging interface pressure in different measuring points using a force pressure sensor. Concerning the subjective evaluation, 10 healthy female subjects agreed to take part in this study in order to evaluate the ergonomic comfort when wearing the designed compression legging.FindingsParticipating subjects delivered their feeling about comfort and motion restriction during the use of the legging. Referring to the volunteers’ answers, the Class I compression legging can be described as comfortable and has a satisfactory fit during wear.Originality/valueThe important feature of this study was the effectiveness of the new designing method in producing a compression legging that delivers the desired amount of pressure and offers a comfort sensation during wear. The outcome of this research is a new method that could be used to create a variety of compression garments that can apply different pressure levels.

Design thinking as sensemaking: Developing a pragmatist theory of practice to (re)introduce sensibility

AbstractDesign thinking is based on designers’ creative ways of working and is defined as a formal method for creative problem solving aimed at fostering innovation by harnessing “the designer's sensibility and methods.” The basic premise is that design “thinking” can be extracted and separated from the situated practice of designing in the studio. This approach has given rise to a widely accepted nomenclature for describing design which has improved communication between designers and managers, leading to massive interest in adoption of design thinking in management settings. However, due to a widespread implicit cognitivism in the literature, scholars find it difficult to explain the cultural and experiential qualities of design thinking and it tends to be presented as a fundamentally cognitive, problem‐solving activity. We argue that these cognitivist tendencies preclude proper attention to and theorization of designers’ creative practice. We contend that the absence of a theory of practice prevents a deeper understanding of the contribution of design thinking to innovation, loses sight of the sensibility on which it relies, and hampers realization of the promise of design thinking. We develop an alternative theoretical perspective, grounded in a pragmatist theory of practice and the studio culture from which designers’ creative practice developed. This theoretical perspective allows design thinking to be understood as sensemaking, foregrounds imagination and improvisation as its core activities, and explains how sensibility is developed and nurtured. We review the design thinking literature through this pragmatist lens and discuss the implications for theory and practice of conceptualizing design thinking as sensemaking.

Experimental demonstration and optimization of X-ray StaticCodeCT.

As the use of X-ray computed tomography (CT) grows in medical diagnosis, so does the concern for the harm a radiation dose can cause and the biological risks it represents. StaticCodeCT is a new low-dose imaging architecture that uses a single-static coded aperture (CA) in a CT gantry. It exploits the highly correlated data in the projection domain to estimate the unobserved measurements on the detector. We previously analyzed the StaticCodeCT system by emulating the effect of the coded mask on experimental CT data. In contrast, this manuscript presents test-bed reconstructions using an experimental cone-beam X-ray CT system with a CA holder. We analyzed the reconstruction quality using three different techniques to manufacture the CAs: metal additive manufacturing, cold casting, and ceramic additive manufacturing. Furthermore, we propose an optimization method to design the CA pattern based on the algorithm developed for the measurement estimation. The obtained results point to the possibility of the real deployment of StaticCodeCT systems in practice.

A Pattern Approach to Comprehensible and Pleasant Human–Robot Interaction

HRI designers are faced with the task of creating robots that are easy and pleasant to use for the users. The growing body of research in human–robot interaction (HRI) is still mainly focused on technical aspects of the interaction. It lacks defined guidelines that describe how behavioral expressions for social robots need to be designed to promote high usability and positive user experience. To achieve this goal, we propose to apply the concept of design patterns to HRI. We present a design process that provides step-by-step guidance and methods for HRI designers to generate high quality behavioral patterns for social robots that can be used for different robots and use cases. To document the resulting patterns, we developed a documentation format that provides a clear, standardized structure to note down all relevant aspects of a pattern so that others can understand its design recommendations and apply them to their own robot and use cases. In the present paper, we demonstrate our pattern approach based on an example and describe how we arrived at a pattern language of 40 behavioral patterns that found the basis for future social robot design and related research activities.

Integrated ion exchange-based system for nitrate and sulfate removal from water of different matrices: Analysis and optimization using response surface methodology and Taguchi experimental design techniques

Although sequestering nitrate by anion exchange resins (AERs) is a proven and well-established technology, many process problems and challenges still exist, such as interference, nitrate dumping, total dissolved solids (TDS) limitations, brine waste disposal, etc. An engineered-integrated approach was devised and assessed to mitigate such limitations. The overall process optimization was based on screening, analyzing, and optimizing each respective step. A front-end sulfate removal step was suggested, evaluated, which yielded removal efficiencies >95%. Back-end options were also introduced, including reduced brine and brine wastes, recycling possibility, and usage as mixed-fertilizer with a NO3/Cl ratio of 0.65 as confirmed by mass balance calculations. Taguchi robust designs (TRD), Box-Behnken Designs (BBD), and central composite design (CCD) experimental design methods were used, enabling information mining from a minimum number of experiments. A one-factor-at-a-time strategy was applied and the regeneration process was optimized using TRD. Response analysis and regression revealed that acid concentration and volume are the most influential factors. Selectivity order was determined as SO42-->Cl−>HCO3− according to their relative coefficients of the BBD and CCD regression models. Field trials confirmed the robustness and viability of the proposed integrated approach. A process flow diagram was devised. Merits of the proposed system include: a) possible resolution of sulfate competition and nitrate dumping, b) elimination of brine waste problems, c) tolerate higher TDS levels than ever possible for AERs, d) improved economics, e) improved process robustness, f) mitigate the corrosiveness of produced water, and g) fulfilling zero liquid discharge criteria.

A generative architectural and urban design method through artificial neural networks

Machine learning, as a computational tool for finding mappings between the input and output data, has been widely used in engineering fields. Researchers have applied machine learning models to generate 2D drawings with pixels or 3D models with voxels, but the pixelization reduces the precision of the geometries. Therefore, in order to learn and generate 3D geometries as vectorized models with higher precision and faster computation speed, we develop a specific artificial neural network, learning and generating design features for the forms of buildings. A customized data structure with feature parameters is constructed, meeting the requirements of the neural network by rebuilding surfaces with controlling points and appending additional input neurons as quantified vectors to describe the properties of the design. The neural network is first trained with generated design data and then tested by adjusting the feature parameters. The prediction of the generated data shows the basic generative ability of the neural network. Furthermore, trained with design data collected from existing buildings, the neural network learns and infers the geometric design features of architectural design with different feature parameters, providing a data-driven method for designers to generate and analyze architectural forms.