Multiple Obstacles Research Articles

Management of Bone Marrow Transplants in Incarcerated Patients with Plasma Cell Dyscrasias: A Case Series

Background The U.S.' incarcerated population aged 55 years or older is expected to increase to 400,000 by 2030. This aging population faces intensifying health issues, including an increase in cancer diagnosis rates without adequate healthcare infrastructure and access. Studies show that individuals who received a cancer diagnosis while incarcerated, or within one year of release, had higher rates of cancer-related and all-cause mortality, compared to the general population. Our research seeks to assess how a cohort of patients with plasma cell dyscrasias (myeloma, amyloidosis, plasma cell leukemia) were treated and managed while incarcerated. Methods We performed a retrospective chart review of three patients with plasma cell dyscrasias in the incarcerated population who have undergone bone marrow transplants. Patients' disease characteristics, treatment sequences and details, and clinical outcomes were described qualitatively. Results Case 1: a 48-year-old Black man diagnosed with multiple myeloma in 2019. He was treated with 5 cycles of CyBorD at an outside hospital and had a favorable response. Stem cells were collected but never transplanted and patient was lost to follow-up due to incarceration. In April 2021, he presented to us with bilateral lower extremity paralysis and difficulty walking while in prison. He received emergent radiation to spine, then underwent both DCEP and VDPAC. The patient was discharged for physical rehabilitation in prison with ixazomib maintenance and monthly lab work. 6 months later, he was sent to another outside hospital with acute renal failure and then transferred to us. He demonstrated relapsed myeloma, received DV-AC, and was discharged back to prison while we awaited banked stem cells from 2019. He was admitted a month later for melphalan and auto-SCT, which was well-tolerated. We were ultimately able to arrange lenalidomide maintenance with prison. Case 2: a 65-year-old Black man with abnormal cardiac imaging and lymph node biopsy concerning for amyloid in 2020 while in prison. No treatment was given at the time. In 2021, an outside hospital conducted a bone marrow biopsy showing monoclonal plasma cells consistent with primary amyloidosis. 3 months later, the patient began CyBorD but completed subsequent cycles at another outside hospital. Correctional authorities indicated transplant would ultimately need to occur at our facility. Patient began stem cell mobilization and was admitted to us for melphalan and auto-SCT in March 2022. Patient was discharged back to corrections but there was a delay in acquiring lenalidomide for maintenance therapy, which was not started until August 2022. Case 3: a 44-year-old Black man was diagnosed with plasma cell leukemia in 2009. That year, he received an auto-SCT and then an allo-SCT from his HLA-matched sister at an outside hospital. In 2016, he received radiation for a large mass in his brain, as well as lenalidomide and dexamethasone. Since then, records indicate limited follow-up until he presented to us in 2022 with leg pain and imaging showing progressing myeloma while in prison. He was given 1 cycle of DCEP, was discharged back to a correctional facility, and subsequently refused 2 nd cycle. He sought a second opinion from an outside hospital for CAR-T therapy but was told eligibility required failure of daratumumab. In January 2023, he was offered Dara-Pom-Dex-Carfilzomib though declined the pomalidomide portion. He has responded well and is continuing maintenance. The CAR-T center offered to see him for treatment if he progresses on this regimen. Discussion Our research suggests that incarcerated patients face multiple obstacles that delay or hinder treatment, including siloed care, poor record-keeping, lack of follow-up, and difficulty obtaining appropriate medications. All three patients were frequently transferred between correctional facilities, outside hospitals, and our institution, which led to incomplete records. Additionally, patients went months or even years without follow-up monitoring after initial treatment and would often re-enter the healthcare system only upon presenting with severe symptoms from relapsed disease. Correctional facilities faced issues procuring expensive medications only available through restricted distribution programs. Further analysis is warranted to understand the generalizability of our results and identify solutions to support this population.

Joy, Compassion, and Job Satisfaction: Insights into the Canadian Prison Chaplaincy.

This paper presents an exploratory study about the experiences of 25 inter-faith chaplains in five Canadian provinces. It utilizes a focus groups methodology. The goal of this qualitative research was to highlight the voices of the chaplains. Hence, the focus groups explored the unique and challenging experiences of chaplains' work in Canadian prisons. Data from all seven focus groups indicated that despite multiple challenges and obstacles, the correctional chaplains remain dedicated to their work and are committed to making a positive impact on their prisoners. Based on the data provided by the chaplains about the intrinsic rewards and various challenges they face in their day-to-day work, the paper makes several research and policy recommendations. The objective of such recommendations is to maximize the role that religion and/or spirituality could play in prisoners' positive adaptation, and eventual criminal desistance in a context of confinement characterized by loss of personal autonomy and self-identity.

A path planning algorithm for three-dimensional collision avoidance based on potential field and B-spline boundary curve

Path planning is one of the key technologies in unmanned aerial systems. The path-planning algorithm for UAVs in this study incorporates a three-dimensional obstacle model, addressing the limitations of existing research that primarily focuses on the two-dimensional plane. This approach elevates traditional two-dimensional obstacle constraints to a three-dimensional space, fulfilling the requirements for precise obstacle avoidance. Utilizing B-spline curves, an obstacle boundary model is proposed, which, in combination with an improved artificial potential field accounting for localized self-locking oscillations, achieves smooth path planning for obstacle avoidance from the starting point to the destination. The simulation results show the effectiveness of this method in collision-free path planning within three-dimensional environments containing static single or multiple obstacles. At the points of maximum curvature in the two-dimensional coordinate system, the path planned by the proposed algorithm exhibits a smoothness improvement of 68 % and 98 %, respectively, as compared to the traditional artificial potential field algorithm with the equivalent three-dimensional obstacle model and the tangent point method. The proposed algorithm enables drones to achieve precise obstacle avoidance along surfaces, generating smoother collision-free flight paths in a shorter period of time.

A Dynamic Path-Planning Method for Obstacle Avoidance Based on the Driving Safety Field.

Establishing an accurate and computationally efficient model for driving risk assessment, considering the influence of vehicle motion state and kinematic characteristics on path planning, is crucial for generating safe, comfortable, and easily trackable obstacle avoidance paths. To address this topic, this paper proposes a novel dual-layered dynamic path-planning method for obstacle avoidance based on the driving safety field (DSF). The contributions of the proposed approach lie in its ability to address the challenges of accurately modeling driving risk, efficient path smoothing and adaptability to vehicle kinematic characteristics, and providing collision-free, curvature-continuous, and adaptable obstacle avoidance paths. In the upper layer, a comprehensive driving safety field is constructed, composed of a potential field generated by static obstacles, a kinetic field generated by dynamic obstacles, a potential field generated by lane boundaries, and a driving field generated by the target position. By analyzing the virtual field forces exerted on the ego vehicle within the comprehensive driving safety field, the resultant force direction is utilized as guidance for the vehicle's forward motion. This generates an initial obstacle avoidance path that satisfies the vehicle's kinematic and dynamic constraints. In the lower layer, the problem of path smoothing is transformed into a standard quadratic programming (QP) form. By optimizing discrete waypoints and fitting polynomial curves, a curvature-continuous and smooth path is obtained. Simulation results demonstrate that our proposed path-planning algorithm outperforms the method based on the improved artificial potential field (APF). It not only generates collision-free and curvature-continuous paths but also significantly reduces parameters such as path curvature (reduced by 62.29% to 87.32%), curvature variation rate, and heading angle (reduced by 34.11% to 72.06%). Furthermore, our algorithm dynamically adjusts the starting position of the obstacle avoidance maneuver based on the vehicle's motion state. As the relative velocity between the ego vehicle and the obstacle vehicle increases, the starting position of the obstacle avoidance path is adjusted accordingly, enabling the proactive avoidance of stationary or moving single and multiple obstacles. The proposed method satisfies the requirements of obstacle avoidance safety, comfort, and stability for intelligent vehicles in complex environments.

A task level fusion autonomous switching mechanism.

Positioning technology is an important component of environmental perception. It is also the basis for autonomous decision-making and motion control of firefighting robots. However, some issues such as positioning in indoor scenarios still remain inherent challenges. The positioning accuracy of the fire emergency reaction dispatching (FERD) system is far from adequate to support some applications for firefighting and rescue in indoor scenarios with multiple obstacles. To solve this problem, this paper proposes a fusion module based on the Blackboard architecture. This module aims to improve the positioning accuracy of a single sensor of the unmanned vehicles within the FERD system. To reduce the risk of autonomous decision-making of the unmanned vehicles, this module uses a comprehensive manner of multiple channels to complement or correct the positioning of the firefighting robots. Specifically, this module has been developed to fusion a variety of relevant processes for precise positioning. This process mainly includes six strategies. These strategies are the denoising, spatial alignment, confidence degree update, observation filtering, data fusion, and fusion decision. These strategies merge with the current scenarios-related parameter data, empirical data on sensor errors, and information to form a series of norms. This paper then proceeds to gain experience data with the confidence degree, error of different sensors, and timeliness of this module by training in an indoor scenario with multiple obstacles. This process is from data of multiple sensors (bottom-level) to control decisions knowledge-based (up-level). This process can obtain globally optimal positioning results. Finally, this paper evaluates the performance of this fusion module for the FERD system. The experimental results show that this fusion module can effectively improve positioning accuracy in an indoor scenario with multiple obstacles. Code is available at https://github.com/lvbingyu-zeze/gopath/tree/master.

Research on the Problems and Strategies of Delegation Management in a Cross-Cultural Context The Case of the University of Sydney

This paper focuses on the decision of a manager or supervisor to delegate a task or responsibility to one or more employees as delegation, or DOA for short; It also focuses on the influence of globalization on the workplace empowerment system and proposes that a mixed cultural environment, the authority of leaders is not only based on actual ability but also on subjective cognitive decision-making. Globalization has made technological skills available to the international market, and governments and non-profit organizations need to establish cross-cultural empowerment systems to promote the growth of different groups. In this context, implementing mandates faces multiple obstacles, such as discrimination and stereotypes based on gender, race, and ethnicity. The impact of discrimination will be examined by data from the Pew Research Centers 2019 Race in America report. This article will compare real-world case studies to weigh the pros and cons of cross-cultural empowerment. Second, make recommendations based on generally accepted views of cultural influence and individual agency. In addition, this paper also discusses the characteristics of the situational leadership model, the third culture, and Hofstedes cultural dimension theory as its foundation. In this papers case study of China Europe International Business School in Shanghai, a significant conflict between different cultures occurred. Based on the situational leadership model, the third culture, and Hofstedes theory of cultural dimensions, to solve the problems of distrust and language barriers in communication, using a third language can effectively alleviate possible conflicts.

Multifunctional Hydrogels Based on Cellulose and Modified Lignin for Advanced Wounds Management.

Considering the complex process of wound healing, it is expected that an optimal wound dressing should be able to overcome the multiple obstacles that can be encountered in the wound healing process. An ideal dressing should be biocompatible, biodegradable and able to maintain moisture, as well as allow the removal of exudate, have antibacterial properties, protect the wound from pathogens and promote wound healing. Starting from this desideratum, we intended to design a multifunctional hydrogel that would present good biocompatibility, the ability to provide a favorable environment for wound healing, antibacterial properties, and also, the capacity to release drugs in a controlled manner. In the preparation of hydrogels, two natural polymers were used, cellulose (C) and chemically modified lignin (LE), which were chemically cross-linked in the presence of epichlorohydrin. The structural and morphological characterization of CLE hydrogels was performed by ATR-FTIR spectroscopy and scanning electron microscopy (SEM), respectively. In addition, the degree of swelling of CLE hydrogels, the incorporation/release kinetics of procaine hydrochloride (PrHy), and their cytotoxicity and antibacterial properties were investigated. The rheological characterization, mechanical properties and mucoadhesion assessment completed the study of CLE hydrogels. The obtained results show that CLE hydrogels have an increased degree of swelling compared to cellulose-based hydrogel, a better capacity to encapsulate PrHy and to control the release of the drug, as well as antibacterial properties and improved mucoadhesion. All these characteristics highlight that the addition of LE to the cellulose matrix has a positive impact on the properties of CLE hydrogels, confirming that these hydrogels can be considered as potential candidates for applications as oral wound dressings.

The integration of palliative care with oncology: the path ahead.

The delivery of comprehensive cancer care within a progressively intricate healthcare environment requires oncology providers to become well-versed in the integration of palliative care (PC). Moreover, as healthcare professionals are urged to prioritize the individual preferences of patients and their families who confront life-limiting illnesses, it has become evident that oncology patients and their families have identified their psychosocial care needs as multifaceted and distinct, calling for specialized attention from care providers. Nevertheless, this is a skill that can be acquired through learning and practice. The landscape of PC is rapidly changing, with paradigm shifting studies highlighting the importance of early concurrent palliative and oncology inpatient and outpatient care for those with new advanced cancer diagnosis. Early concurrent care can notably improve quality of life (QoL), symptom control, patient and caregiver satisfaction, reduce costs and even improve survival. There is no longer a question of if PC should be offered, but instead when referral should be completed, what is the optimal model for service delivery and what barriers are present to achieve concurrent care. Conceptual models have been identified for optimal integrated palliative and oncology care delivery. In order to provide the best integrated care however, multiple obstacles need to be overcome. This narrative review discusses the importance of early integrated oncology and PC for patients with advanced cancer diagnosis, as well as the barriers to the integration of these specialties and potential models for delivery.

A rapid evidence assessment of barriers and strategies in service engagement when working with young people with complex needs

Young people with complex needs often have a range of co-occurring challenges that require the support of multiple government agencies and services. Increasingly, government agencies are working with young people who present with co-occurring and comorbid complex needs requiring co-ordinated multi-agency responses. However, agencies and services are often faced with multiple obstacles and challenges to meeting the needs of these young people, placing them at increased risk of poor outcomes during their adolescence and into adulthood. The objective of this Rapid Evidence Assessment (REA) was to provide practice insights as they relate to service engagement for young people with complex needs to highlight ways in which service delivery can be enhanced. Published academic literature as well as relevant material from the grey literature on young people aged 10–25 was synthesized to identify: (a) the principal barriers to service provision, and (b) strategies that facilitate service engagement. A total of 18 papers met the eligibility criteria for review. Papers were assessed using the critical appraisal skills programme (CASP). Individual and system level barriers were identified, including the characteristics of young people and the nature and structure of services. Strategies were identified at the practitioner level (e.g., benefits of relational, structural and empowerment approaches), and the system level (e.g., flexible services, collaborative approaches and improved staffing and resources). The review highlighted the importance of creating a service environment that is structured around the needs of young people rather than one which requires vulnerable young people to adapt to services.

DUEL: Depth visUal Ego-motion Learning for autonomous robot obstacle avoidance

Reliable obstacle avoidance, which is essential for safe autonomous robot interaction with the real world, raises various challenges such as difficulties with obstacle perception and latent factor cognition impacting multi-modal obstacle avoidance. In this paper, we propose a Depth visUal Ego-motion Learning (DUEL) model, consisting of a cognitive generation network, a policy decision network and a potential partition network, to learn autonomous obstacle avoidance from expert policies. The DUEL model takes advantage of binocular vision to perceive scene depth. This serves as the input to the cognitive generation network which generates obstacle avoidance policies by maximizing its causal entropy. The policy decision network then optimizes the generation of the policies referring to expert policies. The generated obstacle avoidance policies are simultaneously transferred to the potential partition network to capture the latent factors contained within expert policies and perform multi-modal obstacle avoidance. These three core networks iteratively optimize the multi-modal policies relying on causal entropy and mutual information theorems, which are proven theoretically. Experimental comparisons with state-of-the-art models on 7 metrics demonstrate the effectiveness of the DUEL model. It achieves the best performance with an average ADE (Average Displacement Error) of 0.29 and average FDE (Final Displacement Error) of 0.55 across five different scenarios. Results show that the DUEL model can maintain an average obstacle avoidance success rate of 97% for both simulated and real world scenarios with multiple obstacles, demonstrating its success at capturing latent factors from expert policies. Our source codes are available at https://github.com/ACoTAI/DUEL.

Hardware Implementation of Ultra‐Fast Obstacle Avoidance Based on a Single Photonic Spiking Neuron

AbstractVisual obstacle avoidance is widely applied to unmanned aerial vehicles (UAVs) and mobile robot fields. A simple system architecture, low power consumption, optimized processing, and real‐time performance are extremely needed due to the limited payload of some mini UAVs. To address these issues, an obstacle avoidance system harnessing the rate encoding features of a photonic spiking neuron based on a Fabry–Pérot (FP) laser is proposed, which simulates the monocular vision. Here, time to collision is used to describe the distance of obstacles. The experimental results show that the FP laser excites ultra‐fast spike responses in real time for the following cases, facilitating the generation of control commands by motor neurons to realize accurate decision‐making. Four cases of mobile obstacle avoidance scenarios, including “Constant velocity approach”, “Approach and retreat”, “The motion state involving stays”, and “Approach with different velocities”, and obstacle avoidance problems with multiple stationary obstacles appearing simultaneously are experimentally analyzed. The system exhibits a spike response rate of up to 5 GHz. This work proves the feasibility of applying the ultra‐fast photonic obstacle avoidance system to UAVs and other fields in the future and highlights the potential of photonic neuromorphic processor platforms.

Depth-based Sampling and Steering Constraints for Memoryless Local Planners

By utilizing only depth information, the paper introduces a novel two-stage planning approach that enhances computational efficiency and planning performances for memoryless local planners. First, a depth-based sampling technique is proposed to identify and eliminate a specific type of in-collision trajectories among sampled candidates. Specifically, all trajectories that have obscured endpoints are found through querying the depth values and will then be excluded from the sampled set, which can significantly reduce the computational workload required in collision checking. Subsequently, we apply a tailored local planning algorithm that employs a direction cost function and a depth-based steering mechanism to prevent the robot from being trapped in local minima. Our planning algorithm is theoretically proven to be complete in convex obstacle scenarios. To validate the effectiveness of our DEpth-based both Sampling and Steering (DESS) approaches, we conducted experiments in simulated environments where a quadrotor flew through cluttered regions with multiple various-sized obstacles. The experimental results show that DESS significantly reduces computation time in local planning compared to the uniform sampling method, resulting in the planned trajectory with a lower minimized cost. More importantly, our success rates for navigation to different destinations in testing scenarios are improved considerably compared to the fixed-yawing approach.

Hybrid conservative central/WENO finite difference scheme for two-dimensional detonation problems

In the present work, a hybrid finite difference scheme is proposed and tested for the study of two-dimensional detonation problems. The hybrid scheme consists of a fifth-order weighted essentially nonoscillatory (WENO) method for discontinuous regions and a fourth or sixth-order robust conservative central finite difference scheme for the remaining domain. An arbitrary shock sensor is used to identify the discontinuities. The proposed shock sensor is based on the absolute value of the density gradient with an arbitrary threshold computed at each time step using a fast image segmentation technique. The sensor is complemented with a Ducros sensor to avoid the selection of vortices as discontinuities. The hybrid scheme is tested for several benchmark examples, including a two-dimensional transverse detonation wave, detonation wave diffraction, and a multiple obstacles test case. The obtained results show that the proposed sensor detects discontinuities adequately and the hybrid schemes give the same results as the fifth-order WENO in faster computational time.

Identifying and approaching for obscured stairs

We present an autonomous approaching scheme for mobile robot traversing obstacle stairwells, which overcomes the restricted field of vision caused by obstacles. The scheme consists of three parts: stair localization, structural parameter estimation, and nearing the stair. We use LIDAR with full-angle and long-distance measurement capabilities to initially determine the location of the stairs, and estimate staircase parameters using a depth camera with intensive data. Then, we propose an algorithm to optimize the location of stairs for real-time correction of target point locations during approaching. Finally, we conducted tests to verify the accuracy of the estimated stair positions and structural parameters and performed a comprehensive experiment to demonstrate the effectiveness of the scheme, in which the robot approaches autonomously to the front of the stairs around multiple obstacles.

Acoustic reflector utilizing sound speed control by multiple obstacles

Acoustic diffusers have a structure that diffuses sound waves in various directions by utilizing the interference of sound waves caused by surface irregularities. For example, a phase diffraction grating based on number theory has a structure with equally spaced depressions of irregular depth, and the maximum difference between the depressions is half the target wavelength. If the reflector targets 500 Hz sound waves, the thickness of at least 34 cm is required. On the other hand, the acoustic lens proposed by Kock et al. in the 1950s composed by multiple spheres or other obstacles to control the speed of sound. This report proposes a diffuser without depressions of irregular depth by applying the acoustic lens principle of Kock etal. The difference in reflection time caused by the depressions of the diffuser can be controlled by multiple obstacles.

Acoustic lens that diffuses plane waves composing of multiple spherical obstacles

Recently, a non-electrical smartphone loudspeaker based on acoustic horn has been created and marketed. An acoustic horn is directional and has the advantage of propagating strong sound pressure in the direction the horn is facing. However, it has the disadvantage that sound pressure cannot be expected in any direction other than the direction in which the form facing. This study proposed an acoustic lens in the form of a cylinder composed of multiple spherical obstacles. The density of the sphere was calculated using the phase difference equation and the equation proposed by Kock et al. The density of the sphere at the center of the lens is lower than at the circumferential direction. This change in density slows down the apparent sound speed passing through the further from the center. In this work, FDTD simulations were performed to evaluate the sound directivity for the acoustic lens. This work also test manufactured the acoustic lens and performed an experiment in an anechoic chamber to evaluate the characteristics of the lens.

Research on Terminal Distance Index-Based Multi-Step Ant Colony Optimization for Mobile Robot Path Planning

Aiming at the path planning problem of mobile robot, when the traditional ant colony optimization (ACO) is simulated in grid model, it is assumed that ants can only move to adjacent nodes, that is, the step size is 1 and there are 8 movable directions. However, in practice, the moving direction of the ant is completely free. Therefore, an improved terminal distance index-based multi-step ant colony optimization (TDI-MSACO) for mobile robot path planning is proposed in this paper. A multi-step ant colony optimization (MSACO) is firstly used to improve the flexibility of ant’s movement and the path obtained by using MSACO is shorter and more in line with the actual situation, through the simulation of a large number of cases, it is determined that the optimal step size is 2 or 3. In addition, aiming at the problems of pheromone updating mechanism in MSACO, a concept of terminal distance index (TDI) is proposed to replace pheromone concentration and accelerate the convergence speed of the MSACO. In order to verify the effectiveness of the improved TDI-MSACO, the simulations are tested on <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$20\times 20$</tex-math> </inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$30\times 30$</tex-math> </inline-formula> , and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$50\times 50$</tex-math> </inline-formula> grid models and the results show that the improved TDI-MSACO has faster convergence speed and shorter path. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —the motivation of this paper comes from the need to develop a fast and efficient path planning method for practical applications such as material transport in shop floor, cleaning, monitoring of dangerous radioactive sites and military applications, and so on. The ant colony optimization (ACO), inspired from the foraging behavior of ant species, is a swarm intelligence algorithm for solving hard combinatorial optimization problems. The ACO is widely used in robot path planning areas because of its characteristics of positive feedback, distributed computation. However, it has the weaknesses of premature convergence and low search speed, which greatly hinder its application. To improve the performance of the ACO, an improved terminal distance index-based multi-step ant colony optimization (TDI-MSACO) for mobile robot path planning is proposed in this paper. Multi-step and terminal distance index are used to improve the flexibility of ant movement and accelerate the convergence speed, respectively. The effectiveness of the TDI-MSACO method for solving mobile path planning problems is proved by comparing the simulation results with those previously presented in the literature. Furthermore, the proposed method can be expanded to the dynamic environment containing multiple static and dynamic obstacles of many sizes and forms, it also can be used to solve the energy-efficient path planning problems. Meanwhile, it can be further modified and applied to the simultaneous scheduling of machines and transport robots in an actual flexible job shop environment.

Competitive strategies and integration expanses in the large shipping container industry during an era of consecutive global crises

Purpose: This research aims to examine the competitive strategies and integration expanses of three of the largest shipping container companies worldwide, attempting to provide a helpful insight into the strategies adopted and implemented by the shipping container companies in question, in order to overcome the multiple significant obstacles resulting from the consecutive global crises of recent years (the post 2008 global financial crisis, pandemic, and war in Ukraine). Design/approach: The present paper (as a Case Study) examined three large shipping container companies that have played a crucial role in global trade over the years. These are three of the largest in 2023 (Hapag Lloyd, COSCO Shipping Lines, and Maersk). The criteria of these selected companies were mainly the authors’ focus on the significance for the industry of the mentioned three large shipping container companies, as well as the volume of information that could gathered by secondary data sources. Secondary data was collected by reviewing the existing branding literature as discussed in academic and trade journals, books, information databases, professional magazines, government publications, and specialized internet sites (Emerald, Science Direct, Google Scholar, and Scirus). Findings: This research identified that large shipping container companies do not solely adopt Cost Leadership, Differentiation, or Focus Strategy when planning their competitive strategies. Consequently, the decision of competitive strategy choice by large shipping container companies is not a trichotomous one between complete Cost Leadership, Differentiation, or Focus Strategy, but is a matter of combination. Many macro- and micro-environmental and organizational factors have a bearing on such decisions. This study identified that the balance of combination is dependent upon a number of reasons and factors, such as (mainly) macro- and micro-environmental factors, company resources and capabilities, customers’ willing to pay, barriers in the shipping liner industry, and revenue and cost approaches. Research limitations/ implications: The study contains several shortcomings. The theoretical view may contain conceptual elements which hinder more specific observations, e.g., the exhaustive examination of the industry’s competition elements based on Porter’s five forces rivalry view about competition between companies: (1) Rivalry between Existing Competitors, (2) Threat of New Entry, (3) Threat of Substitution, (4) Buyers’ Bargaining Power, and (5) Suppliers’ Bargaining Power. There is a recommendation for future research, which will be on how other large shipping container companies have dealt mainly with the post global financial crisis, as well as the post pandemic era, in terms of a competitive strategies approach having been adopted. This could include qualitative or quantitative research, along with a larger number of case study approaches (and not only large shipping container companies, but medium- and small-sized shipping container firms), which would produce useful results and insights. However, despite limitations, the study contains some managerial implications. Originality/value: The paper reports on the findings of one of the first in its kind (competitive strategies in large shipping container companies during an era of consecutive global crises) of research study carried out in the sector- in general, there are few research papers about competitive strategies in the shipping industry. The findings that emerged attempt to set the foundation for helping the various stakeholders in the sector, contributing towards building their strong international presence.

A novel heuristic algorithm for solving engineering optimization and real-world problems: People identity attributes-based information-learning search optimization

With the scale and dimension of engineering optimization and real-world problems increasing, it will be difficult to find the optimum solutions. This paper proposes a novel people identity attributes-based heuristic technology, named the People Identity Attributes-based Information-learning Search Optimization (ISO), inspired by people’s psychological assessment and learning behaviors for information resources based on the social status-based identity attribute and the self-survival demands-based identity attribute. For the former, a four-level information delivery mechanism is constructed through leader, manager, executor, and freelancer, emphasizing global optimization. For the latter, the staged transforming model based on random accumulation and directed induction behaviors are constructed according to self-survival demands, emphasizing global optimization and exploration. The dual identity attributes-based search strategy emphasizes psychological assessment and selection for the information loss, including the learning behavior for two kinds of information resources with different identity attributes, and the recovering behavior for the information loss by constructing the information resilience equation, which emphasizes local optimization and exploitation. This paper qualitatively analyzes the swarm behavior, search history, and the exploration and exploitation capabilities of ISO. The optimization performances are quantitatively analyzed for ISO and 9 competitive algorithms on 39 benchmark tests, including the convergence, solution accuracy, robustness, sensitivity, significance, statistical investigation-based Wilcoxon test and Friedman test. The scalability of ISO is investigated on CEC2017 (30Dim, 50Dim, 100Dim) and the latest CEC2022 (10Dim, 20Dim) suites. The results reveal that compared to other competitive algorithms, ISO possesses best computing performance with ranking the first in all competitors. In addition, the proposed ISO and 12 competitors consider 10 constraint engineering optimization problems and the real application of path planning with multiple obstacles, suggesting that ISO possesses significant optimization performance.

A wearable assistive system for the visually impaired using object detection, distance measurement and tactile presentation

With the current development of society, ensuring traffic and walking safety for the visually impaired is becoming increasingly important. We propose a wearable system based on a system previously developed by us that uses object recognition, a distance measurement function, and the corresponding vibration pattern presentation to support the mobility of the visually impaired. The system recognizes obstacles in front of a user in real time, measures their distances, processes the information, and then presents safety actions through vibration patterns from a tactile glove woven with shape memory alloy (SMA) actuators. The deep learning model is compressed to achieve real-time recognition using a microcomputer while maintaining recognition accuracy. Measurements of the distances to multiple objects are realized using a stereo camera, and vibration patterns are presented through a tactile glove in response to these distances. Experiments are conducted to verify the system performance to provide safe navigation depending on the positions and the distances of multiple obstacles in front of the user.