Search

The increasing volume of personal motorized vehicles (PMVs) in cities has become a serious issue leading to congestion, noise, air pollution and high land consumption. To ensure the sustainability of urban transportation, it is imperative to transition the current transportation paradigm toward a more sustainable state. Transitions within socio-technical systems often arise from niche innovation. Therefore, this paper pursues the technical optimization of such a niche innovation by applying a technical sustainability perspective on an innovative mobility and logistics concept within a case study. This case study is based on a centrally managed connected, automated, shared and electric (CASE) vehicle fleet which might replace PMV use in urban city centers of the future. The key technical system components of the envisioned mobility and logistics concept are analyzed and optimized with regard to economic, ecological and social sustainability dimensions to maximize the overall sustainability of the ecosystem. Specifically, this paper identifies key challenges and proposes possible solutions across the vehicle components as well as the orchestration of the vehicles' operations within the envisioned mobility and logistics concept. Thereby, the case study gives an example of how different engineering disciplines can contribute to different sustainability dimensions, highlighting the interdependences. Finally, the discussion concludes that the early integration of sustainability considerations in the technical optimization efforts of innovative transportation systems can provide an important building block for the transition of the current transportation paradigm to a more sustainable state. [ABSTRACT FROM AUTHOR]

The paper designs and implements a fully customized and branded hospital billing and recordkeeping system. It is aimed at simplifying the medical billing process and minimizing the daily hassles encountered by hospitals and other healthcare facilities. The system captures patients' information such as demographics, medical history, medication and allergies, immunization status, laboratory test results, radiology images, vital signs, personal status like age and weight, and billing information electronically and stores them in a relational database for easy access, retrieval and processing. Structured system analysis and design methodology (SSADM) uses objects throughout the software development process. The programming languages and development tools used are HTML and CSS for interface design, MYSQL for database design, and PHP for server-side scripting that facilitates communication between the interface and the database. The expected result is an integrated patient billing and recordkeeping system that will keep track of all the transactions of patients with the hospital and associate all health information with specific patients. [ABSTRACT FROM AUTHOR]

In the field of automated technology research and development, trajectory tracking plays a crucial role in the energy consumption of the vehicle's power battery. Reducing the deviation between the actual trajectory and the reference trajectory is the focus of trajectory tracking research. This paper proposes the use of the model predictive control (MPC) method to reduce the deviation of lateral and longitudinal position between the actual driving trajectory and the reference trajectory. First, the driving conditions of the vehicle are reflected by establishing the vehicle dynamics model. Then, the MPC trajectory tracking controller is built by designing the objective function with constraints; Finally, the feasibility of this approach was verified by a joint Carsim-Simulink simulation. The simulation results show that the MPC controller designed in this paper can track the trajectory better, and reduce the lateral and longitudinal position deviation. To a certain extent, the battery energy consumption is reduced and the accuracy of the tracking trajectory and the safety of vehicle driving are improved. [ABSTRACT FROM AUTHOR]

Intravenous therapy is the standard medical procedure that is used for administering medications directly into the vein. The automated drug infusion devices are designed in such a way that they provide exact medication doses with safety measures included. On the other hand, this is why they must be regularly watched by healthcare providers. This paper introduces a cloud-based IoT drug infusion system that was developed to address remote patient care needs. This system enables remote, accurate, and secure management of medication delivery. Its key contributions include allowing healthcare providers to control and monitor IV infusions remotely while maintaining safety features. The system consists of a microcontroller that is responsible for data processing, a control system that oversees infusion rate regulation, and an IoT-based framework that allows for remote monitoring and alerts via a user-friendly web interface. This new approach to care will therefore improve patient care by providing remote management of medications. [ABSTRACT FROM AUTHOR]

Purpose: The British Library (BL) faces a significant challenge with storage space predicted to run out within the next three years. However, alongside a plan to create additional capacity, the BL also intends to take the opportunity to rethink the integration of storage and workflows in order to implement a fully optimised end-to-end model of content management. This approach will incorporate not only storage and workflow design and integration, but also the physical environments and facilities for staff and users. Design/methodology/approach: This paper draws on years of experience in the context of systemic industry changes to lead the reader into new thinking and opportunities in relation to print preservation and access. It should be noted that some of the aspirational new thinking described within this article may not come to fruition due to construction market inflation and resulting budgetary constraints. Findings: As the national library of the UK, BL, like all libraries, has the responsibility of storing (preserving) its collections while making them accessible to everyone. Traditional models of physical storage can often operate in isolation from the processes that accompany them – creating silos of materials, completely remote from either the acquisition and description processes that precede their storage, or misaligned with the processes in place to support access. Practical implications: The presentation of this conceptual thinking could help inform other libraries planning to build new print repositories. Originality/value: The strategic approach outlined within this paper has adopted ideas and concepts from non-library applications, bringing them together to form a holistic solution that delivers the ultimate aims of a library within a modern context. [ABSTRACT FROM AUTHOR]

Retinopathy of Prematurity (ROP) is a disease of the eye and a potential source of blindness in low birth weight preterm infants. It is preventable if diagnosed and treated on time. Artificial Intelligence (AI) has played an important role in developing automated screening systems to assist medical experts. There are many traditional literature review articles available that focus on the scientific content of ROP-AI. The researchers also require a bibliometric analysis to become acquainted with the competing groups and new trends in this field. This paper gives a brief overview of ROP and AI systems for ROP screening with a statistical analysis of the Scopus database's related documents. [ABSTRACT FROM AUTHOR]

The purpose of this study was to collect preliminary data for the design of real-time and integrated performance assessments in science practicum at two public universities and two private universities in Eastern Indonesia. The case study design and quantitative and qualitative approaches were adopted in this study. Cluster random sampling technique was used to select four universities, 376 participants respectively from university students and lecturers, four vice deans, four heads of study programs, four heads of laboratories, and four teaching assistants. Data were gathered through questionnaires, in-depth interviews, and observations. The chi-square test was used to analyze the data descriptively. Findings indicated that a performance assessment was not carried out since standard measurement instruments that provided real-time and integrated feedback had not been developed. There was no significant difference (p > 0.05) between public and private universities on the science practicum assessment, implying that both public and private universities still used paper-based practicum assessments. There was also no significant difference between the responses of university students and lecturers on practicum performance assessments (p > 0.05). University students' experience in assessing science practicums was similar to those of lecturers', which suggests that practicum of performance assessments was not real-time and integrated with feedback. This study recommends developing a real-time and integrated performance assessment with automated feedback on the science practicum, in order to provide continuous improvement of students and monitoring their learning progress. [ABSTRACT FROM AUTHOR]

Reachable and controllable sets for electric propulsion spacecraft are important to many problems including: dynamic replanning, robust mission design, space situational awareness, assessing advanced concepts, and threat assessments. Current methods result in a two-point boundary value problem or are limited in their application. The reachable and controllable problem is solved using an multistage indirect approach. The paper demonstrates our formulation enables rapid, reliable, and autonomous estimates of the reachable and controllable sets. Numerical examples show that the algorithms work in strong multibody environments (i.e., flybys) and incorporates uncertainty in initial conditions. These conditions make the algorithm suitable for space situational awareness and cislunar applications. [ABSTRACT FROM AUTHOR]

The scale of software is growing rapidly for organizations begin to deploy their business on internet. It is a need of avoid ambiguity between engineers and users and to avoid mistakes in software requirements. And provide automatic requirement analysis techniques for modeling and analyzing requirements formally and save manpower. In this paper proposed cloud service method for automated detection of quality requirement in software requirement specification. This paper also present novel approach for process of automatic classification of software quality requirements based on supervised machine learning technique applied for the classification of training document and predict target document software quality requirements. [ABSTRACT FROM AUTHOR]

This research paper focuses on the development and implementation of an IoT-based train detection system aimed at enhancing passenger safety and minimizing accidents. The proposed system addresses the absence of a dedicated train detection system in Sri Lanka, making it an important and timely research topic. A train detection system is an integral component of railway safety, as it allows for real-time monitoring and identification of potential risks along the tracks. However, Sri Lanka currently lacks such a system, leaving passengers vulnerable to safety hazards. Therefore, this research aims to bridge this gap by introducing and implementing an IoT-based train detection system. By leveraging IoT devices, the proposed system enables continuous monitoring and detection of critical events such as unauthorized access to railway tracks, track obstructions, and abnormal train behaviour. Real-time detection of these risks allows for timely interventions, reducing the occurrence of accidents and ensuring passenger safety. The implementation of this train detection system in Sri Lanka holds significant importance. It serves as a catalyst for research and development in the field of railway safety, offering a novel and innovative solution to address the current gaps. By introducing this system, Sri Lanka can enhance its railway infrastructure, improve passenger safety, and serve as a model for other countries facing similar challenges. Through this research, valuable insights will be gained regarding the feasibility, effectiveness, and impact of an IoT-based train detection system in the context of Sri Lanka. The findings will contribute to the body of knowledge on railway safety and provide recommendations for the adoption and adaptation of similar systems in other regions. In conclusion, the implementation of an IoT-based train detection system in Sri Lanka is crucial for ensuring passenger safety and minimizing accidents. This research presents a significant opportunity to address the existing gap, offering a platform for innovation and enhancing the country's railway infrastructure. The findings and recommendations from this study will contribute to the advancement of railway safety globally. [ABSTRACT FROM AUTHOR]

Managing the massive losses associated with large-scale disasters requires significant resources. The unexpected violence of these events generally remains a matter of casualties that urgently need to be identified in a reliable and cost-effective manner. To overcome these difficulties, many researchers have attempted to develop automated methods; moreover, a few recent research have investigated the applicability of artificial intelligence (AI)-based methods using skull, dental, and maxillofacial forensic imaging. In this review, we speculate on the advancement and potential of AI in Dental and Maxillofacial imaging that can help simplify person or victim identification and speed up the process with good accuracy. Using a few prefix search phrases, an online literature search was conducted (AI, Forensic, Skull, Dental, Imaging, Radiology) to identify papers about the advancement of AI in forensic dentistry in all kinds of radiographs, including two-dimensional (2D) and three-dimensional (3D) radiographs, cone beam computed tomography (CT) and CT. Most of the studies reported that automated methods of human identification based on 2D and 3D Dental and Skull radiographs using a convolutional neural network showed to assist in the fast and accurate identification by expertise evaluating a lot of images and quickly coming up with potential matches for identification. We advocate the application of AI techniques in the identification of individuals. However, there is a need to continue research with emphasis to validate models in skull identification. [ABSTRACT FROM AUTHOR]

Evolutionary intelligence has become one of the most important directions that improve the performance and effectiveness of automated systems such as communication systems, robotics and engineering industries. Today, there are many applications of evolutionary intelligence in many engineering fields and the most important fields related to computation and informatics engineering as a part of electrical and communication engineering, as modern engineering applications are involved in these fields. The sensor network is the main data source in the world of smart systems nowadays. Additionally, it has become a field of science used in the development of the rest of scientific applications. The need to use evolutionary intelligence in sensor networks has emerged because of the problems encountered by different types of sensor networks. This paper represents a comprehensive scientific review of the role of evolutionary intelligence in sensor networks and its implications for this important part of engineering applications. This paper discusses the theoretical, mathematical and practical application of evolutionary computing with the use of evolutionary algorithms and the improvements resulting from the application of evolutionary intelligence in sensor networks. The content of this paper will review the most important of the evolutionary intelligence from principles, algorithms and applications. The problems facing the types of sensor network has been solved using evolutionary algorithms. After reviewing the evolutionary intelligence and its details in the sensor network, a performance evaluation is presented in the paper at the end of each of the targeted areas of the sensor network. This performance evaluation represents the measure of the quality of improvements provided by evolutionary intelligence in sensor network field with graphical analysis studies to demonstrate the effect of evolutionary algorithms on the sensor network. [ABSTRACT FROM AUTHOR]

This paper considers successful cash management, which involves not only avoiding insolvency but also selecting appropriate short-term investment vehicles and increasing cash on hand to improve an investor's cash position and profitability. The paper discusses the following: the term 'cash management account' refers to a type of account offered by brokers, dealers and other financial institutions. This type of account combines a brokerage account with a checking account. Broker-dealers have either their own information technology infrastructure or leverage their custodian's IT infrastructure to provide cash management facilities to their clients. There are two broad products under the cash management service: • Automated cash management, which provides automated sweep facilities for short-term investment. • Asset management account, which provides retail-banking facilities for using the free cash, along with the sweep facilities. A sweep account is a bank account that automatically transfers amounts that exceed, or fall short of, a certain level into a higher interest-earning investment option at the close of each business day. Commonly, the excess cash is swept into money market funds or Federal Deposit Insurance Corporation (FDIC) deposits. FDIC is a federal institution that offers sovereign deposit options. [ABSTRACT FROM AUTHOR]

This paper overviews emerging technology development by emphasizing Connected, Automated, Shared, and Electric (CASE) technologies. Existing literature on 15 CASE technologies is reviewed, and adds to the literature by consolidating important predictions of CASE-related technologies, services, and policies. Connected and automated technologies have not yet matured, and there remain many gaps in its abilities. Predictions include that shared mobility will have a large market share, electric technologies will replace internal combustion engines, and CASE-related services and policies will be used in more cities. A survey with 1,036 respondents conducted in April 2021 helps gauge how Americans make mode choices under various scenarios. Data analysis indicates that safety issues are the main factor that hinder people's willingness to use CASE-related technologies, and the low cost encourages more users to choose shared mobility. Challenges that remain, and their associated impacts, are important to consider. [ABSTRACT FROM AUTHOR]

Web data extraction has seen significant development in the last decade since its inception in the early nineties. It has evolved from a simple manual way of extracting data from web page and documents to automated extraction to an intelligent extraction using machine learning algorithms, tools and techniques. Data extraction is one of the key components of end-to-end life cycle in web data extraction process that includes navigation, extraction, data enrichment and visualization. This paper presents the journey of web data extraction over the last many years highlighting evolution of tools, techniques, frameworks and algorithms for building intelligent web data extraction systems. The paper also throws light into challenges, opportunities for future research and emerging trends over the years in web data extraction with specific focus on machine learning techniques. Both traditional and machine learning approaches to manual and automated web data extraction are experimented and results published with few use cases demonstrating the challenges in web data extraction in the event of changes in the website layout. This paper introduces novel ideas such as self-healing capability in web data extraction and proactive error detection in the event of changes in website layout as an area of future research. This unique perspective will help readers to get deeper insights in to the present and future of web data extraction. [ABSTRACT FROM AUTHOR]

Copyright of Revista Pensamento Contemporâneo em Administração is the property of Universidade Federal Fluminense (Revista Pensamento Contemporaneo em Administracao) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Progress monitoring is an essential part of large construction projects. As manual progress monitoring is time-consuming, the need for automation emerges, especially as, nowadays, BIM for the design of buildings and laser scanning for capturing the as-built situation have become well adopted. However, to be able to compare the as-built model obtained by laser scanning to the BIM design, both models need to use the same reference system, which often is not the case. Transforming the coordinate system of the as-built model into the BIM model is a specialist process that is pre-requisite in automated construction progress monitoring. The research described in this paper is aimed at the automation of this so-called registration process and is based on the dominant planar geometry of most buildings with evident corner points in their structures. After extracting these corner points from both the as-built and the design model, a RANSAC-based pairwise assessment of the points is performed to identify potential matching points in both models using different discriminative geometric invariants. Next, the transformation for the potential matches is evaluated to find all the matching points. In the end, the most accurate transformation parameter is determined from the individual transformation parameters of all the matching corner points. The proposed method was tested and validated with a range of both simulated and real-life datasets. In all the case studies including the simulated and real-life datasets, the registration was successful and accurate. Furthermore, the method allows for the registration of the as-built models of incomplete buildings, which is essential for effective construction progress monitoring. As the method uses the standard IFC schema for data exchange with the BIM, there is no loss of geometrical information caused by data conversions and it supports the complete automation of the progress-monitoring process. [ABSTRACT FROM AUTHOR]

Volcanic activity is diverse. Therefore, a lot of volcanic ejecta need to be analyzed to properly assess the condition of a volcano. However, until now, rapid analysis in this regard has been insufficient. To accurately evaluate both the transition and the characteristics of eruptions, we constructed a platform to efficiently analyze volcanic ejecta incorporating a number of automatic processing functions into a data processing system composed of an electron beam microprobe analyzer (EPMA) and personal computers. A number of time-consuming tasks, such as crystal size distribution analysis and ash particle classification, were automated. Further, the analysis platform is equipped with a database function for collecting various analytical data as the basis for the future development of volcanology. Various quantitative values related to the composition and microtexture of the volcanic ejecta were collected and entered into the database. This paper introduces an outline of the system, collected data, and usage examples. [ABSTRACT FROM AUTHOR]

The patch clamp technique is regarded as the gold standard in electrophysiological measurements. It provides quantitative recordings for investigations and analyses of physiological activities by cellular ion channels. The gigaseal formation process is an essential factor for guaranteeing patch clamp recording conditions. This process contributes to monitoring biological ion channel currents by reducing the leakage current between pipette tip and cell membrane. While automated patch clamp systems are thriving, the implementation of criteria derived from empirical values inevitably randomizes the success of giga-ohm seals. In this paper, we addressed the seal condition between the bath current and the seal current in the gigaseal formation process. The sealing limit of the cell membrane to the micro-opening was indicated as the critical point of seal current. A predictive model based on the critical point was proposed to optimize the threshold of the seal current for gigaseal formation. It offers a systematic approach for micro-opening type implementations of high-throughput design. An automated patch clamp system with a predictive model (PM-APCS) was designed and developed to obtain whole cell voltage clamp recordings. In the development, HEK 293 cells and C2C12 cells were employed for the validation of the method. The success rate of gigaseal formation was 95.9%, which could greatly advance the existing manual or automatic methods. Overall, our findings provide important insights for understanding the seal current mechanism. The predictive model has the potential to accelerate the application of various automated systems for electrophysiology. [ABSTRACT FROM AUTHOR]

RFID is a cutting-edge integrated library management system that enables the instantaneous detection and recognition of library materials. RFID applications vary from book monitoring and stock management to security in general and completely automated book classifying at the moment. Shortly, RFID systems will play an important role in data collection, recognition, and analysis required for specific library operations. An RFID-enabled automated library might be a "selfservice station" that involves reducing the amount of interference from staff members. Efforts are being made to implement self-service "check-in" and "checkout" to prevent long delays in the delivery of library collection and to improve operational efficiency. Considering the significance of library security, this paper focuses on the use of Radio frequency identification (RFID) in libraries, including its elements, advantages, and the role of the librarian. The researcher collected the data of 50 users from Maharshi Dayanand University library, Rohtak, to find out the status of RFID implementation and the satisfaction level of users with the system. Most of the users are satisfied with the component and its benefits of it. [ABSTRACT FROM AUTHOR]

The increasing volume of personal motorized vehicles (PMVs) in cities has become a serious issue leading to congestion, noise, air pollution and high land consumption. To ensure the sustainability of urban transportation, it is imperative to transition the current transportation paradigm toward a more sustainable state. Transitions within socio-technical systems often arise from niche innovation. Therefore, this paper pursues the technical optimization of such a niche innovation by applying a technical sustainability perspective on an innovative mobility and logistics concept within a case study. This case study is based on a centrally managed connected, automated, shared and electric (CASE) vehicle fleet which might replace PMV use in urban city centers of the future. The key technical system components of the envisioned mobility and logistics concept are analyzed and optimized with regard to economic, ecological and social sustainability dimensions to maximize the overall sustainability of the ecosystem. Specifically, this paper identifies key challenges and proposes possible solutions across the vehicle components as well as the orchestration of the vehicles’ operations within the envisioned mobility and logistics concept. Thereby, the case study gives an example of how different engineering disciplines can contribute to different sustainability dimensions, highlighting the interdependences. Finally, the discussion concludes that the early integration of sustainability considerations in the technical optimization efforts of innovative transportation systems can provide an important building block for the transition of the current transportation paradigm to a more sustainable state.

The investment securities operations world changed significantly post the 2008 crisis with the increased requirements of market infrastructure and regulations and the changing investment strategies to navigate market conditions for earning returns. Investment middle offices had to both redesign and implement operating workflow structures that could meet and achieve the regulatory requirements and support the front-office investment management strategies. This paper will examine the approaches undertaken by an investment operations division to balance and achieve the various objectives that middle-office operations needs to navigate and undertake. The paper will include key elements that have been implemented within the operating structure of a securities operations group in order to be a strong base for the investment asset management business. The key strategic operating tenets undertaken and implemented will include discussions on automated and integrated workflow models to fulfil all the functions of a global, multi-asset business. Automation will include both internal to the firm's structure and operations and external to the marketplace. It will also include discussions on a data-centric approach imbedded in the operating model through the implementation of a comprehensive data strategy for the investment business. [ABSTRACT FROM AUTHOR]

The effective development of novel therapies in mouse models of neurologic disorders relies on behavioral assessments that provide accurate read-outs of neuronal dysfunction and/or degeneration. We designed an automated behavioral testing system (PiPaw), which integrates an operant lever-pulling task directly into the mouse home cage. This task is accessible to grouphoused mice 24 h per day, enabling high-throughput longitudinal analysis of forelimb motor learning. Moreover, this design eliminates the need for exposure to novel environments and minimizes experimenter interaction, significantly reducing two of the largest stressors associated with animal behavior. Male mice improved their performance of this task over 1 week of testing by reducing intertrial variability of reward-related kinematic parameters (pull amplitude or peak velocity). In addition, mice displayed short-term improvements in reward rate, and a concomitant decrease in movement variability, over the course of brief bouts of task engagement. We used this system to assess motor learning in mouse models of the inherited neurodegenerative disorder, Huntington disease (HD). Despite having no baseline differences in task performance, male Q175-FDN HD mice were unable to modulate the variability of their movements to increase reward on either short or long timescales. Task training was associated with a decrease in the amplitude of spontaneous excitatory activity recorded from striatal medium spiny neurons in the hemisphere contralateral to the trained forelimb in WT mice; however, no such changes were observed in Q175-FDN mice. This behavioral screening platform should prove useful for preclinical drug trials toward improved treatments in HD and other neurologic disorders. [ABSTRACT FROM AUTHOR]

The development of peptide-based pharmaceutics is a hot topic in the pharmaceutical industry and in basic research. However, from the research and development perspective there is an unmet need for new, alternative, solid-phase peptide synthesizers that are highly efficient, automated, robust, able to synthetize peptides in parallel, inexpensive (to obtain and operate), have potential to be scaled up, and even comply with the principles of green chemistry. Moreover, a peptide synthesizer of this type could also fill the gap in university research, and therefore speed the advancement of peptide-based pharmaceutical options. This paper presents a Tecan add-on peptide synthesizer (TaPSy), which has operational flexibility (coupling time: 15–30 min), can handle all manual synthesis methods, and is economical (solvent use: 34.5 mL/cycle, while handling 0.49 mmol scale/reactor, even with ≤3 equivalents of activated amino acid derivatives). Moreover, it can carry out parallel synthesis of up to 12 different peptides (0.49 mmol scale in each). TaPSy uses no heating or high pressure, while it is still resistant to external influences (operating conditions: atmospheric pressure, room temperature 20–40 ˚C, including high [>70%] relative humidity). The system's solvent can also be switched from DMF to a green and biorenewable solvent, γ-valerolactone (GVL), without further adjustment. The designed TaPSy system can produce peptides with high purity (>70%), even with the green GVL solvent alternative. In this paper we demonstrate the optimization path of a newly developed peptide synthesizer in the context of coupling reagents, reaction time and reagent equivalents applying for a synthesis of a model peptide. We compare the results by analytical characteristics (purity of raw material, crude yield, yield) and calculated overall cost of the syntheses of one mg of crude peptide using a specified set of reaction conditions.