Miracle-dz/UniFAR-FTUs huggingface dataset:
Articulated robots motion planning using foraging ant strategy

Many different approaches to tackle the problem of motion planning for articulated robots in an environment with obstacles based on random sampling have been proposed. One popular approach is called single-query bi-directional motion planning with a lazy collision checking probabilistic road map (SBL-PRM). However, the performance of this method is sub-optimal in terms of the number of configurations generated, length of path, amount of collision checking and computational time. To improve the performance, those aspects must be considered further as they are inter-related with each other. A novel modification of SBLPRM that decreases the size of excessive configurations in the roadmap, by incrementally building a one-tree structure originating from the start configuration, is presented. This approach, the single-query unidirectional approach with lazy collision checking (SUL-PRM), has experimentally shown to be equal to the SBL-PRM. However, there still exists generated configurations that were excluded from the successful path. The generation of these unconsumed configurations corresponding to the tree structure has pointlessly utilized the computational resources and affected the planning time. Hence, a new method of configuration generation along with a novel searching style is devised. An alternative search approach using ant behaviour in a robotics application is applied. This paper proposes a novel search technique, the F-Ant algorithm, in order to find a reliable path between the initial configuration and the goal configuration of the articulated robot. This novel algorithm, taking two input configurations, explores the robot's free space by building up a unidirectional search beginning at the initial configuration. The planner samples the free configuration repetitively in the neighbourhood within the radius of the current configuration, and tests the edge for a collision-free path between the new sampled configurations, until it is connected to the goal configuration. Simulation and experimental comparisons of F-Ant and SBL-PRM have been conducted, showing the performance differences between these two techniques.
A general and robust method for multi-criteria design of microwave oscillators using an evolutionary strategy

This paper describes a general and robust method applied to the optimization of microwave oscillators. This method is a combination of the harmonic balance method, the device-line measurement technique and a multi-objective evolutionary optimizer. The importance of using proper harmonic loads is considered. An example shows that the multi-objective evolutionary algorithm allows the robust exploitation of the trade-off curve of the figures of merit of the oscillator.
3Cs: Creating a Culture of Creativity

Creativity and innovation are intrinsic to gaining advantage in the global knowledge economy of our society. So, how can we encourage and teach our students to be more creative? Since 1968, creativity tests have been administered to groups of children. The results have shown that people gradually become less creative as they age; that we learn not to be creative. Through research findings of own experiences this paper investigates ways in which to sustain creativity in the classroom and to advance, rather than degrade, the development of children’s creativity. Through case studies seven methods are presented on how to create a culture of innovation and creativity within the classroom.
Diesel engine performance modelling using neural networks

The aim of this study is to develop, using neural networks, a model to aid the performance monitoring of operational diesel engines in industrial settings. Feed-forward and modular neural network-based models are created for the prediction of the specific fuel consumption on any normally aspirated direct injection four-stroke diesel engine. The predictive capability of each model is compared to that of a published quadratic method. Since engine performance maps are difficult and time consuming to develop, there is a general scarcity of these maps, thereby limiting the effectiveness of any engine monitoring program that aims to manage the fuel consumption of an operational engine. Current methods applied for engine consumption prediction are either too complex or fail to account for specific engine characteristics that could make engine fuel consumption monitoring simple and general in application. This study addresses these issues by providing a neural network-based predictive model that requires two measured operational parameters: the engine speed and torque, and five known engine parameters. The five parameters are: rated power, rated and minimum specific fuel consumption bore and stroke. The neural networks are trained using the performance maps of eight commercially available diesel engines, with one entire map being held out of sample for assessment of model generalisation performance and application validation. The model inputs are defined using the domain expertise approach to neural network input specification. This approach requires a thorough review of the operational and design parameters affecting engine fuel consumption performance and the development of specific parameters that both scale and normalize engine performance for comparative purposes. Network architecture and learning rate parameters are optimized using a genetic algorithm-based global search method together with a locally adaptive learning algorithm for weight optimization. Network training errors are statistically verified and the neural network test responses are validation tested using both white and black box validation principles. The validation tests are constructed to enable assessment of the confidence that can be associated with the model for its intended purpose. Comparison of the modular network with the feed-forward network indicates that they learn the underlying function differently, with the modular network displaying improved generalisation on the test data set. Both networks demonstrate improved predictive performance over the published quadratic method. The modular network is the only model accepted as verified and validated for application implementation. The significance of this work is that fuel consumption monitoring can be effectively applied to operational diesel engines using a neural network-based model, the consequence of which is improved long term energy efficiency. Further, a methodology is demonstrated for the development and validation testing of modular neural networks for diesel engine performance prediction.
Optimizations for efficient and transparent use of IP applications over HF links

This paper describes the architecture of an IP Gateway system implementing various enhancements to enable efficient and transparent use of standard multimedia and data IPv6 applications over strongly varying and bandwidth-limited wireless links such as HF radio. Three optimizations are proposed : (a) an HF-oriented Performance Enhancing Proxy (PEP) to improve the Quality of Service (QoS) of TCP/IP applications (b) Robust Header Compression (RoHC) of headers and (c) Joint Quality of Service and retransmissions management. Performance results obtained in real HF conditions are also presented in this article.
Knowledge transfer and the use of social networks in the biopharmaceutical industry : an investigation into the micro-foundations of external absorptive capacity

In order to grow, the pharmaceutical sector has had to heavily rely on both formal and informal innovation networks. However, many analysts consider that the industry has not achieved its growth potential and suggest that this is in part due to the inherent organisational barriers to knowledge transfer that exist in the pharmaceutical sector. This thesis provides a critical review of the knowledge transfer literature; with particular reference to absorptive capacity, social capital and external knowledge transfer meta-routines. The study takes a pragmatic critical realist approach, using a two stage critical incident technique to elucidate the micro-foundations of problem solving routines as a proxy for knowledge transfer. Thematic analysis on the resulting narratives identifies routinized patterns of information seeking behaviour, reveals the micro-foundations of template use and provides insights into how scientists recognise value in the knowledge that they find. The study answers calls to research the role of the individual in organisational routines; to uncover the micro-foundations of external absorptive capacity and to determine how value is recognised in new knowledge. A model is proposed that suggests that recognising the value of new knowledge is a construct that is influenced by factors which affect the perceived information quality, the relative subjectivity of the solution and the source’s social-identity. The value of knowledge is also further corroborated with the support of other materials or through a wider stakeholder involvement. The study has adopted a ‘strategy-as-practice’ approach and contributes to organisational practice by examining how informal external knowledge transfer through problem solving in a biopharmaceutical organisation is accomplished. These insights enable the author to suggest a number of managerial strategies by which pharmaceutical managers might recognise, optimise and facilitate the use of informal networks; whilst protecting their intellectual property and maintaining the potential for innovation.
Motor Control Technology for Industrial Maintenance

1. Shop Safety and Shop Practices. 2. Lockout, Tag-out. 3. Tools for Electrical Technicians. 4. Symbols and Diagrams. 5. Overview of Motor Controls. 6. Power Distribution and Transformers. 7. Manual Control Devices. 8. Magnetics, Solenoids, and Relays. 9. Contractors and Motor Starters. 10. Pilot Devices. 11. Photoelectric and Proximity Controls. 12. Timers, Counters, and Sequencers. 13. DC Motors. 14. AC Motors. 15. Motor Control Circuits. 16. Advanced Motor Control Circuits: Accelerating and Decelerating Circuits. 17. AC and DC Drives. 18. Programmable Controllers. 19. Electronics for Maintenance Personnel. 20. Troubleshooting.
The case of 'unwanted flexibility' : a study of temporary agency workers in the U.K.

Temporary agency work in Britain has increased dramatically in recent years. Theoretical justification for this growth is centred upon an organisational need for greater efficiency as a result of increased competition in the marketplace. Cost advantages are often associated with the temporary nature of the agency contract and recent discussion suggests that recruitment of agency workers is a strategic practice, used to create competitive advantage. (Williamson 1985; Atkinson and Meager 1986; Matuski and Hill 1998; Lepak and Snell 1999; Houseman et al 2003). Organisationally sound manpower strategies are thus reasoned to be those that deliberately incorporate agency workers in a thoughtful, strategic and continually advantageous way. From this perspective, it is assumed that management control over the contractual nature of the workforce is essential, and failure to retain this autonomy would result in organisational inefficiency. This thesis critically examines this conjecture, by investigating a situation where management cannot actively select the contracts on which they employee their staff. In the case of two Social Services departments in London, management have lost the ability to strategically determine the contractual nature of their workforce, stating a strong preference for open ended contracts, but forced to deploy agency workers when permanent staff cannot be recruited. Previous suggestions would indicate detrimental implications, but in this instance it is argued that these blanket assumptions may facilitate premature conclusions, as the associated consequences of this situation of `unwanted flexibility' are unexplored.
Artificial Intelligence And Precision Medicine For Oncology

AI can help to essentially accelerate the process of analysis of vast amounts of data, anchoring patterns in the data, resulting in faster and recommended decision-making. Sophisticated prescient models are produced using algorithms that extract the patterns from data and predict results. AI is categorized into three stages namely, artificial narrow intelligence (ANI), artificial general intelligence(AGI), and artificial super intelligence(ASI). Precision medicine is a rising methodology for disease prevention and treatment based on the specific hereditary, environment conditions, and lifestyle choices of an individual patient. AI algorithms have been found to be compelling in streamlining malignant growth screening and discovery. AI frameworks are able to recognize singular drug-response variability, making recommendations based on patterns learned from vast amounts of public and exclusive information, and can help expand the frontier of precision medicine, specially of cancer genomics.
Bloodflow modeling for heat transfer applications in cancer treatments: clinical measurements and mathematical models

14 11% "t lil' O ̂3-U. t* 1. I"! « 0 9 C « 0 0 0 0 * 0 < » * 0 0 » 0 0 0 0 0 0 0 0 « > 0 « > 0 0 * 0 « 0 * 0 < > « 0 « » « 36 Methodology Subjects. 18 Xenon Inhalation Procedure. 20 SCaUS . e e . e e . e e . e o o e . Data Acquisition . 21 Data Analysis. 27 Results. 31 Discussion. 41 Conclusions and Recommendations . 46 PART II: A VERSATILE THREE DIMENSIONAL DISCRETE BLOOD VESSEL SIMULATOR WITH REGULAR GEOMETRY Abstract . Introduction . Overall Flow and Structure Program Description . 49
CONGESTION MANAGEMENT SYSTEMS: EVALUATION ISSUES AND METHODS

Evaluation plays a central part in the development and implementation of Congestion Management Systems (CMS) as required within Transportation Management Areas under ISTEA legislation. Specifically, a Final CMS Rule issued by the Federal Highway Administration and Federal Transit Administration states "system monitoring shall be established. to evaluate the effectiveness of implemented actions. " The Rule also states, . "traditional and nontraditional systems shall be identified and evaluated based on. established performance measures. "
Non-Line-of-Sight Electro-Optic Laser Communications in the Middle Ultraviolet

Abstract : A Monte Carlo computer simulation was developed to model hypothesized electro-optic laser communication systems operating in the middle ultraviolet region of the spectrum called the solar blind. By assuming various source, propagation, and detector characteristics as well as certain performance parameters it is possible to predict the effective ranges and operating characteristics of such a system.
The Challenge of Generating Causal Hypotheses Using Network Models

Abstract Statistical network models based on Pairwise Markov Random Fields (PMRFs) are popular tools for analyzing multivariate psychological data, in large part due to their perceived role in generating insights into causal relationships: a practice known as causal discovery in the causal modeling literature. However, since network models are not presented as causal discovery tools, the role they play in generating causal insights is poorly understood among empirical researchers. In this paper, we provide a treatment of how PMRFs such as the Gaussian Graphical Model (GGM) work as causal discovery tools, using Directed Acyclic Graphs (DAGs) and Structural Equation Models (SEMs) as causal models. We describe the key assumptions needed for causal discovery and show the equivalence class of causal models that networks identify from data. We clarify four common misconceptions found in the empirical literature relating to networks as causal skeletons; chains of relationships; collider bias; and cyclic causal models.
Comment on acp-2021-601

The manuscript describes the results of an intensive field study to characterize the PM2.5 burden in a major economic region of Colombia, the Cauca River Valley (CRV), both in terms of total burden and of their sources, in particular sugarcane processing. The presented work relies on the analysis of 24 h filters, and both the major components are reported (following the IMPROVE protocol), and important additional information on possibly source profiles is gathered by the additional analysis of metal and organic markers (specifically primary BB tracers, PAHs, and alkanes). This is then complemented by a Principle Component Analysis (PCA) of the measured variables, with mixed results.
Genome-wide analysis of long non-coding RNAs (lncRNAs) in two contrasting rapeseed (Brassica napus L.) genotypes subjected to drought stress

Background: Drought stress is a major abiotic factor that affects rapeseed ( Brassica napus L.) productivity. Though previous studies indicated that long non-coding RNAs (lncRNAs) play a key role in response to drought stress, a scheme for genome-wide identification and characterization of lncRNAs’ response to drought stress is still lacking, especially in the case of B . napus . In order to further understand the molecular mechanism of the response of B . napus to drought stress, we compared changes in the transcriptome between Q2 (a drought-tolerant genotype) and Qinyou8 (a drought-sensitive genotype) in response to drought stress and rehydration treatment at the seedling stage. Results: A total of 5,546 down-regulated and 6,997 up-regulated mRNAs were detected in Q2 compared with 7,824 and 10,251 in Qinyou8, respectively; 369 down-regulated and 108 up-regulated lncRNAs were detected in Q2 compared with 449 and 257 in Qinyou8, respectively. We further identified 34 TFs corresponding to 126 differently expressed lncRNAs in Q2, and 45 TFs corresponding to 359 differently expressed lncRNAs in Qinyou8. Differential expression analysis of lncRNAs indicated that up- and down-regulated mRNAs co-expressed with lncRNAs participated in different metabolic pathways and were involved in different regulatory mechanisms in the two genotypes . Notably, some lncRNAs were co-expressed and co-located with BnaC07g44670D, which are associated with plant hormone signal transduction. Additionally, some mRNAs which were co-located with LNC_002535 (XLOC_052298), LNC_004924 (XLOC_094954) and LNC_000539 (XLOC_012868) were mainly categorized as signal transport and defense/stress response. Finally, co-expression network analysis indicated that the co-expression network of Q2 was composed of 145 network nodes and 5,175 connections, while the co-expression network of Qinyou8 was composed of 305 network nodes and 22,327 connections. Conclusions: The differentially expressed mRNAs and lncRNAs may play important roles in response to drought stress and rehydration treatments and could provide basic information for new ways to improve the drought resistance of Rapeseed Brassica napus .
Extraction of Pectin from Breadnut Fruit (Artocarpus altilis Fosberg.) with Citric Acid

Pectin is a complex polysaccharide that is found in the primary cell wall of higher plants. Pharmaceutically, pectin has been used as a gelling agent, thickener, stabilizer emulsifier, and edible coating in the food industry. The purpose of this study was to extract and characterize the isolated pectin from breadnut fruit ( Artocarpus altilis Fosberg). Extraction was conducted by using 1% citric acid (pH adjusted to 2, temperature 90 o C) in the variation of times (2 and 3 hours). Furthermore, the yield and characteristics of pectin were evaluated statistically. The results showed that no significant differences in yield, water content, ash content, equivalent weight, and degree of esterification of pectin when extraction was conducted at different times (2 and 3 hours). Variation time of extraction only showed a significant effect on the methoxyl contents and galacturonic acid contents of pectin.
Learning to understand what the ERP system is all about: A literature review.

The purpose of an enterprise resource planning (ERP) system is to bring several benefits to the company by using a mutual database and real time data. Though, empirical studies show that several companies judge the ERP project as unsuccessful. Research has tried to explain why users are disappointed with the ERP system, but findings are scattered and inconsistent. There is need for further development of our knowledge on how ERP systems are viewed and used in companies. Organizational learning (OL) is a concept that has been used in research within the fields of organization theory and management. Still, only a few empirical studies have been conducted on OL in the context of ERP systems. To what extent and how do research conceptualize the ERP system as involved in the organizational learning process? The paper is a review of research on OL in the context of ERP systems: selection, implementation and use. Twelve articles were found in full text. The purpose is to compare and contrast approaches in order to analyze similarities and dissimilarities. The analysis shows that overall there is a lack of definitions and stringency in research on OL and ERP systems. The complexity of the ERP system and how that can be understood, how the artifact functions or interplays with the organization and the organizing process, is seldom discussed in greater detail. If learning in organizations, at least partially, depends on the use of enabling technologies, it would be a worthwhile effort to analyze more closely how, when and why an ERP system can be used in this respect. A major suggestion for future research is that it should be more explicitly engaged with the relationship between OL and the ERP system. Regarding the ERP system as a part of the organizational memory might be a fruitful way to go.
THE NEW DRIVING FORCE

Novem, the Netherlands agency for energy and the environment, plays an important role in implementing sustainable traffic and transport policies. On behalf of the Dutch government Novem manages several programmes covering research and development, testing and implementing various ways of saving energy and reducing pollution by using technological solutions and logistical concepts. One of the programmes is 'The New Driving Force', the former 'Buy eco-wise, Drive eco-nice' programme, which aims to change the attitudes and actions of various target groups by encouraging them to buy and use cars, delivery vans, lorries and buses in a more energy-efficient and environmentally friendly way. Since 1992 a lot of experience has been gained on subjects as company registration and auto-monitoring systems as well as onboard equipment. The effects have been studied in experimental and demonstration projects, In this article the focus is on passenger cars. For the covering abstract see ITRD E110582.
Manufacturing Cell Design: An Integer Programming Model Employing Genetic Algorithms

The design of a cellular manufacturing system requires that a part population, at least minimally described by its use of process technology (part/machine incidence matrix), be partitioned into part families and that the associated plant equipment be partitioned into machine cells. At the highest level, the objective is to form a set of completely autonomous units such that inter-cell movement of parts is minimized. We present an integer program that is solved using a genetic algorithm (GA) to assist in the design of cellular manufacturing systems. The formulation uses a unique representation scheme for individuals (part/machine partitions) that reduces the size of the cell formation problem and increases the scale of problems that can be solved. This approach offers improved design flexibility by allowing a variety of evaluation functions to be employed and by incorporating design constraints during cell formation. The effectiveness of the GA approach is demonstrated on several problems from the literature.