Set Of Objects Research Articles

Optimal planning of distributed generation and energy storage systems in DC distribution networks with application of category-based multi-objective algorithm

The strategic positioning and appropriate sizing of Distributed Generation (DG) and Battery Energy Storage Systems (BESS) within a DC delivery network are crucial factors that influence its economic feasibility and dependable performance. To tackle this vital aspect, we have formulated a multi-objective optimization model aimed at determining the most advantageous locations and capacities for DG and BESS. Our approach establishes a framework for multi-objective optimization that systematically addresses all objectives, minimizing bias towards any specific set of objectives and enhancing overall efficiency. Furthermore, from a variety of collective objectives we introduce an improved Multi-Objective Particle Swarm Optimizer (IMOPSO) tailored to produce and choose Pareto best solutions. To identify the best placement and sizing options for DG and BESS among the Pareto optimal solutions, we apply the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) strategy, integrating an information entropy method. We have conducted simulations using the 33-bus DC distribution grid of IEEE to validate the practical benefits of our suggested methodology.

Experiences of faculty and students regarding a locally developed framework for implementing interprofessional education during international electives in Sub-Saharan Africa

BackgroundGiven that there are hardly any comprehensive frameworks to guide institutions on approaches to use as they implement interprofessional education and collaborative practice during international electives, we developed and piloted a framework to address this gap. The purpose of this study, therefore, was to explore the experiences of faculty and students regarding the use of the developed interprofessional education and collaborative practice framework during international electives.MethodsThis was an exploratory qualitative study. The study participants included faculty and students from four health training universities in Africa who participated in the pilot of international electives guided by the framework developed. Deductive thematic analysis was used to analyze the data. The codes were categorized as per the major themes.ResultsThe major themes regarding the framework included (1) The Strengths, (2) Weaknesses, (3) Opportunities, and (4) Threats. All participants perceived the framework as useful and appropriate to enable the acquisition of interprofessional education and collaborative practice skills objectives set. The framework’s duration of the elective was seen as a weakness with the need for an increment in the duration. The opportunities the framework presented included: acting as a starting point to structure and implement interprofessional education across various training institutions in Africa, advancing research, and networking opportunities to share the best practices. The main threat included siloed training where the current training curriculum of the students does not have opportunities that allow the students to study with, from, and about each other.ConclusionsThe framework developed to guide the implementation of interprofessional education and collaborative practice during international electives is feasible and enabled students to achieve the interprofessional education and collaborative practice objectives set while appreciating the transcultural similarities and differences in another country.

Discrete-event modelling of container terminal cargo fronts

The basis for designing and upgrading new sea ports and container terminals is regulatory documentation. A part of designing a new sea port is making key technological decisions, including on calculating its cargo throughput capacity. However a method for capacity evaluation of operating ports is not described in the regulatory documents. Operating cargo terminals often undergo significant changes since the moment they were put into operation. Equipment, resources and infrastructure of cargo fronts should not be the only thing taken into consideration when evaluating an existing container terminal capacity. The way in which a terminal interacts with external transport systems (railroad, vessel fleet, etc.) as well as interactions between cargo fronts inside a terminal should also be considered. A discrete- event simulation model for the system consisting of a railroad cargo front, a container yard and a berth cargo front of a container terminal is proposed in the paper. This model allows to evaluate the balance between calls of different modes of transport (vessel calls, cargo train calls), as well as the impact of this balance on the state of container yard and on the terminal cargo throughput capacity in general. Container terminal in terms of proposed model is not merely a set of unrelated objects, but a system. In such system interaction with one of elements has influence on all the others. The model is described as mathematical dependencies between key variables. Cargo train and vessel calls generation is performed via standard spreadsheet methods. To acquire more accurate results, specific sea port statistical data should be used.

Effects of Marketing Strategies on the Brand Positioning of a Tourist Hotel, Bagua – Peru

Purpose: The general objective is to determine the effect of marketing strategies on the brand positioning of a tourist hotel, Bagua-Peru. Theoretical framework: The theory found allowed us to deepen the subject since, due to the pandemic, research in the tourism sector has increased, helping researchers to deepen the study. Design/methodology/approach: A mixed approach was used, under a basic, descriptive, and correlational type of research. Also, the non-experimental and phenomenological designs were considered, applying the survey made to 51 guests and interviewing 3 hotel employees, such as the manager, receptionist, and administrator. Findings: The descriptive results revealed that, when the marketing strategies are inappropriate, the brand positioning will be a completely inadequate. On the other hand, the inferential results indicated that both variables reached a r=0.663 and a Kendall's Tau-b of 0.656, thus indicating that both maintain a considerable positive correlation. Research, Practical & Social implications: If prices are based on three key points, as in the client, costs and competition, as long as the adequate distribution channels are considered according to the needs of the clients and an efficient booking system is implemented, and if we add announcements in the different physical and digital platforms that the company has, then it will be able to provide a good organizational communication allowing to achieve the objectives set and therefore this company will achieve the long-awaited brand positioning in the mind of the consumer. Originality/value: The lack of marketing strategies generates that the innovative characteristics of the products or services of the companies are not made known to their clients, and as a consequence the company does not have a marked differentiation from its competitors and does not achieve the market positioning.

On efficiency and the Jain’s fairness index in integer assignment problems

Given two sets of objects, the integer assignment problem consists of assigning objects of one set to objects in the other set. Traditionally, the goal of this problem is to find an assignment that minimizes or maximizes a measure of efficiency, such as maximization of utility or minimization of cost. Lately, the interest in incorporating a measure of fairness in addition to efficiency has gained importance. This paper studies how to incorporate these two criteria in an integer assignment, using the Jain’s index as a measure of fairness. The original formulation of the assignment problem with this index involves a non-concave function, which renders a non-linear non-convex problem, usually hard to solve. To this aim, we develop two reformulations, where one is based on a quadratic objective function and the other one is based on integer second-order cone programming. We explore the performance of these reformulations in instances of real-world data derived from an application of assigning personnel to projects, and also in instances of randomly generated data. In terms of solution quality, all formulations prove to be effective in finding solutions capturing both efficiency and fairness criteria, with some slight differences depending on the type of instance. In terms of solving time, however, the performances of the formulations differ considerably. In particular, the integer quadratic approach proves to be much faster in finding optimal solutions.

Methods of Multi-Criteria Judgment and Selection of Objects Based on Relations with the k-th Order of Strict Preference

Methods of multi-criteria judgment and selection of objects based on the resulting relation with the к -th order of their strict preference are proposed. It is shown that the resulting Pareto and Slater dominance relations are a special case of the resulting relationship with the k-th order of strict preference. A detailed analysis of the method of narrowing the set of nondominable objects, which is based on the coefficient of relative importance (coefficient of compromise) for a pair of criteria, is carried out. Based on the example when one criterion is more important than another in advance, it is shown that there is no need to recalculate the vector estimates of objects, since the initial set of estimates narrows if one simply excludes a less important criterion from consideration. The presented methods of multi-criteria judgment and selection of objects do not require additional expert information on the importance of criteria, are mathematically justified and illustrated by an example.

Search for a possible quasi-periodic structure based on data of the SDSS DR12 LOWZ

ABSTRACT We carry out a statistical analysis of the spatial distribution of galaxies at cosmological redshifts 0.16 ≤ z ≤ 0.47 based on the SDSS DR12 LOWZ catalogue. Our aim is to search and study possible large-scale quasi-regular structures embedded in the cosmic web. We calculate projections of the Cartesian galaxy coordinates on different axes (directions), densely covering certain regions in the sky to look for special directions along which 1D distributions of the projections contain significant quasi-periodic components. These components appear as peaks in the power spectra and lie in a narrow range of wave numbers 0.05 < k < 0.07. Particular attention is paid to the evaluation of the significance of the peaks. It is found that the significance of the dominant peaks for some selected directions exceeds (4–5)σ. In order to reduce possible selection effects, we create a mock homogeneous catalogue of spatial distribution of galaxies by adding a random set of artificial objects (points) to the real galaxies under study. The power spectrum of this cumulative model data also demonstrates significant peak corresponding to approximately the same scale. As a result we assume the existence of an anisotropic cosmological quasi-periodic structure with characteristic scale (116 ± 10) h−1 Mpc.

Neural and behavioral signatures of the multidimensionality of manipulable object processing

Understanding how we recognize objects requires unravelling the variables that govern the way we think about objects and the neural organization of object representations. A tenable hypothesis is that the organization of object knowledge follows key object-related dimensions. Here, we explored, behaviorally and neurally, the multidimensionality of object processing. We focused on within-domain object information as a proxy for the decisions we typically engage in our daily lives – e.g., identifying a hammer in the context of other tools. We extracted object-related dimensions from subjective human judgments on a set of manipulable objects. We show that the extracted dimensions are cognitively interpretable and relevant – i.e., participants are able to consistently label them, and these dimensions can guide object categorization; and are important for the neural organization of knowledge – i.e., they predict neural signals elicited by manipulable objects. This shows that multidimensionality is a hallmark of the organization of manipulable object knowledge.

Fractional Reasoning: Fostering Fundamental Knowledge

Fractional reasoning is a crucial aspect of mathematical understanding that plays a fundamental role in various mathematical concepts, real-world applications, and higher-level mathematical skills. The ability to comprehend and work with fractions is essential for students to develop a solid foundation in mathematics. However, fractional reasoning is often a challenging area for many students, requiring a deep understanding of concepts such as equivalence, ordering, operations, and connections to other mathematical domains. This study aimed to investigate to what extent primary school pupils develop fractional reasoning and the ability to solve related problems. The research involved a sample of eight primary school pupils from Perak (in Malaysia) participating in an interview. The findings revealed that the participants relied on representation methods of enactive and symbolic representations when working on fractions of an area, while they predominantly utilised symbolic representations when determining fractions for a set of objects. These results shed light on the students' fractional reasoning strategies, which are required in solving many other problems in the context of mathematical tasks. Based on the findings, it is recommended that educators employ instructional strategies such as representations that promote fractional reasoning, such as incorporating real-world contexts, to foster students' understanding and proficiency in addressing complex mathematical challenges. Keywords: Representation, Enactive, Symbolic, Fractions, Fractional Reasoning

Making pushbacks public: Secrecy, material witnesses and devices of dis/appearance

In early 2021, the European Parliament established the Frontex Scrutiny Working Group (FSWG) to monitor all aspects of the functioning of the European Border and Coast Guard Agency (Frontex). The FSWG organized a series of public hearings and carried out a ‘fact-finding’ investigation to gather information and evidence about pushbacks of refugees in the Aegean Sea. By unpacking some of the controversies that emerged during the hearings of the FSWG, I explore how secrecy was practised and strategically employed to obscure the responsibility of Frontex for the reported pushbacks, and how it was contested through the presentation of related evidence. I explain how secrecy and related controversies and struggles over making pushbacks public involve a variety of actors that enrol and interact with a heterogeneous set of objects, including digital, visual and archival traces of violence at sea, as well as databases used to record information about maritime incidents. I argue that secrecy regarding pushbacks is not just about keeping information about people and objects involved in security operations hidden. Secrecy is also produced through the selective recording, (mis)categorization and circulation of information in the name of transparency.

Are they equivalent? An examination of task variants of approximate number comparison.

Nonverbal numerical ability supports individuals' numerical information processing in everyday life and is also correlated with their learning of mathematics. This ability is typically measured with an approximate number comparison paradigm, in which participants are presented with two sets of objects and instructed to choose the numerically larger set. This paradigm has multiple task variants, where the two sets are presented in different ways (e.g., two sets are presented either simultaneously or sequentially, or two sets are presented either intermixed or separately). Despite the fact that different task variants have often been used interchangeably, it remains unclear whether these variants measure the same aspects of nonverbal numerical ability. Using a latent variable modeling approach with 270 participants (Mage = 20.75 years, SDage = 2.03, 94 males), this study examined the degree to which three commonly used task variants tapped into the same construct. The results showed that a bi-factor model corresponding to the hypothesis that task variants had both commonalities and uniqueness was a better fit for the data than a single-factor model, corresponding to the hypothesis that task variants were construct equivalent. These findings suggested that task variants of approximate number comparison did not measure the same construct and cannot be used interchangeably. This study also quantified the extent to which general cognitive abilities were involved in both common and unique parts of these task variants.

Tac2Pose: Tactile object pose estimation from the first touch

In this paper, we present Tac2Pose, an object-specific approach to tactile pose estimation from the first touch for known objects. Given the object geometry, we learn a tailored perception model in simulation that estimates a probability distribution over possible object poses given a tactile observation. To do so, we simulate the contact shapes that a dense set of object poses would produce on the sensor. Then, given a new contact shape obtained from the sensor, we match it against the pre-computed set using an object-specific embedding learned using contrastive learning. We obtain contact shapes from the sensor with an object-agnostic calibration step that maps RGB (red, green, blue) tactile observations to binary contact shapes. This mapping, which can be reused across object and sensor instances, is the only step trained with real sensor data. This results in a perception model that localizes objects from the first real tactile observation. Importantly, it produces pose distributions and can incorporate additional pose constraints coming from other perception systems, multiple contacts, or priors. We provide quantitative results for 20 objects. Tac2Pose provides high accuracy pose estimations from distinctive tactile observations while regressing meaningful pose distributions to account for those contact shapes that could result from different object poses. We extend and test Tac2Pose in multi-contact scenarios where two tactile sensors are simultaneously in contact with the object, as during a grasp with a parallel jaw gripper. We further show that when the output pose distribution is filtered with a prior on the object pose, Tac2Pose is often able to improve significantly on the prior. This suggests synergistic use of Tac2Pose with additional sensing modalities (e.g., vision) even in cases where the tactile observation from a grasp is not sufficiently discriminative. Given a coarse estimate of an object’s pose, even ambiguous contacts can be used to determine an object’s pose precisely. We also test Tac2Pose on object models reconstructed from a 3D scanner, to evaluate the robustness to uncertainty in the object model. We show that even in the presence of model uncertainty, Tac2Pose is able to achieve fine accuracy comparable to when the object model is the manufacturer’s CAD (computer-aided design) model. Finally, we demonstrate the advantages of Tac2Pose compared with three baseline methods for tactile pose estimation: directly regressing the object pose with a neural network, matching an observed contact to a set of possible contacts using a standard classification neural network, and direct pixel comparison of an observed contact with a set of possible contacts. Website: mcube.mit.edu/research/tac2pose.html

Children’s use of reasoning by exclusion to infer objects’ identities in working memory

Reasoning by exclusion allows us to form more complete representations of our environments, “filling in” inaccessible information by ruling out known alternatives. In two experiments (Experiment 1: N = 34 4- to 6-year-olds; Experiment 2: N = 85 4- to 8-year-olds), we examined children’s ability to use reasoning by exclusion to infer the identity of an unknown object and investigated the role of working memory in this ability. Children were asked to encode a set of objects that were then hidden, and after a brief retention interval children were asked to select the identity of the object hidden in one of the locations from two alternatives. On some trials, all the images were visible during encoding, so selecting the correct identity when probed required successful working memory storage and retrieval. On other trials, all but one of the images was visible during encoding, so selecting the correct identity when probed also required maintaining a representation of an unknown object in working memory and then using reasoning by exclusion to fill in the missing information retroactively to complete that representation by ruling out known alternatives. To investigate the working memory cost of exclusive reasoning, we manipulated the working memory demands of the task. Our results suggest that children can use reasoning by exclusion to retroactively assign an identity to an incomplete object representation at least by 4 years of age but that this ability incurs some cognitive cost, which eases with development. These results provide new insights into children’s representational capacities and on the foundational building blocks of fully developed exclusive reasoning.

Standardised images of novel objects created with generative adversarial networks

An enduring question in cognitive science is how perceptually novel objects are processed. Addressing this issue has been limited by the absence of a standardised set of object-like stimuli that appear realistic, but cannot possibly have been previously encountered. To this end, we created a dataset, at the core of which are images of 400 perceptually novel objects. These stimuli were created using Generative Adversarial Networks that integrated features of everyday stimuli to produce a set of synthetic objects that appear entirely plausible, yet do not in fact exist. We curated an accompanying dataset of 400 familiar stimuli, which were matched in terms of size, contrast, luminance, and colourfulness. For each object, we quantified their key visual properties (edge density, entropy, symmetry, complexity, and spectral signatures). We also confirmed that adult observers (N = 390) perceive the novel objects to be less familiar, yet similarly engaging, relative to the familiar objects. This dataset serves as an open resource to facilitate future studies on visual perception.

Incremental Learning Based on Granular Ball Rough Sets for Classification in Dynamic Mixed-Type Decision System

Granular computing, a new paradigm for solving large-scale and complex problems, has made significant progresses in knowledge discovery. Granular ball computing (GBC) is a novel granular computing method, which can rapidly generate scalable and robust information granules, that is, granular balls. However, a comprehensive index for measuring the performance of a granular ball does not exist. Furthermore, GBC lacks a mechanism to deal with dynamic decision systems. Therefore, in this study, the quality index of a granular ball is first formulated. Next, with this index, a novel granular ball rough sets model (GBRS) based on GBC is proposed. GBRS is more conducive to learning knowledge from uncertain datasets and more suited to incremental learning than the latest granular ball neighborhood rough sets model based on GBC. Subsequently, an incremental mechanism is introduced into GBRS, and two incremental learning models are developed for objects increasing in stream patterns and batch patterns, respectively. In the incremental learning process, three patterns of granular balls, that is, update, fusion, and split, were well studied when a set of objects was added to the decision system. Finally, to verify the effectiveness and efficiency, we apply GBRS and these two incremental learning models into classification tasks. Compared with four current state-of-the-art classification methods based on granular computing and four classical classifiers in machine learning, the proposed classifiers in this paper achieve higher classification accuracy as well as better efficiency on benchmark datasets.

Proof of Concept for a Data-Driven Vr Spatial Disorientation Training Tool for Navy Pilots

Spatial disorientation (SD) contributes to at least 30% of aviation mishaps, with most being fatal. These mishaps involve not only complex interactions between human, machine, mission, and environment, but also multiple internal neurophysiological systems. Given the complexity of these dynamics, SD competency (i.e., the ability to recognize, confirm, and recover from an SD incident) is hard to predict and teach in the classroom. The Aptima team has developed a data-driven, practical, and realistic virtual reality (VR) training platform for SD called MAVIS, which includes a set of subjective, objective (performance), and physiological measures to rigorously evaluate SD competencies. Preliminary results of this proof of concept confirm the validity of our theoretical framework with a small sample, although rigorous experimentation with a larger sample will be required to validate the approach and justify its operational use. These preliminary results indicated that (1) the MAVIS protocol induces SD; and (2) self-report, performancebased, and neurophysiological measures seem to associate with SD induction and its sequelae.

Konsep Kependudukan Program KB di Indonesia dan Organisasi KB untuk Kesehatan

The objective of the research is to explain the history of UN in Indonesia, to overcome the factors that influence the development of UN, to explain UN organizations in Indonesia and UN programmes in Indonesia. To explain the concept of family planning. This method of research is a type of descriptive research, which means that this research describes an object, phenomenon, or social setting in the form of writing containing a quotation of data or facts or natural manifestations in the field. The results of the research are from the above description we conclude that the family planning program is an attempt to enhance the care and role as well as society through adult marriage age (PUP), birth arrangement, building family resilience, improving the well-being of small families, happiness and prosperity. The main objective of the National Commission's program is to fulfil the public's orders to provide quality reproductive health services, lower the levels of I.C.I. and I.B. as well as overcome reproductive-health problems in order to build quality small families.

A principled link between object naming and representation is available to infants by seven months of age

By their first birthdays, infants represent objects flexibly as a function of not only whether but how the objects are named. Applying the same name to a set of different objects from the same category supports object categorization, with infants encoding commonalities among objects at the expense of individuating details. In contrast, applying a distinct name to each object supports individuation, with infants encoding distinct features at the expense of categorical information. Here, we consider the development of this nuanced link between naming and representation in infants’ first year. Infants at 12 months (Study 1; N = 55) and 7 months (Study 2; N = 96) participated in an online recognition memory task. All infants saw the same objects, but their recognition of these objects at test varied as a function of how they had been named. At both ages, infants successfully recognized objects that had been named with distinct labels but failed to recognize these objects when they had all been named with the same, consistent label. This new evidence demonstrates that a principled link between object naming and representation is available by 7 months, early enough to support infants as they begin mapping words to meaning.

Cross connection compatible discrete normal categories

The concept of normal category was introduced by Nambooripad in his theory of cross connections for describing the structure of regular semigroups. These are essentially the categories of principal left ideals and the categories of principal right ideals of regular semigroups with appropriate morphisms. These categories also have an associated partial order on the set of objects. Discrete normal categories are normal categories in which the partial order on the object set is the identity relation. A cross connection relates two normal categories [Formula: see text] and [Formula: see text] and produces a regular semigroup [Formula: see text] such that one is the category of principal left ideals and the other the category of principal right ideals of the semigroup [Formula: see text]. This paper considers the question of compatibility of two normal categories in order that they can be connected by a cross connection. It is known that given any normal category [Formula: see text] there is a normal category [Formula: see text] called the normal dual of [Formula: see text] such that [Formula: see text] is compatible with [Formula: see text]. The question of finding all normal categories [Formula: see text] that are compatible with a given normal category [Formula: see text] remains unsettled. Such categories [Formula: see text] are called compatible duals of [Formula: see text]. For the class of discrete normal categories the characterization of all compatible duals has been done here.

Probability confidence correlation analysis for many‐objective optimal operation considering a set of conflict interests

AbstractAs the proportion of renewable energy penetrated in power systems further increases, the optimal operation faces a large obstacle to satisfying various conflict interests simultaneously. This paper first formulates a many‐objective optimal operation problem of the new power system considering a comprehensive set of economic, environmental, and reliable objectives. To figure out this problem efficiently, this paper proposes a probability confidence correlation analysis method (PCCA) utilizing a t‐distributed stochastic neighbor embedding (T‐SNE) standard to greatly preserve the distribution information and separability of the objectives. Consequently, the objectives can be aggregated and the objective dimension is reduced based on the important sorting and correlation of the objectives. Based on the outcome of the T‐SNE, the adopted optimal operation problem with low dimensional objectives is solved by a multiple producer group search optimizer (GSOMP) with less computation burden, to obtain the Pareto‐optimal solution set. Simulation studies are conducted on IEEE 30‐bus, 39‐bus and 57‐bus systems to investigate the performance of the proposed PCCA in terms of efficiency and accuracy, making comparisons of the existing many‐objective optimization algorithms.