Object Selection Research Articles

A comparison of applicant and accepted student characteristics to research training programs with implications for recruitment and selection strategy

IntroductionVery few studies have examined the relationship between student characteristics and their acceptance to research training programs that use holistic selection. The present study addressed this question using institutional and applicant data of three NIH undergraduate training programs at California State University, Long Beach. Its first aim was to examine whether the applicants to the training programs were representative of the broader campus population. Its second aim was to investigate whether applicants who were accepted to the programs using a holistic selection process differed in academic discipline, demographics, and psychosocial characteristics from applicants who were not accepted.MethodsInformation on students’ majors, race/ethnicity, and gender was obtained from the university records or applications submitted by students. Majors were categorized as either biomedical or behavioral disciplines, while URM status was defined as students who self-identified their race and ethnicity as African American/Black, Native American, Native Hawaiian/Pacific Islander, or Hispanic. Applicants’ psychosocial characteristics were obtained from a separate online survey. The acceptance status of applicants was obtained from the training programs’ records.ResultsThe applicant and non-applicant groups showed similar distribution of demographic characteristics regarding URM status and gender. Moreover, students’ academic discipline and other demographic variables were not associated with application status at either the lower division (LD) or upper division (UD) levels. Although psychosocial characteristics measured with the online survey were not considered in the selection process, post-hoc analyses showed that LD applicants with higher grit and UD applicants with higher science interests were more likely to be accepted to the programs.ConclusionThe equal representation of URM and female students in the applicant and non-applicant groups suggests that students from these traditionally underrepresented groups in STEM were just as likely to apply to our training programs. Furthermore, while the holistic selection process resulted in comparable acceptance rates across URM status and gender, it appeared to favor LD applicants with higher grit and UD students with higher science interests. These findings imply that research training programs can effectively recruit diverse students from underrepresented populations in STEM by using intentional outreach and recruitment efforts coupled with an objective and holistic selection process.

Manipulable cone based bare hand object selection in high occlusion virtual environment

Manipulable cone based bare hand object selection in high occlusion virtual environment

Relationship between functional structures and horizontal connections in macaque inferior temporal cortex

Horizontal connections in anterior inferior temporal cortex (ITC) are thought to play an important role in object recognition by integrating information across spatially separated functional columns, but their functional organization remains unclear. Using a combination of optical imaging, electrophysiological recording, and anatomical tracing, we investigated the relationship between stimulus-response maps and patterns of horizontal axon terminals in the macaque ITC. In contrast to the “like-to-like” connectivity observed in the early visual cortex, we found that horizontal axons in ITC do not preferentially connect sites with similar object selectivity. While some axon terminal patches shared responsiveness to specific visual features with the injection site, many connected to regions with different selectivity. Our results suggest that horizontal connections in anterior ITC exhibit diverse functional connectivity, potentially supporting flexible integration of visual information for advanced object recognition processes.

Artificial intelligence models assisting physicians in quantifying pancreatic necrosis in acute pancreatitis.

Acute pancreatitis (AP) is a potentially life-threatening condition characterized by inflammation of the pancreas, which can lead to complications such as pancreatic necrosis. The modified computed tomography severity index (MCTSI) is a widely used tool for assessing the severity of AP, particularly the extent of pancreatic necrosis. The accurate and timely assessment of the necrosis volume is crucial in guiding treatment decisions and improving patient outcomes. However, the current diagnostic process relies heavily on the manual interpretation of computed tomography (CT) scans, which can be subjective and prone to variability among clinicians. This study aimed to develop a deep-learning network model to assist clinicians in diagnosing the volume ratio of pancreatic necrosis based on the MCTSI for AP. The datasets comprised retrospectively collected plain and contrast-enhanced CT scans from 144 patients (6 with scores of 0 points, 42 with scores of 2 points, and 65 with scores of 4 points) and the National Institutes of Health contrast-enhanced CT scans from 45 patients with scores of 0 points. An improved fully convolutional neural networks for volumetric medical image segmentation (V-Net) model was developed to segment the pancreatic volume (i.e., the whole pancreas, necrotic pancreatic tissue, and non-necrotic pancreatic tissue) and to quantify the split volume ratios. The improved strategy included three stages of body up- and down-sampling adapted to the task of segmentation in AP, and the selection of objects, loss function, and smoothing coefficients. The model interpretations were compared with those of clinicians with different levels of experience. The reference standard was manually segmented by a pancreatic radiologist. Accuracy, macro recall, and macro specificity were employed to compare the diagnostic efficacy of the model and the clinicians. In total, 144 patients (mean age: 44±13 years; 40 females, 104 males) were included in the study. Optimal training results were obtained using the necrotic pancreatic tissue and whole pancreas as the input objects, and combining dice loss and 500 smoothing coefficients as the loss function for training. The dice coefficient for the whole pancreas was 0.811 and that for the necrotic pancreatic tissue was 0.761. The performance of the artificial intelligence model and clinicians were compared. The accuracy, macro recall, and macro specificity of the improved V-net were 0.854, 0.850 and 0.923, respectively, which were all significantly higher than those of the senior and junior clinicians (P<0.05). Our proposed model could improve the effectiveness of clinicians in diagnosing pancreatic necrosis volume ratios in clinical settings.

Strategic Recruitment of Civil Servant Candidates at BPK RI: Developing Professional Auditors

This research analyzes the implementation of strategic human resource management (HRM) in the recruitment process of Civil Servant Candidates (CPNS) at the Audit Board of the Republic of Indonesia (BPK RI). This process is designed to address the challenge of the need for highly professional and high-integrity personnel while simultaneously creating new innovations in transparency and accountability in public sector recruitment. This study uses a qualitative approach with a case study method, involving in-depth interviews with relevant officials at the BPK RI Human Resources Bureau and direct observations at the recruitment stages. The research results show that the strategic approach begins with meticulous workforce planning, involving long-term needs projections and formation analysis. Merit-based selection is implemented through the use of e-recruitment technology, including Computer-Assisted Test (CAT) to ensure an objective, transparent, and efficient selection process. Additionally, psychological and psychiatric assessments are conducted to evaluate candidates thoroughly, both in terms of technical competencies and personal attributes such as emotional stability and teamwork abilities. This strategic approach not only ensures alignment between the organization's needs and the candidates' qualifications but also supports the enhancement of HR quality through holistic evaluation. The conclusion of this research is that the implementation of innovative HR strategies can strengthen public trust in the recruitment process and support organizational efficiency. These findings make an important contribution to public sector HR management, while also serving as a reference for improving recruitment practices in other government agencies.

Distributed Cortical Regions for the Recall of People, Places, and Objects.

The human medial parietal cortex (MPC) is recruited during multiple cognitive processes. Previously, we demonstrated regions specific to recall of people or places and proposed that the functional organization of MPC mirrors the category selectivity defining the medial-lateral axis of the ventral-temporal cortex (VTC). However, prior work considered recall of people and places only, and VTC also shows object selectivity sandwiched between face- and scene-selective regions. Here, we tested a strong prediction of our proposal: like VTC, MPC should show a region specifically recruited during object recall, and its relative cortical position should mirror the one of VTC. While responses during people and place recall showed a striking replication of prior findings, we did not observe any evidence for object-recall effects within MPC, which differentiates it from the spatial organization in VTC. Importantly, beyond MPC, robust recall effects were observed for people, places, and objects on the lateral surface of the brain. Place-recall effects were present in the angular gyrus, frontal eye fields, and peripheral portions of the early visual cortex, whereas people recall selectively drove response in the right posterior superior temporal sulcus. Object-recall effects were largely restricted to a region posterior to the left somatosensory cortex, in the vicinity of the supramarginal gyrus. Taken together, these data demonstrate that while there are distributed regions active during recall of people, places, and objects, the functional organization of MPC does not mirror the medial-lateral axis of VTC but reflects only the most salient features of that axis-namely, representations of people and places.

Development and Validity Evaluation of a National Digital Entrance Examination Test for Higher Education Student Selection

ABSTRACTHigher education institutions need to develop valid, fair, and objective selection methods. Current literature reporting the development and validation of new national large‐scale selection tests is scarce. This two‐phased study aimed to (1) develop and (2) evaluate the validity of the Finnish digital Universities of Applied Sciences Entrance Examination (UAS Exam). In phase 1 (years 2018–2019), the UAS exam sections were constructed using scoping reviews, document analysis, and expert evaluations. Pilot tests were performed for item analysis using Item Response Theory (IRT). In phase 2, validity evaluation was conducted in a cross‐sectional design (October–November 2019) using classical test theory and IRT. The applicants' (n = 13,048) exam scores and the difficulty levels of the exam questions varied in all the exam sections. Psychometrics supported the structure and the use of several exam sections. The usability of the digital exam was evaluated as acceptable. Item analysis revealed development needs in the exam sections.

The Role of Art Conservation in Preserving the Cultural Value of Seven Busts in the Plaza of the Faculty of Fine Arts, ISI Yogyakarta

The seven busts in the plaza of the Faculty of Fine Arts ISI Yogyakarta are monuments honoring the contributions of the predecessors. The seven statues hold significant cultural value within the ISI Yogyakarta community and its surroundings. However, the condition of the seven statues is currently concerning because their existence is threatened by various destructive agents. If they do not receive immediate conservation treatment, it is feared that physical damage will affect the decline in the cultural value of the statues. This research aims to explore the role of art conservation in preserving the cultural value of seven busts in the Plaza of the Faculty of Fine Arts at ISI Yogyakarta. This study focuses on the seven busts in the Plaza of the Faculty of Fine Arts at ISI Yogyakarta, with considerations of relevance, cultural significance, and accessibility as the basis for object selection. Qualitative research methods were used to understand the role of art conservation in preserving the cultural value of the seven busts, with data collection through structured interviews, field observations, and literature studies. Data analysis was conducted systematically to uncover findings related to the cultural significance and the meaning of art conservation of the research objects. The results of the observation show that the physical damage occurring not only threatens the visual beauty of the statue but also has the potential to diminish the symbolic meaning possessed by each statue. The findings of this research highlight the importance of immediate conservation actions to preserve the physical form of the statues. Conservation is not only necessary to maintain the physical condition but also to preserve the cultural significance contained in the seven busts. Based on the findings of this research, strategic steps are needed regarding the preservation of the seven busts.

Visual Functions in Patients With Leber Hereditary Optic Neuropathy (LHON)

Background: Most of the data on visual functions in Leber hereditary optic neuropathy (LHON) is based on patient questionnaires. Our study assessed the impact of LHON on visual function by testing facial recognition and execution of purposeful actions. Methods: Twelve participants with LHON with central scotoma ranging from 5° to 20° and 12 unaffected age-matched controls were involved in our study. In the face recognition test, participants were asked to recognize the sex and the facial expression of photographs of faces increasing in size to simulate approaching faces. In the purposeful action test, they were asked to manipulate real objects while their eye movements were recorded. Results: Although most patients were able to recognize the correct sex of a face at a size corresponding to a 1-m viewing distance, recognition of facial expressions was severely impaired. Patients were slower than control subjects in executing purposeful tasks. A dynamic strategy to sample information needed for the execution of a task was documented in a longer scanpath and in higher frequency of saccades and fixation eye movements in patients than in control subjects. Conclusions: Face perception is strongly impaired in patients with LHON. In addition, although the selection and manipulation of real objects to execute a task are slowed, they can be performed efficiently using peripheral vision.

AUTOMATIC DETECTION AND RECOGNITION OF ROAD SIGNS USING CONVOLUTIONAL NEURAL NETWORKS

This paper examines the use of convolutional neural networks (CNNs) to improve traffic sign recognition systems, precisely in non-weather conditions. An extended dataset of the German Traffic Sign Recognition Test (GTSRB), based on a new CNN model, is also used, which contains more than fifty thousand labeled images covering more than forty categories. The model presents adaptive object selection layers designed to eliminate visibility problems caused by weather factors such as rain, fog, and snow. Advanced data augmentation techniques are applied to model different weather scenarios, which increases the diversity of the training dataset. Through an analysis of theoretical and practical aspects, the study demonstrates how CNNs enhance the accuracy and efficiency of road sign detection systems in a different weather condition. This study not only examines the theoretical and practical improvements provided by CNNs for traffic sign detection in unfavorable conditions, but also verifies the effectiveness of the model through metrics such as accuracy, responsiveness, and F1 score. The results confirm the effectiveness of the model in minimizing false positives and accurately identifying traffic signs. The paper emphasizes the importance of careful dataset preparation, model optimization and improved training to enhance the performance of the detection system. This has positive implications for intelligent transportation systems, autonomous driving and road safety, indicating future progress in robust traffic sign recognition technologies.

DIRECTIONS OF THE USE OF FINANCIAL RESOURCES FROM THE EUROPEAN UNION FUNDS IN FARMS IN LUBELSKIE VOIVODESHIP IN 2019-2022

The aim of the study is to determine directions the use of European Union (EU) funds on selected farms in the Lubelskie Voivodeship in the period 2019-2022. The primary source of data was information from a questionnaire survey. The survey used the method of a diagnostic survey carried out with an online survey technique using a survey questionnaire tool. The survey was conducted in 2024 among representatives of agricultural holdings from the Lubelskie Voivodeship. The selection of objects for the study was purposive, with the condition of participation in the study being the use of EU aid programmes. The survey showed that farmers mainly used the Young Farmer, Eternit Replacement and Small Farm Development programmes. The farmers used the funds mainly to modernise their farms, including mainly the purchase of agricultural machinery and tractors. These investments arguably contributed to the modernisation, as well as to improving the efficiency and competitiveness of farms. The majority of farm owners would probably not realise the planned investments without the funds from the European Union funds, therefore it is important for the institutions authorised to do so to disseminate information about the projects addressed to farmers, as well as to support farmers in preparing the applications for financing with due diligence.

The stability of the treasury system as a result of treasury risk management

Relevance. The fundamentals of control activities are based on effective risk management. The main burden on the internal control system is aimed at ensuring compliance by the audit subject with regulatory and legislative acts governing the activities of treasury bodies, timely detection and prevention of treasury risks in order to implement the necessary preventive measures aimed at minimizing the likelihood of the occurrence of negative consequences associated with them for the activities of the department.The purpose of the study is to assess the stability of the treasury system as a result of treasury risk management.Objectives: consideration of theoretical and organizational and legal aspects of budget execution, assessment of the treasury system, determination of areas for improving treasury control as a factor in operational efficiency in managing the budget process at the regional level.Methodology. The authors used general scientific methods of research, vertical and horizontal analysis, comparison, summary and grouping, generalization of scientific practice, forecasting.Results. The conducted research allowed to form and highlight the following scientific results: to determine the role of treasury bodies in the system of state financial control at the regional level, to conduct a general analysis of the activities of the Federal Treasury Department in the Kursk Region and to analyze the treasury execution of the budget of the Kursk Region, to identify risks for the treasury system when introducing the digital ruble.Conclusions. Control is the main procedure of the treasury system of budget execution. Cash servicing of budget execution involves the implementation and accounting of cash transactions on income and expenses and sources of financing deficits. The Federal Treasury Department in the Kursk Region plays an important role in the financial system of the region and contributes to sustainable development. The use of a risk-oriented approach by treasury bodies involves the selection of objects of external control of entities of audit activity based on the analysis of the risks of their activities, the application of international audit standards, which is aimed at reducing the audit time, reducing duplicate control functions, forming a unified management paradigm of public management applied in related control and supervisory bodies in the financial and budgetary sphere of Russia.

Understanding user experience, task performance, and task interdependence in symmetric and asymmetric VR collaborations

Asymmetric collaboration is an important topic for the research of multiuser collaborative systems. Previous works have shown that by providing different abilities, devices or content to different users, users can take advantage of the unique features of each side and collaborate effectively with each other. However, there is limited work comparing the differences between asymmetric and symmetric Virtual Reality (VR) collaboration systems. How task complexity may affect symmetric and asymmetric VR collaboration is also unclear. In this paper, we present a comparative study that investigated how user experiences and task performance vary in symmetric and asymmetric VR collaboration. In addition, we also explored how task interdependence correlates with user experience and task performance. Participants were asked to collaboratively perform 3D object selection and manipulation tasks in pairs. A within-subjects study was conducted, where participants used PC and PC, VR and VR, and PC and VR, respectively in three conditions. Our results revealed that the asymmetric collaboration using both PC and VR showed the best results in closeness of relationship, social presence and task performance; the PC symmetric collaborative system showed the worst user experiences and task performance. Both user experience and task performance showed a positive correlation with task interdependence. We discussed the effects of the collaborativ mode and device on the user experience and task performance, and the implications for future symmetric and asymmetric VR collaboration systems.Graphical abstract

Sistem Jakarta Pendukung Keputusan Pemilihan Siswa-Siswi Terbaik Dengan Metode Saw (Simple Additive Weigthing) Pada Sekolah SMP Negeri 16

The selection of the best students in schools is essential to recognize both academic and non-academic achievements and to motivate other students to improve their skills. SMP Negeri 16 Jakarta requires an objective decision support system to select the best students based on predefined criteria. This study aims to design and implement a decision support system using the Simple Additive Weighting (SAW) method to facilitate the selection of the best students at SMPN 16 Jakarta. The SAW method is chosen due to its capability to accommodate multiple criteria through weighting and ranking for each alternative. The research process involves observation, interviews, and documentation, which are then used to determine primary criteria such as academic achievement, social skills, and participation in school activities. The findings show that the application of the SAW method enables a more accurate and objective selection of the best students by ranking based on the final score of each criterion. This system is expected to assist SMPN 16 Jakarta in making more structured decisions and supporting educational quality improvement.

Peningkatan Produktivitas dan Profitabilitas Petani Pisang Barlin di Desa Papringan Kecamatan Temayang Kabupaten Bojonegoro

Barlin Banana is a leading agricultural products in Bojonegoro. However, the shelflife of Pisang Barlin only 10 days at room temperature. Therefore, a lot of which iswasted because of rotten bananas. As a result, the loss is very large bananagrowers. The selling price of the product is also relatively cheap only around Rp1500 per comb. These conditions led to the welfare of farmers Barlin Banana stilllow. Farmers group Barlin Banana "Papringan" which became a partner in thePKM program is in District Papringan Bojonegoro. Farmers group Barlin Banana"Papringan" was established in 2005 with the purpose as a means of fostering theBarlin Banana Farmers so that productivity and quality of crops Barlin Bananacan be maximized. Existence of banana growers group "Papringan" is felt by thesurrounding community. Since its founding five years ago, members of this groupof banana farmers has reached 100 farmers. If we assume that each farmer groupmembers bear live an average of 3 persons consisting of a wife and 2 children, thenit implies the existence of a group of banana farmers "Papringan" relates to thefate of 400 people in the District Papringan Bojonegoro. Activities undertaken inthe stages: 1) the selection of the group's strategic objectives, 2) grant reliefmachinery and equipment which include machine vacuum fryer, spinner, sealer,tool kit, and digital scales, 3) test, 4) ttraining of machine operation , 4) monitoringand evaluation.The results of this activity is a group of farmers Barlin Banana partners have ownedmachinery and processing equipment Barlin Banana and can operate it well. Anincrease product shelf life of up to 7 months, the farmers profit increased 600%from Rp 1,000 to Rp. 6000. So that the welfare of farmers has also increased

Two "What" Networks in the Human Brain.

Ungerleider and Mishkin, in their influential work that relied on detailed anatomical and ablation studies, suggested that visual information is processed along two distinct pathways: the dorsal "where" pathway, primarily responsible for spatial vision, and the ventral "what" pathway, dedicated to object vision. This strict division of labor has faced challenges in light of compelling evidence revealing robust shape and object selectivity within the putative "where" pathway. This article reviews evidence that supports the presence of shape selectivity in the dorsal pathway. A comparative examination of dorsal and ventral object representations in terms of invariance, task dependency, and representational content reveals similarities and differences between the two pathways. Both exhibit some level of tolerance to image transformations and are influenced by tasks, but responses in the dorsal pathway show weaker tolerance and stronger task modulations than those in the ventral pathway. Furthermore, an examination of their representational content highlights a divergence between the responses in the two pathways, suggesting that they are sensitive to distinct features of objects. Collectively, these findings suggest that two networks exist in the human brain for processing object shapes, one in the dorsal and another in the ventral visual cortex. These studies lay the foundation for future research aimed at revealing the precise roles the two "what" networks play in our ability to understand and interact with objects.

Objective Bayesian Model Selection for Spatial Hierarchical Models with Intrinsic Conditional Autoregressive Priors

We develop Bayesian model selection via fractional Bayes factors to simultaneously assess spatial dependence and select regressors in Gaussian hierarchical models with intrinsic conditional autoregressive (ICAR) spatial random effects. Selection of covariates and spatial model structure is difficult, as spatial confounding creates a tension between fixed and spatial random effects. Researchers have commonly performed selection separately for fixed and random effects in spatial hierarchical models. Simultaneous selection methods relieve the researcher from arbitrarily fixing one of these types of effects while selecting the other. Notably, Bayesian approaches to simultaneously select covariates and spatial model structure are limited. Our use of fractional Bayes factors allows for selection of fixed effects and spatial model structure under automatic reference priors for model parameters, which obviates the need to specify hyperparameters for priors. We also show the equivalence between two ICAR specifications and derive the minimal training size for the fractional Bayes factor applied to the ICAR model under the reference prior. We perform a simulation study to assess the performance of our approach and we compare results to the Deviance Information Criterion and Widely Applicable Information Criterion. We demonstrate that our fractional Bayes factor approach assigns low posterior model probability to spatial models when data is truly independent and reliably selects the correct covariate structure with highest probability within the model space. Finally, we demonstrate our Bayesian model selection approach with applications to county-level median household income in the contiguous United States and residential crime rates in the neighborhoods of Columbus, Ohio.

Object Selection and Manipulation in VR Headsets: Research Challenges, Solutions, and Success Measurements

Object Selection and Manipulation in VR Headsets: Research Challenges, Solutions, and Success Measurements

Sistem Jakarta Pendukung Keputusan Pemilihan Siswa-Siswi Terbaik dengan Metode SAW (Simple Additive Weigthing) pada Sekolah SMP Negeri 16

The selection of the best students in schools is essential to recognize both academic and non-academic achievements and to motivate other students to improve their skills. SMP Negeri 16 Jakarta requires an objective decision support system to select the best students based on predefined criteria. This study aims to design and implement a decision support system using the Simple Additive Weighting (SAW) method to facilitate the selection of the best students at SMPN 16 Jakarta. The SAW method is chosen due to its capability to accommodate multiple criteria through weighting and ranking for each alternative. The research process involves observation, interviews, and documentation, which are then used to determine primary criteria such as academic achievement, social skills, and participation in school activities. The findings show that the application of the SAW method enables a more accurate and objective selection of the best students by ranking based on the final score of each criterion. This system is expected to assist SMPN 16 Jakarta in making more structured decisions and supporting educational quality improvement.

Decision window and criterion for its use in two-dimensional discrete filtering

One of the areas of video information preprocessing in machine vision systems is the selection of image areas whose shape and size correspond to the objects of interest. The use of two-dimensional discrete filtering of the Wiener-Hopf type for this purpose is associated with the impossibility of constructing an optimal filter and the problem of determining the filter aperture size, while an inaccurate selection of a prototype object can lead to "missed target" errors. These problems can be solved by introducing hierarchical preprocessing consisting of at least two stages. The use of two-dimensional discrete filtering at the first stage should ensure a sufficiently high probability of false alarm with a minimum probability of missing a target. The purpose of the work is to study the capabilities of quasi-optimal two-dimensional discrete filtering of the Wiener-Hopf type for solving object search problems at the first stage of hierarchical image preprocessing. The paper shows that to synthesize a discrete filter, it is necessary to use an image of a prototype object on a certain background. The concept of a "prototype object window" with an arbitrarily specified contrast is introduced. The paper considers the processing of test images by filters synthesized based on the window of a prototype object and having apertures of the smallest possible sizes, which reduces the influence of nearby objects on the filtering results. All possible combinations of contrast signs of the object of interest and the prototype object are considered, and their influence on the formation of artifacts in the processed image is analyzed. The areas of artifacts that are formed inside and around objects due to the influence of both object samples and background samples are determined. To take into account the filter response in these areas, it is proposed to use a decision window whose parameters are determined by the filter impulse response, the size and shape of the object of interest. It is found that threshold processing based on the maximum output signal level does not allow one to select similar objects that differ in size, so a new criterion, "maximum sum of video signal sample modules in the decision window," is proposed. The results of applying the criterion when processing with the smallest possible filter apertures are presented. The use of the maximum criterion of the sum of the modules of video signal samples in the decision window allows implementing the first stage of hierarchical image processing, where errors of missing targets are minimized and potential areas containing objects of interest are identified. In turn, this helps to minimize computational costs and the probability of false alarms at the second stage of hierarchical processing. The results obtained can be used to automate the processing of video information in machine vision systems.