Types Of Items Research Articles

Bigmart Sales Prediction Based on Voting Classifier Algorithm and Linear Regression

Machine Learning is a technology that allows machines to become more accurate in predicting outcomes without being explicitly programmed for it. The basic premise of machine learning is to build models and deploy algorithms that can receive input data and use statistical analysis to predict an output while modifying outputs as the new data becomes available. These models can be used in different areas and trained to match the expectations so that accurate steps can be taken to achieve the organization’s target. In this paper, the case of Big Mart Shopping Centre has been discussed to predict the sales of different types of items and for understanding the effects of different factors on the sales of different items. Taking various features of a dataset collected for Big Mart, and the methodology followed for building a predictive model, results with high levels of accuracy are generated, and these observations can be used to take decisions to improve sales. Key words : Machine Learning, Sales Prediction, Big Mart, Voting classifier algorithm, Linear Regression.

Students with Aberrant Responses in TIMSS2019 Mathematics Test in Sultanate of Oman: Comparison of Between Squared Residual Index by Content, Cognitive Process, Item Type, and Difficulty.

This study aimed to detect the students with misfit responses for eight grade students in the Sultanate of Oman in 2019, who amounting 6,745 students, by using the Between Squared Residual Index over sections of TIMSS2019 Mathematics test (content, cognitive process, item format and item difficulty). This study also aimed to compare the results of the Between Squared Residual Index over Mathematics test sections with the results of the Squared Residual Index over item level. The results of the study indicated that the percentage of students with misfit responses ranged between (2.16% & 3.22%) and between (2.13% & 3.88%) according to the (unweighted and weighted) Between Squared Residual indices respectively, while their percentage amounted to only 0.30% & 0.95% according to the (unweighted & weighed) Squared Residual indices respectively. The results showed that most of students' abilities with misfit responses in the Mathematics Test in TIMSS2019 ranged between low and medium. The study recommended conducting studies to determine the reasons for the presence of misfit responses in Mathematics tests in TIMSS among students of the Sultanate. It also recommended directing teachers and those in charge of applying TIMSS tests to train students in the basic mathematical skills they need to reduce behaviors that lead to misfit responses.

The endowment effect with different possession times and types of items

The vast literature dealing with the endowment effect (EE) revolves around untangling the various determinants that may be at work in producing the effect itself. We examine two of these likely determinants that remain under-researched: The first is the effect that the length of possession may have on the EE. The second is the type of good (tangible, intangible or exchange goods) used to test the effect. Using an online questionnaire experiment, we investigate these aspects using three different items – a mug, an Amazon gift card, and a quarterly subscription to Spotify – testing whether the EE occurs when subjects imagine owning the item for different lengths of time. We find that the EE appears clearly for all types of goods, while the results are less clear when considering the duration of possession.

Testing the contributions of proactive target and distractor templates in visual search performance

ABSTRACT When searching for objects with particular visual features, performance is sometimes improved by the presence of a salient colour distractor, such as a red item among green objects. Attention to such distractors is thought to be suppressed when the visual system expects their specific features (e.g., redness), but a complication with this view is that distractor expectancies are generally accompanied by anticipated target features, with their own associated attentional facilitation. We tested the role of these mechanisms by separately manipulating the colour specificity of salient distractors and of targets, and thus the ability to build up feature-specific templates for each type of search item. Experiment 1 employed singleton distractors appearing in unpredictable colours, preventing the formation of a feature-specific suppression template. Nevertheless, evidence of suppression was unchanged, suggesting that it does not require a fixed, predictable distractor. In Experiment 2, the singleton colour remained fixed while the target colour varied. Without a constant target colour, markers of singleton suppression were effectively abolished. The pattern of results suggests that observed suppression effects are largely driven by global enhancement of the expected target colour, possibly in combination with a second-order suppression mechanism that is not dependent on specific distractor features.

Improving early cholecystectomy rate in acute cholecystitis with an evidence-based local multidisciplinary protocol and a surgical audit: single-center experience through an Acute Care Surgery Division.

To analyze if, after implementation of an evidence-based local multidisciplinary protocol for acute cholecystitis (AC), an intermediate surgical audit could improve early cholecystectomy (EC) rate and other therapeutic indicators. Longitudinal cohort study at a tertiary center. The local protocol, promoted, created, and periodically revised by the Acute Care Surgery Unit (ACSu) was updated and approved on March 2019. A specific registry was prospectively fulfilled with demographics, comorbidity, type of presentation, diagnostic items, therapeutic decision, and clinical course, considering both non-operative management (NOM) or cholecystectomy, early and delayed (EC and DC). Phase 1: April 2019-April 2021. A critical analysis and a surgical audit with the participation of all the involved Departments were then performed, especially focusing on improving global EC rate, considered primary outcome. Phase 2: May 2021-May 2023. Software SPSS 23.0 was used to compare data between phases. Initial EC rate was significantly higher on Phase 2 (39.3%vs52.5%, p < 0.004), as a significantly inferior rate of patients were initially bailed out from EC to NOM because of comorbidity (14.4%vs8%, p < 0.02) and grade II with severe inflammatory signs (7%vs3%, p < 0.04). A higher percentage of patients was recovered for EC after an initial decision of NOM on Phase 2, but without reaching statistical significance (21.8%vs29.2%, n.s.). Global EC rate significantly increased between phases (52.5%vs66.3%, p < 0.002) without increasing morbidity and mortality. A significant minor percentage of elective cholecystectomies after AC episodes had to be performed on Phase 2 (14%vs6.7%, p < 0.009). Complex EC and those indicated after readmission or NOM failure were usually performed by the ACSu staff. To adequately follow up the implementation of a local protocol for AC healthcare, registering and periodically analyzing data allow to perform intermediate surgical audits, useful to improve therapeutic indicators, especially EC rate. AC constitutes an ideal model to work with an ACSu.

The prey availability and diet of juvenile Atlantic salmon (Salmo salar L.) in low-productivity rivers in northern Europe.

The availability of resources varies across a species distributional range, and a low-productivity area can make a species more vulnerable. We investigated the invertebrate composition and prey choice of juvenile Atlantic salmon (Salmo salar L.) in low-productivity rivers in northeast Iceland, which is one of the species' most northerly distributions. By sampling benthic and drift invertebrate populations, we found that prey availability was similar within and between rivers. Gut content samples showed that the main prey choice for juvenile S. salar was the Chironomidae. The type of food items consumed varied across different weight groups of S. salar, with smaller juveniles having more diverse diet. S. salar did not have a selection preference for chironomids, which indicates that they were eating the highly available prey in their environment, rather than hunting high biomass items such as terrestrial invertebrates and large Dipterans. Estimates of dietary niche showed that S. salar in these low-productivity rivers relied on consuming what was most readily available, the chironomids, and that they must share resources with other salmonid species. This may be due to the low diversity of freshwater invertebrates (fewer prey options), whereas S. salar in nutrient-rich rivers could rely more on terrestrial invertebrates as an additional subsidy in their diet. In conclusion, with limited prey choices, juvenile S. salar in nutrient-poor rivers, especially in a biogeographically isolated region with low species diversity, may increase in vulnerability and decrease in adaptability to environmental change. Management methods that increase benthic prey abundance and diversity are recommended for conserving the S. salar population in a nutrient-poor river.

An effective discrete artificial bee colony for the rectangular cutting problem with guillotine in transformer manufacturing

This paper addresses a two-dimensional rectangular cutting problem with guillotine constraint, applied to the transformer industry. The problem requires a set of rectangular items to be cut from larger and variable-sized rectangles, known as bins. The goal is to minimize the number of bins used to cut all required items. An effective discrete artificial bee colony is proposed to solve the problem. The approach uses a decimal encoding method where each integer represents a type of bin or item, and decodes the list of integers by a constructive heuristic to generate cutting patterns with guillotine-cut constraint. In addition, a copy strategy is designed to improve the solution quality. The approach’s performances and the effectiveness of the strategy are evaluated by three datasets generated from real-world data. The experimental results show that the discrete artificial bee colony is superior to other competitive algorithms, and that the copy strategy can produce higher quality solutions.

Adaptive lexical processing of semantic competitors extends to alternative names: Evidence from blocked-cyclic picture naming.

Naming a picture (e.g., "duck") in the context of semantically related pictures (e.g., "eagle," "stork," "parrot") takes longer than naming it in the context of unrelated pictures (e.g., "knave," "toast," "atlas"). Adaptive models of word production attribute this semantic interference effect in blocked-cyclic naming (BCN) to an adaptive mechanism that makes competitor words, (e.g., the semantically related word "eagle" for the target word "duck") which are activated but not selected for production, less accessible for future retrieval. Results from a recent picture-word-interference study, however, suggested that alternative names (e.g., "bird" for "duck") might be exempt from this mechanism, challenging adaptive lexical processing as a general mechanism. We tested whether converging evidence is obtained in BCN. In Experiment 1, we embedded pictures responded to with alternative (category) names (e.g., "bird") into contexts composed of pictures responded to with specific (exemplar) names (e.g., "duck," "eagle," "stork," and "parrot"). If alternative names are exempt from adaptive lexical processing, interference in the homogeneous context should be found for specific name items but not for alternative name items. In contrast to this prediction, there was similar-sized interference for both types of items. In Experiment 2, we replaced the alternative name items with unrelated items. For these items, interference was largely diminished, ruling out that the effect found in Experiment 1 is a general set effect. Overall, our data suggest that alternative names are not special with respect to adaptive lexical processing.

Combinatorial Benders' decomposition for the constrained two-dimensional non-guillotine cutting problem with defects

This paper studies the constrained two-dimensional non-guillotine cutting problem with defects, in which a set of items of a specific size is cut from a large rectangular sheet with defective areas, with the number of each type of cut item cannot exceed a specified quantity. The objective is to maximise the total value of the cut items. We propose a decomposition approach to address the problem. The process involves decomposing the original problem into a master problem and a subproblem. The master problem is formulated as a one-dimensional contiguous bin packing problem, while the subproblem is an x-Check problem to identify a two-dimensional packing that does not lead to any overlap. The x-Check problem is effectively addressed by using an integer linear programming model. When the x-Check problem proves infeasible, cuts are added to the master problem, and the iteration is repeated until the x-Check finds a feasible solution. Furthermore, we introduce several novel techniques, including valid inequalities, preprocessing techniques, and lifting the cut methods to improve the performance of the algorithm. Extensive computational results show that our method can quickly find the optimal solution for the 5450 instances in the literature.

Examining Position Effects on Students’ Ability and Test-Taking Speed in the TIMSS 2019 Problem-Solving and Inquiry Tasks: A Structural Equation Modeling Approach

Position effects occur when changes in item positions on a test impact the test outcomes (e.g., item parameters or test scores). Previous studies found that position effects may vary by the testing context and conditions and thus affect each test-taker differently. With the increasing adoption of digital assessments involving innovative item types that are focused on problem-solving skills, it is also essential to study position effects within this context. This study incorporates item-level scores and screen-level response time data from the Trends in International Mathematics and Science Study (TIMSS) 2019 problem-solving and inquiry tasks for Grade 4 students to examine position effects on students’ ability and test-taking speed. This dataset included responses from 27,682 students from 36 countries. A structural equation modeling approach was employed to model ability and test-taking speed within the same model. The results indicated a small but statistically significant booklet effect on students’ overall mathematics and science ability. The impact of block position changes within the booklets seemed to be greater than the impact of a reordering of subjects tested in the two sessions. The results also showed that when an item block was placed earlier in a test session, students spent more time on the items and performed better. The implications of these findings are discussed.

Evolving Licensure Examination: Assessing Student Confidence and Accuracy With Next Generation NCLEX.

The Next Generation NCLEX (NGN) includes new item types. Little is known about nursing students' confidence and accuracy in answering these questions. A descriptive comparative study examined prelicensure nursing students' confidence and accuracy in answering NGN-style items versus multiple-choice questions (MCQs) of the same content via a 12-item quiz. Less than one third of students (n = 194; 32.1%) reported feeling confident in answering NGN questions. Students' confidence levels had no relationship on scores with NGN items. When comparing NGN-style items to MCQs, students' (n = 221) scores on NGN-style items were lower with bowtie or a select-all-that-apply questions but higher with highlight table or matrix multiple-choice questions. Students' lack of confidence with certain item types suggests faculty should incorporate these item types into classroom activities or course assignments. NGN test-taking strategies also should be incorporated and frequently reinforced throughout the curriculum. [J Nurs Educ. 2024;63(4):252-255.].

“ TRANSLUCENT CONCRETE ”

Translucent concrete is awesome because it lets natural light in, which means we don't need to use as much artificial lighting during the day. This saves a bunch of energy and makes indoor spaces feel nicer. Plus, it looks really cool and can make buildings more energy-efficient. Even though it might cost more at first, in the long run, it can save a lot of money and energy. So, it's totally worth considering for building projects. We should keep studying it to make buildings even better in the future! Translucent concrete is a cool new thing! It lets natural light shine through, which means we can use less artificial lighting during the day. This not only saves energy but also makes indoor spaces nicer to be in. Plus, it looks pretty cool and can make buildings more energy-efficient. Even though it might cost more upfront, in the long run, it can save a lot of energy and money. So, it's a win-win! We should keep exploring this idea to make buildings even better in the future. Key Words: (Light transmitting , Concrete strenght ,type of items)

Fused SDT/IRT Models for Mixed-Format Exams.

A psychological framework for different types of items commonly used with mixed-format exams is proposed. A choice model based on signal detection theory (SDT) is used for multiple-choice (MC) items, whereas an item response theory (IRT) model is used for open-ended (OE) items. The SDT and IRT models are shown to share a common conceptualization in terms of latent states of "know/don't know" at the examinee level. This in turn suggests a way to join or "fuse" the models-through the probability of knowing. A general model that fuses the SDT choice model, for MC items, with a generalized sequential logit model, for OE items, is introduced. Fitting SDT and IRT models simultaneously allows one to examine possible differences in psychological processes across the different types of items, to examine the effects of covariates in both models simultaneously, to allow for relations among the model parameters, and likely offers potential estimation benefits. The utility of the approach is illustrated with MC and OE items from large-scale international exams.

The effect of lexical triggers on Spanish-English code-switched judgment tasks.

It has been argued that certain words can "trigger" intrasentential code-switching. While some researchers suggest that cognates establish triggering at the lexical level, others have argued that words that lack direct translations are more natural stories switch. Yet to be tested experimentally is to what extent different types of lexical items influence the acceptability of mixed utterances. The current study investigates this methodological consideration for code-switching research by having early US Spanish-English bilinguals (i.e., heritage speakers of Spanish) complete an acceptability judgment task with a 7-point Likert scale directly comparing cognates (e.g., sopa "soup") and culturally specific items (e.g., pozole "traditional Mexican soup") in otherwise identical grammatical switched sentences (N = 24). The results showed that there was no significant effect of condition (p = 0.623) suggesting that cognates and language-specific items are equally acceptable in code-switched sentences. Indeed all conditions were rated on average above 6. These findings show that in this context, judgment tasks are not affected differently by these types of lexical items.

Toward more ethically oriented humanitarian logistics operations: An exploratory research

Ethical standards in humanitarian logistics have been frequently overlooked in the literature. This research aims to explore the interaction between logistics decisions and ethical standards implementation in the context of humanitarian relief operations. The paper adopts a data triangulation approach to collect and validate the primary and secondary data through a literature review, focus group, and interview. The results revealed that logistics decisions and processes affect the implementation of ethical standards. These decisions are physical distribution, facility location, procurement, outsourcing, deprivation cost analysis, visibility and information flow, supply chain collaboration, staff selection and training, types of relief items, staff security, and localization of logistics activities. This research can provide practitioners with insight into a complete set of ethical standards and inform their understanding of which factors affect their implementation. The novelty of this research comes from combining two disciplines, humanitarian logistics and social work, to compile a complementary list of ethical standards in humanitarian operations. It shows how logistics decisions can affect implementing ethical standards and hence achieving core values of social work.

Composition and seasonality of rodent diet in Chimit Kola, Blue Nile Gorge, Ethiopia

A study on the composition and seasonality of rodent diet was carried out during 2020–2022 years in Chimit Kola to determine the type, relative proportion and seasonality of food items consumed. A total of 166 stomach contents that belong to six rodent species (Mastomys awashensis, Acomys louisae, Arvicanthis raffertyi, Lophuromys simensis, Gerbilliscus sp. and Lemniscomys macculus) were investigated. Parametric and non-parametric analyses of variance were used to test the difference. Leaves and stems, seeds, invertebrates, fruits and unidentified food matters were the food items identified in the stomach contents of rodents. There was a significant variation in food items consumed among rodent species. Arvicanthis raffertyi and L. macculus consumed more leaves and stems whereas L. simensis, A. louisae and Gerbilliscus sp. mostly fed on invertebrates. Mastomys awashensis consumed relatively more seeds (30%) than any other rodent species (ranging from 14 to 28%). Acomys louisae, L. simensis and Gerbilliscus sp. consumed more leaves and stems during the dry season and invertebrates during the wet season. Similarly, A. raffertyi consumed more leaves and stems during the wet season and seeds during the dry season. However, the diet of M. awashensis and L. macculus and some food items (fruits and unidentified food matters) of most rodent species were similar between seasons. Mastomys awashensis significantly consumed a higher proportion of seeds in the fallowland (44%) than in other habitats (ranging from 19 to 31%). Similarly, A. louisae and L. macculus consumed a significantly higher proportion of invertebrates in bushland (53%) and riverine forests (48%) than in other habitats (ranging from 16 to 47%), respectively. The present finding concluded that these rodent species are diet generalists, feeding on a variety of available resources depending on seasons and habitats. The study documents the diet composition of these rodent species for the first time. Thus, the management and conservation of these rodents should be in consideration of their feeding habits and factors that influence their diets.

A long-tail alleviation post-processing framework based on personalized diversity of session recommendation

Session-based recommendation leverages the short-term interaction sequence to predict the next item a user is most likely to click on. Generally, in real applications, users often click on different types of items in the same session, which makes the items in the sequence present diversity, and degree of diversity vary with different sequences, that is, there is a phenomenon of personalized diversity. However, the majority of existing session recommendation models primarily focus on improving recommendation accuracy and overlooking the importance of personalized diversity, which leads to the issue of filtering bubbles. In order to alleviate the long-tail effect caused by the filtering bubble, the recommendation system should not only consider the accuracy of recommended items, but also the diversity of users’ demands for recommended items. To address this issue, this paper proposes a model, named as LAP-SR, a Long-tail Alleviation Post-processing framework based on personalized diversity of Session Recommendation. After obtaining the initial recommendation list through the selected initial session model, LAP-SR model generates the long-tail item set and item graph according to session contents. Besides, from the item graph, the model calculates the embedding representation of items, from which the diversity of all sessions is calculated. By combining the obtained diversity and the long-tail item set, the initial recommendation list is soft processed. On this basis, the model yields the final recommendation list, which alleviates the overall long-tail effect. We verified that as a post-processing framework, the proposed model can be applied to various session recommendation models. Extensive experiments on the three datasets of Diginetica, Tmall and Yoochoose1_64 demonstrate that the LAP-SR model has a competitive advantage over the baseline models in mitigating the long-tail effect.

Designing Automation for Pickup and Delivery Tasks in Modern Warehouses Using Multi Agent Path Finding (MAPF) and Multi Agent Reinforcement Learning (MARL) Based Approaches

A warehouse pickup and delivery problem finds its solution using multi agent path finding (MAPF) approach. Also, the problem has been used to showcase the capabilities of the multi agent reinforcement learning (MARL). The warehouse pickup and delivery work needs the agent to pick up a requested item and successfully deliver it to the intended location within the warehouse. The problem has been solved based on two approaches that include single shot and lifelong problem solution. The single shot solution has the delivery as the final goal and thus once it reaches the delivery address, it stops whereas in case of lifelong, the agent needs to deliver the item which it had picked, deliver it to the required place and then again pick up new item until requests are satisfied. The strategy used by multi agent path finding (MAPF) approach aims at constructing collision free paths to reach the delivery location but in case of multi agent reinforcement learning (MARL), the agents’ decision making tactics (or policies) are learned which are then used to help agents decide path to be followed based on environment state and agent’s position. The results show that the lifelong conflict based search (CBS) is a better option when the agents are less in number as in that case, the re-planning will take overall less time but when the agents are large in number then this re-planning can take very long to produce conflict free paths from source to goal nodes. In this case, shared experience action critic (SEAC) which is based on multi agent reinforcement learning (MARL) approach can be more efficient choice as it takes the current environment state to give the most suitable action for that time t. For this study the agents taken for learning are homogeneous in nature that can pickup and deliver any type of requested item. We can address the same pickup and delivery problem when the agents are not all same and differ in their capabilities and the type of item they can handle.

The effects of reverse items on psychometric properties and respondents’ scale scores according to different item reversal strategies

This study aimed to examine the effects of reverse items created with different strategies on psychometric properties and respondents’ scale scores. To this end, three versions of a 10-item scale in the research were developed: 10 positive items were integrated in the first form (Form-P) and five positive and five reverse items in the other two forms. The reverse items in the second and third forms were crafted using antonyms (Form-RA) and negations (Form-RN), respectively. Based on the research results, Form-P was unidimensional, while other forms were two-dimensional. Moreover, although reliability coefficients of all forms were obtained as above .80, the lowest one was acquired for Form-RN. There were strong-positive relationships between students’ scores in the three scale forms. However, the lowest one was estimated between Form-P and Form-RN. Finally, there was a significant difference between the students’ mean scores obtained from Form–RN and other two versions, but the effect size of the said difference was small. In conclusion, all these results indicate that different types of reverse items influence psychometric properties and respondents’ scale scores differently.

Consumers confused 'Where to dispose biodegradable plastics?': A study of three waste streams.

Biodegradable plastics, either fossil- or biobased, are often promoted due to their biodegradability and acclaimed environmental friendliness. However, as demonstrated by previous literature, considerable confusion exists about the appropriate source separation and waste management of these plastics. Present study investigated this confusion based on manual sorting analyses of waste sampled from packaging waste (P), biowaste (B) and residual waste (R) in an urban area of Austria. The results were evaluated relative to near-infrared sensor-based sorting trials conducted in a German urban area. Although existing literature has focused on waste composition analyses (mostly in stand-alone studies) of the three waste streams, the present study focused on identifying the specific types of biodegradable plastic items found in each of these streams. Supermarket carrier bags (P = 90, B = 14, R = 33) and dustbin bags (P = 2, B = 46, R = 6) were found in all three waste streams in the Austrian urban area. Similarly, in the German urban area dustbin bags (P = 1, B = 106, R = 3) were the common items. The results indicate that certain bioplastic items were present in more than one bin; thus, hinting that consumers are not necessarily aware of how-to source-separate the biodegradable plastics. This suggests that neither consumers nor current waste management systems are fully 'adapted' to bioplastics, and the management of these plastics' waste is currently not optimal.