Grocery List Research Articles

Virtual Assistant Using Supervised Learning

Abstract: Todays modern world, everything got evoluted including technology from vacuum tubes to nanoelectronics.Now a days the total world is in single palm of human in the form of mobile.But these days we aren’t using hands, instead we using voice commands to wake electronics devices like mobiles,it is not only in mobiles, also in every electronics.This type of usage is possible by embedding a virtual assistant into electronics. Virtual Assistants are software programs that help you ease your day to day tasks, such as showing weather report, creating reminders, making shopping lists etc. They can take commands via text (online chat bots) or by voice. This paper delivers steps to build a web based virtual assistant using supervised learning to achieve goals which cannot done by the VA’s in market.And as this model uses supervised learning, so there will be limited commands and data to maintain it in our control.

Enhancing Grocery Accessibility with OCR: a User-centered Design Approach

Grapeful, a grocery app, is an online grocery store that not only simplifies shopping but also provides a seamless transition from pantry/grocery planning to purchasing. The user can browse through various categories of groceries, view items, add them to the cart (manually), customize quantity, and pay during checkout. Our list to cart feature enables users to directly add items from their grocery list to the cart. The user will scan their grocery list, and the app will fill the cart with the items listed in the list. This feature is valid for lists written in the English language only. Grapeful is a mobile application that uses Flutter and Dart for the front-end of the application and MongoDB for the database. Node.js is used for the back-end. The list-to-cart feature uses the OCR algorithm to identify the items listed in the grocery list and then add them to the customer's cart.

Modeling behavioral economic strategies in social marketing messages to promote vegetable consumption to low-resource Louisiana residents: A conjoint analysis.

Behavioral economic strategies implemented within social marketing campaigns improve eating behavior. To identify which behavioral economic (BE) strategies in social marketing messages, i.e., messengers, norms, and commitments, will promote low-income Louisiana (LA) residents to add more vegetables to meals. Full profile traditional conjoint analysis survey with single concept ratings. Purposive sample of low-resource LA residents (N = 213) SETTING: Online survey INTERVENTION: Participants rated randomized concepts that featured a messenger and a message. Ratings (1-9) of likelihood to add vegetables to meals. A model of ratings was generated using mixed-effects multiple regression, which accounted for repeated measurement of participants. Interactions of variables and covariates were modeled. There was significant variation in the main effect of the messenger variable (P = 0.02) and the main effect of the message variable (P = 0.008). Pairwise comparisons demonstrated differences between friend (mean = 6.80) and mother (mean = 7.06, P = 0.03) as well as friend and normal weight doctor (mean = 7.03, P = 0.04). Pairwise comparisons demonstrated differences between descriptive norm (mean = 6.79) and grocery list commitment (mean = 7.02, P = 0.05) along with descriptive norm and injunctive norm (mean = 6.98, P = 0.04). Covariate models demonstrated main effects of race (P = 0.006) and gender (P = 0.0001). There was significant variation in the message variable and frequency of vegetable intake interaction (P = 0.01). Both message and messenger variables predicted the likelihood to add vegetables to meals. Race and gender influenced ratings to add vegetables. As reported vegetable consumption increased, behavioral economic messages improved the likelihood to add vegetables to meals. Behavioral economic approaches are well-suited to social marketing messages that aim to promote healthy eating behavior in low-income LA residents.

Adaptive Encoding Speed in Working Memory

Humans can adapt when complex patterns unfold at a faster or slower pace, for instance when remembering a grocery list that is dictated at an increasingly fast rate. Integrating information over such timescales crucially depends on working memory, but although recent findings have shown that working memory capacity can be flexibly adapted, such adaptations have not yet been demonstrated for encoding speed. In a series of experiments, we found that young adults encoded at a faster rate when they were adapted to overall and recent stimulus duration. Interestingly, our participants were unable to use explicit cues to speed up encoding, even though these cues were objectively more informative than statistical information. Our findings suggest that adaptive tuning of encoding speed in working memory is a fundamental but largely implicit mechanism underlying our ability to keep up with the pace of our surroundings.

Price Negotiation of E-Purchasing Catalog In Government Procurement of Goods/Services

The role of the purchasing manager (purchase manager/commitment manager) in price negotiations is very important because the price of the items listed in the catalog is the price set by the catalog supplier. The government details and strictly regulates electronic shopping lists in price negotiations. However, in practice, this is difficult to apply because information about the strategy and ethics of purchasing managers of goods/services in price negotiations is limited, so that the procedures for implementing strategies and ethics in price negotiations for online shopping must be developed. This study is intended as a practical academic approach for procurement organizers to negotiate the price of an electronic purchase list, starting from procurement preparation and implementation of an electronic purchase list in the LKPP online purchase list application. This study uses a qualitative descriptive method by looking at various government regulations regarding the procurement of goods/services and other supporting literature. The result of this study is PP/PPK in negotiating prices for e-Purchasing Catalogs has been given technical guidance by LKPP through Decree of the Head of LKPP Number 122 of 2022 concerning Procedures for Organizing Electronic Catalogs

Cloudbook Website

Abstract: CloudBook is a notes-taking platform that allows users to create and organize notes in separate files with headings, subheadings, and content. The platform automatically updates the changes made when users save and sign out. While phone notepads are commonly used to write down grocery lists, to-do lists, or notes from presentations, these notes often get lost or become disorganized. Additionally, transferring them to a computer can be challenging. To address this issue, CloudBook was created to provide an organized and accessible format for note-taking. The platform includes features such as checklists, emoticons, and the ability to save external links for further reading. Users can access their notes from any device by logging into their accounts.

CloudBook Website

Abstract: CloudBook is a notes-taking platform that allows users to create and organize notes in separate files with headings, subheadings, and content. The platform automatically updates the changes made when users save and sign out. While phone notepads are commonly used to write down grocery lists, to-do lists, or notes from presentations, these notes often get lost or become disorganized. Additionally, transferring them to a computer can be challenging. To address this issue, CloudBook was created to provide an organized and accessible format for note-taking. The platform includes features such as checklists, emoticons, and the ability to save external links for further reading. Users can access their notes from any device by logging into their accounts.

Momma, Refracted

Momma, Refracted JC Andrews (bio) Keywords poetry, JC Andrews, machine, plastic, body, sweat, hospital, ghosts I’m so in love with you all of a sudden, you machine angel. Angel machine. Because I am still learning your new smells. Plastic, salt, animal, finally and still thinking plastic, salt, animal, finally. Because you are letting me stand you up in the shower and wash your hair like you are not my mother, like I am not your daughter. And this distance is good for me. When you are tired, I pull your arm over my strange new shoulders. String your weight into my side. We walk together the long walk back to where you will not sleep but ask questions that I’ll answer again and again with the chestspoken Yes of my body. My body. It sticks these days like a weird rainbow in the corner of your room. I remember now that you were making a grocery list. Everyone wants to see it. The last part. The part you didn’t finish. Minds will make math of this. Alien. Angel. Miracle. Machine. The baseball game will stay on and dreamloop forever. You will forget me. The lines in your neck. The names of things. And I will hold you like I am thick as my slow manners. But right now, you are sweating in your yellow gown with your mouth wide open. You were long gone yesterday, and I see it everywhere I put these wet paper towels from up above the hospital sink. On your wrists, your cheeks, and your chest that is, yes, still moving. From this far away, I can song you down like a child, except you are not a child, and I am all the time, [End Page 150] always your child. From this far away, we can bend each other bright and lonely. Our ghosts are stealing third. We are the slowest light. Weather slung haunted. [End Page 151] JC Andrews jc andrews is a poet from Springfield, AR, with an interest in poems that work as an un-ing, poems that hold questions as a form of caretaking. She is the author of the chap-book Sweetwork, and her writing can be found in The Red Wheelbarrow, New Ohio Review, and elsewhere. She was a semifinalist for the 2021 Red Wheelbarrow Poetry Prize, a finalist for the 2021 New Millenium Writing Award, a finalist for the 2023 NORward prize, and a top ten applicant of the Mountain Words Writer-in-Residence program. She currently serves as an associate editor of Indiana Review. Copyright © 2023 The Massachusetts Review, Inc

Cholinergic system adaptations are associated with cognitive function in people recently abstinent from smoking: a (-)-[18F]flubatine PET study.

The cholinergic system is a critical mediator of cognition in animals. People who smoke cigarettes exhibit cognitive deficits, especially during quit attempts. Few studies jointly examine the cholinergic system and cognition in people while trying to quit smoking. We used positron emission tomography (PET) brain imaging with the β2-subunit containing nicotinic acetylcholine receptor (β2*-nAChR) partial agonist radioligand (-)-[18F]flubatine and the acetylcholinesterase inhibitor physostigmine to jointly examine the cholinergic system, smoking status, and cognition. (-)-[18F]Flubatine scans and cognitive data were acquired from twenty people who recently stopped smoking cigarettes (aged 38 ± 11 years; 6 female, 14 male; abstinent 7 ± 1 days) and 27 people who never smoked cigarettes (aged 29 ± 8 years; 11 female, 16 male). A subset of fifteen recently abstinent smokers and 21 never smokers received a mid-scan physostigmine challenge to increase acetylcholine levels. Regional volume of distribution (VT) was estimated with equilibrium analysis at "baseline" and post-physostigmine. Participants completed a cognitive battery prior to (-)-[18F]flubatine injection and physostigmine administration assessing executive function (Groton Maze Learning test), verbal learning (International Shopping List test), and working memory (One Back test). Physostigmine significantly decreased cortical (-)-[18F]flubatine VT, consistent with increased cortical acetylcholine levels reducing the number of β2*-nAChR sites available for (-)-[18F]flubatine binding, at comparable magnitudes across groups (p values < 0.05). A larger magnitude of physostigmine-induced decrease in (-)-[18F]flubatine VT was significantly associated with worse executive function in people who recently stopped smoking (p values < 0.05). These findings underscore the role of the cholinergic system in early smoking cessation and highlight the importance of neuroscience-informed treatment strategies.

Looking beyond the laboratory: Exploring behavioral and eye-fixation patterns in individuals with severe mental illness during a real-life supermarket task.

Individuals with severe mental illnesses (SMI) often have difficulty performing daily activities that require intact executive functions, such as grocery shopping. Performance-based evaluations are valuable but lack the subjects' viewpoints during task performance. This study aims to combine performance-based observation and cognitive science methods to provide insights regarding real-life behavior and problem-solving in populations with SMI. In this correlational-research study, 42 participants (10 in the SMI group and 32 in the control group) performed the Test of Grocery Shopping Skills (TOGSS) while wearing an eye-tracking device. We hypothesized that patterns in task planning, task-time use, and attention allocation to written information relevant to the task would differ between the groups during the task. The results showed between-group differences in both TOGSS efficiency outcomes (time and redundancy), duration, and number of fixations. An eye-tracking pattern analysis determined between-group differences in scanning patterns of the grocery list but similarities in task planning. The selection process was found to be significantly more accurate and efficient for the control group than for the SMI group. Our findings suggest that a combination of perspectives allows us to better understand the behavior of SMI individuals in a regular daily task.

MARKET BASKET ANALYSIS USING APRIORI ALGORITHM: GROCERY ITEMS RECOMMENDATION

A grocery list is frequently used to make sure that only essential items are bought and nothing else is forgotten. Due to the extensive list of items, they must buy each month, people frequently forget what they need to buy when they get to the supermarket. Even with a list, there are still things that get left out. Therefore, an application called MyGrocery is proposed that offers suggestions for items users frequently buy together and aids users in creating grocery lists. This might help them make a personalised grocery list with items that are suggested based on their past purchases. The aim is to help them keep track of what they have bought as well as to help them create personalised grocery lists. Market basket analysis is used to find associations between items in MyGrocery using past purchased history. The result shows the significant recommendation by MyGrocery where the Market Basket Analysis, which is carried out using the Apriori Algorithm, displayed the recommended item following the calculation of lift value.

Factors Influencing Impulsive Buying Behaviour of Women in Supermarkets of Nepal

The primary goal of this study is to examine the factors influencing Nepalese women's impulsive buying behaviour in supermarkets. Cross-sectional research design was adopted for carrying out the study in which 211 responses were collected both online and in printed form. Selection of respondents was based on convenience and judgement sampling. Women's impulsive purchasing behaviour in supermarkets was found to be highly influenced by their financial independence and the store environment. Further, the outcomes of the study reveal that women are more inclined to shop when they have the financial means to pay for their items by themselves, while the store environment influences women to adjust their inflexible shopping lists. So, supermarkets are advised to arrange the store with good ambience and friendly staffs. Future studies shall take a broader geographic perspective and factors like packaging, culture, and way of life into consideration.

Intervention strategies to promote healthy and sustainable food choices among parents with lower and higher socioeconomic status

BackgroundA global shift towards more healthy and sustainable diets is necessary for the prevention of obesity and chronic diseases, as well as for the growing pressure on our ecosystems. Given that parents are important actors in affecting dietary behaviors of their children, developing intervention strategies targeting families and their practices is promising to reach positive behavior change among children. Also, it is important to tailor these interventions to the needs of parents with different socioeconomic statuses (SES), given that health inequalities continue to grow. This study aims to investigate perspectives of lower and higher SES parents on the usability and acceptability of various innovative intervention strategies.MethodsFourteen focus groups and four individual interviews (n = 78, nlowerSES = 17; nhigherSES = 61) were conducted in Belgium. A semi-structured interview guide was used to facilitate the discussions. The interviews were recorded, transcribed, and analyzed via thematic content analysis using NVivo.ResultsTo encourage healthy and sustainable food choices, interventions via online food shopping platforms and nudging strategies in grocery stores were mostly cited by higher SES parents, but these were less applicable for lower SES parents as they buy less online and mainly consider the price of products. Mobile applications that provide inspiration for healthy and sustainable recipes and easily accessible shopping lists received moderate support among lower and higher SES parents. Furthermore, both lower and higher SES parents showed interest in meal boxes delivered at home, but lower SES parents have not yet tried such meal boxes because of their higher prices. Still, both groups of SES parents mentioned many advantages of these meal boxes, such as the convenience and time-saving component, as well as the cooking inspiration aspect.ConclusionOur study reveals the preferences of lower and higher SES parents for practical intervention strategies, providing insight in what features these strategies should have to be acceptable and useful. Hence, the findings can inform the development of a tailored family-based intervention strategy to improve parental food choices in favor of increased health and sustainability.

Developing an online shop sampling frame from big data

The development of information technologies and the massive generation of data in today’s digital world provides new opportunities for official statistics. Big data, especially produced by a marketplace have a great potential to produce a list of online shops. The aim of this paper is to develop an online shop sampling frame from marketplace data. Using the shop and item datasets, an item-level data algorithm is developed to determine whether a shop is active or not to be included in the frame. In this study, the focus is for online shops in Jakarta Province, Indonesia. The algorithm is built using divide and conquer principle and statistical method. The frame produced consists of 13 attributes such as Shop ID, number of items, annual revenue, shop types, Business scale classification and the location (URL and physical address). The frame contains of 101,443 active online shops which most of it are micro enterprises.

Has the COVID-19 pandemic changed household food management and food waste behavior? A natural experiment using propensity score matching

Household food management behavior changed considerably during the COVID-19 pandemic. A growing body of work has quantified the impact of lockdowns on household food waste. Yet, previous studies used a retrospective study design which undermines the accuracy of the causal effect on household food waste. This paper investigates the causal impact of the COVID-19 pandemic on household food management and food waste using a natural experiment approach. Using two large national-scale longitudinal data sets (n = 8157), this study quantifies the impact of COVID-19 on food waste and food behavior of Australian households. Propensity score matching (PSM) was carried out to address potential endogeneity issues and to select control and treatment groups for analysis. Findings reveal that Australian households reduced food waste by 9% on average in 2020 (during COVID-19) compared to the pre-pandemic (2019) level. The use of a grocery list, discount purchases, and ‘just-in-case’ purchases, and food refrigeration have recorded a marked increase during the pandemic compared to pre-pandemic times. The changes to food management and food discard behavior during the pandemic offer important insights for behavior change campaigns to reduce household food waste. Interventions to sustain good food planning and storage practices and involving food retailers are promising entry points in addressing household food waste. The study also highlights the considerable challenge in achieving SDG 12.3 target by 2030.

Intelligent personalized shopping recommendation using clustering and supervised machine learning algorithms.

Next basket recommendation is a critical task in market basket data analysis. It is particularly important in grocery shopping, where grocery lists are an essential part of shopping habits of many customers. In this work, we first present a new grocery Recommender System available on the MyGroceryTour platform. Our online system uses different traditional machine learning (ML) and deep learning (DL) algorithms, and provides recommendations to users in a real-time manner. It aims to help Canadian customers create their personalized intelligent weekly grocery lists based on their individual purchase histories, weekly specials offered in local stores, and product cost and availability information. We perform clustering analysis to partition given customer profiles into four non-overlapping clusters according to their grocery shopping habits. Then, we conduct computational experiments to compare several traditional ML algorithms and our new DL algorithm based on the use of a gated recurrent unit (GRU)-based recurrent neural network (RNN) architecture. Our DL algorithm can be viewed as an extension of DREAM (Dynamic REcurrent bAsket Model) adapted to multi-class (i.e. multi-store) classification, since a given user can purchase recommended products in different grocery stores in which these products are available. Among traditional ML algorithms, the highest average F-score of 0.516 for the considered data set of 831 customers was obtained using Random Forest, whereas our proposed DL algorithm yielded the average F-score of 0.559 for this data set. The main advantage of the presented Recommender System is that our intelligent recommendation is personalized, since a separate traditional ML or DL model is built for each customer considered. Such a personalized approach allows us to outperform the prediction results provided by general state-of-the-art DL models.

User‐led Design of a Self‐administered Smartphone‐based Learning and Memory Assessment

AbstractBackgroundThe International Shopping List test (ISLT) is a verbal word list learning assessment set within a realistic shopping list context, supporting ease of cultural adaptation, and addressing content validity and patient relevance. Improvements to and the wide adoption of natural language processing (NLP) software has enabled the possibility for self‐administered tests of verbal learning. A beta version of a self‐administered, smartphone‐application (app) was developed, using the virtual assistant and NLP: the “List Learning and Memory Assessment (LilaTM)”.MethodTo ensure usability of the app, a user led design process was followed. A beta version was created via several rounds of focus group development in older adults. 12 older adults were then recruited for interviews (8 healthy and 4 with Mild Cognitive Impairment). Participants were pseudo‐randomly assigned to participate in interviews during test performance, using either iPhone or Nokia devices. Each participant completed the test and provided concept elicitation feedback. Qualitative analysis of the interview results was performed using thematic coding.ResultKey positive themes included the ease with which the app could be navigated, and the clarity of visual display and instructions, whilst an important negative theme was the length of time between different components of the test.ConclusionQualitative analysis of concept elicitation interviews has suggested several areas of improvement to the beta‐app, including improvements to performance that shorten processing and wait times between test components. The clarity of the visual display and test instructions were well supported.

Validity of a remote supervised preclinical Alzheimer’s disease cognitive composite (PACC) score in preclinical and prodromal Alzheimer’s disease.

AbstractBackgroundNeuropsychological tests administered to individuals in locations different from the assessor (i.e., remote assessment) can provide substantial reductions in patient burden, study cost and barriers to access. However, such tests must be optimized and validated for use in remote settings. The preclinical cognitive composite score (PACC) is derived from neuropsychological tests of episodic memory, complex attention, and general mental status. This study determined whether a set of neuropsychological tests of these domains, which can provide a PACC score, can be given in a remote supervised setting and remain sensitive to AD related cognitive impairment.MethodOlder adults classified as cognitively unimpaired (CU, n = 30), preclinical AD (n = 30) or prodromal AD (n = 25), with conventional PACC scores known, completed three computerized tests; the International Shopping list Test (ISLT), Continuous Paired Associate Learning Test (CPAL) and the International Digit Symbol Substitution Test, while supervised by a neuropsychologist in in‐clinic and remote settings. All individuals then completed the remote assessments two more times 7days (+/‐4 days) apartResultMain performance measure from each test on each assessment was standardized using the mean and SD of the CU group, assessed under supervision, at baseline. Standardized scores for each assessment were then averaged to yield a PACC score. There was no difference in rates of missing data or group mean score on individual test scores or PACC score, between in‐clinic and remote settings. Compared to the CU group, impairment in performance on the digital PACC in the prodromal AD was substantial (z = ‐1.56) but equivalent between in clinic (9z = 1.57) and remote (z = ‐1.56) settings. Performance on the digital PACC was slightly worse in the preclinical AD group (z = –0.42) but did not differ for settings. The reliability of the digital PACC score was very high (r = 0.87).ConclusionThe digital PACC derived from neuropsychological tests given in remote supervised contexts is acceptable, valid, reliable and sensitive to AD related cognitive impairment when given in‐clinic or remotely.

Effect of transcranialdirect current stimulation on the right brain temporal area on processing approach and avoidance attitudes with negation

Language describes approach/avoidance intentionality by means of attitudinal verbs (e.g., accept vs. reject). The right superior temporal sulcus (rSTS) has been shown to be recruited in processing action goals and approach intentionality in social contexts. In this study, we examine whether transcranial direct current stimulation (tDCS) of this area improves the processing of attitudinal verbs (either of approach or avoidance) in the context of affirmative and negative sentences [e.g., Julio (did not)/included meat on the grocery list]. After being subjected to tDCS, 46 participants were given sentences for passive reading. Sentences were displayed in segments with a fixed time of exposition, and a verb, either the one mentioned in the sentence or an alternative one was displayed 1,500 ms after the sentence (e.g., included vs. excluded, in the example). Participants were told to read them and then press the space bar to continue the experiment. Results showed shorter latencies for approach verbs that were either mentioned in approach sentences or the alternatives in avoidance sentences, both in affirmative and negative versions under anodal conditions compared to sham conditions. Thus, the anodal stimulation of rSTS affected the accessibility of approach verbs that were not modulated either by being mentioned or by sentence polarity. In addition, mentioned verbs had shorter reading times than the alternative ones in negative sentences in the anodal vs. sham condition. This suggests that stimulation caused an effect of negation in the activation of the mentioned verb. Implications are discussed in the context of the role of the rSTS in processing attitudinal verbs and negation to understand better approach and avoidance mediated by language in the framework of the two-step model of negation processing.

Food Carbon Literacy: A Definition and Framework Exemplified by Designing and Evaluating a Digital Grocery List for Increasing Food Carbon Literacy and Changing Behavior

Public knowledge about the differences in greenhouse gas emissions caused by the production and transportation of different kinds of food are generally low. People with an interest in choosing food with low greenhouse gas emissions must therefore either increase this “food carbon literacy” or be provided with such information when they decide what food to buy. Research about this specific kind of food literacy is, however, scarce, lacking both well-defined terminology and interventions attempting to increase food carbon literacy. In this paper we provide a framework for future research in the area by defining “food carbon literacy”, serving as a starting point for categorizing, comparing, and generalizing future research findings. Drawing on previous work on other kinds of literacies, we distinguish between (1) food carbon literacy, (2) food product carbon literacy, (3) food handling carbon literacy, and (4) financial food carbon literacy. We have furthermore developed and tested a digital behavior change intervention in the form of a digital grocery list used on mobile phones. The list works as other digital grocery shopping lists, but also displays the CO2e footprint of the food added to the list, thereby enabling the user to change products at the planning stage and increase their food carbon literacy. It was tested on a group of 38 people for a duration of 2 weeks. The goals of the pilot study were to investigate quantitatively whether such a tool would increase food carbon literacy, and to investigate qualitatively how such a tool could be used and designed. The results show a strong increase in food carbon literacy for food the respondents had added to their grocery lists, but also for food that had not been added to their lists, indicating a generalization of the knowledge. Finally, we provide implications for the design of such systems, based on the qualitative evaluation.