To see the other types of publications on this topic, follow the link: Product recall process.
Journal articles on the topic 'Product recall process'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Product recall process.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Peters, Wesley, Carl Pellerin, and Cory Janney. "RESEARCH: Evaluation of Orthopedic Hip Device Recalls by the FDA from 2007 to 2017." Biomedical Instrumentation & Technology 54, no. 6 (November 1, 2020): 418–26. http://dx.doi.org/10.2345/0899-8205-54.6.418.
Full textAbstract:
Background: Medical device recalls have increased in the previous two decades. Orthopedic devices are estimated to constitute 12% of all medical devices recalled. Medical devices enter the market via the Food and Drug Administration's (FDA's) premarket approval (PMA) or 510(k) pathways. This article evaluates orthopedic hip device recalls between Jan. 1, 2007, and Dec. 31, 2017. We hypothesized that the 510(k) approval process would have substantially higher recall rates for defective devices. Methods: The FDA's device recall database was queried for all orthopedic hip devices from Jan. 1, 2007, to Dec. 31, 2017. Each recall included product description, recall number, device class, date of recall posting, date of recall termination, manufacturer, FDA-determined cause for recall, number of recalled units, distribution, product classification, and method of approval [510(k), PMA, or unspecified]. Results: In total, 774 orthopedic hip devices were recalled between Jan. 1, 2007, and Dec. 31, 2017. The 510(k) approval process constituted 85% of hip device recalls. The most common FDA-determined cause of hip device recalls was device design, which constituted 37% of 510(k)-approved device recalls but only 6% of PMA-approved device recalls. The most recalled hip devices were hip prostheses. Orthopedic hip device recalls have shown a decrease of about 10 recalls per year during the 11-year period of analysis. Conclusion: Devices approved through the 510(k) process, compared with the PMA process, were more likely to be recalled for design defects. Although device design is the most common reason for device recall, many recalls are due to suboptimally standardized processes (e.g., packaging, process controls, device labeling). Overall, orthopedic hip device recalls decreased during the period of analysis (2007–17).
2
Wynn, M. T., C. Ouyang, A. H. M. ter Hofstede, and C. J. Fidge. "Data and process requirements for product recall coordination." Computers in Industry 62, no. 7 (September 2011): 776–86. http://dx.doi.org/10.1016/j.compind.2011.05.003.
Full text
3
Nandhini B, Balamurlidhara V, Aniket Anant Gulumkar, and Sridhar S. "Drug recall procedure in United Kingdom and Australia: a regulatory overview." International Journal of Research in Pharmaceutical Sciences 11, no. 2 (April 3, 2020): 1457–66. http://dx.doi.org/10.26452/ijrps.v11i2.2018.
Full textAbstract:
Recall occur as a consequence of the safety concerns over a manufacturing defect in a product that may harm its user. Due to their deficient quality, security or effectiveness, medicinal products are accused of being possibly dangerous to customers and may be subject to recall. A recall is defined as the process of recovering. A pharmaceutical product from the distribution chain due to product deficiencies, complaints of serious adverse reactions or corners that the product is or may be defective. The objective of study is to help identify the significance of the recall action and classification and focused on the prospective danger of the patient / consumer defect and, to understand the recall procedure in United Kingdom and Australia. The recall may either be conducted by the license holder or the manufacturer, or and the wholesale dealer. The evaluation should consist of checking the efficacy of the recall and investigating the justification for the recall as well as the remedial measures adopted to avoid the occurrence of the issue. The present work highlights the comparison of the recall procedure between United Kingdom and Australia.
4
Alba, Joseph W., and Amitava Chattopadhyay. "Salience Effects in Brand Recall." Journal of Marketing Research 23, no. 4 (November 1986): 363–69. http://dx.doi.org/10.1177/002224378602300406.
Full textAbstract:
The effects of brand salience on brand recall were investigated in five experiments, each involving a different product category. The authors demonstrate that increasing the salience of a single brand can significantly impair unaided recall of competing brands. The effect was observable even in the early stages of the recall process.
5
Wang, Lei, and Chang Liu. "Evolutionary Game Analysis on Government Supervision and Dairy Enterprise in the Process of Product Recall in China." International Journal of Information Systems in the Service Sector 12, no. 1 (January 2020): 44–66. http://dx.doi.org/10.4018/ijisss.2020010104.
Full textAbstract:
On the basis of stating recall and regulation mode, this paper analyzes long-term evolutionary trend between dairy enterprise and government supervision on bounded rationality with evolutionary game. The authors use Python matplotlib to simulate research results. Studies show that it is helpful to build a standard recall system of defect and dairy products. This system should reduce the costs of government supervision. In addition, in case of mandatory recall, it should strengthen punishment intensity of the government supervision branch on dairy enterprise, increase more losing costs of dairy enterprise, and decrease external environment benefits of dairy enterprise. In case of voluntary recall, the system should encourage various strategies and subsidy of the government supervision branch on dairy enterprise and amplify social influence of dairy enterprise. Especially, the paper puts forward detailed strategies for dairy enterprise.
6
Wang, Chuanxu, Changqun Song, and Lang Xu. "Evolutionary strategies of consumer federation and manufacturer under recall mechanism." Journal of Intelligent & Fuzzy Systems 41, no. 1 (August 11, 2021): 2403–15. http://dx.doi.org/10.3233/jifs-200086.
Full textAbstract:
Based on an unqualified product recalling process in a supply chain, this paper establishes an evolutionary game model between consumer federation and manufacturer, as well as analyzes the effects of manufacturer’s pricing strategy and consumer federation’s supervision on the decision-making and dynamic tendency. Under this structure, the manufacturers’ pricing strategies on recalls mechanism have two scenarios: the high penalty and low penalty from consumer federation. Results shows that, when the consumer federation adopts high penalty measures, there will be an ESS for consumer federation that can both minimize the cost and protect consumers’ rights. Further, the probability of manufacturer adopting “recall” strategy is positively correlated with the change in the product price, and both the probability of consumer federation adopting “regulate” strategy and manufacturer adopting “recall” strategy are positively correlated with the penalty coefficient.
7
Schumacher, Roman, Rob Glew, Naoum Tsolakis, and Mukesh Kumar. "Strategies to manage product recalls in the COVID-19 pandemic: an exploratory case study of PPE supply chains." Continuity & Resilience Review 3, no. 1 (February 3, 2021): 64–78. http://dx.doi.org/10.1108/crr-07-2020-0024.
Full textAbstract:
PurposeThe purpose of this paper is to investigate strategies to manage product recalls where shortages are a critical threat, with impacts such as loss of life. The authors aim to identify key supply chain strategies and opportunities for theoretical advancement by taking a resilience perspective on temporary supply chain design.Design/methodology/approachFirst, the authors conducted an impact event analysis of product recalls by exploring the RAPEX database and official statements of individual country regulators. Second, the authors conducted an exploratory case study with the Cambridge University Hospitals on Personal Protective Equipment to explore product recall risks, utilising an action research methodology.FindingsAdditional processes, mainly testing, can compensate for the risks that may arise from temporary supply chains, where changes in location and product design are not possible due to the immediate nature of demand caused by COVID-19 pandemic. This finding reflects on the resilience of designing and implementing temporary supply chains from the perspective of product, process and location.Research limitations/implicationsThis paper does not employ an in-depth multiple case study methodology. However, the authors argue that the role of institutional actors in global supply chains and its implications on product safety needs to be empirically studied in order to expand existing supply chain management theories to cover resilience in emerging, mature and temporary supply chain.Practical implicationsManagers can learn from the Cambridge University Hospitals case study that a downstream quality inspection system can be deployed to manage product quality and safety risks where recalls are not an option, such as during critical situations in the COVID-19 pandemic.Social implicationsThe authors’ observations suggest that governments may be socially responsible for implementing rigorous mechanisms to manage product recall risks that compromise consumer safety.Originality/valueThe authors’ study is uniquely designed and studies various specific phenomena of product recalls risks in COVID-19. The unique design features include a dynamic and recent database analysis involving a product, process and location centric perspective complemented with a Cambridge University Hospitals case study.
8
Ekstrand, Susie Stærk, and Kristine Lilholt Nilsson. "Faced with a Recall – How good is your Insurance?" European Journal of Risk Regulation 2, no. 2 (June 2011): 244–46. http://dx.doi.org/10.1017/s1867299x00001197.
Full textAbstract:
Any business having experienced a product recall knows how costly this can be. Sometimes the main costs of the recall are concentrated around counteracting bad publicity, but if several or large numbers of batches are affected by the recall, the costs of the recall itself can mount up considerably.In many large companies the overall responsibility for quality assurance and product safety is placed in a different part of the organization from the one responsible for product liability insurance and recall insurance.As a consequence inside the organization there is not always a common understanding of what the insurance should cover and what the insurance actually does cover – or of whether and when the insurance company should become involved in the process.
9
Aboelela, Eman M., Walaa Gad, and Rasha Ismail. "The impact of semantics on aspect level opinion mining." PeerJ Computer Science 7 (June 18, 2021): e558. http://dx.doi.org/10.7717/peerj-cs.558.
Full textAbstract:
Recently, many users prefer online shopping to purchase items from the web. Shopping websites allow customers to submit comments and provide their feedback for the purchased products. Opinion mining and sentiment analysis are used to analyze products’ comments to help sellers and purchasers decide to buy products or not. However, the nature of online comments affects the performance of the opinion mining process because they may contain negation words or unrelated aspects to the product. To address these problems, a semantic-based aspect level opinion mining (SALOM) model is proposed. The SALOM extracts the product aspects based on the semantic similarity and classifies the comments. The proposed model considers the negation words and other types of product aspects such as aspects’ synonyms, hyponyms, and hypernyms to improve the accuracy of classification. Three different datasets are used to evaluate the proposed SALOM. The experimental results are promising in terms of Precision, Recall, and F-measure. The performance reaches 94.8% precision, 93% recall, and 92.6% f-measure.
10
Langer, Philip, Verne Keenan, Julie Wetzel, Juree Jacques-Griffin, and David Chiszar. "Memorial Representations as a Product of Feedback and Text Variants." Psychological Reports 78, no. 3 (June 1996): 803–13. http://dx.doi.org/10.2466/pr0.1996.78.3.803.
Full textAbstract:
This study examined the effects of feedback on several memorial representations of a text. Subjects were given either of two variant texts describing a mythical town. One version (route) describes the town as a driver might encounter it, while the other (survey) describes the town using spatial referents. Each version is 25 sentences long and is presented one sentence at a time to control the reading process. For each text version, after reading the text subjects were given 50 seconds to read the entire text in paragraph form (textual feedback) or see a map of the town (map feedback). They were then asked to recall as much of the text as possible and to verify the accuracy of inferential statements. The subjects then read the same version again. Following the reading subjects were given either the same or the alternate type of feedback. Recall and inferential reasoning protocols were obtained again. The recall protocols were scored for number of propositions, and the scores for accuracy of verification of estimated inferential reasoning using a d′ analysis. Recall yielded a doubling of propositions from the first to the second reading. Analysis yielded several findings: (1) a gain in d′ scores between trials, (2) a significant interaction between text version and trial, with the survey group showing a much larger gain than the route version, and (3) an interaction between version, type of feedback, and sequence, with readers of the survey version showing consistently better scores across all conditions. Data for the route version showed some interference between Trials 1 and 2. The results are described within the context of our memorial model of assisted comprehension.
11
Conzola, Vincent C., and Katherine W. Klein. "Need for Cognition: An Individual Differences Approach to Understanding Warning Effectiveness." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42, no. 11 (October 1998): 811–15. http://dx.doi.org/10.1177/154193129804201109.
Full textAbstract:
Research has shown that trait individual differences in need for cognition influence the evaluation of persuasive messages. Product warning instructions can be considered a form of persuasive message because a goal of warnings is to change attitudes and alter behavior. This research investigated the relationship between need for cognition scores and rating and recall measures of warning quality and effectiveness. Product warning instructions were presented with and without injury outcome statistics, which may act as a heuristic cue in the persuasion process. Results showed that individuals higher in need for cognition recalled more warnings that contained statistics and judged all types of warnings as more important. The potential for individual differences to help explain warning effectiveness is discussed.
12
Sujan, Mita, James R. Bettman, and Harish Sujan. "Effects of Consumer Expectations on Information Processing in Selling Encounters." Journal of Marketing Research 23, no. 4 (November 1986): 346–53. http://dx.doi.org/10.1177/002224378602300404.
Full textAbstract:
The study findings suggest that prior expectations about salespeople affect how consumers process information in a selling situation. When the salesperson is seen as typical, product evaluations are unaffected by the quality of the product arguments cited. Thought listing and recall data provide additional support for the notion that analytical processing of information occurs only when the salesperson is discrepant from expectations.
13
Phua, K. L., and F. I. Achike. "Vioxx and other pharmaceutical product withdrawals: ethical issues in ensuring the integrity of drug and medical device research, development and commercialization." Clinical Ethics 2, no. 3 (September 1, 2007): 155–62. http://dx.doi.org/10.1258/147775007781870029.
Full textAbstract:
The Vioxx drug recall and other cases of withdrawals of approved pharmaceutical products as a result of reports of serious harm to users indicate that there are many problems associated with the process of getting these products to the end user the ordinary person in the street. The problems include those related to drug/medical device research and development, clinical trials, presentation and publication of research results, approval by regulatory authorities, preparation of clinical practice guidelines, marketing of products by commercial companies and post-marketing surveillance. This article discusses threats to the integrity of each of these processes and argues that the steady stream of drug recalls indicates the existence of a systemic problem. It concludes with a discussion of possible solutions to these problems.
14
Wiranti, Dyah Ayu, Kurnia Siwi Kinasih, Ainafatul Nur Muslikah, Dyah Wardani, and Agung Teguh Wibowo Almais. "Implementasi Decision Support System Dynamic Menggunakan Weight Product Untuk Menentukan Uang Kuliah Tunggal." Jurnal Ilmiah Informatika 5, no. 1 (June 30, 2020): 1–8. http://dx.doi.org/10.35316/jimi.v5i1.546.
Full textAbstract:
Single tuition is the extension of the single tuition, which can be interpreted as a payment system made at the time of admission in both State and private colleges in Indonesia. Where this single tuition can provide benefits for the equitable of each student and help the students who are less able in terms of the economy that is certainly derived from the underprivileged family. In the calculation process determines the single tuition money each student needs a long process and time. So, there is an idea to implement a Decision Support System Dynamic (DSSD) so that at the time of determination of single tuition can be evenly and by the actual situation. One method that can be used on DSSD is the Weighted Product (WP) method. By implementing the method of WP combined with the concept of DSSD, then generated values of confusion matrix (recall, precision, f-measure, and accuracy) obtained by looking for the value of comparison between test data with pattern data. Obtained confusion matrix value with system testing and get the results Precision 88.89%, Recall 82.76%, Accuracy 77.14%, F-Measure 85.71%.
15
MINATO, Kota, Akira TSUMAYA, and Itsuo HATONO. "S1420103 A Study of Support Method on Recall Processes by Using Design/Manufacturing Process Information of Individual Product." Proceedings of Mechanical Engineering Congress, Japan 2015 (2015): _S1420103——_S1420103—. http://dx.doi.org/10.1299/jsmemecj.2015._s1420103-.
Full text
16
Manjunath D.N., Shailesh T., and Gowrav M.P. "Annual Product Quality Review." International Journal of Research in Pharmaceutical Sciences 11, no. 2 (April 15, 2020): 1862–69. http://dx.doi.org/10.26452/ijrps.v11i2.2094.
Full textAbstract:
Annual Product Quality Review (APQR) is an estimation prepared according to the Current Goods Manufacturing Practice (CGMP) requirements of different regulatory authorities. A Goods Manufacturing Practice (GMP) ensures that the products are constantly produced and controlled according to quality standards. APQR is not only required for GMP but also required for the quality improvement of the pharmaceutical product. APQR is an evaluation carried out annually to measure the standard of quality of each drug with an intention to verify the constancy of current process and to check the correctness of current specifications and to highlight any trend in order to determine the need to change any drug product specifications or the manufacturing processes or control procedures. It is a written report that is required for every drug, based on the data that was collected in the previous year. It is designed to minimize the risks involved in any pharmaceutical production that cannot be eliminated through testing the finished product. The APQR is globally accepted by the industry and the contents should specify a list of manufactured batches, release data and reviews of deviations, complaints, recall and returned goods. This article gives brief overview of regulatory aspects and regulatory requirements for Annual Product Quality Review of pharmaceutical product. It mainly focusses on the documentation required for the preparation of Annual Product Quality Review. Thus the article is based on the regulatory requirements or standards to manufacture and maintain the quality of any pharmaceutical product.
17
Chung, Hyun. "Some Relationships for the Generalized Integral Transform on Function Space." Mathematics 8, no. 12 (December 19, 2020): 2246. http://dx.doi.org/10.3390/math8122246.
Full textAbstract:
In this paper, we recall a more generalized integral transform, a generalized convolution product and a generalized first variation on function space. The Gaussian process and the bounded linear operators on function space are used to define them. We then establish the existence and various relationships between the generalized integral transform and the generalized convolution product. Furthermore, we obtain some relationships between the generalized integral transform and the generalized first variation with the generalized Cameron–Storvick theorem. Finally, some applications are demonstrated as examples.
18
Chang, Yonghwan, and Yong Jae Ko. "The effects of association strength on attention and product evaluation." European Journal of Marketing 52, no. 5/6 (May 14, 2018): 1257–79. http://dx.doi.org/10.1108/ejm-05-2016-0261.
Full textAbstract:
Purpose The purpose of this study was to test whether endorsements that show a low strength of association (bottom-up bias) benefit from increased attention and processing efforts. The current study also tested whether consumer involvement level (top-down bias) dynamically interacts with the bottom-up attention phenomena. Design/methodology/approach Through a series of pretests, 36 potential celebrity-product matches were identified using real athletes and product brands. Two experiments were conducted: 330 individual responses (110 participants × three conditions) were obtained in a within-subjects lab experiment, and 868 participants were recruited for a between-subjects online experiment. Linear mixed modeling and moderated mediation analysis were performed. Findings The relationships between the strength of image associations and attention time to endorsements and recall and choice consideration of endorsed brands were U-shaped and curvilinear. Attention largely mediated the relationship between the strength of association and recall/choice. Involvement effects were diluted by the strength of association effects, rejecting top-down attentional control. Practical implications Brand managers for both products and celebrities are recommended to search for corresponding not only image-matched partners but also endorsement partners with dissonant pre-existing images. Originality/value The majority of the existing endorsement literature has conventionally suggested that congruence between the endorser and the endorsed property, rather than incongruence, induces consumers’ positive endorsement evaluation. This study constructs important theoretical advancements to the existing literature by empirically proving that through an attentional process, an endorsement contract, conventionally perceived as mismatched, can also generate positive outcomes.
19
Kumar, Sameer, Dawn Heustis, and Jacqueline M. Graham. "The future of traceability within the U.S. food industry supply chain: a business case." International Journal of Productivity and Performance Management 64, no. 1 (January 12, 2015): 129–46. http://dx.doi.org/10.1108/ijppm-03-2014-0046.
Full textAbstract:
Purpose – The purpose of this paper is to analyze the US food industry supply chain based on a case study of a leading US global processed food manufacturer to determine areas for improvement in the recall process to reduce the possibility of harming consumers with unsafe products. Design/methodology/approach – Current US Food and Drug Administration and US Department of Agriculture regulations were evaluated to understand the minimum requirements placed upon members of the supply chain within the US food industry. Thereafter, a situation analysis was conducted followed by a cause and effect analysis to illustrate weaknesses within typical recall procedures. Substantiation of the analysis was based on specific information provided by managers from various functional areas of the processed food manufacturer in their interviews and their perspective about the recall/traceability process and its complexities. Findings – Improvement concepts considered were: the implementation of Radio Frequency Identification Technology (RFID); the Food Marketing Institute (FMI) Recall Portal; and standardized global regulations within the food industry. Various phases of RFID are being piloted within the US food industry, but are not yet being widely studied due to the lack of immediate implementation requirements. Specific results pertaining to the FMI Recall Portal are not available due to its recent launch. Research indicated various regulatory processes implemented in individual countries, but no global standards have been agreed upon and initiated. Practical implications – The improvement ideas have implications for timely communication among supply chain partners, resulting in less contaminated product in the hands of consumers. The ability to make these improvements will require collaboration among global suppliers through global regulations and top management support. Originality/value – Understanding the gaps within current regulations and emphasizing the global footprint of how the food industry truly transformed itself into a global marketplace. Future studies need to focus on the cost impact of full RFID implementation across the entire food industry, with an understanding of cost burden ownership and worldwide integration.
20
Rybaczewska, Maria, Siriphat Jirapathomsakul, Yiduo Liu, Wai Tsing Chow, Mai Thanh Nguyen, and Leigh Sparks. "Slogans, brands and purchase behaviour of students." Young Consumers 21, no. 3 (April 20, 2020): 305–17. http://dx.doi.org/10.1108/yc-07-2019-1020.
Full textAbstract:
Purpose The purpose of this paper is to extend the understanding of the influence of slogans (e.g. “Dare for More”) on brand awareness and purchase behaviour of students. Design/methodology/approach Data were collected thorough 34 in-depth face-to-face interviews with university students, using the customer decision process model as an approach. Findings The authors’ research confirmed that conciseness, rhythm and jingle are key features strengthening customers’ recall and recognition, both being moderators of slogans’ power. The role and influence of slogans depend on the stage of the customer decision-making process. Key influencers remain product quality, popularity and price, but appropriate and memorable slogans enhance products’ differentiation and sale. Practical implications The authors’ findings deliver a particular justification for marketers not to promise young consumers too much through slogans, as this leads to too high expectations adversely influencing their post-purchase feelings. During the information search, slogans can create or strengthen or weaken the willingness to buy the advertised product, depending on the slogan, thus emphasising the need for care over slogan design and use. Originality/value This research expands the understanding of slogans and brand awareness from the perspective of their impact on purchase behaviour. The results revealed that the model approach to shopping behaviour does not confirm the belief that slogans influence consumers the most during the phase of Evaluation of Alternatives. Slogans provide a reference point for young consumers to decide whether they are satisfied or dissatisfied with their purchase during the post-purchase phase and provide information during the information search phase. The authors’ results add to the literature in terms of the criteria determining consumers’ recognition and recall of slogans.
21
O'Connor, Richard, Clifford H. Watson, Gary E. Swan, Destiney S. Nettles, Rebecca C. Geisler, and Tabitha P. Hendershot. "PhenX: Agent measures for tobacco regulatory research." Tobacco Control 29, Suppl 1 (January 2020): s20—s26. http://dx.doi.org/10.1136/tobaccocontrol-2019-054976.
Full textAbstract:
The current paper describes the PhenX (Phenotypes and eXposures) Toolkit Tobacco Regulatory Research Agent specialty area and the Agent Working Group’s (WG’s) 6-month consensus process to identify high-priority, scientifically supported measures for cross-study comparison and analysis. Eleven measures were selected for inclusion in the Toolkit. Eight of these are interviewer-administered or self-administered protocols: history of switching to lower tar and nicotine cigarettes, passive exposures to tobacco products, tobacco brand and variety (covering cigars, cigarettes and smokeless tobacco separately), tobacco product adulteration (vent-blocking or filter-blocking) and tobacco warning label exposure and recall. The remaining three protocols are either laboratory-based or visual inspection-based: measurement of nicotine content in smoked or smokeless tobacco products and the physical properties of these two classes of products. Supplemental protocols include a biomarker of exposure and smoking topography. The WG identified the lack of standard measurement protocols to assess subjective ratings of tobacco product flavours and their appeal to consumers as a major gap. As the characteristics of tobacco products that influence perception and use are tobacco regulatory research priorities, the reliable assessment of flavours remains an area requiring further development.
22
Schindler, Maike, and Achim J. Lilienthal. "Students’ Creative Process in Mathematics: Insights from Eye-Tracking-Stimulated Recall Interview on Students’ Work on Multiple Solution Tasks." International Journal of Science and Mathematics Education 18, no. 8 (December 2, 2019): 1565–86. http://dx.doi.org/10.1007/s10763-019-10033-0.
Full textAbstract:
AbstractStudents’ creative process in mathematics is increasingly gaining significance in mathematics education research. Researchers often use Multiple Solution Tasks (MSTs) to foster and evaluate students’ mathematical creativity. Yet, research so far predominantly had a product-view and focused on solutions rather than the process leading to creative insights. The question remains unclear how students’ process solving MSTs looks like—and if existing models to describe (creative) problem solving can capture this process adequately. This article presents an explorative, qualitative case study, which investigates the creative process of a school student, David. Using eye-tracking technology and a stimulated recall interview, we trace David’s creative process. Our findings indicate what phases his creative process in the MST involves, how new ideas emerge, and in particular where illumination is situated in this process. Our case study illustrates that neither existing models on the creative process, nor on problem solving capture David’s creative process fully, indicating the need to partially rethink students’ creative process in MSTs.
23
SAUER, CHARLES J., JESSE MAJKOWSKI, STANLEY GREEN, and RON ECKEL. "Foodborne Illness Outbreak Associated with a Semi-Dry Fermented Sausage Product." Journal of Food Protection 60, no. 12 (December 1, 1997): 1612–17. http://dx.doi.org/10.4315/0362-028x-60.12.1612.
Full textAbstract:
A state department of health reported an increase in cases of human salmonellosis and found an association (odds ratio 20; 95% confidence interval 4 to 131) between Lebanon bologna consumption and 26 confirmed cases of Salmonella typhimurium. Based on this evidence, the manufacturer initiated a voluntary recall of product in commercial channels and added additional safety measures to their manufacturing processes. The USDA's Food Safety and Inspection Service promptly issued a public notification to consumers stating that the suspected product should be returned to the place of purchase. A team of federal investigators concluded that at the time of the outbreak S. typhimurium may have survived the process used by the manufacturer if present in high numbers in raw beef (greater than 104/g). Additionally, the investigators concluded that other manufacturers of similar product needed to add controls to their processes used to manufacture a semi-dry fermented sausage in order to ensure the safety of the final product.
24
Оганян, Игорь Валериевич, and Сергей Валериевич Епифанов. "Алгоритм классификации технического состояния топливного регулятора в пространстве параметров рабочего процесса." Aerospace technic and technology, no. 4sup1 (August 27, 2021): 158–69. http://dx.doi.org/10.32620/aktt.2021.4sup1.22.
Full textAbstract:
This article solves the problem of constructing an algorithm for classifying the technical state of the fuel regulator of a turboshaft engine of a helicopter in the parameter space of the regulator's working process and obtaining estimates of the state of the investigated product. In the introduction to this work, the main methods of classifying the technical state are considered, and a brief justification for the choice of the method for classifying the state of the product in the space of measured parameters used to construct the algorithm is considered in this article, is given. The criteria for the presence of a malfunction in the investigated controller are determined and the basic requirements for the classification algorithm are formed. To simplify the problem being solved, many assumptions about the diagnosed defects were made. The article provides descriptions of all components of the classification algorithm. A brief description of the mathematical model of the fuel regulator is given. The operating mode of the regulator for analysis is selected, and the list of state parameters required for diagnostics and the list of diagnostic parameters of the working process is given. The technique of linearization of the mathematical model of the controller and the technique of constructing the matrix of influence coefficients, which is the basic element of the entire algorithm, is described. The probabilistic characteristic of the credibility of the classification algorithm is determined, and the derivation of the formula for its calculation, based on the Bayes theorem, is also given. To assess the quality of the classification by the diagnostic algorithm, a test sample of workflow parameters was formed. The methodology for constructing a test sample is described and its size is determined. After the product condition estimates are obtained according to the test sample data by the classification algorithm, such a quality criterion as the recall is calculated. As a result of assessing the recall, a table was formed with the values of this criterion for each class. The recall of the algorithm on average for all defects was 89 %. The conclusions indicate possible methods for improving the quality of diagnosis by the algorithm.
25
Shen, Zhengru, and Marco Spruit. "Automatic Extraction of Adverse Drug Reactions from Summary of Product Characteristics." Applied Sciences 11, no. 6 (March 17, 2021): 2663. http://dx.doi.org/10.3390/app11062663.
Full textAbstract:
The summary of product characteristics from the European Medicines Agency is a reference document on medicines in the EU. It contains textual information for clinical experts on how to safely use medicines, including adverse drug reactions. Using natural language processing (NLP) techniques to automatically extract adverse drug reactions from such unstructured textual information helps clinical experts to effectively and efficiently use them in daily practices. Such techniques have been developed for Structured Product Labels from the Food and Drug Administration (FDA), but there is no research focusing on extracting from the Summary of Product Characteristics. In this work, we built a natural language processing pipeline that automatically scrapes the summary of product characteristics online and then extracts adverse drug reactions from them. Besides, we have made the method and its output publicly available so that it can be reused and further evaluated in clinical practices. In total, we extracted 32,797 common adverse drug reactions for 647 common medicines scraped from the Electronic Medicines Compendium. A manual review of 37 commonly used medicines has indicated a good performance, with a recall and precision of 0.99 and 0.934, respectively.
26
Houston, Michael J., Terry L. Childers, and Susan E. Heckler. "Picture-Word Consistency and the Elaborative Processing of Advertisements." Journal of Marketing Research 24, no. 4 (November 1987): 359–69. http://dx.doi.org/10.1177/002224378702400403.
Full textAbstract:
Many advertisers believe the pictorial and verbal components of an ad should convey the same meaning. Based on theoretical and empirical evidence from a variety of areas, three experiments were conducted that show superior recall for ads in which the picture and copy convey discrepant information about product attributes when the picture and brand name are linked interactively. An elaborative processing explanation for the effect is supported by the finding that this superiority diminishes if consumers have less opportunity to process the ad and form associative linkages in memory.
27
Galindo, Luis Miguel, Roberto Escalante, and Norman Asuad. "El proceso de urbanización y el crecimiento económico en México / The Process of Urbanization and Economic Growth in Mexico." Estudios Demográficos y Urbanos 19, no. 2 (May 1, 2004): 289. http://dx.doi.org/10.24201/edu.v19i2.1188.
Full textAbstract:
El objetivo de este trabajo es analizar el impacto del proceso de urbanización en el crecimiento económico en México utilizando los métodos econométricos modernos. Los resultados obtenidos indican que existe una relación estable de largo plazo y positiva entre el producto, la inversión y un índice de urbanización. Ello indica que la inversión y el proceso de urbanización han favorecido el ritmo de crecimiento económico de México. En este sentido, el acelerado proceso de urbanización del país durante el siglo XX tuvo efectos positivos sobre el ritmo de crecimiento económico. Debe sin embargo considerarse que las características del proceso de urbanización en México se han traducido en un alto nivel de concentración económica, en particular en la Zona Metropolitana de la Ciudad de México, con costos crecientes para el crecimiento económico de largo plazo. Ello se refleja en un proceso de desconcentración de las megalópolis a zonas conurbadas en la década de los ochenta, que se ha estabilizado relativamente en los últimos años. AbstractThis article seeks to analyze the impact of urbanization on economic growth in Mexico, using modern econometric methods. The results obtained suggest that there is a stable, long-term positive relationship between the product, investment and the urbanization index. This suggests that investment and urbanization have contributed to the rate of economic growth in Mexico. In this respect, the country’s rapid urbanization in the 20th century had a positive effect on the economic growth rate. One should, however, recall that the characteristics of urbanization in Mexico have translated into a high level of economic concentration, particularly in the Mexico City Metropolitan Zone, with growing costs for long-term economic growth. This is reflected in the decentralization of megalopolises to conurbations during the 1980’s which has stabilized somewhat in recent years.
28
Lam, Wendy Y. K. "Implementing Communication Strategy Instruction in the ESL Oral Classroom: What Do Low-Proficiency Learners Tell Us?" TESL Canada Journal 27, no. 2 (May 19, 2010): 11. http://dx.doi.org/10.18806/tesl.v27i2.1056.
Full textAbstract:
This article reports findings from a strategy intervention study involving a treatment class (N=20) and a comparison class (N=20) in an ESL oral setting. Oral communication strategies were taught to the treatment class. A data-collection method comprising stimulated recall interviews that aimed to investigate respectively the learning process (i.e., strategy use) and the learning product (i.e.,task performance) was employed. The findings indicate that strategy instruction might affect low-proficiency students more than high-proficiency students in terms of both strategy use and task performance. The article concludes with pedagogic implications for communication strategy instruction.
29
Widiyaningsih, Sandra Dwi, and Atit Pertiwi. "ANALYSIS OF OVO APPLICATION SENTIMENT USING LEXICON BASED METHOD AND K-NEAREST NEIGHBOR." Jurnal Ilmiah Ekonomi Bisnis 25, no. 1 (2020): 14–28. http://dx.doi.org/10.35760/eb.2020.v25i1.2416.
Full textAbstract:
Money that has a function as a measuring tool, medium of exchange, and payment tools is transformed according to the development of the digital era with the issuance of electronic money. Ovo is an electronic money application in Indonesia. The public can provide a review of the service ovo application on the google play store. Further, the company can see how the responses from the user regarding the product as an evaluation of application performance so that improvements can be made. This requires a system for analyzing reviews by applying sentiment analysis use the R language. The initial stage of sentiment analysis is pre-processing which consists of case folding, cleansing, stopword, slang-word, and stemming. The data classification process is divided into two classes, namely positive and negative classes using the lexicon-based method, the data that has been carried out is then divided into training data and test data that will be used in the training and testing process using the Confusion Matrix. The results of the accuracy of the system using the k-nearest neighbor algorithm of 93.84%. with a positive preposition of 96,29%, negative preposition of 68,75%, positive recall of 96,18%, negative recall of 73,33% and error system of 6,16%.
30
Sheu, Ruey-Kai, Lun-Chi Chen, Mayuresh Sunil Pardeshi, Kai-Chih Pai, and Chia-Yu Chen. "AI Landing for Sheet Metal-Based Drawer Box Defect Detection Using Deep Learning (ALDB-DL)." Processes 9, no. 5 (April 27, 2021): 768. http://dx.doi.org/10.3390/pr9050768.
Full textAbstract:
Sheet metal-based products serve as a major portion of the furniture market and maintain higher quality standards by being competitive. During industrial processes, while converting a sheet metal to an end product, new defects are observed and thus need to be identified carefully. Recent studies have shown scratches, bumps, and pollution/dust are identified, but orange peel defects present overall a new challenge. So our model identifies scratches, bumps, and dust by using computer vision algorithms, whereas orange peel defect detection with deep learning have a better performance. The goal of this paper was to resolve artificial intelligence (AI) as an AI landing challenge faced in identifying various kinds of sheet metal-based product defects by ALDB-DL process automation. Therefore, our system model consists of multiple cameras from two different angles to capture the defects of the sheet metal-based drawer box. The aim of this paper was to solve multiple defects detection as design and implementation of Industrial process integration with AI by Automated Optical Inspection (AOI) for sheet metal-based drawer box defect detection, stated as AI Landing for sheet metal-based Drawer Box defect detection using Deep Learning (ALDB-DL). Therefore, the scope was given as achieving higher accuracy using multi-camera-based image feature extraction using computer vision and deep learning algorithm for defect classification in AOI. We used SHapley Additive exPlanations (SHAP) values for pre-processing, LeNet with a (1 × 1) convolution filter, and a Global Average Pooling (GAP) Convolutional Neural Network (CNN) algorithm to achieve the best results. It has applications for sheet metal-based product industries with improvised quality control for edge and surface detection. The results were competitive as the precision, recall, and area under the curve were 1.00, 0.99, and 0.98, respectively. Successively, the discussion section presents a detailed insight view about the industrial functioning with ALDB-DL experience sharing.
31
DELIN, J., S. SHAROFF, S. LILLFORD, and C. BARNES. "Linguistic support for concept selection decisions." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 21, no. 2 (March 19, 2007): 123–35. http://dx.doi.org/10.1017/s0890060407070187.
Full textAbstract:
Affective engineering is being increasingly used to describe a systematic approach to the analysis of consumer reactions to candidate designs. It has evolved from Kansei engineering, which has reported improvements in products such as cars, electronics, and food. The method includes a semantic differential experiment rating candidate designs against bipolar adjectives (e.g., attractive–not attractive, traditional–not traditional). The results are statistically analyzed to identify correlations between design features and consumer reactions to inform future product developments. A number of key challenges emerge from this process. Clearly, suitable designs must be available to cover all design possibilities. However, it is also paramount that the best adjectives are used to reflect the judgments that participants might want to make. The current adjective selection process is unsystematic, and could potentially miss key concepts. Poor adjective choices can result in problems such as misinterpretation of an experimental question, clustering of results around a particular response, and participants' confusion from unfamiliar adjectives that can be difficult to consider in the required context (e.g., is this wristwatch “oppressive”?). This paper describes an artificial intelligence supported process that ensures adjectives with appropriate levels of precision and recall are developed and presented to participants (and thus addressing problems above) in an affective engineering study in the context of branded consumer goods. We illustrate our description of the entire concept expansion and reduction process by means of an industrial case study in which participants were asked to evaluate different designs of packaging for a laundry product. The paper concludes by describing the important advantages that can be gained by the new approach in comparison with previous approaches to the selection of consumer focused adjectives.
32
Trianto, Rahmawan Bagus, Andri Triyono, and Dhika Malita Puspita Arum. "Klasifikasi Rating Otomatis pada Dokumen Teks Ulasan Produk Elektronik Menggunakan Metode N-gram dan Naïve Bayes." Jurnal Informatika Universitas Pamulang 5, no. 3 (September 30, 2020): 295. http://dx.doi.org/10.32493/informatika.v5i3.6110.
Full textAbstract:
Online product ratings usually provide descriptive reviews and also reviews in the form of ratings. Likewise, what was done at the Lazada online store. Descriptive review can provide a clear view compared to a rating review to other potential buyers. However, in reality there is a mismatch between the description review and the rating given. This creates a lack of information for sellers as well as potential buyers. Automatic classification of buyer descriptive reviews is proposed in this study so that there is a match between descriptive reviews and rating reviews. This automatic classification descriptive review uses the Naive Bayes algorithm with n-gram feature extraction and TF-IDF word weighting. The results of this study obtained the best accuracy of 94.06%, a recall of 91.73% and precision of 90.71% in Bigram feature extraction. With this accuracy value it can be used as a reference or model for classifying product description reviews, so that the feedback process between sellers and buyers can run well.
33
Listianingsih, Desi. "ANALISIS KUALITAS TAHU TAKWA DENGAN PENDEKATAN GOOD MANUFACTURING PRACTICES (GMP) DI INDUSTRI RUMAH TANGGA." Indonesian Journal of Public Health 13, no. 2 (February 11, 2019): 288. http://dx.doi.org/10.20473/ijph.v13i2.2018.288-298.
Full textAbstract:
The production process of knowing the traditional poultry requires a supervisory system with Good Manufacturing Practices (GMP) approach as stipulated in Regulation of BPOM Head of 2012 on Good Food Making. The quality of tofu produced by a domestic industry must be in accordance with Indonesian National Standard (SNI) 01-3142-1998 about the quality of tofu so that the products know that piety produced safe. This study aims to analyze the quality of know-how with the approach of Good Manufacturing Practices (GMP) and consumer attitudes toward tofu products in one household industry in Kediri. This research was descriptive with cross sectional approach. Aspects of GMP examined were the location and environment of production, buildings and facilities, production equipment, water supply or water supply facilities, hygiene and sanitation facilities and activities, storage, process control, food labeling, supervision by persons responsible, product recall, record and documentation, and employee training, and see the quality of the IRT. The results of the assessment of the implementation of GMP on IRT know this pardon of 59.67%, included in the category of poor assessment. Therefore, it was necessary to improve the production process from the IRT to know piety against the unfavorable aspects, such as facilities and hygiene and sanitation activities, maintenance and hygiene and sanitation programs, storage, supervision by the responsible person, and recording and documentation, so that aspects it complies with the standards and produces quality tofu according to the standard.
34
Mydyti, Hyrmet. "Data Mining Approach Improving Decision-Making Competency along the Business Digital Transformation Journey: A Case Study – Home Appliances after Sales Service." SEEU Review 16, no. 1 (June 12, 2021): 45–65. http://dx.doi.org/10.2478/seeur-2021-0008.
Full textAbstract:
Abstract Data mining, as an essential part of artificial intelligence, is a powerful digital technology, which makes businesses predict future trends and alleviate the process of decision-making and enhancing customer experience along their digital transformation journey. This research provides a practical implication – a case study - to provide guidance on analyzing information and predicting repairs in home appliances after sales services business. The main benefit of this practical comparative study of various classification algorithms, by using the Weka tool, is the analysis of information and the prediction of repairs in the home appliances after sales services business. The comparison of algorithms is performed considering different parameters, such as the mean absolute error, root mean square error, relative absolute error and root relative squared error, receiver operating characteristic area, accuracy, Matthews’s correlation coefficient, precision-recall curve, precision, F-measure, recall and statistical criteria. Five classification algorithms such as the Naive Bayes, J48, random forest, K-Nearest Neighbor, and logistic regression were implemented in the dataset. J48 has proved to provide the best accuracy and the lowest error among the other examined algorithms applied to a home appliances after sales services dataset to predict repairs based on product guarantee period. The extracted information and results of an after sales services business by using data mining techniques prove to alleviate the process of streamlining decision-making and provide reliable predictions, especially for the customers, as well as increase businesses’ efficiency along their digital transformation journey.
35
Lopulalan, Roger, and M. Nur Matdoan. "PENERAPAN STRATEGI BELAJAR MOOD, UNDERSTAND, RECALL, DIGEST, EXPAND, REVIEW (MURDER) DALAM MENINGKATKAN HASIL BELAJAR BIOLOGI KONSEP SISTEM EKSKRESI MANUSIA PADA KELAS XI IPA1 SMA NEGERI 1 KAIRATU." BIOPENDIX: Jurnal Biologi, Pendidikan dan Terapan 2, no. 2 (March 15, 2016): 140–51. http://dx.doi.org/10.30598/biopendixvol2issue2page140-151.
Full textAbstract:
Background: One of the interesting and applicable learning strategies in the learning process is the MURDER learning strategy. Where this learning strategy aims to train and facilitate students in receiving and understanding the material provided. With the strategy of learning murder is expected the students get involved further in the process of teaching and learning effectively so that students are encouraged to understand every material in teaching teachers.
Methods: Instruments used in this study are non-test instruments in the form of affective ratings sheets and psychomotor sheets and test instruments in the form of items used for initial and final tests. Data collection is done by literature, student learning result test, interview and observation. The data have been obtained in the form of scores analyzed in the form of product moment statistics to see the relationship between the results of learning results by using learning strategies MURDER.
Result: Inferential statistic analysis showed that in table "r" product moment db 27 was consulted at 5% significant level obtained r table = 0,381 while significant 1% at r table = 0,487 so there is significant relation between variable x and variable y.
Conclusion: MURDER learning strategy can improve learning outcomes in SMA Negeri 1 Kairatu students and this strategy is very influential on cognitive, affective and psychomotor assessment on students.
36
Untari, Dhian Tyas, Dudung Darusman, Joko Prihatno, and Harnios Arief. "STRATEGI PENGEMBANGAN KULINER TRADISIONAL BETAWI DI DKI JAKARTA." EKUITAS (Jurnal Ekonomi dan Keuangan) 2, no. 3 (August 6, 2019): 313–40. http://dx.doi.org/10.24034/j25485024.y2018.v2.i3.4011.
Full textAbstract:
Betawi is a reflection of the acculturation process of several tribes in Indonesia and even some nations in the world. But in fact, the existence of Betawi Culinary Culture is now starting eroded by the concept of modernization. Culinary is one of the cultural products of a society, as well as Betawi Culinary. Where now aday Betawi Culinary is not a superior culinary in Jakarta. Thus it is necessary to made a business revitalization strategy in developing traditional culinary (Betawi) in Jakarta. Thus in general purpose of the research is to build Betawi Culinary development strategy in Jakarta, so the Traditional Betawi Culinari, will clasified on 3 classification; Familiar Culinary, Recall Culinary and Past Known Culinary. Quantitaive Metode used; EFAS/IFAS matrix, Grand Matris and SWOT. Pairwise comparing and eigenfactor score used as a referral to giving equal weight on EFAS/ IFAS matrix. Result of the study show that cross-sectoral coordination, Strengthening the marketing system and increase the economic value of Betawi Culinary are needed to increasing the existence of culinary betawi in global market. The results expected to be reference for any relevant agencies in develomping traditional culinary as a culture product.
37
Gerdan, Dilara, Abdullah Beyaz, and Mustafa Vatandaş. "Determination of Pear Cultivars (Pyrus communis L.) Based on Colour Change Levels by Using Data Mining." Turkish Journal of Agriculture - Food Science and Technology 8, no. 6 (June 25, 2020): 1291–96. http://dx.doi.org/10.24925/turjaf.v8i6.1291-1296.3304.
Full textAbstract:
Colour is an essential parameter at product quality control stages, and finally, it is necessary for the consumer marketing decision. It is possible to damage the products during the process from collection to storage. Also, it is a well-known condition, cold environmental conditions protect fruits from deformations negative effects, but most of the time, most of the consumers keep the fruits at room temperature in open packs during the consumption process. Also, this condition affects the product storage time. In this study, it is aimed that to determine the behaviours of the fruits in room temperature and humidity conditions. For this aim the colour change of the damaged pears were determined, in another term, colour change value from red to green and yellow to blue at the damaged pears were determined with lightness values by using image analysis technique and analysed with data mining methods. For this purpose, 100 “Akça” pear and 100 “Deveci” local pear cultivar used for experiments. Fruits were equally damaged by using a pendulum mechanism. The damaged fruits were kept at room temperature. Colour change areas on fruits were evaluated with X-rite Ci60 spectrophotometer, and the hardness of fruits was measured by using a fruit penetrometer. The colour (L, a, b) and ΔE values were analysed for the fruit cultivars. The relationship between fruit hardness and colour change were also demonstrated. The predictions were done supervised machine learning algorithms (Decision Tree and Neural Networks with Meta-Learning Techniques; Majority Voting and Random Forest) by using KNIME Analytics software. The classifier performance (accuracy, error, F-Measure, Cohen's Kappa, recall, precision, true positive (TP), false positive (FP), true negative (TN), false negative (FN) values were given at the conclusion section of the research. The best prediction were found at the Majority Voting method (MAVL) 98.458 % success given with 70% partitioning.
38
Wahyu Adi Kurniawan. "a, the Sistem Pendukung Keputusan Pencarian Universitas di Malang Menggunakan Weight Product dengan Pembobotan Weighted Sum Model." Jurnal Ilmiah Informatika 4, no. 2 (December 21, 2019): 103–10. http://dx.doi.org/10.35316/jimi.v4i2.554.
Full textAbstract:
Decision Support System (DSS) is a system that can help someone in making a decision to solve a problem. Weighted Sum Model (WSM) method and Weighted Product (WP) method are used in this system. The WSM method is the sum of the attribute rating multiplications with attribute weights. In this system, WSM method is used as a weight and will be used on the WP method. This weight is filled manually by the user and then calculated by the WSM method. Whereas the Weighted Product (WP) method is a method that uses multiplication to connect attribute ratings, and the rating must be raised first with the weight of the attribute. This system is used in the selection of college in the city of Malang. In the search process there are several criteria used, namely the number of computer department, tuition fees, campus environment, the number of scholarship programs and accreditation. These criteria are used as a reference for college grades used in the assessment section. The search procedure start when a user enters a criteria value that has been determined by the user. Furthermore, the value of the calculation is compared with the value already on data pattern. To find out whether the chosen university matches with the entered criteria, weight of criteria must be checked based on the university chosen by the user. The conversion value from input are compared by the value in the pattern data. The testing process in this study is by using a confusion matrix. Based on testing using the method confusion matrix, researchers obtained 72.50 % value of accuracy, 82,76% value of precision, 80% value of recall and 81,36% value of f-measure.
39
Flores, Victor, and Claudio Leiva. "A Comparative Study on Supervised Machine Learning Algorithms for Copper Recovery Quality Prediction in a Leaching Process." Sensors 21, no. 6 (March 17, 2021): 2119. http://dx.doi.org/10.3390/s21062119.
Full textAbstract:
The copper mining industry is increasingly using artificial intelligence methods to improve copper production processes. Recent studies reveal the use of algorithms, such as Artificial Neural Network, Support Vector Machine, and Random Forest, among others, to develop models for predicting product quality. Other studies compare the predictive models developed with these machine learning algorithms in the mining industry as a whole. However, not many copper mining studies published compare the results of machine learning techniques for copper recovery prediction. This study makes a detailed comparison between three models for predicting copper recovery by leaching, using four datasets resulting from mining operations in Northern Chile. The algorithms used for developing the models were Random Forest, Support Vector Machine, and Artificial Neural Network. To validate these models, four indicators or values of merit were used: accuracy (acc), precision (p), recall (r), and Matthew’s correlation coefficient (mcc). This paper describes the dataset preparation and the refinement of the threshold values used for the predictive variable most influential on the class (the copper recovery). Results show both a precision over 98.50% and also the model with the best behavior between the predicted and the real values. Finally, the obtained models have the following mean values: acc = 0.943, p = 88.47, r = 0.995, and mcc = 0.232. These values are highly competitive when compared with those obtained in similar studies using other approaches in the context.
40
Jiang, Jehn-Ruey, Jian-Bin Kao, and Yu-Lin Li. "Semi-Supervised Time Series Anomaly Detection Based on Statistics and Deep Learning." Applied Sciences 11, no. 15 (July 21, 2021): 6698. http://dx.doi.org/10.3390/app11156698.
Full textAbstract:
Thanks to the advance of novel technologies, such as sensors and Internet of Things (IoT) technologies, big amounts of data are continuously gathered over time, resulting in a variety of time series. A semi-supervised anomaly detection framework, called Tri-CAD, for univariate time series is proposed in this paper. Based on the Pearson product-moment correlation coefficient and Dickey–Fuller test, time series are first categorized into three classes: (i) periodic, (ii) stationary, and (iii) non-periodic and non-stationary time series. Afterwards, different mechanisms using statistics, wavelet transform, and deep learning autoencoder concepts are applied to different classes of time series for detecting anomalies. The performance of the proposed Tri-CAD framework is evaluated by experiments using three Numenta anomaly benchmark (NAB) datasets. The performance of Tri-CAD is compared with those of related methods, such as STL, SARIMA, LSTM, LSTM with STL, and ADSaS. The comparison results show that Tri-CAD outperforms the others in terms of the precision, recall, and F1-score.
41
Diella, Claresta, Ninik Mudjihartini, Diana Sunardi, Dian Novita Chandra, Yulhasri Yulhasri, and Achmad Mulawarman Jayusman. "Serum Lactate Dehydrogenase Activity and Its Corellation with Carbohydrate Intake in Advanced Lung Cancer Patients." World Nutrition Journal 2, no. 2 (January 4, 2019): 1. http://dx.doi.org/10.25220/wnj.v02.i2.0002.
Full textAbstract:
Introduction : The aim of this study was to determine serum lactate dehydrogenase activity and its correlation with carbohydrate intake in advanced lung cancer patients at Dharmais National Cancer Hospital Jakarta. Cancer Cells are characterized by increase anaerobic glycolysis termed the Warburg effect with lactate as an end product, catalyzed by LDH enzyme. Activities of lactate in cancer influences on tumor growth initiation, survival, proliferation, angiogenesis and metastasis. Serum LDH activity can be used as a diagnostic, prognostic, and predictive marker for tumor sensitivity and resistancy to therapy.Methods :56 subjects of advanced lung cancer from Dharmais National Cancer Hospital Jakarta were included in this cross sectional study. Subjects were recruited by consecutive sampling. Food intake of total carbohydrate was obtained by utilizing 24 hours food recall method. The activity of serum LDH (IU/L) was measured by using enzymatic spectrophotometry method on automated analyzer.Results :The mean of age subjects was 56,98 ± 10,36 years old and 55,4% were male. Carbohydrate intake based on 24 hours food recall was 57,64 ± 10,85%. The median of LDH activity was 541,5 (164–6539) IU/L, 60,7% was increase.Conclusion :This study showed medium negative significant correlation (p = 0,017, r = - 0,317) between total carbohydrate intake per day in grams with LDH serum activity. If carbohydrate source is reduced, the LDH enzyme will increase to keep the glycolysis process going. The results of this study indicate that an adequate carbohydrate needed in patients with cancer.
42
Tieman, Marco. "The Four Pillars of Halal Crisis Management." ICR Journal 12, no. 1 (June 30, 2021): 156–60. http://dx.doi.org/10.52282/icr.v12i1.809.
Full textAbstract:
This viewpoint paper is about how to prepare and respond to a halal crisis. Many companies are preparing for the wrong kind of crisis. Too many companies treat a halal issue and halal crisis as a foreign material problem, like finding metal or glass in food, for which a trade or public product recall is initiated with apology. Poorly managed halal crises hit the bottom line hard and can ultimately kill a company. Getting it right, on the other hand, can have its positive effects. Halal crises can also be an opportunity, although probably not experienced during a crisis itself, which could improve halal trust, Islamic values, and its network. This could strengthen a halal brand, sales, and company market share. However, this is only possible with the right actions and communication with a halal issue and crisis. Best practice halal crisis management is founded on four pillars: process, control, organisation, and information. This requires solid preparation and practice.
43
Crusoe, Jonathan Robin, and Karin Ahlin. "Users’ activities for using open government data – a process framework." Transforming Government: People, Process and Policy 13, no. 3/4 (August 8, 2019): 213–36. http://dx.doi.org/10.1108/tg-04-2019-0028.
Full textAbstract:
PurposeThis paper aims to develop a user process framework with activities and their variations for the use of open government data (OGD) based on empirical material and previous research. OGD is interoperable data that is shared by public organisations (publishers) for anyone (users) to reuse without restrictions to create new digital products and services. The user process was roughly identified in previous research but lacks an in-depth description. This lack can hamper the ability to encourage the use and the development of related theories.Design/methodology/approachA three-stage research approach was used. First, a tentative framework was created from previous research and empirical material. This stage involved three different literature reviews, data mapping and seven interviews with OGD experts. The empirical material was analysed with inductive analysis, and previous research was integrated into the framework through concept mapping. Second, the tentative framework was reviewed by informed OGD experts. Third, the framework was finalised with additional literature reviews, eight interviews with OGD users, and a member check, including all the respondents. The framework was used to guide the data collection and as a tool in the analysis.FindingsThe user process framework covers activities and related variations, where the included phases are: start, identify, acquire, enrich and deploy. The start varies relating to the intended use of the OGD. In the identify phase, the user is exploring the accessible data to decide if the data are relevant. In the acquire phase, the user is preparing for the delivery of the data from the publisher and receiving it. In the enrich phase, the user is concocting and making something. In the final deploy phase, the user has a product or service that can be provided to end-users.Research limitations/implicationsThe framework development has some limitations: the framework needs testing and development in different contexts and further verification. The implications are that the framework can help guide researchers towards relevant and essential data of the user process, be used as a point of comparison in analysis, and be used as a skeleton for more precious theories.Practical implicationsThe framework has some practical implications for users, publishers and portals. It can introduce users to the user process and help them plan for the execution of it. The framework can help publishers understand how the users can work with their data and what can be expected of them. The framework can help portal owners to understand the portal’s role between users and publishers and what functionality and features they can provide to support to the user.Originality/valueIn previous research, no user process with an in-depth description was identified. However, several studies have given a rough recall. Thus, this research provides an in-depth description of the user process with its variations. The framework can support practice and leads to new research avenues.
44
Calderón Urbina, Susan Danissa, Antonios Stamatogiannakis, and Dilney Goncalves. "Consumers’ choices between products with different uniqueness duration." European Journal of Marketing 55, no. 13 (August 14, 2021): 148–76. http://dx.doi.org/10.1108/ejm-01-2020-0050.
Full textAbstract:
Purpose This study aims to introduce the duration of uniqueness, an important dimension of unique products. It studies how choices between products with long versus short duration of uniqueness are influenced by the interaction between pressure and consumers’ need for uniqueness (NFU). Design/methodology/approach This research uses a multi-method study approach. A pilot field-study tested the novelty and importance of the research by asking retail professionals to predict the choice of a hypothetical consumer. A retrospective study assessed the importance of duration of uniqueness in unique product choices, by asking consumers about a real and recent unique product purchase. Four additional experimental studies directly tested hypotheses by manipulating pressure and by measuring or manipulating uniqueness motivations. Findings The pilot field-study showed the novelty and relevance of this research for professionals. Study 1 revealed that, retrospectively, uniqueness duration was considered important for the choice of unique products, by high-NFU consumers under pressure. Studies 2 and 3 demonstrated that pressure increases the tendency of high-NFU, but not low-NFU, consumers to choose products with long over short uniqueness duration. Study 4 provided initial evidence for the process behind the effect. Study 5 showed that considerations of uniqueness duration when choosing mediated the effects. Research limitations/implications The results of the pilot field-study and retrospective study might be affected by recall bias or lay theories. The findings need to be replicated with other sources of pressure and uniqueness. This calls for further research. Practical implications Results are important for companies marketing unique products and they suggest that pressure-based marketing appeals can be used strategically to increase sales of products with long uniqueness duration but decrease sales of products with short uniqueness duration. Although the research provides these guidelines, managers should consider the ethical implications of pressure strategies. Originality/value This is the first attempt to empirically investigate the duration of uniqueness. Although extant research has examined choices between products with different degrees of uniqueness, this research studies choice of products with similar degrees of uniqueness, but different uniqueness duration. Thus, this research adds to the scarce literature studying the duration of symbolic benefits. Moreover, although pressure and NFU frequently co-exist in uniqueness consumption settings, this study is the first to study their joint effects.
45
Baranyi, Péter, Péter Korondi, and Kazuo Tanaka. "Parallel Distributed Compensation Based Stabilization of A 3-DOF RC Helicopter: A Tensor Product Transformation Based Approach." Journal of Advanced Computational Intelligence and Intelligent Informatics 13, no. 1 (January 20, 2009): 25–34. http://dx.doi.org/10.20965/jaciii.2009.p0025.
Full textAbstract:
This paper presents a control solution for the stabilization of the 3-DOF RC helicopter via the combination of the TP (Tensor Product) model transformation and the PDC (Parallel Distributed Compensation) control design framework. First we recall the nonlinear model of the RC helicopter and its simplified version, in order, to facilitate control design. Then we execute the TP model transformation on the simplified model to yield its TP model representation, that is a kind of polytopic model with specific characteristics, whereupon the PDC framework can immediately be applied. The control design considers practical control specifications such as: good speed of response and physical constrain on the control effort to avoid actuator saturations. We guarantee these specifications by LMI (Linear Matrix Inequality) conditions developed under the PDC frameworks. Further, we avoid the discrepancies, introduced via the simplification of the model, by applying LMI conditions specialized for robust control. By simultaneously solving these LMI conditions, we render a stabilizing nonlinear controller that achieves good speed of response with small control effort without actuator saturations. Simulation results are included to validate the control design. It will be pointed out that the resulting controller is equivalent with the controller successfully applied in the real control experiment of the helicopter presented in a recent paper.The main conclusion of this paper is, that the proposed design process is systematic, non-heuristic and straightforward, the stability proof of the resulting controller is tractable via the feasibility test of LMIs and, hence, exact. The whole design procedure is automatically computed via commercialized mathematical tools (MATLAB LMI Toolbox) without analytical interaction. The computational time is about minutes on a regular PC.
46
Haris, M. Syauqi, Tri Astoto Kurniawan, and Fatwa Ramdani. "Automated Features Extraction from Software Requirements Specification (SRS) Documents as The Basis of Software Product Line (SPL) Engineering." Journal of Information Technology and Computer Science 5, no. 3 (December 31, 2020): 279. http://dx.doi.org/10.25126/jitecs.202053219.
Full textAbstract:
Extractive Software Product Line Engineering (SPLE) puts features on the foremost aspect in domain analysis that needs to be extracted from the existing system's artifact. Feature in SPLE, which is closely related to system functionality, has been previously studied to be extracted from source code, models, and various text documents that exist along the software development process. Source code, with its concise and normative standard, has become the most focus target for feature extraction source on many kinds of research. However, in the software engineering principle, the Software Requirements Specification (SRS) document is the basis or main reference for system functionality conformance. Meanwhile, previous researches of feature extraction from text document are conducted on a list of functional requirement sentences that have been previously prepared, not literally SRS as a whole document. So, this research proposes direct processing on the SRS document that uses requirement boilerplates for requirement sentence statement. The proposed method uses Natural Language Processing (NLP) approach on the SRS document. Sequence Part-of-Speech (POS) tagging technique is used for automatic requirement sentence identification and extraction. The features are acquired afterward from extracted requirement sentences automatically using the word dependency parsing technique. Besides, mostly the previous researches about feature extraction were using non-public available SRS document that remains classified or not accessible, so this work uses selected SRS from publicly available SRS dataset to add reproducible research value. This research proves that requirement sentence extraction directly from the SRS document is viable with precision value from 64% to 100% and recall value from 64% to 89%. While features extraction from extracted requirement sentences has success rate from 65% to 88%.
47
Hughes, Callum, Maxim Filimonov, Alison Wray, and Irena Spasić. "Leaving No Stone Unturned: Flexible Retrieval of Idiomatic Expressions from a Large Text Corpus." Machine Learning and Knowledge Extraction 3, no. 1 (March 3, 2021): 263–83. http://dx.doi.org/10.3390/make3010013.
Full textAbstract:
Idioms are multi-word expressions whose meaning cannot always be deduced from the literal meaning of constituent words. A key feature of idioms that is central to this paper is their peculiar mixture of fixedness and variability, which poses challenges for their retrieval from large corpora using traditional search approaches. These challenges hinder insights into idiom usage, affecting users who are conducting linguistic research as well as those involved in language education. To facilitate access to idiom examples taken from real-world contexts, we introduce an information retrieval system designed specifically for idioms. Given a search query that represents an idiom, typically in its canonical form, the system expands it automatically to account for the most common types of idiom variation including inflection, open slots, adjectival or adverbial modification and passivisation. As a by-product of query expansion, other types of idiom variation captured include derivation, compounding, negation, distribution across multiple clauses as well as other unforeseen types of variation. The system was implemented on top of Elasticsearch, an open-source, distributed, scalable, real-time search engine. Flexible retrieval of idioms is supported by a combination of linguistic pre-processing of the search queries, their translation into a set of query clauses written in a query language called Query DSL, and analysis, an indexing process that involves tokenisation and normalisation. Our system outperformed the phrase search in terms of recall and outperformed the keyword search in terms of precision. Out of the three, our approach was found to provide the best balance between precision and recall. By providing a fast and easy way of finding idioms in large corpora, our approach can facilitate further developments in fields such as linguistics, language education and natural language processing.
48
Miller, Chreston, Leah Hamilton, and Jacob Lahne. "Sensory Descriptor Analysis of Whisky Lexicons through the Use of Deep Learning." Foods 10, no. 7 (July 14, 2021): 1633. http://dx.doi.org/10.3390/foods10071633.
Full textAbstract:
This paper is concerned with extracting relevant terms from a text corpus on whisk(e)y. “Relevant” terms are usually contextually defined in their domain of use. Arguably, every domain has a specialized vocabulary used for describing things. For example, the field of Sensory Science, a sub-field of Food Science, investigates human responses to food products and differentiates “descriptive” terms for flavors from “ordinary”, non-descriptive language. Within the field, descriptors are generated through Descriptive Analysis, a method wherein a human panel of experts tastes multiple food products and defines descriptors. This process is both time-consuming and expensive. However, one could leverage existing data to identify and build a flavor language automatically. For example, there are thousands of professional and semi-professional reviews of whisk(e)y published on the internet, providing abundant descriptors interspersed with non-descriptive language. The aim, then, is to be able to automatically identify descriptive terms in unstructured reviews for later use in product flavor characterization. We created two systems to perform this task. The first is an interactive visual tool that can be used to tag examples of descriptive terms from thousands of whisky reviews. This creates a training dataset that we use to perform transfer learning using GloVe word embeddings and a Long Short-Term Memory deep learning model architecture. The result is a model that can accurately identify descriptors within a corpus of whisky review texts with a train/test accuracy of 99% and precision, recall, and F1-scores of 0.99. We tested for overfitting by comparing the training and validation loss for divergence. Our results show that the language structure for descriptive terms can be programmatically learned.
49
Ali, Atif, Yaser Hafeez, Sadia Ali, Shariq Hussain, Shunkun Yang, Arif Jamal Malik, and Aaqif Afzaal Abbasi. "A Data Mining Technique to Improve Configuration Prioritization Framework for Component-Based Systems: An Empirical Study." Information Technology and Control 50, no. 3 (September 24, 2021): 424–42. http://dx.doi.org/10.5755/j01.itc.50.3.27622.
Full textAbstract:
Department of Software Engineering, In the current application development strategies, families of productsare developed with personalized configurations to increase stakeholders’ satisfaction. Product lines have theability to address several requirements due to their reusability and configuration properties. The structuringand prioritizing of configuration requirements facilitate the development processes, whereas it increases theconflicts and inadequacies. This increases human effort, reducing user satisfaction, and failing to accommodatea continuous evolution in configuration requirements. To address these challenges, we propose a framework formanaging the prioritization process considering heterogeneous stakeholders priority semantically. Featuresare analyzed, and mined configuration priority using the data mining method based on frequently accessed andchanged configurations. Firstly, priority is identified based on heterogeneous stakeholder’s perspectives usingthree factors functional, experiential, and expressive values. Secondly, the mined configuration is based on frequentlyaccessed or changed configuration frequency to identify the new priority for reducing failures or errorsamong configuration interaction. We evaluated the performance of the proposed framework with the help ofan experimental study and by comparing it with analytical hierarchical prioritization (AHP) and Clustering.The results indicate a significant increase (more than 90 percent) in the precision and the recall value of theproposed framework, for all selected cases.
50
Chan, Kara, Lennon Tsang, and Jie Chen. "Marketing bank services to youth in China." Young Consumers 18, no. 3 (August 21, 2017): 278–89. http://dx.doi.org/10.1108/yc-03-2017-00672.
Full textAbstract:
Purpose The purpose of this paper is to explore the banking experiences and awareness of marketing efforts of banks among youth in mainland China. Design/methodology/approach Four focus-group interviews were conducted. A convenience sample of 26 participants aged 17 to 20 years was recruited in Laiwu, Shandong, a medium-sized city in China. They were asked to report experiences that could illustrate good and bad banking services. They were also asked to recall bank marketing promotions. Findings Participants’ perceived service quality of banks was determined by staff attitude, service delivery, physical environment and comparison of user experience. The marketing communication activities they recalled most frequently included product placements, advertising slogans, entertaining commercials and co-branding with online games. Research limitations/implications The findings were based on a non-probability sample. The study also did not differentiate between personal experience and indirect experience with family and friends. Similar studies can be conducted in large cities or in rural China to compare banking experiences in different social economic settings. Further studies can be designed using quantitative methodology to measure the importance of various factors in influencing perceptions of service quality. Online banking experience can also be studied in the future. Practical implications Banks in China can enhance their competitiveness and brand reputation through raising the professionalism of their front-line staff, improving efficiency and transparency and streamlining the service process. Banks can make contacts with youth through offline and online promotional activities, such as co-branding with popular online games. Originality/value This is the first study on banking services among youth conducted in a medium-sized city in China.