31 research outputs found
The Role of Author Identities in Peer Review
No full textThere is widespread debate on whether to anonymize author identities in peer
review. The key argument for anonymization is to mitigate bias, whereas
arguments against anonymization posit various uses of author identities in the
review process. The Innovations in Theoretical Computer Science (ITCS) 2023
conference adopted a middle ground by initially anonymizing the author
identities from reviewers, revealing them after the reviewer had submitted
their initial reviews, and allowing the reviewer to change their review
subsequently. We present an analysis of the reviews pertaining to the
identification and use of author identities. Our key findings are: (I) A
majority of reviewers self-report not knowing and being unable to guess the
authors' identities for the papers they were reviewing. (II) After the initial
submission of reviews, 7.1% of reviews changed their overall merit score and
3.8% changed their self-reported reviewer expertise. (III) There is a very weak
and statistically insignificant correlation of the rank of authors'
affiliations with the change in overall merit; there is a weak but
statistically significant correlation with respect to change in reviewer
expertise. We also conducted an anonymous survey to obtain opinions from
reviewers and authors. The main findings from the 200 survey responses are: (i)
A vast majority of participants favor anonymizing author identities in some
form. (ii) The "middle-ground" initiative of ITCS 2023 was appreciated. (iii)
Detecting conflicts of interest is a challenge that needs to be addressed if
author identities are anonymized. Overall, these findings support anonymization
of author identities in some form (e.g., as was done in ITCS 2023), as long as
there is a robust and efficient way to check conflicts of interest
The role of author identities in peer review
No full textThere is widespread debate on whether to anonymize author identities in peer review. The key argument for anonymization is to mitigate bias, whereas arguments against anonymization posit various uses of author identities in the review process. The Innovations in Theoretical Computer Science (ITCS) 2023 conference adopted a middle ground by initially anonymizing the author identities from reviewers, revealing them after the reviewer had submitted their initial reviews, and allowing the reviewer to change their review subsequently. We present an analysis of the reviews pertaining to the identification and use of author identities. Our key findings are: (I) A majority of reviewers self-report not knowing and being unable to guess the authors’ identities for the papers they were reviewing. (II) After the initial submission of reviews, 7.1% of reviews changed their overall merit score and 3.8% changed their self-reported reviewer expertise. (III) There is a very weak and statistically insignificant correlation of the rank of authors’ affiliations with the change in overall merit; there is a weak but statistically significant correlation with respect to change in reviewer expertise. We also conducted an anonymous survey to obtain opinions from reviewers and authors. The main findings from the 200 survey responses are: (i) A vast majority of participants favor anonymizing author identities in some form. (ii) The “middle-ground” initiative of ITCS 2023 was appreciated. (iii) Detecting conflicts of interest is a challenge that needs to be addressed if author identities are anonymized. Overall, these findings support anonymization of author identities in some form (e.g., as was done in ITCS 2023), as long as there is a robust and efficient way to check conflicts of interest
Hybrid simulation based optimization for supply chain management
No full textSupply chain management (SCM) has been recognized as one of the key issues in the process industry. The growing size of the distributed supply chain structures, market dynamics and variability involved in the internal operations pose a challenge to efficiently managing the whole network. Globalization of supply chains and advances in information technology have led to a greater need for integrated operations as they have caused a more distributed network with potentially larger number of customers. It is essential that the various bodies constituting the supply chain operate in an integrated manner and their activities are synchronized towards a common goal. Thus, there is a need for efficient integration of information and decision making among the various functions of the supply chains. The growing need for integrated information and decision-making necessitates the development of a framework which allows the different entities of a supply chain to have access to a common information system as well as provides them with advanced decision-making tools. With the advancements in information technology, it is possible for supply chain members to share information and several such tools are also commercially available. However there is a need to combine intelligent decision making with information sharing to develop the required framework. The main objective of this dissertation is the development of novel methodologies that will facilitate intelligent decision-making and their application in the analysis of supply chains for chemical industries. Simulation models are used to depict supply chain dynamics so that they represent the decision-making by various entities. In order to obtain improved decision-making, a hybrid simulation based optimization framework is proposed. The framework considers the decision rules followed by the different entities and guides the simulation model towards improved solutions. The benefits of these methodologies include a more realistic representation of supply chain dynamics and reduced computational times for large-scale problems. The framework is applied to a number of case studies. Uncertainty in supply chain is also considered and the framework is used to determine the flexibility of the supply chain and manage risk under uncertainty. A derivative free optimization method is also proposed which has been applied to optimize the performance of a multi-enterprise supply chain network.Ph.D.Includes bibliographical referencesby Nihar Saha
Distribution of reviewers’ self reports about their knowledge of author identities.
No full textDistribution of reviewers’ self reports about their knowledge of author identities.</p
Responses to the survey.
No full textThere is widespread debate on whether to anonymize author identities in peer review. The key argument for anonymization is to mitigate bias, whereas arguments against anonymization posit various uses of author identities in the review process. The Innovations in Theoretical Computer Science (ITCS) 2023 conference adopted a middle ground by initially anonymizing the author identities from reviewers, revealing them after the reviewer had submitted their initial reviews, and allowing the reviewer to change their review subsequently. We present an analysis of the reviews pertaining to the identification and use of author identities. Our key findings are: (I) A majority of reviewers self-report not knowing and being unable to guess the authors’ identities for the papers they were reviewing. (II) After the initial submission of reviews, 7.1% of reviews changed their overall merit score and 3.8% changed their self-reported reviewer expertise. (III) There is a very weak and statistically insignificant correlation of the rank of authors’ affiliations with the change in overall merit; there is a weak but statistically significant correlation with respect to change in reviewer expertise. We also conducted an anonymous survey to obtain opinions from reviewers and authors. The main findings from the 200 survey responses are: (i) A vast majority of participants favor anonymizing author identities in some form. (ii) The “middle-ground” initiative of ITCS 2023 was appreciated. (iii) Detecting conflicts of interest is a challenge that needs to be addressed if author identities are anonymized. Overall, these findings support anonymization of author identities in some form (e.g., as was done in ITCS 2023), as long as there is a robust and efficient way to check conflicts of interest.</div
Evaluating fine-tuned transformer models for sarcasm detection in video game reviews
No full textEVALUATING FINE-TUNED TRANSFORMER MODELS FOR SARCASM DETECTION IN VIDEO GAME REVIEWS
Evaluating fine-tuned transformer models for sarcasm detection in video game reviews (1)
Abstract (8)
Keywords (8)
1 Introduction (9)
1.1 Background (9)
1.2 Problem Statement (10)
1.3 Aim of the Study and Research Questions (10)
1.4 Method (11)
1.5 Structure of the Study (11)
2 Literature Review (13)
2.1 Video Game Industry (13)
2.2 Review Usefulness (13)
2.2.1 Influence and Impact of Online Reviews (13)
2.2.2 Online Reviews in the Video Game Industry (14)
2.3 Sarcasm in Online Reviews (16)
2.4 Sarcasm Detection (18)
2.4.1 Automated Sarcasm Detection (18)
2.4.2 Sarcasm Detection using Transformers (20)
2.4.3 Current State of Research for Video Game Reviews (21)
3 Methodology (24)
3.1 Research Objective (24)
3.2 Research Design (24)
3.2.1 Transformers (24)
3.2.2 RoBERTa vs BERT (25)
3.3 Data Collection (25)
3.3.1 Game Selection (25)
3.3.2 Data Scraping (26)
3.4 Model Building Process (28)
3.4.1 Data Cleaning (28)
3.4.2 Data Sampling (28)
3.4.3 Manual Annotation (28)
3.4.4 Data Preprocessing (30)
3.4.5 Model Building (30)
3.4.5.1 Model Training and Testing (31)
3.4.5.2 Hyperparameter Fine-Tuning (31)
3.4.5.3 Generalisability Testing (32)
3.4.5.4 Helpfulness Classification (32)
3.4.5.5 Adding Features to the Model (32)
3.4.5.6 Combined Dataset Modelling (33)
3.5 Methodological Limitations (33)
3.6 Summary (33)
4 Results (34)
4.1 Data Descriptives (34)
4.2 Baseline Model Performance (36)
4.3 Hyperparameter Fine-Tuning (37)
4.4 Evaluation of Best-Performing Model (38)
4.5 Generalisability Test (39)
4.6 Feature-Enhanced Model (41)
4.7 Helpfulness Classification (43)
4.8 Combined Dataset Modelling (44)
5 Discussion (47)
6 Limitations (50)
7 Conclusion (52)
8 References (53)
Appendix A – Model Performance Scores (59)
Appendix B – Code (64
Pseudo forces from asymmetric vibrations can provide movement guidance
No full textWhen a trainee is (re)learning a skilled movement, physical guidance from a trainer is crucial. Yet, providing physical cues to guide movements is highly challenging when training is digitally mediated (e.g.remotely). This work demonstrates the utility of pseudo forces generated by a wearable tactile interface for providing non-intrusive movement guidance. First, we developed hardware to generate pseudo forces using asymmetric vibrations, whose frequency and amplitude can be tuned to vary the acceleration of the pseudo forces. Maximum acceleration of 160 m/sec^2 is obtained at a frequency of 40Hz and amplitude of 1. Second, the utility of the generated pseudo forces to provide movement guidance was explored by involving 19 participants in 4 separate experiments: 1) Symmetric and asymmetric vibration comparison, 2) Duration modulation, 3) Amplitude modulation, 4) Frequency Modulation of asymmetric vibration. For every experiment, the elements of movement guidance: direction and joint angular velocity were investigated. Participants perceive directional cues with 96% accuracy (P<0.001), and translate the perceived pseudo forces into directed arm movements, with a uniform joint angular velocity of 14+/-8 degrees/second for the duration of the provided pseudo force. The joint angular velocity of the arm movement changes until 12 degrees/second with frequency. With these findings, we anticipate pseudo forces to be the foundation for remote guidance of human body movements in fields like rehabilitation and sports.Mechanical Engineering | Biomechanical Design - BioRobotic
Basic statistics of the reviews in ITCS 2023.
No full textThere is widespread debate on whether to anonymize author identities in peer review. The key argument for anonymization is to mitigate bias, whereas arguments against anonymization posit various uses of author identities in the review process. The Innovations in Theoretical Computer Science (ITCS) 2023 conference adopted a middle ground by initially anonymizing the author identities from reviewers, revealing them after the reviewer had submitted their initial reviews, and allowing the reviewer to change their review subsequently. We present an analysis of the reviews pertaining to the identification and use of author identities. Our key findings are: (I) A majority of reviewers self-report not knowing and being unable to guess the authors’ identities for the papers they were reviewing. (II) After the initial submission of reviews, 7.1% of reviews changed their overall merit score and 3.8% changed their self-reported reviewer expertise. (III) There is a very weak and statistically insignificant correlation of the rank of authors’ affiliations with the change in overall merit; there is a weak but statistically significant correlation with respect to change in reviewer expertise. We also conducted an anonymous survey to obtain opinions from reviewers and authors. The main findings from the 200 survey responses are: (i) A vast majority of participants favor anonymizing author identities in some form. (ii) The “middle-ground” initiative of ITCS 2023 was appreciated. (iii) Detecting conflicts of interest is a challenge that needs to be addressed if author identities are anonymized. Overall, these findings support anonymization of author identities in some form (e.g., as was done in ITCS 2023), as long as there is a robust and efficient way to check conflicts of interest.</div
Hijab Imtiaz Ali’s Letters: An Example of Non-Fictional Prose: حجاب امتیاز علی کے مکتوبات، غیر افسانوی نثر کی ایک مثال
No full textHijab Imtiaz Ali is a well-known figure in Urdu literature's fiction genre. Her most well-known works are novels and short stories, but her non-fiction writing, which includes essays, travelogues, letters, diaries, and beautiful prose, is equally captivating. Only a segment of this collection was published in 2006 under the title "Hijab Kitaab" from Lahore city; her letters have not yet been collected into a book. Her character and the period are accurately reflected in these letters. Letters typically reflect a person's private life and experiences. These letters give us a glimpse into the writers' social relationships as well as her society and the times she lived in. These letters have a straightforward and aesthetically pleasing style. The spotlight she gives to her novels and short stories is absent from her letters.
References
Hijab Imtiaz Ali, Lail-o-Nihar, Lahore: Sang-e-Meel Publications, 2015, p: 36
Shadani, Andaleeb, Dr., Foreword to Makatib-e-Jameel, Lahore: Maktaba Jadeed, 1956, p: 14
Hashmi, Naseeruddin, included in Makatib-e-Jameel, Lahore: Maktaba Jadeed, 1956, pp: 20–21
Hijab Imtiaz Ali, Tasveer-e-Butan, Lahore: Sang-e-Meel Publications, 2011, p:159
Tahir, Naeem, Meeting with the Author, Lahore: Model Town, December 25, 2021
Hijab Imtiaz Ali, Lail-o-Nihar, p: 37
Ibid., p: 49
Hijab Imtiaz Ali, Hijab Kitab, Lahore: Sang-e-Meel Publications, 2006, p: 346
Ibid., p; 347
Ibid., p: 350
Ibid., p: 355
Ibid., p: 349
Ibid., p: 365
Ibid., p: 343
Ibid., p: 346
Ibid., p: 352
Ibid., p: 35
Image-Based Fracture Surface Defect Characterization Methods for Additively Manufactured Ti-6Al-4V Tested in Fatigue
No full textFatigue initiation in additively manufactured samples/parts often occurs at processed-induced defects such as lack-of-fusion (LoF), keyhole, or other morphological/microstructural defects that have unique characteristics and measurable qualities. Attempts at identifying and minimizing such defects have utilized optimized processing conditions along with in situ and ex situ characterization that includes metallography and/or X-ray computed tomography (XCT). This paper highlights the benefits of using fracture surface analyses to detect and quantify defects that may not be detected by metallography/XCT due to sectioning and resolution limits. In addition to using manual quantification of fatigue initiating LoF and keyhole defects on fracture surfaces, image-based machine learning using convolutional neural networks such as U-Net were also used to automate the process. Statistical analyses were used to identify the extreme cases of defects that initiated and accelerated fatigue and to model the distribution of defect size and shape characteristics to distinguish the type of defect. Initial results show agreement between trained machine learning models and ground truth data in defect segmentation, and the distributions of defect characteristics are distinguishable to particular process-induced defect types. This article was updated to correct Arafath Nifar to Arafath Nihar in the author list
