{"title":"IAB-Net: Informative and Attention Based Person Re-Identification","authors":"Rao Faizan, M. Fraz, M. Shahzad","doi":"10.1109/ICoDT252288.2021.9441480","DOIUrl":"https://doi.org/10.1109/ICoDT252288.2021.9441480","url":null,"abstract":"This paper proposes Informative Attention Based IAB Network, a advance framework that unifieds multiple attention modules by preserving localized and global contextual information so that the model can learn most informative, representative and discriminative features. Specifically, we have also introduced Channel and Spatial Attention (CASA) Network that consists on a pair of attention modules named as Channel Attention Module and Spatial Attention Module. Channel attention module and spatial attention module primarily focusing on channel aggregation, spatial dimension and position awareness, respectively. In our proposed pipeline, we have used this pair after each convolutional block of ResNet-50, that significantly boost the performance and representation power of network. By using this new lightweight backbone with orthogonality constraint to enforce diversity on both hidden activation and weights and along with attention modules, our experiments on different popular benchmarks i.e Market-1501 and DukeMTMC-reID have achieved state-of-the-art performance and we confirm that our framework manifests harmonious refinement in detection and classification. The code is publicly available at this link https://github.com/faize5/IAB-Net.","PeriodicalId":207832,"journal":{"name":"2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2)","volume":"262 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114600789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Muhammad Usman Aftab, M. Hussain, Anders Lindgren, Abdul Ghafoor
{"title":"Towards A Distributed Ledger Based Verifiable Trusted Protocol For VANET","authors":"Muhammad Usman Aftab, M. Hussain, Anders Lindgren, Abdul Ghafoor","doi":"10.1109/ICoDT252288.2021.9441531","DOIUrl":"https://doi.org/10.1109/ICoDT252288.2021.9441531","url":null,"abstract":"To ensure traffic safety and proper operation of vehicular networks, safety messages or beacons are periodically broadcasted in Vehicular Adhoc Networks (VANETs) to neighboring nodes and road side units (RSU). Thus, authenticity and integrity of received messages along with the trust in source nodes is crucial and highly required in applications where a failure can result in life-threatening situations. Several digital signature based approaches have been described in literature to achieve the authenticity of these messages. In these schemes, scenarios having high level of vehicle density are handled by RSU where aggregated signature verification is done. However, most of these schemes are centralized and PKI based where our goal is to develop a decentralized dynamic system. Along with authenticity and integrity, trust management plays an important role in VANETs which enables ways for secure and verified communication. A number of trust management models have been proposed but it is still an ongoing matter of interest, similarly authentication which is a vital security service to have during communication is not mostly present in the literature work related to trust management systems. This paper proposes a secure and publicly verifiable communication scheme for VANET which achieves source authentication, message authentication, non repudiation, integrity and public verifiability. All of these are achieved through digital signatures, Hash Message Authentication Code (HMAC) technique and logging mechanism which is aided by blockchain technology.","PeriodicalId":207832,"journal":{"name":"2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114169234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hira Asim, Ayesha Asmat, Kiran Ilyas, Malik Tahir Hassan
{"title":"COVID-19: Future Preference of University Students to Promote Online Education in Pakistan","authors":"Hira Asim, Ayesha Asmat, Kiran Ilyas, Malik Tahir Hassan","doi":"10.1109/ICoDT252288.2021.9441486","DOIUrl":"https://doi.org/10.1109/ICoDT252288.2021.9441486","url":null,"abstract":"COVID-19 is a deadly virus that has been transmitted globally in no time. Due to the continuous spread of COVID-19, the Higher Education Commission (HEC) of Pakistan has decided to shift towards online classes. In this study, a survey has been conducted to assess the online learning experience of the students. This paper aims to find the preferences of students regarding e-learning in the upcoming semester(s) for the promotion of digital learning in Pakistan. A well-structured questionnaire is circulated and a total of 519 responses are collected from the prestigious universities of Pakistan after the conclusion of the online semester. It has been observed that only 26% of the students are willing to take online classes in the future. To dig down the reasons behind this low percentage, comparative as well as sentiment analyses of the results have been conducted. The comparative analysis has indicated that the students are not satisfied with their learning outcomes, online examination, and grading in this regard. Similarly, the sentiment analysis of the comments has revealed that 60% of the students have provided negative feedback regarding online classes. Whereas, it has also been observed that many students are in the favor of attending short courses, seminars, and conferences online. Based on the analyses, suitable recommendations have also been provided to promote e-learning in Pakistan.","PeriodicalId":207832,"journal":{"name":"2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114077210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Affinity Based Scheduling Using Bayesian Model and Load Balancing in Multicore Systems","authors":"S. Abbasi, S. Kamal","doi":"10.1109/ICoDT252288.2021.9441513","DOIUrl":"https://doi.org/10.1109/ICoDT252288.2021.9441513","url":null,"abstract":"Problems in the shared caches in multicore systems arise due to the non-affinity scheduling. Tasks are scheduled without considering the possible dependencies they have on each other. It has a negative effect on the overall execution time of the tasks. In this paper, we have proposed affinity based scheduling using Bayesian analysis model and creating groups or clusters of dependent tasks. Clusters are then allocated fairly and equally among the multiple cores. Load balancing is performed on the homogeneous system by feeding all the cores in a multicore architecture from a queue-like pool of tasks. We have used another technique for load balancing by defining a chunk size for each core. Results showed an improvement in an overall execution time of a process by 5.57% and of an individual task by 9.06% on average in comparison with other traditional schedulers used by the operating system for a factorial program. For a quick sort program, overall execution time of a process has been reduced by 1.13% while for an individual task by 1.5%.","PeriodicalId":207832,"journal":{"name":"2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127714400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fine Tuning BERT for Unethical Behavior Classification","authors":"Syeda Faizan Fatima, Seemab Latif, R. Latif","doi":"10.1109/ICoDT252288.2021.9441540","DOIUrl":"https://doi.org/10.1109/ICoDT252288.2021.9441540","url":null,"abstract":"Social media allows people to express themselves, however, there exists a threat of abuse and harassment. This threat leads to a negative impact on society which results in a change in people behaviour and they stop expressing their ideas freely. Classification of unethical behaviour in comments is a multi-label classification task. Due to the limited availability of the dataset, training does not yield worthy accuracies. Hence, a large training corpus is needed. This work, therefore, proposes to supplement training data by making use of transfer learning. Bi-directional Encoder Representations from Transformers (BERT) pre-trained model is fine-tuned to detect unethical users’ behaviour. The approach used in this work achieved competitive accuracy for the task of multi-label classification on the toxicity dataset of Wikipedia Comments Corpus.","PeriodicalId":207832,"journal":{"name":"2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130469681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multiple Solutions Based Particle Swarm Optimization for Cluster-Head-Selection in Wireless-Sensor-Network","authors":"Sakin Jan, M. Masood","doi":"10.1109/ICoDT252288.2021.9441530","DOIUrl":"https://doi.org/10.1109/ICoDT252288.2021.9441530","url":null,"abstract":"Wireless sensor network (WSN) has a significant role in wide range of scientific and industrial applications. In WSN, within the operation area of sensor nodes the nodes are randomly deployed. The constraint related to energy is considered as one of the major challenges for WSN, which may not only affect the sensor nodes efficiency but also influences the operational capabilities of the network. Therefore, numerous attempts of researches have been proposed to counter this energy problem in WSN. Hierarchical clustering approaches are popular techniques that offered the efficient consumption of the energy in WSN. In addition to this, it is understood that the optimum choice of sensor as cluster head can critically help to reduce the energy consumption of the sensor node. In recent years, metaheuristic optimization is used as a proposed technique for the optimal selection of cluster heads. Furthermore, it is noteworthy here that proposed techniques should be efficient enough to provide the optimal solution for the given problem. Therefore, in this regard, various attempts are made in the form of modified versions or new metaheuristic algorithms for optimization problems. The research in the paper offered a modified version of particle-swarm-optimization (PSO) for the optimal selection of sensor nodes as cluster heads. The performance of the suggested algorithm is experimented and compared with the renowned optimization techniques. The proposed approach produced better results in the form of residual energy, number of live nodes, sum of dead nodes, and convergence rate.","PeriodicalId":207832,"journal":{"name":"2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128446741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Muntaha Iqbal, Kamran Amjad, Bilal Tahir, M. Mehmood
{"title":"CURE: Collection for Urdu Information Retrieval Evaluation and Ranking","authors":"Muntaha Iqbal, Kamran Amjad, Bilal Tahir, M. Mehmood","doi":"10.1109/ICoDT252288.2021.9441510","DOIUrl":"https://doi.org/10.1109/ICoDT252288.2021.9441510","url":null,"abstract":"Urdu is a widely spoken language with 163 million speakers across the globe. Information Retrieval (IR) for Urdu entails special consideration of research community due to its rich morphological features and a large number of speakers. In general, IR evaluation task is not extensively explored for Urdu. The most important missing element is the availability of a standardized evaluation corpus specific to Urdu. In this research work, we propose and construct a standard test collection of Urdu documents for IR evaluation and named it Collection for Urdu Retrieval Evaluation (CURE). We select 1,096 unique documents against 50 diverse queries from a large collection of 0.5 million crawled documents using two IR models. The purpose of test collection is the evaluation of IR models, ranking algorithms, and different natural language processing techniques. Next, we perform binary relevance judgment on the selected documents. We also build two other language resources for lemmatization and query expansion specific to our test collection. Evaluation of test collection is carried out using four retrieval models as well using the stop-words list, lemmatization, and query expansion. Furthermore, error analysis is performed for each query with different NLP techniques. To the best of our knowledge, this work is the first attempt for preparing a standardized information retrieval evaluation test collection for the Urdu language.","PeriodicalId":207832,"journal":{"name":"2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129553362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"[Copyright notice]","authors":"","doi":"10.1109/icodt252288.2021.9441521","DOIUrl":"https://doi.org/10.1109/icodt252288.2021.9441521","url":null,"abstract":"","PeriodicalId":207832,"journal":{"name":"2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121333313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}