317 research outputs found
Chroma-Actions Dataset: Acoustic Images: Code
No full textChromagram-based representation of audio extracted from videos. These representations were extracted from the UCF-101 Human Action Recognition dataset. Only videos with audio-channels were considered
Phytopharmacological evaluation of different solvent extract/fractions From<i> Sphaeranthus indicus</i> L. flowers:From traditional therapies to bioactive compounds
No full textSphaeranthus indicus L. is a medicinal herb having widespread traditional uses for treating common ailments. The present research work aims to explore the in-depth phytochemical composition and in vitro reactivity of six different polarity solvents (methanol, n-hexane, benzene, chloroform, ethyl acetate, and n-butanol) extracts/fractions of S. indicus flowers. The phytochemical composition was accomplished by determining total bioactive contents, HPLC-PDA polyphenolic quantification, and UHPLC-MS secondary metabolomics. The reactivity of the phenolic compounds was tested through the following biochemical assays: antioxidant (DPPH, ABTS, FRAP, CUPRAC, phosphomolybdenum, and metal chelation) and enzyme inhibition (AChE, BChE, α-glucosidase, α-amylase, urease, and tyrosinase) assays were performed. The methanol extract showed the highest values for phenolic (94.07 mg GAE/g extract) and flavonoid (78.7 mg QE/g extract) contents and was also the most active for α-glucosidase inhibition as well as radical scavenging and reducing power potential. HPLC-PDA analysis quantified rutin, naringenin, chlorogenic acid, 3-hydroxybenzoic acid, gallic acid, and epicatechin in a significant amount. UHPLC-MS analysis of methanol and ethyl acetate extracts revealed the presence of well-known phytocompounds; most of these were phenolic, flavonoid, and glycoside derivatives. The ethyl acetate fraction exhibited the highest inhibition against tyrosinase and urease, while the n-hexane fraction was most active for α-amylase. Moreover, principal component analysis highlighted the positive correlation between bioactive compounds and the tested extracts. Overall, S. indicus flower extracts were found to contain important phytochemicals, hence could be further explored to discover novel bioactive compounds that could be a valid starting point for future pharmaceutical and nutraceuticals applications.</p
sj-docx-1-wso-10.1177_17474930241237120 – Supplemental material for Stroke and high-risk TIA outcomes with reduction of treatment duration when treatment initiated in emergency rooms (SHORTER-study)
No full textSupplemental material, sj-docx-1-wso-10.1177_17474930241237120 for Stroke and high-risk TIA outcomes with reduction of treatment duration when treatment initiated in emergency rooms (SHORTER-study) by Adel Alhazzani, Fahad S Alajlan, Ali M Alkhathaami, Fahmi Mohammed Al-Senani, Taim A Muayqil, Saeed A Alghamdi, Ammar AlKawi, Saeed AlZahrani, Majid Bakheet, Mohammed Aljohani, Nouran Taher, Abdulkarim Almutairi, Mustafa AlQarni, Sadiq Alsalman, Saeed A Alqahtani, Nouf Almansour, Laila Abukhamsin, Amr Mouminah, Nehal Almodarra, Gamal Mohamed, Meshal Almodhy, Eid Albogumi, Mohamad Alzawahmah, Abdulrahman Alreshaid, Naveed Akhtar, Muhammad Shazam Hussain, Gregory W Albers and Ashfaq Shuaib in International Journal of Stroke</p
Multi-scale pixel-based image fusion using multivariate empirical mode decomposition.
No full textA novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences
Writer Identification Using Microblogging Texts for Social Media Forensics
No full textEstablishing authorship of online texts is fundamental to combat cybercrimes. Unfortunately, text length is limited on some platforms, making the challenge harder. We aim at identifying the authorship of Twitter messages limited to 140 characters. We evaluate popular stylometric features, widely used in literary analysis, and specific Twitter features like URLs, hashtags, replies or quotes. We use two databases with 93 and 3957 authors, respectively. We test varying sized author sets and varying amounts of training/test texts per author. Performance is further improved by feature combination via automatic selection. With a large amount of training Tweets (>500), a good accuracy (Rank-5>80%) is achievable with only a few dozens of test Tweets, even with several thousands of authors. With smaller sample sizes (10-20 training Tweets), the search space can be diminished by 9-15% while keeping a high chance that the correct author is retrieved among the candidates. In such cases, automatic attribution can provide significant time savings to experts in suspect search. For completeness, we report verification results. With few training/test Tweets, the EER is above 20-25%, which is reduced to < 15% if hundreds of training Tweets are available. We also quantify the computational complexity and time permanence of the employed features. © 2019 IEEE.Funding: This work was supported in part by the project 2016-03497 of the Swedish Research Council. Naveed Muhammad has been funded by European Social Fund via IT Academy programme. The authors also thank the CAISR Program of the Swedish Knowledge Foundation.</p
Terrorism affected regions : the impact of different supply chain risk management strategies on financial performance
No full textPurpose: Current geo-political events, such as terrorism and climatologic adversities, have highlighted the potential risks to supply chains (SCs), and their disastrous financial impacts on supply chains. Within supply chains, risk management plays a major role in successfully managing business processes in a proactive manner and ensuring the business continuity and financial performance (FP). The purpose of this study is to explore the supply chain risks and strategies in a terrorism-affected region (TAR), and to examine supply chain risk management (SCRM) strategies and their impacts on FP, including the war on terror (WoT) and its impacts on the local logistics industry. In addition, this study investigates the knowledge gaps in the published research on terrorism-related risk in supply chains, and develops a framework of strategies and effective decision-making to enable practitioners to address terrorism-related risks for SCRM.Methodology: The study initially adopts a novel combination of triangulated methods comprising a systematic literature review, text mining, and network analysis. Additionally, risk identification, risk analysis and strategies scrutiny are conducted by using semi-structured interviews and Qualitative Content Analysis in a TAR. A model of strategies was developed from a review of existing studies and interviews. The model is empirically tested with survey data of 80 firms using fuzzy-set Qualitative Comparative Analysis (fsQCA).Findings: This study reveals a number of key themes in the field of SCRM linked with terrorism. It identifies relevant mitigation strategies and practices for effective strategic decision-making. This subsequently leads to development of a strategic framework, consisting of strategies and effective-decision making practices to address terrorism-related risks that affect SCRM. It also identifies key the knowledge gaps in the literature and explores the main contributions by disciplines (e.g., business schools, engineering, and maritime institutions) and countries.Further, it identifies the SC risks in a TAR, which consist of value streams: disruption risks, operational risks and financial risks. Among these, the emerging risks emcompass terrorist groups’ demand for protection money, smog, paedophilia and the use of containers to block protesters. To mitigate these risks, firms frequently implemented the following strategies: information sharing, SC coordination, risk sharing, SC finance, SC security and facilitation payment. Five strategies out of the six (except facilitation payment) are able to lead to FP, confirmed quantitatively as well. There are various equifinal configurations of SCRM strategies leading to FP. In addition, information sharing acts as a moderator in the relationship between SC security and FP. SC coordination has a mediating role in the relationship between information sharing and SC security capabilities and FP.Research limitations/Contribution: The sample size a limitation of the study, meaning that the findings should be generalized with caution. The most valuable implications is the identification of configurations of strategies that can help managers and policymakers in implementing those findings.Originality/value: No empirical study was found in the SCRM literature that specifically investigates the relationships between the identified strategies and FP with fsQCA, in particular in a TAR context; this study thus fills an important gap in the SCRM literature and contributes empirically
Terrorism affected regions : the impact of different supply chain risk management strategies on financial performance
No full textPurpose: Current geo-political events, such as terrorism and climatologic adversities, have highlighted the potential risks to supply chains (SCs), and their disastrous financial impacts on supply chains. Within supply chains, risk management plays a major role in successfully managing business processes in a proactive manner and ensuring the business continuity and financial performance (FP). The purpose of this study is to explore the supply chain risks and strategies in a terrorism-affected region (TAR), and to examine supply chain risk management (SCRM) strategies and their impacts on FP, including the war on terror (WoT) and its impacts on the local logistics industry. In addition, this study investigates the knowledge gaps in the published research on terrorism-related risk in supply chains, and develops a framework of strategies and effective decision-making to enable practitioners to address terrorism-related risks for SCRM.Methodology: The study initially adopts a novel combination of triangulated methods comprising a systematic literature review, text mining, and network analysis. Additionally, risk identification, risk analysis and strategies scrutiny are conducted by using semi-structured interviews and Qualitative Content Analysis in a TAR. A model of strategies was developed from a review of existing studies and interviews. The model is empirically tested with survey data of 80 firms using fuzzy-set Qualitative Comparative Analysis (fsQCA).Findings: This study reveals a number of key themes in the field of SCRM linked with terrorism. It identifies relevant mitigation strategies and practices for effective strategic decision-making. This subsequently leads to development of a strategic framework, consisting of strategies and effective-decision making practices to address terrorism-related risks that affect SCRM. It also identifies key the knowledge gaps in the literature and explores the main contributions by disciplines (e.g., business schools, engineering, and maritime institutions) and countries.Further, it identifies the SC risks in a TAR, which consist of value streams: disruption risks, operational risks and financial risks. Among these, the emerging risks emcompass terrorist groups’ demand for protection money, smog, paedophilia and the use of containers to block protesters. To mitigate these risks, firms frequently implemented the following strategies: information sharing, SC coordination, risk sharing, SC finance, SC security and facilitation payment. Five strategies out of the six (except facilitation payment) are able to lead to FP, confirmed quantitatively as well. There are various equifinal configurations of SCRM strategies leading to FP. In addition, information sharing acts as a moderator in the relationship between SC security and FP. SC coordination has a mediating role in the relationship between information sharing and SC security capabilities and FP.Research limitations/Contribution: The sample size a limitation of the study, meaning that the findings should be generalized with caution. The most valuable implications is the identification of configurations of strategies that can help managers and policymakers in implementing those findings.Originality/value: No empirical study was found in the SCRM literature that specifically investigates the relationships between the identified strategies and FP with fsQCA, in particular in a TAR context; this study thus fills an important gap in the SCRM literature and contributes empirically
Chroma-Actions Dataset: Acoustic Images
No full text<b>Associated Persons</b><br/>Douglas Chai (Creator)Muhammad Bilal Shaikh (Creator)Chromagram-based representation of audio extracted from videos. These representations were extracted from the UCF-101 Human Action Recognition dataset. Only videos with audio channels were considered. 

Steps to reproduce:
How the data were acquired. Audios of human actions were extracted from UCF101, which was originally collected from YouTube. A script was devised to extract audios of actions from fifty-one different action categories: Archery, Cricket Shot, Hair Cutting, Playing Flute, Rafting, Sky Diving and so on. Data were arranged in two folders train and test to help researchers in evaluating their models
Determination of sun protection factor and physical remanence of dermocosmetic emulgels formulated with Manilkara zapota (L.) fruit extract
No full textPurpose: To develop a stable emulgel formulation from Manilkara zapota fruit extract (MZFE) and evaluate its sun-protective factor (SPF) and its physical retention on facial skin.
Methods: Active test formulations containing MZFE and placebo (containing no active ingredients) were prepared by dispersing the primary emulsion into a gel phase. Both test and placebo emulgel formulations were subjected to physicochemical evaluation, stability studies, and assessment of possible photo-protective properties. The sun-protective factor (SPF) was determined in vitro by spectrophotometric analysis. Non-invasive in vivo skin bioengineering technique was used to assess the UV-quenching effects of the test and placebo emulgel formulations.
Results: A stable and cosmetically acceptable emulgel formulation loaded with MZFE was obtained. The formulation and control exhibited optimum physicochemical stability in stress stability tests. The formulation exhibited promising photo-protective effects both in vitro (SPF = 14.215 ± 0.140) and in vivo (lasted for approximately 120 min).
Conclusion: The developed MZFE-loaded test emulgel formulation possesses suitable photoprotection capability in vitro, and displays quenching effects against specific wavelengths of UV light, indicating a UV-filtering propert
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