1,382 research outputs found
Dr. Khalid Lodhi - Bed Bugs Undercover Agents in Forensic Investigations - September 10 2025
No full textDr. Khalid Lodhi speaks at the Chesnutt Library of Fayetteville State University about his recent research into using bedbugs as a tool in forensic research and criminal justice.
Presented live on September 10, 2025 as part of Chesnutt Library\u27s Faculty Author Series.https://digitalcommons.uncfsu.edu/faculty_author/1016/thumbnail.jp
Genetic assessment of apolipoprotein E polymorphism and PRNP genotypes in rapidly progressive dementias in Pakistan
No full textRapidly progressive dementias (RPDs) are a type of fatal dementias that cause rapid progression of neuronal dysfunction. This study aimed to assess the prevalence of APOE genotypes (ε2, ε3, ε4) and PRNP mutations (E200K, M129V) in the general population of Pakistan because of their association with RPDs, including Rapidly Progressive Alzheimer’s Disease (rpAD) and Creutzfeldt-Jakob Disease (CJD). Blood samples (n = 100) were collected from healthy Pakistani population and the stated mutations were assessed using polymerase chain reaction. In the analysis of the APOE genotype, ε3/ε3 genotype was the most common (95%), followed by ε3/ε4 (5%) and ε2 allele was completely absent. A low frequency of ε4 allele and the absence of a protective ε2 allele is associated with an increased risk of rpAD. In the case of PRNP mutations, the most common genotype was M129-Ε200 (71%) and V129-Ε200 (29%). E200K mutation was completely absent from the given population. It is noteworthy that the MM homozygous genotype was present in 71 samples, VV genotype was present in 29. Homozygosity on codon 129, as observed in most of our samples, has been associated with more efficient production of PrPSc and disease pathology. This study provides preliminary data indicating that rpAD and CJD pose a significant threat to the Pakistani population
Looking Through Paintings by Combining Hyper-Spectral Imaging and Pulse-Compression Thermography
Get PDFThe use of different spectral bands in the inspection of artworks is highly recommended to identify the maximum number of defects/anomalies (i.e., the targets), whose presence ought to be known before any possible restoration action. Although an artwork cannot be considered as a composite material in which the zero-defect theory is usually followed by scientists, it is possible to state that the preservation of a multi-layered structure fabricated by the artist’s hands is based on a methodological analysis, where the use of non-destructive testing methods is highly desirable. In this paper, the infrared thermography and hyperspectral imaging methods were applied to identify both fabricated and non-fabricated targets in a canvas painting mocking up the famous character “Venus” by Botticelli. The pulse-compression thermography technique was used to retrieve info about the inner structure of the sample and low power light-emitting diode (LED) chips, whose emission was modulated via a pseudo-noise sequence, were exploited as the heat source for minimizing the heat radiated on the sample surface. Hyper-spectral imaging was employed to detect surface and subsurface features such as pentimenti and facial contours. The results demonstrate how the application of statistical algorithms (i.e., principal component and independent component analyses) maximized the number of targets retrieved during the post-acquisition steps for both the employed techniques. Finally, the best results obtained by both techniques and post-processing methods were fused together, resulting in a clear targets map, in which both the surface, subsurface and deeper information are all shown at a glance
Traffic aware cyclic sleep‐based power consumption model for a passive optical network
No full textMuhammad, Anwar/0000-0002-0615-3038; Phd, Muhammad Faheem,/0000-0003-4628-4486; Butt, Rizwan Aslam/0000-0002-4784-0918; Mohammadani, Khalid/0000-0002-7640-9772;For a network, a power consumption model is an important tool to test the performance of a network process for different traffic loads. In a Passive optical network (PON), the optical network unit (ONU) is responsible for the major power consumption of PON. Both IEEE and ITU have standardized a cyclic sleep process (CSP) for ONU energy conservation. In next-generation PON; TWDM and XGS PON, the ONU power contribution has increased further due to higher number of ONUs and ONU being tunable. Therefore, an accurate power consumption model of the CSP process for energy efficiency studies under different traffic conditions is of prime importance. The existing CSP power consumption models do not depict the CSP process accurately especially the inactivity of the ONU in the asleep and sleep aware states are not taken into account which reduce the accuracy of the model. The proposed inactivity aware model (IAM) overcomes these gaps and very accurately models the CSP process, as evident from the results, which are better than earlier model results and quite close to earlier published simulation results. The model is also validated through a simulation-based study and the simulation results are observed to be very close to the model results with only a 5% deviation.UTM [08G49]The authors acknowledge the financial support provided by the UTM Institutional Grant through Vote no 08G49 for conducting this research
Tahapan Retorika Dalam Ceramah Ustaz Khalid Basalamah Di Youtube
Get PDFRhetoric Stages in Ustaz Khalid Basalamah's Lecture on Youtube. This research is entitled Rhetoric Stages in Ustaz Khalid Basalamah's Lecture on Youtube. The reason the author chose this title is because this research has never been done at the Islamic University of Riau and the object being carried out has also never been studied by students of the Islamic University of Riau. And Ustadz Khalid Basalamah was able to attract the attention of listeners, so the writer wanted to know the stages used by Ustadz Khalid Basalamah. This research is included in qualitative research using descriptive method. The data collection technique of this research is through documentation. This study uses the theory proposed by Rakhmat (2014), Abidin (2013), Keraf (2015), Morrisan (2014). The results of research on the stages of rhetoric in Ustaz Khalid Basalamah's lecture on Youtube found 40 data. (1) In the invention stage, there are 7 data including 5 evidence indicators and 2 statement indicators. (2) The disposition stage contains 15 data, including 7 preliminary data, 4 content data, and 4 closing data. (3) The Elocutio stage contains 7 data, including 3 asindenton data, 1 paradox data, and 3 hyperbole data. (4) The memory stage contains 6 data, including 3 information storage data and 3 experience data. (5) The Pronontitio stage contains 5 data, the data is included in the rhythm. It can be concluded that Ustaz Khalid Basalamah in the invention stage is more dominant in using evidence. In the disposition stage, the prelude is more dominant using greetings, content is more dominant using arguments, and closing is more dominant using expectations. In the elocutio stage, it is more dominant to use asidentone and hyperbole. In the memory stage, it is more dominant to use the storage of information and experiences. In the pronontitio stage, it is more dominant to use rhythm. Thus, Ustaz Khalid Basalamah has used the five stages of rhetoric
Multimedia – the rise of the south: human progress in a diverse world
No full textKhalid Malik, lead author of the 2013 UNDP Human Development Report, recently shared the report’s findings at LSE. In his talk, he emphasised the importance of focusing on human development for economic growth in the Global South
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School Leadership for Refugees’ Education: Social Justice Leadership for Immigrant, Migrants and Refugees by Khalid Arar
No full textBook Review
Title: School Leadership for Refugees’ Education: Social Justice Leadership for Immigrant, Migrants and Refugees
Author: Khalid Arar
Year: 2020
Publisher:
Pages: 202
ISBN: 9780429021770
Price: $52.95 (paper)
A comparison of scaling subtraction and pulse compression methods for the analysis of elastic nonlinearity
No full textAn Insight into the Machine-Learning-Based Fileless Malware Detection
Get PDFIn recent years, massive development in the malware industry changed the entire landscape for malware development. Therefore, cybercriminals became more sophisticated by advancing their development techniques from file-based to fileless malware. As file-based malware depends on files to spread itself, on the other hand, fileless malware does not require a traditional file system and uses benign processes to carry out its malicious intent. Therefore, it evades conventional detection techniques and remains stealthy. This paper briefly explains fileless malware, its life cycle, and its infection chain. Moreover, it proposes a detection technique based on feature analysis using machine learning for fileless malware detection. The virtual machine acquired the memory dumps upon executing the malicious and non-malicious samples. Then the necessary features are extracted using the Volatility memory forensics tool, which is then analyzed using machine learning classification algorithms. After that, the best algorithm is selected based on the k-fold cross-validation score. Experimental evaluation has shown that Random Forest outperforms other machine learning classifiers (Decision Tree, Support Vector Machine, Logistic Regression, K-Nearest Neighbor, XGBoost, and Gradient Boosting). It achieved an overall accuracy of 93.33% with a True Positive Rate (TPR) of 87.5% at zeroFalse Positive Rate (FPR) for fileless malware collected from five widely used datasets (VirusShare, AnyRun, PolySwarm, HatchingTriage, and JoESadbox)
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