The need for participants’ performance assessments in academia and industry has been a growing concern. It has attendance, among other metrics, is a key factor in engendering a holistic approach to decision-making. For institutions or organizations where managing people is an important yet challenging task, attendance tracking and management could be employed to improve this seemingly time-consuming process while keeping an accurate attendance record. The manual/quasi-analog approach of taking attendance in some institutions could be unreliable and inefficient, leading to inaccurate computation of attendance rates and data loss. This work, therefore, proposes a system that employs embedded technology and a biometric/ web-based application to enhance attendance management. The hardware encompasses the integration of an ESP8266 NodeMCU and the biometric AS608 fingerprint sensor interfaced with the database for which the front-end and back-end integration was through the React framework. The system uses a web application that displays the attendance results and scheduled course data from its database, provides feedback to lecturers on which student missed classes and calculates a student’s average attendance for the semester. By implementing this system, the accuracy of student attendance is expected to experience an appreciable improvement, eliminate proxy signing, provide a more secure alternative for attendance recording, curtail tardiness to classes, and ultimately improve student productivity on execution.
<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver & kroeber, overlap, and pearson correlation
... Show MoreThe accurate identification of internal and external pressures in thick-walled hyperelastic vessels is a challenging inverse problem with significant implications for structural health monitoring, biomedical devices, and soft robotics. Conventional analytical and numerical approaches address the forward problem effectively but offer limited means for recovering unknown load conditions from observable deformations. In this study, we introduce a Graph-FEM/ML framework that couples high-fidelity finite element simulations with machine learning models to infer normalized internal and external pressures from measurable boundary deformations. A dataset of 1386 valid samples was generated through Latin Hypercube Sampling of geometric and l
... Show MoreThis study attempts to test the possibility of developing organizational performance in Zain Telecom by adapting the philosophy and concept of Organizational Identification and its dimensions, the most important of which are (Organizational Identification, organizational loyalty, organizational affiliation).To achieve the goal, the research relied on the questionnaire method, which is one of the methods of collecting information in field studies.
Reishi Mushroom, Ganoderma, is considered one of important wood-decaying medicinal mushrooms. This study aimed to identify three samples of this genus in Mosul city in February and April 2019. Three species of Ganoderma were collected from three various trees including Eucalyptus, Morus, and Olea (olive) in Mosul City, Northern Iraq. Their identifications and their DNA sequences were genetically identified by using PCR techniques according to detect nuclear ribosomal internal transcribed spacer (ITS) regions. Results exhibited the finding of Ganoderma resinaceum, Ganoderma applanatum, and Ganoderma sp. This study is first attempt to identify Reishi Mushroom by molecular methods in Iraq. Thus, the current study is considered new good d
... Show MoreThe direct electron transfer behavior of hemoglobin that is immobilized onto screen-printed carbon electrode (SPCE) modified with silver nanoparticles (AgNPs) and chitosan (CS) was studied in this work. Cyclic voltametry and spectrophotometry were used to characterize the hemoglobin (Hb) bioconjunction with AgNPs and CS. Results of the modified electrode showed quasi-reversible redox peaks with a formal potential of (-0.245 V) versus Ag/AgCl in 0.1 M phosphate buffer solution (PBS), pH7, at a scan rate of 0.1 Vs-1. The charge transfer coefficient (α) was 0.48 and the apparent electron transfer rate constant (Ks) was 0.47 s-1. The electrode was used as a hydrogen peroxide biosensor with a linear response over 3 to 240 µM and a detection li
... Show MoreThe present work folds two qualitative objectives; the first focuses on investigating the multiplicity of motivation-based human needs in Little Bee. The second objective involves examining the linguistic forms adopted to disclose such needs. Consequently, the researchers are to adapt eclectically Alderfer's Existence, Relatedness, and Growth Theory (1969) and Langacker’s theory of Domains (1987) together with his Active Zone Operation (1991). Such a study helps to embody the connectivity between the social and psychological aspects, and the way these two aspects are disclosed using particular linguistic The study has concluded that Bee needed Alderfer’s basic human needs: existence, relatedness, and growth. Besides, satisfying
... Show MoreBinary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin
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