Search results for: abnormal activity detection

Authors: Hemalatha Rallapalli, K. Lal Kishore

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In comparison to systems that are typically designed to provide capabilities over a narrow frequency range through hardware elements, the next generation cognitive radios are intended to implement a broader range of capabilities through efficient spectrum exploitation. This offers the user the promise of greater flexibility, seamless roaming possible on different networks, countries, frequencies, etc. It requires true paradigm shift i.e., liberalization over a wide band of spectrum as well as a growth path to more and greater capability. This work contributes towards the design and implementation of an open spectrum access (OSA) feature to unlicensed users thus offering a frequency agile radio platform that is capable of performing spectrum sensing over a wideband. Thus, an ultra-wideband (UWB) radio, which has the intelligence of spectrum sensing only, unlike the cognitive radio with complete intelligence, is named as a Smart Software Radio (SSR). The spectrum sensing mechanism is implemented based on energy detection. Simulation results show the accuracy and validity of this method.

Keywords: cognitive radio, energy detection, software radio, spectrum sensing

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Authors: Syed Auon Raza, Tahir Mahmood, Syed Basit Ali Bukhari

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In power system properly coordinated protection scheme is designed to make sure that only the faulty part of the system will be isolated when abnormal operating condition of the system will reach. The complexity of the system as well as the increased user demand and the deregulated environment enforce the utilities to improve system reliability by using a properly coordinated protection scheme. This paper presents overview of over current relay coordination techniques. Different techniques such as Deterministic Techniques, Meta Heuristic Optimization techniques, Hybrid Optimization Techniques, and Trial and Error Optimization Techniques have been reviewed in terms of method of their implementation, operation modes, nature of distribution system, and finally their advantages as well as the disadvantages.

Keywords: distribution system, relay coordination, optimization, Plug Setting Multiplier (PSM)

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Authors: Mabroka Omar Sherehe

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Despite the great efficacy of isoniazid (INH) and rifampicine (RIF) combination in the treatment of tuberculosis, hepatotoxicity is the most common serious complication. The potential protective effect of simvastatin (sim) against combination-induced hepatotoxicity was investigated in the present study. The administration of INH-RIF combination (50mg/kg each for 14 days) resulted in a significant increased activities of serum alanine and aspartate aminotransferases, such effects were further supported by histopathological studies. INH-RIF combination produced a significant increase in liver lipid, decreased SOD and CAT, and a significant depletion of GSH level. Additionally, treatment with INH-RIF combination resulted in a significant increase in liver MPO activity. The lipid-lowering drug, Sim demonstrated in the current study an evident antioxidant action, such effect was mediated via decreasing the elevated MDA, MPO, and restoring liver CAT activity. Additionally, Sim restored liver NO level to near basal value Furthermore, one cannot rule out the lipid-lowering effect of Sim that would probably add to its beneficial hepatoprotective antioxidant activity, where Sim decreased the elevated cholesterol, TGs and LDL cholesterol level and increased the serum HDL cholesterol level.

Keywords: isoniazid, rifampicine, oxidative stress, nitric oxide

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Authors: Sneha Leslie

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The current situation in the cyber world is that crimes performed by Botnets are increasing and the masterminds (botmaster) are not detectable easily. The botmaster in the botnet compromises the legitimate host machines in the network and make them bots or zombies to initiate the cyber-attacks. This paper will focus on the live detection of the botmaster in the network by using the strong framework 'metasploit', when distributed denial of service (DDOS) attack is performed by the botnet. The affected victim machine will be continuously monitoring its incoming packets. Once the victim machine gets to know about the excessive count of packets from any IP, that particular IP is noted and details of the noted systems are gathered. Using the vulnerabilities present in the zombie machines (already compromised by botmaster), the victim machine will compromise them. By gaining access to the compromised systems, applications are run remotely. By analyzing the incoming packets of the zombies, the victim comes to know the address of the botmaster. This is an effective and a simple system where no specific features of communication protocol are considered.

Keywords: bonet, DDoS attack, network security, detection system, metasploit framework

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Authors: Dipanshu Sur, Ratnabali Chakravorty, Rimi Pal, Siddhartha Chatterjee, Joyshree Chaterjee, Amal Mallik

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Background: Polycystic ovary syndrome (PCOS) is a common endocrine disease in reproductive women with a complex hormonal disturbance that affects the menstrual cycle and leads to metabolic consequences in later life. Hyperandrogenaemia is noticeable features of PCOS and influence the process of folliculogenesis in women. The levels of Antimüllerian Hormone (AMH) reflect the number of pre-antral follicles and thus are a marker of oocyte pool – germinal reserve of the ovary for reproduction. Besides its utilization in IVF (In-vitro fertilization), determination of AMH may serve as an additional marker in the diagnostics of PCOS, where increased AMH levels reflect the severity of the disease. The positive correlation of serum AMH with the number of antral follicles was found also in patients with PCOS. Objective: The objective of this study was to investigate the relationship between AMH androgens and whether AMH contributes to altered folliculogenesis in non-obese women with PCOS. Methods: We designed a prospective study which included a total of 65 IVF individuals. It enrolled 26 cases of PCOS based on 2003 Rotterdam criteria and 39 ovulatory normal- non PCOS, healthy, age-matched controls. AMH levels and ovarian morphology were assessed. The relationships between AMH and androgenaemia in patients with and without PCOS were studied. Results: Mean age of PCOS patients were slightly higher than controls (32±4 and 28±3 years, respectively). AMH generally increased with antral follicle count (AFC) [P=0.001], testosterone, and luteinising hormone, and decreased with age, and serum sex hormone binding globulin (SHBG). No significant relationships were found between circulating AMH levels and BMI between PCOS and non-PCOS patients. The calculation of AMH production per antral follicle (AMH/AF) showed that there was a significant difference in median AMH/AF between PCOS and non-PCOS (P =0.001). Both PCOS and non-PCOS groups showed a very similar increase in AMH with increases in AFC, but the PCOS patients had consistently higher AMH across all AFC levels. Conclusions: These observations indicate that there is a connection between AMH and androgens levels between PCOS and non-PCOS East Indian women. Excessive granulosa cell activity may be implicated in the abnormal follicular dynamic of the syndrome. They are higher in women with PCOS and, on the other hand, very low in women with an ovarian failure.

Keywords: anti-Mullerian hormone, polycystic ovary syndrome, antral follicle count, androgens

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Authors: Marko Batic, Nikola Tomasevic, Sanja Vranes

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One of the strongholds in the ubiquitous efforts related to the energy conservation and energy efficiency improvement is represented by the retrofit of high energy consumers in buildings. In general, HVAC systems represent the highest energy consumers in buildings. However they usually suffer from mal-operation and/or malfunction, causing even higher energy consumption than necessary. Various Fault Detection and Diagnosis (FDD) systems can be successfully employed for this purpose, especially when it comes to the application at a single device/unit level. In the case of more complex systems, where multiple devices are operating in the context of the same building, significant energy efficiency improvements can only be achieved through application of comprehensive FDD systems relying on additional higher level knowledge, such as their geographical location, served area, their intra- and inter- system dependencies etc. This paper presents a comprehensive FDD system that relies on the utilization of common knowledge repository that stores all critical information. The discussed system is deployed as a test-bed platform at the two at Fiumicino and Malpensa airports in Italy. This paper aims at presenting advantages of implementation of the knowledge base through the utilization of ontology and offers improved functionalities of such system through examples of typical queries and reasoning that enable derivation of high level energy conservation measures (ECM). Therefore, key SPARQL queries and SWRL rules, based on the two instantiated airport ontologies, are elaborated. The detection of high level irregularities in the operation of airport heating/cooling plants is discussed and estimation of energy savings is reported.

Keywords: airport ontology, knowledge management, ontology modeling, reasoning

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Authors: Mansur Abdulrasheed, Ibrahim I. Hussein, Ahmed M. Mubarak, Ahmed F. Umar

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This study was aimed at evaluating the phytochemical constituents and the antimicrobial activity of the seed oil of Moringa oleifera and garlic against some selected food-borne microorganisms (Staphylococcus aureus, Escherichia coli, Salmonella spp and Pseudomonas aeruginosa) using disc diffusion method. The results of the phytochemical screening revealed differences in the presence of the phytochemicals among the extracts. Saponins were detected in both Moringa oleifera and garlic seed oil, while alkaloid and tannins were observed in seed oil of garlic. Furthermore, the antibacterial assay results show that the seed oil of Moringa oleifera was inactive against all the tested organisms, even at 100 % concentration. In contrast, garlic oil was found to be active against all the tested organisms. The highest inhibition was observed in E. coli (12 mm)at 100 % concentration, while at 20 % concentration, Salmonella Sp and P. aeruginosa showed the least inhibit on (6 mm). The antimicrobial activity of the seed oil of garlic may be attributed to its phytochemicals components which were not detected in the seed oil of Moringa oleifera. The results of this study have shown the potentials of the seed oil of garlic as an antimicrobial agent more especially in foods, by inhibiting the growth of the test organisms, which range from food-borne pathogens to food spoilage organisms.

Keywords: antimicrobial, garlic, Moringa oleifera, food borne pathogens

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Authors: Lotfi O. Gargab, Ruichong R. Zhang

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A wave-based framework is presented for modeling seismic motion in multistory buildings and using measured response for system identification which can be utilized to extract important information regarding structure integrity. With one pair of building response at two locations, a generalized model response is formulated based on wave propagation features and expressed as frequency and time response functions denoted, respectively, as GFRF and GIRF. In particular, GIRF is fundamental in tracking arrival times of impulsive wave motion initiated at response level which is dependent on local model properties. Matching model and measured-structure responses can help in identifying model parameters and infer building properties. To show the effectiveness of this approach, the Millikan Library in Pasadena, California is identified with recordings of the Yorba Linda earthquake of September 3, 2002.

Keywords: system identification, continuous-discrete mass modeling, damage detection, post-earthquake

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Authors: Dhanuja S. Patil, Sanjay B. Waykar

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Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

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Authors: Paula K. Novelli, Margarida M. Barros, Luciana F. Flueri

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Utilization of agricultural by-products, wheat ban and soybean bran, as substrate for solid state fermentation (SSF) was studied, aiming the achievement of different enzymes from Aspergillus sp. with distinct biological characteristics and its application and improvement on animal nutrition. Aspergillus niger and Aspergillus oryzea were studied as they showed very high yield of phytase and protease production, respectively. Phytase activity was measure using p-nitrophenilphosphate as substrate and a standard curve of p-nitrophenol, as the enzymatic activity unit was the quantity of enzyme necessary to release one μmol of p-nitrophenol. Protease activity was measure using azocasein as substrate. Activity for phytase and protease substantially increased when the different biochemical characteristics were considered in the study. Optimum pH and stability of the phytase produced by A. niger with wheat bran as substrate was between 4.0 - 5.0 and optimum temperature of activity was 37oC. Phytase fermented in soybean bran showed constant values at all pHs studied, for optimal and stability, but low production. Phytase with both substrates showed stable activity for temperatures higher than 80oC. Protease from A. niger showed very distinct behavior of optimum pH, acid for wheat bran and basic for soybean bran, respectively and optimal values of temperature and stability at 50oC. Phytase produced by A. oryzae in wheat bran had optimum pH and temperature of 9 and 37oC, respectively, but it was very unstable. On the other hand, proteases were stable at high temperatures, all pH’s studied and showed very high yield when fermented in wheat bran, however when it was fermented in soybean bran the production was very low. Subsequently the upscale production of phytase from A. niger and proteases from A. oryzae were applied as an enzyme additive in fish fed for digestibility studies. Phytases and proteases were produced with stable enzyme activity of 7,000 U.g-1 and 2,500 U.g-1, respectively. When those enzymes were applied in a plant protein based fish diet for digestibility studies, they increased protein, mineral, energy and lipids availability, showing that these new enzymes can improve animal production and performance. In conclusion, the substrate, as well as, the microorganism species can affect the biochemical character of the enzyme produced. Moreover, the production of these enzymes by SSF can be up to 90% cheaper than commercial ones produced with the same fungi species but submerged fermentation. Add to that these cheap enzymes can be easily applied as animal diet additives to improve production and performance.

Keywords: agricultural by-products, animal nutrition, enzymes production, solid state fermentation

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

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Authors: Thi Huong Vu, Vijay Jayasena, Zhongxiang Fang, Gary Dykes

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Carob kibble has recently received attention due to the presence of high level of polyphenol antioxidants. The capacity of microorganisms to improve antioxidant activities and total phenolics in carob kibble was investigated in the study. Two types of microorganisms including lactic acid bacteria Lactobacillus plantarum (L. plantarum) and yeast Saccharomyces cerevisiae (S. cerevisiae) were used in single and in their combination as starters. The total phenolic content was determined by the Folin–Ciocalteu method. Antioxidant activities were assessed scavenging capacity using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid (ABTS). The study found that S. cerevisiae alone considerably improved 55% total phenolics content at 15 h, while L. plantarum caused in a loss of 20% through the process. Antioxidant capacity of the yeast-fermented samples significantly increased by 43 % and 10 % in ABTS and DPPH assays, respectively. However, reduction of 13 % and 32 % inhibition were recorded in the carob treated with L. plantarum. In the combination of S. cerevisiae and L. plantarum (1:1), both total phenolic content and antioxidant activity of carob kibble were a similar trend as these of S. cerevisiae single, but a lower improvement. The antioxidant power of the extracts was linearly correlated to their total phenolic contents (R=0.75). The results suggested that S. cerevisiae alone was the better for enhancement of both total phenolic content and antioxidant activity in carob kibble using submerged fermentation. The efficiency of fermentation reached the highest at 15h. Thus submerged fermentation with S. cerevisiae offers a tool with simple and cost effective to further increase the bioactive potential of carob kibble, which is in use for food, cosmetic and pharmaceutical industries.

Keywords: antioxidant activity, carob kibble, lactobacillus plantarum, saccharomyces cerevisiae, total phenolics

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Authors: Martín Pratto Burgos

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The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

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Authors: B. Kriheli, E. Levner, T. C. E. Cheng, C. T. Ng

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During the last decades, research interest in planning, scheduling, and control of emergency response operations, especially people rescue and evacuation from the dangerous zone of marine accidents, has increased dramatically. Until the survivors (called ‘targets’) are found and saved, it may cause loss or damage whose extent depends on the location of the targets and the search duration. The problem is to efficiently search for and detect/rescue the targets as soon as possible with the help of intelligent mobile robots so as to maximize the number of saved people and/or minimize the search cost under restrictions on the amount of saved people within the allowable response time. We consider a special situation when the autonomous mobile robots (AMR), e.g., unmanned aerial vehicles and remote-controlled robo-ships have no operator on board as they are guided and completely controlled by on-board sensors and computer programs. We construct a mathematical model for the search process in an uncertain environment and provide a new fast algorithm for scheduling the activities of the autonomous robots during the search-and rescue missions after an accident at sea. We presume that in the unknown environments, the AMR’s search-and-rescue activity is subject to two types of error: (i) a 'false-negative' detection error where a target object is not discovered (‘overlooked') by the AMR’s sensors in spite that the AMR is in a close neighborhood of the latter and (ii) a 'false-positive' detection error, also known as ‘a false alarm’, in which a clean place or area is wrongly classified by the AMR’s sensors as a correct target. As the general resource-constrained discrete search problem is NP-hard, we restrict our study to finding local-optimal strategies. A specificity of the considered operational research problem in comparison with the traditional Kadane-De Groot-Stone search models is that in our model the probability of the successful search outcome depends not only on cost/time/probability parameters assigned to each individual location but, as well, on parameters characterizing the entire history of (unsuccessful) search before selecting any next location. We provide a fast approximation algorithm for finding the AMR route adopting a greedy search strategy in which, in each step, the on-board computer computes a current search effectiveness value for each location in the zone and sequentially searches for a location with the highest search effectiveness value. Extensive experiments with random and real-life data provide strong evidence in favor of the suggested operations research model and corresponding algorithm.

Keywords: disaster management, intelligent robots, scheduling algorithm, search-and-rescue at sea

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Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

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Authors: Madalin Enache, Simona Neagu, Roxana Cojoc, Ioana Gomoiu, Delia Ionela Dobre, Ancuta Roxana Trifoi

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Various types of halophilic and halotolerant microorganisms able to be cultivated in laboratory on culture media with a wide range of sodium chloride content are isolated from several salted environments. The extracellular enzymes of these microorganisms showed the enzymatic activity in these spectrums of salinity thus being attractive for several biotechnological processes developed at high ionic strength. In present work, a number of amylase, protease, esterase, lipase, cellulase, pectinase, xilanases and innulinase were identified for more than 50th bacterial strains isolated from water samples and sapropelic mud from four saline and hypersaline lakes located in Romanian plain. On the other hand, the cellulase and pectinase activity were also detected in some halotolerant microorganisms isolated from secondary agricultural flow of grapes processing. The preliminary data revealed that from totally tested strains seven harbor proteases activity, eight amylase activity, four for esterase and another four for lipase, three for pectinase and for one strain were identified either cellulase or pectinase activity. There were no identified enzymes able to hydrolase innulin added to culture media. Several strains isolated from sapropelic mud showed multiple extracellular enzymatic activities, namely three strains harbor three activities and another seven harbor two activities. The data revealed that amylase and protease activities were frequently detected if compare with other tested enzymes. In the case of pectinase were investigated, their ability to be used for increasing resveratrol recovery from material resulted after grapes processing. In this way, the resulted material from grapes processing was treated with microbial supernatant for several times (two, four and 24 hours) and the content of resveratrol was detected by High Performance Liquid Chromatography method (HPLC). The preliminary data revealed some positive results of this treatment.

Keywords: halophilic microorganisms, enzymes, pectinase, salinity

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Authors: Al-Hindi Rashad, Alotibi Ibrahim

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The aim of this study was to examine the antibacterial activity of the peroxide components of some locally produced honeys: Toran, Zaitoon (Olive), Shaflah, Saha, Jizan, Rabea Aja, Fakhira, Sedr Aljanoob, Tenhat, Karath and Bareq against two of the drug resistant bacteria; i.e., methicillin resistant Staph. aureus (MRSA, ATCC 43330) and Acinetobacter baumannii. Measurement of the antibacterial activity of honey samples by using the agar well diffusion method was adopted as follows: by using turbidity standard McFaraland 0.5, suspensions of bacterial strains MRSA ATCC 43330 and Acinetobacter baumannii were prepared. By the spreading plate method, 100 µl of the suspension was inoculated onto Muller-Hinton agar medium. On the inoculated agar medium, five wells were made using a sterile cork borer (diameter 5 mm).100 µl of honey dilutions (10%, 30%, 50%, 70% and 100%) were used. The study indicated that the highly effective activity was in some local honey samples such as Toran honey against MRSA, and Shafalah honey against MRSA and Acinetobacter baumannii which showed bactericidal effects at concentrations 70 % to 100 % as well. The majority of local honey samples recorded bacteriostatic effects on MRSA and Acinetobacter baumannii at consternations 50 % and above. In conclusion this investigation indicated that in regard to the majority inhibitory effect on microorganisms, the existing of H2O2 in honey samples together with phenolic content greatly provide a strong antibacterial activities among different types of honey, because in some previous studies the H2O2 content of honey interacts with phenolic content and showed better inhibitory effect than in absent of H2O2.

Keywords: antibacterial activity, honey, hospital acquired, Saudi Arabia

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Authors: Naser Ahmadi Sani, Karim Solaimani, Lida Razaghnia, Jalal Zandi

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In recent decades, rapid and incorrect changes in land-use have been associated with consequences such as natural resources degradation and environmental pollution. Detecting changes in land-use is one of the tools for natural resource management and assessment of changes in ecosystems. The target of this research is studying the land-use changes in Haraz basin with an area of 677000 hectares in a 15 years period (1996 to 2011) using LANDSAT data. Therefore, the quality of the images was first evaluated. Various enhancement methods for creating synthetic bonds were used in the analysis. Separate training sites were selected for each image. Then the images of each period were classified in 9 classes using supervised classification method and the maximum likelihood algorithm. Finally, the changes were extracted in GIS environment. The results showed that these changes are an alarm for the HARAZ basin status in future. The reason is that 27% of the area has been changed, which is related to changing the range lands to bare land and dry farming and also changing the dense forest to sparse forest, horticulture, farming land and residential area.

Keywords: Haraz basin, change detection, land-use, satellite data

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Authors: Alaa Abdullah Altaee

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This paper presents an adaptive decision feedback equalizer (ADFE) for multi-Gbps serial links utilizing a fix-step error signal extracted from cross-points of received data symbols. The extracted signal is generated based on violation of received data symbols with minimum detection requirements at the clock and data recovery (CDR) stage. The iterations of the adaptation process search for the optimum feedback tap coefficients to maximize the data eye-opening and minimize the adaptation convergence time. The effectiveness of the proposed architecture is validated using the simulation results of a serial link designed in an IBM 130 nm 1.2V CMOS technology. The data link with variable channel lengths is analyzed using Spectre from Cadence Design Systems with BSIM4 device models.

Keywords: adaptive DFE, CMOS equalizer, error detection, serial links, timing jitter, wire-line communication

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Authors: Parya Tabei, Maryam Habibifar

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Decision-making is an important cognitive function that can be defined as the process of choosing an option among available options to achieve a specific goal. Consumer ‘need’ is the main reason for purchasing decisions. Human decision-making while buying products online is subject to various factors, one of which is the quality and effect of advertising photos. Advertising photo editing can have a significant impact on people's virtual purchase decisions. This technique helps improve the quality and overall appearance of photos by adjusting various aspects such as brightness, contrast, colors, cropping, resizing, and adding filters. This study, by examining the effect of editing advertising photos on the virtual purchase decision using EEG data, tries to investigate the effect of edited images on the decision-making of customers. A group of 30 participants were asked to react to 24 edited and unedited images while their EEG was recorded. Analysis of the EEG data revealed increased alpha wave activity in the occipital regions (O1, O2) for both edited and unedited images, which is related to visual processing and attention. Additionally, there was an increase in beta wave activity in the frontal regions (FP1, FP2, F4, F8) when participants viewed edited images, suggesting involvement in cognitive processes such as decision-making and evaluating advertising content. Gamma wave activity also increased in various regions, especially the frontal and parietal regions, which are associated with higher cognitive functions, such as attention, memory, and perception, when viewing the edited images. While the visual processing reflected by alpha waves remained consistent across different visual conditions, editing advertising photos appeared to boost neural activity in frontal and parietal regions associated with decision-making processes. These Findings suggest that photo editing could potentially influence consumer perceptions during virtual shopping experiences by modulating brain activity related to product assessment and purchase decisions.

Keywords: virtual purchase decision, advertising photo, EEG parameters, decision Making

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Authors: Fatma Acheuk, Idir Bitam, Leila Bendifallah, Malika Ramdani, Fethia Barika

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Phytochemical study of the plant Artemisia judaica showed the presence of various groups of natural products: saponins, tannins, coumarins, flavonoids, carbohydrates, and reducer compounds. However alkaloids are present as traces. The crude ethanol extract of the test plant presented significant insecticidal activity on mosquito larvae in stage I, II, and III. The LD50 highlighted the excellent insecticidal effect of the tested extract. Similarly, the LT50 are achieved early with high doses. The results obtained are encouraging and suggest the possibility of using the secondary metabolites of this plant such as bio-insecticide.

Keywords: Atamisia judaica, crud extract, mosquito, insecticidal activity

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Authors: Zzibu Mark Brian

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As software systems become increasingly complex, ensuring code security is a growing concern. Traditional vulnerability detection methods often rely on manual code reviews or static analysis tools, which can be time-consuming and prone to errors. This paper presents a distinct approach to enhancing code security by leveraging artificial intelligence (AI) and machine learning (ML) techniques. Our proposed system utilizes a combination of natural language processing (NLP) and deep learning algorithms to identify and classify vulnerabilities in real-world codebases. By analyzing vast amounts of open-source code data, our AI-powered tool learns to recognize patterns and anomalies indicative of security weaknesses. We evaluated our system on a dataset of over 10,000 open-source projects, achieving an accuracy rate of 92% in detecting known vulnerabilities. Furthermore, our tool identified previously unknown vulnerabilities in popular libraries and frameworks, demonstrating its potential for improving software security.

Keywords: AI, machine language, cord security, machine leaning

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Authors: Abid Fida Masih

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Forced degradation study of Rifaximin was conducted to determine the stability indicating potential of HPLC testing method for detection of Rifaximin in formulated tablets to be employed for quality control and stability testing. The questioned method applied with mobile phase methanol: water (70:30), 5µm, 250 x 4.6mm, C18 column, wavelength 293nm and flow rate of 1.0 ml/min. Forced degradation study was performed under oxidative, acidic, basic, thermal and photolytic conditions. The applied method successfully determined the degradation products after acidic and basic degradation without interfering with Rifaximin detection. Therefore, the method was said to be stability indicating and can be applied for quality control and stability testing of Rifaxmin tablets during its shelf life.

Keywords: forced degradation, high-performance liquid chromatography, method validation, rifaximin, stability indicating method

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Authors: Steven Arcidiacono, Robert Stote, Erin Anderson, Molly Richards

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There are numerous standard test methods for antimicrobial textiles that measure activity against specific microorganisms. However, many times these results do not translate to the performance of treated textiles when worn by individuals. Standard test methods apply a single target organism grown under optimal conditions to a textile, then recover the organism to quantitate and determine activity; this does not reflect the actual performance environment that consists of polymicrobial communities in less than optimal conditions or interaction of the textile with the skin substrate. Here we propose the development of in vitro skin model method to bridge the gap between lab testing and wear studies. The model will consist of a defined polymicrobial community of 5-7 commensal microbes simulating the skin microbiome, seeded onto a solid tissue platform to represent the skin. The protocol would entail adding a non-commensal test organism of interest to the defined community and applying a textile sample to the solid substrate. Following incubation, the textile would be removed and the organisms recovered, which would then be quantitated to determine antimicrobial activity. Important parameters to consider include identification and assembly of the defined polymicrobial community, growth conditions to allow the establishment of a stable community, and choice of skin surrogate. This model could answer the following questions: 1) is the treated textile effective against the target organism? 2) How is the defined community affected? And 3) does the textile cause unwanted effects toward the skin simulant? The proposed model would determine activity under conditions comparable to the intended application and provide expanded knowledge relative to current test methods.

Keywords: antimicrobial textiles, defined polymicrobial community, in vitro skin model, skin microbiome

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Authors: Helge Rupprich, Elke Knisel

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In a time of mediazation and reduced physical movement, it is important to change passivity (akinesa) into physical activity to improve health. The approach is to encourage children, junior athletes, recreational athletes, and semi-professional athletes to do sports while attending a top sport event. The concept has the slogan: get out off your seat and move! A top sport event of a series of professional beach volleyball tournaments with 330.000 life viewers, 13,70 million cumulative reach viewers and 215,13 million advertising contacts is used as framework for different sports didactic approaches, social integrative approaches and migration valuations. An important aim is to use the big radiant power of the top sport event to extract active participants from the viewers of the top sport event. Even if it is the goal to improve physical activity, it is necessary to differentiate between the didactic approaches. The first approach contains psycho motoric exercises with children (N=158) between two and five years which was used in the project ‘largest sandbox of the city’. The second approach is social integration and promotion of activity of students (N=54) in the form of a student beach volleyball tournament. The third approach is activity in companies. It is based on the idea of health motivation of employees (N=62) in a big beach volleyball tournament. Fourth approach is to improve the sports leisure time activities of recreational athletes (N=292) in different beach volleyball tournaments. Fifthly approach is to build a foreign friendly measure which is implemented in junior athlete training with the French and German junior national team (N=16). Sixthly approach is to give semi professional athletes a tournament to develop their relation to active life. Seventh approach is social integration for disadvantaged people (N=123) in form of training with professional athletes. The top sport beach volleyball tournament had 80 athletes (N=80) and 34.000 viewers. In sum 785 athletes (N=785) did sports in 13 days. Over 34.000 viewers where counted in the first three days of top sport event. The project was evaluated positively by the City of Dresden, Politics of Saxony and the participants and will be continued in Dresden and expanded for the season 2015 in Jena.

Keywords: beach volleyball, event, sports didactic, sports project

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Authors: Lu Yang, Meiyang Song, Xiang Yu, Wenhao Zhou, Chuntao Feng

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To address the problem that the FM continuous-wave radar (FMCW) extracts human vital sign signals which are susceptible to noise interference and low reconstruction accuracy, a new detection scheme for the sign signals is proposed. Firstly, an improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) algorithm is applied to decompose the radar-extracted thoracic signals to obtain several intrinsic modal functions (IMF) with different spatial scales, and then the IMF components are optimized by a BP neural network improved by immune genetic algorithm (IGA). The simulation results show that this scheme can effectively separate the noise and accurately extract the respiratory and heartbeat signals and improve the reconstruction accuracy and signal-to-noise ratio of the sign signals.

Keywords: frequency modulated continuous wave radar, ICEEMDAN, BP neural network, vital signs signal

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Authors: Mansouri Nabila, Ben Jemaa Yousra, Motamed Cina, Watelain Eric

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Research and development efforts in intelligent Advanced Driver Assistance Systems (ADAS) seek to save lives and reduce the number of on-road fatalities. For traffic and emergency monitoring, the essential but challenging task is vehicle detection and tracking in reasonably short time. This purpose needs first of all a powerful dynamic car detector model. In fact, this paper presents an optimized HOG process based on shape and motion parameters fusion. Our proposed approach mains to compute HOG by bloc feature from foreground blobs using configurable research window and pathway in order to overcome the shortcoming in term of computing time of HOG descriptor and improve their dynamic application performance. Indeed we prove in this paper that HOG by bloc descriptor combined with motion parameters is a very suitable car detector which reaches in record time a satisfactory recognition rate in dynamic outside area and bypasses several popular works without using sophisticated and expensive architectures such as GPU and FPGA.

Keywords: car-detector, HOG, motion, computing time

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Authors: Marta Paszkiewicz, Justyna Łuczak, Martyna Marchelek, Adriana Zaleska-Medynska

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In recent years, photocatalytical processes have been intensively investigated for destruction of pollutants, hydrogen evolution, disinfection of water, air and surfaces, for the construction of self-cleaning materials (tiles, glass, fibres, etc.). Titanium dioxide (TiO2) is the most popular material used in heterogeneous photocatalysis due to its excellent properties, such as high stability, chemical inertness, non-toxicity and low cost. It is well known that morphology and microstructure of TiO2 significantly influence the photocatalytic activity. This characteristics as well as other physical and structural properties of photocatalysts, i.e., specific surface area or density of crystalline defects, could be controlled by preparation route. In this regard, TiO2 particles can be obtained by sol-gel, hydrothermal, sonochemical methods, chemical vapour deposition and alternatively, by ionothermal synthesis using ionic liquids (ILs). In the TiO2 particles synthesis ILs may play a role of a solvent, soft template, reagent, agent promoting reduction of the precursor or particles stabilizer during synthesis of inorganic materials. In this work, the effect of the ILs anion type on morphology and photoactivity of TiO2 is presented. The preparation of TiO2 microparticles with spherical structure was successfully achieved by solvothermal method, using tetra-tert-butyl orthotitatane (TBOT) as the precursor. The reaction process was assisted by an ionic liquids 1-butyl-3-methylimidazolium bromide [BMIM][Br], 1-butyl-3-methylimidazolium tetrafluoroborate [BMIM][BF4] and 1-butyl-3-methylimidazolium haxafluorophosphate [BMIM][PF6]. Various molar ratios of all ILs to TBOT (IL:TBOT) were chosen. For comparison, reference TiO2 was prepared using the same method without IL addition. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Brenauer-Emmett-Teller surface area (BET), NCHS analysis, and FTIR spectroscopy were used to characterize the surface properties of the samples. The photocatalytic activity was investigated by means of phenol photodegradation in the aqueous phase as a model pollutant, as well as formation of hydroxyl radicals based on detection of fluorescent product of coumarine hydroxylation. The analysis results showed that the TiO2 microspheres had spherical structure with the diameters ranging from 1 to 6 µm. The TEM micrographs gave a bright observation of the samples in which the particles were comprised of inter-aggregated crystals. It could be also observed that the IL-assisted TiO2 microspheres are not hollow, which provides additional information about possible formation mechanism. Application of the ILs results in rise of the photocatalytic activity as well as BET surface area of TiO2 as compared to pure TiO2. The results of the formation of 7-hydroxycoumarin indicated that the increased amount of ·OH produced at the surface of excited TiO2 for samples TiO2_ILs well correlated with more efficient degradation of phenol. NCHS analysis showed that ionic liquids remained on the TiO2 surface confirming structure directing role of that compounds.

Keywords: heterogeneous photocatalysis, IL-assisted synthesis, ionic liquids, TiO2

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Authors: N. Meziou-Chebouti, A. Merabet, Y. Chebouti N. Behidj

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This work is a contribution to the knowledge of physicochemical characteristics of mature carob followed by evaluation of the activity, antimicrobial phenolics leaves and green pods of Ceratonia siliqua L. physicochemical study shows that mature carob it has a considerable content of sugar (50.90%), but poor in proteins (7%), fat (8%) and also has a high mineral content. The results obtained from phenolic extracts of leaves and green pods of Ceratonia siliqua L. show a wealth leaf phenolic extract especially flavonoids (0,545 mg EqQ/g) relative to the extract of green pods (0,226 mgEqQ/g). Polyphenols leaves have a slightly inhibitory effect on the growth of strains: Staphylococcus aureus, Escherichia coli, Klebsiella pneumoiae, Streptococcus sp and Sanmonella enteritidis, a strong inhibitory effect on the growth of Pseudomonas strain aerogenosa. Moreover, polyphenols pod have a slightly inhibitory effect on the growth of Streptococcus sp strains, Pseudomonas and aerogenosa Sanmonella enteritidis, a slightly inhibitory effect on the growth of Klebsiella pneumoniae strains, E. coli and Staphylococcus aureus.

Keywords: antimicrobial activity, bacteria, clove, Ceratonia siliqua, polyphenols

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Authors: Stephanie Zuba-Bates

Abstract:

Purpose: This qualitative research study explored the lived experience of people with functional movement disorder (FMD) including how it impacts their quality of life and participation in life activities. It aims to educate health care professionals about FMD from the perspective of those living with the disorder. Background: Functional movement disorder is characterized by abnormal motor movements including tremors, abnormal gait, paresis, and dystonia with no known underlying pathophysiological cause. Current research estimates that FMD may account for 2-20% of clients seen by neurologists. Getting a diagnosis of FMD is typically long and difficult. In addition, many healthcare professionals are unfamiliar with the disorder which may delay treatment. People living with FMD face great disruption in major areas of life including activities of daily living (ADLs), work, leisure, and community participation. OT practitioners have expertise in working with people with both physical disabilities as well as mental illness and this expertise has the potential to guide treatment and become part of the standard of care. In order for occupational therapists to provide these services, they must be aware of the disorder and must advocate for clients to be referred to OT services. In addition, referring physicians and other health professionals need to understand how having FMD impacts the daily functioning of people living with the disorder and how OT services can intervene to improve their quality of life. This study aimed to answer the following research questions: 1) What is the lived experience of individuals with FMD?; 2) How has FMD impacted their participation in major areas of life?; and, 3) What treatment have they found to be effective in improving their quality of life? Method: A naturalistic approach was used to collect qualitative data through semi-structured telephone interviews of five individuals living with FMD. Subjects were recruited from social media websites and resources for people with FMD. Data was analyzed for common themes among participants. Results: Common themes including the variability of symptoms of the disorder; challenges to receiving a diagnosis; frustrations with and distrust of health care professionals; the impact of FMD on the participant’s ability to perform daily activities; and, strategies for living with the symptoms of FMD. Conclusion: All of the participants in the study had to modify their daily activities, roles and routines as a result of the disorder. This is an area where occupational therapists may intervene to improve the quality of life of these individuals. Additionally, participants reported frustration with the medical community regarding the awareness of the disorder and how they were treated by medical professionals. Much more research and awareness of the disorder is in order.

Keywords: functional movement disorder, occupational therapy, participation, quality of life

Procedia PDF Downloads 170