Search results for: limit of detection

Authors: Nadia Ben Youssef, Aicha Bouzid

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Gradient estimation is one of the most fundamental tasks in the field of image processing in general, and more particularly for color images since that the research in color image gradient remains limited. The widely used gradient method is Di Zenzo’s gradient operator, which is based on the measure of squared local contrast of color images. The proposed gradient mechanism, presented in this paper, is based on the principle of the Di Zenzo’s approach using quaternion representation. This edge detector is compared to a marginal approach based on multiscale product of wavelet transform and another vector approach based on quaternion convolution and vector gradient approach. The experimental results indicate that the proposed color gradient operator outperforms marginal approach, however, it is less efficient then the second vector approach.

Keywords: gradient, edge detection, color image, quaternion

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Authors: Dogan Cetin, Omar Hamdi Jasim

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Using some additives is very common method to improve the soil properties such as shear strength, bearing capacity; and to reduce the settlement and lateral deformation. Soil reinforcement with natural materials is an attractive method to improve the soil properties because of their low cost. However, the studies conducted by using natural additive are very limited. This paper presents the results of an investigation on the immediate and long-term effects of the sawdust on the shear strength behavior of a clayey silt soil obtained in Arnavutkoy in Istanbul with sawdust. Firstly, compaction tests were conducted to be able to optimum moisture content for every percentage of sawdust. The samples were obtained from compacted soil at optimum moisture content. UU Triaxial Tests were conducted to evaluate the response of randomly distributed sawdust on the strength of low plasticity clayey silt soil. The specimens were tested with 1%, 2% and 3% content of sawdust. It was found that the undrained shear strength of clay soil with 1%, 2% and 3% sawdust were increased respectively 4.65%, 27.9% and 39.5% higher than the soil without additive. At 5%, shear strength of clay soil decreased by 3.8%. After 90 days cure period, the shear strength of the soil with 1%, 2%, 3% and %5 increased respectively 251%, 302%, 260% and 153%. It can be said that the effect of the sawdust usage has a remarkable effect on the undrained shear strength of the soil. Besides the increasing undrained shear strength, it was also found that the sawdust decreases the liquid limit, plastic limit and plasticity index by 5.5%, 2.9 and 10.9% respectively.

Keywords: compaction test, sawdust, shear strength, UU Triaxial Test

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Authors: Doğan Yıldız, Aydan Müşerref Erkmen

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The controller of the octocopter is mostly based on the PID controller. For complex maneuvers, PID controllers have limited performance capability like in collision avoidance. When an octocopter needs avoidance from an obstacle, it must instantly show an agile maneuver. Also, this kind of maneuver is affected severely by the nonlinear characteristic of octocopter. When these kinds of limitations are considered, the situation is highly challenging for the PID controller. In the proposed study, these challenges are tried to minimize by using the model predictive controller (MPC) for collision avoidance with a nonlinear octocopter model. The aim is to show that MPC-based collision avoidance has the capability to deal with fast varying conditions in case of obstacle detection and diminish the nonlinear effects of octocopter with varying disturbances.

Keywords: model predictive control, nonlinear octocopter model, collision avoidance, obstacle detection

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Authors: Dada Durojaye Joshua

Abstract:

The study examined the combined effect of internal control system and whistle blowing policy while it pursues the following specific objectives, which are to: examine the relationship between monitoring activities and fraud’s detection and prevention; investigate the effect of control activities on fraud’s detection and prevention in Nigerian Deposit Money Banks (DMBs). The population of the study comprises the 89,275 members of staff in the 20 DMBs in Nigeria as at June 2019. Purposive and convenient sampling techniques were used in the selection of the 80 members of staff at the supervisory level of the Internal Audit Departments of the head offices of the sampled banks, that is, selecting 4 respondents (Audit Executive/Head, Internal Control; Manager, Operation Risk Management; Head, Financial Crime Control; the Chief Compliance Officer) from each of the 20 DMBs in Nigeria. A standard questionnaire was adapted from 2017/2018 Internal Control Questionnaire and Assessment, Bureau of Financial Monitoring and Accountability Florida Department of Economic Opportunity. It was modified to serve the purpose for which it was meant to serve. It was self-administered to gather data from the 80 respondents at the respective headquarters of the sampled banks at their respective locations across Nigeria. Two likert-scales was used in achieving the stated objectives. A logit regression was used in analysing the stated hypotheses. It was found that effect of monitoring activities using the construct of conduct of ongoing or separate evaluation (COSE), evaluation and communication of deficiencies (ECD) revealed that monitoring activities is significant and positively related to fraud’s detection and prevention in Nigerian DMBS. So also, it was found that control activities using selection and development of control activities (SDCA), selection and development of general controls over technology to prevent financial fraud (SDGCTF), development of control activities that gives room for transparency through procedures that put policies into actions (DCATPPA) contributed to influence fraud detection and prevention in the Nigerian DMBs. In addition, it was found that transparency, accountability, reliability, independence and value relevance have significant effect on fraud detection and prevention ibn Nigerian DMBs. The study concluded that the board of directors demonstrated independence from management and exercises oversight of the development and performance of internal control. Part of the conclusion was that there was accountability on the part of the owners and preparers of the financial reports and that the system gives room for the members of staff to account for their responsibilities. Among the recommendations was that the management of Nigerian DMBs should create and establish a standard Internal Control System strong enough to deter fraud in order to encourage continuity of operations by ensuring liquidity, solvency and going concern of the banks. It was also recommended that the banks create a structure that encourages whistleblowing to complement the internal control system.

Keywords: internal control, whistleblowing, deposit money banks, fraud prevention, fraud detection

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Authors: Dada Durojaye Joshua

Abstract:

The study examined the combined effect of internal control system and whistle blowing policy while it pursues the following specific objectives, which are to: examine the relationship between monitoring activities and fraud’s detection and prevention; investigate the effect of control activities on fraud’s detection and prevention in Nigerian Deposit Money Banks (DMBs). The population of the study comprises the 89,275 members of staff in the 20 DMBs in Nigeria as at June 2019. Purposive and convenient sampling techniques were used in the selection of the 80 members of staff at the supervisory level of the Internal Audit Departments of the head offices of the sampled banks, that is, selecting 4 respondents (Audit Executive/Head, Internal Control; Manager, Operation Risk Management; Head, Financial Crime Control; the Chief Compliance Officer) from each of the 20 DMBs in Nigeria. A standard questionnaire was adapted from 2017/2018 Internal Control Questionnaire and Assessment, Bureau of Financial Monitoring and Accountability Florida Department of Economic Opportunity. It was modified to serve the purpose for which it was meant to serve. It was self-administered to gather data from the 80 respondents at the respective headquarters of the sampled banks at their respective locations across Nigeria. Two likert-scales was used in achieving the stated objectives. A logit regression was used in analysing the stated hypotheses. It was found that effect of monitoring activities using the construct of conduct of ongoing or separate evaluation (COSE), evaluation and communication of deficiencies (ECD) revealed that monitoring activities is significant and positively related to fraud’s detection and prevention in Nigerian DMBS. So also, it was found that control activities using selection and development of control activities (SDCA), selection and development of general controls over technology to prevent financial fraud (SDGCTF), development of control activities that gives room for transparency through procedures that put policies into actions (DCATPPA) contributed to influence fraud detection and prevention in the Nigerian DMBs. In addition, it was found that transparency, accountability, reliability, independence and value relevance have significant effect on fraud detection and prevention ibn Nigerian DMBs. The study concluded that the board of directors demonstrated independence from management and exercises oversight of the development and performance of internal control. Part of the conclusion was that there was accountability on the part of the owners and preparers of the financial reports and that the system gives room for the members of staff to account for their responsibilities. Among the recommendations was that the management of Nigerian DMBs should create and establish a standard Internal Control System strong enough to deter fraud in order to encourage continuity of operations by ensuring liquidity, solvency and going concern of the banks. It was also recommended that the banks create a structure that encourages whistleblowing to complement the internal control system.

Keywords: internal control, whistleblowing, deposit money banks, fraud prevention, fraud detection

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Authors: Hassane Ouazzani Chahdi, Omar Helli, Bourzgui Nour Eddine, Hassan Maher, Ali Soltani

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The real-time knowledge of the NO, NO₂ concentration at high temperature, would allow manufacturers of automobiles to meet the upcoming stringent EURO7 anti-pollution measures for diesel engines. Knowledge of the concentration of each of these species will also enable engines to run leaner (i.e., more fuel efficient) while still meeting the anti-pollution requirements. Our proposed technology is promising in the field of automotive sensors. It consists of nanostructured semiconductors based on gallium nitride and zirconia dioxide. The development of new technologies for selective detection of NO and NO₂ gas species would be a critical enabler of superior depollution. The current response was well correlated to the NO concentration in the range of 0–2000 ppm, 0-2500 ppm NO₂, and 0-300 ppm NH₃ at a temperature of 600.

Keywords: NOₓ sensors, HEMT transistor, anti-pollution, gallium nitride, gas sensor

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Authors: Osama Abaza, Tanay Datta Chowdhury

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As a driver's speed increases, so do the probability of an incident and likelihood of injury. The presence of equipment, personnel, and a changing landscape in construction zones create greater potential for incident. This is especially concerning in Alaska, where summer construction activity, coinciding with the peak annual traffic volumes, cannot be avoided. In order to reduce vehicular speeding in work zones, and therefore the probability of crash and incident occurrence, variable speed limit (VSL) systems can be implemented in the form of radar speed display trailers since the radar speed display trailers were shown to be effective at reducing vehicular speed in construction zones. Allocation of VSL not only help reduce the 85th percentile speed but also it will predominantly reduce mean speed as well. Total of 2147 incidents along with 385 crashes occurred only in one month around the construction zone in the Alaska which seriously requires proper attention. This research provided a thorough crash analysis to better understand the cause and provide proper countermeasures. Crashes were predominantly recoded as vehicle- object collision and sideswipe type and thus significant amount of crashes fall in the group of no injury to minor injury type in the severity class. But still, 35 major crashes with 7 fatal ones in a one month period require immediate action like the implementation of the VSL system as it proved to be a speed reducer in the construction zone on Alaskan roadways.

Keywords: speed, construction zone, crash, severity

Procedia PDF Downloads 251

Authors: Charawee Butbumrung

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This research aim to study the financial service of the Thailand financial Institution, second is to identify "best practices" offered by four financial institutions, namely, Kasikornthai Bank, Bangkok Bank, Siam Commercial Bank, and Thanachart Bank. In-depth interviews with managers of financial institution and borrowers reveal best practices from each financial institution. Close monitoring of and a close relationship with borrowers appear to be important for early detection of any problem. Another aspect that may be important is building up loyalty and developing reliability among members. A close and informal relationship with borrowers may also help in monitoring and early detection of problems that may arise in non-repayment of loans. Other factors that may be considered important to the success of a financial service scheme are cooperation and coordination among various agencies that provide additional support to borrowers. Indirectly, these support systems contribute to the success of a SME in Thailand.

Keywords: best practices, financial service, financial institution, SME in Thailand

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Authors: Soumya Bhattacharjya, Avinandan Sahoo, Gaurav Datta

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Wind fragility analysis of chimney is often carried out disregarding temperature effect. However, the combined effect of wind and temperature is the most critical limit state for chimney design. Hence, in the present paper, an efficient fragility analysis for concrete chimney is explored under combined wind and temperature effect. Wind time histories are generated by Davenports Power Spectral Density Function and using Weighed Amplitude Wave Superposition Technique. Fragility analysis is often carried out in full Monte Carlo Simulation framework, which requires extensive computational time. Thus, in the present paper, an efficient adaptive metamodelling technique is adopted to judiciously approximate limit state function, which will be subsequently used in the simulation framework. This will save substantial computational time and make the approach computationally efficient. Uncertainty in wind speed, wind load related parameters, and resistance-related parameters is considered. The results by the full simulation approach, conventional metamodelling approach and proposed adaptive metamodelling approach will be compared. Effect of disregarding temperature in wind fragility analysis will be highlighted.

Keywords: adaptive metamodelling technique, concrete chimney, fragility analysis, stochastic extreme wind load, temperature effect

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Authors: Nilson Barbieri, Bruno Matos Martins, Gabriel de Sant'Anna Vitor Barbieri

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In more complex systems, such as automotive gearbox, a rigorous treatment of the data is necessary because there are several moving parts (gears, bearings, shafts, etc.), and in this way, there are several possible sources of errors and also noise. The basic objective of this work is the detection of damage in automotive gearbox. The detection methods used are the wavelet method, the bispectrum; advanced filtering techniques (selective filtering) of vibrational signals and mathematical morphology. Gearbox vibration tests were performed (gearboxes in good condition and with defects) of a production line of a large vehicle assembler. The vibration signals are obtained using five accelerometers in different positions of the sample. The results obtained using the kurtosis, bispectrum, wavelet and mathematical morphology showed that it is possible to identify the existence of defects in automotive gearboxes.

Keywords: automotive gearbox, mathematical morphology, wavelet, bispectrum

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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Authors: Dimitriya A. Mihaylova, Zlatka V. Valkova-Jarvis, Georgi L. Iliev

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One possible approach for maintaining the security of communication systems relies on Physical Layer Security mechanisms. However, in wireless time division duplex systems, where uplink and downlink channels are reciprocal, the channel estimate procedure is exposed to attacks known as pilot contamination, with the aim of having an enhanced data signal sent to the malicious user. The Shifted 2-N-PSK method involves two random legitimate pilots in the training phase, each of which belongs to a constellation, shifted from the original N-PSK symbols by certain degrees. In this paper, legitimate pilots’ offset values and their influence on the detection capabilities of the Shifted 2-N-PSK method are investigated. As the implementation of the technique depends on the relation between the shift angles rather than their specific values, the optimal interconnection between the two legitimate constellations is investigated. The results show that no regularity exists in the relation between the pilot contamination attacks (PCA) detection probability and the choice of offset values. Therefore, an adversary who aims to obtain the exact offset values can only employ a brute-force attack but the large number of possible combinations for the shifted constellations makes such a type of attack difficult to successfully mount. For this reason, the number of optimal shift value pairs is also studied for both 100% and 98% probabilities of detecting pilot contamination attacks. Although the Shifted 2-N-PSK method has been broadly studied in different signal-to-noise ratio scenarios, in multi-cell systems the interference from the signals in other cells should be also taken into account. Therefore, the inter-cell interference impact on the performance of the method is investigated by means of a large number of simulations. The results show that the detection probability of the Shifted 2-N-PSK decreases inversely to the signal-to-interference-plus-noise ratio.

Keywords: channel estimation, inter-cell interference, pilot contamination attacks, wireless communications

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Authors: Shalini Menon, K. Girish Kumar

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Norepinephrine (NE) is one of the naturally occurring catecholamines which act both as a neurotransmitter and a hormone. Catecholamine levels are used for the diagnosis and regulation of phaeochromocytoma, a neuroendocrine tumor of the adrenal medulla. The development of simple, rapid and cost-effective sensors for NE still remains a great challenge. Herein, a dual-channel sensor has been developed for the determination of NE. A mixture of AgNO₃, NaOH, NH₃.H₂O and cetrimonium bromide in appropriate concentrations was taken as the working solution. To the thoroughly vortexed mixture, an appropriate volume of NE solution was added. After a particular time, the fluorescence and absorbance were measured. Fluorescence measurements were made by exciting at a wavelength of 400 nm. A dual-channel optical sensor has been developed for the colorimetric as well as the fluorimetric determination of NE. Metal enhanced fluorescence property of nanoparticles forms the basis of the fluorimetric detection of this assay, whereas the appearance of brown color in the presence of NE leads to colorimetric detection. Wide linear ranges and sub-micromolar detection limits were obtained using both the techniques. Moreover, the colorimetric approach was applied for the determination of NE in synthetic blood serum and the results obtained were compared with the classic high-performance liquid chromatography (HPLC) method. Recoveries between 97% and 104% were obtained using the proposed method. Based on five replicate measurements, relative standard deviation (RSD) for NE determination in the examined synthetic blood serum was found to be 2.3%. This indicates the reliability of the proposed sensor for real sample analysis.

Keywords: norepinephrine, colorimetry, fluorescence, silver nanoparticles

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Authors: Shirin Jalili, Ramin Ghasemi

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Lumbar microdiscectomy is the most commonly performed spinal surgery strategy; it is regularly performed to lighten the indications and signs of sciatica within the lower back and leg caused by a lumbar disc herniation. This surgery aims to progress leg pain, reestablish function, and enable a return to ordinary day-by-day exercises. Rates of lumbar disc surgery show critical geographic varieties recommending changing treatment criteria among working specialists. Few population-based considers have investigated the hazard of reoperation after disc surgery, and regional or inter specialty varieties within the reoperations are obscure. The conventional approach to recouping from lumbar microdiscectomy has been to restrain bending, lifting, or turning for a least 6 weeks in arrange to anticipate the disc from herniating once more. Traditionally, patients were exhorted to limit post-operative action, which was accepted to decrease the hazard of disc herniation and progressive insecurity. In modern hone, numerous specialists don't limit understanding of postoperative action due to the discernment this practice is pointless. There's a need of thinks about highlighting the result by distinctive scores or parameters after surgery for repetitive circle herniations of the lumbar spine at the starting herniation location. This study will evaluate the quality of life after surgical treatment of recurrent herniations with distinctive standardized approved result instruments.

Keywords: post-operative activity, disc, quality of life, treatment, movements

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Authors: Shirin jalili, Hadi Shirzad, Samaneh Nabavi, Somayeh Khanjani

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Biosensors in forensic analysis are ideal biological tools that can be used for rapid and sensitive initial screening and testing to detect of suspicious components like biological and chemical agent in crime scenes. The wide use of different biomolecules such as proteins, nucleic acids, microorganisms, antibodies and enzymes makes it possible. These biosensors have great advantages such as rapidity, little sample manipulation and high sensitivity, also Because of their stability, specificity and low cost they have become a very important tool to Forensic analysis and detection of crime. In crime scenes different substances such as rape samples, Semen, saliva fingerprints and blood samples, act as a detecting elements for biosensors. On the other hand, successful fluid recovery via biosensor has the propensity to yield a highly valuable source of genetic material, which is important in finding the suspect. Although current biological fluid testing techniques are impaired for identification of body fluids. But these methods have disadvantages. For example if they are to be used simultaneously, Often give false positive result. These limitations can negatively result the output of a case through missed or misinterpreted evidence. The use of biosensor enable criminal researchers the highly sensitive and non-destructive detection of biological fluid through interaction with several fluid-endogenous and other biological and chemical contamination at the crime scene. For this reason, using of the biosensors for detecting the biological fluid found at the crime scenes which play an important role in identifying the suspect and solving the criminal.

Keywords: biosensors, forensic analysis, biological fluid, crime detection

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Authors: Afnan Al-Romi, Iman Al-Momani

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The urge of applying the Software Engineering (SE) processes is both of vital importance and a key feature in critical, complex large-scale systems, for example, safety systems, security service systems, and network systems. Inevitably, associated with this are risks, such as system vulnerabilities and security threats. The probability of those risks increases in unsecured environments, such as wireless networks in general and in Wireless Sensor Networks (WSNs) in particular. WSN is a self-organizing network of sensor nodes connected by wireless links. WSNs consist of hundreds to thousands of low-power, low-cost, multi-function sensor nodes that are small in size and communicate over short-ranges. The distribution of sensor nodes in an open environment that could be unattended in addition to the resource constraints in terms of processing, storage and power, make such networks in stringent limitations such as lifetime (i.e. period of operation) and security. The importance of WSN applications that could be found in many militaries and civilian aspects has drawn the attention of many researchers to consider its security. To address this important issue and overcome one of the main challenges of WSNs, security solution systems have been developed by researchers. Those solutions are software-based network Intrusion Detection Systems (IDSs). However, it has been witnessed, that those developed IDSs are neither secure enough nor accurate to detect all malicious behaviours of attacks. Thus, the problem is the lack of coverage of all malicious behaviours in proposed IDSs, leading to unpleasant results, such as delays in the detection process, low detection accuracy, or even worse, leading to detection failure, as illustrated in the previous studies. Also, another problem is energy consumption in WSNs caused by IDS. So, in other words, not all requirements are implemented then traced. Moreover, neither all requirements are identified nor satisfied, as for some requirements have been compromised. The drawbacks in the current IDS are due to not following structured software development processes by researches and developers when developing IDS. Consequently, they resulted in inadequate requirement management, process, validation, and verification of requirements quality. Unfortunately, WSN and SE research communities have been mostly impermeable to each other. Integrating SE and WSNs is a real subject that will be expanded as technology evolves and spreads in industrial applications. Therefore, this paper will study the importance of Requirement Engineering when developing IDSs. Also, it will study a set of existed IDSs and illustrate the absence of Requirement Engineering and its effect. Then conclusions are drawn in regard of applying requirement engineering to systems to deliver the required functionalities, with respect to operational constraints, within an acceptable level of performance, accuracy and reliability.

Keywords: software engineering, requirement engineering, Intrusion Detection System, IDS, Wireless Sensor Networks, WSN

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Authors: Kritika Kulhari, Aparna Sahu

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Test anxiety results from concerns about failure in examinations or evaluative situations. Attentional biases are known to pronounce the symptomatic expression of test anxiety. In recent times, the inattentional blindness (IB) paradigm has shown promise as an attention bias modification treatment (ABMT) for anxiety by overcoming practice and expectancy effects which preexisting paradigms fail to counter. The IB paradigm assesses the inability of an individual to attend to a stimulus that appears suddenly while indulging in a perceptual discrimination task. The present study incorporated an IB task with three critical items (book, face, and triangle) appearing randomly in the perceptual discrimination task. Attentional biases were assessed as detection and identification of the critical item. The sample (N = 50) consisted of low test anxiety (LTA) and high test anxiety (HTA) groups based on the reactions to tests scale scores. Test threat manipulation was done with pre- and post-test assessment of test anxiety using the State Test Anxiety Inventory. A mixed factorial design with gender, test anxiety, presence or absence of test threat, and critical items was conducted to assess their effects on attentional biases. Results showed only a significant main effect for test anxiety on detection with higher accuracy of detection of the critical item for the LTA group. The study presents promising results in the realm of ABMT for test anxiety.

Keywords: attentional bias, attentional bias modification treatment, inattentional blindness, test anxiety

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Authors: Ciprian Briciu-Burghina, Brendan Heery, Dermot Brabazon, Fiona Regan

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Good quality bathing water is a highly desirable natural resource which can provide major economic, social, and environmental benefits. Both in Ireland and Europe, such water bodies are managed under the European Directive for the management of bathing water quality (BWD). The BWD aims mainly: (i) to improve health protection for bathers by introducing stricter standards for faecal pollution assessment (E. coli, enterococci), (ii) to establish a more pro-active approach to the assessment of possible pollution risks and the management of bathing waters, and (iii) to increase public involvement and dissemination of information to the general public. Standard methods for E. coli and enterococci quantification rely on cultivation of the target organism which requires long incubation periods (from 18h to a few days). This is not ideal when immediate action is required for risk mitigation. Municipalities that oversee the bathing water quality and deploy appropriate signage have to wait for laboratory results. During this time, bathers can be exposed to pollution events and health risks. Although forecasting tools exist, they are site specific and as consequence extensive historical data is required to be effective. Another approach for early detection of faecal pollution is the use of marker enzymes. β-glucuronidase (GUS) is a widely accepted biomarker for E. coli detection in microbiological water quality control. GUS assay is particularly attractive as they are rapid, less than 4 h, easy to perform and they do not require specialised training. A method for on-site detection of GUS from environmental samples in less than 75 min was previously demonstrated. In this study, the capability of ColiSense as an early warning system for faecal pollution in freshwater is assessed. The system successfully detected GUS activity in all of the 45 freshwater samples tested. GUS activity was found to correlate linearly with E. coli (r2=0.53, N=45, p < 0.001) and enterococci (r2=0.66, N=45, p < 0.001) Although GUS is a marker for E. coli, a better correlation was obtained for enterococci. For this study water samples were collected from 5 rivers in the Dublin area over 1 month. This suggests a high diversity of pollution sources (agricultural, industrial, etc) as well as point and diffuse pollution sources were captured in the sample size. Such variety in the source of E. coli can account for different GUS activities/culturable cell and different ratios of viable but not culturable to viable culturable bacteria. A previously developed protocol for the recovery and detection of E. coli was coupled with a miniaturised fluorometer (ColiSense) and the system was assessed for the rapid detection FIB in freshwater samples. Further work will be carried out to evaluate the system’s performance on seawater samples.

Keywords: faecal pollution, β-glucuronidase (GUS), bathing water, E. coli

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Authors: Reem M. Altuwirqi, Mohja S. Summan, Entesar A. Ganash, Safia H. Hamidalddin, Tamer E. Youssef, Mohammed A. Gondal

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Laser-Induced Breakdown Spectroscopy (LIBS) technique using 1064 nm Nd: YAG laser was optimized and applied for investigating the existence of radioactive elements (uranium) in twenty-six different ceramic tiles. These tiles were collected from the local Saudi market. Qualitative and quantitative analysis for trace radioactive elements like uranium in these samples was achieved using LIBS. The plasma parameters such as temperature and electron density were calculated to confirm that the plasma generated by the tile samples under laser irradiation can be related to analyte concentrations. In order to perform a quantitative analysis, calibration curves were constructed for two uranium lines (U II (424.166 nm) and U II (424.437 nm)). The Uranium activity concentration in Bq/kg for each sample was measured. Cross-validation of LIBS results with a conventional technique such as Gamma-Ray spectroscopy was also carried out for five ceramic samples. The results show that the LIBS method is an effective way of determining radioactive elements such as uranium in ceramic tiles. Moreover, the uranium concentrations of the investigated samples were below the permissible safe limit for building materials in the majority of samples. Such LIBS system could be applied to determine the presence of natural radioactive elements in ceramic tiles and their radioactivity level rapidly to ensure that they are under the safe allowed limit.

Keywords: laser-induced breakdown spectroscopy, gamma-ray spectroscopy, natural radioactivity, uranium, ceramic tiles

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Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

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The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

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Authors: Vareesha Masood, Ammara Gul, Nabeeha Areej, Muhammad Asif Masood, Hamna Imran

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The universal use of PDF files has prompted hackers to use them for malicious intent by hiding malicious codes in their victim’s PDF machines. Machine learning has proven to be the most efficient in identifying benign files and detecting files with PDF malware. This paper has proposed an approach using a decision tree classifier with parameters. A modern, inclusive dataset CIC-Evasive-PDFMal2022, produced by Lockheed Martin’s Cyber Security wing is used. It is one of the most reliable datasets to use in this field. We designed a PDF malware detection system that achieved 99.2%. Comparing the suggested model to other cutting-edge models in the same study field, it has a great performance in detecting PDF malware. Accordingly, we provide the fastest, most reliable, and most efficient PDF Malware detection approach in this paper.

Keywords: PDF, PDF malware, decision tree classifier, random forest classifier

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Authors: Hwang Ahreum, Kang Taejoon, Kim Bongsoo

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Nanosensors for high sensitive detection of diseases have been widely studied to improve the quality of life. Here, we suggest robust nano-plasmonic diagnostic sensor using cysteine tagged protein G (Cys3-protein G) and ultraflat, ultraclean and single-crystalline Au nanoplates. Protein G formed on an ultraflat Au surface provides ideal background for dense and uniform immobilization of antibodies. The Au is highly stable in diverse biochemical environment and can immobilize antibodies easily through Au-S bonding, having been widely used for various biosensing applications. Especially, atomically smooth single-crystalline Au nanomaterials synthesized using chemical vapor transport (CVT) method are very suitable to fabricate reproducible sensitive sensors. As the C-reactive protein (CRP) is a nonspecific biomarker of inflammation and infection, it can be used as a predictive or prognostic marker for various cardiovascular diseases. Cys3-protein G immobilized uniformly on the Au nanoplate enable CRP antibody (anti-CRP) to be ordered in a correct orientation, making their binding capacity be maximized for CRP detection. Immobilization condition for the Cys3-protein G and anti-CRP on the Au nanoplate is optimized visually by AFM analysis. Au nanoparticle - Au nanoplate (NPs-on-Au nanoplate) assembly fabricated from sandwich immunoassay for CRP can reduce zero-signal extremely caused by nonspecific bindings, providing a distinct surface-enhanced Raman scattering (SERS) enhancement still in 10-18 M of CRP concentration. Moreover, the NP-on-Au nanoplate sensor shows an excellent selectivity against non-target proteins with high concentration. In addition, comparing with control experiments employing a Au film fabricated by e-beam assisted deposition and linker molecule, we validate clearly contribution of the Au nanoplate for the attomolar sensitive detection of CRP. We expect that the devised platform employing the complex of single-crystalline Au nanoplates and Cys3-protein G can be applied for detection of many other cancer biomarkers.

Keywords: Au nanoplate, biomarker, diagnostic sensor, protein G, SERS

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Authors: Dongwan Kang, Joohyung Oh, Chaetae Im

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Advancement of communication technologies and smart devices in the recent times is leading to changes into the integrated wired and wireless communication environments. Since early days, businesses had started introducing environments for mobile device application to their operations in order to improve productivity (efficiency) and the closed corporate environment gradually shifted to an open structure. Recently, individual user's interest in working environment using mobile devices has increased and a new corporate working environment under the concept of BYOD is drawing attention. BYOD (bring your own device) is a concept where individuals bring in and use their own devices in business activities. Through BYOD, businesses can anticipate improved productivity (efficiency) and also a reduction in the cost of purchasing devices. However, as a result of security threats caused by frequent loss and theft of personal devices and corporate data leaks due to low security, companies are reluctant about adopting BYOD system. In addition, without considerations to diverse devices and connection environments, there are limitations in detecting abnormal behaviors such as information leaks which use the existing network-based security equipment. This study suggests a method to detect abnormal behaviors according to individual behavioral patterns, rather than the existing signature-based malicious behavior detection and discusses applications of this method in BYOD environment.

Keywords: BYOD, security, anomaly behavior detection, security equipment, communication technologies

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Authors: Mohamed Fadzlee Sulaiman, Zainurrasyid Abdullah, Mohd Zabri Adil Talib, Aswami Fadillah Mohd Ariffin

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In common digital forensics cases, investigation may rely on the analysis conducted on specific and relevant exhibits involved. Usually the investigation officer may define and advise digital forensic analyst about the goals and objectives to be achieved in reconstructing the trail of evidence while maintaining the specific scope of investigation. With the technology growth, people are starting to realize the importance of cyber security to their organization and this new perspective creates awareness that digital forensics auditing must come in place in order to measure possible threat or attack to their cyber-infrastructure. Instead of performing investigation on incident basis, auditing may broaden the scope of investigation to the level of anomaly detection in daily operation of organization’s cyber space. While handling a huge amount of data such as log files, performing digital forensics audit for large organization proven to be onerous task for the analyst either to analyze the huge files or to translate the findings in a way where the stakeholder can clearly understand. Data visualization can be emphasized in conducting digital forensic audit and investigation to resolve both needs. This study will identify the important factors that should be considered to perform data visualization techniques in order to detect anomaly that meet the digital forensic audit and investigation objectives.

Keywords: digital forensic, data visualization, anomaly detection , log analysis, forensic audit, visualization techniques

Procedia PDF Downloads 287

Authors: Kevin Wang, Jian Ge, Yinan Zhao, Kevin Willis

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Kepler has discovered over 4000 exoplanets and candidates. However, current transit planet detection techniques based on the wavelet analysis and the Box Least Squares (BLS) algorithm have limited sensitivity in detecting minor planets with a low signal-to-noise ratio (SNR) and long periods with only 3-4 repeated signals over the mission lifetime of 4 years. This paper presents a novel precise-period transit signal detection methodology based on a new Graphics Processing Unit (GPU) Fast Folding algorithm in conjunction with a Convolutional Neural Network (CNN) to detect low SNR and/or long-period transit planet signals. A comparison with BLS is conducted on both simulated light curves and real data, demonstrating that the new method has higher speed, sensitivity, and reliability. For instance, the new system can detect transits with SNR as low as three while the performance of BLS drops off quickly around SNR of 7. Meanwhile, the GPU Fast Folding method folds light curves 25 times faster than BLS, a significant gain that allows exoplanet detection to occur at unprecedented period precision. This new method has been tested with all known transit signals with 100% confirmation. In addition, this new method has been successfully applied to the Kepler of Interest (KOI) data and identified a few new Earth-sized Ultra-short period (USP) exoplanet candidates and habitable planet candidates. The results highlight the promise for GPU Fast Folding as a replacement to the traditional BLS algorithm for finding small and/or long-period habitable and Earth-sized planet candidates in-transit data taken with Kepler and other space transit missions such as TESS(Transiting Exoplanet Survey Satellite) and PLATO(PLAnetary Transits and Oscillations of stars).

Keywords: algorithms, astronomy data analysis, deep learning, exoplanet detection methods, small planets, habitable planets, transit photometry

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Authors: Benkouiten Imene, Chabli Ouerdia, Boutoutaou Hamid, Kadri Nesrine, Bouledroua Omar

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Algeria is actively enhancing gas productivity by augmenting the supply flow. However, this effort has led to increased internal pressure, posing a potential risk to the pipeline's integrity, particularly in the presence of corrosion defects. Sonatrach relies on a vast network of pipelines spanning 24,000 kilometers for the transportation of gas and oil. The aging of these pipelines raises the likelihood of corrosion both internally and externally, heightening the risk of ruptures. To address this issue, a comprehensive inspection is imperative, utilizing specialized scraping tools. These advanced tools furnish a detailed assessment of all pipeline defects. It is essential to recalculate the pressure parameters to safeguard the corroded pipeline's integrity while ensuring the continuity of production. In this context, Sonatrach employs symbolic pressure limit calculations, such as ASME B31G (2009) and the modified ASME B31G (2012). The aim of this study is to perform a comparative analysis of various limit pressure calculation methods documented in the literature, namely DNV RP F-101, SHELL, P-CORRC, NETTO, and CSA Z662. This comparative assessment will be based on a dataset comprising 329 burst tests published in the literature. Ultimately, we intend to introduce a novel approach grounded in the finite element method, employing ANSYS software.

Keywords: pipeline burst pressure, burst test, corrosion defect, corroded pipeline, finite element method

Procedia PDF Downloads 58

Authors: Shantha Kumari Muniyandi, Johan Sohaili, Siti Suhaila Mohamad

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The aim of this study was to investigate the suitability of reusing nonmetallic printed circuit boards (PCBs) waste in recycled HDPE (rHDPE) in terms of toxicity and mechanical properties. A series of X-ray Fluorescence Spectrometry (XRF) analysis tests have been conducted on raw nonmetallic PCBs waste to determine the chemical compositions. It can be seen that the nonmetallic PCBs approximately 72% of glass fiber reinforced epoxy resin materials such as SiO2, Al2O3, CaO, MgO, BaO, Na2O, and SrO, 9.4% of metallic materials such as CuO, SnO2, and Fe2O3, and 6.53% of Br. Total Threshold Limit Concentration (TTLC) and Toxicity Characteristic Leaching Procedure (TCLP) tests also have been done to study the toxicity characteristics of raw nonmetallic PCB powders, rHDPE/PCB and virgin HDPE for comparison purposes. For both of the testing, Cu was identified as the highest metal element contained in raw PCBs with the concentration of 905 mg/kg and 59.09 mg/L for TTLC and TCLP, respectively. However, once the nonmetallic PCB was filled in rHDPE composites, the concentrations of Cu were reduced to 134 mg/kg for TTLC and to 3 mg/L for TCLP testing. For mechanical properties testing, incorporation of 40 wt% nonmetallic PCB into rHDPE has increased the flexural modulus and flexural strength by 140% and 36%, respectively. While, Izod Impact strength decreased steadily with incorporation of 10 – 40 wt% nonmetallic PCBs.

Keywords: nonmetallic printed circuit board, recycled HDPE, composites, mechanical properties, total threshold limit concentration, toxicity characteristic leaching procedure

Procedia PDF Downloads 338

Authors: Abanob Nady Wasef Moawed

Abstract:

In more complicated systems, inclusive of automotive gearboxes, a rigorous remedy of the data is essential because there are several transferring elements (gears, bearings, shafts, and many others.), and in this way, there are numerous viable sources of mistakes and also noise. The fundamental goal of these elements are the detection of damage in car gearbox. The detection strategies used are the wavelet technique, the bispectrum, advanced filtering techniques (selective filtering) of vibrational alerts and mathematical morphology. Gearbox vibration assessments were achieved (gearboxes in proper circumstance and with defects) of a manufacturing line of a huge car assembler. The vibration indicators have acquired the use of five accelerometers in distinct positions of the sample. The effects acquired using the kurtosis, bispectrum, wavelet and mathematical morphology confirmed that it's far possible to identify the lifestyles of defects in automobile gearboxes.

Keywords: 3D-shaped electronics, electronic components, thermoforming, component positioningautomotive gearbox, mathematical morphology, wavelet, bispectrum

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Authors: Mehmet Hakan Karaata, Ali Hamdan, Omer Yusuf Adam Mohamed

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Consider a distributed system that delivers messages from a process to another. Such a system is often required to deliver each message to its destination regardless of whether or not the system components experience arbitrary forms of faults. In addition, each message received by the destination must be a message sent by a system process. In this paper, we first identify the necessary and sufficient conditions to detect some restricted form of Byzantine faults referred to as modifying Byzantine faults. An observable form of a Byzantine fault whose effect is limited to the modification of a message metadata or content, timing and omission faults, and message replay is referred to as a modifying Byzantine fault. We then present a distributed protocol to detect modifying Byzantine faults using optimal number of messages over node-disjoint paths.

Keywords: Byzantine faults, distributed systems, fault detection, network protocols, node-disjoint paths

Procedia PDF Downloads 447

Authors: Goutam Kumar Ghorai, Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, G. Sarkar, Ashis K. Dhara

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Diabetes mellitus is one of the most common chronic diseases in all countries and continues to increase in numbers significantly. Diabetic retinopathy (DR) is damage to the retina that occurs with long-term diabetes. DR is a major cause of blindness in the Indian population. Therefore, its early diagnosis is of utmost importance towards preventing progression towards imminent irreversible loss of vision, particularly in the huge population across rural India. The barriers to eye examination of all diabetic patients are socioeconomic factors, lack of referrals, poor access to the healthcare system, lack of knowledge, insufficient number of ophthalmologists, and lack of networking between physicians, diabetologists and ophthalmologists. A few diabetic patients often visit a healthcare facility for their general checkup, but their eye condition remains largely undetected until the patient is symptomatic. This work aims to focus on the design and development of a fully automated intelligent decision system for screening retinal fundus images towards detection of the pathophysiology caused by microaneurysm in the early stage of the diseases. Automated detection of microaneurysm is a challenging problem due to the variation in color and the variation introduced by the field of view, inhomogeneous illumination, and pathological abnormalities. We have developed aconvolutional neural network for efficient detection of microaneurysm. A loss function is also developed to handle severe class imbalance due to very small size of microaneurysms compared to background. The network is able to locate the salient region containing microaneurysms in case of noisy images captured by non-mydriatic cameras. The ground truth of microaneurysms is created by expert ophthalmologists for MESSIDOR database as well as private database, collected from Indian patients. The network is trained from scratch using the fundus images of MESSIDOR database. The proposed method is evaluated on DIARETDB1 and the private database. The method is successful in detection of microaneurysms for dilated and non-dilated types of fundus images acquired from different medical centres. The proposed algorithm could be used for development of AI based affordable and accessible system, to provide service at grass root-level primary healthcare units spread across the country to cater to the need of the rural people unaware of the severe impact of DR.

Keywords: retinal fundus image, deep convolutional neural network, early detection of microaneurysms, screening of diabetic retinopathy

Procedia PDF Downloads 141