Search results for: false alarms

Authors: Jean Berger, Mohamed Barkaoui

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Discrete search path planning in time-constrained uncertain environment relying upon imperfect sensors is known to be hard, and current problem-solving techniques proposed so far to compute near real-time efficient path plans are mainly bounded to provide a few move solutions. A new information-theoretic –based open-loop decision model explicitly incorporating false alarm sensor readings, to solve a single agent military logistics search-and-delivery path planning problem with anticipated feedback is presented. The decision model consists in minimizing expected entropy considering anticipated possible observation outcomes over a given time horizon. The model captures uncertainty associated with observation events for all possible scenarios. Entropy represents a measure of uncertainty about the searched target location. Feedback information resulting from possible sensor observations outcomes along the projected path plan is exploited to update anticipated unit target occupancy beliefs. For the first time, a compact belief update formulation is generalized to explicitly include false positive observation events that may occur during plan execution. A novel genetic algorithm is then proposed to efficiently solve search path planning, providing near-optimal solutions for practical realistic problem instances. Given the run-time performance of the algorithm, natural extension to a closed-loop environment to progressively integrate real visit outcomes on a rolling time horizon can be easily envisioned. Computational results show the value of the approach in comparison to alternate heuristics.

Keywords: search path planning, false alarm, search-and-delivery, entropy, genetic algorithm

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Authors: Dylan Elliott, Katya Pertsova

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Preposition errors are some of the most common errors created by L2 speakers. In addition, improving error correction and detection methods remains an open issue in the realm of Natural Language Processing (NLP). This research investigates whether the bidirectional encoder representations from the transformers model (BERT) have the potential to correct preposition errors accurately enough to be useful in error correction software. This research finds that BERT performs strongly when the scope of its error correction is limited to preposition choice. The researchers used an open-source BERT model and over three hundred thousand edited sentences from Wikipedia, tagged for part of speech, where only a preposition edit had occurred. To test BERT’s ability to detect errors, a technique known as multi-level masking was used to generate suggestions based on sentence context for every prepositional environment in the test data. These suggestions were compared with the original errors in the data and their known corrections to evaluate BERT’s performance. The suggestions were further analyzed to determine if BERT more often agreed with the judgements of the Wikipedia editors. Both the untrained and fined-tuned models were compared. Finetuning led to a greater rate of error-detection which significantly improved recall, but lowered precision due to an increase in false positives or falsely flagged errors. However, in most cases, these false positives were not errors in preposition usage but merely cases where more than one preposition was possible. Furthermore, when BERT correctly identified an error, the model largely agreed with the Wikipedia editors, suggesting that BERT’s ability to detect misused prepositions is better than previously believed. To evaluate to what extent BERT’s false positives were grammatical suggestions, we plan to do a further crowd-sourcing study to test the grammaticality of BERT’s suggested sentence corrections against native speakers’ judgments.

Keywords: BERT, grammatical error correction, preposition error detection, prepositions

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Authors: Marzieh Karimihaghighi, Carlos Castillo

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This work studies how Machine Learning (ML) may be used to increase the effectiveness of a criminal recidivism risk assessment tool, RisCanvi. The two key dimensions of this analysis are predictive accuracy and algorithmic fairness. ML-based prediction models obtained in this study are more accurate at predicting criminal recidivism than the manually-created formula used in RisCanvi, achieving an AUC of 0.76 and 0.73 in predicting violent and general recidivism respectively. However, the improvements are small, and it is noticed that algorithmic discrimination can easily be introduced between groups such as national vs foreigner, or young vs old. It is described how effectiveness and algorithmic fairness objectives can be balanced, applying a method in which a single error disparity in terms of generalized false positive rate is minimized, while calibration is maintained across groups. Obtained results show that this bias mitigation procedure can substantially reduce generalized false positive rate disparities across multiple groups. Based on these results, it is proposed that ML-based criminal recidivism risk prediction should not be introduced without applying algorithmic bias mitigation procedures.

Keywords: algorithmic fairness, criminal risk assessment, equalized odds, recidivism

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Authors: Sidharth Talan, Devendra Kumar Yadav, Yuvraj Singh Rajput, Subhajit Bhattacharjee

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Mining industry is known for its appetite to spend sizeable capital on mine equipment. However, in the current scenario, the mining industry is challenged by daunting factors of non-uniform geological conditions, uneven ore grade, uncontrollable and volatile mineral commodity prices and the ever increasing quest to optimize the capital and operational costs. Thus, the role of equipment reliability and maintenance planning inherits a significant role in augmenting the equipment availability for the operation and in turn boosting the mine productivity. This paper presents the Risk Based Maintenance (RBM) planning conducted on mine loading equipment namely Load Haul Dumpers (LHDs) at Vedanta Resources Ltd subsidiary Hindustan Zinc Limited operated Sindesar Khurd Mines, an underground zinc and lead mine situated in Dariba, Rajasthan, India. The mining equipment at the location is maintained by the Original Equipment Manufacturers (OEMs) namely Sandvik and Atlas Copco, who carry out the maintenance and inspection operations for the equipment. Based on the downtime data extracted for the equipment fleet over the period of 6 months spanning from 1^st January 2017 until 30^th June 2017, it was revealed that significant contribution of three downtime issues related to namely Engine, Hydraulics, and Transmission to be common among all the loading equipment fleet and substantiated by Pareto Analysis. Further scrutiny through Bubble Matrix Analysis of the given factors revealed the major influence of selective factors namely Overheating, No Load Taken (NTL) issues, Gear Changing issues and Hose Puncture and leakage issues. Utilizing the equipment wise analysis of all the downtime factors obtained, spares consumed, and the alarm logs extracted from the machines, technical design changes in the equipment and pre shift critical alarms checklist were proposed for the equipment maintenance. The given analysis is beneficial to allow OEMs or mine management to focus on the critical issues hampering the reliability of mine equipment and design necessary maintenance strategies to mitigate them.

Keywords: bubble matrix analysis, LHDs, OEMs, Pareto chart analysis, spares consumption matrix, critical alarms checklist

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Authors: Gautam Sharda

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The concept of right speech is the third stage of the noble eightfold path as prescribed by the Buddha and followed by millions of practicing Buddhists. The Buddha lays a lot of importance on the notion of right speech (Samma Vacca). In the Angutara Nikaya, the Buddha mentioned what constitutes right speech, which is basically four kinds of abstentions; namely abstaining from false speech, abstaining from slanderous speech, abstaining from harsh or hateful speech and abstaining from idle chatter. The Buddha gives reasons in support of his view as to why abstaining from these four kinds of speeches is favourable not only for maintaining the peace and equanimity within an individual but also within a society. It is a known fact that when we say something harsh or slanderous to others, it eventually affects our individual peace of mind too. We also know about the many examples of hate speeches which have led to senseless cases of violence and which are well documented within our country and the world. Also, indulging in false speech is not a healthy sign for individuals within a group as this kind of a social group which is based on falsities and lies cannot really survive for long and will eventually lead to chaos. Buddha also told us to refrain from idle chatter or gossip as generally we have seen that idle chatter or gossip does more harm than any good to the individual and the society. Hence, if most of us actually inculcate this third stage (namely, right speech) of the noble eightfold path of the Buddha in our daily life, it would be highly beneficial both for the individual and for the harmony of the society.

Keywords: Buddhism, speech, individual, society

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Authors: Samra Naz, Aneeqa Ahmed, Qurat-ul-ain Mubarak, Irum Nausheen

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Driver safety systems protect driver from accidents by sensing signs of drowsiness. The paper proposes a technique which can detect the signs of drowsiness and make corresponding decisions to make the driver alert. This paper presents a technique in which the driver will be continuously monitored by a camera and his eyes, head and mouth movements will be observed. If the drowsiness signs are detected on the basis of these three movements under the predefined criteria, driver will be declared as sleepy and he will get alert with the help of alarms. Three robust techniques of drowsiness detection are combined together to make a robust system that can prevent form accident.

Keywords: drowsiness, eye closure, fatigue detection, yawn detection

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Authors: Noor Azwa Azreen Binti Abd. Aziz, Muhamad Zaim Bin Mohd Rozi

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Moving towards the 4th Industrial Revolution, artificial intelligence (AI) is now more popular than ever. This subject is gaining significance every day and is continually expanding, often merging with other fields. Instead of merely being passive observers, there are benefits to understanding modern technology by delving into its inner workings. However, in a world teeming with digital information, the impact of AI on the spread of disinformation has garnered significant attention. The dissemination of inaccurate or misleading information is referred to as misinformation, posing a serious threat to democratic society, public debate, and individual decision-making. This article delves deep into the connection between AI and the dissemination of false information, exploring its potential, risks, and ethical issues as AI technology advances. The rise of AI has ushered in a new era in the dissemination of misinformation as AI-driven technologies are increasingly responsible for curating, recommending, and amplifying information on online platforms. While AI holds the potential to enhance the detection and mitigation of misinformation through natural language processing and machine learning, it also raises concerns about the amplification and propagation of false information. AI-powered deepfake technology, for instance, can generate hyper-realistic videos and audio recordings, making it increasingly challenging to discern fact from fiction.

Keywords: artificial intelligence, digital information, disinformation, ethical issues, misinformation

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Authors: Nantakrit Yodpijit, Teppakorn Sittiwanchai

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The number of older adults is rising rapidly. The world’s population becomes aging. Falls is one of common and major health problems in the elderly. Falls may lead to acute and chronic injuries and deaths. The fall-prone individuals are at greater risk for decreased quality of life, lowered productivity and poverty, social problems, and additional health problems. A number of studies on falls prevention using fall detection system have been conducted. Many available technologies for fall detection system are laboratory-based and can incur substantial costs for falls prevention. The utilization of alternative technologies can potentially reduce costs. This paper presents the new design and development of a wearable-based fall detection system using an Accelerometer and Gyroscope as motion sensors for the detection of body orientation and movement. Algorithms are developed to differentiate between Activities of Daily Living (ADL) and falls by comparing Threshold-based values with Artificial Neural Networks (ANN). Results indicate the possibility of using the new threshold-based method with neural network algorithm to reduce the number of false positive (false alarm) and improve the accuracy of fall detection system.

Keywords: aging, algorithm, artificial neural networks (ANN), fall detection system, motion sensorsthreshold

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Authors: Lamis Naddaf, Yuval Tabach

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In this research, we identified the missense genetic variants that have the potential to enhance resistance against cancer. Such field has not been widely explored, as researchers tend to investigate mutations that cause diseases, in response to the suffering of patients, rather than those mutations that protect from them. In conjunction with the genomic revolution, and the advances in genetic engineering and synthetic biology, identifying the protective variants will increase the power of genotype-phenotype predictions and can have significant implications on improved risk estimation, diagnostics, prognosis and even for personalized therapy and drug discovery. To approach our goal, we systematically investigated the sites of the coding genomes and picked up the alleles that showed a correlation with the species’ cancer resistance. We predicted 250 protecting variants (PVs) with a 0.01 false discovery rate and more than 20 thousand PVs with a 0.25 false discovery rate. Cancer resistance in Mammals and reptiles was significantly predicted by the number of PVs a species has. Moreover, Genes enriched with the protecting variants are enriched in pathways relevant to tumor suppression like pathways of Hedgehog signaling and silencing, which its improper activation is associated with the most common form of cancer malignancy. We also showed that the PVs are more abundant in healthy people compared to cancer patients within different human races.

Keywords: comparative genomics, machine learning, cancer resistance, cancer-protecting alleles

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Authors: Htay Htay Yi, Zin May Aye

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Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: false negative rate, intrusion detection system, machine learning methods, performance

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Authors: Mavis Ofosuah Asante, Abena Abokoma Asemanyi, Belinda Osei-mensah, Stephen Osei Akyiaw

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The study examined mobile money service fraud experiences and perspectives on control practices at University of Education, Winneba. The objectives of the study included to examine the forms of MoMo fraud strategies experienced by customers of MoMo on UEW Campus, to examine and classify the main perpetrators of the MoMo fraud among UEW students as well as the framework for fraud detection put together by the Telco’s and consumers on UEW Campus. The study adopted the case study research design. The purposive sampling technique was used to select the UEW Campus. Using the convenience sampling technique, five respondents were sampled for the study. The outcome of the in-depth interviews conducted revealed Mobile money fraud was committed in various forms, such as anonymous calls and text messages from scammers, fraudsters calling to deceive subscribers that they are to deliver goods from abroad or from a close relative under false pretexts. Finally, fraudsters sending false cash-out messages to merchants for authorization of which the physical cash is issued by the merchant to the fraudster without the equivalent e-cash. Mobile money fraud has been perpetuated in diverse forms such as mobile money network systems fraud, false promotion fraud, and reversal of erroneous transactions, fortuitous scams, and mobile money agents' fraud. Finally, the frameworks that have been used to detect mobile money fraud include the display of national identifies cards for the transaction, digital identification systems, the use of firewall to protect mobile money accounts, effective information technology architecture for mobile money services, reporting of mobile money fraud to telecoms and the sanctioning of mobile money fraudsters. The study suggested there should be public education and awareness creation on the activities of mobile money fraudsters in Ghana by telecommunication companies in conjunction with the National Communications Authority and the Bank of Ghana. The study, therefore, concluded that the menace of mobile money fraud threatens the integrity of the mobile money financial services.

Keywords: mobile money, fraud, telecommunication, merchant

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Authors: Tarek Dandashi

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WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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Authors: Sorayya Kazemi, Hamed Kharrati, Mehdi Abedinpour Fallah

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This paper presents the design and implementation of a novel electric pressure-sensitive toothbrush, capable of measuring the forces applied to the head of the brush. The developed device is used for gum recession measurement. In particular, the percentage of gum recession is measured by a Programmable Automation controller (PAC). Moreover, the brushing forces are measured by a Force Sensing Resistor (FSR) sensor. These forces are analog inputs of PAC. According to the applied forces during patient’s brushing and the patient’s percentage of gum recession, dentist sets the standard force range. The instrument alarms when the patient applies a force over the set range.

Keywords: gum recession, force sensing resistor, controller, toothbrush

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Authors: David Jurado, Carlos Ávila

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Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

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Authors: Xinghang Lv, Tao Peng, Jia Chen, Junping Liu, Xinrong Hu, Ruhan He, Minghua Jiang, Wenli Cao

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As one of the most dangerous vulnerabilities, effective detection of buffer overflow vulnerabilities is extremely necessary. Traditional detection methods are not accurate enough and consume more resources to meet complex and enormous code environment at present. In order to resolve the above problems, we propose the method for Buffer overflow detection based on Abstract syntax tree, Control flow graph, and Data dependency graph (BodeACD) in C/C++ programs with source code. Firstly, BodeACD constructs the function samples of buffer overflow that are available on Github, then represents them as code representation sequences, which fuse control flow, data dependency, and syntax structure of source code to reduce information loss during code representation. Finally, BodeACD learns vulnerability patterns for vulnerability detection through deep learning. The results of the experiments show that BodeACD has increased the precision and recall by 6.3% and 8.5% respectively compared with the latest methods, which can effectively improve vulnerability detection and reduce False-positive rate and False-negative rate.

Keywords: vulnerability detection, abstract syntax tree, control flow graph, data dependency graph, code representation, deep learning

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Authors: Hye-Kyung Kang

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Social justice is a central principle of the social work profession and education. However, scholars have long questioned the profession’s commitment to putting social justice values into practice. Clinical social work has been particularly criticized for its lack of attention to social justice and for failing to address the concerns of the oppressed. One prominent criticism of clinical social work is that it often relies on individual intervention and fails to take on system-level changes or advocacy. This concern evokes the historical macro-micro tension of the social work profession where micro (e.g., mental health counseling) and macro (e.g., policy advocacy) practices are conceptualized as separate domains, creating a false binary for social workers. One contributor to this false binary seems to be that most clinical practice models do not prepare social work students and practitioners to make a clear link between clinical practice and social justice. This paper presents a model of clinical social work practice that clearly recognizes the essential and necessary connection between social justice, advocacy, and clinical practice throughout the clinical process: engagement, assessment, intervention, and evaluation. Contemporary relational theories, critical social work frameworks, and anti-oppressive practice approaches are integrated to build a clinical social work practice model that addresses the urgent need for mental health practice that not only helps and heals the person but also challenges societal oppressions and aims to change them. The application of the model is presented through case vignettes.

Keywords: social justice, clinical social work, clinical social work model, integrative model

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Authors: Vanessa Roulet, Marc Turini, Juliane Hey, Stéphanie Bord-Romeu, Emilie Bonzom, Mahmoud Badawi, Mohammed-Amine Chakir, Valérie Simon, Vanessa Viotti, Jérémie Gautier, Françoise Le Boulaire, Catherine Coignard, Claire Vincent, Sandrine Greaume, Isabelle Voisin

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Background: Beckman Coulter, Inc. has recently developed fully automated assays for the detection of HBsAg on a new immunoassay platform. The objective of this European multicenter study was to evaluate the performance of the ACCESS HBsAg and ACCESS HBsAg Confirmatory assays† on the recently CE-marked DxI 9000 ACCESS Immunoassay Analyzer. Methods: The clinical specificity of the ACCESS HBsAg and HBsAg Confirmatory assays was determined using HBsAg-negative samples from blood donors and hospitalized patients. The clinical sensitivity was determined using presumed HBsAg-positive samples. Sample HBsAg status was determined using a CE-marked HBsAg assay (Abbott ARCHITECT HBsAg Qualitative II, Roche Elecsys HBsAg II, or Abbott PRISM HBsAg assay) and a CE-marked HBsAg confirmatory assay (Abbott ARCHITECT HBsAg Qualitative II Confirmatory or Abbott PRISM HBsAg Confirmatory assay) according to manufacturer package inserts and pre-determined testing algorithms. False initial reactive rate was determined on fresh hospitalized patient samples. The sensitivity for the early detection of HBV infection was assessed internally on thirty (30) seroconversion panels. Results: Clinical specificity was 99.95% (95% CI, 99.86 – 99.99%) on 6047 blood donors and 99.71% (95%CI, 99.15 – 99.94%) on 1023 hospitalized patient samples. A total of six (6) samples were found false positive with the ACCESS HBsAg assay. None were confirmed for the presence of HBsAg with the ACCESS HBsAg Confirmatory assay. Clinical sensitivity on 455 HBsAg-positive samples was 100.00% (95% CI, 99.19 – 100.00%) for the ACCESS HBsAg assay alone and for the ACCESS HBsAg Confirmatory assay. The false initial reactive rate on 821 fresh hospitalized patient samples was 0.24% (95% CI, 0.03 – 0.87%). Results obtained on 30 seroconversion panels demonstrated that the ACCESS HBsAg assay had equivalent sensitivity performances compared to the Abbott ARCHITECT HBsAg Qualitative II assay with an average bleed difference since first reactive bleed of 0.13. All bleeds found reactive in ACCESS HBsAg assay were confirmed in ACCESS HBsAg Confirmatory assay. Conclusion: The newly developed ACCESS HBsAg and ACCESS HBsAg Confirmatory assays from Beckman Coulter have demonstrated high clinical sensitivity and specificity, equivalent to currently marketed HBsAg assays, as well as a low false initial reactive rate. †Pending achievement of CE compliance; not yet available for in vitro diagnostic use. 2023-11317 Beckman Coulter and the Beckman Coulter product and service marks mentioned herein are trademarks or registered trademarks of Beckman Coulter, Inc. in the United States and other countries. All other trademarks are the property of their respective owners.

Keywords: dxi 9000 access immunoassay analyzer, hbsag, hbv, hepatitis b surface antigen, hepatitis b virus, immunoassay

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Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

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Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: android, API Calls, machine learning, permissions combination

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Authors: Monisha Edirisooriya, Wilma Jack, Dominique Twelves, Jennifer Royds, Fiona Scott, Nicola Mason, Arran Turnbull, J. Michael Dixon

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Introduction: Excision biopsy has been the investigation of choice for patients presenting with pathological axillary lymphadenopathy without a breast abnormality. Core biopsy of nodes can provide sufficient tissue for diagnosis and has advantages in terms of morbidity and speed of diagnosis. This study evaluates the diagnostic accuracy of core biopsy in patients presenting with axillary lymphadenopathy. Methods: Between 2009 and 2019, 165 patients referred to the Edinburgh Breast Unit had a total of 179 axillary lymph node core biopsies. Results: 152 (92%) of the 165 initial core biopsies were deemed to contain adequate nodal tissue. Core biopsy correctly established malignancy in 75 of the 78 patients with haematological malignancy (96%) and in all 28 patients with metastatic carcinoma (100%) and correctly diagnosed benign changes in 49 of 57 (86%) patients with benign conditions. There were no false positives and no false negatives. In 67 (85.9%) of the 78 patients with hematological malignancy, there was sufficient material in the first core biopsy to allow the pathologist to make an actionable diagnosis and not ask for more tissue sampling prior to treatment. There were no complications of core biopsy. On follow up, none of the patients with benign cores has been shown to have malignancy in the axilla and none with lymphoma had their initial disease incorrectly classified. Conclusions: This study shows that core biopsy is now the investigation of choice for patients presenting with axillary lymphadenopathy even in those suspected as having lymphoma.

Keywords: core biopsy, excision biopsy, axillary lymphadenopathy, non-breast malignancy

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Authors: Mariam Kutateladze

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In the twenty-first century, in the customer service settings for hospitality institution’s employee management and their well-being have become a core issue since it is linked to the customers' increased demand for high-quality service. Employees' positive attitude to customers plays an essential role in the serving process; for this reason, in the hospitality institutions service with a smile is a job requirement. This research is devoted to the issues of employee management systems improvement and its effect of the genuine smile as a positive attitude expressed by the employees to the customer. Different researchers work about the effect of the genuine smile, which is analyzed in the present paper. Based on it, the link between satisfied employees from service climate and their genuine smile is determined. An investigation in local resort hotels which are located in the regions of Georgia is conducted. In the methodology of the paper, we have used linkage research, which stated that employee satisfaction in a working place depends on the existing service climate in an organization. We have prepared questioners according to eight dimensions of good service climate by linkage research, and extra questions about the effect of the smile on customers were added. Questionnaires were distributed among employees, and the results have shown that dissatisfaction from organizations’ service climate led to employees' false smile toward customers. Demanding positive emotions from frustrated employees was the mistake of the hotel management. The false smile was easily recognized by the customers, and the frustrated employee with a false smile could not provide high-quality service. The findings of the paper will help managers to realize the importance of forming the positive service climate within the institutions since it is linked to employees' well-being who are the creators of high-quality service. The conclusion drawn from this study indicates there are core issues those managers need to take into account when planning their organizations’ profit. Managers should know their employees very well, their feelings and attitudes toward work before asking them expressing a smile since forced smile does not have a good result and quite often has bad outcomes; therefore, first of all, managers should investigate service climate in the organization. Managers should take into consideration employees’ opinions about the service climate in the organization, motivate their employees, and respect their ideas. Also, they should satisfy employees' basic needs and stress more value on extrinsic goals such as competence, relatedness, and autonomy. Managers should create a positive working environment, positive service climate, which will lead to employee satisfaction and genuine feelings, as well as improve the working environment since negative working climate will cause customers disappointment because of low-quality service provided by the unsatisfied employees.

Keywords: employee management, hotel, quality of service, service climate

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Authors: Evangelia-Chrysanthi Kouklari, Stella Tsermentseli, Claire P. Monks

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Executive function (EF) refers to a set of future-oriented and goal-directed cognitive skills that are crucial for problem solving and social behaviour, as well as the ability to organise oneself. It has been suggested that EF could be conceptualised as two distinct but interrelated constructs, one emotional (hot) and one cognitive (cool), as it facilitates both affective and cognitive regulation. Cool EF has been found to be strongly related to Theory of Mind (ToM) that is the ability to infer mental states, but research has not taken into account the association between hot EF and ToM in Autism Spectrum Disorder (ASD) to date. The present study investigates the associations between both hot and cool EF and ToM in school-aged children with ASD. This cross-sectional study assesses 79 school-aged children with ASD (7-15 years) and 91 controls matched for age and IQ, on tasks tapping cool EF (working memory, inhibition, planning), hot EF (effective decision making, delay discounting), and ToM (emotional understanding and false/no false belief). Significant group differences in each EF measure support a global executive dysfunction in ASD. Strong associations between hot EF and ToM in ASD are reported for the first time (i.e. ToM emotional understanding and delay discounting). These findings highlight that hot EF also makes a unique contribution to the developmental profile of ASD. Considering the role of both hot and cool EF in association with ToM in individuals with ASD may aid in gaining a greater understanding not just of how these complex multifaceted cognitive abilities relate to one another, but their joint role in the distinct developmental pathway followed in ASD.

Keywords: ASD, executive function, school age, theory of mind

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Authors: Yulin Rao, Zhixuan Li, Burra Venkata Durga Kumar

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Intrusion detection refers to monitoring the actions of internal and external intruders on the system and detecting the behaviours that violate security policies in real-time. In intrusion detection, there has been much discussion about the application of neural network technology and artificial immune system (AIS). However, many solutions use static methods (signature-based and stateful protocol analysis) or centralized intrusion detection systems (CIDS), which are unsuitable for real-time intrusion detection systems that need to process large amounts of data and detect unknown intrusions. This article proposes a framework for a distributed intrusion detection system (DIDS) with multi-agents based on the concept of AIS and neural network technology to detect anomalies and intrusions. In this framework, multiple agents are assigned to each host and work together, improving the system's detection efficiency and robustness. The trainer agent in the central server of the framework uses the artificial neural network (ANN) rather than the negative selection algorithm of AIS to generate mature detectors. Mature detectors can distinguish between self-files and non-self-files after learning. Our analyzer agents use genetic algorithms to generate memory cell detectors. This kind of detector will effectively reduce false positive and false negative errors and act quickly on known intrusions.

Keywords: artificial immune system, distributed artificial intelligence, multi-agent, intrusion detection system, neural network

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Authors: Neda Seyyedi, Reza Berangi

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Voice over IP (VOIP) network, also known as Internet telephony, is growing increasingly having occupied a large part of the communications market. With the growth of each technology, the related security issues become of particular importance. Taking advantage of this technology in different environments with numerous features put at our disposal, there arises an increasing need to address the security threats. Being IP-based and playing a signaling role in VOIP networks, Session Initiation Protocol (SIP) lets the invaders use weaknesses of the protocol to disable VOIP service. One of the most important threats is denial of service attack, a branch of which in this article we have discussed as flooding attacks. These attacks make server resources wasted and deprive it from delivering service to authorized users. Distributed denial of service attacks and attacks with a low rate can mislead many attack detection mechanisms. In this paper, we introduce a mechanism which not only detects distributed denial of service attacks and low rate attacks, but can also identify the attackers accurately. We detect and prevent flooding attacks in SIP protocol using Shannon (FDP-S), Renyi (FDP-R) and Tsallis (FDP-T) entropy. We conducted an experiment to compare the percentage of detection and rate of false alarm messages using any of the Shannon, Renyi and Tsallis entropy as a measure of disorder. Implementation results show that, according to the parametric nature of the Renyi and Tsallis entropy, by changing the parameters, different detection percentages and false alarm rates will be gained with the possibility to adjust the sensitivity of the detection mechanism.

Keywords: VOIP networks, flooding attacks, entropy, computer networks

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Authors: Fotios Spyropoulos, Evangelia Androulaki, Vasileios Karagiannopoulos, Aristotelis Kompothrekas, Nikolaos Karagiannis

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The problem of 'fake news' and 'hoaxes' has dominated in recent years the field of news, politics, economy, safety, and security as dissemination of false information can intensively affect and mislead public discourse and public opinion. The widespread use of internet and social media platforms can substantially intensify these effects, which often include public fear and insecurity. Misinformation, malinformation, and disinformation have also been blamed for affecting election results in multiple countries, and since then, there have been efforts to tackle the phenomenon both on national and international level. The presentation will focus on methods of prevention of disseminating false information on social media and on the internet and will discuss relevant criminological views. The challenges that have arisen for criminal law will be covered, taking into account the potential need for a multi-national approach required in order to mitigate the extent and negative impact of the fake news phenomenon. Finally, the analysis will include a discussion on the potential usefulness of non-legal modalities of regulation and crime prevention, especially situational and social measures of prevention and the possibility of combining an array of methods to achieve better results on national and international level. This project has received funding from the Hellenic Foundation for Research and Innovation (HFRI) and the General Secretariat for Research and Technology (GSRT), under grant agreement No 80529.

Keywords: cybercrime, disinformation, fake news, prevention

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Authors: Omar Shakra

Abstract:

This paper contains a huge number of benefits that we can use it in several places and times in fire safety protection in the Middle East especially in Egypt . People here in Egypt did not consider the safety and fire protection as important as it is. But on the other hand, its very important for them to contain the fire systems and safety in every facility, the companies , hospitals , police stations , and even the super markets must use the fire system. It makes the facility safe to the visitors while they are using it.From my point of view as the owner Fire Safety Company called Deluge Egypt , i can say that not all of the companies use the fire system protection according to the high cost they prefer to build their company without the protection, and this is make the building totally unsafe to be used from the visitors or client.So, i am looking for new methods and technology to invest in Egypt, and this is through attending this Conference and let the audiences know more about the services i provide and [to let them know about the importance of the Fire Safety in Egypt. The Objectives of my research 1- The system that i used in my Company. 2- The benefits of the Fire System Protection. 3-The importance of the Fire System and safety. 4-The use of the new Technologies. 5-The hardships that i found while having new deals with new clients.

Keywords: fire, system, protection, fire hydrants, security, alarms

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Authors: Prof. Ammal Mokhtar Metwally, Samia M. Sami, Nihad A. Ibrahim, Fatma A. Shaaban, Iman I. Salama

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Objectives: Reducing neonatal mortality by 2030 is still a challenging goal in developing countries. low birth weight (LBW) is a significant contributor to this, especially where weighing newborns is not possible routinely. The present study aimed to determine a simple, easy, reliable anthropometric measure(s) that can predict LBW) and neonatal mortality. Methods: A prospective cohort study of 570 babies born in districts of El Menia governorate, Egypt (where most deliveries occurred at home) was examined at birth. Newborn weight, length, head, chest, mid-arm, and thigh circumferences were measured. Follow up of the examined neonates took place during their first four weeks of life to report any mortalities. The most predictable anthropometric measures were determined using the statistical package of SPSS, and multiple Logistic regression analysis was performed.: Results: Head and chest circumferences with cut-off points < 33 cm and ≤ 31.5 cm, respectively, were the significant predictors for LBW. They carried the best combination of having the highest sensitivity (89.8 % & 86.4 %) and least false negative predictive value (1.4 % & 1.7 %). Chest circumference with a cut-off point ≤ 31.5 cm was the significant predictor for neonatal mortality with 83.3 % sensitivity and 0.43 % false negative predictive value. Conclusion: Using chest circumference with a cut-off point ≤ 31.5 cm is recommended as a single simple anthropometric measurement for the prediction of both LBW and neonatal mortality. The predicted measure could act as a substitute for weighting newborns in communities where scales to weigh them are not routinely available.

Keywords: low birth weight, neonatal mortality, anthropometric measures, practical screening

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Authors: Shirly Bar-Lev, Michal Morag

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Cults are usually thought of as suppressive organizations, where creativity is systematically stifled. Except for few scholars, creativity in cults remains an uncharted terrain (Boeri and Pressley, 2010). This paperfocuses on how cult members sought real and imaginary spaces to express themselves and even used their bodies as canvases on which to assert their individuality, resistance, devotion, pain, and anguish. We contend that cult members’ creativity paves their way out of the cult. This paper is part of a larger study into the experiences of former members of cults and cult-like NewReligiousMmovements (NRM). The research is based on in-depth interviews conducted with thirtyIsraeli men and women, aged 24 to 50, who either joined an NRM or were born into one. Their stories reveal that creativity is both emplaced and embedded in power relations. That is why Foucault’s idea of Heterotopia and Winnicott’s idea of the battle between True and False self canbenefit our understanding of how cult members creatively assert their autonomy over their bodies and thoughts while in the cult. Cults’ operate on a complex tension between submission and autonomy. On the one hand, they act as heterotopias byallowing for a ‘simultaneousmythic and real contestation of the space in which we live. Ascounter-hegemonic sites, they serve as‘the greatest reserve of theimagination’, to use Foucault’s words. Cults definitely possesselements of mystery, danger, and transgression where an alternative social ordering can emerge. On the other hand, cults are set up to format alternative identities. Often, the individuals who inhibit these spaces look for spiritual growth, self-reflection, and self-actualization. They might willingly relinquish autonomy over vast aspects of their lives in pursuit of self-improvement. In any case, cultsclaim the totality of their members’ identities and absolute commitment and compliance with the cult’s regimes. It, therefore, begs the question how the paradox between autonomy and submissioncan spur instances of creativity. How can cult members escape processes of performative regulation to assert their creative self? Both Foucault and Winnicott recognize the possibility of an authentic self – one that is spontaneous and creative. Both recognize that only the true self can feel real andmust never comply. Both note the disciplinary regimes that push the true self into hiding, as well as the social and psychological mechanisms that individuals develop to protect their true self. But while Foucault spoke of the power of critic as a way of salvaging the true self, Winnicott spoke of recognition and empathy - feeling known by others. Invitinga dialogue between the two theorists can yield a productive discussion on how cult members assert their ‘true self’ to cultivate a creative self within the confines of the cult.

Keywords: cults, creativity, heterotopia, true and false self

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Authors: Aya Idriss, Esraa Othman, Lujain Malak

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Artificial intelligence is the emulation of human intelligence processes by machines, particularly computer systems that act logically. Some of the specific applications of AI include natural language processing, speech recognition, and machine vision. Cortana is a virtual assistant and she’s an example of an AI Application. Microsoft made it possible for this app to be accessed not only on laptops and PCs but can be downloaded on mobile phones and used as a virtual assistant which was a huge success. Cortana can offer a lot apart from the basic orders such as setting alarms and marking the calendar. Its capabilities spread past that, for example, it provides us with listening to music and podcasts on the go, managing my to-do list and emails, connecting with my contacts hands-free by simply just telling the virtual assistant to call somebody, gives me instant answers and so on. A questionnaire was sent online to numerous friends and family members to perform the study, which is critical in evaluating Cortana's recognition capacity and the majority of the answers were in favor of Cortana’s capabilities. The results of the questionnaire assisted us in determining the level of Cortana's skills.

Keywords: artificial intelligence, Cortana, AI, abstract

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Authors: Engy Shokry, Giancarlo La Marca, Maria Luisa Della Bona

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Newborn screening for Congenital Adrenal Hyperplasia (CAH) relies on quantification of 17α-hydroxyprogesterone using enzyme immunoassays. These assays, in spite of being rapid, readily available and easy to perform, its reliability was found questionable due to lack of selectivity and specificity resulting in large number of false-positives, consequently family anxiety and associated hospitalization costs. To improve specificity of conventional 17α-hydroxyprogesterone screening which may experience false transient elevation in preterm, low birth weight or acutely ill neonates, steroid profiling by LC-MS/MS as a second-tier test was implemented. Unlike the previously applied LC-MS/MS methods, with the disadvantage of requiring a relatively high number of blood drops. Since newborn screening tests are increasing, it is necessary to minimize the sample volume requirement to make the maximum use of blood samples collected on filter paper. The proposed new method requires just one 3.2 mm dried blood spot (DBS) punch. Extraction was done using methanol: water: formic acid (90:10:0.1, v/v/v) containing deuterium labelled internal standards. Extracts were evaporated and reconstituted in 10 % acetone in water. Column switching strategy for on-line sample clean-up was applied to improve the chromatographic run. The first separative step retained the investigated steroids and passed through the majority of high molecular weight impurities. After the valve switching, the investigated steroids are back flushed from the POROS® column onto the analytical column and separated using gradient elution. Found quantitation limits were 5, 10 and 50 nmol/L for 17α-hydroxyprogesterone, androstenedione and cortisol respectively with mean recoveries of between 98.31-103.24 % and intra-/ inter-assay CV% < 10 % except at LLOQ. The method was validated using standard addition calibration and isotope dilution strategies. Reference ranges were determined by analysing samples from 896 infants of various ages at the time of sample collection. The method was also applied on patients with confirmed CAH. Our method represents an attractive combination of low sample volume requirement, minimal sample preparation time without derivatization and quick chromatography (5 min). The three steroid profile and the concentration ratios (17OHP + androstenedione/cortisol) allowed better screening outcomes of CAH reducing false positives, associated costs and anxiety.

Keywords: congenital adrenal hyperplasia (CAH), 17α-hydroxyprogesterone, androstenedione, cortisol, LC-MS/MS

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Authors: Arkadiusz Gut, Robert Mirski

Abstract:

The nativist-constructivist debate constitutes a considerable part of current research on mindreading. Peter Carruthers and his colleagues are known for their nativist position in the debate and take issue with constructivist views proposed by other researchers, with Henry Wellman, Alison Gopnik, and Ian Apperly at the forefront. More specifically, Carruthers together with Evan Westra propose a nativistic explanation of Theory of Mind Scale study results that Wellman et al. see as supporting constructivism. While allowing for development of the innate mindreading system, Westra and Carruthers base their argumentation essentially on a competence-performance gap, claiming that cross-cultural differences in Theory of Mind Scale progression as well as discrepancies between infants’ and toddlers’ results on verbal and non-verbal false-belief tasks are fully explainable in terms of acquisition of other, pragmatic, cognitive developments, which are said to allow for an expression of the innately present Theory of Mind understanding. The goal of the present paper is to bring together arguments against the view offered by Westra and Carruthers. It will be shown that even though Carruthers et al.’s interpretation has not been directly controlled for in Wellman et al.’s experiments, there are serious reasons to dismiss such nativistic views which Carruthers et al. advance. The present paper discusses the following issues that undermine Carruthers et al.’s nativistic conception: (1) The concept of innateness is argued to be developmentally inaccurate; it has been dropped in many biological sciences altogether and many developmental psychologists advocate for doing the same in cognitive psychology. Reality of development is a complex interaction of changing elements that is belied by the simplistic notion of ‘the innate.’ (2) The purported innate mindreading conceptual system posited by Carruthers ascribes adult-like understanding to infants, ignoring the difference between first- and second-order understanding, between what can be called ‘presentation’ and ‘representation.’ (3) Advances in neurobiology speak strongly against any inborn conceptual knowledge; neocortex, where conceptual knowledge finds its correlates, is said to be largely equipotential at birth. (4) Carruthers et al.’s interpretations are excessively charitable; they extend results of studies done with 15-month-olds to conclusions about innateness, whereas in reality at that age there has been plenty of time for construction of the skill. (5) Looking-time experiment paradigm used in non-verbal false belief tasks that provide the main support for Carruthers’ argumentation has been criticized on methodological grounds. In the light of the presented arguments, nativism in theory of mind research is concluded to be an untenable position.

Keywords: development, false belief, mindreading, nativism, theory of mind

Procedia PDF Downloads 184