Search results for: false alarm

Authors: Kalluru Maheswaramma, Putta Padma

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This study makes an attempt to demonstrate the wondrous world of the upwardly middle black community in Gloria Naylor’s Linden Hills. Gloria Naylor’s first novel The Women of Brewster Place is about the working class and Linden Hills about middle-class Black America. Naylor believes their serenity that is lost in the middle or working class black people as they move into the upper patriarchal society. Naylor challenges the different forms of superiority, homophobia, and chauvinism, interracial bias, and the like, which plague a community so significantly trying to be acceptable in the larger white community. In an ironic twist, Naylor creates characters that recognize their desire for a solid black community but who in reality ignore blackness and negate any emergent sign of its development. Linden Hills is an expose of the wealthy and spiritually dissolute upper class. Linden Hills is an examination of an upper-middle-class African American community in which women are largely exploited or invisible and in which men have, in the course of upward mobility, sacrificed their racial identity and their essence. Linden Hills is a social world, which includes firm stratification, false values, and an immobilizing impact on its residents. Touching a brief note upon the origin and development of African American Literature as well a note on the chosen writer and her works, the paper proceeds to depict the middle-class black community of Linden Hills.

Keywords: gloria naylor, linden hills, African American community, the middle black community

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Authors: Kelvin Mwaba, Nicole Strickland

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Background and Objectives: Overexploitation and illegal fishing have been identified as the primary cause of the global decline in the fish stock. While commercial companies and small-scale fishing sectors are strictly regulated in South Africa, recreational anglers are not. The underlying assumption seems to be that recreational anglers can self-regulate. The aim of the present study was to investigate the relationship that recreational anglers have with nature and how this relationship can predict unlawful fishing practices. Methods: Using a survey design, 99 self-identified recreational anglers were recruited through convenient sampling. The anglers were accessed from fishing tackle shops around False Bay in the Western Cape province of South Africa. Data was collected using a self-administered questionnaire that consisted of pro-environmental behavior survey and the Nature Relatedness Scale. Results: Data analyses indicated that significant differences with regard to nature relatedness on the basis of participants’ age and level of education. Older and more educated anglers scored higher on nature relatedness than younger and less educated anglers. Logistic regression analysis showed that nature relatedness was a significant predictor of pro-environmental behaviors (R²= 0.061). Discussion and Conclusion: The findings of the present study provide support regarding the importance of encouraging healthy and sustainable relationships between humans and nature. Combating harmful fishing practices can achieve through understanding and promoting human care for nature among anglers and others involved in fishing.

Keywords: pro-environmental, behavior, anglers, South Africa

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Authors: Jingting Luo, Yong Wang, Ying Wang

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Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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Authors: Angela Fabris, Joerg Helbig

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Our paper deals with feature films set in Venice which focus on the influence of Italian life style on anglophone characters. Usually, these films emphasize the different cultures and mentalities of Italian and British (or American) people. More often than not, these encounters result in a profound change of the anglophone characters' attitude towards romance and sensuality. A case in point is David Lean's Summer Madness (UK 1955). This film recounts the love affair between the American tourist Jane Hudson (Katherine Hepburn) and the Venetian antique shop owner Renato de Rossi (Rossano Brazzi). Jane is a spinster in her mid-forties who longs for love and romance. The chance arrives when she meets Renato who feels attracted to her. Jane's immediate reaction, however, is to reject Renato's advances. What follows is a struggle between the strict morality of a puritan upbringing and the irresitable charm of Mediterranean temptations. Similar conflicts can be found in many other movies. Apart from Summer Madness we will discuss Aldo Lado's Chi l'ha vista morire? (It 1972), Nicolas Roeg's Don't Look Now (UK/It 1973) and Paul Schrader's The Comfort of Strangers (It/UK/USA 1990). Our paper raises the question whether or not these and other films present false stereotypes and chlichés. The paper is part of our large-scale research project which explores the history of erotic cinema in Italy and England.

Keywords: culture clash, erotic cinema, film, Venice

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Authors: Reza Rezaeipour Honarmandzad

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This paper introduces an aircraft cable fault detection and location method in light of TFDR keeping in mind the end goal to recognize the intermittent faults adequately and to adapt to the serial and after-connector issues being hard to be distinguished in time domain reflection. In this strategy, the correlation function of reflected and reference signal is used to recognize and find the airplane fault as per the qualities of reflected and reference signal in time-frequency domain, so the hit rate of distinguishing and finding intermittent faults can be enhanced adequately. In the work process, the reflected signal is interfered by the noise and false caution happens frequently, so the threshold de-noising technique in light of wavelet decomposition is used to diminish the noise interference and lessen the shortcoming alert rate. At that point the time-frequency cross connection capacity of the reference signal and the reflected signal based on Wigner-Ville appropriation is figured so as to find the issue position. Finally, LabVIEW is connected to execute operation and control interface, the primary capacity of which is to connect and control MATLAB and LABSQL. Using the solid computing capacity and the bottomless capacity library of MATLAB, the signal processing turn to be effortlessly acknowledged, in addition LabVIEW help the framework to be more dependable and upgraded effectively.

Keywords: aircraft cable, fault location, TFDR, LabVIEW

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Authors: Waled A. Dawoud, Abdelazim M. Negm, Nasser M. Saleh

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Offshore piling generates underwater sound at level high enough to cause physical damage or hearing impairment to the marine mammals. Several methods can be used to mitigate the effect of underwater noise from offshore pile driving on marine mammals which can be divided into three main approaches. The first approach is to keep the mammal out of the high-risk area by using aversive sound waves produced by acoustic mitigation devices such as playing-back of mammal's natural predator vocalization, alarm or distress sounds, and anthropogenic sound. The second approach is to reduce the amount of underwater noise from pile driving using noise mitigation techniques such as bubble curtains, isolation casing, and hydro-sound dampers. The third approach is to eliminate the overlap of underwater waves by using prolonged construction process. To investigate the effectiveness of different noise mitigation methods; a pile driven with 235 kJ rated energy diesel hammer near Jeddah Coast, Kingdom of Saudi Arabia was used. Using empirical sound exposure model based on Red Sea characteristics and limits of National Oceanic and Atmospheric Administration; it was found that the aversive sound waves should extend to 1.8 km around the pile location. Bubble curtains can reduce the behavioral disturbance area up to 28%; temporary threshold shift up to 36%; permanent threshold shift up to 50%; and physical injury up to 70%. Isolation casing can reduce the behavioral disturbance range up to 12%; temporary threshold shift up to 21%; permanent threshold shift up to 29%; and physical injury up to 46%. Hydro-sound dampers efficiency depends mainly on the used technology and it can reduce the behavioral disturbance range from 10% to 33%; temporary threshold shift from 18% to 25%; permanent threshold shift from 32% to 50%; and physical injury from 46% to 60%. To prolong the construction process, it was found that the single pile construction, use of soft start, and keep time between two successive hammer strikes more than 3 seconds are the most effective techniques.

Keywords: offshore pile driving, sound propagation models, noise effects on marine mammals, Underwater noise mitigation

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Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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Authors: Jaime Otavo

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Oscar del Barco, a former member of Los Montoneros, an Argentine guerrilla group of the 1970s, published a letter in 2004 that sparked a heated debate in his country about revolutionary violence. Del Barco, on the subject of «No matarás» (Thou shalt not kill) –as this debate was known– wrote to Sergio Schmucler, his addressee, the following: "There is no 'ideal' that justifies the death of a man. The founding principle of any community is 'Thou shalt not kill'. Thou shalt not kill the man because every man is sacred, and every man is all men".In this paper, the «No matarás» debate will be used to problematize two interconnected ideas that, in Colombia, underpinned the use of revolutionary violence by the guerrilla movements that emerged in the 1970s. On the one hand, an anthropological optimism; on the other, a theological scheme of converting violence into justice. Based on this, two arguments are put forward: 1) that revolutionary violence arose from an ethical-political certainty, namely: the confidence in being on the right side of history (because the violent ones were others), but 2) that its persistence over time made visible a tragic element, that is, that the bipolarity between victim and executioner, good and evil, or friend and foe that is inscribed in the class struggle is a false dilemma for in the context of revolutionary violence –as in the context of Greek tragedy–, no one ever has to make a decision, nor can he do so. For this reason, it is maintained that the fundamental aspect about guerrilla violence in Colombia is that it imposed itself as a violence of negativity which not only exceeded the capacity of the extreme left to control its revolutionary praxis but also exploited the link with the political subjectivation to which it aspired, the proletariat as the gravedigger of the bourgeoisie.

Keywords: marxism, social movements, armed struggle, debate thou shalt not kill

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Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani

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One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Keywords: automatic target recognition (ATR), high resolution range profile (HRRP), motion compensation, stepped frequency waveform technique (SFW), target motion parameters (TMPs)

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Authors: Idowu Olugbenga Adewumi, Foluke Iyabo Oluwatoyinbo

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Presently, there are several discussions on the food security with increase in yield of arable crop throughout the world. This article, briefly present research efforts to create digital interfaces to nature, in particular to area of crop production in agriculture with increase in yield with interest on pervasive computing. The approach goes beyond the use of sensor networks for environmental monitoring but also by emphasizing the development of a system architecture that detect intruder (Intrusion Process) which reduce the yield of the farmer at the end of the planting/harvesting period. The objective of the work is to set a model for setting up the hand held or portable device for increasing the quality and quantity of arable crop. This process incorporates the use of infrared motion image sensor with security alarm system which can send a noise signal to intruder on the farm. This model of the portable image sensing device in monitoring or scaring human, rodent, birds and even pests activities will reduce post harvest loss which will increase the yield on farm. The nano intelligence technology was proposed to combat and minimize intrusion process that usually leads to low quality and quantity of produce from farm. Intranet system will be in place with wireless radio (WLAN), router, server, and client computer system or hand held device e.g PDAs or mobile phone. This approach enables the development of hybrid systems which will be effective as a security measure on farm. Since, precision agriculture has developed with the computerization of agricultural production systems and the networking of computerized control systems. In the intelligent plant production system of controlled greenhouses, information on plant responses, measured by sensors, is used to optimize the system. Further work must be carry out on modeling using pervasive computing environment to solve problems of agriculture, as the use of electronics in agriculture will attracts more youth involvement in the industry.

Keywords: pervasive computing, intrusion detection, precision agriculture, security, arable crop

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Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: information gain (IG), intrusion detection system (IDS), k-means clustering, Weka

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Authors: Angela U. Makolo, Temitayo A. Olagunju

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The knowledge of signaling pathways is central to understanding the biological mechanisms of organisms since it has been identified that in eukaryotic organisms, the number of signaling pathways determines the number of ways the organism will react to external stimuli. Signaling pathways are studied using protein interaction networks constructed from protein-protein interaction data obtained using high throughput experimental procedures. However, these high throughput methods are known to produce very high rates of false positive and negative interactions. In order to construct a useful protein interaction network from this noisy data, computational methods are applied to validate the protein-protein interactions. In this study, a computational technique to identify signaling pathways from a protein interaction network constructed using validated protein-protein interaction data was designed. A weighted interaction graph of the Saccharomyces cerevisiae (Baker’s Yeast) organism using the proteins as the nodes and interactions between them as edges was constructed. The weights were obtained using Bayesian probabilistic network to estimate the posterior probability of interaction between two proteins given the gene expression measurement as biological evidence. Only interactions above a threshold were accepted for the network model. A pathway was formalized as a simple path in the interaction network from a starting protein and an ending protein of interest. We were able to identify some pathway segments, one of which is a segment of the pathway that signals the start of the process of meiosis in S. cerevisiae.

Keywords: Bayesian networks, protein interaction networks, Saccharomyces cerevisiae, signalling pathways

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Authors: Nadine Sammy, Mark Wilson, Samuel Vine

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The Theory of Challenge and Threat States in Athletes (TCTSA) states that self-efficacy is an antecedent of challenge and threat. These states result from conscious and unconscious evaluations of situational demands and personal resources and are represented by both cognitive and physiological markers. Challenge is considered a more adaptive stress response as it is associated with a more efficient cardiovascular profile, as well as better performance and attention effects compared with threat. Self-efficacy is proposed to influence challenge/threat because an individual’s belief that they have the skills necessary to execute the courses of action required to succeed contributes to a perception that they can cope with the demands of the situation. This study experimentally examined the effects of self-efficacy on cardiovascular responses (challenge and threat), demand and resource evaluations, performance and attention under pressurised conditions. Forty-five university students were randomly assigned to either a control (n=15), low self-efficacy (n=15) or high self-efficacy (n=15) group and completed baseline and pressurised golf putting tasks. Self-efficacy was manipulated using false feedback adapted from previous studies. Measures of self-efficacy, cardiovascular reactivity, demand and resource evaluations, task performance and attention were recorded. The high self-efficacy group displayed more favourable cardiovascular reactivity, indicative of a challenge state, compared with the low self-efficacy group. The former group also reported high resource evaluations, but no task performance or attention effects were detected. These findings demonstrate that levels of self-efficacy influence cardiovascular reactivity and perceptions of resources under pressurised conditions.

Keywords: cardiovascular, challenge, performance, threat

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Authors: Duangduen L. Bhanthumnavin, Duchduen E. Bhanthumnavin

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Widening gap between new academic knowledge in all areas and habit of exploring and exploiting this precious information by students causes an alarm and need for urgent prevention. At present, all advanced nations are committed to WHO’s Sustainable Development Goals (SDGs), which require some objective achievements by the year 2030 and further. The responsibility has been enforced on university lecturers, in addition to the higher education learning outcomes (HELO). The two groups of goals (SDGs and HELO) can be realized if most university instructors are capable of inculcating some important psychological characteristics and behavioral change in the new generations. Thus, this study aimed at pinpointing the significant factors for additional teaching skills of instructors regardless of the area of study. University lecturers from various parts of Thailand, with the total of 540 persons, participated in this cross-sectional study. Based on interactionism model of behavior antecedents, it covers psychological situational factors, as well as their interaction. Most measuring instruments were summated rating with 10 or more items, each accompanied by a six-point rating scale. All these measures were constructed with acceptable standards. Most of the respondents were volunteers who gave their written responses in a meeting room or conference hall. By applying Multiple Regression Analysis in the total sample as well as in the subsamples of these university instructors, about 70 to 73 predictive percentages with 4 to 6 significant predictors were found. The major dependent variable was instructor’s teaching behavior for inculcating the psycho-moral strength for academic exploration and knowledge application. By performing ANOVA, the less-active instructors were identified as the ones with lower education (Master’s level or lower), the minimal research producers, and the ones with less in-service trainings. The preventive factors for these three groups of instructors were intention to increase the students’ psychological development as well as moral development in their regular teaching classes. In addition, social support from their supervisors and coworkers was also necessary. Recommendations for further research and training are offered and welcomed.

Keywords: psychological inculcation, at-risk instructors, preventive measures, undergraduate teaching

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Authors: Ali Almadan, Anoop Krishnan, Ajita Rattani

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Facial recognition is a widely adopted technology in surveillance, border control, healthcare, banking services, and lately, in mobile user authentication with Apple introducing “Face ID” moniker with iPhone X. A lot of research has been conducted in the area of face recognition on datasets captured by surveillance cameras, DSLR, and mobile devices. Recently, face recognition technology has also been deployed on body-worn cameras to keep officers safe, enabling situational awareness and providing evidence for trial. However, limited academic research has been conducted on this topic so far, without the availability of any publicly available datasets with a sufficient sample size. This paper aims to advance research in the area of face recognition using body-worn cameras. To this aim, the contribution of this work is two-fold: (1) collection of a dataset consisting of a total of 136,939 facial images of 102 subjects captured using body-worn cameras in in-door and daylight conditions and (2) evaluation of various deep-learning architectures for face identification on the collected dataset. Experimental results suggest a maximum True Positive Rate(TPR) of 99.86% at False Positive Rate(FPR) of 0.000 obtained by SphereFace based deep learning architecture in daylight condition. The collected dataset and the baseline algorithms will promote further research and development. A downloadable link of the dataset and the algorithms is available by contacting the authors.

Keywords: face recognition, body-worn cameras, deep learning, person identification

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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: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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Authors: Reyhane Abdollahi

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The beauty of appearance has been important in people's lives since the beginning of history. In every era, beauty has had a specific meaning, and individuals have represented the standards of beauty during each period. According to statistics, the beauty industry has experienced significant economic growth in recent decades, with projections indicating it will reach $583 billion by 2027. The emergence of social media, backed by technological advancements, has created a suitable platform for various beauty brands to engage in economic activities. It can be said that today, beauty bloggers represent the beauty standards of society, actively engaging on social media platforms such as Instagram. Beauty bloggers promote cosmetic and skin care products in front of the camera in their ideal state, utilizing their skills. Instagram, with its limited two-way communication between users and influencers, has also created a suitable environment for advertising. The aim of this research is to study the relationship between beauty bloggers and the consumption patterns of female followers. This research was conducted through interviews with Ten women over the age of 20 who have followed these pages for three years or more, and the findings were analyzed using qualitative content analysis. According to the findings, beauty bloggers encourage women to purchase cosmetic products by creating a sense of identification through sharing their experiences. Beauty bloggers generate a false sense of need for consumption among their audience by promoting beauty products. The feeling of inadequacy, stemming from women's comparisons with bloggers who are always beautiful, leads women to try to imitate the consumption habits and appearance of these bloggers.

Keywords: beauty blogger, instagram, beauty, consumption

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Authors: Divyani Redhu, Manisha Rathaur

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India has emerged as a very lucrative market for the smartphones in a very short span of time. The number of smartphone users here is growing massively with each passing day. Also, the expansion of internet services to far corners of the nation has also given a push to the smartphone revolution in India. Millennial, also known as Generation Y or the Net Generation is the generation born between the early 1980s and mid-1990s (some definitions extending further to early 2000s). Spanning roughly over 15 years, different social classes, cultures, and continents; it is irrational to imagine that millennial have a unified identity. But still, it cannot be denied that the growing millennial population is not only young but is highly tech-savvy too. It is not just the appearance of the device that today; we call it ‘smart’. Rather, it is the numerous tasks and functions that it can perform which has led its name to evolve as that of a ‘smartphone’. From usual tasks that were earlier performed by a simple mobile phone like making calls, sending messages, clicking photographs, recording videos etc.; today, the time has come where most of our day – to – day tasks are being taken care of by our all-time companion, i.e. smartphones. From being our alarm clock to being our note-maker, from our watch to our radio, our book-reader to our reminder, smartphones are present everywhere. Smartphone has now become an essential device for particularly the millennial to communicate not only with their friends but also with their family, colleagues, and teachers. The study by the researchers would be quantitative in nature. For the same, a survey would be conducted in particularly the capital of India, i.e. Delhi and the National Capital Region (NCR), which is the metropolitan area covering the entire National Capital Territory of Delhi and urban areas covering states of Haryana, Uttarakhand, Uttar Pradesh and Rajasthan. The tool of the survey would be a questionnaire and the number of respondents would be 200. The results derived from the study would primarily focus on the increasing reach of smartphones in India, smartphones as technological innovation and convergent tools, smartphone usage pattern of millennial in India, most used applications by the millennial, the average time spent by them, the impact of smartphones on the personal interactions of millennial etc. Thus, talking about the smartphone technology and the millennial in India, it would not be wrong to say that the growth, as well as the potential of the smartphones in India, is still immense. Also, very few technologies have made it possible to give a global exposure to the users and smartphone, if not the only one is certainly an immensely effective one that comes to the mind in this case.

Keywords: Delhi – NCR, India, millennial, smartphone

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: Anacletus Ogbunkwu

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It is very disheartening that fake news or inaccurate information spread like wide fire and even with greater speed than fact based news/information. The peak of this anomaly is manifest in information management on the Corona virus pandemic, political/leadership based information, ethnic bigotry, unwarranted panics, false alarms, religious fanaticism, and business moguls in their advertorials, comedies, etc. This ugly situation has left Nigeria and her citizens with emotional trauma, unguided agitations, incessant tribal wars, lost of life and property, widened disunity among Nigerian ethnic and religious groups, amplified insecurity, aided election violence, etc. Unfortunately, among the major driving factors to this misinformation and conspiracy are the official/government and private news agencies, gossip, comedians, and social media handles such as; facebook, twitter, whatsapp, instagram, and online news agencies, etc. Thus this paper examines the impact of misinformation here referred to as infodemic. Also, it studies the epistemic effect of misinformation on the citizens of Nigeria in order to find ways of abating this anomaly for a better society. The methods of exposition and hermeneutics will be used in order to gain in-depth study of the details of infodemic in Nigeria and to offer philosophical analysis/interpretation of data as gathered, respectively. This paper concludes that misinformation or fake news has a perilous effect of epistemic mistrust to Nigeria and her citizens; hence infodemic is a cog in the wheel of National progress.

Keywords: nigeria, infodemic, language, media, news, progress

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Authors: Mostafa Refat Ismail, Hazem Eldaly

Abstract:

The adaptation of architecture design to building function is getting highly needed in contemporary designs, especially with the great progression in design methods and tools. This, in turn, requires great flexibility in design strategies, as well as a wider spectrum of space settings to achieve the required environment that special activities imply. Acoustics is an essential factor influencing cognitive acts and behavior as well as, on the extreme end, the physical well-being inside a space. The complexity of this constrain is fueled up by the extended geometric dimensions of multipurpose halls, making acoustic adequateness a great concern that could not easily be achieved for each purpose. To achieve a performance oriented acoustic environment, various parametric shaped false ceilings based on origami folded notion are simulated. These parametric origami shapes are able to fold and unfold forming an interactive structure that changes the mutual acoustic environment according to the geometric shapes' position and its changing exposed surface areas. The mobility of the facets in the origami surface can stretch up the range from a complete plain surface to an unfolded element where a considerable amount of absorption is added to the space. The behavior of the parametric origami shapes are being modeled employing a ray tracing computer simulation package for various shapes topology. The conclusion shows a great variation in the acoustical performance due to the variation in folding faces of the origami surfaces, which cause different reflections and consequently large variations in decay curves.

Keywords: parametric, origami, acoustics, architecture

Procedia PDF Downloads 285

Authors: Ande Nesmith

Abstract:

There is an ongoing shortage of foster parents worldwide to take on a growing population of children in need of out-of-home care. Currently, resources are primarily aimed at recruitment rather than retention. Retention rates are extraordinarily low, especially in the first two years of fostering. Qualitative interviews with 19 foster parents averaging 20 years of service provided insight into the challenges they faced and how they overcame them. Thematic analysis of interview transcripts identified sources of stress and resiliency. Key stressors included lack of support and responsiveness from the children’s social workers, false maltreatment allegations, and secondary trauma from children’s destructive behaviors and emotional dysregulation. Resilient parents connected with other foster parents for support, engaged in creative problem-solving, recognized that positive feedback from children usually arrives years later, and through training, understood the neurobiological impact of trauma on child behavior. Recommendations include coordinating communication between the foster parent licensing agency social workers and the children’s social workers, creating foster parent support networks and mentoring, and continuous training on trauma including effective parenting strategies. Research is needed to determine whether these resilience indicators in fact lead to long-term retention. Policies should include a mechanism to develop a cohesive line of communication and connection between foster parents and the children’s social workers as well as their respective agencies.

Keywords: foster care stability, foster parent burnout, foster parent resiliency, foster parent retention, trauma-informed fostering

Procedia PDF Downloads 350

Authors: Zoubida Mahi

Abstract:

A successful satellite mission in space requires a reliable attitude and orbit control system to command, control and position the satellite in appropriate orbits. Several sensors are used for attitude control, such as magnetic sensors, earth sensors, horizon sensors, gyroscopes, and solar sensors. The star tracker is the most accurate sensor compared to other sensors, and it is able to offer high-accuracy attitude control without the need for prior attitude information. There are mainly three approaches in star sensor research: digital simulation, hardware in the loop simulation, and field test of star observation. In the digital simulation approach, all of the processes are done in software, including star image simulation. Hence, it is necessary to develop star image simulation software that could simulate real space environments and various star sensor configurations. In this paper, we present a new stellar image simulation tool that is used to test and validate the stellar sensor algorithms; the developed tool allows to simulate of stellar images with several types of noise, such as background noise, gaussian noise, Poisson noise, multiplicative noise, and several scenarios that exist in space such as the presence of the moon, the presence of optical system problem, illumination and false objects. On the other hand, we present in this paper a new star extraction algorithm based on a new centroid calculation method. We compared our algorithm with other star extraction algorithms from the literature, and the results obtained show the star extraction capability of the proposed algorithm.

Keywords: star tracker, star simulation, star detection, centroid, noise, scenario

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Authors: Hei Yuen Pak

Abstract:

Steer Toward Rock, Fae Myenne Ng’s second novel after the National Bestseller Bone, is superficially concluded as a story of pessimism, which underestimates the sophistication of Ng’s portrayal. It is often summarized as a “heartbreaking novel of unrequited love” or “a story of timeless and tragic”; yet, Ng’s novel conveys more than a mere sense of tragedy and heartbreak, but rather an overflowing warmth and optimism. Ng is complimented of “illuminating a part of U.S. history few are aware of”—the false identity established on the paper relationships. Nevertheless, toward the end of the novel, this falsity enlightens the male protagonist, Jack Moon Szeto, of the ultimate realization of the “truthfulness” to himself, with the escort of the female characters. This paper intends to investigate how Ng’s depiction subverts the traditional sex/gender system and also the patriarchal savior stereotype. This paper mainly examines the characterization of and the relations among the four major characters: Jack Moon Szeto, Joice Qwan, Veda Qwan, and Ilin Cheung. By deploying Kate Millett’s, Marilyn French’s, Mary Daly’s feminist theories, the first half of the essay elucidates the power relations between Jack and the three females Joice, Veda, and Ilin in terms of gender and sexuality. After analyzing the relations, Jack, this male caged bird, is set free by the epiphany derived from the three female characters, which is the pivot of the second half. In reference to Jean-Paul Sartre and Simone de Beauvoir’s existentialist perspectives, I argue how Jack is transformed from, in Satre’s term, being-for-others to being-for-itself. Hence, the caged bird is free by the women saviors.

Keywords: Fae Myenne Ng, gender and sexuality, feminism, power relations

Procedia PDF Downloads 574

Authors: Arwa Alzughaibi

Abstract:

Human Motion detection is a challenging task due to a number of factors including variable appearance, posture and a wide range of illumination conditions and background. So, the first need of such a model is a reliable feature set that can discriminate between a human and a non-human form with a fair amount of confidence even under difficult conditions. By having richer representations, the classification task becomes easier and improved results can be achieved. The Aim of this paper is to investigate the reliable and accurate human motion detection models that are able to detect the human motions accurately under varying illumination levels and backgrounds. Different sets of features are tried and tested including Histogram of Oriented Gradients (HOG), Deformable Parts Model (DPM), Local Decorrelated Channel Feature (LDCF) and Aggregate Channel Feature (ACF). However, we propose an efficient and reliable human motion detection approach by combining Histogram of oriented gradients (HOG) and local phase quantization (LPQ) as the feature set, and implementing search pruning algorithm based on optical flow to reduce the number of false positive. Experimental results show the effectiveness of combining local phase quantization descriptor and the histogram of gradient to perform perfectly well for a large range of illumination conditions and backgrounds than the state-of-the-art human detectors. Areaunder th ROC Curve (AUC) of the proposed method achieved 0.781 for UCF dataset and 0.826 for CDW dataset which indicates that it performs comparably better than HOG, DPM, LDCF and ACF methods.

Keywords: human motion detection, histograms of oriented gradient, local phase quantization, local phase quantization

Procedia PDF Downloads 258

Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

Abstract:

A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

Procedia PDF Downloads 199

Authors: Magdalena Igras, Joanna Grzybowska, Mariusz Ziółko

Abstract:

The study of emotions expressed in emergency phone call is presented, covering both statistical analysis of emotions configurations and an attempt to automatically classify emotions. An emergency call is a situation usually accompanied by intense, authentic emotions. They influence (and may inhibit) the communication between caller and responder. In order to support responders in their responsible and psychically exhaustive work, we studied when and in which combinations emotions appeared in calls. A corpus of 45 hours of conversations (about 3300 calls) from emergency call center was collected. Each recording was manually tagged with labels of emotions valence (positive, negative or neutral), type (sadness, tiredness, anxiety, surprise, stress, anger, fury, calm, relief, compassion, satisfaction, amusement, joy) and arousal (weak, typical, varying, high) on the basis of perceptual judgment of two annotators. As we concluded, basic emotions tend to appear in specific configurations depending on the overall situational context and attitude of speaker. After performing statistical analysis we distinguished four main types of emotional behavior of callers: worry/helplessness (sadness, tiredness, compassion), alarm (anxiety, intense stress), mistake or neutral request for information (calm, surprise, sometimes with amusement) and pretension/insisting (anger, fury). The frequency of profiles was respectively: 51%, 21%, 18% and 8% of recordings. A model of presenting the complex emotional profiles on the two-dimensional (tension-insecurity) plane was introduced. In the stage of acoustic analysis, a set of prosodic parameters, as well as Mel-Frequency Cepstral Coefficients (MFCC) were used. Using these parameters, complex emotional states were modeled with machine learning techniques including Gaussian mixture models, decision trees and discriminant analysis. Results of classification with several methods will be presented and compared with the state of the art results obtained for classification of basic emotions. Future work will include optimization of the algorithm to perform in real time in order to track changes of emotions during a conversation.

Keywords: acoustic analysis, complex emotions, emotion recognition, machine learning

Procedia PDF Downloads 398

Authors: Devadrita Dey Sarkar

Abstract:

Regardless of the many technologic advances in the past decade, increased training and experience, and the obvious benefits of uniform standards, the false-negative rate in screening mammography remains unacceptably high .A computer aided neural network classification of regions of suspicion (ROS) on digitized mammograms is presented in this abstract which employs features extracted by a new technique based on independent component analysis. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral breast images has the potential to improve the overall performance in the detection of breast lumps. Because breast lumps can be detected reliably by computer on lateral breast mammographs, radiologists’ accuracy in the detection of breast lumps would be improved by the use of CAD, and thus early diagnosis of breast cancer would become possible. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for breast CAD may include the computerized detection of breast nodules, as well as the computerized classification of benign and malignant nodules. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with these CAD systems, which would be reliable and useful method for quantifying the similarity of a pair of images for visual comparison by radiologists.

Keywords: CAD(computer-aided design), lesions, neural network, ROS(region of suspicion)

Procedia PDF Downloads 456

Authors: E. Bennion, A. Acharya, S. Barnes, D. Ferrell, S. Luckett-Cole, G. Mower, J. Nelson, Y. Nguyen

Abstract:

Objective: This study aimed to evaluate the validity of a firearm injury query in the Early Notification of Community-based Epidemics syndromic surveillance system. Syndromic surveillance data are used at the Utah Department of Health for early detection of and rapid response to unusually high rates of violence and injury, among other health outcomes. The query of interest was defined by the Centers for Disease Control and Prevention and used chief complaint and discharge diagnosis codes to capture initial emergency department encounters for firearm injury of all intents. Design: Two epidemiologists manually reviewed electronic health records of emergency department visits captured by the query from April-May 2020, compared results, and sent conflicting determinations to two arbiters. Results: Of the 85 unique records captured, 67 were deemed probable, 19 were ruled out, and two were undetermined, resulting in a positive predictive value of 75.3%. Common reasons for false positives included non-initial encounters and misleading keywords. Conclusion: Improving the validity of syndromic surveillance data would better inform outbreak response decisions made by state and local health departments. The firearm injury definition could be refined to exclude non-initial encounters by negating words such as “last month,” “last week,” and “aftercare”; and to exclude non-firearm injury by negating words such as “pellet gun,” “air gun,” “nail gun,” “bullet bike,” and “exit wound” when a firearm is not mentioned.

Keywords: evaluation, health information system, firearm injury, syndromic surveillance

Procedia PDF Downloads 167