Search results for: automatic speech recognition
1272 An Examination of the Powers of the Executive to Continued Detention of Suspects in Disobedience to Court Orders
Authors: Chukwuemeka Castro Nwabuzor
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The 2015 Administration of Criminal Justice Act in Nigeria clearly sets out conditions for bail for felonies, lesser offenses and capital offenses. Even where the conditions for bail are met, granting an application for bail is not automatic as it is subject to the discretion of the court. Where the court, however, grants bail to an accused, the detaining authority which usually is the executive arm of government is bound to comply with the order of the court. This paper discusses the constitutionality of the continued detention of criminal suspects in disobedience to an order of the court and in the absence of an appeal. Particularly, the paper looks at the rights to personal liberty, the dignity of the human person and also the presumption of innocence which remains one of the crucial pillars of our criminal jurisprudence. The paper analyses the reasons posed by the executive for the continued detention of a suspect including State security and security of the suspect and questions whether the reasons are reasonable justifiable in a constitutional democratic society and whether they breach the principles of separation of powers. The paper concludes that the continued detention criminal of suspects in disobedience to court orders constitutes contempt of court and dishonours the principles of separation of powers enshrined in the Nigerian Constitution. This paper makes a strong case for the donation of more enforceable powers to the judiciary particularly with regards to the granting of compensation orders against the executive and ensuring compliance by the executive to bail orders.Keywords: breach of fundamental rights, contempt of court, discretion of court, right to bail, separation of powers
Procedia PDF Downloads 1651271 An Aptasensor Based on Magnetic Relaxation Switch and Controlled Magnetic Separation for the Sensitive Detection of Pseudomonas aeruginosa
Authors: Fei Jia, Xingjian Bai, Xiaowei Zhang, Wenjie Yan, Ruitong Dai, Xingmin Li, Jozef Kokini
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Pseudomonas aeruginosa is a Gram-negative, aerobic, opportunistic human pathogen that is present in the soil, water, and food. This microbe has been recognized as a representative food-borne spoilage bacterium that can lead to many types of infections. Considering the casualties and property loss caused by P. aeruginosa, the development of a rapid and reliable technique for the detection of P. aeruginosa is crucial. The whole-cell aptasensor, an emerging biosensor using aptamer as a capture probe to bind to the whole cell, for food-borne pathogens detection has attracted much attention due to its convenience and high sensitivity. Here, a low-field magnetic resonance imaging (LF-MRI) aptasensor for the rapid detection of P. aeruginosa was developed. The basic detection principle of the magnetic relaxation switch (MRSw) nanosensor lies on the ‘T₂-shortening’ effect of magnetic nanoparticles in NMR measurements. Briefly speaking, the transverse relaxation time (T₂) of neighboring water protons get shortened when magnetic nanoparticles are clustered due to the cross-linking upon the recognition and binding of biological targets, or simply when the concentration of the magnetic nanoparticles increased. Such shortening is related to both the state change (aggregation or dissociation) and the concentration change of magnetic nanoparticles and can be detected using NMR relaxometry or MRI scanners. In this work, two different sizes of magnetic nanoparticles, which are 10 nm (MN₁₀) and 400 nm (MN₄₀₀) in diameter, were first immobilized with anti- P. aeruginosa aptamer through 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS) chemistry separately, to capture and enrich the P. aeruginosa cells. When incubating with the target, a ‘sandwich’ (MN₁₀-bacteria-MN₄₀₀) complex are formed driven by the bonding of MN400 with P. aeruginosa through aptamer recognition, as well as the conjugate aggregation of MN₁₀ on the surface of P. aeruginosa. Due to the different magnetic performance of the MN₁₀ and MN₄₀₀ in the magnetic field caused by their different saturation magnetization, the MN₁₀-bacteria-MN₄₀₀ complex, as well as the unreacted MN₄₀₀ in the solution, can be quickly removed by magnetic separation, and as a result, only unreacted MN₁₀ remain in the solution. The remaining MN₁₀, which are superparamagnetic and stable in low field magnetic field, work as a signal readout for T₂ measurement. Under the optimum condition, the LF-MRI platform provides both image analysis and quantitative detection of P. aeruginosa, with the detection limit as low as 100 cfu/mL. The feasibility and specificity of the aptasensor are demonstrated in detecting real food samples and validated by using plate counting methods. Only two steps and less than 2 hours needed for the detection procedure, this robust aptasensor can detect P. aeruginosa with a wide linear range from 3.1 ×10² cfu/mL to 3.1 ×10⁷ cfu/mL, which is superior to conventional plate counting method and other molecular biology testing assay. Moreover, the aptasensor has a potential to detect other bacteria or toxins by changing suitable aptamers. Considering the excellent accuracy, feasibility, and practicality, the whole-cell aptasensor provides a promising platform for a quick, direct and accurate determination of food-borne pathogens at cell-level.Keywords: magnetic resonance imaging, meat spoilage, P. aeruginosa, transverse relaxation time
Procedia PDF Downloads 1521270 Frequent-Pattern Tree Algorithm Application to S&P and Equity Indexes
Authors: E. Younsi, H. Andriamboavonjy, A. David, S. Dokou, B. Lemrabet
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Software and time optimization are very important factors in financial markets, which are competitive fields, and emergence of new computer tools further stresses the challenge. In this context, any improvement of technical indicators which generate a buy or sell signal is a major issue. Thus, many tools have been created to make them more effective. This worry about efficiency has been leading in present paper to seek best (and most innovative) way giving largest improvement in these indicators. The approach consists in attaching a signature to frequent market configurations by application of frequent patterns extraction method which is here most appropriate to optimize investment strategies. The goal of proposed trading algorithm is to find most accurate signatures using back testing procedure applied to technical indicators for improving their performance. The problem is then to determine the signatures which, combined with an indicator, outperform this indicator alone. To do this, the FP-Tree algorithm has been preferred, as it appears to be the most efficient algorithm to perform this task.Keywords: quantitative analysis, back-testing, computational models, apriori algorithm, pattern recognition, data mining, FP-tree
Procedia PDF Downloads 3611269 Impact of Gold and Silver Nanoparticles on Terrestrial Flora and Microorganisms
Authors: L. Steponavičiūtė, L. Steponavičienė
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Despite the rapid nanotechnology progress and recognition, its potential impact in ecosystems and health of humans is still not fully known. In this paper, the study of ecotoxicological dangers of nanomaterials is presented. By chemical reduction method, silver (AgNPs) and gold (AuNPs) nanoparticles were synthesized, characterized and used in experiments to examine their impact on microorganisms (Escherichia coli, Staphylococcus aureus and Candida albicans) and terrestrial flora (Phaseolus vulgaris and Lepidium sativum). The results collected during experiments with terrestrial flora show tendentious growth stimulations caused by gold nanoparticles. In contrast to these results, silver nanoparticle solutions inhibited growth of beans and garden cress, compared to control samples. The results obtained from experiments with microorganisms show similarities with ones collected from experiments with terrestrial plants. Samples treated with AuNPs of size 13 nm showed stimulation in the growth of the colonies compared with 3,5 nm size nanoparticles.Keywords: nanomaterials, ecotoxicology, nanoparticles, ecosystems
Procedia PDF Downloads 3081268 Enhancement Dynamic Cars Detection Based on Optimized HOG Descriptor
Authors: Mansouri Nabila, Ben Jemaa Yousra, Motamed Cina, Watelain Eric
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Research and development efforts in intelligent Advanced Driver Assistance Systems (ADAS) seek to save lives and reduce the number of on-road fatalities. For traffic and emergency monitoring, the essential but challenging task is vehicle detection and tracking in reasonably short time. This purpose needs first of all a powerful dynamic car detector model. In fact, this paper presents an optimized HOG process based on shape and motion parameters fusion. Our proposed approach mains to compute HOG by bloc feature from foreground blobs using configurable research window and pathway in order to overcome the shortcoming in term of computing time of HOG descriptor and improve their dynamic application performance. Indeed we prove in this paper that HOG by bloc descriptor combined with motion parameters is a very suitable car detector which reaches in record time a satisfactory recognition rate in dynamic outside area and bypasses several popular works without using sophisticated and expensive architectures such as GPU and FPGA.Keywords: car-detector, HOG, motion, computing time
Procedia PDF Downloads 3231267 Large Neural Networks Learning From Scratch With Very Few Data and Without Explicit Regularization
Authors: Christoph Linse, Thomas Martinetz
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Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets
Procedia PDF Downloads 881266 Expanded Access through Open and Distance Learning in Nigeria
Authors: Okoro Ngozi Priscilla
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Education is the bedrock of development in every nation of the world, and it is very useful in ensuring quality of life for every individual and a better world for the people. Education, therefore, is the basic instrument of economic growth and technological advancement in any society. It is in recognition of this fact that the Nigerian government commits immense resources to ensuring that its citizens acquire education and also policies are being made to ensure the accessibility of education, qualitative higher education is highly recognized as a vital driving force for the socio-economic growth and technological development of nations yet the problem of access to University education in the country persists and therefore brought about the introduction of Open and Distance Learning (ODL) which has as its main objective, the attainment of mass literacy and providing opportunities for those who could not gain admission through designated entrance examination agencies as well as those who could not afford to leave their job to attend a full-time educational programme. Open and distance learning seeks to improve skilled manpower and also improve the skills for those already at work.Keywords: accessibility, open and distant learning programme, fulltime educational programme, distance learning
Procedia PDF Downloads 4581265 Polymorphisms of STAT5A and DGAT1 Genes and Their Associations with Milk Trait in Egyptian Goats
Authors: Othman Elmahdy Othman
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The objectives of this study were to identify polymorphisms in the STAT5A using Restriction Fragment Length Polymorphism and DGAT1 using Single-Strand Conformation Polymorphism genes among three Egyptian goat breeds (Barki, Zaraibi, and Damascus) as well as investigate the effect of their genotypes on milk composition traits of Zaraibi goats. One hundred and fifty blood samples were collected for DNA extraction, 60 from Zaraibi, 40 from Damascus and 50 from Barki breeds. Fat, protein and lactose percentages were determined in Zaraibi goat milk using an automatic milk analyzer. Two genotypes, CC and CT (for STAT5A) and C-C- and C-C+ (for DGAT1), were identified in the three Egyptian goat breeds with different frequencies. The associations between these genotypes and milk fat, protein and lactose were determined in Zaraibi breed. The results showed that the STAT5A genotypes had significant effects on milk yield, protein, fat and lactose with the superiority of CT genotype over CC. Regarding DGAT1 polymorphism, the result showed the only association between it with milk fat where the animals with C-C+ genotype had greater milk fat than animals possess C-C- genotype. The association of combined genotypes with milk trait declared that the does with heterozygous genotypes for both genes are preferred than does with homozygous genotypes where the animals with CTC-C+ have more milk yield, fat and protein than those with CCC-C- genotype. In conclusion, the result showed that C/T and C-/C+ SNPs of STAT5A and DGAT1 genes respectively may be useful markers for assisted selection programs to improve goat milk compositionKeywords: DGAT1, genetic polymorphism, milk trait, STAT5A
Procedia PDF Downloads 1631264 Media, Myth and Hero: Sacred Political Narrative in Semiotic and Anthropological Analysis
Authors: Guilherme Oliveira
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The assimilation of images and their potential symbolism into lived experiences is inherent. It is through this exercise of recognition via imagistic records that the questioning of the origins of a constant narrative stimulated by the media arises. The construction of the "Man" archetype and the reflections of active masculine imagery in the 21st century, when conveyed through media channels, could potentially have detrimental effects. Addressing this systematic behavioral chronology of virile cisgender, permeated imagistically through these means, involves exploring potential resolutions. Thus, an investigation process is initiated into the potential representation of the 'hero' in this media emulation through idols contextualized in the political sphere, with the purpose of elucidating the processes of simulation and emulation of narratives based on mythical, historical, and sacred accounts. In this process of sharing, the narratives contained in the imagistic structuring offered by information dissemination channels seek validation through a process of public acceptance. To achieve this consensus, a visual set adorned with mythological and sacred symbolisms adapted to the intended environment is promoted, thus utilizing sociocultural characteristics in favor of political marketing. Visual recognition, therefore, becomes a direct reflection of a cultural heritage acquired through lived human experience, stimulated by continuous representations throughout history. Echoes of imagery and narratives undergo a constant process of resignification of their concepts, sharpened by their premises, and adapted to the environment in which they seek to establish themselves. Political figures analyzed in this article employ the practice of taking possession of symbolisms, mythological stories, and heroisms and adapt their visual construction through a continuous praxis of emulation. Thus, they utilize iconic mythological narratives to gain credibility through belief. Utilizing iconic mythological narratives for credibility through belief, the idol becomes the very act of release of trauma, offering believers liberation from preconceived concepts and allowing for the attribution of new meanings. To dissolve this issue and highlight the subjectivities within the intention of the image, a linguistic, semiotic, and anthropological methodology is created. Linguistics uses expressions like 'Blaming the Image' to create a mechanism of expressive action in questioning why to blame a construction or visual composition and thus seek answers in the first act. Semiotics and anthropology develop an imagistic atlas of graphic analysis, seeking to make connections, comparisons, and relations between modern and sacred/mystical narratives, emphasizing the different subjective layers of embedded symbolism. Thus, it constitutes a performative act of disarming the image. It creates a disenchantment of the superficial gaze under the constant reproduction of visual content stimulated by virtual networks, enabling a discussion about the acceptance of caricatures characterized by past fables.Keywords: image, heroic narrative, media heroism, virile politics, political, myth, sacred performance, visual mythmaking, characterization dynamics
Procedia PDF Downloads 501263 Plant Leaf Recognition Using Deep Learning
Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath
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Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.Keywords: convolutional autoencoder, anomaly detection, web application, FLASK
Procedia PDF Downloads 1631262 Development of Zinc Oxide Coated Carbon Nanoparticles from Pineapples Leaves Using SOL Gel Method for Optimal Adsorption of Copper ion and Reuse in Latent Fingerprint
Authors: Bienvenu Gael Fouda Mbanga, Zikhona Tywabi-Ngeva, Kriveshini Pillay
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This work highlighted a new method for preparing Nitrogen carbon nanoparticles fused on zinc oxide nanoparticle nanocomposite (N-CNPs/ZnONPsNC) to remove copper ions (Cu²+) from wastewater by sol-gel method and applying the metal-loaded adsorbent in latent fingerprint application. The N-CNPs/ZnONPsNC showed to be an effective sorbent for optimum Cu²+ sorption at pH 8 and 0.05 g dose. The Langmuir isotherm was found to best fit the process, with a maximum adsorption capacity of 285.71 mg/g, which was higher than most values found in other research for Cu²+ removal. Adsorption was spontaneous and endothermic at 25oC. In addition, the Cu²+-N-CNPs/ZnONPsNC was found to be sensitive and selective for latent fingerprint (LFP) recognition on a range of porous surfaces. As a result, in forensic research, it is an effective distinguishing chemical for latent fingerprint detection.Keywords: latent fingerprint, nanocomposite, adsorption, copper ions, metal loaded adsorption, adsorbent
Procedia PDF Downloads 841261 Understanding Work-Related Values of Generation Z: The Lessons for Employers
Authors: Nebojša Janićijević
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The paper presents the results of a study on work-related values of Generation Z, comprised of young people born between the late 1990s and 2010. Following Millennials, Generation Z is the first generation of digital natives. This is the reason, along with some other circumstances that accompanied them during their growing up, why Generation Z has somewhat different work-related values than previous generations. Since they are just beginning to enter the labor market and will be the majority of the workforce in the next decade or two, it is very important and useful for their employers to understand what Generation Z values when it comes to work. The study was conducted by surveying the students of the Faculty of Economics, University of Belgrade, Serbia, during 2022 and 2023. The research results show that Generation Z values safety, achievement, and status the most in the workplace. From the individual perspective, future employees consider it most important that their job provides good working conditions, recognition for the work performed, and the possibility of achievement. It is noticeable that Generation Z students, to a significant extent, expect to be protected and safe at work in the future, both in terms of the job itself and in terms of social relations. According to the research findings, Generation Z is relatively homogeneous, and no significant differences in work-related values were found among them, except by gender.Keywords: generation Z, work related values, students, Serbia
Procedia PDF Downloads 251260 The Influence of Online Audience Response on Journalists
Authors: Raja Arslan Ahmad Khan
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Audience feedback and data play an increasingly crucial role, particularly in the digital age. The advent of digital media and the digitalization of news have given rise to novel forms of audience feedback, markedly different from traditional channels. The engagement of online audiences challenges the conventional role of journalists, introducing a dynamic where audiences can wield both direct and indirect influence. This struggle between the audience and journalists is evident in their contributions and interactions. Media professionals are grappling with challenges such as derogatory remarks, hate speech, online harassment, audience hostility, and attacks from online audiences. The influence of online audiences extends to shaping journalists' daily routines and work practices. Consequently, this study seeks to analyze the impact of online audience feedback on journalists at a routine level within the Malaysian context. Employing a Hierarchy of Influence model as a theoretical framework, the study will utilize a quantitative approach with a snowball survey method. The study's findings aim to enhance our understanding of how online audiences influence journalists and their work practices, encompassing aspects like journalists' autonomy and integrity, editorial decision-making, performance and accountability, daily routines, work practices, as well as the psychological and emotional costs they bear. It's important to note that the study has limitations due to the use of the snowball survey method and its focus within the specific context of Malaysia, making it relatively small in scale.Keywords: online audiences, feedback, influence, journalists, Malaysia
Procedia PDF Downloads 681259 Case Report of Angioedema after Application of Botulinum Toxin
Authors: Sokol Isaraj, Lorela Bendo
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Botulinum toxin is the most commonly used treatment to reduce the appearance of dynamic facial wrinkles. It can smooth out wrinkles and restore a more youthful appearance. Although allergic reactions after botox injection are rare, care should be taken by the physician to diagnose the condition and provide suitable treatment in time. The authors report a case of allergic reaction with angioedema to abobotulinumtoxin A. A 50-year-old woman complaining of dynamic wrinkles was injected in a private clinic with Dysport. After two weeks, she returned to the clinic for the touch-up session. Thirty minutes after the completion of the injections in the crow’s feet area, she described the feeling of mild pain and warmth in the injected area, followed by angioedema. The symptoms couldn’t be controlled by IM corticosteroid, and the patient was referred to a hospital center. After adequate systemic treatment for four days, there was a resolution of the symptoms. Despite the reported safety of abobotulinumtoxin A, this case warns practitioners of unpredictably adverse reactions, which require rapid recognition and intravenous support.Keywords: botulinum toxin, side effects, angioedema, injections
Procedia PDF Downloads 1061258 Automated Feature Detection and Matching Algorithms for Breast IR Sequence Images
Authors: Chia-Yen Lee, Hao-Jen Wang, Jhih-Hao Lai
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In recent years, infrared (IR) imaging has been considered as a potential tool to assess the efficacy of chemotherapy and early detection of breast cancer. Regions of tumor growth with high metabolic rate and angiogenesis phenomenon lead to the high temperatures. Observation of differences between the heat maps in long term is useful to help assess the growth of breast cancer cells and detect breast cancer earlier, wherein the multi-time infrared image alignment technology is a necessary step. Representative feature points detection and matching are essential steps toward the good performance of image registration and quantitative analysis. However, there is no clear boundary on the infrared images and the subject's posture are different for each shot. It cannot adhesive markers on a body surface for a very long period, and it is hard to find anatomic fiducial markers on a body surface. In other words, it’s difficult to detect and match features in an IR sequence images. In this study, automated feature detection and matching algorithms with two type of automatic feature points (i.e., vascular branch points and modified Harris corner) are developed respectively. The preliminary results show that the proposed method could identify the representative feature points on the IR breast images successfully of 98% accuracy and the matching results of 93% accuracy.Keywords: Harris corner, infrared image, feature detection, registration, matching
Procedia PDF Downloads 3041257 A Fuzzy Control System for Reducing Urban Stormwater Runoff by a Stormwater Storage Tank
Authors: Pingping Zhang, Yanpeng Cai, Jianlong Wang
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Stormwater storage tank (SST) is a popular low impact development technology for reducing stormwater runoff in the construction of sponge city. At present, it is difficult to perform the automatic control of SST for reducing peak flow. In this paper, fuzzy control was introduced into the peak control of SST to improve the efficiency of reducing stormwater runoff. Firstly, the design of SST was investigated. A catchment area and a return period were assumed, a SST model was manufactured, and then the storage capacity of the SST was verified. Secondly, the control parameters of the SST based on reducing stormwater runoff were analyzed, and a schematic diagram of real-time control (RTC) system based on peak control SST was established. Finally, fuzzy control system of a double input (flow and water level) and double output (inlet and outlet valve) was designed. The results showed that 1) under the different return periods (one year, three years, five years), the SST had the effect of delayed peak control and storage by increasing the detention time, 2) rainfall, pipeline flow, the influent time and the water level in the SST could be used as RTC parameters, and 3) the response curves of flow velocity and water level fluctuated very little and reached equilibrium in a short time. The combination of online monitoring and fuzzy control was feasible to control the SST automatically. This paper provides a theoretical reference for reducing stormwater runoff and improving the operation efficiency of SST.Keywords: stormwater runoff, stormwater storage tank, real-time control, fuzzy control
Procedia PDF Downloads 2041256 Effect of Early Therapeutic Intervention for the Children With Autism Spectrum Disorders: A Quasi Experimental Design
Authors: Sultana Razia
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The number of children whose social, communication and behavior pattern is affected due to mental and developmental conditions is on the rise. Most of these conditions develop to uncontrollable levels because of ignorance and unaware about their child’s condition. The many myths surrounding mental or developmental conditions are a major cause of families of affected children to develop bitterness and to shy off from seeking appropriate help in time. Several early intervention programs have been put in place, and the number of beneficiaries of these programs is increasing by the day. This research seeks to look into early intervention programs and their effectiveness. The purpose of this study was to investigate the effect of early therapeutic intervention for the children with autism spectrum disorder. Participants were 140 children with autism spectrum disorder from Autism Corner in a selected rehabilitation center of Bangladesh. This study included children who are at age of 18-month to 36-month and who were taking occupational therapy and speech and language therapy from the autism center. They were primarily screened using M-CHAT; however, children with other physical disability or medical conditions excluded. 3-months interventions of 6 sessions per week are a minimum of 45-minutes long per session, one to one interaction followed by parent-led structured home-based therapy were provided. The results indicated that early intensive therapeutic intervention improve understanding, social skills and sensory skills. It can be concluded that therapeutic early intervention a positive effect on diminishing symptoms of Autism Spectrum Disorder.Keywords: M-CHAT, ASD, sensory cheeklist, OT
Procedia PDF Downloads 741255 Unattended Crowdsensing Method to Monitor the Quality Condition of Dirt Roads
Authors: Matias Micheletto, Rodrigo Santos, Sergio F. Ochoa
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In developing countries, the most roads in rural areas are dirt road. They require frequent maintenance since are affected by erosive events, such as rain or wind, and the transit of heavy-weight trucks and machinery. Early detection of damages on the road condition is a key aspect, since it allows to reduce the main-tenance time and cost, and also the limitations for other vehicles to travel through. Most proposals that help address this problem require the explicit participation of drivers, a permanent internet connection, or important instrumentation in vehicles or roads. These constraints limit the suitability of these proposals when applied into developing regions, like in Latin America. This paper proposes an alternative method, based on unattended crowdsensing, to determine the quality of dirt roads in rural areas. This method involves the use of a mobile application that complements the road condition surveys carried out by organizations in charge of the road network maintenance, giving them early warnings about road areas that could be requiring maintenance. Drivers can also take advantage of the early warnings while they move through these roads. The method was evaluated using information from a public dataset. Although they are preliminary, the results indicate the proposal is potentially suitable to provide awareness about dirt roads condition to drivers, transportation authority and road maintenance companies.Keywords: dirt roads automatic quality assessment, collaborative system, unattended crowdsensing method, roads quality awareness provision
Procedia PDF Downloads 1991254 English Pashto Contact: Morphological Adaptation of Bilingual Compound Words in Pashto
Authors: Imran Ullah Imran
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Language contact is a familiar concept in the present global world. Across the globe, languages get mixed up at different levels. Borrowing, code-switching are some of the means through which languages interact. This study examines Pashto-English contact at word and syllable levels. By recording the speech of 30 Pashto native speakers, selected via 'social network' sampling, the study located a number of Pashto-English compound words, which is a unique contact of its kind. In data analysis, tokens were categorized on the basis of their pattern and morphological structure. The study shows that Pashto-English Bilingual Compound words (BCWs) are very prevalent in the Pashto language. The study also found that the BCWs in Pashto are completely productive and have their own meanings. It also shows that the dominant pattern of hybrid words in Pashto is the conjugation of an independent English root word followed by a Pashto inflectional morpheme, which contributes to the core semantic content of the construction. The BCWs construction shows that how both the languages are closer to each other. Pashto-English contact results into bilingual compound and hybrid words, which forms a considerable number of tokens in the present-day spoken Pashto. On the basis of these findings, the study assumes that the same phenomenon may increase with the passage of time that would, in turn, result in the formation of more bilingual compound or hybrid words.Keywords: code-mixing, bilingual compound words, pashto-english contact, hybrid words, inflectional lexical morpheme
Procedia PDF Downloads 2491253 The Rise of Boko Haram in Nigeria: Lesson for Ghana
Authors: Emmanuel Anim
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Ghana has been touted as an oasis of peace in Africa following her relatively peaceful democratic elections, proliferated number of the media, and freedom of speech. Besides, the former Gold Coast country is yet to experience any major incidence of terrorism. Nevertheless, the somewhat occasional simmering violence and conflicts arising from political, religious and chieftaincy skirmishes, largely at its northern part portrays that it is not immune to the political violence of terrorism. The predominantly-based qualitative research reveals that current conditions of socio-politico-economic, and religious issues in Ghana places the West African country on the possible sidelines of the phenomenon of terrorism, when its status quo is juxtaposed with the factors enumerated to have culminated in the rise of Boko Haram, and its accompanying insurgency in Nigeria. Arguing from the perspective of the theory of Social Movement, the analyses and discussions note that the current state of affairs in Ghana could foster domestic terrorism in the country. What is more, the research shows that Ghana faces threats from transnational terrorism given the tendency for elements in Ghana to sympathize and subscribe to the ideological dictates and appeals from Boko Haram and other terrorist organizations. As a consequence, the study recommends that adverse conditions of poverty, poor governance, unemployment, and rising levels of (Islamic) religious radicalization should be remedied by economic improvements, good governance, job creation, and de-radicalization programs by government officials to aid mitigate the incidence of terrorism in the country.Keywords: Boko Haram, Ghana, Nigeria, terrorism
Procedia PDF Downloads 4281252 Low Cost Real Time Robust Identification of Impulsive Signals
Authors: R. Biondi, G. Dys, G. Ferone, T. Renard, M. Zysman
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This paper describes an automated implementable system for impulsive signals detection and recognition. The system uses a Digital Signal Processing device for the detection and identification process. Here the system analyses the signals in real time in order to produce a particular response if needed. The system analyses the signals in real time in order to produce a specific output if needed. Detection is achieved through normalizing the inputs and comparing the read signals to a dynamic threshold and thus avoiding detections linked to loud or fluctuating environing noise. Identification is done through neuronal network algorithms. As a setup our system can receive signals to “learn” certain patterns. Through “learning” the system can recognize signals faster, inducing flexibility to new patterns similar to those known. Sound is captured through a simple jack input, and could be changed for an enhanced recording surface such as a wide-area recorder. Furthermore a communication module can be added to the apparatus to send alerts to another interface if needed.Keywords: sound detection, impulsive signal, background noise, neural network
Procedia PDF Downloads 3201251 Classifications of Sleep Apnea (Obstructive, Central, Mixed) and Hypopnea Events Using Wavelet Packet Transform and Support Vector Machines (VSM)
Authors: Benghenia Hadj Abd El Kader
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Sleep apnea events as obstructive, central, mixed or hypopnea are characterized by frequent breathing cessations or reduction in upper airflow during sleep. An advanced method for analyzing the patterning of biomedical signals to recognize obstructive sleep apnea and hypopnea is presented. In the aim to extract characteristic parameters, which will be used for classifying the above stated (obstructive, central, mixed) sleep apnea and hypopnea, the proposed method is based first on the analysis of polysomnography signals such as electrocardiogram signal (ECG) and electromyogram (EMG), then classification of the (obstructive, central, mixed) sleep apnea and hypopnea. The analysis is carried out using the wavelet transform technique in order to extract characteristic parameters whereas classification is carried out by applying the SVM (support vector machine) technique. The obtained results show good recognition rates using characteristic parameters.Keywords: obstructive, central, mixed, sleep apnea, hypopnea, ECG, EMG, wavelet transform, SVM classifier
Procedia PDF Downloads 3711250 Towards Integrating Statistical Color Features for Human Skin Detection
Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani
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Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.Keywords: color space, neural network, random forest, skin detection, statistical feature
Procedia PDF Downloads 4621249 A Large Language Model-Driven Method for Automated Building Energy Model Generation
Authors: Yake Zhang, Peng Xu
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The development of building energy models (BEM) required for architectural design and analysis is a time-consuming and complex process, demanding a deep understanding and proficient use of simulation software. To streamline the generation of complex building energy models, this study proposes an automated method for generating building energy models using a large language model and the BEM library aimed at improving the efficiency of model generation. This method leverages a large language model to parse user-specified requirements for target building models, extracting key features such as building location, window-to-wall ratio, and thermal performance of the building envelope. The BEM library is utilized to retrieve energy models that match the target building’s characteristics, serving as reference information for the large language model to enhance the accuracy and relevance of the generated model, allowing for the creation of a building energy model that adapts to the user’s modeling requirements. This study enables the automatic creation of building energy models based on natural language inputs, reducing the professional expertise required for model development while significantly decreasing the time and complexity of manual configuration. In summary, this study provides an efficient and intelligent solution for building energy analysis and simulation, demonstrating the potential of a large language model in the field of building simulation and performance modeling.Keywords: artificial intelligence, building energy modelling, building simulation, large language model
Procedia PDF Downloads 261248 Attitude of Tertiary Students on Multiculturalism in Indonesia
Authors: Budi Annisa Sidi
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Present-day Indonesia maintains a narrative of a culturally plural but unified nation. At the same time, multicultural policies extend different degrees of recognition, accommodation, toleration and even discrimination towards different socio-cultural groups. In conjunction with different ethnographic landscapes across regions in Indonesia, this approach leads to a varied experience and understanding of national identity and multiculturalism among people. As a result, governments seeking to maintain national unity while practicing multiculturalism have to juggle different expectations. This situation is examined through the microcosms of university students using questionnaires followed up by focus group discussions and personal interviews. A comparison between university students across four different provinces in Indonesia (Aceh, Jakarta, West Java and the Moluccas) highlights the influence of one’s surroundings on their perception of multiculturalism. Students in the more heterogeneous areas generally show more acceptance towards diversity compared to students in primarily homogenous areas who have little actual experience in dealing with diversity. Regardless of their environment, students claim to have positive feelings and a strong sense of attachment to Indonesia but hold different ideas of what constitutes an ideal Indonesian national identity.Keywords: Indonesia, multiculturalism, national identity, nationalism
Procedia PDF Downloads 2331247 Ethical Decision-Making in AI and Robotics Research: A Proposed Model
Authors: Sylvie Michel, Emmanuelle Gagnou, Joanne Hamet
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Researchers in the fields of AI and Robotics frequently encounter ethical dilemmas throughout their research endeavors. Various ethical challenges have been pinpointed in the existing literature, including biases and discriminatory outcomes, diffusion of responsibility, and a deficit in transparency within AI operations. This research aims to pinpoint these ethical quandaries faced by researchers and shed light on the mechanisms behind ethical decision-making in the research process. By synthesizing insights from existing literature and acknowledging prevalent shortcomings, such as overlooking the heterogeneous nature of decision-making, non-accumulative results, and a lack of consensus on numerous factors due to limited empirical research, the objective is to conceptualize and validate a model. This model will incorporate influences from individual perspectives and situational contexts, considering potential moderating factors in the ethical decision-making process. Qualitative analyses were conducted based on direct observation of an AI/Robotics research team focusing on collaborative robotics for several months. Subsequently, semi-structured interviews with 16 team members were conducted. The entire process took place during the first semester of 2023. Observations were analyzed using an analysis grid, and the interviews underwent thematic analysis using Nvivo software. An initial finding involves identifying the ethical challenges that AI/robotics researchers confront, underlining a disparity between practical applications and theoretical considerations regarding ethical dilemmas in the realm of AI. Notably, researchers in AI prioritize the publication and recognition of their work, sparking the genesis of these ethical inquiries. Furthermore, this article illustrated that researchers tend to embrace a consequentialist ethical framework concerning safety (for humans engaging with robots/AI), worker autonomy in relation to robots, and the societal implications of labor (can robots displace jobs?). A second significant contribution entails proposing a model for ethical decision-making within the AI/Robotics research sphere. The model proposed adopts a process-oriented approach, delineating various research stages (topic proposal, hypothesis formulation, experimentation, conclusion, and valorization). Across these stages and the ethical queries, they entail, a comprehensive four-point comprehension of ethical decision-making is presented: recognition of the moral quandary; moral judgment, signifying the decision-maker's aptitude to discern the morally righteous course of action; moral intention, reflecting the ability to prioritize moral values above others; and moral behavior, denoting the application of moral intention to the situation. Variables such as political inclinations ((anti)-capitalism, environmentalism, veganism) seem to wield significant influence. Moreover, age emerges as a noteworthy moderating factor. AI and robotics researchers are continually confronted with ethical dilemmas during their research endeavors, necessitating thoughtful decision-making. The contribution involves introducing a contextually tailored model, derived from meticulous observations and insightful interviews, enabling the identification of factors that shape ethical decision-making at different stages of the research process.Keywords: ethical decision making, artificial intelligence, robotics, research
Procedia PDF Downloads 791246 An Analytical View to the Habitat Strategies of the Butterfly-Like Insects (Neuroptera: Ascalaphidae)
Authors: Hakan Bozdoğan
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The goal of this paper is to evaluate the species richness, diversity and structure of in different habitats in the Kahramanmaraş Province in Turkey by using a mathematical program called as Geo-Gebra Software. The Ascalaphidae family comprises the most visually remarkable members of the order Neuroptera due to large dimensions, aerial predatory behaviour and dragonfly-like (or even butterfly-like) habits, allowing an immediate recognition also for occasional observers. Otherwise, they are one of the more poorly known families of the order in respect to biology, ecology and especially larval morphology. This discrepancy appears particularly noteworthy considering that it is a fairly large family (ca. 430 species) widely distributed in tropical and temperate areas of the World. The use of Dynamic Geometry, Analytical Softwares provides researchers a great way of visualising mathematical objects and encourage them to carry out tasks to interact with such objects and add to support of their researching. In this study we implemented; Circle with Center Through Point, Perpendicular Line, Vectors and Rays, Segments and Locus to elucidate the ecological and habitat behaviours of Butterfly-like lacewings in an analytical plane by using Geo-Gebra.Keywords: neuroptera, Ascalaphidae, geo-gebra software, habitat selectivity
Procedia PDF Downloads 2791245 Phonological Characteristics of Severe to Profound Hearing Impaired Children
Authors: Akbar Darouie, Mamak Joulaie
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In regard of phonological skills development importance and its influence on other aspects of language, this study has been performed. Determination of some phonological indexes in children with hearing impairment and comparison with hearing children was the objective. A sample of convenience was selected from a rehabilitation center and a kindergarten in Karaj, Iran. Participants consisted of 12 hearing impaired and 12 hearing children (age range: 5 years and 6 months to 6 years and 6 months old). Hearing impaired children suffered from severe to profound hearing loss while three of them were cochlear implanted and the others were wearing hearing aids. Conversational speech of these children was recorded and 50 first utterances were selected to analyze. Percentage of consonant correct (PCC) and vowel correct (PVC), initial and final consonant omission error, cluster consonant omission error and syllabic structure variety were compared in two groups. Data were analyzed with t test (version 16th SPSS). Comparison between PCC and PVC averages in two groups showed a significant difference (P< 0/01). There was a significant difference about final consonant emission error (P<0/001) and initial consonant emission error (P<0/01) too. Also, the differences between two groups on cluster consonant omission were significant (P<0/001). Therefore, some changes were seen in syllabic structures in children with hearing impairment compared to typical group. This study demonstrates some phonological differences in Farsi language between two groups of children. Therefore, it seems, in clinical practices we must notice this issue.Keywords: hearing impairment, phonology, vowel, consonant
Procedia PDF Downloads 2441244 Application of GPRS in Water Quality Monitoring System
Authors: V. Ayishwarya Bharathi, S. M. Hasker, J. Indhu, M. Mohamed Azarudeen, G. Gowthami, R. Vinoth Rajan, N. Vijayarangan
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Identification of water quality conditions in a river system based on limited observations is an essential task for meeting the goals of environmental management. The traditional method of water quality testing is to collect samples manually and then send to laboratory for analysis. However, it has been unable to meet the demands of water quality monitoring today. So a set of automatic measurement and reporting system of water quality has been developed. In this project specifies Water quality parameters collected by multi-parameter water quality probe are transmitted to data processing and monitoring center through GPRS wireless communication network of mobile. The multi parameter sensor is directly placed above the water level. The monitoring center consists of GPRS and micro-controller which monitor the data. The collected data can be monitor at any instant of time. In the pollution control board they will monitor the water quality sensor data in computer using Visual Basic Software. The system collects, transmits and processes water quality parameters automatically, so production efficiency and economy benefit are improved greatly. GPRS technology can achieve well within the complex environment of poor water quality non-monitored, and more specifically applicable to the collection point, data transmission automatically generate the field of water analysis equipment data transmission and monitoring.Keywords: multiparameter sensor, GPRS, visual basic software, RS232
Procedia PDF Downloads 4121243 Comprehensive Analysis of RNA m5C Regulator ALYREF as a Suppressive Factor of Anti-tumor Immune and a Potential Tumor Prognostic Marker in Pan-Cancer
Authors: Yujie Yuan, Yiyang Fan, Hong Fan
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Objective: The RNA methylation recognition protein Aly/REF export factor (ALYREF) is considered one type of “reader” protein acting as a recognition protein of m5C, has been reported involved in several biological progresses including cancer initiation and progression. 5-methylcytosine (m5C) is a conserved and prevalent RNA modification in all species, as accumulating evidence suggests its role in the promotion of tumorigenesis. It has been claimed that ALYREF mediates nuclear export of mRNA with m5C modification and regulates biological effects of cancer cells. However, the systematical regulatory pathways of ALYREF in cancer tissues have not been clarified, yet. Methods: The expression level of ALYREF in pan-cancer and their normal tissues was compared through the data acquired from The Cancer Genome Atlas (TCGA). The University of Alabama at Birmingham Cancer data analysis Portal UALCAN was used to analyze the relationship between ALYREF and clinical pathological features. The relationship between the expression level of ALYREF and prognosis of pan-cancer, and the correlation genes of ALYREF were figured out by using Gene Expression Correlation Analysis database GEPIA. Immune related genes were obtained from TISIDB (an integrated repository portal for tumor-immune system interactions). Immune-related research was conducted by using Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and TIMER. Results: Based on the data acquired from TCGA, ALYREF has an obviously higher-level expression in various types of cancers compared with relevant normal tissues excluding thyroid carcinoma and kidney chromophobe. The immunohistochemical images on The Human Protein Atlas showed that ALYREF can be detected in cytoplasm, membrane, but mainly located in nuclear. In addition, a higher expression level of ALYREF in tumor tissue generates a poor prognosis in majority of cancers. According to the above results, cancers with a higher expression level of ALYREF compared with normal tissues and a significant correlation between ALYREF and prognosis were selected for further analysis. By using TISIDB, we found that portion of ALYREF co-expression genes (such as BIRC5, H2AFZ, CCDC137, TK1, and PPM1G) with high Pearson correlation coefficient (PCC) were involved in anti-tumor immunity or affect resistance or sensitivity to T cell-mediated killing. Furthermore, based on the results acquired from GEPIA, there was significant correlation between ALYREF and PD-L1. It was exposed that there is a negative correlation between the expression level of ALYREF and ESTIMATE score. Conclusion: The present study indicated that ALYREF plays a vital and universal role in cancer initiation and progression of pan-cancer through regulating mitotic progression, DNA synthesis and metabolic process, and RNA processing. The correlation between ALYREF and PD-L1 implied ALYREF may affect the therapeutic effect of immunotherapy of tumor. More evidence revealed that ALYREF may play an important role in tumor immunomodulation. The correlation between ALYREF and immune cell infiltration level indicated that ALYREF can be a potential therapeutic target. Exploring the regulatory mechanism of ALYREF in tumor tissues may expose the reason for poor efficacy of immunotherapy and offer more directions of tumor treatment.Keywords: ALYREF, pan-cancer, immunotherapy, PD-L1
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