Search results for: demonstration wildfire detection and action from space

Authors: Hailyie Tekleselase

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Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

Procedia PDF Downloads 131

Authors: José Eugenio Ortiz, Pierre Plaza, Josefa Herrero, Iván Cabria, José Luis Blanco, Javier Gavilanes, José Ignacio Escavy, Ignacio López-Cilla, Virginia Yagüe, César Pérez, Silvia Rodríguez, Jorge Rico, Cecilia Serrano, Jesús Bernat

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The development of Artificial Intelligence services in mining processes, specifically in aggregate quarries, is facilitating automation and improving numerous aspects of operations. Ultimately, AI is transforming the mining industry by improving efficiency, safety and sustainability. With the ability to analyze large amounts of data and make autonomous decisions, AI offers great opportunities to optimize mining operations and maximize the economic and social benefits of this vital industry. Within the framework of the European DIGIECOQUARRY project, various services were developed for the identification of material quality, production estimation, detection of anomalies and prediction of consumption and production automatically with good results.

Keywords: aggregates, artificial intelligence, automatization, mining operations

Procedia PDF Downloads 92

Authors: Samuel Escandón, María J. Peñaherrera-Vélez, Signe Vargas-Rosvik, Carlos Jerves Córdova, Ximena Vélez-Calvo, Angélica Ochoa-Avilés

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Overweight and obesity are considered risk factors in childhood for developing nutrition-related non-communicable diseases (NCDs), such as diabetes, cardiovascular diseases, and cancer. In Ecuador, 35.4% of 5- to 11-year-olds and 29.6% of 12- to 19-year-olds are overweight or obese. Globally, unhealthy food environments characterized by high consumption of processed/ultra-processed food and rapid urbanization are highly related to the increasing nutrition-related non-communicable diseases. The evidence shows that in low- and middle-income countries (LMICs), fiscal policies and regulatory measures significantly reduce unhealthy food environments, achieving substantial advances in health. However, in some LMICs, little is known about the impact of governments' action to implement healthy food-environment policies. This study aimed to generate evidence on the state of implementation of public policy focused on food environments for the prevention of overweight and obesity in children and adolescents in Ecuador compared to global best practices and to target key recommendations for reinforcing the current strategies. After adapting the INFORMAS' Healthy Food Environment Policy Index (Food‐EPI) to the Ecuadorian context, the Policy and Infrastructure support components were assessed. Individual online interviews were performed using fifty-one indicators to analyze the level of implementation of policies directly or indirectly related to preventing overweight and obesity in children and adolescents compared to international best practices. Additionally, a participatory workshop was conducted to identify the critical indicators and generate recommendations to reinforce or improve the political action around them. In total, 17 government and non-government experts were consulted. From 51 assessed indicators, only the one corresponding to the nutritional information and ingredients labelling registered an implementation level higher than 60% (67%) compared to the best international practices. Among the 17 indicators determined as priorities by the participants, those corresponding to the provision of local products in school meals and the limitation of unhealthy-products promotion in traditional and digital media had the lowest level of implementation (34% and 11%, respectively) compared to global best practices. The participants identified more barriers (e.g., lack of continuity of effective policies across government administrations) than facilitators (e.g., growing interest from the Ministry of Environment because of the eating-behavior environmental impact) for Ecuador to move closer to the best international practices. Finally, within the participants' recommendations, we highlight the need for policy-evaluation systems, information transparency on the impact of the policies, transformation of successful strategies into laws or regulations to make them mandatory, and regulation of power and influence from the food industry (conflicts of interest). Actions focused on promoting a more active role of society in the stages of policy formation and achieving more articulated actions between the different government levels/institutions for implementing the policy are necessary to generate a noteworthy impact on preventing overweight and obesity in children and adolescents. Including systems for internal evaluation of existing strategies to strengthen successful actions, create policies to fill existing gaps and reform policies that do not generate significant impact should be a priority for the Ecuadorian government to improve the country's food environments.

Keywords: children and adolescents, food-EPI, food policies, healthy food environment

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Authors: Mansoureh Zangiabadi, Shamil Velji, Rajendra Kelkar, Neal Wade, Volker Pickert

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The EU has set itself a long-term goal of reducing greenhouse gas emissions by 80-95% of the 1990 levels by 2050 as set in the Energy Roadmap 2050. This paper reports on the European Union H2020 funded E-Lobster project which demonstrates tools and technologies, software and hardware in integrating the grid distribution, and the railway power systems with power electronics technologies (Smart Soft Open Point - sSOP) and local energy storage. In this context this paper describes the existing policies and regulatory frameworks of the energy market at European level with a special focus then at National level, on the countries where the members of the consortium are located, and where the demonstration activities will be implemented. By taking into account the disciplinary approach of E-Lobster, the main policy areas investigated includes electricity, energy market, energy efficiency, transport and smart cities. Energy storage will play a key role in enabling the EU to develop a low-carbon electricity system. In recent years, Energy Storage System (ESSs) are gaining importance due to emerging applications, especially electrification of the transportation sector and grid integration of volatile renewables. The need for storage systems led to ESS technologies performance improvements and significant price decline. This allows for opening a new market where ESSs can be a reliable and economical solution. One such emerging market for ESS is R+G management which will be investigated and demonstrated within E-Lobster project. The surplus of energy in one type of power system (e.g., due to metro braking) might be directly transferred to the other power system (or vice versa). However, it would usually happen at unfavourable instances when the recipient does not need additional power. Thus, the role of ESS is to enhance advantages coming from interconnection of the railway power systems and distribution grids by offering additional energy buffer. Consequently, the surplus/deficit of energy in, e.g. railway power systems, is not to be immediately transferred to/from the distribution grid but it could be stored and used when it is really needed. This will assure better energy management exchange between the railway power systems and distribution grids and lead to more efficient loss reduction. In this framework, to identify the existing policies and regulatory frameworks is crucial for the project activities and for the future development of business models for the E-Lobster solutions. The projections carried out by the European Commission, the Member States and stakeholders and their analysis indicated some trends, challenges, opportunities and structural changes needed to design the policy measures to provide the appropriate framework for investors. This study will be used as reference for the discussion in the envisaged workshops with stakeholders (DSOs and Transport Managers) in the E-Lobster project.

Keywords: light railway, electrical distribution network, Electrical Energy Storage, policy

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Authors: Ripon Sarkar, Kabita Chaterjee, Ananya Barui

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Smoking is one of the leading causes of oral cancer. Cigarette smoke affects various cellular parameters and alters molecular metabolism of cells. Epithelial cells losses their cytoskeleton structure, membrane integrity, cellular polarity that subsequently initiates the process of epithelial cells to mesenchymal transition due to long exposure of cigarette smoking. It changes the normal cellular metabolic activity which induces oxidative stress and enhances the reactive oxygen spices (ROS) formation. Excessive ROS and associated oxidative stress are considered to be a driving force in alteration in cellular phenotypes, polarity distribution and mitochondrial metabolism. Noninvasive assessment of such parameters plays essential role in development of routine screening system for early diagnosis of oral cancer. Electrical cell-substrate impedance sensing (ECIS) is one of such method applied for detection of cellular membrane impedance which can be correlated to cell membrane integrity. Present study intends to explore the alteration in cellular impedance along with the expression of cellular polarity molecules and cytoskeleton distributions in oral epithelial cells of habitual smokers and to correlate the outcome to that of clinically diagnosed oral leukoplakia and oral squamous cell carcinoma patients. Total 80 subjects were categorized into four study groups: nonsmoker (NS), cigarette smoker (CS), oral leukoplakia (OLPK) and oral squamous cell carcinoma (OSCC). Cytoskeleton distribution was analyzed by staining of actin filament and generation of ROS was measured using assay kit using standard protocol. Cell impedance was measured through ECIS method at different frequencies. Expression of E-cadherin and protease-activated receptor (PAR) proteins were observed through immune-fluorescence method. Distribution of actin filament is well organized in NS group however; distribution pattern was grossly varied in CS, OLPK and OSCC. Generation of ROS was low in NS which subsequently increased towards OSCC. Expressions of E-cadherin and change in cellular electrical impedance in different study groups indicated the hallmark of cancer progression from NS to OSCC. Expressions of E-cadherin, PAR protein, and cell impedance were decreased from NS to CS and farther OSCC. Generally, the oral epithelial cells exhibit apico-basal polarity however with cancer progression these cells lose their characteristic polarity distribution. In this study expression of polarity molecule and ECIS observation indicates such altered pattern of polarity among smoker group. Overall the present study monitored the alterations in intracellular ROS generation and cell metabolic function, membrane integrity in oral epithelial cells in cigarette smokers. Present study thus has clinical significance, and it may help in developing a noninvasive technique for early diagnosis of oral cancer amongst susceptible individuals.

Keywords: cigarette smoking, early oral cancer detection, electric cell-substrate impedance sensing, noninvasive screening

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Authors: Sachin Kumar

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Fuzzy fractional diffusion equation is widely useful to depict different physical processes arising in physics, biology, and hydrology. The motive of this article is to deal with the fuzzy fractional diffusion equation. We study a mathematical model of fuzzy space-time fractional diffusion equation in which unknown function, coefficients, and initial-boundary conditions are fuzzy numbers. First, we find out a fuzzy operational matrix of Legendre polynomial of Caputo type fuzzy fractional derivative having a non-singular Mittag-Leffler kernel. The main advantages of this method are that it reduces the fuzzy fractional partial differential equation (FFPDE) to a system of fuzzy algebraic equations from which we can find the solution of the problem. The feasibility of our approach is shown by some numerical examples. Hence, our method is suitable to deal with FFPDE and has good accuracy.

Keywords: fractional PDE, fuzzy valued function, diffusion equation, Legendre polynomial, spectral method

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Authors: Zhenqiu Liu

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Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

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Authors: Zeineb Deymi-Gheriani

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In the last two decades, one can clearly observe a boom of interest for e-learning and web-supported programs. However, one can also notice that many of these programs focus on the accumulation and delivery of content generally as a business industry with no much concern for theoretical underpinnings. The existing research, at least in online English language teaching (ELT), has demonstrated a lack of an effective online teaching pedagogy anchored in a well-defined theoretical framework. Hence, this paper comes as an attempt to present constructivism as one of the theoretical bases for the design of an effective online language teaching pedagogy which is at the same time technologically intelligent and theoretically informed to help envision how education can best take advantage of the information and communication technology (ICT) tools. The present paper discusses the key principles underlying constructivism, its implications for online language teaching design, as well as its limitations that should be avoided in the e-learning instructional design. Although the paper is theoretical in nature, essentially based on an extensive literature survey on constructivism, it does have practical illustrations from an action research conducted by the author both as an e-tutor of English using Moodle online educational platform at the Virtual University of Tunis (VUT) from 2007 up to 2010 and as a face-to-face (F2F) English teaching practitioner in the Professional Certificate of English Language Teaching Training (PCELT) at AMIDEAST, Tunisia (April-May, 2013).

Keywords: active learning, constructivism, experiential learning, Piaget, Vygotsky

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Authors: Pius W. Molo Chin

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Real life problems such as the Huxley equation are always modeled as nonlinear differential equations. These problems need accurate and reliable methods for their solutions. In this paper, we propose a nonstandard finite difference method in time and the Galerkin combined with the compactness method in the space variables. This coupled method, is used to analyze a two dimensional Huxley equation for the existence and uniqueness of the continuous solution of the problem in appropriate spaces to be defined. We proceed to design a numerical scheme consisting of the aforementioned method and show that the scheme is stable. We further show that the stable scheme converges with the rate which is optimal in both the L2 as well as the H1-norms. Furthermore, we show that the scheme replicates the decaying qualities of the exact solution. Numerical experiments are presented with the help of an example to justify the validity of the designed scheme.

Keywords: Huxley equations, non-standard finite difference method, Galerkin method, optimal rate of convergence

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Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

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Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

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Authors: Sabah El-Sawalhi, Elie Fayad, Roula M. Abdel-Massih

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Ilex paraguariensis (Yerba Mate) is a medium to large tree commonly consumed by South Americans. Its leaves and stems are associated with different biological activities. The purpose of this study was to evaluate the antibacterial activity of Yerba Mate against Gram-positive and Gram-negative bacterial strains and its action against some resistant bacteria with different resistance profiles. Yerba Mate aqueous extracts were prepared at 70°C for 2 hrs, and the microdilution method was used to determine the minimum inhibitory concentration (MIC). Gram-positive bacteria exhibited a stronger antibacterial activity (MIC ranged between 0.468 mg/mL and 15 mg/mL) than Gram-negative bacteria. Yerba Mate was also extracted with acetone: water (1:1) and then further sub-fractionated with hexane, chloroform, and ethyl acetate. MIC values against Staphylococcus aureus ranged from 0.78 to 2.5 mg/ml for the chloroform fraction, from 1.56 to 3.75 mg/ml for the ethyl acetate fraction, and 0.78 to 1.87 mg/ml for the water fraction. The water fraction also exhibited antibacterial activity against Salmonella species (MIC ranged from 1.56 mg/ml to 3.12 mg/ml). The water fraction exhibited the highest antibacterial activity among all the fractions obtained. More studies are needed to determine the molecule or molecules responsible for this activity.

Keywords: antibacterial activity, bacterial resistance, minimum inhibitory concentration, yerba mate

Procedia PDF Downloads 148

Authors: R. Gadea, J. M. Monzó, F. J. Puertas, M. Castro, A. Tebar, P. J. Fito, R. J. Colom

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There exists a wide array of ailments impacting the structural soundness of the esophageal walls, predominantly linked to digestive issues. Presently, the techniques employed for identifying esophageal tract complications are excessively invasive and discomforting, subjecting patients to prolonged discomfort in order to achieve an accurate diagnosis. This study proposes the creation of a sensor with profound measuring capabilities designed to detect fluids coursing through the esophageal tract. The multi-sensor detection system relies on radiofrequency photospectrometry. During experimentation, individuals representing diverse demographics in terms of gender and age were utilized, positioning the sensors amidst the trachea and diaphragm and assessing measurements in vacuum conditions, water, orange juice, and saline solutions. The findings garnered enabled the identification of various liquid mediums within the esophagus, segregating them based on their ionic composition.

Keywords: radiofrequency spectrophotometry, medical device, gastroesophageal disease, photonics

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Authors: Balachandra Kumaraswamy, P. G. Poonacha

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Automatic Music Information Retrieval has been one of the challenging topics of research for a few decades now with several interesting approaches reported in the literature. In this paper we have developed a pitch extraction method based on a finite Fourier series approximation to the given window of samples. We then estimate pitch as the fundamental period of the finite Fourier series approximation to the given window of samples. This method uses analysis of the strength of harmonics present in the signal to reduce octave as well as harmonic errors. The performance of our method is compared with three best known methods for pitch extraction, namely, Yin, Windowed Special Normalization of the Auto-Correlation Function and Harmonic Product Spectrum methods of pitch extraction. Our study with artificially created signals as well as music files show that Fourier Approximation method gives much better estimate of pitch with less octave and harmonic errors.

Keywords: pitch, fourier series, yin, normalization of the auto- correlation function, harmonic product, mean square error

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Authors: Rafat M. Mohareb

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Several D-ring alkylated estrone analogues display exceptionally high affinity for estrogen receptors. In particular, compounds in which an E-ring is formed are known to be involved in the inhibition of steroidogenic enzymes. Such compounds also have an effect on steroid dehydrogenase activity and the ability to inhibit the detrimental action of the steroid sulfatase enzyme. Generally, E-ring extended steroids have been accessed by modification of the C17-ketone in the D-ring by either arylimine or oximino formation, addition of a carbon nucleophile or hydrazone formation. Other approaches have included ketone reduction, silyl enol ether formation or ring-closing metathesis (giving five- or six-membered E-rings). Chemical modification of the steroid D-ring provides a way to alter the functional groups, sizes and stereochemistry of the D-ring, and numerous structure-activity relationships have been established by such synthetic alterations. Steroids bearing heterocycles fused to the D-ring of the steroid nucleus have been of pharmaceutical interest. In the present paper, we report on the efficient synthesis of estrone possessing pyran, pyrimidine and thiazole ring systems. This study focused on the synthesis and biochemical evaluation of newly synthesized heterocyclic compounds which were then subjected through inhibitory evaluations towards human cancer and normal cell lines.

Keywords: estrone, heterocyclization, cytotoxicity, biomedicine

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Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

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Authors: Adnan Baig, Ishteeaq Naeem, Saad Mansoor

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The Internet of Things (IoT) gadgets have advanced quickly in recent years, and their use is steadily rising daily. However, cyber-attackers can target these gadgets due to their distributed nature. Additionally, many IoT devices have significant security flaws in their implementation and design, making them vulnerable to security threats. Hence, these threats can cause important data security and privacy loss from a single attack on network devices or systems. Botnets are a significant security risk that can harm the IoT network; hence, sophisticated techniques are required to mitigate the risk. This work uses a machine learning-based method to identify IoT orchestrated by botnets. The proposed technique identifies the net attack by distinguishing between legitimate and malicious traffic. This article proposes a hyperparameter tuning model to improvise the method to improve the accuracy of existing processes. The results demonstrated an improved and more accurate indication of botnet-based cyber-attacks.

Keywords: Internet of Things, Botnet, BoT-IoT dataset, ML techniques

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Authors: Y. Laib Dit Leksir, S. Bouhouche

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Analysis and processing of data bases resulting from infrared thermal measurements made on the electrical installation requires the development of new tools in order to obtain correct and additional information to the visual inspections. Consequently, the methods based on the capture of infrared digital images show a great potential and are employed increasingly in various fields. Although, there is an enormous need for the development of effective techniques to analyse these data base in order to extract relevant information relating to the state of the equipments. Our goal consists in introducing recent techniques of modeling based on new methods, image and signal processing to develop mathematical models in this field. The aim of this work is to capture the anomalies existing in electrical equipments during an inspection of some machines using A40 Flir camera. After, we use binarisation techniques in order to select the region of interest and we make comparison between these methods of thermal images obtained to choose the best one.

Keywords: infrared thermography, defect detection, troubleshooting, electrical equipment

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Authors: J. D. Martínez-Vargas, C. Castro-Hoyos, G. Castellanos-Dominguez

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In this work, we propose a novel approach for measuring the stationarity level of a multichannel time-series. This measure is based on a stationarity definition over time-varying spectrum, and it is aimed to quantify the relation between local stationarity (single-channel) and global dynamic behavior (multichannel dynamics). To assess the proposed approach validity, we use a well known EEG-BCI database, that was constructed for separate between motor/imagery tasks. Thus, based on the statement that imagination of movements implies an increase on the EEG dynamics, we use as discriminant features the proposed measure computed over an estimation of the non-stationary components of input time-series. As measure of separability we use a t-student test, and the obtained results evidence that such measure is able to accurately detect the brain areas projected on the scalp where motor tasks are realized.

Keywords: stationary measure, entropy, sub-space projection, multichannel dynamics

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Authors: Sihem Chaibeddra, Fatoum Kharchi

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This study deals with the characterization of stabilized earth in the field of construction from the behavior under changes in conservation conditions that may occur during the lifetime of the material, namely, the exposure to high humidity and temperature variations. These two parameters are involved increasingly, because of climate changes that are confronting earth-based constructions to conditions for which they were not originally designed. These exposure conditions may affect the long-term behavior of the material and the entire structure. A cement treatment was adopted for stabilizing the earth with dosages ranging from 4, 6, 8 to 10%. The influence of addition percentage was analyzed in this context based on laboratory tests measuring the evolution of compressive strength, rate of absorption and shrinkage, and finally thermal conductivity. It was shown that the behaviour was dependent on the ambient conditions which influence the action of the binder. Temperate cure has proved beneficial for the material as the cement content increased. Moisture has less affected the compressive strength with increasing the cement content. The absorption was reduced with the increase of cement dosage. Regarding the variation of shrinkage, cement assays have presented an optimum value beyond which the addition of further quantities was less advantageous. The thermal conductivity on the other hand, increased with increasing cement content, which decreased the insulating properties of the material.

Keywords: behavior, characterization, construction, earth, stabilization

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Authors: Jonathon Smith, Alba Agostino

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Autism, also referred to as autism spectrum disorder (ASD), is commonly associated with difficulties in social and communication skills. Other characteristics common to autistic individuals include repetitive behaviours, difficulties adhering to routine, as well as paying attention. Recent findings indicate that autism is the fastest-growing neurodevelopmental disorder in North America, yet programming aimed at improving the quality of autistic individual’s real-world social interactions is limited. Although there are social skills programs for autistic youth, participation appears to improve social knowledge, but that knowledge does not improve social competence or transfer to the participant’s daily social interactions. Peers are less likely to interact with autistic people based thin slice judgements, meaning that even when an autistic youth has successfully completed a social skills program, they most likely will still be rejected by peers and not have a social group to participate in. Recently, many researchers are exploring therapeutic interventions using Dungeon and Dragons (D&D) for conditions such as social anxiety, loneliness, and identity exploration. D&D is a table-top role-playing game (TTRPG) based on social play experience where the players must communicate, plan, negotiate, and compromise with other players to achieve a shared goal. The game encourages players to assume the role of their character and act out their play within the rules of the game with the guidance of the games dungeon master. The popularity Dungeons and Dragons has increased at a rapid rate, and many suggest that there social-emotional benefits of joining and participating in these types of gaming experiences, however this is an under researched topic and studies examining the benefits of such games is lacking in the field. The main purpose of this exploratory study is to examine the autistic youth’s experiences of participating in a D&D club. Participants of this study were four high functioning autistic youth between the ages of 14-18 (average age – 16) enrolled in a D&D Club that was specifically designed for neurodiverse youth. The youth participation with the club ranged from 4 months to 8 months. All participants completed a 30–40-minute semi-structured interview where they were able to express their perceptions as participants of the D&D club. Preliminary findings suggest that the game provided a place for the youth to engage in authentic social interactions. Additionally, preliminary results suggest that the youth report being in a positive space with other neurodivergent youth created an atmosphere where they felt confident and could connect with others. The findings from this study will aid clinicians, researchers, and educators in developing programming aimed at improving social interactions and connections for autistic youth.

Keywords: autism, social connection, dungeons and dragons, neurodivergent affirming space

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Authors: Y. Atibi, A. Boutaleb Joutei, T. Slimani

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Insecticidal properties of Alliaceae are widely known, they are plant with varied biological properties. Garlic and onion are known for their positive effect on health, including the prevention of cardiovascular disease and some digestive cancers. These health benefits molecules are also responsible for pest potential control of Alliaceae. With these properties, we can consider using Alliaceae as acaricides. The purpose of this study was to compare the effect of chemical and biopesticides on citrus mites, especially Tetranychus urticae, Panonychus citri and Eutetranychus orientalis. Chemical treatment (Dicofol) and biopesticides (Garlic juice + Alcohol) applied on this study to control the various stages of mites, have reduced the proliferation of mobile forms and reducing the number of eggs to acceptable levels. Garlic juice + alcohol revealed efficiency from 50 to 57.69 % against the mobile forms of T. urticae, however, it was effective against the mobile forms of P. citri and E. orientalis with an efficiency of 85.71 % and 100 % respectively, its action has also reduced the number of eggs of T. urticae and E. orientalis at low levels. Therefore, this biopesticide is conceivable viewpoint technical and economic as the infestation by mite is low.

Keywords: Garlic juice, acaricide, biopesticide, mites, alcohol, Tetranychus urticae, Panonychus citri, Eutetranychus orientalis.

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Authors: Man Guo

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This paper delves into the intricate interplay between spatial morphology and spatial cognition in Lidukou Village, utilizing a combined approach of spatial syntax and field data. Through a comparative analysis of the gathered data, it emerges that the spatial integration level of Lidukou Village exhibits a direct positive correlation with the spatial cognitive preferences of its inhabitants. Specifically, the areas within the village that exhibit a higher degree of spatial cognition are predominantly distributed along the axis primarily defined by Shuxiang Road. However, the accessibility to historical relics remains limited, lacking a coherent systemic relationship. To address the morphological challenges faced by Lidukou Village, this study proposes optimization strategies that encompass diverse perspectives, including the refinement of spatial mechanisms and the shaping of strategic spatial nodes.

Keywords: traditional villages, spatial syntax, spatial integration degree, morphological problem

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Authors: Tian-Fang Kang, Chao-Nan Ge, Rui Li

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An electrochemical biosensor for the determination of organophosphorus pesticides was developed based on electrochemical co-deposition of Au and Pd nanoparticles on glassy carbon electrode (GCE). Energy disperse spectroscopy (EDS) analysis was used for characterization of the surface structure. Scanning electron micrograph (SEM) demonstrates that the films are uniform and the nanoclusters are homogeneously distributed on the GCE surface. Acetylcholinesterase (AChE) was immobilized on the Au and Pd nanoparticle modified electrode (Au-Pd/GCE) by cross-linking with glutaraldehyde. The electrochemical behavior of thiocholine at the biosensor (AChE/Au-Pd/GCE) was studied. The biosensors exhibited substantial electrocatalytic effect on the oxidation of thiocholine. The peak current of linear scan voltammetry (LSV) of thiocholine at the biosensor is proportional to the concentration of acetylthiocholine chloride (ATCl) over the range of 2.5 × 10-6 to 2.5 × 10-4 M in 0.1 M phosphate buffer solution (pH 7.0). The percent inhibition of acetylcholinesterase was proportional to the logarithm of parathion concentration in the range of 4.0 × 10-9 to 1.0 × 10-6 M. The detection limit of parathion was 2.6 × 10-9 M. The proposed method exhibited high sensitivity and good reproducibility.

Keywords: acetylcholinesterase, Au-Pd nanoparticles, electrochemical biosensors, parathion

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Authors: Shahram Payandeh

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This paper presents an overview of a model which can be used as a part of a decision support system when fusing information from multiple sensing environment. Data fusion has been widely studied in the past few decades and numerous frameworks have been proposed to facilitate decision making process under uncertainties. Multi-sensor data fusion technology plays an increasingly significant role during people tracking and activity recognition. This paper presents an overview of a quantum model as a part of a decision-making process in the context of multi-sensor data fusion. The paper presents basic definitions and relationships associating the decision-making process and quantum model formulation in the presence of uncertainties.

Keywords: quantum model, sensor space, sensor network, decision support

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Authors: Mercy Chepkirui, Paul Orina, Robin Abell, Leonard Akwany, Tonny Orina, Mercy Matuma, Rasowo Joseph

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Lake jipe, a shared water resource between Kenya and Tanzania located at the East African Coast, is under multiple pressures. The lake has receded from 30Km2 to 27.32Km2 due to prolonged dry spells and intensified water abstraction for irrigation and re-route to Mungu ya Nyumba Dam in Tanzania. Agricultural activities have significantly (90%) contributed to the lake levels decline and further affected the lakes’ aquatic biodiversity. Among the most affected are the commercially important endemic fish species of the lake, of which Oreochromis jipe has experienced the greatest decline. Overfishing, use of illegal unreported and unregulated fishing gears, intensified fishing along protected fish breeding areas as well as poor management and uncoordinated conservation efforts have significantly contributed to the decline of fish catches from 348 kg of O. jipe in 2016 to 90 kg daily catches in 2022. Therefore, the lake is on the verge of extinction if no action is taken. This calls for awareness of the significance of the L. Jipe ecosystems and its immediate and long-term benefits. Further, there is a need to revive alternative economic activities, including aquaculture and sustainable agriculture, to offer alternative livelihood to local communities.

Keywords: biodiversity, ecosystem, conservation, fisheries

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Authors: Fatih Tarlak

Abstract:

Predictive microbiology can be considered as an important field in food microbiology in which it uses predictive models to describe the microbial growth in different food products. Predictive models estimate the growth of microorganisms quickly, efficiently, and in a cost-effective way as compared to traditional methods of enumeration, which are long-lasting, expensive, and time-consuming. The mathematical models used in predictive microbiology are mainly categorised as primary and secondary models. The primary models are the mathematical equations that define the growth data as a function of time under a constant environmental condition. The secondary models describe the effects of environmental factors, such as temperature, pH, and water activity (aw) on the parameters of the primary models, including the maximum specific growth rate and lag phase duration, which are the most critical growth kinetic parameters. The combination of primary and secondary models provides valuable information to set limits for the quantitative detection of the microbial spoilage and assess product shelf-life.

Keywords: shelf-life, growth model, predictive microbiology, simulation

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Authors: R. Sharma, J. K. Bhatnagar, Poonam, R. C. Sharma

Abstract:

Metal–air batteries have been designed and developed as an essential source of electric power to propel automobiles, make electronic equipment functional, and use them as the source of power in remote areas and space. High energy and power density, lightweight, easy recharge capabilities, and low cost are essential features of these batteries. Both primary and rechargeable magnesium air batteries are highly promising. Our focus will be on the basics of electrode reaction kinetics of Mg–air cell in this paper. Design and development of Mg or Mg alloys as anode materials, design and composition of air cathode, and promising electrolytes for Mg–air batteries have been reviewed. A brief note on the possible and proposed improvements in design and functionality is also incorporated. This article may serve as the primary and premier document in the critical research area of Mg-air battery systems.

Keywords: air cathode, battery design, magnesium air battery, magnesium anode, rechargeable magnesium air battery

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Authors: Degale Desta, Cheng Jian

Abstract:

The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

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Authors: Magy Magdy Danial Riad

Abstract:

Introduction: Glycosides: Enzymatic and hydrolysis reactions of glycosides, mechanism of action, SAR, therapeutic uses and toxicity of glycosides. Cardiac glycosides of digitalis, bufa and squill. Structure of salicin, hesperidin and rutin. Glycosides are certain molecules in which a sugar part is bound to some other part. Glycosides play numerous important roles in living organisms. Formally, a glycoside is any molecule in which a sugar group is bonded through its anomeric carbon to another group and form glycosidic bonds via an O-glycosidic bond or an S-glycosidic bond; glycosides involving the latter are also called thioglycosides. The purpose: the addition of sugar be bonded to a non-sugar for the molecule to qualify as a glycoside, The sugar group is then known as the glycone and the non-sugar group as the aglycone or genin part of the glycoside. The glycone can consist of a single sugar group (monosaccharide) or several sugar groups (oligosaccharide). The glycone and aglycone portions can be chemically separated by hydrolysis in the presence of acid. Methods: There are also numerous enzymes that can form and break glycosidic bonds. Results: The most important cleavage enzymes are the glycoside hydrolases, and the most important synthetic enzymes in nature are glycosyltransferases. Mutant enzymes termed glycosynthases have been developed that can form glycosidic bonds. Conclusions: There are a great many ways to chemically synthesize glycosidic bonds.

Keywords: glycosides, bufa, squill, thioglycosides

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Authors: Nikolaos Georgoulopoulos, Alkis Hatzopoulos, Konstantinos Karamitsios, Konstantinos Kotrotsios, Alexandros I. Metsai

Abstract:

In modern server systems, business critical applications run in different types of infrastructure, such as cloud systems, physical machines and virtualization. Often, due to high load and over time, various hardware faults occur in servers that translate to errors, resulting to malfunction or even server breakdown. CPU, RAM and hard drive (HDD) are the hardware parts that concern server administrators the most regarding errors. In this work, selected RAM, HDD and CPU errors, that have been observed or can be simulated in kernel ring buffer log files from two groups of Linux servers, are investigated. Moreover, a severity characterization is given for each error type. Better understanding of such errors can lead to more efficient analysis of kernel logs that are usually exploited for fault diagnosis and prediction. In addition, this work summarizes ways of simulating hardware errors in RAM and HDD, in order to test the error detection and correction mechanisms of a Linux server.

Keywords: hardware errors, Kernel logs, Linux servers, RAM, hard disk, CPU

Procedia PDF Downloads 161