Search results for: isolation forest method

Authors: Bohsiu Wu

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Among serious crimes, child homicide is a rather rare event. However, the killing of children stirs up a special type of emotion in society that pales other criminal acts. This study examines the relevancy of three possible community-level explanations for child homicide: social deprivation, female empowerment, and social isolation. The social deprivation hypothesis posits that child homicide results from lack of resources in communities. The female empowerment hypothesis argues that a higher female status translates into a higher level of capability to prevent child homicide. Finally, the social isolation hypothesis regards child homicide as a result of lack of social connectivity. Child homicide data, aggregated by US postal ZIP codes in California from 1990 to 1999, were analyzed with a negative binomial regression. The results of the negative binomial analysis demonstrate that social deprivation is the most salient and consistent predictor among all other factors in explaining child homicide victimization at the ZIP-code level. Both social isolation and female labor force participation are weak predictors of child homicide victimization across communities. Further, results from the negative binomial regression show that it is the communities with a higher, not lower, degree of female labor force participation that are associated with a higher count of child homicide. It is possible that poor communities with a higher level of female employment have a lesser capacity to provide the necessary care and protection for the children. Policies aiming at reducing social deprivation and strengthening female empowerment possess the potential to reduce child homicide in the community.

Keywords: child homicide, deprivation, empowerment, isolation

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Authors: Rozalina Keremedchieva, Ivan Svinyarov, Milen G. Bogdanov

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In continuation of a research project on the application of ionic liquids (ILs) as an alternative to the conventional organic solvents used in the recovery of value added chemicals of industrial interest1-3 we developed a procedure for back extraction and isolation in pure form of the biologically active alkaloid glaucine from IL-based aqueous solutions. One of the approaches applied was the formation of two-phase systems (IL-ATPS) by the addition of kosmotropic salts to the plant extract. The ability of the salts (Na2CO3, MgSO4, (NH4)2SO4, NaH2PO4) to induce the formation of two-phase systems and the influence of pH value on the partition coefficients of glaucine was comprehensively studied. As a result, it was found that the target alkaloid is preferably partitioned into the IL-rich phase regardless of the pH value of the medium and thus shows the inapplicability of the approach used for the isolation of the target compound from the ionic liquid. However, the results obtained can be used as a platform for the development of an analytical method for the quantitative determination of low concentrations of glaucine in biological samples. We further examined the ability of a series of organic solvents such as diethyl ether, Tert-butylmethyl ether, ethyl acetate, butyl acetate, toluene, chloroform, dichloromethane to recover glaucine form raw IL-based aqueous extracts. Optimal conditions for quantitative extraction of glaucine into chloroform were found from which, after removal of the solvent and subsequent recrystallization from ethanol, the target compound was isolated in a high purity as a hydrobromide salt – The form in which it entrance as an active ingredient in various medicines.

Keywords: natural products, ionic liquids, solid-liquid extraction, liquid-liquid extraction

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Authors: Riffat Sultana Pathan, Waheed Ali Panhwar, Muhammad Saeed Wagan

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Tettigonioidea are phytophagous insects damaging agricultural crops, forest, fruit orchards, berry shrubs, and grasses. The material was collected from different agricultural fields of rice, sugarcane, wheat, maize surrounding by different grasses. Beside this, forest, hilly areas, semi-desert and desert regions were also inspected time to time. All material was captured, killed and stored by using the standard entomological method. As a result of extensive survey fair numbers were captured from the different climatic zone of country. Seven sub-families of Tettigonioidea viz: Pseudophyllinae, Phaneropterinae, Conocephalinae, Tettigoniinae, Hexacentrinae, Mecopodinae and Decticinae came in collection. This fauna contributes 29 new records to Pakistan and 5 new species to science. Beside this, a brief description of each supra-generic category of Tettigonioidea along with photographs and synonymy is also documented. In addition to this, detailed list of host plants from Pakistan was also composed. This study provides important data for Integrated Pest Management (IPM) of Tettigonioidea biodiversity conservation and grassland restoration in Pakistan.

Keywords: agriculture, conocephalinae, pest, phaneropterinae, tettigoniidae

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Authors: Rama Debbarma

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The present study deals with the performance of Linear base isolation system to mitigate seismic response of structures characterized by random system parameters. This involves optimization of the tuning ratio and damping properties of the base isolation system considering uncertain system parameters. However, the efficiency of base isolator may reduce if it is not tuned to the vibrating mode it is designed to suppress due to unavoidable presence of system parameters uncertainty. With the aid of matrix perturbation theory and first order Taylor series expansion, the total probability concept is used to evaluate the unconditional response of the primary structures considering random system parameters. For this, the conditional second order information of the response quantities are obtained in random vibration framework using state space formulation. Subsequently, the maximum unconditional root mean square displacement of the primary structures is used as the objective function to obtain optimum damping parameters Numerical study is performed to elucidate the effect of parameters uncertainties on the optimization of parameters of linear base isolator and system performance.

Keywords: linear base isolator, earthquake, optimization, uncertain parameters

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Authors: Menuka Maharjan

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In the name of food security, agriculture intensification through conventional farming is being implemented in Nepal. Government focus on increasing agriculture production completely ignores soil as well human health. This leads to create serious soil degradation, i.e., reduction of soil fertility and microbial activity and health hazard in the country. On this note, organic farming is sustainable agriculture approach which can address challenge of sustaining food security while protecting the environment. This creates a win-win situation both for people and the environment. However, people have limited knowledge on significance of organic farming for environment conservation and food security especially developing countries like Nepal. Thus, the objective of the study was to assess the impacts of organic farming on soil fertility and microbial activity compared to conventional farming and forest in Chitwan, Nepal. Total soil organic carbon (C) was highest in organic farming (24 mg C g⁻¹ soil) followed by conventional farming (15 mg C g⁻¹ soil) and forest (9 mg C g⁻¹ soil) in the topsoil layer (0-10 cm depth). A similar trend was found for total nitrogen (N) content in all three land uses with organic farming soil possessing the highest total N content in both 0-10 cm and 10-20 cm depth. Microbial biomass C and N were also highest under organic farming, especially in the topsoil layer (350 and 46 mg g⁻¹ soil, respectively). Similarly, microbial biomass phosphorus (P) was higher (3.6 and 1.0 mg P kg⁻¹ at 0-10 and 10-20 cm depth, respectively) in organic farming compared to conventional farming and forest at both depths. However, conventional farming and forest soils had similar microbial biomass (C, N, and P) content. After conversion of forest, the P stock significantly increased by 373% and 170% in soil under organic farming at 0-10 and 10-20 cm depth, respectively. In conventional farming, the P stock increased by 64% and 36% at 0-10 cm and 10-20 cm depth, respectively, compared to forest. Overall, organic farming practices, i.e., crop rotation, residue input and farmyard manure application, significantly alters soil fertility and microbial activity. Organic farming system is emerging as a sustainable land use system which can address the issues of food security and environment conservation by increasing sustainable agriculture production and carbon sequestration, respectively, supporting to achieve goals of sustainable development.

Keywords: organic farming, soil fertility, micobial biomas, food security

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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

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Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

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Authors: Moschos Vogiatzis, K. Perakis

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Spatial-explicit and up-to-date land use/land cover information is fundamental for spatial planning, land management, sustainable development, and sound decision-making. In the last decade, many satellite-derived land cover products at different spatial, spectral, and temporal resolutions have been developed, such as the European Copernicus Land Cover product. However, more efficient and detailed information for land use/land cover is required at the regional or local scale. A typical Mediterranean basin with a complex landscape comprised of various forest types, crops, artificial surfaces, and wetlands was selected to test and develop our approach. In this study, we investigate the improvement of Copernicus Land Cover product (CLC2018) using Landsat 8 and Sentinel-2 pixel-based classification based on all available existing geospatial data (Forest Maps, LPIS, Natura2000 habitats, cadastral parcels, etc.). We examined and compared the performance of the Random Forest classifier for land use/land cover mapping. In total, 10 land use/land cover categories were recognized in Landsat 8 and 11 in Sentinel-2A. A comparison of the overall classification accuracies for 2018 shows that Landsat 8 classification accuracy was slightly higher than Sentinel-2A (82,99% vs. 80,30%). We concluded that the main land use/land cover types of CLC2018, even within a heterogeneous area, can be successfully mapped and updated according to CLC nomenclature. Future research should be oriented toward integrating spatiotemporal information from seasonal bands and spectral indexes in the classification process.

Keywords: classification, land use/land cover, mapping, random forest

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Authors: Isomar Lima da Silva, Aristeu Jonatas Leite de Oliveira, Roberto Maia Augusto

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Biological isolation capsules are equipment commonly used in the control and prevention of infectious diseases in the hospital environment. This type of equipment, combined with pre-established medical protocols, contributes significantly to the containment of highly transmissible pathogens such as COVID-19. Due to its hermetic isolation, it allows more excellent patient safety, protecting companions and the health team. In this context, this work presents the development, testing, and validation of a medical capsule to treat patients affected by COVID-19. To this end, requirements such as low cost and easy handling were considered to meet the demand of people infected with the virus in remote locations in the Amazon region and/or where there are no ICU beds and mechanical ventilators for orotracheal intubation. Conceived and developed in a partnership between SAMEL Planos de Saúde and Instituto Conecthus, the device entitled "Vanessa Capsule" was designed to be used together with the NIV protocol (non-invasive ventilation), has an automatic exhaust system and filters performing the CO2 exchange, in addition to having BiPaps ventilatory support equipment (mechanical fans) in the Cabin Kit. The results show that the degree of effectiveness in protecting against infection by aerosols, with the protection cabin, is satisfactory, implying the consideration of the Vanessa capsule as an auxiliary method to be evaluated by the health team. It should also be noted that the medical observation of the evaluated patients found that the treatment against the COVID-19 virus started earlier with non-invasive mechanical ventilation reduces the patient's suffering and contributes positively to their recovery, in association with isolation through the Vanessa capsule.

Keywords: COVID-19, mechanical ventilators, medical capsule, non-invasive ventilation

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Authors: Sampriti Panda

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Earning one’s own livelihood is the most basic and inseparable activity for survival and existence of humankind. In any kind of situation and in every type of geographical terrain, human does adopt various strategies and ways of earning their own livelihood. Since time immemorial, anthropocentrism has been the saga of livelihood where environment is out casted and exploited to any limit so that mankind can survive. With the passage of time, humans regained their consciousness and realized that the time has arrived now to shift to sustainable livelihood and stop being self centered. This paper tries to focus on the very central issue and the hotpot of discussion in the present era which revolves around sustainable livelihood. The aim of the paper is to find out how the tribal communities which are primarily forest based are the best example of sustainable livelihood since their existence. The paper also tries to throw light on the burning issue of the so-called term ‘development’ affecting the traditional ways of livelihood opted by the forest based tribal communities. The data presented in the paper are primary and have been collected using various techniques and methodology like observation, interviews, life histories, case studies and other techniques used in a self conducted fieldwork among the Juangs, who are one of the PVTGs of Odisha.

Keywords: forest, livelihood, sustainability, tribe

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Authors: Daniele Losanno, H. A. Hadad, Giorgio Serino

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This paper presents a numerical investigation on the seismic performance of a benchmark bridge with different optimal isolation systems under near fault ground motion. Usually, very large displacements make seismic isolation an unfeasible solution due to boundary conditions, especially in case of existing bridges or high risk seismic regions. Hence, near-fault ground motions are most likely to affect either structures with long natural period range like isolated structures or structures sensitive to velocity content such as viscously damped structures. The work is aimed at analyzing the seismic performance of a three-span continuous bridge designed with different isolation systems having different levels of damping. The case study was analyzed in different configurations including: (a) simply supported, (b) isolated with lead rubber bearings (LRBs), (c) isolated with rubber isolators and 10% classical damping (HDLRBs), and (d) isolated with rubber isolators and 70% supplemental damping ratio. Case (d) represents an alternative control strategy that combines the effect of seismic isolation with additional supplemental damping trying to take advantages from both solutions. The bridge is modeled in SAP2000 and solved by time history direct-integration analyses under a set of six recorded near-fault ground motions. In addition to this, a set of analysis under Italian code provided seismic action is also conducted, in order to evaluate the effectiveness of the suggested optimal control strategies under far field seismic action. Results of the analysis demonstrated that an isolated bridge equipped with HDLRBs and a total equivalent damping ratio of 70% represents a very effective design solution for both mitigation of displacement demand at the isolation level and base shear reduction in the piers also in case of near fault ground motion.

Keywords: isolated bridges, near-fault motion, seismic response, supplemental damping, optimal design

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Authors: Salman Abdul Majeed, Vidur Solanki, Ruqiya Shama Tareen

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BACKGROUND: The COVID-19 pandemic has affected the way of living as we have known for all strata of society. While disease containment measures imposed by governmental agencies have been instrumental in controlling the spread of the virus, it has had profound collateral impacts on all populations. However, the disruption caused in the lives of one segment of population has been far more damaging than most others: the emotional wellbeing of our child and adolescent populations. This impact was even more pronounced in children who already suffered from neurodevelopmental or psychiatric disorders. In particular, school closures have not only led to profound social isolation, but also negative impacts on normal developmental opportunities and interruptions in mental health services obtained through school systems. It is too soon to understand the full impacts of quarantine, isolation, stress of social detachment and fear of pandemic, but we have started to see the devastating impact on C&A already. This review intends to shed light on the current understanding of psychiatric wellbeing of C&A during COVID-19 pandemic. METHOD: Literature search utilizing key words COVID-19 and children, quarantine and children, social isolation, Loneliness, pandemic stress and children, and mental health of children, disease containment measures was carried out. Over 200 articles were identified, out of which 81 articles were included in this review article. RESULTS: The disruption caused by COVID-19 in the lives of C&A is much more damaging and its impact is far reaching. The C&A ED visits for possible suicide attempts have jumped to 22.3% in 2020 and 39.1% during 2021. One study utilizing T1-weighted structural images, computed the thickness of cortical and subcortical structures including amygdala, hippocampus, and nucleus accumbens. The Peri-COVID group showed reduced cortical and subcortical thickness and more advanced brain aging compared to pre pandemic studies. CONCLUSION: Mental health resources for C&A remain under funded, neglected, and inaccessible to population that needs it most. Children with ongoing mental health disorders were impacted worst, along with those with predisposed biopsychosocial risk factors.

Keywords: COVID-19 and children, quarantine and children, social isolation, Loneliness, pandemic stress and children, disease containment measures, mental health of children

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Authors: Şeyma Özçirak Ergün, Ergün Şakalar, Emrah Yalazi̇, Nebahat Şahi̇n

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Food irradiation is a usage of exposing food to ionising radiation (IR) such as gamma rays. IR has been used to decrease the number of harmful microorganisms in the food such as spices. Excessive usage of IR can cause damage to both food and people who consuming food. And also it causes to damages on food DNA. Generally, IR detection techniques were utilized in literature for spices are Electron Spin Resonance (ESR), Thermos Luminescence (TL). Storage creates negative effect on IR detection method then analyses of samples have been performed without storage in general. In the experimental part, red pepper (Capsicum annuum) and mint (Mentha piperita) as spices were exposed to 0, 0.272, 0.497, 1.06, 3.64, 8.82, and 17.42 kGy ionize radiation. ESR was applied to samples irradiated. DNA isolation from irradiated samples was performed using GIDAGEN Multi Fast DNA isolation kit. The DNA concentration was measured using a microplate reader spectrophotometer (Infinite® 200 PRO-Life Science–Tecan). The concentration of each DNA was adjusted to 50 ng/µL. Genomic DNA was imaged by UV transilluminator (Gel Doc XR System, Bio-Rad) for the estimation of genomic DNA bp-fragment size after IR. Thus, agarose gel profiles of irradiated spices were obtained to determine the change of band profiles. Besides, samples were examined at three different time periods (0, 3, 6 months storage) to show the feasibility of developed method. Results of gel electrophoresis showed especially degradation of DNA of irradiated samples. In conclusion, this study with gel electrophoresis can be used as a basis for the identification of the dose of irradiation by looking at degradation profiles at specific amounts of irradiation. Agarose gel results of irradiated samples were confirmed with ESR analysis. This method can be applied widely to not only food products but also all biological materials containing DNA to predict radiation-induced damage of DNA.

Keywords: DNA, electrophoresis, gel electrophoresis, ionizeradiation

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Y. Kourd, D. Lefebvre, N. Guersi

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The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. In this paper we propose a method of fault diagnosis based on neuro-fuzzy technique and the choice of a threshold. The validation of this method on a test bench "Actuator Electro DAMADICS Benchmark". In the first phase of the method, we construct a model represents the normal state of the system to fault detection. With residuals analysis generated and the choice of thresholds for signatures table. These signatures provide us with groups of non-detectable faults. In the second phase, we build faulty models to see the flaws in the system that are not located in the first phase.

Keywords: residuals analysis, threshold, neuro-fuzzy system, residual evaluation

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Authors: Isahakyan Heghine

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Intertextuality, being in the centre of attention of both linguists and literary critics, is vividly expressed in the outstanding British novelist and philosopher J. Fowles' works. 'The Magus’ is a deep psychological and philosophical novel with vivid intertextual links with the Greek mythology and authors from different epochs. The aim of the paper is to show how intertextuality might serve as a dialogue between two authors (J. Fowles and J. Donne) disguised in the dialogue of two protagonists of the novel : Conchis and Nicholas. Contrastive viewpoints concerning man's isolation, loneliness are stated in the dialogue. Due to the conceptual analysis of the text it becomes possible both to decode the conceptual information of the text and find out its intertextual links.

Keywords: dialogue, conceptual analysis, isolation, intertextuality

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Authors: Karthick Gopalan, Selvamohan Thankiah

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Biosurfactants are lipid compounds produced by microbes, which are amphipathic molecules consisting of hydrophophic and hydrophilic domains. In the present investigation, ten bacterial strains were isolated from petroleum oil contaminated sites near petrol bunk. Oil collapsing test, haemolytic activity were used as a criteria for primary isolation of biosurfactant producing bacteria. In this study, all the bacterial strains gave positive results. Among the ten strains, two were observed as good biosurfactant producers, they utilize the diesel as a sole carbon source. Optimization of biosurfactant producing bacteria isolated from petroleum oil contaminated sites was carried out using different parameters such as, temperature (20ºC, 25ºC, 30ºC, 37ºC and 45ºC), pH (5,6,7,8 & 9) and nitrogen sources (ammonium chloride, ammonium carbonate and sodium nitrate). Biosurfactants produced by bacteria were extracted, dried and quantified. As a result of optimization of parameters the suitable values for the production of more amount of biosurfactant by the isolated bacterial species was observed as 30ºC (0.543 gm/lt) in the pH 7 (0.537 gm/lt) with ammonium nitrate (0.431 gm/lt) as sole carbon source.

Keywords: isolation and identification, biosurfactant, microorganism, bioaugmentation

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Authors: Kamand Bagherian, Nariman Niknejad

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A vibration isolation technology for precise position control of a rotary system powered by two permanent magnet DC (PMDC) motors is proposed, where this system is mounted on an oscillatory frame. To achieve vibration isolation for this system, active damping and disturbance rejection (ADDR) technology is presented which introduces a cooperation of a main and an auxiliary PMDC, controlled by discrete-time sliding mode control (DTSMC) based schemes. The controller of the main actuator tracks a desired position and the auxiliary actuator simultaneously isolates the induced vibration, as its controller follows a torque trend. To determine this torque trend, a combination of two algorithms is introduced by the ADDR technology. The first torque-trend producing algorithm rejects the disturbance by counteracting the perturbation, estimated using a model-based observer. The second torque trend applies active variable damping to minimize the oscillation of the output shaft. In this practice, the presented technology is implemented on a rotary system with a pendulum attached, mounted on a linear actuator simulating an oscillation-transmitting structure. In addition, the obtained results illustrate the functionality of the proposed technology.

Keywords: active damping, discrete-time nonlinear controller, disturbance tracking algorithm, oscillation transmitting support, position control, stability robustness, vibration isolation

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Authors: Aarthi Sridhar, Henri Gavin, Karah Kelly

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Rolling Isolation Systems (RISs) are simple and effective means to mitigate earthquake hazards to equipment in critical and precious facilities, such as hospitals, network collocation facilities, supercomputer centers, and museums. The RIS works by isolating components acceleration the inertial forces felt by the subsystem. The RIS consists of two platforms with counter-facing concave surfaces (dishes) in each corner. Steel balls lie inside the dishes and allow the relative motion between the top and bottom platform. Formerly, a mathematical model for the dynamics of RISs was developed using Lagrange’s equations (LE) and experimentally validated. A new mathematical model was developed using Gauss’s Principle of Least Constraint (GPLC) and verified by comparing impulse response trajectories of the GPLC model and the LE model in terms of the peak displacements and accelerations of the top platform. Mathematical models for the RIS are tedious to derive because of the non-holonomic rolling constraints imposed on the system. However, using Gauss’s Principle of Least constraint to find the equations of motion removes some of the obscurity and yields a system that can be easily extended. Though the GPLC model requires more state variables, the equations of motion are far simpler. The non-holonomic constraint is enforced in terms of accelerations and therefore requires additional constraint stabilization methods in order to avoid the possibility that numerical integration methods can cause the system to go unstable. The GPLC model allows the incorporation of more physical aspects related to the RIS, such as contribution of the vertical velocity of the platform to the kinetic energy and the mass of the balls. This mathematical model for the RIS is a tool to predict the motion of the isolation platform. The ability to statistically quantify the expected responses of the RIS is critical in the implementation of earthquake hazard mitigation.

Keywords: earthquake hazard mitigation, earthquake isolation, Gauss’s Principle of Least Constraint, nonlinear dynamics, rolling isolation system

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Authors: Pius Akindele Adeniyi

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Developing countries including Nigeria are greatly saddled with problems emanating from environmental deterioration. These problems are glaringly threatening the existence of mankind. A wide range of factors contribute to environmental problems and prominent among these are: increase in human population, deforestation, industrialization, urbanization, ignorance and socio-economic activities. The economic function of the forest has for quite a long time played a major role in the economic life of the people of Nigeria while the social function such as the recreational use of the forest has until today play very little role in the cultural development of the country. Recreation forest ameliorates the environment, reduces psychological stress, and broadens individual outlook and horizon. Unfortunately domestic tourism of recreational forest is not developed and almost unknown due to poverty and non existence of recreational facilities. Social forestry is seen as a sustainable means of combating ecological problems especially in third world countries such as Nigeria. The programme also provides social and economic benefits to the rural people. As a rural-based activity, people's participation is crucial for its success. There is need to create awareness on recreational forestry and social forestry as well as harness their resources for the country .This paper therefore highlights the constraints in the practice of social and recreational forestry in developing countries and suggests ways to motivate the rural people to participate in the programme. . Attempt has been made to trace the causes and consequences of Nigerian environmental deterioration, while suggestions on possible solutions are proffered .

Keywords: recreational, social, deteriorating, forestry

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Authors: Muhammad Nurrizka Ramadhan

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Today,Demand for wood increase in rapid rate. Wood is widely used for many things range from building materials to furniture materials. This makes the forest area in Indonesia dropped dramatically, it is estimated that the area of Indonesiaan forest in 2020 will be only about 16 million hectares. The more forest in Indonesia loss, people are required to look for another material to subtitute wood for the furniture. Jepara, a city with the largest furniture industry in Indonesia, requires a large supply of wood, it can reach 300.000 – 500.000 cubic meters per year. Most of the furniture in Jepara use teak, mahogany, and rosewood. Though teak wood is a rare species that must be protected. Today the availability of bamboo in Indonesia is very big. With cheap price, and the period of rapid growth makes bamboo can be used as a substitute for wood for the furniture industry in the future. By making use bamboo to make wood bamboo composite to replace the use of wood for furniture material. This paper is about the use of bamboo as a substitute for wood bamboo composite for the furniture industry. Expected in future, wood can be replaced by a wood bamboo composite.

Keywords: bamboo, composite, furniture, wood

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Authors: Lin Zhang

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The fear of leprosy has been longstanding throughout the human history. In an era where isolation is practiced as a means of epidemic prevention, the leprosy rehabilitation group has itself become an isolated community with an entrenched metaphor. In the process of new mediatization of the leprosy isolation community, what are the relations among media literacy, the leprosy internalized stigma and social support? To address the question, the “portrait” of leprosy rehabilitation group is re-delineated through two field studies in the “post-leprosy age” in 2012 and 2020, respectively. Taking an isolation community on Si’an Leprosy Island in Dongguan City, Guangdong Province, China as the study object, it is found that new media promotes the dissolution of segregation effect of the leprosy isolation community and the cultivation of opinion leaders by breaking spatial, psychological and social segregation and by building a community of village affairs and public space in the following way: the cured patients with high new media literacy, especially those who use WeChat and other applications and largely rely on new media for information, have a low level of leprosy internalized stigma and a high level of social support, and they are often the opinion leaders inside their community; on the contrary, the cured patients with low new media literacy, a high level of leprosy internalized stigma and a low level of social support are often the followers inside their community. Such effects of dissolution and construction are reflected not only in the vertical differentiation of the same individual at different times, but also in the horizontal differentiation between different individuals at the same time.

Keywords: segregation, the leprosy rehabilitation group, new mediatization, digital empowerment, opinion leaders

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Authors: Nicolò Vaiana, Filip C. Filippou, Giorgio Serino

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In order to reduce numerical computations in the nonlinear dynamic analysis of seismically base-isolated structures, a Mixed Explicit-Implicit time integration Method (MEIM) has been proposed. Adopting the explicit conditionally stable central difference method to compute the nonlinear response of the base isolation system, and the implicit unconditionally stable Newmark’s constant average acceleration method to determine the superstructure linear response, the proposed MEIM, which is conditionally stable due to the use of the central difference method, allows to avoid the iterative procedure generally required by conventional monolithic solution approaches within each time step of the analysis. The main aim of this paper is to investigate the stability and computational efficiency of the MEIM when employed to perform the nonlinear time history analysis of base-isolated structures with sliding bearings. Indeed, in this case, the critical time step could become smaller than the one used to define accurately the earthquake excitation due to the very high initial stiffness values of such devices. The numerical results obtained from nonlinear dynamic analyses of a base-isolated structure with a friction pendulum bearing system, performed by using the proposed MEIM, are compared to those obtained adopting a conventional monolithic solution approach, i.e. the implicit unconditionally stable Newmark’s constant acceleration method employed in conjunction with the iterative pseudo-force procedure. According to the numerical results, in the presented numerical application, the MEIM does not have stability problems being the critical time step larger than the ground acceleration one despite of the high initial stiffness of the friction pendulum bearings. In addition, compared to the conventional monolithic solution approach, the proposed algorithm preserves its computational efficiency even when it is adopted to perform the nonlinear dynamic analysis using a smaller time step.

Keywords: base isolation, computational efficiency, mixed explicit-implicit method, partitioned solution approach, stability

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Authors: Abdul-Razak Saeed

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Addressing the climate change crisis that this generation faces has evolved to include the consideration of a policy mechanism referred to as reduced emissions from deforestation and forest degradation with plus components of conservation, sustainable forest management and enhancement of forest carbon stocks (REDD+). REDD+ emerged from the International level of UNFCCC but its implementation is by developing countries. It challenges the development paradigm of nations that depend on the unsustainable clearing of forests and land use change for economic development whilst posing as an opportunity or risk for forest community livelihoods, institutions and their interaction with the forest resources. As a novel policy mechanism, it is imperative to gain global insight into local contexts of its implementation and to understand local level mobilization of their agency for institutional sustainability as reconfigured by new carbon economy initiatives like REDD+. Using a systematic review process, as the initial stages of this study, secondary data of REDD+ projects across the globe were evaluated to pick up gaps in research and that of on ground REDD+ implementation. Primary data was gathered from 30 actors in the government, NGO, private sector and traditional authorities using face-to-face semi structured interviews in Ghana; participation in meetings and workshops and policy and strategy document reviews. Preliminary findings of the study include REDD+ knowledge being a key determinant of power distribution and affects who shapes the process; in Ghana, informal relationships are playing key roles in advancing REDD+ unlike in traditional forestry and a subjectivity shift of local communities from an 'emotive-link' of environmental care to one of 'economic self-seeking and enriching' domain of thought.

Keywords: climate change, communities, forests, REDD+

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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Authors: Muhammad Suhail Ibrahim, Ahmad Mujtaba

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Background: The accuracy of the most frequently used tests for diagnosing Helicobacter pylori is always under consideration in clinical settings. A reliable diagnosis is crucial to confirm the success of therapy. Objective: The aim of this research was to study the isolation frequency of H. pylori from patients compatible with gastritis or gastric ulcer and to compare some feasible non-invasive and invasive methods for the diagnosis of infection. Materials and Methods: Ninety-six gastric biopsy and blood samples were obtained with various gastroduodenal symptoms after obtaining informed consent. The biopsies were analyzed and compared using the culture, microscopic examination, histopathology, Rapid urease RUT), serology, biochemical, antibiotic susceptibility test and molecular method. Results: A number of 40 (41.67%) were considered H. pylori positive in both histopathology and RUT. On the other hand, 46 patients were positive against anti IgA and IgG by ELISA. Eighteen biopsies were positive according to the culture test. This was further confirmed by endoscopic examination, urease, catalase and oxidase tests. A high percentage of resistance to polymyxin B, amoxicillin, and kanamycin was observed (100, 88.89, and 77.78%, respectively). A gene (Cag A) was also detected by using molecular technique which appeared positive in 16 patients. The sensitivity/specificity (%) of diagnostic method was 95/77 for histology, 100/83.5 for rapid urease, 85.7/90 for gram staining, 100/66.6 for IgG serology, 100/79.5 for IgA serology, 100/75.0 for PCR, 100/79.04 for combination of RUT and IgG serology and 100/92.4 for combination of RUT, gram staining and IgG serology. Conclusion: In view of the result obtained, PCR appeared to be the most reliable test. However, higher sensitivity and specificity were also recorded for other tests. So, for more accurate results, it is advisable not to rely solely on a single method for detection.

Keywords: helicobacter pylori, isolation, detection, culture, urease, polymerase chain reaction, antibiotic susceptibility test, dyspeptic patients

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Authors: Z. A. Al Marhoon, H. S. Al Ramis, C. Teodoriu

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Well-integrity is one of the major elements considered for drilling geothermal, oil, and gas wells. Well-integrity is minimizing the risk of unplanned fluid flow in the well bore throughout the well lifetime. Well integrity is maximized by applying technical concepts along with practical practices and strategic planning. These practices are usually governed by standardization and regulation entities. Practices during well construction can affect the integrity of the seal at the time of abandonment. On the other hand, achieving a perfect barrier system is impracticable due to the needed cost. This results in a needed balance between regulations requirements and practical applications. The guidelines are only effective when they are attainable in practical applications. Various governmental regulations and international standards have different guidelines on what constitutes high-quality isolation from unwanted flow. Each regulating or standardization body differ in requirements based on the abandonment objective. Some regulation account more for the environmental impact, water table contamination, and possible leaks. Other regulation might lean towards driving more economical benefits while achieving an acceptable isolation criteria. The research methodology used in this topic is derived from a literature review method combined with a compare and contrast analysis. The literature review on various zonal isolation regulations and standards has been conducted. A review includes guidelines from NORSOK (Norwegian governing entity), BSEE (USA offshore governing entity), API (American Petroleum Institute) combined with ISO (International Standardization Organization). The compare and contrast analysis is conducted by assessing the objective of each abandonment regulations and standardization. The current state of well barrier regulation is in balancing action. From one side of this balance, the environmental impact and complete zonal isolation is considered. The other side of the scale is practical application and associated cost. Some standards provide a fair amount of details concerning technical requirements and are often flexible with the needed associated cost. These guidelines cover environmental impact with laws that prevent major or disastrous environmental effects of improper sealing of wells. Usually these regulations are concerned with the near future of sealing rather than long-term. Consequently, applying these guidelines become more feasible from a cost point of view to the required plugging entities. On the other hand, other regulation have well integrity procedures and regulations that lean toward more restrictions environmentally with an increased associated cost requirements. The environmental impact is detailed and covered with its entirety, including medium to small environmental impact in barrier installing operations. Clear and precise attention to long-term leakage prevention is present in these regulations. The result of the compare and contrast analysis of the literature showed that there are various objectives that might tip the scale from one side of the balance (cost) to the other (sealing quality) especially in reference to zonal isolation. Furthermore, investing in initial well construction is a crucial part of ensuring safe final well abandonment. The safety and the cost saving at the end of the well life cycle is dependent upon a well-constructed isolation systems at the beginning of the life cycle. Long term studies on zonal isolation using various hydraulic or mechanical materials need to take place to further assess permanently abandoned wells to achieve the desired balance. Well drilling and isolation techniques will be more effective when they are operationally feasible and have reasonable associated cost to aid the local economy.

Keywords: plug and abandon, P&A regulation, P&A standards, international guidelines, gap analysis

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Authors: Beng Yew Low, Cher Liang Cha, Cheng Yong Teoh

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Due to a lack of continual assessment or grade related data, identifying first-year engineering students in a polytechnic education at risk of failing is challenging. Our experience over the years tells us that there is no strong correlation between having good entry grades in Mathematics and the Sciences and excelling in hardcore engineering subjects. Hence, identifying students at risk of failure cannot be on the basis of entry grades in Mathematics and the Sciences alone. These factors compound the difficulty of early identification and intervention. This paper describes the development of a predictive analytics model in the early detection of students at risk of failing and evaluates its effectiveness. Data from continual assessments conducted in term one, supplemented by data of student psychological profiles such as interests and study habits, were used. Three classification techniques, namely Logistic Regression, K Nearest Neighbour, and Random Forest, were used in our predictive model. Based on our findings, Random Forest was determined to be the strongest predictor with an Area Under the Curve (AUC) value of 0.994. Correspondingly, the Accuracy, Precision, Recall, and F-Score were also highest among these three classifiers. Using this Random Forest Classification technique, students at risk of failure could be identified at the end of term one. They could then be assigned to a Learning Support Programme at the beginning of term two. This paper gathers the results of our findings. It also proposes further improvements that can be made to the model.

Keywords: continual assessment, predictive analytics, random forest, student psychological profile

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Authors: Md Mizanur Rahman, Lotanna Micah Nneji, Adeola C. Adeniyi, Edem Archibong Eniang, Abiodun B. Onadeko, Felista Kasyoka Kilunda, Babatunde E. Adedeji, Ifeanyi C. Nneji, Adiaha A. A. Ugwumba, Jie-Qiong Jin, Min-Sheng Peng, Caroline Olory, Nsikan Eninekit, Jing Che

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Nigeria contains a number of forest habitats that believed to host highly rich amphibian diversity. However, a dearth of herpetological studies has restricted information on the amphibian diversity in Nigeria. To cover the gap of knowledge, this study focused field surveys on relatively less studied forests–Afi Forest Reserve and Ikpan forest ecosystem. The goal of this study is to make a checklist and to investigate the habitat preferences of amphibians in these two forests. The study areas were surveyed between August 2018 and July 2019 following visual and acoustic methods. Individuals were identified using the morphological and molecular (16S ribosomal RNA) approach. Literature searches were conducted to document additional species that were not encountered during the current field surveys. Using the observational records and arrays of diversity indices, the patterns of species richness and abundance across habitat types were evaluated. Voucher specimens and tissue samples were deposited in the museums of the Department of Zoology, University of Ibadan Nigeria, and the remainder at the Kunming Institute of Zoology (KIZ), Chinese Academy of Sciences, Kunming, China. The result of this study revealed the presence of 30 and 31 amphibian species from the Afi Forest Reserve and the Ikpan Forest Ecosystem, respectively. There were two unidentified species from AFR and one from IFE. In total, 324 individuals of amphibian species were observed from the two study areas. Forest and swamps showed high species diversity and richness than the agricultural field and savannah. Savannah and agricultural fields had the highest similarity in the species composition. Given the increased human disturbances and consequent threats to these forests, this study offers recommendations for the initiation of conservation plans immediately.

Keywords: biodiversity, conservation, cryptic species, ecology, integrated taxonomy, species inventory

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Authors: Tahere Fazilat

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Caspian red deer or maral (Cervus elaphus maral) is the largest type of deer in iran. Maral in the past has lived in the north forests of Iran from the Caspian sea coast, Alborz mountains chain and oak forest of Zagros margin from the Azarbaijan up to fars province. However, the generation of them was completely destroyed in the north west and west of Iran. According to reports about 50 years and out of reach of humans. In the present studies, data were collected from 2004 to 2014 in the Mazandaran state Hyrcanian forest by means of guard of environment and justiciary office of department of environment of Mazandaran in this process the all arrested illegal hunting of red deer and the population census, estimation and the correlation of these data was assayed. We provide a first evaluation of how suitable these methods are by comparing the results with population estimates obtained using cohort analysis, and by analyzing the within-season variation in number of seen deer. The data gave us the future of red deer in northern forest of Iran and the results of policy of department of environment in Iran in red deer conservation.

Keywords: illegal hunting, red deer, census, concervation

Procedia PDF Downloads 527