Search results for: adaptive filter

Authors: Nurul Amziah Md Yunus, Izhal Abdul Halin, Nasri Sulaiman, Noor Faezah Ismail, Ong Kai Sheng

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The MEMS pressure sensor has been introduced and presented in this paper. The types of pressure sensor and its theory of operation are also included. The latest MEMS technology, the fabrication processes of pressure sensor are explored and discussed. Besides, various device applications of pressure sensor such as tire pressure monitoring system, diesel particulate filter and others are explained. Due to further miniaturization of the device nowadays, the pressure sensor with nanotechnology (NEMS) is also reviewed. The NEMS pressure sensor is expected to have better performance as well as lower in its cost. It has gained an excellent popularity in many applications.

Keywords: pressure sensor, diaphragm, MEMS, automotive application, biomedical application, NEMS

Procedia PDF Downloads 653

Authors: Da Kuang

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Resilience is a hotly debated topic in many research fields (e.g., engineering, ecology, society, psychology). In flood management studies, we are experiencing the paradigm shift from flood resistance to flood resilience. Flood resilience refers to tolerate flooding through adaptation or transformation. It is increasingly argued that our city as a social-ecological system holds the ability to learn from experience and adapt to flood rather than simply resist it. This research aims to investigate what kinds of adaptation knowledge the frequently flooded village learned from past experience and its advantages and limitations in coping with floods. The study area – Xinnongcun village, located in the west of Wuhan city, is a linear village and continuously suffered from both flash flood and drainage flood during the past 30 years. We have a field trip to the site in June 2017 and conducted semi-structured interviews with local residents. Our research summarizes two types of adaptation knowledge that people learned from the past floods. Firstly, at the village scale, it has formed a collective urban form which could help people live during both flood and dry season. All houses and front yards were elevated about 2m higher than the road. All the front yards in the village are linked and there is no barrier. During flooding time, people walk to neighbors through houses yards and boat to outside village on the lower road. Secondly, at individual scale, local people learned tacit knowledge of preparedness and emergency response to flood. Regarding the advantages and limitations, the adaptation knowledge could effectively help people to live with flood and reduce the chances of getting injuries. However, it cannot reduce local farmers’ losses on their agricultural land. After flood, it is impossible for local people to recover to the pre-disaster state as flood emerges during June and July will result in no harvest. Therefore, we argue that learning from past flood experience could increase people’s adaptive capacity. However, once the adaptive capacity cannot reduce people’s losses, it requires a transformation to a better regime.

Keywords: adaptation, flood resilience, tacit knowledge, transformation

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Authors: Andy Alubaidy

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In this work, a robotic additive manufacturing system (RAMS) that is capable of three-dimensional (3D) printing in six degrees of freedom (DOF) with very high accuracy and virtually on any surface has been designed and built. One of the major shortcomings in existing 3D printer technology is the limitation to three DOF, which results in prolonged fabrication time. Depending on the techniques used, it usually takes at least two hours to print small objects and several hours for larger objects. Another drawback is the size of the printed objects, which is constrained by the physical dimensions of most low-cost 3D printers, which are typically small. In such cases, large objects are produced by dividing them into smaller components that fit the printer’s workable area. They are then glued, bonded or otherwise attached to create the required object. Another shortcoming is material constraints and the need to fabricate a single part using different materials. With the flexibility of a six-DOF robot, the RAMS has been designed to overcome these problems. A feeding mechanism using an adaptive Proportional-Integral-Derivative (PID) controller is utilized along with a national instrument compactRIO (NI cRIO), an ABB robot, and off-the-shelf sensors. The RAMS have the ability to 3D print virtually anywhere in six degrees of freedom with very high accuracy. It is equipped with an ABB IRB 120 robot to achieve this level of accuracy. In order to convert computer-aided design (CAD) files to digital format that is acceptable to the robot, Hypertherm Robotic Software Inc.’s state-of-the-art slicing software called “ADDMAN” is used. ADDMAN is capable of converting any CAD file into RAPID code (the programing language for ABB robots). The robot uses the generated code to perform the 3D printing. To control the entire process, National Instrument (NI) compactRIO (cRio 9074), is connected and communicated with the robot and a feeding mechanism that is designed and fabricated. The feeding mechanism consists of two major parts, cold-end and hot-end. The cold-end consists of what is conventionally known as an extruder. Typically, a stepper-motor is used to control the push on the material, however, for optimum control, a DC motor is used instead. The hot-end consists of a melt-zone, nozzle, and heat-brake. The melt zone ensures a thorough melting effect and consistent output from the nozzle. Nozzles are made of brass for thermo-conductivity while the melt-zone is comprised of a heating block and a ceramic heating cartridge to transfer heat to the block. The heat-brake ensures that there is no heat creep-up effect as this would swell the material and prevent consistent extrusion. A control system embedded in the cRio is developed using NI Labview which utilizes adaptive PID to govern the heating cartridge in conjunction with a thermistor. The thermistor sends temperature feedback to the cRio, which will issue heat increase or decrease based on the system output. Since different materials have different melting points, our system will allow us to adjust the temperature and vary the material.

Keywords: robotic, additive manufacturing, PID controller, cRIO, 3D printing

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Authors: Yui Okuno, Mariko Era, Takayoshi Kawahara, Takahide Kanyama, Hiroshi Morita

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Introduction: Fungus and mite are known as allergens that cause an allergic disease for example asthma bronchiale and allergic rhinitis. Cladosporium cladosporioides is one of the most often detected fungi in the indoor environment and causes pollution and deterioration. Dermatophagoides farinae is major mite allergens indoors. Therefore, the creation of antifungal agents with high safety and the antifungal effect is required. Fatty acid salts are known that have antibacterial activities. This report describes the effects of fatty acid salts against Cladosporium cladosporioides NBRC 30314 and Dermatophagoides farinae. Methods: Potassium salts of 9 fatty acids (C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, C18:1, C18:2, C18:3) were prepared by mixing the fatty acid with the appropriate amount of KOH solution to a concentration of 175 mM and pH 10.5. The antifungal method, the spore suspension (3.0×104 spores/mL) was mixed with a sample of fatty acid potassium (final concentration of 175 mM). Samples were counted at 0, 10, 60, 180 min by plating (100 µL) on PDA. Fungal colonies were counted after incubation for 3 days at 30 °C. The MIC (minimum inhibitory concentration) against the fungi was determined by the two-fold dilution method. Each fatty acid salts were inoculated separately with 400 µL of C. cladosporioides at 3.0 × 104 spores/mL. The mixtures were incubated at the respective temperature for each organism for 10 min. The tubes were then contacted with the fungi incubated at 30 °C for 7 days and examined for growth of spores on PDA. The acaricidal method, twenty D. farinae adult females were used and each adult was covered completely with 2 µL fatty acid potassium for 1 min. The adults were then dried with filter paper. The filter paper was folded and fixed by two clips and kept at 25 °C and 64 % RH. Mortalities were determained 48 h after treatment under the microscope. D. farina was considered to be dead if appendages did not move when prodded with a pin. Results and Conclusions: The results show that C8K, C10K, C12K, C14K was effective to decrease survival rate (4 log unit) of the fatty acids potassium incubated time for 10 min against C. cladosporioides. C18:3K was effective to decrease 4 log unit of the fatty acids potassium incubated time for 60 min. Especially, C12K was the highest antifungal activity and the MIC of C12K was 0.7 mM. On the other hand, the fatty acids potassium showed no acaricidal effects against D. farinae. The activity of D. farinae was not adversely affected after 48 hours. These results indicate that C12K has high antifungal activity against C. cladosporioides and suggest the fatty acid potassium will be used as an antifungal agent.

Keywords: fatty acid salts, antifungal effects, acaricidal effects, Cladosporium cladosporioides, Dermatophagoides farinae

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Authors: Alma Mendoza-Ponce, Rogelio Corona-Núñez, Florian Kraxner

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Mexico is a megadiverse country and it has nearly halved its natural vegetation in the last century due to agricultural and livestock expansion. Impacts of land use cover change and climate change are unevenly distributed and spatial prioritization to minimize the affectations on biodiversity is crucial. Global and national efforts for prioritizing biodiversity conservation show that ~33% to 45% of Mexico should be protected. The width of these targets makes difficult to lead resources. We use a framework based on vulnerability and irreplaceability to prioritize conservation efforts in Mexico. Vulnerability considered exposure, sensitivity and adaptive capacity under two scenarios (business as usual, BAU based, on the SSP2 and RCP 4.5 and a Green scenario, based on the SSP1 and the RCP 2.6). Exposure to land use is the magnitude of change from natural vegetation to anthropogenic covers while exposure to climate change is the difference between current and future values for both scenarios. Sensitivity was considered as the number of endemic species of terrestrial vertebrates which are critically endangered and endangered. Adaptive capacity is used as the ration between the percentage of converted area (natural to anthropogenic) and the percentage of protected area at municipality level. The results suggest that by 2050, between 11.6 and 13.9% of Mexico show vulnerability ≥ 50%, and by 2070, between 12.0 and 14.8%, in the Green and BAU scenario, respectively. From an ecosystem perspective cloud forests, followed by tropical dry forests, natural grasslands and temperate forests will be the most vulnerable (≥ 50%). Amphibians are the most threatened vertebrates; 62% of the endemic amphibians are critically endangered or endangered while 39%, 12% and 9% of the mammals, birds, and reptiles, respectively. However, the distribution of these amphibians counts for only 3.3% of the country, while mammals, birds, and reptiles in these categories represent 10%, 16% and 29% of Mexico. There are 5 municipalities out of the 2,457 that Mexico has that represent 31% of the most vulnerable areas (70%).These municipalities account for 0.05% of Mexico. This multiscale approach can be used to address resources to conservation targets as ecosystems, municipalities or species considering land use cover change, climate change and biodiversity uniqueness.

Keywords: biodiversity, climate change, land use change, Mexico, vulnerability

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Authors: Chandan Kumar

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Background and Context: Population growth and rapid urbanization resulted nearly 2 Lacs migrants along with families moving to Delhi each year in search of jobs. Most of these poor migrant families end up living in slums and constitute an estimated population of 1.87 lacs every year. Further, more than half (52 per cent) of Delhi’s population resides in places such as unauthorized and resettled colonies. Slum population is fully dependent on public toilet to defecate. In Public toilets, manholes either connected with Sewer line or septic tank. Septic tank connected public toilet faces major challenges to dispose of waste water. They have to dispose of waste water in outside open drain and waste water struck out side of public toilet complex and near to the slum area. As a result, outbreak diseases such as Malaria, Dengue and Chikungunya in slum area due to stagnated waste water. Intervention and Innovation took place by Save the Children in 21 Public Toilet Complexes of South Delhi and North Delhi. These public toilet complexes were facing same waste water disposal problem. They were disposing of minimum 1800 liters waste water every day in open drain. Which caused stagnated water-borne diseases among the nearest community. Construction of Soak Well: Construction of soak well in urban context was an innovative approach to minimizing the problem of waste water management and increased water table of existing borewell in toilet complex. This technique made solution in Ground water recharging system, and additional water was utilized in vegetable gardening within the complex premises. Soak well had constructed with multiple filter media with inlet and safeguarding bed on surrounding surface. After construction, soak well started exhausting 2000 liters of waste water to raise ground water level through different filter media. Finally, we brought a change in the communities by constructing soak well and with zero maintenance system. These Public Toilet Complexes were empowered by safe disposing waste water mechanism and reduced stagnated water-borne diseases.

Keywords: diseases, ground water recharging system, soak well, toilet complex, waste water

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Authors: Igor Belykh

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Anti-scatter grids used in radiographic imaging for the contrast enhancement leave specific artifacts. Those artifacts may be visible or may cause Moiré effect when a digital image is resized on a diagnostic monitor. In this paper, we propose an automated grid artifacts detection and suppression algorithm which is still an actual problem. Grid artifacts detection is based on statistical approach in spatial domain. Grid artifacts suppression is based on Kaiser bandstop filter transfer function design and application avoiding ringing artifacts. Experimental results are discussed and concluded with description of advantages over existing approaches.

Keywords: grid, computed radiography, pattern recognition, image processing, filtering

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Authors: Shankha Sanyal, Archi Banerjee, Sayan Biswas, Sourya Sengupta, Sayan Nag, Ranjan Sengupta, Dipak Ghosh

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The term ‘gestalt’ has been widely used in the field of psychology which defined the perception of human mind to group any object not in part but as a 'unified' whole. Music, in general, is polyphonic - i.e. a combination of a number of pure tones (frequencies) mixed together in a manner that sounds harmonious. The study of human brain response due to different frequency groups of the acoustic signal can give us an excellent insight regarding the neural and functional architecture of brain functions. Hence, the study of music cognition using neuro-biosensors is becoming a rapidly emerging field of research. In this work, we have tried to analyze the effect of different frequency bands of music on the various frequency rhythms of human brain obtained from EEG data. Four widely popular Rabindrasangeet clips were subjected to Wavelet Transform method for extracting five resonant frequency bands from the original music signal. These frequency bands were initially analyzed with Detrended/Adaptive Fractal analysis (DFA/AFA) methods. A listening test was conducted on a pool of 100 respondents to assess the frequency band in which the music becomes non-recognizable. Next, these resonant frequency bands were presented to 20 subjects as auditory stimulus and EEG signals recorded simultaneously in 19 different locations of the brain. The recorded EEG signals were noise cleaned and subjected again to DFA/AFA technique on the alpha, theta and gamma frequency range. Thus, we obtained the scaling exponents from the two methods in alpha, theta and gamma EEG rhythms corresponding to different frequency bands of music. From the analysis of music signal, it is seen that loss of recognition is proportional to the loss of long range correlation in the signal. From the EEG signal analysis, we obtain frequency specific arousal based response in different lobes of brain as well as in specific EEG bands corresponding to musical stimuli. In this way, we look to identify a specific frequency band beyond which the music becomes non-recognizable and below which in spite of the absence of other bands the music is perceivable to the audience. This revelation can be of immense importance when it comes to the field of cognitive music therapy and researchers of creativity.

Keywords: AFA, DFA, EEG, gestalt in music, Hurst exponent

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Authors: Yara Bajnaid, Malak Zaidan, Eman Dakkak

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This research explores the use of Artificial Intelligence in Duolingo, a popular mobile application for language learning. Duolingo's success hinges on its gamified approach and adaptive learning system, both heavily reliant on AI functionalities. The research also analyzes user feedback regarding Duolingo's AI functionalities. While a significant majority (70%) consider Duolingo a reliable tool for language learning, there's room for improvement. Overall, AI plays a vital role in personalizing the learning journey and delivering interactive exercises. However, continuous improvement based on user feedback can further enhance the effectiveness of Duolingo's AI functionalities.

Keywords: AI, Duolingo, language learning, application

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Authors: W. Shin, Y. Kim

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This study focuses on disconfirming that wide-area networks can be made mobile, highly-available, and wireless. This methodological test shows that IPv7 and context-free grammar are mismatched. In the cases of robots, a similar tendency is also revealed. Further, we also prove that public-private key pairs could be built embedded, adaptive, and wireless. Finally, we disconfirm that although hash tables can be made distributed, interposable, and autonomous, XML and DNS can interfere to realize this purpose. Our experiments soon proved that exokernelizing our replicated Knesis keyboards was more significant than interrupting them. Our experiments exhibited degraded average sampling rate.

Keywords: collaborative communication, DNS, local-area networks, XML

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Authors: T. C. C. Soo, S. Bhassu

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Unlike the common presence of both innate and adaptive immunity in vertebrates, crustaceans, in particular, shrimps, have been discovered to possess only innate immunity. This further emphasizes the importance of innate immunity within shrimps in pathogenic resistance. Under the study of pathogenic immune challenge, different shrimp species actually exhibit varying degrees of immune resistance towards the same pathogen. Furthermore, even within the same shrimp species, different batches of challenged shrimps can have different strengths of immune defence. Several important pathways are activated within shrimps during pathogenic infection. One of them is JAK-STAT pathway that is activated during bacterial, viral and fungal infections by which STAT(Signal Transducer and Activator of Transcription) gene is the core element of the pathway. Based on theory of Central Dogma, the genomic information is transmitted in the order of DNA, RNA and protein. This study is focused in uncovering the important evolutionary patterns present within the DNA (non-coding region) and RNA (coding region). The three shrimp species involved are Macrobrachium rosenbergii, Penaeus monodon and Litopenaeus vannamei which all possess commercial significance. The shrimp species were challenged with a famous penaeid shrimp virus called white spot syndrome virus (WSSV) which can cause serious lethality. Tissue samples were collected during time intervals of 0h, 3h, 6h, 12h, 24h, 36h and 48h. The DNA and RNA samples were then extracted using conventional kits from the hepatopancreas tissue samples. PCR technique together with designed STAT gene conserved primers were utilized for identification of the STAT coding sequences using RNA-converted cDNA samples and subsequent characterization using various bioinformatics approaches including Ramachandran plot, ProtParam and SWISS-MODEL. The varying levels of immune STAT gene activation for the three shrimp species during WSSV infection were confirmed using qRT-PCR technique. For one sample, three biological replicates with three technical replicates each were used for qRT-PCR. On the other hand, DNA samples were important for uncovering the structural variations within the genomic region of STAT gene which would greatly assist in understanding the STAT protein functional variations. The partially-overlapping primers technique was used for the genomic region sequencing. The evolutionary inferences and event predictions were then conducted through the Bayesian Inference method using all the acquired coding and non-coding sequences. This was supplemented by the construction of conventional phylogenetic trees using Maximum likelihood method. The results showed that adaptive evolution caused STAT gene sequence mutations between different shrimp species which led to evolutionary divergence event. Subsequently, the divergent sites were correlated to the differing expressions of STAT gene. Ultimately, this study assists in knowing the shrimp species innate immune variability and selection of disease resistant shrimps for breeding purpose. The deeper understanding of STAT gene evolution from the perspective of both purifying and adaptive approaches not only can provide better immunological insight among shrimp species, but also can be used as a good reference for immunological studies in humans or other model organisms.

Keywords: gene evolution, JAK-STAT pathway, immunology, STAT gene

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Authors: Ahlem Mougaida, Hedi Bel Hadj Salah

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Several methods are suggested to improve the numerical integration in Galerkin weak form for Meshless methods. In fact, integrating without taking into account the characteristics of the shape functions reproduced by Meshless methods (rational functions, with compact support etc.), causes a large integration error that influences the PDE’s approximate solution. Comparisons between different methods of numerical integration for rational functions are discussed and compared. The algorithms are implemented in Matlab. Finally, numerical results were presented to prove the efficiency of our algorithms in improving results.

Keywords: adaptive methods, meshless, numerical integration, rational quadrature

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Authors: Syed Asif Hassan, Tabrej Khan

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Multiple sclerosis (MS) is a chronic demyelinating autoimmune disorder, of the central nervous system (CNS). In the present scenario, the current therapies either do not halt the progression of the disease or have side effects which limit the usage of current Disease Modifying Therapies (DMTs) for a longer period of time. Therefore, keeping the current treatment failure schema, we are focusing on screening novel analogues of the available DMTs that specifically bind and inhibit the Sphingosine1-phosphate receptor1 (S1PR1) thereby hindering the lymphocyte propagation toward CNS. The novel drug-like analogs molecule will decrease the frequency of relapses (recurrence of the symptoms associated with MS) with higher efficacy and lower toxicity to human system. In this study, an integrated approach involving ligand-based virtual screening protocol (Ultrafast Shape Recognition with CREDO Atom Types (USRCAT)) to identify the non-toxic drug like analogs of the approved DMTs were employed. The potency of the drug-like analog molecules to cross the Blood Brain Barrier (BBB) was estimated. Besides, molecular docking and simulation using Auto Dock Vina 1.1.2 and GOLD 3.01 were performed using the X-ray crystal structure of Mtb LprG protein to calculate the affinity and specificity of the analogs with the given LprG protein. The docking results were further confirmed by DSX (DrugScore eXtented), a robust program to evaluate the binding energy of ligands bound to the ligand binding domain of the Mtb LprG lipoprotein. The ligand, which has a higher hypothetical affinity, also has greater negative value. Further, the non-specific ligands were screened out using the structural filter proposed by Baell and Holloway. Based on the USRCAT, Lipinski’s values, toxicity and BBB analysis, the drug-like analogs of fingolimod and BG-12 showed that RTL and CHEMBL1771640, respectively are non-toxic and permeable to BBB. The successful docking and DSX analysis showed that RTL and CHEMBL1771640 could bind to the binding pocket of S1PR1 receptor protein of human with greater affinity than as compared to their parent compound (Fingolimod). In this study, we also found that all the drug-like analogs of the standard MS drugs passed the Bell and Holloway filter.

Keywords: antagonist, binding affinity, chemotherapeutics, drug-like, multiple sclerosis, S1PR1 receptor protein

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Authors: Sardar Ameer Akram Khan, Shahzad Amin Sheikh

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Blind equalization is an important technique amongst equalization family. Multimodulus algorithms based on blind equalization removes the undesirable effects of ISI and cater ups the phase issues, saving the cost of rotator at the receiver end. In this paper a new algorithm combination of recursive least square and Multimodulus algorithm named as RLSMMA is proposed by providing few assumption, fast convergence and minimum Mean Square Error (MSE) is achieved. The excellence of this technique is shown in the simulations presenting MSE plots and the resulting filter results.

Keywords: blind equalizations, constant modulus algorithm, multi-modulus algorithm, recursive least square algorithm, quadrature amplitude modulation (QAM)

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Authors: Vinai K. Singh

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For reducing impulsive noise without degrading image contours, median filtering is a powerful tool. In multiband images as for example colour images or vector fields obtained by optic flow computation, a vector median filter can be used. Vector median filters are defined on the basis of a suitable distance, the best performing distance being the Euclidean. Euclidean distance is evaluated by using the Euclidean norms which is quite demanding from the point of view of computation given that a square root is required. In this paper an optimal piece-wise linear approximation of the Euclidean norm is presented which is applied to vector median filtering.

Keywords: euclidean norm, quasi euclidean norm, vector median filtering, applied mathematics

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Authors: Airy Huang, Fuji Foo, Aries Prasetya Wibowo

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In recent years, the focus of Natural Language Processing (NLP) development has been gradually shifting from the semantics-based approach to deep learning one, which performs faster with fewer resources. Although it performs well in many applications, the deep learning approach, due to the lack of semantics understanding, has difficulties in noticing and expressing a novel business case with a pre-defined scope. In order to meet the requirements of specific robotic services, deep learning approach is very labor-intensive and time consuming. It is very difficult to improve the capabilities of conversational AI in a short time, and it is even more difficult to self-learn from experiences to deliver the same service in a better way. In this paper, we present an adaptive conversational AI algorithm that combines both semantic knowledge and deep learning to address this issue by learning new business cases through conversations. After self-learning from experience, the robot adapts to the business cases originally out of scope. The idea is to build new or extended robotic services in a systematic and fast-training manner with self-configured programs and constructed dialog flows. For every cycle in which a chat bot (conversational AI) delivers a given set of business cases, it is trapped to self-measure its performance and rethink every unknown dialog flows to improve the service by retraining with those new business cases. If the training process reaches a bottleneck and incurs some difficulties, human personnel will be informed of further instructions. He or she may retrain the chat bot with newly configured programs, or new dialog flows for new services. One approach employs semantics analysis to learn the dialogues for new business cases and then establish the necessary ontology for the new service. With the newly learned programs, it completes the understanding of the reaction behavior and finally uses dialog flows to connect all the understanding results and programs, achieving the goal of self-learning process. We have developed a chat bot service mounted on a kiosk, with a camera for facial recognition and a directional microphone array for voice capture. The chat bot serves as a concierge with polite conversation for visitors. As a proof of concept. We have demonstrated to complete 90% of reception services with limited self-learning capability.

Keywords: conversational AI, chatbot, dialog management, semantic analysis

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Authors: Ishita Singh

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Social-dimension of Climate Change is no longer peripheral to Science, Technology and Innovation (STI). Indeed, STI is being mobilized to address small farmers’ vulnerability and adaptation to Climate Change. The experiences from the cold desert of Leh (Ladakh) in North-West Himalaya illustrate the potential of STI to address the challenges of Climate Change and the needs of small farmers through the use of Artificial Glacier Techniques. Small farmers have a unique technique of water harvesting to augment irrigation, called “Artificial Glaciers” - an intricate network of water channels and dams along the upper slope of a valley that are located closer to villages and at lower altitudes than natural glaciers. It starts to melt much earlier and supplements additional irrigation to small farmers’ improving their livelihoods. Therefore, the issue of vulnerability, adaptive capacity and adaptation strategy needs to be analyzed in a local context and the communities as well as regions where people live. Leh (Ladakh) in North-West Himalaya provides a Case Study for exploring the ways in which adaptation to Climate Change is taking place at a community scale using Artificial Glacier Technology. With the above backdrop, an attempt has been made to analyze the rural poor households' vulnerability and adaptation practices to Climate Change using this technology, thereby drawing lessons on vulnerability-livelihood interactions in the cold desert of Leh (Ladakh) in North-West Himalaya, India. The study is based on primary data and information collected from 675 households confined to 27 villages of Leh (Ladakh) in North-West Himalaya, India. It reveals that 61.18% of the population is driving livelihoods from agriculture and allied activities. With increased irrigation potential due to the use of Artificial Glaciers, food security has been assured to 77.56% of households and health vulnerability has been reduced in 31% of households. Seasonal migration as a livelihood diversification mechanism has declined in nearly two-thirds of households, thereby improving livelihood strategies. Use of tactical adaptations by small farmers in response to persistent droughts, such as selling livestock, expanding agriculture lands, and use of relief cash and foods, have declined to 20.44%, 24.74% and 63% of households. However, these measures are unsustainable on a long-term basis. The role of policymakers and societal stakeholders becomes important in this context. To address livelihood challenges, the role of technology is critical in a multidisciplinary approach involving multilateral collaboration among different stakeholders. The presence of social entrepreneurs and new actors on the adaptation scene is necessary to bring forth adaptation measures. Better linkage between Science and Technology policies, together with other policies, should be encouraged. Better health care, access to safe drinking water, better sanitary conditions, and improved standards of education and infrastructure are effective measures to enhance a community’s adaptive capacity. However, social transfers for supporting climate adaptive capacity require significant amounts of additional investment. Developing institutional mechanisms for specific adaptation interventions can be one of the most effective ways of implementing a plan to enhance adaptation and build resilience.

Keywords: climate change, adaptation, livelihood, stakeholders

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Authors: Mohammad Umar Azizi, Tetsuya Ando

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This study investigates the transformation of the traditional landscape of Kabul Old City through an examination of five case study areas. Based on physical observation, three types of houses are found: traditional, mixed and modern. Firstly, characteristics of the houses are described according to construction materials and the number of stories. Secondly, internal and external factors are considered in order to implement a conservation plan. Finally, an adaptive conservation plan is suggested to protect the traditional landscape of Kabul Old City.

Keywords: conservation, district 1, Kabul Old City, landscape, transformation, traditional houses

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Authors: Muhammad Zeeshan, Rabia Nazir, Lubna Tahir

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Low cost filter based on iron doped zeolite (Fe-Z) and pottery clay was developed for an effective and efficient treatment of the drinking water contaminated with microbes. Fe-Z was characterized using powder XRD, SEM and EDX and shown to have average particle size of 49 nm with spongy appearance. The simulated samples of water self-contaminated with six microbes (S. typhi, B. subtilus, E. coli, S. aures, K. pneumoniae, and P. aeruginosa) after treatment with Fe-Z indicated effective removal of all the microbes in less than 30 min. Equally good results were obtained when actual drinking water samples, totally unfit for human consumption, were treated with Fe-Z.

Keywords: iron doped zeolite, biological and chemical treatment, drinking water

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Authors: Yasaman Ashrafi, Stephen Kajewski, Annastiina Silvennoinen, Madhav Nepal

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Mega projects either in construction, urban development or energy sectors are one of the key drivers that build the foundation of wealth and modern civilizations in regions and nations. Such projects require economic justification and substantial capital investment, often derived from individual and corporate investors as well as governments. Cost overruns and time delays in these mega projects demands a new approach to more accurately predict project costs and establish realistic financial plans. The significance of this paper is that the cost efficiency of megaprojects will improve and decrease cost overruns. This research will assist Project Managers (PMs) to make timely and appropriate decisions about both cost and outcomes of ongoing projects. This research, therefore, examines the oil and gas industry where most mega projects apply the classic methods of Cost Performance Index (CPI) and Schedule Performance Index (SPI) and rely on project data to forecast cost and time. Because these projects are always overrun in cost and time even at the early phase of the project, the probabilistic methods of Monte Carlo Simulation (MCS) and Bayesian Adaptive Forecasting method were used to predict project cost at completion of projects. The current theoretical and mathematical models which forecast the total expected cost and project completion date, during the execution phase of an ongoing project will be evaluated. Earned Value Management (EVM) method is unable to predict cost at completion of a project accurately due to the lack of enough detailed project information especially in the early phase of the project. During the project execution phase, the Bayesian adaptive forecasting method incorporates predictions into the actual performance data from earned value management and revises pre-project cost estimates, making full use of the available information. The outcome of this research is to improve the accuracy of both cost prediction and final duration. This research will provide a warning method to identify when current project performance deviates from planned performance and crates an unacceptable gap between preliminary planning and actual performance. This warning method will support project managers to take corrective actions on time.

Keywords: cost forecasting, earned value management, project control, project management, risk analysis, simulation

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Authors: Michael Heuer, Ayoub Al-Hamadi, Alexander Rain, Marc-Michael Meinecke

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Vulnerable road users, e.g. pedestrians, have a high impact on fatal accident numbers. To reduce these statistics, car manufactures are intensively developing suitable safety systems. Hereby, fast and reliable environment recognition is a major challenge. In this paper we describe a tracking approach that is only based on a 24 GHz radar sensor. While common radar signal processing loses much information, we make use of a track-before-detect filter to incorporate raw measurements. It is explained how the Range-Doppler spectrum can help to indicated pedestrians and stabilize tracking even in occultation scenarios compared to sensors in series.

Keywords: radar, pedestrian detection, active safety, sensor

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Authors: Radwa Mabrook

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Virtual Reality (VR) content creation is a complex and an expensive process, which requires multi-disciplinary teams of content creators. Grant schemes from technology companies help media organisations to explore the VR potential in journalism and factual storytelling. Media organisations try to do as much as they can in-house, but they may outsource due to time constraints and skill availability. Journalists, game developers, sound designers and creative artists work together and bring in new cultures of work. This study explores the collaborative experimental nature of VR content creation, through tracing every actor involved in the process and examining their perceptions of the VR work. The study builds on Actor Network Theory (ANT), which decomposes phenomena into their basic elements and traces the interrelations among them. Therefore, the researcher conducted 22 semi-structured interviews with VR content creators between November 2017 and April 2018. Purposive and snowball sampling techniques allowed the researcher to recruit fact-based VR content creators from production studios and media organisations, as well as freelancers. Interviews lasted up to three hours, and they were a mix of Skype calls and in-person interviews. Participants consented for their interviews to be recorded, and for their names to be revealed in the study. The researcher coded interviews’ transcripts in Nvivo software, looking for key themes that correspond with the research questions. The study revealed that VR content creators must be adaptive to change, open to learn and comfortable with mistakes. The VR content creation process is very iterative because VR has no established work flow or visual grammar. Multi-disciplinary VR team members often speak different languages making it hard to communicate. However, adaptive content creators perceive VR work as a fun experience and an opportunity to learn. The traditional sense of competition and the strive for information exclusivity are now replaced by a strong drive for knowledge sharing. VR content creators are open to share their methods of work and their experiences. They target to build a collaborative network that aims to harness VR technology for journalism and factual storytelling. Indeed, VR is instilling collaborative and experimental cultures in journalism.

Keywords: collaborative culture, content creation, experimental culture, virtual reality

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Authors: Janneth González, George Barreto, Ludis Morales, Angélica Sabogal

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Sea anemone neurotoxins are peptides that interact with Na+ and K+ channels, resulting in specific alterations on their functions. Some of these neurotoxins (1ROO, 1BGK, 2K9E, 1BEI) are important for the treatment of nearly eighty autoimmune disorders due to their specificity for Kv1.3 channel. The aim of this study was to identify the common residues among these neurotoxins by computational methods, and establish whether there is a pattern useful for the future generation of a treatment for autoimmune diseases. Our results showed eight new key common residues between the studied neurotoxins interacting with a histidine ring and the selectivity filter of the receptor, thus showing a possible pattern of interaction. This knowledge may serve as an input for the design of more promising drugs for autoimmune treatments.

Keywords: neurotoxins, potassium channel, Kv1.3, computational methods, autoimmune diseases

Procedia PDF Downloads 367

Authors: Rodrigo S. Moreira, Nelson F. F. Ebecken

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This paper proposes a maritime vessel tracker composed of an ensemble of WiSARD weightless neural network classifiers. A failure detector analyzes vessel movement with a Kalman filter and corrects the tracking, if necessary, using FFT matching. The use of the WiSARD neural network to track objects is uncommon. The additional contributions of the present study include a performance comparison with four state-of-art trackers, an experimental study of the features that improve maritime vessel tracking, the first use of an ensemble of classifiers to track maritime vessels and a new quantization algorithm that compares the values of pixel pairs.

Keywords: ram memory, WiSARD weightless neural network, object tracking, quantization

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Authors: Eiman Kattan, Hong Wei

Abstract:

In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: Mohammad A. Obeidat, Ayman M. Mansour

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Capturing the dynamic behavior of the heart to improve control performance, enhance robustness, and support diagnosis is very important in establishing real time models for the heart. Control Techniques and strategies have been utilized to improve system costs, reliability, and estimation accuracy for different types of systems such as biomedical, industrial, and other systems that required tuning input/output relation and/or monitoring. Simulations are performed to illustrate potential applications of the technology. In this research, a new control technology scheme is used to enhance the performance of the Af system and meet the design specifications.

Keywords: atrial fibrillation, dynamic behavior, closed loop, signal, filter

Procedia PDF Downloads 407

Authors: Mihaela Popescu, Alexandru Bitoleanu

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This paper is focused on the reference current calculation in the compensation mode of the active DC traction substations. The so-called p-q theory of the instantaneous reactive power is used as theoretical foundation. The compensation goal of total compensation is taken into consideration for the operation under both sinusoidal and nonsinusoidal voltage conditions, through the two objectives of unity power factor and perfect harmonic cancelation. Four blocks of reference current generation implement the conceived algorithms and they are included in a specific Simulink library, which is useful in a DSP dSPACE-based platform working under Matlab/Simulink. The simulation results validate the correctness of the implementation and fulfillment of the compensation tasks.

Keywords: active power filter, DC traction, p-q theory, Simulink library

Procedia PDF Downloads 661

Authors: Bjorn Kierulf, Arun Chundru

Abstract:

Over the past decade, collegiate rocketry teams have emerged across the country with various goals: space, liquid-fueled flight, etc. A critical piece of the development of knowledge within a club is the use of so-called "sounding rockets," whose goal is to take in-flight measurements that inform future rocket design. Common measurements include acceleration from inertial measurement units (IMU's), and altitude from barometers. With a properly tuned filter, these measurements can be used to find velocity, but are susceptible to noise, offset, and filter settings. Instead, velocity can be measured more directly and more instantaneously using a pitot tube, which operates by measuring the stagnation pressure. At supersonic speeds, an additional thermodynamic property is necessary to constrain the upstream state. One possibility is the stagnation temperature, measured by a thermocouple in the pitot tube. The routing of the pitot tube from the nosecone tip down to a pressure transducer is complicated by the nosecone's structure. Commercial-off-the-shelf (COTS) nosecones come with a removable metal tip (without a pitot tube). This provides the opportunity to make custom tips with integrated measurement systems without making the nosecone from scratch. The main design constraint is how the nosecone tip is held down onto the nosecone, using the tension in a threaded rod anchored to a bulkhead below. Because the threaded rod connects into a threaded hole in the center of the nosecone tip, the pitot tube follows a winding path, and the pressure fitting is off-center. Two designs will be presented in the paper, one with a curved pitot tube and a coaxial design that eliminates the need for the winding path by routing pressure through a structural tube. Additionally, three manufacturing methods will be presented for these designs: bound powder filament metal 3D printing, stereo-lithography (SLA) 3D printing, and traditional machining. These will employ three different materials, copper, steel, and proprietary resin. These manufacturing methods and materials are relatively low cost, thus accessible to student researchers. These designs and materials cover multiple use cases, based on how fast the sounding rocket is expected to travel and how important heating effects are - to measure and to avoid melting. This paper will include drawings showing key features and an overview of the design changes necessitated by the manufacture. It will also include a look at the successful use of these nosecone tips and the data they have gathered to date.

Keywords: additive manufacturing, machining, pitot tube, sounding rocketry

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Authors: Rana Mahmoud

Abstract:

This study represents a systematic study of the Operational Transconductance Amplifiers capacitance (OTA-C) filters or as it is often called Gm-C filters. OTA-C filters have been paid a great attention for the last decades. As Gm-C filters operate in an open loop topology, this makes them flexible to perform in low and high frequencies. As such, Gm-C filters can be used in various wireless communication applications. Another property of Gm-C filters is its electronic tunability, thus different filter frequency characteristics can be obtained without changing the inductance and resistance values. This can be achieved by an OTA (Operational Transconductance Amplifier) and a capacitor. By tuning the OTA transconductance, the cut-off frequency will be tuned and different frequency responses are achieved. Different high-order analog filters can be design using Gm-C filters including low pass, high pass and band pass filters. 1st and 2nd order low pass, high pass and band pass filters are presented in this paper.

Keywords: Gm-C, filters, low-pass, high-pass, band-pass

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Authors: Sou Watanabe, Hiromichi Ogi, Atsuhiro Shibata, Kazunori Nomura

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As a part of STRAD project conducted by JAEA, condensation of radioactive liquid waste containing various chemical compounds using reverse osmosis (RO) membrane filter was examined for efficient and safety treatment of the liquid wastes accumulated inside hot laboratories. NH₄⁺ ion in the feed solution was successfully concentrated, and NH₄⁺ ion involved in the effluents became lower than target value; 100 ppm. Solidification of simulated aqueous and organic liquid wastes was also tested. Those liquids were successfully solidified by adding cement or coagulants. Nevertheless, optimization in materials for confinement of chemicals is required for long time storage of the final solidified wastes.

Keywords: condensation, radioactive liquid waste, solidification, STRAD project

Procedia PDF Downloads 150