Search results for: seed sensor

Authors: G. Disciglio, F. Lops, A. Carlucci, G. Gatta, A. Tarantino, L. Frabboni, F. Carriero, F. Cibelli, M. L. Raimondo, E. Tarantino

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The Phelipanche ramosa is is an important crop whose cultivation in the Mediterranean basin is severely contained the phitoparasitic weed Phelipanche ramose. The semiarid regions of the world are considered the main center of this parasitic weed, where heavy infestation is due to the ability to produce high numbers of seeds (up to 500,000 per plant), that remain viable for extended period (more than 19 years). In this paper 12 treatments of parasitic weed control including chemical, agronomic, biological and biotechnological methods have been carried out. In 2014 a trial was performed at Foggia (southern Italy). on processing tomato (cv Docet), grown in field infested by Phelipanche ramosa, Tomato seedlings were transplant on May 5, 2014 on a clay-loam soil (USDA) fertilized by 100 kg ha-1 of N; 60 kg ha-1 of P2O5 and 20 kg ha-1 of S. Afterwards, top dressing was performed with 70 kg ha-1 of N. The randomized block design with 3 replicates was adopted. During the growing cycle of the tomato, at 56-78 and 92 days after transplantation, the number of parasitic shoots emerged in each pot was detected. At harvesting, on August 18, the major quantity-quality yield parameters were determined (marketable yield, mean weight, dry matter, pH, soluble solids and color of fruits). All data were subjected to analysis of variance (ANOVA), using the JMP software (SAS Institute Inc., Cary, NC, USA), and for comparison of means was used Tukey's test. Each treatment studied did not provide complete control against Phelipanche ramosa. However among the 12 tested methods, Fusarium, gliphosate, radicon biostimulant and Red Setter tomato cv (improved genotypes obtained by Tilling technology) proved to mitigate the virulence of the attacks of Phelipanche ramose. It is assumed that these effects can be improved by combining some of these treatments each other, especially for a gradual and continuing reduction of the “seed bank” of the parasite in the soil.

Keywords: control methods, Phelipanche ramosa, tomato crop, mediterranean basin

Procedia PDF Downloads 555

Authors: Mateusz Meserszmit, Mariusz Chrabąszcz, Adriana Trojanowska-Olichwer, Zygmunt Kącki

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Semi-natural meadows are valuable communities from the point of view of biodiversity, but their survival is strongly related to human activity. Unfortunately, the current status of preservation of extensively used meadows in Europe is frequently assessed as “unfavorable”. This is due to agricultural activity, in particular the lack of appropriate conservation procedures such as the cutting of meadows or livestock grazing. However, for more effective protective measures, the preservation of the biological diversity of meadows requires an interdisciplinary approach from both scientists and practitioners from many fields. Our research aimed to present the possibility of conservation of semi-natural meadows using cut biomass for the production of bioenergy – biogas, taking into consideration the botanical characteristics of the studied habitat and the chemical properties of biomass. A field study was conducted in Poland, within an area covered by the European Union's nature conservation programme. The samples were collected on four dates (May 24th, July 1st, July 23rd, and September 1st) from a study site established within a Molinion meadow. The biomass collected at the earliest date mostly consisted of plants with flowers in bud or fully open flowers. At the later harvest dates, most plants were at the fruiting or seed shed stage. An earlier stage of plant growth contributed to a lower biomass yield, which also resulted in a lower methane yield per hectare. The methane yield per hectare was at the end of May 482 m3 CH4 ha-1, at the beginning of July 867 m3 CH4 ha-1, at the end of July 759 m3 CH4 ha-1 and at the beginning of September 730 m3 CH4 ha-1. The biomass harvested in May demonstrated a significantly higher content of the elements: N, P, and K, but a lower Ca content compared to later harvested biomass, which may affect the biogas production process. The use of hay as a source of renewable energy can become an important element of conservation adapted for this type of habitat.

Keywords: nature conservation, biomass, bioenergy, grassland

Procedia PDF Downloads 100

Authors: Hao Li, Guy Y. Cornejo Maceda, Yiqing Li, Jianguo Tan, Marek Morzynski, Bernd R. Noack

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We propose an automated analysis of the flow control behaviour from an ensemble of control laws and associated time-resolved flow snapshots. The input may be the rich database of machine learning control (MLC) optimizing a feedback law for a cost function in the plant. The proposed methodology provides (1) insights into the control landscape, which maps control laws to performance, including extrema and ridge-lines, (2) a catalogue of representative flow states and their contribution to cost function for investigated control laws and (3) visualization of the dynamics. Key enablers are classification and feature extraction methods of machine learning. The analysis is successfully applied to the stabilization of a mixing layer with sensor-based feedback driving an upstream actuator. The fluctuation energy is reduced by 26%. The control replaces unforced Kelvin-Helmholtz vortices with subsequent vortex pairing by higher-frequency Kelvin-Helmholtz structures of lower energy. These efforts target a human interpretable, fully automated analysis of MLC identifying qualitatively different actuation regimes, distilling corresponding coherent structures, and developing a digital twin of the plant.

Keywords: machine learning control, mixing layer, feedback control, model-free control

Procedia PDF Downloads 210

Authors: Tayyab Hassan, Talha Rehman, Qasim Abdul Aziz, Ahmad Salman

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The constant monitoring of blood glucose level is necessary for maintaining health of patients and to alert medical specialists to take preemptive measures before the onset of any complication as a result of diabetes. The current clinical monitoring of blood glucose uses invasive methods repeatedly which are uncomfortable and may result in infections in diabetic patients. Several attempts have been made to develop non-invasive techniques for blood glucose measurement. In this regard, the existing methods are not reliable and are less accurate. Other approaches claiming high accuracy have not been tested on extended dataset, and thus, results are not statistically significant. It is a well-known fact that acetone concentration in breath has a direct relation with blood glucose level. In this paper, we have developed the first of its kind, reliable and high accuracy breath analyzer for non-invasive blood glucose measurement. The acetone concentration in breath was measured using MQ 138 sensor in the samples collected from local hospitals in Pakistan involving one hundred patients. The blood glucose levels of these patients are determined using conventional invasive clinical method. We propose a linear regression classifier that is trained to map breath acetone level to the collected blood glucose level achieving high accuracy.

Keywords: blood glucose level, breath acetone concentration, diabetes, linear regression

Procedia PDF Downloads 163

Authors: Esra Ece Var

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Beekeeping plays essential role both in terms of agricultural yields and agricultural economy; they produce honey, wax, royal jelly, apitoxin, pollen, and propolis. Nowadays, these natural products become more importantly suitable and preferable for nutrition, food supplement, medicine, and industry. However, to produce organic honey, majority of the apiaries are located in remote or distant rural areas where utilities such as electricity and Internet network are not available. Additionally, due to colony failures, world honey production decreases year by year despite the increase in the number of beehives. The objective of this paper is to develop a smart beehive monitoring system for apiaries including those that do not have access to Internet network. In this context, temperature and humidity inside the beehive, and ambient temperature were measured with RFID sensors. Control center, where all sensor data was sent and stored at, has a GSM module used to warn the beekeeper via SMS when an anomaly is detected. Simultaneously, using the collected data, an unsupervised machine learning algorithm is used for detecting anomalies and calibrating the warning system. The results show that the smart beehive monitoring system can detect fatal anomalies up to 4 weeks prior to colony loss.

Keywords: beekeeping, smart systems, machine learning, anomaly detection, apiculture

Procedia PDF Downloads 220

Authors: Illyas Md Isa, Maryam Musfirah Che Sobry, Mohamad Syahrizal Ahmad, Nurashikin Abd Azis

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A single-walled carbon nanotube (SWCNT) that has been modified with magnesium layered hydroxide 3-(4-methoxyphenyl)propionic acid nanocomposite was proposed for the determination of uric acid and bisphenol A by square wave voltammetry. The results obtained denote that MLH-MPP nanocomposites enhance the sensitivity of the voltammetry detection responses. The best performance is shown by the modified carbon nanotube paste electrode (CNTPE) with the composition of single-walled carbon nanotube: magnesium layered hydroxide 3-(4-methoxyphenyl)propionic acid nanocomposite at 100:15 (% w/w). The linear range where the sensor works well is within the concentration 1.0 10-7 – 1.0 10-4 and 3.0 10-7 – 1.0 10-4 for uric acid and bisphenol A respectively with the limit of detection of 1.0 10-7 M for both organics. The interferences of uric acid and bisphenol A with other organic were studied and most of them did not interfere. The results shown for each experimental parameter on the proposed CNTPE showed that it has high sensitivity, good selectivity, repeatability and reproducibility. Therefore, the modified CNTPE can be used for the determination of uric acid and bisphenol A in real samples such as blood, plastic bottles and foods.

Keywords: bisphenol A, magnesium layered hydroxide 3-(4-methoxyphenyl)propionic acid nanocomposite, Nanocomposite, uric acid

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Authors: Yoshie Asahara, Hidekuni Takao

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Non-invasive positive pressure ventilation (NPPV), a type of ventilation therapy, is a treatment in which a mask is attached to the patient's face and delivers gas into the mask to support breathing. The NPPV mask uses a strap, which is necessary to attach and secure the mask in the appropriate facial position, but the tensile strength of the strap is adjusted by the sensation of the hands. The strap uniformity and fine-tuning strap tension are judged by the skill of the operator and the amount felt by the finger. In the future, additional strap operation and adjustment methods will be required to meet the needs for reducing the burden on the patient’s face. In this study, we fabricated a mechanism that can measure, adjust and fix the tension of the straps. A small amount of strap tension can be adjusted by rotating the shaft. This makes it possible to control the slight strap tension that is difficult to grasp with the sense of the operator's hand. In addition, this mechanism allows the operator to control the strap while controlling the movement of the mask body. This leads to the establishment of a suitable mask fitting method for each patient. The developed mechanism enables the operation and fine reproducible adjustment of the strap tension and the mask balance, reducing the burden on the face.

Keywords: balance of the mask strap, fine adjustment, film sensor, mask fitting technique, mask strap tension

Procedia PDF Downloads 223

Authors: Surajit Chakrabarty, Piyush Chauhan, Subhasis Panda, Sujoy Bhattacharya

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A large proportion of roads in India are not well maintained as per the laid down public safety guidelines leading to loss of direction control and fatal accidents. We propose a technique to detect speed breakers and potholes using mobile sensor data captured from multiple vehicles and provide a profile of the road. This would, in turn, help in monitoring roads and revolutionize digital maps. Incorporating randomness in the model formulation for detection of speed breakers and potholes is crucial due to substantial heterogeneity observed in data obtained using a mobile application from multiple vehicles driven by different drivers. This is accomplished with Hidden Markov Models, whose hidden state sequence is found for each time step given the observables sequence, and are then fed as input to LSTM network with peephole connections. A precision score of 0.96 and 0.63 is obtained for classifying bumps and potholes, respectively, a significant improvement from the machine learning based models. Further visualization of bumps/potholes is done by converting time series to images using Markov Transition Fields where a significant demarcation among bump/potholes is observed.

Keywords: deep learning, hidden Markov model, pothole, speed breaker

Procedia PDF Downloads 132

Authors: Angela Meyer

Abstract:

The operation and maintenance cost for wind parks make up a major fraction of the park’s overall lifetime cost. To minimize the cost and risk involved, an optimal operation and maintenance strategy requires continuous monitoring and analysis. In order to facilitate this, we present a decision support system that automatically scans the stream of telemetry sensor data generated from the turbines. By learning decision boundaries and normal reference operating states using machine learning algorithms, the decision support system can detect anomalous operating behavior in individual wind turbines and diagnose the involved turbine sub-systems. Operating personal can be alerted if a normal operating state boundary is exceeded. The presented decision support system and method are applicable for any turbine type and manufacturer providing telemetry data of the turbine operating state. We demonstrate the successful detection and diagnosis of anomalous operating states in a case study at a German onshore wind park comprised of Vestas V112 turbines.

Keywords: anomaly detection, decision support, machine learning, monitoring, performance optimization, wind turbines

Procedia PDF Downloads 156

Authors: Muhammad Maqsood, Yasir Nawab, Syed Talha Ali Hamdani

Abstract:

Stretchable fabrics have diverse applications ranging from casual apparel to performance sportswear and compression therapy. Compression therapy is the universally accepted treatment for the management of hypertrophic scarring after severe burns. Mostly stretchable knitted fabrics are used in compression therapy but in the recent past, some studies have also been found on bi-stretch woven fabrics being used as compression garments as they also have been found quite effective in the treatment of oedema. Therefore, the objective of the present study is to compare the compression properties of stretchable knitted and bi-stretch woven fabrics for compression garments. For this purpose four woven structures and four knitted structures were produced having the same areal density and their compression, comfort and mechanical properties were compared before and after 5, 10 and 15 washes. Four knitted structures used were single jersey, single locaste, plain pique and the honeycomb, whereas four woven structures produced were 1/1 plain, 2/1 twill, 3/1 twill and 4/1 twill. The compression properties of the produced samples were tested by using kikuhime pressure sensor and it was found that bi-stretch woven fabrics possessed better compression properties before and after washes and retain their durability after repeated use, whereas knitted stretchable fabrics lost their compression ability after repeated use and the required sub garment pressure of the knitted structures after 15 washes was almost half to that of woven bi-stretch fabrics.

Keywords: compression garments, knitted structures, medical textiles, woven bi-stretch

Procedia PDF Downloads 399

Authors: Justin Tang

Abstract:

Balance tests are frequently used to diagnose concussions on the sidelines of sporting events. Manual scoring, however, is labor intensive and subjective, and many concussions go undetected. This study institutes a novel approach to conducting the Balance Error Scoring System (BESS) more quantitatively using Microsoft’s gaming system Kinect, which uses a contactless sensor and several cameras to receive data and estimate body limb positions. Using a machine learning approach, Visual Gesture Builder, and a deterministic approach, MATLAB, we tested whether the Kinect can differentiate between “correct” and erroneous stances of the BESS. We created the two separate solutions by recording test videos to teach the Kinect correct stances and by developing a code using Java. Twenty-two subjects were asked to perform a series of BESS tests while the Kinect was collecting data. The Kinect recorded the subjects and mapped key joints onto their bodies to obtain angles and measurements that are interpreted by the software. Through VGB and MATLAB, the videos are analyzed to enumerate the number of errors committed during testing. The resulting statistics demonstrate a high correlation between manual scoring and the Kinect approaches, indicating the viability of the use of remote tracking devices in conducting concussion tests.

Keywords: automated, concussion detection, contactless sensors, microsoft kinect

Procedia PDF Downloads 309

Authors: Teklay Tesfay, Gebreyesus Brhane Tesfahunegn, Abadi Berhane, Selemawit Girmay

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Adjusting the proper sowing date of a crop at a particular location with a changing climate is an essential management option to maximize crop yield. However, determining the optimum sowing date for rainfed maize production through field experimentation requires repeated trials for many years in different weather conditions and crop management. To avoid such long-term experimentation to determine the optimum sowing date, crop models such as AquaCrop are useful. Therefore, the overall objective of this study was to evaluate the performance of AquaCrop model in simulating maize productivity under varying sowing dates. A field experiment was conducted for two consecutive cropping seasons by deploying four maize seed sowing dates in a randomized complete block design with three replications. Input data required to run this model are stored as climate, crop, soil, and management files in the AquaCrop database and adjusted through the user interface. Observed data from separate field experiments was used to calibrate and validate the model. AquaCrop model was validated for its performance in simulating the green canopy and aboveground biomass of maize for the varying sowing dates based on the calibrated parameters. Results of the present study showed that there was a good agreement (an overall R2 =, Ef= d= RMSE =) between measured and simulated values of the canopy cover and biomass yields. Considering the overall values of the statistical test indicators, the performance of the model to predict maize growth and biomass yield was successful, and so this is a valuable tool help for decision-making. Hence, this calibrated and validated model is suggested to use for determining optimum maize crop sowing date for similar climate and soil conditions to the study area, instead of conducting long-term experimentation.

Keywords: AquaCrop model, calibration, validation, simulation

Procedia PDF Downloads 49

Authors: Manpreet Kaur, Amita Rani, Sanjay Kumar

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The Internet of Things (IoT), a cyber-physical paradigm, allows a large number of devices to connect and send the sensory data in the network simultaneously. This tremendous amount of data generated leads to very high network load consequently resulting in network congestion. It further amounts to frequent loss of useful information and depletion of significant amount of nodes’ energy. Therefore, there is a need to control congestion in IoT so as to prolong network lifetime and improve the quality of service (QoS). Hence, we propose a two-level clustering based routing algorithm considering congestion score and packet priority metrics that focus on minimizing the network congestion. In the proposed Priority based Congestion Control (PBCC) protocol the sensor nodes in IoT network form clusters that reduces the amount of traffic and the nodes are prioritized to emphasize important data. Simultaneously, a congestion score determines the occurrence of congestion at a particular node. The proposed protocol outperforms the existing Packet Discard Network Clustering (PDNC) protocol in terms of buffer size, packet transmission range, network region and number of nodes, under various simulation scenarios.

Keywords: internet of things, cyber-physical systems, congestion control, priority, transmission rate

Procedia PDF Downloads 298

Authors: Nhat Linh Ho, Thanh-Phong Dao, Shyh-Chour Huang, Hieu Giang Le

Abstract:

This paper presents a design and optimization for a compliant gripper. The gripper is constructed based on the concept of compliant mechanism with flexure hinge. A passive force regulation mechanism is presented to control the grasping force a micro-sized object instead of using a sensor force. The force regulation mechanism is designed using the planar springs. The gripper is expected to obtain a large range of displacement to handle various sized objects. First of all, the statics and dynamics of the gripper are investigated by using the finite element analysis in ANSYS software. And then, the design parameters of the gripper are optimized via Taguchi method. An orthogonal array L₉ is used to establish an experimental matrix. Subsequently, the signal to noise ratio is analyzed to find the optimal solution. Finally, the response surface methodology is employed to model the relationship between the design parameters and the output displacement of the gripper. The design of experiment method is then used to analyze the sensitivity so as to determine the effect of each parameter on the displacement. The results showed that the compliant gripper can move with a large displacement of 213.51 mm and the force regulation mechanism is expected to be used for high precision positioning systems.

Keywords: flexure hinge, compliant mechanism, compliant gripper, force regulation mechanism, Taguchi method, response surface methodology, design of experiment

Procedia PDF Downloads 315

Authors: Bruk Gebregziabher

Abstract:

The safe and efficient operation of Autonomous Mobile Robots (AMRs) in complex environments, such as manufacturing, logistics, and agriculture, necessitates accurate multiobject tracking and predictive collision avoidance. This paper presents algorithms and techniques for addressing these challenges using Lidar sensor data, emphasizing ensemble Kalman filter. The developed predictive collision avoidance algorithm employs the data provided by lidar sensors to track multiple objects and predict their velocities and future positions, enabling the AMR to navigate safely and effectively. A modification to the dynamic windowing approach is introduced to enhance the performance of the collision avoidance system. The overall system architecture encompasses object detection, multi-object tracking, and predictive collision avoidance control. The experimental results, obtained from both simulation and real-world data, demonstrate the effectiveness of the proposed methods in various scenarios, which lays the foundation for future research on global planners, other controllers, and the integration of additional sensors. This thesis contributes to the ongoing development of safe and efficient autonomous systems in complex and dynamic environments.

Keywords: autonomous mobile robots, multi-object tracking, predictive collision avoidance, ensemble Kalman filter, lidar sensors

Procedia PDF Downloads 70

Authors: Aoqi Zhang, Changgil Lee Lee, Seunghee Park

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A non-contact nondestructive technique using laser-induced ultrasonic wave generation method was applied to visualize corrosion damage at aluminum alloy plate structures. The ultrasonic waves were generated by a Nd:YAG pulse laser, and a galvanometer-based laser scanner was used to scan specific area at a target structure. At the same time, wave responses were measured at a piezoelectric sensor which was attached on the target structure. The visualization of structural damage was achieved by calculating logarithmic values of root mean square (RMS). Damage-sensitive feature was defined as the scattering characteristics of the waves that encounter corrosion damage. The corroded damage was artificially formed by hydrochloric acid. To observe the effect of the location where the corrosion was formed, the both sides of the plate were scanned with same scanning area. Also, the effect on the depth of the corrosion was considered as well as the effect on the size of the corrosion. The results indicated that the damages were successfully visualized for almost cases, whether the damages were formed at the front or back side. However, the damage could not be clearly detected because the depth of the corrosion was shallow. In the future works, it needs to develop signal processing algorithm to more clearly visualize the damage by improving signal-to-noise ratio.

Keywords: non-destructive testing, corrosion, pulsed laser scanning, ultrasonic waves, plate structure

Procedia PDF Downloads 291

Authors: Qian Liu, Steve Furber

Abstract:

To explore how the brain may recognize objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor~(DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network~(SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modeled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study's largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognize the postures with an accuracy of around 86.4% -only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much-improved cost to performance trade-off in its approach.

Keywords: spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system

Procedia PDF Downloads 455

Authors: P. Chambe, B. Canova, A. Balabanian, M. Pele, N. Coeur

Abstract:

To avoid battery assisted tags with limited lifetime batteries, it is proposed here to replace them by energy harvesting systems, able to feed from local environment. This would allow total independence to RFID systems, very interesting for applications where tag removal from its location is not possible. Example is here described for luggage safety in airports, and is easily extendable to similar situation in terms of operation constraints. The idea is to fix RFID tag with energy harvesting system not only to identify luggage but also to supply an embedded microcontroller with a sensor delivering luggage weight making it impossible to add or to remove anything from the luggage during transit phases. The aim is to optimize the harvested energy for such RFID applications, and to study in which limits these applications are theoretically possible. Proposed energy harvester is based on two energy sources: piezoelectricity and electromagnetic waves, so that when the luggage is moving on ground transportation to airline counters, the piezo module supplies the tag and its microcontroller, while the RF module operates during luggage transit thanks to readers located along the way. Tag location on the luggage is analyzed to get best vibrations, as well as harvester better choice for optimizing the energy supply depending on applications and the amount of energy harvested during a period of time. Effects of system parameters (RFID UHF frequencies, limit distance between the tag and the antenna necessary to harvest energy, produced voltage and voltage threshold) are discussed and working conditions for such system are delimited.

Keywords: RFID tag, energy harvesting, piezoelectric, EM waves

Procedia PDF Downloads 441

Authors: Muhammad Afzal, Shahbaz Mushtaq, Duc-Anh-An-Vo, Kathryn Reardon Smith, Thanh Ma

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Climate change has become one of the most challenging environmental issues in the 21st century. Climate change-induced natural disasters, especially floods, are the major factors of livelihood vulnerability, impacting millions of individuals worldwide. Evaluating and mitigating the effects of floods requires an in-depth understanding of the relationship between vulnerability and livelihood capital assets. Using an integrated approach, sustainable livelihood framework, and system thinking approach, the study developed a conceptual model of a generalized livelihood system in District Rajanpur, Pakistan. The model visualizes the livelihood vulnerability system as a whole and identifies the key feedback loops likely to influence the livelihood vulnerability. The study suggests that such conceptual models provide effective communication and understanding tools to stakeholders and decision-makers to anticipate the problem and design appropriate policies. It can also serve as an evaluation technique for rural livelihood policy and identify key systematic interventions. The key finding of the study reveals that household income, health, and education are the major factors behind the livelihood vulnerability of the rural poor of District Rajanpur. The Pakistani government tried to reduce the livelihood vulnerability of the region through different income, health, and education programs, but still, many changes are required to make these programs more effective especially during the flood times. The government provided only cash to vulnerable and marginalized families through income support programs, but this study suggests that along with the cash, the government must provide seed storage facilities and access to crop insurance to the farmers. Similarly, the government should establish basic health units in villages and frequent visits of medical mobile vans should be arranged with advanced medical lab facilities during and after the flood.

Keywords: livelihood vulnerability, rural communities, flood, sustainable livelihood framework, system dynamics, Pakistan

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Authors: Ow Tze Weng, Suhaila Isaak, Yusmeeraz Yusof

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The trend of health care screening devices in the world is increasingly towards the favor of portability and wearability, especially in the most common electrocardiogram (ECG) monitoring system. This is because these wearable screening devices are not restricting the patient’s freedom and daily activities. While the demand of low power and low cost biomedical system on chip (SoC) is increasing in exponential way, the front end ECG sensors are still suffering from flicker noise for low frequency cardiac signal acquisition, 50 Hz power line electromagnetic interference, and the large unstable input offsets due to the electrode-skin interface is not attached properly. In this paper, a high performance CMOS amplifier for ECG sensors that suitable for low power wearable cardiac screening is proposed. The amplifier adopts the highly stable folded cascode topology and later being implemented into RC feedback circuit for low frequency DC offset cancellation. By using 0.13 µm CMOS technology from Silterra, the simulation results show that this front end circuit can achieve a very low input referred noise of 1 pV/√Hz and high common mode rejection ratio (CMRR) of 174.05 dB. It also gives voltage gain of 75.45 dB with good power supply rejection ratio (PSSR) of 92.12 dB. The total power consumption is only 3 µW and thus suitable to be implemented with further signal processing and classification back end for low power biomedical SoC.

Keywords: CMOS, ECG, amplifier, low power

Procedia PDF Downloads 236

Authors: Betina Luiza Koop, Lenilton Santos Soares, Karina Cesca, Germán Ayala Valencia, Alcilene Rodrigues Monteiro

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Active and smart food packaging has been studied to control and extend the food shelf-life. However, active compounds such as anthocyanins (ACNs) are unstable to high temperature, light, and pH changes. Several alternatives to stabilize and protect the anthocyanins have been researched, such as adsorption on nanoclays. Thus, this work aimed to stabilize anthocyanin extracted from jambolan fruit (Syzygium cumini), a noncommercial fruit, to development of food package sensors. The anthocyanin extract from jambolan pulp was concentrated by ultrafiltration and adsorbed on montmorillonite. The final biohybrid material was characterized by pH and color. Anthocyanins were adsorbed on nanoclay at pH 1.5, 2.5, and 3.5 and temperatures of 10 and 20 °C. The highest adsorption values were obtained at low pH at high temperatures. The color and antioxidant activity of the biohybrid was maintained for 60 days. A test of the color stability at pH from 1 to 13, simulating spoiled food using ammonia vapor, was performed. At pH from 1 to 5, the ACNs pink color was maintained, indicating that the flavylium cation form was preserved. At pH 13, the biohybrid presented yellow color due to the ACN oxidation. These results showed that the biohybrid material developed has potential application as a sensor to indicate the freshness of meat products.

Keywords: anthocyanin, biohybrid, food, smart packaging

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Authors: Joseph C. Chen, Venkata Mohan Kudapa

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Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations

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Authors: Shabistana Nisar, Parvez Qamar Rizvi, Sheeraz Malik

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The potential advantage of nanotechnology is comparably marginal due to its unclear benefits in agriculture and insufficiency in public opinion. The nanotech products might solve the pesticide problems of societal concern fairly at acceptable or low risk for consumers and environmental applications. The deleterious effect of chemicals used on crops can be compacted either by reducing the existing active ingredient to nanosize or by plummeting the metals into nanoform. Considering the above facts, an attempt was made to determine the efficacy of nanoelements viz., Silver, Copper Manganese and Neem seed kernel extract (NSKE) for effective management of gram pod borer, Helicoverpa armigera infesting chickpea, being the most damaging pest of large number of crops, gram pod borer was selected as test insect to ascertain the impact of nanoparticles under controlled conditions (25-27 ˚C, 60-80% RH). The respective nanoformulations (0.01, 0.005, 0.003, 0.0025, 0.002, 0.001) were topically applied on 4th instar larvae of pod borer. In general, nanochemicals (silver, copper, manganese, NSKE) produced relatively high mortality at low dilutions (0.01, 0.005, 0.003). The least mortality was however recorded at 0.001 concentration. Nanosilver proved most efficient producing significantly highest (f₄,₂₄=129.56, p < 0.05) mortality 63.13±1.77, 83.21±2.02 and 96.10±1.25 % at 0.01 concentration after 2nd, 4th and 6th day, respectively. The least mortality was however recorded with nanoNSKE. The mortality values obtained at respective days were 21.25±1.50%, 25.20±2.00%, and 56.20±2.25%. Nanocopper and nanomanganese showed slow rate of killing on 2nd day of exposure, but increased (79.20±3.25 and 65.33±1.25) at 0.01 dilution on 3rd day, followed by 83.00±3.50% and 70.20±2.20% mortality on 6thday. The sluggishness coupled with antifeedancy was noticed at early stage of exposure. The change in body colour to brown due to additional melanisation in copper, manganese, and silver treated larvae and demalinization in nanoNSKE exposed larvae was observed at later stage of treatment. Thus, all the nanochemicals applied, produced the significant lethal impact on Helicoverpa armigera and can be used as valuable tool for its effective management.

Keywords: chickpea, helicoverpa armigera, management, nanoparticles

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Authors: Auwal Ibrahim Magashi, Lawan Dan Larai Fagwalawa, Muhammad Bello Ibrahim

Abstract:

A research was conducted to study genetic variability of some quantitative traits in varieties of cowpea (Vigna unguiculata L. [Walp]) under water stressed from Zaria, Nigeria. Seeds of seven varieties of cowpea (Sampea 1, Sampea 2, IAR1074, Sampea 7, Sampea 8, Sampea 10 and Sampea 12) collected from Institute for Agricultural Research (IAR), Samaru, Zaria were screened for water stressed tolerance. The seeds were then sown in poly bags containing sandy-loam arranged in Completely Randomized Design with three replications for quantitative traits evaluation. The nutritional composition of the seeds obtained from the water stress tolerant varieties of cowpea were analyzed. The result obtained revealed highly significant difference (P ≤ 0.01) in the effects of water stress on the number of wilted and dead plants at 40 days after sowing (DAS) and significant (P ≤ 0.05) 34 DAS. However, sampea 10 has the highest mean performance in terms of number of wilted plants at 34 DAS while sampea 2 and IAR 1074 has the lowest mean performance. However, sampea 7 was found to have the highest mean performance for the number of wilted plants at 40 DAS and sampea 2 is lowest. The result for quantitative traits study indicated highly significant difference (P ≤ 0.01) in the plant height, number of days to 50% flowering, number of days to maturity, number of pods per plant, pod length, number of seeds per plant and 100 seed weight; and significant (P ≤ 0.05) at seedling height and number of branches per plant. Similarly, IAR1074 was found to have high performance in terms of most of the quantitative traits under study. However, sampea 8 has the highest mean performance at nutritional level. It was therefore concluded that, all the seven cowpea genotypes were water stress tolerant and produced considerable yield that contained significant nutrients. It was recommended that IAR1074 should be grown for yield while sampea 8 should be grown for protein supplements.

Keywords: cowpea, genetic variability, quantitative traits, water stress

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Authors: Mujahid Farid, Shafaqat Ali, Muhammad Bilal Shakoor

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Heavy metals pollution of soil is a prevalent global problem and oilseed rape (Brassica napus L.) are considered useful for the restoration of metal contaminated soils. Phytoextraction is an in-situ environment-friendly technique for the clean-up of contaminated soils. Response to cadmium (Cd) toxicity in combination with a chelator, Ethylenediamminetetraacetic acid (EDTA) was studied in oilseed rape grown hydroponically in greenhouse conditions under three levels of Cd (0, 10, and 50 µM) and two levels of EDTA (0 and 2.5 mM). Cd decreased plant growth, biomass and chlorophyll concentrations while the application of EDTA enhanced plant growth by reducing Cd-induced effects in Cd-stressed plants. Significant decrease in photosynthetic parameters was found by the Cd alone. Addition of EDTA improved the net photosynthetic and gas exchange capacity of plants under Cd stress. Cd at 10 and 50 μM significantly increased electrolyte leakage, the production of hydrogen peroxidase (H2O2) and malondialdehyde (MDA) and a significant reduction was observed in the activities of catalase (CAT), guaiacol peroxidase (POD), ascorbate peroxidase (APX), and superoxide dismutase under Cd stress plants. Application of EDTA at the rate of 2.5 mM alone and with combination of Cd increased the antioxidant enzymes activities and reduced the electrolyte leakage and production of H2O2 and MDA. Oilseed rape (Brassica napus L.) actively accumulated Cd in roots, stems and leaves and the addition of EDTA boosted the uptake and accumulation of Cd in oil seed rape by dissociating Cd in culture media. The present results suggest that under 8 weeks Cd-induced stress, application of EDTA significantly improve plant growth, chlorophyll content, photosynthetic, gas exchange capacity, improving enzymes activities and increased the metal uptake in roots, stems and leaves of oilseed rape (Brassica napus L.) respectively.

Keywords: antioxidant enzymes, cadmium, chelator, EDTA, growth, oilseed rape

Procedia PDF Downloads 383

Authors: Yao-Hong Tsai

Abstract:

Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: unmanned aerial vehicle, object tracking, deep learning, collision avoidance

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Authors: Tuji Jemal Ahmed

Abstract:

Food security and utilization are critical aspects of ensuring the well-being and prosperity of a nation. This paper examines the current state of food security and utilization in Ethiopia, focusing on the challenges, opportunities, and strategies employed to address the issue. Ethiopia, a country in East Africa, has made significant progress in recent years to improve food security and utilization for its population. However, persistent challenges such as recurrent droughts, limited access to resources, and low agricultural productivity continue to pose obstacles to achieving sustainable food security. The paper begins by providing an overview of the concept of food security, emphasizing its multidimensional nature and the importance of access, availability, utilization, and stability. It then explores the specific factors influencing food security and utilization in Ethiopia, including natural resources, climate variability, agricultural practices, infrastructure, and socio-economic factors. Furthermore, the paper highlights the initiatives and interventions implemented by the Ethiopian government, non-governmental organizations, and international partners to enhance food security and utilization. These efforts include agricultural extension programs, irrigation projects, investments in rural infrastructure, and social safety nets to protect vulnerable populations. The study also examines the role of technology and innovation in improving food security and utilization in Ethiopia. It explores the potential of sustainable agricultural practices, such as conservation agriculture, improved seed varieties, and precision farming techniques. Additionally, it discusses the role of digital technologies in enhancing access to market information, financial services, and agricultural inputs for smallholder farmers. Finally, the paper discusses the importance of collaboration and partnerships between stakeholders, including government agencies, development organizations, research institutions, and communities, in addressing food security and utilization challenges. It emphasizes the need for integrated and holistic approaches that consider both production and consumption aspects of the food system.

Keywords: food security, utilization, Ethiopia, challenges

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Authors: Tuji Jemal Ahmed

Abstract:

Food security and utilization are critical aspects of ensuring the well-being and prosperity of a nation. This paper examines the current state of food security and utilization in Ethiopia, focusing on the challenges, opportunities, and strategies employed to address the issue. Ethiopia, a country in East Africa, has made significant progress in recent years to improve food security and utilization for its population. However, persistent challenges such as recurrent droughts, limited access to resources, and low agricultural productivity continue to pose obstacles to achieving sustainable food security. The paper begins by providing an overview of the concept of food security, emphasizing its multidimensional nature and the importance of access, availability, utilization, and stability. It then explores the specific factors influencing food security and utilization in Ethiopia, including natural resources, climate variability, agricultural practices, infrastructure, and socio-economic factors. Furthermore, the paper highlights the initiatives and interventions implemented by the Ethiopian government, non-governmental organizations, and international partners to enhance food security and utilization. These efforts include agricultural extension programs, irrigation projects, investments in rural infrastructure, and social safety nets to protect vulnerable populations. The study also examines the role of technology and innovation in improving food security and utilization in Ethiopia. It explores the potential of sustainable agricultural practices, such as conservation agriculture, improved seed varieties, and precision farming techniques. Additionally, it discusses the role of digital technologies in enhancing access to market information, financial services, and agricultural inputs for smallholder farmers. Finally, the paper discusses the importance of collaboration and partnerships between stakeholders, including government agencies, development organizations, research institutions, and communities, in addressing food security and utilization challenges. It emphasizes the need for integrated and holistic approaches that consider both production and consumption aspects of the food system.

Keywords: food security, utilization, Ethiopia, challenges

Procedia PDF Downloads 75

Authors: Samar Saadeldin Abdelmotalab Omer, Ikram Mohammed Eltayeb Elsiddig, Amna Beshir Medani Ahmed, Saad Mohammed Hussein Ayoub

Abstract:

Many herbal medicinal products are considered as potential hypocholesterolemic agents with encouraging safety profiles, however, only a limited amount of clinical research exists to support their efficacy. The present study was designed to compare the antihypercholesterolaemic and antioxidant activities of the crude ethanolic extracts of Citrus reticulata peel, Zingiber officinale rhizome, and Sesamum indicum seeds. Forty-five rats were used throughout the experiment, which were divided into nine groups, five rats in each as follows; normal control group (normal rats fed with standard normal diet), rats fed hypercholesterolemic diet consisting of 1% cholesterol and 10% saturated animal fat, which were further divided into eight groups; hypercholesterolemic control group (rats only fed hypercholesterolemic diet), groups 3,4,5,6,7, and 8 were given Citrus reticulata, Zingiber officinale, and Sesamum indicum ethanolic extracts at doses of (250mg/kg and 500mg/kg, respectively) orally; and group 9 rats were given atorvastatin (0.18mg/kg) orally as a reference antihypercholesterolaemic drug. Blood samples were obtained four weeks following treatment from the retro-orbital venous plexus after fasting overnight from all groups and the lipid profile (serum total cholesterol (TC), high-density-lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), and triglycerides levels) was measured and the risk ratio (TC/HDL-C) was assessed. The antioxidant activity of the three plant extracts was determined using DPPH free-radical assay. Results of in vivo and in vitro antihypercholesterolaemic and antioxidant assay, respectively, revealed that the three extracts possess comparable antioxidant and anti-hypercholesterolaemic activities.

Keywords: anti hypercholesterolemic effects, antioxidant activity, HDL, LDL, TC, TGs, citrus reticulata, sesamum indicum, zingiber officinale

Procedia PDF Downloads 449

Authors: Eleni Stefanidou, Nikolaos Katsenios, Ioanna Karamichali, Aspasia Efthimiadou, Panagiotis Madesis

Abstract:

The excessive use of pesticides and fertilizers has significant environmental and human health-related negative effects. In the frame of the development of sustainable agriculture practices, especially in the context of extreme environmental changes (climate change), it is important to develop alternative practices to increase productivity and biotic and abiotic stress tolerance. Beneficial bacteria, such as symbiotic bacteria in legumes (rhizobia) and symbiotic or free-living Plant Growth Promoting Rhizobacteria (PGPR), which could act as "plant probiotics", can promote plant growth and significantly increase the resistance of crops under adverse environmental conditions. In this study, we explored the symbiotic relationships between Faba bean (Vicia faba L.) cultivars with different PGPR bacteria, aiming to identify the possible influence on yield and biotic-abiotic phytoprotection benefits. Transcriptomic analysis of root and whole plant samples was executed for two Vicia faba L. cultivars (Polikarpi and Solon) treated with selected PGPR bacteria (6 treatments: B. subtilis + Rhizobium-mixture, A. chroococcum + Rhizobium-mixture, B. subtilis, A. chroococcum and Rhizobium-mixture). Preliminary results indicate a significant yield (Seed weight and Total number of pods) increase in both varieties, ranging around 25%, in comparison to the control, especially for the Solon cultivar. The increase was observed for all treatments, with the B. subtilis + Rhizobium-mixture treatment being the highest performing. The correlation of the physiological and morphological data with the transcriptome analysis revealed molecular mechanisms and molecular targets underlying the observed yield increase, opening perspectives for the use of nitrogen-fixing bacteria as a natural, more ecological enhancer of legume crop productivity.

Keywords: plant probiotics, PGPR, legumes, sustainable agriculture

Procedia PDF Downloads 65