Search results for: millimetre-wave signal generation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4886

Search results for: millimetre-wave signal generation

3986 Enhancing Large Language Models' Data Analysis Capability with Planning-and-Execution and Code Generation Agents: A Use Case for Southeast Asia Real Estate Market Analytics

Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

Abstract:

Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

Procedia PDF Downloads 76
3985 [Keynote Talk]: New Generations and Employment: An Exploratory Study about Tensions between the Psycho-Social Characteristics of the Generation Z and Expectations and Actions of Organizational Structures Related with Employment (CABA, 2016)

Authors: Esteban Maioli

Abstract:

Generational studies have an important research tradition in social and human sciences. On the one hand, the speed of social change in the context of globalization imposes the need to research the transformations are identified both the subjectivity of the agents involved and its inclusion in the institutional matrix, specifically employment. Generation Z, (generally considered as the population group whose birth occurs after 1995) have unique psycho-social characteristics. Gen Z is characterized by a different set of values, beliefs, attitudes and ambitions that impact in their concrete action in organizational structures. On the other hand, managers often have to deal with generational differences in the workplace. Organizations have members who belong to different generations; they had never before faced the challenge of having such a diverse group of members. The members of each historical generation are characterized by a different set of values, beliefs, attitudes and ambitions that are manifest in their concrete action in organizational structures. Gen Z it’s the only one who can fully be considered "global," while its members were born in the consolidated context of globalization. Some salient features of the Generation Z can be summarized as follows. They’re the first fully born into a digital world. Social networks and technology are integrated into their lives. They are concerned about the challenges of the modern world (poverty, inequality, climate change, among others). They are self-expressive, more liberal and open to change. They often bore easily, with short attention spans. They do not like routine tasks. They want to achieve a good life-work balance, and they are interested in a flexible work environment, as opposed to traditional work schedule. They are critical thinkers, who come with innovative and creative ideas to help. Research design considered methodological triangulation. Data was collected with two techniques: a self-administered survey with multiple choice questions and attitudinal scales applied over a non-probabilistic sample by reasoned decision. According to the multi-method strategy, also it was conducted in-depth interviews. Organizations constantly face new challenges. One of the biggest ones is to learn to manage a multi-generational scope of work. While Gen Z has not yet been fully incorporated (expected to do so in five years or so), many organizations have already begun to implement a series of changes in its recruitment and development. The main obstacle to retaining young talent is the gap between the expectations of iGen applicants and what companies offer. Members of the iGen expect not only a good salary and job stability but also a clear career plan. Generation Z needs to have immediate feedback on their tasks. However, many organizations have yet to improve both motivation and monitoring practices. It is essential for companies to take a review of organizational practices anchored in the culture of the organization.

Keywords: employment, expectations, generation Z, organizational culture, organizations, psycho-social characteristics

Procedia PDF Downloads 198
3984 Modeling and Power Control of DFIG Used in Wind Energy System

Authors: Nadia Ben Si Ali, Nadia Benalia, Nora Zerzouri

Abstract:

Wind energy generation has attracted great interests in recent years. Doubly Fed Induction Generator (DFIG) for wind turbines are largely deployed because variable-speed wind turbines have many advantages over fixed-speed generation such as increased energy capture, operation at maximum power point, improved efficiency, and power quality. This paper presents the operation and vector control of a Doubly-fed Induction Generator (DFIG) system where the stator is connected directly to a stiff grid and the rotor is connected to the grid through bidirectional back-to-back AC-DC-AC converter. The basic operational characteristics, mathematical model of the aerodynamic system and vector control technique which is used to obtain decoupled control of powers are investigated using the software Mathlab/Simulink.

Keywords: wind turbine, Doubly Fed Induction Generator, wind speed controller, power system stability

Procedia PDF Downloads 369
3983 The High Precision of Magnetic Detection with Microwave Modulation in Solid Spin Assembly of NV Centres in Diamond

Authors: Zongmin Ma, Shaowen Zhang, Yueping Fu, Jun Tang, Yunbo Shi, Jun Liu

Abstract:

Solid-state quantum sensors are attracting wide interest because of their high sensitivity at room temperature. In particular, spin properties of nitrogen–vacancy (NV) color centres in diamond make them outstanding sensors of magnetic fields, electric fields and temperature under ambient conditions. Much of the work on NV magnetic sensing has been done so as to achieve the smallest volume, high sensitivity of NV ensemble-based magnetometry using micro-cavity, light-trapping diamond waveguide (LTDW), nano-cantilevers combined with MEMS (Micro-Electronic-Mechanical System) techniques. Recently, frequency-modulated microwaves with continuous optical excitation method have been proposed to achieve high sensitivity of 6 μT/√Hz using individual NV centres at nanoscale. In this research, we built-up an experiment to measure static magnetic field through continuous wave optical excitation with frequency-modulated microwaves method under continuous illumination with green pump light at 532 nm, and bulk diamond sample with a high density of NV centers (1 ppm). The output of the confocal microscopy was collected by an objective (NA = 0.7) and detected by a high sensitivity photodetector. We design uniform and efficient excitation of the micro strip antenna, which is coupled well with the spin ensembles at 2.87 GHz for zero-field splitting of the NV centers. Output of the PD signal was sent to an LIA (Lock-In Amplifier) modulated signal, generated by the microwave source by IQ mixer. The detected signal is received by the photodetector, and the reference signal enters the lock-in amplifier to realize the open-loop detection of the NV atomic magnetometer. We can plot ODMR spectra under continuous-wave (CW) microwave. Due to the high sensitivity of the lock-in amplifier, the minimum detectable value of the voltage can be measured, and the minimum detectable frequency can be made by the minimum and slope of the voltage. The magnetic field sensitivity can be derived from η = δB√T corresponds to a 10 nT minimum detectable shift in the magnetic field. Further, frequency analysis of the noise in the system indicates that at 10Hz the sensitivity less than 10 nT/√Hz.

Keywords: nitrogen-vacancy (NV) centers, frequency-modulated microwaves, magnetic field sensitivity, noise density

Procedia PDF Downloads 432
3982 Simulation of Wind Solar Hybrid Power Generation for Pumping Station

Authors: Masoud Taghavi, Gholamreza Salehi, Ali Lohrasbi Nichkoohi

Abstract:

Despite the growing use of renewable energies in different fields of application of this technology in the field of water supply has been less attention. Photovoltaic and wind hybrid system is that new topics in renewable energy, including photovoltaic arrays, wind turbines, a set of batteries as a storage system and a diesel generator as a backup system is. In this investigation, first climate data including average wind speed and solar radiation at any time during the year, data collection and analysis are performed in the energy. The wind turbines in four models, photovoltaic panels at the 6 position of relative power, batteries and diesel generator capacity in seven states in the two models are combined hours of operation with renewables, diesel generator and battery bank check and a hybrid system of solar power generation-wind, which is optimized conditions, are presented.

Keywords: renewable energy, wind and solar energy, hybrid systems, cloning station

Procedia PDF Downloads 391
3981 Pareto System of Optimal Placement and Sizing of Distributed Generation in Radial Distribution Networks Using Particle Swarm Optimization

Authors: Sani M. Lawal, Idris Musa, Aliyu D. Usman

Abstract:

The Pareto approach of optimal solutions in a search space that evolved in multi-objective optimization problems is adopted in this paper, which stands for a set of solutions in the search space. This paper aims at presenting an optimal placement of Distributed Generation (DG) in radial distribution networks with an optimal size for minimization of power loss and voltage deviation as well as maximizing voltage profile of the networks. And these problems are formulated using particle swarm optimization (PSO) as a constraint nonlinear optimization problem with both locations and sizes of DG being continuous. The objective functions adopted are the total active power loss function and voltage deviation function. The multiple nature of the problem, made it necessary to form a multi-objective function in search of the solution that consists of both the DG location and size. The proposed PSO algorithm is used to determine optimal placement and size of DG in a distribution network. The output indicates that PSO algorithm technique shows an edge over other types of search methods due to its effectiveness and computational efficiency. The proposed method is tested on the standard IEEE 34-bus and validated with 33-bus test systems distribution networks. Results indicate that the sizing and location of DG are system dependent and should be optimally selected before installing the distributed generators in the system and also an improvement in the voltage profile and power loss reduction have been achieved.

Keywords: distributed generation, pareto, particle swarm optimization, power loss, voltage deviation

Procedia PDF Downloads 358
3980 Systematic NIR of Internal Disorder and Quality Detection of Apple Fruit

Authors: Eid Alharbi, Yaser Miaji, Saeed Alzahrani

Abstract:

The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic convener belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300 nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950 nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950 nm region the online sorting system was constructed.

Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology

Procedia PDF Downloads 492
3979 The Impact of an Ionic Liquid on Hydrogen Generation from a Redox Process Involving Magnesium and Acidic Oilfield Water

Authors: Mohamed A. Deyab, Ahmed E. Awadallah

Abstract:

Under various conditions, we present a promising method for producing pure hydrogen energy from the electrochemical reaction of Mg metal in waste oilfield water (WOW). Mg metal and WOW are primarily consumed in this process. The results show that the hydrogen gas output is highly dependent on temperature and solution pH. The best conditions for hydrogen production were found to be a low pH (2.5) and a high temperature (338 K). For the first time, the Allyl methylimidazolium bis-trifluoromethyl sulfonyl imide) (IL) ionic liquid is used to regulate the rate of hydrogen generation. It has been confirmed that increasing the solution temperature and decreasing the solution pH accelerates Mg dissolution and produces more hydrogen per unit of time. The adsorption of IL on the active sites of the Mg surface is unrestricted by mixing physical and chemical orientation. Inspections using scanning electron microscopy (SEM), energy dispersive X-ray (EDX), and FT-IR spectroscopy were used to identify and characterise surface corrosion of Mg in WOW. This process is also completely safe and can create energy on demand.

Keywords: hydrogen production, Mg, wastewater, ionic liquid

Procedia PDF Downloads 148
3978 Equilibrium Modeling of a Two Stage Downdraft Gasifier Using Different Gasification Fluids

Authors: F. R. M. Nascimento, E. E. S. Lora, J. C. E. Palácio

Abstract:

A mathematical model to investigate the performance of a two stage fixed bed downdraft gasifier operating with air, steam and oxygen mixtures as the gasifying fluid has been developed. The various conditions of mixtures for a double stage fluid entry, have been performed. The model has been validated through a series of experimental tests performed by NEST – The Excellence Group in Thermal and Distributed Generation of the Federal University of Itajubá. Influence of mixtures are analyzed through the Steam to Biomass (SB), Equivalence Ratio (ER) and the Oxygen Concentration (OP) parameters in order to predict the best operating conditions to obtain adequate output gas quality, once is a key parameter for subsequent gas processing in the synthesis of biofuels, heat and electricity generation. Results show that there is an optimal combination in the steam and oxygen content of the gasifying fluid which allows the user find the best conditions to design and operate the equipment according to the desired application.

Keywords: air, equilibrium, downdraft, fixed bed gasification, mathematical modeling, mixtures, oxygen steam

Procedia PDF Downloads 473
3977 RBF Neural Network Based Adaptive Robust Control for Bounded Position/Force Control of Bilateral Teleoperation Arms

Authors: Henni Mansour Abdelwaheb

Abstract:

This study discusses the design of a bounded position/force feedback controller developed to ensure position and force tracking for bilateral teleoperation arms operating with variable delay, and actuator saturation. Also, an adaptive robust Radial Basis Function (RBF) neural network is used to estimate the environment torque. The parameters of the environment torque are then sent from the slave site to the master site as a non-power signal to avoid passivity problems. Moreover, a nonlinear function is applied to each controller term as a smooth saturation function, providing a bounded control signal and preserving the system’s actuators. Lastly, the Lyapunov approach demonstrates the global stability of the controlled system, and numerical experiment results further confirm the validity of the presented strategy.

Keywords: teleoperation manipulators system, time-varying delay, actuator saturation, adaptive robust rbf neural network approximation, uncertainties

Procedia PDF Downloads 69
3976 Improved Wearable Monitoring and Treatment System for Parkinson’s Disease

Authors: Bulcha Belay Etana, Benny Malengier, Janarthanan Krishnamoorthy, Timothy Kwa, Lieva VanLangenhove

Abstract:

Electromyography measures the electrical activity of muscles using surface electrodes or needle electrodes to monitor various disease conditions. Recent developments in the signal acquisition of electromyograms using textile electrodes facilitate wearable devices, enabling patients to monitor and control their health status outside of healthcare facilities. Here, we have developed and tested wearable textile electrodes to acquire electromyography signals from patients suffering from Parkinson’s disease and incorporated a feedback-control system to relieve muscle cramping through thermal stimulus. In brief, the textile electrodes made of stainless steel was knitted into a textile fabric as a sleeve, and their electrical characteristic, such as signal-to-noise ratio, was compared with traditional electrodes. To relieve muscle cramping, a heating element made of stainless-steel conductive yarn sewn onto cotton fabric, coupled with a vibration system, was developed. The system integrated a microcontroller and a Myoware muscle sensor to activate the heating element as well as the vibration motor when cramping occurs, and at the same time, the element gets deactivated when the muscle cramping subsides. An optimum therapeutic temperature of 35.5 °C is regulated by continuous temperature monitoring to deactivate the heating system when this threshold value is reached. The textile electrode exhibited a signal-to-noise ratio of 6.38dB, comparable to that of the traditional electrode’s value of 7.05 dB. For a given 9 V power supply, the rise time was about 6 minutes for the developed heating element to reach an optimum temperature.

Keywords: smart textile system, wearable electronic textile, electromyography, heating textile, vibration therapy, Parkinson’s disease

Procedia PDF Downloads 99
3975 Methodology for Temporary Analysis of Production and Logistic Systems on the Basis of Distance Data

Authors: M. Mueller, M. Kuehn, M. Voelker

Abstract:

In small and medium-sized enterprises (SMEs), the challenge is to create a well-grounded and reliable basis for process analysis, optimization and planning due to a lack of data. SMEs have limited access to methods with which they can effectively and efficiently analyse processes and identify cause-and-effect relationships in order to generate the necessary database and derive optimization potential from it. The implementation of digitalization within the framework of Industry 4.0 thus becomes a particular necessity for SMEs. For these reasons, the abstract presents an analysis methodology that is subject to the objective of developing an SME-appropriate methodology for efficient, temporarily feasible data collection and evaluation in flexible production and logistics systems as a basis for process analysis and optimization. The overall methodology focuses on retrospective, event-based tracing and analysis of material flow objects. The technological basis consists of Bluetooth low energy (BLE)-based transmitters, so-called beacons, and smart mobile devices (SMD), e.g. smartphones as receivers, between which distance data can be measured and derived motion profiles. The distance is determined using the Received Signal Strength Indicator (RSSI), which is a measure of signal field strength between transmitter and receiver. The focus is the development of a software-based methodology for interpretation of relative movements of transmitters and receivers based on distance data. The main research is on selection and implementation of pattern recognition methods for automatic process recognition as well as methods for the visualization of relative distance data. Due to an existing categorization of the database regarding process types, classification methods (e.g. Support Vector Machine) from the field of supervised learning are used. The necessary data quality requires selection of suitable methods as well as filters for smoothing occurring signal variations of the RSSI, the integration of methods for determination of correction factors depending on possible signal interference sources (columns, pallets) as well as the configuration of the used technology. The parameter settings on which respective algorithms are based have a further significant influence on result quality of the classification methods, correction models and methods for visualizing the position profiles used. The accuracy of classification algorithms can be improved up to 30% by selected parameter variation; this has already been proven in studies. Similar potentials can be observed with parameter variation of methods and filters for signal smoothing. Thus, there is increased interest in obtaining detailed results on the influence of parameter and factor combinations on data quality in this area. The overall methodology is realized with a modular software architecture consisting of independently modules for data acquisition, data preparation and data storage. The demonstrator for initialization and data acquisition is available as mobile Java-based application. The data preparation, including methods for signal smoothing, are Python-based with the possibility to vary parameter settings and to store them in the database (SQLite). The evaluation is divided into two separate software modules with database connection: the achievement of an automated assignment of defined process classes to distance data using selected classification algorithms and the visualization as well as reporting in terms of a graphical user interface (GUI).

Keywords: event-based tracing, machine learning, process classification, parameter settings, RSSI, signal smoothing

Procedia PDF Downloads 123
3974 Digital Signal Processor Implementation of a Novel Sinusoidal Pulse Width Modulation Algorithm Algorithm for a Reduced Delta Inverter

Authors: Asma Ben Rhouma, Mahmoud Hamouda

Abstract:

The delta inverter is considered as the reduced three-phase dc/ac converter topology. It contains only three two-quadrant power switches compared to six in the conventional one. This reduced power conversion topology is widely considered in many industrial applications, such as electric traction and large photovoltaic systems. This paper is focused on a new sinusoidal pulse width modulation algorithm (SPWM) developed for the delta inverter. As an unconventional inverter’s structure, irregular modulating functions waveforms of the SPWM switching technique are generated. The performances of the proposed SPWM technique was proven through computer simulations carried out on a delta inverter feeding a three-phase RL load. Digital Signal Processor (DSP) implementation of the novel SPWM algorithm have been realized on a laboratory prototype of the delta inverter feeding an RL load and a squirrel cage induction motor. Experimental results have highlighted its high performances under the proposed SPWM method.

Keywords: delta inverter, SPWM, simulation, DSP implementation

Procedia PDF Downloads 155
3973 A Teaching Learning Based Optimization for Optimal Design of a Hybrid Energy System

Authors: Ahmad Rouhani, Masood Jabbari, Sima Honarmand

Abstract:

This paper introduces a method to optimal design of a hybrid Wind/Photovoltaic/Fuel cell generation system for a typical domestic load that is not located near the electricity grid. In this configuration the combination of a battery, an electrolyser, and a hydrogen storage tank are used as the energy storage system. The aim of this design is minimization of overall cost of generation scheme over 20 years of operation. The Matlab/Simulink is applied for choosing the appropriate structure and the optimization of system sizing. A teaching learning based optimization is used to optimize the cost function. An overall power management strategy is designed for the proposed system to manage power flows among the different energy sources and the storage unit in the system. The results have been analyzed in terms of technics and economics. The simulation results indicate that the proposed hybrid system would be a feasible solution for stand-alone applications at remote locations.

Keywords: hybrid energy system, optimum sizing, power management, TLBO

Procedia PDF Downloads 568
3972 Enabling Oral Communication and Accelerating Recovery: The Creation of a Novel Low-Cost Electroencephalography-Based Brain-Computer Interface for the Differently Abled

Authors: Rishabh Ambavanekar

Abstract:

Expressive Aphasia (EA) is an oral disability, common among stroke victims, in which the Broca’s area of the brain is damaged, interfering with verbal communication abilities. EA currently has no technological solutions and its only current viable solutions are inefficient or only available to the affluent. This prompts the need for an affordable, innovative solution to facilitate recovery and assist in speech generation. This project proposes a novel concept: using a wearable low-cost electroencephalography (EEG) device-based brain-computer interface (BCI) to translate a user’s inner dialogue into words. A low-cost EEG device was developed and found to be 10 to 100 times less expensive than any current EEG device on the market. As part of the BCI, a machine learning (ML) model was developed and trained using the EEG data. Two stages of testing were conducted to analyze the effectiveness of the device: a proof-of-concept and a final solution test. The proof-of-concept test demonstrated an average accuracy of above 90% and the final solution test demonstrated an average accuracy of above 75%. These two successful tests were used as a basis to demonstrate the viability of BCI research in developing lower-cost verbal communication devices. Additionally, the device proved to not only enable users to verbally communicate but has the potential to also assist in accelerated recovery from the disorder.

Keywords: neurotechnology, brain-computer interface, neuroscience, human-machine interface, BCI, HMI, aphasia, verbal disability, stroke, low-cost, machine learning, ML, image recognition, EEG, signal analysis

Procedia PDF Downloads 115
3971 Enhancement of Genetic Diversity through Cross Breeding of Two Catfish (Heteropneustes fossilis and Clarias batrachus) in Bangladesh

Authors: M. F. Miah, A. Chakrabarty

Abstract:

Two popular and highly valued fish, Stinging catfish (Heteropneustes fossilis) and Asian catfish (Clarias batrachus) are considered for observing genetic enhancement. Cross breeding was performed considering wild and farmed fish through inducing agent. Five RAPD markers were used to assess genetic diversity among parents and offspring of these two catfish for evaluating genetic enhancement in F1 generation. Considering different genetic data such as banding pattern of DNA, polymorphic loci, polymorphic information content (PIC), inter individual pair wise similarity, Nei genetic similarity, genetic distance, phylogenetic relationships, allele frequency, genotype frequency, intra locus gene diversity and average gene diversity of parents and offspring of these two fish were analyzed and finally in both cases higher genetic diversity was found in F1 generation than the parents.

Keywords: Heteropneustes fossilis, Clarias batrachus, cross breeding, genetic enhancement

Procedia PDF Downloads 242
3970 New NIR System for Detecting the Internal Disorder and Quality of Apple Fruit

Authors: Eid Alharbi, Yaser Miaji

Abstract:

The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.

Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology

Procedia PDF Downloads 395
3969 Novel NIR System for Detection of Internal Disorder and Quality of Apple Fruit

Authors: Eid Alharbi, Yaser Miaji

Abstract:

The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.

Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology

Procedia PDF Downloads 384
3968 The Experiences of First-Generation Afro/Black Caribbean-American Women Navigating Sexual Pleasure and Their Bicultural Identity as a Result of Immigration

Authors: Jessie André

Abstract:

In the past 10 years, more studies have begun exploring the psychological impact of those who have been subjected to and have adopted two different cultures. Currently, there is no existing literature regarding how individuals with a bicultural identity navigate their often-conflicting cultures on topics such as sexual pleasure and sexual scripts. The purpose of this study was to explore how first-generation Afro/Black Caribbean-American women navigate their multiple cultural identities with regards to sexual pleasure and sexual scripts. This study contains an exploration of participants self-described challenges, attitudes, and beliefs associated to how they navigate and experience their sexuality. This research study uses an explanatory, qualitative method design with semi structured interviews to answer the primary and secondary research question. Research findings indicate that the later the age of immigration, the stronger their ties were to the culture from their country of origin, which affected their self-assessments of sexual desirability and sexual self-esteem. Findings also suggest that even though women who immigrated at a younger age had higher rates of difficulty navigating and identifying with their adopted culture’s sexual mores. These women also reported lower ratings of comfort voicing sexual desires and concerns to their partner and had lower self-ratings of feeling connected to their cultural identity. These participants had challenges utilizing the dual and conflicting sexual mores and rules they received from U.S. society and their country of origin, resulting in less pleasurable sexual experiences. Whereas women who immigrated at an older age reported having more pleasurable sexual experiences.

Keywords: bicultural identity, sexual pleasure, first-generation immigrants, afro/black caribbean-American

Procedia PDF Downloads 230
3967 Reburning Characteristics of Biomass Syngas in a Pilot Scale Heavy Oil Furnace

Authors: Sang Heon Han, Daejun Chang, Won Yang

Abstract:

NOx reduction characteristics of syngas fuel were numerically investigated for the 2MW pilot scale heavy oil furnace of KITECH (Korea Institute of Industrial Technology). The secondary fuel and syngas was fed into the furnace with two purposes- partial replacement of main fuel and reburning of NOx. Some portion of syngas was fed into the flame zone to partially replace the heavy oil, while the other portion was fed into the furnace downstream to reduce NOx generation. The numerical prediction was verified by comparing it with the experimental results. Syngas of KITECH’s experiment, assumed to be produced from biomass, had very low calorific value and contained 3% hydrocarbon. This study investigated the precise behavior of NOx generation and NOx reduction as well as thermo-fluidic characteristics inside the furnace, which was unavailable with experiment. In addition to 3% hydrocarbon syngas, 5%, and 7% hydrocarbon syngas were numerically tested as reburning fuels to analyze the effect of hydrocarbon proportion to NOx reduction. The prediction showed that the 3% hydrocarbon syngas is as much effective as 7% hydrocarbon syngas in reducing NOx.

Keywords: syngas, reburning, heavy oil, furnace

Procedia PDF Downloads 432
3966 A Detail Analysis of Solar Energy Potential of Provinces of Pakistan for Power Generation

Authors: M. Akhlaque Ahmed, Maliha Afshan

Abstract:

Solar energy potential of Capital city Islamabad and five major cities Peshawar, Lahore, Multan, Quetta and Karachi have been analyzed by using sun shine hour data of the area. Global and diffused solar radiation on horizontal surfaces has been assessed to see the feasibility of solar energy utilization. The result obtained shows 70% direct and 30% diffuse solar radiation for five cities throughout the year except Karachi which shows large variation in direct and diffuse component of solar radiation 57% direct and 43% diffuse in the month of July and August. The cloudiness index were also calculated which lies between 60 to 70% for all the cities except for Karachi which shows 37% clear sky in monsoon month July and August. All the cities show high solar potential throughout the year except Karachi which shows low solar potential during July and August months.

Keywords: global and diffuse solar radiations, Pakistan, power generation, solar potential, sunshine hour

Procedia PDF Downloads 178
3965 Integrating Wearable-Textiles Sensors and IoT for Continuous Electromyography Monitoring

Authors: Bulcha Belay Etana, Benny Malengier, Debelo Oljira, Janarthanan Krishnamoorthy, Lieva Vanlangenhove

Abstract:

Electromyography (EMG) is a technique used to measure the electrical activity of muscles. EMG can be used to assess muscle function in a variety of settings, including clinical, research, and sports medicine. The aim of this study was to develop a wearable textile sensor for EMG monitoring. The sensor was designed to be soft, stretchable, and washable, making it suitable for long-term use. The sensor was fabricated using a conductive thread material that was embroidered onto a fabric substrate. The sensor was then connected to a microcontroller unit (MCU) and a Wi-Fi-enabled module. The MCU was programmed to acquire the EMG signal and transmit it wirelessly to the Wi-Fi-enabled module. The Wi-Fi-enabled module then sent the signal to a server, where it could be accessed by a computer or smartphone. The sensor was able to successfully acquire and transmit EMG signals from a variety of muscles. The signal quality was comparable to that of commercial EMG sensors. The development of this sensor has the potential to improve the way EMG is used in a variety of settings. The sensor is soft, stretchable, and washable, making it suitable for long-term use. This makes it ideal for use in clinical settings, where patients may need to wear the sensor for extended periods of time. The sensor is also small and lightweight, making it ideal for use in sports medicine and research settings. The data for this study was collected from a group of healthy volunteers. The volunteers were asked to perform a series of muscle contractions while the EMG signal was recorded. The data was then analyzed to assess the performance of the sensor. The EMG signals were analyzed using a variety of methods, including time-domain analysis and frequency-domain analysis. The time-domain analysis was used to extract features such as the root mean square (RMS) and average rectified value (ARV). The frequency-domain analysis was used to extract features such as the power spectrum. The question addressed by this study was whether a wearable textile sensor could be developed that is soft, stretchable, and washable and that can successfully acquire and transmit EMG signals. The results of this study demonstrate that a wearable textile sensor can be developed that meets the requirements of being soft, stretchable, washable, and capable of acquiring and transmitting EMG signals. This sensor has the potential to improve the way EMG is used in a variety of settings.

Keywords: EMG, electrode position, smart wearable, textile sensor, IoT, IoT-integrated textile sensor

Procedia PDF Downloads 64
3964 Changing Roles and Skills of Urban Planners in the Turkish Planning System

Authors: Fatih Eren

Abstract:

This research aims to find an answer to the question of which knowledge and skills do the Turkish urban planners need in their business practice. Understanding change in cities, making a prediction, making an urban decision and putting it into practice, working together with actors from different organizations from various academic disciplines, persuading people to accept something and developing good personal and professional relationships have become very complex and difficult in today’s world. The truth is that urban planners work in many institutions under various positions which are not similar to each other by field of activity and all planners are forced to develop some knowledge and skills for success in their business in Turkey. This study targets to explore what urban planners do in the global information age. The study is the product of a comprehensive nation-wide research. In-depth interviews were conducted with 174 experienced urban planners, who work in different public institutions and private companies under varied positions in the Turkish Planning System, to find out knowledge and skills needed by next-generation urban planners. The main characteristics of next-generation urban planners are defined; skills that planners needed today are explored in this paper. Findings show that the positivist (traditional) planning approach has given place to anti-positivist planning approaches in the Turkish Planning System so next-generation urban planners who seek success and want to carve out a niche for themselves in business life have to equip themselves with innovative skills. The result section also includes useful and instructive findings for planners about what is the meaning of being an urban planner and what is the ideal content and context of planning education at universities in the global age.

Keywords: global information age, Turkish Planning System, the institutional approach, urban planners, roles, skills, values

Procedia PDF Downloads 276
3963 The Evaluation of Electricity Generation and Consumption from Solar Generator: A Case Study at Rajabhat Suan Sunandha’s Learning Center in Samutsongkram

Authors: Chonmapat Torasa

Abstract:

This paper presents the performance of electricity generation and consumption from solar generator installed at Rajabhat Suan Sunandha’s learning center in Samutsongkram. The result from the experiment showed that solar cell began to work and distribute the current into the system when the solar energy intensity was 340 w/m2, starting from 8:00 am to 4:00 pm (duration of 8 hours). The highest intensity read during the experiment was 1,051.64w/m2. The solar power was 38.74kWh/day. The electromotive force from solar cell averagely was 93.6V. However, when connecting solar cell with the battery charge controller system, the voltage was dropped to 69.07V. After evaluating the power distribution ability and electricity load of tested solar cell, the result showed that it could generate power to 11 units of 36-wattfluorescent lamp bulbs, which was altogether 396W. In the meantime, the AC to DC power converter generated 3.55A to the load, and gave 781VA.

Keywords: solar cell, solar-cell power generating system, computer, systems engineering

Procedia PDF Downloads 315
3962 Economic Activities Associated with Extraction of Riverbed Materials in the Tinau River, Nepal

Authors: Khet Raj Dahal, Dhruva Dhital, Chhatra Mani Sharma

Abstract:

A study was conducted during 2012 to 2013 in the selected reach of Tinau River, Nepal. The main objective of the study was to quantify employment and income generation from the extraction of construction materials from the river. A 10 km stretch of the river was selected for the study. Sample survey with a semi-structured questionnaire and field observation were the main tools used during field investigation. Extraction of riverbed materials from the banks, beds and floodplain areas of the river has provided many kinds of job opportunities for the people living in the vicinity of the river. It has also generated an adequate amount of revenues. The collected revenue has been invested for many kinds of social and infrastructures development for years. Though extraction of riverbed materials is beneficial for income and employment generation, it has also negative environmental impacts in and around the river. Furthermore, the study concluded that river bed extraction should be continued with special monitoring and evaluation in the areas where there is still room for extraction.

Keywords: extraction, crusher plants, economic activities, Tinau River

Procedia PDF Downloads 688
3961 Genetic Algorithms for Feature Generation in the Context of Audio Classification

Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

Abstract:

Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: feature generation, feature learning, genetic algorithm, music information retrieval

Procedia PDF Downloads 427
3960 Technical and Economic Environment in the Polish Power System as the Basis for Distributed Generation and Renewable Energy Sources Development

Authors: Pawel Sowa, Joachim Bargiel, Bogdan Mol, Katarzyna Luszcz

Abstract:

The article raises the issue of the development of local renewable energy sources and the production of distributed energy in context of improving the reliability of the Polish Power System and the beneficial impact on local and national energy security. The paper refers to the current problems of local governments in the process of investment in the area of distributed energy projects, and discusses the issues of the future role and cooperation within the local power plants and distributed energy. Attention is paid to the local communities the chance to raise their own resources and management of energy fuels (biomass, wind, gas mining) and improving the local energy balance. The material presented takes the issue of the development of the energy potential of municipalities and future cooperation with professional energy. As an example, practical solutions used in one of the communes in Silesia.

Keywords: distributed generation, mini centers energy, renewable energy sources, reliability of supply of rural commune

Procedia PDF Downloads 594
3959 Kuwait Environmental Remediation Program: Waste Management Data Analytics for Planning and Optimization of Waste Collection

Authors: Aisha Al-Baroud

Abstract:

The United Nations Compensation Commission (UNCC), Kuwait National Focal Point (KNFP) and Kuwait Oil Company (KOC) cooperated in a joint project to undertake comprehensive and collaborative efforts to remediate 26 million m3 of crude oil contaminated soil that had resulted from the Gulf War in 1990/1991. These efforts are referred to as the Kuwait Environmental Remediation Program (KERP). KOC has developed a Total Remediation Solution (TRS) for KERP, which will guide the Remediation projects, comprises of alternative remedial solutions with treatment techniques inclusive of limited landfills for non-treatable soil materials disposal, and relies on treating certain ranges of Total Petroleum Hydrocarbon (TPH) contamination with the most appropriate remediation techniques. The KERP Remediation projects will be implemented within the KOC’s oilfields in North and South East Kuwait. The objectives of this remediation project is to clear land for field development and treat all the oil contaminated features (dry oil lakes, wet oil lakes, and oil contaminated piles) through TRS plan to optimize the treatment processes and minimize the volume of contaminated materials to be placed into landfills. The treatment strategy will comprise of Excavation and Transportation (E&T) of oil contaminated soils from contaminated land to remote treatment areas and to use appropriate remediation technologies or a combination of treatment technologies to achieve remediation target criteria (RTC). KOC has awarded five mega projects to achieve the same and is currently in the execution phase. As a part of the company’s commitment to environment and for the fulfillment of the mandatory HSSEMS procedures, all the Remediation contractors needs to report waste generation data from the various project activities on a monthly basis. Data on waste generation is collected in order to implement cost-efficient and sustainable waste management operations. Data analytics approaches can be built on the top of the data to produce more detailed, and in-time waste generation information for the basis of waste management and collection. The results obtained highlight the potential of advanced data analytic approaches in producing more detailed waste generation information for planning and optimization of waste collection and recycling.

Keywords: waste, tencnolgies, KERP, data, soil

Procedia PDF Downloads 106
3958 Modelling and Simulation of Bioethanol Production from Food Waste Using CHEMCAD Software

Authors: Kgomotso Matobole, Noluzuko Monakali, Hilary Rutto, Tumisang Seodigeng

Abstract:

On a global scale, there is an alarming generation of food waste. Food waste is generated across the food supply chain. Worldwide urbanization, as well as global economic growth, have contributed to this amount of food waste the environment is receiving. Food waste normally ends on illegal dumping sites when not properly disposed, or disposed to landfills. This results in environmental pollution due to inadequate waste management practices. Food waste is rich in organic matter and highly biodegradable; hence, it can be utilized for the production of bioethanol, a type of biofuel. In so doing, alternative energy will be created, and the volumes of food waste will be reduced in the process. This results in food waste being seen as a precious commodity in energy generation instead of a pollutant. The main aim of the project was to simulate a biorefinery, using a software called CHEMCAD 7.12. The resulting purity of the ethanol from the simulation was 98.9%, with the feed ratio of 1: 2 for food waste and water. This was achieved by integrating necessary unit operations and optimisation of their operating conditions.

Keywords: fermentation, bioethanol, food waste, hydrolysis, simulation, modelling

Procedia PDF Downloads 352
3957 A Multi-Population DE with Adaptive Mutation and Local Search for Global Optimization

Authors: Zhoucheng Bao, Haiyan Zhu, Tingting Pang, Zuling Wang

Abstract:

This paper proposes a multi-population DE with adaptive mutation and local search for global optimization, named AMMADE. In order to better coordinate the cooperation between the populations and the rational use of resources. In AMMADE, the population is divided based on the Euclidean distance sorting method at each generation to appropriately coordinate the cooperation between subpopulations and the usage of resources, such that the best-performed subpopulation will get more computing resources in the next generation. Further, an adaptive local search strategy is employed on the best-performed subpopulation to achieve a balanced search. The proposed algorithm has been tested by solving optimization problems taken from CEC2014 benchmark problems. Experimental results show that our algorithm can achieve a competitive or better than related methods. The results also confirm the significance of devised strategies in the proposed algorithm.

Keywords: differential evolution, multi-mutation strategies, memetic algorithm, adaptive local search

Procedia PDF Downloads 148