Search results for: radiation processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5074

Search results for: radiation processing

2764 Data Presentation of Lane-Changing Events Trajectories Using HighD Dataset

Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba

Abstract:

We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).

Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process

Procedia PDF Downloads 263
2763 Chinese Event Detection Technique Based on Dependency Parsing and Rule Matching

Authors: Weitao Lin

Abstract:

To quickly extract adequate information from large-scale unstructured text data, this paper studies the representation of events in Chinese scenarios and performs the regularized abstraction. It proposes a Chinese event detection technique based on dependency parsing and rule matching. The method first performs dependency parsing on the original utterance, then performs pattern matching at the word or phrase granularity based on the results of dependent syntactic analysis, filters out the utterances with prominent non-event characteristics, and obtains the final results. The experimental results show the effectiveness of the method.

Keywords: natural language processing, Chinese event detection, rules matching, dependency parsing

Procedia PDF Downloads 142
2762 Secret Security Smart Lock Using Artificial Intelligence Hybrid Algorithm

Authors: Vahid Bayrami Rad

Abstract:

Ever since humans developed a collective way of life to the development of urbanization, the concern of security has always been considered one of the most important challenges of life. To protect property, locks have always been a practical tool. With the advancement of technology, the form of locks has changed from mechanical to electric. One of the most widely used fields of using artificial intelligence is its application in the technology of surveillance security systems. Currently, the technologies used in smart anti-theft door handles are one of the most potential fields for using artificial intelligence. Artificial intelligence has the possibility to learn, calculate, interpret and process by analyzing data with the help of algorithms and mathematical models and make smart decisions. We will use Arduino board to process data.

Keywords: arduino board, artificial intelligence, image processing, solenoid lock

Procedia PDF Downloads 71
2761 Hydrogen: Contention-Aware Hybrid Memory Management for Heterogeneous CPU-GPU Architectures

Authors: Yiwei Li, Mingyu Gao

Abstract:

Integrating hybrid memories with heterogeneous processors could leverage heterogeneity in both compute and memory domains for better system efficiency. To ensure performance isolation, we introduce Hydrogen, a hardware architecture to optimize the allocation of hybrid memory resources to heterogeneous CPU-GPU systems. Hydrogen supports efficient capacity and bandwidth partitioning between CPUs and GPUs in both memory tiers. We propose decoupled memory channel mapping and token-based data migration throttling to enable flexible partitioning. We also support epoch-based online search for optimized configurations and lightweight reconfiguration with reduced data movements. Hydrogen significantly outperforms existing designs by 1.21x on average and up to 1.31x.

Keywords: hybrid memory, heterogeneous systems, dram cache, graphics processing units

Procedia PDF Downloads 105
2760 The Effect of Transparent Oil Wood Stain on the Colour Stability of Spruce Wood during Weathering

Authors: Eliska Oberhofnerova, Milos Panek, Stepan Hysek, Martin Lexa

Abstract:

Nowadays the use of wood, both indoors and outdoors, is constantly increasing. However wood is a natural organic material and in the exterior is subjected to a degradation process caused by abiotic factors (solar radiation, rain, moisture, wind, dust etc.). This process affects only surface layers of wood but neglecting some of the basic rules of wood protection leads to increased possibility of biological agents attack and thereby influences a function of the wood element. The process of wood degradation can be decreased by proper surface treatment, especially in the case of less naturally durable wood species, as spruce. Modern coating systems are subjected to many requirements such as colour stability, hydrophobicity, low volatile organic compound (VOC) content, long service life or easy maintenance. The aim of this study is to evaluate the colour stability of spruce wood (Picea abies), as the basic parameter indicating the coating durability, treated with two layers of transparent natural oil wood stain and exposed to outdoor conditions. The test specimens were exposed for 2 years to natural weathering and 2000 hours to artificial weathering in UV-chamber. The colour parameters were measured before and during exposure to weathering by the spectrophotometer according to CIELab colour space. The comparison between untreated and treated wood and both testing procedures was carried out. The results showed a significant effect of coating on the colour stability of wood, as expected. Nevertheless, increasing colour changes of wood observed during the exposure to weathering differed according to applied testing procedure - natural and artificial.

Keywords: colour stability, natural and artificial weathering, spruce wood, transparent coating

Procedia PDF Downloads 223
2759 Comparative Analysis between Corn and Ramon (Brosimum alicastrum) Starches to Be Used as Sustainable Bio-Based Plastics

Authors: C. R. Ríos-Soberanis, V. M. Moo-Huchin, R. J. Estrada-Leon, E. Perez-Pacheco

Abstract:

Polymers from renewable resources have attracted an increasing amount of attention over the last two decades, predominantly due to two major reasons: firstly environmental concerns, and secondly the realization that our petroleum resources are finite. Finding new uses for agricultural commodities is also an important area of research. Therefore, it is crucial to get new sources of natural materials that can be used in different applications. Ramon tree (Brosimum alicastrum) is a tropical plant that grows freely in Yucatan countryside. This paper focuses on the seeds recollection, processing and starch extraction and characterization in order to find out about its suitability as biomaterial. Results demonstrated that it has a high content of qualities to be used not only as comestible but also as an important component in polymeric blends.

Keywords: biomaterials, characterization techniques, natural resource, starch

Procedia PDF Downloads 327
2758 Frequent Item Set Mining for Big Data Using MapReduce Framework

Authors: Tamanna Jethava, Rahul Joshi

Abstract:

Frequent Item sets play an essential role in many data Mining tasks that try to find interesting patterns from the database. Typically it refers to a set of items that frequently appear together in transaction dataset. There are several mining algorithm being used for frequent item set mining, yet most do not scale to the type of data we presented with today, so called “BIG DATA”. Big Data is a collection of large data sets. Our approach is to work on the frequent item set mining over the large dataset with scalable and speedy way. Big Data basically works with Map Reduce along with HDFS is used to find out frequent item sets from Big Data on large cluster. This paper focuses on using pre-processing & mining algorithm as hybrid approach for big data over Hadoop platform.

Keywords: frequent item set mining, big data, Hadoop, MapReduce

Procedia PDF Downloads 440
2757 Proposal of a Damage Inspection Tool After Earthquakes: Case of Algerian Buildings

Authors: Akkouche Karim, Nekmouche Aghiles, Bouzid Leyla

Abstract:

This study focuses on the development of a multifunctional Expert System (ES) called post-seismic damage inspection tool (PSDIT), a powerful tool which allows the evaluation, the processing and the archiving of the collected data stock after earthquakes. PSDIT can be operated by two user types; an ordinary user (engineer, expert or architect) for the damage visual inspection and an administrative user for updating the knowledge and / or for adding or removing the ordinary user. The knowledge acquisition is driven by a hierarchical knowledge model, the Information from investigation reports and those acquired through feedback from expert / engineer questionnaires are part.

Keywords: buildings, earthquake, seismic damage, damage assessment, expert system

Procedia PDF Downloads 90
2756 On the Qarat Kibrit Salt Dome Faulting System South of Adam, Oman: In Search of Uranium Anomalies

Authors: Alaeddin Ebrahimi, Narasimman Sundararajan, Bernhard Pracejus

Abstract:

Development of salt domes, often a rising from depths of some 10 km or more, causes an intense faulting of the surrounding host rocks (salt tectonics). The fractured rocks then present ideal space for oil that can migrate and get trapped. If such moving of hydrocarbons passes uranium-carrying rock units (e.g., shales), uranium is collected and enriched by organic carbon compounds. Brines from the salt body are also ideal carriers for oxidized uranium species and will further dislocate uranium when in contact with uranium-enriched oils. Uranium then has the potential to mineralize in the vicinity of the dome (blue halite is evidence for radiation having affected salt deposits elsewhere in the world). Based on this knowledge, the Qarat Kibrit salt dome was investigated by a well-established geophysical method like very low frequency electromagnetic (VLF-EM) along five traverses approximately 250 m in length (10 m intervals) in order to identify subsurface fault systems. In-phase and quadrature components of the VLF-EM signal were recorded at two different transmitter frequencies (24.0 and 24.9 kHz). The images of Fraser filtered response of the in-phase components indicate a conductive zone (fault) in the southeast and southwest of the study area. The Karous-Hjelt current density pseudo section delineates subsurface faults at depths between 10 and 40 m. The stacked profiles of the Fraser filtered responses brought out two plausible trends/directions of faults. However, there seems to be no evidence for uranium enrichment has been recorded in this area.

Keywords: salt dome, uranium, fault, in-phase component, quadrature component, Fraser filter, Karous-Hjelt current density

Procedia PDF Downloads 242
2755 Parallel Computing: Offloading Matrix Multiplication to GPU

Authors: Bharath R., Tharun Sai N., Bhuvan G.

Abstract:

This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

Procedia PDF Downloads 62
2754 1/Sigma Term Weighting Scheme for Sentiment Analysis

Authors: Hanan Alshaher, Jinsheng Xu

Abstract:

Large amounts of data on the web can provide valuable information. For example, product reviews help business owners measure customer satisfaction. Sentiment analysis classifies texts into two polarities: positive and negative. This paper examines movie reviews and tweets using a new term weighting scheme, called one-over-sigma (1/sigma), on benchmark datasets for sentiment classification. The proposed method aims to improve the performance of sentiment classification. The results show that 1/sigma is more accurate than the popular term weighting schemes. In order to verify if the entropy reflects the discriminating power of terms, we report a comparison of entropy values for different term weighting schemes.

Keywords: 1/sigma, natural language processing, sentiment analysis, term weighting scheme, text classification

Procedia PDF Downloads 206
2753 Compact Dual-band 4-MIMO Antenna Elements for 5G Mobile Applications

Authors: Fayad Ghawbar

Abstract:

The significance of the Multiple Input Multiple Output (MIMO) system in the 5G wireless communication system is essential to enhance channel capacity and provide a high data rate resulting in a need for dual-polarization in vertical and horizontal. Furthermore, size reduction is critical in a MIMO system to deploy more antenna elements requiring a compact, low-profile design. A compact dual-band 4-MIMO antenna system has been presented in this paper with pattern and polarization diversity. The proposed single antenna structure has been designed using two antenna layers with a C shape in the front layer and a partial slot with a U-shaped cut in the ground to enhance isolation. The single antenna is printed on an FR4 dielectric substrate with an overall size of 18 mm×18 mm×1.6 mm. The 4-MIMO antenna elements were printed orthogonally on an FR4 substrate with a size dimension of 36 × 36 × 1.6 mm3 with zero edge-to-edge separation distance. The proposed compact 4-MIMO antenna elements resonate at 3.4-3.6 GHz and 4.8-5 GHz. The s-parameters measurement and simulation results agree, especially in the lower band with a slight frequency shift of the measurement results at the upper band due to fabrication imperfection. The proposed design shows isolation above -15 dB and -22 dB across the 4-MIMO elements. The MIMO diversity performance has been evaluated in terms of efficiency, ECC, DG, TARC, and CCL. The total and radiation efficiency were above 50 % across all parameters in both frequency bands. The ECC values were lower than 0.10, and the DG results were about 9.95 dB in all antenna elements. TARC results exhibited values lower than 0 dB with values lower than -25 dB in all MIMO elements at the dual-bands. Moreover, the channel capacity losses in the MIMO system were depicted using CCL with values lower than 0.4 Bits/s/Hz.

Keywords: compact antennas, MIMO antenna system, 5G communication, dual band, ECC, DG, TARC

Procedia PDF Downloads 145
2752 Evaluation and Strategic Development of IT in Accounting in Turkey

Authors: Eda Kocakaya, Sebahat Seker, Dogan Argun

Abstract:

The aim of this study is to determine the process of information technologies and the connections between concepts in accounting management services in Turkey. The objective of this study is to determine the adaptation and evaluation process of information technologies and the connections between concepts and differences in accounting management services in Turkey. The situation and determination of the IT applications of Accounting Management were studied. The applications of • Billing • Order Processing • Accounts Receivable/Payable Management • Contract Management • Bank Account Management Were discussed in this study. The IT applications were demonstrated and realized in actual accounting services. The sectoral representative's companies were selected, and the IT application was searched by bibliometric analysis.

Keywords: management, accounting, information technologies, adaptation

Procedia PDF Downloads 311
2751 Radar-Based Classification of Pedestrian and Dog Using High-Resolution Raw Range-Doppler Signatures

Authors: C. Mayr, J. Periya, A. Kariminezhad

Abstract:

In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

Procedia PDF Downloads 247
2750 Data Analysis Tool for Predicting Water Scarcity in Industry

Authors: Tassadit Issaadi Hamitouche, Nicolas Gillard, Jean Petit, Valerie Lavaste, Celine Mayousse

Abstract:

Water is a fundamental resource for the industry. It is taken from the environment either from municipal distribution networks or from various natural water sources such as the sea, ocean, rivers, aquifers, etc. Once used, water is discharged into the environment, reprocessed at the plant or treatment plants. These withdrawals and discharges have a direct impact on natural water resources. These impacts can apply to the quantity of water available, the quality of the water used, or to impacts that are more complex to measure and less direct, such as the health of the population downstream from the watercourse, for example. Based on the analysis of data (meteorological, river characteristics, physicochemical substances), we wish to predict water stress episodes and anticipate prefectoral decrees, which can impact the performance of plants and propose improvement solutions, help industrialists in their choice of location for a new plant, visualize possible interactions between companies to optimize exchanges and encourage the pooling of water treatment solutions, and set up circular economies around the issue of water. The development of a system for the collection, processing, and use of data related to water resources requires the functional constraints specific to the latter to be made explicit. Thus the system will have to be able to store a large amount of data from sensors (which is the main type of data in plants and their environment). In addition, manufacturers need to have 'near-real-time' processing of information in order to be able to make the best decisions (to be rapidly notified of an event that would have a significant impact on water resources). Finally, the visualization of data must be adapted to its temporal and geographical dimensions. In this study, we set up an infrastructure centered on the TICK application stack (for Telegraf, InfluxDB, Chronograf, and Kapacitor), which is a set of loosely coupled but tightly integrated open source projects designed to manage huge amounts of time-stamped information. The software architecture is coupled with the cross-industry standard process for data mining (CRISP-DM) data mining methodology. The robust architecture and the methodology used have demonstrated their effectiveness on the study case of learning the level of a river with a 7-day horizon. The management of water and the activities within the plants -which depend on this resource- should be considerably improved thanks, on the one hand, to the learning that allows the anticipation of periods of water stress, and on the other hand, to the information system that is able to warn decision-makers with alerts created from the formalization of prefectoral decrees.

Keywords: data mining, industry, machine Learning, shortage, water resources

Procedia PDF Downloads 122
2749 Partial Differential Equation-Based Modeling of Brain Response to Stimuli

Authors: Razieh Khalafi

Abstract:

The brain is the information processing centre of the human body. Stimuli in the form of information are transferred to the brain and then brain makes the decision on how to respond to them. In this research, we propose a new partial differential equation which analyses the EEG signals and make a relationship between the incoming stimuli and the brain response to them. In order to test the proposed model, a set of external stimuli applied to the model and the model’s outputs were checked versus the real EEG data. The results show that this model can model the EEG signal well. The proposed model is useful not only for modelling of EEG signal in case external stimuli but it can be used for modelling of brain response in case of internal stimuli.

Keywords: brain, stimuli, partial differential equation, response, EEG signal

Procedia PDF Downloads 556
2748 A New Approach for Assertions Processing during Assertion-Based Software Testing

Authors: Ali M. Alakeel

Abstract:

Assertion-based software testing has been shown to be a promising tool for generating test cases that reveal program faults. Because the number of assertions may be very large for industry-size programs, one of the main concerns to the applicability of assertion-based testing is the amount of search time required to explore a large number of assertions. This paper presents a new approach for assertions exploration during the process of Assertion-Based software testing. Our initial exterminations with the proposed approach show that the performance of Assertion-Based testing may be improved, therefore, making this approach more efficient when applied on programs with large number of assertions.

Keywords: software testing, assertion-based testing, program assertions, generating test

Procedia PDF Downloads 463
2747 Alterations of Molecular Characteristics of Polyethylene under the Influence of External Effects

Authors: Vigen Barkhudaryan

Abstract:

The influence of external effects (γ-, UV–radiations, high temperature) in presence of air oxygen on structural transformations of low-density polyethylene (LDPE) have been investigated dependent on the polymers’ thickness, the intensity and the dose of external actions. The methods of viscosimetry, light scattering, turbidimetry and gelation measuring were used for this purpose. The comparison of influence of external effects on LDPE shows, that the destruction and cross-linking processes of macromolecules proceed simultaneously with all kinds of external effects. A remarkable growth of average molecular mass of LDPE along with the irradiation doses and heat treatment exposure growth was established. It was linear for the mass average molecular mass and at the initial doses is mainly the result of the increase of the macromolecular branching. As a result, the macromolecular hydrodynamic volumes have been changed, and therefore the dependence of viscosity average molecular mass on the doses was going through the minimum at initial doses. A significant change of molecular mass, sizes and shape of macromolecules of LDPE occurs under the influence of external effects. The influence is limited only by diffusion of oxygen during -irradiation and heat treatment. At UV–irradiation the influence is limited both by diffusion of oxygen and penetration of radiation. Consequently, the molecular transformations are deeper and evident in case of -irradiation, as soon as the polymer is transformed in a whole volume. It was also established, that the mechanism of molecular transformations in polymers from the surface layer distinctly differs from those of the sample deeper layer. A comparison of the results of these investigations allows us to conclude, that the mechanisms of influence of investigated external effects on polyethylene are similar.

Keywords: cross-linking, destruction, high temperature, LDPE, γ-radiations, UV-radiations

Procedia PDF Downloads 319
2746 Performance Analysis of ERA Using Fuzzy Logic in Wireless Sensor Network

Authors: Kamalpreet Kaur, Harjit Pal Singh, Vikas Khullar

Abstract:

In Wireless Sensor Network (WSN), the main limitation is generally inimitable energy consumption during processing of the sensor nodes. Cluster head (CH) election is one of the main issues that can reduce the energy consumption. Therefore, discovering energy saving routing protocol is the focused area for research. In this paper, fuzzy-based energy aware routing protocol is presented, which enhances the stability and network lifetime of the network. Fuzzy logic ensures the well-organized selection of CH by taking four linguistic variables that are concentration, energy, centrality, and distance to base station (BS). The results show that the proposed protocol shows better results in requisites of stability and throughput of the network.

Keywords: ERA, fuzzy logic, network model, WSN

Procedia PDF Downloads 280
2745 Features Dimensionality Reduction and Multi-Dimensional Voice-Processing Program to Parkinson Disease Discrimination

Authors: Djamila Meghraoui, Bachir Boudraa, Thouraya Meksen, M.Boudraa

Abstract:

Parkinson's disease is a pathology that involves characteristic perturbations in patients’ voices. This paper describes a proposed method that aims to diagnose persons with Parkinson (PWP) by analyzing on line their voices signals. First, Thresholds signals alterations are determined by the Multi-Dimensional Voice Program (MDVP). Principal Analysis (PCA) is exploited to select the main voice principal componentsthat are significantly affected in a patient. The decision phase is realized by a Mul-tinomial Bayes (MNB) Classifier that categorizes an analyzed voice in one of the two resulting classes: healthy or PWP. The prediction accuracy achieved reaching 98.8% is very promising.

Keywords: Parkinson’s disease recognition, PCA, MDVP, multinomial Naive Bayes

Procedia PDF Downloads 280
2744 Predicting the Product Life Cycle of Songs on Radio - How Record Labels Can Manage Product Portfolio and Prioritise Artists by Using Machine Learning Techniques

Authors: Claus N. Holm, Oliver F. Grooss, Robert A. Alphinas

Abstract:

This research strives to predict the remaining product life cycle of a song on radio after it has been played for one or two months. The best results were achieved using a k-d tree to calculate the most similar songs to the test songs and use a Random Forest model to forecast radio plays. An 82.78% and 83.44% accuracy is achieved for the two time periods, respectively. This explorative research leads to over 4500 test metrics to find the best combination of models and pre-processing techniques. Other algorithms tested are KNN, MLP and CNN. The features only consist of daily radio plays and use no musical features.

Keywords: hit song science, product life cycle, machine learning, radio

Procedia PDF Downloads 157
2743 A Review of Accuracy Optical Surface Imaging Systems for Setup Verification During Breast Radiotherapy Treatment

Authors: Auwal Abubakar, Ahmed Ahidjo, Shazril Imran Shaukat, Noor Khairiah A. Karim, Gokula Kumar Appalanaido, Hafiz Mohd Zin

Abstract:

Background: The use of optical surface imaging systems (OSISs) is increasingly becoming popular in radiotherapy practice, especially during breast cancer treatment. This study reviews the accuracy of the available commercial OSISs for breast radiotherapy. Method: A literature search was conducted and identified the available commercial OSISs from different manufacturers that are integrated into radiotherapy practice for setup verification during breast radiotherapy. Studies that evaluated the accuracy of the OSISs during breast radiotherapy using cone beam computed tomography (CBCT) as a reference were retrieved and analyzed. The physics and working principles of the systems from each manufacturer were discussed together with their respective strength and limitations. Results: A total of five (5) different commercially available OSISs from four (4) manufacturers were identified, each with a different working principle. Six (6) studies were found to evaluate the accuracy of the systems during breast radiotherapy in conjunction with CBCT as a goal standard. The studies revealed that the accuracy of the system in terms of mean difference ranges from 0.1 to 2.1 mm. The correlation between CBCT and OSIS ranges between 0.4 and 0.9. The limit of agreements obtained using bland Altman analysis in the studies was also within an acceptable range. Conclusion: The OSISs have an acceptable level of accuracy and could be used safely during breast radiotherapy. The systems are non-invasive, ionizing radiation-free, and provide real-time imaging of the target surface at no extra concomitant imaging dose. However, the system should only be used to complement rather than replace x-ray-based image guidance techniques such as CBCT.

Keywords: optical surface imaging system, Cone beam computed tomography (CBCT), surface guided radiotherapy, Breast radiotherapy

Procedia PDF Downloads 67
2742 Hole Characteristics of Percussion and Single Pulse Laser-Incised Radiata Pine and the Effects of Wood Anatomy on Laser-Incision

Authors: Subhasisa Nath, David Waugh, Graham Ormondroyd, Morwenna Spear, Andy Pitman, Paul Mason

Abstract:

Wood is one of the most sustainable and environmentally favourable materials and is chemically treated in timber industries to maximise durability. To increase the chemical preservative uptake and retention by the wood, current limiting incision technologies are commonly used. This work reports the effects of single pulse CO2 laser-incision and frequency tripled Nd:YAG percussion laser-incision on the characteristics of laser-incised holes in the Radiata Pine. The laser-incision studies were based on changing laser wavelengths, energies and focal planes to conclude on an optimised combination for the laser-incision of Radiata Pine. The laser pulse duration had a dominant effect over laser power in controlling hole aspect ratio in CO2 laser-incision. A maximum depth of ~ 30 mm was measured with a laser power output of 170 W and a pulse duration of 80 ms. However, increased laser power led to increased carbonisation of holes. The carbonisation effect was reduced during laser-incision in the ultra-violet (UV) regime. Deposition of a foamy phase on the laser-incised hole wall was evident irrespective of laser radiation wavelength and energy. A maximum hole depth of ~20 mm was measured in the percussion laser-incision in the UV regime (355 nm) with a pulse energy of 320 mJ. The radial and tangential faces had a significant effect on laser-incision efficiency for all laser wavelengths. The laser-incised hole shapes and circularities were affected by the wood anatomy (earlywoods and latewoods in the structure). Subsequently, the mechanism of laser-incision is proposed by analysing the internal structure of laser-incised holes.

Keywords: CO2 Laser, Nd: YAG laser, incision, drilling, wood, hole characteristics

Procedia PDF Downloads 243
2741 Effect of Green Roofs to Prevent the Dissipation of Energy in Mountainous Areas

Authors: Mina Ganji Morad, Maziar Azadisoleimanieh, Sina Ganji Morad

Abstract:

A green roof is formed by green plants alive and has many positive impacts in the regional climatic, as well as indoor. Green roof system to prevent solar radiation plays a role in the cooling space. The cooling is done by reducing thermal fluctuations on the exterior of the roof and by increasing the roof heat capacity which cause to keep the space under the roof cool in the summer and heating rate increases during the winter. A roof garden is one of the recommended ways to reduce energy consumption in large cities. Despite the scale of the city green roofs have effective functions, such as beautiful view of city and decontaminating the urban landscape and reduce mental stress, and in an exchange of energy and heat from outside to inside spaces. This article is based on a review of 20 articles and 10 books and valid survey results on the positive effects of green roofs to prevent energy waste in the building. According to these publications, three of the conventional roof, green roof typical and green roof with certain administrative details (layers of glass) and the use of resistant plants and shrubs have been analyzed and compared their heat transfer. The results of these studies showed that one of the best green roof systems for mountainous climate is tree and shrub system that in addition to being resistant to climate change in mountainous regions, will benefit from the other advantages of green roof. Due to the severity of climate change in mountainous areas it is essential to prevent the waste of buildings heating and cooling energy. Proper climate design can greatly help to reduce energy.

Keywords: green roof, heat transfer, reducing energy consumption, mountainous areas, sustainable architecture

Procedia PDF Downloads 399
2740 Refining Sexual Assault Treatment: Recovered Survivors and Expert Therapists Concur on Effective Therapy Components

Authors: Avigail Moor, Michal Otmazgin, Hagar Tsiddon, Avivit Mahazri

Abstract:

The goal of the present study was to refine sexual assault therapy through the examination of the level of agreement between survivor and therapist assessments of key recovery-promoting therapeutic interventions. This is the first study to explore the level of agreement between those who partake in the treatment process from either position. Semi structured interviews were conducted in this qualitative study with 10 survivors and 10 experienced therapists. The results document considerable concurrence between them regarding relational and trauma processing treatment components alike. Together, these reports outline key effective interventions, both common and specific in nature, concomitantly supported by both groups.

Keywords: sexual assault, rape treatment, therapist training, psychotherapy

Procedia PDF Downloads 60
2739 Effect of Signal Acquisition Procedure on Imagined Speech Classification Accuracy

Authors: M.R Asghari Bejestani, Gh. R. Mohammad Khani, V.R. Nafisi

Abstract:

Imagined speech recognition is one of the most interesting approaches to BCI development and a lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works.

Keywords: brain computer interface, silent talk, imagined speech, classification, signal processing

Procedia PDF Downloads 155
2738 A Multi Function Myocontroller for Upper Limb Prostheses

Authors: Ayad Asaad Ibrahim

Abstract:

Myoelectrically controlled prostheses are becoming more and more popular, for below-elbow amputation, the wrist flexor and extensor muscle group, while for above-elbow biceps and triceps brachii muscles are used for control of the prosthesis. A two site multi-function controller is presented. Two stainless steel bipolar electrode pairs are used to monitor the activities in both muscles. The detected signals are processed by new pre-whitening technique to identify the accurate tension estimation in these muscles. These estimates will activate the relevant prosthesis control signal, with a time constant of 200 msec. It is ensured that the tension states in the control muscle to activate a particular prosthesis function are similar to those used to activate normal functions in the natural hand. This facilitates easier training.

Keywords: prosthesis, biosignal processing, pre-whitening, myoelectric controller

Procedia PDF Downloads 364
2737 The Effect of Photovoltaic Integrated Shading Devices on the Energy Performance of Apartment Buildings in a Mediterranean Climate

Authors: Jenan Abu Qadourah

Abstract:

With the depletion of traditional fossil resources and the growing human population, it is now more important than ever to reduce our energy usage and harmful emissions. In the Mediterranean region, the intense solar radiation contributes to summertime overheating, which raises energy costs and building carbon footprints, alternatively making it suitable for the installation of solar energy systems. In urban settings, where multi-story structures predominate and roof space is limited, photovoltaic integrated shading devices (PVSD) are a clean solution for building designers. However, incorporating photovoltaic (PV) systems into a building's envelope is a complex procedure that, if not executed correctly, might result in the PV system failing. As a result, potential PVSD design solutions must be assessed based on their overall energy performance from the project's early design stage. Therefore, this paper aims to investigate and compare the possible impact of various PVSDs on the energy performance of new apartments in the Mediterranean region, with a focus on Amman, Jordan. To achieve the research aim, computer simulations were performed to assess and compare the energy performance of different PVSD configurations. Furthermore, an energy index was developed by taking into account all energy aspects, including the building's primary energy demand and the PVSD systems' net energy production. According to the findings, the PVSD system can meet 12% to 43% of the apartment building's electricity needs. By highlighting the potential interest in PVSD systems, this study aids the building designer in producing more energy-efficient buildings and encourages building owners to install PV systems on the façade of their buildings.

Keywords: photovoltaic integrated shading device, solar energy, architecture, energy performance, simulation, overall energy index, Jordan

Procedia PDF Downloads 85
2736 Non-Destructive Technique for Detection of Voids in the IC Package Using Terahertz-Time Domain Spectrometer

Authors: Sung-Hyeon Park, Jin-Wook Jang, Hak-Sung Kim

Abstract:

In recent years, Terahertz (THz) time-domain spectroscopy (TDS) imaging method has been received considerable interest as a promising non-destructive technique for detection of internal defects. In comparison to other non-destructive techniques such as x-ray inspection method, scanning acoustic tomograph (SAT) and microwave inspection method, THz-TDS imaging method has many advantages: First, it can measure the exact thickness and location of defects. Second, it doesn’t require the liquid couplant while it is very crucial to deliver that power of ultrasonic wave in SAT method. Third, it didn’t damage to materials and be harmful to human bodies while x-ray inspection method does. Finally, it exhibits better spatial resolution than microwave inspection method. However, this technology couldn’t be applied to IC package because THz radiation can penetrate through a wide variety of materials including polymers and ceramics except of metals. Therefore, it is difficult to detect the defects in IC package which are composed of not only epoxy and semiconductor materials but also various metals such as copper, aluminum and gold. In this work, we proposed a special method for detecting the void in the IC package using THz-TDS imaging system. The IC package specimens for this study are prepared by Packaging Engineering Team in Samsung Electronics. Our THz-TDS imaging system has a special reflection mode called pitch-catch mode which can change the incidence angle in the reflection mode from 10 o to 70 o while the others have transmission and the normal reflection mode or the reflection mode fixed at certain angle. Therefore, to find the voids in the IC package, we investigated the appropriate angle as changing the incidence angle of THz wave emitter and detector. As the results, the voids in the IC packages were successfully detected using our THz-TDS imaging system.

Keywords: terahertz, non-destructive technique, void, IC package

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2735 Optimization of Real Time Measured Data Transmission, Given the Amount of Data Transmitted

Authors: Michal Kopcek, Tomas Skulavik, Michal Kebisek, Gabriela Krizanova

Abstract:

The operation of nuclear power plants involves continuous monitoring of the environment in their area. This monitoring is performed using a complex data acquisition system, which collects status information about the system itself and values of many important physical variables e.g. temperature, humidity, dose rate etc. This paper describes a proposal and optimization of communication that takes place in teledosimetric system between the central control server responsible for the data processing and storing and the decentralized measuring stations, which are measuring the physical variables. Analyzes of ongoing communication were performed and consequently the optimization of the system architecture and communication was done.

Keywords: communication protocol, transmission optimization, data acquisition, system architecture

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