Search results for: smart signature

Authors: Murtadha Kareem, Oliver Faust

Abstract:

Wearable biosensor systems can be designed and developed for health monitoring. There is much interest in both scientific and industrial communities established since 2007. Fundamentally, the cost of healthcare has increased dramatically and the world population is aging. That creates the need to harvest technological improvements with small bio-sensing devices, wireless-communication, microelectronics and smart textiles, that leads to non-stop developments of wearable sensor based systems. There has been a significant demand to monitor patient's health status while the patient leaves the hospital in his/her personal environment. To address this need, there are numerous system prototypes which has been launched in the medical market recently, the aim of that is to provide real time information feedback about patient's health status, either to the patient himself/herself or direct to the supervising medical centre station, while being capable to give a notification for the patient in case of possible imminent health threatening conditions. Furthermore, wearable health monitoring systems comprise new techniques to address the problem of managing and monitoring chronic heart diseases for elderly people. Wearable sensor systems for health monitoring include various types of miniature sensors, either wearable or implantable. To be specific, our proposed system able to measure essential physiological parameter, such as heart rate signal which could be transmitted through Bluetooth to the cloud server in order to store, process, analysis and visualise the data acquisition. The acquired measurements are connected through internet of things to a central node, for instance an android smart phone or tablet used for visualising the collected information on application or transmit it to a medical centre.

Keywords: Wearable sensor, Heart rate, Internet of things, Chronic heart disease

Procedia PDF Downloads 160

Authors: Muhammad Bilal, Adil Ahmed

Abstract:

This study proposes an approach for electrical induction motor predictive maintenance utilizing machine learning algorithms. On the basis of a study of temperature data obtained from sensors put on the motor, the goal is to predict motor failures. The proposed models are trained to identify whether a motor is defective or not by utilizing machine learning algorithms like Support Vector Machines (SVM) and K-Nearest Neighbors (KNN). According to a thorough study of the literature, earlier research has used motor current signature analysis (MCSA) and vibration data to forecast motor failures. The temperature signal methodology, which has clear advantages over the conventional MCSA and vibration analysis methods in terms of cost-effectiveness, is the main subject of this research. The acquired results emphasize the applicability and effectiveness of the temperature-based predictive maintenance strategy by demonstrating the successful categorization of defective motors using the suggested machine learning models.

Keywords: predictive maintenance, electrical induction motors, machine learning, temperature signal methodology, motor failures

Procedia PDF Downloads 112

Authors: Kristin Drexler

Abstract:

Climate change has exacerbated food and livelihood insecurity for Mayan milpa farmers in Central America. For centuries, milpa farming has been sustainable for subsistence; however, in the last 50 years, milpas have become less reliable due to accelerating climate change, resource degradation, declining markets, poverty, and other factors. Using interviews with extension leaders and milpa farmers in Belize, this qualitative study examines the capacity for increasing climate-smart agriculture (CSA) aspects of existing traditional milpa practices, specifically no-burn mulching, soil enrichment, and the use of cover plants. Applying community capitals and socio-ecological systems frameworks, this study finds four key capitals were perceived by farmers and agriculture extension leaders as barriers for increasing CSA practices: (1) human-capacity, (2) financial, (3) infrastructure, and (4) governance-justice capitals. The key barriers include a lack of CSA technology and pest management knowledge-sharing (human-capacity), unreliable roads and utility services (infrastructure), the closure of small markets and crop-buying programs in Belize (financial), and constraints on extension services and exacerbating a sense of marginalization in Maya communities (governance-justice). Recommendations are presented for government action to reduce barriers and facilitate an increase in milpa crop productivity, promote food and livelihood security, and enable climate resilience of Mayan milpa communities in Belize.

Keywords: socio-ecological systems, community capitals, climate-smart agriculture, food security, milpa, Belize

Procedia PDF Downloads 88

Authors: Mohammad M. Garmabia, Peyman Shahia, Jimi Tjonga, Mohini Saina

Abstract:

Flame retardant composite filaments with functional carbon in the composition were fabricated, and printed parts showed enhancedcrash resistance pproperties and imporved EMI shielding. The negligible mass difference after prolonged immersion in automobile chemicals revealed the outstanding performance of parts for under-the-hood high-temperature applications.

Keywords: FDM, crash worthy, EMI Shield, lightweight, automotive parts

Procedia PDF Downloads 96

Authors: Amjad Alsulami, Farah Albishri, Kholod Alzubidi, Lama Almehemadi, Salma Elhag

Abstract:

Food allergy is a common and rising problem among children. Many students have their first allergic reaction at school, one of these is anaphylaxis, which can be fatal. This study discovered that several schools' processes lacked safety regulations and information on how to handle allergy issues and chronic diseases like diabetes where students were not supervised or monitored during the cafeteria purchasing process. There is no obvious prevention or effort in academic institutions when purchasing food containing allergens or negatively impacting the health status of students who suffer from chronic diseases. Students must always be stable to reflect positively on their educational development process. To address this issue, this paper uses a business reengineering process to propose the automation of the whole food-purchasing process, which will aid in detecting and avoiding allergic occurrences and preventing any side effects from eating foods that are conflicting with students' health. This may be achieved by designing a smart card with an embedded QR code that reveals which foods cause an allergic reaction in a student. A survey was distributed to determine and examine how the cafeteria will handle allergic children and whether any management or policy is applied in the school. Also, the survey findings indicate that the integration of QR technology into the food purchasing process would improve health condition detection. The suggested system would be beneficial to all parties, the family agreed, as they would ensure that their children didn't eat foods that were bad for their health. Moreover, by analyzing and simulating the as-is process and the suggested process the results demonstrate that there is an improvement in quality and time.

Keywords: QR code, smart card, food allergies, business process reengineering, health condition detection

Procedia PDF Downloads 73

Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

Abstract:

Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: neural network, motion detection, signature detection, convolutional neural network

Procedia PDF Downloads 81

Authors: V. Sivakumar, R. Neelakantan

Abstract:

Mineral mapping on the Moon surface provides the clue to understand the origin, evolution, stratigraphy and geological history of the Moon. Recently, reflectance imaging spectroscopy plays a significant role in identifying minerals on the planetary surface in the Visible to NIR region of the electromagnetic spectrum. The Moon Mineralogy Mapper (M3) onboard Chandrayaan-1 provides unprecedented spectral data of lunar surface to study about the Moon surface. Here we used the M3 sensor data (hyperspectral imaging spectroscopy) for analysing mineralogy of Orientale basin region on the Moon surface. Reflectance spectrums were sampled from different locations of the basin and continuum was removed using ENvironment for Visualizing Images (ENVI) software. Reflectance spectra of unknown mineral composition were compared with known Reflectance Experiment Laboratory (RELAB) spectra for discriminating mineralogy. Minerals like olivine, Low-Ca Pyroxene (LCP), High-Ca Pyroxene (HCP) and plagioclase were identified. In addition to these minerals, an unusual type of spectral signature was identified, which indicates the probable Fe-Mg-spinel lithology in the basin region.

Keywords: chandryaan-1, moon mineralogy mapper, mineral, mare orientale, moon

Procedia PDF Downloads 391

Authors: G. C. Tikkiwal, Mukesh Upadhyay

Abstract:

During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving the army, moving convoys etc. The radar operator selects one of the promising targets into single target tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper, we present a technique using mathematical and statistical methods like fast fourier transformation (FFT) and principal component analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, FFT, principal component analysis, eigenvector, octave-notes, DSP

Procedia PDF Downloads 393

Authors: Khaled Missaoui, Amina Beldjazia, Rachid Gharzouli, Yamna Djellouli

Abstract:

Optical remote sensing makes use of visible, near infrared and short-wave infrared sensors to form images of the earth's surface by detecting the solar radiation reflected from targets on the ground. Different materials reflect and absorb differently at different wavelengths. Thus, the targets can be differentiated by their spectral reflectance signatures in the remotely sensed images. In this work, we are interested to study the distribution of vegetation in the massif forest of Boutaleb (North East of Algeria) which suffered between 1998 and 1999 very large fires. In this case, we use remote sensing with Landsat images from two dates (1984 and 2000) to see the results of these fires. Vegetation has a unique spectral signature which enables it to be distinguished readily from other types of land cover in an optical/near-infrared image. Normalized Difference Vegetation Index (NDVI) is calculated with ENVI 4.7 from Band 3 and 4. The results showed a very important floristic diversity in this forest. The comparison of NDVI from the two dates confirms that there is a decrease of the density of vegetation in this area due to repeated fires.

Keywords: remote sensing, boutaleb, diversity, forest

Procedia PDF Downloads 555

Authors: Zeynep Selin Acar

Abstract:

In the world of wars, it is aimed to find ways to protect civilians propound by political elites. Current threats may come from edges of the security concerns, meaning uncontrollable terrorist groups, unanticipated government-supported armed groups or separatists, and unimaginable merge of the previous with foreign supports or oppositions of which could flow into all groups– flaws of international state system. These threats resulted in transformation of inter-state system into a world system with distinctive actors and brought along the changes in strategic plans of political and military bodies, as well as adaptations of principles framing the strategies in terms of may-be-applicable international law constrained by ethical considerations. This paper aims to analyse the Responsibility to Protect (RtoP), being one of those, with its criteria aiming to regulate military interventions taking the protection of civilians both as the reason for intervention, jus ad bellum or right to war, and as the duties during the intervention, jus in bello or how to conduct the war. In addition it will discuss the rise of its bindingness in terms of Responsibility Not to Veto (RNtoV), Franco/Mexican Political Declaration opened in signature for UN member states on September 2015.

Keywords: civilian protection, protection as responsibility, responsibility to protect, responsibility not to veto

Procedia PDF Downloads 259

Authors: M. G. Ghanem, A. M. M. A. Allam, Diaa E. Fawzy, Mehmet Faruk Cengiz

Abstract:

This paper is devoted to the design and implementation of a smartwatch textile antenna for Wi-Fi bio-medical applications in millimetric wave bands. The antenna is implemented on a leather textile-based substrate to be embedded in a smartwatch. It enables the watch to pick Wi-Fi signals without the need to be connected to a mobile through Bluetooth. It operates at 60 GHz or WiGig (Wireless Gigabit Alliance) band with a wide band for higher rate applications. It also could be implemented over many stratified layers of the body organisms to be used in the diagnosis of many diseases like diabetes and cancer. The structure is designed and simulated using CST (Studio Suite) program. The wearable patch antenna has an octagon shape, and it is implemented on leather material that acts as a flexible substrate with a size of 5.632 x 6.4 x 2 mm3, a relative permittivity of 2.95, and a loss tangent of 0.006. The feeding is carried out using differential feed (discrete port in CST). The work provides five antenna implementations; antenna without ground, a ground is added at the back of the antenna in order to increase the antenna gain, the substrate dimensions are increased to 15 x 30 mm2 to resemble the real hand watch size, layers of skin and fat are added under the ground of the antenna to study the effect of human body tissues human on the antenna performance. Finally, the whole structure is bent. It is found that the antenna can achieve a simulated peak realized gain in dB of 5.68, 7.28, 6.15, 3.03, and 4.37 for antenna without ground, antenna with the ground, antenna with larger substrate dimensions, antenna with skin and fat, and bent structure, respectively. The antenna with ground exhibits high gain; while adding the human organisms absorption, the gain is degraded because of human absorption. The bent structure contributes to higher gain.

Keywords: bio medical engineering, millimetric wave, smart watch, textile antennas, Wi-Fi

Procedia PDF Downloads 118

Authors: Babak Bashari Rad

Abstract:

A metamorphic computer virus uses different code transformation techniques to mutate its body in duplicated instances. Characteristics and function of new instances are mostly similar to their parents, but they cannot be easily detected by the majority of antivirus in market, as they depend on string signature-based detection techniques. The purpose of this research is to propose a Hidden Markov Model for classification of metamorphic viruses in executable files. In the proposed solution, portable executable files are inspected to extract the instructions opcodes needed for the examination of code. A Hidden Markov Model trained on portable executable files is employed to classify the metamorphic viruses of the same family. The proposed model is able to generate and recognize common statistical features of mutated code. The model has been evaluated by examining the model on a test data set. The performance of the model has been practically tested and evaluated based on False Positive Rate, Detection Rate and Overall Accuracy. The result showed an acceptable performance with high average of 99.7% Detection Rate.

Keywords: malware classification, computer virus classification, metamorphic virus, metamorphic malware, Hidden Markov Model

Procedia PDF Downloads 313

Authors: Andrew Kirabira

Abstract:

This study is an investigation into the effectiveness of climate-smart agriculture (CSA) technologies in improving productivity through managing biotic and abiotic stresses in the coffee agroecological zones of Uganda. The motive is to enhance farmer livelihoods. The study was initiated as a result of the decreasing productivity of the crop in Uganda caused by the increasing prevalence of pests, diseases and abiotic stresses. Despite 9 years of farmers’ application of CSA, productivity has stagnated between 700kg -800kg/ha/yr which is only 26% of the 3-5tn/ha/yr that CSA is capable of delivering if properly applied. This has negatively affected the incomes of the 10.6 million people along the crop value chain which has in essence affected the country’s national income. In 2019/20 FY for example, Uganda suffered a deficit of $40m out of singularly the increasing incidence of one pest; BCTB. The amalgamation of such trends cripples the realization of SDG #1 and #13 which are the eradication of poverty and mitigation of climate change, respectively. In probing CSA’s effectiveness in curbing such a trend, this study is guided by the objectives of; determining the existing farmers’ knowledge and perceptions of CSA amongst the coffee farmers in the diverse coffee agro-ecological zones of Uganda; examining the relationship between the use of CSA and prevalence of selected coffee pests, diseases and abiotic stresses; ascertaining the difference in the market organization and pricing between conventionally and CSA produced coffee; and analyzing the prevailing policy environment concerning the use of CSA in coffee production. The data collection research design is descriptive in nature; collecting data from farmers and agricultural extension workers in the districts of Ntungamo, Iganga and Luweero; each of these districts representing a distinct coffee agroecological zone. Policy custodian officers at district, cooperatives and at the crop’s overseeing national authority were also interviewed.

Keywords: climate change, food security, field stresses, Productivity

Procedia PDF Downloads 54

Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

Procedia PDF Downloads 256

Authors: Amaechi O. Azi, Uche D. Aluge, Lim H. San, Godwin A. Agbo

Abstract:

This paper is centered on the investigation of mineral deposits in selected locations in Oshiri province in Ebonyi State. Mineral deposits contribute immensely to the economic growth of a society. In researching lead and zinc oxide-bearing sites at Oshiri, geological and geophysical research technique was employed. Petrozenith, Earth Resistivity Meter, and Schlumberger setup were selected to examine the electrical characteristics of the subsurface. To determine the apparent resistivity of the subsurface, five soundings were taken, and the field data were processed using WinResist software. The mudstone, lead-shale, shale-granite, and lateritic topsoil were the four geoelectric strata that were found. The third layer, which corresponds to the shale-lead lithology, has a resistivity value between 211.9 m to 807.7 m at a depth of 25 m. Due to its resistivity levels and geological trend, this layer makes an excellent signature for lead-zinc occurrence. This zone is expected to house deposits of lead and zinc oxide in commercial quantity.

Keywords: Schlumberger, current, resistivity, lithology

Procedia PDF Downloads 73

Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 56

Authors: Anil Kumar Gupta, Dronadula Venkata Sai Praneeth, Brajesh Dubey, Arundhuti Devi, Suravi Kalita, Khanindra Sharma

Abstract:

Increase in urbanization and industrialization have led to improve in the standard of living. However, at the same time, the challenges due to improper solid waste management are also increasing. Municipal Solid Waste management is considered as a vital step in the development of urban infrastructure. The present study focuses on developing a solid waste management plan for an urban area in a developing country. The current scenario of solid waste management practices at various urban bodies in India is summarized. Guwahati city in the northeastern part of the country and is also one of the targeted smart cities (under the governments Smart Cities program) was chosen as case study to develop and implement the solid waste management plan. The whole city was divided into various divisions and waste samples were collected according to American Society for Testing and Materials (ASTM) - D5231-92 - 2016 for each division in the city and a composite sample prepared to represent the waste from the entire city. The solid waste characterization in terms of physical and chemical which includes mainly proximate and ultimate analysis were carried out. Existing primary and secondary collection systems were studied and possibilities of enhancing the collection systems were discussed. The composition of solid waste for the overall city was found to be as: organic matters 38%, plastic 27%, paper + cardboard 15%, Textile 9%, inert 7% and others 4%. During the conference presentation, further characterization results in terms of Thermal gravimetric analysis (TGA), pH and water holding capacity will be discussed. The waste management options optimizing activities such as recycling, recovery, reuse and reduce will be presented and discussed.

Keywords: proximate, recycling, thermal gravimetric analysis (TGA), solid waste management

Procedia PDF Downloads 186

Authors: Amira Abdelrasoul

Abstract:

This study aimed to ascertain the controlled permeability of biomimetic cellulose triacetate (CTA) membranes by investigating the electrical oscillatory behavior across impregnated membranes (IM). The biomimetic CTA membranes were infused with a fatty acid to induce electrical oscillatory behavior and, hence, to ensure controlled permeability. In situ synchrotron radiation micro-computed tomography (SR-μCT) at the BioMedical Imaging and Therapy (BMIT) Beamline at the Canadian Light Source (CLS) was used to evaluate the main morphology of IMs compared to neat CTA membranes to ensure fatty acid impregnation inside the pores of the membrane matrices. A monochromatic beam at 20 keV was used for the visualization of the morphology of the membrane. The X-ray radiographs were recorded by means of a beam monitor AA-40 (500 μm LuAG scintillator, Hamamatsu, Japan) coupled with a high-resolution camera, providing a pixel size of 5.5 μm and a field of view (FOV) of 4.4 mm × 2.2 mm. Changes were evident in the phase transition temperatures of the impregnated CTA membrane at the melting temperature of the fatty acid. The pulsations of measured voltages were related to changes in the salt concentration of KCl in the vicinity of the electrode. Amplitudes and frequencies of voltage pulsations were dependent on the temperature and concentration of the KCl solution, which controlled the permeability of the biomimetic membranes. The presented smart biomimetic membrane successfully combined porous polymer support and impregnating liquid not only imitate the main barrier properties of the biological membranes but could be easily modified to achieve some new properties, such as facilitated and active transport, regulation by chemical, physical and pharmaceutical factors. These results open new frontiers for the facilitation and regulation of active transport and permeability through biomimetic smart membranes for a variety of biomedical and drug delivery applications.

Keywords: biomimetic, membrane, synchrotron, permeability, morphology

Procedia PDF Downloads 96

Authors: Yanick Blaise Ketchaya, Taofa Zhou

Abstract:

The type of primary source of gold deposit can be explored by using the study of trace element analysis of placer gold which is a valuable exploration tool. Au-bearing deposits are investigated through the placer gold, which is an important indicator mineral. The hydrothermal fluid interacting with diverse geological settings exerts an important function on the chemical composition of gold. Consequently, alluvial gold particles from the placer deposits within the Gamba district in northern Cameroon were examined by an electron probe microanalyzer (EPMA) to show discriminant chemical signatures. The gold grains from a different locality show the same trace element composition, which appears to be in a solid solution in Au. These trace element compositions, contained in gold grains, indicate a homogeneous source. The placer gold particles have significant chemical characteristics (low Ag content), consistent with a mesothermal source. The gold particle signatures in the Gamba district, with high Te and Bi contents, reflect the chemical characteristics of the felsic host rock superimposed on the chemical signature of the hydrothermal fluid.

Keywords: hypogene source, Northern Cameroon, placer gold, trace element

Procedia PDF Downloads 104

Authors: Amjed Sid Ahmed, Rosilah Hassan, Nor Effendy Othman

Abstract:

Limited functioning of the Internet Protocol version 4 (IPv4) has necessitated the development of the Internetworking Protocol next generation (IPng) to curb the challenges. Indeed, the IPng is also referred to as the Internet Protocol version 6 (IPv6) and includes the Neighbor Discovery Protocol (NDP). The latter performs the role of Address Auto-configuration, Router Discovery (RD), and Neighbor Discovery (ND). Furthermore, the role of the NDP entails redirecting the service, detecting the duplicate address, and detecting the unreachable services. Despite the fact that there is an NDP’s assumption regarding the existence of trust the links’ nodes, several crucial attacks may affect the Protocol. Internet Engineering Task Force (IETF) therefore has recommended implementation of Secure Neighbor Discovery Protocol (SEND) to tackle safety issues in NDP. The SEND protocol is mainly used for validation of address rights, malicious response inhibiting techniques and finally router certification procedures. For routine running of these tasks, SEND utilizes on the following options, Cryptographically Generated Address (CGA), RSA Signature, Nonce and Timestamp option. CGA is produced at extra high costs making it the most notable disadvantage of SEND. In this paper a clear description of the constituents of CGA, its operation and also recommendations for improvements in its generation are given.

Keywords: CGA, IPv6, NDP, SEND

Procedia PDF Downloads 381

Authors: G. C. Tikkiwal, Mukesh Upadhyay

Abstract:

During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving army, moving convoys etc. The Radar operator selects one of the promising targets into Single Target Tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper we present a technique using mathematical and statistical methods like Fast Fourier Transformation (FFT) and Principal Component Analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, fft, principal component analysis, eigenvector, octave-notes, dsp

Procedia PDF Downloads 343

Authors: Samira Kalantary, Sara Taghipour, Mansoure Ghias Abadi

Abstract:

The Internet of Things (IOT) is a technological revolution that represents the future of computing and communications. IOT is the convergence of Internet with RFID, NFC, Sensor, and smart objects. Fog Computing is the natural platform for IOT. At present, the IOT as a new network communication technology has rapidly shifted from concept to application under fog computing virtual storage computing platform. In this paper, we describe everything about IOT and difference between cloud computing and fog computing.

Keywords: cloud computing, fog computing, Internet of Things (IoT), IOT application

Procedia PDF Downloads 581

Authors: Sakshi Singh, Shampa Chakraverty

Abstract:

One of the essential characteristics of Blockchain is the ability to validate the integrity of new transactions added to the Blockchain. Moreover, one of the essential consensus algorithms, Proof of Work, performs this job. In this work, we implemented the Proof of Work consensus method on the block formed by performing the transaction using Ganache. The primary goal of this implementation is to understand the process and record how Proof of Work works in reality on newly created blocks.

Keywords: proof of work, blockchain, ganache, smart contract

Procedia PDF Downloads 161

Authors: Wan Aminah Hasbullah

Abstract:

The knowledge of medicine in Malay society stemmed out from the need to remedy disease process. Such knowledge came from observations by looking at the signs on the plants which signify it uses, the doctrine of signature, and also observing what kind of animal and its parts that can be used to treat the disease. Prayers (jampi and doa’) play a very important role in the therapeutic processes addressing the ethereal part of the body. In Malay medicine, prayers were said in the heart of the Malay bomoh (medicine man) when they are first approaching the diseased person, seeking the help of Allah in accurately directing his mind into making the right diagnosis and subsequently the right choice of treatment. In the making of medicine, similar rituals were religiously followed, starting from gathering the materia medica to the final concoction of the medicine. Thus, all the materia medica and the prayers in Malay medicine were gathered and documented in the medical manuscript known as MSS 2999 Kitab Tibb. For this study, a collection of vegetative materia medica which is specialized for the women illness from this manuscript will be gathered and analysed. A medical and cultural interpretation will be highlighted to see the relationship between efficacy in traditional Malay medicine as practiced in the past and the recent practice of the modern medicine.

Keywords: vegetative, materia medica, woman illness, Malay medical manuscript

Procedia PDF Downloads 249

Authors: Moshmi Sangavarapu

Abstract:

The US healthcare industry has undergone tremendous digital transformation in recent years, but critical care access to lower-income ethnicities is still in its nascency. This population has historically showcased substantial hesitation to seek any medical assistance. While the lack of sufficient financial resources plays a critical role, the existing cultural and knowledge barriers also contribute significantly to widening the access gap. It is imperative to break these barriers to ensure timely access to therapeutic procedures that can save important lives! Based on ongoing research, healthcare access barriers can be best addressed by tapping the untapped potential of caregiver communities first. They play a critical role in patients’ diagnoses, building healthcare knowledge and instilling confidence in required therapeutic procedures. Recent technological advancements have opened many avenues by developing smart ways of reaching the large caregiver community. A digitized go-to-market strategy featuring connected media coupled with smart IoT devices and geo-location targeting can be collectively leveraged to reach this key audience group. AI/ML algorithms can be thoroughly trained to identify relevant data signals from users' location and browsing behavior and determine useful marketing touchpoints. The web behavior can be further assimilated with natural language processing to identify contextually relevant interest topics and decipher potential caregivers on digital avenues to serve that brand message. In conclusion, grasping the true health access journey of any lower-income ethnic group is important to design beneficial touchpoints that can alleviate patients’ concerns and allow them to break their own access barriers and opt for timely and quality healthcare.

Keywords: healthcare access, market access, diversity barriers, patient journey

Procedia PDF Downloads 51

Authors: Laura Çami (Vorpsi), Xhon Skënderi

Abstract:

In today's rapidly evolving technological landscape, the traditional principles of contract law are facing significant challenges. The emergence of new technologies, such as electronic signatures, smart contracts, and online dispute resolution mechanisms, is transforming the way contracts are formed, interpreted, and enforced. This paper examines the implications of these technological advancements on the constitutional principles of contract law. One of the fundamental principles of contract law is freedom of contract, which ensures that parties have the autonomy to negotiate and enter into contracts as they see fit. However, the use of technology in the contracting process has the potential to disrupt this principle. For example, online platforms and marketplaces often offer standard-form contracts, which may not reflect the specific needs or interests of individual parties. This raises questions about the equality of bargaining power between parties and the extent to which parties are truly free to negotiate the terms of their contracts. Another important principle of contract law is the requirement of consideration, which requires that each party receives something of value in exchange for their promise. The use of digital assets, such as cryptocurrencies, has created new challenges in determining what constitutes valuable consideration in a contract. Due to the ambiguity in this area, disagreements about the legality and enforceability of such contracts may arise. Furthermore, the use of technology in dispute resolution mechanisms, such as online arbitration and mediation, may raise concerns about due process and access to justice. The use of algorithms and artificial intelligence to determine the outcome of disputes may also raise questions about the impartiality and fairness of the process. Finally, it should be noted that there are many different and complex effects of technical improvements on the fundamental constitutional foundations of contract law. As technology continues to evolve, it will be important for policymakers and legal practitioners to consider the potential impacts on contract law and to ensure that the principles of fairness, equality, and access to justice are preserved in the contracting process.

Keywords: technological advancements, constitutional principles, contract law, smart contracts, online dispute resolution, freedom of contract

Procedia PDF Downloads 137

Authors: Atakan Aral Ormancı, Tuğçe Arslantaş, Murat Özcü

Abstract:

This study presents the design and implementation of an experimental chassis-level system for various control applications. Specifically, the height level of the chassis is controlled using proportional integrated derivative, fuzzy logic, and deep learning control methods. Real-time data obtained from height and pressure sensors installed in a 6x2 truck chassis, in combination with pulse-width modulation signal values, are utilized during the tests. A prototype pneumatic system of a 6x2 truck is added to the setup, which enables the Smart Pneumatic Actuators to function as if they were in a real-world setting. To obtain real-time signal data from height sensors, an Arduino Nano is utilized, while a Raspberry Pi processes the data using Matlab/Simulink and provides the correct output signals to control the Smart Pneumatic Actuator in the truck chassis. The objective of this research is to optimize the time it takes for the chassis to level down and up under various loads. To achieve this, proportional integrated derivative control, fuzzy logic control, and deep learning techniques are applied to the system. The results show that the deep learning method is superior in optimizing time for a non-linear system. Fuzzy logic control with a triangular membership function as the rule base achieves better outcomes than proportional integrated derivative control. Traditional proportional integrated derivative control improves the time it takes to level the chassis down and up compared to an uncontrolled system. The findings highlight the superiority of deep learning techniques in optimizing the time for a non-linear system, and the potential of fuzzy logic control. The proposed approach and the experimental results provide a valuable contribution to the field of control, automation, and systems engineering.

Keywords: automotive, chassis level control, control systems, pneumatic system control

Procedia PDF Downloads 76

Authors: B. Karabuluter, O. Karaduman

Abstract:

Traffic management and traffic planning are important issues, especially in big cities. Due to the increase of personal vehicles and the physical constraints of urban roads, the problem of transportation especially in crowded cities over time is revealed. This situation reduces the living standards, and it can put human life at risk because the vehicles such as ambulance, fire department are prevented from reaching their targets. Even if the city planners take these problems into account, emergency planning and traffic management are needed to avoid cases such as traffic congestion, intersections, traffic jams caused by traffic accidents or roadworks. In this study, in smart traffic management issues, proposed solutions using intelligent vehicles acting in cooperation with urban roads are examined. Traffic management is becoming more difficult due to factors such as fatigue, carelessness, sleeplessness, social behavior patterns, and lack of education. However, autonomous vehicles, which remove the problems caused by human weaknesses by providing driving control, are increasing the success of practicing the algorithms developed in city traffic management. Such intelligent vehicles have become an important solution in urban life by using 'swarm intelligence' algorithms and cooperative driving methods to provide traffic flow, prevent traffic accidents, and increase living standards. In this study, studies conducted in this area have been dealt with in terms of traffic jam, intersections, regulation of traffic flow, signaling, prevention of traffic accidents, cooperation and communication techniques of vehicles, fleet management, transportation of emergency vehicles. From these concepts, some taxonomies were made out of the way. This work helps to develop new solutions and algorithms for cities where intelligent vehicles that can perform cooperative driving can take place, and at the same time emphasize the trend in this area.

Keywords: intelligent traffic management, cooperative driving, smart driving, urban road, swarm intelligence, connected vehicles

Procedia PDF Downloads 328

Authors: Tunde Puskas, Anita Andersson

Abstract:

In Swedish early childhood education research, the issues related to religious identifications and practices have often been marginalized or relegated either to the realm of diversity and multiculturalism or to the realm of national traditions. This paper is part of a research project about whether religion is considered as part of Swedish cultural heritage in Swedish preschools. Our aim in this paper is to explore how a Swedish preschool balance between keeping the education non-confessional and at the same time introducing the traditions associated with advent and Christmas. Christmas was chosen because of the religious background of the holiday and because it is a tradition widely celebrated in Swedish preschools. In Swedish education system, the concept of freedom of religion is understood in the sense that education is declared to be non-confessional. Nevertheless, as the major state holidays in Sweden are tied to Lutheran Christian traditions, and according to the curriculum preschool educators, are given the task to pass on a cultural heritage, defined in terms of values, traditions, history, language, and knowledge, it is the preschool teams or individual preschool teachers who determine whether and to what extent religious considerations are/ought to be seen as part of the cultural heritage the preschool passes on. The data consists of ten video taped observations from two preschools. The video data was transcribed and the transcripts were thereafter analysed through content analysis. In the analysis, we draw on the concept of banal religiosity that has helped us to draw attention to the workings of religious considerations that are so familiar that they rarely are noticed as religious and on Ninian Smart’s theory on the dimensions of religion. The analysis shows that what the adults actually do with religion fulfils six of seven dimensions common to religious traditions as outlined by Smart. At the same time, Christmas is performed as a lived tradition within which the commercial and religious rituals intersect and result in a banal, national religiosity.

Keywords: secular advent, banal religiosity, dimensions of religion, rites

Procedia PDF Downloads 186

Authors: Muhammad Isa Khan, Jalil Ur Rehman, Muhammad Afzal Khan Rao, James Chow

Abstract:

Purpose: This study investigates the dose-volume variations in planning target volume (PTV) and organs-at-risk (OARs) using different collimator angles for smart arc prostate volumetric modulated arc therapy (VMAT). Awareness of the collimator angle for PTV and OARs sparing is essential for the planner because optimization contains numerous treatment constraints producing a complex, unstable and computationally challenging problem throughout its examination of an optimal plan in a rational time. Materials and Methods: Single arc VMAT plans at different collimator angles varied systematically (0°-90°) were performed on a Harold phantom and a new treatment plan is optimized for each collimator angle. We analyzed the conformity index (CI), homogeneity index (HI), gradient index (GI), monitor units (MUs), dose-volume histogram, mean and maximum doses to PTV. We also explored OARs (e.g. bladder, rectum and femoral heads), dose-volume criteria in the treatment plan (e.g. D30%, D50%, V30Gy and V38Gy of bladder and rectum; D5%,V14Gy and V22Gy of femoral heads), dose-volume histogram, mean and maximum doses for smart arc VMAT at different collimator angles. Results: There was no significance difference found in VMAT optimization at all studied collimator angles. However, if 0.5% accuracy is concerned then collimator angle = 45° provides higher CI and lower HI. Collimator angle = 15° also provides lower HI values like collimator angle 45°. It is seen that collimator angle = 75° is established as a good for rectum and right femur sparing. Collimator angle = 90° and collimator angle = 30° were found good for rectum and left femur sparing respectively. The PTV dose coverage statistics for each plan are comparatively independent of the collimator angles. Conclusion: It is concluded that this study will help the planner to have freedom to choose any collimator angle from (0°-90°) for PTV coverage and select a suitable collimator angle to spare OARs.

Keywords: VMAT, dose-volume histogram, collimator angle, organs-at-risk

Procedia PDF Downloads 509