Search results for: WSN (wireless sensor networks)

Authors: Fumin Wang, Jiaqi Yin, Lajun Wang, Nan Chi

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In this article, we demonstrate a visible light communication (VLC) system over 8 meters free space transmission based on a commercial LED and a receiver in connection with an audio interface of a smart phone. The signal is in FSK modulation format. The successful experimental demonstration validates the feasibility of the proposed system in future wireless communication network.

Keywords: visible light communication, smartphone communication, frequency shift keying, wireless communication

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Authors: Márcia Aparecida Teixeira

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Sports, in particular football, boosts considerably the financial market of a certain locality, be it city or even a country. The financial transactions involving this medium stand out from other existing businesses, such as small industries. Strategically, social networks are inserted in this sporting environment, in order to promote and attract new fans of this modality. The present study analyzes the use of social networks in Sports Marketing with a focus on football. For the object of this study, it was chosen a specific club, the Club Atlético Mineiro, a Brazilian club of great national notoriety. The social networks on focus will be: Facebook, Twitter, and Instagram. It will be analyzed the content and frequency of the posts, reception of the target public in relation to the content made available and its feedback.

Keywords: social network, sport, strategy, marketing

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Authors: Young-San Shin, Seongsoo Lee

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Hall sensor is widely used to measure rotation angle. When the Hall voltage is measured for linear displacement, it is converted to angular displacement using arctangent function, which requires a large lookup table. In this paper, a lookup table reduction technique is presented for angle measurement. When the input of the lookup table is small within a certain threshold, the change of the outputs with respect to the change of the inputs is relatively small. Thus, several inputs can share same output, which significantly reduce the lookup table size. Its error analysis was also performed, and the threshold was determined so as to maintain the error less than 1°. When the Hall voltage has 11-bit resolution, the lookup table size is reduced from 1,024 samples to 279 samples.

Keywords: hall sensor, angle measurement, lookup table, arctangent

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Authors: Vijay Kumar, Jaspreet Singh, Manoj Wadhwa

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Piezo-resistive pressure sensors were one of the first developed micromechanical system (MEMS) devices and still display a significant growth prompted by the advancements in micromachining techniques and material technology. In MEMS based piezo-resistive pressure sensors, temperature can be considered as the main environmental condition which affects the system performance. The study of the thermal behavior of these sensors is essential to define the parameters that cause the output characteristics to drift. In this work, a study on the effects of temperature and doping concentration in a boron implanted piezoresistor for a silicon-based pressure sensor is discussed. We have optimized the temperature coefficient of resistance (TCR) and temperature coefficient of sensitivity (TCS) values to determine the effect of temperature drift on the sensor performance. To be more precise, in order to reduce the temperature drift, a high doping concentration is needed. And it is well known that the Wheatstone bridge in a pressure sensor is supplied with a constant voltage or a constant current input supply. With a constant voltage supply, the thermal drift can be compensated along with an external compensation circuit, whereas the thermal drift in the constant current supply can be directly compensated by the bridge itself. But it would be beneficial to also compensate the temperature coefficient of piezoresistors so as to further reduce the temperature drift. So, with a current supply, the TCS is dependent on both the TCπ and TCR. As TCπ is a negative quantity and TCR is a positive quantity, it is possible to choose an appropriate doping concentration at which both of them cancel each other. An exact cancellation of TCR and TCπ values is not readily attainable; therefore, an adjustable approach is generally used in practical applications. Thus, one goal of this work has been to better understand the origin of temperature drift in pressure sensor devices so that the temperature effects can be minimized or eliminated. This paper describes the optimum doping levels for the piezoresistors where the TCS of the pressure transducers will be zero due to the cancellation of TCR and TCπ values. Also, the fabrication and characterization of the pressure sensor are carried out. The optimized TCR value obtained for the fabricated die is 2300 ± 100ppm/ᵒC, for which the piezoresistors are implanted at a doping concentration of 5E13 ions/cm³ and the TCS value of -2100ppm/ᵒC is achieved. Therefore, the desired TCR and TCS value is achieved, which are approximately equal to each other, so the thermal effects are considerably reduced. Finally, we have calculated the effect of temperature and doping concentration on the output characteristics of the sensor. This study allows us to predict the sensor behavior against temperature and to minimize this effect by optimizing the doping concentration.

Keywords: piezo-resistive, pressure sensor, doping concentration, TCR, TCS

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Authors: Rajeshwari Madli, Santhosh Hebbar, Vishwanath Heddoori, G. V. Prasad

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Agriculture is the major occupation in India and forms the backbone of Indian economy in which irrigation plays a crucial role for increasing the quality and quantity of crop yield. In spite of many revolutionary advancements in agriculture, there has not been a dramatic increase in agricultural performance. Lack of irrigation infrastructure and agricultural knowledge are the critical factors influencing agricultural performance. However, by using advanced agricultural equipment, the effect of these factors can be curtailed.  The presented system aims at increasing the yield of crops by using an intelligent irrigation controller that makes use of wireless sensors. Sensors are used to monitor primary parameters such as soil moisture, soil pH, temperature and humidity. Irrigation decisions are taken based on the sensed data and the type of crop being grown. The system provides a mobile application in which farmers can remotely monitor and control the irrigation system. Also, the water pump is protected against damages due to voltage variations and dry running.

Keywords: android application, Bluetooth, wireless sensors, irrigation, temperature, soil pH

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Authors: Wael M. Bazzi, Amir Rastegarnia, Azam Khalili

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In this paper we consider the issue of reliability of measurements in distributed adaptive estimation problem. To this aim, we assume a sensor network with different observation noise variance among the sensors and propose new estimation method based on incremental distributed least mean-square (IDLMS) algorithm. The proposed method contains two phases: I) Estimation of each sensors observation noise variance, and II) Estimation of the desired parameter using the estimated observation variances. To deal with the reliability of measurements, in the second phase of the proposed algorithm, the step-size parameter is adjusted for each sensor according to its observation noise variance. As our simulation results show, the proposed algorithm considerably improves the performance of the IDLMS algorithm in the same condition.

Keywords: adaptive filter, distributed estimation, sensor network, IDLMS algorithm

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Authors: Syed Jawad Hussain, Abir Touati, Farid Touati

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Free-Space Optics (FSO) is a wireless technology that enables the optical transmission of data though the air. FSO is emerging as a promising alternative or complementary technology to fiber optic and wireless radio-frequency (RF) links due to its high-bandwidth, robustness to EMI, and operation in unregulated spectrum. These systems are envisioned to be an essential part of future generation heterogeneous communication networks. Despite the vibrant advantages of FSO technology and the variety of its applications, its widespread adoption has been hampered by rather disappointing link reliability for long-range links due to atmospheric turbulence-induced fading and sensitivity to detrimental climate conditions. Qatar, with modest cloud coverage, high concentrations of airborne dust and high relative humidity particularly lies in virtually rainless sunny belt with a typical daily average solar radiation exceeding 6 kWh/m2 and 80-90% clear skies throughout the year. The specific objective of this work is to study for the first time in Qatar the effect of solar irradiation on the deliverability of the FSO Link. In order to analyze the transport media, we have ported Embedded Linux kernel on Field Programmable Gate Array (FPGA) and designed a network sniffer application that can run into FPGA. We installed new FSO terminals and configure and align them successively. In the reporting period, we carry out measurement and relate them to weather conditions.

Keywords: free space optics, solar irradiation, field programmable gate array, FSO outage

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Authors: Zeyad Abdelmageid, Xianbin Wang

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Choosing the operational channel for a WLAN access point (AP) in WLAN networks has been a static channel assignment process initiated by the user during the deployment process of the AP, which fails to cope with the dynamic conditions of the assigned channel at the station side afterward. However, the dramatically growing number of Wi-Fi APs and stations operating in the unlicensed band has led to dynamic, distributed, and often severe interference. This highlights the urgent need for the AP to dynamically select the best overall channel of operation for the basic service set (BSS) by considering the distributed and changing channel conditions at all stations. Consequently, dynamic channel selection algorithms which consider feedback from the station side have been developed. Despite the significant performance improvement, existing channel selection algorithms suffer from very high feedback overhead. Feedback latency from the STAs, due to the high overhead, can cause the eventually selected channel to no longer be optimal for operation due to the dynamic sharing nature of the unlicensed band. This has inspired us to develop our own dynamic channel selection algorithm with reduced overhead through the proposed low-overhead, cluster-based station reporting mechanism. The main idea behind the cluster-based station reporting is the observation that STAs which are very close to each other tend to have very similar channel conditions. Instead of requesting each STA to report on every candidate channel while causing high overhead, the AP divides STAs into clusters then assigns each STA in each cluster one channel to report feedback on. With the proper design of the cluster based reporting, the AP does not lose any information about the channel conditions at the station side while reducing feedback overhead. The simulation results show equal performance and, at times, better performance with a fraction of the overhead. We believe that this algorithm has great potential in designing future dynamic channel selection algorithms with low overhead.

Keywords: channel assignment, Wi-Fi networks, clustering, DBSCAN, overhead

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Authors: Min-Ah Woo, Min-Cheol Lim, Hyun-Joo Chang, Sung-Wook Choi

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We developed a paper-based colorimetric sensor utilizing magnetic nanoparticles conjugated with aptamers (MNP-Apts) against E. coli O157:H7. The MNP-Apts were applied to a test sample solution containing the target cells, and the solution was simply dropped onto PVDF (polyvinylidene difluoride) membrane. The membrane moves the sample radially to form the sample spots of different compounds as concentric rings, thus the MNP-Apts on the membrane enabled specific recognition of the target cells through a color ring generation by MNP-promoted colorimetric reaction of TMB (3,3',5,5'-tetramethylbenzidine) and H₂O₂. This method could be applied to rapidly and visually detect various bacterial pathogens in less than 1 h without cell culturing.

Keywords: aptamer, colorimetric sensor, E. coli O157:H7, magnetic nanoparticle, polyvinylidene difluoride

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Authors: Devin Atkin, Orly Yadid-Pecht

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The continual demands for increasing resolution and dynamic range in CMOS image sensors have resulted in exponential increases in the amount of data that needs to be read out of an image sensor, and existing readouts cannot keep up with this demand. Interesting approaches such as sparse and burst readouts have been proposed and show promise, but at considerable trade-offs in other specifications. To this end, we have begun designing and evaluating various new readout topologies centered around an attempt to parallelize the sensor readout. In this paper, we have designed, simulated, and started testing a new light-controlled oscillator topology with dual column and row readouts. We expect the parallel readout structure to offer greater speed and alleviate the trade-off typical in this topology, where slow pixels present a major framerate bottleneck.

Keywords: CMOS image sensors, high-speed capture, wide dynamic range, light controlled oscillator

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Authors: Sheng-Che Chen, Keng-Ren Lin, Che-Hsin Lin, Hao-Yuan Tseng, Chih-Han Chang

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Teeth play an important role in providing the essential nutrients. The force loading of chewing on the crow is important condition to evaluate long-term success of many dental treatments. However, the quantification of the force regarding forces are distributed over the dental crow is still not well recognized. This study presents an industrial-grade piezoelectric-based multilayer ceramic capacitors (MLCCs) force sensor for measuring the distribution of the force distribute over the first molar. The developed sensor array is based on a flexible polyimide electrode and barium titanate-based MLCCs. MLCCs are commonly used in the electronic industry and it is a typical electric component composed of BaTiO₃, which is used as a capacitive material. The most important is that it also can be used as a force-sensing component by its piezoelectric property. In this study, to increase the sensitivity as well as to reduce the variation of different MLCCs, a treatment process is utilized. The MLCC force sensors are able to measure large forces (above 500 N), making them suitable for measuring the bite forces on the tooth crown. Moreover, the sensors also show good force response and good repeatability.

Keywords: force sensor array, multilayer ceramic capacitors, occlusal force, piezoelectric

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Authors: M. M. Hefnawy, A. M. A. Homoda, M. A. Abounassif, A. M. Alanazia, A. Al-Majed, Gamal A. E. Mostafa

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PVC membrane sensors using different approach e.g. ion-pair, ionophore, and Schiff-base has been used as testing membrane sensor. Analytical applications of membrane sensors for direct measurement of variety of different ions in complex biological and environmental sample are reported. The most important step of such PVC membrane sensor is the sensing active material. The potentiometric sensors have some outstanding advantages including simple design, operation, wide linear dynamic range, relative fast response time, and rotational selectivity. The analytical applications of these techniques to pharmaceutical compounds in dosage forms are also discussed. The construction and electrochemical response characteristics of Poly (vinyl chloride) membrane sensors for moxifloxacin HCl (MOX) are described. The sensing membranes incorporate ion association complexes of moxifloxacin cation and sodium tetraphenyl borate (NaTPB) (sensor 1), phosphomolybdic acid (PMA) (sensor 2) or phosphotungstic acid (PTA) (sensor 3) as electroactive materials. The sensors display a fast, stable and near-Nernstian response over a relative wide moxifloxacin concentration range (1 ×10-2-4.0×10-6, 1 × 10-2-5.0×10-6, 1 × 10-2-5.0×10-6 M), with detection limits of 3×10-6, 4×10-6 and 4.0×10-6 M for sensor 1, 2 and 3, respectively over a pH range of 6.0-9.0. The sensors show good discrimination of moxifloxacin from several inorganic and organic compounds. The direct determination of 400 µg/ml of moxifloxacin show an average recovery of 98.5, 99.1 and 98.6 % and a mean relative standard deviation of 1.8, 1.6 and 1.8% for sensors 1, 2, and 3 respectively. The proposed sensors have been applied for direct determination of moxifloxacin in some pharmaceutical preparations. The results obtained by determination of moxifloxacin in tablets using the proposed sensors are comparable favorably with those obtained using the US Pharmacopeia method. The sensors have been used as indicator electrodes for potentiometric titration of moxifloxacin.

Keywords: potentiometry, PVC, membrane sensors, ion-pair, ionophore, schiff-base, moxifloxacin HCl, sodium tetraphenyl borate, phosphomolybdic acid, phosphotungstic acid

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Authors: Somayeh Sadat Hashemi Kamangar, Fatemeh Bakouie, Shahriar Gharibzadeh

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In this study, we target to exploit Maximum Spanning Trees (MST) of children's semantic networks to investigate their language development. To do so, we examine the graph-theoretic properties of word-embedding networks. The networks are made of words children learn prior to the age of 30 months as the nodes and the links which are built from the cosine vector similarity of words normatively acquired by children prior to two and a half years of age. These networks are weighted graphs and the strength of each link is determined by the numerical similarities of the two words (nodes) on the sides of the link. To avoid changing the weighted networks to the binaries by setting a threshold, constructing MSTs might present a solution. MST is a unique sub-graph that connects all the nodes in such a way that the sum of all the link weights is maximized without forming cycles. MSTs as the backbone of the semantic networks are suitable to examine developmental changes in semantic network topology in children. From these trees, several parameters were calculated to characterize the developmental change in network organization. We showed that MSTs provides an elegant method sensitive to capture subtle developmental changes in semantic network organization.

Keywords: maximum spanning trees, word-embedding, semantic networks, language development

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Authors: Toru Shionoya, Yosuke Kurihara, Takashi Kaburagi, Kajiro Watanabe

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Mass-produced bidirectional microphones have attractive characteristics. They work as a microphone as well as a sensor with high gain over a wide frequency range; they are also highly reliable and economical. We present novel multiple functional uses of the microphones. A mathematical model for explaining the high-pass-filtering characteristics of bidirectional microphones was presented. Based on the model, the characteristics of the microphone were investigated, and a novel use for the microphone as a sensor with a wide frequency range was presented. In this study, applications for using the microphone as a security sensor and a human biosensor were introduced. The mathematical model was validated through experiments, and the feasibility of the abovementioned applications for security monitoring and the biosignal monitoring were examined through experiments.

Keywords: bidirectional microphone, low-frequency, mathematical model, frequency response

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Authors: Benjamin Anderson-Sackaney, Amr Abdel-Dayem

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This paper presents a comprehensive survey of recent source camera identification (SCI) systems. Then, the performance of various sensor pattern noise (SPN) estimators was experimentally assessed, under common photo response non-uniformity (PRNU) frameworks. The experiments used 1350 natural and 900 flat-field images, captured by 18 individual cameras. 12 different experiments, grouped into three sets, were conducted. The results were analyzed using the receiver operator characteristic (ROC) curves. The experimental results demonstrated that combining the basic SPN estimator with a wavelet-based filtering scheme provides promising results. However, the phase SPN estimator fits better with both patch-based (BM3D) and anisotropic diffusion (AD) filtering schemes.

Keywords: sensor pattern noise, source camera identification, photo response non-uniformity, anisotropic diffusion, peak to correlation energy ratio

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Authors: Dimitar Karastoyanov, Todor Penchev

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The paper presents the research of a kind of autonomous mobile robots, intended for work and adaptive perception in unknown and unstructured environment. The objective are robots, dedicated for multi-sensory environment perception and exploration, like measurements and samples taking, discovering and putting a mark on the objects as well as environment interactions–transportation, carrying in and out of equipment and objects. At that ground classification of the different types mobile robots in accordance with the way of locomotion (wheel- or chain-driven, walking, etc.), used drive mechanisms, kind of sensors, end effectors, area of application, etc. is made. Modular system for the mechanical construction of the mobile robots is proposed. Special PLC on the base of AtMega128 processor for robot control is developed. Electronic modules for the wireless communication on the base of Jennic processor as well as the specific software are developed. The methods, means and algorithms for adaptive environment behaviour and tasks realization are examined. The methods of group control of mobile robots and for suspicious objects detecting and handling are discussed too.

Keywords: mobile robots, wireless communications, environment investigations, group control, suspicious objects

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Authors: Dhananjay Singh, M. Abdullah-Al-Wadud

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The Internet of Things is a concept of a large scale ecosystem of wireless actuators. The actuators are defined as things in the IoT, those which contribute or produces some data to the ecosystem. However, ubiquitous data collection, data security, privacy preserving, large volume data processing, and intelligent analytics are some of the key challenges into the IoT technologies. In order to solve the security requirements, challenges and threats in the IoT, we have discussed a message authentication mechanism for IoT applications. Finally, we have discussed data encryption mechanism for messages authentication before propagating into IoT networks.

Keywords: Internet of Things (IoT), message authentication, privacy, security

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Authors: P. Behera, K. K. Singh, D. K. Saini, M. De

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Implementation of 2D materials in the detection of bio analytes is highly advantageous in the field of sensing because of its high surface to volume ratio. We have designed our sensor array with different cationic two-dimensional MoS₂, where surface modification was achieved by cationic thiol ligands with different functionality. Green fluorescent protein (GFP) was chosen as signal transducers for its biocompatibility and anionic nature, which can bind to the cationic MoS₂ surface easily, followed by fluorescence quenching. The addition of bio-analyte to the sensor can decomplex the cationic MoS₂ and GFP conjugates, followed by the regeneration of GFP fluorescence. The fluorescence response pattern belongs to various analytes collected and transformed to linear discriminant analysis (LDA) for classification. At first, 15 different proteins having wide range of molecular weight and isoelectric points were successfully discriminated at 50 nM with detection limit of 1 nM. The sensor system was also executed in biofluids such as serum, where 10 different proteins at 2.5 μM were well separated. After successful discrimination of protein analytes, the sensor array was implemented for bacteria sensing. Six different bacteria were successfully classified at OD = 0.05 with a detection limit corresponding to OD = 0.005. The optimized sensor array was able to classify uropathogens from non-uropathogens in urine medium. Further, the technique was applied for discrimination of bacteria possessing resistance to different types and amounts of drugs. We found out the mechanism of sensing through optical and electrodynamic studies, which indicates the interaction between bacteria with the sensor system was mainly due to electrostatic force of interactions, but the separation of native bacteria from their drug resistant variant was due to Van der Waals forces. There are two ways bacteria can be detected, i.e., through bacterial cells and lysates. The bacterial lysates contain intracellular information and also safe to analysis as it does not contain live cells. Lysates of different drug resistant bacteria were patterned effectively from the native strain. From unknown sample analysis, we found that discrimination of bacterial cells is more sensitive than that of lysates. But the analyst can prefer bacterial lysates over live cells for safer analysis.

Keywords: array-based sensing, drug resistant bacteria, linear discriminant analysis, two-dimensional MoS₂

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Authors: Esmail Sadipour

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The use of social networks is increasing day by day in all societies. The purpose of this research was to know the relationship between the use of social networks (Instagram, WhatsApp, and Telegram) with executive functions and academic performance in first-year female high school students. This research was applied in terms of purpose, quantitative in terms of data type, and correlational in terms of technique. The population of this research consisted of all female high school students in the first year of district 2 of Tehran. Using Green's formula, the sample size of 150 people was determined and selected by cluster random method. In this way, from all 17 high schools in district 2 of Tehran, 5 high schools were selected by a simple random method and then one class was selected from each high school, and a total of 155 students were selected. To measure the use of social networks, a researcher-made questionnaire was used, the Barclay test (2012) was used for executive functions, and last semester's GPA was used for academic performance. Pearson's correlation coefficient and multivariate regression were used to analyze the data. The results showed that there is a negative relationship between the amount of use of social networks and self-control, self-motivation and time self-management. In other words, the more the use of social networks, the fewer executive functions of students, self-control, self-motivation, and self-management of their time. Also, with the increase in the use of social networks, the academic performance of students has decreased.

Keywords: social networks, executive function, academic performance, working memory

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Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

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The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

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Authors: K. A. Laptinskiy, S. A. Burikov, A. M. Vervald, S. A. Dolenko, T. A. Dolenko

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The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of nanodiamonds against the background autofluorescence of egg white with high accuracy - better than 3 ug/ml.

Keywords: artificial neural networks, fluorescence, data aggregation, biomarkers

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Authors: Su Sin Chong, Abdul Aziz Abdul Raman, Sulaiman Wadi Harun, Hamzah Arof

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Chemical Oxygen Demand (COD) plays a vital role determination of an appropriate strategy for wastewater treatment including the control of the quality of an effluent. In this study, a new sensing method was introduced for the first time and developed to investigate chemical oxygen demand (COD) using a Mach-Zehner Interferometer (MZI)-based dye sensor. The sensor is constructed by bridging two single mode fibres (SMF1 and SMF2) with a short section (~20 mm) of multimode fibre (MMF) and was formed by tapering the MMF to generate evanescent field which is sensitive to perturbation of sensing medium. When the COD concentration increase takes effect will induce changes in output intensity and effective refractive index between the microfiber and the sensing medium. The adequacy of decisions based on COD values relies on the quality of the measurements. Therefore, the dual output response can be applied to the analytical procedure enhance measurement quality. This work presents a detailed assessment of the determination of COD values in synthetic wastewaters. Detailed models of the measurement performance, including sensitivity, reversibility, stability, and uncertainty were successfully validated by proficiency tests where supported on sound and objective criteria. Comparison of the standard method with the new proposed method was also conducted. This proposed sensor is compact, reliable and feasible to investigate the COD value.

Keywords: chemical oxygen demand, environmental sensing, Mach-Zehnder interferometer sensor, online monitoring

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Authors: Saed Khawaldeh, Mohamed Elsharnouby, Alaa Eddin Alchalabi, Usama Pervaiz, Tajwar Aleef, Vu Hoang Minh

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Taxonomic classification has a wide-range of applications such as finding out more about the evolutionary history of organisms that can be done by making a comparison between species living now and species that lived in the past. This comparison can be made using different kinds of extracted species’ data which include DNA sequences. Compared to the estimated number of the organisms that nature harbours, humanity does not have a thorough comprehension of which specific species they all belong to, in spite of the significant development of science and scientific knowledge over many years. One of the methods that can be applied to extract information out of the study of organisms in this regard is to use the DNA sequence of a living organism as a marker, thus making it available to classify it into a taxonomy. The classification of living organisms can be done in many machine learning techniques including Neural Networks (NNs). In this study, DNA sequences classification is performed using Convolutional Neural Networks (CNNs) which is a special type of NNs.

Keywords: deep networks, convolutional neural networks, taxonomic classification, DNA sequences classification

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Authors: Latif Adnane, C. E. Ait Zaouiat, M. Eddabbah

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In Wireless Body Area Networks, the issue of systems lifetime is a big challenge to complete. In this paper, we have tackled this subject to suggest some solutions. For this aim, we have studied some batteries characteristics related to human body temperature. Moreover, we have analyzed a mathematical model which defines sensors lifetime (battery lifetime). Based on this model, we note that the random access increases the energy consumption, because nodes are waking up during the whole superframe period. Results show that using scheduled mode access of IEEE 802.15.6 maximizes the lifetime function, by setting nodes in the sleep mode in the inactive period of transmission.

Keywords: battery, energy consumption, IEEE 802.15.6, lifetime, polling

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Authors: Samuel Nii Tackie, Oyebade K. Oyedotun, Ebenezer O. Olaniyi, Adnan Khashman

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Artificial neural networks have been used in different fields of artificial intelligence, and more specifically in machine learning. Although, other machine learning options are feasible in most situations, but the ease with which neural networks lend themselves to different problems which include pattern recognition, image compression, classification, computer vision, regression etc. has earned it a remarkable place in the machine learning field. This research exploits neural networks as a data mining tool in predicting the number of times a student repeats a course, considering some attributes relating to the course itself, the teacher, and the particular student. Neural networks were used in this work to map the relationship between some attributes related to students’ course assessment and the number of times a student will possibly repeat a course before he passes. It is the hope that the possibility to predict students’ performance from such complex relationships can help facilitate the fine-tuning of academic systems and policies implemented in learning environments. To validate the power of neural networks in data mining, Turkish students’ performance database has been used; feedforward and radial basis function networks were trained for this task; and the performances obtained from these networks evaluated in consideration of achieved recognition rates and training time.

Keywords: artificial neural network, data mining, classification, students’ evaluation

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Authors: Hyungmo Kim, Hwang Bae, Seok-Kyu Chang, Dong Won Lee, Yung Joo Ko, Sun Rock Choi, Hae Seob Choi, Hyeon Seok Woo, Dong-Jin Euh, Hyeong-Yeon Lee

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Flow mixing characteristics in the wire-wrapped 37-pin rod bundle were measured by using a wire-mesh sensing system for a sodium-cooled fast reactor (SFR). The subchannel flow mixing in SFR core subchannels was an essential characteristic for verification of a core thermal design and safety analysis. A dedicated test facility including the wire-mesh sensor system and tracing liquid injection system was developed, and the conductivity fields at the end of 37-pin rod bundle were visualized in several different flow conditions. These experimental results represented the reasonable agreements with the results of CFD, and the uncertainty of the mixing experiments has been conducted to evaluate the experimental results.

Keywords: core thermal design, flow mixing, a wire-mesh sensor, a wire-wrap effect

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Authors: Daidai Shen, Jean Claude Thill, Wenjia Zhang

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This study explores the dynamics of synergy and complementarity within city networks, specifically focusing on the headquarters-subsidiary relations of firms. We begin by defining these two types of networks and establishing their pivotal roles in shaping city network structures. Utilizing the mesoscale analytic approach of weighted stochastic block modeling, we discern relational patterns between city pairs and determine connection strengths through statistical inference. Furthermore, we introduce a community detection approach to uncover the underlying structure of these networks using advanced statistical methods. Our analysis, based on comprehensive network data up to 2017, reveals the coexistence of both complementarity and synergy networks within China’s technology-intensive manufacturing cities. Notably, firms in technology hardware and office & computing machinery predominantly contribute to the complementarity city networks. In contrast, a distinct synergy city network, underpinned by the cities of Suzhou and Dongguan, emerges amidst the expansive complementarity structures in technology hardware and equipment. These findings provide new insights into the relational dynamics and structural configurations of city networks in the context of technology-intensive manufacturing, highlighting the nuanced interplay between synergy and complementarity.

Keywords: city system, complementarity, synergy network, higher-order network

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Authors: Raquel Ramos López, Anissa El-Khattabi, Ana Lucila Sandoval Orozco, Luis Javier García Villalba

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An increasing number of mobile devices with integrated cameras has meant that most digital video comes from these devices. These digital videos can be made anytime, anywhere and for different purposes. They can also be shared on the Internet in a short period of time and may sometimes contain recordings of illegal acts. The need to reliably trace the origin becomes evident when these videos are used for forensic purposes. This work proposes an algorithm to identify the brand and model of mobile device which generated the video. Its procedure is as follows: after obtaining the relevant video information, a classification algorithm based on sensor noise and Wavelet Transform performs the aforementioned identification process. We also present experimental results that support the validity of the techniques used and show promising results.

Keywords: digital video, forensics analysis, key frame, mobile device, PRNU, sensor noise, source identification

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Authors: Riki H. Patel, Arpan Desia, Trushit Upadhayay

Abstract:

The demand of compact antenna is ever increasing since the inception of wireless communication devices. In the age of wireless communication, requirement of miniaturized antennas is quite high. It is quite often that antenna dimensions are decided based on application based requirement compared to practical antenna constraints. The tradeoff in efficiency and other antenna parameters against to antenna size is always a debatable issue. The article presents detailed review of fundamentals of electrically small antennas and its potential applications. In addition, constraints and challenges of electrically small antennas are also presented in the article.

Keywords: bandwidth, communication, electrically small antenna, communication engineering

Procedia PDF Downloads 531

Authors: Christoph Ramsauer, Jaydeep Karandikar, Tony Schmitz, Friedrich Bleicher

Abstract:

Machining stability is an important limitation to discrete part machining. In this work, a networked implementation of milling stability optimization with Bayesian learning is presented. The milling process was monitored with a wireless sensory tool holder instrumented with an accelerometer at the Vienna University of Technology, Vienna, Austria. The recorded data from a milling test cut is used to classify the cut as stable or unstable based on the frequency analysis. The test cut result is fed to a Bayesian stability learning algorithm at the University of Tennessee, Knoxville, Tennessee, USA. The algorithm calculates the probability of stability as a function of axial depth of cut and spindle speed and recommends the parameters for the next test cut. The iterative process between two transatlantic locations repeats until convergence to a stable optimal process parameter set is achieved.

Keywords: machining stability, machine learning, sensor, optimization

Procedia PDF Downloads 206